Advances in the Study of Behavior, Volume 35 (Advances in the Study of Behavior)

Advances in THE STUDY OF BEHAVIOR Edited by

Peter J. B. Slater Charles T. Snowdon Timothy J. Roper H. Jane Brockmann Marc Naguib

Contents

Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ix xi

Mechanisms and Evolution of Communal Sexual Displays in Arthropods and Anurans MICHAEL D. GREENFIELD I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Choruses and Light Shows: Nine Vignettes . . . . . . . . . . . . III. Structural Elements: Adjustments of Diel Activity Pattern, Phase, and Rhythm. . . . . . . . . . . . . . . . . . IV. Adaptations and Emergent Properties. . . . . . . . . . . . . . . . . V. Summary and Prognosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 2 15 28 52 54

A Functional Analysis of Feeding GEORGE COLLIER I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Distinctions Between Approaches to the Study of Feeding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. The Currency of Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Deprivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Satiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Consumption Cost Versus Foraging Cost . . . . . . . . . . . . . . VIII. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

63 64 77 79 83 89 91 97 100

The Sexual Behavior and Breeding System of Tufted Capuchin Monkeys (Cebus apella) MONICA CAROSI, GARY S. LINN, AND ELISABETTA VISALBERGHI I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Social Structure and Mating System . . . . . . . . . . . . . . . . . . v

105 107

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CONTENTS

III. Reproductive Physiology and Sexual Behavior . . . . . . . . . . IV. Reproductive Competition and Mate Choice . . . . . . . . . . . V. Conclusions: A One-Male or a Multi-Male Breeding System? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Areas for Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

113 127 139 141 143 144

Acoustic Communication in Noise HENRIK BRUMM AND HANS SLABBEKOORN I. II. III. IV. V.

The Problem of Background Noise . . . . . . . . . . . . . . . . . . . The Sender’s Side—Signal Production . . . . . . . . . . . . . . . . . The Receiver’s Side—Signal Perception . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

151 154 169 192 193 194

Ethics and Behavioral Biology PATRICK BATESON I. II. III. IV. V. VI. VII. VIII.

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Origins of Animal Liberation and Animal Rights. . . . . . . . Other Ethical Positions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Ethical Case for Using Animals in Research . . . . . . . . Towards Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Making the Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

211 212 214 218 220 224 229 230 231

Prenatal Sensory Ecology and Experience: Implications for Perceptual and Behavioral Development in Precocial Birds ROBERT LICKLITER I. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Developmental Analysis of the Prenatal Sensory Ecology of Precocial Birds. . . . . . . . . . . . . . . . . . . . . . . . . . . III. The Developmental Dynamics of the Prenatal Sensory Ecology of Precocial Birds . . . . . . . . . . . . . . . . . . .

235 238 244

CONTENTS

IV. Prenatal Sensory Ecology: Sources of Stability and Variability in Behavioral Development . . . . . . . . . . . . . . . . V. Effects of Prenatal Sensory Ecology on Arousal, Attention, and Perceptual Processing . . . . . . . . . . . . . . . . . VI. Prenatal Sensory Ecology in Real-Time: The Arousal/Attention Complex . . . . . . . . . . . . . . . . . . . . . . . . . VII. Effects of Prenatal Sensory Stimulation on Perception, Learning, and Memory . . . . . . . . . . . . . . . . . . . VIII. The Dividends of an Ecological/Developmental Systems Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IX. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vii

248 252 255 257 262 264 265

Conflict and Cooperation in Wild Chimpanzees MARTIN N. MULLER AND JOHN C. MITANI I. II. III. IV. V. VI.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chimpanzee Society, Demography, and Ecology . . . . . . . . Conflict . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cooperating to Compete . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

275 277 278 299 317 319 321

Trade-Offs in the Adaptive Use of Social and Asocial Learning RACHEL L. KENDAL, ISABELLE COOLEN, YFKE VAN BERGEN, AND KEVIN N. LALAND I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Evidence That Animals Exploit Socially Transmitted Information Where Asocial Learning Would Be Costly . . III. Evidence That Animals Exploit Social Information When Uncertain as to What to Do . . . . . . . . . . . . . . . . . . . IV. Implications for Social Learning Researchers . . . . . . . . . . . V. General Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

333

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

381

Contents of Previous Volumes . . . . . . . . . . . . . . . . . . . . . . . . . . . .

391

335 346 364 370 373 374

Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

PATRICK BATESON (211), Sub-Department of Animal Behaviour, University of Cambridge, Cambridge CB3 8AA, United Kingdom HENRIK BRUMM (151), School of Biology, University of St. Andrews, St. Andrews KY16 9TS, United Kingdom MONICA CAROSI (105), Unit of Cognitive Primatology and Primate Center, Institute for Cognitive Sciences and Technologies, National Research Council, Rome, Italy; Laboratory of Comparative Ethology, National Institute of Child Health & Human Development, NIH Animal Center, Poolesville, Maryland 20837, USA GEORGE COLLIER (63), Department of Psychology, Rutgers University, New Brunswick, New Jersey 08901, USA ISABELLE COOLEN (333), Institut de Recherche sur la Biologie de l’Insecte, Universite´ de Tours, France MICHAEL D. GREENFIELD (1), Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas 66045, USA RACHEL L. KENDAL (333), Department of Biological Sciences, Stanford University, California 94305, USA KEVIN N. LALAND (333), Centre for Social Learning and Cognitive Evolution, School of Biology, University of St. Andrews, St. Andrews KY16 9TS, United Kingdom ROBERT LICKLITER (235), Department of Psychology, Florida International University, Miami, Florida 33199, USA GARY S. LINN (105), Program in Cognitive Neuroscience and Schizophrenia, The Nathan S. Kline Institute for Psychiatric Research, NYSOMH, Orangeburg, New York 10962, USA; Department of Psychiatry, New York University School of Medicine, Orangeburg, New York 10962, USA JOHN C. MITANI (275), Department of Anthropology, University of Michigan, Ann Arbor, Michigan 48109, USA ix

x

CONTRIBUTORS

MARTIN N. MULLER (275), Department of Anthropology, Boston University, Boston, Massachusetts 02215, USA HANS SLABBEKOORN (151), Institute of Biology, Leiden University, 2300 RA Leiden, The Netherlands YFKE VAN BERGEN (333), Zoology Department, University of Cambridge, Cambridge CB3 8AA, United Kingdom ELISABETTA VISALBERGHI (105), Unit of Cognitive Primatology and Primate Center, Institute for Cognitive Sciences and Technologies, National Research Council, Rome, Italy

Preface The aim of Advances remains as it has been since the series began: to serve the increasing number of scientists who are engaged in the study of animal behavior by presenting their theoretical ideas and research to their colleagues and to those in neighboring fields. We hope that the series will continue its ‘‘contribution to the development of cooperation and communication among scientists in our field,’’ as its intended role was phrased in the Preface to the first volume in 1965. Since that time, traditional areas of animal behavior research have achieved new vigor by the links they have formed with related fields and by the closer relationship that now exists between those studying animal and human subjects. Scientists studying behavior today range more widely than ever before: from ecologists and evolutionary biologists, to geneticists, endocrinologists, pharmacologists, neurobiologists, and developmental psychobiologists, not forgetting the ethologists and comparative psychologists whose prime domain the subject is. It is our intention not to focus narrowly on one or a few of these fields, but to publish articles covering the best behavioral work from a broad spectrum. The skills and concepts of scientists in such diverse fields necessarily differ, making the task of developing cooperation and communication among them a difficult one. But it is one that is of great importance, and one to which the Editors and publisher of Advances in the Study of Behavior are committed. We will continue to provide the means to this end by publishing critical reviews, by inviting extended presentations of significant research programs, by encouraging the writing of theoretical syntheses and reformulations of persistent problems, and by highlighting especially penetrating research that introduces important new concepts. The eight chapters in this volume are a particularly wide ranging collection. At the laboratory psychologists’ end of the spectrum, though each with a functional perspective, Collier reviews his long series of studies of feeding patterns in rats and Lickliter uses the system that development within an egg allows to examine prenatal influences on bird behavior. There are two chapters on primates: Muller and Mitani on conflict and cooperation in chimpanzees, and Carosi et al. on reproductive behavior in capuchins. Two active and related areas of study within communication are covered by Greenfield, on communal displays, and Brumm and Slabbekoorn on the problems that noise poses for acoustic communication.

xi

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PREFACE

Then Kendal et al. consider why animals sometimes learn socially and sometimes individually, and in a more philosophical vein, Bateson considers the important ethical issues that must concern us all as behavioral biologists. There is certainly something in this volume to satisfy all interests. Peter J. B. Slater Charles T. Snowdon Timothy J. Roper H. Jane Brockmann Marc Naguib

ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

Mechanisms and Evolution of Communal Sexual Displays in Arthropods and Anurans Michael D. Greenfield department of ecology and evolutionary biology university of kansas lawrence, kansas 66045, usa

I. INTRODUCTION Advertisement signals of sexually displaying males are among the most widely and thoroughly studied phenomena in animal behavior. Many of our current advances in understanding sexual selection, signal evolution and species recognition, biomechanics, sensory and cognitive ecology, and neuro‐ethology derive from studies that focus on male signaling activities. Communal sexual displays are a subset of these signaling phenomena, and they merit special attention on two grounds: First, communal displays of acoustically and visually signaling animals are acknowledged to include some of the ‘‘great spectacles of the living world’’ (Wilson, 1975). Anyone who has borne witness to the chorusing of periodical cicadas in central and eastern North America or the collective flashing of fireflies in the Indo‐ Malayan region cannot help but marvel at the sheer numbers of individuals involved and the intensity of their collective signaling output. But, communal sexual displays are noteworthy for more than just masses of participants and their volume of sound or brilliance of light. In many cases, the signals of individual participants are precisely choreographed in space and time, often giving rise to striking alternation or synchrony between neighbors (Alexander, 1975). Here, underlying aesthetic sensibilities may account for much of our interest: Perhaps related to a concern with orderliness and pattern in the natural world, we remain fascinated with synchronous phenomena of all forms (Pikovsky et al., 2002; Strogatz, 2003; see Neda et al., 2000 for an intriguing example from human behavior), particularly when these events defy obvious explanation. And it is this latter point that brings us to our second reason for focusing attention on communal sexual displays: The mechanisms and evolution of an individual’s signaling are often concealed from casual view, and it is only when signaling is interactive that these 1 0065-3454/05 $35.00 DOI: 10.1016/S0065-3454(05)35001-7

Copyright 2005, Elsevier Inc. All rights reserved.

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MICHAEL D. GREENFIELD

features may be revealed. Moreover, neighbor‐neighbor interaction is the natural setting in which male advertisement signaling normally occurs in many species (Bradbury and Vehrencamp, 1998; McGregor, 2005). Thus, we are compelled to examine the interactions in communal displays if we are to acquire a full understanding of the mechanisms regulating signaling and how natural and sexual selection have shaped signal evolution. In this chapter, I describe and analyze communal signaling phenomena found among invertebrate and vertebrate animals. I concentrate on those phenomena that exhibit some sort of fine‐scale spatio‐temporal structure and have been subjected to experimental analysis in the field or laboratory. By the first limitation, I omit the arena behaviors of lekking birds (see Ho¨ glund and Alatalo, 1995 on avian lekking; see also Staicer et al., 1996; Todt and Naguib, 2000; and Naguib, 2005 on the dawn chorus and other vocal interactions in birds) and restrict coverage largely to the chorusing displays of acoustic insects and anurans (Bailey, 1991; Gerhardt and Huber, 2002; Greenfield, 1994a) and the bioluminescent displays of fireflies (Buck and Buck, 1976). Because the latter share various features with choruses, they offer the opportunity to make comparisons across signaling modalities. I also discuss recent findings of chorusing‐like displays in animals signaling with substrate vibration (Kotiaho et al., 2004) and reflected light (Backwell et al., 1998), and I entertain the possibility that further analogues are found among yet other modalities (i.e., olfactory and electrostatic signals). In every case, we find a rich source of material for advancing our understanding of animal communication.

II. CHORUSES

AND

LIGHT SHOWS: NINE VIGNETTES

To introduce the phenomena we analyze later in this chapter, I begin with a series of nine vignettes: seven insect and anuran choruses, and two analogous bioluminescent displays. These have been chosen to represent the most spectacular communal displays as well as the range of spatio‐temporal structures observed and the various problems we face in understanding how and why such displays arise. The first vignette describes a display that may be familiar to many readers, but whose control mechanisms and evolution remain elusive. A. SON

ET

LUMIE`RE: PERIODICAL CICADAS

Most of the world’s 1500 or so species of cicadas produce loud male advertisement songs (Bennet‐Clark, 1998), and collectively these may yield an impressive chorus when local densities are high. But only the seven

MECHANISMS AND EVOLUTION OF COMMUNAL SEXUAL DISPLAYS

3

members of the genus Magicicada, occurring in central and eastern North America, earn the distinction of being periodical in their life cycle, and it is among these that adult population density—and chorusing output—reach the highest levels (Williams and Simon, 1995). Generation times in all cicadas are long, generally greater than seven years, and all but the final few weeks are spent underground while in the nymphal stage. Because generations typically overlap extensively within local populations, some adults emerge, sing, mate, and oviposit during each year—except in Magicicada, the 13‐ and 17‐year ‘‘periodical cicadas.’’ Here, generations within a population may be synchronized so perfectly that all but a negligible few adults emerge within a three‐ to four‐week period of the same year; adults of the subsequent generation then appear after another 12.9 or 16.9 years have elapsed (Alexander and Moore, 1962). Whereas multiple ‘‘broods’’ are found in some locations, these overlapping generations are separated by a minimum of four years, and each individual generation is synchronized nearly perfectly as above (Helio¨ vaara et al., 1994). This synchronization of lengthy generations means that the number of adults observed during the brief emergence period can be truly staggering. The formation of ‘‘chorus centers,’’ specific locations at which large numbers of males congregate and sing, further enhances both adult population density and song intensity (Lloyd and Karban, 1983). It has been argued that clumping in time, and space, afford periodical cicadas protection from natural enemies via over‐ satiation (Lloyd and Dybas, 1966). Some evidence supports this contention (Karban, 1982, 1984; Williams et al., 1993), but other researchers point out that additional factors are probably necessary to initiate selection for synchronous emergence (Bulmer 1977; Hoppensteadt and Keller, 1976). 1. Magicicada cassini (Vignette 1) Were synchronization of emergence not sufficiently astonishing, one of the 17‐year species, Magicicada cassini, exhibits the added effect of fine‐ scale synchronization of male advertisement song. Recordings made at M. cassini chorus centers show that males may align their 5‐sec song periods in phase (see Box 1 for terminology) such that most individuals within a local area broadcast song at approximately the same time and remain silent at approximately the same time (Alexander and Moore, 1958). This activity yields a chorus that regularly undulates in sound amplitude by 6–10 dB every 5 sec (Fig. 1). The males often, but not always, fly a short distance to a new perch between successive songs, a movement pattern that generates a visual effect accompanying the regularly undulating chorus. This son et lumie`re exhibition is most readily seen in dense chorus centers of M. cassini. The display retains a high degree of synchronization throughout an extended portion of daily singing, and the period of amplitude peaks

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MICHAEL D. GREENFIELD

BOX I TERMINOLOGY OF SIGNALING AND SIGNAL INTERACTIONS IN COMMUNAL DISPLAYS Alternation: where the regularly repeating signals of two (or possibly three) individuals are broadcast such that they do not occur at the same time; may be applied to entire chirps or elements of chirps (pulses, notes); alternating signals are said to be ‘‘out‐of‐phase’’ and separated by a phase angle of approximately
180 ; see phase. Call: acoustic signal; may be applied to chirp or trill. Chirp: longest regularly repeating unit in acoustic signaling; consecutive chirps are generally separated by an inter‐chirp interval as long as or longer than the chirp; contrast with trill; commonly used in acoustic insects. Cycle: see period. Endogenous rhythm: see free‐running rhythm. Flash: bioluminescent signal; analogous to call in acoustic signaling. Follower: a regularly repeated signal (chirp, flash) or signal element (note, pulse) that is broadcast shortly after a neighbor’s signal or signal element; a follower has a small positive phase angle with respect to its neighbor, designated a leader; see phase. Free‐running rhythm: rhythm established by central oscillator and uninfluenced by external stimuli; applied to the signal rhythm of an individual who does not perceive signals from neighbors; also termed endogenous rhythm. Leader: a regularly repeated signal (chirp, flash) or signal element (note, pulse) that is broadcast shortly before a neighbor’s signal or signal element; a leader has a small negative phase angle with respect to its neighbor, designated a follower; see phase. Note: regularly repeating element of a call (chirp or trill), which is comprised of multiple notes; commonly used in anurans. Period: time interval between onsets of consecutive signals in a regularly repeating sequence; may be applied to calls, chirps, flashes, notes, and pulses. Phase: temporal relationship between two rhythms; commonly expressed as an angular measurement, where phase angle of rhythm A relative to rhythm B is the onset time of A’s signal minus the onset time of either B’s next or its preceding signal, divided by the length of A’s free‐running period and multiplied by 360 ; thus, synchronized rhythms have a phase angle of approximately 0 , and alternating rhythms have a phase angle of approximately
180 . Phase advance: an adjustment to signal rhythm in which an individual shortens its concurrent period in response to a neighbor’s signal; if the neighbor only broadcasts a single isolated chirp or flash, the focal signaler shortens only one period then returns to its free‐running rhythm following the adjusted period. Phase delay: an adjustment to signal rhythm in which an individual lengthens its concurrent period in response to a neighbor’s signal; if the neighbor only broadcasts a single isolated chirp or flash, the focal signaler lengthens only one period and then returns to its free‐running rhythm following the adjusted period. Pulse: regularly repeating element of a call (chirp or trill), which is comprised of multiple pulses; commonly used in acoustic insects, a pulse may represent the sound produced by one complete cycle of stridulatory movement by the wings or legs. Rhythm: reciprocal of period; number of signals per unit time, may be applied to calls, chirps, flashes, notes, and pulses. Syllable: individual element of a call, which may be comprised of multiple syllables. Synchrony: co‐occurrence of the signals of two or more individuals at approximately the same time; may be applied to single, isolated signals or to signals that are repeated with a regular rhythm; regularly repeating signals that are synchronized are said to be ‘‘in‐phase’’ and separated by a phase angle of approximately 0 ; see phase. Trill: continuous sequence of acoustic notes or pulses that is not regularly interrupted by lengthy intervals; contrast with chirp.

MECHANISMS AND EVOLUTION OF COMMUNAL SEXUAL DISPLAYS

5

Fig. 1. Synchronous chorus produced by the 17‐year periodical cicada Magicicada cassini (Brood IV; Jefferson Co., Kansas, U.S.A.; 12 June 1998). Oscillogram represents the field recording of many hundreds of males; song periods are approximately 5 sec long, and the regular undulation in amplitude indicates that the majority of individuals in a local area align their songs in phase with their neighbors.

in the chorus does not waver. We can then ask how the massive numbers of chorus members remain in phase every song cycle, and whether visual as well as acoustic input is involved in timing the chorus. More importantly, why do M. cassini males stage this highly choreographed show? B. FLASH SYNCHRONY

IN

FIREFLIES

1. Pteroptyx malaccae (2) Halfway around the world from the North American periodical cicada choruses, an equally amazing light show unfolds nightly in forests of the Indo‐Malayan region. Thousands of male fireflies (Coleoptera: Lampyridae) Pteroptyx, and to a lesser extent Luciola, congregate on particular trees, often along the banks of tidal waterways, where they flash in synchrony and do so with remarkable precision (Buck, 1938; Buck and Buck, 1976; Strogatz and Stewart, 1993). In Pteroptyx malaccae, which may be the most precise synchronizer—not only among Pteroptyx but among all communally displaying animals (Buck, 1988)—congregating males maintain 0.6‐ sec flash periods that are in nearly perfect phase with their neighbors for hours on end; flash periods of neighbors may vary by less than one percent. The displays have been reported by European travelers since the 16th

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MICHAEL D. GREENFIELD

century, and some were so mesmerized by the sight of an entire tree flashing on and off that they refused to believe their own observations. In recent years, the tourist industry in Malaysia and Thailand has recognized the value of synchronous fireflies, and several congregation sites are now considered for protection within parks and reserves. Unlike synchrony in Magicada cassini choruses, mechanisms potentially responsible for flash synchrony in Pteroptyx malaccae have been analyzed and modeled in detail (Ermentrout, 1991). These studies suggest that P. malaccae males attain, and continue, synchrony by advancing or delaying the phase relationships they maintain with their neighbors’ rhythms and also by accelerating or decelerating their underlying (free‐running) rhythms. But as with M. cassini, we still have no understanding of why these improbable flash displays occur. This ignorance remains, despite no fewer than 20 articles on these synchronous fireflies that have appeared in the journal Science since 1881, and a comparable number of hypotheses (e.g., Buck and Buck, 1978; Otte, 1980; Otte and Smiley, 1977). In other Pteroptyx species, synchrony is less precise and extensive, and may be controlled by phase adjustments only (Buck et al., 1981a). 2. Photinus pyralis (3) Synchronous flash displays are also generated in several genera of North American fireflies, but the synchronization is generally even less precise and more local in scope. This crude level of synchronization may be constrained by males flashing in flight rather than while perched and stationary. In Photinus pyralis, ‘‘roving’’ males produce 0.5‐sec advertisement flashes approximately every 6 sec while scanning the ground for the specialized reply flashes of receptive females (Case, 1984). If a female’s reply is seen during a specific time window, the male approaches while continuing his advertisement flash rhythm. This courtship dialogue, a ‘‘visual duet,’’ is maintained until the male reaches the female or until she ceases to reply. Where local density is high and roving males flash within view of neighboring males, a fleeting synchrony may arise for several flash cycles when several male search paths converge, only to end as the males invariably move apart (Buck, 1935; Case, 1984; Rau, 1932). Thus, Photinus synchrony might be characterized as nodes of unison activity that blink on and off sporadically at different points in the landscape. But in Photinus carolinus, found in the southern Appalachian Mountains, synchrony is longer lasting, may involve large numbers of males over an extended portion of the landscape, and can achieve and maintain considerable temporal precision (Copeland and Moiseff, 1995; Moiseff and Copeland, 1995). P. carolinus displays have begun to attract the attention of observers of natural history and students of synchronous phenomena. Recently, heightened temporal

7

MECHANISMS AND EVOLUTION OF COMMUNAL SEXUAL DISPLAYS

precision has also been noted in the synchronous flash displays of Photuris frontalis, found in southeastern North America (Copeland and Moiseff, 2004; Moiseff and Copeland, 2000). It is likely that additional cases of bioluminescent synchrony will be revealed as more species, among both fireflies and certain other bioluminescent groups, are carefully investigated. The various bioluminescent species of marine ostracod crustaceans, for example, Vargula, ‘‘firefleas of the sea’’ (Morin, 1986), may be particularly fruitful subjects for this exploration. C. ACOUSTIC SYNCHRONY ANURAN AMPHIBIANS

AND

ALTERNATION

IN THE

ORTHOPTERA

AND

1. Oecanthus fultoni (4) Synchrony generated by acoustically signaling animals is generally less exact than that attained by Pteroptyx fireflies. In North America, snowy tree crickets (Oecanthus fultoni) are among the more regular synchronizers (Fulton, 1934), and their timing mechanisms have been analyzed via controlled playback experiments in the laboratory (Walker, 1969). Individual males broadcast 40–150 msec chirps, each containing 2–11 pulses, at a rate of 2.1–2.6 sec‐1 (at 24.5  C). When singing in the presence of neighbors, males align their chirps, but not pulses within chirps, in fairly close synchrony (Fig. 2). Chirp periods of neighbors may vary by less than 10% during runs of synchronous singing. In any given chirp cycle, one male will normally lead the other by a brief interval (mean ¼ 27 msec), but this relationship appeared to change randomly over successive cycles such that each of two males may exhibit equivalent incidences of leading and following chirps. As in some of the Pteroptyx fireflies, Oecanthus synchrony is generated by phase adjustments, but shortening and lengthening of chirps,

Fig. 2. Synchronous chorus produced by two male snowy tree crickets (Oecanthus fultoni; Gryllidae: Oecanthinae). Upper and lower traces represent transcriptions of oscillograms of chirps of individuals A and B, respectively (adapted from Walker, 1969, with permission from AAAS).

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MICHAEL D. GREENFIELD

by adding or deleting pulses, may also play a role. Field observations indicate that synchronous choruses of these arboreal singers regularly involve large numbers of advertising males. 2. Mecopoda (5) Choruses of Mecopoda katydids in the Indo‐Malayan region also generate acoustic synchrony, and recordings of singing pairs indicate a relatively high degree of precision, which may approach that observed in Pteroptyx fireflies—the ‘‘absolute standard’’ for synchronous displays. Males calling in solo can maintain chirp periods with remarkable constancy (variation <2%), and a pair of singers broadcasting comparable solo rates may establish regular synchrony that lasts for many cycles (Sismondo, 1990). Unlike any of the examples of bioluminescent or acoustic synchrony listed thus far, Mecopoda choruses may include phase relationships other than synchrony in their interactive repertoire. Under certain circumstances, as when neighbors are separated by greater distances or have different solo rates, Mecopoda may shift from synchrony to alternation—calling 180 out‐ of‐phase—and also to more complex timing relationships that regularly pass through synchrony and various relationships between synchrony and alternation, each effected with a high degree of precision. This versatility has been duly noted and analyzed (Hartbauer et al., 2005). Some evidence supports the role of female choice, acting indirectly by favoring males who produce leading calls, in establishing the chorus structure (Ro¨ mer et al., 2002). 3. Pterophylla Camellifolia (6) In other acoustic insect choruses, regular alternation of neighbors’ songs is the standard interactive format. In central and eastern North America, males of the true katydid (Pterophylla camellifolia) are commonly heard alternating their 2–5 ‘‘syllable’’ calls on late summer evenings (Gwynne, 2001). Pterophylla camellifolia are among the more storied insects in North American natural history lore, and their three‐syllable song has given rise—some would say in a curious, non‐onomatopoetic fashion (Dethier, 1992)—to the common epithet (ka¯ ‐te¯ ‐did) used for tettigoniids in North America. Several extended epithets for their four‐ and five‐syllable songs also exist (e.g., ka¯ ‐te¯ ‐did‐not). Although loud, P. camellifolia males typically call from the tops of the highest trees, and only through laboratory playbacks have biologists been able to probe their behavior and identify mechanisms underlying the out‐of‐phase song relationship maintained by pairs, as shown in Fig. 3 (Shaw, 1968). As in Oecanthus, phase adjustments and call lengthening and shortening appear to be responsible.

MECHANISMS AND EVOLUTION OF COMMUNAL SEXUAL DISPLAYS

9

Fig. 3. Alternating chorus produced by two male true katydids (Pterophylla camellifolia; Tettigoniidae: Pseudophyllinae; Northern population producing two‐pulse chirps) recorded in the laboratory. Upper and lower traces represent transcriptions of oscillograms of chirps of individuals A and B, respectively (adapted from Shaw, 1968; used with full acknowledgment from Brill Academic Publishers [# Brill Academic Publishers, Leiden, The Netherlands, 1968]).

However, when male P. camellifolia sing in the forest canopy, they are often surrounded by numerous conspecific neighbors. Under these circumstances, what chorus structures may be generated by the phase and call adjustments identified above? Unlike synchrony, we have difficulty predicting the specific manner in which alternation might extend beyond pairs, or possibly trios (e.g., Goin, 1949), of callers. For example, does male A alternate with B, B with C (who, by default, synchronizes with A), C with D, etc.; or does temporal structure break down entirely? Obviously, further examination of chorusing in natural populations would help, and to address this problem we turn our attention to more accessible choruses. 4. Ephippiger ephippiger (7) In Ephippiger katydids, a genus distributed throughout shrub habitats in the Mediterranean region of Europe (Duijm, 1990), male pairs typically exhibit regular alternation of calls (Busnel, 1967). In Ephippiger ephippiger, a common species found in the garigue (chaparral) and disturbed habitats of southern France, local densities may be relatively high, with nearest‐neighbor distances between males averaging 4 m. Recordings of E. ephippiger choruses in these situations at first suggest an almost haphazard temporal relationship between males (Fig. 4). That is, at any given instant, several of the males may call, and there is no immediately obvious pattern, such as calls sweeping in wavelike fashion across the chorus during a call cycle. However, further analyses reveal rules by which males select particular neighbors with whom to interact—alternate with—while ignoring the rest (Greenfield and Snedden, 2003). Such focusing of attention (Dukas, 2002) may represent a major part of the cognitive ecology that structures choruses and other communal displays.

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MICHAEL D. GREENFIELD

Fig. 4. Choruses produced by multiple males of various orthopteran species recorded in the field. (a) Katydids, Ephippiger ephippiger (Tettigoniidae: Bradyporinae), recorded at St. Jean de Bue`ges, Dept. He´ rault, France; 23 July 1999 (adapted from Greenfield and Snedden, 2003; used with full acknowledgment from Brill Academic Publishers [# Brill Academic Publishers, Leiden, The Netherlands, 2003]). Seven traces represent transcriptions of oscillograms of chirps of individual males A–G, respectively. Regular alternation of songs occurs within certain pairs (e.g., B and C, C and D, F and G). (b) Tarbush grasshoppers, Ligurotettix planum ded at Portal, Arizona, U.S.A.; 2 August 1997 (adapted from Greenfield and Snedden, 2003; used with full acknowledgment from Brill Academic Publishers [# Brill Academic Publishers, Leiden, The Netherlands, 2003]). Eight traces represent transcriptions of oscillograms of calls of individual males A–H, respectively. Alternation occurs within certain pairs (e.g., A and B, C and D).

5. Neoconocephalus spiza (8) Even choruses that do not exhibit prolonged and regular temporal relationships involving large numbers of singers may prove valuable for revealing how communal displays function. In various acoustic insects, male congregations display brief episodes of synchrony separated by

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11

periods of reduced calling, during which fewer individuals sing and, of those that do, many call at a slower rate. This sort of ‘‘imperfect synchrony’’ has been studied in the neotropical coneheaded katydid, Neoconocephalus spiza, a common species in savanna and disturbed habitats in the lowlands of Central America (Walker and Greenfield, 1983). N. spiza males produce 20–70 msec sparrow‐like chirps at rates ranging from 1.8–5 sec1. Where local density is high, males repeatedly accelerate to the higher rates throughout the evening activity period and exhibit inter‐neighbor synchrony for 10–30 sec, or occasionally longer. During synchrony, individual males normally drop out of the chorus for a cycle or two and then re‐enter in phase (Fig. 5a). Despite the great range in chirp rates in solo singing, chirp rates during bouts of synchrony are highly regular, varying between and within individuals by less than 15%. As in Oecanthus N. spiza male ordinarily leads or follows his neighbor by a brief interval, the relationship shifting between leading and following in a seemingly random fashion over successive chirp cycles. Laboratory playback indicates that N. spiza males adjust phase relationships with their neighbors’ songs and that these adjustments yield synchrony (Greenfield and Roizen, 1993). Tests with N. spiza females indicate that preference for leading male songs has selected for the male phase adjustments and is ultimately responsible for synchronous chorusing. 6. Physalaemus pustulosus (9) Temporally structured choruses occur widely among anuran amphibians; a common format in many species features bouts of male‐male alternation separated by intervals of markedly reduced calling or even silence, as shown in Fig. 6 (Wells, 1977; Whitney and Krebs, 1975). This pattern normally continues throughout the daily activity period. In the Tu´ ngara frog, Physalaemus pustulosus, found widely throughout lowland Central America, pairs, and sometimes trios, of males will alternate during singing bouts. However, higher male densities often occur at breeding sites, temporary pools that form during the rainy season, and occurrences of four or more males per square meter are not uncommon. Here, rules similar to those described for the structure of Ephippiger katydid choruses may apply (Greenfield and Rand, 2000; see Section IV.B.4). As a generalization, anurans display a greater flexibility in phase and call modification than acoustic insects (Gerhardt and Huber, 2002). Thus, when an interval of relative quiet opens in an anuran chorus, a given male is often capable of responding quickly enough, perhaps within 40–50 msec, to insert his call in that gap (e.g., Moore et al., 1989; Schwartz, 1993; Zelick and Narins, 1985).

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Fig. 5. Choruses of imperfect synchrony produced by pairs of males of various orthopteran and crustacean species recorded in the field. (a) Coneheaded katydids, Neoconocephalus spiza (Tettigoniidae: Conocephalinae), recorded at Gamboa, Panama; 25 July 1996. (b) Katydids, Sphyrometopa femorata (Tettigoniidae: Agraeciinae), recorded at Monteverde, Costa Rica; 30 May 1993 (adapted from Greenfield, 1994b, with permission). (c) Ghost crabs, Ocypode jousseaumei (Brachyura: Ocypodidae), rapping on sand, recorded in Oman, Arabian Peninsula (courtesy of David Clayton). Upper and lower traces represent oscillograms of individuals A and B, respectively. x indicates an individual dropping out of the chorus temporarily; weak signals at these points reflect crosstalk from other individual(s). Note occasional signal lengthening and shortening in (b) and (c), respectively.

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13

Fig. 6. Alternating choruses produced by various anuran species recorded in the field. (a) Two male treefrogs, Phrynohyas venulosa (Hylidae), recorded at Gamboa, Panama; 25 May 1998. Upper and lower traces represent oscillograms of individuals A and B, respectively. (b) Five male Tu´ ngara frogs, Physalaemus pustulosus (Leptodactylidae), recorded at Gamboa, Panama; 2 June 1998. Five traces represent transcriptions of oscillograms of calls of individuals A–E, respectively.

D. SIGNAL INTERACTIONS

IN

REFLECTED LIGHT

AND

VIBRATION

While the flash synchrony of fireflies and the choruses of acoustic insects and anurans are probably the most highly structured, and thoroughly studied, of communal advertisement displays, the phenomenon is not restricted

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MICHAEL D. GREENFIELD

to these groups and signal modalities. Recent studies have documented synchronous leg waving displays by male fiddler crabs, Uca annulipes (Backwell et al., 1998), and Ilyoplax pusilla (Aizawa, 1998) (also see Gordon, 1958), whose signaling was transmitted by reflected light; and vibratory displays by male wolf spiders, Hygrolycosa rubrofasciata, (Kotiaho et al., 2004) and male ghost crabs, Ocypode jousseaumei (David Clayton, personal communication), whose signaling was transmitted by bending and Rayleigh waves, respectively, in the substrate (Fig. 5c.). Further exploration of other groups and signaling modalities less conspicuous to human observers will likely reveal yet additional examples. E. GENERAL FEATURES OF COMMUNAL SEXUAL DISPLAYS All of the above cases of communal male sexual advertisement involve individuals whose signaling activity is clustered in time as well as space. Moreover, the individuals have underlying signaling rhythms, and a phase relationship of some sort exists between the rhythms of neighbors. These phase relationships are maintained with varying degrees of precision, and they last from bouts of only several seconds in length (generally repeated at irregular intervals throughout the daily activity period) to displays that continue uninterruptedly for the entire period. The number of signalers involved in these displays also varies, ranging from only two or three nearest neighbors to most of those in a local population. In the latter case, the phase relationship may spread in wave‐like fashion to the farthest reaches of the population, even though such widely separated individuals would not be capable of direct mutual response. Known cases of communal advertisement display involve light (both bioluminescent and reflected), airborne sound, and substrate vibration. These signaling modalities are characterized by relatively rapid transmission (>5 msec1) across long distances and, with the exception of substrate vibration, they spread across or are detectable from three dimensions—unless environmental barriers are present. Such characteristics suggest that the electrostatic signals of various freshwater fish—which are now known to function in sexual advertisement (Hagedorn and Heiligenberg, 1985; Stoddard, 2002) as well as in navigation—may too be found to form communal displays in some species. Finally, structured communal displays are generally produced by, and most readily studied in, stationary signalers, flash synchrony among Photinus fireflies being a notable exception. In the next section, we explore the mechanisms by which animals may maintain these phase relationships. We pay special attention to attainment of precision in phase relationships, as it is this feature that leads to spectacular choreography, the hallmark of the most celebrated communal displays.

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15

III. STRUCTURAL ELEMENTS: ADJUSTMENTS OF DIEL ACTIVITY PATTERN, PHASE, AND RHYTHM A. TEMPORAL CLUSTERING Rhythm is a key feature common to most structured communal displays. At the same time, clustering of overall activity in time and space should be considered equally fundamental, since neighboring signalers would be unable to express specialized phase relationships between their rhythms were activity periods non‐overlapping. Typically, male signalers who happen to be sufficiently clustered in space to be within perceptual range will broadcast during a given daily activity period. But even where males are widely dispersed and beyond perceptual range, temporal clustering within a specific activity period may be established by common response to an environmental cue (Hutchinson et al., 1993). The specific time of the activity period may be influenced by environmental conditions (e.g., Crawford and Dadone, 1979; Young, 1981), such as temperature, ambient light, or background sound level, which are conducive to signal transmission, and also by the daily activity of females who then respond to male signaling (Greenfield, 1992; Murphy, 1999). Male‐male signal competition is expected to reinforce the temporal clustering of the communal display, as a given male may be required to match or exceed his neighbors’ signals in order to achieve any chance of attracting or courting receptive females (Bee and Perrill, 1996; Gerhardt et al., 2000; Jia et al., 2001). These factors have led to the designation of temporally clustered signaling as a ‘‘spree’’ (sensu Walker, 1983), the temporal analogy of a lek. The various biotic and abiotic factors will shape the onset and length of the daily activity period, which can range from less than one hour at a critical transition (e.g., dawn or dusk) to much of the day or night. The repeated cycles of collective singing bouts and silence that characterize many anuran choruses (see Greenfield, 1983; Sueur and Aubin, 2002 for examples among acoustic insects) may represent further temporal clustering generated by energy limitations and inter‐male variation (Schwartz, 1991; Schwartz et al., 1995). In situations where receptive females may arrive over a period of many hours but males lack the energy reserves to sing continuously over that period, the most effective strategy may be intermittent signaling. Here, particular male individuals that have high levels of energy reserves or motivation may typically initiate singing. As noted previously, local males may then follow suit to match their neighbors’ signaling, and a collective singing bout is generated. Temporal clustering of daily signaling activity may involve modalities other than light, sound, and substrate vibration. For example, female

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Fig. 7. Female pheromonal chorusing in an arctiid moth, Utetheisa ornatrix. Proportion of chemically signaling females rises more steeply at the onset of the normal activity period, the beginning of the night, when females are congregated (solid regression line and filled triangles) and exposed to each other’s pheromone than when solitary (dashed regression line and open circles).

Utetheisa ornatrix moths (Lepidoptera: Arctiidae) emit an advertisement sex pheromone attractive to males (Conner et al., 1980), and a recent study (Lim et al., unpublished manuscript) has shown that the females, when clustered in space and within olfactory range, detect each other’s pheromone plumes and synchronize onsets of their daily advertisement periods (Fig. 7). (See McClintock [1971] for the human analogy, synchronous menstrual cycling among women in close living quarters.) They are also more likely to advertise uninterruptedly and for a longer duration under such circumstances. These mutual responses—‘‘female pheromonal chorusing’’—possibly represent competition to attract males, who in U. ornatrix are known to donate substantial paternal investment packaged in the spermatophores that are transferred at mating (Gonzalez et al., 1999). However, the slow rate of pheromonal transmission in air, by diffusion and by convection, would most likely preclude any finer level of temporal structure in the communal display (Greenfield, 2002), and we have no evidence of such structure occurring in any other cases of chemical signaling. While U. ornatrix females are known to pump their abdomens rhythmically during pheromone emission (Conner et al., 1980; Itagaki and Conner, 1987), diffusion is expected to coalesce the rhythmic bursts of

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17

pheromone into a single cloud within a relatively short distance from the moth. Thus, the opportunity for specialized phase adjustments and fine‐scale temporal structure in the communal display, as shown in Figs. 1–6, would be extremely limited, if not absent entirely. B. ENDOGENOUS OSCILLATORS Each of the structured communal displays described in the vignettes at the beginning of this chapter assumes that central nervous system (CNS) rhythms exist in the individual signalers. Evidence supporting the existence of central free‐running rhythms comes indirectly from observations in various species that individuals may continue to signal with a more or less constant period in the absence of neighboring signalers, and even in the absence of sensory feedback from their own signaling (Buck et al., 1981b; Hanson et al., 1971; Shaw, 1968; Walker, 1969). That is, blinded and deafened animals may flash and sing with a normal rhythm. Moreover, signalers are not even required to signal in order to maintain their rhythm, as solo individuals may skip one or more signal cycles and then resume signaling at the expected instant, two, three, four, (and so forth) periods later. This effect may be seen by graphing the frequency distribution of an individual’s periods, which reveals a series of harmonics: The fundamental peak in the distribution represents the incidence of inter‐signal intervals of one period; the first harmonic is the incidence of intervals of two periods, etc. (Buck et al., 1981b) (see Fig. 8). However, confirming that a particular free‐running rhythm does occur is difficult in many species, as individuals may seldom sustain signaling long enough in the absence of stimulation from neighbors. The central rhythms under consideration here can be modeled as endogenous oscillators that rise steadily from ‘‘basal’’ to ‘‘peak level’’ of activation, at which instant return (descent) to basal level begins, and production of a signal is triggered (Buck et al., 1981a; Greenfield, 1994a; Hanson, 1978). Thus, repeated oscillator cycles are depicted as a ‘‘sawtooth graph’’ (Fig. 9). A brief ‘‘effector delay’’ elapses between the instant of triggering in the CNS and actual onset of the signal broadcast (Loftus‐Hills, 1974; Walker, 1969). The effector delay represents the time needed for neural transmission from the CNS oscillator to the signaling organ plus the time needed for activation of that organ, a motor delay. That is, it is a minimum latency period between a stimulus and a receiver’s response. Experiments on phase adjustments (see following section) support the existence of effector delays and indicate that they range in length from 40–200 msec among insects and anurans.

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Fig. 8. Temporal analysis of rhythmic signaling. (a) Hypothetical signaler generally broadcasts (dashes) at regular intervals, but interruptions of this signaling pattern, indicated by x, sometimes occur. (b) Frequency distribution of intervals measured between onsets of consecutive signals in Fig. 8a indicates a fundamental peak (3 sec) representing intervals one period long, a 2nd harmonic peak (6 sec) representing intervals two periods long, and a 2nd harmonic peak (9 sec) representing intervals three periods long.

Fig. 9. Endogenous oscillator controlling rhythmic production of male advertisement signal. Sawtooth graph depicts oscillator ascent from basal to peak level, followed by return to basal level. T, signal period; t, effector delay; r, oscillator return interval (to basal level). Thick horizontal line segments represent signals.

C. PHASE‐RESETTING MECHANISMS Neighboring signalers may achieve and maintain regular phase relationships between their respective rhythms by several mechanisms (Buck and Buck, 1968). Phase‐advance and phase‐delay mechanisms allow a signaler to make a large phase adjustment within a single oscillator cycle. Here, the length of the signaler’s period is adjusted for one and only one

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19

Fig. 10. Phase‐advance mechanism. (a) Signaler A advances its phase in response to B, calling earlier than expected based on its free‐running rhythm. (b) Adaptation of sawtooth graph (Fig. 9) to depict acceleration of A’s oscillator to peak level and phase advance of its call.

cycle. Following this adjustment, the signaler immediately returns to its free‐running rhythm. 1. Phase Advance In a phase‐advance mechanism, a period‐shortening adjustment is made in response to a signal (stimulus) perceived during the concurrent period. Consequently, phase‐advance mechanisms can also be termed ‘‘homoepisodic’’ (sensu Walker, 1969). For example, if signaler A perceives B’s signal toward the end of his own (A’s) period but prior to triggering his next signal, A may quickly advance his own oscillator’s ascent and signal slightly sooner than he would have been expected to when calling in solo (Fig. 10). Thus, some degree of synchrony among neighbors can be achieved in that very cycle. But, given the minimum length of known effector delays, the precision of that phase relationship would be limited. Preliminary tests and observations have suggested that phase‐advance mechanisms may be responsible for the overlapping synchrony observed in Magicicada cassini (periodical cicada) choruses (Alexander and Moore, 1958) and in flash displays in bioluminescent marine crustaceans (Morin, 1986). 2. Phase Delay Phase‐delay mechanisms, also termed ‘‘proepisodic’’ (sensu Walker, 1969), offer the opportunity for greater perfection in chorus structure. Here, signaler A perceives B’s signal prior to triggering of his own (A’s) signal and immediately resets his oscillator to its basal level, which

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MICHAEL D. GREENFIELD

Fig. 11. Phase‐delay mechanism. (a) Signalers A and B call independently until time i, after which they can hear each other’s calls; signaler A delays its phase in response to B, calling later than expected based on its free‐running rhythm. (b) Adaptation of sawtooth graph (Fig. 9) to

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21

lengthens his concurrent period by a significant amount, as seen in Fig. 11a and b. (Buck et al., 1981a; Hanson, 1978; Hanson et al., 1971). Thus, A’s next signal is delayed to the extent that it may synchronize with B during the next cycle—provided that the time length added at the instant of resetting is approximately one free‐running period, and both A and B respond to each other mutually (Hanson et al., 1971; Jones, 1966). However, if signaler A has already triggered its own signal when it perceives B, the timing of A’s next signal cannot be altered. Instead, A slightly advances his second signal by immediately resetting his oscillator to its basal level at the instant he perceives B (Fig. 11b). This adjustment too may yield synchrony, but not until the second cycle. Playback experiments in which single, isolated signals were broadcast to solo male signalers support the existence of phase‐delay mechanisms in various acoustic and bioluminescent insects displaying communal synchrony (Buck et al., 1981a; Greenfield and Roizen, 1993; Walker, 1969). In some species, adjustments in signal length may accompany the adjustments in phase: Length of the subsequent signal may be increased when the modified period is lengthened and decreased when the modified period is shortened (Walker, 1969). (For example, see Fig. 5b, individual A; and Fig. 5c, individual B.) When signal length comprises a significant proportion of the period, tonic inhibition, holding the oscillator at its basal level, for the duration of the neighbor’s signal, may also accompany phase adjustments (Fig. 11c). The time length added at the instant of resetting increases in proportion to the length of the perceived stimulus (neighbor’s signal). This effect may be modeled as the retaining of signaler A’s oscillator at its basal level for the duration of B’s signal, and phase‐delay mechanisms that include such effects may be termed ‘‘inhibitory resetting’’ (sensu Greenfield and Roizen, 1993). As a general rule, the rhythms observed in communal synchrony are

depict resetting of A’s oscillator to basal level and phase delay of its call, indicated by x. (c) Inhibitory‐resetting mechanism: Following resetting, A’s oscillator is tonically inhibited at basal level for the duration of stimulus B; x indicates phase delay of A’s call. (d) Repeated resetting of A’s oscillator to basal level in response to a rapidly delivered stimulus, B. (e) Rapid rebound to peak level of A’s oscillator following resetting late in its free‐running period results in alternation of calls with stimulus B; x indicates alternated call. (f) Stochastic variation in free‐running period: Despite rapid oscillator rebound, A and B synchronize at x following an unusually short period in B’s rhythm; synchrony remains one cycle later, y. (g) Stochasticity in initial conditions: Despite rapid oscillator rebound, A and B synchronize for several cycles following their chance mutual onset of calling at x. (h) Unequal free‐running rhythms, plus a rapid oscillator rebound: B is 22% faster than A, which causes an increment in A’s phase angle with respect to B each successive cycle and episodes of synchrony, x, approximately every 4–5 cycles (generated from Monte Carlo simulation and adapted from Greenfield et al., 1997).

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similar to the free‐running rhythms that individual participants exhibit in solo calling. Signalers who regulate their timing with a phase‐delay mechanism may achieve synchrony only when their free‐running rhythms are roughly equivalent. Otherwise, the slower individual (A) will repeatedly reset his oscillator to its basal level before triggering his own signal, a predicament arising whenever the signal of his faster neighbor (B) is perceived during his (A’s) oscillator’s ascent to peak level (Fig. 11d). If that slower individual is replaced by a simulated signal broadcast at the same slow rate, the faster individual’s signal will then consistently follow the simulated broadcast by a given delay. This phenomenon probably underlies most of the cases of experimental ‘‘phase locking’’ and ‘‘entrainment’’ reported in playback trials with rhythmic anurans (e.g., Loftus‐Hills, 1974; Zelick and Narins, 1985), which may thus be considered as experimental artifacts. Phase‐delay mechanisms do not necessarily entail period lengthening by approximately one free‐running period at the instant of resetting. In many acoustic insects and anurans, the lengthening can be much less than one free‐running period, perhaps reflecting a rapid rebound to the peak level following resetting (Fig. 11e). This effect is strongest when resetting by an external stimulus (e.g., a neighbor’s signal) occurs toward the end of the individual’s period. When the time length added at the instant of resetting is relatively short, mutually interacting individuals signal in an out‐of‐ phase, alternating relationship (Greenfield, 1994a; Greenfield et al., 1997). Again, playback experiments using single, isolated stimuli indicate that phase‐delay mechanisms incorporating rapid rebound may control signal alternation in various acoustic insects (e.g., Greenfield, 1994b; Minckley et al., 1995) and anurans (e.g., Lemon and Struger, 1980; Loftus‐Hills, 1974; Moore et al., 1989; Zelick and Narins, 1985). As in synchrony, paired individuals may only achieve regular alternation when their free‐running rhythms are roughly equivalent. In general, the rhythms observed in pairwise alternation are 25–50% slower than the free‐running rhythms that individual participants exhibit in solo (e.g., Cade and Otte, 1982). Normally, regular signal alternation is only observed in species and populations wherein individual free‐running rhythms are relatively slow; that is, <1 signalsec1 (Greenfield, 1994a,b). However, the converse is not true, as not all communal displays generated by slow signalers entail regular alternation among paired neighbors (e.g., Meixner and Shaw, 1986). That only synchronous displays are found where individual free‐ running rhythms are relatively fast, that is, 1 signalsec1 (e.g., Finke and Prager, 1980), may reflect physiological constraints operating within

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23

phase‐delay mechanisms: When the free‐running period is <1 sec in length, it may not be possible for the oscillator to rebound (ascend) to its peak level following resetting by a neighbor’s signal in an interval much less than one free‐running period. These considerations suggest that chorusing format in some species may be temperature dependent, shifting from alternation to synchrony as temperature rises and rhythms accelerate. 3. Stochastic Behavior in Phase Resetting Because even the most precisely timed communal displays are not generated by clockwork machinery, stochasticity may enter phase‐delay mechanisms and influence the resulting displays in several ways (Greenfield et al., 1997; Sismondo, 1990). First, stochastic variation in an individual’s signal length, effector delay, and free‐running rhythm, and in the phase adjustments to that rhythm when neighbors’ signals are perceived, have the potential to inject brief episodes of alternation within a synchronous interaction and of synchrony within an alternating one. Either of these departures is observed with varying incidences in most naturally occurring communal displays (e.g., Fig. 6a). Departures from regular synchrony may arise whenever an individual’s free‐running period is unusually long, such that he is reset by a neighbor prior the triggering of his own signal. Similarly, departures from regular alternation may arise when an individual’s period is unusually short, and he triggers his own signal just prior to or coincident with his neighbor’s broadcast (Fig. 11f) (e.g., Cade and Otte, 1982; Jones, 1966). Second, the initial phase relationships in evidence when a bout of communal display begins may determine whether it assumes an alternating or synchronous format. For example, consider two individuals whose signal interactions are controlled by a phase‐delay mechanism in which the oscillator rebounds rapidly to peak level following resetting by a neighbor. Ordinarily, these individuals would be expected to alternate signals, but if both happen to broadcast their initial signals at the same time, their succeeding signals will remain in synchrony (Fig. 11g). In this predicament, the likelihood of synchrony will depend on the length of the effector delay relative to the free‐running period, and on the variation inherent in the free‐running period. Synchrony is more likely when the effector delay is relatively long, which increases the possibility that one individual is not reset by the other during that initial cycle; and when variation in the free‐ running period is low, which increases the probability that the phase relationship occurring during the initial cycle does not shift. Either of these sources of stochasticity may account for the anomalous phase relationships observed in natural displays.

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D. COUPLED OSCILLATORS

AND THE

ATTAINMENT

OF

PERFECT SYNCHRONY

Whereas variants of phase‐advance and phase‐delay mechanisms may account for the majority of rhythmic communal displays, they do not appear to be responsible for the extremely precise displays of synchrony exhibited by Pteroptyx and Luciola fireflies in Southeast Asia. In the flash displays of P. malaccae, P. tener, and L. pupilla, sometimes termed ‘‘perfect synchrony,’’ individuals do not make major phase resettings upon perceiving a neighbor, but the adjustments to rhythm that they do make can last for many successive cycles (Ermentrout, 1991). These fireflies appear to adjust their actual free‐running rhythms to match their neighbors (Fig. 12), provided the difference between rhythms is small, and they rely largely on these adjustments to remain very nearly in phase with all individuals in the local population. A coupled‐oscillator model, developed by the Japanese physicist Yoshiki Kuramoto (see Strogatz, 2000) and modified by the American applied mathematician Bard Ermentrout (Ermentrout, 1991; also see Strogatz and Mirollo, 1990), provides an adequate description of communal signaling behavior in P. malaccae and may represent the underlying physiological mechanism. When a small cluster of oscillators (fireflies) happen to cycle (flash) with similar free‐running rhythms, they mutually affect each other such that the faster oscillators (signalers) slow down; the slower ones speed up, and all converge on a common rhythm and align in phase after a number of cycles. The model assumes that each individual oscillator continuously monitors its level relative to its neighbors and makes the appropriate decrement or increment in rhythm. Because the effects of synchronized oscillators add constructively and nearby oscillators exert a greater influence than more distant ones, oscillators adjacent to the small synchronous cluster will receive a strong and clear message and adopt the cluster’s rhythm. As this synchronous cluster of coupled oscillators grows, its message to neighbors will become ever stronger relative to that of the haphazard (asynchronous) cycling of other oscillators in the population.

Fig. 12. Attainment of perfect synchrony: A shortens its free‐running period during each successive cycle in response to perceiving B ahead of it in phase; similarly, B lengthens its free‐ running period during each successive cycle in response to perceiving A behind it in phase. A and B eventually synchronize and maintain equivalent free‐running rhythms.

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25

Thus, the cluster acts as a the nucleus of a crystal, and once its size reaches a critical population, the rhythm may quickly spread to thousands of oscillators as long as their initial rhythms are similar enough that they can make the necessary adjustment in free‐running rate. After communal synchrony is attained, minor phase‐delay adjustments may retain a nearly precise phase alignment between each individual and the overall group’s rhythm. Experiments with P. malaccae have shown that individuals can increase or decrease their free‐running rhythm by as much as 15% to synchronize with the population. Nonetheless, many questions remain on actual regulation of flash synchrony in Pteroptyx and Luciola fireflies, and we have precious few data on their communal displays in natural populations (Buck and Buck, 1968; Lloyd et al., 1989a,b). E. MODELING INTERACTIONS

OF

ADJUSTABLE OSCILLATORS

At first analysis, the various adjustable oscillators described for chorusing animals appear to represent a diverse set of mechanisms. However, most of these mechanisms can be modeled by a single graphical device, the phase response curve, PRC (Buck et al., 1981a; Greenfield and Roizen, 1993; Hanson et al., 1971). Phase response curves regress the response phase (the proportional change in length of the modified oscillator period relative to the free‐running, or previous, period) on the stimulus phase (the time during that modified period at which the stimulus began relative to the free‐running period), as shown in Fig. 13. Phase‐delay mechanisms that generate synchrony typically have a PRC with a relatively steep positive slope (0.7–1.0) and extend from a stimulus phase of approximately ‐60 to þ300 ; for mechanisms that tend to generate alternation, the PRC has a shallower slope (0.5–0.7) extending over this range of stimulus phase (Greenfield, 1994a,b). The transition phase, the break in the PRC occurring at approximately 300 (or ‐60 ), represents the beginning of the effector delay of the subsequent (or concurrent) period (Fig. 13b). Period lengthening occurs where the PRC rises above the x‐axis; period shortening occurs where it falls below. In general, PRCs for phase‐delay mechanisms cross the x‐axis slightly to the right of the origin at low stimulus phases (Greenfield et al., 1997). For phase‐advance mechanisms, the PRC begins toward the end of the concurrent period (at relatively high stimulus phase) and angles up toward the origin from a negative response phase (i.e., only period shortening occurs). Where a phase‐delay and phase‐advance mechanism are combined, as may occur in Mecopoda katydids (Hartbauer et al., 2005), the PRC resembles that found in a phase‐delay mechanism yielding alternation (shallow positive slope), except that the transition phase is at a much lower value, approximately 180 (Sismondo, 1990). For perfect

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Fig. 13. Phase‐response curve (PRC). (a) Phase‐delay mechanism showing calculation of stimulus phase and response phase. T, free‐running period; T0 , lengthened period modified in response to stimulus or neighbor; d, stimulus delay following onset of previous call by focal animal. (b) PRC, regression of response phase on stimulus phase, where oscillator rebound following resetting is equivalent to free‐running period, T. (c) PRC where oscillator rebound may be considerably shorter than T. (d) Sawtooth graph (Fig. 9; Fig. 11c) depicting adjustable oscillator responsible for relatively steep PRC in (b); where both animals use this oscillator, synchrony is predicted. (e) Sawtooth graph (Fig. 11e) depicting adjustable oscillator responsible for relatively shallow PRC in (c); where both animals use this oscillator, alternation is predicted (adapted from Greenfield, 1994a; used with permission from the Annual Review of Ecology and Systematics, Volume 25 # 1994 by Annual Reviews [www.annualreviews.org]).

synchrony generated by coupled oscillators, the PRC passes close to the origin and rises only slightly above (stimulus phase from approximately 0 to þ180 ) and below (stimulus phase from approximately þ180 to þ360 ) the x‐axis (i.e., only very small modifications in period length are

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made in a given cycle). Curiously, the PRC slope, and consequently the chorusing format, may shift in some species as stimulus amplitude is increased (Sismondo, 1990). A major advantage of using PRCs to describe chorusing mechanisms is that they lend themselves to characterization by simple algebraic models. Thus, chorusing mechanisms can be simulated, and the results can indicate the changing format of the chorus expected under different parameter values. This approach has been used for the basic phase‐delay mechanism, where Monte Carlo simulations of paired, equivalent signalers indicate how synchrony typically arises when the PRC slope is steep and alternation occurs where it is shallower than 0.7, as shown in Fig. 14 (Greenfield et al., 1997). Other parameters, including the length of the effector delay, the time required for the oscillator to return to basal level, lengths of the signal and the free‐running period, presence of tonic inhibition, transmission velocity of the broadcast signal, ability of a signaler to perceive a neighbor while broadcasting its own signal, and the degree of stochasticity in signal and interval lengths, also influence chorusing format—the relative incidence of synchrony versus alternation exhibited by the pair. But where the two signalers are slightly unequal in free‐running rhythm, and the PRC slopes are relatively shallow, the simulations predict a more complex format in which the phase relationship in the pair is incremented each

Fig. 14. Chorusing format generated by Monte Carlo simulation of two males whose signal rhythms are controlled by identical adjustable oscillators. For each pair of values of the oscillator return interval (r; see Fig. 9) and PRC slope (s; see Fig. 13b), the contour graph indicates the proportion of synchronous calling by the two simulated males. Diagonal hatching indicates bivariate region where synchronous calling occurs in >70% of call cycles; vertical dashes indicate bivariate region where synchrony occurs in <30% of call cycles (adapted from Greenfield et al., 1997).

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cycle. Consequently, a brief episode of synchrony occurs approximately every n cycles (Fig. 11h). IV. ADAPTATIONS AND EMERGENT PROPERTIES Determining the mechanisms underlying the specialized timing interactions among signalers and modeling their collective display are only the first steps toward understanding chorusing and related visual and vibrational phenomena. While we have a modest knowledge of how some communal displays are regulated, our understanding of the evolution of these events is generally poor. Here, I organize these explanations in broad categories and examine the evidence supporting the various hypotheses within each category. Chorusing and related phenomena may be classified as either adaptive or incidental. Adaptive phenomena are those in which the specialized communal display per se has been favored by selection. On the other hand, many chorusing phenomena are incidental byproducts that merely arise from the collective action of simple pairwise interactions (Camazine et al., 2001), which have been selected. From a different perspective, pairwise signal interactions and resulting communal displays are by definition social exchanges, which may be cooperative or competitive events (Otte and Loftus‐Hills, 1979). A. BYPRODUCT MUTUALISM 1. Synchrony: Beacon Effects, Rhythm Preservation, and Enemy Confusion To most observers of natural phenomena, synchrony evokes a notion of cooperation, a purposeful adjustment of rhythm in which the several participants benefit from the orderly communal display they generate. For example, the pacemaker cells of the heart must align their individual contractions in phase in order to create a single beat, without which the organism, and its constituent cells, would perish (Peskin, 1975). In animal communication, the adaptiveness of synchrony is less obvious, as it is not immediately clear why sexually advertising males—who are generally inclined to be strong competitors—would cooperatively arrange the manner with which they broadcast their signals. The various hypotheses proposed for adaptive synchrony focus on ‘‘byproduct mutualism’’ (Dugatkin, 2002) and group‐level benefits: enhanced attraction of females and reduced attacks from natural enemies that might be enjoyed by groups of signalers who broadcast in phase.

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First, male signalers who happen to be congregated in space, either passively because of habitat heterogeneity or actively because of lek formation, might call, flash, or vibrate synchronously in order to maximize the intensity of their collective broadcast (Greenfield, 1994a; Greenfield and Shaw, 1983). This byproduct mutualism proposition, termed the ‘‘beacon hypothesis’’ by firefly researchers (Buck, 1988; Buck and Buck, 1968, 1976, 1978), assumes that a male congregation competes with neighboring congregations for receptive females and that females are more responsive to peak signal amplitude than to amplitude integrated over a lengthy time interval. Were signals broadcast in an alternating format or haphazardly in time, the congregation’s amplitude integrated over multiple cycles of signaling would be higher, but the peak signal amplitude would never match the levels attained in synchrony (Fig. 15a). While cooperation among males within a congregation could maximize the number of females attracted to that group, it should be noted that female choice and male‐ male competition of some sort would be expected once females have arrived at the group (Forrest and Raspet, 1994). Importantly, the increased number of females attracted to the group would have to counterbalance the increased number of males present. Despite having been mentioned in the literature for many years, the beacon hypothesis has not been adequately tested, and no firm evidence in its favor exists for any synchronizing species. Second, a group of male signalers might broadcast in phase because synchrony allows females outside that group to hear the species‐specific rhythm (Walker, 1969). It is assumed that females must perceive this rhythm before orienting toward a male and that non‐synchronous signaling would obscure it. The rhythm‐preservation hypothesis may be a credible explanation in synchronizing species in which female preference imposes stabilizing selection on the male signal repetition rate, which exhibits little variance, for example, Oecanthus fultoni (Walker, 1957). (See Perdeck [1957] for an example of such stabilizing selection among acridid grasshoppers.) However, in other synchronizing species, female preference is open ended and thereby imposes directional selection on the male repetition rate, which varies considerably within and among individuals (e.g., Neoconocephalus spiza). Moreover, it is not clear that females perceiving several out‐of‐phase signalers in different directions would be unable to discern the rhythms from specific individuals. Recent studies suggest that acoustic insects and anurans commonly exhibit selective attention to specific individuals while ignoring spatially separated neighbors (Brush and Narins, 1989; Pollack, 1998; Ro¨ mer and Krusch, 2000; also see Section IV.B.4 of this chapter), suggesting that species‐ specific rhythms are not necessarily obscured by asynchronous signaling.

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Fig. 15. Beacon effect in group signaling. (a) Where the temporal integration time constant for processing received stimuli is short (<<1 signal period), perceived amplitude of the collective signaling produced by a group will be similar to the actual sound pressure level (SPL) of the group. Thus, the perceived amplitude of a group of alternating signalers (right) never attains the peak perceived values of a group of synchronizing signalers (left). (b) Where the temporal integration time constant for processing received stimuli is long ( 1 signal period), perceived amplitude of the collective signaling produced by a group will be relatively constant over time and will not reflect momentary peaks in actual SPL of the group. Because the group SPL of n synchronizers is much lower than n times the SPL of a single individual, the perceived amplitude of a group of synchronizing signalers (left) will be lower than the perceived amplitude of a group of alternating signalers (right).

As with the first hypothesis, rhythm preservation has not been tested with sufficient rigor to allow a definitive verdict at this time. A third way in which male signalers might benefit from synchronizing their rhythms is through evasion of predators and parasites that detect prey and hosts by localizing their signals (Greenfield and Shaw, 1983). Here, it is assumed that phonotactic and visually orienting predators and parasites would be thwarted from localizing any one potential victim when signals are synchronized and are perceived from all directions at once, a type of ‘‘mobbing effect.’’ But, does synchrony actually afford such confusion of natural enemies in natural populations? The only evidence in support

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of the enemy‐confusion hypothesis comes from a non‐rhythmic signaler, the Central American hylid frog Smilisca sila, a species in which males typically congregate near waterfalls and therefore call in an acoustic environment with substantial background noise. All males in these congregations will vocalize within a 0.5‐sec interval, remain silent for an indeterminate period of 30–60 sec, and then repeat the cycle many times during the nightly activity period. S. sila likely achieve this synchrony by responding with extremely short latencies (50–80 msec) to those individuals who happen to be motivated to call on their own, without the stimulus of neighbors (Ryan, 1986). These latencies may be achieved by an uncoupling of call detection from call recognition. Playback experiments have shown that broadcasts of synchronized S. sila calls draw fewer predatory bats (Trachops cirrhosus), which forage passively on frogs by listening for their vocalizations, than isolated calls (Tuttle and Ryan, 1982). In summary, while several plausible explanations for adaptive synchrony via byproduct mutualism are offered, little evidence currently supports any one. The communal displays most likely to represent adaptive synchrony may be those generated by coupled‐oscillator mechanisms, the cases of so‐ called perfect synchrony. The interactive format in perfect synchrony is, by definition, most precise, and the mutual adjustment of actual rhythms by the participants probably does not represent a simple emergent property or default phenomenon. Further study of the cognitive ecology of signalers and their natural enemies (Dukas, 1998), especially regarding the expression of selective attention (Dukas, 2002), is called for to evaluate the adaptive explanations. Investigations in which the genetic relationships among signalers are accounted for may also prove fruitful, as kin selection acting on displays of individuals occurring in groups of genetic relatives might favor synchrony per se. 2. Alternation: Enhancement of Signal Power, Unobscured Broadcast Time, and Perception of Rivals Can other formats of communal display also represent cooperative, adaptive phenomena? Regular alternation would demand the mutual adjustment of phase, and it could offer the participants a means of maximizing the effectiveness of their advertisements at several levels. Analogous to the beacon hypothesis for synchrony, alternation would maximize a group’s collective amplitude integrated over a lengthy interval, one cycle or longer (Fig. 15b). Should female receivers evaluate male groups by integrating signal amplitude over such intervals, groups in which individual signals are spaced out over the course of a cycle would be more attractive than groups with signals clustered in time. While theoretically conceivable, no observations support this notion, and the temporal integration time constants for

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signal evaluation in insect and anuran species that have been examined are considerably shorter than an average cycle (e.g., Faure and Hoy, 2000; Narins, 1992a; Prinz and Ronacher, 2002; Ronacher et al., 2000). In addition to having an even distribution of signaling over time, alternation may also be characterized as individual signalers broadcasting during open time slots. Thus, each male generates advertisement signals that are unobscured by neighboring males, which may be critical where females evaluate temporal or spectral information embedded within signals (Grafe, 1996, 2003; Schwartz, 1987, 1993). Additionally, each male is able to perceive his neighbors’ signals clearly and take appropriate action if necessary (e.g., shift position or adjust rhythm). The latter point follows from a general reduction in perception that acoustic animals experience during broadcasts of their own signals (Brush et al., 1985; Greenfield and Minckley, 1993; Hedwig, 1990; Narins, 1992b; Schwartz and Rand, 1991); for bioluminescent and vibrational channels, the incompatibility of signaling and perception has not been adequately investigated. Where these forms of signal interference occur, males may also be expected to alternate with certain heterospecific callers as they do with conspecifics. Such heterospecific signal interactions do occur and are particularly evident among acoustic insect species that call loudly and share the same frequency bands (e.g., Greenfield, 1988, 1990; Latimer and Broughton, 1984; Ro¨ mer et al., 1989; Schatral, 1990) and among anuran species that cluster at the same breeding ponds (e.g., Schwartz and Wells, 1983, 1984); see Aizawa (2000) for an example in visual signaling. Studies of both katydids (Greenfield, 1993) and tree frogs (Marshall, 2004; Marshall et al., 2005) have shown that females may not localize conspecific male calls that are overlapped by certain heterospecific calls. A closer analysis of alternation, however, suggests that this format too is unlikely to be cooperative and adaptive per se in many cases. While some studies have shown that females will orient toward a pair of alternating calls over a pair of overlapping ones (Bosch and Marquez, 2000, 2001), Passmore and Telford (1981) report the absence of this effect. The attractiveness of individuals within these pairs would need to be considered before judging alternation to be conferring mutual benefit: Would the leading (or following) caller in the overlapping pair have an advantage over either caller in the alternating pair? Additionally, it is not certain whether individual callers ever achieve regular alternation by mutually adjusting their free‐running rhythms to converge on a common value. Similarly, the alternating interactions observed in multi‐species choruses are normally characterized by a dominant/subordinate relationship: In acoustic insects, the species with more intermittent signaling (lower duty cycle) typically inserts its calls in gaps between calls of the more

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continuously singing species, which may be unaffected by the intermittent singer (Greenfield, 1988; Schatral, 1990). Moreover, in heterospecific signal interactions among North American Hyla treefrogs, females of a species (H. versicolor) with lower trill rates appear less able to localize conspecific calls when they are overlapped, whereas females of a species (H. chrysoscelis) whose calls have higher trill rates are not disoriented (Marshall, 2004). These points suggest that alternation of signals, like most cases of imperfect synchrony, is more readily explained in many species as an incidental byproduct or default phenomenon that emerges when two or more individuals, all resetting their rhythms via a phase‐delay mechanism, happen to be generating roughly equivalent rates. The following section describes why phase‐delay mechanisms may occur and how they may create these alternating and synchronous epiphenomena in various species. B. STRUCTURED COMMUNAL DISPLAYS

AS

EPIPHENOMENA

Because the signals forming alternating and synchronous displays are male sexual advertisements, an understanding of how and why these communal displays are generated cannot ignore female choice among and response toward male signals. In this section, we examine how receiver psychophysics (Wyttenbach and Farris, 2004) may influence females to choose males based on the relative timing of their signals, which can select for phase‐ adjustment mechanisms that collectively yield alternation and synchrony. 1. Receiver Psychophysics: Preference for Signal Order In the neotropical coneheaded katydid, Neoconocephalus spiza, females presented with the playback of conspecific male songs in two‐choice laboratory tests will orient toward the song comprised of longer chirps (Greenfield and Roizen, 1993). This choice is typical of arthropods communicating with airborne sound, substrate vibration, and bioluminescence: a largely open‐ended female preference, possibly subject to constraints at extreme values, for male signals that contain greater energy by virtue of delivery at a faster rate, length or continuity, or intensity (Greenfield, 2002). This preference, however, is reversed in N. spiza if the phase relationship between the two songs is adjusted so that the shorter one precedes the longer by only a brief interval, 12–70 msec; for a chirp period of 500 msec, this offset represents a phase angle of 8.6–50.4 (Greenfield and Roizen, 1993), as shown in Fig. 16. The same reversal of preference is observed when two songs differing in amplitude are adjusted in phase: Females prefer songs that are as much as 4 dB lower in sound pressure level (SPL) when the weaker one precedes the louder by a brief interval (Snedden and Greenfield, 1998). Similar preferences for leading acoustic

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Fig. 16. Precedence effect in the response of females of a coneheaded katydid, Neoconocephalus spiza, to playback of conspecific male calls. (a) Oscillogram of two stimulus calls presented from opposite sides of a laboratory arena in stereo playback trials; upper trace, 55‐msec call; lower trace, 27.5‐msec call whose onset leads the longer call by 12 msec. Both calls were delivered with a 500‐msec period, yielding a 24 phase angle between them. (b) Females generally orient toward the longer calls, save when the shorter calls lead by a brief interval: phase angles of 54 and 24 (adapted from Greenfield and Roizen, 1993; used with permission from Nature Publishing Group).

signals have been observed in several other katydids (Galliart and Shaw, 1996; Greenfield et al., 2004; Stiedl, 1991; Tauber, 2001), in grasshoppers (Minckley and Greenfield, 1995), and in frogs (Bosch and Marquez, 2002; Dyson and Passmore, 1988a,b; Dyson et al., 1994; Howard and Palmer, 1995; Schwartz, 2001); in some species, the preferences may extend to heterospecific interactions, and a female may orient toward a heterospecific call if it leads (and overlaps) a conspecific one (Marshall et al., 2005). The general characteristics of leading preferences are orientation or response toward the first of two or more spatially separated rhythmic songs, where the several songs are offset in time by a relatively small phase

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angle. In many cases, particularly in insects, it has been shown that the several songs need not overlap in time, implying that the preference for the leading song does not depend on the onset of the following song being physically obscured by the leader. Rather, ‘‘contralateral forward masking,’’ a form of non‐simultaneous temporal masking, in the receiver’s peripheral nervous system is likely responsible: Immediately following onset of a stimulus the receiver’s hearing sensitivity is inhibited on the contralateral side for a subsequent interval, which lasts 50–2000 msec in the various species studied (Ro¨ mer et al., 1997, 2002). Readers may note that the preferences for leading signals described above bear some resemblance to ‘‘precedence effects’’ known in avian and mammalian, including human, hearing (Litovsky et al., 1999; Wallach et al., 1949; Zurek, 1987). Precedence effects are mechanisms that allow a receiver to distinguish the initial sound generated by a source from echoes that follow in a reverberant environment. In humans and several other mammalian models in which precedence effects have been tested extensively, receivers presented with two clicks broadcast from different directions and separated by a brief time interval may: (1) perceive the sounds as a single (fused) auditory event when the interval is extremely brief; (2) perceive the sounds as broadcast from the location of the leading click; (3) exhibit a reduced discrimination of any variation in the following click (Litovsky and Shinn‐Cunningham, 2001). It is now suspected that the dominance of directional cues associated with the leading click reflects desensitization of central neural elements involved specifically with localization, not with general sensitivity (Freyman et al., 1998). Thus, a receiver may still be expected to perceive the following click, which would make the physiological basis of this effect operationally different from the preferences for leading calls in acoustic insects, and possibly in frogs as well (but see Marshall, 2004). Nonetheless, both mammalian and insect phenomena yield the same behavioral responsiveness toward leading acoustic stimuli and suppression of potential distraction by echoes. Additionally, some analyses indicate that the role of forward masking in human precedence effects cannot be ruled out (Gaskell and Henning, 1999). For these reasons, and for the sake of simplicity and to keep with prior terminology, I refer to the insect and anuran psychoacoustic phenomena discussed here as precedence effects sensu lato. 2. Signaler Response to Receiver Psychophysics: Selection for Phase Resetting In species where female response and orientation are influenced by a precedence effect that renders leading male calls more attractive ceteris paribus, selection can favor phase‐adjustment mechanisms by which males

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enhance their rates of encountering females. In particular, a resetting of signal rhythm leading to a decreased incidence of ineffective following calls and an increased chance of producing leading calls may be expected. While both results improve a male’s attractiveness, they are not functionally identical. Phase‐delay mechanisms, including inhibitory resetting, may offer a male one or both improvements (Greenfield, 1994a,b). Empirically, we evaluate these changes in incidences of following and leading calls via a ‘‘call delay histogram,’’ a graph depicting the frequency of a focal male’s calls in time bins beginning at the onset of a single, isolated stimulus call. In various rhythmically signaling species, call delay histograms show that males refrain from initiating calls during an interval beginning approximately 50–200 msec after stimulus onset and lasting 50–2000 msec (Greenfield and Snedden, 2003), as shown in Fig. 17. Importantly, this interval often, but not always, coincides largely with the interval during which female receivers do not respond to calls broadcast following a

Fig. 17. Frequency histograms of male calls produced at increasing delays measured from the onset of a single, isolated stimulus call (time 0) in various orthopteran species. Thick horizontal bar represents the duration of the precedence effect in female orientation: the time interval, relative to the onset of a leading call (time 0), during which a female will generally fail to respond toward a following call. (a) Tarbush grasshopper, Ligurotettix planum (Acrididae); (b) Coneheaded katydid, Neoconocephalus spiza (Tettigoniidae); (c) Katydid, Ephippiger ephippiger (Tettigoniidae), two‐syllable population; (d) Ephippiger ephippiger, one‐syllable population (adapted from Greenfield and Snedden, 2003; used with full acknowledgment from Brill Academic Publishers [# Brill Academic Publishers, Leiden, The Netherlands, 2003]). Calls given immediately following onset of the stimulus are interpreted as having been triggered prior to the stimulus. Hence, the time elapsing from stimulus onset to the beginning of the gap in male calls approximates the length of the effector delay in the endogenous oscillator.

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leading signal, here represented by the stimulus call. That the gap in male calling does not begin precisely at stimulus onset probably reflects the 50–100 msec effector delay: Once triggered by the central rhythm generator, calls cannot be aborted (Buck et al., 1981a). The call‐delay histogram in N. spiza (Fig. 17b) presents the interesting case in which the gap in male calling does not begin until the end of the interval during which female receivers do not respond to calls following a leading signal. Thus, N. spiza males do not immediately decrease their incidence of following calls by inhibitory‐resetting adjustments to rhythm. However, by inhibiting and resetting their rhythm, they may improve their chance of producing a leading call during the subsequent cycle. 3. Evolutionary Stability of Signal Interaction Mechanisms In order to analyze the predicted benefits of phase‐delay mechanisms in a more extensive way, the Monte Carlo simulation used to model pairwise signal interactions was rerun, except that this time the two males were made to differ in one critical parameter: one male adhered to the adjustment mechanism for phase resetting, while the other called regardless of his neighbor’s signals; that is, he called as if deaf (Greenfield et al., 1997). The incidences of leading and following calls of each male, as perceived by a female receiver positioned midway between the males, were then tallied. These pairwise simulations showed that resetting males produce calls that are more attractive to females provided that: (1) female perception is influenced by a precedence effect, and (2) the male oscillator returns to its basal level, after reaching its peak level and triggering a signal, over a relatively lengthy interval (Fig. 18). Both of these conditions are found in various chorusing species that have been analyzed. First, precedence effects in female response and orientation are reported in various chorusing insects and frogs in which male rhythm is controlled by a phase‐delay mechanism (Greenfield et al., 1997). These effects range from nearly complete dominance of the leading sound to a 70:30 preference for it over a following sound. The Monte Carlo simulation predicts that the resetting male will be more attractive with even slight dominance of the leading sound (i.e., a 55:45 preference for it). Second, analyses of oscillators in chorusing species suggest that return intervals are generally lengthy. Relative length of the oscillator‐return interval can be evaluated by inspecting the phase response curve (PRC), which will pass below the origin if the return interval is longer than the effector delay. This PRC feature is typically found in species displaying imperfect synchrony or alternation, and it may reflect selection imposed by female precedence effects as operating in natural populations. Because the velocity of sound is not infinitely fast (v ¼ 0.34 mmsec1) and calling males may be separated by

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Fig . 18. Relative attractiveness of two simulated males signaling with identical calls and rhythms, save that one adjusts its calls with an adjustable oscillator (phase‐delay mechanism) in response to a neighbor while the other does not (calls as if deaf). Calling of phase‐resetter is modeled as T0 ¼ (T þ e) þ s((d þ l/v) – (r – t)) þ (y – x); T, free‐running period; T0 , modified period following stimulus; e, stochastic element; s, PRC slope; d, stimulus delay; l, distance between two signalers; v, velocity of signal transmission; r, oscillator return interval; t, effector delay; y, stimulus length; x, signal length. For each pair of values of the PRC slope (see Fig. 13b) and the relative attractiveness of a leading call to females (a) or the PRC slope and the oscillator return interval (relative to the effector delay, t; see Fig. 9) (b), contour graph indicates the proportion of females expected to orient toward the phase‐ resetter; relative attractiveness is determined from the total number of leading and following calls produced by the two males. Diagonal hatching indicates the bivariate region where the phase‐resetter is more attractive than the non‐resetting male (adapted from Greenfield et al., 1997).

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long distances (>10 m), a male could reset his rhythm and time his call—from his own perspective—before a neighbor’s during the next cycle yet be perceived by a female situated close to that neighbor as a follower (Fig. 19a). He can overcome this relativistic debacle, however, by overcompensating in his resetting adjustment and leading his neighbor’s call by more than a minimum interval (Fig. 19b). A PRC passing below the origin is the indication of such overcompensation, and a lengthy oscillator‐return interval is one way for a male to move his PRC downward (Fig. 19c). The preceding observations strongly suggest that psychoacoustic influences on female choice, specifically precedence effects, have selected for

Fig. 19. Relativistic debacle in phase‐resetting. (a) In absolute time, phase‐resetting male calls slightly before its neighbor D, who calls as if deaf, but a female may perceive D’s call as leading if she is situated closer to him than to the phase resetter. (b) A phase resetter (A0 ) with a lengthy oscillator return interval (r; see Fig. 9) will advance its call relative to a neighbor (B0 ) more than a phase resetter with a shorter return interval (A) will, ceteris paribus. (c) The relativity adjustment gained by the phase resetter with a lengthy oscillator return interval (see Fig. 19b) is expressed as a PRC shifted downward and passing below the origin (solid curve, PRC0 ). In cases where the female preference for leading calls is strong and can override an amplitude difference, males following this adjustment may improve their attractiveness substantially.

