Volume 79, No. 3 June 2004 The Quarterly Review of Biology

BEHAVIORAL SYNDROMES: AN INTEGRATIVE OVERVIEW

Andrew Sih Department of Environmental Science and Policy, University of California Davis, California 95616 USA e-mail: [email protected]

Alison M. Bell Department of Evolution and Ecology, University of California Davis, California 95616 USA

J. Chadwick Johnson Department of Biological Sciences, University of Kentucky Lexington, Kentucky 40506 USA Department of Environmental Science and Policy, University of California Davis, California 95616 USA

Robert E. Ziemba Department of Biology, Centre College Danville, Kentucky 40422 USA Department of Biological Sciences, University of Kentucky Lexington, Kentucky 40506 USA keywords behavioral syndromes, behavioral correlations, tradeoffs, aggressiveness, shy/bold continuum, proactive/reactive coping styles, limited plasticity, behavioral types, animal personalities, behavioral genetics

The Quarterly Review of Biology, September 2004, Vol. 79, No. 3 Copyright ᭧ 2004 by The University of Chicago. All rights reserved. 0033-5770/2004/7903-0001$15.00

241 242 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

abstract A behavioral syndrome is a suite of correlated behaviors expressed either within a given behavioral context (e.g., correlations between foraging behaviors in different habitats) or across different contexts (e.g., correlations among feeding, antipredator, mating, aggressive, and dispersal behaviors). For exam- ple, some individuals (and genotypes) might be generally more aggressive, more active or bold, while others are generally less aggressive, active or bold. This phenomenon has been studied in detail in humans, some primates, laboratory rodents, and some domesticated animals, but has rarely been studied in other organisms, and rarely examined from an evolutionary or ecological perspective. Here, we present an integrative overview on the potential importance of behavioral syndromes in evolution and ecology. A central idea is that behavioral correlations generate tradeoffs; for example, an aggressive genotype might do well in situations where high aggression is favored, but might be inappropriately aggressive in situations where low aggression is favored (and vice versa for a low aggression genotype). Behavioral syndromes can thereby result in maladaptive behavior in some contexts, and potentially maintain individual variation in behavior in a variable environment. We suggest terminology and methods for studying behavioral syndromes, review examples, discuss evolutionary and proximate approaches for understanding behavioral syndromes, note insights from human personality research, and outline some potentially important ecological implications. Overall, we suggest that behavioral syndromes could play a useful role as an integrative bridge between genetics, experience, neuroendocrine mechanisms, evolution, and ecology.

NDIVIDUAL HUMANS SHOW consistent dif- aggression syndrome (Huntingford 1976; I ferences in their behavioral tendencies. Riechert and Hedrick 1993). Although all Compared to others, some people are rela- individuals alter their aggression levels tively assertive, or bold, or friendly, or decep- depending on the context (feeding, mating, tive. Analogous patterns of individual varia- predator avoidance), some are consistently tion have been documented in several more aggressive than others across contexts. primates, domesticated animals, laboratory Analogous consistent between-individual dif- rodents, and a scattering of other animals ferences in behavior have been noted for (Gosling and John 1999; Gosling 2001). In activity (Henderson 1986; Sih et al. 2003), humans, these differences have been termed shyness/boldness (Wilson et al. 1994; Fraser personality types (Pervin and John 1999). In et al. 2001), fearfulness (Boissy 1995), and other taxa, they have been referred to as cop- reactivity (Koolhaas et al. 1997). Most extant ing styles, temperaments, behavioral tenden- literature examines proximate (e.g., genetic, cies, strategies, syndromes, axes, or constructs neuroendocrine, developmental) bases of (Gosling 2001). From an ecological and evo- these syndromes. Our focus is on the evolu- lutionary view, an underlying theme of these tion and ecological importance of behavioral related concepts is that they refer to suites of syndromes. We also review relevant literature correlated behaviors that can include those on proximate bases and suggest that behav- expressed either within a given behavioral ioral syndromes could play a useful role as a context (e.g., foraging behaviors in different bridge that integrates genetic, physiological, habitats) or across different contexts (e.g., ecological, and evolutionary approaches to feeding, antipredator, mating, contest, and studying behavior. dispersal contexts). In evolutionary ecology, The reason why behavioral syndromes have suites of correlated characters are commonly critical implications for evolution and ecology referred to as syndromes (e.g., life-history is simple. The existence of behavioral syn- syndromes, dispersal syndromes), thus we dromes implies correlations between behav- refer to suites of correlated behaviors as iors expressed in different contexts; i.e., what behavioral syndromes. an individual does in one context is coupled An example of a behavioral syndrome that with what it does in other contexts. When has been documented in several species is an traits are correlated, single traits (here, September 2004BEHAVIORAL SYNDROMES 243 behavior in any single context) do not evolve given context requires an understanding of in isolation. Instead the suite of correlated their correlated behaviors in other contexts. traits (here, the behavioral syndrome) evolves This is true for behaviors that are similar as a package (Price and Langen 1992; Lynch (e.g., aggression during feeding and during and Walsh 1998). In particular, the correla- mating) and behaviors that are seemingly tions can generate tradeoffs across contexts unrelated (e.g., aggression and dispersal). that can play a major role in evolution. Second, the existence of behavioral tenden- A useful analogy can be drawn between life- cies that carry over across contexts (e.g., the history evolution and the evolution of behav- aggression syndromes described above) ioral syndromes. Life-history correlations could mean that individuals show suboptimal (e.g., the cost of reproduction expressed as a behavior (when judged in an isolated con- negative correlation between current repro- text) in some, perhaps many, situations. duction and future reproduction or survival) Third, the notion that individuals do well in clearly play a major role in shaping life-his- some contexts and poorly in others could tory evolution (Roff 1992; Stearns 1992). Due help to explain the maintenance of individual to tradeoffs generated by these correlations, variation in behavior. individuals typically do not attempt to maxi- Our goal here is to provide a conceptual mize their reproductive effort or survival in overview on the study of behavioral syn- any given year. Instead, depending on the dromes. We discuss: 1) terminology and basic selection regime, tradeoffs can favor delayed empirical designs for studying behavioral syn- reproduction, limited reproduction in any dromes; 2) examples of how behavioral syn- given year, and senescence (Roff 1992; dromes might shape ecologically important Stearns 1992). If we look at any one of these behaviors; 3) the evolution of behavioral syn- traits in isolation, it can appear suboptimal; dromes; 4) proximate mechanisms (genetics, however, across the organism’s lifetime, these experience, and neuroendocrine bases); 5) traits can be part of an optimal life history. In insights from the study of human psychology; addition, the combination of spatiotemporal and 6) ecological implications (e.g., for popu- variation in selection regimes and life-history lation or community ecology, conservation tradeoffs can explain the maintenance of life- biology). history variation within and among species (Roff 1992; Mangel and Stamps 2001; Orzack Terminology and Methods and Tuljapurkar 2001). Returning to behavior, consider a species As noted above, trait correlations and the with an aggression syndrome where some resulting tradeoffs are at the heart of many individuals are more aggressive than others in issues in modern evolutionary ecology (Fig- more than one context. More aggressive indi- ure 1). To illustrate how behavioral syn- viduals that do well in situations where aggres- dromes relate to traditional concepts about siveness is called for (e.g., in competition for tradeoffs in behavioral ecology, we distin- food or mates) might be unsuitably aggressive guish between within- versus across-situation in situations where caution or care is more conflicts involving one or more behavioral appropriate (e.g., in the presence of a dan- contexts. By a context, we mean a functional gerous predator or in a parental care con- behavioral category—e.g., feeding, mating, text). Conversely, less aggressive individuals antipredator, parental care, contest, or dis- should do well in situations where low aggres- persal contexts. A situation is a given set of sion is appropriate, but might fare poorly in conditions at one point in time. Different sit- situations where aggression is favored. Follow- uations could involve different levels along an ing the analogy from life-history evolution, environmental gradient (e.g., different levels these tradeoffs should have three important, of predation risk or different food levels), or general implications for behavioral ecolo- different sets of conditions across time (e.g., gists. First, behaviors that are part of a syn- the nonbreeding season versus the breeding drome should not be studied in isolation. season, or juvenile versus adult stages). Cor- Understanding what individuals do in any relations can involve behaviors expressed in: 244 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Figure 1. Types of Behavioral Correlations that Generate Conflicts Two types of behavioral correlations that generate conflicts: (a) negative behavioral correlations produced by time budget conflicts within any given situation; e.g., conflicts between feeding and hiding; (b) positive behavioral correlations across situations produced by behavioral tendencies that carry over across situations.

1) different contexts within the same situa- activities, taken in isolation, should increase tion (e.g., feeding activity and mating activity fitness, organisms cannot simultaneously in one set of ecological conditions); 2) the maximize both. Instead, they must adaptively same context, but in different situations (e.g., balance these conflicting demands (e.g., Sih feeding activity in the presence versus 1980, 1987; Houston et al. 1993; Lima and absence of predators or the voracity of juve- Bednekoff 1999). Time budget conflicts play niles versus adults); or 3) different contexts a major role in modern thinking about adap- in different situations (e.g., aggression toward tive behavior. conspecifics in the absence of predators ver- Behavioral correlations within a given sit- sus feeding activity in the presence of preda- uation can also be generated by individual tors). variation in behavioral tendencies. For exam- One major source of behavioral correla- ple, individuals might exhibit a general attack tions involves time budget conflicts within a syndrome that, within a feeding context, given situation; these exemplify the first type tends to produce positive correlations among of correlation noted above—correlations for individuals in their probability of attacking different behavioral contexts within a given different food types in one habitat. “High situation. Simply because individuals have a voracity” individuals should have high overall limited amount of total time, more time spent feeding rates, but might also frequently err on one activity tends to result in less time by attacking prey that are unpalatable, dan- spent on other mutually exclusive activities. gerous, or otherwise difficult to capture or The various elements of a time budget thus handle. Positive correlations associated with tend to be negatively correlated (Figure 1a). For behavioral syndromes can mask negative cor- example, often animals cannot feed while relations due to time budget conflicts. For hiding and vice versa. If these are the main example, if some individuals are generally activities in a time budget, then time spent more active than others, this could result in hiding versus feeding should be negatively a positive correlation between mating and correlated. As a result, even though both feeding activity within a given time period September 2004BEHAVIORAL SYNDROMES 245