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male phase adjustments in response to conspecific—and, in some cases, heterospecific—calls, which collectively generate temporally structured choruses in various acoustic insects and anurans. Monte Carlo simulations run with parameter values taken from these species show that males who make the adjustments call more attractively than males who do not—even in N. spiza, where the timing of the female precedence effect does not coincide with the post‐stimulus interval during which males do not initiate calls. These findings demonstrate that phase adjustment can be an evolutionarily stable strategy (ESS) in various rhythmic species (Partridge and Krebs, 1978). They also demonstrate the value of modeling for revealing subtle functions that might not be intuitively obvious at first analysis (i.e., why and how male signalers overcompensate when they reset their rhythms). 4. Selective Attention within Communal Displays Because females in natural populations seldom encounter a choice of only two male signalers and male signalers ordinarily have more than one signaling neighbor, full treatment of the relationship between precedence effects and phase‐adjustment mechanisms must consider more complex, realistic situations. Where a male signaler is surrounded by multiple signaling neighbors, he would ordinarily confront the following dilemma: Were he to adjust his phase whenever perceiving a neighbor, he would avoid producing ineffective following signals, but his signaling rate may be greatly reduced. On the other hand, if he ignores his many neighbors and forgoes phase adjustments, he may continue signaling at a relatively high rate, but his repertoire will include many following signals. But a third option—and potential solution—would be to employ selective attention toward a subset of signaling neighbors and effect rhythm adjustments only in response to them (Snedden et al., 1998). We now ask whether chorusing insects and frogs avail themselves of this potential solution and whether it actually does maintain a male’s attractiveness in a complex signaling environment. Where females arrive at a congregation of chorusing signalers and then make simultaneous comparisons among the males, we may expect that a given male’s strongest competitors are often his nearest neighbors. Thus, if selective attention is employed in rhythm adjustment, it might be directed toward only one or a few neighbors. That is, it might not matter to a male whether his calls follow a distant male, as females may be unlikely to compare the two signalers. Playback experiments conducted in the field on various chorusing insects have upheld some of these predictions (Minckley et al., 1995; Snedden et al., 1998). In Ligurotettix grasshoppers, species with female precedence effects in female orientation, males

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presented with stimulus calls broadcast from two loudspeakers positioned on either side but at different distances will reset their rhythms in response to the nearer loudspeaker while largely ignoring the other if its location is two or more times distant. When the distant call is the only one presented, however, males will respond to it. From the perspective of relative signal amplitude, these findings may imply that a male tends to ignore signals that are perceived as weaker than the loudest by an SPL differential of six or more dB. But in Neoconocephalus spiza katydids tested in the same manner, an SPL differential of at least 12 dB was needed to elicit ignoring of the weaker (more distant) broadcast (Greenfield and Snedden, 2003). To evaluate whether selective attention influences how the precedence effect functions, female N. spiza were tested in a laboratory sound‐attenuating chamber with four loudspeakers positioned in the four cardinal directions and at various distances (Snedden and Greenfield, 1998). By timing the loudspeaker broadcasts of stimulus calls such that three of the loudspeakers followed the leading one in close succession, it was determined that females still oriented toward the leader unless it was perceived as four or more dB weaker than the followers; females could pick out the leader among multiple calls, but they would attend to later signals if the leader was considerably weaker (more distant). While the above experiments on male rhythm adjustment appear to indicate a ‘‘sliding threshold mechanism’’ regulating selective attention, several alternatives might also be operating (Fig. 20). A male may attend to the n loudest calls—a ‘‘fixed number mechanism’’—or he may combine this rule with a sliding or fixed threshold. These several possibilities were investigated in the Tu´ ngara frog Physalaemus pustulosus, another species with a strong precedence effect in female orientation, using the four‐ loudspeaker arrangement (Greenfield and Rand, 2000) (Fig. 21a). When the loudspeakers broadcast stimulus calls at a rapid rate such that silent gaps did not occur (Fig. 21b), male P. pustulosus exhibited a pattern of selective attention toward a subset of the loudspeakers that indicated a sliding threshold mechanism (Fig. 21c). They attended to the loudest one plus any whose perceived SPL was within 6 dB. But further testing showed that this sliding threshold was modified by a fixed number mechanism that varied with absolute amplitude level and that arbitrary decision rules might also be used. At lower amplitude levels, the males generally did not attend to more than two loudspeakers, even when three or more exceeded the sliding threshold, but the way in which they selected two loudspeakers while ignoring the others was not clear. These findings indicate that a hidden structure may underlie the seemingly chaotic timing of calls in a dense chorus. They also offer a glimpse of the potential complexity that can govern rules of interaction contributing to such structure.

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Fig. 20. Potential selective attention protocols in choruses. (a) Absolute threshold: focal male (filled circle) attends to any neighbor whose calls exceed a fixed amplitude, or who is located within a given radius (filled squares); more distant neighbors (open squares) are ignored. (b) Fixed number: focal male attends to the n loudest, or nearest, neighbors (filled squares; n ¼ 2) provided they exceed a perceptual threshold; he ignores all other neighbors (open squares) regardless of their call amplitude. (c) Sliding threshold: focal male attends to the loudest, or nearest, neighbor and all others (n ¼ 3) whose call amplitudes are within x dB of that loudest one; x ¼ 6 dB in the depicted example (adapted from Snedden et al., 1998; used with permission of Springer Science and Business Media).

Among other anurans, some investigators have found similar spatio‐ temporal structuring in choruses (Boatright‐Horowitz et al., 2000; Brush and Narins, 1989; Schwartz, 1993), whereas others have found little correlation between call‐timing interactions and distances separating the interacting callers (Schwartz et al., 2002). This variation may reflect the different influences of male spacing and density, call‐timing mechanisms, and female psychoacoustics on chorusing among anuran species. In some communal sexual displays, a focal male may attend to particular neighbors based on their activity rather than their location. For example, in the fiddler crabs Uca annulipes and U. tangeri, males modify their leg‐ waving advertisement when courting a female, and this modification is often detected by neighboring males, who then limit their signal interactions to the courting male (Pope, 2005). Presumably, this form of interceptive eavesdropping and selective attention improves a male’s opportunity for intervening in that courtship, even when he has not observed the female directly.

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Fig. 21. Selective attention in male Tu´ ngara frogs (Physalaemus pustulosus). (a) Laboratory testing arena showing positions of four loudspeakers around central male. (b) Pseudorandom sequence used to time broadcasts of stimulus calls from the four loudspeakers. In any given playback trial, the loudspeakers all broadcast identical calls, but their gains were adjusted to different amplitudes. (c) Attention to loudspeakers in four playback experiments in which males were tested with four different sets of call amplitudes (90–78 dB, 84–72 dB, 81–69 dB, 78–66 dB). Bars indicate numbers of males that refrain from calling during a specific interval following onset of stimulus call (adapted from Greenfield and Rand, 2000; used with permission of Blackwell Publishing).

As was done earlier with pairwise signal interactions, the Monte Carlo simulation developed to model phase‐delay mechanisms was adapted to accommodate choruses of multiple males visited by multiple females (Greenfield et al., 1997). Thus, the conditions under which phase‐delay mechanisms would be favored by selection might be evaluated in a more realistic setting. Up to 10 simulated males were spaced randomly or in a regular pattern on a two‐dimensional grid and designated as phase‐ resetters or deaf callers, as before. The males were also assigned one of

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various levels of selective attention, ranging from attention to only one (nearest) neighbor, or those neighbors within a short radius, to attention toward all other males in the grid. Similarly, up to 10 females were designated to exhibit a modest precedence effect and then assigned one of the various levels of selective attention. To test the evolutionary stability of phase‐resetting, the relative attractiveness to females enjoyed by a single deaf caller within a chorus of up to nine phase‐resetters was evaluated (Fig. 22). As expected from our consideration of the dilemma faced by a male signaler in a dense chorus, the single deaf caller exceeded his phase‐ resetting neighbors in attractiveness, unless the resetters—and the females—showed a high level of selective attention. Conversely, a single phase‐resetter in a chorus of up to nine deaf callers was less attractive than his deaf neighbors, unless he—and the females—showed a high level of selective attention. These simulation results demonstrate that a male phase‐delay mechanism can be an ESS when a precedence effect influences female choice—but only if both males and females show a high level of selective attention toward their nearest neighbors. Importantly, the level of selective attention predicted by these simulations is quite high: No more than one or two males can be attended by males, and no more than two or three males can be attended by females in order for phase resetting to be evolutionarily stable. Multi‐channel recordings of natural choruses in three species of Orthoptera, each characterized by precedence effects in female choice and phase‐resetting in male signaling, largely confirmed the simulation predictions. In two alternating species, Ligurotettix planum (Acrididae) and Ephippiger ephippiger (Tettigoniidae) (Fig. 4), and one synchronizer, Neoconocephalus spiza (Tettigoniidae) (Fig. 5a), the recordings demonstrated that calling males typically attended to only one (L. planum, E. ephippiger) or two (N. spiza) neighbors (Greenfield and Snedden, 2003). That is, they reset their rhythms in response to the calls of the nearest one or two neighbors while ignoring the rest (Narins, 1992a; Schwartz, 1993), as shown in Fig. 23. In E. ephippiger, further tests with male choruses showed that female mate choice was based heavily on relative call rate, but influences of relative call timing were also detected (Berg and Greenfield, 2005). Where call rates and other signal parameters were equivalent, females exhibited a 70:30 preference for leading calls, a precedence effect strength comparable to that observed in two‐choice playback tests in the laboratory. 5. Summary: Epiphenomenon Model To summarize the above modeling and empirical findings, chorusing in various species of acoustic insects and anurans appears to be an epiphenomenon that originates in psychoacoustic precedence effects and

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Fig. 22. Evolutionary stability of phase resetting in simulated choruses of multiple males. Each simulated chorus included nine phase‐resetting males and one non‐resetter; 10 females were allowed to choose among the 10 males based on their production of leading and following calls. (a) Phase‐resetting males attend to all neighbors; females attend to all males in the chorus. (b) Phase‐resetting males attend only to their nearest neighbor; females attend only to the two nearest males. For each pair of values of the PRC slope (see Fig. 13b) and the oscillator return interval (relative to the effector delay; see Fig. 9), the contour graph indicates the mean attractiveness of phase‐resetters as compared with the single non‐resetter. Diagonal hatching indicates the bivariate region where phase‐resetting is more attractive on average than non‐resetting (adapted from Greenfield et al., 1997).

relies on the presence of selective attention in perception. Precedence effects could be a means of reducing distraction by echoes, but the potential arrival of echoes from many directions suggests that these effects may also be means by which animals improve directional hearing (see Ro¨ mer et al., 2002). That precedence effects occur in both arthropods and chordates implies

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Fig. 23. Selective attention in a chorus of five male tarbush grasshoppers, Ligurotettix planum (Acrididae). Matrix indicates strong (X) and weak (x) attention, indicated where a focal individual refrains from calling during a specific interval (see Fig. 17a) following onset of neighbor’s call. Relative male locations are mapped below matrix; arrows show attention between males (adapted from Greenfield and Snedden, 2003; used with full acknowledgment from Brill Academic Publishers [# Brill Academic Publishers, Leiden, The Netherlands, 2003]).

convergent evolution, perhaps shaped by universal physical constraints in the design of sensory systems (Dumont and Robertson, 1986) and by strong selection for mechanisms of stimulus localization. Attention toward nearby, loud stimuli largely represents sensory adaptation to ambient noise level, a process that allows an animal to pick out a given individual(s) against the background din of a chorus, regardless of the absolute sound level (Brumm and Slabbekoorn, 2005). Where precedence effects influence the hearing of female receivers, selection favors male rhythm adjustments that reduce the incidence of calls that follow neighbors while at the same time increasing the incidence of those that lead, a form of ‘‘sensory exploitation’’ (sensu Ryan et al., 1990; see also Ro¨ mer et al., 2002). Thus, communal synchrony and alternation may simply be emergent properties (Camazine et al., 2001) that arise by default when local signalers sustain

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comparable call rates. Under these circumstances, the temporal structure per se may be of no interest to females choosing mates and of no benefit to males generating the chorus. While the epiphenomenon model may offer a cogent account of chorusing in certain species, its overall explanatory value among acoustic insects and anurans is presently unclear. We do not know the full extent of precedence effects influencing perception and orientation. For example, these effects may be selected against in those species where perception of echoes is critical. Moreover, where precedence effects are known to occur, their overall importance in female choice in natural choruses is seldom determined. Much of this gap in our knowledge stems from a general lack of information on how females actually choose males in the field. That is, we have little understanding of how long females assess choruses and individual males within a given chorus, the routes traveled during their assessment phase, and the number of males that they may evaluate prior to mating (but see Murphy and Gerhardt, 2002; Schwartz et al., 2004). Finally, chorusing interactions do not invariably occur where precedence effects influence perception in rhythmically singing species (e.g., Wyttenbach and Hoy, 1993), and we are unable to identify why such displays form in some species but fail to arise in others. Two factors pertinent to our assessment of the epiphenomenon model are that it does not necessarily preclude other mechanisms, and it may operate over only specific time scales. In many anurans, males effect signal timing adjustments that allow them to call suddenly in very brief gaps that arise in a chorus, and thereby avoid masking. These same adjustments may also allow males to avoid broadcasting following calls, toward which females seldom orient. The importance of time scale is seen in certain anuran species that produce lengthy multi‐note calls. Here, females may prefer calls whose individual notes lead, even when the entire call follows (and overlaps) the neighbor’s call. Can the epiphenomenon model for imperfect synchrony and alternation operate in signaling modalities other than airborne sound? This possibility may depend on the way in which a receiver processes signals that are transmitted and arrive at approximately the same time but from different directions. In the case of substrate vibrations, normally detected by receptors in the legs (arthropods) or inner ear (anurans), precedence effects and selective attention may be expected. Paired receptors, or paired sets in arthropods bearing receptors in multiple legs, are used to localize the source of a surface (Rayleigh) or bending wave created by the vibration (e.g., Cocroft et al., 2000), and in some species vibration‐sensitive receptors are anatomically associated with the tympanal ears that detect airborne sound (Greenfield, 2002). Thus, mechanisms that enhance the relative

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sensitivity of the ipsilateral receptor (or receptor set) over the contralateral one following detection of the initial wave group might operate. Several recent studies indicate temporally structured male communal displays in leafhoppers (Hunt and Morton, 2001), wolf spiders (Kotiaho et al., 2004), and ghost crabs (David Clayton, personal communication; Fig. 5c) signaling with rhythmic substrate vibrations. Except in the wolf spider Hygrolycosa rubrofasciata, however, responses by female receivers have not been investigated to examine whether precedence effects or other preferences based on signal order might impose selection on the male signal interactions. In visual signaling, either via bioluminescence or reflected light, a receiver generally does not experience difficulty in localizing the direction to the source, and specialized mechanisms enhancing responses to one stimulus over another might not be expected. Thus, it may come as a surprise to learn that females in synchronizing species among both fireflies, Photinus pyralis, (Vencl and Carlson, 1998), and fiddler crabs, Uca annulipes (Backwell et al., 1998, 1999), have been found to exhibit precedence effects in response to leading flashes and leg waves, respectively. Possibly, attention toward a specific visual stimulus can be more of a problem than had been anticipated, particularly where general visual resolution is poor, as is often the case in arthropods, or when multiple stimuli appear at once in the visual field. As with acoustic perception, a mechanism for locking onto a given (leading) stimulus might prevent a receiver from distraction by surrounding ones—and yet be vulnerable to selection for signal timing adjustments that generate synchrony. Clearly, much work is needed to improve our understanding of interaction mechanisms and receiver psychophysics in these non‐acoustic modalities. 6. Receiver Psychophysics Revisited: Shifts in Preference for Signal Order Before closing the book on the overall importance of precedence effects in selecting for phase‐adjustment mechanisms among rhythmic signalers and ultimately generating the temporally structured choruses we observe, it is appropriate to consider alternative evidence and models. Whereas the great majority of studies on signal order report positive responses by receivers to leaders and a disregard for followers, several recent studies on synchrony in non‐rhythmic signalers report otherwise and merit our focus. In the wolf spider Hygrolycosa rubrofasciata, males signal to females by drumming briefly (ca. 1 sec) on the substrate at irregular intervals of 1–9 drummingsmin1 (Kotiaho et al., 2004). Neighboring males synchronize their signals, and playback experiments show that females are more responsive to leading signals than following ones when the drummings are loosely clustered in time (i.e., 3-sec elapses from the onset of one

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drumming to the next). However, under tighter clustering in which only 1sec elapses between drumming onsets, females shift their preference toward the follower or last signal. Do these results imply that following preferences, perhaps effected by a receiver’s need to perceive an unobscured signal ending or by a type of backward masking (Gaskell and Henning, 1999), may operate in some species? While such psychophysical effects are possible and may conceivably enhance stimulus localization, several questions must be asked at this point. Our most fundamental question is a logical one that was not encountered in considering precedence effects in receivers and signal competition via phase resetting in rhythmic singers to avoid generating following calls: Given a female preference for signals that immediately follow a leader, why would a male ever opt to initiate signaling? Perhaps males vary in energy or motivation, and those individuals who happen to be high in either may be more liable to initiate, provided that other males are often unable or unwilling to follow each signal. On the other hand, males who follow may actually have higher motivation or energy reserves, which allows them to respond very quickly to a neighbor’s call. If responding quickly to a neighbor’s signal is a reliable indication of male energy, quality, or condition, then female preference for following calls may be favored by selection. Investigating these several possibilities thoroughly will demand both game theory modeling, and analyses of male and female responses to signal order and signal energy and power. But another potential explanation of the shift in female preference toward following signals in H. rubrofasciata is an artifact of design of the playback experiment: Leading and following signals were not presented from different directions, and female responses interpreted as preferences for following signals may have simply represented drumming replies given at the end of a tight succession of male advertisement drummings. Here, further investigation of the relative timing—and spacing—in male‐female duets is needed. In other species featuring male‐female dialogues, such as fireflies (Case, 1984) and various katydid species (Bailey, 2003; Bailey and Hammond, 2004; Heller and von Helversen, 1986; Robinson et al., 1986; Tauber et al., 2001), female replies are given in a specific time window following the end of a male’s signal, partly as a means of species and mate recognition and partly to avoid signal jamming. Similar findings in the African running frog Kassina fusca indicate, however, that observed shifts in female preference toward following signals may be genuine. As in H. rubrofasciata, male K. fusca advertise to females with brief (ca. 140 msec) calls at irregular intervals (1–160 callsmin1). Neighboring males synchronize their calls, and playback experiments show that females preferentially orient toward leading calls when they precede the onsets of following calls by 15–70 msec (an overlap of 50–90%) (Grafe,

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1999). However, when the delay between leading and following call onsets is increased to 105–125 msec (an overlap of 25–10%), female preference shifts toward the following call. Importantly, male K. fusca typically respond to the playback of stimulus calls by overlapping only the final 20% (a delay of 100–140 msec). While the phonoresponses of K. fusca males would appear to be a means of signal competition for effective broadcasting time at the expense of a neighbor, we must again ask why males in natural choruses ever initiate calls and whether those whose call endings are overlapped deploy any countermeasures. Without speculating further on possible solutions to this apparent instability, I suggest that recordings of natural choruses, with special attention to variation in male calls, call rates, and phonoresponse latencies, and to female orientation toward chorusing males, are necessary for a fuller understanding. C. FEEDBACK LOOPS: CAN EMERGENT PROPERTIES ALSO FUNCTION SELECTIVE SIGNALING ENVIRONMENTS?

AS

Another challenge to the epiphenomenon model of communal sexual display is the possibility that in some circumstances sexual selection might favor certain aspects of a synchronous or alternating chorus and, consequently, underlying psychophysical effects that drive it. For example, females often prefer male signals delivered at faster call rates (e.g., Berg and Greenfield, 2005; Gerhardt, 1991, 1994; see Branham and Greenfield, 1996 and Jennions and Backwell, 1998 for examples in bioluminescent and reflected‐light signaling), possibly as a reliable means for assessing male energy reserves; but a female’s precise evaluation of signal rates could be impaired when among a dense congregation of chorusing males. Where a precedence effect exists in female receivers and male signalers have evolved a phase‐resetting mechanism, however, females may be able to assess male call rates more easily. The faster signalers would do most of the calling, whereas the slower ones would seldom call because of being trapped in a cruel bind: Forgoing phase‐resetting would lead them to produce a high incidence of ineffective following calls, while practicing it—which males generally seem to do when interacting with their nearest neighbors—would lead to repeated inhibition and a slow call rate. Thus, a precedence effect can magnify small differences between males in an energy‐based signal character and thereby render it more readily evaluated by females. This possibility underscores how a receiver trait that is at first selectively neutral in a sexual context can become favored by sexual selection on receivers via a feedback loop that ultimately reinforces its maintenance (Greenfield, 1997) (Fig. 24).

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Fig. 24. Feedback loop augmenting selection for precedence effect in female response. (a) Males A and B call independently with relatively fast and slow free‐running rhythms, respectively, until time x, after which B calls less frequently owing to repeated resetting in response to A’s calls (see Fig. 11c); that is, the small difference in call rhythm is magnified during interactive calling. (b) Precedence effect in receivers may originate in selection for efficient localization. Where this effect influences female response, phase‐resetting mechanisms may be selected in male signalers. Phase‐resetting magnifies small differences in call rhythm, thereby affording females more precise evaluation of males and ultimately increasing selection maintaining precedence effect.

Other feedback loops may arise because a chorus establishes an acoustic environment that can favor certain properties in the male phase‐adjustment mechanisms. In analyzing selective attention in orthopteran choruses, it was observed that male selective attention in two alternating species (Ephippiger ephippiger, Ligurotettix planum) was strong, being limited to one nearest neighbor, while selective attention in a synchronous species (Neoconocephalus spiza) was weaker (Greenfield and Snedden, 2003). While a pattern based on three species, chosen without regard to their phylogenetic relationship, ought not to be over‐interpreted, it is nonetheless tempting to speculate that in an acoustic environment (alternation) where calls are initiated at all times, males may be selected to reset their phase in response to only a limited number of neighbors. But in an acoustic environment (synchrony) where most calls are initiated all at once and then

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Fig. 25. Feedback loop augmenting selection for selective attention in male signal adjustment mechanism. Where precedence effect in receivers influences female response, phase‐ resetting mechanisms that include selective attention to nearest neighbors may be selected in male signalers (the feedback loop at the top of the diagram, augmenting receiver psychophysics, is outlined in Fig. 24). Phase‐resetting yields alternating choruses as an emergent property where the rebound following resetting is rapid. Alternating choruses immerse a male participant in an acoustic environment where sound is present at most times, thereby increasing selection pressure maintaining selective attention to particular neighbors (adapted from Greenfield and Snedden, 2003; used with full acknowledgment from Brill Academic Publishers [# Brill Academic Publishers, Leiden, The Netherlands, 2003]).

followed by a general silent interval, strong selective attention may be less critical. That is, a male who resets in response to multiple neighbors in a synchronous chorus may still call at a relatively high rate. Here, feedback loops raise the possibility that a group effect (i.e., synchronous or alternating chorusing) arising merely as an emergent property may yet exert selection on the behavior of individuals who collectively create that property (Fig. 25). As a parting comment, I raise the question of whether perfect synchrony is an adaptation that evolved under such selection pressure.

V. SUMMARY

AND

PROGNOSIS

The fine temporal structure characterizing communal sexual displays may be an epiphenomenon in some, and perhaps many, species of rhythmically signaling animals. According to this model, alternation and

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synchrony, the latter format in particular, rivet our attention because of human perceptual sensibilities (Strogatz, 2003), but they are of little or no interest to female receivers—responsive primarily to leading signals or to signals unobscured by neighbors—or the male signalers who create them via phase‐resetting mechanisms. But notable exceptions exist, the most striking of which are cases of perfect synchrony, which appear to be established by mutual adjustments made by multiple individuals. Other communal displays that may not fit the basic epiphenomenon model are synchrony in non‐rhythmic signalers and synchrony driven by receiver preferences for following, as opposed to leading, signals. These various displays, which may co‐occur within the same family (Tettigoniidae) or even genus (Pteroptyx fireflies), are controlled by different mechanisms, and it would be of great interest to examine their evolution (Dumont and Robertson, 1986). For example, phase‐delay and coupled‐oscillator mechanisms both occur in Pteroptyx, which suggests that the underlying central neural elements for visual processing are much more similar than their behavioral manifestations. Do very minor changes in these elements yield the major differences in rhythmic control that we observe? And, what selection pressures might have favored a configuration of neural elements yielding phase‐delay control in one species (Pteroptyx cribellata) but a configuration yielding oscillator‐coupling in another (Pteroptyx malaccae)? While studies of communal sexual displays have taught us much about the neuromuscular control of rhythmic activity, receiver psychophysics, and certain aspects of signal evolution, important questions remain. We still do not understand why most communal sexual displays present their particular format of fine temporal structure, and field investigations are generally lacking. More importantly, specific hypotheses for the evolution and adaptiveness of synchrony and alternation have been tested all too seldom. These phenomena continue to fascinate us, however, and it is hoped that this appeal will lead to further exploration of communal displays and the much needed experimental analyses and studies in natural populations.

Acknowledgments Much of this chapter is based on or inspired by my own field and laboratory studies, as well as forays into the modeling of chorusing, and I thank the U.S. National Science Foundation, the University of California, Los Angeles, and the University of Kansas for supporting those research efforts. More recently, I was invited by the Animal Behavior Society to present a Fellow’s Lecture on the subject of cooperation and conflict in chorusing at its 2004 Annual Meeting held in Oaxaca, Mexico, and I have used that presentation as a guide for organizing this chapter. I am indebted to the many people attending that meeting with whom I discussed

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the ideas presented here, as well as to many colleagues, including Bob Minckley, Stan Rand, Igor Roizen, Andy Snedden, and Michael Tourtellot. The final version of this chapter benefited greatly from constructive suggestions by Jane Brockmann, Gerlinde Ho¨ bel, Marc Naguib, Rafa Rodriguez, Joshua Schwartz, and Peter Slater.

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Tauber, E., Cohen, D., Greenfield, M. D., and Pener, M. P. (2001). Duet singing and female choice in the bushcricket Phaneroptera nana. Behaviour 138, 411–430. Todt, D., and Naguib, M. (2000). Vocal interactions in birds: The use of song as a model in communication. Adv. Study Behav. 29, 247–296. Tuttle, M. D., and Ryan, M. J. (1982). The role of synchronized calling, ambient light, and ambient noise in anti‐bat‐predator behavior of a treefrog. Behav. Ecol. Sociobiol. 11, 125–131. Vencl, F. V., and Carlson, A. D. (1998). Proximate mechanisms of sexual selection in the firefly Photinus pyralis (Coleoptera : Lampyridae). J. Insect Behav. 11, 191–207. Walker, T. J. (1957). Specificity in the response of female tree crickets (Orthoptera, Gryllidae, Oecanthinae) to calling songs of the males. Ann. Entomol. Soc. Am. 50, 626–636. Walker, T. J. (1969). Acoustic synchrony: Two mechanisms in the snowy tree cricket. Science 166, 891–894. Walker, T. J. (1983). Diel patterns of calling in nocturnal Orthoptera. In ‘‘Orthopteran Mating Systems: Sexual Competition in a Diverse Group of Insects’’ (D. T. Gwynne and G. K. Morris, Eds.), pp. 45–72. Westview Press, Boulder, Colorado. Walker, T. J., and Greenfield, M. D. (1983). Songs and systematics of Caribbean Neoconocephalus (Orthoptera: Tettigoniidae). Trans. Am. Entomol. Soc. 109, 357–389. Wallach, H., Newman, E. B., and Rosenzweig, M. R. (1949). The precedence effect in sound localization. Am. J. Psychol. 62, 315–336. Wells, K. D. (1977). The social behaviour of anuran amphibians. Anim. Behav. 25, 666–693. Whitney, C. L., and Krebs, J. R. (1975). Mate selection in Pacific treefrogs. Nature 255, 325–326. Williams, K. S., and Simon, C. (1995). The ecology, behavior, and evolution of periodical cicadas. Annu. Rev. Entomol. 40, 269–295. Williams, K. S., Smith, K., and Stephen, F. M. (1993). Emergence of 13‐yr periodical cicadas (Cicadidae, Magicicada). Phenology, mortality, and predator satiation. Ecology 74, 1143–1152. Wilson, E. O. (1975). ‘‘Sociobiology: The New Synthesis.’’ Harvard University Press, Cambridge, Massachusetts. Wyttenbach, R. A., and Farris, H. E. (2004). Psychophysics in insect hearing. Microscop. Res. Tech. 63, 375–387. Wyttenbach, R. A., and Hoy, R. R. (1993). Demonstration of the precedence effect in an insect. J. Acoust. Soc. Am. 94, 777–784. Young, A. M. (1981). Temporal selection for communicatory optimization: The dawn‐dusk chorus as an adaptation in tropical cicadas. Am. Nat. 117, 826–829. Zelick, R., and Narins, P. M. (1985). Characterization of the advertisement call oscillator in the frog Eleutherodactylus coqui. J. Comp. Physiol. A 156, 223–229. Zurek, P. M. (1987). The precedence effect. In ‘‘Directional Hearing’’ (W. A. Yost and G. Gourevitch, Eds.), pp. 85–105. Springer‐Verlag, New York.

ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

A Functional Analysis of Feeding George Collier department of psychology, rutgers university new brunswick, new jersey, 08901, usa

I. INTRODUCTION Feeding is the prototypic behavior that is studied in a variety of different disciplines (physiology, psychology, nutrition, and ecology), venues, and economies—all with very different degrees of experimenter intervention. In psychology, many theorists were actually studying feeding behavior when they thought they were studying something else. In the first half of the 20th century, for example, Thorndike (1911), Skinner (1932a,b, 1938), and Hull (1943) sought the basic laws of learning in the behavior of hungry animals that performed some target behavior in exchange for food. A subsequent generation of psychologists also followed the classical approach in seeking the laws that govern choice (e.g., Herrnstein, 1970, 1974; Herrnstein and Loveland, 1975; Ito and Fantino, 1986; Lea and Roper, 1977; Navarick and Fantino, 1972), feeding hungry animals larger or smaller portions either sooner or later for performing some target behavior. In effect, ‘‘operant psychology started with a meal’’ (Collier et al., 1977, p. 28). Researchers who adopted this approach studied the behavior of animals because it was simpler and easier to reveal the basic processes that were presumed to underlie human behavior (Skinner, 1953). The significance of species differences was discounted. In the second half of the twentieth century, the emerging field of behavioral ecology attracted increasing attention (Collier and Rovee‐Collier, 1981; Heinrich, 1979; Krebs and Davies, 1978, 1984, 1991; MacArthur and Pianka, 1966; McFarland, 1977; Mellgren et al., 1984; Pietrewicz and Kamil, 1979; Pulliam, 1974; Pyke et al., 1977; Schoener, 1971). Researchers who adopted this approach viewed animal behavior as the product of evolutionarily successful strategies that minimized the cost to the animal of engaging in a given activity relative to the benefit of doing so. The cost was reckoned in terms of the amount of time and/or energy that animals allocated to the 63 0065-3454/05 $35.00 DOI: 10.1016/S0065-3454(05)35002-9

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solution of the many different survival‐related problems that they had to solve (Schoener, 1971), and the benefit was reckoned in terms of their immediate success in doing so and, ultimately, in terms of reproductive success. Because all survival‐related problems could not be studied at once, feeding was usually chosen as the model behavior, with the underlying assumption that an optimal (or efficient) solution to this survival‐related problem would predict an optimal (or efficient) solution overall. This approach yields a functional analysis of feeding behavior. These two basic approaches to the study of food intake, the classical approach and the functional approach, are characterized by four useful distinctions: (1) open versus closed economies, (2) single responses versus bouts of behavior, (3) reinforcement versus global contingencies, and (4) consumption versus foraging. In this chapter, I will consider these distinctions and present evidence that supports the utility of a functional analysis of feeding. Along the way, I will point out critical differences in the predictions for behavior that the two approaches have generated. These differences pose another major challenge for the generality of the so‐called ‘‘laws of learning.’’

II. DISTINCTIONS BETWEEN APPROACHES A. OPEN

VERSUS

TO THE

STUDY

OF

FEEDING

CLOSED ECONOMIES

Animals feed in one of two basic economies—open or closed. The use of an open economy characterizes the classical approach in which the experimenter, not the animal, initiates and terminates feeding bouts (‘‘when’’), chooses the venue (‘‘where’’), the resource (‘‘what’’), and the pattern of resource use (‘‘how much’’) by determining the length of a session, the intersession or inter‐bout interval, and the amount consumed. In studies using an open economy, animals are deprived to ensure that they are active and attentive during the limited session. They typically receive supplemental food outside of the experimental setting if they fail to acquire enough food within a session to maintain the experimenter‐specified body weight. The use of a closed economy characterizes the functional approach. Here, I define a closed economy as one that is determined by the animal. Thus, the animal—not the experimenter—chooses the venue; discovers, selects, and procures access to the resource; and then consumes or uses it. Thus, the animal, rather than the experimenter, determines the initiation, termination, and distribution of its bouts of feeding, that is, its pattern of resource use. In a closed economy, feeding entails a chain of behavioral

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Fig. 1. The feeding chain in closed economies.

and physiological events (Fig. 1). Closed economies occur in natural habitats in the animal’s niche (Owen, 1980). In laboratory simulations or agricultural versions of closed economies, the experimenter or farmer chooses the venue and the resource, but the animal procures access to the resource and uses it. Thus, the initiation, termination, and distribution of bouts (i.e., the pattern of resource use) are again determined by the animal (Collier, 1983; Collier and Johnson, 1990; Collier et al., 1977; Hursh, 1980). Traditional classical and operant conditioning paradigms are versions of the open economy: The experimenter determines the venue (cage, runway, maze, operant box, etc.), the contingencies, and the resources (a reward or an aversive event). A deprived animal eating meals in sessions in a refined, restricted, isolated, and asocial environment defines the quintessential operant paradigm for studying how the consummatory portion of the feeding chain is modified by experience. The classical approach has yielded a large body of reliable and lawful relationships that reveal the logic of association, consequences, and schedules of reinforcement (Domjan, 2003; Mackintosh, 1974). However, these relationships have had no predictive validity for field studies or laboratory simulations of feeding and drinking behavior, as both types of study involve a closed economy. Nor do these functions have generality for the study of species‐specific, survival‐ related activities such as courtship, parenting, predator avoidance, nesting, hibernation, territorial defense, migration, and so forth. In short, the fundamental difference between the classical and functional approaches to the study of food intake is the difference between open and closed economies.

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B. SINGLE RESPONSES VERSUS BOUTS

OF

BEHAVIOR

In the classical approach, the unit of analysis is the response, which is a physical unit. Response strength is measured in terms of probability, rate, latency, and resistance to extinction as a function of reinforcement, its schedule, and the homeostatic state of the organism (Skinner, 1932a,b, 1938). In the functional approach, the unit of analysis is a bout of behavior (e.g., a bout of feeding, drinking, running, nesting, courtship), which has biological dimensions that consist of innate, species‐specific behavioral units. Bouts are measured in terms of their frequency, size, duration, and distribution. Freely feeding animals, for example, eat in bouts (called meals) that are interpolated between bouts of other activities. The first rigorous, closed‐ economy laboratory study of feeding in freely behaving rats was by Richter (1927). He found that rats initiated 9–10 bouts of feeding daily (~70% in the dark) and consumed approximately 3 g per bout. From these results, Richter concluded that the ‘‘central problem of psychology’’ was the discovery of the determinants of the initiation and termination of bouts of behavior. Richter was perplexed by the fact that meal initiations and meal sizes appeared to be relatively random and uncorrelated, but total daily intake was constant. What started and stopped meals? How was information about intake from individual meals integrated into a total? To answer these questions, he shifted his research focus to physiological interventions that might influence the initiation and termination of meals (Richter, 1942)—a focus that is still central in most analyses of feeding and drinking. LeMagnen (1971) attempted to answer Richter’s conundrum of what started and stopped meals by hypothesizing that meal size and intermeal intervals were correlated—the so‐called prandial correlations. The preprandial correlation predicted that the longer the intermeal interval (‘‘deprivation’’), the larger the next meal; the postprandial correlation predicted that the larger the meal, the longer the succeeding intermeal interval (‘‘satiation’’). The prandial correlations were an averaging mechanism that predicted a relatively constant intake. LeMagnen (1983, 1985) subsequently emphasized the postprandial correlation and added a physiological mechanism that compared energy expenditure with caloric intake. Whether prandial correlations actually exist has been the subject of extended controversy (e.g., Collier, 1982; Collier and Johnson, 1990; Collier et al., 1977, 1999; deCastro, 1975; LeMagnen, 1985; Panksepp, 1973). Another account of the initiation and termination of bouts was embedded in the theory of homeostasis (Cannon, 1932), which proposed that the internal milieu was defended. By this account, feeding was initiated in response to perturbations of the internal milieu and was terminated when

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the perturbation ended and the stability of the internal milieu was restored—a depletion‐repletion model (e.g., Bolles, 1975; Booth, 1978; Cannon, 1932; Collier, 1964, 1969; LeMagnen, 1985; Novin et al., 1976). Most of the research on the depletion‐repletion model has been performed in open economies, although tests of the constancy of intake (i.e., regulation) have also been conducted in closed economies. More recently, an ecological account of the initiation and termination of bouts has emerged that focuses on the frequency, size, and distribution of bouts in terms of the total costs and benefits across many bouts of many different behaviors. The period over which an organism reckons the total costs and benefits of all bouts of behavior (i.e., the time window) is difficult to examine, but the time window for a single activity, feeding, will be considered in this chapter. The proximal determinants of the initiation and termination of a bout of feeding, however, remain unknown. C. CONSUMPTION VERSUS FORAGING The final behavioral portion of the feeding chain is consumption. Consumption is the behavior by which an animal actually consumes the food or uses the resource to which it has gained access. In analyzing the consumption cost of food, it has been convenient to use ‘‘portions of a meal’’ (e.g., bites of food or pellets, or sips of solutions) and to impose an instrumental price on each portion—for example, 10 bar presses per bite or sip. In fact, the consumption paradigm is the traditional operant conditioning paradigm in which the experimenter instead of the animal provides the initial access to the resource (i.e., an open economy). Recall that in a closed economy, the animal initiates access to a resource, which turns out to be a very important difference for both foraging and consumption. In nature, however, feeding entails more than merely eating; rather, feeding entails the performance of a sequence of foraging behaviors before the animal can actually consume its food (Fig. 1). In the traditional operant conditioning paradigm, researchers study only consumption, or within‐bout resource use, measuring either the rate at which hungry animals consume the food they are given (here, bar pressing is viewed as an arbitrary, initial feeding reflex; Skinner, 1932a,b, 1938) or animals’ choice of a response lever that will enable them to consume the largest amount of food in the brief period that is allotted for an experimental session. In these paradigms, a meal begins when the session begins and ends when the session ends. The foraging paradigm, in contrast, is modeled after the animals’ ecological niche. Here, animals are no longer in the open economy of the ‘‘welfare state,’’ in which the experimenter supplies the resource and determines the pattern of resource use. Rather, animals live in a closed economy in which

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they must solve the problems associated with feeding themselves. Among other things, they must initiate their own feeding bouts and then discover, evaluate, and earn access to the nutrients they consume. The animals must also determine: (1) the amount of food they consume on any given occasion (i.e., meal size) by terminating the feeding bout, (2) their total daily intake, and (3) the distribution or pattern of their meals—in addition to the distribution of the various other activities in which they engage. In laboratory simulations of foraging, animals achieve this autonomy by virtue of being housed in the experimental apparatus 24 hr per day with continuous access to food and water. There is no experimenter intervention except what is required for daily maintenance. It is not necessary to reduce the amount of external stimulation by enclosing them in barren, soundproof, and light‐tight boxes, as in traditional conditioning studies. Cats are free to roam about the lab, and the living cages of other animals are open to the sounds and activities of each other, the experimenters, intruders, and the lab—just as in a natural venue. All of the animals, irrespective of species, compensate for any distractions over time by altering the distribution of their activities. In fact, none of these so‐called ‘‘extraneous’’ factors affects the fundamental cost:benefit relationships that are measured. Even wild‐caught rats, which are notably shy, produce the same cost:benefit relationships as domesticated rats if they are provided a hiding place, such as a brown bottle (Kaufman and Collier, 1983a). Once the animal discovers where the resource is, acquisition is usually rapid. No shaping is required: The introduction of a manipulandum is the most interesting thing that has happened to the animal recently and incites its immediate attention. Its focus on the feeder is not driven by deprivation. Standard errors are very small, and only a few animals are required to establish reliable functions (Collier et al., 1977). Our many unsuccessful attempts to replicate LeMagnen’s (1971) prandial correlations led us to the discovery that the number of instrumental responses required to make the feeder available (the access or procurement cost) when the animal is allowed to eat a meal of any size is a major determinant of both the frequency of initiating meals and their size. Our meal termination criterion, 10 consecutive min without additional responding, was drawn from LeMagnen (1971), but we later verified the criterion via log survival functions (Collier et al., 1986). As access or procurement cost increased, the frequency with which the animal initiated meals decreased, and the size of its meals increased compensatorily. As a result, the animal’s total daily total intake was conserved (Fig. 2). This finding was not species specific. The relations between procurement cost and the frequency and size of bouts also hold for numerous other activities, including drinking, nesting,

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Fig. 2. Generic functions relating meal frequency, meal size, and total intake to log procurement price.

wheel running and treadmill activity, and temperature regulation (Collier et al., 1990; Marwine and Collier, 1979; Mathis et al., 1996; Schultz et al., 1999); and they hold for numerous species, including rats, Guinea pigs, cats, chickens, blue jays, and ferrets (Collier and Rovee‐Collier, 1981). The instrumental responses that are selected for study are arbitrary; they can be bar presses, wheel turns, panel pushes, chain pulls, key pecks, and so on. The particular responses that are studied do not affect the cost:benefit relationships that are obtained; rather, they are merely surrogates for the responses that animals use in natural settings and, in combination with fixed or variable schedules, simulate the time and energy costs of feeding (Collier and Rovee‐Collier, 1981). In the case of rats, gradually increasing the log procurement cost from 1 to 5,000 bar presses for access to a meal led to a monotonic, linear decrease in meal frequency and a monotonic, hyperbolic increase in meal size. Eventually, rats ate only one large meal per day (Collier and Johnson, 1990; Collier et al.,, 1972, 1986). Subsequent random presentations of the costs replicated the function. In the case of chickens, increasing the log procurement cost from 1 to 5,000 key pecks per meal led to one large meal every 3 to 4 days (Kaufman and Collier, 1983b); in the case of cats, not until the log procurement cost was increased to 10,000 bar presses per meal did they eat only one meal every 3 to 4 days (Collier et al. 1978; Kaufman et al., 1980). In every case, animals conserved total intake and maintained a constant body weight. When the caloric density of the diet is varied, animals must eat meals of different sizes more or less frequently in order to maintain a constant total

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daily caloric intake. Using a constant procurement cost of 80 bar presses per meal access and a constant consumption cost of 10 bar presses per pellet in a Latin‐square design, we required rats to earn access to and consume four diets that varied in caloric density from 2.5 to 4.0 kcal/g. Here, animals had to perform more bar presses within a meal when it consisted of low caloric density pellets in order to consume the same number of calories as when pellets were higher in caloric density. Again, animals solved the problem. Their total daily intake in grams was a declining function of caloric density, but their total daily intake in calories was constant over diets (Fig. 3). The animals achieved the constant caloric intake by decreasing meal frequency, decreasing meal size in grams, and increasing meal size in calories as the

Fig. 3. Two squads of four rats each foraged for food pellets differing in caloric density (2.5, 3.0, 3.5, and 4.0 kcal/g). Meal initiation cost 80 bar presses and consumption cost 10 bar presses per pellet. Eight control rats had free access to the same diets, and consumption was free. Each rat experienced all four caloric densities in a Latin-square design. The rats adjusted their intake so that they obtained a constant caloric intake. The caloric intake of foraging rats did not differ from that of controls. Reprinted from Johnson et al. (1986). Copyright # 1986, with permission from Elsevier.

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caloric density of the diet increased (Fig. 4). When rats were shifted from one diet to the other, their meal frequency shifted almost immediately to an appropriate value, but their meal size did not reach the new value for 4 to 5 days (Johnson et al., 1986). Each shift produced a typical contrast effect in meal size, with meal size initially overshooting after a shift to a higher caloric density diet and undershooting after a shift to a lower caloric density diet. The cost‐sensitive strategy of initiating fewer but larger meals when the access cost is higher has a net effect of minimizing procurement or access cost; however, large meals are expensive to process, which might explain why animals always revert to frequent, small meals when access costs are low (Woods, 1991). Optimal meal patterns represent a compromise between minimizing foraging costs by eating infrequent meals and minimizing processing costs by eating small meals. Although meal patterns are species‐specific and reflect an animal’s niche, they solve the same problems for all species: The critical variables that determine the pattern of feeding bouts are costs and benefits. We originally had expected that the prandial correlations would be strengthened when access costs increased because intermeal intervals became longer and meals became bigger. As it turned out, the average intermeal interval and average meal size were highly correlated between procurement costs, but the intermeal intervals and meal sizes at a given procurement cost were not correlated. In numerous studies over the years under a variety of conditions, however, we have still never found significant prandial correlations (Collier and Johnson, 1990). In short, Richter’s (1927) ‘‘randomness’’ persists. D. REINFORCEMENT VERSUS GLOBAL CONTINGENCIES In classical and operant conditioning paradigms, the reflex is the unit of analysis, and response strength is the measure of learning (Nevin, 1979; Pavlov, 1927). In the operant conditioning paradigm, response strength is a function of its immediate consequences. In the foraging paradigm, however, the intimate connection between responses and consequences (reinforcement) is broken. Response rate during procurement is not a function of the instrumental cost, and meal size (traditionally viewed as the ‘‘amount of reward’’) is determined by the animal. These differences raise a number of other questions about what determines the initiation and termination of meals. How, for example, do animals decide what size of meal to eat? One hypothesis is that animals regulate meal size by paying attention to the cost of the just‐earned meal. To explore this possibility, we used variable‐ratio rather than fixed‐ratio

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Fig. 4. Meal frequency and meal size in g and in kcal as a function of the caloric density of the diet. Reprinted from Johnson et al. (1986). Copyright # 1986, with permission from Elsevier.

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procurement schedules with rats and cats. Procurement costs were randomized within successive blocks of five meals. At the outset of the study, animals were presented with procurement costs that varied randomly from meal to meal within a five‐meal block. For rats, for example, the lowest‐ cost block required 1, 2, 4, 8, or 16 bar presses (geometric mean ¼ 4 bar presses) for access to a meal. For cats, the lowest‐cost block required 40, 80, 160, 320, and 640 bar presses (geometric mean ¼ 160 bar presses) for access to a meal. These block‐randomized procurement costs remained in effect until animals exhibited stable responding in terms of the frequency and duration of meals (i.e., 10–20 days). At this point, a block of higher procurement costs, still randomized over five meals, was introduced and remained in effect until animals’ behavior again stabilized, and so forth. For rats, the highest‐cost block required 128, 256, 512, 1,024, or 2,048 bar presses (geometric mean ¼ 512 bar presses) (Johnson and Collier, 1994). For cats, the highest‐cost block required 640, 1,280, 2,560, 5,120, and 10,240 bar presses (geometric mean ¼ 2560 bar presses) (Collier et al., 1997). Surprisingly, both rats and cats averaged meal costs across the random encounters within a block. The average frequency and size of meals for a given block of five meals did not differ from the frequency and size of meals taken by animals that were presented with single meal procurement costs equal to the geometric mean of each randomized block (for rats, see Fig. 5; Johnson and Collier, 1994). Figure 6 shows the meal sizes for rats at each of the five meal costs, from low to high, within each randomized block (Johnson and Collier, 1994). In fact, animals did not vary their meal size with meal access cost from meal to meal within a block, except at the highest average costs. Thus, meal size cannot be predicted from the cost of access to an individual meal; rather, the average meal size is appropriate to the average costs of the meals that are encountered within each block. These surprising results are interesting for at least three reasons: First, they show that consequences can be ‘‘reckoned’’ over long series of events, that is, globally, rather than event by event. Second, when the average cost is sufficiently high that an animal initiates a meal only infrequently, the average cost of meals must be constructed or integrated over these relatively infrequent encounters. That is, the average cost is calculated from the access costs of meals that can be separated by many hours or, in the case of cats, many days when procurement costs are high. This result reveals that the time window within which animals ‘‘calculate’’ average meal cost in a closed economy can be quite large. Third, regulating meal size according to average meal cost is clearly a viable strategy for animals living in variable environments.

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Fig. 5. Mean meal frequency (top panel), meal size (middle panel), and total daily intake (bottom panel) of four rats as a function of the procurement ratio (PR) when the procurement

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Still unclear, however, is the proximal mechanism by which animals regulate average daily intake over the randomly varying costs of the resources they encounter. According to conventional wisdom, two tendencies regulate meal‐ taking behavior: (1) as the intermeal interval increases, the tendency to initiate a meal increases (hunger); and (2) as meal size increases, the tendency to terminate a meal increases (satiation). Conventional wisdom also holds that concurrent physiological changes are the proximal causes of both tendencies. However, intermeal interval and meal size are coordinated parts of a global economic strategy that minimizes the total cost of access to food resources as those costs increase while defending total intake. In fact, the same cost‐minimizing relationships are seen between access cost and the exploitation of other resources (e.g., nesting, wheel running, temperature regulation) that have different physiological consequences than food and water. These findings suggest that meal patterns are not determined by the current homeostatic state of the organism. Rather, they are determined by the species’ niche, and they reflect the cost:benefit relations within that niche for the resources being harvested. This suggestion is further supported by the occurrence of anticipatory behaviors. For example, when procurement costs occur in a regular fashion,

Fig. 6. Mean meal size for four rats as a function of the procurement cost of the meal when the procurement cost within a block of five meals was randomized. The middle cost in each schedule is listed on the right. Reprinted from Johnson et al. (1994). Copyright # 1994, with permission from Elsevier.

cost per meal was constant (open circles) or randomized across a block of five meals (closed circles). On the x‐axis, ‘‘middle PR’’ refers to the geometric mean of a given block of five procurement costs (‘‘schedule’’). Reprinted from Johnson et al. (1994). Copyright # 1994, with permission from Elsevier.

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Fig. 7. The number of the meals taken by two rats in the light phase, the dark phase, and the total number of meals taken as a function of the increasing cost of procuring access to a meal in the dark phase (left panel) and in the light phase (right panel). Reprinted from Jensen et al. (1983). Copyright # 1983, with permission from Elsevier.

rats use this predictability to increase their efficiency of resource exploitation. That is, they are able to anticipate the future availability of a cheaper resource and restrict or even forego the use of a currently available resource that costs more. Rats, for example, normally eat approximately 70% of their meals at night (Collier, 1982; Richter, 1927). When we increased the procurement cost in the dark, rats initiated meals less often and ate larger meals in the dark (Jensen et al., 1983). As the nocturnal feeding cost continued to increase, rats finally switched from feeding nocturnally to a diurnal feeding pattern in which meal frequency and size were appropriate to the diurnal cost (Fig. 7). Likewise, when a day of high‐cost meals was

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followed by a day of low‐cost meals (rather than by another day of high‐cost meals), rats reduced or even eliminated feeding on the high‐cost days and ate more on the low‐cost days (Jensen et al., 1983; Morato et al. 1995). Again, this strategy defended total intake (Fig. 8; Morato et al., 1995). This anticipatory strategy can be an extended series of high‐cost meals preceding low‐cost meals. There is, of course, a species‐specific limit.

III. THE CURRENCY

OF

COST

What is the currency of cost for the animal (Schoener, 1971)? Is it time? Or is it effort? In the preceding studies, requiring a higher instrumental procurement cost (i.e., the number of responses that must be performed in order to produce access to food) also required that the animal spend more time completing it, thereby confounding effort and time. In an attempt to tease apart their contributions, we manipulated time independently of effort, defining procurement cost in terms of the amount of time that an animal had to wait after initiating a meal in order to feed (Mathis et al., 1995). One way to envision this problem is to think of the problem that is faced by a sit‐and‐wait predator like a cat in a field. In this study, rats pressed a bar once to start a timer, and then the bar was immediately retracted. When a preset interval had timed out, the feeder door opened, and food became available. When the animal terminated the meal by remaining out of the feeder for 10 consecutive min, the feeder door shut, and the bar was reinserted. The time between the single bar press and the opening of the feeder door progressively increased from only a few seconds to 46 hr. These times corresponded to the times required to complete the bar press requirement in previous studies in which number of bar presses had been progressively increased. The rats treated waiting time as a procurement cost, decreasing the frequency of initiating meals and increasing meal size as waiting time increased, just as they had when procurement cost was defined by the number of bar presses required to gain access to a meal (Fig. 9). The rats accomplished this feat by adjusting how long they waited after the end of a meal before bar pressing to initiate the next waiting time. Both activity level (wheel running) and presence at the feeder were monitored, and they remained relatively constant both within (during) a given waiting time and across different waiting times. These measures did not increase as waiting time increased, as might have been expected after the two longest delays, had animals exhibited typical deprivation effects. The surprising outcome, in terms of the classic view of learning derived from studies of deprived animals in open economies, is that a consequence which occurs so long

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after a single response—even as long as 2 days afterward—can control that response. So much for the generality of the classic principle of delay of reinforcement! Taking another tack, we examined the currency question by varying bar or wheel‐turn procurement effort (Collier et al., 2002). Here, we concurrently varied the effort of pressing a bar (5–1500 N) or turning a running wheel (0.5–32 Nm) and the procurement cost (i.e., number of bar presses or wheel turns, respectively). The results showed the usual decline in meal frequency and compensatory increase in meal size as a function of procurement cost. Here, too, time rather than effort accounted for the greater portion of the variance. The results of the preceding studies reveal that, for the procurement of food, the connection between action and consequences is global. Animals optimize their behavior over the temporal and physical structure of the environment instead of responding to immediate contingencies.

IV. CHOICE In our initial studies, we were concerned with how an animal optimized its acquisition and consumption of a single resource. To examine the costs and benefits of optimization further, we developed the apparatus that is diagrammed in Fig. 10. In this apparatus, the animal initiates a meal by pressing the ‘‘search bar,’’ which is activated during intermeal intervals as indicated by the cue light. Completing the instrumental requirement on the search bar turns off its cue light and turns on the cue light over one of the two feeders, which are differentiated by the procurement cost (number of bar presses) of accessing that resource (opening the feeder door, turning on the pellet magazine, raising the food cup, presenting the drinking tube, etc.), by the particular benefit (e.g., pellet size, caloric density, nutrient quality) that can be accessed there, or both. Resources varying both in cost and value are encountered sequentially in a random order. Depending on which cue light was lit, the animal can either accept the feeding opportunity that its search ‘‘turned up’’ by completing the procurement requirement or reject it and search further. To reject the meal Fig. 8. Daily meal frequency (top row), average meal size (middle row), and food intake (bottom row) over alternating days of a high procurement cost (400 bar presses/meal; filled circles) and a low procurement cost (10 bar presses/meal; open circles). Values are the means of six rats on each day. The open and filled columns (‘‘baseline’’) represent the means for each variable over 20 consecutive days at each cost. Reprinted from Morato et al. (1995). Copyright # 1995, with permission from Elsevier.

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Fig. 9. Mean meal frequency (top panel), mean meal length in min (middle panel), and total daily intake (bottom panel) of six rats as a function of the procurement interval. Filled squares represent random replications of selected points after the initial experimental series had been completed.

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Fig. 10. The choice apparatus. Activation of the search bar (left) during an intermeal interval is signaled by illumination of the search cue light. Completing the criterion number of bar presses on the search bar (the search cost) leads to illumination (in a random sequence) of one of two food patch cue lights (right), which signals the availability of that patch. The animal has the option of either accepting or rejecting the opportunity to procure access to that food patch. Making a criterion number of bar presses on the patch bar (the procurement cost) makes the patch available, as signaled by the consumption cue light, and enables the rat to earn a meal by performing a criterion number of bar presses per pellet (the consumption cost). Waiting for 30 s (passive rejection) or pressing the search bar a criterion number of times (active rejection) returns the program to the search mode, which is again signaled by illumination of the search cue light. Note that only one cue light is illuminated at any moment in time.

opportunity, the animal can wait 30 s (in some studies, the animal rejects it by pressing the search bar once), at which point the cue light over the feeder goes off, and the cue light over the search bar goes back on, indicating that the animal can now search again. In this choice paradigm, then, the animal must make three foraging decisions: (1) how often to search, (2) whether to accept or reject an encountered feeding opportunity (a food ‘‘patch’’), and (3) how large a meal to eat. Using this apparatus, we tested some of the predictions of the contingency model of choice. (For a review, see Schoener, 1987.) According to this model, the optimal exploitation of a sequence of encounters with patches of food or prey requires that an animal pursue access to a given patch or prey if, and only if, during the time the pursuit (procurement) of the patch or prey will take, the animal could not expect to locate a better patch or prey (MacArthur and Pianka, 1966). The model makes three fundamental

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predictions: First, a low‐cost patch should always be exploited; second, a high‐cost patch should either always or never be exploited (i.e., the acceptance function for a high‐cost patch or prey should be a discontinuous, step function of the cost difference between patches); and third, switching from acceptance to rejection of a high‐cost patch should depend on the frequency of encountering the low‐cost patch but not the high‐cost patch. In our choice procedure, after animals search for food and encounter a food patch, they can choose whether to accept the opportunity to procure that food patch or reject the opportunity and search further in the hopes of encountering a cheaper meal. We found that animals reliably made choices that tended to reduce their cost of feeding (Collier and Rovee‐Collier, 1981). As predicted by the model, they consistently accepted most of the opportunities to procure low‐cost meals; however, animals rejected a proportion of the low‐cost patches, and their acceptance of the high‐cost patches was a monotonically decreasing function of their cost, violating the second prediction of the model. The failure to generate a discontinuous function for the acceptance of high‐cost opportunities is termed a ‘‘partial preference’’ (Krebs and Davies, 1978; Stephens and Krebs, 1986). The usual explanation for a partial preference in terms of animals’ errors, however, is unlikely to apply in this instance because the function relating animals’ acceptance of high‐cost patches to their cost was both systematic and reproducible. In a second experiment, we varied the frequency of encountering the low‐ and high‐cost patches (Collier et al., 1998). Following search, an animal encountered the low‐cost patch either 50% or 20% of the time, meaning that its searches turned up the high‐cost patch either 50% or 80% of the time, respectively. The finding that rejection of the high‐cost patch was not affected by the frequency of encountering the low‐cost patch violated the third prediction of the model (Fig. 11). The number of searches per day and meal size increased as the relative frequency of high‐cost meal opportunities increased. These increases were greater for the 20%/80% condition. Meal sizes at the two patches did not differ, and total daily intake was conserved. Animals typically have multiple, exclusive resources that they can choose to exploit, and optimal allocation models of activities have been developed that predict their choices (e.g., McFarland, 1977). We examined how these choices interact when the access costs of each resource vary, specifically, the cost of access to food, water, nest, and a running wheel (Collier et al., 1990). We again found the usual functions—the frequency of initiating access to a given resource decreased, and the size of each bout tended to increase compensatorily as the cost of access to that resource

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Fig. 11. Mean daily opportunities rejected of six rats as a function of the high‐cost procurement price (low price ¼ 10 bar presses) when either the patches were encountered randomly but equally often (50%/50%, left panel) or when the low‐cost patch was encountered randomly 20% of the time (20%/80%, right panel). Figure 3 in Collier et al. (1998). Copyright # 1998 by the Society for the Experimental Analysis of Behavior, Inc.

increased. Total daily food intake and, to a somewhat lesser extent, total daily water intake were conserved. Some behaviors proved to be more elastic than others; that is, the animal’s total use of the resource was not defended as strongly. The relation between bout size and bout frequency, for example, was not reliably compensatory for wheel running and nesting. Further, the latter resources were increasingly likely to be abandoned as the cost of access increased (Mathis et al., 1996).

V. DEPRIVATION Together, the theory of homeostasis (Cannon, 1932) and the resulting depletion‐repletion model of motivation have formed the centerpiece of the classical approach to the study of food intake. Whereas a homeostatic account of feeding focuses on the internal state of the animal and the animal’s response to it, the ecological approach focuses on the state of the environment (i.e., niche variables such as the quality and quantity of food resources, the cost of the resources, predation, competition, etc.) and the animal’s response to it.

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The depletion‐repletion model of motivation has led to the experimental use of deprivation to stimulate repletion (Bolles, 1975; Booth, 1978; Kissileff and Van Itallie, 1982; Novin et al., 1976), and controlling body weight loss has become a standard technique for manipulating the degree of motivation. Thus, to ensure that motivation remains ‘‘constant’’ over successive sessions, experimenters reduce animals to and maintain them at a constant fraction (e.g., 80–90%) of their free‐feeding body weight throughout the course of an experiment. In fact, in traditional studies of conditioning and learning, deprivation has long been considered necessary to get animals to ‘‘do anything.’’ Thus, the experimenter deprives the animal of an essential resource and measures the rate at which the animal replaces it bite‐by‐bite (in the case of food) or sip‐by‐sip (in the case of water). As shown in Fig. 12, after some threshold value of log percent body weight loss (usually 10%) has been exceeded, the animal’s response rate increases monotonically up to the point of inanition (usually 40–50% log percent body weight loss) (Collier, 1969; Saltzman and Koch, 1948; see also Collier, 1964, and Collier and Levitsky, 1967). When percent body weight loss is used to ensure responding, experimental sessions are kept short so that increases in body weight

Fig. 12. Log bar presses per half hr as a function of log percentage of body weight loss (
) in thirsty rats. The E‐3 function represents data from independent groups who received a percentage of their ad lib water intake each day; the E‐4 function represents data from a group that was completely deprived of water except for the small amount received in the Skinner box. The rate of weight loss for each animal was different and most likely reflected their differing metabolic rates. Each point represents the average rate of bar pressing at a given percent of weight loss. Figure 2, bottom panel, in Collier (1969). Copyright # 1969 New York Academy of Sciences, U.S.A.

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(which would produce changes in response rate) will not occur, thus keeping the level of motivation constant throughout a session. In laboratory simulations that use closed economies and in nature, however, freely feeding animals rarely undergo body weight loss exceeding 7–10%; that is, they are rarely physiologically depleted. In fact, this degree of body weight loss marks the threshold between the ecologically based, closed economy, cost:benefit accounts of feeding and the homeostatic‐ based, open economy, depletion/repletion accounts of feeding (Collier et al., 1977). When the environment is predictable, animals that live in a closed economy can anticipate their requirements and feed anticipatorily. Deprivation results only from an emergency situation that leads to inanition. In nature, this situation may be caused by a failure of foraging or by an environment that has been disturbed (e.g., by flood, drought, blizzard, pests) or otherwise made unpredictable by factors such as competition or predation. Even though nondeprived animals that live in closed economies eat infrequently when meal costs are higher (i.e., their meals are larger, and their intermeal intervals are longer), their rates of responding remain constant. In contrast, the response rates of deprived animals increase when costs are higher, as discussed previously. Further, nondeprived animals that live in closed economies do not lose body weight, as they would if they were physiologically depleted or deprived. Instead, the larger amount of food that they consume is stored and metered out later, buffering any adverse effects of periodic intake on the internal milieu by ensuring that the animals never become physiologically depleted in the first place. Depending on the species, these storage mechanisms include the gut load, crop load, fat deposits, muscle stores, behaviors such as hoarding or caching, and so forth. Fat storage, for example, is a buffer against the extreme energetic demands of migration and cold, while crop storage is a common buffer against the nocturnal fast, which most birds undergo (Dawson et al., 1983; Griminger et al., 1969; Kaufman and Collier, 1983b; Richardson, 1970). Crop storage is also used when chickens are on a very large key‐peck procurement schedule that has reduced their meal frequency to one every 3 or 4 days. Their crop engorges during the meal and then slowly contracts over succeeding days as food is metered into the gut, until they initiate the next meal. In short, animals in closed economies pay attention to total intake—not to the momentary load, that is, the momentary amount ingested (Collier and Johnson, 2004). Satiation is presumably correlated with the momentary load. Animals also exploit the microenvironment as a buffer against weight loss. Figure 13 shows the apparatus in which animals lived continuously and that was maintained at an ambient temperature of either 23 or 3 C

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Fig. 13. A choice apparatus in which rats bar pressed for food pellets and access to a nest. The apparatus was housed in a refrigerator that enabled the ambient temperature to be maintained at either 23 or 3oC. The nest was maintained at either ambient temperature or could be heated to 23oC. Access to the nest could be gained by bar pressing. Nest access cost was varied from 10 to 320 bar presses. The procurement cost for access to the feeder was 20 bar presses, and the consumption cost of food once the feeder was accessed was either l0 bar presses per pellet (abundant condition) or 80 bar presses per pellet (scarce condition). Water was continuously available. Reprinted from Schultz et al. (1999). Copyright # 1999, with permission from Elsevier.

(Schultz et al., 1999). The apparatus contained a feeder that delivered a pellet each time the animal completed a specified number of bar presses (the pellet consumption cost) and a nest that either was maintained at the same ambient temperature as the apparatus or was independently heated. The animal could procure access to the nest by completing a specified number of bar presses (the nest procurement cost). The pellet consumption cost was either 10 bar presses per pellet (‘‘abundant food’’) or 80 bar presses per pellet (‘‘scarce food’’), and the nest procurement cost varied from 10 to 320 bar presses. Over the course of the experiment, all rats encountered three environmental conditions in a fixed order (warm cage and nest, cold cage and nest, and cold cage with warm nest) and two food abundance conditions (abundant, scarce) that were combined factorially.

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Thus, for example, when the cage was cold, animals could remain in the warm nest until, at some point, they might venture out into the cold cage and bar press a lot (scarce condition) or a little (abundant condition) for food. The basic question was how rats solve the problem of caloric expenditure versus caloric conservation and maintain a stable body weight when these conditions are pitted against each other. Some of the dynamics of the rats’ behavior are shown in Fig. 14. The top row shows total intake for the three environmental conditions when food was either abundant or scarce. As expected, food intake was greatest in the cold/cold condition, least in the warm/warm condition, and intermediate in the cold cage/warm nest condition. Food abundance did not affect total intake. The middle row shows that nesting time overall was a decreasing function of nest access cost. Interestingly, when the cage was cold, rats nested longer when food was abundant, whether the nest was warm or not. The bottom row shows that the body weight was greatest when food was abundant and decreased as the cost of nest access increased. The shift to each new environmental condition caused an initial drop in weight. In summary, when the ambient temperature of the cage and nest was warm and both the price of food and the cost of nest access were cheap, animals spent less time either feeding or nesting. Introduction of a cold ambient temperature into both cage and nest increased the amount of time spent in both activities. When the cage was cold and the nest was warm, rats spent more time in the nest, regardless of whether food was cheap (abundant) or expensive (scarce). So, how did rats deal with the ‘‘energy crisis’’ and maintain a stable body weight when nesting, feeding, and ambient temperature were pitted against each other? These results show that animals’ time budgets were determined jointly by strategies that reduced caloric expenditure and increased caloric intake. When the ambient temperature was cold, rats standing in the cold to bar press for food ate more as access to the nest got increasingly more expensive, whether the nest was cold or not. These strategies were successful: Except immediately following the unpredictable introduction of a new cold condition, animals maintained a stable body weight. In fact, animals’ body weight changed less than 2 g/day under even the most stringent conditions of nest access cost, food scarcity, and ambient temperature. Johnson and Cabanac (1982) obtained a similar result in an earlier study. When rats were required to leave a thermoneutral refuge and travel distances ranging from 1 to 16 m in the cold (–15 oC) in order to feed, their number of trips to the feeder decreased by >80%, but their meal duration increased compensatorily at all but the greatest distance. As a result, total intake was conserved.

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Fig. 14. Daily food intake (top panel), daily nesting time (middle panel), and body weight change (bottom panel) as a function nest access cost for four rats living an ambient temperature and nest temperature of 23oC (‘‘warm‐warm’’), 3oC (‘‘cold‐cold’’), and an ambient

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Digestive physiology provides a further buffer by which an animal adjusts to varied nutritional inputs. The interaction between this internal buffer and ecological factors has been characterized as ‘‘a dialog between the House Economist and the Resident Physiologist’’ (Collier, 1986). The vocation of the House Economist is the acquisition of multiple resources at the lowest possible costs and the greatest value, which requires an intimate knowledge of an animal’s niche. The vocation of the Resident Physiologist is the efficient utilization of the variable resources provided by the House Economist in defense of the internal milieu. Again, then, we see that a variety of physiological and behavioral mechanisms can buffer the differing patterns of food intake.

VI. SATIATION In studies using an open economy paradigm with deprived animals, the common finding is that the rate of intake within a meal gradually slows as a session proceeds. This decline in rate is attributed to satiation, which is thought to be the mechanism that determines the amount consumed. Is there any evidence of satiation in studies using a closed economy paradigm with nondeprived animals that initiate and terminate their own meals as a function of the cost of initiating the meal? The answer is ‘‘no.’’ Figure 15 shows a typical cumulative record of a rat whose procurement cost to gain access to a meal was 1,280 bar presses and whose consumption cost was 80 bar presses per pellet. In other words, after the animal had paid a price of 1,280 bar presses for access to the feeder (i.e., to activate the feeder), it then had to make 80 bar presses for each pellet that it subsequently received in the meal. The initial part of the cumulative record is the foraging component, and the latter part is the consumption component. As can be seen, the rate of responding differed between the foraging and consumption components. In this example, the procurement cost of 1,280 bar presses led the rat to consume only three meals in each 24‐hr period. As can be seen, its response rate did not decline over the course of any of the meals. Rather, the animal simply quit eating and left the feeder without returning for 10 consecutive minutes—the meal‐termination criterion that is seen in the flat portion of

temperature of 3oC and nest temperature of 23oC (‘‘cold‐warm’’). In each condition, food was either abundant (10 bar presses/pellet; open circles) or scarce (80 bar presses/pellet; filled circles). Reprinted from Schultz et al. (1999). Copyright # 1999, with permission from Elsevier.

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Fig. 15. The 24‐hr cumulative record of a rat that took three meals per day when the procurement cost was 1,280 bar presses per meal, and the consumption cost was 80 bar presses per pellet. The initial portion of each meal depicts bar pressing during the procurement phase. Each procurement phase terminated, and the ensuing consumption phase began at the tick indicated by the marker on lines 1, 6, and 7. The subsequent portion of the meal reflects bar pressing during the consumption phase. The flat portion of the cumulative record at the end of each meal indicates the 10‐min meal‐termination criterion period. The flat portions of the cumulative record between successive meals are the intermeal intervals.

the record at the end of each feeding bout. Also note that there was no relation between the length of the intermeal interval and the size of the subsequent meal—a fact that becomes especially apparent when several days of data are inspected (Collier, 1982). Another example from two different experiments (Johnson, 1996) is shown in Fig. 16, which presents the rate of pellet consumption within deciles of meals. As can be seen, there is no evidence that the rate of responding declines over successive deciles. In fact, satiation functions are found only when deprived animals are tested in open economies. In closed economies, meal termination by nondeprived animals is a function of costs and benefits rather than the momentary load (see Section IV.

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F IG. 16. Records from two different experiments (n ¼ 8) showing the pellets earned per min in deciles of meals.

‘‘Deprivation’’). The size of the meal is a function of meal cost and not of the momentary load or the intermeal interval (Collier and Johnson, 1990). The rate at which it is eaten is a function of cost, portion size, quality, and competition and not the amount eaten or the duration of the meal (Collier et al., 1992). So much for the traditional account that meal termination is due to satiation!

VII. CONSUMPTION COST VERSUS FORAGING COST Are meal size and meal frequency affected in the same way by foraging cost and consumption cost in a closed economy? Recall that when foraging cost increases, meal frequency decreases, and meal size increases compensatorily. Total intake is defended. In contrast, the main effect of increasing consumption cost in a closed economy is on meal size, which decreases as consumption cost increases. Because meal frequency does not increase compensatorily, however, total intake falls (Fig. 17). In economics, the

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Fig. 17. Generic figure depicting meal frequency, meal size, and total intake as a function of increasing log consumption cost.

decrease in bout size and the decline in intake as the price of consumption increases is known as the Demand Function (Hursh, 1980). Thus, the changes in meal parameters that accompany increases in consumption cost are the opposite of the changes that accompany increases in foraging cost. There are also other aspects of behavior that are affected by increases in consumption cost but not by increases in foraging cost. For example, as consumption cost increases, the time between successive pellets within a meal increases because of the increased number of responses that must be completed to obtain each pellet. During consumption, the only way an animal can minimize the increase in the total time required to eat as consumption cost (pellet price) increases is by increasing response rate. Thus, the rate of bar pressing for pellets increases with the increase in instrumental price per pellet, but the increase in response rate is not sufficient to conserve the rate of intake, which falls (Fig. 18). In contrast, when foraging costs (search cost, procurement cost) increase, response rate does not change. During the consumption component, if animals behave in a manner to conserve time while they are eating a meal, then they should respond faster when pellets are small than when pellets are large because they have to earn more of them in order to acquire the same total daily intake (equivalent to ~500 45‐mg pellets). In fact, they do (Collier et al., 1992) (Fig. 19). Similar results are obtained when magazine access time is varied: In order to meet their daily intake requirement and yet conserve the amount of time spent eating, animals also respond faster for brief periods of magazine access than for long ones (Collier et al., 1986). The finding that animals respond more slowly for pellets that are bigger and cheaper and respond faster for pellets that are smaller and more expensive (and faster for

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Fig. 18. Generic figure depicting bar press rate (presses/min) and the associated eating rate (pellets/min) within a meal as a function of increasing consumption cost.

Fig. 19. Rate of bar pressing as a function of pellet size (20, 45, and 97 mg) and two fixed‐ ratio consumption costs (10 and 40 bar presses per pellet).

shorter periods of magazine access) is contrary to the law of effect, which predicts that responding for larger rewards will be faster. This prediction, however, is manifested only in the behavior of deprived animals in open economies. So much for the generality of the principle of magnitude of reward! Next consider what happens when rats choose between food sources that differ only in consumption cost. Here, the foraging animal ‘‘searches’’ for a feeding opportunity and can either accept or reject a food patch that his search turns up (Fig. 10). The data in Fig. 20 are from an experiment in which the two food sources differed in both the price per pellet (consumption cost) and the size of each pellet (Johnson and Collier, 1989). Not surprisingly, when the pellet prices of the two food sources were equal, rats preferred the source containing larger pellets. They accepted more

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Fig. 20. Generic plots for rats foraging for pellets in the choice apparatus showing meal opportunities of large pellets (open squares) and small pellets (filled squares) accepted and the corresponding meal size (g) as a function of the increasing cost of large pellets when rats were given the option to accept or reject the opportunity to consume a meal following a search.

meal opportunities of large pellets, ate fewer but larger meals, obtained a larger total daily intake from that source, and spent less total time feeding. As the price of large pellets increased, thereby increasing the time required to earn them (the cost of small pellets was constant), animals’ preference increasingly shifted to the source containing the cheaper, small pellets. Eventually, rats took most of their meals at that source, ate larger meals of small pellets, and obtained a larger proportion of their total daily intake from small pellets. Further, as the price of large pellets increased, response rate for the more expensive, large pellets increased, but the eating rate (pellets/min) fell, as before (Fig. 21). Importantly, although the rats responded faster for the more expensive, large pellets, they chose them less often and ate fewer of them. These results differ from results obtained in open economies, where response rate is viewed as an index of preference

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Fig. 21. Rate of bar pressing for large pellets (closed squares) and small pellets (open squares) and associated eating rates (g/min) as functions of the increasing consumption cost of large pellets.

or a measure of motivation. In closed economies, response rate is not a predictor of preference! Figure 22 reveals how smart rats really are. Log relative intake, acceptance, and meal size at one source in relation to the other are plotted against the log relative profitability, in terms of the unit price, or g/bar press (left panels), and relative intake rate or g/min (right panels) (Johnson and Collier, 1989). The relative intake rate, or g/min, was the best predictor of relative intake patterns, thus confirming that time is the currency of cost. Similar results were obtained when the caloric density of the pellets, rather than pellet size, was manipulated, when the resource was water (Collier et al., 1994), and when feeding rate was manipulated by the use of fixed interval schedules rather than fixed ratio schedules (Johnson and Collier, 1994). Animals exploiting a patch containing finite resources must decide when to leave it and find another. A bear feeding at a berry bush, for example, has to work harder to harvest each berry as the number of berries left on the bush gets smaller. At some point, the bear will decide that too few berries are left to make it worth his while to harvest them, and he will abandon that bush and seek another berry bush to exploit. Patch depletion

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Fig. 22. Log relative intake (upper panels), log relative acceptance (middle panels), and log relative meal size (lower panels) of the less profitable of two available foods as a function of log relative unit price (g/bar press; left panels) or log relative eating rate (g/min; right panels) of the food. The correlations were high. The goodness of fit of each of the regression lines for unit price is R2 ¼ .70 (intake), R2 ¼ .55 (acceptance), and R2 ¼ .65 (meal size); the goodness of fit of each of the regression lines for eating rate is R2 ¼ .81 (intake), R2 ¼ .69 (acceptance), and R2 ¼ .83 (meal size). Reprinted from Johnson et al. (1989). Copyright # 1989, with permission from Elsevier.

strategies have been described in terms of the marginal value theorem, which states that an animal should leave a patch when the rate of return equals the average rate of return in the environment (Charnov, 1976). This decision is based on the amount consumed, the rate of return within the

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patch (which decreases as progressively less of the resource remains), and the cost of traveling to another patch. To simulate this problem in a closed economy, we used a progressive ratio schedule in which the price of a pellet progressively increased within a bout of feeding as an analog of the rate of return, and patch access (procurement) cost was an analog of inter‐patch travel cost. The progressive increment in pellet price within a patch and the cost of travel to patches (a fixed ratio schedule) were varied. As expected, the frequency of initiating a meal decreased, and meal size increased as the cost of access (inter‐patch travel) increased. However, the frequency of initiating a meal increased, and meal size decreased as the size of the increment in the progressive ratio increased; that is, the rat left sooner and ate smaller meals as the patch depleted more and more rapidly. Daily intake fell under the more stringent conditions (Fig. 23). These results did not conform exactly to the marginal value theorem: The animals stayed in the patch longer than predicted (Johnson et al., 1993). In an attempt to develop various rule‐of‐thumb versions of Charnov’s marginal value theorem that might account for this deviation, we varied travel cost, prey size (pellet size), and dense or sparse (rate of return) patches (Johnson and Collier, 1999). Again, meals were larger in denser patches (i.e., patches that offered a higher rate of return), in patches containing larger prey sizes, and when the travel time between patches was lower. These results suggest that meals are ended when the rate of return reaches some level relative to some comparison value. The end‐of‐meal rate of return was lower, however, than the average rate of return in the environment, which was calculated over both foraging and feeding time. As a result, meals were too large to either maximize rate of return or minimize foraging and feeding costs. The take‐home message from the preceding studies is that (1) an animal’s choice between food sources that differ in consumption cost (or pellet price) reflects the difference in profitability between the sources, and (2) the animal behaves in a way that maximizes profitability. These results are very different from those obtained from deprived animals that are tested in short sessions in an open economy. Under those conditions, deprived animals tend to minimize the delay to reward. In short, hungry animals have a problem being rational.

VIII. SUMMARY Studies of feeding in both open and closed economies produce repeatable, lawful relations, yet they differ in fundamental ways. The same variables, schedules, consequences, portion sizes, quality, and time

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Fig. 23. Rats earned a meal by first responding on a procurement schedule that simulated the cost, in time and/or energy, of traveling to (accessing) a food patch. After accessing the food patch, they then paid an instrumental price for each pellet (the consumption cost) from that patch on a progressive ratio schedule, which simulated the progressive depletion of the patch. Ending the meal at the patch was indicated by 10 consecutive min of no responding. Traveling to another patch was simulated by performing the original procurement schedule again. When the rat accessed the next patch, the progressive ratio schedule was reset and increased as before as the patch was depleted. Over the course of the study, all rats received three progressive ratio schedules in which pellet price within a meal was incremented by a factor of 1.05 (circles), 1.10 (squares), or 1.15 (triangles) times the preceding price. The mean meal size (top panel), meals per day (middle panel), and daily intake (bottom panel) are plotted as a function of increasing log procurement (travel) cost for six rats. Reprinted from Anim. Behav., 46, Johnson, D. F., Triblehorn, J., and Collier, G., The effects of patch depletion on meal patterns in rats, 55–62, Copyright # 1993, with permission from Elsevier.

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windows produce different functions in each. They differ in the unit of analysis. In classical learning studies in open economies, the unit of analysis is the reflex, which has physical dimensions (Skinner, 1932a,b, 1938). Functions are determined by contingencies between stimuli, responses, and consequences. Consequences are characterized by immediacy, magnitude, and quality. The homeostatic state of the organism is varied to increase attention, the level of activity, and the effectiveness of consequences. Response strength is measured by probability or rate of responding and choice. Reinforcement is not a universal principle but describes only a very limited set of behavioral relations within a meal. The function of learning is the discovery of the structure of the environment. Learning is studied in open economies to insulate it from regulatory behavior. The relationships discovered in open and closed economies, however, are fundamentally different. Studies that take a functional approach are performed in closed economies. In feeding studies conducted in closed economies, the unit of analysis is bouts of behavior, which have biological dimensions consisting of innate, species‐specific behavioral units. The pattern of feeding in closed economies is a function of cost‐benefit algorithms and an animal’s energy budget. Costs are minimized; benefits are maximized; and energy and nutrients are efficiently processed, allocated, conserved, and stored. Costs and benefits have different effects on foraging and consumption. Response rate and total intake during foraging are independent of costs and dependent on benefits, whereas response rate and total intake during consumption depend on both costs and benefits. The pattern of intake as a function of foraging costs jointly optimizes access cost and processing costs while total caloric intake is defended; that is, during foraging, the time window over which costs and benefits are calculated is the regulatory window. The proximal mechanisms by which these costs are calculated and integrated over time are unknown. These relations reflect the fact that animals have been shaped by natural selection for optimal resource exploitation. Their problems are threefold: the optimal allocation of time and effort to biologically important resources, the optimal exploitation of a resource, and the acquisition of the required amount and kind of resources within natural time windows. The function of the initiation and termination of feeding bouts is to optimize the regulation and use of resources. Currently, the emphasis of this analysis has been on the efficient exploitation of resources. More than a half‐century ago, Richter (1927) set up the problem. Today, we know the functional determinants of the initiation and termination of meals, but we still do not know their proximal causes.

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Acknowledgments This chapter is based in part on an invited address presented at a workshop entitled ‘‘Psychological Mechanisms of Food Intake’’ that was held at the University of Wu¨ rzburg, Germany, in June, 2003. The research reported in it was funded by grants AM‐31016, DK‐ 31016, and HD‐10588 from the National Institutes of Health. As can be seen from the references, this chapter is heavily indebted to my students and, especially, my late colleague, Deanne Johnson. The chapter has undergone intense, critical commentary by my wife, Carolyn Rovee‐Collier, to whom I am intensely grateful.

References Bolles, R. C. (1975). ‘‘Theories of Motivation,’’ 2nd ed. Harper, New York. Booth, D. A. (1978). Prediction of feeding behavior from energy flows in the rat. In ‘‘Hunger Models’’ (D. A. Booth, Ed.), pp. 227–278. Academic, New York. Cannon, W. B. (1932). ‘‘The Wisdom of the Body.’’ Norton, New York. Charnov, E. L. (1976). Optimal foraging: The marginal value theorem. Theor. Pop. Biol. 2, 129–136. Collier, G. (1964). Thirst as a determinant of reinforcement. In ‘‘Thirst’’ (M. J. Wayner, Ed.), pp. 287–300. Pergamon, Oxford. Collier, G. (1969). Body weight loss as a measure of motivation in hunger and thirst. Ann. NY Acad. Sci. 157, 594–609. Collier, G. (1982). Determinants of choice. In ‘‘Nebraska Symposium on Motivation: Response Structure and Organization’’ (D. Bernstein, Ed.), pp. 69–127. University of Nebraska Press, Lincoln. Collier, G. (1983). Life in a closed economy: The ecology of learning and motivation. In ‘‘Advances in the Analysis of Behavior. Vol. 3: Biological Factors in Learning’’ (M. D. Zeiler and P. Harzem, Eds.), pp. 223–274. Wiley, Chichester. Collier, G. (1986). The dialogue between the House Economist and the Resident Physiologist. Nutr. Behav. 3, 9–26. Collier, G., Hirsch, E., and Hamlin, P. (1972). The ecological determinants of reinforcement in the rat. Physiol. Behav. 9, 705–716. Collier, G., Hirsch, E., and Kanarek, R. (1977). The operant revisited. In ‘‘Handbook of Operant Behavior’’ (W. K. Honig and J. E. R. Staddon, Eds.), pp. 28–51. Prentice‐Hall, New York. Collier, G., and Johnson, D. F. (1990). The time window of feeding. Physiol. Behav. 48, 771–777. Collier, G., and Johnson, D. F. (2004). The paradox of satiation. Physiol. Behav. 82, 149–153. Collier, G., Johnson, D. F., and Berman, J. (1998). Patch choice as a function of procurement cost and encounter rate. J. Exp. Anal. Behav. 69, 5–16. Collier, G., Johnson, D. F., Borin, G., and Mathis, C. E. (1994). Drinking in a patchy environment: The effect of the price of water. J. Exp. Anal. Behav. 62, 169–184. Collier, G., Johnson, D. F., Cy Bulski, K. A., and McHale, C. (1990). Activity patterns in rats as a function of the cost of access to four resources. J. Comp. Psychol. 104, 53–65. Collier, G., Johnson, D. F., Hill, W. L., and Kaufman, L. W. (1986). The economics of the law of effect. J. Exp. Anal. Behav. 46, 113–136. Collier, G., Johnson, D. F., and Mathis, C. E. (2002). The currency of procurement cost. J. Exp. Anal. Behav. 78, 31–61.

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Collier, G., Johnson, D. F., and Mitchell, C. (1999). The relation between meal size and time between meals: Effects of cage complexity and food cost. Physiol. Behav. 67, 39–346. Collier, G., Johnson, D. F., and Morgan, C. (1992). The magnitude‐of‐reinforcement function in closed and open economies. J. Exp. Anal. Behav. 57, 81–89. Collier, G., Johnson, D. F., and Morgan, C. (1997). Meal patterns of cats encountering variable food procurement costs. J. Exp. Anal. Behav. 67, 303–310. Collier, G., Kaufman, L. W., Kanarek, R., and Fagen, J. (1978). Optimization of time and energy constraints in the feeding behavior of cats. Carnivore 1, 34–41. Collier, G., and Levitsky, D. (1967). Defense of water balance in rats: Behavioral and physiological responses to depletion. J. Comp. Physiol. Psychol. 64, 59–67. Collier, G., and Rovee‐Collier, C. (1981). A comparative analysis of optimal foraging behavior: laboratory simulations. In ‘‘Foraging Behavior: Ecological, Ethological, and Psychological Approaches’’ (A. C. Kamil and T. Sargent, Eds.), pp. 39–76. Garland STPM Press, New York. Dawson, W. R., Marsh, R. L., and Yacoe, M. E. (1983). Metabolic adjustments of small passerine birds for migration and cold. Am. J. Physiol. 245 (Reg. Integ. Comp. Physiol. 14), R755–R767. deCastro, J. M. (1975). Meal pattern correlations: Facts and artifacts. Physiol. Behav. 15, 13–15. Domjan, M. (2003). ‘‘The Principles of Learning and Behavior.’’ Wadsworth, Belmont, CA. Griminger, P. W., Villamil, V., and Fisher, H. (1969). The meal‐eating response of the chicken: Species differences and the role of partial starvation. J. Nutr. 99, 368–374. Heinrich, H. (1979). ‘‘Bumblebee Economics.’’ Harvard University Press, Cambridge. Herrnstein, R. J. (1970). On the law of effect. J. Exp. Anal. Behav. 13, 243–266. Herrnstein, R. J. (1974). Formal properties of the matching law. J. Exp. Anal. Behav. 21, 159–164. Herrnstein, R. J., and Loveland, D. H. (1975). Maximizing and matching on concurrent ratio schedules. J. Exp. Anal. Behav. 24, 107–116. Hull, C. L. (1943). ‘‘Principles of Behavior.’’ Appleton‐Century‐Crofts, New York. Hursh, S. R. (1980). Economic concepts for the analysis of behavior. J. Exp. Anal. Behav. 21, 159–164. Ito, M., and Fantino, E. (1986). Choice, foraging, and reinforcer duration. J. Exp. Anal. Behav. 34, 219–238. Jensen, G. B., Collier, G., and Medvin, M. B. (1983). A cost‐benefit analysis of nocturnal feeding in the rat. Physiol. Behav. 31, 555–559. Johnson, D. F. (1996). Do freely‐feeding rats exhibit a satiety function? Poster presented at the meeting of the Society for the Study of Ingestive Behavior, Banff, CA. Johnson, D. F., Ackroff, K., Peters, J., and Collier, G. (1986). Changes in rats’ meal patterns as a function of the caloric density of the diet. Physiol., Behav. 36, 929–936. Johnson, D. F., and Collier, G. (1989). Patch choice and meal size of foraging rats as a function of the profitability of food. Anim. Behav. 38, 285–297. Johnson, D. F., and Collier, G. (1994). Meal patterns of rats encountering variable food procurement cost. Anim. Behav. 47, 1279–1287. Johnson, D. F., and Collier, G. (1999). Prey size and prey density affect meal patterns of rats in depleting and nondepleting patches. Anim. Behav. 58, 409–419. Johnson, D. F., Triblehorn, J., and Collier, G. (1993). The effects of patch depletion on meal patterns in rats. Anim. Behav 46, 55–62. Johnson, K. G., and Cabanac, M. (1982). Homeostatic competition in rats fed at various distances from a thermoneutral refuge. Physiol. Behav. 29, 715–720.

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Kaufman, L. W., and Collier, G. (1983a). Cost and meal patterns in wild‐caught rats. Physiol. Behav. 30, 445–449. Kaufman, L. W., and Collier, G. (1983b). Meal‐taking by domestic chicks. Anim.Behav. 31, 397–403. Kaufman, L. W., Collier, G., Hill, W. L., and Collins, K. (1980). Meal cost and meal patterns in an uncaged domestic cat. Physiol. Behav. 25, 135–137. Kisseleff, H. R., and Van Itallie, T. B. (1982). Physiology of the control of food intake. Ann. Rev. Nutr. 2, 371–418. Krebs, J. R., and Davies, N. B. (Eds.) (1978). ‘‘Behavioral Ecology.’’ Sinauer Associates, Sunderland, MA. Krebs, J. R., and Davies, N. B. (Eds.) (1984). ‘‘Behavioral Ecology.’’ Blackwell Scientific Publications, London. Krebs, J. R., and Davies, N. B. (Eds.) (1991). ‘‘Behavioral Ecology.’’ Blackwell Scientific Publications, London. Lea, S. E. G., and Roper, T. J. (1977). Demand for food on fixed‐ratio schedules as a function of the quality of concurrently available reinforcement. J. Exp. Anal. Behav. 46, 93–103. LeMagnen, J. (1971). Advances in studies on the physiological control and regulation of food intake. In ‘‘Progress in Physiological Psychology, Vol. 4’’ (E. Stellar and J. M. Sprague, Eds.), pp. 203–261. Academic, New York. LeMagnen, J. (1983). Body energy balance and food intake: A neuroendocrine regulatory mechanism. Physiol. Rev. 63, 314–386. LeMagnen, J. (1985). ‘‘Hunger.’’ Cambridge University Press, Cambridge. MacArthur, R. H., and Pianka, E. R. (1966). On the optimum use of a patchy environment. Am. Nat. 100, 603–610. Mackintosh, N. J. (1974). ‘‘The Psychology of Animal Learning.’’ Academic, New York. Marwine, A., and Collier, G. (1979). The rat at the waterhole. J. Comp. Physiol. Psychol. 93, 391–402. Mathis, C. E., Johnson, D. F., and Collier, G. (1995). Procurement time as a determinant of meal frequency and meal duration. J. Exp. Anal. Behav. 63, 295–309. Mathis, C. E., Johnson, D. F., and Collier, G. (1996). Food and water intake as functions of resource consumption costs in a closed economy. J. Exp. Anal. Behav. 65, 527–547. McFarland, D. J. (1977). Decision making in animals. Nature 269, 15–21. Mellgren, R. L., Misasi, L., and Brown, S. W. (1984). Optimal foraging theory: Prey density and travel requirements in Rattus norvegicus. J. Comp. Psychol. 98, 142–153. Morato, S., Johnson, D. F., and Collier, G. (1995). Feeding patterns of rats when food‐access cost is alternately low and high. Physiol. Behav. 57, 21–26. Navarick, D. J., and Fantino, E. (1972). Transitivity as a property of choice. J. Exp. Anal. Behav. 18, 389–401. Nevin, J. A. (1979). Response schedules and response strength. In ‘‘Advances in the Analysis of Behavior. Vol. 1: Reinforcement and the Organization of Behavior’’ (M. D. Zeiler and P. Harzem, Eds.), pp. 117–158. Wiley, Chichester. Novin, D., Wyrwicka, W., and Bray, G. A. (Eds.) (1976). ‘‘Hunger.’’ Raven Press, New York. Owen, J. (1980). ‘‘Feeding Strategy: Survival in the Wild.’’ University of Chicago Press, Chicago. Panksepp, J. (1973). Reanalysis of feeding patterns in the rat. J. Comp. Physiol. Psychol. 82, 78–94. Pavlov, I. P. (1927). ‘‘Conditioned Reflexes.’’ Oxford University Press, Oxford. Pietrewicz, A. T., and Kamil, A. C. (1979). Search image formation in the blue jay (Cyanocitta cristata). Science 204, 1332–1333. Pulliam, H. R. (1974). On the theory of optimal diets. Am. Nat. 106, 59–74.

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Pyke, G. H., Pulliam, H. R., and Charnov, E. L. (1977). Optimal foraging: A selective review of theory and tests. Q. Rev. Biol. 2, 307–343. Richardson, A. J. (1970). The role of the crop in the feeding behavior of the domestic chicken. Anim. Behav. 18, 633–639. Richter, C. P. (1927). Animal behavior and internal drives. Q. Rev. Biol. 2, 307–323. Richter, C. P. (1942). Total self‐regulatory functions in animals and human beings. Harvey Lect. 38, 63–103. Saltzman, I., and Koch, S. (1948). The effect of low intensities of hunger on the behavior mediated by a habit of maximum strength. J. Exp. Psychol. 38, 347–370. Schoener, T. W. (1971). Theory of feeding strategies. Ann. Rev. Ecol. Syst. 2, 369–404. Schoener, T. W. (1987). A brief history of optimal foraging ecology. In ‘‘Foraging Behavior’’ (A. C. Kamil, J. R. Krebs, and H. R. Pulliam, Eds.), pp. 5–67. Plenum, New York. Schultz, L. A., Collier, G., and Johnson, D. F. (1999). Behavioral strategies in the cold: Effects of feeding and nesting costs. Physiol. Behav. 67, 107–115. Skinner, B. F. (1938). ‘‘The Behavior of Organisms.’’ Appleton‐Century‐Crofts, New York. Skinner, B. F. (1932a). Drive and reflex strength. J. Gen. Psychol. 6, 22–37. Skinner, B. F. (1932b). Drive and reflex strength, II. J. Gen. Psychol. 6, 38–48. Skinner, B. F. (1953). ‘‘Science and Human Behavior.’’ Macmillan, New York. Stephens, D. W., and Krebs, J. R. (1986). ‘‘Foraging Theory.’’ Princeton University Press, Princeton, NJ. Thorndike, E. R. (1911). ‘‘Animal Intelligence.’’ Macmillan, New York. Woods, S. C. (1991). The eating paradox. Physiol. Behav. 98, 488–501.

ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

The Sexual Behavior and Breeding System of Tufted Capuchin Monkeys (Cebus apella) Monica Carosi,*,{ Gary S. Linn,{ and Elisabetta Visalberghi* *unit of cognitive primatology and primate center institute for cognitive sciences and technologies national research council, rome, italy { laboratory of comparative ethology, national institute of child health & human development, nih animal center poolesville, maryland 20837, usa { program in cognitive neuroscience and schizophrenia the nathan s. kline institute for psychiatric research nysomh, orangeburg, new york 10962, usa department of psychiatry, new york university school of medicine orangeburg, new york 10962, usa

I. INTRODUCTION According to traditional sexual selection theory (Darwin, 1871), as well as to usual portrayals of animal sexual behavior, there is a choosy female facing an ardent male. In other words, the female is the selective but otherwise passive partner in courtship and copulation, in opposition to the active male. However, this does not hold true for several primate species where the female’s readiness to mate (female receptivity) is also expressed by initiating sexual interactions and overt solicitation towards the male (female proceptivity). In no primate species is proceptivity so flamboyant as in the South American tufted capuchin (Cebus apella).1 The most recent classification of the genus Cebus (Groves, 2001; Rylands et al., 2000; see also Fragaszy et al., 2004) has split the species Cebus apella into Cebus apella, Cebus libidinosus, Cebus xanthosternos, and Cebus nigritus. However, up to now all of the published literature on tufted capuchins has referred to the traditional species C. apella. Thus, in order to be consistent with the original authors of the research, this chapter will refer only to C. apella. Nevertheless, in Table I, for the studies carried out in the wild (for which species identification is possible on the basis of geographical distribution), we provide also the new taxonomic names when possible. In contrast, we will not do this for the tufted capuchins living in the laboratory as hybridization may have occurred. 1

105 0065-3454/05 $35.00 DOI: 10.1016/S0065-3454(05)35003-0

Copyright 2005, Elsevier Inc. All rights reserved.

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Charles Janson first described in detail how the proceptive capuchin female ‘‘changes behavior radically . . ., she becomes very skittish. . .,’’ she directs proceptive grins and ‘‘exaggerated raising of the eyebrows . . .’’ at the male, ‘‘[she] produces a distinctive vocalization’’ which may last ‘‘for over three hours without pause . . ., she often harasses him [the alpha male] by approaching very closely and touching or pushing him on the rump . . . then running away’’ (Janson, 1984, p. 185). This pattern of behavior increases in intensity and duration over the next few days until it becomes almost continuous at its peak. The initial response of the alpha male is lack of interest and, occasionally, intolerance, including threats and chases. In the following days, when female behavior reaches its peak, the male begins to respond and pursue her. At this point, both partners engage actively in courtship and mating. The pattern described above is typical of the pattern of sexual interactions between a C. apella female and the alpha male. In this species, the alpha male’s status makes him the most attractive member of the group. Janson (1984, 1985, 1986b, 1988a,b, 1990), on the basis of ecological variables such as feeding strategies, social behavior, and group spatial structure, argued that the mating system of C. apella is a resource‐defense polygyny. The dominant male controls access to food sources, and by mating with him females (and their offspring) are allowed to feed on preferred food sources (Janson, 1994; Janson and Wright, 1980). Better access to food sources is likely to improve an offspring’s chance of survival; infant survivorship is greater in a provisioned than in an unprovisioned group (Di Bitetti and Janson, 2001). In fact, males are extremely tolerant of infants and sometimes carry them (Fragaszy et al., 2004) (Fig. 1). They promptly defend them (Izawa, 1980; Janson and Wright, 1980; Janson, 1984, 1986a) and may ‘‘baby‐sit’’ infants while their mothers leave them (Izawa, 1980). This evidence shows that the male’s role is not limited to providing access to food resources. Since Janson’s original field study, the understanding of mating systems and sexual behavior, and their morphological and physiological correlates, has greatly increased for many primate species (Dixson, 1998a). However, despite the recent surge of studies on Cebus apella, the relationship between sexual behavior and mating system has not been thoroughly addressed. Also, in a recent book by Fragaszy et al. (2004), in which the literature on sexual behavior and social structure of the genus Cebus is reviewed and discussed, questions concerning the mating system of C. apella remain unanswered. In particular, it is unclear whether the mating system of C. apella is best characterized as multi‐male/multi‐female (that is, both dominant and subordinate males gain reproductive access to females) or single male (i.e., only the dominant male mates successfully). The aim of

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Fig. 1. An adult male C. apella with an infant on his back (drawing courtesy of Arianna De Marco).

this chapter is to address this question by examining evidence relevant to socio‐sexual behavior, sexual choice, reproductive physiology, and sexually selected traits. In Section II, we review and discuss the social structure and mating system of C. apella; in Section III we cover sexual behavior in relation to reproductive physiology (including sexual and reproductive maturity, hormonal correlates of sexual behavior, and reproductive seasonality). In Section IV, we describe and discuss intrasexual competition and mate choice, pre‐ and post‐copulatory competition (sperm competition and cryptic female choice), sexual dimorphism, infanticide, and paternity. We present conclusions and suggestions for future research in Sections V and VI. II. SOCIAL STRUCTURE A. GROUP SIZE, SEX RATIO,

AND

AND

MATING SYSTEM

RANK

Wild C. apella live in multi‐male/multi‐female groups whose size and adult sex ratio are presented in Table I (see also Fig. 2 for number of adult males and females in groups of different size). Group size ranges from a few individuals to more than 30. According to Janson (1988a), group size is constrained by the foraging efforts required to obtain enough food within the limits of daylight. Sex ratio (male:female) ranges from less than 1:1 at

TABLE I GROUP SIZE AND COMPOSITION IN WILD CEBUS Study site [group name]

Group size (range)

APELLA

Sex ratio (adult M:adult F)

References

COLOMBIA a a

a

108

a

Monte Seco‐Hacienda Barbascal

5 7 16 12 21 (6–12, estimated)

La Macarena National Park [M] [S] [E] La Macarena National Park El Tuparro National Park

(Isolated forest)

6 11 12 (3–5)

(Continuous forest) Caqueta River Basin

(15–20) 18–20

Thorington 1967 (in Izawa, 1980) 1:1.33 (3M:4F) 1:2 (2M:4F) 1:2 (3M:6F)

Izawa, 1980*

Klein and Klein 1975, 1976 (in Freese and Oppenheimer, 1981) Defler, 1982

Hernandez‐Camacho and Cooper, 1976 (in Freese and Oppenheimer, 1981)

00

Izawa, 1976 (in Freese and Oppenheimer, 1981)

BRAZIL (Mato Grosso) b Carlos Botelho State Park (Sao Paulo) b Caratinga Biological Station (Minais Gerais) (Southern Bahia)

(8–18, estimated) 4–13 (26–29) (1–6)

1:2 (2M:4F) 1:1.75 (4M:7F)

10–14 (3–14)

1:1.33 (3M:4F)

Kuhlhorn, 1939 (in Izawa, 1980) Izar, 2004* Lynch and Rimoli, 2000* Pinto and Tavares, 1993 (in Lynch and Rimoli, 2000)

PERU a

Cocha Cashu Biological Station (Manu National Park)

[A]

Janson, 1985*

[B] [C] [D] Samiria River

10–11 5–7 3 (5–10)

Pacaya‐Samiria National Reserve (Cahuana Island) ?

10

?

(up to 30)

1:0.66 (3M:2F) 1:1.5 (2M:3F) 1:1 (1M:1F)

Janson, 1988a*

Neville et al., 1976 (in Freese and Oppenheimer, 1981) Soini, 1986 (in Lynch and Rimoli, 2000)

(6–11)

Freese, 1975, 1977 (in Freese and Oppenheimer, 1981) Grimwood, 1969 (in Freese and Oppenheimer, 1981)

ARGENTINA b

Iguazu National Park [Macuco] [Macuco] [Macuco]

22 (7–30) 26–29 (8–33) (35–40)

109

VENEZUELA (Isla de Margarita)

(3–6)

BOLIVIA

10

a

SURINAME *

(10–20)

1:2 (3M:6F) 1:2 (4M:8F) 1:2.17 (6M:13F)

Janson and Di Bitetti, 1997* Di Bitetti et al., 2000* Agostini and Visalberghi (2005) (data for 2004)* Sanz and Marquez, 1994 (in Lynch and Rimoli, 2000) Heltne et al., 1975 (in Freese and Oppenheimer, 1981) Husson, 1957 (in Freese and Oppenheimer, 1981)

Data used in Fig. 2. According to the most recent classification of the genus Cebus (Groves, 2001; Rylands et al., 2000; see also Fragaszy et al., 2004) the capuchins living at this site belong to the species C. apella. b According to the most recent classification of the genus Cebus (Groves, 2001; Rylands et al., 2000; see also Fragaszy et al., 2004) the capuchins living at this site belong to the species C. nigritus. a

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F IG. 2. Number of adult males and females present in C. apella groups (N ¼ 12) in relation to group size (F[1,10] ¼ 142.9, p << 0.001, r2 ¼ 0.89 for males; F[1,10] ¼ 78.889 p << 0.001, r2 ¼ 0.93; the data reported are taken from eight field studies asterisked in Table I). The regression equations are also provided.

Manu National Park (NP), Peru to 1:2 at La Macarena NP, Colombia and Iguazu NP, Argentina, and the ratio varies as a function of group size. In the wild, a linear dominance hierarchy has been described for both males and females with a distinct alpha position for each sex, although in some cases only one uncontested alpha position has been detected, the other ranks being indeterminate (Escobar‐Pa´ ramo, 2000; Izawa, 1980; Janson, 1984, 1990; Lynch et al., 2002). The alpha female is often dominant over subordinate males (Cebus spp., Robinson and Janson, 1987; C. apella, Escobar‐Pa´ ramo, 2000), though adult males are generally dominant over adult females (C. apella, Janson, 1984; Lynch, 1999). Similarly, in captivity each sex has a dominance hierarchy, with the alpha female often dominant to subordinate males (Linn et al., 1995; see also Costin, 1992 for females). According to Welker (1986, 1992), group members are not easy to rank, apart from one dominant male and one dominant female. The tenure of the alpha male varies considerably (e.g., a minimum of four years at Manu NP, Janson, 1984; >8.5 years at Iguazu NP, Di Bitetti and Janson, 2001; >10 years in captive groups, M. Carosi, G. Linn, personal

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observation). A few cases of takeovers have been described. In the wild, Izawa (1997) reported two such cases in three years (one by the group’s beta male, the other 2 years later by an outsider); and Lynch and Rimoli (2000) report a single takeover (by the beta male). In a captive group, 8 years elapsed between two successive takeovers (the first takeover was reported by Byrne et al., 1996 and the second found by M. Carosi in 2001, personal observation; see also Cooper et al., 2001); in both cases, the previous alpha males were removed, due to repeated attacks and severe injuries by both the ‘‘alpha male to be’’ and other group members. On the other hand, a smooth change in male leadership, with no injury, has also been observed (Visalberghi, personal observation). Group membership is mostly stable over many years, though temporary subgroups can be frequent (Lynch et al., 2002). Over the years, the six groups observed at Iguazu NP had a varying average group size (from 12.4  7.0 to 16.8  9.5) due to group fusion and fission (Di Bitetti and Janson, 2001; see also Izar, 2004). Subadult and young adult males frequently migrate between groups. Females remain in their natal groups, though occasionally adult females may transfer between groups (Izar, 2004; Janson, 1990; Lynch and Rimoli, 2000). At Iguazu NP, females’ change of residency may result from group fissions and fusions (Di Bitetti and Janson, 2001). B. MATING SYSTEM

AND

SEXUAL BEHAVIOR

Numerous field and laboratory studies have reported that in capuchins most females direct the majority of their proceptive and mating behavior towards the alpha male (Janson, 1984; Linn et al., 1995; Welker et al., 1990; for a review see Fragaszy et al., 2004). However, this preference decreases at the end of the female’s proceptive period, when she may copulate with up to six subordinate males in a day, or even with four males in 10 minutes (Janson, 1984; Visalberghi and Welker, 1986). Females mating with three to four different males have also been observed by Lynch (1998). Sometimes, when the alpha female and a lower‐ranking female are simultaneously proceptive, the dominant one courts the alpha male, whereas the subordinate (even when she is at her mid‐proceptive period) may solicit subordinate males (Janson, 1984). Sometimes, females solicit and mate with subordinate males in view of the dominant male (Di Bitetti and Janson, 2001; see Section IV.A.1.a, for more details). Matings between individuals belonging to different groups sometimes occur (Lynch, 2002). In captivity, sexual preferences differ among females. Visalberghi and Welker (1986) reported that all females (N ¼ 9, observed over 26 months) mated with more than one partner (both in different proceptive periods

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and within the same one), and that some females consistently preferred the beta male to the alpha male (see also Welker et al., 1990; Di Bitetti and Janson, 2001). On the other hand, Linn et al. (1995) reported that in four captive groups (N ¼ 15 females, observed over 23 months) 100% of the four dominant females’ copulations were with the alpha male of their group. Sometimes females switch from soliciting the dominant to the subordinate male throughout the proceptive period (Linn et al., 1995; M. Carosi, personal observation). Sometimes females solicit males living in adjoining cages (Carosi and Linn, personal observation; Welker et al., 1990). Data on timing of ovulation matched with the different mating patterns reported, however, are not available; and comparisons between timing of dominant versus subordinate male mating in relation to female maximum fertility cannot, unfortunately, be made. A male’s sexual behavior varies according to his rank (Janson, 1984; Lynch, 2002). The alpha male almost never initiates sexual interactions, and he is solicited by the female for days before reciprocating and eventually mating. In contrast, subordinate males may actively solicit females and often engage in ‘‘sneak’’ copulations, which are more frequent when conceptions are likely to occur (based on observed births, Lynch, 2002). Subordinate males are solicited by females far less than dominant ones; when subordinate males are solicited, they respond by readily mating (Janson, 1984; Welker et al., 1990; see also Dal Secco, 1999). The difference in readiness to mate between dominant and subordinate males may account for the similarity in overall mating frequency observed by Lynch (2002) (see also Lynch and Rimoli, 2000). The sexual behavior of females towards a newly established alpha male and his response to them give further evidence of the behavioral flexibility of C. apella. Females, regardless of their hormonal state, promptly react to the new alpha male with persistent solicitations. At any time during their cycle, they can solicit a new alpha male as if they were in the periovulatory phase, so that matings outside the fertile phase occur (Carosi and Visalberghi, 2002; Fragaszy et al., 2004). The flexibility of female sexual behavior is particularly striking when the new dominant male was formerly within the group as a subordinate male, and she had therefore ignored him prior to his rise in rank (Linn, personal observation). To provide an insight into the behavior of a newly established alpha male, we can describe what happened in a large captive group (N ¼ 28), after a dramatic take over. At first, the new alpha male was extremely aroused whenever a female courted him: it seemed as if he ‘‘could not believe’’ the female was choosing him as sexual target! So at the beginning of his tenure, he promptly reciprocated sexual behavior, as typical subordinate males do. However, over the next few months, his response became more and more indifferent

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and intolerant, as typically described for alpha males (Carosi, personal observation). The behavior of subordinate males is also flexible. We have observed beta males react to female solicitations with intolerance and indifference for days before eventually mating. Their indifference is not due to sexual inhibition (see following) because when they mate, they do so in full view of the dominant male. In all respects, the behavior of these atypical subordinate males resembles that typical of alpha males (Visalberghi, personal observation). It is possible that when males are consistently targets of females’ solicitation, they respond less readily than when they are not.

III. REPRODUCTIVE PHYSIOLOGY

AND

SEXUAL BEHAVIOR

Understanding the diversity of sexual behavior requires that it be viewed within the context of reproductive physiology and life history parameters. In this section, we will review the available information on sexual and reproductive maturity, and on seasonality of reproduction. Then, we will discuss the relationship between the ovulatory cycle of females and timing of courtship, mating, and copulation. Since the data on reproductive physiology are from both wild and captive animals, and since differences in diet affect reproductive parameters, we begin by reporting the little we know on this issue. Although more data are needed, in C. apella food quality and abundance do not seem to strongly affect reproductive maturity, birth rates (Di Bitetti and Janson, 2001), and interbirth intervals (averaging 19.4 and 20.6 months, in wild and captive groups, respectively, Fragaszy and Adam‐Curtis, 1998). However, they do affect infant survivorship (see also Section IV.C). A. SEXUAL AND REPRODUCTIVE MATURITY Fertility is not synonymous with sexual maturity, nor is it synonymous with full physical maturity (Dixson, 1998a). Bearing this in mind, we will examine the (mostly indirect) evidence of sexual and reproductive maturity in capuchin monkeys. 1. The Female Behavioral and hormonal signs indicating forthcoming sexual and reproductive maturity occur at about 4 years of age (wild females, Robinson and Janson, 1987; Di Bitetti and Janson, 2001; captive females, Phillips et al., 1994; Nagle and Denari, 1982; Di Giano et al., 1987). For regularly cycling

LENGTH OF THE OVULATORY CYCLE IN C.

APELLA.

TABLE II WE INDICATE THE NUMBER OF SUBJECTS AND THE METHODOLOGY USED TO MONITOR THE CYCLE

Cycle length (days) Mean

Range

No. females

No. cycles

114

18.08 17.08 21.14

16–23 16–20 –

1 1 6

6 7 13

21.0  1.1b

18–24

10

10

20.8 1.2b

13–28

?

108

– 20.8  1.2a

18–22 17–26

15 15

21 20.4  2.2a 20.6 1.6a

20–22 – 17–24

2 18 4

a b

Standard deviation. Not specified.

Method Peaks of vaginal sediment

References Hamlett, 1939

00

00

Wright and Bush, 1977

– 254

Menstruation (bleeding, vaginal smears) Plasma E2 and P4; menstruation (vaginal smears) Menstruation (bleeding, vaginal swabs/smears) Menstruation (vaginal smears) Menstruation (vaginal swabs)

2 – 20

Plasma progesterone Bleeding; vaginal smears Urinary and fecal progestins

Nagle et al., 1979 Nagle and Denari, 1983 Nagle et al., 1989 Linn et al., 1995 (additional data in Fig. 3) Linn et al., 1995 Ortiz et al., 1995 Carosi et al., 1999

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females, the ovulatory cycle lasts on average 20.7 days (Table II) and pregnancy 5 months (Nagle and Denari, 1982). In captivity, first delivery can occur as early as 4 years and 7 months of age (on average 5 years and 7 months, Fragaszy and Adam‐Curtis, 1998; see also Di Giano et al., 1987). In contrast, Patin˜ o et al. (1996) report that three females first became pregnant at 6 to 7 years of age. In the wild, Di Bitetti and Janson (2001) reported that first delivery occurred at 5 years and 3 months, and modal age at first birth was 7 years. As far as we know, socially mediated suppression of ovulation does not occur (e.g., captive data, Fragaszy and Adam‐Curtis, 1998). Menstruation is an indicator of reproductive maturity. However, this parameter is not as reliable an indicator of ovulation as hormone levels. First, external menstruation is not easily detected. Despite the observation by Rengerr (1831) of menstruation in wild capuchins, in general menstruation is so slight in Cebus that vaginal lavages or swabs are necessary to detect it (captive animals, Hamlett, 1939; Hill, 1941; but see Wright and Bush, 1977). Second, both regular and irregular menstruation can be associated with an anovulatory cycle (Hamlett, 1939; Nagle et al., 1979). Finally, matched hormonal and menstrual data show that an ovulatory cycle is usually but not always accompanied by menstrual bleeding (Hamlett, 1939). Nevertheless, as shown in Table II, cycle lengths determined by vaginal swabs are very accurate and do not differ from those determined by hormone levels. Still, given the greater reliability of hormonal data and advances in the methodology which allow hormonal levels to be determined non‐invasively from fecal or urine samples, we advocate their use over menstrual data, when possible. 2. The Male Male puberty and reproductive maturity have not been studied in wild capuchins. In captive capuchins, testicular hormone levels remain below the active gonadal pattern until around 3 years and 4 months of age (Nagle and Denari, 1982). In one‐male groups, siring can occur as early as at 4 years 2 months of age (range 4 yr, 2 mo–4 yr, 5 mo, N ¼ 3 males, Fragaszy and Adam‐Curtis, 1998). Rey et al. (1993) monitored volumetric changes in testes, appearance of spermatogonia, and steroidogenic activity of single‐caged males and found that maturation occurred over several years, between 4 and 7 years of age. However, we doubt that these findings are representative of normal sexual development because when paired with females these hand‐reared males did not exhibit normal sexual behavior and never ejaculated (nor did they ejaculate when electrically stimulated) before being 7 to 8 years old (Nagle, personal communication).

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As far as we know, dentition and body weight provide little information about reproductive maturity. In capuchins, incomplete versus complete deciduous dentition, as well as complete deciduous dentition versus complete permanent dentition, do not match reproductive physiology (Gilmore, 1943). Data on body weight from birth to adulthood are available only for captive animals (e.g., Fragaszy and Adam‐Curtis, 1998; Nagle and Denari, 1982; Patin˜ o et al., 1996; see Section IV.B); the differences in body weights reported in different studies make the use of body weight as an indicator of reproductive maturity unreliable. Social environment also affects reproductive behavior and physiology. For young or subordinate males, social constraints on matings reduce their chance of siring offspring (see Section IV.A.1.c). Although males can sire as early as 4.5 years of age, this happens only if no other male is present in their group (Fragaszy and Adam‐Curtis, 1998). The finding that single‐ caged males start to ejaculate very late (at 7 to 8 years of age, Rey et al., 1993) may indicate that a lack of appropriate social stimuli alters normal development. B. EFFECTS

OF

SEXUAL HORMONES

ON

BEHAVIOR

AND

BODY

1. Proceptive Behavior and Ovulation The ovulatory cycle is related to cyclic proceptivity. Janson (1984), on the basis of vaginal cornified epithelium desquamation and relative cell counting during the menstrual cycle (Wright and Bush, 1977), hypothesized that the days of proceptivity (4 to 6 days range) correspond to the 5 days of desquamation induced by estrogen. Moreover, since the peak of desquamation occurs in the 3 middays (Wright and Bush, 1977), and since Hamlett (1939) argued that the peak of desquamation approximates to the time of ovulation, Janson concluded that ovulation occurs during the middays of proceptivity. However, Nagle and Denari (1982) demonstrated that the curve of desquamation has at least a 1‐day delay relative to the estrogen curve, and that the peak of desquamation coincides with that of LH and also with an increase in progesterone levels. Although more recent matched physiological and behavioral data (Carosi et al., 1999; Linn et al., 1995) fully confirm that proceptive and ovulatory cycles overlap, a new issue has been raised. Carosi et al. (1999) consider unwarranted the assumption that ovulation is likely to occur in the midproceptive period, and on the basis of indirect hormonal evidence suggest that ovulation takes place toward the end of a 1‐ to 5‐day proceptive period. This argument is partly based on the analogy between the effects of sexual hormones on morphology in other primate species. Sexual steroids

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act peripherally on target tissues as well as through the central nervous system, affecting behavior (Dixson, 1983; see also Dixson, 1990). Experiments investigating the effects of estrogens and progestagens upon female sexual skin demonstrate a stimulatory action (estrogens) and an inhibitory action (progestagens) of the reddening and swelling of the female ano‐ genital area (e.g., baboons, chimpanzees; for a review see Dixson, 1998a). When a sexual swelling is the major external evidence of the periovulatory phase, ovulation usually occurs toward the end of the maximal swelling period. In wild chimpanzees (Pan troglodytes), in 74% of the ovarian cycles studied (N ¼ 33), ovulation occurred between days –3 and –1 from the end of maximum tumescence (Deschner et al., 2003). In baboons (Papio spp.) laparoscopic studies demonstrate that the majority of follicles (about 65%) rupture between the last day of maximal swelling and the first day of detumescence (Wildt et al., 1977, in Dixson, 1998a). Moreover, in a few primate species, experiments investigating the effects of sexual hormones upon female behavior suggest a stimulatory action of estrogens and an inhibitory action of progestagens upon female proceptivity (Dixson, 1998a). Assuming that the relation between sexual hormones and behavior is analogous to that between sexual hormones and morphological changes, we expect ovulation in C. apella to occur toward the end, and not in the middle, of the 1‐ to 5‐day proceptive period (Carosi et al., 1999). As we described earlier, the female’s surge in progesterone levels occurs at the end of the proceptive period; this provides further strength to our view. The significance of this difference in timing of ovulation becomes important when one considers the copulatory patterns described by Janson (1984). If ovulation occurs at the end of a female’s proceptive phase, then copulations with subordinate males have a greater chance of being conceptive matings than if ovulation occurs in the middle of her proceptive period, when most copulations are with the alpha male (at least in the groups observed by Janson and colleagues). Most of the studies on C. apella reproduction concern only its behavioral aspects, and sexual hormones have received less attention. Female cycling has usually been assessed by measuring the occurrence of her sexual solicitations. As shown in Table III, the duration of the cyclic occurrence of female solicitation is quite variable, whereas the duration of the sexual hormone cycles (Table II) is rather constant. Three explanations (not mutually exclusive) could account for this contrast: (1) female behavior is, at least partially, free from hormonal regulation; (2) some of the behaviors used as indicators of female proceptivity are inadequate; (3) female behavior may differ, depending on the signaler and/or the recipient of the signal. We will analyze these three possibilities in detail.

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TABLE III LENGTH OF THE CYCLICAL OCCURRENCE OF SEXUAL SOLICITATIONS IN C. APELLA FEMALES. THE BEHAVIORAL PARAMETERS CONSIDERED VARY ACCORDING TO THE STUDIES (SEE EACH REFERENCE FOR MORE DETAILS) Cycle length (days) Mean

Range

No. females

No. cycles

18.8  1.2a

6–32

16

39

21.9

n.a.

4

20

12–32

11

13

21.5  5.5b a b

Female proceptivity estimated on the basis of a broad range of socio‐sexual behaviors a subset of proceptive behaviors having a cycle whose length corresponds to that of the sexual hormones typical proceptive behaviors, vocalizations

References Phillips et al., 1994 Carosi et al., 1999

Lynch, 1998, 2002

Standard error. Standard deviation.

a. Female behavior is, at least partially, free from hormonal regulation Observations of females soliciting a male when they cannot be in the periovulatory phase would provide support to this hypothesis. The response of females to a new alpha male, regardless of cycle phase, described above (Section II.B), is one example. Instances of courtship behavior during the first month after an infant’s birth have also been described (Janson, 1984; within a week following birth, Fragaszy and Adam‐Curtis, 1998). The alpha female frequently chases off a soliciting subordinate female just as the dominant male is about to mount her, and then goes into a full proceptive behavioral repertoire (including vocalizations) without being in the periovulatory phase (monitored through vaginal swabs; Linn, personal observation). Proceptivity and copulation have been observed during pregnancy (Welker, 1983, cited in Visalberghi and Welker, 1986; Phillips et al., 1994, Carosi, unpublished data), when progesterone levels are high (high urinary levels have been detected after only 2 weeks from conception, Nagle and Denari, 1982). For example, 3 days after the arrival of a new alpha male, a multiparous female (a month and a half pregnant by the former alpha male) sexually solicited him (Carosi, personal observation). We know that the relative levels of hormones can be very important. For example, sexual swellings are affected by the relative proportion of estrogen and progesterone levels. In pregnant females, sexual swelling is caused by the positive estrogen:progesterone ratio that occurs during some stages of pregnancy. Capuchin

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proceptivity during pregnancy could also result from the balance between these hormones. Many years ago, Hrdy (1981) labeled female primate willingness to get involved in sexual activities throughout the cycle, and especially when it could be advantageous to her, as ‘‘situation‐dependent receptivity.’’ By analogy, capuchins’ proceptivity might be labeled as ‘‘situation‐dependent proceptivity.’’ Compared to morphological signals, proceptivity is potentially far more flexible, since it concerns the expression of behavioral signals and may thus represent a powerful component of female capuchins’ sexual and reproductive strategy (see also patas monkey, Erythrocebus patas, females solicitation of matings during pregnancy or after an infanticide in the nonconceptive season, Enstam et al., 2002). b. Some of the behaviors used as indicators of female proceptivity are inadequate This is certainly true. To court the male, females use a strikingly varied behavioral repertoire, whose richness has been thoroughly described by Carosi and Visalberghi (2002). Nevertheless, only a few behaviors (the cluster includes: eyebrow raising with vocalization, touching and running, head cocking, nuzzling), out of the 12 performed during courtship, were negatively correlated with the rise of postovulatory progesterone. In fact, the progesterone cycle and the cycle of the cluster of these behaviors were almost identical: 21.3 days and 21.9 days, respectively (Carosi et al., 1999). It follows that only specific behaviors can be reliable indicators of the female periovulatory phase, whereas others are not. Most of the behaviors used by the female when proceptive (including those of the previously mentioned cluster) are also used outside of the periovulatory phase in non‐sexual, affiliative contexts. In the latter contexts, the behaviors are less intense, less frequent, and do not occur in the sequence described for sexual behavior (Carosi and Visalberghi, 2002). Nevertheless, it is important to mention that the fertile female may trigger, simply by raising her eyebrows, the male’s sexual response (including copulation and possibly ejaculation). Moreover, the female can use the same behavior to console a male victim of aggression, regardless of the phase of her ovulatory cycle. c. Behavioral signaling may differ, depending on the signaler and/or intended recipient of the signal A female may perform more elaborate courtship when the sexual target is the alpha male and a less elaborate/ shorter one when courting a subordinate male (e.g., Janson, 1984; Linn et al., 1995; Lynch et al., 2002). Females also make use of different assortments of behaviors when soliciting the same alpha male (Carosi et al., 1999; see also Carosi and Visalberghi, 2002).

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2. Scent‐Marking Behavior and Ovulation Scent‐marking behavior using urine, cutaneous glands, and genital secretions is extremely common in New World primate species. The effects of sexual steroids on female odors have been widely demonstrated in both non‐primate and primate mammal species; less obvious, however, is how males use the olfactory cue (Dixson, 1998a). Observations of tufted capuchin males sniffing either the female’s body or urine are extremely rare, both in the wild and in captivity. Chest rubbing and urine washing behavior may be involved in scent marking. Chest rubbing is very common during courtship and consists of an individual rubbing its hands on its own (or another animal’s) chest. In one tufted capuchin male, in the chest area used for rubbing, Epple and Lorenz (1967) found a cutaneous gland, but, unfortunately, only this single male was examined. An association between rubbing behavior and the exocrine scent‐producing nature of this gland needs to be demonstrated (Carosi and Visalberghi, 2002). Urine washing consists of voiding the urine onto the hand palms and feet soles, and then rubbing them together. If urine washing serves as an olfactory signal to attract males, then females should perform this behavior more in the follicular than the luteal phase. Data show exactly the opposite trend (Carosi and Visalberghi, unpublished data; Carosi et al., 1999). The same trend was evident for C. capucinus (Carnegie and Fedigan, 2005). This supports a thermoregulatory function of urine washing (Carosi et al., in preparation; Fragaszy et al., 2004). In short, no evidence of urine washing as a scent‐marking behavior or as playing a role in reproductive communication in C. apella has been provided to date. 3. Female Genital Morphology As in many other New World monkeys, female tufted capuchins do not show a sexual swelling, and behavior appears to be the only conspicuous signal of the female ovulatory cycle phases. An increased puffiness of female genitalia during the periovulatory phase of the cycle has been reported in the congeneric albifrons (Castellanos and McComb, 1968). No data are available for C. apella in this respect, and, in addition, female genitals apparently do not specifically elicit male interest (wild: Janson, 1984; captive: Phillips et al., 1994; Carosi et al., 1999). It is worth mentioning, though, that the external genitalia do indeed show a certain conspicuousness. Early papers had described the clitoris of C. apella as male‐like in structure (Cebus spp.: Pocock, 1920; Wislocki, 1936; Hill, 1958; C. apella: Hill, 1960; Fragaszy et al., 2004). Clitoral morphology and size in female infants and juveniles have often resulted in inaccurate sexing, even in captive capuchins.

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By adulthood, the clitoris appears less conspicuous (Freese and Oppenheimer, 1981; Carosi, personal observation), and clitoral erections, so common in immature females, have not been reported. A cross‐sectional study shows how potentially reproductively mature females (>4 yr, N ¼ 13) exhibit a significantly shorter clitoris than immature females (<4 yr, N ¼ 9) (Carosi et al., manuscript in preparation). Hormonal changes throughout pre‐ and post‐natal development and, later on, during puberty and early adulthood (e.g., data on rhesus monkeys, reviewed in Dixson, 1998a), could be a potential proximate mechanism, worth investigating as responsible for development of such male‐like genitalia and, later, for reduction of clitoral size in maturing individuals. A socio‐sexual function of such a modified clitoris during male‐female sexual interactions in adult individuals is unlikely. 4. Mounting Behavior and Ejaculation in Relation to Ovulation and Fertilization Mounting activity occurs at any phase of the cycle, with no significant differences between the periovulatory and the non‐periovulatory phase (Carosi and Visalberghi, 2002). This is not surprising since mounting is a behavior often used in contexts other than the sexual one (Manson et al., 1997; see also Dixson, 1998a). However, when ejaculation (i.e,. the transfer of sperm for possible fertilization) is considered, the picture changes quite a bit. In Carosi et al., (1999), ejaculations occur only during female proceptive days and around the time of ovulation (N ¼ 20 cycles, N ¼ 4 females, N ¼ 5 males). In this study, ejaculation was scored only when, after mounting, semen was observed on male and female genitalia. In a larger sample of animals (N ¼ 254 cycles, N ¼ 15 females, N ¼ 8 males), ejaculations (i.e., copulations when either ejaculate was observed or ejaculation inferred from patterns of copulation, facial expressions, and post‐ copulation self‐grooming), although more dispersed throughout the cycle, had a definite peak at mid‐cycle (Fig. 3). When frequency of ejaculation was investigated in a study in which proceptive females were observed for 7 to 8 hours a day during the entire proceptive period (Dal Secco, 2000), alpha males were observed to ejaculate on average 0.7 times per female’s proceptive period, and subordinate males were never observed to ejaculate, though sometimes they mated. Although ejaculation is difficult to assess in the wild, both Janson (1984) and Lynch (2002) found evidence for low ejaculatory frequency in male C. apella. Finally, by using a surgical procedure, Ortiz et al. (1995) found that one third of the ejaculations recorded in pair‐living animals occurred before ovulation, while for the other two thirds timing could not be determined.

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F IG. 3. Distribution of copulations with ejaculation (either observed or inferred, see below) per cycle across the menstrual cycle for 15 female C. apella living in four social groups (each group has two adult males) in Linn’s laboratory. A total of 191 copulations with ejaculation were observed over 254 monitored cycles. Cycles were monitored via vaginal swabs, and only those bounded by detection of menstrual blood were included. Copulation with ejaculation was recorded when, after successful intromission and pelvic thrusting, the ejaculate was observed or ejaculation was inferred by typical body posture, facial expressions, and post‐ copulatory grooming of genitals. Individual cycles, which ranged from 17–26 days were not normalized to mean cycle length (20.8  1.2 days). The dataset includes data from the 182 cycles reported in Linn et al. (1995).

Unfortunately, it was not possible to compare the fertilization success of ejaculations occurring before and after ovulation. Once ejaculated, the semen forms a ‘‘sperm plug’’ (also called vaginal, or copulatory, plug). This ‘‘transparent, celloidin‐like mass so filling the vagina that it was almost impossible to get anything in the lavages other than fragments of the plug’’ (Hamlett, 1939, p. 174; see also Bush et al., 1975; Nagle and Denari, 1983) can be used to ascertain that ejaculation has occurred. In wild‐caught, captive capuchins (one male and five females), for two females Hamlett detected a vaginal plug in 10 out of 13 cycles. Ejaculations occurred during the female periovulatory phase (as detected by vaginal cytology) and never earlier than 3 days prior to the peak of the

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vaginal cycle. Interestingly, the three females whose vaginal cycles appeared very irregular never presented vaginal plugs. Further information about vaginal plugs is necessary to better appreciate the process of fertilization and to address the question of male‐male competition (Section IV). The plug is found in the female tract up to 12 hours after mating (Bush et al., 1975). Semen obtained by means of electro ejaculation from three fertile males lacked a liquid fraction and consisted only of a coagulum fraction; a predominance of the coagulated fraction is typical of natural matings as well. Spermatozoa are ‘‘trapped’’ in the coagulum in a patchy/streaming distribution, and there is no correlation between semen volume and concentration of spermatozoa. By comparing the ejaculate from the alpha and the lowest‐ranking male (respective ages not reported), Bush and co‐workers showed that the alpha was producing a bigger amount of ejaculate with a lower sperm concentration than the subordinate male. Nagle and Denari (1983) report that in C. apella, as in other monkey species, semen coagulates quickly and does not show spontaneous autolysis. Therefore, the vaginal plug has to be either expelled or partially liquefied. Bush et al. (1975) hypothesized the existence of a mechanism within the female tract that would soften and melt the coagulum, in order to free the spermatozoa trapped in it. To track the spermatozoa inside the body, different portions of the uterus of pair‐living females were monitored following a single ejaculation (Ortiz et al., 1995). Spermatozoa were recovered from the uterus, isthmus, and ampulla (i.e., part of the genital tract after the vagina and progressively closer to the ovaries) at different time intervals (1–7 hours, 19–31 hours, 45–56 hours). Sperm was recovered from the ampulla (the wide portion of the fallopian tube near the fimbriated extremity where the egg spends most time) as early as 1 hour after mating. In one case, a fertilized egg was recovered in the isthmus less than seven hours after a single mating. In addition, ovulation facilitated sperm migration only in the female tract on the side of ovulation. The pattern of sperm distribution and the number of spermatozoa recovered in different female tracts, even at identical time intervals after a single mating, showed high inter‐female variability. In primates, fluctuations in steroid hormones during the female cycle may affect the physical characteristics of female genital secretions which, in turn, may affect sperm migration. For example, low vaginal pH (e.g., 3.5–4.0 in the human female) negatively affects sperm motility and survival (Dixson, 2002). Therefore, it can be hypothesized that given a specificity of each female vaginal tract, different females may differently affect the sperm from the same male, and a female capuchin may differently affect the migration of sperm from different males (see Dixson, 2002 and Section IV.D).

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C. REPRODUCTIVE SEASONALITY Among factors known to affect reproductive seasonality (photoperiod, rainfall, food availability) photoperiod has been proven, in primates, to be a common proximate cue to initiate reproductive activity. Obviously, this proximate cue is not relevant to species living in the equatorial areas. Tufted capuchins are very widely distributed from Venezuela through northern Argentina. Birth data are available for a very limited number of field sites and for several laboratories around the world. According to Di Bitetti and Janson (2000, 2001) wild tufted capuchins have a clear seasonal pattern of births (birth season defined as a distinct period of the year in which all births occur, Lancaster and Lee, 1965), and reverse birth seasonality in different hemispheres, as is typical of species influenced by photoperiod. Interestingly, during 21 years, in Visalberghi’s laboratory (animal housed indoor/outdoor all year round) no births occurred in December and January (based on N ¼ 37 births), although regular proceptivity and hormonal activity (for 1996, the one year for which we have data) occurred between March and July (with expected births from September to January, Carosi et al., 1999). December and January are outside the birth season also for wild capuchins living in the Northern hemisphere (Di Bitetti and Janson, 2000) while they are within the birth season for those living in the Southern hemisphere. As Di Bitetti and Janson (2000) state, diet and food availability also play a role in birth seasonality. We investigated the role of nutrition and photoperiod by comparing the length of the birth season of capuchins living in captivity and kept indoors all year round (with a fixed schedule of light and dark), living in captivity with outdoor access all year round, and living in the wild (Fig. 4). In both the latter two conditions, capuchins are exposed to a seasonal variation in photoperiod, but only the captive ones have constant food supply. Capuchins in both the former two conditions have constant food supply, but only those living outdoors experience seasonal variation in photoperiod. The data show that in captive conditions births occur almost all year around, although this tendency is stronger when monkeys are kept indoors than when they have outdoor access, where fluctuations in photoperiod occur. Birth seasonality is significantly less in captive outdoor conditions than in the wild (Kruskal‐Wallis, chi square ¼ 6.7, df ¼ 1, p < 0.01), where photoperiod fluctuations prompt seasonal changes in food availability. In a different species (cotton‐top tamarins, Saguinus oedipus), a field study in Northern Colombia has shown that birth season was closely related to the onset of the rainy season. However, captive tamarins housed outdoors at the same site, and fed consistently throughout the year, had no seasonality, suggesting that food

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F IG. 4. Duration of the birth season in C. apella. Data are grouped according to monkeys’ living conditions. W indicates groups studied in the wild, CO groups living in outdoor captive conditions, and CI groups living in indoor captive conditions. Location, hemisphere, latitude, and reference for each bar are provided below. For groups living indoors, namely ‘‘l’’ and ‘‘m,’’ the light (L)/dark (D) cycle was 12L:12D and 14L:10D, respectively. a, Duda River, Colombia, N 2 40 (Izawa, 1990, 1992, 1997; Klein, 1971, in Di Bitetti and Janson, 2000); b, Cocha Cashu, Peru, S 11 540 (Janson, 1984, personal communication); c, Ana´ polis, Goia´ s Brazil, 16 320 (Hamlett, 1939); d, Caratinga, Brazil, S 19 830 (Lynch and Rı´moli, 2000), e, Iguazu, Argentina, S 26 (Di Bitetti and Janson, 2001); f, CNR Rome, Italy, N 41 480 (Riviello and Wirz, personal communication); g, NIH Poolesville, MD, USA, N 39 080 (Carosi and Suomi, unpublished data); h, CAPRIM Provincia de Corrientes, Argentina, S 27 300 (Zunino, 1990, data from 1978 to 1985); i, CAPRIM Provincia de Corrientes, Argentina, S 27 300 (Patin˜ o et al., 1996, same colony as Zunino, 1990, data from 1989 to 1995); l, CEMIC, Argentina (Nagle et al., 1980, Nagle and Denari, 1983); m, University of Georgia, Athens, GA, USA (Fragaszy and Leighty, personal communication).

availability may be more critical than either rainfall or photoperiod in reproduction (Snowdon, personal communication). Further ad hoc studies should be undertaken to tease apart the roles of photoperiod and food availability. The mating season of wild females lasts longer than the following birth season (more than twice as long at Manu NP, Janson, 1984; at least 2 months longer at Iguazu NP, Di Bitetti and Janson, 2001; at least 4 months longer at La Macarena NP, Izawa, 1980; at least 6 months longer at Estac¸ a˜ o Biolo´ gica de Caratinga, Lynch et al., 2002). At Iguazu NP, females need two to five proceptive cycles before conceiving (Di Bitetti and Janson, 2001), whereas at Estac¸ a˜ o Biolo´ gica de Caratinga, females

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start conceiving as soon as the mating season starts (Lynch et al., 2002; see also variability in ‘‘cycling‐to‐conception’’ delays in the muriqui, Brachyteles arachnoides, Strier et al., 2003). Unfortunately, physiological data, either alone or related to the female behavioral cycle and/or following births, are only available for captive animals for which no apparent seasonal pattern of female ovulatory cycling has been observed (Carosi et al., 1999; Linn et al., 1995; Nagle and Denari, 1983; Nagle et al., 1980). Laparotomy showed that anovulatory cycles in capuchins are extremely rare (Hamlett, 1939). Only three studies have looked at seasonality of male reproductive function as a factor affecting the pattern of births. Captive adult males, living either indoors or outdoors, do not show breeding seasonality in plasma testosterone and semen profiles (sperm concentration, total sperm count, motility, and ratio of living to dead spermatozoa: Nagle and Denari, 1982; see also Nagle and Denari, 1983). It is important to mention that females belonging to this same colony cycled all year round, and births were not seasonal. In contrast, Vaz Guimara˜ es et al. (2003) found seasonal changes in testicular volume in captive capuchins. Also in wild capuchins, fecal testosterone shows a clear seasonal pattern. Lynch et al. (2002) describe a rise in testosterone in all males (all adults including alpha male, and subadults) when the sexual activity of adult females peaks and confirmed conceptions occur, and low testosterone levels during the following months when female sexual activity decreases (and also during the birth season). Sustained levels of testosterone might explain the capuchins’ ability to breed throughout the year in captivity (Lynch et al., 2002). In capuchins, a pre‐ breeding season increase in testosterone, typical of primates with same duration and fully overlapping mating and conception seasons, was not observed. Testosterone levels in all adult males in Lynch and collaborators’ study showed a sustained increase (a four‐fold increase or more in 1 day) right at the onset of the breeding season, and the first female proceptive activity was observed 1 day after the increase in male testosterone. Interestingly, non sexually active males also showed increased testosterone levels during the period of increased female sexual activity. The different patterns of testosterone found in the wild and in captivity (seasonal and non‐seasonal, respectively) could be attributed to ecological factors, such as a difference in diet (but see Vaz Guimara˜ es et al., 2003; see also Lynch et al., 2002), and possibly to female social cueing. To tease these factors apart, Lynch urges studying the hormonal seasonality of males and females belonging to different groups living at the same field site; this would be an ideal setting because the females in different groups show peaks of sexual activity at different times (Lynch, 2002).

BREEDING SYSTEM IN CEBUS APELLA

IV. REPRODUCTIVE COMPETITION

AND

127

MATE CHOICE

A. MALE‐MALE COMPETITION 1. Precopulatory Competition a. Aggressive competition Dominant capuchin males monopolize proceptive females by aggressively interrupting their copulations with subordinate males (Janson, 1984; Lynch, 1998). The same males become rather tolerant when females are at the end of their proceptive period (Janson, 1984). In contrast, Lynch (2002) reports ‘‘non‐agonistic sequential matings’’ as rather common, some of which involved the alpha male as well. In addition, very few aggressive interruptions of mating activity by different males on different targets have been observed (Lynch et al., 2002). However, no details are given on when, during the proceptive period, they have been observed. Finally, in a wild group, the long‐tenured dominant male (more than 8 years in the alpha position) mated with older females in the group (>14 years old) but never courted or mated with the young ones (<10 years old), which he might have sired. In this case, there was little sexual competition between the alpha male and other males (Di Bitetti and Janson, 2001; Escobar‐Pa´ ramo, 2000; Janson, personal communication) (for more details on paternity data, see following). When male interference was studied in captive groups, results were mixed. Welker et al. (1990) reported that male interruptions were rare (Phillips et al., 1994), whereas in groups at the National Research Council in Rome and at the NIH Animal Center in Poolesville, Maryland, dominant male interruptions of subordinate male copulations were common (Carosi, personal observation). Linn et al. (1995) provide the greatest evidence of direct male competition through copulation interference in four groups (N ¼ 297 copulations), with one dominant and one subordinate adult male in each group. Subordinate males had 34% of their copulations interrupted by dominant males. Unfortunately, as the interference data set used by Linn et al. includes data from females whose cycles were not monitored, it cannot be discerned whether interference by dominant males was more likely to occur during the next to last day of a female’s proceptive period, as Janson (1984) reported. During interference, contact aggression was infrequent. Usually a direct stare from the dominant male, or his threat and approach, were sufficient to break up copulation (Linn et al., 1995; Carosi, personal observation; also observed in a wild group, Lynch, 2002). When the recipient of aggression could be determined, in only 1 case out of 15 was it the female (Linn et al., 1995). Subordinate males do not interfere when the dominant male copulates (Carosi, personal observation; Janson, 1984; Linn et al., 1995).

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We believe that group size, age‐sex composition, and degree of relatedness among group members are responsible for these differences. For example, group size and the number of simultaneously fertile females present in the group can account for the low levels of male‐male competition for access to females reported by Lynch (2002) and the high levels reported by Janson (1984) (see also Takahashi, 2004; for group size and sex ratio, see Table I). When two or more females are proceptive at the same time, the dominant male cannot monopolize all of them. Factors such as age of males, group composition, and relatedness could also account for the differences in male‐male competition for access to females evident in captive studies. For example, it is possible that very young subordinate males (3.5 and 5 years old), not perceived by the alpha male as real competitors, were responsible for the low rate of male competition observed by Phillips et al. (1994). The groups studied by Linn et al. (1995) consisted of unrelated individuals with continuously cycling females (because males were vasectomized, females could not conceive); these conditions may have provided a social environment where male competition was more likely to occur. Finally, in the study by Welker et al. (1990), the alpha male had long tenure and had sired some of the adult females; if male‐female kinship lowers attraction, this may account for the low levels of competition observed (see Section IV.F). b. Infanticide Though witnessed in several primate species, infanticide by males is not common. Despite this, infanticide has attracted a lot of attention as part of males’ reproductive strategy (Hrdy, 1974; van Schaik and Janson, 2000), since females who have lost their infants start cycling again and conceive earlier than females whose infants survive until weaning. In wild C. apella, disappearances of infants and juveniles have been reported (e.g., Izawa, 1994; Lynch and Rimoli, 2000), although no case of infanticide has ever been witnessed (but see Fedigan, 2003; Valderrama et al., 1990 for C. capucinus and C. olivaceus, respectively). In the field site of Lynch and Rimoli (2000) infant mortality is one of the highest reported for capuchins (55%), and disappearance of infants is not confined to takeovers. They report one infant and one juvenile disappearing after a successful takeover by the beta male, as well as disappearance of two other infants (conceived after the new alpha male’s tenure had started). Di Bitetti (personal communication) reports that in Iguazu NP, when a peripheral subordinate male attempted to take over, one of the newborn infants disappeared. Soon after the unsuccessful takeover, he became the beta male. As soon as the female that lost her infant resumed cycling, she solicited this beta male, and only 3 months later she resumed soliciting the alpha male, her previous sexual partner.

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Therefore, strong evidence that capuchin males use infanticide to increase their chances of siring infants is lacking so far. In any case, infanticide is not likely to play a major role in tufted capuchin males’ reproductive strategy. c. Non‐aggressive competition Male‐male sexual competition can also consist of actively avoiding aggressive situations. Subordinate males can simply behave as if they were not interested in females. This latter strategy seems rather common in tufted capuchin monkeys. In fact, subordinate males do not mate with alpha females, even when continuously solicited by them (Linn et al., 1995). If dominance is well established, this is usually the case; however, when relative ranks are not yet clearly established, as is the case right after the replacement of the dominant male, we have observed a subordinate male attempting to copulate with an alpha female during her two subsequent proceptive phases. On both these occasions, several attempts to copulate were interrupted by the new dominant male, who then copulated with the alpha female. Afterwards, the subordinate male was never observed attempting copulation when solicited by the alpha female (Linn et al., 1995). Experimental evidence fully supports the view, suggested by Linn et al. (1995), that the social environment inhibits the sexual behavior of subordinate males. We observed sexual behavior in tests in which the constraints imposed by the presence of the dominant male were removed (Carosi and Visalberghi, 1996; Visalberghi and Moltedo, 2001). A subordinate male and a proceptive female were separated from the dominant male with or without the rest of the group. Their behavior was observed before, during, and after separation. Results showed that the animals readily exploited the opportunity provided by the absence of the dominant male to mate, although the subordinate male’s mounting and courtship were less pronounced when he was not alone with the female. Most of the time, mating was prompted by the females that actively courted the subordinate males, or it occurred with the subordinate male taking the initiative with no opposition from the female. Only one female, when separated from the alpha male, kept courting in the direction of the alpha male (who was out of view, on the other side of a sliding door), while mating with the subordinate male. Often these sexual interactions lacked the loud vocalizations typical of capuchin sexual behavior (see also Lynch, 2002, for quiet/furtive matings with subordinate males). Lynch (2002) describes sexual inhibition in her wild group as well. In conclusion, once relative male ranks are established, male tufted capuchins do not seem to directly compete for access to females with overt aggression. Rather, sexual inhibition seems to play a major role in regulating their mating system.

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2. Postcopulatory Competition a. Sperm competition Sperm competition occurs when the sperm of two different males compete for fertilization of the same egg(s) of a female (Parker, 1970). Large testicular volume provides indirect evidence of sperm competition, since it reflects the production of large numbers of viable sperm; in general, primates species with multimale/multifemale mating systems possess large testes (Dixson, 1998a; Harcourt et al., 1981; Møller, 1988; Short, 1979). Cebus males have a testicular/body weight ratio of 0.35% (testicular weight, 9.1 g; body weight, 2.6 kg; see references in Møller, 1988): this value is within the range of species with multimale‐multifemale mating systems, in which sperm competition is hypothesized to occur (Harcourt et al., 1981). Further data confirm this finding on a larger sample. Carosi, Gerald, and Suomi (unpublished data) determined the testicular/body weight ratio of 16 captive C. apella adult males (older than 7 years). They obtained an average testicular weight of 9.9 g and an average body weight of 3.9 kg, resulting in a ratio of 0.26%. It is important to stress that, on average, alpha males have both larger testes and bodies (13.1 g and 4.2 kg, N ¼ 4) than subordinate males (8.9 g and 3.75 kg, N ¼ 12); therefore, differences in body weight partly account for differences in testis weight (Fig. 5). This finding matches the results on testosterone profiles in alpha and subordinate adult males provided by Lynch et al. (2002) in a wild group. The authors showed that, whereas adult males did differ in their mating activity depending on rank (the alpha male participated in more extended courtship sequences, multiple‐mounts, and ‘‘postcopulatory display’’ [see Section IV.A.2.c]; subordinate adult males showed a distinctive more rapid pattern of mating), testosterone profiles did not differ between alpha and subordinate adult males. Differences in testosterone levels were only found between adult and subadult males. These results need to be confirmed for other groups. Behavioral data also support the sperm competition hypothesis (matings with multiple partners, Section II.B). In the ‘‘non‐agonistic sequential matings’’ described by Lynch (2002), the temporal pattern observed (the interval between the last mount by one male and the first mount by another male on the same female, lasted 2 to 33 minutes, 6 observations; Lynch et al., 2002), makes the competition between sperm of different males for fertilization likely to occur (Section III.B.4). The experiments by Carosi and Visalberghi (1996) and Visalberghi and Moltedo (2001), described previously, also indirectly support the sperm competition hypothesis: Dominant males were more likely to copulate with females after the females had been separated from them and isolated with

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F IG. 5. Logarithmic plot of combined weight of testes versus body weight in captive males (N ¼ 16 adult males, NIH Animal Center, Poolesville, MD, USA). A weak relation between weight of testes and body weight (F[1,14] ¼ 7.8 p ¼ 0.01424, r2 ¼ 0.36) turned into a significant relation after the removal of the animal who deviated from the regression line (log body weight ¼ 0.62; log weight of testes ¼ 0.66; F[1,13] ¼ 26.2 p < 0.0002, r2 ¼ 0.67). Weight of testes is calculated using the algorithm provided in Harcourt et al. (1995) from average values of testis length and width. Average values of testis length and width were obtained by measuring each testis twice. In order to maximize independence of measurements, data were collected blindly by M. Carosi by means of a caliper, and the measure obtained (not visible to M. C.) was read by a collaborator.

subordinate males (interestingly, no aggression toward either partner was observed) than when females were simply isolated by themselves for the same period of time. However, since female courtship toward the dominant male was greater upon reunion, further experiments are necessary to establish whether the increased dominant male copulatory behavior is simply due to increased female courtship (it also raises the issue of why female courtship was increased in this situation). b. Sperm plug In species in which sperm competition occurs, sexual selection has favored the evolution of biochemical mechanisms of seminal coagulation after ejaculation, resulting in sperm plug formation (Dixson

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and Anderson, 2002). Possible functions of sperm plug formation in mammals include preventing subsequent matings by sealing the vaginal entrance, minimizing loss of sperm from the vaginal tract, and protecting sperm from the acidic vaginal environment until released in the female reproductive tracts (Dixson and Anderson, 2002). In primates, semen may coagulate to different extents. Dixson and Anderson (2002) used a four‐point scale to rate seminal coagulation (from 1 ¼ no coagulation, to 4 ¼ copulatory plug formation) and used this scale to assess coagulation in different primate genera and to correlate these values with their mating system. Results showed that the genera in which females commonly mate with multiple partners (multimale/multifemale and dispersed mating systems) had the highest values, whereas those genera in which females belong to monogamous or polygynous mating systems had the lowest values. In their dataset, capuchins are lacking. We rate the C. apella sperm plugs between three and four (Carosi, personal observation), values similar to species with a multimale/multifemale mating system. Seminal vesicles produce the fluid portion of the ejaculate and the enzyme responsible for seminal coagulation after ejaculation. Dixson (1998b) demonstrated that the seminal vesicles are larger in those primate genera in which females typically mate with more males during the same fertile phase (i.e., multimale/multifemale and dispersed mating systems). The large size of the seminal vesicles reported for Cebus (species unspecified) is further indirect evidence suggesting a multimale/multifemale mating system in capuchins. c. Courtship after copulation After ejaculation has occurred, the partners show strong interest towards one another in ways that strongly resemble the courtship behavior that precedes and accompanies mating (postcopulatory behavior, Janson, 1984; postejaculatory courtship, Carosi and Visalberghi, 2002; postcopulatory display, Lynch et al., 2002), the only difference being that after ejaculation the male more actively ‘‘courts’’ the female than vice versa (Dal Secco and Visalberghi, 2001; but see Janson, 1984, who attributes to the female the occurrence of postcopulatory behaviors). Both alpha and subordinate males perform postejaculatory ‘‘courtship,’’ and its duration is not affected by rank (Lynch, 2002). During postejaculatory ‘‘courtship,’’ the female attempts to extract the solidified sperm, reaching with her fingers deep into her vagina, sometimes also pressing her lower abdomen with her hand (Dal Secco and Visalberghi 2001; Visalberghi and Carosi, 1997). In cases where we observed the female extracting male sperm, the longer the postejaculatory behavior lasts (N ¼ 18, average duration 23 min; range 9–52 min) the later the female extracts the sperm. Carosi (personal observation) observed the alpha female within

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an hour after mating extracting a cylinder‐shaped sperm plug, inspecting it, and dropping it. Alpha females have also been observed extracting the sperm plug from subordinate females (Linn, personal observation). Copulatory plug displacement also occurs, as described for multimale/multifemale mating system species (e.g., ringtail lemur, Lemur catta; Parga, 2003). When the female copulates with more males in sequence, some of the coagulated semen of the previous partner’s ejaculate is removed during the following partner copulation (Lynch, 2002). Can postejaculatory ‘‘courtship’’ be considered a ‘‘mate guarding’’ strategy? When the female is target of the male ‘‘courtship,’’ she reciprocates and is not interested in other males. Therefore, postejaculatory ‘‘courtship’’ prevents (or delays) sperm plug displacement and sperm competition (Lynch, 2002). This hypothesis is also supported by the relationship between the duration of the postejaculatory ‘‘courtship’’ and female latency to actively extract sperm, and also by the finding that in wild capuchins the ‘‘post‐copulatory displays’’ last longer in the dry season, in which most conceptions occur, than in the wet season (Lynch, 2002). Further studies of this fascinating aspect of tufted capuchin behavior should be undertaken. B. SEXUAL DIMORPHISM Species in which there is intrasexual competition for access to mates (e.g., in polygynous and multimale/multifemale societies) often show sexual dimorphism (e.g., body size, canine teeth size) (Darwin, 1871). According to sexual selection theory, although the degree of dimorphism in weight is constrained by lifestyle (terrestriality and larger bodies allow a higher degree of dimorphism than arboreality and small bodies), the intensity of male‐male competition affects the degree of dimorphism (see also Ford, 1994 for New World primates). The number of females available affects male‐male competition; however, when the intensity of male competition was estimated by using the ‘‘socionomic sex ratio’’ (number of adult males to adult females), no clear causal link with the degree of sexual dimorphism was found (Martin et al., 1994). To better estimate the intensity of male competition, Mitani et al. (1996) adopted the ‘‘operational sex ratio,’’ based on the number of reproductively active males to fertile females; this ratio considers the duration of the mating season and of the female cycle, the number of female cycles before conception, and interbirth intervals. Operational sex ratio is a good predictor of the degree of sexual dimorphism. How about tufted capuchins? Do they have sexual dimorphism, suggesting intrasexual competition? Male tufted capuchins have larger bodies (Izawa, 1980; Robinson and Janson, 1987; present study, see below) and larger canine teeth than females (Masterson and Hartwig, 1998). In

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F IG. 6. Body weights (means  SE) from birth to adulthood of captive male (N ¼ 40) and female (N ¼ 20) C. apella (NIH Animal Center, Poolesville MD, USA). Each animal was weighed twice a year.

primates, sex differences in body weight usually arise postnatally; males grow more rapidly or continue to grow for a longer time than females (Dixson, 1998a). Female and male growth patterns in body weight of captive C. apella are shown in Fig. 6 (see also Fragaszy et al., 2004). By 6 months of age, males already tend to be heavier than females. The females’ growth slows at about 4 to 5 years of age (average weight 2.4–2.5 kg), whereas males continue to grow until they are about 7 to 8 years old (average weight 3.6 kg) (Carosi and Suomi, unpublished data). Consequently, the adult male/adult female body weight ratio for captive C. apella is 1.44. This value is within the range of those reported for species with a multimale/multifemale mating system (Dixson, 1998a). Therefore, the sexual dimorphism present in canine teeth and body weight of tufted capuchins suggests a multimale/multifemale mating system. C. FEMALE‐FEMALE COMPETITION Although male‐male reproductive competition and female mate choice are the most recognized forms of sexual selection in primates, female‐female

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reproductive competition also plays an important role (Dixson, 1998a; Smuts, 1987). Aggressive or direct female‐female reproductive competition, by means of copulation interference, was first suggested by Fragaszy (personal communication in Welker et al., 1990) and thereafter observed in many captive groups of C. apella (Linn et al., 1995; Phillips et al., 1994). Linn et al. (1995) reported 42 attempts at disrupting copulations, 35 of which were successful. Females directed aggression almost exclusively to the female partner of the copulating pair (in 32 out of the 33 cases in which the recipient of aggression could be determined). High‐ranking as well as low‐ranking females attempted to interfere with copulations, but interference always occurred down the hierarchy. This latter point is further supported by data on the direction of interference after dyadic rank reversals. Within the same dyad, rank reversal resulted in a reversal of the direction of all observed copulation interferences (five dyads; Linn, unpublished data). Through statistical inference, Linn and co‐workers suggest that copulation interference by females significantly constrains low‐ranking females’ mating with dominant males. Finally, infant survivorship, interbirth intervals, and age at onset of reproduction differ for dominant and subordinate females (Costin, 1992, 1990). These findings cannot be accounted for by differences in feeding rate and body weight between dominant and subordinate females. Female reproductive outcome was partially controlled by female‐female competition: During late pregnancy subordinate females were often targets of aggression (Costin, 1990). In wild C. apella, more dominant females interfere with the mating of more subordinate ones, and a very strong competition occurs for the alpha male. Very interestingly, dominant females interfere, not only when their proceptive period overlaps with that of a subordinate female, but also when it does not, and even when they are already pregnant (Janson, personal communication). Since female‐female competition constrains subordinate females from mating with the dominant male, the subordinate females end up mating with subordinate males. Nevertheless, in the wild, contrasting data are available for aggressive female competition. Janson observed females interrupting other females’ copulations at Manu NP (Peru) but not at Iguazu NP (Argentina) (Janson, personal communication). At the latter field site, subordinate females directed their sexual soliciting at subordinate males and mated with them, without eliciting female competition. Most of these younger females were born during the long tenure of the dominant male; therefore, they were likely to be his daughters (Escobar‐Pa´ ramo, 2000; for more details on paternity data and incest avoidance, see following).

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D. CRYPTIC FEMALE CHOICE Female choice taking place inside the female body is called ‘‘cryptic female choice’’ (Eberhard, 1985); the choice is ‘‘cryptic’’ because ‘‘it will be missed using classical, Darwinian criteria for sexual selection by female choice: a male can succeed in being accepted as a partner in copulation and achieve genitalic coupling but nevertheless be rejected as a sire’’ (Eberhard, 1996, p. 42). According to Eberhard, the female’s anatomy and physiology may represent a barrier for the sperm and, as such, may affect the evolution of the morphology of the male genitalia involved in sperm transport and fertilization. Eberhard predicts a higher complexity in male genital morphology in species in which females mate with more than one male in each fertile period, than in species in which females mate with a single partner. Primates fit this prediction (Dixson, 1987). Unfortunately, C. apella was not included in Dixson’s study. Let us then consider the morphology of the tufted capuchin’s penis and the kind of mating system it might predict. C. apella males possess a penis whose distal part is flattened and disk shaped; this complex penile morphology (which, in Brazil, earned the species the local name of macaco prego—in Portuguese macaco means monkey, and prego means nail) predicts a multi‐male/multi‐ female mating system in which cryptic female choice occurs. The hypothesis that cryptic female choice may occur is further supported by several other characteristics of capuchin’s sexual behavior, namely that copulation occurs with more than one male within the same fertile phase (see Section II.B); that there is variability in sperm distribution within different females’ genital tracts and variability in male sperm quality (see Section III.B.4); and that capuchin males have a low frequency of ejaculation (see Section III.B.4). The selective effects of female cryptic choice affect male genital morphology and behavior as well (Eberhard, 1996). A male’s behavior should be aimed at increasing his chances of fertilization by controlling the female’s postcopulatory processes; for example, the male should remove sperm from previous males and prevent the female from prematurely interrupting his own copulation, ejaculation, and removal of his sperm plugs. With this in mind, the extended post‐ejaculation ‘‘courtship’’ performed by the male C. apella (see Section IV.A.2) can delay sperm plug removal and increase his chances of fertilization. Although the occurrence of female cryptic choice in primates is still controversial and sperm competition alone could be responsible for male genital evolution, it should be considered that these two processes are not mutually exclusive (Dixson, 2002).

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E. PATERNITY Although paternity data are crucial for assessing male reproductive success, data available for tufted capuchins are still very few. Welker et al. (1990) mentioned ‘‘a weak correlation between courtship/copulation and paternity’’ (p. 169) without providing the method used for assessing paternity (see Fragaszy et al., 2004 for other early studies). Escobar‐ Pa´ ramo (2000) was the first to establish paternity in wild C. apella, using DNA microsatellite loci as markers. This technique assigns paternity by exclusion; that is, the likely father is the individual (among those considered) that shares the highest number of loci with the infant. Sometimes more than one individual has the same score, and they should all therefore be considered as possible fathers. It follows that the more kin‐related fertile individuals that are present, the more paternity assignment becomes problematic. In order to single out the most likely father, the use of many polymorphic loci is advisable. Escobar‐Pa´ ramo (2000) extracted DNA from fecal samples in two wild capuchin groups (Macuco group, Iguazu NP, N ¼ 13 offspring; Macarena group, La Macarena NP, N ¼ 9 offspring) and from blood samples in one captive group (NIH group, Poolesville, US, N ¼ 13 offspring) and established paternity for 35 offspring. Given its importance, we present this study in detail. Escobar‐Pa´ ramo (2000) used five loci for the Macarena and NIH groups (C8, L4, C59, C3, and C40) and three loci for the Macuco group (C8, L4, and C59), and she concluded that the alpha males sired 71.4% of the offspring (25 out of 35). The 10 infants not sired by the alpha male were those born from his own daughters (see the following section on inbreeding avoidance). In her study, most individuals (sometimes the adult males which were candidate fathers, or the mothers) had missing data for two to three loci; therefore, the paternity assessment of the 35 infants was based on a limited number of loci: one locus (two offspring), two loci (seven offspring), three loci (16 offspring), four loci (eight offspring), and five loci (two offspring). While the alpha was the most likely father of 25 out of 35 infants, unfortunately, in most cases, the attribution of his paternity was based on a number of loci that was even smaller than the number of loci analyzed. For 13 infants, alpha male paternity assignment was based on one locus, for eight infants on two loci, for one infant on three loci, and for one infant on five loci. For the two remaining offspring, paternity was based on two loci, and both the alpha and the beta male could be the father; however, since only the alpha male was present in the group at the time of conception, paternity was assigned to him. This assignment of paternity

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based on a subset of loci leaves open the possibility that other males could be fathers. Although lacking a sufficient number of loci, this dataset is a significant contribution to the field of paternity assessment, the first to date available for tufted capuchins. Male perception of mating history with a female is the best proximal cue for him to ‘‘recognize’’ offspring as his own (van Schaik, 2000). Paternity confidence based on exclusive mating with females should increase tolerance toward their infants, and tolerance toward infants and juveniles by the alpha male has been considered indirect evidence of his paternity. In most of the studies carried out in the wild, the alpha male was very tolerant and protective (Izawa, 1980; Janson, 1984, 1986a); the only exception is Lynch’s, (2002) observations. In Lynch’s study, the alpha male had become dominant only 1 year before; often there was more than one female proceptive at the same time, and females usually solicited and mated with more than one male. In this group, the alpha male was never observed to baby‐sit. This finding fits well with the idea that male capuchins will be more infant‐oriented when they are more ‘‘confident’’ of having sired the offspring. F. INBREEDING AVOIDANCE In Escobar‐Pa´ ramo’s (2000) study, besides two offspring which could be assigned to both the alpha and another male, 8 offspring out of 35 were considered not to be sired by the alpha male. Two infants were conceived during unstable social conditions following a takeover (NIH group), but the other six could result from inbreeding avoidance (Macuco and Macarena groups). The behavioral evidence available for the same individuals in the Macuco group fully supports inbreeding avoidance. Di Bitetti and Janson (2001) did not observe young adult females soliciting the alpha male (their possible father), or the alpha male mating with young adult females, or the alpha male interfering while these females had sexual interactions with other males. This suggests that inbreeding avoidance is behaviorally maintained by both sexes. However, in Piauı` (Brazil), a young adult female (possible daughter of the alpha male) was observed courting and mating with the beta male in full view of a disinterested and tolerant dominant male. The day after, she courted the dominant male, who did not reciprocate (Visalberghi, personal observation). Inbreeding avoidance was first suggested by Welker et al. (1990) for captive C. apella to explain why some females consistently preferred as a sexual partner a subordinate male rather than the dominant male, and why courtship was never observed in mother‐son pairs. They argued that the dominant male was too familiar to the females to be the target of sexual interest (a proximal mechanism), since he was already in the group at the

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time of her birth. However, familiarity cannot account for inbreeding avoidance found in a study in the wild, since the beta male (with whom the young females mated) was in the group as long as the alpha male (with whom the young females did not mate) (Di Bitetti and Janson, 2001). However, in our opinion, familiarity should be assessed by strong affiliative relationships and not simply group residency. This causal mechanism should be tested. V. CONCLUSIONS: A ONE‐MALE

OR A

MULTI‐MALE BREEDING SYSTEM?

C. apella live in multimale/multifemale groups, but up to now the species has been considered to have a polygynous (one‐male) breeding system, in which the dominant male has an almost exclusive access to fertile females (Janson, 1984; Robinson and Janson, 1987). In the preceding sections, we have reviewed a series of studies that provide new insights into whether C. apella should be considered to have a one‐male or a multimale/ multifemale breeding system (Table IV). To discuss C. apella’s breeding system, it is imperative to start with the sexual behavior of the female. Female sexual behavior is elaborate, flexible, and opportunistic. Apparently, having more than one sexual partner within the same periovulatory phase is frequent. Females usually, but certainly not always, prefer to mate with the dominant male; moreover, although tightly related to sexual hormones, proceptive displays are to some extent independent of the female hormonal state and under females’ partial control. In the case of capuchin females, the words of Martin (1992, p. 250) seem appropriate: ‘‘it is by no means so obvious that it is in the female interest to have her offspring fathered by the top ranking male . . . it may be in her interest to copulate most with that male and to create the impression that he is likely to be the father of her offspring.’’ The female’s ‘‘flamboyant’’ courtship, by monopolizing the attention of the alpha male, might effectively work to ‘‘convince’’ him that this is indeed the case. Certainly, what we know up to now about the female’s behavior does not support the view that a single male breeding system characterizes the species. Multimale/multifemale breeding systems are usually associated with high levels of intermale aggression (e.g., rhesus monkeys, Macaca mulatta), or with low levels of aggression, as with the promiscuous mating system shown by muriquis (Brachyteles arachnoides). C. apella does not seem to fit in this picture. It is possible that females’ assertiveness in sexual choice, and the sexual inhibition of subordinate males makes male‐male aggressive competition for access to them unnecessary (Janson, 1984).