(rather than the expected negative correla- To quantify a behavioral syndrome, we tion based on time budget constraints for need at least two observations of behavior individuals with identical activity levels). (preferably in different contexts or situa- Behavioral tendencies can also carry over tions) for each of a set of individuals. With to cause correlations between behaviors these data we can quantify two distinct aspects exhibited in the same context but across dif- of a behavioral syndrome: within-individual ferent situations. For example, individual versus between-individual consistency in behav- variation in general activity could result in a ior. Within-individual consistency refers to positive correlation between foraging activity the tendency for any given individual to in the presence versus absence of predators. exhibit consistent behavior across observa- Individuals that feed most actively during tions (e.g., for an individual to be generally periods of safety might also continue to feed aggressive). In principle, this can be quanti- relatively actively and thus take the greatest fied for a single individual, independent of risks when predators are present (Sih et al. the behavior of others. Between-individual 2003). The result would be a tradeoff consistency refers to consistent differences between foraging and predator avoidance among individuals in behavior (e.g., rank- due to an activity carryover across situations order consistency in aggressiveness) rather than the usual time budget conflict expressed statistically as a behavioral correla- within a situation. tion. If the study involves repeated observa- Most interestingly, behavioral syndromes tions of the same type of behavior in the same can involve different behavioral contexts context and situation, we refer to behavioral expressed across different situations. For consistency as repeatability (Boake 1994). A example, as noted earlier, an aggression syn- behavioral syndrome is a suite of correlated drome might result in positive correlations behaviors across multiple (two or more) between aggression levels in intrasexual com- observations—most interesting, if it involves petition, male-female conflict, feeding, anti- multiple contexts or situations. Within the predator, and/or parental care contexts syndrome, each individual has a behavioral type (Huntingford 1976; Riechert and Hedrick (e.g., more versus less aggressive individuals). 1993; Figure 1b). Across-situation correla- Behavioral syndromes can be most inter- tions could involve behaviors that seem simi- esting when they result in less than optimal lar but are measured in different situations behavioral plasticity (limited behavioral plas- (e.g., aggression in contests versus tendency ticity). For example, a shy/bold syndrome to attack dangerous prey), or different yet (Wilson et al. 1994) is particularly interesting plausibly related behaviors (e.g., aggression if bold individuals are inappropriately bold in in contests versus parental feeding of off- situations where they should be cautious. The spring). existence of between-individual consistency Of course, whether a correlation is positive need not imply within-individual consistency or negative depends on how the variables are or limited plasticity. It is possible, for exam- defined. For example, the correlation ple, for individuals to differ consistently in between mating activity in the absence of mean aggressiveness, but for all individuals, predators and behavior in the presence of including those that are more aggressive, to predators depends on whether the latter is be highly plastic in their aggressiveness across defined as time spent hiding or time exposed. contexts. If, however, individuals show limited If individuals exhibit consistent activity levels behavioral plasticity, we refer to this as a behav- across situations, mating activity without pred- ioral carryover or spillover. ators will be positively correlated with expo- These distinctions can be illustrated using sure, but negatively correlated with refuge plasticity plots (Figure 2a) and correlation use. Throughout this paper, we define behav- plots (Figure 2b). These plots are analogous iors such that higher activity (or aggression to reaction norm (2a) or genetic correlation or boldness) results in larger values; thus a plots (2b) of quantitative genetics (Via and consistent behavioral tendency produces a Lande 1985; Roff 1997), except that for our positive correlation. purposes each line (2a) or point (2b) can rep- 246 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Figure 2. Graphs of Behavioral Correlations Graphical representations of behavioral correlations borrowed from the literature on adaptive plasticity: (a) plasticity plots (reaction norms if each line is for a different genotype); (b) correlations across environments. E1 and E2 might represent, for example, activity in the absence and presence of predators. The stars are the optima for each environment. resent either a genotype or simply an individ- ism’s overall life. In Gould and Lewontin’s ual. Different behavioral types are repre- (1979) terminology, we “atomize” the organ- sented as different lines (2a) or points (2b). ism. The concept of behavioral syndromes In our example, due to stabilizing selection, inherently advocates a more holistic view of there is an optimal trait (represented by the the organism’s behavior over its lifetime. stars) in each environment. A fixed behavior Organisms encounter many contexts and sit- in a uations over their lifetime, many of which (0 ס would appear as a flat line (slope plasticity plot, and a point on the 45-degree contribute to their overall fitness. If there are line in a correlation plot. A positive behav- correlations across some of these contexts or ioral correlation is shown as a line of positive situations, they need to be understood. In slope in Figure 2b, and as a tendency for plas- many fields, following individuals across con- ticity lines to be parallel in Figure 2a. It is pos- texts or situations is not the norm. For exam- sible for behaviors to be negatively correlated; ple, in order to satisfy statistical indepen- however, our main emphasis is on positive dence, predator-prey studies generally correlations associated with behavioral syn- examine different individuals in different dromes. A behavioral carryover (less than treatment conditions (e.g., presence versus optimal plasticity) is indicated if the slope of absence of predators). We suggest that addi- the plasticity line is less than the optimal plas- tional, new insights can be gained by studying ticity, or if a point on the correlation plot is the same individuals across contexts or situa- closer to the 45-degree line than is the opti- tions. Studies of social behavior often follow mal point. A behavioral correlation poses a individuals over a long time period, through potentially important constraint if no plastic- multiple contexts and situations (e.g., terri- ity line or point coincides with the optimum, tory establishment, intraspecific competition due to behavioral carryovers. and mate choice, nesting and parental care); The basic empirical design for studying however, few studies have then examined car- behavioral syndromes involves following a set ryovers or correlations across these contexts of individuals across multiple contexts or sit- or situations. uations in order to measure their behavior A matrix of correlations among multiple and, ideally, related traits (e.g., morphology, behaviors can contain more than one set of neuroendocrine profile) and performance correlated behaviors. A multivariate analysis (e.g., feeding rate, mating success, survival) (e.g., factor analysis) might distinguish dis- in each context or situation. Although this tinct suites of behaviors that represent one or design is simple, it represents a philosophical more separate syndromes—e.g., an aggres- shift in how many of us study behavior. Many sion syndrome and a fear syndrome (Budaev of us are specialists who focus on one type of 1998; Gosling 2001). Personality psycholo- behavior over a limited range of the organ- gists have developed other statistical methods September 2004BEHAVIORAL SYNDROMES 247 to assess individuals across multiple contexts (Riechert 1993). If, however, qualitatively dif- that should also be useful here (e.g., Camp- ferent behaviors are exhibited by different bell and Fiske 1959; Shrout and Fiske 1995; taxa (e.g., different species or even more dis- Briggs 1999). The literature on human per- tantly related taxa), then attempts to contrast sonalities suggests that humans have four or their levels of “aggression” or “activity” five axes or dimensions of behavioral variation become problematic. Can aggression in (see the later section on Human Personali- squids be meaningfully compared to aggres- ties). Each individual exhibits a behavioral sion in impala (for an early attempt to answer tendency on each dimension. Across the a similar question, see Glickman and Sroges entire population, these dimensions should 1966)? A related and potentially even more be uncorrelated; however, subsets of the complicated issue is whether the same suites population can show a correlated suite of ten- of traits are present in different groups, or dencies—e.g., a “computer nerd” might be whether the very structure of “personality” conscientious and introverted (Gosling, per- varies: aggression toward food and conspecif- sonal suggestion)—that represents a multi- ics might be tightly correlated in one group dimensional behavioral type (Robins et al. but unrelated in another. One broad 1996). approach asks whether factor analysis pro- Path analysis (e.g., Pedhazur 1982; Schei- duces the same factors in different groups ner and Callahan 1999; Sih et al. 2002) can (Gosling and John 1999). For example, in quantify relationships between behavioral humans, personality can be quantified in syndromes, other traits, and performance. If terms of five major axes: extroversion, neu- positive correlations are significant for behav- roticism, openness, agreeableness, and con- iors within one basic context (e.g., positive scientiousness (see section on Human Per- correlations for attack tendency on different sonalities). Studies on other animals (e.g., food types or at different food levels), but not other primates, dogs) have asked whether between contexts (e.g., for attack tendency these same five factors can be identified in on food versus tendency to attack potential these other animals. This approach, however, mates), the correlations are referred to as ignores more subtle differences between domain specific, whereas if the correlations groups in correlation structures. An alterna- occur across multiple contexts, they are tive approach, that to our knowledge has not termed domain general (Kagan et al. 1988; Wil- been applied in animal behavior, is to use sta- son 1998). Although to us, domain-general tistical methods drawn from evolutionary syndromes seem particularly interesting, biology (e.g., confirmatory factor analysis) to often domain-specific correlations should compare correlation matrices from different still be ecologically and evolutionarily impor- groups (Steppan et al. 2002). tant. Up to this point, we have been discussing A Selective Review of Examples behavioral syndromes as a property of a single population. For some issues, however, we and Issues might be interested in contrasting behavioral Gosling’s review of animal personalities syndromes or types for different populations (2001) noted four behavioral syndromes that or species. For example, do different dog have been quantified repeatedly in humans breeds differ in behavioral type, or do dogs and “model organisms” (other primates, lab- differ from cats? If the same behaviors have oratory rodents, and domesticated mammals been quantified in different groups, then we like dogs, cats, and farm animals): 1) aggres- can directly compare mean behavioral types sion (tendency to attack other individuals); 2) across groups. For example, funnel web spi- general activity level; 3) sociability (tendency ders from two populations differ in their over- to seek out social interactions); and 4) fear- all willingness to attack conspecifics and food fulness (nervousness, avoidance of novel items: spiders from one population are more stimuli) (Boissy 1995). Much of this work has “aggressive” toward food and conspecifics focused on proximate (genetic, neuroendo- than spiders from another population crine) mechanisms. In contrast, behavioral 248 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 syndromes have received only limited atten- the presence and absence of predators. Sih et tion in other organisms, and relatively few al. (2003) studied the role of activity correla- studies have examined syndromes from an tions across situations in determining preda- evolutionary ecological perspective. Next, we tion rates and coexistence in a sunfish (pred- review selected examples of behavioral syn- ator)/salamander (prey) system. Streamside dromes studied in nonmodel organisms from salamander larvae, Ambystoma barbouri, are an evolutionary ecological view. found in streams with a mix of relatively per- For aggression syndromes, a notable study manent pools with predatory sunfish and is the work by Riechert and coworkers on the ephemeral, fishless pools. Because larvae funnel web spider, Agelenopsis aperta. Riechert drift among pools, to survive to metamorpho- and Hedrick (1993) showed that relative to sis they must exhibit behavioral plasticity to less aggressive spiders, more aggressive ones cope with selection pressures in both pool showed higher attack tendencies on both types. Habitat ephemerality favors high activ- prey and conspecific competitors (territory ity that drives high feeding, growth, and invaders), and a shorter latency to emerge developmental rates (Petranka and Sih 1987; from refuge after a simulated predator attack Maurer and Sih 1996). In contrast, in fish (i.e., reduced antipredator responses). Later pools, in the daytime larvae should show little work showed that aggressive spiders also tend or no activity, though they need to be some- to exhibit high levels of excessive, nonadap- what active at night in order to move through tive wasteful killing (Maupin and Riechert a fish pool to drift out the downstream end 2001), and some possibly nonadaptive sexual (Sih et al. 1992). The optimal behavior cannibalism (Riechert, personal observa- should be to be very active in the absence of tion). More aggressive genotypes were found fish, moderately active in fish pools at night, in populations with a history of low food avail- and very inactive in fish pools in the day. Sal- ability (relative to less aggressive populations; amanders, however, exhibited positive activity Riechert 1993), though gene flow among correlations between the presence and populations could result in overly aggressive absence of fish cues, and between activity in animals in sites with high food levels (Riech- the day versus at night (Sih et al. 2003). Thus ert 1993). Controlled crosses between popu- larvae that tended to be more active in fish- lations revealed a simple, single locus, sex- less pools tended to also drift more among linked basis to aggressive tendency pools, and unfortunately also tended to be counteracted somewhat by an autosomal, inappropriately active in fish pools in the day. quantitative (polygenic) level of fearfulness The latter result at least partially explains the (Riechert and Maynard Smith 1989). Similar poor ability of these larvae to persist in fish correlations between aggression in territorial pools or streams with too many fish pools and antipredator contexts have been docu- (Petranka 1983; Sih et al. 1992). Full sib anal- mented in sticklebacks by Huntingford and yses suggested some heritability of activity syn- coworkers (Huntingford 1976, 1982). dromes in this system (Sih et al. 2003). Main- Another ecologically important syndrome tenance of genetic variation in activity types involves activity correlations across situations. can apparently be explained by gene flow and Activity level has been posited to be a key trait spatiotemporal variation in selection pres- that links behavior to feeding rate, metabolic sures (Storfer and Sih 1998; Sih et al. 2003). expenditures, and predation risk and, thus, On a larger taxonomic scale, Richardson to population/community dynamics (Sih (2001) found positive correlations across 13 1987; Werner and Anholt 1993). While hun- species of anurans between the evolution of dreds of experiments have quantified tadpole activity in the absence of predators changes in average activity in response to versus in the presence of either of three pred- changes in food availability or predation risk ators (fish, newts, dragonflies). That is, spe- (Hassell 1978; Lima 1998), few studies have cies that evolve higher activity in the absence looked at activity correlations across contexts. of predators also appear to simultaneously For example, surprisingly few studies have have higher activity in the presence of any of quantified the activity of the same animals in the three major predators. September 2004BEHAVIORAL SYNDROMES 249