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LIST

OF

TABLE IV FEATURES AND THEIR COMPATIBILITY WITH A MULTI-MALE/MULTI-FEMALE AND/OR A SINGLE‐MALE BREEDING SYSTEM IN CEBUS APELLA Breeding system

Occurrence Female behavior Mating with multiple males within same periovulatory phase Sexual behavior flexible and opportunistic Male behavior Subordinate males mating only when female not fertile Alpha male tolerance and care for infants Female‐female competition Elaborate forms of courtship behavior Overt female‐female aggression Male‐male competition and sexually selected traits Overt male‐male aggression Subordinate male inhibition of sexual behavior Sperm competition Sexual dimorphism in body weight Complexity of male genitals Sperm plug formation

Multimale/ multifemale

Single male

yes



yes



no



yesa





yes yes

 

 

little yesb





yes yes yes yes

   



a

But see Section IV, Paternity. When the male tenure is long, subordinate males are not inhibited and mate with females (see Section IV, Inbreeding avoidence). b

At this point, to better discuss male‐male competition it is necessary to consider the social and ecological factors that affect access to females in a more general sense. The number of reproductive females in the group (depending on group size2 and sex ratio) and the temporal clumping of fertile females (depending on reproductive seasonality and female synchronicity) affect the extent to which the alpha male is able to monopolize the females and consequently his reproductive success. Given the variability of group size, sex ratio, and reproductive seasonality of C. apella, and given its wide geographical distribution, we expect variability in the reproductive 2 The length of alpha male tenure may also affect the number of females available for reproduction. As reported in two groups (Di Bitetti and Janson, 2001), a long‐tenured alpha male does not mate with all mature females present in the group, since some of them might be his daughters; conversely, because of this, the beta male mates with them overtly.

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success of the alpha male. This suggests that the essentially unimale breeding system described by Janson may be the outcome of demographic and ecological conditions, rather than a trait of the species as a whole. Finally, the findings on sexually selected traits (relative testis size, formation of a copulatory plug, post‐ejaculatory courtship, and complexity of penile morphology) of C. apella fit better with those of primate species with a multimale/multifemale breeding system than with those of species with a single male breeding system. In conclusion, on the basis of the behavioral and morphological evidence discussed, we propose that the breeding system of C. apella be considered as generally multimale/multifemale, but one that may become effectively unimale under certain socio‐ecological conditions.

VI. AREAS

FOR

FUTURE RESEARCH

The reader might have wondered why the focus of this chapter has been C. apella rather than capuchins more generally. The reasons are trivial. In the other Cebus species, there is an overall lack of data on sexual behavior, reproductive physiology, and related issues, from both laboratory and wild animals (Fragaszy et al., 2004). Furthermore, what is known on the mating system of other capuchin species appears less contradictory and raises fewer open questions than in C. apella. Future studies should gather knowledge from different disciplines related to sexual and reproductive issues (behavior, physiology, morphology, etc.) for all species of capuchins, and then examine whether the mating system described and the new data fit together. As Kummer (1992, p. 1) realized when the first studies using reliable techniques for the assessment of paternity in nonhuman primates appeared: Primate field workers have collected years of data in order to address the effects of male dominance on male fitness. With paternity unknown their analysis ended with the unsatisfactory substitute measure of copulation frequency. The extensive study of variation of male reproductive strategies was little more than interesting descriptions of primate behavioral versatility; now, researchers can measure and compare their effects on reproductive success.

This phrase clearly indicates the direction of future primatological research: 1. The assessment of paternity/kinship by using DNA should be undertaken whenever possible. In C. apella, Paternity data are crucial to assess

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whether the alpha male’s success is affected by group size, sex ratio, and ecological conditions; to inquire whether his tolerance is higher towards his own offspring, why his mate guarding or intolerance of subordinate male matings is limited to certain periods, whether the breeding system is unimale or multimale/multifemale, etc. Paternity data are the condicio sine qua non for assessing reproductive success. However, to understand the complexity and function of a species’ socio‐sexual behavior, we need to integrate paternity data with behavior. 2. In primates, and especially in some species (e.g., Pan paniscus, de Waal, 1987; Cebus capucinus, Manson et al., 1997; C. apella, Carosi and Visalberghi, 2002), sexual behavior has both a reproductive and a non‐ reproductive function (e.g., to appease potential aggressors, paternity confusion). An understanding of the non‐reproductive function of sexual behavior can only be reached by comparing paternity data with a thorough characterization of sexual behavior. In this respect, two aspects should always be considered in future studies: the timing of sexual behavior in relation to the female periovulatory phase; and whether mounting, mating, or copulation do or do not involve ejaculation. Although hard to detect, especially in the wild, ejaculation is accompanied by specific behaviors that can be noticed and quantified in the laboratory. Once specific behaviors are recognized as reliable indicators of ejaculation, they can be used as the indirect indication of ejaculation in the field. The mating system, however, is just one of the open questions related to tufted capuchin sexual/reproductive behavior. Possibly most intriguing of all is the apparent sex‐role reversal during courtship, which is usually observed when the targeted male is the alpha male. Why is the male so reticent and reluctant to reciprocate the female courtship? Is the female proceptivity the behavioral counterpart of the sexual swelling exhibited by females of some other primate species to attract males, and is the male able to evaluate the female’s quality from the richness and duration of her proceptive signal? In fact, proceptive phase length was found to be longer when most conceptions occurred than at other times of the year (Lynch, 2002). Is the male coyness a strategy to verify female intensity/persistency (therefore reliability) of the signal? Does female courtship serve to trigger male response at a both behavioral and hormonal level? The flexibility observed in males’ sexual response, depending on rank (both within and between individuals, this chapter) and the influence that their behavior has on the expression of female courtship (the longer their reticence, the more the female courtship is persistent), make the whole picture even more complex. Although most of these issues have been raised and discussed in Carosi and Visalberghi (2002), few studies to date have focused on these questions.

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Other questions concern how aspects of female sexual behavior may increase their infant survivorship. When female proceptive phases overlap, the higher‐ranking female usually forms a consort and mates with the alpha male. Is female rank a predictor of alpha male protection of her babies? As multiple‐male mating does occur, is there any difference between alpha male behavior towards infants of females that do mate exclusively with him versus those who don’t? Is there a differential access to food sources among these infants? When a pregnant female courts a newly established alpha male, what will be the alpha male behavior towards that infant?

VII. SUMMARY In several nonhuman primate species, females play an active role in sexual interactions. In this respect, Cebus apella represents an extreme case: female tufted capuchins take the sexual initiative, and they solicit the male with a prolonged, flamboyant, and versatile courtship. In most cases, the target of the female’s sexual interest is the alpha male, who typically responds with apparent lack of interest and occasional intolerance. Because of the overt and persistent courtship directed to the alpha male, this species has been considered as having a one‐male breeding system. The aim of this chapter is to provide insights into the tufted capuchins’ mating system by examining the evidence from their socio‐ sexual behavior, sexual choice, reproductive physiology, and sexually selected traits as they relate to whether they have a multimale/multifemale mating system or a uni‐male mating system. As summarized in Table IV, and in contrast to what has been previously argued in the literature, we find convergent evidence supporting a multimale/multifemale mating system, although both breeding systems are indeed possible. Variables such as number of fertile females available in a group (which depends on group size, sex ratio, and seasonality of reproduction) and ecological conditions (namely, availability and distribution of food) are likely factors that influence variations in the breeding system.

Acknowledgments We are extremely grateful to our colleagues who graciously took the time to provide us with suggestions, data, or their unpublished manuscripts: Barbara De Vinney, Dorothy Fragaszy, Melissa Gerald, Katherine Leighty, Ginevra Moltedo, Tim Newman, Joseph Soltis, Amy E. Ulland. We are indebted to Mario Di Bitetti and two other anonymous reviewers whose thorough and detailed comments and criticisms, on a previous version of this chapter, helped us to focus on important matters and improve the overall structure of the chapter. We are

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extremely grateful to Charles Snowdon, Tim Roper, and Peter Slater for their constructive feedback and their help in adding clarity to this chapter. Special thanks for their support to Stephen J. Suomi, Charles Janson, with whom an intense and illuminating e‐mailing exchange occurred, Jessica Lynch, Carlos Nagle, and Rodolfo Rey. Thanks to Margherita Stammati for her help in editing the manuscript.

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ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

Acoustic Communication in Noise Henrik Brumm* and Hans Slabbekoorn{ *school of biology university of st. andrews st. andrews ky16 9ts, united kingdom { institute of biology leiden university 2300 ra leiden, the netherlands

I. THE PROBLEM

OF

BACKGROUND NOISE

Communication is the foundation upon which all social relationships between animals are built. However, the use of signals within most sensory modalities is crucially constrained by background noise, for decreased signal‐to‐noise‐ratios at the position of the receiver limit the active space of a signal (Klump, 1996). Nevertheless, the problem of noise has often been neglected in studies on animal communication. In a general sense, noise is any factor that reduces the ability of a receiver to detect a signal or to discriminate one signal from another. It can be classified as either external noise, which arrives at the auditory receptor cells of receivers from the environment, or internal noise, which emerges within the sensory pathway of a receiver (Ronacher et al., 2004).1 However, the term ‘‘noise’’ is most commonly used to describe interfering sounds, occurring externally in the ‘‘background’’ during acoustic signal transmission from sender to receiver. Accordingly, we will focus here on how animals that use sound to communicate cope with such interference from background noise. Although in many instances we fail to notice it, noise is ubiquitous in all habitats, and ambient noise levels are often quite substantial. The 1 Furthermore, classic Signal Detection Theory emphasizes that discriminating between ‘‘noise with signal’’ or ‘‘noise‐only’’ may lead to false negative and false positive responses with respect to the detection of the signal. These false decisions are dependent on another type of internal noise related to the decision rule and detection criteria which may be affected for example by previous exposure, faulty memory, or level of attention (Green and Swets, 1974; Lockhead, 2004).

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characteristics of ambient noise have been investigated in many biotopes, including tropical and temperate forests as well as grasslands (Ellinger and Ho¨ dl, 2003; Lang et al., 2005; Morton, 1975; Ro¨ mer et al., 1989; Ryan and Brenowitz, 1985; Slabbekoorn, 2004a; Slabbekoorn and Smith, 2002; Waser and Brown, 1986), reed fields (Heuwinkel, 1990), aquatic environments such as streams (Lugli and Fine, 2003), and oceans (Andrew et al., 2002; Curtis et al., 1999; Wenz, 1962), as well as urban areas (Brumm, 2004b; Slabbekoorn and Peet, 2003). The major low‐frequency noise source in many terrestrial habitats is wind passing over vegetation, substrate edges, and the head and body of the receiver. In addition to sounds generated by air turbulence, other kinds of abiotic noise are caused, for instance, by rain or running water such as torrents or waterfalls. In marine waters, abiotic noise generates a continuous background sound over a broad frequency band, which is mainly caused by surf, waves, and currents passing over rough substrates, as well as wind and rain. Moreover, biotic noise produced by other animals also adds to the ambient noise scheme in a given habitat. In both water and air, arthropods can produce a considerable level of background sounds (Bradbury and Vehrencamp, 1998). However, the nature of biotic noise differs with the species composition between habitats (Slabbekoorn, 2004a); in some places, the major biotic noise source may be the chorus of songbirds (Catchpole and Slater, 1995) and in others the sounds produced by aggregations of anurans (Gerhardt and Huber, 2002). Another example of a particularly severe biotic noise source is in colonial birds (Aubin and Jouventin, 2002), where a calling animal has to make itself heard against the background of a multitude of vocalizing conspecifics. In addition to all kinds of biotic and abiotic noise sources present in every habitat, this world has become a more and more noisy place due to human activity. In particular, the dramatic increase in traffic during the last century has changed the acoustic environment in many habitats. Consequently, special attention has been paid to the impact of anthropogenic noise on the acoustic communication of many species, including frogs (Sun and Narins, 2005), birds (Brumm, 2004b; Il’ichev et al., 1995; Rheindt, 2003; Skiba, 2000; Slabbekoorn and Peet, 2003), whales (e.g., Buckstaff, 2004; Croll et al., 2001; Erbe, 2002; Foote et al., 2004; Fristrup et al., 2003; Lesage et al., 1999; Miller et al., 2000; Rendell and Gordon, 1999; Richardson et al., 1995), and other mammals (e.g., Rabin et al., 2003; Terhune et al., 1979). Indisputably, there can be a lot of different types of noise sources in a given habitat, and thus the characteristics of the interfering sounds are varied. Firstly, background noises may be of a relatively continuous nature or may consist of rather discrete events (e.g., the constant roar of a

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waterfall represents a quite different noise problem to a vocalizing animal than the relatively short clap of thunder). Secondly, background noises can also differ in their bandwidth (i.e., they can cover rather broad or narrow frequency bands). Thirdly, the occurrence of certain noises is predictable at some locations (e.g., the onset of bird choruses at dawn, or rainfall at noon in some areas in the inner tropics), whereas other noises are quite unpredictable). Furthermore, it is noteworthy that in a given habitat the level and nature of noise can vary crucially in space, for noise is often complex and multifaceted with multiple source locations producing noise characteristics that are likely to vary. Thus, noise conditions can be highly variable in space or relatively homogeneous. For example, wind may reach many locations in a habitat, but level and spectrum of the noise generated may depend, for example, on the abundance and type of leaves in the trees. Noise from biotic sources such as frogs, birds, or primates can be highly aggregated at specific heights or locations in a habitat. On the other hand, cicadas may be spread throughout a forest and sing in concert, generating an omnipresent sound arriving from all directions with amplitudes fluctuating in space but with a relatively constant spectrum (Slabbekoorn, 2004a). When trying to understand how these possibly complex background noise patterns can constrain acoustic communication, we have to bear in mind that the level of signal interference depends on the degree to which the frequencies of the noise and the signal overlap (Dooling, 1982; Hulse, 2002; Klump, 1996). Studies on anurans and mammals have shown how masking noise impairs the exchange of information between individuals by acoustic signals: Ultimately, signal masking by noise may limit mate choice (Gerhardt and Klump, 1988), constrain territorial responses (Pa´ ez et al., 1993), or interfere with the coordination of behavior between mother and offspring (Algers and Jensen, 1985). However, in recent decades bioacoustic research has revealed that animals are not exposed defenselessly to the masking of their signals. Rather, it has emerged that they have evolved a variety of solutions to the background noise problem, which will be addressed in this chapter. We will start off with the sender’s side by considering potential evolutionary shaping of species‐specific signal characteristics and individual short‐term adjustments of signal features. Subsequently, we will focus on the receivers of signals and review their sensory capacities for signal detection, recognition, and discrimination; and we will relate these issues to auditory scene analysis and the ecological concept of signal space.

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II. THE SENDER’S SIDE—SIGNAL PRODUCTION Studies on transmission of long‐range signals have emphasized that acoustic communication is constrained considerably by habitat properties such as microclimate and vegetation structure (Morton, 1975; Wiley and Richards, 1982). While traveling through the environment, acoustic signals are subjected to degradation, and signal propagation is especially limited by frequency‐dependent attenuation. Within this conceptual framework, the evolution of acoustic long‐range signals has been discussed with regard to reducing degradation and attenuation effects to increase the transmission range (Brown and Handford, 2000; Heuwinkel, 1982; Holland et al., 1998; Naguib, 2003; Wiley, 1991). It is noteworthy that it is the degree to which signals stand out against background noise at the position of the receiver which determines the transmission distance; hence, the signal‐to‐ noise ratio is a crucial factor for the exchange of acoustic signals (Klump, 1996).2 Thus, signal design features that increase sound transmission can also be interpreted as adaptations to increase signal‐to‐noise ratios at the position of receivers. Therefore, sound transmission problems cannot be viewed in isolation from constraints by background noise, and we suggest that adaptations for optimal sound transmission in both signal design and sound production mechanisms can as well be viewed as adaptations to cope with background noise. Using signals that transmit especially well through a given habitat is not the only way in which animals can increase signal‐to‐noise ratios at the position of receivers. In addition, the sender can further increase signal‐to‐ noise ratios by positioning itself well for effective sound transmission according to the properties of the habitat (Hunter, 1989; Nemeth et al., 2001; Parris, 2002; Waas, 1988; Wilczynski et al., 1989). Moreover, it has been shown that songbirds can position themselves for the most effective signal transmission according to the perceived position of intended receivers (Brumm and Todt, 2003), thereby increasing signal‐to‐noise ratios at the receiver’s position by exploiting the directional sound radiation pattern of their songs (Brumm, 2002). Most animals that use sound to communicate have to face the problem of communicating through masking noise and, with regard to signal production, they have evolved various adaptations for making their signals more 2

However, there are also other important variables, such as the degradation of signals. For example, a strongly degraded signal may still be well above the level of masking background noise, but nevertheless information transfer would be impaired. When considering noise in the broader sense of Shannon and Weaver’s (1949) mathematical theory of communication, signal degradation can be referred to as signal inherent noise (Wiley, 1994).

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audible. Such solutions to the background noise problem may involve evolutionary changes in signal characteristics leading to long‐term adaptations, or they may be short‐term adaptations; that is, individual adjustments of signal traits in response to variation in the background noise.

A. LONG‐TERM ADAPTATIONS 1. Changes in Acoustic Signal Structure Many habitats have their own typical pattern of ambient noise, due, for instance, to the exposure of wind and the composition of sound‐producing animals (Fig. 1). More or less constant noise in a given frequency range that is present during significant times may act as a selection pressure upon the evolution of acoustic signals in the habitat concerned (Slabbekoorn, 2004a). As a result, acoustic signals will be shaped to stand out against the sounds of the background (Fig. 2), or, in other words, signals will be favored that are better audible to the intended receiver. In line with this consideration, a significant effect of background noise on the evolution of frequency spectra has been suggested for bird and primate vocalizations (Brenowitz 1982; Morton, 1975; Ryan and Brenowitz, 1985; Waser and Brown, 1986; Wiley and Richards, 1982). Indeed, a study on songs of red‐winged blackbirds (Agelaius phoeniceus) and their relationship with environmental noise proposes that males use a ‘‘silent window’’ of comparatively low levels of background noise for acoustic communication (Brenowitz, 1982). Similarly, blue monkeys (Cercopithecus mitis) and pygmy marmosets (Cebuella pygmaea) produce calls with dominant frequencies coinciding with typical low‐amplitude regions in the environmental noise spectra of their habitats, which may be the result of an evolutionary shaping of the call structure to minimize masking by background noise (Brown and Waser, 1984; de la Torre and Snowdon, 2002). Recently, it has been discovered that concave‐eared torrent frogs (Amolops tormotus) and a songbird, the black‐faced warbler (Abroscopus albogularis), produce acoustic signals that contain prominent ultrasonic harmonics (Narins et al., 2004). Perhaps these unusual high‐frequency components help the vocalizations to stand out against the constant acoustic masking of lower frequencies in their habitats by noisy streams. (However, it still remains to be shown that these frog and bird species can hear the high‐frequency components at all.) Another songbird found in the same habitat provides a classic example of a possible long‐term vocal adaptation to environmental noise. It is the large‐billed leaf‐ warbler (Phylloscopus magnirostris), a species living close to torrents in the Himalayas. Torrents and waterfalls generate a constant high‐intensity

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F IG. 1. Environmental noise levels in two forests. (A) Typical background noise spectrum in a temperate forest. Contributions of abiotic noise (wind) and biotic noise (bird songs and calls) are indicated. (B) Typical background noise spectrum in a tropical rainforest consisting of numerous biotic noises produced by birds, frogs, and insects. (Figures are based on recordings done by HB in a German beech forest (A) and in a primary rainforest in the Brazilian Amazon (B).)

noise over a broad frequency band up to 4 kHz, and large‐billed leaf‐ warblers evade masking of their territorial songs by producing high‐pitched notes in narrow frequency bands around 6 kHz (Dubois and Martens, 1984). Interestingly enough, the simple acoustic structure of large‐billed leaf‐warbler songs is more similar to the calls of frogs from the same habitat than to the more complex songs of all other Phylloscopus species, which show rapid frequency modulations.

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FIG. 2. The use of a ‘‘silent window’’ in the communication channel. Power spectra of dipper (Cinclus cinclus) calls (shown in gray) and the background noise in the bird’s habitat (shown in black). During the breeding season, dippers live on fast‐running waters, especially stony streams and torrents, which produce constant high levels of background noise. Birds evade acoustical masking of their vocalizations by calling at frequencies well above the typical background noise in their habitats. (Sound recordings made by HB on a mountain creek in Perthshire, Scotland.)

Differences in song or call structure based upon differences in habitat noise are not only suspected between species but also between subspecies (Douglas and Conner, 1999), or even in different populations of the same species. The latter case has been demonstrated by Slabbekoorn and Smith (2002) for the songs of little greenbuls (Andropadus virens). In this African bird, males living in rainforests sing low‐frequency notes that are not used by birds in ecotone forests. This song divergence seems to be related to differences in the noise characteristics in the two habitats, for in ecotone forests noise levels are equal throughout the frequency band of greenbul song, whereas in the rainforest low song frequencies are affected by much lower noise levels compared to high song frequencies. Thus, the song divergence in ecotone and rainforest populations might have been driven by the selection pressure imposed by the typical spectral distinction of background noise in their respective habitats. Long‐term adaptations in signal characteristics could also account for the observation that urban great tits (Parus major) tend to sing with a higher

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minimum frequency at locations exposed to high levels of low‐frequency noise than those in quieter areas (Slabbekoorn and Peet, 2003). However, it is conceivable that habitat‐dependent signal differences could also be the outcome of plasticity during the lifetime of individuals instead of more long‐term adaptations over evolutionary time. Through ontogenetic changes based on individual learning processes, an animal could reduce the masking effects of habitat‐specific noise by adjusting the properties of its signals. Such putative ontogenetic plasticity could have population‐wide consequences, potentially resulting in habitat‐dependent acoustic shifts. Although relative plasticity during ontogeny may be viewed as a long‐term adaptation in itself, this is not necessarily an evolutionary adaptation to environmental noise in the first place. However, it is a challenging task to assess whether a given signal is adapted to habitat‐specific noise by evolutionary or ontogenetic changes, and yet there are, to our knowledge, no studies addressing this issue. 2. Use of Different Communication Channels Many animal displays are complex; they can include various signal components, and may also combine signals of two or more sensory modalities (Guilford and Dawkins, 1991; Partan and Marler, 1999). For example, many avian sexual displays are highly elaborated combinations of acoustic and optic components (Bo¨ hner and Veit, 1993; Cooper and Goller, 2004; Malacarne et al., 1991). Such multicomponent signals could convey multiple messages or facilitate information transfer by increasing the probability of signal detection (Johnstone, 1996; Rowe, 1999). Signal masking by background noise could have driven the evolution of multimodal displays of the latter kind; and the use of additional, non‐acoustic signals might be a phylogenetic route followed by some species to compensate for the masking of their vocalizations. Indeed, the use of two communication channels at the same time improves the detectability of displays (Rowe, 1999), and it is tempting to assume that animals in noisy environments may increase the effectiveness of their vocal signals by the simultaneous use of visual cues. Corroborative evidence for this idea comes from nestling birds. Begging calls of most birds evolved in an especially noisy context, because the vocalizations of a nestling are constantly masked by the calls of its nest mates. Interestingly, in addition to their begging calls nestlings also use optic signals, such as colorful mouth markings (Immelmann et al., 1977) and conspicuous postures (Leonard et al., 2003). A similar relationship has been suggested for vocalizations accompanied by optic signals in some frogs and toads. In their review on visual signaling in anurans, Ho¨ dl and Ame´ zquita (2001) suggest that optic signals might represent a complementary form of communication for those species

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inhabiting noisy habitats. A particularly striking optic signal in frogs is the so‐called foot‐flagging display, in which calling males stretch out one or two hind legs and vibrate their feet or stretch out their toes. Foot‐flagging displays have been found mainly in species living in noisy environments—for example, along neotropical and oriental fast‐flowing stream (Haddad and Giaretta, 1999; Ho¨ dl and Ame´ zquita, 2001) or at locations with high levels of heavy rains and numerous conspecific and heterospecific calling males (Ame´ zquita and Ho¨ dl, 2004). Moreover, constant masking of vocal signals may also lead to a predominance of optic signals, as proposed for the Panamanian golden frog (Atelopus zeteki), a species living close to fast‐flowing montane streams (Lindquist and Hetherington, 1996). Experimental evidence suggests that during male‐male agonistic interactions these frogs appear to rely preferentially on optic signaling rather than acoustic signaling. Interestingly, this species lacks a tympanic middle earhowever, we are still in the dark about the causal relationship between reduced hearing capabilities, optic communication, and populating noisy habitats. Also, it should not be forgotten that in most habitats optic displays act at much shorter range than acoustic signals, and thus long‐range limitations of vocalizations cannot generally be compensated for by optic cues. However, the more intense the background noise (and, as a result, the shorter the communication range of acoustic signals), the more important optic short‐range signals will be. We believe that the study of multicomponent signals has great potential to further elucidate how the environment shapes signal design, particularly when considering that a low signal‐to‐noise ratio in one signal component might be outweighed by the additional use of a second communication channel. However, most work on the function of complex animal displays has focused on each component separately. But we should bear in mind that, in the end, selection will act upon displays as a whole, and thus we require knowledge of how the components function collectively. Such integrative research has just begun (Leonard et al., 2003; Narins et al., 2003; Rosenthal et al., 2004), and more data are needed on how receivers perceive the acoustic and optic components of complex displays before we can understand the role of environmental noise in the evolution of multicomponent displays in more detail. B. SHORT‐TERM ADAPTATIONS In addition to the evolutionary or ontogenetic shaping of signal traits, animals may also adjust the characteristics of their vocalizations in response to temporary changes in the background noise. Such vocal short‐ term adaptations have been examined in much greater detail than

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F IG. 3. The Lombard effect in a songbird. Nightingales regulate the sound level of their songs depending on the sound level of the background noise. Data are an example from one bird (medians and interquartiles ranges); n denotes the number of songs (from Brumm and Todt, 2002, used with permission).

long‐term changes, and studies addressing this issue encompass insects, anurans, birds, and mammals.3 In order to get their messages through the noise, sound‐producing animals may adjust the characteristics of their acoustic signals (i.e., by regulation of signal amplitude, duration, redundancy, and pitch) and also the timing of their signals. 1. Adjustment of Signal Characteristics a. Regulation of signal amplitude The most obvious way to counteract masking from background noise is to increase signal amplitude as the noise level rises (Fig. 3). This phenomenon is termed the Lombard effect, after the French ear specialist Etienne Lombard, who discovered it in human speech and reported his findings to the French Academy of Medicine almost a century ago (Lombard, 1911). In the following six decades, 3

However, one has to be cautious when interpreting observations from uncontrolled experiments. There have been several reports that animals (e.g., marine mammals) decrease vocal activity when exposed to unusually high noise levels (reviewed in Richardson et al., 1995), but it is not clear whether in these cases environmental noise only represents a problem for acoustic communication, or also acts as a stimuli eliciting disturbance reactions, such as flight behaviors. When trying to investigate the effects of noise on acoustic communication these effects must be disentangled.

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Lombard’s discovery stimulated fruitful research activity amongst physicians and experimental psychologists, resulting in more than 60 published articles related to the issue (reviewed in Lane and Tranel, 1971). Since then, the Lombard effect has continued to be the subject of numerous studies in humans, concerning spectral noise characteristics and the speaker’s gender (Egan, 1972), age and task (Amazi and Garber, 1982; Siegel et al., 1976), and voluntary control (Brown and Brandt, 1972; Pick et al., 1989; Tonkinson, 1994; Winkworth and Davis, 1997) as well as clinical aspects (Adams and Lang, 1992; Ho et al., 1999; Ternstrom et al., 2002; Zeine and Brandt, 1988) and technical applications (Junqua, 1993). However, it took more than 60 years until this well‐recognized vocal mechanism attracted the attention of researchers working on acoustic communication in non‐human animals. One of the first to investigate this topic was Potash (1972), who studied noise‐induced changes in the calls of Japanese quail (Coturnix coturnix japonica). He played white noise to males in sound‐ proof chambers and recorded the birds’ separation calls after their mates had been removed, and, indeed, the louder the white noise, the louder the quails vocalized, showing that the Lombard effect is not unique to human speech. Subsequently, the Lombard effect has been reported for several bird and some mammal species (Table I). From all the evidence, it is clear that the induction of the Lombard effect does not depend on whether the vocalizations concerned are learned or not, because amplitude regulation in noise is found in learned vocal behaviors such as bird song and the calls of parrots, as well as in quails and monkeys, which do not acquire their calls by learning. Furthermore, Cynx et al. (1998) demonstrated that zebra finches (Taeniopygia guttata) exhibit the Lombard effect in both learned vocalizations by males and unlearned vocalizations by females. The Lombard effect depends on the spectral characteristics of the background noise in relation to those of the signal. As shown with psychoacoustic experiments with budgerigars (Melopsittacus undulatus), it is noise in the spectral region of the birds’ own calls that is most effective in inducing budgerigars to increase vocal intensity (Manabe et al., 1998). This crucial effect of masking noise, instead of noise in general, was also found in a songbird (Brumm and Todt, 2002) and macaques (Sinnott et al., 1975). Thus, it is reasonable to assume that these animals assess the signal‐to‐ noise‐ratio between their vocalizations and the masking noise, and that they regulate their vocal amplitude accordingly. Given the difficulties of reliable sound level measurements in the field, almost all studies addressing the Lombard effect have been conducted in laboratory settings. But a recent study in nightingales (Luscinia megarhynchos) showed that birds also exhibit the Lombard effect in their natural habitats, indicating the significance of vocal amplitude regulation

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TABLE I SHORT‐TERM ADAPTATIONS FOR ACOUSTIC COMMUNICATION IN NOISE: REGULATION OF SIGNAL CHARACTERISTICS IN RESPONSE TO SIGNAL MASKING

Birds Japanese quail (Coturnix c. japonica) Budgerigar (Melopsittacus undulatus) Zebra finch (Taeniopygia guttata) King penguin (Aptenodytes patagonicus) Nightingale (Luscinia megarhynchos) Bengalese finch (Lonchura striata domestica) Blue‐throated hummingbird (Lampornis clemenciae) Mammals Long‐tailed macaque (Macaca fascicularis) Pigtailed macaque (Macaca nemestrina) Domestic cat (Felis silvestris catus) Common marmoset (Callithrix jacchus) a

Lombard effecta

Regulation of serial redundancya

Yes Yes Yes

Yes

Regulation of signal durationa

Reference

Yes Yes

Potash, 1972 Manabe et al., 1998 Cynx et al., 1998 Lengagne et al., 1999 Brumm, 2004b; unpubl. data; Brumm and Todt, 2002 Kobayasi and Okanoya, 2003a,b Pytte et al., 2003

Yes Yes Yes Yes

Sinnott et al., 1975 Sinnott et al., 1975 Nonaka et al., 1997 Brumm et al., 2004

Yes

Yes No

No

Cells with no entries indicate that the mechanism concerned has not been investigated.

No

Yes

HENRIK BRUMM AND HANS SLABBEKOORN

Species

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for the behavioral ecology of bird song (Brumm, 2004b). Males in noisier territories sang with higher sound pressure levels than birds at less noisy locations; thus, it seems as if they tried to maintain the active space of their songs by adjusting song amplitude in relation to the level of noise. In fact, analysis of individual song levels revealed that males adjusted the amplitude of their songs depending on the background noise amplitude: Birds with territories in urban areas sang louder on working days than on weekend days, when there was less traffic in the morning hours and environmental noise levels were lower. As shown in laboratory experiments (Brumm and Todt, 2003), individual song levels can be adjusted to a great extent (on the average about 10 dB), indicating the great potential of vocal amplitude regulation for acoustic communication noise. It should be clear when discussing the Lombard effect that noise‐ dependent vocal amplitude regulation has to be viewed from the perspective of both signal perception and production. An increase in signal amplitude (and connected to this an increase in the signal‐to‐noise ratio) not only counteracts interference from masking noise for the receiver but also for the sender. Hence, animals may also vocalize louder in noise to hear themselves, maintaining a feedback loop between perception and vocal production. Thus, the Lombard effect may serve to maintain a given signal‐to‐noise ratio that is favorable for both signal perception and production. These two functions of noise‐dependent amplitude regulation have been attributed to human speech (Amazi and Garber, 1982; Lane and Tranel, 1971) and vocalizations of birds (Brumm, 2004a; Brumm and Todt, 2002; Cynx et al., 1998; Kobayasi and Okanoya, 2003b; Manabe et al., 1998). A comparative view on the distribution of the Lombard effect is also interesting, as it may shed light on the evolution of this form of vocal plasticity. If the Lombard effect is a homologous mechanism of vocal production in birds and mammals, one should expect to find it also in reptiles. This may be verified by examining vocally active species such as some geckoes or crocodiles. Furthermore, the Lombard effect might have an evolutionary history that even extends back prior to the phylogenetic origins of reptiles. For example, frogs are able to adjust their call amplitude in response to social variables (Lopez et al., 1988), indicating that they have at least one precondition for showing the Lombard effect (i.e., vocal amplitude control during sound production). Given the recent advances in the study of acoustic communication in fish (Zelick et al., 1999), this taxon might be a promising field to trace back further the history of noise‐ dependent vocal regulation. The current view is that stridulating insects most likely are not capable of controlling the amplitude of their chirps. One important reason for this may be that auditory feedback seems not to play a role in sound production in insects at all (reviewed in Gerhardt and

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Huber, 2002). Thus, a convergent evolution of the Lombard effect in insects is not very likely. b. Regulation of signal duration Perceptual studies have shown that the detectability of brief acoustic signals (below a few hundred milliseconds) improves considerably with increasing signal duration, a phenomenon based on the temporal summation of signal energy in the peripheral auditory system of receivers (see Section III.B.2). On this basis, Brumm et al. (2004) suggested that some animals may adjust the duration of brief acoustic signals to reduce the masking effects of temporally elevated noise. They found that common marmosets (Callithrix jacchus) increased their call syllable durations in response to increased levels of white noise played back to them (Fig. 4). Thus, in this neotropical primate, the duration of call syllables appears to be a flexible trait, which can be regulated according to ecological constraints from environmental noise. Moreover, the marmosets not only increased signal duration to cope with interference from background noise, but also exhibited the Lombard effect, indicating the capacity for multiple vocal adaptations for communication in noise within one species. The same phenomenon of multiple adaptations for communication in noisy conditions can be observed in human speech. When exposed to masking noise, speakers maintain speech intelligibility by increasing both

F IG. 4. Noise‐dependent regulation of signal duration in a monkey. Common marmosets increase the duration of their call syllables to counteract the masking effects of increased levels of background noise. Data shown are examples from one monkey; each data point represents the median syllable duration of one call series comprising 5–13 syllables (from Brumm et al., 2004, used with permission).

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vocal amplitude (Section II.B.1.a) and the duration of words, which is mainly due to an increase in vowel duration (e.g., Castellanos et al., 1996; Newman, 2003; Pittman and Wiley, 2001; Summers et al., 1988; Tartter et al., 1993). Recent studies on baleen whales could not find an effect of anthropogenic low‐frequency noise on the whales’ song length (Croll et al., 2001; Fristrup et al., 2003). However, it is important to be clear that since the whale songs were several minutes long, a putative increase could not relate to an exploitation of temporal summation, but merely to a more general increase in signaling time, thereby increasing the probability of hitting a silent window in fluctuating noise. In contrast, the so‐called primary call of killer whales (Orcinus orca) can be rather brief (about 1 second or shorter), and Foote et al. (2004) found that killer whale calls were longer in the presence of boat noise, maybe allowing them to cope with signal masking. However, as the calling whales could not be individually identified in this study, it is not clear yet whether the finding is based on individual call regulation or whether individuals with longer calls were more likely to vocalize in the presence of boats. c. Regulation of serial redundancy The mathematical theory of communication indicates that if the communication channel is affected by noise, the amount of information transmitted could be maintained by an increase of redundancy (Shannon and Weaver, 1949). Indeed, empirical studies on acoustic communication suggest that some animals use an increased redundancy to maintain the efficiency of information transfer. Again, it was the pioneering work of Potash (1972) that demonstrated a noise‐dependent adjustment of serial redundancy for the first time: As the noise level rose, Japanese quail increased the number of call syllables per call series. Another particularly interesting example on this topic is in the display calls of king penguins (Aptenodytes patagonicus). The hubbub of the colony and the roaring sound of often strong circumpolar winds are a common noise source in their sub‐Antarctic breeding grounds. The penguins respond with an increase in the number of syllables in their calls when the background noise levels rise due to increased wind speed (Lengagne et al., 1999). Noise‐dependent regulation of serial redundancy was not found in the calls of common marmosets (Brumm et al., 2004) or in the number of notes in the trill sections of nightingale songs (Brumm, unpublished data). Perhaps an adjustment of redundancy or signal duration cannot be used to counteract interference from noise in all signals, because these parameters might be used to encode information in some cases. However, given the paucity of studies, any speculation on this topic seems to be quite premature.

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d. Regulation of spectral characteristics Further challenges remain in the domain of noise‐dependent regulation of spectral signal characteristics. If a given acoustic signal is only partly masked by noise in a narrow frequency band, it is well within the bounds of possibility that in response the sender may shift the spectral energy distribution of its vocalizations to mitigate acoustic masking. Lesage et al. (1999) found that some beluga whales (Delphinapterus leucas) tend to use calls with higher frequencies when exposed to boat noise. However, the results were inconsistent, and frequency shifts were also observed in the presence of broad‐band noise where the increase of call frequency did not result in more favorable signal‐ to‐noise ratios. Thus, it is questionable whether the observed call changes were due to the masking effects of background noise. In accordance with the idea of noise‐dependent vocal pitch adaptation, Rendell et al. (1999) suggested that differences in call frequencies between pilot whale (Globicephala macrorhynchos, G. melas) populations might be the result of different levels of background noise. However, controlled experiments are needed to shed some light on how whales actually perform under noisy conditions. For example, research on echolocation clicks has shown that toothed whales can vary them in response to masking from noise (Au, 1993). In San Diego Bay, almost all clicks of a beluga whale had a peak energy between 40–60 kHz. But when the animal was moved to Hawaiian waters, where there was a high level of biotic noise from snapping shrimps in this frequency band, the whale shifted the peak energy of the majority of its clicks to above 90 kHz (Au et al., 1985). In addition, we also need information about other taxa in which it could be promising to approach this issue. For example it has been shown that frogs (Bee et al., 2000; Lardner and bin Lakim, 2002) and birds (Hultsch and Todt, 1996; Manabe, 1997) are able to alter vocal pitch in the short term, and it will be interesting to learn if they use this capacity to evade masking from noise. e. Summary To sum up then, the overall picture shows that the common problem of communication in noise led to the common solution of amplitude regulation in all vertebrates tested so far. Thus, the Lombard effect seems to be the basic mechanism to cope with background noise. In addition to the Lombard effect, some birds and one primate species have been shown to adjust the redundancy or the duration of their signals to counteract interference from environmental noise. Further studies will show whether these forms of plasticity in signal production represent more general counterstrategies in animal communication systems or whether they are rather special adaptations found in only a few taxa.

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2. Adjustment of Signal Timing In some cases, high‐intensity noise inhibits acoustic signaling (i.e., if the masking noise exceeds a certain sound level, some animals give up vocalizing). An example of a possible inhibition caused by abiotic noise has been shown by Lengagne and Slater (2002) for the calls of tawny owls (Strix aluco). During wet nights, most birds observed stopped calling with increased levels of background noise produced by rain. However, it is not easy to distinguish the effects of masking noise from other variables, such as decreased overall activity of both senders and receivers in wet weather. In addition to abiotic noise, biotic noise can also lead to inhibition, in which the masking signals of one species suppress the signaling by another species on a long time scale (Ro¨ mer et al., 1989; Schwartz and Wells, 1983). Interspecific inhibition can result in an activity shift of signaling, as demonstrated by Greenfield (1988) for the bushcricket Neoconocephalus spiza. Primarily, males stridulate during the night, but in places where closely related nocturnal species with spectrally similar signals occur, N. spiza males circumvent signal masking by chirping mainly during the day. When the inhibiting species were removed, males quickly shifted their time of stridulating back from diurnal to nocturnal. As well as varying the diel rhythm of signaling activity, animals can also avoid competition for acoustic space by adjusting the timing of their signals within minutes or seconds. The first evidence for such a short‐term adjustment came from a study of Cody and Brown (1969) on the singing activity of neighboring wrentits (Chamaea fuscata) and Bewick’s wrens (Thryomanes bewickii). They found that during the morning hours both species exhibited a periodicity of song output, reaching peak values approximately every 50 minutes. But the two cycles were out of phase, resulting in asynchronous patterns between the two species: when one was at its maximum song output, the other sang the least. Moreover, birds and frogs can adjust the timing of their signal patterns on an even finer time scale to make themselves heard against the background of interfering sound from other species. Such fine‐scale patterns of signal timing among heterospecifics have been revealed for different forest birds where males were singing at the same time of day, but they tended to avoid overlapping songs of nearby birds (Ficken et al., 1974; Popp and Ficken, 1987; Popp et al., 1985). But the timing of songs is not the only way in which songbirds counteract masking from songs of other species. In addition, they can also try to cope with competitors by increasing vocal amplitude, as shown for nightingales. Brumm and Todt (2004) found that males competing for acoustic space with the playback of heterospecific bird songs were

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likely to avoid overlapping and, at the same time, they sang considerably louder compared to their solo singing. The extent of precise fine‐scale timing in response to changes in the background noise level has been demonstrated with playback experiments on the Coqui treefrog (Eleutherodactylus coqui). Male calling is suppressed by masking noise, but Zelick and Narins (1985) found that Coqui frogs could call within short gaps of 750 ms. The frogs studied were even able to do so when the occurrence of these gaps was varied in a pseudorandom fashion, so that males could not foresee the onset of quiet windows in the communication channel (Fig. 5). Basically, the frogs started calling as soon as the bursts of masking noise ended, a behavior which seems highly adaptive in the noisy environments of chorusing anurans. Aggregations of vocalizing conspecifics are environments with a high level of masking noise, and these mechanisms for a fine‐scale adjustment of call timing could lead to signal asynchrony between individuals (Greenfield, 2005). Indeed, alternation of vocalizations can often be observed in conspecifics, and it has been suggested that birds (Evans, 1991; Ficken et al., 1985; Wasserman, 1977) and frogs (Grafe, 1996; Schwartz, 1987) avoid signal overlapping to prevent auditory masking. However, the timing of signals in male‐male interactions sometimes plays a more complicated role than just to avoid acoustical masking, but as an aggressive or dominance signal between rivals (for timing of songs in birds, see Todt and Naguib, 2000; for vocalizations of anurans and stridulations of insects, see Gerhardt and Huber, 2002).

F IG. 5. Fine‐scale adjustment of signal timing in a frog. The figure shows oscillograms of the calls (arrows) by a Coqui treefrog within 750 ms gaps in masking noise (asterisked). The treefrogs could not anticipate when the next gap would occur; they started calling as soon as the bursts of masking noise ended—a behavior which seems highly adaptive in noisy environments, such as in chorusing anurans (modified from Zelick and Narins, 1985, Fig. 6; used with permission).

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III. THE RECEIVER’S SIDE—SIGNAL PERCEPTION Many animals rely on acoustic signals in a rather noisy world. This must mean that they can deal with the environmental conditions to such an extent that an important role for auditory stimuli in fitness‐related tasks is still a likely evolutionary outcome of natural selection. This may suggest even greater constraints in other signaling modalities, but it is also due to the receivers’ abilities to extract relevant signals from irrelevant noise. Although the receiving end of the auditory communication channel may seem to be the passive one, it has a variety of ways for dealing with ambient noise. Animals do not just accept passively how signals and noise arrive from the outside world and enter their auditory system. Receivers can play an active role in adjusting signal‐to‐noise ratios in several ways. Therefore, we will start this section by reviewing aspects of what could be labeled as ‘‘hearing ecology.’’ Second, after sound has arrived at the ear, a range of sensory adaptations in the auditory system operate together to extract signals from the background noise. Sensory adaptations are found at different levels, at the auditory periphery as well as at more central levels in the brain, and they concern both ‘‘bottom‐up’’ and ‘‘top‐ down’’ processes. ‘‘Bottom‐up’’ refers to how sound stimuli trigger auditory neurons selectively on the primary sensory epithelium in the vertebrate cochlea and how firing patterns are subsequently transferred and integrated to higher auditory nuclei. ‘‘Top‐down’’ refers to perceptual phenomena controlled by higher cognitive centers that affect the perceptual salience of acoustic features through shifting of selectivity at some stage in the upward auditory pathway of firing neurons. Perceptual phenomena related to top‐down processes will be addressed in the third part of this section. When potential signals are well within the audible range and picked up by the ear, the perceptual processing is by no means finished, and complex tasks are still to come. Animals may find themselves exposed to multiple sounds from multiple sources, more or less overlapping in time. All of these sounds, each with a suite of acoustic features, arrive at the ears and enter the auditory system as a whole. The animal has to decide which acoustic features belong to what source and which of those sources it is worthwhile to respond to. We will address studies that have shown the ability of receivers to extract relevant acoustic signals from a mixture of potentially interfering sounds, something that has become known as the cocktail‐party effect and which requires so‐ called ‘‘auditory scene analysis.’’ In the final section, we relate the insights in this field of research, mainly derived from laboratory studies on animals and psycho‐acoustic studies with humans, to the ecological concept of ‘‘signal space.’’

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A. HEARING ECOLOGY Signals and noise are usually spatially separated, coming towards the receiver from a different location via transmission pathways varying in length and angle. Different transmission pathways implicate variation in the relative proximity of the receiver to the various sound sources, and this is likely to mean a difference in number and kind of obstacles and reflective surfaces that sound waves will meet on their way. Another impact on the quality of sound upon arrival at the ear due to different transmission pathways is variation in how exposure to microclimatic factors (such as air turbulence, wind, and temperature gradients) affects the level of attenuation and degradation. Consequently, when a receiver moves through its habitat, it will change its position relative to surrounding sound sources and thereby affect the characteristics of both perceived signals and noise (Fig. 6).

F IG. 6. Schematic illustration of some aspects of hearing ecology. Two countersinging birds may experience different signal‐to‐noise ratios despite singing at the same amplitude level, because of different distances from the source of ambient noise (AN), or because of variation in transmission properties for signals and/or noise. A receiver bird may improve the signal‐to‐ noise ratio for the mixture of sound arriving at its ears by approaching the signal source (1) or by changing position in such a way that transmission pathways change in favor of the signal relative to the noise (2).

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Relative proximity to the source location of signal and noise will clearly have a direct impact on the signal‐to‐noise ratio. The ratio will improve when approaching the sender of the signal or moving away from the noise source. Sound attenuates at about 6 dB per doubling of the transmission distance, and obviously this will affect both signal and noise. Furthermore, sound transmits through a natural environment with trees and shrubs in a frequency‐dependent way. In general, low‐frequencies transmit better than high frequencies and reach farther, especially through dense vegetation (Slabbekoorn and Smith, 2002; Wiley and Richards, 1982). Consequently, both signal and noise may undergo spectral energy shifts when a receiver moves through its habitat; moving towards a signal sender will result in less attenuation for high frequencies in the signal and improve possibilities for assessment of original spectral characteristics. Similarly, moving away from a noise source will lead to more attenuation of its high‐frequency component, and, consequently, this will result in a shift in the remaining noise towards lower frequencies. The significance of these acoustic changes will depend on the spectral range of signal and noise, the distance between sound sources and the receiver, and the vegetation density of the animal’s habitat. Signal‐to‐noise ratio will also improve when the receiver moves to a position in the habitat in which the transmission pathway of the signal is better than that for the pathway of the noise. Climbing up in the vegetation is a common response to playback of song in birds, and one by which the receiver is actively improving the signal‐to‐noise ratio (Holland et al., 1998; Mathevon et al., 1996). A study investigating the habitat for auditory communication for European blackbirds (Turdus merula) revealed that moving up from ground level to a perch at about 9 meters high resulted in a gain in audibility comparable to moving horizontally towards the sound source over a distance of 90 meters (Dabelsteen et al., 1993). Changes in noise level and spectrum as a result of a receiver moving are often more complicated than changes in signal level. Noise often emanates less from a point source than a signal, except for the case of biotic noise from another single signalling animal. In addition to changing position in the habitat relative to signal and noise sources, receivers can also affect audibility by just moving their head around or pointing their ears. Turning of the body, head, or pinnae after initial signal detection may benefit signal recognition through shielding off the noise and optimizing the transmission pathway of the signal to the ear (e.g., Keller et al., 1998; Musicant et al., 1990; Obrist et al,. 1993). Bringing a hand to the ear by humans may also enlarge the sound‐guiding capacity of the pinnae and improve signal‐to‐noise ratios. Pinnae may improve hearing in noisy environments for several species, but they may also be a noise

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source right at the ear, when air is flowing by at high speed under windy conditions or when the animal is moving fast. In addition to aerodynamics, significant noise levels due to heavy air turbulence during flight is probably one of the reasons for the lack of true pinnae in birds. B. SENSORY ADAPTATIONS Besides the various ways in which animals may adjust signal‐to‐noise ratios actively, there are a number of sensory adaptations in the auditory system that allow them to cope with noise in picking up signals. Each of these adaptations may increase the distance at which signals are detected and recognized, given a certain noise level; or, in other words, they may help to increase the noise resistance at a certain distance from the sound source. The auditory system varies in complexity and sensitivity among species, but general patterns are often quite similar across taxa. Adaptations in hearing are inherently related to detecting specific sounds from a background of other sounds. As a consequence, some very general characteristics of the auditory system can be regarded as adaptations for hearing in a noisy world, while there are also some more specialized phenomena that improve the perceptual contrast between signal and noise. 1. Spectral Sensitivity and Pitch Processing The first sensory adaptation concerns restrictions or variations in spectral sensitivity. The frequency range for which the ear is sensitive varies between species; for example, elephants (Loxodonta africana) and pigeons (Columba livia) do hear infra‐sound (Langbauer et al., 1991; Schermuly and Klinke, 1990), which is too low to be heard by humans, and bats (e.g., Phyllostomus hastatus) and rats (Rattus norvegicus) are sensitive to ultra‐ sound (Bohn et al., 2004; Brudzynski et al., 1999), which is too high to be audible to humans. The species‐specific audible frequency range usually covers at least those frequencies used by conspecifics (Dooling, 1982, 2004; Gerhardt and Schwartz, 2001; Konishi, 1970; Meyer and Elsner, 1996; but see, e.g., Mason et al., 1999; Pytte et al., 2004). Auditory sensitivity beyond the range used for conspecific signals can be explained by the existence of other sounds that are relevant to animals, such as sounds made by predators or prey (e.g., Capranica and Moffat, 1983; Pollack and Faulkes, 1998). However, any sound beyond the sensitivity range for a species will not play a role in masking signals and will be filtered out by the band‐pass filter of species‐specific spectral sensitivity. The hearing range of freshwater gobies (Padogobius martensii and Gobius nigricans) was found to match well the frequency of conspecific calls and to fit with a favorable region of the underwater noise spectrum

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(Lugli et al., 2003). Such a correlation of the spectrum of perceptual sensitivity with those of sound production and ambient noise may be a typical general result of environmental selection on the acoustic communication channel (Dooling, 1982; Endler, 1992; Ryan and Keddy‐Hector, 1992), although not many studies have examined both sensitivity and habitat‐specific noise patterns. An example of ambient noise as an explanation for a considerable spectral mismatch between the apparent sensitivity range and conspecific signals is found in the Australian bushcricket Sciarasaga quadrata (Ro¨ mer and Bailey, 1998). This species is most sensitive to frequencies about 5.0 kHz higher than their conspecific calls. A higher call frequency would lead to a lot of spectral overlap with other insect species in their habitat of coastal heathland, and relative amount of acoustic competition has possibly driven call evolution towards an unusually low frequency for an insect. Intriguingly, these crickets, which have ‘‘ears’’ in their knees, have evolved the ability to shift their maximum sensitivity down by partially occluding the aperture of the auditory spiracle, the leg trachea dedicated to sound transmission (Fig. 7). In this way,

F IG. 7. Hearing sensitivity of the Australian bushcricket (Sciarasaga quadrata) when the aperture of the auditory spiracle is completely open (dashed line) and experimentally manipulated with the aperture partly blocked using wax (solid line). The spectral range of male calls is indicated in light gray; the spectral range of two other sympatric cricket species with loud and relatively continuous calls is indicated in dark gray (modified from Ro¨ mer and Bailey, 1998; Fig. 9, used with permission).

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they are able to tune in to their conspecific call frequency after all and avoid the noisy high‐frequency channel (Ro¨ mer and Bailey, 1998). Another interesting example of variation in sensitivity within the conspecific spectral range can be found in bats, which use sounds not only for communication but also for echo‐location. Some species have been shown to be highly sensitive to frequencies just above the typical frequency of the second harmonic of the sound pulses they produce for echo‐location, while being relatively insensitive for the frequency of that second harmonic itself. This peculiar sensory adaptation allows detailed analysis of echo‐ characteristics important for detection and location of prey, as the returning echo will be Doppler‐shifted upward in frequency, right into the most sensitive frequency range (Kanwal, 1999; Suga et al., 1978). The auditory sensitivity across frequencies is typically investigated in the absence of noise, but when detection thresholds are determined in the presence of noise, they are expressed as the ‘‘critical ratio.’’ This is the amplitude of a tone relative to the background noise at the masking threshold, the ratio below which a tone just becomes inaudible (e.g., Moore, 1997; Scharf, 1970). Many studies have given insight into auditory sensitivity: We now know, for example, that the critical ratio is relatively constant over a fairly wide range of noise levels in birds, but that excitation patterns in mammals may vary to some extent, depending on noise amplitude. Furthermore, critical ratios typically increase monotonically with frequency in most species (Dooling et al., 2000; Fay, 1988; Hawkins and Stevens, 1950). However, there are exceptions to this frequency dependence. For example, budgerigars have their lowest critical ratio around 3.0 kHz, and it increases from there, both up and down the frequency axis (Dooling and Saunders, 1975; Okanoya and Dooling, 1987). Another deviant sensitivity pattern is found in great tits, which show no increase with frequency and have similar critical ratios across a wide frequency range (Langemann et al., 1998). Critical ratios can be extrapolated to field conditions by using typical environmental noise spectra and a certain signal source level to calculate the acoustic reach or active space available for communication (Klump, 1996; Lohr et al., 2003). Calculations on active space in the field based on laboratory measurements can be made more realistically when critical ratios are determined for natural conspecific calls instead of artificial tones (Okanoya and Dooling, 1991) and when not only detection, but also the usually higher thresholds for discrimination ability, are taken into account (Lohr et al., 2003). Variation in spectral sensitivity is closely linked to another key feature of the auditory system, crucial for understanding pitch perception and hearing in noise: the ‘‘spectral segregation’’ of sound processing. Sound stimuli trigger neurons at the auditory periphery, and this forms the basis of a

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cascade of neuronal activity change in the ascending auditory pathway. The frequency of a sound is encoded by the auditory system in two ways: in the location of activated cells and in their firing patterns. Cell clusters that selectively respond to certain frequencies are tonotopically arranged along the sensory epithelium (i.e., spatially segregated by frequency). The result is some sort of spectrum analyser with a bank of bandpass filters (e.g., Ehret and Schreiner, 1997; Fletcher, 1940; Lewis et al., 1982; Manley, 1996; Moore, 1997; Scharf, 1970), which provides groups of cells for which the activation by the signal can only be masked by noise of frequencies within their sensitive range, the so‐called ‘‘critical bandwidth.’’ The response sensitivity of the frequency‐dependent neurons decreases away from the characteristic frequency to the edges of the critical bandwidth. The tuning of sensitivity curves may be relatively symmetrical, as in insects, frogs, and birds (Gerhardt and Huber, 2002; Necker, 2000) or rather asymmetrical with shallower tails to lower frequencies, as in mammals (Moore, 1997). The asymmetrical tuning of mammalian sensitivity curves implies that sounds below a signal may cause so‐called ‘‘upward masking,’’ whereas there is less physiological basis for downward masking (e.g., Egan and Hake, 1950; Moore, 1997). The second way the auditory system codes the frequency characteristics of incoming sounds is so‐called ‘‘phase‐locking,’’ which refers to the phenomenon of synchronization or matching of the phase between firing neurons on the basilar membrane and the waveform of the incoming sound. As a result, both information on amplitude modulations of the signal and spectral characteristics are encoded in the temporal pattern of firing, especially for the lower part of the frequency range. Phase‐locking sensitivity above 5.0 kHz is rare and only found in exceptional species such as the barn owl (Tyto alba) (Ko¨ ppl, 1997). The phase‐dependent synchronization code for signal frequency has proven to be relatively resistant to masking noise in a variety of species, giving an additional advantage for using relatively low‐pitched sounds under noisy conditions (Costalupes et al., 1984; Gleich and Narins, 1988; Narins and Wagner, 1989; Palmer and Russel, 1986; Ratnam and Feng, 1998). A study on the Tokay gecko (Gekko gecko), one of the relatively few studies on reptiles, also revealed a greater robustness of signal detection correlated to the frequency range covered by phase‐locking (Sams‐Dodd and Capranica, 1996). It is important to note that the variation in sensitivity between and within species and in the frequency‐dependent processing have some important implications for the way in which signal‐to‐noise ratios should be analyzed. Sound pressure level measurements are often taken without detailed knowledge of the spectral distribution of the noise, while only noise within

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the critical bandwidth of the signal should be taken into account for a perceptually relevant ratio. 2. Amplitude and Duration Dependence There are a number of sensory adaptations that specifically relate to the amplitude or duration of signal and noise. Neuronal ‘‘adaptation’’ concerns an adjustment of sensitivity with ongoing exposure to high noise levels (e.g., Costalupes et al., 1984; Zelick and Narins, 1985). Via an adjustment of cell response sensitivity, an increase in sound intensity to levels that would otherwise have been well above the plateau rate still results in increased firing rates. This mechanism may allow detection of a signal, despite some sort of continuously loud noise source. In fact, neurons always have to deal with some level of noise, internal as well as external in origin (Ronacher et al., 2004), and a phenomenon related to adaptation illustrates that noise can sometimes even facilitate signal detection. ‘‘Stochastic resonance’’ in hearing can be described as improved detection of weak sound stimuli resulting from the simultaneous presentation of a low‐intensity noise. As a result, small amplitude changes which would otherwise have gone unnoticed in the absence of noise are now detected, which is likely to result from improved detection through phase‐locking during adaptation in response to the noise. The impact of stochastic resonance on hearing has a wide taxonomic distribution; improved auditory detection related to the presence of external noise has been reported in humans (Long et al., 2004; Zeng et al., 2000), several other mammals (e.g., Frisina et al., 1996; Henry, 1999; Svirskis et al., 2002), several frog species (e.g., Bibikov, 2002; Lewis and Henry, 1995; Narins and Wagner, 1989), and is likely to be present in birds and reptiles based on evidence for self‐generated internal noise and its impact as a ‘‘cochlear amplifier’’ (Kaiser and Manley, 1994; Manley et al., 2001; Ricci et al., 2000). Besides high or low noise levels, detection thresholds may also be affected by the duration of sounds. ‘‘Temporal summation’’ refers to the phenomenon of duration‐dependent detectability of brief sounds (Brown and Maloney, 1986; Dooling, 1979; Watson and Gengel, 1969). Detection thresholds can vary considerably with longer sounds being easier to hear, as measured, for example, for different bird species, such as budgerigars, zebra finches, and European starlings (Dooling and Searcy, 1985; Klump and Maier, 1990; Okanoya and Dooling, 1990). Most dramatic changes in sensitivity usually occur for sound durations in the range up to 200 ms. Furthermore, this interval contributing to a lowering of the threshold, the so‐called integration time is also related to sound frequency. Humans, cats (Felis domestica), and mice (Mus musculus) (Costalupes, 1983; Ehret, 1976; Plomp and Bouman, 1959) show a general decline in integration time

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with increasing pitch, while blue monkeys, grey‐cheeked mangabeys (Cercocebus albigena), bottlenose dolphins (Tursiops truncatus), and starlings are found to have the longest integration times in mid‐frequencies around 1.0 and 2.0 kHz (Brown and Maloney, 1986; Johnson, 1968; Klump and Maier, 1990); it seems that the highest integration times match the frequency range of highest environmental noise levels within the relevant species‐specific range of absolute sensitivity. Again, the impact of the phenomenon is similar across vertebrate taxa. Physiological and perceptual studies in humans and cats suggest that integration of the sound pressure envelope over time is the mechanism behind the lowered threshold for sounds of longer duration (Heil and Neubauer, 2003). The beneficial effect on signal detection in noise due to the selective threshold shift by temporal summation arises through the improved sensitivity for signals over 200 ms and filtering out to some extent noises of shorter duration. 3. Using Noise Characteristics for Masking Release Signals and noise originating from all sorts of sources, and affected by transmission to the receiver in a variety of ways, will result in a non‐random acoustic structure, which may help in perceiving the relevant signals (Nelken et al., 1999; Singh and Theunissen, 2003). There are two main perceptual mechanisms which result in lower masking thresholds for signal detection in noise by using acoustic cues from the noise itself. The first is ‘‘comodulation masking release,’’ which refers to the phenomenon of improved detection of signals in background noise based on coherent amplitude modulation patterns in the noise across frequencies (Festen, 1993; Hall et al., 1984; Klump and Langemann, 1995; Moore, 1997). The mechanism depends on a comparison of noise with and without signal present. A release from masking occurs because the signal stands out more when amplitude modulations in the noise within the critical band of the signal vary coherently with those of other critical bands at other frequencies, except for when the signal is present (Fig. 8A). The amount of masking release has been found to be similar for species as diverse as humans and starlings, Sturnus vulgaris, (Klump and Langemann, 1995; Schooneveldt and Moore, 1989), and presumably the phenomenon occurs across a wide range of taxa. Besides this effect, which requires cross‐ channel analysis, within‐channel patterning of noise may already improve detection (Fig. 8B). For example, work on the chinchilla (Chinchilla lanigera) has revealed that detection can improve significantly, depending on the periods of low energy in an amplitude‐modulated masker within the frequency channel of the signal (Mott et al., 1990). Between two otherwise equivalent maskers, the one with the periods of lowest energy resulted in lower detection thresholds.

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F IG. 8. Release of masking through noise amplitude modulation patterns: schematic drawings of amplitude waves of a signal (at the top) and the same signal with background noise in one or more frequency channels (below). (A) Across‐channel modulation masking release: The presence of a stimulus in frequency channel II is easier to detect against a background noise pattern that varies coherently across frequency channels (same noise amplitude wave in I, II, and III on the left) compared to a noise pattern that varies inconsistently in neighboring frequency channels (different amplitude wave in I, II, and III on the right). This is typically referred to as ‘‘true’’ comodulation masking release. (B) Within‐channel modulation masking release: For two amplitude modulation patterns of noise that are equal in overall sound energy level within a single frequency channel but vary in modulation range, the one with periods of lowest noise levels (on the left) leads to less masking. Both processes may contribute in concert to improve signal detection.

Variation in auditory masking dependent on within‐channel cues may have an even wider taxonomic distribution than the use of cross‐channel analyses, as low‐frequency modulations also reduce masking thresholds in the grasshopper Chorthippus biguttulus, for which there is no indication of masking release through comparisons across channels (Ronacher and Hoffmann, 2003). The relative contributions to masking release from within‐channel and across‐channel mechanisms may differ between species and can be investigated by comparing tests with narrow noise maskers that fall within a critical bandwidth and tests with wide‐band maskers that go beyond. The masking release generally increases with the masker bandwidth, and the across‐channel component becomes larger with wider noise maskers covering more channels (Carlyon et al., 1989). However, recent studies in both humans and starlings suggest that within‐channel cues are

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usually more effective than across‐channel cues (Borrill and Moore, 2002; Klump and Nieder, 2001; Langemann and Klump, 2001; Moore and Borrill, 2002). The second well‐studied phenomenon involving masking release concerns lower auditory thresholds through spatial separation of signal and noise. As stated earlier, sounds that arrive from different locations will be affected differently by their respective transmission channels. However, in addition to these general aspects of attenuation and degradation, sounds arriving at different angles will produce different firing patterns in the two ears, due to the differences in arrival times, phase, sound level, and spectral profile (Blauert, 1996). The last two are mainly caused by the attenuating impact of the head, the so‐called ‘‘head‐related transfer function’’ (e.g., Keller et al., 1998; Spezio et al., 2000), and by the direction‐dependent spectral modification caused by the external ears through reflections and resonance (Musicant et al., 1990; Obrist et al., 1993). Such spectral modifications may be considerable, especially when pinnae are large, as for example in wallabies (Macropus eugenii) (Coles and Guppy, 1986). Subtle differences between acoustic stimulation of the left and right ears will vary for signal and noise when arriving from different locations, which can directly affect firing rates in certain integrative cells (e.g., Carr and Konishi, 1990). Internal coupling of the two ears through the interaural pathway may add cues to compare sounds that differ in angle of arrival (Larsen, 2004). Binaural disparities are widely used in sound localization as indicated by detailed studies on, for example, birds, frogs, and fish (e.g., Fay and Edds‐Walton, 1997; Klump et al., 1986; Knudsen and Konishi, 1979; Xu et al., 1996), but also result in lower masking thresholds. Spatial release can be studied under close‐field conditions using earphones and free‐field conditions, with speakers placed at various distances and angles from a test subject. Both types of study reveal lower masking levels when sound sources are separated in space instead of originating from exactly the same location. In some way, the auditory system is able to use cues of spatial separation for perceptual segregation of signal and noise (Dent et al., 1997; Hine et al., 1994; Saberi et al., 1991; Schwartz and Gerhardt, 1989; Shinn‐Cunningham et al., 2001). Accordingly, the highest potential for sound localization and spatial release is found in birds with large heads, such as barn owls, or large mammals, such as horses (Equus caballus) and cattle (Bos taurus) (Heffner and Heffner, 1984, 1992; Knudsen and Konishi, 1979). In addition to the release from masking based on directional hearing, a specific neural mechanism found in crickets and katydids may enhance signal detection in noise, even if signal and masking noise come from the same direction (Pollack, 1988; Ro¨ mer and Krusch, 2000). So‐called

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‘‘omega neurons’’ on each side of the insect show some sort of ‘‘selective attention’’ to the more intense of two or more sounds. The encoding of the temporal pattern of the louder sound suppresses the encoding of the weaker stimulus, which results in a neurophysiological mechanism that improves signal detection in noisy environments. 4. Feature Detectors Another type of adaptation improving the ability to hear signals in noise is one step up from frequency‐dependent activity and concerns selective responsiveness to more complex, usually species‐specific, features by so‐ called ‘‘feature detectors.’’ It became clear in early studies on squirrel monkeys (Saimiri sciureus) that auditory responses to pure tones are not a reliable indicator for excitation patterns of natural calls covering the same frequencies (Newman and Wollberg, 1973; Winter and Funkelstein, 1973). Auditory neurons often selectively respond to sound features that fit detailed properties of conspecific calls, while acoustic variants that only differ slightly have much less effect. Such feature detectors may include cells that are specifically tuned to certain sound durations, or to amplitude or frequency modulations. The pallid bat (Antrozous pallidus), for example, has a high number of cells sensitive to stimulus durations that match durations of its own high‐pitched sound pulses (Fuzessery, 1994). Also, animals that depend less on hearing acoustic stimuli of specific duration still have a significant number of duration‐tuned neurons, as discovered for chinchillas (Chen, 1998) and humans (Kaukoranta et al., 1989). The highest‐order selectivity occurs in combination‐sensitive neurons that fire exclusively upon exposure to a whole set of conspecific characteristics based on an accumulation of excitatory and inhibitory effects. These call‐ specialized neurons may even trigger a higher firing response (120%) to the entire call or syllable than what would be expected, based on the sum of the responses to individual spectral components, something referred to as ‘‘spectral facilitation.’’ Highly selective feature detectors responsible for an increased sensitivity to natural recordings of conspecific calls have been discovered, for example, in frogs (Fuzessary and Feng, 1983; Narins and Capranica, 1980; Simmons et al., 1992), birds (Doupe, 1997; Leppelsack and Voigt, 1976; Margoliash and Fortune, 1992; Scheich et al., 1979), and a variety of mammal species (e.g., Esser et al., 1997; Geissler and Ehret, 2004; Kanwal, 1999; Rauschecker et al., 1995; Tian et al., 2001; Wang et al., 1995). Voice‐selective brain areas have also been revealed in humans using functional magnetic resonance imaging (Belin et al., 2000), and there is evidence for distinct processing of phonetic and other auditory stimuli: Specific complex sounds result in distinct ‘‘event‐related potentials’’ when heard in isolation as non‐speech ‘‘chirps’’ or as formant transitions

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embedded in speech (Gokcen and Fox, 2001). As all sounds lacking highly specific criteria do not receive the perceptual boost that conspecific vocalizations do, feature detectors are clearly advantageous to picking up signals from a noisy background. Highly selective feature detectors in birds are known to arise during ontogeny based on genetic predispositions for an increased sensitivity to conspecific acoustic structure and syntax (Doupe, 1997; Soha and Marler, 2000, 2001; Whaling et al., 1997). This implies that experience may affect the development of perceptual sensitivity guided by some sort of species‐ specific auditory template. This is an example of the fact that it is not always easy to distinguish bottom‐up from top‐down processes. Firing patterns are transferred upward in the auditory pathway, but the bottom‐ up integration in combination‐sensitive neurons can be affected by higher cognitive processes, allowing for top‐down guided ontogeny of sensitivity and even shifts in selectivity during adulthood (see Section III.C.3). Interestingly, a study on zebra finches and budgerigars revealed detection thresholds in continuous broadband white noise that were similar for natural calls and reversed versions of those calls (Okanoya and Dooling, 1991). This result seemed to indicate that frequency‐based filtering is sufficient to explain call detection in noise and that highly specialized feature detectors are not important. However, this may be true for near‐ threshold conditions, but more specific profile differences may be crucial in other situations and for a slightly different task (Green and Forrest, 1986). In line with this, the same study by Okanoya and Dooling (1991) showed that discriminability is higher among conspecific calls than among heterospecific calls: Adding background noise increased latencies in a discrimination task with heterospecific calls but not in a task with conspecific calls. In a later study, these differences between detection and discrimination came out again. At threshold, species advantages are absent, and detection thresholds are primarily determined by the general acoustic characteristics of the calls themselves (Lohr et al., 2003). Budgerigar calls have clear amplitude modulations and energy concentrated in relatively narrow frequency bands, which makes them detectable at higher noise levels than canary (Serinus canaria) or zebra finch calls by all three test species: canaries, zebra finches, and budgerigars. However, when it comes to discrimination, instead of just detection, each of these species may do best in discriminating among their own conspecific calls (Lohr et al., 2003). The distinction between detection and discrimination thresholds is important, and the biological relevance is nicely illustrated by several studies on noise‐level‐dependent female mate choice in frogs and toads (Gerhardt, 1982; Ma´ rquez and Bosch, 1997; Schwartz, 1993; Schwartz and Gerhardt, 1998; Wollerman and Wiley, 2002). For example, at relatively low noise

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levels, female hourglass treefrogs (Hyla ebraccata) prefer males with low‐ frequency calls. At high noise levels, however, they do not discriminate at all, and at a moderate noise level, they go for males with calls of modal properties for the population (Wollerman and Wiley, 2002). Apparently, when ambient noise, in this case generated by other chorusing frogs, allows detection but interferes with discrimination, females have another tactic and seem to play safe, responding more to those calls most reliably of a conspecific male. Hence, highly selective auditory sensitivity to features of conspecific calls may aid hearing in noise; but with increasing noise levels, first discrimination ability may be lost, and then signal‐to‐noise ratios deteriorate beyond detection ability. 5. Summary To sum up this section on sensory adaptations, it is clear that the neuronal coding of spectral, temporal, and amplitude characteristics of incoming sounds all exhibit features contributing to signal detection and discrimination against a noisy background. Some sensory mechanisms, such as sensitivity adjustment by neuronal adaptation, can be regarded as short‐term perceptual plasticity. Almost all of the auditory mechanisms found to counteract poor signal‐to‐noise ratios have a widespread distribution through all vertebrate taxa studied, and they are sometimes even shared with insect species. This means that most of these mechanisms in bottom‐up processing are likely to be evolutionarily old neurobiological adaptations.

C. AUDITORY SCENE ANALYSIS When sounds are loud enough to be detected and discriminated, animals are still left with the perceptual task of recognizing the presence or absence of relevant signals among all audible sounds in their environment, each component of it varying in complexity and level. Bottom‐up sensory processing ultimately integrates a sequence of static features with the temporal envelope of incoming sound and forms some sort of auditory stimulus representation aligned in time. Critically important, with multiple stimuli arriving from multiple directions, the neural code at this level has to be subdivided again into auditory images that represent separate sound streams of individual sound sources (e.g., Bregman, 1990; Moore, 1997; Na¨ a¨ ta¨ nen and Winkler, 1999; Yost, 1991). This crucial perceptual step of hearing in noise has been labeled ‘‘auditory scene analysis,’’ which is the perceptual separation of meaningful signals and meaningless noise in the continuous stream of audible sounds (Fig. 9).

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F IG. 9. Auditory perception in noise. The boundary line between gray and white illustrates a simplified power spectrum of ambient noise, with, as typical for many habitats, more noise at lower frequencies. Above this line, the detection threshold indicates the difference in amplitude in favor of the signal needed for detection; this is the critical ratio (CR) which often increases with frequency. In addition, the parallel line on top of that illustrates the additional power needed for the more demanding task of discrimination of sounds. All sounds below the detection threshold are completely masked by noise and are thus inaudible; all sounds above the discrimination threshold potentially play a role in auditory scene analysis.

1. Top‐Down Meets Bottom‐Up Perceptual grouping of sounds depends heavily on top‐down cognitive processes, but it is based on involuntary ‘‘stream segregation.’’ The grouping into coherent auditory streams depends on a large set of acoustic features, more or less following general ‘‘Gestalt psychological criteria’’ such as proximity, similarity, and continuity (e.g., Bregman, 1990; Lattner et al., 2003; Thorpe and Hall‐Craggs, 1976). Features such as spectral separation of two sounds, similarity in amplitude modulation profile, separation in time and space, but also the presence of harmonic relationships, and common onset and offset times, are all likely to contribute to grouping features into auditory images (Yost, 1991). Accordingly, in a classic psycho‐acoustic experiment, a simple alternating series of high and low tones can be perceived as one or two auditory streams. It will be perceived as one coherent tone series when high and low are relatively close in the spectrum, but it will sound like two independent tone series, one high and one low, when tone frequencies are sufficiently far apart (Bregman and Campbell, 1971; Miller and Heise, 1950). The critical threshold can be determined in humans by asking subjects to ‘‘hold on’’ to hearing the sound sequence as

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an integrated alternating series of tones while increasing the spectral gap step‐wise in subsequent tests (e.g., Bregman et al., 1990, 2001). In a similar way, the effect of tone duration and interval can be investigated (Bregman et al., 2000; Van Noorden, 1971). The few studies on auditory stream segregation in other animals suggest it to be a common feature of auditory systems in a wide range of taxa. Evidence for goldfish (Carassius auratus) to be able to segregate auditory streams from a complex mixture of sounds has been derived from conditioning‐generalization tests (Fay, 1998, 2000). Fish trained with artificial tone sequences at alternating frequencies were tested for their tendency to generalize to new tone sequences of just one frequency but with varying repetition rate (Fig. 10). It turned out that spectral separation affects subdivision into single or multiple auditory streams in a similar way as in humans and starlings. The latter species revealed spectral separation‐dependent

F IG. 10. Acoustic stimuli used for studying stream segregation in goldfish (Carassius auratus). (A) Examples of alternating pulse trains used as conditioning stimuli: pulse sequence 1 is combined with either sequence 2, 3, or 4 to generate alternating pulse trains with variable spectral separation (1 and 2 are in black to indicate a complete alternating pulse train used for playback; 3 and 4 are in gray to indicate that they are alternative substitutes for 2 in combination with 1). (B) Examples of generalization test stimuli; each sequence has the frequency of sequence 1 in the conditioning stimuli, but 1, 2, and 3 vary in repetition rate (exposure only separately). If an alternating conditioning stimulus is perceptually segregated into two streams, sequence 1 should sound most similar, while if perceived as one stream, sequence 3 should sound more similar, and the fish are expected to generalize accordingly (based on Fay, 2000).

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auditory streaming with artificial sound sequences in both a psycho‐acoustical study (MacDougall‐Shackleton et al., 1998) and a recent neurophysiological study (Bee and Klump, 2004). Similar results on auditory stream segregation and the impact of spectral separation, tone duration, and repetition rate have also been found in long‐tailed macaques, Macaca fascicularis (Fishman et al., 2001, 2004). Data on segregation of artificial sound stimuli may tell us something about the perceptual mechanisms underlying auditory scene analysis of more natural sounds. In the real world, tasks may be more complex with respect to acoustic diversity in sound stimuli, as well as temporal unpredictability. On the other hand, the task may become easier, as many additional factors may contribute to the formation of coherent auditory images. Auditory streaming may, for example, be especially sensitive to conspecific or familiar sound streams, as shown for human speech perception (Darwin and Ciocca, 1992; Lattner et al., 2003; Na¨ a¨ ta¨ nen et al., 2001). Furthermore, it is known that the encoding of information in both animal vocalizations and human speech is highly redundant (e.g., Johnstone, 1996; Morris et al., 2001; Rowe, 1999), which makes it possible to ‘‘extrapolate’’ acoustic characteristics if part of the signal is severely masked. Studies on human sound perception have revealed, for example, that speech masked by loud noise bursts can be perceived as a continuous sound stream (Warren, 1970). This so‐called ‘‘auditory induction’’ can even lead to the illusionary presence of sound: When a sentence is mutilated by cutting out parts of the speech sound stream before overlapping these same segments by loud noise bursts, subjects will hear the sentence as uninterrupted (Bashford et al., 1992). In these test stimuli, the presence of noise bursts may even improve intelligibility of the sentence. The continuity illusion has been shown with more simple stimuli, such as pure tones in humans as well as in cotton‐top tamarins (Saguinus oedipus) and rhesus macaques (Macaca mulatta), and there is also some evidence for domestic cats, Felis domesticus (Kluender and Jenison, 1992; Miller et al., 2001; Petkov et al., 2003; Sugita, 1997; Warren et al., 1972). Tamarins respond to playback of conspecific ‘‘coos,’’ but not when a temporal gap is inserted. A brief noise burst co‐occurring with the gap restores the vocal response (Miller et al., 2001). In addition to temporal gaps, it has also been shown that the human auditory system restores spectral gaps (Warren et al., 1997), something that would also be very useful for animal species that are exposed to continuous and loud noise bands, for example those produced by cicadas in Mediterranean or tropical environments. Besides redundancy in auditory cues, there are often also visual cues that co‐occur with sound patterns (see Section II.A.2). A strong example of cross‐modal facilitation of signal extraction can be found in the lip

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movements during speech in humans. Lip movements improve speech perception under noisy conditions, part of which is due to temporal cueing by the comodulating visual stimulus and part due to more detailed information transfer through lip‐reading cues (Besle et al., 2004; Grant and Seitz, 2000; Schwartz et al., 2004; Sumby and Pollack, 1954). The latter plays such an important part in speech processing that conflicting auditory and visual information, for example generated by manipulating the synchronization of a video‐tape, may lead to illusory fusion of speech sounds, the so‐called ‘‘McGurk effect.’’ Apparently, visual and auditory stimuli are integrated in speech processing unconsciously and automatically, and neither one of them is completely dominant over the other (MacDonald and McGurk, 1978; McGurk and MacDonald, 1976). Synchronized displays may sometimes play a role in emphasizing acoustic details and thereby promote information transfer, but at least it may draw attention to the sound of the associated source (e.g., Spence et al., 2000; Ward et al., 2000). Drawing attention depends on the capacity to focus attention on one of a number of auditory streams and is of key importance to the process of auditory scene analysis. Humans at a noisy cocktail party are able to zoom in on a conversation of their choice, raising intelligibility of one auditory stream at the expense of another (Cherry, 1953, 1954; Cherry and Wiley, 1967; and see Barber et al., 2003 for discussion of a similar attentional conflict in bats). Spatial cues contributing to perceptual segregation of auditory streams are essential to this phenomenon of selective attention, which appropriately has become known as the ‘‘cocktail‐party effect’’ (Aubin and Jouventin, 1998; Busnel and Mebes, 1975; Wood and Cowan, 1995; Yost, 1991). 2. Cocktail Party for Birds Paralleling the studies on audibility and intelligibility of speech in humans, there are several studies on detection and recognition of song features in birds under conditions equivalent to those for humans at a cocktail party. Acoustic exposure to natural recordings of conspecific song mixed in with songs of other species or with songs of other conspecific individuals has been tested both in the field and in the laboratory. Bre´ mond (1978) conducted a series of pioneering outdoor experiments on song masking in the winter wren (Troglodytes troglodytes). He found that birds still responded to conspecific song when overlapped in time completely by songs of other species that naturally occur as neighbors, played back from the same speaker at the same amplitude. He tested masking by songs of the blackcap (Sylvia atricapilla), willow warbler (Phylloscopus trochilus), and dunnock (Prunella modularis), of which the last was judged to be most similar to wren song (Fig. 11). Response levels for masked signals were

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F IG. 11. Spectral overlap and acoustic similarity in two songbird species which were both used in outdoor playback experiments by Bre´ mond (1978). (A) Sonogram of a typical winter wren song. (B) Sonogram of the same winter wren song masked by the song of a dunnock.

lower than control songs without masking sounds, but detection of the natural conspecific song against the variety of noisy backgrounds was clear in all tests. Detection levels seemed especially affected when masking songs were spectrally more similar, and when they started before wren songs and continued during intervals in wren song. In a more recent laboratory study, European starlings detected the presence of conspecific song in a playback mixture of two songs selected from four different songbird species (Hulse, 2002; Hulse et al., 1997). The stimulus presentations concerned songs of nightingale, northern mockingbird (Mimus polyglottos), brown thrasher (Toxostoma rufum), and starling; and the test birds were able to discriminate between the three out of six possible pairings that included conspecific song and those that did not. Overlapping all stimuli with a dawn chorus recording still did not prevent the starlings from singling out the presence of starling song in the me´ lange of sounds. Similarly, zebra finches and Bengalese finches were able to detect the presence of a conspecific song in a mixture of three songs (Benney and Braaten, 2000). They learned to discriminate between mixtures with and without conspecific song from a set of 20 composite stimuli. Each stimulus was an overlapping song combination of three out of six possible species: the two test species and four unrelated North American

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songbird species. Interestingly, zebra finches that were trained by rewarding them for detecting the presence of heterospecific Bengalese finch song also learned the task, although less rapidly. Furthermore, a second indication that conspecific song is perceptually special was derived from the finding that conspecific song was a more efficient distracter from detecting the presence of the heterospecific song than the other species’ songs. However, this capability for enhanced detection of conspecific song was not found in the Bengalese finches. Besides detecting the presence of a conspecific song or call among sounds of different species, birds often also have to extract information from intra‐ specific acoustic variation under noisy conditions. Numerous playback experiments in the field have revealed sensitivity to conspecific acoustic variants in the presence of the natural sound environment (e.g., Catchpole and Slater, 1995; Collins, 2004; ten Cate et al., 2002), but obviously experimenters have usually avoided challenging signal‐to‐noise ratios. An exception is an outdoor experiment with king penguins, using sound mixtures consisting of six adult calls, one of which was from one of the parents of the focal chick (Aubin and Jouventin, 1998, 2002). Penguin chicks were able to detect the presence of the parental call during outdoor playbacks at a distance of about seven meters, even when the combined amplitude level of the five extraneous calls was 6 dB greater than the familiar target call. Another explicit test of recognizing intra‐specific variation with interference of natural noises concerns another operant set‐up with European starlings. Starlings trained to discriminate songs of two different individuals of their own species were still able to do so with the songs of four other unfamiliar individual starlings superimposed on the playback recording. Discrimination accuracy dropped, but the test performance remained well above chance levels (Wisniewski and Hulse, 1997). These studies clearly show the capacity of birds for detection and recognition of songs despite severe temporal and spectral overlap, even when the use of spatial cues is limited by the use of playback of mixtures through a single speaker. This remarkable competence is probably related to auditory stream segregation and the ability to pay selective attention to separate sound channels. Although very beneficial for many biologically relevant perceptual tasks, selective attention also reduces the ability to perceive details in other auditory streams. This means that, in humans for example, comprehension clearly drops when attention is briefly drawn away from listening to a person reading from a text. Interestingly, losing perceptual focus on one auditory stream is not so much determined by the acoustic structure of competing sounds, but especially by their information content. Selective attention to one of two simultaneously heard voices can be disrupted by functionally relevant sounds spoken by the voice in

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the task‐irrelevant channel. This recruitment of attention is, for example, especially effective when one’s name is included in a sentence (Moray, 1959; Wood and Cowan, 1995). Similarly, zebra finch song was a better distracter for zebra finches than for Bengalese finches in the operant tasks discussed previously (Benny and Braaten, 2000). As a consequence of the impact of functional overlap on selective attention, auditory masking can be regarded as the resultant of frequency‐dependent sound energy masking and so‐called ‘‘informational masking’’ (e.g., Appeltants, 2005; Brungart, 2001; Oh and Lufti, 1999; Pollack, 1975). 3. The Ecological Concept of Signal Space The task of discriminating among sounds and paying selective attention to one of them will be particularly daunting when signals are acoustically similar and if there is some potential for functional overlap. This may be especially the case for those species in a community that are phylogenetically closely related, have a relatively similar body and vocal apparatus, and may share food sources and predation risks. Nelson and Marler (1990) developed the theory of ‘‘signal space’’ in such an ecological context in a North American bird community. They determined signal space for songs of 13 songbird species through a multi‐dimensional representation of signal structure based on a set of arbitrarily chosen measurements, such as song duration, frequency use, and number of notes and syllables. They found that a species like the chipping sparrow (Spizella passerina) may have fewer acoustic competitors being on the edge of the signal space, and another species like the field sparrow (Spizella pusilla) may have a more difficult task to communicate being in the center of the signal space, acoustically overlapping with many other species. This concept of signal space provides a basis for studying the impact of acoustic similarity among community members on both the signals that are produced (e.g., Espmark, 1999; Naugler and Ratcliffe, 1994) and especially on how these signals are perceived (de Kort et al., 2002; Nelson and Marler, 1990). Nelson (1988, 1989) performed a series of playback experiments with the field sparrow to find out whether relative overlap with other species had any impact on which of the available acoustic features was important to elicit a territorial response. He found that parameter changes of two to three standard deviations led to a reduction in response (the so‐called ‘‘just‐meaningful difference’’). This was true for multiple features, including those most important in statistically discriminating among species. Therefore, the overall results were partly in line with the expectation that the features most distinctive among species would be important recognition cues, but alternative explanations could not be excluded. One reason for this result may be that the acoustic overlap suggested by the

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discriminant function analyses may not reflect perceptual overlap as perceived by the birds. Parameters that are statistically relevant in terms of distinguishing between groups are not necessarily perceptually relevant. However, the perceptual salience of acoustic parameter differences between closely related species has hardly been investigated. An interesting exception in this respect is a study on the perceptual relevance of species‐ specific differences in the acoustic structure of coos for two partly sympatric turtle dove species, Streptopelia decaocto and S. chinensis (Beckers and ten Cate, 2001). Furthermore, in a second study Beckers et al. (2003) tested another dove species (S. risoria) for the ability to discriminate between conspecific coos and coos of 12 other species from within the genus. The number of mistakes resulted in a measure of perceptual similarity (Fig. 12), which in combination with a detailed analysis of inter‐specific coo variation, allowed assessment of the relative salience of acoustic characteristics to the doves. Another study system in which acoustic feature weighting has been investigated in recognition and discrimination tasks concerns the mate attraction call of the Tungara frog (Physalaemus pustulosus)

F IG. 12. Perceptual similarity scores for African turtle doves Streptopelia risoria based on a discrimination task testing their own coo against heterospecific coos of 12 related turtle dove species from within the Streptopelia genus (from Beckers et al., 2002, used with permission).