Antipredator and feeding activity might be Recent work by this group showed that elements of a fearfulness, or shy/bold contin- exploratory behavior and boldness are both uum (Wilson et al. 1993, 1994; Wilson 1998). repeatable and heritable (Dingemanse et al. This shy/bold syndrome has been examined 2002; van Oers et al. 2004), and respond to by behavioral ecologists by comparing suites bidirectional artificial selection over the of behaviors and performance for individual course of four generations (Drent et al. animals that readily approach or are easily 2002). Finally, fast explorers showed greater trapped by humans versus other individuals dispersal in the field (Dingemanse et al. that avoid humans and traps. Bolder sunfish 2003). Thus reactivity appears to be a behav- tend to also approach predators (engage in ioral trait with substantial evolutionary and predator inspection), acclimate quickly to the ecological implications. laboratory, feed more on exposed and diffi- Other possible examples of important cult to capture prey, and carry different par- behavioral carryovers emerged from attempts asites (Wilson et al. 1994). Bolder killifish dis- to explain apparently maladaptive behavior. perse further and grow faster (Fraser et al. In several cases, authors have suggested that 2001), and bolder bighorn sheep tend to sur- an important general behavioral tendency vive better in the field (Re´ale et al. 2000) than has spilled over to produce inappropriate less bold ones. behavior in other similar contexts or situa- A syndrome involving exploratory behav- tions. For example, Jamieson (1986) noted ior, fearfulness, aggression, and response to that host feeding of brood parasites (that environmental change has been identified in often bear little resemblance to their own off- a number of species and termed the “proac- spring) presumably reflects a spillover from tive-reactive axis” (Hessing et al. 1994; Benus strong selection favoring parental feeding of and Ro¨ndigs 1997; Koolhaas et al. 1997, their own offspring. Brood parasites have 1999). Pro-active individuals manipulate or obviously evolved adaptations to take advan- control their environments, while reactive tage of this parental feeding tendency. Jamie- individuals cope with their environments. son (1989) then took the additional step of Relative to reactive individuals, proactive indi- suggesting that helping at the nest in coop- viduals quickly explore their environment, erative breeders also represents a misguided readily form routines, and are more aggres- spillover from parental feeding per se. This sive. Different “types” of individuals might do latter idea was met with considerable resis- well in different environments. While proac- tance (Emlen et al. 1991). Another well- tive animals might outcompete reactive indi- known idea that involves spillover is the pre- viduals in a relatively constant environment, existing sensory bias hypothesis (Ryan and it takes proactive individuals a long time to Rand 1993), which posits that females prefer adjust to changing conditions. In contrast, males that produce signals that are attractive reactive individuals pay close attention to for some other reason; e.g., signals that their environment and, as a result, may be resemble feeding cues (Proctor 1991). favored in more variable environments. Spillover effects could extend across ontog- Drent and colleagues have studied this proac- eny. For example, Arnqvist and Henriksson tive-reactive syndrome in the great tit (Parus (1997) suggested that excessive sexual can- major) in both the laboratory and field. They nibalism in fishing spiders (resulting in some found correlations between exploratory females having a high percentage of infertile behavior (Verbeek et al. 1994), foraging eggs possibly because they attacked all males behavior (Drent and Marchetti, 1999; Mar- that they encountered in their lifetime) could chetti and Drent, 2000), boldness/reactions be the outcome of a general feeding aggres- to a novel environment (Verbeek et al. 1994; sion syndrome expressed over a lifetime. Juve- Drent and Marchetti 1999), aggressiveness/ niles that are more voracious should feed at dominance in juveniles (Verbeek et al. 1996), a higher rate and thus grow faster and larger, responses to lost contests (Verbeek et al. ultimately into more fecund adult females 1999), and behavioral/physiological reac- ( Johnson 2001). Adult females that continue tions to stress (Carere et al. 2001, 2003). to be more voracious should further enhance 250 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 their fecundity. If, however, there are positive male and female sibs has indeed been correlations between attack tendencies on detected in Drosophila (Partridge 1994). Fur- various potential prey including conspecific thermore, the correlation across sexes could males (i.e., a “voracity syndrome”), then this involve superficially unrelated, gender- could explain the observed excessive sexual dependent behaviors. For example, artificial cannibalism. Recent studies confirmed the selection in mice for highly aggressive, terri- existence of a voracity syndrome in another torial males did not influence female terri- species of fishing spider ( Johnson and Sih, torial aggression (females do not typically personal communication). show territorial aggression), but increased Discussion of carryovers over ontogeny female proactivity expressed as an increased brings up the general issue of the temporal tendency to bury (rather than avoid) an elec- stability of behavioral correlations. The liter- tric prod (Koolhaas et al. 1999). ature on humans, primates, and laboratory It is worth emphasizing that depending on and domesticated animals includes consider- the contexts or situations compared, behav- able data on this issue (Gosling 2001); how- ioral correlations need not generate conflicts ever, little information exists for other organ- or tradeoffs. Conflicts occur when behavior is isms. Clearly, a behavioral syndrome is likely beneficial in some contexts or situations and to be particularly ecologically and evolution- costly in others. For example, high activity is arily important if it is consistent over a life- often advantageous in feeding or mating con- time. We suggest, however, that even a short- texts, but costly in an antipredator context. term behavioral carryover should be Similarly, aggressiveness might often be ben- important. In the sunfish-salamander system eficial in a contest context, but costly if discussed above, we found reasonably strong directed against offspring. However, no con- correlations between activity in the presence flict arises across contexts or situations where of fish cues versus in the absence of cues a the behavior is always favored. If, for example, few days earlier or later, but weak correlations high activity levels result in higher mating suc- several weeks earlier or later in the larval cess across a range of different social situa- period (Sih, personal communication). How- tions (e.g., different densities or sex ratios), ever, given that even an hour of inappropri- then a positive activity correlation across ately high activity in a fish pool in the day social situations does not result in a tradeoff strongly increases larval mortality, a carryover in mating success across situations. Nonethe- that lasts for even a few weeks can be ecolog- less, the correlation still has an important ically very important. effect in that it increases variation among The definition of a behavioral syndrome individuals in performance. In this social/ can be extended beyond behavioral carryo- mating example, a positive activity correla- vers within a given individual to also include tion increases variation in mating success and carryovers among individuals with the same thus the opportunity for sexual selection. A or similar genotypes. For example, for a study on water striders found that this “win- clonal species, a behavioral syndrome could ners are winners, and losers are losers” effect involve a carryover between the feeding activ- of a positive activity correlation increased ity of some individuals to the mating activity overall opportunity for sexual selection by of other clonemates. Taking this notion a step almost 50% (Sih, personal observation). further, behavioral correlations can even It should also be noted that while our carry over across the sexes (e.g., between examples have emphasized positive behav- brothers and sisters). For example, since sex- ioral correlations, the concept of a behavioral ual selection often favors males with high syndrome includes both positive and negative mating tendencies, Halliday and Arnold correlations. A strong negative behavioral (1987) suggested that a genetic correlation correlation across contexts or situations still between the sexes could cause some females has the potential to be evolutionarily and eco- to mate more frequently than necessary rela- logically important. For example, Hedrick tive to their own fitness needs. A positive (2000) showed that male crickets that have genetic correlation between mating drives of longer courtship calling bouts (i.e., take September 2004BEHAVIORAL SYNDROMES 251 greater risks while calling) compensate for individuals. Dominant and subordinate indi- this risky behavior by being more cautious viduals typically differ in a suite of behav- when danger is imminent by exhibiting iors—e.g., in foraging, antipredator, and mat- longer latencies to emerge from shelter when ing contexts. Relatively little is known, placed in a novel, potentially risky environ- however, about behavioral syndromes for ment, and longer latencies to reinitiate call- other behavioral dichotomies. For example, ing after being interrupted by a predator cue. we suspect that dispersing individuals might In general, adaptive behavioral compensa- often be more bold or aggressive than site tion that reduces the costs of other costly faithful ones. If so, how is this reflected in a (e.g., risky) behaviors might often generate broad range of behaviors across multiple negative behavioral correlations across con- environmental situations? texts. A behavioral syndrome might then con- In sum, while existing examples suggest sist of a suite of positive correlations among that behavioral syndromes might often be similar behaviors that carry over across con- very important, the basic quantitative natural texts or situations, mixed with negative cor- history of behavioral syndromes remains to relations due to adaptive compensatory be worked out for most nonlaboratory ani- behaviors. Finally, some behaviors may not be mals. Which behaviors are correlated across significantly correlated at all. In particular, which contexts, and how stable are these cor- behavioral correlations might often be con- relations? Given that behavioral syndromes text specific or domain specific (Coleman can be important, we next discuss approaches and Wilson 1998). While different behaviors to understanding these syndromes might be correlated within a feeding context or within an aggression context, these might Evolutionary Issues represent different domains that are uncor- First, we examine the evolution of behav- related. Overall, it seems likely that a study ioral syndromes per se; i.e., the evolution of that quantifies multiple aspects of behavior behavioral carryovers (that involve less than for the same set of individuals will yield a mix optimal plasticity) and behavioral genetic cor- of positive, negative, and nonsignificant cor- relations. If these generate suboptimal behav- relations. iors, why do they persist? We then address the Unfortunately, quantifying all these corre- evolution of behavioral types within a syn- lations can be a difficult, if not overwhelming, drome. Which behavioral types (e.g., more logistical task. How far afield do we need to versus less aggressive) should be found in any go in our search for behavioral syndromes? One approach should be to examine corre- given environment? What conditions allow lations that have been shown to be important for the maintenance of genetic and individ- in the few systems that have been studied in ual variation in behavioral types within or this context (e.g., activity in the presence ver- among populations? Although no extant sus absence of predators, aggression in feed- models explicitly address the evolution of ing, mating and contest contexts). Another behavioral syndromes, we draw on an analo- approach could be to examine behavior in a gous literature on the evolution of adaptive broader spectrum of situations for systems plasticity (e.g., Scheiner 1993; Sibly 1996; with known individual variation in behavioral Schlichting and Pigliucci 1998; de Jong and types for one focal context. We suggest, for Gavrilets 2000) to generate intuitively reason- example, contrasting a range of behaviors able predictions and to provide guidelines on (feeding, antipredator, contest, mating) for directions for future modeling. alternative male mating types (Shuster and Wade 2003), dispersers versus site faithful evolutionary persistence of limited individuals (Dingle 2001), producer versus plasticity scrounger foragers (Barnard and Sibly 1981; What mechanisms might explain the evo- Giraldeau and Beauchamp 1999), ambush lutionary persistence of behavioral carryovers versus active foragers (Eckhardt 1979; Mc- (i.e., of limited plasticity)? Although at first Laughlin 1989), or high versus low vigilance glance it might seem counterintuitive, under 252 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 realistic scenarios natural selection can favor individuals from exposure to the costs of the evolution of limited plasticity. If individ- behavioral carryovers; e.g., “geared up” indi- uals have poor information about their envi- viduals that would do poorly with predators ronment—i.e., weak covariance between can survive by avoiding habitats with preda- environmental cues that induce plasticity and tors. the actual selective environment—then the optimal reaction norm (given the poor infor- evolution of behavioral genetic mation) can have a much shallower slope correlations (less plasticity) than the optimal reaction While genetic correlations among life his- norm, given complete information (Tufto tory and morphological traits have been well 2000). Using a stock market metaphor, given studied (Roff 1992), we know less about poor information about future market genetic correlations among behavioral traits. changes, “staying the course” can be more Genetic correlations have been treated in two profitable than attempting to predict and main ways in evolutionary ecology. One view, “play the market.” For an ecological example, exemplified by conventional life-history the- if prey have poor information about the pres- ory, treats genetic correlations as a source of ence of dangerous predators, then even if constraint on the evolution of optimal traits. predators are only occasionally present, prey The assumption is that the correlation might be forced to act as if predators posed a reflects some underlying mechanism that is continual threat (Sih 1992); e.g., prey might difficult to decouple even over evolutionary evolve group living or ambush hunting as time. For example, a genetic correlation essentially fixed responses to predators that might be due to pleiotropy (where one gene are only occasionally present. Luttbeg and Warner (1999) similarly showed, in a mating governs two or more traits), or to a deep, context, that while environmental variation underlying physiological constraint (e.g., the favors learning and behavioral responses, inherent size/number tradeoff or an energy relatively little response is expected if individ- allocation tradeoff). An alternative view uals have poor information or if they are sub- assumes that proximate mechanisms, includ- ject to substantial time lags. These models, ing genetic mechanisms, can themselves however, do not consider behavioral syn- evolve by natural selection. For example, if dromes across multiple contexts. Further pleiotropy causes a maladaptive behavioral models should examine the basic logic out- correlation, then selection ought to alter that lined above in scenarios explicitly designed to pleiotropy (e.g., via genetic modifiers) to include behavioral syndromes. decouple the fitness-reducing correlation. Alternatively, even if selection favors the Overall, natural selection ought to shape opti- decoupling of behavioral carryovers, they mal genetic correlations to produce adaptive might still persist if they have a proximate phenotypes with functionally integrated (e.g., a genetic or neuroendocrine) basis that suites of traits (Cheverud 1996, 2000; Wagner is difficult to break (see Proximate Mecha- et al. 2000). This view has been applied to nisms, below). Even if the proximate mecha- understanding the genetics governing the nism can be decoupled, if that decoupling development of integrated morphologies takes a long time relative to the pace of envi- (Leamy et al. 1999; Klingenberg et al. 2001). ronmental change, then low plasticity is Our discussion of behavioral syndromes favored (Padilla and Adolph 1996). Finally, primarily falls within the “constraint” view of limited plasticity should be more likely to per- behavioral correlations. We emphasize sce- sist if its cost is mediated by compensatory narios where underlying proximate mecha- traits (e.g., other behaviors or morphological nisms produce behavioral genetic correla- traits) that reduce the cost of the behavioral tions across contexts that generate conflicts carryovers (DeWitt et al. 1999), or if individ- that cause suboptimal behavior in one or uals strongly avoid situations where they both contexts. Because of the conflict, no behave inappropriately (i.e., situation individuals or genotypes attain the uncon- choice). Situation choice effectively shields strained optimum (Figure 2). Instead, many September 2004BEHAVIORAL SYNDROMES 253 alternative behavioral types (e.g., a mix of types should be favored by selection in a par- high and low aggression or high and low activ- ticular environment? For example, consider ity genotypes) might all cope equally well— prey activity in the absence and presence of all exhibiting variations on “making the best predators. Prey that are more “geared up” of a bad situation.” In contrast, the “optimal feed and grow rapidly in the absence of pred- genetic architecture” view posits that natural ators but suffer high mortality when preda- selection should break up deleterious behav- tors are present, while “geared down” prey ioral correlations, so that behaviors should be survive relatively well when predators are either decoupled (and thus free to evolve to present but do poorly in the absence of pred- the optimum in all environments) or corre- ators (e.g., Sih et al. 2003). Prey with inter- lated in an adaptive way. An adaptive behav- mediate activity profiles presumably show ioral correlation could reflect alternative intermediate fitness in both habitats. What optimal strategies for coping with two situa- conditions should favor the evolution of tions. For example, as noted earlier, male “geared up” versus “geared down” versus crickets that have longer calling bouts when intermediate activity types? predators are absent compensate by exhibit- In theory, the fitness isocline method (Lev- ing stronger antipredator behavior when ins 1968; Leon 1993) could provide some predators are present (Hedrick 2000); males insights (Figure 3). This method has been with shorter calling bouts exhibit less used to address optimal life histories (Pianka response to predators. Although no explicit and Parker 1975; Roff 1992), given tradeoffs theory exists on the evolution of behavioral that produce a negative correlation between genetic correlations and behavioral syn- traits (e.g., between current reproduction dromes, it should depend presumably on an and future survival) that are captured in a interplay between the strength of selection constraint function (Figure 3a). Only life-his- tory combinations that are on or below this (against or favoring the correlation) and the function are possible. Fitness isoclines are ease of decoupling the mechanisms underly- lines of equal fitness on a fitness landscape ing behavioral correlations. where overall fitness is higher for lines that which behavioral type should be are further from the origin (that have higher favored? current reproduction and higher future sur- vival). The optimal life history (indicated by Optimality models predict optimal behav- the star) is found by looking for the point on iors across a broad range of environmental the constraint function that yields the highest contexts (Krebs and Davies 1996; Dugatkin fitness. A conceptually similar construct has and Reeve 1998; Houston and McNamara been used to analyze optimal diets of herbi- 1999; Clark and Mangel 2000). These models vores (via linear programming: Belovsky assume that genetic mechanisms governing 1984), and in theory could be used to exam- behavior do not constrain the power of nat- ine time budget conflicts in behavioral ecol- ural selection to drive the evolution of opti- ogy, in general. mal behavior. Simple quantitative genetic Behavioral syndromes, however, differ models of adaptive plasticity confirm that from the scenario in Figure 3a in two ways: 1) although genetic correlations can influence traits are often positively, rather than nega- evolutionary trajectories, ultimately if there tively, correlated; and 2) due to stabilizing are no limits to plasticity selection should selection (i.e., that accounts for time budget indeed result in the evolution of optimal conflicts within each environment), there is traits in all environments (Via and Lande an optimal behavior in each environment 1985; Gomulkiewicz 1998). Behavioral syn- (Figure 3b). Despite these differences, the dromes and, in particular, behavioral carryo- method still allows us to visualize the optimal vers, can produce a limit to plasticity, how- behavioral types (represented by the double ever. If constraints prevent individuals and line) as the intersection between the con- genotypes from exhibiting optimal responses straint function (due to the behavioral carry- to environmental variation, which behavioral over) and the highest attainable point on a 254 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Figure 3. Fitness Isoclines and Selection on Correlated Traits A fitness isocline view of selection on correlated traits. (a) A standard view on the evolution of life histories given a cost of reproduction that results in a negative correlation between current reproduction and future survival (represented by the constraint function). Fitness isoclines are lines of equal fitness. Higher survival and reproduction yields higher overall fitness. The optimal life history is represented by the star. (b) An analogous view for behavioral syndromes that produce a positive correlation (shown by the constraint line) between activity in two environments (taken from Figure 2). The concentric ovals show a fitness landscape with a maximum (optimum in the absence of behavioral carryovers) at the star. The shaded region on the constraint function indicates the best behavioral types (all with similar fitness) given the behavioral carryover.