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(Ryan and Rand, 1995, 2001; Wilczynski et al., 2001). Interestingly, female frogs seem to weigh parameters differently depending on the task, and their use of parameters for discrimination among closely related species does not match the parameters that are most discriminating in a statistical procedure. However, both the Streptopelia dove and the Tungara frog were tested with a set of species without much ecological relevance. The species sets were not part of one community, as the domesticated dove, S. risoria, is derived from a species that overlaps in range with only some of the test species, and the frog species hardly occur in sympatry. An earlier study on two frog species that do occur sympatrically, the barking treefrog (Hyla gratiosa) and the green treefrog (Hyla cinerea), revealed that the two species used a different set of acoustic features when tested on the same task of discriminating each other’s mating call (Gerhardt, 1981). Such species divergence in perceptual salience for the same pair of sounds may trace back into the phylogenetic history (Ryan et al., 2001), but for many species perceptual salience may also change during an individual’s lifetime, especially through experience with conspecific vocalizations under natural noisy conditions. This may be obvious when one thinks of learning an auditory task in humans. For example, if a starting birder has to discriminate among songs of five songbird species, the very first exposure allows hearing all acoustic details, but only repeated exposure will allow focusing on distinctive features. The particular five species that are singing will affect which features are most likely to be used in discrimination and therefore gain perceptual salience. Auditory guiding by experienced birders will speed up the learning process, and different tutors may result in different feature weightings with equal accuracy. Variation and shifts in feature weighting in discriminating complex auditory stimuli are comparable to the reversible attentional shifts in ‘‘search image’’ formation found in studies on visual perception, as where predators search for cryptic prey (e.g., Langley et al., 1996; Pietrewicz and Kamil, 1979; Tinbergen, 1960). Plasticity in feature weighting may also be expected in animals, especially when raised in their habitat‐specific community with ample exposure to conspecific vocalizations and equipped with specialized feature detectors shaped by evolution, ontogeny, and experience as an adult. This implies that crude acoustic similarities among species, in particular spectral overlap, may contribute to the habitat‐specific overall noise spectra and thereby affect average detection and discrimination thresholds. However, when vocalizations are well within the audible range, confusion is less likely, and any communicative interference may be predominantly determined by functional instead of acoustic overlap. Clearly, there is still an interesting gap to fill between the ecological concept of signal space and the studies on auditory perception.

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IV. CONCLUSIONS Successful acoustic communication in noise may make the difference between attracting a mate or not, between safeguarding a territory or not, or between detecting predators and prey or not. This close relationship with matters of life and death and sexual selection means that variation in signal efficiency has major fitness consequences. Strong selection related to noise may therefore shape acoustic signal design over evolutionary time to make it stand out best under the noise conditions of the typical habitat of a given species. Both the potential and constraints for producing acoustic variation and the sensitivity for perceiving sounds will determine likely evolutionary pathways and may also co‐evolve with the signal (ten Cate, 2004). It has become clear that signal production may be adapted to ambient noise in the sense of long‐term adaptations in the signal features as well as in various short‐term vocal adjustments in response to changing noise conditions. It is noteworthy that the capacity for short‐term adjustments can be regarded as a long‐term adaptation in the relative plasticity of the vocal behavior. At the same time, many sensory adaptations clearly result from selection on the ability to extract relevant signals from background noise. This concerns both a series of bottom‐up sensory adaptations that improve detection thresholds and counteract constraints on discrimination, but also top‐down processes based on auditory stream segregation and selective attention which filter out relevant signals from a mixture of audible sounds. These are all long‐term adaptations of the auditory system that have co‐evolved with the conspecific signal features, other biologically relevant sounds, and the noise characteristics of the environment. Some sensory mechanisms, such as sensitivity adjustment in neuronal adaptation, but also selective attention to one of multiple sound streams, are examples of immediate perceptual plasticity, which parallel short‐term adaptations in production such as the Lombard effect. There are two main reasons to expect a fruitful and exciting future for the study of acoustic communication in noise. The first relates to increasing knowledge about a variety of different aspects across taxa. The growing amount of data from insects, fishes, anurans, birds, and mammals, including humans, allows more and more detailed comparisons of behavioral strategies and the related physiology of producing and perceiving acoustic signals under noisy conditions (Dooling et al., 2000; Ehret and Riecke, 2002; Hienz and Sachs, 1987; Manley, 1996; Manley and Ko¨ ppl, 1998; Sinnott and Brown, 1993). For example, a recent revision of neurobiological nomenclature has been specifically aimed at facilitating bird‐mammal comparisons (Reiner et al., 2004). Comparisons often reveal striking similarities and widespread general adaptations, which suggest phylogenetically old

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character states, but sometimes show intriguing exceptions to the general patterns. Insight into the generality of patterns and the evolutionary reason behind exceptions across taxonomic groups may be particularly useful in expanding our understanding of acoustic communication in a noisy world. The other reason why future research in this area will be of great interest is that it will draw a wide audience to the growing impact of humans on the noise conditions of animal habitats. People may cause subtle changes in ambient noise spectra by changing species compositions through alteration of habitat features (Slabbekoorn, 2004a), or more dramatic changes in a complete habitat make‐over in the process of urbanization. Anthropogenic noise is determined by all sorts of electric devices, heavy machinery, cars, trains, ships, and planes. This typically low‐frequency noise is increasingly present in many places and may affect acoustic communication of animals (and humans) living in cities, in natural habitats close to urban or industrial areas and highways, and also under water. Investigating acoustic communication in such dramatically different and, evolutionarily speaking, new environments may lead to interesting scientific findings, some of which may turn out to be important to conservation of species or habitats.

V. SUMMARY Environmental noise can affect acoustic communication through limiting the broadcast area, or active space, of a signal by decreasing signal‐to‐noise ratios at the position of the receiver. At the same time, noise is ubiquitous in all habitats and is therefore likely to disturb animals as well as humans under many circumstances. However, both animals and humans have evolved diverse solutions to the background noise problem, and here we review recent advances in studies of vocal adaptations to interference by background noise and relate these to fundamental issues in sound perception. We consider individual short‐term adjustments of signal features, as well as the evolutionary shaping of species‐specific signal characteristics. On the perceptual side, we stress that receivers can play an active role in adjusting signal‐to‐noise ratios by addressing the ecology of hearing, and we review sensory adaptations in the auditory pathway. In doing so, we discuss data from studies on insects, anurans, birds, and mammals, including humans, and to a lesser extent available work on fish and reptiles. We make an attempt to integrate research studying sensory capacities for detection, recognition, and discrimination against background noise, with that on auditory scene analysis and the ecological concept of signal space. After reviewing and connecting these fields, we suggest that the study of acoustic communication in noise needs insights from a combination of

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psycho‐acoustical and neurobiological experiments, as well as from laboratory and field studies providing behavioral data on vocal production, response‐eliciting characteristics, and environmental correlates to signal design. The growing insights across taxa in these various subdisciplines should guide us towards a more thorough understanding of the use of sound signals in the natural environment.

Acknowledgments We would like to thank Carel ten Cate, Gabriel Beckers, and Vincent Janik for their helpful comments on the manuscript. In addition, this chapter benefited from valuable suggestions by Marc Naguib, Charles Snowdon, and Peter Slater. H.B. acknowledges funding by the Emmy Noether Programme of the German Research Foundation (award BR 2309/2–1) and the support of the Wissenschaftskolleg zu Berlin, where a fellowship in the academic year 2004–2005 provided excellent working conditions. H.S. was funded by a PULS‐grant from the Netherlands Organization for Scientific Research (NWO).

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ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

Ethics and Behavioral Biology Patrick Bateson sub‐department of animal behaviour university of cambridge cambridge cb3 8aa, united kingdom

I. INTRODUCTION Behavioral biologists and experimental psychologists regularly encounter critics who feel that no animal should be affected adversely by what scientists do in the course of their research. Some scientists may find the vehemence of those who hold such views infuriating, puzzling, or distressing. They may also sympathize with some of what they hear since most of them also care about the welfare of animals. Behavioral biologists in particular often become interested in animal behavior because of their love for animals. They may also assume that those colleagues who do not care for their subjects are likely to be in the wrong job. This assumption stems from the belief that their own effectiveness as scientists derives from being sensitive to the state of the animals they study. Conditions in the laboratory must be good, and treatment of animals in the field must be considerate, if only because frightened or maltreated animals simply will not do most of the things in which behavioral biologists are interested, such as court, play, explore, and solve difficult problems. Scientists may be as confused about their own feelings as they are by the emotions of those people who bear down on them with such moral indignation. In this article, I shall examine some of the ethical positions that lie behind these confrontations, in the hope that some readers at least will find themselves helped by an explicit treatment of the issues. I am not a philosopher and, indeed, sense that some ethical dilemmas are best resolved by not thinking about them too much. Even so, I do not propose to end the analysis of the ethical uses of animals in quite such an insouciant manner. To do so would be to surrender the moral high ground to those who have a hostile, one‐dimensional view of the ethics of using animals in research. The moral landscape is much more complicated and interesting 211 0065-3454/05 $35.00 DOI: 10.1016/S0065-3454(05)35005-4

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than certain critics of behavioral biology and experimental psychology seem to realize or, at least, are willing to accept. Nevertheless, those of us who study animal behavior somehow have to resolve the tension between our science and the responsibility that we have for the animals in our care. I shall consider how that might be done so that our science makes real contributions to the public good while, at the same time, we treat our animal subjects with the respect and consideration that many of us feel they deserve.

II. ORIGINS

OF

ANIMAL LIBERATION

AND

ANIMAL RIGHTS

Beyond simple intuitions, two major streams of thought have fed into the strongly held view that animals must be treated well and, as an eventual goal, must not be used in research at all. One of these is the utilitarian position deriving from Jeremy Bentham and John Stuart Mill. The costs and benefits of different actions are to be considered and weighed against each other in order to decide what is the ethically appropriate behavior. Since the moral decision depends on outcomes of possible actions, this approach is often referred to as ‘‘consequentialist’’ or ‘‘extrinsic’’ (Reiss, 1993). The other position, influenced strongly by the writing of Immanuel Kant, is that certain morally based actions are absolutely good or bad in themselves and should not be influenced by cost‐benefit calculations. Certain rights and freedoms are especially regarded as fundamental. This position is called ‘‘non‐consequentialist,’’ ‘‘intrinsic,’’ or ‘‘deontological’’ (from the Greek word deon for duty). The two philosophers who have had the biggest impact on the subject of animal use are Singer (1990), representing the utilitarians, and Regan (1983), representing the rights and freedoms position. They are by no means the only ones and, although their views are conventionally presented as the starting point for any modern discussion, many other ethical positions exist. Indeed, any one person may hold several alternative views at the same time, causing confusion when an attempt is made to nail down exactly where he or she stands. Nevertheless, it is entirely proper to begin with the two big names, since their writings provide much of the intellectual impetus for the attacks on those scientists who use animals in their research. The essence of Singer’s thinking is that a person’s act is right if—and only if—its consequences are better than or at least as good as those of alternative acts open to that person. This is plainly utilitarian in that the moral decision rests on some kind of weighing against each other of the conflicting outcomes. Singer expresses good and bad outcomes in terms of preferences. Living subjects’ interests are expressed in terms of what they

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prefer and whether if their preferences are thwarted, a wrong has been done to those subjects. Singer believes that when animals are the subjects of an action, their interests should be taken into account, just as those of humans would be. He argues that by degrees the civilized world has been ridding itself of sexual and racial discrimination, and now it should rid itself of discrimination against other species. Humans who are moral agents affecting other individuals should consider animals as moral subjects, even though animals may never be capable of becoming agents. The analogy involves very young children or people who are so disabled intellectually by injury or disease that they cannot make moral decisions, yet they are worthy of moral consideration. Since a moral decision rests on weighing alternative outcomes, Singer could see ways in which experiments on animals might be justified. The preferences of human subjects may outweigh those of animal subjects. Tough judgments are often expressed in terms of thought experiments (sometimes called fantasy dilemmas). Consider four people and a large dog in a lifeboat which is too low in the water to be safe. Do you throw overboard a person or the dog to safeguard the others? Five lives are at stake, and, even though the dog may be regarded as morally valuable as each person, it is considered to have less premonition of its own mortality than the people—so the dog is sacrificed. By the same token, if the subject in question were a human passenger suffering from Alzheimer’s disease rather than a dog, the senile person would be thrown overboard. The solutions to such dilemmas are shocking and often grate against intuition in such a way that they suggest more is at stake than some straightforward metric of preference. Singer would argue that it is necessary to move towards a morality based on rationality rather than rely on gut feelings. Even so, the old utilitarian slogan of the greatest good for the greatest number is often opposed by the argument that those individuals who benefit are different from those who suffer. Furthermore, measuring ‘‘good,’’ or in Singer’s case ‘‘preference,’’ is virtually impossible. Far from being rational, it is seen as an unsatisfactory basis for making practical moral decisions. And when it comes to animals, which animals? Does a rat have the same status as a moral subject as a chimpanzee? Does an ant have the same status as a rat? Does an amoeba have the same status as an ant? By contrast with Singer, Regan takes the view that certain actions are absolutely wrong. He shares Singer’s view that animals should be treated as moral subjects but disagrees with him that actions that might adversely affect their welfare can be justified by their beneficial consequences for humans or other animals. Animals have inherent rights that should be respected as much as those of humans. Which animals? Regan understands the problem of continuity from simple to complex mental existence and

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suggests that the cutoff should be between those animals that are ‘‘subject of a life’’ and those that are not. What is meant is that rights are granted to those animals that have beliefs, desires, perceptions, memories, a sense of the future, feelings of pleasure and pain accompanying a rich emotional life, an ability to initiate action in pursuit of desires and goals, and a psychological identity over time. Anybody who deals with animal behavior will recognize at once the difficulty of identifying animals that might qualify for rights in the Regan sense. So here again the views of a prominent philosopher are difficult to implement in practice, other than by abandoning further thought and pressing for outright abolition of all animal experiments. More seriously for the integrity of his position, Regan retreats from his absolutist views with a series of special considerations that inevitably lead to a utilitarian position and to the view that animals can be used for human benefit after all. He would sacrifice a dog to save his own child. At the most fundamental level, the whole issue of rights is fraught with difficulty. Midgley (1983) pointed out that rights are part of an implicit contract with the social community; people accept conventions on which the smooth functioning of society depends, and these lead inevitably to the need to honor commitments. In short, rights bring with them responsibilities with the caveat that the very young and the very disabled are exempted—an issue to which I shall return. Even the most fundamental human right to life may be waived in emergencies, and the irony can be that those in authority who risk the lives of others may not themselves be at risk, and, worse, they may have concocted the case for sending other people to their deaths. Midgley argued that, with the exception of those already mentioned, no one should have a right who cannot understand and claim it. These considerations suggest that giving a right to an animal is about as sensible as giving it a vote. The positions of Singer and Regan are the most clearly articulated and the most commonly criticized. Many have argued that their views, particularly when expressed in pamphleteering form, are one‐dimensional. Petrinovich (1999) has sharply attacked both of them and adopted a much more pluralistic view. It is still necessary, however, to identify the multiplicity of other positions that lie behind a distaste for the use of animals in research.

III. OTHER ETHICAL POSITIONS A quite different ethical concern from either that of Singer or of Regan is that good treatment of animals is important because of the way it affects attitudes to fellow human beings. This view might be accompanied by

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scepticism about the existence of consciousness in animals other than humans. The concern is that the human readiness to empathize with other animals means that if such feelings in this direction are denied, they will also be denied to humans. According to Thomas (1983), Aquinas interpreted Old Testament biblical teachings about giving respect to animals in these terms. Many have followed since. In modern times, the argument is often countered by the observation that Hitler loved dogs, and the German Third Reich had the most draconian laws to protect animals ever passed. The suggestion is that desensitization generated by maltreatment of one group does not necessarily generalize to another group, whether it be from animals to humans or the other way about. George Bernard Shaw is said to have remarked about those who kill animals for sport: ‘‘I know many sportsmen and none of them are ferocious. I know several humanitarians and all of them are ferocious’’ (Thomas, 1983). It seems entirely plausible that humans compartmentalize their empathy, and, if that is so, the desensitization argument for the good treatment of animals loses much of its force. A separate strand to the human‐orientated approach is to respect the views of those who care deeply about animals. The argument runs that we should be careful not to cause offense to others by our actions, even if we have doubts about their reasons for being offended. (Of course, people may not beat their dogs because they fear being prosecuted—but that is another matter.) The moral case for old‐fashioned good manners works all ways and applies rather more strongly to those who protest against the use of animals in research than it does to those who quietly get on with their science. Not causing offense to others does not provide a compelling basis for stopping animal research. Many people who are opposed to the use of animals in research are not simply worried about animal suffering. The killing of an animal disturbs them whether or not suffering is involved. Their ethical position is essentially that adopted by Regan, based on a sense of justice and a projection of rights from humans to animals. However, an additional thought is that each species has its own set of goals (its own telos) and should be accorded dignity on this account (Rollin, 1998). This sense of the dignity of the species has been applied to plants as well as animals (Heaf and Wirz, 2001). A related thought springs from a view about the connections between all forms of life, often generalized to include inanimate environments such as mountainsides and wetlands. Jamieson (2002) argues that these inanimate parts of the human environment have a moral claim on us. The exact meaning of such a claim is not entirely clear. Nevertheless, nobody should doubt the moral fervor of such holism, and many biologists and psychologists would share much of it. My sense is that the outrage about the senseless or greedy despoiling of the environment extends to the

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destruction of anything that is regarded as beautiful and can be readily generalized to much‐loved works of art and to architecture. Some people have ethical concerns about the use of animals in research quite simply because they are extremely fond of animals (or at least some animals). This is obvious enough in the way that UK legislation is framed to give special status to those groups that vast numbers of the public keep as pets, namely cats and dogs, or with which they have close relationships, namely the horse family (Scientific Procedures (Animals) Act 1986). Many of these positions have not been worked into a moral stance as thoroughly as those of Singer or Regan, but I believe that they lie behind many strong feelings about the use of animals issue. If the rights argument is rejected on the grounds that animals cannot be part of a contract that grants rights in return for responsibilities, where does that leave very young children and the intellectually disabled? Either because they have not yet achieved full cognitive capacity, never had it, or have lost such capacity, these people are unable to exercise their responsibilities in return for the rights that society freely grants them. Petrinovitch (1999) suggested that consideration of human evolution is helpful here. He argued, on the basis of evidence, that in the thought experiment of the unsafe lifeboat, most people would throw out an unrelated Nobel laureate before their own child. Humans support close kin first and in‐group members next; those fellow humans who cannot fend for themselves are given higher status than any non‐human animal. Fifty years before Petrinovitch was considering these issues, Julian Huxley, picking up the interests of his grandfather, Thomas Huxley, wrote: Is there any external standard for morals? Any touchstone by which goodness may be recognised, any yardstick by which it may be measured? Does there exist any natural foundation on which human superstructure of right and wrong may safely rest, any cosmic sanction for ethics? (Huxley and Huxley, 1947)

Julian Huxley implied that if we could only understand the ‘‘cosmic sanction,’’ then we should know how to conduct our lives. Even so, he was ambivalent, and the relativism which he clearly detected in ethical judgments and the sheer complexity of cultural evolution deterred biologists from contributing much to the debate about the origin of ethics for many years. Subsequently, the writings of two men, Wilson (1978) and Alexander (1980), were especially influential in reawakening the old subject of evolutionary ethics that interested Petrinovitch (see also Ruse, 1986). More recently, Hinde (2002) has discussed these issues with great care and insight. Understanding the evolutionary origins of our behavior may well be helpful in dealing with the muddles and inconsistencies that arise in dealing

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with moral issues—such as the use of animals in research. They explain our intuitions but do not help us to understand where our adaptability might take us. The general point was emphasized by Alexander (1980). A functional interpretation of human behavior only makes sense in the environment to which the behavior patterns were adapted. Even if human cleverness was the product of blind Darwinian evolution, such intelligence can clearly be turned towards maladaptive practices such as procuring of addictive drugs for self‐use. The cognitive rules that give rise to rational action may have increased reproductive success in one set of conditions, while having quite different consequences in the modern world. Hinde (2002) has developed these points much more extensively in his book Why Good is Good. Since adaptive propensities can lead to the expression of characteristics with emergent and even non‐adaptive features, it is not plausible to argue that every ethical judgment represents a ‘‘good’’ solution to some present (or past) problem in the social environment (Williams, 1983). Julian Huxley may have hoped that biology would eventually offer a ‘‘cosmic sanction for ethics’’ (Huxley and Huxley, 1947). So far, biology has failed to deliver. What it has done, however, is to suggest ways in which human propensities, shaped by Darwinian and cultural evolution, have played their part in influencing the historical development of socially transmitted norms of behavior (Bateson, 1989). In the context of the rights argument, Petrinovitch (1999) is surely correct to point to these influences when attempting to explain why most people intuitively value an incapacitated human being more highly than a non‐human animal. Whether they are right to do so is another matter. Thomas (1983) described how the moral concerns of those who had preached and pamphleteered against cruelty to animals had remained remarkably constant in England from the fifteenth to the nineteenth century. He summarized their views as follows: Man, it was said, was fully entitled to domesticate animals and to kill them for food and clothing. But he was not to tyrannize or to cause unnecessary suffering. Domestic animals should be allowed food and rest and their deaths should be as painless as possible. Wild animals could be killed if they were needed for food or thought to be harmful. But, although game could be shot and vermin hunted, it was wrong to kill for mere pleasure. (Thomas, 1983, p. 159)

This account still captures the views of many people to this day, particularly in relation to suffering. Certainly, a great many behavioral biologists who work on animals in the course of their own research are strongly bound to an ethic of caring for them. This view is strongly expressed in

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the ethical guidelines offered to authors of papers submitted to the journal Animal Behaviour and has been the subject of much comment in recent years (Bateson and Klopfer, 1991; Bekoff and Jamieson, 1990; Rogers, 1997). In its guidance to scientists working on animals, the Royal Society (2004) states uncompromisingly: ‘‘All possible measures must be taken to minimise the suffering of animals used in research’’ (p. 27). Not everybody speaks with the same voice, however. One colleague told me that he gave up laboratory work in favor of field studies because he did not like having to kill animals at the end of an experiment. Some field biologists are more concerned about the death of animals than they are about suffering. This is presumably because their interest is in populations, biodiversity, and conservation rather than in animal welfare. Conservation is placed above welfare because, in their eyes, suffering is a part of natural life. The clash of views is brought into sharp focus when suffering is caused intentionally—by poisoning cats, for example, in order to protect an endangered species of bird whose existence is threatened by the cats. These tensions within the biological community and the ways in which they may sometimes be resolved lie outside the scope of this article but are discussed elsewhere by Bradshaw and Bateson (2000).

IV. THE ETHICAL CASE

FOR

USING ANIMALS IN RESEARCH

In addition to the moral objections to the use of animals in research, strong ethical arguments are mounted on the other side for using animals in scientific studies. In the past, many biologists took the view that they had a right to pursue knowledge for its own sake, and this aspect of academic life, highly valued in universities, trumped all other considerations. Not many would adopt such an unvarnished view these days, but most of us would continue to argue that great benefits flow from biological research. These benefits might be in terms of improvements in medical or veterinary practice achieved in the short to medium term or in terms of fundamental contributions to the understanding of biological processes. The provision of such benefits is seen as good and morally important. Those who favor work on animals commonly wish that, by such work, suffering of humans or other animals will be alleviated. Many scientists who work on animals do so because they feel strongly that their research will help to relieve suffering. They may feel this way because they are directly involved in attempting to discover a cure for a human or animal disease or because they aim to uncover fundamental principles that will have general benefits for understanding. Scientists in favor of this moral stance hope that their research will lead to a fundamental understanding

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of aspects of biology and hope that such understanding in turn may facilitate the development of therapeutic measures for both animals and humans. Critics respond by questioning the motives of biologists, suggesting that the real goals are fame, career advancement, and occasionally fortune, coupled with extraordinary insensitivity when it comes to the treatment of animals used in research. An unwillingness to use alternatives to living animals is attributed to vanity, laziness, or conservatism. Some scientists will doubtless have the base motives attributed to them, and you will find among the scientific community those who are just as vain, lazy, and conservative as would be found in any other group of people. However, others are strongly motivated by a desire to relieve suffering, and they understand the fundamental problems of biology—an understanding that must underpin most advances in medicine. One serious moral critique of the scientists’ position is that the individual animals suffering in the course of scientific research do not benefit from any advances in knowledge that derive from their suffering. In human and veterinary medicine, causing pain or suffering in a patient is often considered unethical unless it is for the direct benefit of that patient. If it is not for the human patient’s benefit, informed consent is crucial. In research involving animals, one ethical principle (not harming individuals) is in direct conflict with another (helping the majority). The dilemmas seem inescapable. Before considering how they might be resolved, I shall discuss briefly whether scientists are correct in their belief that work on animals has led to major medical and veterinary benefits. The sins of the non‐violent anti‐vivisectionists are ones of omission. Protection of the animals is carried out at the expense of stopping medical research. When the activists come into contact with lobbying groups formed by human patients, they are aware that they are on weak ground and seek to argue that no benefit has flowed to medicine from studies of animals (Pound et al., 2004). In justifying the demand that current research be stopped, activists suggest that the animal work is scientifically trivial, of no medical importance, that it could be done without using animals, or would be better done on humans. Most scientists would disagree (The Royal Society, 2004). Blanket denials that medical advance has ever been served by the animal studies is not simply a matter of opinion and is susceptible to the test of evidence. The US Department of Health and Human Services (1994) concluded that almost every form of conventional medical treatment, such as drugs, vaccines, radiation, or surgery, required the study of animals. In the UK, a House of Lords Select Committee, after listening carefully to both sides of the argument, concluded that the case for research on animals was strong (House of Lords, 2002). They also

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argued that more effort should be made to find replacements—a view that is supported by the Royal Society, the UK’s academy of science.

V. TOWARDS RESOLUTION Both the extreme animal rights activists and the most zealous scientists defending their work on animals tend to suppose that the values they hold dear are more important than those of their opponents. Even when people holding such different moral positions are totally inflexible and seem set for a fight to the finish, it is possible to devise practical ways of helping the majority to resolve the undoubted moral conflicts. In much of the debate about the use of animals in research, a particular moral stand is taken as an absolute, over‐riding all other moral claims. The alternative to such absolutism on either side of the debate is to respect both positions and to attempt to minimize suffering inflicted on animals used in research while maximizing the scientific and medical gain. Varner (1994) has written sensitively and optimistically about the prospects for some convergence in the animal rights debate. Rawls (1999) has been at the forefront of developing what he calls an ‘‘overlapping consensus.’’ He considers how to achieve fair agreements between reasonable people who accept that they must give some ground in order to achieve a peaceful solution. As Hinde (2002) notes, many different and seemingly incompatible concerns claim highest priority for action. The apparent oppositions are familiar enough: fish stocks versus fishing villages, pure air versus abundant energy, and abundant food versus biodiversity and unpolluted environments. Reducing matters to single issues makes for rousing rhetoric, convenient slogans, and easily understood manifestos. But it is not a good way to organize a society in which people have to go on living with each other. Intransigence can end up with outcomes that are regarded as undesirable by everybody: no fish and no fishing villages; dirty air and devastated sources of energy; dead waterways, unproductive land, and massive reductions in biological diversity. The equivalent messy outcome of allowing intransigence to dominate the debate about the use of animals in research is that medical research is seriously delayed, and animals are treated poorly in the unregulated laboratories of countries lacking appropriate legislation. In the UK, pharmaceutical companies are threatening to withdraw their research activities to other parts of the world (Mansell, 2004), and Singapore is making itself attractive to them by minimizing regulation and maximizing protection from animal rights activists (Tomlinson, 2004). Seemingly irreconcilable views can sometimes be brought together. Indeed, the UK Act of Parliament specifically concerned with the use of

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animals in research states: ‘‘In determining whether and on what terms to grant a project licence the Secretary of State shall weigh the likely adverse effects on the animals concerned against the benefit likely to accrue as a result of the programme to be specified in the licence’’ (Animals (Scientific Procedures) Act 1986 5. [4]). UK law requires the Animal Procedures Committee, the committee appointed to advise on the running of the 1986 Act, to operate such a cost/benefit approach. The ‘‘weighing’’ required by law is not an exact process since the assessment of scientific and medical benefit and that of animal suffering, in as much as either can be quantified, are not expressed in the same terms. The assessments are incommensurate, and, therefore, referring to the judgment as cost‐benefit analysis is strictly speaking misleading. How then is this weighing process to be carried out? Most people consciously, or more often unconsciously, take many different things into account when making everyday decisions. Suppose, for instance, you want to buy a new pair of shoes. You will want good quality, and you may well want shoes that are not unfashionable or at least are acceptably classical. At the same time, you are also likely to want to pay as little as possible. You will probably set an upper limit for how much you will pay and a lower limit for the quality. If you are forced to pay more, you will expect higher quality and maybe shoes that conform to current fashions. I suggest that the analogy is relevant to the present case: A much lower amount of animal suffering would be tolerated in scientific research if the work were not regarded as being important. Conversely, a high expected return from the science would justify more suffering. When I first used the shoe‐buying analogy at a public meeting some 25 years ago, some of those present were unhappy because they felt that no animal suffering could be justified merely in the name of good science. If the words ‘‘medical benefit’’ were added to ‘‘important science,’’ the answer seemed more satisfactory to them, however. Great human suffering, and plenty of it exists in the world, was felt to be worse than the possibility of pain inflicted on an animal in the course of research. Of course, the likely benefits of biological science for human and animal welfare are not easily predicted. The best bet is often to back science that is likely to lead to the discovery of fundamental and unifying principles. Many governmental and charitable funding bodies accept that the funding of high quality biological research is one of the most satisfactory ways of contributing to the medicine of the future. Nonetheless, the delivery of real benefits to humans or animals is uncertain. Many people would be deeply unhappy about animals suffering when the possible medical or veterinary value of the experiments had not been estimated. It was for that reason I included in the decision rules the probability of generating medically

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FIG. 1. A decision cube for representing the rules, arrived at by consensus, about whether a scientific research project should be allowed to proceed. Three independent assessments are made. The first assessment is of the maximum suffering that the animals are likely to endure in the course of the project, the second is of the overall scientific importance of the project, and the third is of the likelihood of medical benefit. If the three assessments fall into the solid part of the cube, the project would be deemed unacceptable, otherwise it would be deemed acceptable (from Bateson, 1986).

important results (Bateson, 1986). The model for achieving an overlapping consensus was republished by Driscoll and Bateson (1988) for the benefit of behavioral biologists and further developed in Smith and Boyd (1991) and Bateson (1992). One advantage of a set of rules, such as those suggested by the decision cube shown in Fig. 1, is the acknowledgment that, in deciding whether a particular activity should be tolerated in a civilized society, more than one thing matters. This is a general point, even though the figure focuses on the use of animals in research. For the purposes of making decisions about possible animal use in a scientific project, three separate dimensions are to be assessed independently: the scientific importance of the research, the probability of medical benefit, and the likelihood of animal suffering. Animal suffering should be tolerated only when both the importance of the research importance and the probability of medical benefit are assessed as being high. Moreover, certain levels of animal suffering would generally be unacceptable, regardless of the quality of the research or its probable benefit. The decision rules used would permit research of high importance involving little or no animal suffering—even if the work had no obvious potential benefit to humans. This feature takes note of the concern of scientists who want to understand phenomena that have no immediate and obvious benefit for humans. This is seen as a ‘‘good’’ in itself, even

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though an indirect but unforeseeable benefit might be an advance in medicine. The decision cube, sometimes denigrated as traditionally utilitarian, is emphatically not a cost‐benefit piece of accountancy since it does not depend on a common currency or on balancing incommensurable properties. It is a set of pragmatic rules that can be helpful, I believe, in determining whether or not a particular piece of research should be carried out. I did not imagine that the positions of the lines indicating whether or not to give assent to a research project would be forever frozen. The positions represent a political consensus acceptable to the majority of the public. Therefore, they would require debate in the institutions set up in democracies in order to bring together a representative set of opinions. All the evidence suggests that in highly developed countries the political consensus has been moving towards a more restrictive view of what is acceptable. However, it might well change in the opposite direction, were affluent human populations to be afflicted by a new and terrible plague and vaccines could only be developed on animals very similar to humans. Emlen (1993) criticized the cube because he believed (incorrectly) that I had couched benefit largely in terms of knowledge that has obvious benefit to humans. He wrote: ‘‘In this era of diminishing biodiversity it is imperative that we increase our knowledge of organisms that can serve as general models for larger categories of species.’’ I agree, but I think that my formulation would cover the type of work he would like to see carried out. My representation of what I believed to be a consensus view was that high grade research that increased fundamental knowledge would be acceptable if the level of suffering was low. The acceptance bar would, indeed, be lowered if the research were also like to have medical benefit. Nevertheless, high grade research with a conservation goal or research that aimed to find general models for larger categories of species would be acceptable, even if some suffering were inflicted on the animals used. The decision cube has not captured universal admiration. Finsen (1990) felt that it does not offer a way of transcending subjective and individual judgments, and she concluded that the model is too vague to be of any use. Her mistake was to suppose that the model proposes an ethic. It does not. It proposes a way of dealing with competing ethics. Reiss (1993) was more generous in his criticism. He wrote: ‘‘The most obvious problem with this approach is not so much in deciding where a piece of research lies on these three axes, but on deciding how to balance the costs (animal suffering) against the benefits (quality of research and medical benefit).’’ However, Reiss went on to point out that the approach had been used successfully by the Association for the Study of Animal Behaviour in Europe and its sister

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organization in the United states when deciding whether or not to publish papers in their jointly run journal, Animal Behaviour. Petrinovich (1999) concurred, judging the model to be useful. UK law protects all vertebrates, but the use of more complex vertebrates such as primates is even more strictly controlled. The use of animals is not permitted where a replacement alternative is available. Where no replacement alternative is available, then experimental protocols must be refined in such a way as to reduce any pain or suffering to a minimum using, for example, analgesics and humane end‐points. Finally, the number of animals used must be reduced to the minimum consistent with achieving the scientific objectives of the study. These general points are derived from a famous book by Russell and Burch (1959), who developed the principle of the 3Rs (Replacement, Refinement, Reduction). Some people have suggested to me that the principle of the 3Rs requires that another dimension to be added to the decision cube. This would be a mistake in my view. If animals were replaced, the cube would not be needed, since it is designed specifically for the purposes of deciding whether or not a project involving animals should proceed. If procedures were refined, animal suffering would be improved by definition. If numbers were reduced with good experimental design, in all probability the quality of the research would go up. This is partly because the replacement of one experimental treatment by the simultaneous use of two or more treatments within the same experiment leads to a reduction in the total number of animals required, but also because interactions between independent variables are more likely to be discovered. In short a fourth dimension, however it were to be drawn, is unnecessary.

VI. MAKING

THE

ASSESSMENTS

The benefits of research must be assessed; they are based on likely contributions to human understanding, education, the economy, and the environment, as well as to human and veterinary medicine. Finsen (1990) was sceptical that it would be possible to find a way of measuring the future importance of research since so much depends on luck. I had foreseen the objection (Bateson, 1986). Virtually all funding of future scientific research depends on making informed judgments about how particular projects will develop. Nobody denies that funding decisions are difficult and can be mistaken, but nobody who lives in the real world supposes that grant applications should be decided by tossing a coin. The same applies to the assessment of medical benefit. Difficult though it may seem, committees judging planned medical research are asked to assess the probability of a

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therapeutic outcome. They manage to do so. For these reasons, I reject Finsen’s (1990) sweeping assertion that ‘‘it is not really possible to use the dimension of ‘expected benefits.’ What about animal suffering? The intrinsic difficulty is that suffering is a subjective state, and no person can be sure that another would, in the same circumstances, suffer as he or she does. The usual way of dodging this ancient philosophical catch is to rely on the similarities between people. So if I suffer when I am burnt, I assume that you too will suffer in much the same way when you are burnt. Undoubtedly, this is the implicit assumption of most veterinarians when dealing with the issue of pain in animals. If the animal has the same neural equipment for detecting damage and processing the information in its central nervous system as a human and if it behaves in situations that humans would find painful in much the same way as a human, the intuitive rule is that the animal should be treated humanely (Bateson, 1991). Identical arguments are mounted for other aspects of suffering by those concerned about animal welfare (Smith and Boyd, 1991). This general line of attack lies behind the UK Farm Animal Welfare Council guidelines for maintaining the good welfare of animals on farms. The animals should be given five freedoms: freedom from hunger and thirst, freedom from the inability to behave normally, freedom from discomfort, freedom from fear and distress, and freedom from pain, injury, and disease (Farm Animal Welfare Council, 2004). Various alternatives to the human‐centred approach have been offered. Some authors focus on the conditions that push an animal’s capacity to adapt to changing conditions outside normal limits (e.g., Broom, 1986; Ewbank, 1985). The quality of an animal’s welfare is determined, therefore, by judging the animal’s ‘‘state as regards its attempts to cope with its environment’’ (Broom, 1986). Animals maintain their internal state within certain limits. Movement outside those limits is countered by behavioral and/or physiological reactions that operate to bring the state, which might be body temperature, within the limits. Stress is thought to arise when attempts to return the internal state to the optimum persistently fail (Toates, 1995). The intention of those who advocate this approach is to avoid the anthropocentric approach adopted by those who simply focus on the similarities of the animal’s behavior and physiology to that of humans. However, implicit in the coping definition of welfare is the notion that an animal that fails to cope suffers and, more centrally, that some organisms suffer more than others. The failure to cope by bacteria is of less concern than failure to cope by monkeys. The human‐centred approach based on notions of behavioral complexity enters via the back door. A different approach is offered by a consideration of the animal’s goals (Rollin, 1998). If the animal’s attempts to achieve certain endpoints are

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obstructed by human intervention, then its welfare has been damaged. The superficial attractiveness of this Aristotelian telos position is marred by the sheer difficulty of knowing what the particular goal of any one component of an animal’s behavioral repertoire might be for. The behavioral ecologists have a hard enough time sorting out biological function in wild‐living animals. What is one to make of the purposes for living of domesticated animals with all sorts of characteristics artificially selected by humans? Painting on a much broader canvas, evolutionary biologists would argue that the only serious goal for an animal is reproductive success. Survival is necessary, but it is not a sufficient goal because, without reproduction (or more broadly, the care of kin), the individual animal can make no further contribution to subsequent evolution. On this argument, animals kept in captivity and used freely for breeding are fulfilling their purpose much more successfully than animals living short lives in the wild. Behavioral biologists who have entered the debate on welfare have argued that proper account should be taken of the special adaptations to ecological conditions in which the animal evolved (Barnard and Hurst, 1996; Bateson, 1991; Timberlake, 1997). When an animal does not behave as humans would in the same circumstances, scientists should be sensitive to its requirements, its evolutionary history, and the details of its social life. Therefore, it is argued that assessments of suffering will also depend on good observational data about the natural behavior of the species in question: its normal requirements, its vulnerability to damage and the ecological conditions in which it lives, and the decision rules by which it maximizes its reproductive success in that environment. Some animals, when threatened by extreme danger, remain rigid and silent because that is the safest thing to do. They do not look to the casual human observer as though they are in a state of stress, because alarmed humans would not normally behave like this. Part of the problem is that some species can experience subtle odors, high‐pitched sounds, infra‐red light, ultra‐violet light, or magnetic fields that humans are unable to detect and, therefore, do not regard as being important. Few people have much fellow feeling for fish, even though many fish are long lived, have complicated nervous systems, and are capable of learning complicated tasks. Awareness of an animal’s natural behavior, it is argued, can also provide great insight into what is and what is not likely to be stressful. For example, isolation from other members of its own kind may be traumatic for an individual belonging to a gregarious species, such as many monkeys. However, isolation may be the preferred state for members of species that are habitually solitary, such as birds of prey. Moreover, even social animals that have been kept in isolation for a long time may be stressed when they are introduced once more to members of their own species. Barnard and

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Hurst (1996) argue strongly that undue attention to the human condition leads to a focus on health and survival. They point out cogently that both may be sacrificed by animals in the interests of reproduction. Frustrating an organism’s attempts to ‘‘spend itself,’’ adaptively, on the mistaken assumption that such expenditure reflects an inability to cope, could create a welfare problem. Barnard (2004) gives as a possible example the housing of rats in single cages in which they show relatively low levels of physiological stress. However, when given a choice, rats prefer to interact with other members of their own species, even though this may involve fighting and higher levels of stress. Politicians and administrators would like scientists to provide incontrovertible evidence for welfare problems generated by human activity. Little in science is incontrovertible—even if those who controvert may be way out on a limb from the central trunk of scientific opinion. Many of the judgments about poor welfare in animals have been disputed by Bermond (2001), who argued that animals do not have the necessary neural equipment to suffer in the way that humans do. My own view is that this attempt to adjudicate about what animals feel on the basis of a very incomplete understanding of the brain is treading on treacherous ground. In the past, many surgeons took the view that the central nervous systems of human babies are so immature that they could not feel pain. Therefore, they argued that human babies undergoing surgery should not be treated with potentially dangerous analgesic drugs or anaesthesia. Wall (1999) described how endless philosophical musings were brought to an end by a rigorous empirical examination of the fate of babies who had been given analgesics or anaesthesia during surgery and those who had not. Those who had not been protected from the pain of surgery were much less likely to survive. That horrifying evidence should generate a measure of thoughtfulness in anybody who is tempted to pontificate on what animals do and do not feel. One way to penetrate the motivation of an animal is to question it by behavioral means (Dawkins, 1980). Colpaert et al. (1980) tested the responses of animals to analgesics when in a state that might be expected to be painful on the basis of what is known about humans. They knew that normal rats drink sugar solution rather than water containing an analgesic. Rats with chronically inflamed joints similar to those in an arthritic person preferred to drink the solution containing the analgesic. Danbury et al. (2000) used a very similar approach. Lame and sound broiler chickens were taken from commercial flocks. The chickens were trained to discriminate between differently colored feeds, one of which contained the analgesic drug carprofen. The two feeds were then offered simultaneously, and the birds were allowed to select their own diet from the two feeds. The lame

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birds tended to consume more analgesic than the sound birds. In another study, they showed that the more afflicted were the birds with lameness, the more drugged feed they took. Cooper and Mason (2001) made mink work for a variety of resources by requiring them to push a heavily weighted access door. They varied the weight of the door to see how much the mink would ‘‘pay’’ to reach different resources such as extra space, an extra nest site, novel objects, toys, and a water bath. The mink pushed against heavy doors particularly to reach swimming water. Indeed, so keen were these smallish animals, weighing considerably less than a kilo themselves, they would push open a door with 2 kg of weight added to it. While preference tests have their place in welfare assessments, Bateson (2004) noted that the outcome depends greatly on how choices are presented. A preference can change when a third, less preferred option is added to a binary choice. The third option can change the relative preference or, more surprisingly, the absolute preference. The scientific approach to the problems of assessing suffering in animals has to be evidence based, and collecting evidence requires orderly methods. Many debates about what should and should not be measured in welfare studies suggest that a variety of approaches are more likely to benefit understanding than a single approach (Mason and Mendl, 1993). All of the following approaches contribute to an assessment of adverse welfare: (a) measurements of physical damage to the animal; (b) measurement of the extent to which it has been required chronically to operate homeostatic mechanisms that would normally operate acutely; (c) measurements of physiological states that would be found in suffering humans; (d) measurement of the animal’s preferences; and (e) considerations of the ecological conditions to which the animal is adapted, its normal social structure, and the decision rules it uses to maximise its reproductive success. When all of these are taken into consideration, judgments about the quality of an animal’s welfare are much more likely to win widespread agreement than if only one approach has been used. Given that no royal road to making a judgment about welfare exists, ideally some overall assessment should be reached from the various perspectives that are used (behavior, body state, and behavioral ecology). The very different approaches used by the psychologists, the behavioral ecologists, and the veterinarians all lead to separate assessments of the severity of the welfare problem (say from zero to two), and the overall score might be used as an indication of the severity of the problem (from zero to six). A separate issue is that the harms of research have many different facets. Smith and Boyd (1991), representing the views of a remarkably disparate working party, argued that in making an overall assessment, most attention

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should be focussed on the greatest harm to the animals that would be used in the research. If equal attention were to be given to low, medium, and high assessments in response to the various questions about harm, a project involving an excruciatingly painful procedure preceded by husbandry conditions involving very little stress or anxiety might be assessed as having a lower overall cost to the animal than one involving a set of conditions that were only moderately severe in their effects. Once the assessment of the welfare problem has been made, this assessment can then be put together with the independent assessments of likely scientific importance and expected therapeutic benefit of the research to make a concluding judgment of the acceptability of a research programme. Some of the moral tensions are not easily resolved in the abstract since the position that a person adopts will be swayed by the choices he or she is offered. Social psychologists have often noticed the contextual effects that can arise when different forms of assessment are used. For instance, on academic appointment committees Candidate A may be preferred to Candidate B because his research is more extensive; Candidate B may be preferred to Candidate C because her work shows more promise, but Candidate C may perform most impressively at interview and be appointed by the committee, with seeming amnesia of what went before. The committee focuses unduly on the personality characteristics of the candidates because the vividness of their recent face‐to‐face experience dominates the context for making a decision (Tversky and Simonson, 1993). The human weakness can be met in part by ensuring that the different dimensions on which the final choice depends are made independently and only then are brought together for the overall decision.

VII. CONCLUSION The well‐known philosophical positions, based on principles of animal liberation and animal rights, leading to criticism of the use of animals in research have been seriously questioned. Thoughtful writers such as Petrinovich (1999) have argued for a pluralism that honors both utilitarian treatments and concerns about basic rights and freedoms. I have suggested, furthermore, that these positions do not embrace all the ethical views of people who care strongly about animals and the natural world. Scientists who care about animals accept responsibility for the good stewardship of the animals they study. If they also believe that the moral case for doing their research is strong, they are forced into accepting that their scientific behavior is influenced by more than one ethical position.

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A lot of one desirable outcome does not have to mean a little of the other. It is possible to reconcile a strong moral commitment to understand biology and benefit from such understanding by using scientific methods with an equally strong moral desire to minimize animal suffering. Alternatives can be found to the destructive opposition between the morality of advancing the understanding the natural world through science and the morality of eliminating the suffering that science sometimes brings with it. When the assessments are put together, the overall judgment depends particularly on the quality of the benefits and the severity of the costs. The debate about the ways of bringing different ethical positions together continues and, in the UK, the Animal Procedures Committee has recently published a long report on the so‐called ‘‘cost‐benefit’’ approach (Animal Procedures Committee, 2003). The aim of the whole process is to encourage scientific research that brings maximum benefit with minimum suffering to the animals. None of this is especially easy, but I think that, because they care for both animals and their science, behavioral biologists are well placed to help the process of resolving the tension between seemingly opposed moral positions. A lot of fair‐minded people, who often start with utterly different views, are finding ways of reaching agreement. Not everybody is fair minded, alas. Bigotry and fanaticism in all their forms may never be eradicated, but they can, at least, be marginalized.

VIII. SUMMARY The ethical positions, on which attacks on the use of animals in research are based, have depended most commonly on treating the preferences of non‐human animals as worthy of equal respect to those of humans. More radically, animals are believed to hold the same rights as humans. Such simplistic views are readily criticized and do not capture all the reasons why many people believe that animals, particularly complex ones, should be treated responsibly and with consideration. Moreover, strong moral arguments can also be mounted for using animals in order to understand the fundamental problems of biology and for helping to alleviate the suffering of humans and other animals. The tensions may be eased in practice by making every effort to minimize the suffering of those animals while ensuring that research is focused on important biological problems and, where possible, that it takes into account the likely benefits to health and well‐being that may derive from the research. Assessments along these different dimensions of the moral dilemma are not trivial, but the assessment of welfare has, in particular made big strides in recent years.

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Behavioral biologists are well placed to advance discussion so that any one moral issue does not dominate the debate.

Acknowledgments I am grateful to a number of friends and colleagues for their comments on an earlier version of this article. I thank warmly Robert Hinde, Halvard Lillehammer, Georgia Mason, Michael Reiss, Tim Roper, Peter Slater, and Charles Snowdon.

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ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

Prenatal Sensory Ecology and Experience: Implications for Perceptual and Behavioral Development in Precocial Birds Robert Lickliter department of psychology florida international university miami, florida 33199, usa

I. INTRODUCTION In the several decades since the publication of the first volume of the Advances in the Study of Behavior series in 1965, biologists and psychologists have increasingly come to view behavior as an emergent phenomenon resulting from ongoing interactions between an organism and its physical, biological, and social environments over the course of individual ontogeny. Notions of innate or hard‐wired behavior have gradually given way to a growing appreciation that behavioral development is more than simply the unfolding or triggering of a fixed program or blueprint, independent of the activity, experience, or context of the organism. There is now widespread acknowledgement that young organisms do not come into the world with ready‐made response systems. Rather, behavior emerges and is maintained or transformed over individual development through the interactions of inner and outer events and conditions occurring over the course of the organism’s activity and experience. A wealth of studies from animal behavior and comparative psychology over the last 40 years have collectively demonstrated that behavioral development is best viewed as the result of the coaction of multiple features and levels of the organism and its environments, including genes, hormones, diet, sensory experience, and social interactions, to name but a few (see Michel and Moore, 1995 for a useful overview). At the level of behavior, the organism and its context constitute an integrated developmental system. Genetic, neural, hormonal, and other physiological factors are always part an parcel of this developmental system, as are 235 0065-3454/05 $35.00 DOI: 10.1016/S0065-3454(05)35006-6

Copyright 2005, Elsevier Inc. All rights reserved.

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the specific extrinsic factors that make up the developmental context of the individual organism (Gottlieb, 1991, 2002; Gottlieb et al., 1998; Lickliter and Honeycutt, 2003; Oyama, 1985; Oyama et al., 2001; Robert, 2004). Approaching behavioral development as a ‘‘system’’ property that is generated in context rather than expressed from a predetermined template has fostered a more focused concern with the ecology of development, the immediate or proximate properties of the organism’s niche that guide, facilitate, maintain, or constrain behavior. Development occurs ‘‘in the middle of things,’’ and the world presents the young organism with physical, biological, and social environments that are structured, organized, and often specific to the organism. There is growing appreciation across the behavioral sciences that the study of behavior must include an in‐depth analysis of the physical, biological, and social surround of the organism as well as the genetic, hormonal, and physiological processes taking place inside the organism (and their multileveled interactions). That being said, assessing the kinds and range of stimuli to which individuals of a given species are normally exposed in the course of development and determining the particular aspects of the available stimulus array to which the organism is sensitive and responsive at different stages of development have received relatively little research attention (but see Alberts and Cramer, 1988; Gottlieb, 1971a, 1997; Johanson and Terry, 1988; Khayutin, 1985; Miller, 1988; White et al., 2002 for examples). As a number of investigators have pointed out, the specific stimulative and experiential features of the environments in which development takes place for any given species constitute one of the most understudied parameters of animal behavior (see Kaufman, 1975; Reed, 1996; van der Weele, 1999; West et al., 2003 for further discussion). Due in part to the difficulties of gaining access to the embryo or fetus of birds and mammals, this lack of ecological insight is particularly true for the prenatal period of the life cycle. Despite over a century of behavioral embryology documenting the ability of the embryo or fetus to detect and respond to sensory stimuli (Gottlieb, 1973; Hamburger, 1963; Kuo, 1967; Oppenheim, 1982), relatively little is known regarding the specific nature of the sensory stimuli typically available to the young organism in ovo or in utero or its particular effects on the emergence, maintenance, and transformation of behavioral organization (but see Gottlieb, 1971a, 1997; Lickliter, 1993; Rogers, 1995; Ronca and Alberts, 1995; Smotherman and Robinson, 1988; Vince, 1973). Although there is now widespread appreciation that the prenatal environment of avian and mammalian species is rich in tactile, vestibular, chemical, and auditory sensory stimulation (Freeman and Vince, 1974; Smotherman and Robinson, 1986) and that sensory systems capable of responding to these types of inputs are already developed

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and functional before birth or hatching (Alberts, 1984; Bradley and Mistretta, 1975; Gottlieb, 1971b; Lecanuet and Schaal, 1996), the specific details of how the sensory capabilities of the young organism and the stimulative features of its prenatal and early postnatal environment coact to influence the emergence of such basic processes as selective attention, perception, learning, or memory during prenatal and early postnatal development have received relatively little systematic research attention. For example, immediately following birth or hatching, newborn birds and mammals emerge into a world of multimodal stimulation to the senses. All vertebrates have multiple sensory systems that enable them to rely on this rich combination of multisensory information to guide their perception and action (Partan, 2004; Stein and Meredith, 1993; ten Cate, 1994). Across different species and ecologies, young organisms must quickly come to selectively attend to relevant stimulation in their immediate environment and ignore irrelevant stimulation if they are to survive and prosper. Given that most objects and events present a mix of visual, auditory, olfactory, and tactile impressions simultaneously, how do young organisms determine which patterns of sensory stimulation belong together and which ones are unrelated? What causes some patterns of sensory stimulation to be salient, attended to, and remembered and other patterns of stimulation to be ignored? Although much remains to be learned of the perinatal conditions and experiential events that facilitate this selective process, it is clear that at birth or hatching the neonate has had a great deal of prenatal experience, and the nature and type of this experience must be taken into account when seeking explanations of infant perception and behavior (Lickliter and Bahrick, 2000). In the case of precocial birds and mammals, all of the sensory modalities are capable of function in the prenatal period, and all the senses are subject to ongoing temporally patterned stimulation during the prenatal period (Gottlieb, 1971b). Consequently, newborns are not sensorally naive at birth, and the sequential onset of functioning of the sensory systems during very early development and the resulting patterns of prenatal intersensory competition and integration across the senses can have a significant influence on how young organisms respond to and learn about their developmental niche in the period before and after birth or hatching (Alberts, 1984; Gottlieb, 1971b; Lickliter, 1995; Turkewitz and Kenny, 1982). In this chapter, I review evidence derived from research with precocial birds that provides support for this insight. This research shows that embryos’ and hatchlings’ sensitivity and responsiveness to the different types and amounts of sensory stimulation present in their developmental milieu are modulated by several related factors, including the individual’s previous experiential history, its present developmental stage, and the context in

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which particular sensory experience is provided or denied. This body of work has demonstrated a remarkable degree of sensitivity to various features of sensory stimulation on the part of the avian embryo, including the amount and intensity of stimulation provided, the timing and relative order of presentation of stimulation, and the type of sensory stimulation available for exploration (Deng and Rogers, 2002; Gottlieb, 1997; Lickliter, 2000b; Rogers, 1995). Most significantly, research with precocial avian species has provided several examples of how normally occurring prenatal experience plays an essential role in the development of species‐typical behavior after hatching. Parallel evidence is available from research with mammalian fetuses (Fifer and Moon, 1995; Pedersen and Blass, 1982; Ronca and Alberts, 1994; Smotherman and Robinson, 1990) but will not be reviewed in any detail here. The perspective that features of instinctive or species‐typical behavior could be a consequence of experience that occurred prenatally was raised by Zing‐Yang Kuo (1921) early in the last century, and several comparative and developmental theorists subsequently elaborated on and provided empirical support for this idea, including Lehrman (1953, 1970), Schneirla (1956, 1965), Gottlieb (1968, 1971a), and Miller (1988, 1997). Although we are still a long way from understanding the specific pathways and processes by which prenatal sensory ecology influences early perceptual, behavioral, and cognitive development in birds and mammals, research with precocial birds has provided significant insights into some of the conditions and experiences of prenatal development that appear to be involved in the achievement of species‐typical patterns of perception and behavior.

II. DEVELOPMENTAL ANALYSIS OF THE PRENATAL SENSORY ECOLOGY OF PRECOCIAL BIRDS An empirical concern with the species‐specific environments of development (‘‘developmental ecology’’; see West et al., 2003) involves assessing the kinds of conditions and stimuli to which animals are normally exposed in the course of development and determining experimentally the particular aspects of the available environment to which the developing organism is sensitive and responsive (Johnston, 1985; Miller, 1988). Developmentalists are thus faced with the challenge of determining both how the features of the immediate environment contribute to and constrain the perceptual information available to the young organism and how these contributions and constraints are themselves specified by the changing structure and capacities of the developing organism. Despite methodological and

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technical advances in fetal monitoring and imaging over the last several decades (Lecanuet et al., 1995; Shair et al., 1991), studies that describe or manipulate the amount, type, or timing of prenatal sensory experience remain difficult to undertake with mammalian infants, including humans. In contrast, because their prenatal development takes place in ovo rather than in utero, avian embryos are more accessible to various types of experiential manipulations than are mammalian fetuses (as are those of most reptiles; see Sleigh and Birchard, 2001). For example, it is relatively easy to give the precocial chicken, duck, or quail embryo exposure to modified amounts of tactile, vestibular, or auditory experience or unusually early visual experience by removing a small portion of the top of the egg shell and inner shell membrane in the days prior to hatching (e.g., Gottlieb, 1971a; 1988; Lickliter, 1990a; Lickliter and Stoumbos, 1992) (Fig. 1). Manipulating available prenatal sensory stimulation does not typically affect the hatchability or survivability of the embryo or hatchling, and a number of investigators have successfully used such procedures to assess the various effects of prenatal and early postnatal sensory experience on embryos’ and hatchlings’ responsiveness to the audible and visible features of their social environment, including the maternal hen and broodmates (e.g., Gottlieb, 1985, 1993; Honeycutt and Lickliter, 2001, 2002; Lickliter and Lewkowicz, 1995; Miller and Blaich, 1984; Sleigh and Lickliter, 1997, 1998; Vince, 1972, 1980). Access to the precocial avian embryo during the prenatal period affords the use of several types of experiential manipulations designed to identify the aspects of the available stimulative environment to which the young organism is sensitive and responsive. As pointed out by a number of developmentalists (Johnston, 1985; Miller, 1988; Petrinovich, 1981; West and King, 1996), relatively unobtrusive observations and descriptions of ongoing behavior in a variety of natural, everyday contexts provide a necessary anchor, but a fuller understanding of behavioral development also requires an experimental approach, whereby certain experiential variables are held relatively constant while others are varied systematically. This back‐and‐forth cycle between descriptive or normative assessment and experimental manipulation is particularly important for students of early development because, as the young organism develops, its relation to the external world changes rapidly and dramatically such that the embryo’s or infant’s effective environment—the actual physical, biological, and social factors with which it interacts—also changes. Gottlieb (1977) and Miller (1981) have provided overviews of the most common experimental manipulations used in such developmental analyses, including: (a) experiential attenuation, in which features of normally occurring stimulation are withheld or removed from the embryo or infant’s

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Fig. 1. A Day 21 bobwhite quail embryo with the top of the egg shell and inner shell membranes removed. Note that the embryo’s head is positioned so that the left eye is occluded by the body and the right eye is exposed.

developmental context. This procedure is exemplified by Gottlieb’s devocalization technique to prevent duck embryos from hearing their own vocalizations during prenatal development (Gottlieb, 1978); (b) experiential enhancement, in which additional stimulative features are added to normally available stimulation, resulting in the embryo or infant receiving more overall stimulation than it would normally encounter. For example, bird embryos can be exposed to increased amounts of vestibular stimulation prior to hatching (Carlsen and Lickliter, 1999; Radell and Gottlieb,

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1992); (c) experiential rearrangement, in which normally occurring prenatal or postnatal events or experiences are reconfigured or transposed. Emlen’s (1970) work on the development of migratory orientation in several altricial bird species, in which he reconfigured aspects of the night sky in a planetarium setting, illustrates this type of procedure; (d) experiential substitution, in which normally occurring stimulation is replaced with a different form of stimulation. The use of various objects such as lights or boxes as maternal surrogates in imprinting research with precocial birds is a well‐known example of this type of manipulation; and (e) experiential displacement, in which the specific temporal relations between features of normally occurring prenatal or postnatal stimulation are shifted by providing stimulus events either forward or backward in time in relation to their usual presentation or occurrence. For example, avian embryos can be exposed to unusually early visual experience in the form of pulsed or patterned light during the period prior to hatching (Gottlieb, Tomlinson, and Radell, 1989; Lickliter, 1990a,b, 1994). These types of manipulation and the resulting evaluation of their consequences are often used in parallel with one another to unpack the complexity and contingency of early perceptual and behavioral development (e.g., Banker and Lickliter, 1993). Taken together, these manipulations provide a way to empirically access the ‘‘experience of experience’’ (West and King, 1987a,b) during the perinatal period, thereby better defining the relevant features and relationships of the structured surround with which the embryo or infant interacts. While several of these methods have been used in studies of mammalian fetuses (Smotherman, 1982; Smotherman and Robinson, 1985, 1986, 1996), they have been more widely used in studies of the prenatal origins of species‐typical behavior in precocial birds (Gottlieb, 1971a, 1997; Lickliter, 1995; Lickliter and Banker, 1994; Miller, 1997; Oppenheim, 1974; Radell and Gottlieb, 1992). For example, providing bobwhite quail (Colinus virginianus) embryos with unusually early (prenatal) visual experience in the days prior to hatching has been found to alter their subsequent auditory and visual responsiveness to a bobwhite hen after hatching (Lickliter, 1990a,b). Although the precocial avian embryo is responsive to visual stimulation during the later stages of incubation (Heaton, 1973; Ockleford and Vince, 1977; Oppenheim, 1968; Rogers, 1982), the embryo does not ordinarily experience ongoing patterned visual stimulation prior to hatching. Although diffuse light passes through the eggshell in periods when the hen is off the nest, providing some possible temporal patterning of light input to the embryo, continuing patterned visual experience is not typically available until after hatching (Rogers, 1995). Thus, unlike the other sensory systems, under normal conditions of development there is relatively little

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ongoing prenatal stimulation of the visual system. We modified this typical situation by exposing bobwhite quail embryos to a temporally patterned pulsing light for 10 min/h during the last 24–36 h of incubation (experiential enhancement and displacement). As a result of this manipulation, the stimulation histories of the auditory and visual modalities were made to coincide during the later stages of the prenatal period. Following hatching, the prenatally stimulated chicks were tested in simultaneous choice tests between auditory and visual features of a bobwhite hen versus auditory and visual features of hens of other species. Results were compared to those obtained from normal quail hatchlings, which, not receiving abnormally early visual experience, show a strong auditory preference for the bobwhite maternal call following hatching, but do not initially exhibit a preference for the visual features of the maternal hen (Lickliter and Virkar, 1989). Chicks that experienced patterned light as embryos did not exhibit an auditory preference for their species‐specific maternal call following hatching, indicating that the earlier than normal availability of visual experience altered functioning in the auditory system (Fig. 2). In addition, chicks receiving patterned visual stimulation prenatally used species‐specific visual cues to direct their social preferences as early as 24 h following hatching. In contrast, normally incubated chicks did not successfully use species‐ specific visual information until 72 hr of age. Embryonically stimulated chicks thus appeared more visually oriented than did normally incubated controls during the days following hatching. These results suggest that the absence of ongoing embryonic visual stimulation during late prenatal development is one factor underlying the persistence of responsiveness to the maternal call for some days following hatching in normally incubated embryos. This is an example, among many, of how the normal sensory ecology plays a role in species‐typical development, as will be described further. In addition, we found that chicks that received unusually early visual experience as embryos demonstrated an altered pattern of postnatal sensory dominance (Lickliter, 1994). Work with a variety of precocial animal infants (whose sensory systems are all functional at birth or hatching) has suggested a hierarchy in the functional priority of the auditory and visual systems in the period following birth or hatching, with infants initially relying on auditory over visual information to direct their early perceptual and social preferences (Gottlieb, 1971b; Johnston and Gottlieb, 1981; Lewkowicz, 1988; Lickliter and Virkar, 1989). These findings conform to what is known about the neuroembryological development of the sensory systems, in that the auditory system develops in advance of the visual system in both birds and mammals. We examined whether the initial salience of auditory information over visual information is influenced by

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Fig. 2. Premature stimulation of the later developing visual system can influence functioning of the earlier developing auditory system. In this case, embryos receiving prenatal visual stimulation failed to show species‐typical responsiveness to a bobwhite maternal call at both 24 h and 48 h following hatching (from Lickliter, 1990a).

the limitations of prenatal sensory experience, given that under normal conditions the earlier developing auditory modality has accumulated substantially more experience that the later developing visual modality. As in the previous study, we exposed embryos to a temporally patterned pulsing light for 10 min/h during the last 24–36 h of incubation, thereby altering the normal pattern of competition between the developing auditory and visual modalities. Quail chicks that received unusually early visual experience as embryos preferred maternal visual cues over maternal auditory cues by 96 h after hatching, unlike unmanipulated control chicks, which continued to prefer maternal auditory cues over visual cues at this stage of postnatal development (Lickliter, 1994). Taken together, these results suggest that the restricted visual experience of normal prenatal development contributes to hatchlings’ species‐typical pattern of perceptual organization. Adding visual experience to the prenatal milieu served to alter typical patterns of both auditory and visual responsiveness to features of the bobwhite maternal hen in the period

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following hatching. As discussed in the next section, findings from the study of precocial birds have consistently demonstrated that the features and properties of available sensory stimulation (such as amount or intensity, the timing of presentation, and the sources of stimulation) coact with specific organismic characteristics (such as the stage of organization of the sensory systems, previous history with the given properties of stimulation, and the current state of arousal of the embryo) to contribute to the developmental course of young organisms’ emerging capacity for perceptual differentiation, perceptual learning, and memory. This dynamic highlights an important insight into the process of behavioral development—the organism‐environment system is one that is structured on both sides, and developmental change results from the changing relationships between the structured organism and its structured environment (Gottlieb, 1991; Johnston and Edwards, 2002; Lerner, 1991; Lickliter, 2000a; Oyama, 1985). As a result, developmental causation cannot be viewed as residing in either the organism or the environment alone, but rather in the ongoing interactions between the developing organism and its changing environments, what Gottlieb and Halpern (2002) have termed relational causality (see also Lickliter and Honeycutt, 2003; Lerner, 1998; Oyama et. al., 2001).

III. THE DEVELOPMENTAL DYNAMICS OF THE PRENATAL SENSORY ECOLOGY OF PRECOCIAL BIRDS All sensory systems begin to develop prenatally and in precocial birds and mammals are more or less functional at birth or hatching. However, their sensory systems do not become functional at the same time in prenatal and early postnatal development (Gottlieb, 1968, 1971b). Rather, the onset of function within the various sensory modalities proceeds in a sequential pattern across birds and mammals (tactile ! vestibular ! chemical ! auditory ! visual), whether the young of a particular species are born in a precocial (with all sensory systems functional at birth) or altricial (with one or more of the later developing modalities not functional at birth) condition (Alberts, 1984; Gottlieb, 1971b). Given this invariant pattern of onset of function across the sensory modalities, each sensory system has a unique experiential history by the time of birth or hatching. For example, across birds and mammals the earlier developing tactile and vestibular systems have had a longer period of experience by the late stages of the prenatal period than has the later developing auditory system. Likewise, the auditory system has had more experience at the time of birth or hatching than has the even later developing visual system,

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Fig. 3. The sequence of prenatal sensory stimulation histories in precocial birds and mammals. Under normal conditions, the earlier developing somesthetic (tactile) and vestibular systems accrue a longer period of experience than do the later developing auditory and visual systems.

which typically receives relatively little stimulation during the prenatal period (Fig. 3). The fact that the sensory systems do not become functional at the same time in development raises the question of how the sensory systems and their respective stimulative histories influence one another, particularly during the prenatal period. Building on the pioneering work of Gottlieb (1968, 1971b, 1973), Turkewitz and Kenny (1982, 1985) proposed a novel view of early perceptual development based on their insight that the limitations arising from the sequential emergence of sensory functioning during prenatal development could provide an important organizational mechanism for the developing embryo or fetus. They argued that sensory limitations resulting from the immature state of some sensory systems during early development serve to (a) provide a reliable order and structure to prenatal and early postnatal sensory experience, (b) minimize the quantity and/or complexity of sensory experience, and (c) reduce and regulate the attentional demands placed on the developing embryo or infant (see also Turkewitz and Mellon, 1989). The structured pattern of sensory limitations is believed to regulate the competition between developing modalities for neural and attentional resources, allowing those relatively earlier‐developing sensory modalities (e.g., tactile or vestibular) to emerge under conditions of reduced competition from other later‐developing sensory modalities (e.g., auditory or visual). According to this view, altering the amount and/or timing of sensory stimulation to one modality could have significant developmental consequences on other sensory modalities. In particular, without the limited sensory functioning associated with the prenatal period, a later developing system (i.e., the visual system) could interfere with or impede earlier developing systems (i.e., olfactory or auditory systems) when the latter were still undergoing rapid development.

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Research with altricial rodents in the days and weeks following birth provided initial support for this view of the role of sensory limitations during early development (Foreman and Altaha, 1991; Kenny and Turkewitz, 1986; Symons and Tees, 1990). For example, Kenny and Turkewitz (1986) showed that rat pups that received unusually early visual experience by having their eyelids surgically opened at seven days of postnatal age (some 8 days prior to spontaneous eye opening) showed a decline in their use of olfactory cues for homing and an earlier and enhanced use of visual cues in finding their nest site location when compared to normal pups. Research with precocial birds has provided converging evidence for the strong links between the various sensory systems during prenatal and early postnatal development and their effects on perceptual organization and responsiveness (e.g., Carlsen and Lickliter, 1999; Foushee and Lickliter, 2002; Gottlieb, 1993; Gottlieb et al., 1989; Honeycutt and Lickliter, 2003; Lickliter, 1994; Lickliter and Stoumbos, 1991; Radell and Gottlieb, 1992; Sleigh and Lickliter, 1995, 1998). For example, several studies with ducklings and quail chicks have shown that providing unusually early (prenatal) temporal and spatial visual experience can alter auditory responsiveness to species‐specific maternal vocalizations in the periods before and after hatching. Gottlieb et al. (1989) found that mallard duck embryos reared in their typical prenatal developmental context (in the intact egg, with little or no patterned visual stimulation present) were capable of learning an individual mallard maternal assembly call during the days prior to hatching and that they preferred that familiar call over novel calls in the days following hatching. In contrast, embryos given unusually early visual experience by exposure to a temporally patterned pulsing light concurrently with exposure to an individual maternal call failed to prefer that familiar maternal call over a novel maternal call in the period following hatching (see Honeycutt and Lickliter, 2001; Lickliter and Hellewell, 1992 for parallel examples in bobwhite quail). Of course, under naturally occurring conditions of incubation, the developing embryo receives regular exposure to its hen’s vocalizations in the period prior to hatching, but would not receive regular exposure to concurrent patterned visual stimulation (Gottlieb, 1963). In addition to developmental sensory limitations, the structured and sequestered environment provided by the avian egg (including the inner shell membrane, yolk sac, and albumen) also serves to reduce and regulate sensory stimulation available to the developing embryo. The hard but porous eggshell is a protective barrier from various physical changes in the environment, while maintaining adequate gas exchange through the chorioallantoic membrane (Tasawa et al., 1999). The buffered nature of the developmental milieu provided by the egg (or by the uterus in mammals)

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provides additional constraints on demands for the embryo’s emerging attentional and perceptual capacities, and it can significantly influence the nature and range of sensory experience available at different stages of prenatal development. This is not to suggest that the egg provides homogeneous conditions over the course of the prenatal period. On the contrary, there are numerous sources of change and fluctuation in thermal, tactile, vestibular, auditory, and visual stimulation as the hen leaves and returns to the nest during incubation (Freeman and Vince, 1974; Rogers, 1995; Stokes, 1967). Nonetheless, relative to the postnatal environment encountered after hatching, the egg provides the developing avian embryo a relatively simplified and buffered milieu during an ontogenetic period of rapid growth and developmental change. In particular, the egg serves to regulate the amount, intensity, or pattern of sensory stimulation available to the embryo. For example, in the later stages of prenatal development, the precocial avian embryo is oriented in the egg such that its left eye and left ear are occluded by the body and yolk sac, whereas the right eye is exposed to diffuse light passing through the egg shell when the hen is off the nest during the incubation period. The differential prenatal visual experience resulting from this postural orientation prior to hatching appears to facilitate the development of the left hemisphere of the brain in advance of the right and to significantly influence the direction of hemispheric specialization for a variety of postnatal behaviors, including visual discrimination, spatial orientation, feeding behavior, and various visual and motor asymmetries (Casey and Lickliter, 1998; Casey and Martino, 2000; Rogers, 1986, 1991; Rogers and Bolden, 1991; Zappia and Rogers, 1983). The role of perinatal light stimulation on the development of visual and motor asymmetries has been extensively studied in precocial birds (e.g., Rogers, 1997; Rogers and Andrew, 2002), and it provides an important source of evidence for the neural and hormonal details of how the sensory ecology of the embryo and hatchling can influence the trajectory of perceptual and behavioral development (Deng and Rogers, 2002). Taken together, these findings suggest that the asynchronous but orderly functional emergence of the various sensory systems (tactile ! vestibular ! chemical ! auditory ! visual) in concert with the sequestered milieu of the egg combine to order and regulate the amount and the timing of prenatal input to the various sensory (and motor) systems while also reducing intersensory competition between developing sensory systems. This dynamic view emphasizes that the structure of the rapidly developing organism and the structure of its changing developmental environment together form a relationship of mutual influence on the experiential resources available (or not available) to support the emergence, maintenance, and transformation of behavior. This resulting system of resources

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and constraints provides a reliable order and organization, as well as a wide range of individual variation to the sensory ecology of young organisms and helps explain both the stability and variability of behavioral outcomes observed across members of a population.

IV. PRENATAL SENSORY ECOLOGY: SOURCES OF STABILITY VARIABILITY IN BEHAVIORAL DEVELOPMENT

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The developmental dynamics of the organism‐environment system outlined here suggest that species‐typical behavioral phenotypes are generated during individual ontogeny because particular aspects of the temporal and spatial arrangements of organisms and their contexts reliably occur at times when the organism is in particular developmental states, having had a particular developmental past (Oyama, 1985, 1993). The reliable and repeatable features of sensory stimulation occurring outside the organism (the developmental context) have been termed the ‘‘ontogenetic niche’’ by West and King (1987b), defined as the set of ecological and social circumstances inherited by members of a species. An important theme of this chapter is that this ontogenetic niche is available both prenatally and postnatally, and it provides diverse but dependable resources and influences for the developing organism. The recurrence from generation to generation of these specific resources and interactions at particular times and places is one basis for the development of species‐typical behavior (Caporael, 2003; Haraway and Maples, 1998; Kaufman, 1975; Miller, 1997; West et al., 1988, 2003). For example, findings from the study of several precocial avian species have repeatedly demonstrated that social experience with conspecifics can have a significant effect on the hatchling’s emerging species‐typical perceptual preferences and filial behavior (e.g., Blaich and Miller, 1986; Casey and Lickliter, 1996; Columbus and Lickliter, 1998; Johnston and Gottlieb, 1985; Lickliter and Gottlieb, 1985, 1988; McBride and Lickliter, 1994 Sleigh et al., 1996; see Lickliter et al., 1993 for an overview). These studies have consistently found that sensory stimulation provided by the embryo’s or hatchling’s immediate social environment (in particular, its broodmates) can dramatically influence the young bird’s species‐typical perceptual functioning during both prenatal and early postnatal periods. Bobwhite quail chicks denied interaction with broodmates during either the prenatal (Lickliter and Lewkowicz, 1995) or postnatal periods (McBride and Lickliter, 1993), or reared with quail chicks of another species (scaled quail, McBride and Lickliter, 1993) fail to prefer species‐specific maternal auditory and visual cues at ages when socially reared chicks reliably

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Fig. 4. Filial responsiveness of bobwhite quail chicks reared with conspecific bobwhite chicks or non‐conspecific scaled quail chicks following hatching. Chicks failed to demonstrate a visual preference for a bobwhite hen at 72 h following hatching when reared with scaled quail chicks (from McBride and Lickliter, 1993).

demonstrate such filial preferences (Fig. 4). Further, simply modifying the amount of tactile, auditory, or visual stimulation available from broodmates in the period immediately following hatching can delay intersensory responsiveness to maternal auditory and visual cues in quail chicks (Columbus and Lickliter, 1998). Mallard ducklings denied physical contact and interaction with broodmates following hatching likewise show altered patterns of auditory and visual responsiveness to their maternal hen (Dyer et al., 1989; Gottlieb, 1993; Miller, 1994). These types of results suggest that specific experiential features of embryos’ and chicks’ species‐typical social environment are important contributors to the realization of species‐ typical patterns of perceptual and behavioral development. Like other aspects of the developmental milieu, conspecifics are experiential resources to the developing individual and appear to facilitate the rapid perceptual, behavioral, and social adaptations required during early development. A well‐known example of this contribution comes from the observation that a variety of precocial avian chicks and ducklings respond selectively to

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the maternal assembly call of their own species in the days following hatching, even without any prior prenatal or postnatal exposure to maternal vocalizations (Allen, 1977; Gottlieb, 1971a; Heaton et al., 1978; Heinz, 1973; Ramsay, 1951). This naı¨ve species‐specific auditory preference in newly hatched chicks or ducklings is thus not dependent on prior experience with the species‐specific maternal call itself. At least in the case of mallard and wood ducks, this distinctive preference has been shown to be dependent upon prenatal exposure of the embryo to its own vocalizations or to those of its siblings in the days prior to hatching (see Gottlieb, 1997 for an overview). In the case of the mallard, the embryo requires prenatal exposure to embryonic vocalizations that contain the normal range of variations in repetition rate (2–6 notes/sec) if it is to maintain preferential responsiveness to the mallard maternal assembly call after hatching. In the case of the wood duckling, exposure to its own descending frequency‐ modulated calls is necessary for the preferential response to the wood duck maternal call. The dramatic finding that exposure to its own or sibling embryonic vocalizations is necessary for hatchlings to show a species‐ specific auditory preference for their own species’ maternal call highlights an important caveat in the study of behavior development—experiential factors that are not necessarily apparent or obvious precursors to a particular behavior may nonetheless prove to be critical contributors. Further, these non‐obvious experiential factors can be ubiquitous, in the sense that they are reliably present during particular stages of development for nearly all members of a given species. The presence of conspecifics is virtually guaranteed in the context of normal development of precocial avian embryos and hatchlings, and early interaction with and stimulation from these conspecifics seems to be essential for the normal development of species‐specific perceptual organization (see Lickliter et al., 1993 for further discussion). This account of behavioral development represents a radically different view from that assumed by traditional notions of innate, instinctive, or other internally determined characterizations of the regularities of species‐typical behavior. From this dynamic and contingent perspective, behavioral phenotypes are generated, constrained, maintained, and reorganized through the activities of an historical organism actively engaged with its surround. Rather than assuming that the expression of a given behavioral trait or skill is based on some set of internally prespecified instructions, behavioral development is seen as a self‐organizing, probabilistic process in which pattern and order emerge and change as a result of ongoing coactions among developmentally relevant components both internal (e.g., genes, hormones, neural networks) and external (e.g., diet, temperature, social interaction) to the organism. Some of these

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interactions are unique or idiosyncratic to the individual organism (organism‐specific), and many are common to nearly all members of a species (species‐specific). Both types of experiences contribute to behavioral development—in the first case promoting individual variation in behavior, and in the second case promoting the development of species‐ typical behavior. Thus, the same developmental processes result in both individual differences and inter‐individual similarities within a given population or species. In the case of precocial birds like ducks or quail, all embryos reliably receive exposure to their own and their siblings’ vocalizations after they move into the air space of the egg in the days immediately prior to hatching. This reliably present, species‐specific, prenatal auditory experience results in nearly all hatchlings preferring their own species’ maternal call over the maternal call of other species in the days following hatching, even when they have been experimentally denied exposure to maternal vocalizations (Gottlieb, 1971b; 1997; Heaton et al., 1978). Additionally, precocial avian embryos also receive regular exposure to the individual vocalizations of their own maternal hen on the nest prior to hatching. This auditory experience results in chicks preferring their own hen’s maternal assembly call over those of other hens (Gottlieb, 1988; Lickliter and Hellewell, 1992). In this case, the embryo’s prenatal auditory exposure to the specific acoustic features of its hen’s maternal call is unique to that individual embryo and its broodmates, and this results in a specific and idiosyncratic perceptual preference not seen in other members of its species (see Bailey and Ralph, 1975; Fa¨ lt, 1981, for examples from pheasants and domestic chickens). Organisms and their particular developmental contexts have both a reliable and repeatable history of interaction common to nearly all individuals of that species (species‐specific) and a unique history of interaction particular to the individual (organism‐ specific). This perspective on the various roles of experience in the development of behavior argues against dichotomous frameworks that attribute specific behavioral outcomes to separate developmental processes (i.e., innate vs. acquired; instinctive vs. learned). Instead, this perspective emphasizes the contributions of the various components and levels of the organism‐environment system and their interactions, some unique to the individual organism and some common to most members of the species, to all forms of behavioral development. Research on the relationship between physiological and behavioral effects of prenatal sensory ecology on perceptual development and learning in precocial birds provides one example of this approach. This body of work has made initial steps in specifying how internal organismic factors coact with external environmental features to

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exert particular effects on perceptual skills and preferences at particular times in development.