fitness landscape. In our example, a range of trait that is not well adapted to the later selec- behavioral types yield similar highest fitness. tive environment, individuals cannot further To emphasize, while these optimal behavioral adjust their trait. For example, if individuals types exhibit suboptimal behavior (relative to grow up with predators and induce a spine an infinitely plastic optimum) in every situa- (Tollrian and Harvell 1999), they cannot lose tion, they still represent the “best of a bad that spine even if they end up in a predator- situation” in that they show the best available free habitat where the spine reduces compet- strategy given the constraint of limited plas- itive ability. This clearly differs from the usual ticity associated with the behavioral syn- assumption in behavioral ecology that behav- drome. iors are infinitely plastic and reversible; how- While the fitness isocline method has some ever, it might not be unrealistic for behavioral heuristic value, progress in modeling behav- syndromes. An individual’s early experiences ioral syndromes will require more explicit might shape its behavioral type that then models that formalize specific scenarios and results in relatively fixed (or at least less than assumptions. Some guidelines can be found infinitely plastic) behavioral tendencies in models of adaptive plasticity (often life-his- across a range of contexts. tory plasticity) in a variable environment The evolution of adaptive plasticity in the (e.g., Houston and McNamara 1992; Moran above scenario then depends heavily on the 1992; Kawecki and Stearns 1993; Sibly 1995, match (or mismatch) between the environ- 1996; Zhivotovsky et al. 1996; de Jong and ments of development and selection (statisti- Gavrilets 2000). In these models, the usual cally, the covariance between X and Y ) (de scenario is that individuals experience a Jong and Gavrilets 2000). X and Y can be mis- developmental environment X that deter- matched either because of spatial or tempo- mines a focal trait that then influences fitness ral variation in the environment. Alterna- at a later time in the selective environment Y. tively, even in a nonvarying environment, the For example, depending on whether individ- focal trait can be mismatched to Y if X pro- uals develop in the presence or absence of vides imprecise cues on Y (e.g., Sih 1992; predators, they induce morphologies, life his- Getty 1996; Tufto 2000). Drawing from mod- tories, or behavioral tendencies that then els of adaptive plasticity, we suggest the fol- influence their subsequent fitness. These lowing predictions on the evolution of behav- models typically assume that plasticity is irre- ioral types. First and fundamentally, the versible. If the early environment induces a expected behavior in any given situation September 2004BEHAVIORAL SYNDROMES 255 depends on selection in all situations that are siderations—reversible plasticity with time part of the same behavioral syndrome. That lags. They focused on conditions where plas- is, selection in each environment affects the ticity is favored over fixed traits that are opti- evolution of behavioral types that then carries mal for one environment but costly in over to influence behavior in all other rele- another. Not surprisingly, they found that vant situations. All else the same, the optimal plasticity is favored if time lags are short rela- behavioral type should be more heavily influ- tive to the rate of environmental change (see enced by selection in: 1) environments that also Levins 1968). Their model allowed the individuals experience more frequently; 2) plastic genotype to exhibit the optimal trait environments with a stronger selection gra- in each environment; i.e., they did not dient—a stronger effect of behavior on fit- include a limit to plasticity, a notion that is at ness; and 3) higher quality environments— the heart of the idea of behavioral carryovers. e.g., selection in source habitats outweighs Future work adding behavioral carryovers to selection in sink habitats (Holt and Gaines models that examine reversible plasticity with 1992; Holt 1996). Thus, for example, prey are time lags should be insightful. likely to evolve a “geared up” activity type that does well in the absence of predators, even maintenance of variation in though it fares poorly with predators present behavioral syndromes (e.g., Sih et al. 2000, 2003), if prey spend most The maintenance of variation is a major of their time in habitats without predators, if issue in evolutionary biology, in general activity has a relatively weak relationship to (Futuyma 1998). Individual variation also has risk, and if predators are so effective that hab- important ecological implications (Bolnick et itats with predators are evolutionary sinks. Given that the pattern of environments al. 2003). Despite this, in behavioral ecology, encountered by individuals matters, the evo- the tradition has generally been to ignore lution of behavioral types should depend on individual variation and instead emphasize situation selection (Holt 1996; Zhivotovsky et shifts in mean behavior in response to chang- al. 1996). If individuals choose situations that ing environments. Indeed, in a simple, pure they do particularly well in, then as noted ear- optimality view, over time natural selection lier this reduces the fitness costs of limited should result in little or no genetic variation plasticity. Situation choice could drive the among individuals—all individuals should be evolution of behavioral specialists, each pri- optimal in all environments. In reality, indi- marily using their best habitats, with low vidual variation in behavior is probably ubiq- genetic variation in behavioral types within uitous (Clark and Ehlinger 1987; Wilson each situation, but possibly the maintenance 1998). Some of this variation might persist of high individual variation in the overall because multiple optima exist within a single metapopulation. environment. Optimal behaviors depend on Although the above predictions seem rea- a balance of conflicting demands (tradeoffs). sonable, we need theory developed specifi- If individuals differ in their tradeoffs—e.g., cally for addressing behavioral syndromes. due to differences in individual state (condi- Specifically, rather than assume that each tion, energy reserves, size)—they can exhibit individual goes through one cycle of irrevers- different optimal behaviors within the same ible, plastic response in each generation (the environment (Houston and McNamara 1999; usual assumption in models of adaptive plas- Clark and Mangel 2000; Mangel and Stamps ticity), we need models that allow for multiple 2001). Coexistence of multiple behaviors is episodes of reversible plasticity. Rather than probably often further enhanced by negative assume instantaneous, infinite plasticity (the frequency dependence that has been mod- usual assumption in optimality models), we eled using game theory (Maynard Smith need models that include time lags and limits 1982; Dugatkin and Reeve 1998). to plasticity (limits to the slope and perhaps We suggest that behavioral syndromes height of plasticity functions). Padilla and might also play an important role in enhanc- Adolph (1996) considered two of these con- ing the maintenance of individual variation 256 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 in behavior. The basic rationale is simple. If ance, migration/selection balance, behavioral carryovers are important, then no frequency dependence, and overdominance individual exhibits the optimal behavior in all (Barton and Turelli 1989; Burger 1998; Hed- situations. Different individuals should be rick 2000). The most relevant theory for best suited for different situations—all of behavioral syndromes should be the theory which are part of the organism’s overall life. on mechanisms maintaining genetic varia- Bold individuals might do well in some social tion in adaptive plasticity. Models on this or ecological situations, while shy individuals issue confirm the usual expectations based do well in others. A range of behavioral types on nonplastic traits (e.g., Via and Lande can coexist in the long-term given suitable 1987; de Jong and Gavrilets 2000). Interest- variation in contexts and environments (see ingly, de Jong and Gavrilets (2000) also pre- Figure 3b where a range of behavioral types dicted that greater environmental variation have similar fitness). The logic is analogous should actually reduce the amount of genetic to theory on the persistence of behavioral or variation in plasticity (e.g., in slopes and life-history polymorphisms in a variable envi- heights of plasticity functions) within popu- ronment; e.g., coexistence of specialists and lations. Their logic is that greater environ- generalists (Moran 1992; van Tienderen mental variation exposes genotypes to poten- 1997), or of high mean/high variance versus tially more serious mismatches resulting in low mean/low variance life histories (Orzack stronger selection against suboptimal reac- and Tuljapurkar 2001). One can think of it as tion norms. “behavioral niche partitioning” (different types do well in different situations) in a vari- other evolutionary considerations able environment. Just as frequency dependence can enhance An exciting future area should be analyses the coexistence of alternative mating, con- of the joint evolution of behavioral syn- test, or foraging tactics, the persistence of dromes and other fitness-related traits (e.g., individual variation in behavioral types (e.g., life histories, morphology). This takes the different coping styles, aggression, or activity “deatomizing” of traits a step further. Rather types) should presumably be increased by fre- than simply look at correlated behaviors across quency dependent selection. Coexistence contexts, we can look at functional integra- could involve mixed ESSs (where all types tion of several types of traits across situations. have equal fitness), or condition dependent A few studies have indeed focused on syn- strategies where high condition individuals dromes of multiple types of traits (e.g., attain higher fitness than low condition ones, Endler 1995; Dingle 2001). As with most but all exhibit a behavioral type that is a best aspects of behavior, however, previous studies solution given the individual’s condition. have emphasized the joint evolution of mor- Behavioral syndromes that revolve around phology and behavior in one particular con- social interactions (e.g., aggression, proactiv- text (e.g., Brodie 1992; Smith and Sku´lason ity) where outcomes, benefits, and costs likely 1996; DeWitt et al. 1999). A broadening of depend on the population’s mix of behav- this approach to consider more behavioral ioral types (e.g., on whether most individuals contexts (predator-prey, aggression, mating, are highly aggressive, or unaggressive, or a dispersal) will be rewarding; i.e., how do mix of both) seem particularly ready for game behavioral syndromes coevolve with other theory analyses. traits? The above mechanisms based on multiple The existence of behavioral syndromes and selective optima can have, but need not their joint evolution with morphology and have, a genetic basis; e.g., behavioral varia- other traits could facilitate speciation (Wcislo tion due to condition dependence is often 1989; Wilson 1998). In brief, if different thought of as nongenetic. Based on a long behavioral types within a species evolve asso- history of evolutionary theory, genetic vari- ciated differences in morphology and other ation can be maintained by a variety of mech- traits, this could enhance both disruptive anisms including a mutation/selection bal- selection against hybrids and assortative mat- September 2004BEHAVIORAL SYNDROMES 257 ing by behavioral type eventually resulting in ticity (e.g., response lags, imprecise informa- speciation. For example, active versus sit-and- tion). Finally, future models should incorpo- wait foragers within one species (that might rate what is known about underlying also differ in their antipredator, mating, con- mechanisms: genetic or physiological. A later test, and dispersal behaviors) should evolve set of models could look at the joint evolution different morphologies, physiologies, and life of behavioral syndromes and other function- histories. Individuals that exhibit intermedi- ally related traits (e.g., morphology, life his- ate traits in this entire suite might generally tory). fare poorly. In addition, the overall differ- ences in a suite of traits could reduce mating Proximate Mechanisms encounters between the types (e.g., if they Although a thorough understanding of the live in different habitats or evolve different mechanisms that underlie behavioral syn- life-history phenologies), and favor positive dromes is important in its own right, we focus assortative mate choice. This basic scenario in particular on several key mechanistic issues for speciation has been discussed in the con- that have potentially powerful evolutionary text of trophic polymorphisms (Wilson 1998), and ecological implications. Specifically, we but might apply more broadly to behavioral address the role of proximate mechanisms in syndromes (and their other associated traits), determining the existence and stability of in general. behavioral correlations and limits to plastic- Finally, an exciting future direction ity. involves tracking the evolution of behavioral To understand the existence and stability syndromes by contrasting behavioral types for of behavioral correlations, a critical issue is related taxa in an evolutionary ecological framework (e.g., Dewsbury et al. 1982; Riech- whether the behaviors are governed by com- ert and Hedrick 1993; Gosling 2001; Sih et al. mon versus independent mechanisms. Consider 2003). We hypothesize that differences a simple case where three behaviors, A, B and between species in behavioral type could have C, are positively correlated: individuals that major effects on their ecology and evolution are the most aggressive toward conspecifics (see Ecological Implications). For example, (A) are also the boldest toward predators (B) work by Lefebvre and colleagues using a and the most voracious foragers (C). In one blend of the comparative method and exper- possible scenario, A and B are both governed iments on focal species have revealed that by mechanism X, while C is governed inde- bird taxa with large brains (relative to body pendently by mechanism Y (Figure 4a). size) tend to be less neophobic, better at Mechanism X might be a single gene with problem solving, more likely to exhibit feed- effects on multiple traits (pleiotropy), a hor- ing innovations, and show greater evolution- mone that affects more than one behavior, or ary diversification and ecological invasiveness an experience that influences multiple (Lefebvre et al. 1997; Sol and Lefebvre 2000). aspects of the phenotype. In this case, con- In conclusion, formal theory on the evo- ditions that favor an increase in A will indi- lution of behavioral syndromes remains to be rectly cause a change in B, and the correla- developed. We first need simple models that tion between A and B cannot be uncoupled address reversible plasticity in scenarios with without changing the underlying mechanism. limits to plasticity and perhaps correlations In contrast, the correlations between A-C or between the means and heights of reaction B-C—e.g., due to a correlation, but not a norms (i.e., specialists with more extreme causal link, between X and Y—are more easily mean traits should have less plasticity than broken apart because they are controlled by generalists that have intermediate mean separate factors. For example, whereas both traits). We can then add other major ele- aggression toward conspecifics (A) and bold- ments of behavioral ecology (e.g., games, ness to predators (B) might be affected by lev- state dependence, explicit tradeoff func- els of a gonadal steroid, foraging behavior tions), as well as more detailed aspects that (C) might be regulated by an independent are important for understanding limited plas- hormonal mechanism. In that case, we would 258 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Figure 4. Mechanisms that Generate or Decouple Behavioral Syndromes Mechanisms that can generate or decouple behavioral syndromes: (a) Behaviors A and B are governed by a common mechanism (e.g., pleiotropy), while behavior C is governed by a separate, independent mechanism Y. If X and Y are correlated (e.g., via linkage disequilibrium), this could result in correlations between A, B, and C. A and B should be difficult to uncouple, whereas it should be relatively easy to decouple C from A and B. (b) Mechanism X governs a fixed trait Y that then produces limited plasticity in behavior A. (c) The effect of a common mechanism X on behaviors A and B can be influenced by modifier Y; e.g., differential epistasis. (d) Effects of a common mechanism X on behaviors A and B are modified by independent modifiers Y and Z; e.g., tissue-specific hormone receptors. September 2004BEHAVIORAL SYNDROMES 259 expect the correlation between aggression genetics, applied animal science, human psy- and antipredator behavior to be more stable chology and behavioral genetics, behavioral than the correlation between foraging behav- endocrinology). We first discuss each type of ior and aggression or antipredator behavior. mechanism separately, and then conclude by Although, in reality, proximate control of emphasizing that they interact; both genetics behavioral syndromes likely involves complex and experience often influence neuroendo- webs of several interacting components that crine mechanisms that govern behavior. Ulti- include multiple genes, experiences, and hor- mately, an interdisciplinary approach that mones, the key to the tightness of behavioral integrates these mechanisms should prove correlations should be the tightness of the most powerful. interdependencies among these compo- nents. genetics To understand how proximate mechanisms Information about the genetic basis of might underlie limited behavioral plasticity, behavioral correlations and limited behavioral we focus on two main lines of logic. First, lim- plasticity is critical for understanding the evo- ited behavioral plasticity can be due to a tight lution of behavioral syndromes. Here, we dis- (perhaps adaptive) connection between a cuss a broad range of genetic approaches that relatively fixed trait (e.g., morphology or neu- have been applied to these issues, albeit almost rophysiology) and behavior (Figure 4b). For exclusively in a few model systems. In most example, low activity individuals might lack taxa, little or no information exists on the the morphological or physiological capacity genetics of behavioral syndromes. to move efficiently, and thus might be rela- Standard quantitative genetic methods tively inactive even when high activity is oth- erwise favored. Second, within-individual (Lynch and Walsh 1998) can be used to mea- consistency in behavior could be the result of sure behavioral genetic correlations and the a behavioral positive feedback loop, often heritability of behavioral types (Boake 1994). driven by learning. Choice of a given behav- Given that behavioral syndromes involve con- ioral lifestyle in the short term might predis- necting behaviors across environments, key pose individuals via learning to continue that issues are the genetic basis of and genetic vari- lifestyle. Both of these mechanisms can cause ation in response to environmental variation, time lags in an individual’s behavioral or reaction norms and gene x environment response to environmental change; it can interactions (Via and Lande 1985; Via et al. take time for individuals to learn that the 1995). The quantitative genetics of behavioral environment has changed and to learn to syndromes has long been a focal issue in the adapt to a new environment, or behavioral behavioral genetics of a few model systems plasticity might depend on an underlying (laboratory mice: Henderson 1986; Koolhaas physiological or morphological trait that et al. 1999; humans: Bouchard and Loehlin takes time to change. As noted in the earlier 2001). In laboratory mice, for example, par- section on the evolution of limited plasticity, ent-offspring regressions have quantified long behavioral response lags (relative to the behavioral genetic correlations, and long- rate of environmental change) can favor lim- term selection lines have produced corre- ited plasticity (Sih 1992; Padilla and Adolph lated changes in suites of behaviors (Sluyter 1996). For both lines of logic, it should be et al. 1995; Bult and Lynch 2000). Similarly, useful to understand how they are governed in several domesticated species, artificial by underlying mechanisms. selection produced evolutionary changes in Below, we discuss three major types of behavioral types such as fearfulness or tame- mechanisms that likely influence behavioral ness (Trut 1999). syndromes: genetic, environmental experi- Many aspects of the genetics of behavioral ence, and neuroendocrine effects. We briefly syndromes remain to be studied, however. review literature from diverse fields, many of Most importantly, only a few studies have which are relatively rarely read by behavioral looked at even the most basic aspects of the ecologists (e.g., mouse and fly behavioral genetics of behavioral syndromes in nondo- 260 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 mesticated animals (Palmer and Dingle 1989; otropy (Greenspan 2001). This possibility is Riechert and Maynard Smith 1989; Dinge- referred to as differential epistasis (Cheverud manse et al. 2002; Drent et al. 2002). Other 1996; Wagner et al. 2000; Figure 4c). quantitative genetic issues that are important, To estimate the number of loci and their in theory, but are largely unstudied include relative importance in determining a given the genetics of limited plasticity and the relationship, an invaluable tool is quantitative genetics of situation choice (e.g., a tendency trait locus (QTL) analysis. If only a few major for bold individuals to choose risky environ- QTLs control a trait, a goal is to identify can- ments). To understand the evolution of lim- didate genes, their function, and interactions ited plasticity, key issues are the heritability of among them. If focal behaviors are controlled plasticity per se (Schlichting and Pigliucci by many QTLs of small effect, then a key issue 1995) and the possibility that low behavioral is the pattern of pleiotropy underlying plasticity might be genetically correlated with genetic correlations. Are all the correlations other relatively fixed traits (e.g., morphol- determined by one set of pleiotropic loci, or ogy). To measure a genetic tendency for a are different correlations governed by largely given behavioral type to experience some independent modules of pleiotropies (Chev- environments more than others—e.g., either erud 1996; Mezey et al. 2000). In theory, nat- due to situation choice by the focal individual ural selection through differential epistasis or because its parents had a genetic tendency could shape the genetic architecture to pro- to provide a particular rearing environ- duce optimal sets of functionally integrated ment—the relevant metric is the gene x envi- suites of traits (Cheverud 1996; Wagner et al. ronment correlation. While the behavioral G 2000) or optimal behavioral syndromes. Note x E correlation has been well studied in that the “optimal” behavioral syndrome could humans (Rutter and Silberg 2002), it remains still involve limited behavioral plasticity and largely unstudied in other species. apparently suboptimal behavior if, for exam- Standard quantitative genetics provides ple, information constraints prevent even the only a statistical snapshot of a potentially best individuals from rapidly tracking a dynamic, evolving genetic system. To better changing environment (see sections on the understand the mechanisms governing the evolution of limited plasticity and the sections evolution of behavioral syndromes, it is useful on experience and neuroendocrine mecha- to know the genetic architecture that under- nisms). Some recent studies on model sys- lies genetic correlations and limited plasticity. tems have indeed shown that behavioral The number of loci affecting behaviors and genetic correlations can evolve (Bult and their relative importance, pleiotropy, domi- Lynch 2000), and other studies have applied nance interactions among alleles at one QTL methods to examine the genetics of locus, and epistatic interactions among loci behavioral syndromes (Flint et al. 1995; Toye (Cheverud 1996) might all influence behav- and Cox 2001; Turri et al. 2001). In particu- ioral syndromes. As noted above, a simple lar, Turri et al. (2001) found that “anxiety” in idea is that the stability of a genetic correla- mice might be the outcome of at least three tion between two behaviors should depend separate behavioral tendencies—low activity on whether it is caused by a common or inde- per se, avoidance of aversive stimuli, and low pendent genetic mechanism. A behavioral exploration—governed by QTLs on separate genetic correlation due to pleiotropy (a com- chromosomes. mon mechanism for the two behaviors) Finally, molecular genetic methods have should be harder to decouple than one based revealed numerous single-gene effects on on linkage disequilibrium (a statistical rela- suites of behaviors in a few model systems tionship between mechanistically indepen- (laboratory mice: Greenspan 2001; Buc´an dent genes) (Figure 4a). However, genetic and Abel 2002; Drosophila: Sokolowski 2001). correlations due to pleiotropy can, at least in Perhaps the best example of a naturally theory, also be broken up by selection on occurring, single-gene behavioral polymor- modifiers (i.e., other loci) that alter the plei- phism involves the for gene that influences September 2004BEHAVIORAL SYNDROMES 261 foraging activity in Drosophila melanogaster experience (Pereira and Sokolowski 1993). In D. melano- In most cases, behavioral syndromes are R gaster, larvae homozygous for the for allele likely to be determined not just by genes but (rovers) have considerably longer foraging also by individual experiences. What role trails than individuals homozygous for the does experience play in explaining differ- s for allele (sitters). Rovers and sitters differ in ences among individuals in behavioral type, ways beyond larval feeding rate. Relative to or changes in behavioral type over a lifetime? sitters, rovers exhibit a higher tendency to Conversely, how do behavioral types differ in encapsulate parasitoid wasp eggs (Hughes the ways in which they learn from their expe- and Sokolowski 1996), and the higher activ- riences? Again, these issues have only been ity of rovers persists into adulthood even addressed in a few animals (e.g., humans and though adults and larvae have very different other primates). Below, we discuss some ideas means of locomotion and feeding. The fit- drawn from either the limited literature on ness of rovers versus sitters depends on fly experience and behavioral syndromes (see density—rovers are favored under high den- Stamps 2003 for a more detailed review), or sities and sitters in low densities (Sokolowski from the extensive literature on the effects of et al. 1997)—and on wasp parasitism rates experience on a single behavior. (Hughes and Sokolowski 1996). Experiences over the course of ontogeny Recent reviews on the genetics of behavior can either produce or break up behavioral in laboratory mice (Greenspan 2001; Buc´an syndromes. On the one hand, experiences and Abel 2002) and Drosophila (Sokolowski can start an individual on an ontogenetic tra- 2001) emphasize, however, some important jectory that sets its later behavioral type. For limitations of molecular genetic studies. First, a methodological problem is that many example, stressful or traumatic early juvenile molecular genetic studies involve drastic experiences can cause an individual to be changes in gene expression (e.g., complete anxious or fearful for the rest of its life. On knockouts) that very possibly have qualita- the other hand, experience can also reshape tively different effects on behavior than more or modify a behavioral syndrome. For exam- subtle genetic variation. More relevant ple, while aggressive behavior might be cor- insights might come from further studies on related with antipredator behavior prior to the behavioral effects of relatively small any experience with a predator, subsequent changes in gene expression (e.g., hypo- experience with a predator might decouple morphic mutations) or localized tissue-spe- this correlation by changing the individual’s cific changes in gene expression (Greenspan antipredator behavior without affecting 2001). Even more fundamental is the growing aggressive behavior in the absence of risk. evidence that effects of any given single gene The role of experience in building versus on behavior depend heavily on the genetic breaking up behavioral syndromes likely background (epistasis). For example, the depends on the timing of experience over effect of a given knockout mutation varies ontogeny. Early experiences might often among genetic lines (Buc´an and Abel 2002; build behavioral syndromes; that is, variations Crabbe 2002). Behavioral syndromes appear in early experience might produce individual to be under polygenic control with wide- differences in behavioral types. In species spread pleiotropy and epistasis. In that case, with extended parental care, parental behav- molecular genetic studies that focus on one ior can obviously play in important role in or a few genes might not be an efficient determining the behavioral types of their off- method for understanding the genetics of spring. For example, interactions between behavior. DNA microarrays that simulta- mothers and infants influence the develop- neously assess gene expression for thousands ment of personality in rats (Meaney 2001) of loci might yield suggestions for further and rhesus monkeys (Stevenson-Hinde et al. directions to pursue, though the problem of 1980; Suomi 1987). Even in species without interpreting microarray data is clearly non- extended parental care, parental choices trivial. (e.g., oviposition site choice or parental 262 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 investment in eggs) can have major impacts 1996; Capitanio 1999). From an evolutionary on offspring behavior. For example, maternal ecological perspective, it seems likely that choices can produce small differences in the selection should uncouple a behavioral syn- growth rate and behavior of juveniles that drome through ontogeny when environmen- ultimately result in the development of dis- tal conditions experienced by juveniles differ crete alternative mating strategies (Caro