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Based on his work with newly hatched domestic chicks, Gray (1990) proposed that young organisms’ attention and perceptual responsiveness to sensory experience are directly influenced by their current arousal level. To evaluate the effects of prestimulus activity levels on auditory responsiveness in young chicks, Gray used chicks’ rates of vocalizations (peeping) as a measure of prestimulus activity and chicks’ delays in ongoing vocalizations as a measure of their auditory responsiveness. Results showed increased responsiveness (cessation of vocalizations) to pure tones at intermediate levels of prestimulus activity and reduced responsiveness during periods of high and low activity. Research with infant mammals, including humans, has indicated a similar relationship between arousal levels and sensitivity or attention to sensory stimulation during early development. Lewkowicz and Turkewitz (1980) found that prestimulation of human newborns with a pulse of white noise resulted in infants’ increased looking at a dimmer light and decreased looking at a brighter light. Likewise, infants exposed to auditory stimulation immediately preceding or concurrently with visual stimuli preferred less intense visual stimulation than did unstimulated control infants (Lewkowicz and Turkewitz, 1981). Gardner and Karmel (1995) found that the attentional value of specific sensory stimulation can be modified by either altering the infant’s overall arousal level or by altering the nature of available sensory experience. Full‐term and high‐risk preterm infants both preferred less stimulating visual events when highly aroused and more stimulating visual events when less aroused. This arousal‐modulated selective attention was seen both when infants are endogenously more aroused (such as before feeding) or less aroused (after feeding) as well as when they are exogenously more or less aroused due to the presence of increased or decreased amounts of sensory stimulation. This link between arousal and attention in early development likely plays an important role in the young organism’s perceptual learning and development. We recently examined this link by experimentally manipulating the prenatal physiological arousal level of bobwhite quail embryos and assessing their capacity for perceptual learning prior to hatching (Toth et al., 2004). We reasoned that if changes in normal levels of prenatal arousal

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can interfere with or modify the embryo’s ability to attend or process information present in the immediate environment, then pharmacologically altering physiological arousal during the late prenatal period should result in changes in perceptual processing and learning compared to unmanipulated controls. As a first step in evaluating this hypothesis, we injected groups of quail embryos with a single dose of norepinephrine or saline early in the last day of incubation. The adrenergic stimulant norepinephrine (NE) is known to elevate heart rate in both young birds and mammals, and preliminary dose response studies in our lab indicated that the minimum threshold dose of NE necessary to achieve a mean increase in heart rate of 60 bpm in quail embryos at 2 h following injection was 0.049 Moles. Injections of NE or saline were delivered through a small hole at the top of the egg into the back muscle of the embryo. Embryos in an additional control condition received the same egg opening and handling, but did not receive an injection. As predicted, the embryos receiving the single NE injection showed a significant increase in heart rate from baseline when compared to embryos in the saline and no‐injection conditions at 2 min following the injection and at 2 h following the injection. Following these measurements, embryos in all three conditions were exposed to an individual maternal call for 15 min/h for the last 16 h of incubation. Following hatching, chicks that received the saline injection as embryos and chicks that received no prenatal injection both showed a significant preference for the familiar bobwhite maternal call they heard prenatally over a novel bobwhite maternal call, replicating the results of earlier prenatal auditory learning studies (Honeycutt and Lickliter, 2001; Lickliter and Hellewell, 1992; Sleigh et al., 1996). In contrast, embryos that received the NE injection (resulting in sustained prenatal heart rate elevation) and the same prenatal exposure to the individual bobwhite maternal call did not show a significant preference for that familiar call in postnatal testing. The increased physiological arousal level induced by the NE appeared to interfere with embryos’ attentional or perceptual learning processes during their prenatal exposure to the maternal call, thereby limiting their ability to remember and prefer that familiar maternal call after hatching. Gottlieb (1993) argued a similar view on the important link between arousal, attention, and perception during early development. He found that by manipulating the sensory stimulation available to ducklings immediately following hatching, he could affect both their arousal levels and their ability to learn non‐conspecific maternal calls (a chicken maternal call). For example, ducklings’ learning to prefer the chicken maternal call over the mallard maternal call was significantly affected by the presence or absence

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of tactile stimulation. Mallard ducklings denied tactile stimulation from broodmates following hatching did not learn to prefer the chicken maternal call over the mallard maternal call, whereas ducklings allowed normal levels of postnatal tactile experience strongly preferred the chicken call over the mallard maternal call. These outcomes were determined by the ducklings’ level of arousal during exposure to the chicken call. Ducklings denied normal postnatal tactile experience demonstrated higher levels of behavioral arousal (as indexed by distress vocalizations and time spent awake) than did ducklings not deprived of tactile contact. Birds not permitted tactile contact slept less and were highly aroused before, during, and after playbacks of the chicken call. In contrast, socially reared ducklings slept more and were less aroused than the isolates, suggesting that elevated arousal interfered with the usual (normal) degree of malleability following hatching. Ducklings that experienced tactile contact with siblings before and after hatching were highly malleable, whereas those deprived of tactile contact were not. Similarly, Lickliter and Lewkowicz (1995) showed the importance of prenatal tactile and vestibular stimulation from broodmates to the successful emergence of species‐typical responsiveness to maternal cues in bobwhite quail chicks. In this study, quail eggs were incubated in individual opaque plastic tubs during the last 24–36 h prior to hatching. This physical isolation from other eggs in their clutch during the hatching stage of prenatal development prevented embryos from receiving the normally occurring vestibular and tactile stimulation typically provided from broodmates during the active hatching process. Following hatching, these chicks failed to show typical patterns of postnatal responsiveness to both maternal auditory and visual stimulation seen in communally incubated embryos. In addition, embryos denied normal levels of tactile and vestibular stimulation from broodmates failed to demonstrate auditory learning of an individual maternal call, a behavior reliably seen in unmanipulated, communally incubated embryos (Sleigh et al., 1996). This impairment in learning ability in the absence of tactile contact with siblings is consonant with Gottlieb’s finding discussed previously. Taken together, these results from studies of precocial avian embryos and hatchlings suggest that the species‐typical prenatal environment provides the developing embryo with an optimal range and timing of sensory stimulation, thereby supporting an effective level of arousal and attention for early perceptual learning and development (see Lickliter, 2000b; Radell and Gottlieb, 1992, for further discussion). Deviations above or below this optimal window of stimulation likely modify the embryo’s arousal level and negatively affect the young organism’s ability to attend and process available sensory information.

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VI. PRENATAL SENSORY ECOLOGY IN REAL‐TIME: THE AROUSAL/ATTENTION COMPLEX Studies examining the behavioral and physiological arousal levels associated with various types and amounts of prenatal or postnatal sensory stimulation help document the conditions under which embryos or hatchlings are able to successfully attend and process stimulation available in the prenatal environment. However, as seen in the studies briefly reviewed in this chapter, experiments designed to test hypotheses regarding the link between arousal and attention typically present subjects with altered sensory experience or altered arousal levels at one point in development, and they subsequently assess the behavioral or physiological effects of that altered experience at later points in development. Few studies have explicitly focused on how the developing organism actually responds in the presence of modified sensory stimulation, and we thus know little about the ‘‘experience’’ of experience during manipulations of the prenatal sensory ecology of the precocial avian embryo. Vocalizations, bill claps, head movements, and body movements have, however, been shown to be reliable ‘‘real‐time’’ behavioral indices of arousal level in precocial avian species, with low arousal associated with a low level of vocalizations and movement, and high arousal associated with higher levels of vocalizations and movement (Gottlieb, 1965, 1971a; Gray, 1990; Sleigh and Lickliter, 1997). In addition, measures of heart rate have also been successfully used in a number of studies of embryos’ real‐time sensitivity to sensory stimulation (e.g., Gottlieb, 1971a; Ockleford and Vince, 1977; Tolhurst and Vince, 1976). Following in this tradition, Reynolds and Lickliter (2002) explored the effects of various types of prenatal sensory stimulation on behavioral and physiological arousal in bobwhite quail embryos. Embryos’ behavioral activity was videotaped, and their heart rate was measured before, during, and after brief exposure to auditory stimulation (a bobwhite maternal call), visual stimulation (a pulsing light), concurrent intramodal stimulation (two different bobwhite maternal calls), or asynchronous bimodal stimulation (pulsed light and an individual maternal call). Concurrent asynchronous audio‐visual stimulation was found to elicit significantly higher levels of behavioral and physiological arousal when compared to all other exposure conditions. Embryos exposed to bimodal stimulation showed significant increases in behavioral activity levels during stimulus exposure, as well as significantly greater changes from baseline heart rate during stimulus exposure than all other exposure groups and controls. These arousal patterns may explain previous findings that precocial avian embryos successfully learn an individual maternal call under unimodal auditory exposure

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conditions, but not under concurrent bimodal (audio‐visual) conditions (Honeycutt and Lickliter, 2001; Lickliter and Hellewell, 1992; Radell and Gottlieb, 1992). In these studies, intersensory interference with perceptual learning occurred only when two sensory systems (auditory and visual) were stimulated concurrently. Under normal prenatal conditions, light can penetrate through the egg shell, but the shell and inner shell membrane of the egg and the regular presence of the broody hen on the nest would likely minimize embryos’ opportunity for repeated exposure to concurrent auditory and visual stimulation. Reynolds and Lickliter (2004) also showed that prenatal exposure to asynchronous audio‐visual stimulation can have sustained effects that continue into the postnatal period. Bobwhite quail chicks that received asynchronous bimodal stimulation during the late stages of incubation demonstrated significantly higher levels of behavioral activity when compared to chicks receiving no supplemental prenatal stimulation or only augmented auditory stimulation (exposure to the maternal call), and they also failed to use maternal visual cues to direct their species‐specific perceptual preferences following hatching. These results provide initial evidence that concurrent asynchronous auditory and visual stimulation during prenatal development can have enduring effects on early postnatal behavioral arousal and perceptual responsiveness, and they further support the role of developmental limitations on prenatal sensory stimulation in the emergence and maintenance of species‐typical perception and behavior. More generally, these findings from precocial avian embryos and hatchlings suggest that the attentional value of features of the prenatal sensory ecology cannot be understood simply by referring to their specific physical or quantitative attributes. Rather, consistent with Schneirla’s (1965) approach/withdrawal theory of early development, they must be considered within the broader context of the stage of development of the organism, its previous developmental history, the interaction of internal sources of stimulation with external sources of sensory stimulation, and the resultant level of organismic activity. Thus, the same stimulus can have significantly different effects on the embryo or hatchling, depending on the type and amount of concurrent sensory stimulation available and the embryo’s or hatchlings’ current state and level of arousal. As discussed in the next section, early perception, learning, and memory appear to be guided and constrained by the interaction of the young organism’s arousal and attentional systems and by their dynamic relationship to the particular stimulative features of its developmental context.

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PRENATAL SENSORY STIMULATION ON PERCEPTION, LEARNING, AND MEMORY

Learning capacities and the behaviors they generate are effective ways of adjusting and modifying the functional fit between developing organisms and their changing physical and social environments (Johnston, 1981, 1985; Lickliter, 1996). Over the last several decades, researchers have provided a wealth of evidence for the capability of embryos, fetuses, and infants to learn. We now appreciate that prenatal and early postnatal learning can significantly contribute to the progression of normal behavioral development in a wide range of birds and mammals. Progress in this area has stemmed in large part from the realization that embryos, fetuses, and infants are not miniature adults (see Bjorklund, 1997; Oppenheim, 1981, for further discussion). Rather, they have unique sensory and motor capabilities, and they develop in physical and social environments that are often markedly different from those of adults. These differences must be addressed when assessing prenatal or early postnatal learning tasks and abilities (e.g., Impekoven, 1973; Johanson and Terry, 1988; Rosenblatt, 1983; Smotherman, 1982; Spear, 1984). Given the strong link between arousal and attention during early development, and given that departures from normal or usual sensory experience during the prenatal period can influence embryos’ arousal and attention, perhaps one of the most significant effects of prenatal sensory ecology is its influence on early learning and memory abilities. Evidence from several precocial bird species indicates that the patterns of recurring sensory stimulation and experience typically present in the prenatal and early postnatal developmental milieu can guide and constrain attentional selectivity, learning, and memory during early development. For example, as briefly reviewed in previous sections, research with mallard ducks and bobwhite quail has shown that concurrent asynchronous bimodal stimulation can interfere with prenatal perceptual learning. Duck and quail embryos successfully learn an individual maternal call when it is presented unimodally (auditory only) during the days prior to hatching (Gottlieb, 1988; Lickliter and Hellewell, 1992; Radell and Gottlieb, 1992). In contrast, duck and quail embryos fail to learn an individual maternal call when it is presented concurrently (but asynchronously) with visual stimulation in the form of patterned light in the period prior to hatching (Gottlieb et al., 1989; Honeycutt and Lickliter, 2001; Lickliter and Hellewell, 1992). It was thought that the precocial avian embryo was not capable of adequately attending to simultaneous bimodal stimulation, in that the overall amount of prenatal auditory and visual stimulation appeared to effectively overwhelm the young organism’s attentional or

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learning capabilities (Radell and Gottlieb, 1992). However, more recent studies have indicated that it was not the amount of bimodal stimulation that contributed to the observed intersensory interference with perceptual learning, but rather how the bimodal stimulation was presented. Context of presentation appears to have a significant effect on attentional selectivity to the specific features of sensory stimulation and in turn on what is learned and how it is remembered. Considerable evidence for this insight is available from work on song learning in various oscine birds (e.g., Baptista and Gaunt, 1997; Johnston, 1988; Nelson, 1998; Petrinovich, 1990; Slater et al., 1988; Todt et al., 1979). For example, Hultsch et al. (1999) showed that laboratory‐reared nightingales learned more songs and were more accurate in their imitations when the tutor songs were paired with a synchronized flashing light than when the songs were presented without the redundant visual stimulus. Learning under the bimodal (auditory and visual) condition was consistently better in terms of both an increase in repertoire size and in the number of imitations that accurately matched the songs presented during tutoring (7 months earlier) when compared to the auditory only condition. In this case, redundant bimodal stimulation to the auditory and visual systems appeared to foster improved attention and selective learning in the song acquisition process. Importantly, the patterned flashes of light occurred in temporal synchrony (i.e., redundantly) with the auditory stimuli, providing bimodally specified information about the specific temporal features (i.e., rate, rhythm, duration) of the tutor song. Temporal and spatial aspects of sensory stimulation, including such properties as rhythm, tempo, duration, synchrony, and collocation, are examples of information not specific to a single sensory modality (i.e., amodal). For example, the sight and sound of hands clapping share temporal synchrony, a common tempo of action, and common rhythm. These amodal stimulus properties are specified redundantly across the auditory and visual modalities. A growing body of research from studies of both avian and mammalian infants, including humans, has shown remarkable sensitivity to such amodal stimulus properties in the days, weeks, and months following birth (e.g., Bahrick and Pickens, 1994; Kraebel and Spear, 2000; Lickliter et al., 1996; Spear and McKinzie, 1994). For example, we found that bobwhite quail are remarkably sensitive to bimodally specified temporal information even during the prenatal period (Lickliter et al., 2002, 2004). We exposed bobwhite quail embryos to an individual bobwhite maternal call for 10 min/h for 6, 12, or 24 h on the day prior to hatching, under conditions of unimodal auditory stimulation, concurrent but non‐synchronous auditory and visual stimulation, or temporally synchronous auditory and visual stimulation (Lickliter et al., 2002). In the last

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condition, redundant stimulation was provided by presenting a pulsing light that flashed in synchrony and with the temporal patterning (rhythm, rate, duration) of the notes of the maternal call. All chicks were then tested 24 h later (1 day after hatching) to determine whether they would prefer the familiar maternal call over an unfamiliar variant of the maternal call. Only chicks that received redundant audio‐visual exposure as embryos demonstrated perceptual learning under all exposure periods. They preferred the familiar maternal call following 6, 12, and 24 h of prenatal exposure, whereas chicks that received nonredundant (asynchronous) audio‐visual exposure prenatally showed no preference for the familiar call following any exposure duration. Chicks receiving the unimodal auditory familiarization prior to hatching showed perceptual learning only following the longest period (24 h) of prenatal exposure (Fig. 5). Thus, synchronous, bimodally specified information that provided intersensory redundancy for the temporal features of the call fostered auditory learning at a rate that was four times that of unimodal auditory exposure. Importantly, this dramatic facilitation of perceptual learning in embryos receiving redundant,

Fig. 5. Number of quail chicks (out of 26 in a group) preferring the familiar maternal call over a novel maternal call following 60, 120, or 240 min of exposure to a call alone, a call and light presented asynchronously, or a call and light presented synchronously (from Lickliter et al., 2002).

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bimodal information cannot be explained by a simple increase in overall amount of prenatal stimulation. Chicks that received concurrent but asynchronous audio‐visual stimulation as embryos showed no preference for the familiar call following any exposure period (Fig. 5). A subsequent study assessing memory for the familiar maternal call found that chicks receiving redundant, bimodally specified information about the temporal features of the maternal call as embryos remembered the call four times longer into postnatal development than did chicks receiving unimodal (auditory only) exposure as embryos (Lickliter et al., 2004). These results demonstrate that simultaneous exposure of the precocial avian embryo to bimodal sensory stimulation does not necessarily disrupt its limited attentional and learning processes. Further, these findings of enhanced learning and memory under conditions of bimodally specified, redundant prenatal exposure to a maternal call suggest that embryos are sensitive to amodal features of sensory stimulation. Temporally based amodal properties like rate, rhythm, and duration are redundant across synchronous auditory and visual stimulation and they appear to receive greater selective attention and perceptual processing than other stimulative features of the embryo’s or infant’s immediate sensory ecology (see Bahrick et al., 2004 for further discussion and evidence from human infants). As pointed out by Rogers (1995), the conditions provided by natural incubation can provide the developing avian embryo multiple sensory inputs at the same time. As the hen stands up from the nest to turn the eggs of her clutch, she causes simultaneous stimulation of the tactile, vestibular, proprioceptive, auditory (and to some extent the visual) systems of the embryo. These bouts of multimodal exposure can also be initiated by the embryo. For example, a study by Tuculescu and Griswold (1983) found that the production of distress calls by the domestic chick embryo elicits egg turning and vocalizations by the maternal hen. Functioning tactile, vestibular, and auditory modalities are clearly interacting during the late stages of prenatal development in precocial avian species (e.g., Carlsen and Lickliter, 1999; Honeycutt and Lickliter, 2003), and the onset of visual experience at hatching significantly increases opportunities for multimodal stimulation during the postnatal period (Banker and Lickliter, 1993; Sleigh et al., 1998). The gaps in our understanding of the nature of these early sensory interactions and their implications for subsequent perceptual and behavioral development are large and provide a wealth of opportunities for future research. In this light, of particular interest is the finding from a number of neurophysiological studies that the temporal and spatial pairing of stimuli from different sensory modalities can elicit a neural response in the superior colliculus that is greater than the sum of the neural responses to the

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unimodal components of stimulation considered separately, the so‐called ‘‘multiplicative’’ or ‘‘super‐additive effect’’ (Stein and Meredith, 1993; Stein et al., 1994). In other words, the activity of a neuron exposed to redundant multisensory stimulation (i.e., simultaneous auditory and visual stimulation) differs significantly from the activity of the same cell when exposed to stimulation in any single modality (Meredith and Stein, 1986). Spatially coordinated and temporally synchronous multimodal stimulus combinations have been shown to produce significant increases over unimodal responses in several extracellular measures of neural activity, including response reliability, number of impulses evoked, and peak impulse frequency. This super‐additive effect of bimodal stimulation, in which the magnitude of neural effects resulting from bimodal stimulation consistently exceeds the level predicted by adding together responsiveness to each single‐modality stimulus alone (i.e., neural enhancement) has also been reported in behavioral investigations. For example, Stein et al., (1989) demonstrated that the effectiveness of a visual stimulus in eliciting attentive and orientation behaviors in cats is dramatically affected by the presence of a temporally congruent and spatially collocated stimulus in the auditory modality. These findings provide further support for the notion that spatially and temporally coordinated multimodal stimulation is highly salient at the levels of neural and behavioral responsiveness. How this stimulation is presented across multiple senses is, however, crucial for its facilitative or interfering effects during early development. For example, audible and visible stimulation must be temporally aligned (synchronous) for intersensory redundancy to be effective in facilitating selective attention and perceptual learning prior to hatching (Lickliter et al., 2002). Asynchronous presentations of the same auditory and visual stimulation result in interference with prenatal perceptual learning (Gottlieb et al., 1989; Honeycutt and Lickliter, 2001), even though the overall amount of available sensory stimulation was constant across these two conditions. These contrasting results highlight the range and richness of sensory stimulation present, even in the relatively buffered milieu of the avian egg. The ecological psychologist J. J. Gibson (1979) argued for an approach to the study of perception in which the researcher is concerned with the specific structure of the environment, with how the organism moves about in it, and with what sorts of perceptual information the environment provides the perceiving organism. From this view, all organisms come to find out about the world through their actual encounters with the world (Taylor and Haila, 2001). Because perceptual and behavioral development depends on these encounters and experiences (often in non‐obvious ways), the task of defining the relevant developmental resources made available

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by the sensory ecology of young organisms becomes an essential step in any systematic analysis of perception or behavior. Phenotypic development depends on exposure to or interaction with particular features of the environment, and research with precocial avian species provides multiple examples of how normally occurring prenatal sensory experience can play an important role in the development of behavior, both before and after hatching.

VIII. THE DIVIDENDS OF AN ECOLOGICAL/DEVELOPMENTAL SYSTEMS PERSPECTIVE Empirical findings from a wide range of species and a number of disciplines have now converged to remind us that development cannot be represented as the unfolding of a fixed or predetermined substrate, independent of the activity, experience, or context of the individual. For example, the environment of development has been shown to determine the sexual phenotype in some species of reptiles and fish, to induce specific morphological changes that allow individuals to escape predation in several amphibian species, and to bring on caste determination in a number of species of insects (see Gilbert, 2001 for discussion and additional examples). This focus on the ecological contribution to the generation of phenotypes undermines any meaningful separation between genetic and environmental sources of information for development, a framework still common in some disciplines within the behavioral sciences. Recent advances in genomics, developmental biology, and related fields have combined to demonstrate that development cannot be effectively characterized as the result of the summation of genetic and environmental factors; rather, development results from the dynamic interaction of genes, cells, tissues, organs, and organisms during the course of individual ontogeny (Johnston and Edwards, 2002; Lickliter and Honeycutt, 2003). Much of the conceptual foundation for this explicitly developmental view has come from a family of related approaches to development and evolution (e.g., Ford and Lerner, 1992; Griffiths and Gray, 1994; Oyama, 1985; Richardson, 1998; Robert, 2004) collectively referred to as developmental systems theory (DST). DST is perhaps best known for its cogent critiques of simple genetic or environmental determinism (Oyama et al., 2001). In particular, DST rejects the assumption of any vital force that oversees or controls development and also argues against any prespecification of phenotypic traits or characters. Instead, development is characterized as a situated, self‐organizing, probabilistic process where pattern and order emerge and change, as a

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Fig. 6. Phenotypic development results from the changing relationships between a structured organism (genes, hormones, neural systems) and a structured environment (physical, biological, social milieus).

result of complex interactions and relationships among developmentally relevant resources both internal (including genes, but also cells, hormones, organs) and external to the organism (and not from some set of prespecified instructions) (Fig. 6). A developmental systems perspective thus rejects the assumption that genes are the sole source of developmental information transmitted across generations and in its place promotes an expanded view of inheritance. From this perspective, what is inherited across generations is a structured developmental system that includes components internal (e.g., genes, cytoplasm) and external (e.g., diet, conspecifics) to the organism (see Gottlieb, 1997, 2002; Oyama, 1985; West and King, 1987b). In other words, what offspring inherit from parents is not simply genes, but a host of reliable and repeatable developmental resources. The structure and interactions among the physical and social components of an organism’s developmental system are as causally informative to the development and transmission of phenotypic traits as are the strands of DNA contained within this system. As a result, definitions of inheritance that do not include components of the developmental system that are replicated in each generation and which play a role in the production of the life cycle of the organism are certain to be less than complete (Gray, 1992). The expanded view of heredity promoted by developmental systems theory recognizes that there are many genetic and extragenetic influences to which young organisms are exposed during their prenatal and postnatal development that contribute to phenotypic regularity across generations. The various studies and their findings reviewed in this chapter serve to highlight this point by demonstrating examples of the dynamic, historical, and contingent processes (involving both endogenous and exogenous features) which give rise to early perceptual and behavioral development in precocial birds. In particular, the studies reviewed here reveal the

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nonarbitrary connection between the developing organism’s species‐typical surroundings and the generation of species‐typical behavior during early development. By characterizing not only the genes but also the stimulative developmental context as providing the necessary elements for behavioral development, the organism‐context interaction process becomes an explicit focus of study, thereby including a large class of extragenetic variables that have often been omitted from explanations of species‐typical behavior. This is not a new insight. Writing over 35 years ago, King (1968) noted that ‘‘individuals of a species are usually raised by parents of the same species in the environment which has been occupied by that species for many generations. This continuity of early experience from one generation to the next envelopes the young of each species in an environment as characteristic of the species as its genotype.’’ The study of behavior still has much to gain from this insight, and a continued empirical focus on the dynamics of the organism‐environment relationship will undoubtedly provide a deeper appreciation of the roles of normally occurring sensory stimulation to perceptual and behavioral development across a wide array of avian and mammalian species.

IX. SUMMARY Development always takes place in some ‘‘experiential’’ context, where experience is defined broadly to include the various stimulative aspects to which individuals are subject during prenatal and postnatal life. Approaching behavioral development as a system property that is generated in context, rather than expressed from an innate or predetermined template, fosters a more focused concern with the ecology of development—the immediate or proximate properties of the organism’s niche that guide, facilitate, maintain, or constrain behavior. All phenotypic development depends on exposure to or interaction with particular features of the organism’s developmental ecology, and research with precocial avian species has provided multiple examples of how normally occurring prenatal sensory experience can play an important role in the development of behavior before and after hatching. Reliable and repeatable features of sensory stimulation are available both prenatally and postnatally, and they provide diverse but dependable resources and influences for the developing embryo and hatchling. Evidence from work with precocial birds indicates that these specific resources, interactions, and constraints at particular times and places (the developmental ecology) are a vital feature in the realization of species‐typical behavior. Further, findings from the study of chicken, duck, and quail embryos and hatchlings demonstrate that the

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features and properties of available prenatal sensory stimulation (such as amount or intensity, the timing of presentation, and the sources of stimulation) interact with specific organismic characteristics (such as the stage of organization of the sensory systems, previous history with the given properties of stimulation, and the current state of arousal of the embryo) to contribute to the developmental course of young organisms’ emerging capacity for perceptual differentiation, perceptual learning, and memory. Exploring the specific contributions of prenatal ecology and experience to perception and behavior highlights the point that the young organism’s context or environment cannot be viewed as merely a permissive or triggering factor in the developmental process; rather, the specific physical, biological, and social environments within which the individual organism develops provide essential contributions to the achievement of its varied phenotypic outcomes.

Acknowledgments The writing of this chapter was supported in part by NIMH grant RO1 MH62225. I thank Gilbert Gottlieb for his many years of inspiration and friendship; the large group of dedicated graduate and undergraduate students whom I have had the good fortune to work with and who contributed to many of the studies discussed in this chapter; and Gilbert Gottlieb, Charles Snowdon, Philip Stoddard, and an anonymous reviewer for their constructive comments on an earlier version of this chapter.

References Alberts, J. R. (1984). Sensory‐perceptual development in the Norway rat: A view towards comparative studies. In ‘‘Comparative Perspectives on Memory Development’’ (R. Kail and N. S. Spear, Eds.), pp. 65–101. Erlbaum, Hillsdale, NJ. Alberts, J. R., and Cramer, C. P. (1988). Ecology and experience: Sources of means and meaning of developmental change. In ‘‘Handbook of Behavioral Neurobiology, Vol. 9, Developmental Psychobiology and Behavioral Ecology’’ (E. M. Blass, Ed.), pp. 1–39. Plenum Press, New York. Allen, H. M. (1977). The response of willow grouse chicks to auditory stimuli. 1. Preference for hen grouse calls. Behav. Process. 2, 27–32. Bahrick, L. E., Lickliter, R., and Flom, R. (2004). Intersensory redundancy guides infants’ selective attention, perceptual, and cognitive development. Curr. Dir. Psychol. Sci. 13, 99–102. Bahrick, L. E., and Pickens, J. (1994). Amodal relations: The basis for intermodal perception and learning in infancy. In ‘‘The Development of Intersensory Perception: Comparative Perspectives’’ (D. J. Lewkowicz and R. Lickliter, Eds.), pp. 205–233. Erlbaum, Hillsdale, NJ. Bailey, E. D., and Ralph, K. M. (1975). The effects of embryonic exposure to pheasant vocalizations in later call identification by chicks. Can. J. Zool. 53, 1028–1034.

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Turkewitz, G., and Kenny, P. A. (1985). The role of developmental limitations of sensory input on sensory/perceptual organization. J. Dev. Behav. Pediatr. 6, 302–306. Turkewitz, G., and Mellon, R. C. (1989). Dynamic organization of intersensory function. Can. J. Psychol. 43, 286–301. van der Weele, C. (1999). ‘‘Images of Development: Environmental Causes of Ontogeny.’’ State University of New York Press, Albany, NY. Vince, M. A. (1972). Communication between quail embryos and the synchronization of hatching. P XV Int. Ornitholog. Cong. 357–362. Vince, M. A. (1973). Some environmental effects on the activity and development of the avian embryo. In ‘‘Behavioral Embryology’’ (G. Gottlieb, Ed.), pp. 285–323. Academic, New York. Vince, M. A. (1980). The posthatching consequences of prehatching stimulation: Changes with amount of prehatching and posthatching exposure. Behav. 75, 36–53. West, M. J., and King, A. P. (1987a). Coming to terms with the everyday language of comparative psychology. In ‘‘Comparative Perspectives in Modern Psychology, Vol. 35, Nebraska Symposium on Motivation’’ (D. W. Leger, Ed.), pp. 51–89. University of Nebraska Press, Lincoln, NE. West, M. J., and King, A. P. (1987b). Settling nature and nurture into an ontogenetic niche. Dev. Psychobiol. 20, 549–562. West, M. J., and King, A. P. (1996). Eco‐gen‐actics: A systems approach to the ontogeny of avian communication. In ‘‘The Evolution and Ecology of Acoustic Communication in Birds’’ (D. Kroodsma and E. H. Miller, Eds.), pp. 2–38. Cornell University Press, Ithica, NY. West, M. J., King, A. P., and Arberg, A. A. (1988). The inheritance of niches: The role of ecological legacies in ontogeny. In ‘‘Handbook of Behavioral Neurobiology, Vol. 9, Developmental Psychobiology and Behavioral Ecology’’ (E. M. Blass, Ed.), pp. 41–62. Plenum, New York. West, M. J., King, A. P., and White, D. J. (2003). The case for developmental ecology. Anim. Behav. 66, 617–622. White, D. J., King, A. P., Cole, A., and West, M. J. (2002). Opening the social gateway: Early vocal and social sensitivities in brown‐headed cowbirds (Molothrus ater). Ethology 108, 23–37. Zappia, J. V., and Rogers, L. J. (1983). Light experience during development affects asymmetry of forebrain function in chickens. Dev. Brain. Res. 11, 93–106.

ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

Conflict and Cooperation in Wild Chimpanzees Martin N. Muller* and John C. Mitani{ *department of anthropology boston university boston, massachusetts, 02215, usa { department of anthropology university of michigan ann arbor, michigan, 48109, usa

I. INTRODUCTION The twin themes of competition and cooperation have been the focus of many studies in animal behavior (Alcock, 2001; Dugatkin, 2004; Krebs and Davies, 1997). Competition receives prominent attention because it forms the basis for the unifying, organizing principle of biology. Darwin’s (1859) theory of natural selection furnishes a powerful framework to understand the origin and maintenance of organic and behavioral diversity. Because the process of natural selection depends on reproductive competition, aggression, dominance, and competition for mates serve as important foci of ethological research. In contrast, cooperation in animals is less easily explained within a Darwinian framework. Why do animals cooperate and behave in ways that benefit others? Supplements to the theory of natural selection in the form of kin selection, reciprocal altruism, and mutualism provide mechanisms that transform the study of cooperative behavior in animals into a mode of inquiry compatible with our current understanding of the evolutionary process (Clutton‐Brock, 2002; Hamilton, 1964; Trivers, 1971). If cooperation can be analyzed via natural selection operating on individuals, a new way to conceptualize the process emerges. Instead of viewing cooperation as distinct from competition, it becomes productive to regard them together. Students of animal behavior have long recognized that an artificial dichotomy may exist insofar as animals frequently cooperate to compete with conspecifics. In taxa as diverse as insects, birds, and mammals, animals cooperate to obtain immediate or deferred fitness benefits. 275 0065-3454/05 $35.00 DOI: 10.1016/S0065-3454(05)35007-8

Copyright 2005, Elsevier Inc. All rights reserved.

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Well‐known examples include sterile castes of eusocial insects and cooperatively breeding birds and mammals (Koenig and Dickinson, 2004; Solomon and French, 1997; Wilson, 1971). In these cases, individuals cooperate with others and forego reproduction to gain direct or indirect fitness payoffs. Chimpanzees and their behavior have been well studied in the wild. As one of our closest living relatives, chimpanzees generate considerable interest, given the insights they can provide to understanding human behavioral evolution (e.g., Moore, 1996; Wilson and Wrangham, 2003; Wrangham, 1999; Wrangham and Pilbeam, 2001). Chimpanzees also furnish a model system to investigate the manner in which animals compete and cooperate. Pioneering field research by Jane Goodall (Goodall et al., 1979; Goodall, 1968) and Toshisada Nishida (Kawanaka and Nishida, 1975; Nishida, 1983; Nishida and Kawanaka, 1972) demonstrated that conflict plays a significant role in chimpanzee social relations, both within and between communities. Male chimpanzees compete for dominance status within communities and engage in lethal aggression between communities. Early observations of wild chimpanzees also highlighted their cooperative nature. Male chimpanzees spend a substantial amount of time grooming each other (Simpson, 1973) and form both short‐term coalitions and long‐term alliances that have important fitness consequences (Nishida, 1983; Riss and Goodall, 1977). Considerable field research, totaling more than 180 years at seven sites, has been undertaken since Goodall and Nishida initiated their seminal studies (Table I). As a result of new and continuing research, we now possess a rich body of information regarding competition and cooperation in chimpanzee society. Recent observations of aggressive behavior within and between communities are changing our views of the functional significance of chimpanzee aggression. Behavioral endocrinological studies are providing new insights into the physiological mechanisms underlying competitive relationships. New field observations are revealing unsuspected complexity in cooperative behavior, with chimpanzees reciprocally exchanging commodities that are both similar and different in kind. Finally, genetic data are being employed to explore the evolutionary mechanisms that might account for cooperation in chimpanzees. In this chapter, we review our current knowledge of competition and cooperation in wild chimpanzees. We focus explicitly on recent field studies that shed new light on how chimpanzees compete, cooperate, and cooperate to compete. For part of this review, we rely on the results of our own research that bear on competition and cooperation. We make no attempt to summarize the extensive literature on the behavior of captive chimpanzees, as excellent reviews of this work can be found elsewhere (e.g., de Waal, 1998). We begin by outlining the social, demographic, and ecological contexts within which wild chimpanzees compete and cooperate.

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TABLE I LONG‐TERM CHIMPANZEE FIELD STUDIES Location Budongo Forest Reserve, Uganda Bossou,Guinea Gombe National Park, Tanzania Kibale National Park, Uganda Kibale National Park, Uganda Mahale Mountains National Park, Tanzania Taı¨ National Park, Ivory Coast

Community

Duration of study

Reference

Sonso

1990–present

Reynolds, 1992

Bossou Kasakela and Kahama Kanyawara

1976–present 1960–present

Sugiyama, 2004 Goodall, 1986

1987–present

Wrangham et al., 1996

Ngogo

1995–present

Mitani et al., 2002b

Kajabala and Mimikiri

1965–present

Nishida, 1990

North

1979–present

Boesch and Boesch‐ Achermann, 2000

II. CHIMPANZEE SOCIETY, DEMOGRAPHY,

AND

ECOLOGY

Chimpanzees live in fission‐fusion communities that vary considerably in size, ranging from 20 to 150 individuals (Boesch and Boesch‐Achermann, 2000; Goodall, 1986; Nishida, 1968; Nishida et al., 2003; Sugiyama, 2004). Within communities, chimpanzees form temporary subgroups or parties that fluctuate in size, composition, and duration. Parties include 4–10 individuals on average, and usually contain more males than females (Boesch, 1996; Chapman et al., 1995; Matsumoto‐Oda et al., 1998; Mitani et al., 2002a; Newton‐Fisher et al., 2000; Sakura, 1994; Wrangham, 2000). Membership in chimpanzee communities is open due to dispersal. Female chimpanzees, typically, but not always, disperse from their natal groups after reaching sexual maturity at an age of about 11 years (Boesch and Boesch‐Achermann, 2000; Nishida et al., 2003; Sugiyama, 2004; Williams et al., 2002b). In contrast, males are philopatric and remain on their natal territories for life. After dispersing, and following a 2‐ to 3‐year period of adolescent subfecundity, female chimpanzees begin to reproduce, with an average interbirth interval of 5 to 6 years for offspring who survive to weaning (Boesch and Boesch‐Achermann, 2000; Nishida et al., 2003; Sugiyama, 2004; Wallis, 1997). Chimpanzees feed principally on ripe fruit, although at most sites they also consume insects and hunt vertebrate prey (Newton‐Fisher, 1999a; Nishida and Uehara, 1983; Wrangham, 1977; Wrangham et al., 1998; Yamakoshi, 1998). As large‐bodied frugivores (female median weight at

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Gombe ¼ 31 kg; Pusey et al., 2005), chimpanzees move over extensive areas in search of seasonally scarce fruit resources. Territory sizes average between 5–30 km2 depending on habitat type and quality (Chapman and Wrangham, 1993; Hasegawa, 1990; Herbinger et al., 2001; Lehmann and Boesch, 2003; Newton‐Fisher, 2003; Williams et al., 2002b). Male chimpanzees defend their territories vigorously against neighbors (Boesch and Boesch‐Achermann, 2000; Goodall et al., 1979; Watts and Mitani, 2001; Williams et al., 2004). Intercommunity interactions are extremely hostile and occasionally result in fatalities (Wilson and Wrangham, 2003; Wrangham, 1999). This social, demographic, and ecological setting forms the background for investigating conflict and cooperation in chimpanzees. Competition for scarce fruit resources sets the stage for conflict between female chimpanzees. Long birth intervals produce a skewed operational sex ratio, leading to intense male‐male competition. Territoriality adds conflict between communities to the already high levels that exist within communities. Despite the labile nature of chimpanzee parties, male chimpanzees are typically more social than females (Boesch, 1996; Halperin, 1979; Newton‐Fisher, 1999b; Nishida, 1968; Pepper et al., 1999; Sakura, 1994; Wrangham, 2000; Wrangham et al., 1992). Male sociality predisposes them to affiliate and cooperate in several behavioral contexts. As noted previously, male chimpanzees spend considerable time grooming each other and are well known for forming short‐term coalitions in which two individuals join forces to direct aggression toward third parties. Males also hunt together, share meat, develop long‐term alliances to improve their dominance rank, and communally defend their territories during boundary patrols. In what follows, we will show that cooperation and competition are inexorably intertwined in the lives of chimpanzees, and that attempts to characterize their behavior as either one or the other are neither valid nor useful. Competition nevertheless frequently represents the driving force behind chimpanzee cooperation. We therefore consider patterns of conflict between chimpanzees before turning to the manner in which they cooperate.

III. CONFLICT Wild chimpanzees can spend hours resting and grooming peacefully in mixed social groups, and affiliative interactions among them are frequent and varied. Nevertheless, conflict over food, females, and dominance status

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is a regular occurrence in chimpanzee society, and this can lead to intense aggression both within and between groups. Data on rates of aggression in chimpanzees are surprisingly rare, given the behavior’s conspicuous expression and years of systematic observation in the wild. However, clear sex differences have emerged from long‐term research. First, males are aggressive much more frequently than females (Bygott, 1979; Goodall, 1986; Muller, 2002). Second, males employ aggression in different contexts than females. Most female aggression is related to competition over food or defense of offspring, whereas male aggression tends to result from competition over dominance status (Goodall, 1986; Muller, 2002; Nishida, 1989; Wittig and Boesch, 2003a). Males are also aggressive to individuals from neighboring communities in the context of territorial defense. The most forceful displays of chimpanzee aggression occur during intercommunity encounters, as males sometimes cooperate to inflict lethal wounds on strangers. Although females occasionally accompany males on territorial patrols, they do not generally play an active role in such encounters (Goodall, 1986; Nishida, 1979; Watts et al., in press). An exception to this is at Taı¨, where females frequently join in aggressive calls directed at neighbors, but nonetheless refrain from participating in physical attacks (Boesch, 2003; Boesch and Boesch‐Achermann, 2000). Sex differences in chimpanzee aggression are best understood with reference to the different factors that affect male and female reproduction. Female reproduction is limited primarily by environmental resources such as food, whereas male reproduction is limited primarily by access to females (Bradbury and Vehrencamp, 1977; Emlen and Oring, 1977; Trivers, 1972). Patterns of aggression, their proximate mechanisms, and their relationships to underlying reproductive strategies, are discussed in detail in following sections. We consider males first because aggression between them is currently better understood. A. WITHIN‐GROUP COMPETITION AMONG MALES Chimpanzees exhibit an extreme female bias in parental investment and pronounced male skews in the operational sex ratio and potential reproductive rate. Consequently, sexual selection theory predicts that mating competition among males should be relatively intense (Clutton‐ Brock and Parker, 1992; Trivers, 1972). Observations from long‐term field studies are consistent with this prediction, as males compete aggressively for both dominance status and access to sexually receptive females (Muller, 2002).

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1. Male Status Competition Male chimpanzees are famously preoccupied with rank, and chimpanzee society neatly fits Vehrencamp’s (1983) criteria for despotism (Boehm, 1999). Accordingly, status rivalry among males is prominent and observable, mitigating the problems associated with conceptualizing dominance systems in some species (e.g., Fedigan, 1983; Drews, 1993). For example, chimpanzees have a distinct vocalization, the pant‐grunt, which functions as a formal signal of subordinance (Bygott, 1979; Goodall, 1986; Hayaki et al., 1989). Pant‐grunt orientation has repeatedly been shown to correlate with a range of aggressive and submissive interactions (Boesch and Boesch‐ Achermann, 2000; Bygott, 1979; Hayaki et al., 1989; Nishida and Hosaka, 1996). Within communities, alpha males are normally easy to identify, and it is often possible to rank all males in a linear hierarchy (Goodall, 1986; Newton‐Fisher, 2004; Nishida, 1979; Wittig and Boesch, 2003a). When insufficient dyadic interactions have been observed to produce a linear hierarchy, males can be assigned to dominance levels ( i.e., alpha, high, middle, or low) (Bygott, 1979; Watts, 1998). Males regularly perform elaborate agonistic displays to intimidate conspecifics, and thereby maintain or challenge the existing dominance hierarchy. These displays involve exaggerated locomotion, piloerection, and a combination of vigorous branch swaying, branch dragging, rock throwing, ground slapping, and stomping; they can persist for a few seconds to several minutes. Dominance reversals are regularly preceded by a period of heightened aggression and increased rates of display by one or both males in the dyad (Goodall, 1986). Reversals are frequently the result of dyadic fights, but coalitions can also play a critical role in challenges to status (see Section IV.A). High rank is normally associated with increased aggression among male chimpanzees, even within stable dominance hierarchies (Muller, 2002). This relationship has been quantified in several ways. High‐ranking males have been found to exhibit higher rates of agonistic display (Boesch and Boesch‐Achermann, 2000; Bygott, 1979; Muller and Wrangham, 2004a), to employ escalated forms of aggression more often (Muller and Wrangham, 2004a; Wittig and Boesch, 2003a), and to initiate aggression more frequently (Nishida and Hosaka, 1996; Wittig and Boesch, 2003a) than lower‐ranking conspecifics. High‐ranking males also tend to win the aggressive interactions that they initiate (Muller and Wrangham, 2004b; Wittig and Boesch, 2003a). Among primates generally, high rank is most often associated with aggression in unstable hierarchies when the status of high‐ranking males is threatened (Sapolsky, 1992). The frequent positive association between rank and aggression in chimpanzee males suggests that their hierarchies are

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perpetually unstable in comparison to other primates, with more or less continuous status challenges. Muller (2002) suggested that two characteristics of chimpanzee society might account for this phenomenon: fission‐ fusion sociality, and the frequent use of coalitionary aggression. Because chimpanzee parties frequently break apart and come together, males may not see each other for hours, days, or weeks. It follows that high‐ranking males should find it difficult to closely monitor the social relationships of other community members. Because coalitions are important to males in maintaining and improving their status (see Section IV.A), and because coalitions are fluid, with males showing high degrees of ‘‘allegiance fickleness’’ (Newton‐Fisher, 2002; Nishida, 1983), a level of uncertainty is expected in male status relationships that necessitates frequent aggression to reassert dominance (Muller and Wrangham, 2001, 2004a). Despite the difficulties of maintaining high rank in chimpanzee society, males are regularly able to maintain the alpha position for years at a time, through skillful social manipulation (Boesch and Boesch‐Achermann, 2000; Goodall, 1986). Ntologi, for example, was the alpha male at Mahale for more than 15 years (Uehara et al., 1994). Imoso, the current alpha male at Kanyawara, has held his position for more than seven years. Maintaining rank, however, is a costly exercise. The performance of agonistic displays and maintenance of social alliances both demand significant investments of time, energy, and valuable resources such as meat (Mitani and Watts, 2001; Nishida et al., 1992). They also incur significant physiological costs, which include elevated levels of the steroid hormones testosterone and cortisol (Muller and Wrangham, 2004a,b). Finally, dominance‐related agonistic interactions frequently lead to injury, and they can result in potentially lethal wounds (Fawcett and Muhumuza, 2000; Goodall, 1992; Nishida, 1996; Nishida et al., 1995; Watts, 2004). 2. The Benefits of Status The substantial costs associated with status striving in chimpanzees imply the existence of compensatory benefits. High rank could theoretically confer a survival advantage through enhanced access to resources, an indirect reproductive advantage via kin selection, or a direct reproductive benefit through greater access to cycling females (Muller and Wrangham, 2001). Direct reproductive benefits of male dominance have received the most attention in the primate literature (e.g., Cowlishaw and Dunbar, 1991), as they will here. We first consider other possibilities. a. Increased survival Preferential access to resources could theoretically provide a survival advantage to high‐ranking males. Goodall (1986) argued that such an advantage would likely be minor because, when food is scarce,

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chimpanzees predictably fragment into small parties or travel alone. Long‐ term data on weights of individuals from Gombe, however, suggest an advantage to male rank; dominant individuals there show less variance in weight across seasons than subordinates (Pusey et al., 2005). This indicates that contest competition over food is potentially important among males (Pusey et al., 1995). The specific mechanism, however, remains unclear. Dominant males do tend to occupy prime feeding sites (Goodall, 1986), and may also monopolize high‐quality foods such as meat. At Gombe and Ngogo, for example, dominants are more likely than subordinates to steal carcasses from other males, though outright theft of meat is still rare among adult males (Goodall, 1986; Mitani and Watts, 1999). Quantifying the effects of contest competition over food, however, has proven difficult. Recent work by Houle (2004) documenting predictable within‐tree variation in fruit quality suggests a possible way forward in this regard. Houle showed that because the availability of light is higher in the upper canopy than the lower canopy, fruits in the former are larger, more abundant, and higher in sugar content than fruits in the latter. Behavioral observations across four frugivorous primate species in Kibale confirm that dominant species and dominant individuals within species tend to monopolize the upper part of the canopy, presumably gaining feeding benefits. Kahlenberg (unpublished data) has recently studied the relationship between rank and feeding height in chimpanzees at Kanyawara, Kibale National Park. She found that high‐ranking males consistently fed higher in the canopy than low‐ranking males when co‐feeding in trees. There were no rank‐related differences in height when males were in trees but not feeding, however. Furthermore, in cases where males were observed fighting over food, losers predictably fed lower in the canopy or left the tree altogether after the aggressive interaction. These data suggest a role for contest competition within fruiting trees, but more work is necessary to quantify rank‐related differences in actual caloric intake over time. Work is currently in progress on this topic at the Kanyawara study site. Even if high‐ranking males do gain advantages in intragroup feeding competition, it is not certain that this translates into a direct survival advantage. The physiological costs associated with maintaining high rank might still outweigh any benefits of increased food. Long‐term data on mortality rates across high‐ and low‐ranking males could eventually settle this issue. b. Indirect reproductive advantage Little is known about the potential kin‐selected benefits of male rank. Evidence from Gombe suggests that female rank has significant effects on reproduction, through increased infant survivorship and decreased interbirth intervals (Pusey et al., 1997).

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The possibility that a male’s status can influence the dominance standing of his mother or brothers, however, remains unexplored. Since most females transfer from their natal community during adolescence, males would not normally be expected to influence the rank of their sisters. c. Direct reproductive advantage Altmann’s (1962) ‘‘priority of access’’ model proposes that across primates, dominance rank and reproductive success should be positively correlated because high‐ranking males monopolize matings with estrous females. Historically, tests of the model have employed indirect measures of reproductive success, such as copulation frequency, that may or may not reflect actual paternity (Fedigan, 1983). More recently, advances in extracting, amplifying, and sequencing DNA from non invasively collected samples have facilitated direct assessment of male reproductive success in wild chimpanzees (Constable et al., 2001; Vigilant et al., 2001). Behavioral assessment of chimpanzee paternity is complicated by the fact that mating takes place in three distinct contexts (Tutin, 1979). Opportunistic mating occurs in multi‐male parties with no male herding or coercion. Possessive mating is characterized by male attempts to gain exclusive access to a female by directing aggression at both her and rival males. In a consortship, a male restricts access to a female by accompanying her to a peripheral part of the territory for several days to more than a month. Goodall (1986) argued that rank should not be expected to show a strong relationship with reproductive success in male chimpanzees because low‐ ranking males have ample mating opportunities in the opportunistic and consortship contexts. She further hypothesized that the intense drive for status that characterizes male chimpanzees must have evolved in a different social context from the one that chimpanzees currently find themselves in (Goodall, 1986). Long‐term observations, however, indicate that, despite variation in the frequency of consortships across study sites, this is never the predominant male strategy (Muller and Wrangham, 2001). Gombe falls at one end of the distribution, with an estimated 25% of conceptions resulting from consortships (Wallis, 1997). At the other extreme, only one clear consortship has been recorded in more than 15 years of observation at Kanyawara (Wrangham, 2002). Consortships have been estimated to account for between 8–20% of conceptions at Mahale (Hasegawa and Hiraiwa‐ Hasegawa, 1990), and around 6% at Taı¨ (Boesch and Boesch‐Achermann, 2000). Why the number of consortships at Gombe appears to be higher than at other sites is not currently known, but it may be related to the low rate of female transfer recorded there (Constable et al., 2001). Constable and

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colleagues (2001) noted that Gombe females often consorted with low‐ ranking males when they had high‐ranking male relatives in the community. This, together with the fact that males sometimes attempt to force copulations with their unwilling mothers or sisters, suggests that consortships with low‐ranking males may be a female strategy to avoid inbreeding. Most conceptions result from mating in multi‐male parties. At first glance, observations of such parties do not strongly support the priority of access model. For when total copulation rate is plotted against male rank, the results are inconsistent, even within study sites across time. Most studies find no significant relationship between dominance rank and total copulation rate (Gombe: 1972–1975; Tutin, 1979; Mahale: 1980–1982 and 1991; Hasegawa and Hiraiwa‐Hasegawa, 1990; Nishida, 1997; Taı¨: Boesch and Boesch‐Achermann, 2000; Kanyawara: Wrangham, 2002; Budongo: Newton‐Fisher, 2004), though occasionally a significant relationship exists (Gombe: 1973–1974; Goodall: 1986; Mahale, 1992: Nishida, 1997). It has recently become clear, however, that total copulation rate is not an informative behavioral measure, because all copulations do not have an equal probability of conception. Variation in the likelihood of conception is predictable: (1) between females, (2) between cycles within a female, and (3) at different times within a female’s cycle. Male chimpanzees respond to this variation, and it now appears that high‐ranking males consistently monopolize the copulations that are most likely to result in conceptions. Variation between females in the likelihood of conception is pronounced in nulliparous versus parous females. Wrangham (2002) reviewed evidence that nulliparous females consistently exhibit more cycles per conception than parous females. Thus, each copulation with a nulliparous female is less likely to result in conception than one with a parous female. Males respond by showing less interest in nulliparous females. They do not mate‐guard nulliparous females, nor do they employ other forms of sexual coercion when nulliparous females are in estrous (reviewed in Wrangham, 2002). Furthermore, males do not show increased testosterone levels in response to fully swollen nulliparous females, as they do with parous females (Muller and Wrangham, 2004a). Presumably, this is due to the lack of male competition for nulliparous females. The net result is that while total copulation rates for high‐versus low‐ranking males and for parous versus nulliparous females are similar, high‐ranking males consistently show higher copulation rates with parous females (Hasegawa and Hiraiwa‐ Hasegawa, 1990; Wrangham, 2002). Low‐ranking males, then, are copulating most frequently with less fecund nulliparous females. Individual females also show variation in the probability of conception across cycles. Female fecundity has been quantified in a number of field studies by measuring urinary or fecal metabolites of ovarian steroids that

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have a significant influence on reproduction (Emery Thompson, in press). Early and late follicular estrogen levels, luteal estrogen levels, and luteal progesterone levels are all measures that have been shown to correlate with conceptive success in humans and other apes (Emery Thompson, in press; Lipson and Ellison, 1996; Nadler and Collins, 1991; Wasser, 1996). Two recent studies of ovarian function in wild chimpanzees (Deschner et al., 2004, Emery Thompson, in press) suggest that males assess female fecundity across cycles, and that high‐ranking males show greater interest in females when they are more likely to conceive. Emery Thompson (in press), for example, found that at Gombe, Kanyawara, and Budongo, urinary estrone conjugates in female chimpanzees were significantly higher in the swelling and post‐swelling phases of conception cycles than in non‐ conception cycles. Female copulation rates were also higher in conception cycles than non‐conception cycles. Because most copulations are initiated by males (Goodall, 1986), this suggests increased male interest during conception cycles. It is not clear from this study whether males competed more intensely for females in conception cycles. Deschner et al. (2004), however, found that as the number of cycles to conception decreased at Taı¨, the alpha male associated with individual females significantly more often and copulated more frequently during the periovulatory period. Urinary estrogen levels in Taı¨ females also increased significantly as the number of cycles to conception decreased (ibid.). The cue that males use to monitor female reproductive condition is not known, but swelling size probably plays a role, as both wild and captive data show a positive relationship between swelling size and hormonal measures of fecundity (Deschner et al., 2004; Emery and Whitten, 2003). At Taı¨, Deschner et al. (2004) showed that swelling size within individual females grew progressively larger with each cycle as females approached the conception cycle. At the same time, urinary estrogen concentrations in the periovulatory period also increased across cycles, peaking during the conception cycle. Finally, chimpanzee females show variation in the probability of conception within periods of peak sexual swelling. Maximal swelling lasts for 10–12 days on average, and mating is normally restricted to this period (Goodall, 1986; Tutin, 1979; Wallis, 1997). Hormonal studies of wild (Deschner et al., 2003; Emery Thompson, in press) and captive (Emery and Whitten, 2003; Graham, 1981) females indicate that ovulation consistently occurs during the last 6 days of maximal swelling, and most frequently (though not exclusively) in the 2 days prior to detumescence. Because of limitations on gamete survival, copulations during the first half of a female’s maximal swelling are extremely unlikely to lead to conception (Emery Thompson, in press). Male behavior is consistent with

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the idea that early copulations are less valuable. High‐ranking males are more likely to mate‐guard females during the periovulatory period, resulting in increased rates of aggression and increased intensity of aggression at this time (Muller and Wrangham, 2004a; Watts, 1998; Wrangham, 2002) (Fig. 1). As a result, high‐ranking males regularly have more copulations with females in the periovulatory period than low‐ranking males do (Hasegawa and Hiraiwa‐Hasegawa, 1990; Matsumoto‐Oda, 1999a; Nishida, 1997; Tutin and McGinnis, 1981). In sum, behavioral data from across study sites are consistent with the priority of access model. Male interest in females varies with female fecundity, and high‐ranking males use aggression to maintain preferential access to females when they are most likely to conceive. However

Fig. 1. Relationship between female swelling stage and rates of copulation and mate‐ guarding. Composite figure shows copulation rates from Mahale (circles), mate‐guarding rates from Gombe (triangles), and levels of urinary estrone conjugates (E2) from captive chimpanzees (dashed line), across days of maximal tumescence (shaded areas). Within the period of maximal swelling, rates of copulation and mate‐guarding increase in the days surrounding ovulation. Ovulation is assumed to occur approximately 2 days after the peak in E2. Captive estrogen data adapted from Emery and Whitten (2003). Mahale data adapted from Hasegawa and Hiraiwa‐Hasegawa (1990). Gombe data adapted from Tutin and McGinnis (1981).

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persuasive the behavioral data, they are still an indirect measure of reproductive success, and genetic data on actual paternity would provide convincing corroboration. Preliminary genetic data from Taı¨, however, seemed to undermine these behavioral data because they indicated that a large number of conceptions were from extra‐community males (Boesch and Boesch‐Achermann, 2000; Gagneux et al., 1997). This claim was even more surprising because in some cases the behavioral data allowed for an extremely narrow window during which females might have mated with extra‐community males. This suggested a deliberate attempt to cuckold the community males, but no clear benefit to the females was evident (e.g., Wrangham, 1997). Ultimately, it was discovered that the genetic data from Taı¨ were flawed, due to mislabeling of samples and other technical problems (Vigilant et al., 2001). Because of these errors, Gagneux et al. (2001) later retracted the original publication. More recent genetic studies from Gombe (Constable et al., 2001) and Taı¨ (Boesch et al., in press; Vigilant et al., 2001) have confirmed that high‐ranking males, and particularly alphas, have significantly higher reproductive rates than lower‐ranking males. B. MALE AGGRESSION AGAINST FEMALES Despite the intense competition among chimpanzee males for dominance status, female chimpanzees are as likely as males to be victims of male aggression (Goodall, 1986; Muller, 2002). Much of this aggression probably functions as sexual coercion, as it appears to make females more likely to mate with some males and less likely to mate with others (Smuts and Smuts, 1993). Systematic tests of this idea have yet to be performed, however, and few published data exist. Forced copulations represent an apparently straightforward example of sexual coercion, but these are uncommon (Goodall, 1986). Tutin (1979) recorded only two instances in 1137 observed copulations at Gombe. Males at Gombe, Mahale, and Ngogo occasionally direct aggression at both anestrous and estrous females until they accompany them on consortships (Goodall, 1986; Smuts and Smuts, 1993; Mitani, personal observation), but forced consortships are apparently rare or absent at Taı¨ (Boesch and Boesch‐Achermann, 2000). Establishing that other forms of male aggression function as sexual coercion is difficult, as this requires knowledge not only of the aggression itself, but the subsequent behavior of the aggressor, the victim, and other individuals (Smuts and Smuts, 1993). Much male aggression against females takes place in contexts suggestive of sexual coercion, however. For example, estrous females are subject to significantly higher rates of

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aggression from males than anestrous females (Mahale: Matsumoto‐Oda and Oda, 1998; Kanyawara: Muller, 2002). This includes aggressive interference in copulations and herding by mate‐guarding males (Goodall, 1986; Watts, 1998; Wrangham, 2002). Preliminary evidence from Kanyawara suggests that male sexual aggression imposes serious physiological costs on females (Muller, unpublished data). Parous females there show dramatic increases in urinary cortisol excretion during periods of maximal swelling, when they receive increased aggression from males. Nulliparous females, on the other hand, are not mate‐guarded by males, and they do not exhibit such cortisol increases during periods of maximal swelling. The extent to which male coercion constrains female choice among chimpanzees is not known. Because females are expected to be choosier when they are more likely to conceive (Stumpf and Boesch, 2005), efforts to quantify female choice have focused on the periovulatory period (POP). At Mahale, Matsumoto‐Oda (1999b) found that copulations with high‐ ranking males increased significantly during the POP, suggesting to her that females preferred high‐ranking males at this time. It is nonetheless difficult to discriminate between this hypothesis and the alternative that high‐ranking males constrain female behavior during the POP. In the same study, for example, male solicitations were significantly more likely to succeed when higher‐ranking males were absent (Matsumoto‐Oda, 1999b). Similarly, almost all female solicitations of adult males failed when higher‐ranked males were nearby. Stumpf and Boesch (2005) recently examined female proceptivity and resistance at Taı¨, and found that females were more selective during periods when they were more likely to conceive. Rates of female proceptivity were lower, and female resistance rates higher, during the POP compared to the non‐POP. No significant difference in male aggression toward females was detected from the non‐POP to the POP, suggesting that male coercion was not responsible for the pattern. Similar to Mahale, females at Taı¨ showed a general preference during the POP for males that were high‐ranking or soon became high ranking (Stumpf and Boesch, 2005). Thus, it is possible that female interests are generally aligned with those of high‐ranking males during the POP. These studies are based on a small sample of males, though, and further observations are needed to establish female preferences. Infanticide is a final, indirect form of male aggression against females that has been recorded within groups at Mahale, Kanyawara, and Ngogo (Clark Arcadi and Wrangham, 1999; Mitani and Watts, unpublished data; Nishida and Kawanaka, 1985; Takahata, 1985). At Mahale, victims’ mothers have sometimes resided in peripheral areas between communities

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(Nishida, 1990). This suggested to researchers there (Hamai et al., 1992; Nishida, 1990) that infanticide functions as sexual coercion, forcing females to shift away from peripheral areas and to mate more restrictively. This idea remains speculative, however. C. WITHIN‐GROUP COMPETITION AMONG FEMALES Whereas dominance rank is easy and reproductive success difficult to assess in male chimpanzees, precisely the opposite is true for females. Female chimpanzees do not exhibit overt concern with status as males do, and their dominance relationships are correspondingly subtle. Observers often find it difficult to rank female chimpanzees, because submissive signals and aggressive interactions between them are rare (Bygott, 1974; Goodall, 1986, Muller, 2002; Nishida, 1989; Pusey et al., 1997). Given the association between low levels of agonistic behavior and stable dominance hierarchies in other primate species (Sapolsky, 1983, 1993), it seems likely that female chimpanzee status relationships are generally more stable than those of males. Evidence for rank stability comes from Gombe, where Pusey et al. (1997) were able to assign females to dominance levels (high, medium, or low) by combining data in 2‐year blocks. They found that a female’s rank at age 21 strongly predicted her rank a decade later. The importance of early rank acquisition is supported by the fact that parous female residents direct a significant proportion of aggression toward nulliparous immigrants, who represent future resource competitors (Goodall, 1986; Muller, 2002; Nishida, 1989). Nishida (1989) argued that once females have settled into their core areas, they ‘‘have no pressing reason to strive for higher rank,’’ and thus show little aggression toward other resident females. By this reasoning, the costs of escalated aggression, which include potential danger to offspring, outweigh any benefits of increased dominance standing. The idea that females do not incur significant benefits as a result of dominance rank is consistent with the view that scramble competition is more important than contest competition for female chimpanzees (e.g., Sterck et al., 1997). However, two recent studies from Gombe suggest that there, at least, contest competition may be significant. First, as with male chimpanzees, dominant females at Gombe show less variation in weight across seasons, suggesting better access to resources (Pusey et al., 2005). Dominant females are also heavier, though it is not clear whether this is a consequence or a cause of dominance. Second, high‐ranking females at Gombe live longer than low‐ranking females, and they enjoy shorter inter‐ birth intervals and higher offspring survival (Pusey et al., 1997). They also produce daughters that reach sexual maturity earlier than those of

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low‐ranking mothers. Presumably, these benefits are related to improved nutrition (Pusey et al., 1997). Wittig and Boesch (2003b) have also stressed the importance of contest competition for female chimpanzees at Taı¨. They argue that contest competition is more intense there than in other communities because females have frequent access to monopolizable resources such as meat and stone tools for nut cracking, and they are more social than females at other sites. Consistent with this idea, they detected a higher rate of pant‐grunting (a formal signal of subordinance) among adult females at Taı¨ than at other sites. In addition, they were able to rank females in a linear hierarchy, and they found that dominant females outcompeted subordinates for monopolizable resources. Despite these tantalizing hints, the absence of data on body weights and reproductive outcomes makes it difficult to assess the ultimate importance of dominance rank for Taı¨ females. The precise mechanism of contest competition among female chimpanzees is not clear, but both long‐ and short‐term processes may be involved. In the short term, high‐ranking females probably occupy the best feeding sites. As discussed previously (Section III.A.2.a), the upper canopy represents a particularly high‐quality site, because increased light renders fruits there larger, more abundant, and more nutrient dense than those in the lower canopy (Houle, 2004). Kahlenberg (unpublished data) recently discovered consistent differences in feeding height related to female dominance rank among chimpanzees at Kanyawara. When females were classified in broad rank categories based on pant‐grunt vocalizations and agonistic interactions, high‐ranking females were found to feed higher than low‐ranking females when co‐feeding in trees. No height difference was found when females were in trees but not feeding. Furthermore, in cases where females were observed fighting over food, losers predictably fed lower in the canopy or left the tree altogether after the aggressive interaction. Detailed observations of feeding rates and nutritional analyses of fruits from different parts of the canopy are currently underway at Kanyawara. These data will permit a more precise evaluation of female feeding competition. In the long term, high‐ranking females may also occupy better core areas within a community’s territory. A rigorous test of this hypothesis has not been conducted and would require detailed ecological data from specific habitats within a community range. Currently available observations from Kanyawara and Gombe are suggestive, but ambiguous. Emery Thompson et al. (in press) reported that peripheral females at Kanyawara exhibited longer inter‐birth intervals and lower levels of ovarian steroids than more central females. At Gombe, Williams et al. (2002b) found that peripheral females did either very well or very poorly reproductively and suggested

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that being peripheral is a high‐risk strategy. It is not clear, however, whether differences between central and peripheral females are related to decreased food availability in peripheral areas, or to an increased threat of aggression and infanticide to peripheral females from males in neighboring territories. Additional aspects of female ranging at Gombe are consistent with the idea that high‐ranking females impose costs on low‐ranking females. Williams (2000) found that young females at Gombe tend to settle in areas away from the highest‐ranking female. Furthermore, low‐ranking females at Gombe are significantly less social than high‐ranking females, and they avoid high‐ranking females when they do associate with others (Williams et al., 2002a). Again, the specific costs are unclear. Feeding costs, as described previously, represent one possibility. Infanticide by high‐ranking females may also be a significant risk for low‐ranking mothers. Infanticides and attempted infanticides by high‐ranking females are well documented at Gombe (Goodall, 1986; Pusey et al., 1997). Even as the mechanisms of competition among female chimpanzees become clearer, the significant effect of female status on reproduction at Gombe remains puzzling. For if dominance regularly has important effects on female reproduction, one would expect females to show more overt competition over rank than they do. Ultimately, it will be possible to examine long‐term patterns of female reproduction from various study sites to determine whether female dominance rank is consistently associated with a significant reproductive advantage. Until that is done, the possibility remains that female competition at Gombe is extreme compared to most sites. Muller (2002) reviewed three lines of evidence that female competition at Gombe is particularly intense. First, young females at Gombe exhibit a low rate of transfer (Williams, 2000). A female that stays in her natal community presumably bears increased costs associated with inbreeding, but may benefit from associating with a high‐ranking mother, for example, by settling in her core area. Second, both infanticide and attempted infanticide by high‐ranking females against low‐ranking mothers appear to be more common at Gombe than at other sites (Clark Arcadi and Wrangham, 1999; Pusey et al., 1997). Finally, aggressive interactions between parous females appear to be more common at Gombe than at Kanyawara (Muller, 2002). D. INTERGROUP CONFLICT Intergroup relations among wild chimpanzees are predictably hostile. Male chimpanzees are philopatric, and they aggressively defend their community range from incursions by neighboring males (Boesch and

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Boesch‐Achermann, 2000; Goodall, 1986; Nishida, 1979; Watts and Mitani, 2001). In the course of such defense, they sometimes cooperate to inflict lethal wounds on vulnerable strangers (Goodall et al., 1979; Watts et al., in press; Wilson et al., 2004). We briefly review what is currently known about the patterns, mechanisms, and functional significance of intergroup aggression in chimpanzees. More comprehensive treatments of this topic can be found in recent reviews by Wrangham (1999) and Wilson and Wrangham (2003). Intergroup encounters occur both by chance, when chimpanzees feed in peripheral parts of their range, and by design, when males patrol those areas. Patrolling males move to the periphery of their territories, where they actively search for signs of members of other communities (Boesch and Boesch‐Acherman, 2000; Goodall, 1986; Watts and Mitani, 2001). An unusual suite of behaviors makes patrolling one of the most distinctive aspects of wild chimpanzee behavior (ibid.). Chimpanzees are uncharacteristically silent during patrols, moving in single file and maintaining close proximity to each other. In contrast, chimpanzee parties of similar size are usually noisy and scattered as individuals feed, travel, and socialize. Patrolling individuals are extremely wary. They stop frequently to scan the environment and are attentive to motion in the trees and on the ground; patrollers also sniff the ground and vegetation and inspect signs of conspecifics such as nests, food remains, urine, and feces. Chimpanzees only rarely feed during patrols. Instead they alter their normal foraging movements, occasionally making deep incursions (or ‘‘commando attacks’’: Boesch, 2003; Boesch and Boesch‐Acherman, 2000) into the territories of their neighbors, traveling two or more kilometers past the border, with the apparent intention of finding and attacking strangers (Wrangham, 1999). Patrolling is primarily a male activity, with the extent of female participation varying among populations. Females occasionally join males on deep incursions but play a bystander role during attacks (Boesch and Boesch‐Acherman, 2000; Muller and Mitani, personal observation). 1. Aggression Against Males When a group of males encounters a lone male from another community, or isolates a single male from a larger party, prolonged and vicious attacks can occur. During such gang attacks, males cooperate to immobilize their victim, and subsequently take turns biting, kicking, and pummeling him (Goodall et al., 1979; Watts et al., in press; Wilson et al., 2004). Because they outnumber their target, the risk to aggressors appears low. Attacks can last for more than 20 minutes, during which the antagonists receive no apparent injuries (ibid.).

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Targets of gang attacks, on the other hand, may be killed. In some situations, death occurs immediately, whereas in other cases victims are left alive, but with obviously fatal injuries. The latter may be more likely when an attack is interrupted by the arrival of additional chimpanzees from the victim’s community (Watts et al., in press). A detailed summary of observed, lethal intercommunity attacks on adults and adolescents is presented by Wilson and Wrangham (2003). These include nine killings at Gombe (two of females), two at Kanyawara, and three at Ngogo. Two additional killings of adults were observed at Ngogo in 2004 (Watts et al., in press; S. Amsler and H. Sherrow, personal communication). In Table II, we update information from Wilson and Wrangham’s (2003) Table I to include more recent observations. The relative rarity of lethal intercommunity attacks makes it problematic to estimate a reliable rate (Wrangham, 1999). The actual number of killings

INTERCOMMUNITY KILLINGS

TABLE II ADULTS AND ADOLESCENTS, 1972–2004

OF

Site

Year

Victim (Sex)

Aggressors’ Community

Victim’s Community

Evidence

Gombe Gombe Gombe Gombe Gombe Gombe Gombe Gombe Gombe Kibale Kibale Kibale Kibale Kibale Kibale Kibale

1972 1974 1974 1975 1975 1977 1977 1998 2002 1992 1998 2002 2002 2002 2004 2004

Unknown (F) Godi (M) De´ (M) Goliath (M) Madam Bee (F) Sniff (M) Charlie (M) Unknown (M) Rusambo (M) Ruwenzori (M) Unknown (M) Unknown (M) Unknown (M) Unknown (M) Unknown (M) Unknown (M)

Kahama? Kasekela Kasekela Kasekela Kasekela Kasekela Kasekela Kasekela Kasekela Rurama Kanyawara Ngogo Ngogo Ngogo Ngogo Ngogo

Kalande? Kahama Kahama Kahama Kahama Kahama Kahama Kalande Mitumba Kanyawara Sebitole Unknown Unknown Unknown Unknown Unknown

Inf.a Obs.b Obs.b Obs.b Obs.b Obs.b Inf.b Obs.d Inf.d Inf.c Inf.e Obs.e Obs.e Obs.e Obs.e Obs.e

Table has been updated from Wilson and Wrangham (2003). ‘‘Evidence’’ denotes whether the attack was directly observed (Obs.) or inferred from strong evidence, such as finding a body with wounds consistent with a chimpanzee attack (Inf.). a Wrangham, 1975. b Goodall, 1986. c Wrangham, 1999. d Wilson et al., 2004. e Watts et al., in press.

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must be higher than the observed number, as fission‐fusion grouping patterns make it difficult to keep track of all community members, even at long‐term study sites. At Mahale, six healthy males disappeared under suspicious circumstances. Researchers attributed these diappearances to probable intergroup attacks (Nishida et al., 1985). Healthy young males have also disappeared suddenly from other communities, suggesting, but by no means confirming, intercommunity aggression as the cause (Wrangham, 1999). Given the number of chimpanzee deaths from known causes, however, it is clear that lethal intercommunity aggression is a significant contributor to mortality (ibid.). Wrangham (1999) estimated a rate of 0.25 lethal attacks per year for communities of eastern chimpanzees. Current data suggest a lower rate of intercommunity killing among western chimpanzees (Boesch and Boesch‐Achermann, 2000; Wilson and Wrangham, 2003; Wrangham, 1999). Despite strikingly similar patterns of patrolling and territorial aggression between Taı¨ and the eastern study sites, including gang attacks with wounding, adult fatalities have never been witnessed at Taı¨. One possible reason for this is that food availability at Taı¨ is comparatively high, resulting in consistently large party sizes and a low rate of solitary foraging (Boesch and Boesch‐Achermann, 2000). This probably reduces imbalances of power during intergroup encounters, significantly increasing the cost of prolonged attacks. Consistent with this idea, during some gang attacks at Taı¨, males have been ‘‘rescued’’ by the arrival of other community members (Boesch and Boesch‐Achermann, 2000). Additionally, males in one community at Taı¨ stopped patrolling and avoided their neighbors altogether when predation and disease had killed all but four of them (Boesch and Boesch Achermann, 2000). 2. Aggression Against Females and Infants When multiple males from one community encounter a strange female, responses vary according to her age and reproductive state (Williams et al., 2004). Males normally interact peacefully with cycling, swollen females, but frequently attack older non‐swollen females and females with infants. Although these attacks can lead to serious wounds, it appears that males are less interested in killing strange females than males. Only two documented cases of females being killed in intergroup encounters exist; both of these were at Gombe (Wilson and Wrangham, 2003). Males do appear to target infants, however, during encounters with strange females. Intergroup infanticides have been recorded at Gombe (Goodall, 1986; Wilson et al., 2004), Mahale (Kutsukake and Matsusaka, 2002), Kibale (Watts and Mitani, 2000; Watts et al., 2002), and Budongo (Newton‐Fisher, 1999c). In one case at Taı¨, females were found consuming

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a dead infant, but it was not clear whether inter‐ or intracommunity infanticide was responsible (Boesch and Boesch‐Achermann, 2000). As with lethal attacks on adults, it is difficult to estimate a rate of intercommunity infanticide, but in the eastern study sites it is clearly a significant source of infant mortality. In Table III we update Wilson and Wrangham’s (2003) Table II to present a current tally of observed instances of intergroup infanticide in chimpanzees. 3. Proximate Mechanisms The leading proximate explanation for lethal intercommunity aggression in chimpanzees is Manson and Wrangham’s (1991) ‘‘imbalance of power hypothesis.’’ This hypothesis focuses on the costs rather than the benefits of aggression, suggesting that males are motivated to attack conspecifics when they can do so with little or no risk to themselves (Wrangham, 1999). The proximate benefit of wounding or killing neighbors is suggested to be an increase in relative intercommunity dominance (ibid.). Wrangham (1999) and Wilson and Wrangham (2003) reviewed observational evidence supporting the imbalance of power hypothesis from Gombe, Mahale, Kibale, and Taı¨. At all of these sites, relative party size appears to be a strong predictor of the intensity of aggression during intergroup encounters. At Taı¨, for example, large parties are more likely than small ones to make incursions into neighboring territories and to attack strangers (Boesch and Boesch‐Achermann, 2000). At Ngogo, small patrols are more likely than large ones to flee upon encountering strangers, and large parties are more likely than small ones to attack strangers (Watts and Mitani, 2001). A recurrent problem with such observational data, though, is that precise numbers of males in neighboring parties are rarely known, so it is difficult to accurately assess relative party size and power imbalances (Mitani et al., 2002b). Experimental evidence from Kanyawara confirms that males are extremely sensitive to imbalances of power. In a series of playbacks, Wilson et al. (2001) showed that male decisions to approach a simulated intruder depended primarily on whether a favorable numerical asymmetry existed. When the pant‐hoot call of a single foreign male was played to parties of varying size and composition, Wilson and colleagues found that: (1) all‐ female parties predictably stayed silent, or moved away from the call; (2) parties with one or two males remained silent, but moved cautiously toward the call about 50% of the time; and (3) parties with three or more males tended to respond immediately with loud calls, moving quickly and excitedly toward the playback site. Finally, patterns of ranging and association are consistent with the imbalance of power hypothesis, and they highlight the pervasive effects of

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TABLE III OBSERVED

AND INFERRED INTERCOMMUNITY INFANTICIDES,

1967–2005

Site

Year

Infant’s sex

Aggressors’ Community

Victim’s Community

Evidence

Budongo Budongo Gombe Gombe Gombe Gombe Gombe Gombe Kibale Kibale Kibale Kibale Kibale Kibale Kibale Mahale Mahale Mahale

1995 1995 1971 1975 1975 1979 1993 1998 1999 1999 2001 2001 2004 2004 2005 1974 1976 2000

Unknown M Unknown M F Unknown F Unknown Unknown Unknown Unknown Unknown M Unknown Unknown M M M

Sonso Sonso Kasekela Kasekela Kasekela Kasekela Kasekela Kasekela Ngogo Ngogo Ngogo Ngogo Ngogo Ngogo Ngogo Mahale Mahale Mahale

N15 N15 Unknown Unknown Unknown Unknown Mitumba Kalande Unknown Unknown Unknown Unknown Unknown Unknown Unknown M Group K Group Unknown

Inf.e Obs.e Obs.a Inf.b Obs.b Obs.d Obs.i Obs.i Obs.f Obs.f Obs.g Inf.g Obs.j Obs.j Inf.k Inf.c Sus.c Inf.h

Table has been updated from Wilson and Wrangham (2003). ‘‘Evidence’’ denotes whether the attack was directly observed (Obs.), inferred from strong evidence, such as finding males eating a freshly killed infant (Inf.), or suspected from the sudden disappearance of a healthy individual (Sus.). a Bygott, 1972. b Goodall, 1977. c Nishida et al., 1979. d Goodall, 1986. e Newton‐Fisher, 1999. f Watts and Mitani, 2000. g Watts et al., 2002. h Kutsukake and Matsusaka, 2002. i Wilson et al., 2004. j S. Amsler and H. Sherrow, personal communication. k Mitani, personal observation.

territoriality and intergroup aggression on chimpanzee life (Wrangham, 1999). Chimpanzees tend to use the central parts of their territories most intensely, visiting peripheral areas infrequently (Boesch and Boesch‐ Achermann, 2000; Herbinger et al., 2001). When they do pass through peripheral parts of their territories or patrol, they tend to do so in parties that are large or contain many males (Mitani and Watts, in press; Wrangham, 1999).