and substantially from those experienced by Bateson 1986; Gross 1996; Emlen 1997). Of adults, particularly if a behavioral syndrome course, postnatal social interactions can also that works well in juveniles does not work as influence behavioral types. In house mice, well in adults. We might thus expect to see a juvenile coping styles are shaped more by decoupling of behavioral syndromes in spe- their postnatal social environment (sex ratio: cies with complex life cycles or those which Benus and Henkelmann 1998) than by their experience ontogenetic niche shifts during mother’s coping style (Benus and Ro¨ndigs development (e.g., holometabolous insects, 1997). In general, because the social environ- anurans). ment experienced by developing organisms While the above discussion has focused on often influences their subsequent social how experience influences behavioral syn- behavior and life history (e.g., Rodd and dromes, the interaction also goes the other Sokolowski 1995; White et al. 2002), we pre- way: behavioral syndromes can also shape dict that future studies will reveal important experience and influence learning. Interest- effects of the social environment on the devel- ingly, the relationship between behavioral opment of behavioral syndromes. types (e.g., boldness) and speed of learning Two basic mechanisms could underlie a varies, depending apparently on the syn- tendency for early experiences to canalize drome and the type of task to be learned. subsequent behavioral types. One mecha- One view is that bolder individuals experi- nism involves the effects of early experience ence more of their environment and thus (e.g., habitat use) on the development of rela- learn more rapidly. Some studies indeed tively fixed traits (e.g., morphology, physiol- show that neophobia (avoidance of novel ogy: Wainwright et al. 1991) that set an indi- stimuli) is associated with slow learning of for- vidual’s subsequent lifestyle and behavioral aging tasks in birds (Greenberg 1990; Seferta type. Alternatively, early experiences might et al. 2001; Webster and Lefebvre 2001). The set off a positive feedback loop involving literature on the proactive-reactive axis, how- learning and tradeoffs between performance ever, emphasizes the opposite: proactive indi- in different lifestyles (Immelmann 1975). If viduals (more aggressive, active, and bold) individuals that have learned a particular life- tend to form set routines and learn about style cannot easily learn a new one, or if the environmental changes more slowly (Verbeek cost of switching is large, then they might be et al. 1994, 1996; Koolhaas et al. 1997). Proac- constrained to maintain their current life- tive individuals try to manipulate situations, style. rather than react to them. In colloquial Behavioral types, however, are not neces- terms, they bluster through life at high speed sarily set for life. Some inference on the role and do not appear to notice subtle changes of later experiences in altering behavioral in their environment. In contrast, reactive types can be gleaned from the literature in individuals adapt to situations; they are more comparative psychology on the stability of sensitive to environmental changes. Putting personalities over the life course. Ongoing the two views together, it appears that bolder experience can either enhance stability by individuals might be better at learning novel reinforcing a package of traits, or experience tasks, while more shy and reactive individuals might modify personality. Most studies look- are better at sensing environmental changes ing at the stability of personality have found within a familiar task. More work, however, is that some aspects of personality are stable clearly needed to clarify generalities on the while others are not (dairy goats: Lyons et al. relationship between behavioral syndromes 1988; wolves: MacDonald 1983; great tits: Ver- and learning. beek et al. 1994, rhesus monkeys: Suomi et al. In summary, much remains to be learned September 2004BEHAVIORAL SYNDROMES 263 about the effects of experience on behavioral mone synthesis and breakdown, binding syndromes outside of primates. Further globulins, and hormone-hormone interac- empirical and theoretical work should tions can all influence how a given hormone address when experience is limiting versus is related to a particular behavior or behav- flexible, and how the salience, duration, and ioral syndrome (Figure 4d). These mediating timing of experience affect behavioral syn- factors ought to allow for an easier decou- dromes. A particularly exciting avenue might pling of the tendency for hormones to pro- be the ongoing feedback between behavioral duce behavioral syndromes. syndromes and learning. For example, selection has apparently decoupled trait expression from the under- neuroendocrine mechanisms lying hormonal pathway in the sex-role- Because hormones regularly act on multi- reversed Wilson’s phalarope (Phalaropus tri- ple target tissues, thus mediating “suites of color). Female aggression occurs without correlated phenotypic traits” (Ketterson and increases in plasma testosterone levels (Fiviz- zani et al. 1986). Instead, female phalaropes Nolan 1999), it seems plausible that hor- apparently increase their aggression levels by mones might generate behavioral syndromes increasing levels of androstenedione, a tes- (e.g., testosterone levels might underlie tosterone precursor (Fivizzani et al. 1994). aggression syndromes). Some studies indeed Selection acting independently on target tis- show associations between hormonal profiles sue characteristics, such as enzyme conver- and behavioral types. For example, different sion of androstenedione into testosterone, or coping styles in house mice (Mus musculus) variation in target-tissue receptors should are associated with different neuroendocrine yield fewer correlated responses than selec- profiles. Proactive individuals show low hypo- tion acting on overall levels of a circulating thalamic-pituitary-adrenal axis reactivity in hormone such as testosterone. Altering the response to stress (low plasma corticosterone level of a hormone that mediates a suite of response) but high sympathetic reactivity traits thus could be an effective way to change (high levels of catecholamines), while the the timing of a syndrome, while altering reverse is true for reactive individuals receptors is more effective at changing indi- (reviewed in Koolhaas et al. 1997). In addi- vidual traits. Situations where behavior seems tion, there are differences between the two to no longer be under the control of a tradi- coping styles with respect to gonadal activity, tional hormonal pathway should allow us to disease vulnerability, and stress pathology. better understand evolutionary lability in the Other studies have measured the neuroen- endocrine system that allows some decou- docrine basis of reactivity or fearfulness in pling of the correlated effects of a circulating other mammalian species (reviewed in Boissy hormone on a behavioral syndrome (Hews 1995), and neuroendocrine correlates of the and Moore 1997). migratory syndrome (flight, delayed repro- Although the pathway from hormones to duction, flight muscle development) in behavior can be complex, some insights can insects (Fairbairn 1994; Zera and Denno be gained by classifying hormonal effects into 1997; Dingle 2001). two main categories: organizational effects Recent work in behavioral endocrinology versus activational effects (Arnold and Breed- emphasizes, however, that the relationship love 1985; Moore et al. 1998). Organizational between hormones and behavior is often far effects are usually thought to act early in more complex and plastic than the simple development by organizing brain anatomy notion that circulating levels of hormones and neurochemistry, and other aspects of govern behavior (Hews and Moore 1997; Ket- morphology or physiology, that set the stage terson and Nolan 1999). Hormonal impacts for later hormonal effects on behavior. Orga- on behavior depend on many mediating fac- nization is thus traditionally associated with tors. For example, variability in hormonal effects that are fixed for life (e.g., primary receptors (receptor density, specificity, bind- sexual differentiation through sex-specific ing affinities), metabolic properties of hor- gonadal development), or at least for some 264 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 significant amount of time. In contrast, acti- et al. 1990). If the animal moves quickly vational effects of hormones are usually between the two contexts, but hormone levels thought to act later in life; e.g., adult mating change relatively slowly, the mechanism is not behavior might be activated by a hormonal as plastic as it needs to be for the animal to surge. Both organizational and activational instantly behave optimally in both situations. effects can come into play in a given system, Aggression in the territorial defense context although their relative importance likely var- could then “spillover” into the parental con- ies across systems. In the context of alterna- text, resulting in behavior that might appear tive mating tactics, Moore et al. (1998) pro- maladaptive if aggression was not viewed as a posed a “relative plasticity hypothesis” that syndrome of correlated behaviors expressed posits that organizational effects of hormones in multiple contexts. early in development produce fixed alterna- Most extant work on the neuroendocrine tive phenotypes, while activational effects basis of behavioral syndromes has been done later in life govern plastic alternative pheno- on model systems and domesticated animals, types. Both effects can be important in one and has generally not addressed the evolu- system. Once a male has been fixed into an tionary and ecological implications of hor- organizational strategy (e.g., territorial versus mones and behavioral syndromes. A line of satellite), activational hormone effects trigger research that looks particularly promising the short-term expression of type-specific involves manipulating hormonal levels (at behavior patterns (e.g., sedentary satellite either an organizational or activational stage) behavior versus wide-ranging mate search). to “phenotypically engineer” phenotypes out- The comparison between organizational side the range of natural variation to investi- versus activational effects of hormones on sin- gate the causes and consequences of variation gle traits can be applied to behavioral syn- in behavior (Marler and Moore 1988; Sinervo dromes. Organizational effects of hormones and Huey 1990; Ketterson et al. 1996; Ketter- early in development often involve hormonal son and Nolan 1999; Bell 2001). Further elu- control of the development of fixed traits cidation of the complex pathways that influ- (e.g., morphology) that can then limit the ence hormonal effects on behavior, including range of behavioral plasticity and produce study of the many mediating factors and feed- correlations that endure through ontogeny. backs, should reveal much about how and In fact, recent work shows that early exposure when behavioral syndromes are either gen- to exogenous hormones from littermates erated or uncoupled. (Clark and Galef 1995, 1998) and from the mother (Schwabl 1993, 1996; Adkins-Regan integrating proximate mechanisms et al. 1995; Gil et al. 1999) can influence sub- sequent behavior. Two themes that emerge are that: 1) while In contrast, activational effects of hor- proximate mechanisms underlying behav- mones occurring later in development likely ioral syndromes have been studied in consid- produce correlations of a shorter duration, erable detail in a few model systems, they which are more easily altered by modifica- remain largely unstudied in most animals; tions of the hormonal pathway, such as sea- and 2) while a simple view of proximate sonal variations or tissue-specific sensitivity of mechanisms might suggest that they can eas- hormone receptors (Soma et al. 2000; Tra- ily generate behavioral correlations, in reality montin and Brenowitz 2000). While activa- behavior might often be governed by com- tional effects, by definition, tend to involve plex regulatory networks that can, in princi- less widespread impact on fixed traits, they ple, break up behavioral syndromes. Despite might still limit behavioral plasticity in the the potential for mechanistic decoupling of short term whenever hormonal plasticity is behavioral syndromes, these syndromes less or slower than optimal behavioral plastic- clearly exist and are likely widespread (Gos- ity. For example, levels of aggression in paren- ling 2001). tal care and territorial defense might both be Although we discussed the three types of influenced by testosterone levels (Wingfield proximate mechanisms separately, they September 2004BEHAVIORAL SYNDROMES 265 clearly interact. Genes, experiences, and their conditions, such as when infants were sepa- interactions all influence neuroendocrine rated from their mothers or during physical phenomena that, in turn, affect suites of or social challenges (Suomi 1987). Individual behaviors. Behavioral geneticists studying responses to mildly stressful situations were model systems have emphasized how genes heritable and stable throughout development influence cellular and neuroendocrine (Suomi et al. 1996). Temperament was also mechanisms that underlie suites of behaviors affected strongly by a mother’s behavior (laboratory rodents: Boissy 1995; Koolhaas et toward her infant. Cross-fostering experi- al. 1999; Buc´an and Abel 2002; Drosophila: ments showed that an individual’s reactivity Sokolowski 2001). For example, allelic varia- depends on the reactivity of its biological tion in the for gene (the rover-sitter polymor- mother, the reactivity of its foster mother, and phism) in Drosophila is associated with differ- the conditions under which the individual’s ences in expression of a cGMP-dependent reactivity was measured (Suomi 1987). Reac- protein kinase (PKG: Osborne et al. 1997) tivity of neonates was most strongly related to and in neurophysiology (Renger et al. 1999) the biological mother’s reactivity. In contrast, that plausibly explain the behavioral differ- under stable social conditions, a juvenile’s ences. Individual experience also affects reactivity was best explained by its foster behavioral syndromes in these model systems; mother’s reactivity. When a juvenile was however, geneticists typically attempt to min- exposed to an environmental challenge, how- imize (as opposed to study) the effects of envi- ever, the importance of its pedigree resur- ronmental experiences on behavior (Buc´an faced. That is, the phenotypic expression of and Abel 2002). In contrast, behavioral endo- genetic differences was seen under stressful crinologists often explicitly examine effects of conditions, but not stable ones. experience on subsequent behavior through Individual variation in fearfulness in rhesus effects on the neuroendocrine system (e.g., monkeys is associated with genetically-based Hews and Moore 1997). A few studies have differences in the autonomic nervous looked at the genetic basis of differential response and in serotonergic activity. For response to experiences; e.g., fish from high example, variation at the serotonin trans- predation localities respond more to the porter gene regulatory locus (5-HTTLPR) is effects of experience with a predator than fish associated with variations in both serotoner- from low predation localities (Magurran gic function and behavioral anxiety. The 1990). The most powerful approach should effects of genotype on serotonin function be to integrate all of the above approaches. (Bennett et al. 2002) and behavior (Cham- An example of the integration of genetics, poux et al. 2002) depend, however, on the experience, and neuroendocrine bases of environment and on individual experiences. behavioral syndromes comes from the long- For monkeys reared by their mother, there term studies on temperament in rhesus mon- were no phenotypic differences between indi- keys (Macaca mulatta) conducted by Suomi viduals that were homozygous versus hetero- and colleagues. Rhesus monkeys show consid- zygous at the 5-HTTLPR locus. When mon- erable variation in “reactivity,” or fearfulness keys were reared in a nursery, however, which that is expressed in how individuals respond was presumably more stressful for the mon- to novelty, environmental changes, and social keys, heterozygous and homozygous individ- challenges. Temperament influences social uals differed in behavior and physiology interactions (both agonism and affiliation) (Champoux et al. 2002). Thus, understand- and exploratory behavior that mediates inter- ing the physiological bases underlying varia- actions with the nonsocial environment. tion in temperament helped to explain some Detailed longitudinal studies on captive mon- of the complex patterns in the environment- keys showed that the expression of tempera- dependent expression of genetic differences. ment depends on the interaction between genetics, experience, and the particular situ- Human Personalities ation. Individual variation in temperament The authors do not pretend to have emerged most clearly under mildly stressful detailed expertise on this huge literature. 266 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Based on recent reviews representing a range ecologists is that expression of behavioral syn- of views (Mischel and Shoda 1998; Lubinski dromes might depend on the situations stud- 2000; Tett and Guterman 2000; Bouchard ied, and that our goal should be to under- and Loehlin 2001; Funder 2001), we offer a stand which situations allow behavioral selection of insights for behavioral ecologists. syndromes to emerge. First, the literature on human personality has Another insight from integration empha- a long history of using sophisticated, multi- sizes that people with different personalities variate statistical methods (e.g., variations on tend to choose different situations (e.g., risk factor analysis) to identify multiple personal- seeking or not: Buss 1987). In that case, even ity axes. In contrast, relatively few studies of if people are highly flexible in their behavior nonmodel animals have attempted to distin- in different situations, a significant amount of guish two or more distinct behavioral axes variation in overall behavior might still be (e.g., Reichert and Maynard Smith 1989; explained by personality (i.e., by their choice Budaev 1998; Gosling 2001). In humans, of situations). The analogy for behavioral some authors suggest (in some cases, ecology is that the expression of behavioral begrudgingly) that the Big Five has emerged syndromes could come through habitat as the dominant paradigm. The Big Five char- choice for different situations, above and acterizes human personalities in terms of beyond correlated behavior across those sit- scores on five axes: neuroticism, extroversion, uations. More aggressive individuals might agreeableness, openness, and conscientious- not just be aggressive in contests against con- ness. Comparative psychologists have specifics (or fight rather than flee from pred- attempted to identify and quantify analogs of ators), they might also spend more time seek- the Big Five in animals (Gosling 2001). ing contests (or in risky habitats) than less Regardless of whether we agree with the valid- aggressive individuals. ity of the Big Five, behavioral ecologists study- Finally, studies on humans offer the gen- ing behavioral syndromes could clearly ben- eral insight that integrated interdisciplinary efit from borrowing statistical techniques and studies on behavioral syndromes should be cautionary comments on their limitations valuable. With regard to proximate control of from human personality studies. personality, personality scores (e.g., the Big Other insights come from attempts to inte- Five) are heritable (e.g., Loehlin et al. 1998; grate personality-based and situation-depen- Bouchard and Loehlin 2001; Funder 2001) dent views of human personality. The situa- and have some basis in brain structures and tion-dependent (“situationist”) view posits hormone levels (Funder 2001). Personality that human behavior is so flexible that the also depends on experiences and vice versa; entire concept of human personalities is mis- i.e., there is an ongoing interaction over a life- leading (Revelle 1995; Mischel and Shoda time between personalities and experiences 1998). An integrative view suggests that (Scarr 1992; Lubinski 2000). With regard to whether a personality tendency is expressed effects of personality on individual perfor- might depend on the situation. For example, mance, research in applied psychology exam- it has been suggested that variations in ines relationships between personality and human personality might be most apparent life outcomes (e.g., job performance, marital during transitional events and around stability, tendency to not get depressed or periods of stress (Caspi and Bern 1999). involved with substance abuse, happiness). Alternatively, variations in aggressive tenden- Interestingly, large-scale studies and meta- cies might emerge most clearly in situations analyses suggest that out of the Big Five, the where low-moderate aggressiveness is normal best predictor of overall positive life out- (e.g., in the office, on the highway, playing comes is conscientiousness (Barrick and sports, or at home), but might be masked in Mount 1991; Tett et al. 1991; Soldz and Vail- situations where either no one is aggressive lant 1999). Overall, an integrative view that (e.g., at church) or where everyone is aggres- emerges is that a combination of genes and sive (e.g., in hand-to-hand combat: Tett and experience, mediated through effects on the Guterman 2000). The insight for behavioral brain and endocrine system, shape personal- September 2004BEHAVIORAL SYNDROMES 267 ities that along with specific contexts deter- focus here is instead on key suboptimal traits. mine behaviors that then influence life out- Limited plasticity associated with behavioral comes. Development and application of a syndromes could clearly play a key role in this similarly integrative view, but with an explicit approach. An example, outlined earlier, evolutionary overview (e.g., Buss 1991), involves how salamander activity syndromes should be a goal for the study of animal help to explain why predatory sunfish limit behavioral syndromes. the distribution and abundance of salaman- der larvae (Sih et al. 2003). Ecological Implications For community ecology, tradeoffs (e.g., Finally, we return to the issue of the poten- between abilities to collect different tial ecological consequences of behavioral resources, or between foraging versus anti- syndromes. A simple generality is that since predator or competition versus dispersal abil- behavior often influences ecological patterns, ities) are a key to understanding patterns of behavioral syndromes should also often have species diversity and variation in community composition in space and time (MacArthur important ecological implications. Two keys 1972; Connell 1975; Lubchenco 1978; Tilman to how behavioral syndromes might affect 1988). That is, the fact that some species are ecological patterns are: 1) behavioral syn- better at some tasks (or in some habitats) dromes are a type of tradeoff that involves while other species are more adept at alter- limits to plasticity and often suboptimal native tasks is critical for explaining how spe- behavior (and these then influence ecologi- cies coexist, and which species dominate in cal patterns); and 2) behavioral syndromes— any given situation. Again, it is plausible that e.g., correlations between reproductive, pred- limited plasticity associated with behavioral ator-prey, and dispersal behaviors—connect syndromes could underlie some of these behaviors underlying three key components tradeoffs; i.e., differences among species in of species performance (births, deaths, and general activity or aggression levels and their dispersal) that might otherwise be uncoup- limited abilities to alter these levels could gen- led. We focus on how these aspects of behav- erate the tradeoffs that explain some patterns ioral syndromes might affect some selected of community structure. A classical approach ecological issues. for connecting species’ traits (as limited by Tradeoffs and limited plasticity often play tradeoffs) to patterns of coexistence focuses a major role in population and community on niche partitioning (Pianka 1981; Abrams ecology. For population ecology, one can 1983). While a species’s niche can be defined define the goal of the field as understanding broadly to include how the species copes with factors that limit the distribution and abun- all environmental dimensions, most analyses dance of organisms. A long-standing of niche partitioning have emphasized one or approach in ecology involves doing experi- two dimensions (most commonly the feeding ments to identify limiting factors (e.g., pre- niche). The behavioral syndrome view sug- dation, competition, abiotic stress, lack of gests reexpanding the niche concept to resources). A “limiting traits” approach (cf. include suites of correlated behavioral Sih and Gleeson 1995) suggests that after responses to multiple ecological factors. identifying limiting factors, a useful focus Coexistence might be better explained by should be to identify and understand limiting species differences in their overall behavioral traits—e.g., inappropriate behaviors (or type than by resource partitioning per se. other traits) that explain the poor ability of a Limited plasticity is presumably most criti- species to cope with limiting factors. If, for cal immediately after a major environmental example, a species’s distribution or abun- change. For many species, environmental dance is limited by predation, what does the change due to human disturbance—climate focal species do poorly to explain why it does change, habitat loss and fragmentation, not cope well with predators? This is a twist urbanization, spread of exotic species, chem- on the usual emphasis on adaptation and how ical pollution—will probably be the single adaptive traits shape species interactions. The most important factor governing their future 268 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 persistence. A key issue is how well different over to influence their ecological interactions species respond to human-induced change. and impacts in the new habitat. Bottleneck Some species are thriving with humans (e.g., selection on a behavioral syndrome could urbanized, invasive species), while others are thus have critical, underappreciated impacts being driven extinct. Sometimes both on various ecological phenomena in tempo- extremes of the ability to cope with human- rally or spatially variable environments. induced change can be found within the For example, one major type of environ- same genus. We suggest that species differ- mental change involves the spread of exotic ences in several aspects of behavioral syn- species. Many studies have attempted to iden- dromes could play important roles in deter- tify traits associated with invasive species (e.g., mining their relative response to Lodge 1993; Mack et al. 2000). Although environmental change: 1) the species’s aver- reviews have listed some behaviors, few stud- age behavioral type; 2) time lags in individual ies have explicitly explored the behavioral behavioral response to new environments; 3) mechanisms underlying species invasions the degree of plasticity shown by individuals; (Holway and Suarez 1999). One notable and 4) between-individual variation in behav- exception suggested that invasive bird species ioral types within the species. Clearly, a spe- tend to be less neophobic (more bold) and cies should be able to cope more effectively better at innovative problem solving than with a new environment if most individuals similar noninvasive species (Sol et al. 2002). have a suitable behavioral type, or if individ- Kolar and Lodge (2001) emphasized that to uals show rapid adaptive shifts in behavior. be an invasive pest, a species must be highly For example, for some taxa, more flexible, successful in each of three phases of the inva- less neophobic species appear to respond sion process: it must disperse readily; grow more favorably to novel environments (Sol well from an initially small propagule; and and Lefebvre 2000; Sol et al. 2002). However, when it gets more abundant, have major even if most individuals in a species are not impacts on the invaded community. Not all of an appropriate behavioral type for coping species have the ability to do well in all three with an environmental change, the species phases; however, success in the three phases can persist if it has large between-individual might be correlated if they represent parts of variation so that some individuals respond an overall bold/ aggressive/active behavioral appropriately (Bolnick et al. 2003). syndrome. Bold individuals disperse, aggres- Regardless of whether environmental sive individuals compete well even when rare, change is due to temporal variation in a par- and aggressive/active individuals have major ticular site or dispersal to a new site, environ- impacts on their community. The dispersal mental change might often represent a process per se might select for bold/aggres- strong, nonrandom bottleneck with respect sive/active individuals (i.e., only they dis- to behavioral types. First, dispersal probabili- perse), who then have a particularly strong ties appear to often be associated with a dis- tendency to disrupt their invaded communi- persal syndrome or an aggression syndrome; ties. e.g., either more aggressive individuals are Behavioral syndromes associated with dis- more bold and disperse more readily, or persal (Clobert et al. 2001; Dingle 2001) more aggressive individuals drive out less might also relate to another major type of aggressive ones. Second, the probability of environmental change: habitat loss and frag- surviving the environmental change might mentation. The ability of a species to persist often be related to behavioral type. In any in a fragmented habitat depends on both sur- case, regardless of which behavioral aspect vival and reproduction within the remaining was important in determining success in get- habitat, and movement between habitat frag- ting through the bottleneck, the key is that if ments. It seems likely that fitness within hab- this behavior is part of a behavioral syn- itat fragments depends on not just one type drome, it brings along with it an entire suite of behavior, but on an entire suite of behav- of correlated behaviors. If bold individuals iors (e.g., foraging, aggression, mating, tend to disperse, their boldness could spill parental care). Furthermore, both the ten- September 2004BEHAVIORAL SYNDROMES 269