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4. Functional Explanations Wrangham (1999) proposed that male chimpanzees employ lethal intergroup aggression to reduce the coalitionary strength of their neighbors and to expand their territories. Until recently, however, the functional significance of territorial expansion was not clear. Two benefits seemed possible. First, larger territories might include more females. Second, females living in larger territories might have higher reproductive rates, due to enhanced access to resources. Recent data from Gombe favor the latter explanation. As described previously, at both Gombe and Kibale males can be extremely aggressive toward strange females, attacking them and their infants. Perhaps because of this, territorial expansion does not automatically result in new females being added to a community (Williams et al., 2004). Rather, females living in shrinking territories often shift or contract their ranges to stay within the new border areas (Williams et al., 2002b). The clearest examples of females being added to a community through territorial expansion occurred with the extinction of community males at Gombe and Mahale. Following these extinctions, neighboring males at both sites appropriated territory and females from the affected communities (Goodall, 1986; Goodall et al., 1979; Nishida et al., 1985). It is not currently clear how common it is for communities to lose all of their adult males in this fashion. The primary benefit of territorial aggression, then, appears to be the acquisition of a secure feeding area. Two recent studies from Gombe support this idea. First, long‐term data on chimpanzee weights show that in years when the community range was larger, the density of chimpanzees was lower, and mean weights were higher (Pusey et al., 2005). Chimpanzees were about 4.4% lighter in the high‐density than the low‐density years (ibid.). Second, interbirth intervals of resident females at Gombe were shorter during periods when the territory was larger (Williams et al., 2004). During these times both males and females became more gregarious, suggesting increased food availability (ibid.). If males defend a territory primarily to secure feeding benefits, then attacks against infants may simply function to remove future competitors and drive strange females away from border areas. Infanticide by males might also be a strategy to coerce females to leave their community, and join that of the aggressors (mountain gorillas: Watts, 1989), but the apparently low rate of secondary female transfer in chimpanzees argues against this hypothesis (Watts et al., 2002; Williams et al., 2004). Given the significant number of observed gang attacks on adult females and their infants, the low number of fatalities in comparison to males is striking. Could males

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be less motivated to kill strange females because such females do occasionally transfer between communities, offering potential reproductive opportunities? The answer is not presently known; more long‐term data on females from adjacent communities is needed. 5. Controversies Although the preceding outline of intergroup aggression would probably satisfy most researchers studying chimpanzees in the wild, this picture has proven controversial among some anthropologists (e.g., Ferguson, 1999; Marks, 2002; Power, 1991; Sussman, 1999). These critics have maintained that escalated aggression in chimpanzees is the result of human influence and that chimpanzees in an ‘‘undisturbed’’ state are generally peaceful and ‘‘egalitarian’’ (Power, 1991). The original argument is based on the observations that early researchers did not witness lethal aggression among chimpanzees and that provisioning at Gombe and Mahale led to increased rates of aggression among chimpanzees (ibid.). However, the failure of early chimpanzee researchers to observe intercommunity aggression is entirely predictable, given that the study communities were not fully habituated, nor were individuals routinely followed to the borders of their territory (Watts et al., in press). Although Goodall began working at Gombe in 1960, early observations were largely restricted to a banana feeding station located in the center of the community range. Observations of chimpanzees away from this area were rare before 1968, and all‐day follows of males were not routine until well after that date. The first lethal intercommunity attacks at Gombe were observed in 1971 (Bygott, 1972). Power (1991) took Ghiglieri’s (1984) failure to observe intergroup aggression during early work at Ngogo as evidence that this unprovisioned community was not territorial and aggressive. However, the Ngogo chimpanzees were not well habituated during this study. Ghiglieri (1984) estimated a community size of 55 chimpanzees and concluded that predation on monkeys was rare or absent. Further habituation and subsequent observations at Ngogo have revealed that the community size is actually greater than 140, and predation on monkeys is more frequent than at any other site (Mitani and Watts, 1999; Watts and Mitani, 2002). Similarly, with the identification of territorial boundaries at Ngogo, territorial aggression and intergroup killings are regularly observed, despite the fact that the Ngogo chimpanzees have never been provisioned (Watts and Mitani, 2000, 2001; Watts et al., 2002; Watts et al., in press). With the provisioning hypothesis convincingly refuted (Watts et al., in press; Wilson and Wrangham, 2003; Wrangham, 1999), critics have increasingly focused on alternative forms of human interference as hypothetical

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causes of chimpanzee aggression. Ferguson (2002), for example, recently suggested that experiments in which calls from strange males were played to chimpanzees at Kanyawara were responsible for the lethal attack observed there in 1998. This scenario is unlikely, for at least three reasons. First, as described previously, similar attacks have been observed at Ngogo, where chimpanzees have never been subjected to playback experiments. Second, long‐term data from Kanyawara indicate that the rate of intergroup encounters during 1998, when playbacks were conducted, was indistinguishable from those of previous years (Wrangham, unpublished data). Third, long‐term data from Ngogo indicate that the rate of territorial boundary patrolling by chimpanzees is not affected by the rate at which chimpanzees encounter their neighbors, either vocally or visually (Mitani and Watts, in press). Both Ferguson (1999) and Sussman (2004) have also proposed that escalated aggression in chimpanzees is simply the result of general ‘‘stress’’ from human encroachment. As Wrangham (1999) has noted, however, attributing lethal coalitionary attacks in chimpanzees to human interference, whether in the form of playbacks, provisioning, deforestation, or poaching, fails to explain why other primate species, such as bonobos or baboons, that are regularly provisioned by humans, subjected to playback experiments by researchers, or killed by poachers, do not exhibit lethal coalitionary aggression between groups. This is not to suggest that human disturbance cannot influence rates of intercommunity aggression in chimpanzees. Deforestation of a community’s range could potentially lead to more intercommunity encounters, and poaching of a community’s males could change the balance of power during these encounters. However, similar demographic and spatial changes occur naturally in chimpanzee habitats, even in the absence of human interference. The underlying motivations driving male chimpanzee behavior are clearly not the result of such interference.

IV. COOPERATION The cooperative interactions that take place in chimpanzee societies stand in stark contrast to the aggression displayed within and between communities. As is the case with aggression, there is a clear sex difference in chimpanzee cooperation. The relatively asocial nature of female chimpanzees limits the number of cooperative interactions in which they participate. In the absence of frequent interactions, it has been difficult to study female chimpanzee social behavior in the wild, and as a result, our current understanding of the form, frequency, and contexts of female cooperation remains incomplete. In contrast, male chimpanzees are much more gregarious than females, and males cooperate in a wide variety of behavioral

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situations. Cooperation between male chimpanzees generates considerable theoretical and empirical interest because the resource over which they primarily compete, females, is not easily divided and shared (Trivers, 1972). In the following, we review patterns of cooperation between male chimpanzees in the contexts of coalition and alliance formation, grooming, group territoriality, hunting, and meat sharing. A. COALITIONS

AND

ALLIANCES

Nowhere is cooperation in chimpanzees on better display than in their coalitionary behavior. Male chimpanzees form short‐term coalitions by cooperating to direct aggression toward conspecifics (Mitani, in press; Nishida, 1983; Nishida and Hosaka, 1996; Riss and Goodall, 1977; Uehara et al., 1994; Watts, 2002). Coalitions between male chimpanzees are notable for their frequent occurrence and complexity. The fluid nature of coalitions contributes to part of this complexity. Some males repeatedly engage in coalitionary behavior with each other over several months or years, in which case they are referred to as alliances (de Waal and Harcourt, 1992; Goodall, 1986; Riss and Goodall, 1977). In contrast, chimpanzees are also extremely opportunistic, occasionally switching between coalition partners from one interaction to another (Newton‐Fisher, 2002; Nishida, 1983). Early research suggested that alliances play a critical role in male chimpanzee status competition. Riss and Goodall (1977) described a situation at Gombe where one adult male, Figan, rose to the top of the dominance hierarchy only after receiving consistent support from Faben, an older male presumed to be his brother. Continued support from Faben helped Figan maintain his position as the alpha male for the next 2 years (Goodall, 1986). Because male chimpanzee dominance rank is positively related to mating and reproductive success (see Section III.A.2.c), coalitions likely have significant fitness consequences. Fieldwork at Mahale illustrates the complex nature of coalitions and the unsuspected fitness benefits that males can derive through their strategic use (Nishida, 1983). In one small community consisting of three adult males, the alpha male (Kasonta) maintained his position for several years with the help of the gamma male (Kamemanfu). The beta male (Sobongo) was able to take over the top position, however, after the gamma began to aid him instead of the former alpha. The two alpha males achieved the highest mating success before and after the rank reversal. Intriguingly, the other two males appeared to cede matings to the gamma male while they competed for his help during the period of rank instability (Fig. 2).

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F IG. 2. Temporal changes in male chimpanzee mating success at Mahale. (A) During a stable period preceding a rank reversal, the alpha male (Kasonta) maintained his position at the top of the dominance hierarchy and copulated more frequently than two other males. (B) During a period of instability, the alpha (Kasonta) and beta (Sobongo) males competed for coalitionary support from the gamma male (Kamemanfu). The alpha and beta ceded matings to the gamma who mated most frequently. (C) After a rank reversal involving the former alpha and beta males, the new alpha asserted his dominance to achieve the most matings (adapted from Table IV in Nishida, 1983).

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Additional research at Ngogo has documented a novel coalitionary tactic employed by males and confirms the critical role of coalitions in mating competition (Watts, 1998). The Ngogo chimpanzee community is unusually large, and estrous females typically attract several males. Under these circumstances, high‐ranking duos and trios of males have been witnessed to mate‐guard females (Watts, 1998). These mate‐guarding coalitions form, both successfully and unsuccessfully, when the male party size grows so large that it becomes difficult for a single male to mate‐guard females (Fig. 3). Males who engage in mate‐guarding coalitions share matings with each other and achieve higher mating success in coalitions than they would by mate guarding alone (ibid.). Given the significant fitness effects derived from coalitions, male chimpanzees compete for coalition partners in several, sometimes complex, ways. Observations at Mahale indicate that alpha males frequently associate, groom, and support their alliance partners, who in turn aid alphas secure their position at the top of the hierarchy (Nishida, 1983; Nishida and Hosaka, 1996). Alpha males are responsible for maintaining relationships with their allies, and they perform ‘‘separating interventions’’ (sensu de Waal, 1998) to keep their rivals apart. Studies by de Waal (de Waal 1992; de Waal and Luttrell, 1988) indicate that male chimpanzees in captivity may adopt coercive tactics by supporting others against those who have previously formed coalitions against them.

Fig. 3. Mate‐guarding form and success vary with male chimpanzee party size. Mean ( 1 SE) values are shown for single male and coalitionary mate‐guarding episodes at Ngogo (adapted from Watts, 1998 and Mitani et al., 2002b).

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Research at Ngogo suggests that males manipulate the frequency of support they receive by engaging in reciprocal exchanges that involve goods and services that are both similar and different in kind. Studies there reveal that male chimpanzees exchange coalitionary support reciprocally at a group level (Mitani, in press; Watts, 2002). These exchanges are evenly balanced within dyads, with males and their partners initiating coalitions a similar number of times (Mitani, in press). Male chimpanzees at Ngogo also trade other commodities, in the form of grooming and meat, for support (Mitani, in press; Mitani and Watts, 2001; Watts, 2002). Before concluding that giving depends on receiving in these cases, it is important to exclude other factors that might confound the relationship. Because of their fission‐fusion society, chimpanzees do not associate with all members of their community equally often. Thus, reciprocal exchanges could result as by‐products of association if males directed behaviors toward those with whom they remained in contact frequently (de Waal and Luttrell, 1988; Hemelrijk and Ek, 1991). In some primate species, similarity in age and rank affect association patterns (de Waal and Luttrell, 1986), leading to the expectation that reciprocity in behavior may result from exchanges between closely bonded individuals who share common characteristics. Additional analyses are not consistent with these interpretations. At Ngogo, reciprocity in coalition formation at the group level persists after controlling for several potential confounds, including association frequency, male age, male rank, and maternal kinship (Mitani, in press; Watts, 2002). The trade of different commodities, such as grooming and meat for support, is also unaffected by these confounds (ibid.). Reciprocal exchanges underscore the cooperative nature of chimpanzee coalitions. Between‐site variation in coalitionary behavior adds another layer to their complexity. Variability occurs at two levels. First, coalitions at Taı¨ often involve two subordinate individuals directing aggression jointly toward dominants (60%, N ¼ 30, Boesch and Boesch‐Achermann, 2000). In contrast, similar ‘‘revolutionary’’ coalitions (Chapais, 1995) occur very rarely at Mahale (1%, N ¼ 23, Nishida and Hosaka, 1996) and Ngogo (< 5%, N ¼ 885, Watts, 2002). Second, substantial variation exists in the frequency of ‘‘loser‐support’’ coalitions (de Waal et al., 1976) in which subordinate individuals are helped in disputes with higher‐ranking chimpanzees (Boesch and Boesch‐Achermann, 2000; Nishida and Hosaka, 1996; Watts, 2002). While most coalitions observed at Taı¨ (90%) and Mahale (68%) are of this type, they occur infrequently at Ngogo (< 5%). Because coalitions play a critical role in the acquisition and maintenance of male rank, the variability described is likely to reflect important aspects of dominance relationships. For example, revolutionary and loser‐support coalitions tend to destabilize dominance hierarchies (de Waal, 1992), and

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the reported variability in their occurrence across study sites may reflect differences in male social relationships. During periods of rank instability, the frequency of such coalitions is expected to increase. In contrast, ‘‘conservative’’ and ‘‘winner‐support’’ coalitions involve dominant individuals directing aggression toward subordinates and chimpanzees supporting high ranking over low ranking individuals. These types of coalitions tend to reinforce the status quo and are expected to characterize times of stable rank relationships between chimpanzees. Observations at Mahale and Ngogo furnish some support for these predictions. Frequent observations of loser‐support coalitions at Mahale were made while three high‐ranking males were jockeying for dominance status (Nishida and Hosaka, 1996), while the recurrent conservative and winner‐support coalitions at Ngogo were recorded during periods when male rank relationships were relatively stable (Watts, 2002). B. GROOMING Social grooming is the most frequent affiliative behavior observed among primates (Goosen, 1981). Chimpanzees are no exception, although some individuals do so more than others. A consistent sex bias in chimpanzee grooming behavior exists; males groom each other much more frequently than do females (Arnold and Whiten, 2003; Boesch and Boesch‐ Achermann, 2000; Goodall, 1986; Takahata, 1990a,b; Watts, 2000a; Wrangham, et al., 1992). The paucity of grooming by female chimpanzees is easily understood given their general asocial nature (Arnold and Whiten, 2003; Goodall, 1986; Wrangham et al., 1992). In contrast, the substantial amount of time male chimpanzees devote to grooming requires explanation. In three communities at Mahale, Ngogo, and Budongo, males groomed seven to nine other males (Arnold and Whiten, 2003; Nishida and Hosaka, 1996; Watts, 2000a). This consistency occurs despite major differences in the total number of potential male grooming partners at each site (Mahale ¼ 8; Ngogo ¼ 23–24; Budongo ¼ 8–10), and probably reflects the fact that time, energy, and social constraints limit the amount of time available to groom (Dunbar 1984, 1991). Male chimpanzees do not distribute their grooming randomly. They tend to groom others with whom they frequently associate (Boesch and Boesch‐Achermann, 2000; Mitani et al., 2000; Newton‐Fisher, 2002). In addition, male chimpanzees distribute their grooming disproportionately to only a few individuals, giving and receiving most of their grooming (66–81%) to their top three partners (Arnold and Whiten, 2003; Nishida and Hosaka, 1996; Watts, 2000a). Grooming undoubtedly serves a hygienic function (Barton, 1985; Hutchins and Barash, 1976), but studies of several primates suggest that

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it also plays an important role in the development and maintenance of social relationships (Cords, 1997; Dunbar, 1991; Seyfarth, 1977; Walters and Seyfarth, 1987). In this context, several researchers have hypothesized that male chimpanzees use grooming tactically to invest in partners from whom they receive fitness benefits (Arnold and Whiten, 2003; Mitani, in press; Newton‐Fisher, 2002; Nishida, 1983; Nishida and Hosaka, 1996; Watts, 2002). The tactical deployment of grooming can result in several direct benefits for participants. Grooming can be reciprocated either immediately within the same bout or at a later time. Recent fieldwork indicates that male chimpanzees groom each other reciprocally at a group level (Arnold and Whiten, 2003; Mitani, in press; Newton‐Fisher, 2002; Watts, 2000a, 2002). Mutual grooming during the same bout may contribute to this pattern (Barrett et al., 1999), but the immediate exchange of grooming does not furnish a complete explanation because reciprocity in grooming holds after excluding bouts of mutual grooming (Arnold and Whiten, 2003). Grooming can also be exchanged for other goods and services, such as coalitionary support. In an influential model, Seyfarth (1977) proposed that agonistic support is the primary benefit received by grooming. According to this model, individuals are assumed to vary in their quality as grooming partners. Because high‐ranking individuals are competitively superior to low‐ranking animals, the former should be the most attractive grooming partners. Thus, low‐ranking individuals should invest in grooming high‐ ranking partners, and grooming should be directed up the dominance hierarchy. Competition to groom high‐ranking individuals will force some animals to compromise, with the result that adjacently ranked individuals will groom most often. Observations of male chimpanzees provide only partial support for Seyfarth’s model. While some studies show that grooming is directed up the hierarchy (Arnold and Whiten, 2003; Newton‐Fisher, 2002; Watts, 2000b), additional research indicates that dominant males sometimes give as much grooming to subordinate individuals as they receive from them (Takahata, 1990b). Grooming is common between adjacently ranked males at Ngogo and Budongo (Arnold and Whiten, 2003; Watts, 2000b), but rank distance between partners does not affect grooming between males at Mahale (Nishida and Hosaka, 1996; Watts, 2000b). Whether chimpanzees exchange grooming for coalitionary support has seldom been investigated. In the only tests of this hypothesis, recent work at Ngogo has shown that adult males there consistently trade grooming for support (Mitani, in press; Watts, 2002). High‐ranking male chimpanzees use grooming to cultivate social bonds with low‐ranking individuals. The latter in turn form coalitions with

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high‐ranking males to help them maintain their dominance status (Nishida, 1983; Nishida and Hosaka, 1996; Takahata, 1990b). Given these circumstances, grooming will not always be directed up the hierarchy as predicted by Seyfarth’s grooming competition hypothesis. Other factors may also affect the distribution of grooming between male chimpanzees. For example, de Waal (de Waal, 1991; de Waal and Luttrell, 1986) has hypothesized that instead of being attracted to high‐ranking individuals, primates form selective bonds with others whom they resemble in terms of kinship, rank, and age. This ‘‘similarity’’ principle predicts that male kin will groom frequently, independent of rank differences between them, and that grooming between pairs close in rank will be prevalent, irrespective of kinship. It does not assume that grooming will be directed up the hierarchy and thus differs from Seyfarth’s grooming competition model. Kin may obtain indirect fitness benefits by grooming each other. In contrast, mutualism or reciprocity may account for frequent grooming by animals who belong to the same age and rank class. Members of the same age cohort and rank class share similar needs, access to resources, and power; and for these reasons they are likely to be in the best position to provide and exchange fitness benefits (de Waal and Luttrell, 1986). Current evidence does not support the hypothesis that kinship plays a significant role in structuring patterns of grooming among male chimpanzees. Maternal kinship, as assayed by mtDNA haplotype sharing and genetic distance, does not correlate with male grooming at a group level in the Kanyawara and Ngogo communities of chimpanzees (Goldberg and Wrangham, 1997; Mitani et al., 2000). Moreover, male pairs that groom more often than expected by chance are not typically related to each other through the maternal line (Mitani et al., 2002c). In contrast, additional studies reveal strong effects of male age and rank on grooming patterns. At Gombe and Taı¨, older males groom more often than younger males, and high‐ranking chimpanzees groom more frequently than low‐ranking individuals (Boesch and Boesch‐Achermann, 2000; Simpson, 1973). Similarly, pairs of males at Ngogo who groom significantly more than chance expectation tend to belong to the same age and rank classes (Mitani et al., 2002c). The preceding observations reinforce the view, held by many, that male chimpanzees use grooming in multiple ways to compete for socially valuable partners from whom they derive fitness benefits (Arnold and Whiten, 2003; Newton‐Fisher, 2002; Nishida, 1983; Nishida and Hosaka, 1996; Watts, 2000b). Males trade grooming for the direct benefits that it provides, either during bouts of mutual grooming or reciprocally over time. Male chimpanzees use grooming to cultivate and reinforce social bonds with others upon whom they rely for coalitionary support. The grooming

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ties that bind male chimpanzees together within communities are displayed in their group territorial behavior. C. GROUP TERRITORIALITY Coalition formation and grooming relationships among males are two well‐known examples of chimpanzee cooperation that take place within communities. Male chimpanzees also cooperate to compete between communities during group territorial behavior. Group territoriality is rare in non‐primate mammals, though it does occur in some social carnivores (Caro, 1994; Creel and Creel, 2002; Heinsohn and Packer, 1995; Mech and Boitani, 2003). It is equally uncommon among primates, having been described in a few species such as howler monkeys, red colobus monkeys, and mountain gorillas (Pope, 1990; Struhsaker, 1975; Watts, 1994). Group territoriality in chimpanzees is of particular interest because of boundary patrols and coalitionary attacks on neighbors, two unusual forms of cooperative behavior displayed by males in this context. Patrolling is an integral part of chimpanzee territoriality (see Section III. D), and males are likely to obtain several benefits by doing so. By engaging in patrols and defending their territory, males could increase their access to food, improve their safety, recruit new females into their community, and improve the foraging efficiency and hence reproduction of resident females. As reviewed previously (Section III.D.3), current evidence is consistent with the hypothesis that male chimpanzees communally defend territories to increase their access to food resources. In this case, the benefits obtained via patrolling and territoriality are shared among all individuals. Further observations are not consistent with the hypothesis that males cooperate with kin during boundary patrols; males who are closely related genetically through the maternal line, as assayed by mtDNA haplotype sharing, do not show any tendency to patrol together (Mitani et al., 2000, 2002c). Additional research, however, indicates that some males accrue direct fitness benefits. Observations at Ngogo reveal that there is considerable inter‐individual variation in the tendency to patrol. Some males participate frequently, while others do so less often (Watts and Mitani, 2001). Analyses reveal that patrol participation is positively correlated with male mating success. Males who mate frequently, and potentially have the most offspring in the group to protect, appear to be motivated to patrol more often. While patrolling yields direct fitness payoffs, it is also costly. Patrols occasionally lead to encounters with neighbors; these are typically hostile and sometimes result in fatalities (see Section III.D). The risk of attack by

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members of other communities constitutes a potentially significant cost of patrols. Male chimpanzees appear to reduce this cost by patrolling with as many males as possible. Recent work at Ngogo reveals considerable temporal variation in the frequency of patrols, ranging between 0–9 times per month (Mitani and Watts, in press). Much of this variation depends on a single factor, male party size. When the Ngogo chimpanzees gather in parties with a large number of males, the odds of patrolling increase (ibid.). Additional observations indicate that male chimpanzees further minimize the costs of patrols by doing so with partners with whom they have developed strong social bonds and on whom they might be able to rely to take risks (Watts and Mitani, 2001). At Ngogo, males who patrol together also groom and form coalitions with each other frequently. In addition, patrolling effort is positively correlated with the frequency of participation in red colobus hunts. Pursuing prey is a dangerous activity (see Section IV.E) and likely to give others an indication of a male’s willingness and ability to take risks in intercommunity aggression (Watts and Mitani, 2001). At Taı¨ and Ngogo about 25–33% of all patrols result in aural or visual contact with chimpanzees from other groups (Boesch and Boesch‐ Achermann, 2000; Watts and Mitani, 2001). Patrollers at Taı¨ have been described to employ some complex, cooperative tactics to attack conspecifics (Boesch, 2003; Boesch and Boesch‐Achermann, 2000). These include ‘‘lateral’’ attacks on the smallest and most vulnerable parties encountered and surprise assaults supported from the rear by fellow patrollers. Attacks described at most sites, however, involve direct, frontal confrontations between members of different communities. Cooperative attacks on neighbors are one of the most striking aspects of chimpanzee group territorial behavior. During attacks, males assist each other in holding victims down and taking turns beating them (see Section III.D). Because attacks are made only when males enjoy overwhelming numerical superiority, aggressors do not appear to be subject to retaliation by victims. Attackers suffer few, if any wounds, and generally remain unharmed. D. COOPERATIVE HUNTING Unlike humans, few nonhuman primate species habitually hunt and eat meat. Chimpanzees are a prominent exception. Field studies reveal that some individuals hunt frequently and consume several kilograms of meat per year (Boesch and Boesch‐Achermann, 2000; Hosaka et al., 2001; Stanford, 1998; Watts and Mitani, 2002). Meat, a scarce and valuable resource, is shared readily with others. The predatory behavior of

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chimpanzees provides an unusual opportunity to examine cooperation in the contexts of hunting and meat sharing. Chimpanzee hunting behavior has been studied intensively at four sites—Gombe, Mahale, Taı¨, and Ngogo (Table I)—and, as a result, we possess considerable information about prey choice, the identity of hunters, hunting frequency, and success (Boesch and Boesch‐Achermann, 2000; Gilby, 2004; Hosaka et al., 2001; Stanford, 1998; Watts and Mitani, 2002). Chimpanzees prefer to hunt red colobus monkeys (Procolobus badius). These monkeys represent 81–88% of all vertebrate prey captured. Chimpanzees prey selectively on members of the youngest age classes. Juvenile and infant red colobus compose over 50% of all prey. Although adult male chimpanzees make the majority of kills, other chimpanzees show a keen interest in hunting. Hunting frequency shows substantial variation across study sites. Part of this variability is due to the fact that chimpanzees do not hunt uniformly over time. At all study sites, seasonal hunting ‘‘binges’’ or ‘‘crazes’’ occur. During these times, chimpanzees hunt almost every day for periods that last up to 10 weeks. Chimpanzees are very successful predators. Hunting success rates, measured by the percentage of hunts that result in kills, average over 50% across sites. Controversy exists about the degree to which chimpanzees cooperate during hunts. Some fieldworkers describe high levels of behavioral coordination during hunts. In contrast, others examine the outcomes of group hunting to determine whether cooperation yields fitness benefits. Boesch and Boesch (1989) reported that chimpanzees at Taı¨ cooperate behaviorally to capture prey. Most hunts of red colobus involve groups of chimpanzees, and hunters at Taı¨ assume different roles when pursuing red colobus (Boesch and Boesch‐Achermann, 2000). While some chimpanzees serve as ‘‘drivers’’ by chasing prey in one direction, ‘‘blockers’’ anticipate the movements of monkeys to obstruct their escape routes. These tactics permit ‘‘ambushers’’ to encircle and capture monkeys or to force them back toward ‘‘drivers.’’ Most hunts (77% ¼ 211/274) at Taı¨ appear to involve chimpanzees collaborating and performing these different complementary roles (Boesch and Boesch‐Achermann, 2000). Researchers studying the hunting behavior of chimpanzees at other sites have not been able to replicate observations made at Taı¨. Fieldwork at Gombe suggests that chimpanzees there act individually while pursuing prey during group hunts (Stanford, 1998). In contrast, limited coordination has been described in the hunting behavior of chimpanzees at Mahale and Kibale (Hosaka et al., 2001; Watts and Mitani, 2002). Most observers agree that it is extremely difficult to follow individual chimpanzees as they move rapidly in the treetops and on the ground in pursuit of monkeys (Hosaka

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et al., 2001; Stanford, 1998; Watts and Mitani, 2002). Hunts typically involve several chimpanzees attempting to capture monkeys spread over large areas, exacerbating the problem of documenting cooperation. Those studying social carnivores who hunt communally in much more open conditions concur that establishing whether animals cooperate behaviorally while hunting is neither straightforward nor easy (e.g., Creel and Creel, 2002). Given the difficulty of observing the behavior of individual chimpanzees during hunts, several investigators have turned to analyzing the outcomes of hunts to evaluate the fitness effects of cooperation. Cooperative hunting will evolve if individuals who hunt in groups obtain fitness payoffs relative to solitary hunters. Packer and Ruttan (1988) proposed a widely adopted criterion to assess the efficacy of cooperative hunting: that cooperation occurs when hunting success increases with the group size of hunters. Results of some studies satisfy this criterion, while others do not. Busse (1978) was the first to show that hunting success, measured by the number of kills per individual, decreases with group size at Gombe. Additional studies that employ other variables to assay hunting success have failed to demonstrate that communal hunting yields feeding benefits. The per capita amount of meat obtained from hunts shows no relationship with group size at most sites (Gombe: Gilby, 2004; Stanford, 1998; Taı¨: Stanford, 1998; Ngogo: Watts and Mitani, 2002). In contrast to these studies, other research has produced positive results. Using the percentage of hunts that result in kills to assay hunting success, Packer and Ruttan (1988) and Stanford (1998) showed that hunting success increases with group size at Gombe. Similarly, the percentage of successful hunts and the total amount of meat obtained from hunts increase significantly with group size at Taı¨ and Ngogo (Boesch, 1994b; Watts and Mitani, 2002). Reconciling these different results is not easy, but, in the end, they may have little bearing on the question of whether chimpanzees hunt cooperatively. To assess the fitness payoffs of cooperative hunting, we require information about the net gains achieved by individuals who hunt in groups and those who hunt alone. The studies we have outlined, however, have focused exclusively on the feeding benefits acquired by chimpanzee hunters. Various measures of hunting success, such as the per capita amount of meat obtained from hunts, do not take account of potentially important costs. For example, chimpanzees are likely to expend more energy to capture prey when hunting alone compared with when they hunt in large groups. Even if per capita meat intake decreases with group size, factoring in these costs may yield a situation in which the net benefit accrued by individuals who hunt in groups is actually higher than that of solitary

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F IG. 4. The relationship between hunting success and hunting party size. Hunting success is estimated as the kiloJoules of meat acquired per individual per hunt. There is no correlation between these two variables (adapted from Table I in Boesch, 1994b).

hunters. These considerations illustrate that conclusions based on measures of hunting success do not constitute strong tests of the efficacy of cooperative hunting. Instead, measures of net energy intake are necessary (Creel, 1997; Packer and Caro, 1997). Only one study has quantified costs and benefits to estimate the net energy obtained by chimpanzee hunters. Boesch (1994b) suggested that in the Taı¨ National Park the net benefit of hunting was greater for chimpanzees who hunt in groups compared with solitary hunters. A close examination of his data, however, reveals that the net benefit accrued by chimpanzees shows no relationship with hunting group size (Spearman r ¼ 0.14, N ¼ 7, p > 0.70) (Fig. 4). Solitary hunters at Taı¨ acquire large amounts of meat for their efforts (X ¼ 4015 kJ), but their net benefits do not differ from chimpanzees who hunt in groups (X ¼ 3427 kJ, Student’s t ¼ 0.34, df ¼ 5, p > 0.50). In sum, the role of cooperation in chimpanzee hunting is unclear. Most fieldworkers emphasize the apparent lack of behavioral coordination during hunts (Hosaka et al., 2001; Stanford, 1998; Watts and Mitani, 2002). These same observers indicate that cooperation sometimes increases hunting success (Stanford, 1998; Watts and Mitani, 2002), but firm evidence on this matter in the form of the net benefits of hunting remains elusive. More convincing data for cooperation exists in the context of meat sharing.

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E. MEAT SHARING Chimpanzee hunting involves several costs. At two sites, Taı¨ and Ngogo, chimpanzees actively search for prey during hunting ‘‘patrols’’ (Boesch and Boesch, 1989; Mitani and Watts, 1999). Patrols at Ngogo can last up to 5 to 6, hours during which chimpanzees move several kilometers in search of suitable prey (Mitani and Watts, 1999; Watts and Mitani, 2002). After encountering red colobus prey, chimpanzees can continue to pursue monkeys for more than 2 hours (Boesch, 1994a). In addition to the energetic costs incurred during the search for and pursuit of prey, chimpanzees run the risk of injury during hunts. Male colobus monkeys mob chimpanzee hunters, occasionally inflicting severe wounds on them (Busse, 1977; Goodall, 1986; Mitani and Watts, 1999; Stanford, 1995; Uehara et al., 1992). Wild chimpanzees share meat readily and widely with conspecifics (Boesch, 1994b; Mitani and Watts, 2001; Stanford et al., 1994; Teleki, 1973). Meat is a scarce and valuable resource, representing less than 5% of a chimpanzee’s total annual dietary intake (Goodall, 1986; McGrew 1992). Because of this and the known costs incurred by chimpanzees while hunting, meat sharing is paradoxical. Three hypotheses have been advanced to explain meat sharing in chimpanzees. One hypothesis invokes an important role for cooperation during hunts. As noted previously, Boesch and Boesch‐Achermann (2000) have suggested that chimpanzees display a high degree of behavioral coordination while hunting. Boesch (1994b) has gone on to make a distinction between chimpanzees who cooperate and hunt together and ‘‘bystanders,’’ individuals who are present but fail to participate in hunts. Observations at Taı¨ indicate that individuals who cooperate to capture prey derive greater net benefits in terms of net energy obtained than do bystanders (Fig. 2 in Boesch, 1994b). This difference is reported to result from meat sharing. At Taı¨, chimpanzees share meat selectively with others who have cooperated with them to make kills. This pattern of selective sharing ensures that individuals who fail to hunt cannot exploit the efforts of cooperators. While the cooperative hunting hypothesis may explain meat sharing among the Taı¨ chimpanzees, methodological problems preclude evaluating its generality. Observers at Gombe, Mahale, and Ngogo report that the distinction between hunters and bystanders is not clear cut, as chimpanzees often switch between pursuing prey and standing by during the same hunt (Hosaka et al., 2001; Stanford, 1998; Watts and Mitani, 2002). Prevailing observation conditions further hamper describing the activities of chimpanzees during hunts. For example, hunting parties are large, averaging over 20 chimpanzees at Ngogo (Mitani and Watts, 1999; Watts and Mitani,

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2002), and, because of this, it is not feasible to track the rapid movements of all hunters as they pursue red colobus high in the trees over areas that cover several hundred meters. Taken together, these factors make it difficult to differentiate reliably between cooperators and cheaters. A second hypothesis, advocated by Stanford (Stanford, 1996, 1998; Stanford et al., 1994), suggests that cooperation between the sexes accounts for chimpanzee meat sharing patterns. His observations of the Gombe chimpanzees revealed that male chimpanzees often hunt in the presence of estrous females. This finding, combined with additional observations that male chimpanzees frequently possess meat (mentioned previously) and occasionally exchange meat for matings with females, led Stanford to propose a provocative ‘‘meat‐for‐sex’’ hypothesis. According to this hypothesis, male chimpanzees hunt to obtain meat that they can swap for matings. Despite its simplicity and allure, the meat‐for‐sex hypothesis has not been validated empirically. For example, Stanford failed to provide evidence for the regular occurrence of predicted behaviors. Observations at Ngogo indicate that estrous females obtain meat less than half the time after begging from males and that matings do not always follow meat exchanges (Mitani and Watts, 2001). Recent work at Gombe confirms both of these findings (Gilby, 2004). Furthermore, the presence of estrous females does not affect whether male chimpanzees hunt at Ngogo (Mitani and Watts, 2001). In a recent reanalysis of 25 years of observations from Gombe, Gilby (2004) has shown that the presence of estrous females actually decreases the probability of hunting by male chimpanzees there. Gombe males apparently suffer opportunity costs in the form of lost matings if they hunt when estrous females are present. The strongest evidence against the meat‐for‐sex hypothesis, however, is the finding that males who share meat with females do not gain any mating advantage by doing so. The mating success of males who share does not exceed that of males who do not share (Mitani and Watts, 2001). A third hypothesis suggests that male chimpanzees use meat as a political tool (de Waal, 1982) and that meat sharing represents an integral part of male cooperative behavior. Observations of a former alpha male at Mahale led Nishida et al. (1992) to hypothesize that male chimpanzees share meat strategically with others to build and strengthen social bonds between them. This particularly cunning alpha male shared meat nonrandomly and selectively with other males, who in turn supported him in long‐term alliances. These alliances helped the alpha male to maintain his position at the top of dominance hierarchy for over 16 years (Uehara et al., 1994). Observations at Ngogo are consistent with the male social bonding hypothesis (Mitani and Watts, 2001). Male chimpanzees are the most frequent

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participants in meat sharing episodes. Males swap meat nonrandomly with specific individuals, and sharing is evenly balanced within dyads (Mitani, in press). Meat is also shared reciprocally at the group level, with males exchanging meat for coalitionary support (Mitani and Watts, 2001). Additional analyses indicate that males also trade grooming for meat (Mitani, in press). Observations from Gombe, on the other hand, do not support the hypothesis that meat exchange is related to male cooperation. Gilby (2004) found that Gombe males did not share meat preferentially with adult males who were frequent associates or grooming partners. Stevens and Gilby (2004) have recently pointed out that reciprocal food sharing may occur as a by‐product of other processes. For example, sharing between two individuals will likely show a reciprocal pattern if they spend considerable time together and thus have more opportunities to share (see Section IV.A). In addition, similarities in age and rank might affect association patterns (de Waal and Luttrell, 1986), with the result that reciprocal exchanges might occur disproportionately between males who share these characteristics. We can rule out these possibilities in cases involving the Ngogo chimpanzees. At Ngogo, reciprocity in sharing between males at a group level persists after controlling for their joint participation in hunts, and for male age, and male rank (Mitani, in press). F. EVOLUTIONARY MECHANISMS The preceding review illustrates that male chimpanzees derive important fitness benefits by developing strong social bonds with each other and by cooperating. Males form well‐differentiated grooming relationships. Grooming is reciprocated and traded for coalitionary support. Coalitionary support is frequently necessary for males to achieve and maintain high dominance rank, and high rank in turn is correlated with mating and reproductive success. Given the importance of coalitions, male chimpanzees work hard to obtain this valuable social service. Individuals exchange meat, a scarce and valuable resource, for support in agonistic contests. Male chimpanzees not only cooperate in contests with their own community members, but also defend their territories communally against members of other groups. While the fitness benefits obtained by male chimpanzees who cooperate are reasonably clear, the evolutionary mechanisms that ultimately account for such cooperation require further study. Kin selection, reciprocity, and mutualism are three well‐known evolutionary processes that lead to cooperation in animals (Clutton‐Brock, 2002; Hamilton, 1964; Trivers, 1971). Kin selection has historically been invoked to explain the evolution of cooperation between male chimpanzees. In a pioneering study conducted

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at Gombe, Morin et al. (1994) suggested that philopatric male chimpanzees are more closely related to each other than are dispersing females. This finding was used to explain why male chimpanzees typically cooperate more than females and supported the hypothesis that kin selection accounts for the evolution of cooperation between males (ibid.). Additional research at Taı¨ and reanalysis of the previously published Gombe data, however, paint a different picture; despite a sex‐biased pattern of dispersal, male chimpanzees appear to be no more closely related to each other than females are (Vigilant et al., 2001). Research at Ngogo has combined genetic data with observations of male social behavior to investigate directly the relationship between kinship and cooperation. Using mtDNA haplotype sharing and genetic distances to assay genetic relatedness between individuals, results indicate that kinship is a poor predictor of who cooperates with whom (Mitani et al., 2000, 2002c). Male chimpanzees who are closely related through the maternal line do not selectively form coalitions, groom each other, patrol together, or share meat (ibid.). Interpreting these results is problematic. The failure to show a strong effect of kinship may reflect demographic constraints that limit the number of kin with whom males can cooperate (Mitani et al., 2002c). Given the fission‐fusion nature of chimpanzee society, interactions between close kin may not always be possible. Alternatively, males might simply lack the time to cooperate with all of their collateral kin. These and other factors will likely combine to limit the deployment of cooperation between closely related chimpanzees (Chapais, 2004). Additional theoretical and empirical work suggests that, in cases where individuals do not disperse, high levels of local competition act to offset the potential indirect benefits obtained via kin selection (Griffin and West, 2002). This finding provides a possible rationale to explain why male kin fail to cooperate in chimpanzee societies. Male chimpanzees are philopatric; they remain in their natal communities and compete vigorously with other males in their own social groups. In this case, the costs of competing with collateral kin may dampen the indirect fitness benefits accrued by helping them. Although results to date do not implicate an important role for kin selection in the evolution of male chimpanzee cooperation, additional research will be necessary resolve this issue completely. Thus far, our ability to assess the genetic relatedness of male chimpanzees has been limited to relatively crude measures utilizing mtDNA. Ongoing research employing nuclear DNA markers will provide a better resolution of who is related to whom. These data will allow us to conduct more precise tests of the effects of kinship on male chimpanzee social behavior. This information will also be required to evaluate the role of reciprocal altruism in the evolution of male chimpanzee cooperation.

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Reciprocal altruism has frequently been proposed to account for the evolution of cooperative behavior between unrelated individuals (Dugatkin, 1997). Reciprocity occurs when individuals restrict their help to those who aid them in return (Trivers, 1971). Theoretical analyses of reciprocal altruism emphasize the contingent nature of interactions; in situations where partners defect, reciprocity dissolves (Axelrod and Hamilton, 1981). The studies outlined in this chapter indicate that male chimpanzees reciprocally exchange commodities that are both similar and different in kind. Males show reciprocity in coalition formation, grooming, and meat sharing at a group level. In addition, they trade grooming for support, meat for support, and grooming for meat. These relationships persist after controlling for potential confounds such as maternal kinship, male age, and male rank. While consistent with reciprocal altruism, these correlational results do not provide strong tests of the hypothesis that reciprocal exchanges between male chimpanzees have evolved as a result of this process. Critical tests will require much more information than is presently available regarding the pattern of exchanges within dyads. For any given pair, is there a contingent nature to the exchange with giving depending on receiving? Do males terminate exchanges with those who fail to reciprocate? Obtaining these data in the wild will be difficult, if not impossible. The fission‐fusion nature of chimpanzee society makes it hard to track and record the behavior of single individuals reliably over periods sufficiently long enough to determine whether males trade commodities in a reciprocally altruistic fashion. Rigorous tests are more likely to be made in captivity, where the temporal sequence of interactions between individuals can be controlled and monitored in detail (e.g., de Waal, 1997; Hauser et al., 2003). The lack of compelling evidence regarding reciprocal altruism in wild chimpanzees may not be surprising, given our current understanding of other animals. Despite many years of study, few convincing examples of reciprocal altruism exist (Hammerstein, 2003). Mutualism represents an alternative evolutionary route to cooperation and occurs in situations where both participants benefit through interaction. Mutualism provides an evolutionary explanation for cases in which individuals cooperate in the pursuit of a common goal, such as joint hunting and group territoriality in chimpanzees. Mutualism has also been hypothesized to explain cooperation in the contexts of coalitions, grooming, and meat sharing (Chapais, 1995; Henzi and Barrett, 1999; Stevens and Gilby, 2004). At first blush, coalitionary behavior involves a tangible cost to the intervener who exposes himself to attack while helping another individual. This cost may be more illusory than real, however, in cases of ‘‘conservative’’ coalitions (sensu Chapais, 1995) where interveners outrank both

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opponents. In these situations, individuals engage in relatively low‐risk cooperative attacks on vulnerable targets. By reinforcing their own dominance ranks, they obtain an immediate benefit through their coalitionary behavior. When grooming is reciprocated between two individuals within the same bout, individuals may cooperate to receive the immediate benefit that grooming itself provides (Barrett et al., 1999; Henzi and Barrett, 1999). Finally, coercion has been invoked to furnish a mutualistic explanation for meat sharing. According to this interpretation, individuals harass others into sharing food with them; sharers cooperate and relinquish food to avoid the costs of further harassment (Gilby, 2004; Stevens and Gilby, 2004). While mutualism may provide a simple and parsimonious explanation for several examples of chimpanzee cooperation, some patterns continue to defy easy explanation. For instance, reciprocity in grooming between pairs of individuals persists after excluding bouts of mutual grooming (Arnold and Whiten, 2003). In these situations, the immediate exchange of grooming for itself does not provide an adequate explanation for cooperation. By virtue of their high status, dominant males are not easily coerced by others. These males nevertheless share meat quite readily and often (Mitani and Watts, 2001). Why does meat sharing occur in the absence of any harassment? Male chimpanzees reciprocally exchange goods and services that differ in kind (Watts, 2002). For instance, males trade meat for coalitionary support (Mitani, in press; Mitani and Watts, 2001; Nishida et al., 1992). Such complex exchanges take place over time and are not easily interpreted in terms of trading immediate, mutual benefits. As these examples attest, answers to many questions about the evolution of chimpanzee cooperation remain elusive. Additional research is clearly needed.

V. COOPERATING

TO

COMPETE

The preceding review illustrates that cooperation and competition are fundamentally interrelated. The most prevalent forms of cooperation among chimpanzees, however, are rooted in male contest competition. Chimpanzee males maintain short‐term coalitions and long‐term alliances to improve their dominance status within communities and defend their territories cooperatively against foreign males. Other prominent cooperative activities, such as grooming and meat sharing, relate strategically to these goals. Females are far less social than males, and they do not cooperate as extensively. Nevertheless, the most conspicuous examples of female cooperation also involve contest competition, as females sometimes cooperate to kill the infants of rivals.

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The competitive context of most male cooperation prompted Sugiyama (1999, 2004) to ask whether male chimpanzees form long‐term social bonds primarily to communally defend a range against their neighbors. His observations at Bossou shed some light on this question. Because the Bossou community is isolated from its neighbors by agricultural land, it is the only group in which males do not show cooperative territorial behavior. It is also the only community in which male emigration has been documented (Sugiyama, 1999, 2004). Sugiyama (1999, 2004) has argued that the lack of intergroup aggression at Bossou eliminates the principal incentive for male cooperation. Because young males cannot serve as allies in territorial defense, their relationship with the alpha male is solely a competitive one. Consequently, alphas are intolerant of young males, who emigrate from the community. Additional studies of chimpanzees across a range of habitats are needed to test the hypothesis that male sociality is critically affected by the costs and benefits of territoriality. Male emigration represents a behavioral extreme in this regard. Other cooperative behaviors could provide an alternate means to examine this issue. For instance, one might expect patterns of male grooming and meat sharing to be affected by levels of intercommunity aggression. By the same logic, the rate of peaceful post‐conflict interactions might also be expected to vary with the intensity of intergroup aggression. Current theory suggests that such interactions function to repair valuable relationships that have been damaged by conflict (Aureli and de Waal, 2000; de Waal and van Roosmalen, 1979; but see Silk, 2002). Reconciliation should thus be more common where territorial aggression is more intense and male relationships more valuable. This has not yet been tested, although Wittig and Boesch (2003c) reported that patterns of reconciliation at Taı¨ fit well with the expectations of the valuable relationship hypothesis. Specifically, male dyads exhibited higher rates of reconciliation than female dyads, and individuals reconciled most frequently with cooperative partners and frequent associates. Further research is also necessary to clarify the ultimate effects of cooperation on chimpanzee competition. Variation in alpha tenure, and presumably reproductive success, exists both within and between sites, but our understanding of what makes a successful alpha is incomplete. Data from Pusey et al. (2005) suggest that body size is not a primary factor as, in contrast to females, high‐ranking males at Gombe do not weigh more than low‐ranking males. Although it is clear that coalitions can play an important role in male dominance striving, their significance varies. In some cases, males rely on coalitions to achieve alpha status, yet in other situations males attain high rank with little help from others (Boesch and

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Boesch‐Achermann, 2000; Goodall, 1986; Nishida, 1983). Why some males are able to maintain high status without aid requires more study. Despite its variable importance, chimpanzee coalitionary behavior appears to have a long evolutionary history. Across primates, species with relatively high rates and high intensities of aggression exhibit relatively large canines (Plavcan et al., 1995). Species in which coalitions frequently affect the outcome of agonistic behavior represent an exception to this pattern, presumably because the benefits of enhanced canine size in these species are insufficient to offset their costs. Male chimpanzees possess smaller than expected canines, a fact possibly attributable to their frequent coalitionary behavior in aggressive contexts (Plavcan et al., 1995). We do not suggest that all chimpanzee cooperation is driven by contest competition. Although direct observations are few, chimpanzees do sometimes cooperate to mob predators such as pythons or leopards (Goodall, 1986; Hiraiwa‐Hasegawa et al., 1986). And, as discussed previously, male hunting provides a potential, yet ambiguous, example of cooperation in the context of resource acquisition. In comparison with humans, however, the general lack of cooperative behavior by chimpanzees in noncompetitive contexts, such as foraging, is conspicuous. Cooperative food gathering occurs routinely among all human foragers (e.g., Hill, 2002). Even the simplest forms of such behavior, such as Hadza men climbing baobab trees to shake down fruits for the women below (Muller, personal observation), lack an apparent equivalent in chimpanzee behavior. Thus, although chimpanzees may provide striking examples of cooperation, we see nothing in their behavior to challenge the idea that the extent of human cooperation is unique in the animal world (Fehr and Fischbacher, 2003). Unfortunately, humans are so successful in their own cooperative behavior that chimpanzees are now critically endangered. It is becoming increasingly doubtful whether the next generation of fieldworkers will have an opportunity to conduct studies of chimpanzee behavior in the wild. If we are to pursue answers to the questions posed here, it will take considerable political skill and some bold, new initiatives to save chimpanzees.

VI. SUMMARY Competition and cooperation are fundamentally interrelated in chimpanzee society. Chimpanzee males are more gregarious than females, and they exhibit both higher rates of aggression and more complicated forms of cooperation. Within groups, males compete over status and access to fecundable females. High‐ranking males gain clear reproductive benefits,

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as they monopolize matings with females when they are most likely to conceive. Rank striving also incurs significant physiological costs, and the extent to which these are mitigated by survival benefits, such as increased access to resources, is not clear. Males direct frequent aggression against females, much of which appears to function as sexual coercion, decreasing the chance that a female will mate with other males. Females are aggressive primarily in the context of feeding competition. Despite evidence that female rank has important effects on reproduction, aggression by parous females against other parous females is rare, and female dominance ranks are stable over long periods of time. Intergroup relations among chimpanzees are predictably hostile. Male chimpanzees are territorial, and they cooperatively defend their feeding range against neighboring groups. When costs are low, males employ lethal intergroup aggression, primarily against infants and adult males, to reduce the coalitionary strength of their neighbors and to expand their territories. The primary benefit of territorial expansion appears to be enhanced access to resources, which increases female reproductive rates. Although chimpanzees cooperate in a variety of contexts, most of these relate strategically to male contest competition. Chimpanzee males form short‐term coalitions and long‐term alliances to improve their dominance standing within communities, and they use grooming and meat sharing to cultivate and reinforce social bonds. At Ngogo, males show reciprocity in coalition formation, grooming, and meat sharing at a group level, and they trade grooming for support, meat for support, and grooming for meat. Reciprocity persists, even after controlling for potential confounds such as association patterns, male age, male rank, and maternal kinship. Males who frequently groom and form coalitions with each other also tend to patrol the territory together. Despite long‐ term data from multiple sites, the role of cooperation in chimpanzee hunting is ambiguous. Cooperation sometimes increases hunting success, but clear evidence of net energetic gains is elusive. The evolutionary mechanisms that account for chimpanzee cooperation require further study. Current data suggest little role for kin selection. Some patterns of exchange are suggestive of reciprocal altruism, but better data are required to rule out the alternative hypothesis of mutualism.

Acknowledgments We thank Professors Charles Snowdon and Peter Slater for inviting us to prepare this review. Our fieldwork in Uganda has been sponsored by the Makerere University, the Uganda National Council for Science and Technology, and the Ugandan National Parks. We are grateful to: G. I. Basuta, J. Kasenene, and the staff of the Makerere University Biological Field Station for providing logistical assistance in the field; our Ugandan field assistants,

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without whom our research would not have been possible; D. Watts and R. Wrangham for their help and collaboration at home and abroad; and S. Amsler, M. Emery Thompson, I. Gilby, and S. Kahlenberg for comments on the manuscript. We also thank M. Emery Thompson, I. Gilby, A. Houle, S. Kahlenberg, A. Pusey, R. Stumpf, and R. Wrangham for providing access to unpublished data, and R. Wrangham for compiling the Gombe and Mahale data in Fig. 1. Our research on chimpanzees has been funded by grants from the Detroit Zoological Institute, the L. S. B. Leakey Foundation, the National Geographic Society, the National Science Foundation, the National Institutes of Health, the University of Michigan, and the Wenner‐Gren Foundation for Anthropological Research.

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Wrangham, R. (2002). The cost of sexual attraction: Is there a tradeoff in female Pan between sex appeal and received coercion? In ‘‘Behavioural Diversity in Chimpanzees and Bonobos’’ (C. Boesch, G. Hohmann, and L. Marchant, Eds.), pp. 204–215. Cambridge University Press, Cambridge. Wrangham, R., and Pilbeam, D. (2001). African apes as time machines. In ‘‘All Apes Great and Small. Volume 1. African Apes’’ (B. Galdikas, N. Briggs, L. Sheeran, G. Shapiro, and J. Goodall, Eds.), pp. 5–17. Kluwer Academic Publishers, New York. Wrangham, R., Clark, A., and Isabiryre‐Basuta, G. (1992). Female social relationships and social organization of Kibale Forest chimpanzees. In ‘‘Topics in Primatology. Volume 1. Human Origins’’ (T. Nishida, W. McGrew, P. Marler, M. Pickford, and F. de Waal, Eds.), pp. 81–98. Univ. of Tokyo Press, Tokyo. Wrangham, R., Conklin‐Brittain, N., and Hunt, K. (1998). Dietary response to chimpanzees and cercopithecines to seasonal variation in fruit abundance. I. Antifeedants. Int. J. Primatol. 19, 949–970. Wrangham, R., Chapman, C., Clark‐Arcadi, A., and Isabirye‐Basuta, G. (1996). Social ecology of Kanyawara chimpanzees: Implications for understanding the costs of great ape groups. In ‘‘Great Ape Societies’’ (W. McGrew, L. Marchant, and T. Nishida, Eds.), pp. 45–57. Cambridge Univ. Press, Cambridge. Yamakoshi, G. (1998). Dietary responses to fruit scarcity of wild chimpanzees at Bossou, Guinea: Possible implications for ecological importance of tool use. Am. J. Phys. Anthrop. 106, 283–295.

ADVANCES IN THE STUDY OF BEHAVIOR, VOL. 35

Trade‐Offs in the Adaptive Use of Social and Asocial Learning Rachel L. Kendal,* Isabelle Coolen,{ Yfke van Bergen,{ and Kevin N. Laland} *department of biological sciences stanford university california 94305, usa { institut de recherche sur la biologie de l’insecte universite´ de tours, france { zoology department university of cambridge, cambridge cb3 8aa, united kingdom } centre for social learning and cognitive evolution school of biology university of st. andrews, st. andrews ky16 9ts, united kingdom

I. INTRODUCTION A common assumption by ethologists, behavioral ecologists, and anthropologists, albeit rarely made explicit, is that the acquisition of learned information from others (henceforth ‘‘social information’’) is inherently adaptive. Individuals are deemed to gain fitness benefits by copying others on the assumption that they acquire adaptive information while avoiding some of the costs associated with learning for themselves (the costs of ‘‘personal information’’). Social learning is known to enable naı¨ve animals to acquire information relevant to many life skills, including when, where, what, and how to eat (Galef and Giraldeau, 2001), with whom to mate (White, 2004), or fight (Peake and McGregor, 2004), as well as which predators to avoid and how (Griffin, 2004). The unspoken supposition is that the acquisition and exploitation of such information will inevitably confer fitness benefits on the learner, since individuals will save themselves the costs, for instance, of searching their entire home range, sampling all potential foods, or learning to escape predators for themselves.

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In fact, the use of social information does not guarantee success (Boyd and Richerson, 1985; Laland, 2004). Individuals face evolutionary trade‐ offs between the acquisition of costly but accurate information and the use of cheap but potentially less reliable information (Boyd and Richerson, 1985). Theoretical models investigating the adaptive advantages of different forms of learning conclude that social learning cannot be employed in a blanket or indiscriminate manner, and that individuals should adopt flexible strategies that dictate the circumstances under which they copy others (Laland, 2004). Such theoretical analyses reveal that social learners would have higher fitness than asocial learners only when copying is rare, when most potential demonstrators would be asocial learners who have acquired and display accurate information about the environment (Boyd and Richerson, 1985, 1995; Giraldeau et al., 2002; Rogers, 1988). As the frequency of social learners increases, however, the value of using social information would decline, because the proportion of individuals demonstrating accurate personal information would decrease. At the extreme, with all individuals copying, the population would have to rely upon unreliable and possibly inaccurate information1 as no one would have acquired accurate personal information by sampling the environment. In order for the use of social learning to be adaptive, individuals must use social learning selectively and engage in the collection of accurate personal information some of the time (Galef, 1995; Laland, 2004). The circumstances under which individuals might switch between reliance on different sources of information remain relatively unexplored. What context‐dependent rules have evolved in animals dictating how they exploit both personal and social information? Do animals copy the behavior of others when they are uncertain how to solve a problem? Do they copy others when it is easy to do so and only learn asocially when copying is not an option? Or is social learning a last resort when asocial learning has failed? Following Laland (2004), the term ‘‘strategies’’ is used here to equate such learning heuristics with those strategies commonly analyzed using evolutionary game theory (Maynard‐Smith, 1982). Of course, animals 1 Some readers may object to our use of the phrase ‘‘unreliable information,’’ on the grounds that the cues that form the bases of social learning are not so much reliable or unreliable as more or less informative. While we are sympathetic to this objection, we persist with the terminology for three reasons. First, whether appropriate or not, use of such terms is common in the literature that we review. Second, there are no obvious alternative expressions that we find entirely satisfactory. For instance, an ‘‘uninformative cue’’ does not distinguish between a signal designed to mislead and a cue that contains no information at all. Third, it is apparent that we are frequently concerned with the reliability and error associated with potential social and asocial sources of information, for which our use of ‘‘reliable or unreliable information’’ can be taken as shorthand.

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need not be aware that they are following a strategy, nor need they understand why such strategies may work. Until relatively recently, the existence and characteristics of social learning strategies have not been allotted a great deal of empirical attention, despite assumptions and predictions pertaining to such strategies in theoretical models. However, experimental support is now emerging for the existence of two broad classes of strategies, dictating both when animals will use social information and from whom they will learn (Laland, 2004). In this article, we will focus on when strategies, reviewing the current empirical support for the putative strategies of copy others when asocial learning is costly and copy others when uncertain. We hope that by emphasizing consistent findings in a range of species, including fishes, birds, and mammals, the prevalence of trade‐offs in the use of social and asocial learning will become apparent, and will be taken into account in future studies of social learning. A further aim is to encourage the integration of theoretical and empirical work in animal social learning, where there is considerable potential for combining laboratory experiments and game theoretical analyses (Laland and Kendal, 2003; Laland, 2004).

II. EVIDENCE THAT ANIMALS EXPLOIT SOCIALLY TRANSMITTED INFORMATION WHERE ASOCIAL LEARNING WOULD BE COSTLY A. THEORETICAL FOUNDATION Several theoretical analyses have reached the conclusion that reliance upon social information should be increasingly favored as the costs associated with acquiring personal information increase (Boyd and Richerson, 1985, 1988; Feldman et al., 1996; but see Section III.C.1). Trial‐and‐error learning is often both costly and error prone. Personal interaction with the environment may entail costs that directly influence survival, such as risk of injury, poisoning or predation, as well as ‘‘missed opportunity’’ costs, such as the loss of time or energy that could be allocated elsewhere. The existence of these costs restricts an animal’s investment in asocial learning, and may lead to ‘‘errors’’ such as a failure to perform an adaptive behavior or the retention of a sub‐optimal variant. When these costs are substantive, selection ought to favor shortcuts to learning, such as copying others (Boyd and Richerson, 1985). On the basis of an extensive theoretical investigation, Boyd and Richerson (1985) proposed their ‘‘costly information hypothesis,’’ which proposes an evolutionary trade‐off between acquiring accurate but costly information versus less accurate but cheap information.

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While this trade‐off manifests itself at various different levels, for our purposes this hypothesis can be summarized as the idea that when information is too costly to acquire or to utilize personally, individuals will take advantage of the relatively cheap information that can be learned from others. An identical argument had earlier been put forward by Bandura (1977, pp. 12), who stated that ‘‘the more costly and hazardous the possible mistakes, the heavier is the reliance on observational learning from competent examples.’’ Although the costly information hypothesis places emphasis on the costs of acquiring personal information, the same reasoning holds when considering the costs of using personal information. As highlighted by Galef (1995), once an individual has acquired a behavior pattern, whether through social or asocial learning, its continued use depends primarily upon the consequences of the behavior relative to the available behavioral alternatives. Moreover, it also follows that as the costs associated with acquiring or using social information increase, we might expect increasing reliance on personal information. For example, on the basis of a theoretical model in which individuals’ only source of social information is the decisions of others (i.e., without seeing the cues upon which such decisions are based), Giraldeau et al. (2002) state that the greater the costs of engaging in an erroneous ‘‘informational cascade’’ (Bikhchandani et al., 1992, 1998), the greater the selective pressure to ignore the decisions of others and rely upon personally acquired information. B. EMPIRICAL EVIDENCE We will summarize empirical support for the costly information hypothesis in fishes, birds, and mammals. Our primary focus will be on the relatively well‐studied topics of foraging and mate‐choice, but we also dwell on other subject matters of interest, such as aggressive encounters in fish. Although learning about predators would seem an obvious context where it can be very costly to learn asocially, we are unable to present any data on the costs of direct experience with predators. Thus, we cannot yet judge whether the apparent importance of social learning on predator recognition ‘‘reflects an evolutionary trend favoring acquisition of risky information from others, rather than at one’s own peril,’’ as asserted by Griffin (2004, pp. 131). 1. Foraging a. Fish Laland and Williams (1998) provide an experimental example in which fish were seemingly prepared to pay the relatively trivial costs of using suboptimal foraging information provided by conspecifics in order to

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avoid the potentially more substantive cost of vulnerability to predation associated with the asocial learning of more efficient foraging. Small groups of ‘‘founder’’guppies (Poecilia reticulata) were trained to take either an energetically costly circuitous route to a feeder or a less costly direct route. In a transmission chain design, these founders were gradually replaced with naı¨ve conspecifics, one individual being replaced each day for a week. Three days after all the trained individuals had been removed, the groups of fish whose founders were trained to swim the circuitous route continued often to use this route to reach the feeder, despite its cost relative to the available direct route. In addition, individuals in groups with founders trained to take the circuitous route took longer to switch to the short route than did otherwise equivalent solitary fish. It is well established that guppies are reluctant to leave conspecifics and forage alone due to predation risk (Day et al., 2001), thus the perpetuation of a suboptimal behavioral tradition in these fish can be explained by the relative cost of acquiring personal information regarding the least costly foraging route and the benefit of conforming to the majority for predator defense. Kendal et al. (2004) exploited the fact that losing visual contact with shoal members is potentially costly to guppies to manipulate the cost of using previously acquired personal information in a social foraging experiment. Individuals were allocated to three conditions in which they either received (1) prior personal information only, (2) prior personal and social information, or (3) no information (Fig. 1). Individuals in the first two conditions had the opportunity to learn through direct experience that food was located in only one of two differently colored feeders at the ends of their tanks. The feeder that contained food was located behind an opaque barrier, while the one that did not was in open water. In the next stage of the experiment, one group was then provided with conflicting social information. The fish in the condition that received both personal and social information (2) observed a shoal of demonstrators feed at the feeder in the open water, which their personal experience had indicated never contained food, while fish in the other two conditions, (1) and (3), were constrained opposite nondemonstrating fish. Following this observation period, there was a test in which the demonstrator shoal was restricted to the center of the tank, both feeders were baited with food, and the fish were released to investigate where each fed. Fish with both sources of information faced a choice between using personal information (i.e., feeding at the feeder that had consistently contained food but that necessitated losing visual contact with conspecifics) or using the social information (i.e., feeding at a feeder that had never previously contained food but did not necessitate loss of contact with conspecifics). Fish in all conditions fed at the feeder in the open water rather than the one behind the opaque

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Fig. 1. (Fig. 3 from Kendal et al., 2004) Experimental procedure, showing the personal experience training of observer guppies to feed (food designated as F) from either blue (B) or yellow (Y) feeders, behind an opaque barrier and demonstrators to feed at the open end of the tank; the social experience procedure for guppies in all conditions (prior personal and social information, personal information only, and no information); and the identical test period for all conditions, in which observers must lose visual contact with the constrained demonstrator shoal in order to feed at the trained feeder. Solid lines indicate opaque partitions, and dashed lines transparent partitions (Kendal, R.L. et al., 2004; role of conformity in foraging when personal and social information conflict. Behav. Ecol. used with by permission of Oxford University Press).

partition, supporting the assumption that swimming behind the opaque barrier to feed represented a cost that guppies would avoid, if possible. However, fish with both sources of information ignored their personal information and fed at the feeder in the open water more rapidly, and with less variability, than did fish with personal information alone (Fig. 2); hence, it would appear that the former used the social information provided in preference to their personal information. An otherwise equivalent prior experiment with no visual barrier, in which the use of personal information did not necessitate loss of contact with conspecifics, found that, at test, fish with both sources of information, but not those in other

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Fig. 2. (Fig. 7 from Kendal et al., 2004) The latency (median and interquartile range) of guppies to enter the demonstrators’ (no barrier) feeder in the no information, personal information only, and personal and social information conditions (**p < 0.01, ***p < 0.001) (Kendal, R.L. et al., 2004; used with permission of Oxford University Press).

conditions, continued to use their personal information and ignored the conflicting social information (Kendal et al., 2004). As social information only outweighed contradictory personal information where the latter was costly to use, it appears that the guppies were employing a strategy of ‘‘copy others when asocial learning is costly.’’ Theory and experiments suggest that public information use, which refers to the ability to assess the quality of a resource, such as a food patch, by observing the relative success or failure of others, could lead to faster, more accurate assessment than private information alone, and that a flexible combination of these sources of information potentially provides for adaptive decision making (Valone, 1989; Templeton and Giraldeau, 1996; Valone and Templeton, 2002). However, assumptions about when animals gather and exploit these different types of information have only recently been tested explicitly. A good illustration of how and why the use of public information is not always adaptive is provided by a series of experiments on public‐information use in two closely related species of sticklebacks that differ in their anti‐predator defenses (Coolen et al., 2003). Coolen et al. examined the propensity of wild‐caught three‐spined (Gasterosteus aculeatus) and nine‐spined (Pungitius pungitius) sticklebacks to use public information about the profitability of food patches. Individual fish were restricted to a central compartment of an aquarium from where they could see two equivalent‐sized shoals of conspecifics feeding at one of two identical but spatially separate feeders dispensing food at different

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Fig. 3. (Fig. 1 from Coolen et al., 2003) Diagram of the experimental tank set up allowing single sticklebacks to observe conspecifics feeding at two feeders. Thick lines represent opaque partitions; thin lines represent transparent partitions, and dashed lines represent goal zone delimitations (Coolen, I. et al., 2003; used with permission of the Royal Society of London).

rates (Fig. 3). Food was delivered to the demonstrators down a tube that was transparent at the front but opaque at the sides, hence visible to demonstrators but not observers, and consumed from a ‘‘hopper’’ at the base of the tube. Following a 10‐minute observation period, the demonstrators and all food were removed from the tank and, after a brief pause, the observer was released and its choice of feeder monitored (as measured by the goal zone to which the fish swam first, and in which it spent most time). Thus, solely on the basis of the demonstrators’ success, observers were required to choose the richer of the two feeders. Coolen et al. found that, at test, nine‐spined sticklebacks preferentially chose the goal zone that had formerly held the rich feeder, indicating that they were able to exploit public information. The experimental design ensured that this preference could not be attributed to residual olfactory cues, direct observation of the food in the feeder, or local enhancement. However, three‐spines, when subject to the same test, swam with equal frequency to the former locations of rich and poor patches. This species difference held, regardless of whether individuals observed conspecific or heterospecific demonstrators (Fig. 4), and in spite of good power in the statistical analysis. Previous studies have indicated that the two species exhibit subtle habitat‐partitioning as nine‐spines use weeded areas more than three‐spines,

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Fig. 4. (Fig. 3A from Coolen et al., 2003) The proportion of three‐spined and nine‐spined sticklebacks that entered first the goal zone corresponding to the feeder that appeared ‘‘rich,’’ rather than ‘‘poor’’ during the demonstration period (n ¼ 20 for each species). The dashed line indicates the proportion expected at random (**p < 0.01, n.s., not significant) (Coolen, I. et al., 2003; used with permission of the Royal Society of London).

even when food is present only in open water (FitzGerald and Wootton, 1996; Hart, 2003). In a final experiment, observers were provided with optional use of vegetative cover during the demonstration and, as expected, in the course of collecting public information, nine‐spines observed the demonstration from within the vegetation, while three‐spines did not. In fact, the three‐spines did not appear to observe each demonstrator shoal equally, as in each trial they would spend more time near one shoal than the other. This latter finding was thought by Coolen et al. to reflect the preference of three‐spines for physical sampling of the environment, consistent with Gotceitas and Colgan’s (1991) findings, and with the collection of personal information. Previous studies have shown that when allowed to join conspecifics and sample directly, three‐spines will join the shoal feeding at the richer food patch (Krause, 1992). In contrast, the collection of personal information in open water is costlier for nine‐spines than for three‐spines because nine‐spines have inferior structural anti‐predator defenses (e.g., lack of girdle and body armor and shorter dorsal spines). Indeed, piscivorous predators are known to preferentially consume nine‐spines over three‐spines (Hoogland et al., 1957). Because of these costs, nine‐spines may forego the opportunity to collect reliable personal information and favor vicarious assessment of foraging opportunities. More generally, public‐information use may be an adaptation that allows animals vulnerable to predation to acquire valuable foraging information at low risk. However, individuals that do not incur such costs would be

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expected to acquire and utilize personal information, since this is typically more reliable. Public‐information use is often thought to require more complex cognition than assessment of the mere presence or absence of a resource (Valone and Templeton, 2002). Coolen et al.’s finding that three‐ spines could acquire the latter, but not the former, type of information suggests that increases in the complexity of the information gathered may favor the evolution of advanced cognition. This finding is consistent with the assumption that ‘‘the value of public information may depend upon the cost of acquiring sample (personal) information’’ (Valone and Templeton, 2002, pp. 21; parentheses added). b. Birds In a study involving the use of personal and public information, regarding patch quality, Templeton and Giraldeau (1996) demonstrated that starlings preferentially use public information when it is easy to acquire but use personal information otherwise. Naı¨ve starlings were paired with ‘‘low information’’ or ‘‘high information’’ demonstrators who respectively sampled few or many holes in an artificial foraging patch. As the observers’ patch contained few or no baited holes, they had to sample several holes before deciding whether the patch was empty and departing it, but could also use the simultaneous foraging behavior of their demonstrator. When patches were arranged in a linear array and thus personal information was easy to collect, naı¨ve starlings ignored the public information. Observers sampled an equal number of holes before departure for another patch, irrespective of whether they were paired with a high‐ or low‐ information demonstrator. However, when the foraging patch comprised a square array of holes, it was simultaneously more difficult for birds to keep track of which holes they had personally sampled and easier for them to observe the demonstrators. Here, the number of holes observers sampled before patch departure decreased as the amount of information provided by demonstrators increased. In accordance with theoretical predictions, this indicates an increased use of public information as the cost of acquiring accurate personal information increased. Here, relative reliance on personal or public information appeared to depend on the difficulty of acquiring personal (and social) information (see also Templeton and Giraldeau, 1995a). c. Mammals Galef and Whiskin (1998) found that the food intake of rats exposed to novel food sources of equal palatability (cayenne‐ or cinnamon‐ flavored rat chow) was significantly influenced by exposure to a demonstrator that had recently eaten one or other of the food sources. For example, rats exposed to a demonstrator that had eaten cayenne‐flavored food ate more of this flavored food when subsequently exposed to both flavored foods

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simultaneously. However, where there was no difficulty in discriminating between the palatability of food sources, either because one was made relatively unpalatable (increased cayenne: experiment 1) or relatively more palatable (addition of sugar to cinnamon: experiment 2), the effect of demonstrator rats on the observer’s food intake diminished. One interpretation of these findings is that the rats only use social information when it would be too time consuming (costly) to distinguish between the two food sources. The cost of acquiring personal foraging information was manipulated in a study of social foraging in callitrichid monkeys, involving seven lion tamarin (Leontopithecus), tamarin (Saguinus), and marmoset (Callithrix) species. Day (2003; Day et al., 2003) presented a series of novel artificial‐ fruit tasks, requiring the extraction of preferred food items, to zoo‐housed groups of monkeys. Judging by the latency between the first contact of the task and successful food extraction, as well as by the total number of food items extracted, the tasks varied significantly in difficulty. For each task, there were two options (doors or holes) by which monkeys could extract food, with the alternatives being equivalent, except in location and color. While the monkeys learned all of the tasks, a detailed statistical analysis revealed that the means of opening the difficult, but not the easier tasks, were learned socially. For the difficult, but not the easy, tasks, there was a significant tendency for individuals within a group to extract food using the same colored option as others, suggesting nonindependent learning. Presumably, the personal information required to solve the easy tasks could be acquired at little personal cost, in terms of time and energy, while the solutions of the more complex tasks were associated with a sufficiently large cost to render social learning adaptive. Similarly, Baron et al. (1996) reported that human subjects were found to imitate more as task difficulty increased. 2. Mate Choice Assessing and choosing potential mates is thought to be a demanding task, requiring the acquisition and processing of a variety of information indicating mate quality. Several researchers have proposed that the costs associated with mate assessment, such as increased vulnerability to predation, search costs, opportunity costs, and errors, will favor reliance on mate‐ choice copying (see review by White, 2004). As the costs of mate choice increase, personal sampling will decrease with a concomitant increase in vicarious sampling (Gibson and Ho¨ glund, 1992). a. Fish Female guppies possess a heritable preference for orange body coloration in male mates (Houde, 1988). In a mate‐choice experiment in which ‘‘observer’’ females choose between two males, Dugatkin (1996)

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pitted this personal information concerning coloration against conflicting social information, by constraining ‘‘demonstrator’’ females in such a way as they appeared to the observer to choose the male with the least orange coloration. He found that, when the orange coloration of the two males differed by 24% or less, females used the social information provided by demonstrators. Thus, when females could potentially make an erroneous decision based upon personal assessment, plausibly representing a cost in terms of reproductive success, females appeared to disregard their personal information in favor of social information. However, when male coloration differed by 40% or more, the personal preference overrode the social information, as females chose the male with the greater orange body coloration. The empirical evidence for this phenomenon is not unequivocal, however, as Brooks (1996) found that females’ ease of discrimination of males based upon ornamentation did not influence the incidence of mate‐choice copying in guppies. Briggs et al. (1996) explicitly tested whether mate‐choice copying of laboratory‐housed guppies was affected by the cost of potential predation from a piscivorous fish. They found that guppies disregarded their personal preference and chose males according to the apparent preference of another female in the absence of an immediate threat of predation. However, there was no evidence for copying under threat of predation, possibly because observer females choose between males with less discrimination under such risks. As other studies (e.g., Dugatkin, 1992; Dugatkin and Godin, 1992) used guppies originating from low‐predation sites, and did not compare guppies originating from low and high predation sites, to our knowledge researchers have not tested whether predation costs influence the extent to which individuals rely on social information in mate choice. Similarly, studies currently provide no evidence to support an avoidance of search costs explanation for the use of social over personal information in fish mate assessment. On the contrary, Dugatkin and Godin (1998) found that food‐deprived guppies, who would presumably face high energetic costs in collecting personal information due to lost foraging time, did not show an enhanced tendency to use social information, in their mate choice, compared to satiated females. In fact, the guppies were less likely to use social information as food deprivation increased, possibly because females do not prioritize mate choice when hungry. b. Birds Gibson et al. (1991) examined the mating distributions of wild sage grouse (Centrocerus urophasianus) at two leks, and suggested that although females assess males directly, they also take advantage of the opportunity to copy the decisions of conspecifics. They argue that this indicates that personal assessment of potential males may be costly to females, and copying may allow them to make greater investment in

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foraging or nest‐site defense. However, a subsequent study by Gibson and Bachman (1992) reported that sage grouse incur only trivial increases in energetic expenditure and predation risk, and no reduction in foraging time or nest defense, when repeatedly sampling males at leks versus visiting once, suggesting there may be little opportunity to reduce costs by copying. One potential explanation is that copying may increase the reliability of decision making over the use of personal information alone, rather than reducing costs. A second possibility is that these birds are locked into ‘‘information cascades’’ (Giraldeau et al., 2002). Moreover, it is also possible that copying itself entails some costs to females due to inaccurate identification of preferred male traits and the possibility that females waiting in line for a particular male risk reduced fertility through sperm depletion (Gibson and Bachman, 1992; Gibson and Ho¨ glund, 1992). Sirot (2001) proposed that mate‐choice copying may incur a cost whereby offspring of the preferred male may be disadvantaged due to increased competition among offspring of the same father. Finally, in a series of experiments (reviewed by White, 2004) with Japanese quail (Coturnix japonica), White and Galef show that social information overrides prior personal preferences for mates in both males and females, although the costs of using personal information have yet to be explicitly manipulated in this system. c. Mammals In many lekking species of mammals, females often join males that have the largest harems (Clutton‐Brock et al., 1989). However, after a series of experiments, McComb and Clutton‐Brock (1994) determined that, for fallow deer (Dama dama) at least, this did not reflect mate‐ choice copying but a tendency of estrus females to follow each other’s movements due to the costs of predation and of harassment by males in mixed‐sex groups. Here, the costs of using personal information to join a preferred male may indirectly cause social information to be used in mate choice. 3. Aggression The benefits of fighting may include gaining or maintaining access to limited resources, such as food, mates, or shelter, while the costs include injury, increased risk of predation, and time and energy costs (Huntingford and Turner, 1987; Neat et al., 1998). As fights are costly for both interactants (Neat et al., 1998), but more so for losers, it may pay for individuals not directly involved in aggressive interactions to gather social information about the quality of future opponents (Johnsson and Akerman, 1998; Peake and McGregor, 2004).

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a. Fish Male Siamese fighting fish (Betta splendens) monitor aggressive interactions between neighboring conspecifics and use the information on relative fighting ability in subsequent aggressive interactions with the males they have observed (Oliveira et al., 1998). Similar observations have been made in rainbow trout (Johnsson and Akerman, 1999). This exploitation of communicated signals in a network has become known as ‘‘eavesdropping’’ (McGregor, 1993). Oliveira et al.’s findings suggest that the level of aggression that eavesdroppers observe in interactions between a pair of demonstrators strongly affects their subsequent agonistic interactions. We suspect that it is no coincidence that the exploitation of social information concerning fighting ability has evolved in a species for which the asocial gathering of equivalent information (i.e., by fighting all parties) would be extremely costly, as these fish frequently fight to the death. We anticipate that this ability may not be found in other Gourami species in which the costs of agonistic encounters are lower, and encourage research comparing species differing in the cost of agonistic encounters. In sum, a large amount of empirical evidence has amassed in support of the hypothesis that animals will show greater reliance on social learning as the costs of acquiring or using asocial information increase. This evidence is all the more compelling, as it spans a variety of species and behavioral domains covering costs of predation, injury, lost opportunities, or energy and reproductive success. There still remains, however, a paucity of experiments designed specifically to test whether animals adhere to a strategy of copy others when asocial learning is costly, especially outside of the foraging domain and in the obviously costly domain of anti‐predator behavior.

III. EVIDENCE THAT ANIMALS EXPLOIT SOCIAL INFORMATION WHEN UNCERTAIN AS TO WHAT TO DO A. UNCERTAIN BECAUSE THEY HAVE NO RELEVANT INFORMATION 1. Theoretical Foundation In 1988, Boyd and Richerson published a model exploring the advantages of reliance on social and asocial learning in a temporally variable environment, in which hypothetical animals have to make a decision as to which of two environments they are in and choose the most appropriate behavior. Behavior 1 is appropriate in environment 1, behavior 2 in environment 2, and performing the alternate behavior results in a fitness cost. The animals base their decision on the magnitude of a continuous parameter (x) representing the outcome of direct observation. If x has high values, above a threshold value d, the animals ‘‘know’’ they are in environment

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1 and perform behavior 1; if x has low values (below –d) they ‘‘know’’ they are in environment 2 and perform behavior 2; while if x has intermediate values (–d < x < d), they are uncertain and copy the behavior of others. The model consequently assumes that animals adopt a copy when uncertain strategy (Boyd and Richerson, 1988; Laland, 2004). Thus, when prior personal experience leaves individuals certain as to how to behave, it is assumed that they will ignore social information. However, when their prior experience leaves them uncertain as to which pre‐established behavior pattern is appropriate in a given context, animals are expected to attend to the behavior of others. Note, Boyd and Richerson present no data in support of this assumption, and at the time it was unclear whether animals were more likely to use social learning when they were uncertain. We note a (i) broad and a (ii) narrow interpretation of Boyd and Richerson’s (1988) assumption. Individuals may be predisposed to rely on social information (i) if they lack relevant prior knowledge to guide their decision‐making, or (ii) if they are uncertain as to which of two or more established behavior patterns is appropriate. There is considerable empirical evidence (detailed in the following section) for the broad assumption, albeit often inadvertent and circumstantial, but none that we know of for the narrow assumption, which must be regarded as the strict interpretation of Boyd and Richerson’s assumption. 2. Empirical Evidence As before, we will now summarize empirical support, in fishes, birds, and mammals, for Boyd and Richerson’s hypothesis. a. Foraging i. Fish In an experiment related to that described previously, Kendal et al. (2004) tested the propensity of guppies in three conditions to use social information concerning the availability of food at two differentially colored feeders, although this time the use of personal and social information did not differ in cost. One group was provided with both prior personal and conflicting social information; a second was solely given social information, and a control group had no personal information. They found that fish that were provided with social information only, and lacked relevant prior information, fed at the feeder indicated by conspecifics significantly more than chance expectation. In contrast, individuals with both sources of information ignored the social information and continued to feed according to their personal information. This finding holds, irrespective of the order in which personal and social information are experienced (Laland, unpublished data). Similarly, Coolen et al. (2003; see Section II.B.1.a) found that nine‐spined sticklebacks that did not have personal information

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copied the patch choices of others, whereas van Bergen et al. (2004; see Section III.B.2.a), testing the same species in an identical set‐up, found that fish would ignore social information when they had relevant personal information. ii. Birds An illustration of how animals may sometimes ignore social information is provided by Dorrance and Zentall’s (2002) study of imitation in pigeons. These researchers conducted a series of experiments involving a conditional discrimination foraging task whereby, in order to receive access to grain, pigeons learned to step on a treadle in the presence of one light (either white or green) and to peck at the treadle in the presence of the other light. Although the study was designed to investigate aspects of imitation in these birds, the experimental design sheds light upon the trade‐off between personal and social information. First, they found that social information was ignored in the initial acquisition of the conditional discrimination. Second, pigeons ignored a single demonstration that was contradictory to their previously acquired personal information relating to which behavior (peck or step) should be performed in the presence of which light (white or green). In order to say that the social information was ignored, one must be able to show that the social information was actually acquired. They found that where birds were required to learn the reverse of their conditional discrimination, those pigeons provided with demonstrations that were consistent with the current reinforcement regime (e.g., grain provided if peck on treadle in presence of green light) learned to reverse their prior conditional discrimination more rapidly than did those provided with a demonstration that was inconsistent with the current reinforcement regime (e.g., grain provided if step on treadle in presence of green light). Thus, it appears that the pigeons ignored social information when they had the relevant personal information available to them but were predisposed to use social information, rather than personal information, when uncertain of what to do. The importance of social information for those individuals who lack personal information is highlighted by experimental work on the developmental basis of social learning in chickens. Nicol (2004) reports that sensitivity to social information, which is very high in chicks, reduces as chickens mature. For example, day‐old chicks avoided pecking at an aversive stimulus after observing the ‘‘disgust’’ response of another chick (Johnston et al., 1998), whereas 9‐week‐old, adult hens showed no avoidance of a food that had previously elicited ‘‘disgust’’ in their demonstrators (Sherwin et al., 2002). It appears that a lack of personal information, in this case ingestive experience, regarding food preferences in young chickens may foster reliance upon social information (Nicol, 2004). However, as these birds gain greater experience, their reliance on social learning seemingly diminishes.