Figure 5. An Integrative Overview on Behavioral Syndromes Our integrative overview on behavioral syndromes. dency and ability to disperse should depend actions), a focus on behavioral syndromes on behavioral type (e.g., boldness: Fraser et yields the potential for connecting correlated al. 2001; aggressiveness: Chitty 1960). Corre- suites of behaviors to not just one major eco- lations among these behaviors, if they exist, logical factor but to a broad set of factors could play an important role in explaining relating potentially to birth, death, and dis- the relative ability of different species to cope persal rates—the three major factors that gov- with habitat loss, or more generally, to persist ern population dynamics. With regard to in metapopulation or source/sink population proximate mechanisms underlying behavior, structures. Finally, cycles in the prevalence of it has long been the case that one of the most different behavioral types within populations powerful and attractive reasons for studying driven by their relative ability to do well in the mechanistic bases of behavior (e.g., hor- different social conditions, and by their dis- monal or experience effects) is the fact that persal tendencies, could be associated with these mechanisms have the potential to influ- cycles in overall population abundance ence not just one behavior but suites of (Chitty 1960). behaviors. Our suggestion is that it should be useful to explicitly connect our knowledge on Concluding Remarks mechanisms that govern suites of behaviors to Behavioral syndromes could play a useful the effects that these suites have on individual role as a central core in interdisciplinary stud- fitness and population/community dynamics. ies that integrate genetics, neuroendocrine, Finally, while there has been a long tradition and developmental bases of behavior, and of studying the genetics and evolution of cor- ecological consequences of behavior, all with related characters for other types of traits an evolutionary overview (Figure 5). With (morphology, life histories), this tradition has regard to ecology, we suggest that while sig- not been widely applied to suites of behav- nificant progress has been made in relating ioral tendencies. In our view, it is unfortunate specific behaviors to specific aspects of ecol- that while many have espoused the value of ogy (e.g., behavior and predator-prey inter- integrative research, the trend in fact is more 270 THE QUARTERLY REVIEW OF BIOLOGY Volume 79 toward a drifting apart of the cultures of the Behavioral Syndromes working group featuring: J L mechanistic study of genetics and hormones, Conrad, J Davis, J DeBose, H Dingle, J Hammond, S on the one hand, and larger-scale ecology on Hanser, A Hedrick, K Kostan, M Lawniczak, T Leo- the other, with a reduced appreciation for the nardo, K Mabry, A Rundus, J Stamps, T Stankowich, role of behavior in both. We suggest that a H Swarts, and J Watters. M Benard, S Gosling, W J Hamilton, J Stamps, D S Wilson, and an anonymous focus on behavioral syndromes offers the reviewer provided useful comments on an earlier ver- potential to refocus integration and generate sion of the manuscript, and M S Baltus-Sih and L Sih new and exciting insights across these levels contributed personal testimony. The working group of study. and a workshop on Behavioral Syndromes were sup- ported by the UC/Davis Animal Behavior Graduate Group and the Center for Animal Behavior. The over- acknowledgments all project was supported by National Science Foun- This paper emerged after many open, agreeable, and dation grants to A Sih, NSF IBN 0078033 and IBN conscientious discussions, in particular with the 0222063.

REFERENCE

Abrams P. 1983. The theory of limiting similarity. influences the development of aggression and Annual Review of Ecology and Systematics 14:359– behavioural strategy in male Mus domesticus. Behav- 376. iour 135:1229–1249. Adkins-Regan E, Ottinger M A, Park J. 1995. Maternal Benus R F, Ro¨ndigs M. 1997. The influence of the transfer of estradiol to egg yolks alters sexual dif- postnatal maternal environment in accounting for ferentiation of avian offspring. Journal of Experimen- differences in aggression and behavioural strate- tal Zoology 271:466–470. gies in Mus domesticus. Behaviour 134:623–641. Arnold A P, Breedlove S M. 1985. Organizational and Boake C R B, editor. 1994. Quantitative Genetic Studies activational effects of sex steroids on brain and of Behavioral Evolution. Chicago (IL): University of behavior: a reanalysis. Hormones and Behavior 19: Chicago Press. 469–498. Boissy A. 1995. Fear and fearfulness in animals. Quar- Arnqvist G, Henriksson S. 1997. Sexual cannibalism in terly Review of Biology 70:165–191. the fishing spider and a model for the evolution Bolnick D I, Svanba¨ck R, Fordyce J A, Yang L H, Davis of sexual cannibalism based on genetic constraints. J M, Hulsey C D, Forister M L. 2003. The ecology Evolutionary Ecology 11:255–273. of individuals: incidence and implications of indi- Barnard C J, Sibly R M. 1981. Producers and scroung- vidual specialization. American Naturalist 161:1–28. ers: a general model and its application to captive Bouchard T J, Loehlin J C. 2001. Genes, evolution, flocks of house sparrows. Animal Behaviour 29:543– and personality. Behavior Genetics 31:243–273. 550. Briggs S. 1999. Personality measurement. Pages 27–65 Barrick M R, Mount M K. 1991. The big five person- in Personality: Contemporary Theory and Research, Sec- ality dimensions and job performance: a meta- ond Edition, edited by V J Derlega, B A Winstead, analysis. Personnel Psychology 44:1–26. and W H Jones. Chicago (IL): Nelson-Hall. Barton N H, Turelli M. 1989. Evolutionary quantita- Brodie E D. 1992. Correlational selection for color tive genetics: how little do we know? Annual Review pattern and antipredator behavior in the garter of Genetics 23:337–370. snake Thamnophis ordinoides. Evolution 46:1284– Bell A M. 2001. Effects of an endocrine disrupter on 1298. courtship and aggressive behaviour of male three- Buc´an M, Abel T. 2002. The mouse: genetics meets spined stickleback, Gasterosteus aculeatus. Animal behaviour. Nature Reviews Genetics 3:114–123. Behaviour 62:775–780. Budaev S V. 1998. How many dimensions are needed Belovsky G E. 1984. Herbivore optimal foraging: a to describe temperament in animals: a factor comparative test of three models. American Natu- reanalysis of two data sets. International Journal of ralist 124:97–115. Comparative Psychology 11:17–29. Bennett A J, Lesch K P, Heils A, Long J C, Lorenz J G, Bult A, Lynch C B. 2000. Breaking through artificial Shoaf S E, Champoux M, Suomi S J, Linnoila M V, selection limits of an adaptive behavior in mice and Higley J D. 2002. Early experience and serotonin the consequences for correlated responses. Behav- transporter gene variation interact to influence ior Genetics 30:193–206. primate CNS function. Molecular Psychiatry 7:118– Bu¨rger R. 1998. Mathematical properties of mutation- 122. selection models. Genetica 102:279–298. Benus R F, Henkelmann C. 1998. Litter composition Buss D M. 1987. Selection, evocation, and manipula- September 2004BEHAVIORAL SYNDROMES 271