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It is possible also that foraging mistakes are more costly for day‐old than for 9‐week‐old chicks, hence a greater reliance on social learning at earlier ages (see Section II). Templeton and Giraldeau (1995a) found that when opaque barriers prevented starlings from watching foraging conspecifics at the same time as they acquired personal information by probing for food, they ceased to acquire social information. When the opaque barriers were absent, the same individuals behaved as if they were combining personal and social information. Thus, this study provides further support for the hypothesis that asocial learning is the preferred source of information, and social information will only be acquired or used if personal information is inadequate. A second study involving starlings (Templeton and Giraldeau, 1995b) showed that individuals ignored conflicting social information when they possessed personal information as to the location of food (according to a color association), but used it when they had no such personal information. iii. Mammals Galef and colleagues (see review by Galef and Giraldeau, 2001) have repeatedly demonstrated that Norway rats (Rattus norvegicus) use various sources of social information to decide whether to consume novel foods. Galef et al. (2001) further highlighted contexts in which rats appear to use social information only when they lack relevant personal information. Here, a series of experiments were conducted to determine when individuals steal food (kleptoparasitism) from conspecifics, despite the presence of a surplus of food. In one experiment, rats were divided into two conditions, each being fed a different type of food (food type 1 and 2). Pairs of rats, from the same condition, were then placed in a test arena, containing 10 pellets of food type 2, for 10 minutes. Significantly less food stealing was observed in the pairs that had been pre‐exposed to food type 2 than in those that had not. Seemingly, rats lacking prior personal experience with a food will ignore personal sampling opportunities in favor of using social information to discern the safety of a food item. In a subsequent experiment, rats were assigned to three conditions according to their relative ages; (1) both ‘‘old,’’ seven to eight weeks; (2) both ‘‘young,’’ four to five weeks; and (3) one ‘‘young’’ and one ‘‘old.’’ Although the total number of food stealing instances did not differ between conditions (Fig. 5A), in the young‐old condition, young rats attempted to, and succeeded in, stealing from older rats more frequently than did old rats from young rats (Fig. 5B). This corresponds to the findings with guppies and chickens that young individuals who lack personal experience may rely more heavily on social information than their elders. Visalberghi and Fragaszy (1995) reported enhanced consumption of novel, but not familiar, foods among capuchin monkeys (Cebus apella) in

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Fig. 5. (Fig. 4 from Galef et al., 2001) The mean (±SE) total number of successful and unsuccessful instances of food stealing by rats during a 10‐minute test, for (A) rats assigned to groups YY (young‐young), OO (old‐old), and YO (young‐old); and (B) within group YO, young rats stealing from old rats (Y from O) and old rats stealing from young rats (O from Y) (Galef, B. G. Jr. et al., 2001. Copyright # 2001 by the American Psychological Association. Reprinted with permission).

the presence of conspecifics, compared with when alone. However, in a subsequent study (Fragaszy et al., 1997), involving many novel and familiar foods, infant capuchins showed no evidence of selective use of social information from older or more experienced individuals. Similarly, Queyras et al. (2000) found that young common marmosets were as likely to favor personal information, regarding food palatability, despite contrasting social information provided by older conspecifics, as were older individuals paired with younger demonstrators. In contrast, several studies of callitrichid monkeys suggest that young animals seek out social information regarding novel but not familiar food. For instance, studies of captive family groups of lion tamarins have reported that infants are less willing to take novel food items from food bowls themselves than they are to take familiar items (Price and Feistner, 1993). Furthermore, young golden lion tamarins were found to be less likely to reject novel foods acquired from other group members than they were to reject foods that they had obtained independently (Rapaport, 1999), a process that may be enhanced by emission of vocalizations in adults when ‘‘offering’’ foods (Snowdon, 2001; Roush and Snowdon, 2001).

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b. Mate Choice A theoretical model by Sto¨ hr (1998) reports that mate‐choice copying is likely to evolve when young females discriminate poorly among males and need to learn what high‐quality males look like. Similarly, in considering mate‐choice copying in a public information (see Section II.B.1.a) framework, Nordell and Valone (1998) predict that copying behavior should increase as the discrimination task becomes more difficult for an individual. i. Fish Prior to these models, Dugatkin and Godin (1993) designed an experiment in which female guppies observed the apparent mate choice decision of females who were either bigger (experiment 1) or smaller (experiment 2) than the observer. They assumed that smaller fish were younger than their larger counterparts and that larger females had had more experience of choosing mates than younger ones. Dugatkin and Godin reported that, following the observation period, smaller females spent more time in proximity to the male that had seemingly been chosen by larger demonstrators, whereas larger females chose mates randomly with respect to the mate choice of smaller demonstrators. If this finding proves robust, it would appear that guppies rely upon social information in mate choice decisions where relevant personal information is lacking. However, alternative explanations must be ruled out. For example, smaller females may be more vulnerable to predation than larger ones, and they may rely on social information to avoid comparatively large sampling costs. In sum, there is ample empirical evidence that animals will ignore social information unless they lack requisite personal information. Although not true for all species studied, there is evidence that young animals appear to be more reliant on social learning than older animals. B. UNCERTAIN BECAUSE PRIOR INFORMATION IS UNRELIABLE 1. Theoretical Foundation In relatively spatially homogenous environments, animals may be expected to rely on genetic inheritance of pertinent information, while learning is likely to be of utility in situations that are more changeable. Boyd and Richerson (1985, 1988) modeled the use of social information in a spatially heterogeneous environment where individuals of the same age cohort experience different environments, resulting in the possibility of observers and demonstrators having differing experiences. The average quality of information available from demonstrators enables individuals to weight their use of asocial and social learning according to the likelihood of acquiring erroneous information from each source (Boyd and Richerson, 1985). In other words, as environmental heterogeneity increases

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and personal information becomes more error prone (or less reliable), the optimal amount of social learning from local residents increases, while as the rate of dispersal between environments increases, social information becomes increasingly unreliable, and the optimal amount of social learning decreases (Boyd and Richerson, 1988). Giraldeau et al. (2002; see Bikhchandani et al., 1992) proposed that individuals may use social information not because their personal information is in itself unreliable but because the accumulated knowledge of conspecifics potentially represents a source of information with even greater reliability. For instance, where an individual witnesses a sequence of individuals responding to the environment in the same manner, it may conceivably be optimal for that individual to ignore its own personal information and use the more prevalent social information, particularly where individuals can detect the decisions of others but not the cues on which such decisions are based. They suggest such reliance on social information concerning the decisions of others can lead to arbitrary or even maladaptive traditions in animals (Giraldeau et al., 2002; see also Section IV). Despite this, current theoretical work regarding the reliability and value of information in communication systems (Koops, 2004) suggests that, even if the costs of misinformation are high, animals should still use information, provided that it is usually reliable. This requires animals to be able to assess the relative reliability of personal versus social information correctly. Finally, using a mate‐choice model, Sirot (2001) found that females should use personal information if male phenotypic value is a reliable indicator of reproductive success, but as this reliability decreases, they should use public information and copy the choices of other females. In summary, a variety of theoreticians have proposed that animals should use social information, either when their personal information is unreliable or when it is merely less reliable than the social information available to them. 2. Empirical Evidence a. Foraging i. Fish In a study of nine‐spined sticklebacks, van Bergen et al. (2004) manipulated the reliability of personal information concerning the profitability of two foraging patches, using a similar experimental design as Coolen et al. (2003; see Section II.B.1.a and Fig. 3). Fish were allocated to three conditions, where they received (1) 100%, (2) 78%, or (3) 56% reliable personal information as to which of two feeders was ‘‘rich’’ and which ‘‘poor.’’ Following this training period, fish were tested individually for their feeder preference. Those in the 100% reliable condition significantly preferred the ‘‘rich’’ feeder, as did those in the 78% condition,

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although to a lesser extent. Individuals in the 56% reliable condition showed no feeder preference. Subsequently, the profitability of the two feeders was reversed, and fish were presented with (now conflicting) public information in which they observed demonstrators feeding at the two feeders, with what was according to their earlier sampling the poor feeder now the rich feeder, and vice versa. Following this demonstration, only fish in the 100% reliable condition continued to prefer the feeder that was ‘‘rich’’ according to their personal information, as fish in the other conditions exhibited no preference. As shown in Fig. 6, only fish with completely reliable personal information (100%) ignored the public information. Since fish with 56% reliable information probably had not acquired private information (they did not prefer the rich feeder immediately after their training period), this experiment does not provide unequivocal evidence that fish increasingly relied on the social information provided by their demonstrators as the reliability of their personal experience diminished, although it is consistent with this interpretation. It does, however, demonstrate that

Fig. 6. (Fig. 2A from van Bergen et al., 2004) The proportion of nine‐spined sticklebacks that, after receiving personal information of varying reliability followed by conflicting public information, entered first the goal zone of the feeder that was ‘‘rich’’ according to personal information. The dashed line indicates the proportion expected at random, and the hatched bar represents data from Coolen et al. (2003). *p < 0.05, **p < 0.005, n.s. indicates not significant (van Bergen, Y. et al., 2004; used with permission of the Royal Society of London).

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fish with completely reliable private information will ignore conflicting social information. ii. Birds Starlings (Sturnus vulgaris) have been found to value social information in an unpredictable, but not in a predictable, environment (Rafacz and Templeton, 2003). The birds were assigned to four conditions: predictable environment with an informative demonstrator, predictable environment with an uninformative demonstrator, unpredictable environment with an informative demonstrator, and unpredictable environment with an uninformative demonstrator. The ‘‘environment’’ consisted of three wooden wells covered with paper circles, of differing colors or patterns, which could be pierced to retrieve a mealworm. In the predictable conditions, a demonstrator bird would always locate a mealworm beneath the same colored/patterned circle (regardless of hole position), whereas in the unpredictable conditions, a demonstrator was seen to obtain food from each of the three colored/patterned circles an equal number of times. In the informative conditions, demonstrators and observers were provided with the same combination of colored/patterned circles and acquired a mealworm from the same colored/patterned well. However, in the uninformative conditions, the demonstrator was provided with three white circles, representing irrelevant information to the observer, who was subsequently provided with a consistent combination of three colored/patterned circles. Following each of 30 demonstration periods, observers were provided with three wells, and the color/pattern of the circle they first pierced was noted. As expected, birds in the predictable conditions discovered more mealworms than those in the unpredictable conditions. Although in the unpredictable environment foraging success was greater for birds with informative, rather than uninformative, demonstrators, no such effect was found in the predictable environment (Fig. 7). These results are consistent with theoretical predictions that the value of social information increases as the reliability of personal information decreases. This study may allow assessment of the interpretation of Boyd and Richerson’s (1988) assumption: that animals will tend to use social information when uncertain as to which pre‐established behavior pattern is appropriate in a given context (see Section III.A.1). As can be seen in Fig. 7, for birds in an unpredictable environment, there was a time delay (of 20 trials or 2 days) before the foraging success of birds with an informative demonstrator exceeded that of those with an uninformative demonstrator. Rafacz and Templeton (2003) argued that this delay reflects the fact that birds with the informed demonstrator were initially relying upon their personally acquired information, despite their low foraging success, and it took them time to recognize the value of the social information. Birds in

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Fig. 7. (Fig. 2 from Rafacz and Templeton, 2003) The mean number of prey items eaten by starlings in four environment/demonstrator treatment groups over three days of testing. UU ¼ unpredictable/uninformative, UI ¼ unpredictable/informative, PU ¼ predictable/uninformative, PI ¼ predictable/informative (Rafacz, M. et al., 2003; used with permission of Blackwell Publishing Ltd).

unpredictable environment conditions were always provided with the same three colored/patterned wells (although the food was not reliably associated with any one) and over several trials may have learned, through personal sampling, that food may be associated with either of two colors or patterns. Thus, the delayed use of social information by these birds may represent indirect confirmation of the narrow version of Boyd and Richerson’s (1988) assumption, to the extent that learned preferences for the two colors or patterns equate to ‘‘pre‐established’’ behavior patterns. iii. Mammals Dewar (2003a) developed a cue reliability approach to elucidate when foragers should accept or reject a novel food. The basic principle states that, when the average payoff for consuming familiar foods is high relative to other payoffs (here the consumption of novel foods), foragers subsequently require more reliable personal or social information that a new food is beneficial or safe to consume. In Dewar’s terms, these animals have a HIGH reliability threshold and hence a low probability of eating a further novel food. Conversely, animals that experience novel foods of higher caloric value than their familiar food will develop a LOW

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reliability threshold and a high probability of eating further novel foods. An initial experiment provided empirical support for this proposal (Dewar, 2004). Norway rats were familiarized with encapsulated food of moderate caloric value (marjoram flavor), and all experienced the same probability that encapsulated food had a positive caloric value (i.e., 10/12 capsules). The rats were then split into two groups that received either 10 novel foods with an average caloric value that was higher than the familiar food or 10 novel foods with an average caloric value that was lower than the familiar food. The resulting reliability thresholds acquired by the rats were then tested by simultaneously presenting both groups with two foods of moderate caloric value, one being completely novel and the other familiar (marjoram flavor). For the group that received novel foods of higher caloric value than the familiar food, the probability that the novel food was eaten, rather than the familiar food, was dictated by a LOW reliability threshold; and hence they were expected to consume more of the novel food. This occurred because their prior experience had been that novel foods were on average of higher caloric value than familiar foods, resulting in a requirement for relatively little information, indicating that a novel food has a higher payoff than a familiar one. In contrast, the group that received novel foods of lower caloric value than the familiar food had a HIGH reliability threshold, as their prior experience indicated that novel foods were on average of lesser caloric value than familiar foods, and they were expected to eat less of the novel food. These rats require greater confidence than the other group that consumption of a new food will be more profitable than that of a familiar food. Indeed, Dewar reports that rats in the LOW, but not HIGH, reliability threshold group consumed more of the novel, than familiar, food in the test phase. This is presumably because the personal information is reliable for LOW threshold rats (the 10 novel foods and the test novel food all had a positive caloric value) but not for HIGH threshold rats (the 10 novel foods had a negative caloric value, and the test novel food did not). Indeed, the high caloric value of LOW threshold rats’ diet yielded a reliability threshold below the probability that encapsulated food had a positive caloric value and was thus reliable. In contrast, rats in the HIGH threshold group had unreliable personal cues; the low caloric value of their diet generated a reliability threshold that exceeded the probability that novel food had a positive caloric value. According to Dewar’s theory, rats with a HIGH reliability threshold require additional information indicating that a novel food will have a higher payoff for them than a familiar food, compared to LOW reliability threshold rats. Thus, Dewar proposed a social cue dependency hypothesis whereby foragers should show increasing dependence on social cues as asocial cues become less reliable (i.e., as their reliability threshold

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increases). In a second experiment, Dewar presented HIGH and LOW reliability threshold rats with two completely novel foods, one of which a demonstrator had recently eaten (socially marked via the breath of the demonstrator) and one that the demonstrator had not eaten (socially unmarked).2 As expected, rats in the LOW threshold group ate more of the socially unmarked food than did rats in the HIGH threshold group, indicating that rats with low expectations about the value of novel foods (HIGH threshold group) required the additional information provided by the demonstrator. This therefore indicates that individuals with reliable personal information (LOW reliability threshold), as to the expected profitability of novel foods, do not ignore the opportunity to acquire personal information in the presence of conflicting social information. However, as rats in the HIGH threshold group (who have unreliable personal information) did not eat more of the socially marked food than did rats in the LOW threshold group (Gwen Dewar, personal comunication.), the findings are not completely consistent with the prediction that animals will use social information when their personal information is unreliable. b. Social behavior i. Mammals Dewar (2003b) demonstrated that female macaques (Macaca mulatta) discriminate between reliable and unreliable social information, providing further support for the cue reliability approach. Here, an observer macaque may obtain reliable social information, pertaining to the relative social rank of an unfamiliar individual, if she observes the unfamiliar individual being outranked by a familiar individual who is subordinate to herself. In contrast, the observer can obtain unreliable social information, pertaining to the relative rank of an unfamiliar individual, if she observes the unfamiliar individual being outranked by a familiar individual who is dominant to herself. This is the case because the unfamiliar individual may either have a rank lower than the observer or intermediate to the observer and the familiar dominant. Thus, in this scenario, for social information to be considered reliable, it must provide evidence that the observer’s attempt to dominate the unfamiliar individual will succeed with a probability exceeding the reliability threshold. In addition, the reliability threshold increases, requiring information indicating an increasing probability of success, as the costs (i.e., injury) of failing to outrank an unfamiliar individual increase.

2

As socially marked novel foods may be considered safer to consume than unmarked novel foods, Dewar attempted to make the willingness of rats to eat each of the novel foods equivalent. Thus, the socially marked food was further away and less abundant than the unmarked food.

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Mid‐ranking female observers were exposed to three conditions, where unfamiliar individuals appeared subordinate to a familiar subordinate, a familiar dominant, or an unfamiliar female. The behavior of the observer towards the unfamiliar female was subsequently tested. As expected, observers were more assertive towards unfamiliar individuals in the familiar subordinate condition than either the familiar dominant or unfamiliar conditions. This finding is consistent with the hypothesis that macaques are capable of discriminating between unreliable and reliable social cues, although it is difficult to be certain that ‘‘reliability’’ underpins this discrimination. It is possible that the macaques are not making a discrimination based on cue reliability but are rather making differential use of cues that vary in their informativeness.3 c. Anti‐predator behavior i. Mammals Among yellow‐bellied marmots (Marmota flaviventris), which produce individually distinct alarm calls, Blumstein et al. (2004) report that caller reliability is negatively associated with the amount of time allocated to personal assessment of the level of threat. In an initial experiment, individual marmots appeared to conspecifics to be ‘‘reliable’’ or ‘‘unreliable’’ alarm callers through the pairing of their calls with the presence of a predator or non‐predator, respectively. In playback tests, group members allocated more time to vigilance behavior following the alarm call of an ‘‘unreliable’’ than ‘‘reliable’’ individual, consistent with their gathering personal information when social information is unreliable. In a second experiment, marmots were presented with degraded and non‐ degraded alarm calls, representing distant and adjacent alarm callers, respectively. The degraded calls were considered unreliable, as alarm calls from distant individuals were assumed to represent a lesser certainty of risk than those emitted by adjacent individuals. Again, during playback of calls, marmots responded to the ‘‘unreliable’’ rather than ‘‘reliable’’ social information with increased vigilance and collection of personal information. This second experiment may well be better considered in the following section, where a trade‐off in the use of information is assumed when one or other source is likely to be outdated or inappropriate. In a review of social learning about predators, Griffin (2004) argued that social learning might be expected to be faster and more robust in species in which social information (here alarm behavior) reliably predicts a high 3 Inevitably, many of these examples could have been discussed under different strategies. For instance, the Dewar (2003b) macaque example could fit equally well with a strategy such as ‘‘copy others when uncertain what to do because have no relevant information’’ rather than ‘‘when personal information is unreliable.’’

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predator threat than in other species (e.g., fish versus birds and mammals; Griffin, 2004). There is, as yet, little evidence to assess the validity of this argument. In sum, although the empirical evidence that animals copy others when their personal information is unreliable is somewhat limited, it does cover several different species, and it includes situations where information pertaining to food, conspecifics, and predators is unreliable. Dewar’s cue reliability approach and the domain of anti‐predator behavior offer promising sources of greater evidence for a trade‐off in animal decision making according to the relative reliability of social and personal information.

C. UNCERTAIN BECAUSE PRIOR INFORMATION IS OUTDATED 1. Theoretical Foundation Boyd, Richerson, and colleagues (1985, 1988; Henrich and Boyd, 1998) have modeled the use of social information in temporally fluctuating environments, where individuals in different age cohorts experience different environments, resulting in the possibility of observers acquiring social information from models who are demonstrating optimal behavior for an earlier state of the environment. The analyses suggest that species living in an environment of intermediate levels of fluctuation will be most likely to use social learning. Conversely, those experiencing the extremes of a highly fluctuating environment or, alternatively, a stable environment, would have less to gain from observing others and should rely to a greater extent upon asocial learning or genetic inheritance of information, respectively (Boyd and Richerson, 1985, 1988; Laland et al., 1996). Social learning is thought to be favored at intermediate rates of change, as individuals can acquire relevant information without bearing the costs of direct interaction with the environment associated with asocial learning, but with greater phenotypic flexibility than if the behavior were unlearned (Boyd and Richerson, 1985, 1988). Consequently, as socially transmitted information becomes increasingly outdated, we might expect individuals to become less likely to rely on it and more likely to evaluate it through personal sampling. In another theoretical analysis, Doligez et al. (2003) predicted that strategies based on public information use (here the breeding success of conspecifics on particular patches) perform best when fluctuation in patch quality is of intermediate or high temporal predictability. Similarly, Moscarini et al. (1998) have looked at the effect of a changing world on the likelihood of informational cascades and predict that blind copying may occur for some limited time if the state of the world changes stochastically, but it will not happen anymore when the environment changes too

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unpredictably (or randomly). In a more recent theoretical analysis, based upon an earlier model by Henrich and Boyd (1998), Kameda and Nakanishi (2002) reported that in a fluctuating environment, increasing costs of asocial learning initially results in a concomitant increase in social learning, a lesser amount of fresh information, and thus an outdated ‘‘cultural knowledge pool.’’ However, they predict that natural selection will act against reliance on social learning when doing so is based on such flawed information. Thus, when acquisition of personal information is costly (see Section II), conformity, or frequency‐dependent social learning (see Boyd and Richerson, 1985; Day et al., 2001), should be weaker in fluctuating than in stable environments, ensuring that cultural knowledge tracks environmental change. These models predict that individuals should acquire personal information and ignore social information, when the latter is likely to be outdated. Equally, individuals should opt to frequently update information, if the use of their current information, whether acquired asocially or socially, is likely to be costly due to its being outdated. 2. Empirical Evidence a. Foraging i. Fish In another experimental study of nine‐spined sticklebacks, van Bergen et al. (2004) manipulated the degree to which personal information, regarding the profitability of two foraging patches, was outdated and explored how this prior experience affected individuals’ subsequent acquisition of public information. Again, a similar experimental design as Coolen et al. (2003; see Section II.B.1.a and Fig. 3) was used. Fish were allocated to four conditions, where they received personal information as to which of two feeders was ‘‘rich’’ and which ‘‘poor,’’ either 1, 3, 5, or 7 days prior to receiving conflicting public information individually. Immediately following the conflicting demonstration and the removal of demonstrators, the fish were tested to see which feeder they visited first. Fish with only a 1‐day delay between receiving personal and public information ignored the social information and first visited the feeder that was ‘‘rich’’ according to their personal information. Fish with delays of three and five days since acquiring their personal information showed no feeder preference, and those experiencing a 7‐day delay first visited the feeder that was ‘‘rich’’ according to the public information (Fig. 8). Accepting van Bergen et al.’s arguments that personal information was not forgotten after 7 days, comparison with results from Coolen et al. (2003), where fish received public information only, appeared to indicate that fish in the 7‐day condition instead ignored their personal information in favor of the public information. Thus, in accordance with the theory, as personal

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Fig. 8. (Fig. 3A from van Bergen et al., 2004) The proportion of nine‐spined sticklebacks that, after receiving personal information followed at varying time lags by conflicting public information, entered first the goal zone of the feeder that was ‘‘rich’’ according to personal information. The dashed line indicates the proportion expected at random, and the hatched bar represents data from Coolen et al. (2003). *p < 0.05, **p < 0.005, n.s. indicates not significant (van Bergen, Y. et al., 2004; used with permission of the Royal Society of London).

information becomes increasingly outdated, nine‐spined sticklebacks become increasingly reliant upon socially acquired information. Although not specifically tested, this reliance upon the more recently acquired source of information could equally apply if personal information follows social information. ii. Mammals In a study involving several species of domestic dogs, Pongra´ cz et al. (2003) trained dogs to acquire a food reward through a door in a fence. Upon closing of this door, which prevented dogs from using their personal information, those dogs that saw a demonstrator detour around the fence learned to do the same to obtain the reward, and they learned more quickly than did those with no such demonstration. Confirmation of theoretical predictions was not the authors’ aim, and although the study demonstrates that social information was used when personal information was no longer useable, hence outdated, it lacks a condition enabling assessment of the extent to which dogs would have used the social detour information when their personal information was a concurrently available alternative to social information.

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Galef and Whiskin (2004) assessed Boyd and Richerson’s (1988) prediction that animals will show greater reliance on social learning in relatively stable, rather than rapidly changing, environments. Observer rats were assigned to a variable‐environment group, where over 12 days they experienced random variation in time, location, duration, and type of food presented; and a stable‐environment group, that each day received the same food in the same location, at the same time, and for the same length of time. On the 13th day, a demonstrator rat that had eaten either cinnamon‐ or cocoa‐flavored food (both novel to observers) was placed in each observer’s cage for 30 minutes. Following this, observers were provided with equal amounts of cinnamon‐ and cocoa‐flavored food for 22 hours. Although observers in both the variable‐ and stable‐environment groups consumed more of the food that their demonstrator had eaten, those in the stable‐environment condition did so to a significantly greater extent than those in the variable‐environment group. As this study did not pit personal information against social information, both cinnamon and cocoa flavor being novel to observers, it is not possible to fully assess whether the rats relied more heavily on personal or social information in environments of differing variability. Nonetheless, the behavior of the rats is consistent with their increasing reliance on copying as the expected reliability of transmitted information increases. We do not have, however, any evidence to suggest that rats in the stable‐environment condition would have favored social over personal information to a greater extent than did those in the variable‐environment condition. In fact, the reverse may well have occurred, were variable‐environment rats to consider their personal information to be outdated relative to the social information gleaned from the breath of the demonstrators. b. Mate choice i. Birds There is some circumstantial evidence that Japanese quail are sensitive to the possibility that their social information regarding mate choice is outdated. In this species, there appears to be a sex difference in the extent to which sources of information become outdated. Although we refer to the value of outdated social information here, rather than personal information, it is interesting to note that males avoid a female they just saw mating, most likely because of sperm competition. However, 2 days later, males no longer avoid females they saw mating earlier; at this point, first male precedence, in sperm competition, is thought to give way to last male advantage (Birkhead et al., 1995), and social information regarding female unsuitability becomes outdated (White and Galef, 2000). Until empirical tests are carried out, however, we cannot rule out the possibility that males simply forget social information concerning females after 2 days. In contrast, for females, social information regarding a male’s quality remains

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valuable in the future (over 2 days; White and Galef, 2000). The fact that female quails can remember social information about mate quality after two days hints at a similar capacity of information retention in males of the same species, and it suggests that the discarding of 2‐day‐old social information by males is due to a decision to do so rather than mere forgetting. c. Monetary reward i. Mammals Using human subjects, Kameda and Nakanishi (2002) tested their prediction that, in a variable environment, individuals will be less likely to conform (or copy the majority) to the behavioral decisions of others with increasing costs of acquiring personal information (see Section III.C.1). A fluctuating environment was created through the use of a computer game where subjects had to guess whether a rabbit was located in one of two holes, over 60 trials. As the rabbit had a non‐perfect tendency to remain in the same hole over time, the location of the rabbit corresponded to the current state of the fluctuating environment. The subjects were told that they would earn money for every trial in which they guessed the location of the rabbit correctly. Each individual played the computer game in isolation but at the same time as five others, and they could use personal or social information. Social information was free and always visible. It consisted of a random selection of three of the other players’ decisions in the previous trial. Personal information through assistance from a ‘‘rabbit search machine’’ had to be paid for. Depending upon condition, acquisition of personal information cost either 50% (high cost condition) or 16.7% (low cost condition) of the reward for successfully locating the rabbit in that trial. A table of accumulated rewards, of all six players, was displayed to players after every five trials, thereby enabling adaptive learning of strategies. As expected (see Section II), individuals used personal information to a lesser extent when it was costly to acquire than when it was relatively cheap. In addition, under these changeable conditions, conformity to the majority decision of the previous trial in the current trial choice was greater when personal information was cheap to acquire than when it was costly; due to the increased cost of acquiring personal information, fewer players acquire it, and thus the prior majority decision would constitute unreliable information. This was true, irrespective of whether the majority decision matched the individual’s decision in the previous trial. These results support the theoretical prediction that social information will be valued to a lesser extent in contexts where it is likely to be outdated, in this case as everybody is attempting to avoid the cost of acquiring personal information, and thus contributes less to the renewal of social information. However, in this experiment, individuals did not make an active choice to

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acquire social information, merely as to whether to use it; thus, it is questionable that this study can be directly compared to the theoretical analyses of Boyd and Richerson (1985, 1988). In addition, the experiment does not evaluate the degree of conformity, with regard to the cost of acquiring personal information, in a non‐fluctuating or less‐changeable environment, which we might expect to increase with the costs of asocial learning. In sum, it appears that empirical evidence indicating that individuals rely increasingly heavily on social information as personal information becomes outdated is, as yet, rather limited. What evidence there is, however, does cover several different species, including humans, and pertains to the domains of foraging, mate‐choice, and monetary reward. Considering how widely researchers cite the benefits of social learning in variable environments, there is a surprising lack of experiments designed explicitly to test this prediction.

IV. IMPLICATIONS

FOR

SOCIAL LEARNING RESEARCHERS

This review has surveyed a rapidly growing field of empirical study that supports the existence of ‘‘social learning strategies’’ (Laland, 2004), corresponding to trade‐offs in animals’ reliance on social and asocial sources of information. In the following sections, we consider the broad implications of the reliance of animals on such strategies for researchers studying social learning processes.

A. COPY WHEN ASOCIAL LEARNING IS COSTLY 1. Plausibility of Social Learning in the Wild The accumulating evidence for a strategy of copy others when asocial learning is costly may guide field researchers in their expectations as to which behavior patterns, observed in the wild, are likely to have been learned socially. As stated by Byrne (1999; Byrne and Russon, 1998) there are some behavior patterns for which asocial learning may appear to be a contrived alternative to social learning. For example, Byrne and Russon (1998) proposed that certain food‐processing skills, seen in gorillas, are too complex and costly for an individual to acquire asocially. Here, the costs of time, energy, and physical discomfort, involved in acquiring personal information as to how to process physically and chemically defended plants successfully, point towards the use of social information. Such reasoning is now bolstered by empirical support for the tenet that reliance on social

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learning increases with the costs of asocial learning, and by the findings of theoretical analyses. However, this support merely enhances the probability that a plausibility argument is correct, and it does not negate the need for experimental evaluation (Galef, 2004). For example, reproductive information may be particularly costly to acquire asocially (as a whole breeding year may be lost), and social information use may allow circumvention of these costs. In fact, several species of birds have been reported to rely on the observed reproductive success of conspecifics to make their breeding habitat choice (Brown et al., 2000; Doligez et al., 1999), an observation confirmed through experimental manipulation (Doligez et al., 2002). Such findings also point to the validity of the converse argument. It follows that researchers might question the legitimacy of putative cultural traits that are relatively simple and cheap to acquire asocially. Several of the empirical findings reviewed here appear to indicate that the costs associated with acquiring or using personal information may promote the evolution of increasingly complex social learning processes. In Coolen et al.’s (2003) study of foraging in sticklebacks, public information use, which is often regarded as cognitively more complex to acquire and utilize than other types of social information such as local enhancement (Valone and Templeton, 2002), was reported for nine‐spines but not for three‐spines, which was interpreted as reflecting the greater cost of acquiring personal information for nine‐spines. Similarly, in an attempt to account for the relative lack of evidence for imitation in frugivorous monkeys compared to birds, Zentall (2004) argues that birds may face greater costs associated with asocial learning because they are generally smaller and have higher energetic needs than monkeys, and because their seed‐based diet requires learning of complex extractive foraging techniques. In discussing the evolution of human culture, Castro and Toro (2004) suggested that the greater the difficulty or cost of developing a behavior through asocial learning, the greater the selection pressure in favor of the development of imitative processes, ensuring rapid information acquisition. This argument might also generalize to the process of ‘‘emulation,’’ where the observer duplicates the results of others’ behavior, but not the means of achieving them (Tomasello, 1990), and perhaps to other social learning processes. Note: implicit in this argument is Castro and Toro’s assumption that imitation allows the learning of behavior patterns for which indirect social learning processes (e.g., stimulus enhancement, response facilitation) are insufficient, and that imitation facilitates more rapid learning than alternative processes. A pragmatic stance would be to assume that behavior patterns are unlikely to be cultural in cases where asocial learning is ‘‘cheap’’ enough to accomplish the task in question, but plausible in cases where asocial

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learning is costly. However, we guard against reliance on subjective impressions of the difficulty or cost of asocial learning, which can be misleading. For example, in a study of grubbing in woodpecker finches (Cactospiza pallida), Tebbich et al. (2001) demonstrate that the use of cactus spines, as extractive foraging tools, is not socially learned but instead develops by trial‐and‐error learning during a sensitive period of development. Rather, we wish to encourage the evaluation of the costs of asocial learning through direct experimentation. Such experiments will not only add weight to arguments concerning the plausibility of putative cases of culture but also generate data that can be employed to determine the probability of social learning statistically (see Laland and Kendal, 2003). 2. Suboptimal Cultural Traditions Where the acquisition or use of personal information is costly compared to the acquisition or use of social information, the use of social information may be adaptive for an individual, even where that information results in suboptimal traditions. In game theory terms, traditions may be Nash equilibria if it never pays anyone to abandon them unilaterally. Individuals may be locked into conventions by virtue of their being penalized by the (asocial learning) costs of breaking the convention, resulting in traditions tracking changing environments less efficiently than individual learners, and only slowly, or never, converging on the global optimum. Such maladaptive traditions have been reported in animals and humans (Boyd and Richerson, 1985; Cavalli‐Sforza and Feldman, 1981; Laland and Williams, 1998; see also Section II.B.1.a; Pongra´ cz et al., 2003) and may have evolutionary implications. Similarly, Giraldeau et al. (2002) discuss a number of possible cases where maladaptive behavior may spread as a result of informational cascades, where individuals base behavioral decisions on the prior decisions of others. They proposed that the propensity to use social information depends upon the costs of engaging in erroneous cascades. For example, they posit that in the case of birds learning how to evade a predator, the cost of an erroneous cascade may be small (loss of time that could otherwise be allocated to foraging) relative to its benefits (successful evasion of a predator). However, were the costs of an erroneous cascade to be increased, for instance if birds were seriously food deprived, such that the risk of death by starvation approaches predation risk, animals might be expected to pay less attention to their companion’s decisions to flee and to require a stronger, more predictive personally acquired cue to pass up on a foraging opportunity. It is conceivable that where the costs of personal mate choice are extremely high, most individuals will copy others, potentially resulting in maladaptive mate choice due to erroneous informational cascades, based

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upon the initial choice of one or a small number of individuals (Losey et al., 1986). In a study of lekking sage grouse, Gibson et al. (1991) reported that the decisions of females using personal information to decide whom to mate with were more closely correlated with male phenotypic traits indicating quality than were the decisions of individuals using social information. This was thought to be due to females copying the mate choice of other females who had not themselves assessed male quality directly (i.e., an informational cascade). As mate‐choice copying resulted in increased variance in male mating success and a reduced correlation between male quality and male reproductive success, Gibson et al. (pp. 178) stated that ‘‘the variance in male mating success on leks is inversely related to the strength of sexual selection on male traits.’’ Similarly, Gibson and Ho¨ glund (1992) predict that where mate‐choice copying is primarily a cost‐reduction strategy, the relationship between male quality and mating success will be noisier, resulting in unpredictable ‘‘fads’’ in the characters that females find attractive and a lowering of the intensity of sexual selection. This occurs because most individuals will use social information, and males will rarely be directly sampled, resulting in mate choice becoming increasingly divorced from male quality. In contrast, where mate‐choice copying is due to uncertainty on the part of females, or an inability to discriminate between males, copying should increase the intensity of sexual selection (see Section IV.B.2).

B. COPY WHEN UNCERTAIN 1. Plausibility of Social Learning in the Wild Dewar (2003a, 2004) argued that her proposed cue reliability approach (see Section III.B.2.a) has two important implications for the study of social learning: (1) it encourages researchers to consider why animals might try a novel behavior for the first time; and (2) it provides a new test for identifying behavioral traditions in the wild. The latter is based on the hypothesis that, if convergent asocial learning can be ‘‘ruled out’’ because individuals lack reliable asocial cues, a case can be made that a widespread behavior is traditional, since social cues are the only cues that exceed the reliability thresholds constraining individuals. Conversely, where personally acquired information is reliable, foragers do not need to use social information in order to decide what is safe to eat. Thus, a unique shared dietary preference in one population, which is absent in other populations, cannot always be assumed to be a cultural tradition. In an argument akin to the ecological independence of population‐level differences in chimpanzee behavior patterns (Whiten et al., 1999), Dewar (2003a, 2004) proposes that the possibility that reliability thresholds vary across environments must be

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eliminated before cultural differences can be assumed. She states (2004, p. 87) that the case for a behavior being cultural is ‘‘strongly supported if social cues are the only reliable cues available. If, however, asocial cues are also reliable, more caution is warranted.’’ This novel approach may well result in new insights. It does not require direct observation of social transmission, which may make it a practical method for determining whether behavior seen in the wild is traditional. In addition, its strongly quantitative emphasis allows evaluation using conventional statistical tools. However, the approach is restricted to situations where individuals must decide whether to treat unfamiliar stimuli as profitable or safe, and it is of little use for the study of traditions involving complex behavioral sequences. It also remains to be shown whether the complex environments of natural populations make it realistic to collect the data necessary to calculate payoffs and reliability thresholds and indeed whether the model itself provides a close fit to the real world (Dewar 2003). 2. Sub‐Optimal Cultural Traditions Giraldeau et al. (2002) proposed that the point at which an informational cascade begins (i.e., when an individual adopts the behavioral ‘‘decisions’’ of others despite the absence of the cue, or ‘‘signal,’’ to which they responded) may depend upon the uncertainty involved in the signal. For example, the moving of a branch is a signal only loosely associated with the approach of a predator, compared to the sight of the predator itself. In the former case, an informational cascade may take longer to begin, involving the prior decisions (fleeing) of more individuals, than the latter case. Indeed, Blumstein et al. (2004) found yellow‐bellied marmots responded more strongly to an equivalent number of alarm calls apparently emitted by two individuals than by one. As discussed in Section III.B.2.c, Blumstein et al. (2004) found that the necessity of avoiding missed opportunities, for activities other than antipredator behavior, requires an assessment of the reliability of social information provided by alarm callers and thus may have promoted the evolution of individually distinctive alarm calls. The growing body of literature concerning the responsiveness of individuals to alarm calls of different individuals (see Blumstein et al., 2004 and references therein) merits further discussion in consideration of social learning strategies dictating from whom individuals learn (see Laland 2004). Rafacz and Templeton (2003) in their study of starlings, outlined in Section III.B.2.a, reported an example of an arbitrary, personally acquired behavior. Of the birds assigned to conditions of varying environmental predictability and demonstrator informativeness, only those in the unpredictable environment and uninformative demonstrator condition developed arbitrary color aversions and color preferences. Those individuals in

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the predictable environment and uninformative demonstrator condition did not develop such biases, despite the fact that their demonstrators also provided irrelevant information pertaining to the utility of color cues in locating food. This occurs because it is only in the unpredictable environment that the birds required social information to assist their foraging decisions. The use of social information in unpredictable environments may prevent the development of erroneous personal behavior. The apparent delay before which individuals in the unpredictable environmental condition with informative demonstrators exhibited greater foraging success than those with uninformative demonstrators led Rafacz and Templeton (2003) to assert that individuals may need to learn to recognize when social information is more valuable to them than personal information. This is consistent with Kendal et al.’s (2004) finding that individuals appear preferentially to rely on personal over social information. Both the characteristics of a species and the predictability of the environment that it inhabits will influence to what extent animals value social information. For example, Klopfer (1959, 1964) found that dietarily conservative greenfinches (Chloris chloris) relied on social over personal information in a foraging experiment, whereas more opportunistic great tits (Parus major) did not. As indicated by Coussi‐Korbel and Fragaszy (1995), highly social species might have greater social tolerance (e.g., tolerance of close proximity of others during foraging), which may conceivably favor placing a higher value on social information than do less social species (van Schaik, 2003). Conceivably, there will be a delay before animals recognize the altered value of different sources of information, in response to a change in environmental predictability. In contrast to when mate‐choice copying functions to reduce the cost of mating decisions (see Section IV.A.2), Gibson and Ho¨ glund (1992) predict that where it functions to reduce the uncertainty of mating decisions (e.g., due to an inability to discriminate accurately between males), copying should increase the intensity of sexual selection. The argument here is that erroneous informational cascades would not be expected, as only those individuals who were unable to discriminate accurately (e.g., due to inexperience) will copy the choices of others, and a substantial proportion of the female population will directly sample the males and choose mates according to personally acquired information. C. IMPLICATIONS

FOR

THEORETICAL MODELS

OF

SOCIAL LEARNING

These findings have several implications for mathematical models of social learning. First, as individuals appear to switch between reliance on social and asocial sources of information in a flexible and facultative

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manner, theoretical models of social transmission would benefit from the routine incorporation of both asocial and social learning processes, rather than treating each as an entirely separate process, as they often do (Galef, 1995). Second, models would benefit from assuming variation in (1) the reliability of social and asocial information, and (2) individual and species differences in the propensity to exploit these two types of information. These two factors will depend on the costs associated with acquiring and using social and asocial information, as well as the level of noise associated with information acquisition and the rates of change of relevant features of the environment. Third, evidence is emerging that animals may not weight social and asocial information equally, as has frequently been assumed in social foraging models (e.g., Clark and Mangel, 1984; Valone and Giraldeau, 1993; Templeton and Giraldeau, 1995a, 1996). By highlighting these current issues concerning potential trade‐offs between reliance on social and asocial information, it is hoped that further empirical work testing the assumptions and predictions of theoretical models of social learning will be forthcoming.

V. GENERAL DISCUSSION A. THE EVOLUTION

OF

SOCIAL LEARNING ABILITIES

Many researchers have suggested that social learning abilities may be more strongly associated with ecology than taxonomy (Coolen et al., 2003; Fragaszy and Visalberghi, 1996; Klopfer, 1959; Lefebvre and Palameta, 1988; Zentall, 2004), a position that we endorse. Yet the belief that social learning is particularly important to large‐brained species, or to animals closely related to humans, remains widespread. Consideration of the social learning strategies outlined in this review may help to explain why social learning is more prevalent in some populations, and in some species, compared with others. If individuals use social information when personal information is costly, unreliable, or easily outdated, then there may be differing propensities for social learning in populations for which survival demands vary along these dimensions. For example, populations at greater risk of predation when they collect personal information will be more likely to use social information than others less at risk (e.g., sympatric sticklebacks; Coolen et al., 2003). Dietarily conservative species are exposed to the kind of slowly changing environmental conditions that favor reliance on social learning, whereas generalists are exposed to the kind of rapidly changing and spatially heterogeneous conditions that favor asocial learning (e.g., Klopfer, 1964; but see Dall and Cuthill, 1997, for theoretical evidence

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indicating that generalists may be more reliant on social learning than specialists in order to reduce sampling costs). Among food‐caching species, there may be a greater reliance on social information in those that cache perishable, rather than non‐perishable, foods, as information relating to the edibility of personally cached foods is likely to be outdated relative to the recently observed caches of others (e.g., Clayton and Dickinson, 1998). There may also be a greater reliance on social information in species that use complex foraging skills or must overcome challenging prey defenses, compared to those that do not (e.g., folivorous vs. frugivorous species: Fragaszy and Visalberghi, 1996; extractive vs. non‐extractive foragers: Day et al., 2003; Zentall, 2004). However, as highlighted by Lefebvre and Giraldeau (1996), there are many problems inherent in drawing general inferences on the basis of comparative studies of social learning. The majority of empirical evidence reviewed here avoids these issues by assessing whether the use of social information is an adaptive specialization to specific ecological conditions within a species. Consideration of social learning strategies may also help to explain why social learning is more prevalent in some populations than others. For example, it is possible that there is a greater propensity for social learning in populations exposed to ‘‘risky’’ environments compared to benign ones (e.g., guppies living in high predation sites; Reader, 2000), where the costs of individual assessment of these risks are likely to be high. Similarly, populations at the periphery versus the center of their species range or those exposed to greater climatic variability may have a greater need for social learning to enable them to cope with the increased demands of these environments (Reader and MacDonald, 2003). In a similar vein, it is interesting to note that ‘‘social release’’ of conformity to a socially learned escape route is more readily achieved in domesticated guppies tested in the laboratory (Brown and Laland, 2002) than wild guppies tested in the wild (Reader et al., 2003). Wild guppies may be under stronger selection to shoal and minimize predation risk than are domestic guppies (Reader et al., 2003). Consequently, it is conceivably more costly for wild guppies to acquire personal information about alternative escape routes than to use social information and conform to the majority, while this balance is tipped the other way in domestic strains. B. FUTURE DIRECTIONS There are several social learning strategies for which empirical evidence is, as yet, lacking. Even those strategies that have been subject to attention are largely supported by circumstantial rather than direct evidence. As noted by Peake and McGregor (2004) and Griffin (2004), the use of social

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information in communication, aggression, and anti‐predator behavior is relatively understudied; and it would seem ripe for tests of costs and uncertainty involved with the acquisition and use of personal information. Similarly, there is a paucity of data regarding the strict interpretation of Boyd and Richerson’s (1988) assumption that animals copy others when they are uncertain as to which pre‐established behavior pattern is appropriate in a given context. In addition, despite the fact that social learning researchers commonly introduce their subject matter by quoting Boyd and Richerson’s predictions regarding the costs of outdated information, very few studies have addressed this issue empirically. More specifically, there are many outstanding questions that would make interesting avenues for future research. First, we have not touched upon social learning strategies regarding from whom individuals should learn (see Laland, 2004), partly because this topic remains relatively unexplored. It is quite probable that such strategies as copy the majority, copy successful individuals, copy kin or familiar individuals, and copy older individuals, will interact with the when strategies outlined in this review. (Indeed the who/when division breaks down in some cases, for instance, where individuals copy any other that is reaping greater benefits than they.) We may ask whether the expected strategy of using social information if, and only if, personal information is costly, unreliable, or outdated, is violated when social information is provided by individuals with the characteristics listed above. For example, many of the studies reviewed here (e.g., Kendal et al., 2004; van Bergen et al., 2004) could be extended through replication with conditions of varying demonstrator characteristics. A second avenue of research is the possible interaction of observer characteristics and social learning strategies. To what extent do state‐ dependent factors (such as social status, hunger, age, and sex), and individual differences (in for example, neophilia/neophobia and mental abilities) influence the use of social learning strategies regarding both when individuals use social information and from whom they acquire it? For example, in Kendal et al.’s (2004) study (see Section II.B.1.a), a small proportion of trained‐observer fish continued to use their personal information, despite its apparent cost and the availability of social information. It would seem likely that there are individual differences in the tendency of guppies to weight one source of information over the other, as seen in foraging great tits (Marchetti and Drent, 2000). Characteristics of observers favoring the overriding of social learning strategies and the continued acquisition of personal information may be influential in determining innovatory capacities of individuals. While social learning strategies have provided a useful framework with which to structure this review, some potential limitations to the framework

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are considered briefly here. First, in most instances, it remains to be established whether animals are actually employing these strategies and whether they do so consistently. There may not be uniform patterns in animals’ reliance on unlearned and learned behavior, or on asocial and social information. All that can be claimed is that an animal’s behavior is (or is not) consistent with one or more of the proposed social learning strategies. Second, we do not know what specific cues animals attend to when their behavior appears to be consistent with a social learning strategy. For instance, it may be difficult to distinguish between animals copying successful individuals, animals copying the successful behavior of other individuals, or animals responding to some correlated cue that may signal prior success. Third, social learning strategies are potentially not mutually exclusive, and animals may well apply combinations of these strategies. For instance, animals may copy familiar individuals when uncertain as to what to do because relevant asocial information is lacking. Fourth, at this stage, it is not entirely clear whether the hierarchical approach proposed by Laland (2004), which posits that animals would use social information when asocial learning proves ineffective and only resort to innovation when both social and asocial information leave them uncertain as to what to do, reflects the actual decision‐making processes of animals. Such new frameworks must not only be proposed but also tested, employing both theoretical and empirical approaches, if we are to gain new perspectives for future work in the field of social learning.

VI. SUMMARY Theoretical models investigating the adaptive advantages of social learning conclude that social learning cannot be employed in a blanket or indiscriminate manner, and that individuals should adopt flexible strategies that dictate the circumstances under which they copy others. As highlighted in this review, laboratory and captive‐population based evidence is amassing, mostly with regard to foraging and mate choice, indicating that individuals preferentially rely on personally acquired information, but acquire and use social or public information (i) when asocial learning would be costly, or (ii) when asocial learning leaves them uncertain as to what to do. Individuals ignore social cues when they have relevant personal experience but rely on social learning when the costs of acquiring or implementing personal knowledge is high, when they are uncertain of the optimal behavior, when their personal information is unreliable, or when it has become outdated. We encourage theoreticians to incorporate social learning strategies into their models and empiricists to evaluate and test explicitly the assumptions

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and predictions of such models, even where they are already widely accepted. It is hoped that consideration of the trade‐offs inherent in the adaptive use of social and asocial learning will contribute to an increased understanding of the observed pattern of social learning processes and behavioral traditions in the animal kingdom, especially as the use of social information may lead to cultural evolution, which may in turn affect biological evolution (Danchin et al., 2004). The hypothesis that individuals increasingly rely on social learning as the costs of asocial learning increase potentially explains the existence of maladaptive cultural traditions in humans and other animals. Furthermore, consideration of social learning strategies may explain why evidence for complex social learning processes appears to be related to ecological rather than taxonomic affinities among species.

Acknowledgments RLK would like to thank Deborah Gordon of Stanford University for generously providing writing facilities. IC was supported by a European Community postdoctoral fellowship (under the ‘‘Information Society Technologies‐IST’’ Programme, Future and Emergent Technologies (FET), Lifelike Perception System action), and YvB by a Biotechnology and Biological Sciences Research Council PhD studentship. We would like to thank Jeremy Kendal for stimulating discussion and Sasha Dall, Peter Richerson, Peter Slater, and Charles Snowdon for helpful comments on an earlier draft of this paper.

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Index

A Acoustic communication in noise background noise characteristics, 151–152 sources, 152–153 prospects for study, 192–194 signal perception auditory scene analysis cocktail party analogy for birds, 186–189 signal space concept, 189–191 top-down versus bottom-up processing, 183–186 hearing ecology, 169–172 sensory adaptations amplitude and duration dependence, 176–177 feature detectors, 180–182 masking release using noise characteristics, 177–180 spectral sensitivity and pitch processing, 172–176 signal production long-term adaptations acoustic signal structure changes, 155–158 communication channel utilization, 158–159 short-term adaptations serial redundancy regulation, 165 signal amplitude regulation, 160–161, 163–164 signal duration regulation, 164–165 signal timing adjustment, 167–168

spectral characteristic regulation, 166 signal-to-noise ratio optimization, 154 Adaptive social learning, see Social learning African running frog, communal sexual displays, 49–50 Aggression, see Chimpanzee Animal research ethics animal rights origins, 212–214 assessment benefits of research, 224–225 suffering, 225–229 cognitive capacity arguments, 216–217 empathy concerns, 214–215 ethical arguments for animal research, 218–220, 230 killing concerns, 215–216 resolution of opposing views, 220–224 suffering minimization, 215–217, 229–230 Arctiid moth, communal sexual displays, 16 Arousal, prenatal sensory ecology studies in precocial birds, 252–256 Attention communal sexual displays and selective attention, 40–44 prenatal sensory ecology studies in precocial birds, 253–256 Auditory scene analysis, see Acoustic communication in noise Australian bushcricket, acoustic communication in noise, 173 381

382

INDEX

B Baboon, ovulation, 117 Barking treefrog, acoustic communication in noise, 191 Barn owl, acoustic communication in noise, 17, 175 Bats acoustic communication in noise, 172, 180 frog communal sexual displays and predation, 31 Beacon hypothesis, communal sexual display synchronization, 29 Beluga whale, acoustic communication in noise, 166 Bengalese finch, acoustic communication in noise, 187–188 Bewick’s wren, acoustic communication in noise, 167 Birds, see also specific species acoustic communication, see Acoustic communication in noise prenatal sensory ecology, see Prenatal sensory ecology, precocial birds social learning exploitation costly asocial learning conditions foraging, 342 mate choice, 344–345 prior information unreliability in foraging, 354–355 relevant information deficiency in foraging, 348–349 Blackcap, acoustic communication in noise, 186 Black-faced warbler, acoustic communication in noise, 155 Blue monkey, acoustic communication in noise, 177 Bobwhite quail, see Prenatal sensory ecology, precocial birds Bottlenose dolphin, acoustic communication in noise, 177 Brown thrasher, acoustic communication in noise, 187

Budgerigar, acoustic communication in noise, 161 Byproduct mutualism, communal sexual displays alternation benefits, 31–33 synchronization beacon hypothesis, 29 predator evasion, 30–31 rhythm-preservation hypothesis, 29–30

C Caloric density, feeding behavior studies, 69–71 Canary, acoustic communication in noise, 181 Cat acoustic communication in noise, 176, 185 feeding behavior studies, 69 Cattle, acoustic communication in noise, 179 Chicken, crop storage, 85 Chimpanzee advantages of behavioral studies, 276 community demography and ecology, 277–278 conflict between groups aggression against females and infants, 294–295 aggression against males, 292–294 functional explanations, 297–298 human interference effects on studies, 298–299 overview, 291–292 proximate mechanisms, 295–296 conflict within groups female–female competition, 289–291 male aggression against females, 287–289 male–male competition and status

INDEX

ranking, 280–281 reproductive advantage, 282–287 survival benefits, 281–282 overview, 278–279 cooperation coalitions and alliances, 300, 302–304 competition interactions, 317–320 evolutionary mechanisms, 314–317 grooming, 304–307 hunting, 308–311 meat sharing, 312–314 territoriality of groups, 307–308 long-term field studies, 276–277 ovulation, 117 Chinchilla, acoustic communication in noise, 177 Cicadas, communal sexual displays Magicacada cassini, 3, 5 overview, 2–3 Closed economy, feeding behavior analysis, 64–65 Cocktail party, auditory scene analysis analogy for birds, 186–189 Communal sexual displays byproduct mutualism alternation benefits, 31–33 synchronization beacon hypothesis, 29 predator evasion, 30–31 rhythm-preservation hypothesis, 29–30 cicadas Magicacada cassini, 3, 5 overview, 2–3 coupled oscillators, 24–25 feedback loops, 50–52 fireflies Photinus pyralis, 6–7 Pteroptyx malaccae, 5–6, 53 general features, 14 katydids Ephippiger ephippiger, 9, 44, 51

383

Mecopoda, 8 Neoconocephalus spiza, 10–11, 29, 41, 44, 51 Pterophylla camellifolia, 8–9 phase response curves and modeling of adjustable oscillator interactions, 25–28 prospects for study, 52–53 rationale for study, 1–2 receiver psychophysics epiphenomenon model, 44–48 evolutionary stability of signal interaction mechanisms, 37, 39–40 preference of signal order, 33–35, 48–50 selective attention within communal displays, 40–44 signaler response, 35–37 signal interactions in reflected light and vibration, 13–14 snowy tree cricket, 7–8, 29 structural elements endogenous oscillators, 17 phase-resetting mechanisms phase advance, 19 phase delay, 19, 21–23 stochastic behavior, 23 temporal clustering, 15–17 terminology, 4 Tu´ ngara frog, 11, 41 Comodulation masking release, acoustic communication in noise, 177 Competition, see Chimpanzee; Tufted capuchin Concave-eared torrent frog, acoustic communication in noise, 155 Consumption cost, functional analysis of feeding, 70, 91–97 Cooperation, see Chimpanzee Coqui treefrog, acoustic communication in noise, 168 Coupled oscillators, communal sexual displays, 24–25

384

INDEX

Cryptic female choice, Tufted capuchin, 136 Cue reliability, adaptive social learning, 357–358

D Decision cube, resolution of opposing views in animal research, 222–223 Depletion-repletion model, feeding behavior, 67 Deprivation, functional analysis of feeding, 83, 85–87, 89 Dog, social learning, 361 Dove, acoustic communication in noise, 190–191 Duck, prenatal sensory ecology, 246, 249, 254 Dunnock, acoustic communication in noise, 186

E Elephant, acoustic communication in noise, 172 Epiphenomenon model, communal sexual displays, 44–48 ESS, see Evolutionary stable strategy (insert i1) Ethics, see Animal research ethics European blackbird, acoustic communication in noise, 171 European starling, acoustic communication in noise, 187 Evolutionary stable strategy, (insert i1), phase adjustment of communal sexual displays, 37, 39–40

F Fallow deer, social learning, 345 Feeding behavior, functional analysis

choice of food, 79, 81–83 consumption cost versus foraging cost, 91–97 currency of procurement cost, time versus effort, 77, 79 deprivation studies, 83, 85–87, 89 distinction from classical analysis approach consumption versus foraging, 67–71 open versus closed economies, 64–65 reinforcement versus global contigencies, 71, 73, 75–77 single responses versus bouts of behavior, 66–67 history of study, 63–64 optimal resource exploitation, 99 satiation studies, 89–91 Female competition chimpanzees, 289–291 tufted capuchins, 134–135 Female proceptivity, see Tufted capuchin Fiddler crab, communal sexual displays, 48 Fireflies, communal sexual displays Photinus pyralis, 6–7 Pteroptyx malaccae, 5–6, 53 Fish, see also specific species acoustic communication in noise, 184 social learning exploitation costly asocial learning conditions aggression, 346 foraging, 336–342 mate choice, 343–344 prior information unreliability in foraging relevant information deficiency foraging, 347–348 mate choice, 351 Foraging chimpanzee cooperation hunting, 308–311 meat sharing, 312–314

385

INDEX

consumption distinction, 67–71 cost in functional analysis of feeding, 91–97 functional analysis, see Feeding behavior, functional analysis social learning birds, 342, 348–349, 354–355 fish, 336–342, 347–348, 352–354, 360–361 mammals, 342–343, 349–350, 355–357, 361–362 Frogs, see also specific species acoustic communication in noise, 155, 159, 168, 181, 190–191 communal sexual displays, 11, 31, 41, 49–50 G Gecko, acoustic communication in noise, 175 Gobies, acoustic communication in noise, 172–173 Goldfish, acoustic communication in noise, 184 Grasshopper, acoustic communication in noise, 178 Great tit acoustic communication in noise, 157–158 social learning, 369 Green treefrog, acoustic communication in noise, 191 Greenfinch, social learning, 369 Grey-cheeked mangabey, acoustic communication in noise, 177 Grooming, chimpanzees, 304–307 Guppies, social learning, 337 H Hearing, see Acoustic communication in noise Hearing ecology, acoustic communication in noise, 169–172

Horse, acoustic communication in noise, 179 Hourglass treefrog, acoustic communication in noise, 181, 191 Hunting, cooperation in chimpanzees, 308–311 I Inbreeding, avoidance by tufted capuchins, 138–139 Infanticide chimpanzees, 294–295 tufted capuchin, 128–129 Internal milieu, functional analysis of feeding behavior, 66–67, 85, 89 J Japanese quail, social learning, 345 K Katydids acoustic communication in noise, 167 communal sexual displays Ephippiger ephippiger, 9, 44, 51 Mecopoda, 8 Neoconocephalus spiza, 10–11, 29, 41, 44, 51 Pterophylla camellifolia, 8–9 Killer whale, acoustic communication in noise, 165 King penguin, acoustic communication in noise, 165, 188 L Large-billed leaf warbler, acoustic communication in noise, 155–156 Learning prenatal sensory ecology studies in precocial birds, 257–262 social learning, see Social learning

386

INDEX

Little greenbul, acoustic communication in noise, 157 Lombard effect, signal amplitude regulation in acoustic communication in noise, 160–161, 163–164

M Macaque, acoustic communication in noise, 185 Male competition chimpanzees conflict between groups aggression against females and infants, 294–295 aggression against males, 292–294 functional explanations, 297–298 human interference effects on studies, 298–299 proximate mechanisms, 295–296 conflict within groups aggression against females, 287–289 ranking, 280–281 reproductive advantage, 282–287 survival benefits, 281–282 tufted capuchins postcopulatory competition courtship after copulation, 132–133 sperm competition, 130–131 sperm plug, 131–132 precopulatory competition aggressive competition, 127–128 infanticide, 128–129 non-aggressive competition, 129 Marginal value theorem, feeding behavior, 96–97 Marmoset acoustic communication in noise, 164 social learning, 343

Marmot, social learning, 358 Masking release, acoustic communication in noise, 177–180 Mating chimpanzee competition, see Chimpanzee female proceptivity in tufted capuchins, see Tufted capuchin single-male versus multi-male breeding system comparison, 139–141 social learning exploitation in mate choice costly asocial learning conditions birds, 344–345 fish, 343–344 mammals, 345 outdated prior information in birds, 362–363 relevant information deficiency, 351 McGurk effect, illusory fusion of speech sounds, 186 Mockingbird, acoustic communication in noise, 187 Mouse, acoustic communication in noise, 176 Muriqui breeding system, 139 mating season, 126

N Nest procurement cost, feeding behavior, 86 Nightingale, acoustic communication in noise, 161, 163 Noise, see Acoustic communication in noise Norepinephrine, prenatal sensory ecology studies of arousal, 253 Norway rat acoustic communication in noise, 172 social learning, 349

387

INDEX

O Open economy, feeding behavior analysis, 64–65

P Pallid bat, acoustic communication in noise, 180 Panamanian golden frog, acoustic communication in noise, 159 Patas monkey, female proceptivity, 119 Perceptual processing, prenatal sensory ecology studies in precocial birds, 253–254 Phase response curve, modeling of adjustable oscillator interactions in communal sexual displays, 25–28 Pigeon, acoustic communication in noise, 172 Pilot whale, acoustic communication in noise, 166 Postprandial correlation, feeding behavior, 66 PRC, see Phase response curve Precocial birds, see Prenatal sensory ecology, precocial birds Prenatal sensory ecology, precocial birds arousal studies, 252–256 attention studies, 253–256 developmental analysis access advantages, 239 bobwhite quail as model, 241–243 experiential attenuation, 239–240 experiential displacement, 241 experiential enhancement, 240–241 experiential rearrangement, 241 experiential substitution, 241 sensory system dominance studies, 242–243 developmental dynamics, 244–248 developmental systems theory, 262–263

learning and memory studies, 257–262 overview, 236–238 perceptual processing studies, 253–254 prospects for study, 263–265 stability and variability sources in behavioral development, 248–252 Preprandial correlation, feeding behavior, 66 Procurement cost feeding behavior, 68–71 time versus effort, 77, 79 Pygmy marmoset, acoustic communication in noise, 155

R Rats acoustic communication in noise, 172 feeding behavior studies, 69–71, 73, 76–77, 84, 87, 89–96 social learning studies, 349, 362 Red-winged blackbird, acoustic communication in noise, 155 Rhesus monkey acoustic communication in noise, 185 breeding system, 139

S Sage grouse, social learning, 344–345 Satiation, functional analysis of feeding, 89–91 Scent marking, tufted capuchin, 120 Sexual behavior, see Chimpanzee; Communal sexual displays; Tufted capuchin Siamese fighting fish, social learning, 346 Signal space, ecological concept, 189–191

388

INDEX

Snowy tree cricket, communal sexual displays, 7–8, 29 Social cue dependency hypothesis, adaptive social learning, 356–357 Social learning adaptive use, 333–334 evolution of abilities, 370–371 exploitation where asocial learning could be costly aggression in fish, 346 foraging birds, 342 fish, 336–342 mammals, 342–343 mate choice birds, 344–345 fish, 343–344 mammals, 345 theory, 335–336 exploitation where prior information is outdated foraging fish, 360–361 mammals, 361–362 mate choice in birds, 362–363 monetary reward studies in human, 363–364 theory, 359–360 exploitation where prior information is unreliable anti-predator behavior in mammals, 358–359 foraging birds, 354–355 fish, 352–354 mammals, 355–357 social behavior in mammals, 357–358 theory, 351–352 exploitation where relevant information is lacking foraging birds, 348–349 fish, 347–348 mammals, 349–350

mate choice in fish, 351 theory, 346–347 implications of adaptive use for social learning researchers plausibility of social learning in the wild, 364–368 suboptimal cultural traditions, 366–369 theoretical model implications, 369–370 prospects for study, 371–374 Sparrow, acoustic communication in noise, 189–190 Sperm competition, tufted capuchin, 130–131 Squirrel monkey, acoustic communication in noise, 180 Starling acoustic communication in noise, 177, 187 social learning, 354 Stickleback, social learning, 339–341 Stochastic resonance, hearing, 176

T Tamarin acoustic communication in noise, 185 social learning, 343 Tawny owl, acoustic communication in noise, 167 Temporal summation, hearing, 176 Tufted capuchin cryptic female choice, 136 female–female competition, 134–135 female proceptivity, 105–106, 116–119, 143 female sex hormones cycles, 117–119 genital morphology changes, 120–121 proceptive behavior and ovulation, 116–119

389

INDEX

groups ranking, 110–111 size and sex ratio, 107–110 stability, 111 inbreeding avoidance, 138–139 male–infant interactions, 107 male–male competition postcopulatory competition courtship after copulation, 132–133 sperm competition, 130–131 sperm plug, 131–132 precopulatory competition aggressive competition, 127–128 infanticide, 128–129 non-aggressive competition, 129 mating system, 111–113 mounting behavior and ejaculation in relation to ovulation and fertilization, 121–123 paternity analysis, 137–138 prospects for sexual behavior studies, 141–143 puberty and reproductive maturity females, 113, 115 males, 115–116 scent-marking behavior, 120 seasonality of reproduction, 124–126 sexual dimorphism and intrasexual competition, 133–134 single-male versus multi-male breeding system comparison, 139–141 social learning, 349–350 Tu´ ngara frog

acoustic communication in noise, 190–191 communal sexual displays, 11, 41

V Vocalization, see Acoustic communication in noise

W Wallaby, acoustic communication in noise, 179 Whales, acoustic communication in noise, 165–166 Willow warbler, acoustic communication in noise, 186 Winter wren, acoustic communication in noise, 186 Wolf spider, communal sexual displays, 48–49 Woodpecker finch, social learning, 366 Wrentit, acoustic communication in noise, 167

Z Zebra finch, acoustic communication in noise, 161, 187–188

Contents of Previous Volumes

Volume 18 Song Learning in Zebra Finches (Taeniopygia guttata): Progress and Prospects PETER J. B. SLATER, LUCY A. EALES, AND N. S. CLAYTON Behavioral Aspects of Sperm Competition in Birds T. R. BIRKHEAD Neural Mechanisms of Perception and Motor Control in a Weakly Electric Fish WALTER HEILIGENBERG Behavioral Adaptations of Aquatic Life in Insects: An Example ANN CLOAREC The Cicadian Organization of Behavior: Timekeeping in the Tsetse Fly, A Model System JOHN BRADY

The Evolution of Courtship Behavior in Newts and Salamanders T. R. HALLIDAY Ethopharmacology: A Biological Approach to the Study of Drug-Induced Changes in Behavior A. K. DIXON, H. U. FISCH, AND K. H. MCALLISTER Additive and Interactive Effects of Genotype and Maternal Environment PIERRE L. ROUBERTOUX, MARIKA NOSTEN-BERTRAND, AND MICHELE CARLIER Mode Selection and Mode Switching in Foraging Animals GENE S. HELFMAN Cricket Neuroethology: Neuronal Basis of Intraspecific Acoustic Communication FRANZ HUBER Some Cognitive Capacities of an African Grey Parrot (Psittacus erithacus) IRENE MAXINE PEPPERBERG

Volume 19 Volume 20 Polyterritorial Polygyny in the Pied Flycatcher P. V. ALATALO AND A. LUNDBERG Kin Recognition: Problems, Prospects, and the Evolution of Discrimination Systems C. J. BARNARD Maternal Responsiveness in Humans: Emotional, Cognitive, and Biological Factors CARL M. CORTER AND ALISON S. FLEMING

Social Behavior and Organization in the Macropodoidea PETER J. JARMAN The t Complex: A Story of Genes, Behavior, and Population SARAH LENINGTON The Ergonomics of Worker Behavior in Social Hymenoptera PAUL SCHMID-HEMPEL 391

392

CONTENTS OF PREVIOUS VOLUMES

‘‘Microsmatic Humans’’ Revisited: The Generation and Perception of Chemical Signals BENOIST SCHAAL AND RICHARD H. PORTER

Parasites and the Evolution of Host Social Behavior ANDERS PAPE MOLLER, REIJA DUFVA, AND KLAS ALLANDER

Lekking in Birds and Mammals: Behavioral and Evolutionary Issues R. HAVEN WILEY

The Evolution of Behavioral Phenotypes: Lessons Learned from Divergent Spider Populations SUSAN E. RIECHERT

Volume 21

Proximate and Developmental Aspects of Antipredator Behavior E. CURIO

Primate Social Relationships: Their Determinants and Consequences ERIC B. KEVERNE The Role of Parasites in Sexual Selection: Current Evidence and Future Directions MARLENE ZUK Conceptual Issues in Cognitive Ethology COLIN BEER Response in Warning Coloration in Avian Predators W. SCHULER AND T. J. ROPER Analysis and Interpretation of Orb Spider Exploration and Web-Building Behavior FRITZ VOLLRATH Motor Aspects of Masculine Sexual Behavior in Rats and Rabbits GABRIELA MORALI AND CARLOS BEYER On the Nature and Evolution of Imitation in the Animal Kingdom: Reappraisal of a Century of Research A. WHITEN AND R. HAM

Volume 22 Male Aggression and Sexual Coercion of Females in Nonhuman Primates and Other Mammals: Evidence and Theoretical Implications BARBARA B. SMUTS AND ROBERT W. SMUTS

Newborn Lambs and Their Dams: The Interaction That Leads to Sucking MARGARET A. VINCE The Ontogeny of Social Displays: Form Development, Form Fixation, and Change in Context T. G. GROOTHUIS

Volume 23 Sneakers, Satellites, and Helpers: Parasitic and Cooperative Behavior in Fish Reproduction MICHAEL TABORSKY Behavioral Ecology and Levels of Selection: Dissolving the Group Selection Controversy LEE ALAN DUGATKIN AND HUDSON KERN REEVE Genetic Correlations and the Control of Behavior, Exemplified by Aggressiveness in Sticklebacks THEO C. M. BAKKER Territorial Behavior: Testing the Assumptions JUDY STAMPS Communication Behavior and Sensory Mechanisms in Weakly Electric Fishes BERND KRAMER

CONTENTS OF PREVIOUS VOLUMES

Volume 24 Is the Information Center Hypothesis a Flop? HEINZ RICHNER AND PHILIPP HEEB Maternal Contributions to Mammalian Reproductive Development and the Divergence of Males and Females CELIA L. MOORE Cultural Transmission in the Black Rat: Pine Cone Feeding JOSEPH TERKEL The Behavioral Diversity and Evolution of Guppy, Poecilia reticulata, Populations in Trinidad A. E. MAGURRAN, B. H. SEGHERS, P. W. SHAW, AND G. R. CARVALHO Sociality, Group Size, and Reproductive Suppression among Carnivores SCOTT CREEL AND DAVID MACDONALD Development and Relationships: A Dynamic Model of Communication ALAN FOGEL Why Do Females Mate with Multiple Males? The Sexually Selected Sperm Hypothesis LAURENT KELLER AND HUDSON K. REEVE

393

An Overview of Parental Care among the Reptilia CARL GANS Neural and Hormonal Control of Parental Behavior in Birds JOHN D. BUNTIN Biochemical Basis of Parental Behavior in the Rat ROBERT S. BRIDGES Somatosensation and Maternal Care in Norway Rats JUDITH M. STERN Experiential Factors in Postpartum Regulation of Maternal Care ALISON S. FLEMING, HYWEL D. MORGAN, AND CAROLYN WALSH Maternal Behavior in Rabbits: A Historical and Multidisciplinary Perspective GABRIELA GONZA¨LEZ-MARISCAL AND JAY S. ROSENBLATT Parental Behavior in Voles ZUOXIN WANG AND THOMAS R. INSEL Physiological, Sensory, and Experiential Factors of Parental Care in Sheep F. LE¨VY, K. M. KENDRICK, E. B. KEVERNE, R. H. PORTER, AND A. ROMEYER

Cognition in Cephalopods JENNIFER A. MATHER

Socialization, Hormones, and the Regulation of Maternal Behavior in Nonhuman Simian Primates CHRISTOPHER R. PRYCE

Volume 25

Field Studies of Parental Care in Birds: New Data Focus Questions on Variation among Females PATRICIA ADAIR GOWATY

Parental Care in Invertebrates STEPHEN T. TRUMBO Cause and Effect of Parental Care in Fishes: An Epigenetic Perspective STEPHEN S. CRAWFORD AND EUGENE K. BALON Parental Care among the Amphibia MARTHA L. CRUMP

Parental Investment in Pinnipeds FRITZ TRILLMICH Individual Differences in Maternal Style: Causes and Consequences of Mothers and Offspring LYNN A. FAIRBANKS

394

CONTENTS OF PREVIOUS VOLUMES

Mother–Infant Communication in Primates DARIO MAESTRIPIERI AND JOSEP CALL Infant Care in Cooperatively Breeding Species CHARLES T. SNOWDON

Volume 27 The Concept of Stress and Its Relevance for Animal Behavior DIETRICH VON HOLST Stress and Immune Response VICTOR APANIUS

Volume 26 Sexual Selection in Seawood Flies THOMAS H. DAY AND ANDRE¨ S. GILBURN Vocal Learning in Mammals VINCENT M. JANIK AND PETER J. B. SLATER Behavioral Ecology and Conservation Biology of Primates and Other Animals KAREN B. STRIER How to Avoid Seven Deadly Sins in the Study of Behavior MANFRED MILINSKI Sexually Dimorphic Dispersal in Mammals: Patterns, Causes, and Consequences LAURA SMALE, SCOTT NUNES, AND KAY E. HOLEKAMP Infantile Amnesia: Using Animal Models to Understand Forgetting MOORE H. ARNOLD AND NORMAN E. SPEAR Regulation of Age Polyethism in Bees and Wasps by Juvenile Hormone SUSAN E. FAHRBACH Acoustic Signals and Speciation: The Roles of Natural and Sexual Selection in the Evolution of Cryptic Species GARETH JONES

Behavioral Variability and Limits to Evolutionary Adaptation P. A. PARSONS Developmental Instability as a General Measure of Stress ANDERS PAPE MOLLER Stress and Decision-Making under the Risk of Predation: Recent Developments from Behavioral, Reproductive, and Ecological Perspectives STEVEN L. LIMA Parasitic Stress and Self-Medication in Wild Animals G. A. LOZANO Stress and Human Behavior: Attractiveness, Women’s Sexual Development, Postpartum Depression, and Baby’s Cry RANDY THORNHILL AND F. BRYANT FURLOW Welfare, Stress, and the Evolution of Feelings DONALD M. BROOM Biological Conservation and Stress HERIBERT HOFER AND MARION L. EAST

Volume 28

Understanding the Complex Song of the European Starling: An Integrated Ethiological Approach MARCEL EENS

Sexual Imprinting and Evolutionary Processes in Birds: A Reassessment CAREL TEN CATE AND DAVE R. VOS

Representation of Quantities by Apes SARAH T. BOYSEN

Techniques for Analyzing Vertebrate Social Structure Using Identified

CONTENTS OF PREVIOUS VOLUMES

Individuals: Review and Recommendations HAL WHITEHEAD AND SUSAN DUFAULT Socially Induced Infertility, Incest Avoidance, and the Monopoly of Reproduction in Cooperatively Breeding African Mole-Rats, Family Bathyergidae NIGEL C. BENNETT, CHRIS G. FAULKES, AND JENNIFER U. M. JARVIS Memory in Avian Food Caching and Song Learning: A General Mechanism or Different Processes? NICOLA S. CLAYTON AND JILL A. SOHA Long-Term Memory in Human Infants: Lessons in Psychobiology CAROLYN ROVEE-COLLIER AND KRISTIN HARTSHORN Olfaction in Birds TIMOTHY J. ROPER Intraspecific Variation in Ungulate Mating Strategies: The Case of the Flexible Fallow Deer SIMON THIRGOOD, JOCHEN LANGBEIN, AND RORY J. PUTMAN

Volume 29 The Hungry Locust STEPHEN J. SIMPSON AND DAVID RAUBENHEIMER Sexual Selection and the Evolution of Song and Brain Structure in Acrocephalus Warblers CLIVE K. CATCHPOLE Primate Socialization Revisited: Theoretical and Practical Issues in Social Ontogeny BERTRAND L. DEPUTTE

395

Ultraviolet Vision in Birds INNES C. CUTHILL, JULIAN C. PARTRIDGE, ANDREW T. D. BENNETT, STUART C. CHURCH, NATHAN S. HART, AND SARAH HUNT What Is the Significance of Imitation in Animals? CECILIA M. HEYES AND ELIZABETH D. RAY Vocal Interactions in Birds: The Use of Song as a Model in Communication DIETMAR TODT AND MARC NAGUIB

Volume 30 The Evolution of Alternative Strategies and Tactics H. JANE BROCKMANN Information Gathering and Communication during Agonistic Encounters: A Case Study of Hermit Crabs ROBERT W. ELWOOD AND MARK BRIFFA Acoustic Communication in Two Groups of Closely Related Treefrogs H. CARL GERHARDT Scent-Marking by Male Mammals: Cheat-Proof Signals to Competitors and Mates L. M. GOSLING AND S. C. ROBERTS Male Facial Attractiveness: Perceived Personality and Shifting Female Preferences for Male Traits across the Menstrual Cycle IAN S. PENTON-VOAK AND DAVID I. PERRETT The Control and Function of Agonism in Avian Broodmates HUGH DRUMMOND

396

CONTENTS OF PREVIOUS VOLUMES

Volume 31 Conflict and Cooperation in a Female-Dominated Society: A Reassessment of the ‘‘Hyperaggressive’’ Image of Spotted Hyenas MARION L. EAST AND HERIBERT HOFER Birdsong and Male–Male Competition: Causes and Consequences of Vocal Variability in the Collared Dove (Streptopelia decaocto) CAREL TEN CATE, HANS SLABBEKOORN, AND MECHTELD R. BALLINTIJN Imitation of Novel Complex Actions: What Does the Evidence from Animals Mean? RICHARD W. BYRNE Lateralization in Vertebrates: Its Early Evolution, General Pattern, and Development LESLEY J. ROGERS Auditory Scene Analysis in Animal Communication STEWART H. HULSE Electric Signals: Predation, Sex, and Environmental Constraints PHILIP K. STODDARD How to Vocally Identify Kin in a Crowd: The Penguin Model THIERRY AUBIN AND PIERRE JOUVENTIN

Volume 32 Self-Organization and Collective Behavior in Vertebrates IAIN D. COUZIN AND JENS KRAUSE Odor-Genes Covariance and Genetic Relatedness Assessments: Rethinking

Odor-Based Recognition Mechanisms in Rodents JOSEPHINE TODRANK AND GIORA HETH Sex Role Reversal in Pipefish ANDERS BERGLUND AND GUNILLA ROSENQVIST Fluctuating Asymmetry, Animal Behavior, and Evolution JOHN P. SWADDLE From Dwarf Hamster to Daddy: The Intersection of Ecology, Evolution, and Physiology That Produces Paternal Behavior KATHERINE E. WYNNE-EDWARDS Paternal Behavior and Aggression: Endocrine Mechanisms and Nongenomic Transmission of Behavior CATHERINE A. MARLER, JANET K. BESTER-MEREDITH, AND BRIAN C. TRAINOR Cognitive Ecology: Foraging in Hummingbirds as a Model System SUSAN D. HEALY AND T. ANDREW HURLY

Volume 33 Teamwork in Animals, Robots, and Humans CARL ANDERSON AND NIGEL R. FRANKS The ‘‘Mute’’ Sex Revisited: Vocal Production and Perception Learning in Female Songbirds KATHARINA RIEBEL Selection in Relation to Sex in Primates JOANNA M. SETCHELL AND PETER M. KAPPELER

CONTENTS OF PREVIOUS VOLUMES

Genetic Basis and Evolutionary Aspects of Bird Migration PETER BERTHOLD

397

Evolutionary Significance of Sexual Cannibalism MARK A. ELGAR AND JUTTA M. SCHNEIDER

Vocal Communication and Reproduction in Deer DAVID REBY AND KAREN MCCOMB

Social Modulation of Androgens in Vertebrates: Mechanisms and Function RUI F. OLIVEIRA

Referential Signalling in Non-Human Primates: Cognitive Precursors and Limitations for the Evolution of Language ¨ HLER KLAUS ZUBERBU

Odor Processing in Honeybees: Is the Whole Equal to, More Than, or Different from the Sum of Its Parts? HARALD LACHNIT, MARTIN GIURFA, AND RANDOLF MENZEL

Vocal Self-stimulation: From the Ring Dove Story to Emotion-Based Vocal Communication MEI-FANG CHENG

Begging, Stealing, and Offering: Food Transfer in Nonhuman Primates GILLIAN R. BROWN, ROSAMUNDE E. A. ALMOND, AND YFKE VAN BERGEN

Volume 34

Song Syntax in Bengalese Finches: Proximate and Ultimate Analyses KAZUO OKANOYA

Reproductive Conflict in Insect Societies ¨ RGEN HEINZE JU Game Structures in Mutualistic Interactions: What Can the Evidence Tell Us About the Kind of Models We Need? REDOUAN BSHARY AND JUDITH L. BRONSTEIN Neurobehavioral Development of Infant Learning and Memory: Implications for Infant Attachment TANIA L. ROTH, DONALD A. WILSON, AND REGINA M. SULLIVAN

Behavioral, Ecological, and Physiological Determinants of the Activity Patterns of Bees P. G. WILLMER AND G. N. STONE