tion. Journal of Personality and Social Psychology of litter-bearing rodents. Developmental Neuropsy- 53:1214–1221. chology 14:197–211. Buss D M. 1991. Evolutionary personality psychology. Clobert J, Danchin E, Dhondt A A, Nichols J D. 2001. Annual Review of Psychology 42:459–491. Dispersal. Oxford: Oxford University Press. Carere C, Groothuis T G G, Mo¨stl E, Daan S, Koolhaas Coleman K, Wilson D S. 1998. Shyness and boldness J M. 2003. Fecal corticosteriods in a territorial bird in pumpkinseed sunfish: individual differences are selected for different personalities: daily rhythm context-specific. Animal Behaviour 56:927–936. and the response to social stress. Hormones and Connell J H. 1975. Some mechanisms producing Behavior 43:540–548. structure in natural communities: a model and evi- Carere C, Welink D, Drent P J, Koolhaas J M, Gro- dence from field experiments. Pages 460–491 in othuis T G G. 2001. Effect of social defeat in a ter- Ecology and Evolution of Communities, edited by M L ritorial bird (Parus major) selected for different Cody and J Diamond. Cambridge (MA): Harvard coping styles. Physiology and Behavior 73:427–433. University Press. Campbell D T, Fiske D W. 1959. Convergent and dis- Crabbe J C. 2002. Genetic contributions to addiction. criminant validation by the multitrait-multimethod Annual Review of Psychology 53:435–462. matrix. Psychological Bulletin 56:81–105. de Jong G, Gavrilets S. 2000. Maintenance of genetic Capitanio J P. 1999. Personality dimensions in adult variation in phenotypic plasticity: the role of envi- male rhesus macaques: prediction of behaviors ronmental variation. Genetical Research 76:295–304. across time and situation. American Journal of Pri- DeWitt T J, Sih A, Hucko J A. 1999. Trait compensa- matology 47:299–320. tion and cospecialization in a freshwater snail: size, Caro T M, Bateson P. 1986. Organization and ontog- shape and antipredator behaviour. Animal Behav- iour 58:397–407. eny of alternative tactics. Animal Behaviour Dewsbury D A, Baumgardner D J, Sawrey D K, Webster 34:1483–1499. D G. 1982. The adaptive profile: comparative psy- Caspi A, Bern D J. 1999. Personality continuity and chology of red-backed voles (Clethrionomys gapperi). change across the life course. Pages 300–326 in Journal of Comparative and Physiological Psychology Handbook of Personality: Theory and Research, Second 96:649–660. Edition, edited by L A Pervin and O P John. New Dingemanse N J, Both C, Drent P J, van Oers K, van York: Guilford Press. Noordwijk A J. 2002. Repeatability and heritability Champoux M, Bennett A, Shannon C, Higley J D, of exploratory behaviour in great tits from the Lesch K P, Suomi S J. 2002. Serotonin transporter wild. Animal Behaviour 64:929–938. gene polymorphism, differential early rearing, and Dingemanse N J, Both C, van Noordwijk A J, Rutten behavior in rhesus monkey neonates. Molecular Psy- A L, Drent P J. 2003. Natal dispersal and person- chiatry 7:1058–1063. alities in great tits (Parus major). Proceedings of the Cheverud J M. 1996. Developmental integration and Royal Society London B 270:741–747. the evolution of pleiotropy. American Zoologist Dingle H. 2001. The evolution of migratory syn- 36:44–50. dromes in insects. Pages 159–181 in Insect Move- Cheverud J M. 2000. The genetic architecture of plei- ment: Mechanisms and Consequences, edited by I P otropic relations and differential epistasis. Pages Woiwod, D R Reynolds, and C D Thomas. Walling- 411–433 in The Character Concept in Evolutionary ford (UK): CABI Publishers. Biology, edited by G Wagner. New York: Academic Drent P J, Marchetti C. 1999. Individuality, explora- Press. tion and foraging in hand raised juvenile great tits. Chitty D. 1960. Population processes in the vole and Pages 896–914 in Proceedings of the 22nd Interna- their relevance to general theory. Canadian Journal tional Ornithological Congress, Durban, edited by of Zoology 38:99–113. N J Adams and R H Slotow. Johannesburg: Birdlife Clark A B, Ehlinger T J. 1987. Pattern and adaptation South Africa. in individual behavioral differences. Pages 1–47 in Drent P J, van Oers K, van Noordwijk A J. 2002. Real- Perspectives in Ethology, Volume 7, edited by P P G ized heritability of personalities in the great tit Bateson and P H Klopfer. New York: Plenum Press. (Parus major). Proceedings of the Royal Society of Lon- Clark C W, Mangel M. 2000. Dynamic State Variable Mod- don B 270:45–51. els in Ecology: Methods and Applications. New York: Dugatkin L A, Reeve H K, editors. 1998. Game Theory Oxford University Press. and Animal Behavior. New York: Oxford University Clark M M, Galef B G. 1995. Prenatal influences on Press. reproductive life history strategies. Trends in Ecology Eckhardt R C. 1979. The adaptive syndromes of two & Evolution 10:151–153. guilds of insectivorous birds in the Colorado Rocky Clark M M, Galef B G. 1998. Effects of intrauterine Mountains. Ecological Monographs 49:129–149. position on the behavior and genital morphology Emlen D J. 1997. Alternative reproductive tactics and 272 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

male-dimorphism in the horned beetle Onthopha- ioral development: theory. Developmental Psychology gus acuminatus (Coleoptera: Scarabaeidae). Behav- 27:4–13. ioral Ecology and Sociobiology 41:335–341. Gould S J, Lewontin R C. 1979. The spandrels of San Emlen S T, Reeve H K, Sherman P W, Wrege P H, Marco and the Panglossian paradigm: a critique of Ratnieks F L W, Shellman-Reeve J. 1991. Adaptive the adaptationist programme. Proceedings of the versus nonadpative explanations of behavior: the Royal Society of London B 205:581–598. case of alloparental helping. American Naturalist Greenberg R. 1990. Feeding neophobia and ecologi- 138:259–270. cal plasticity: a test of the hypothesis with captive Endler J A. 1995. Multiple-trait coevolution and envi- sparrows. Animal Behaviour 39:375–379. ronmental gradients in guppies. Trends in Ecology Greenspan R J. 2001. The flexible genome. Nature & Evolution 10:22–29. Reviews Genetics 2:383–386. Fairbairn D J. 1994. Wing dimorphism and the migra- Gross M R. 1996. Alternative reproductive strategies tory syndrome: correlated traits for migratory ten- and tactics: diversity within sexes. Trends in Ecology dency in wing dimorphic insects. Researches on & Evolution 11:92–98. Population Ecology 36:157–163. Halliday T, Arnold S J. 1987. Multiple mating by Fivizzani A J, Colwell M A, Oring L W. 1986. Plasma females: a perspective from quantitative genetics. steroid-hormone levels in free-living Wilson’s phal- Animal Behaviour 35:939–941. aropes, Phalaropus tricolor. General and Comparative Hassell M P. 1978. The Dynamics of Arthropod Predator- Endocrinology 62:137–144. Prey Systems. Princeton (NJ): Princeton University Fivizzani A, Delehanty D, Oring L, Wrege P, Emlen S. Press. 1994. Elevated female androstenedione levels in Hedrick AV. 2000. Crickets with extravagant mating two sex role reversed avian species. American Zool- songs compensate for predation risk with extra ogist 34:22A. caution. Proceedings of the Royal Society of London B Flint J, Corley R, DeFries J C, Fulker D W, Gray J A, 267:671–675. Miller S, Collins A C. 1995. A simple genetic basis Hedrick P W. 2000. Genetics of Populations. Second Edi- for a complex psychological trait in laboratory tion. Boston (MA): Jones & Bartlett Publishers. mice. Science 269:1432–1435. Henderson N D. 1986. Predicting relationships Fraser D F, Gilliam J F, Daley M J, Le A N, Skalski G T. between psychological constructs and genetic 2001. Explaining leptokurtic movement distribu- characters: an analysis of changing genetic influ- tions: intrapopulation variation in boldness and ences on activity in mice. Behavior Genetics 16:201– exploration. American Naturalist 158:124–135. 220. Funder D C. 2001. Personality. Annual Review of Psy- Hessing M J C, Hagelsø A M, Schouten W G P, Wiep- chology 52:197–221. kema P R, Van Beek J A M. 1994. Individual behav- Futuyma D J. 1998. Evolutionary Biology. Third Edition. ioral and physiological strategies in pigs. Physiology Sunderland (MA): Sinauer. & Behavior 55:39–46. Getty T. 1996. The maintenance of phenotypic plastic- Hews D K, Moore M C. 1997. Hormones and sex-spe- ity as a signal detection problem. American Natu- cific traits: critical questions. Pages 277–292 in Par- ralist 148:378–385. asites and Pathogens: Effects on Host Hormones and Gil D, Graves J, Hazon N, Wells A. 1999. Male attrac- Behavior, edited by N E Beckage. New York: Chap- tiveness and differential testosterone investment in man & Hall. zebra finch eggs. Science 286:126–128. Holway D A, Suarez A V. 1999. Animal behavior: an Giraldeau L-A, Beauchamp G. 1999. Food exploita- essential component of invasion biology. Trends in tion: searching for the optimal joining policy. Ecology & Evolution 14:328–330. Trends in Ecology & Evolution 14:102–106. Holt R D. 1996. Adaptive evolution in source-sink envi- Glickman S E, Sroges R W. 1966. Curiosity in zoo ani- ronments: direct and indirect effects of density- mals. Behaviour 26:151–188. dependence on niche evolution. Oikos 75:182–192. Gomulkiewicz R. 1998. Game theory, optimization, Holt R D, Gaines M S. 1992. Analysis of adaptation in and quantitative genetics. Pages 283–303 in Game heterogeneous landscapes: implications for the Theory and Animal Behavior, edited by L A Dugatkin evolution of fundamental niches. Evolutionary Ecol- and H K Reeve. New York: Oxford University Press. ogy 6:433–447. Gosling S D, John O P. 1999. Personality dimensions Houston A I, McNamara J M. 1992. Phenotypic plas- in nonhuman animals: a cross-species review. Cur- ticity as a state-dependent life-history decision. Evo- rent Directions in Psychological Science 8:69–75. lutionary Ecology 6:243–253. Gosling S D. 2001. From mice to men: what can we Houston A I, McNamara J M. 1999. Models of Adaptive learn about personality from animal research. Psy- Behaviour: An Approach Based on State. Cambridge: chological Bulletin 127:45–86. Cambridge University Press. Gottleib G. 1991. Experiential canalization of behav- Houston A I, McNamara J M, Hutchinson J M C. 1993. September 2004BEHAVIORAL SYNDROMES 273

General results concerning the trade-off between mals: current status in behavior and stress-physi- gaining energy and avoiding predation. Philosoph- ology. Neuroscience and Biobehavioral Reviews 23:925– ical Transactions of the Royal Society of London B 935. 341:375–397. Krebs J R, Davies N B. 1996. Behavioral Ecology: An Evo- Hughes K, Sokolowski M B. 1996. Natural selection in lutionary Approach. Fourth Edition. Sunderland the laboratory for a change in resistance by Dro- (MA): Sinauer Associates. sophila melanogaster to the parasitoid wasp Asobara Leamy L J, Routman E J, Cheverud J M. 1999. Quan- tabida. Journal of Insect Behavior 9:477–491. titative trait loci for early- and late-developing skull Huntingford F A. 1976. The relationship between anti- characters in mice: a test of the genetic indepen- predator behaviour and aggression among conspe- dence model of morphological integration. Amer- cifics in the three-spined stickleback, Gasterosteus ican Naturalist 153:201–214. aculeatus. Animal Behaviour 24:245–260. Lefebvre L, Whittle P, Lascaris E, Finkelstein A. 1997. Huntingford F A. 1982. Do inter- and intraspecific Feeding innovations and forebrain size in birds. aggression vary in relation to predation pressure Animal Behaviour 53:549–560. in sticklebacks? Animal Behaviour 30:909–916. Leon J A. 1993. Plasticity in fluctuating environments. Immelmann K. 1975. Ecological significance of Lecture Notes in Biomathematics 98:105–121. imprinting and early learning. Annual Review of Levins R. 1968. Evolution in Changing Environments: Ecology and Systematics 61:15–37. Some Theoretical Explorations. Princeton (NJ): Jamieson I G. 1986. The functional approach to behav- Princeton University Press. ior: is it useful? American Naturalist 127:195–208. Lima S L. 1998. Stress and decision-making under the Jamieson I G. 1989. Behavioral heterochrony and the risk of predation: recent developments from evolution of birds’ helping at the nest: an unse- behavioral, reproductive and ecological perspec- lected consequence of communal breeding? Amer- tives. Advances in the Study of Behavior 27:215–290. ican Naturalist 133:394–406. Lima S L, Bednekoff P A. 1999. Temporal variation in Johnson J C. 2001. Sexual cannibalism in fishing spi- danger drives antipredator behavior: the preda- ders (Dolomedes triton): an evaluation of two expla- tion risk allocation hypothesis. American Naturalist nations for female aggression towards potential 153:649–659. mates. Animal Behaviour 61:905–914. Lodge D M. 1993. Biological invasions: lessons for Kagan J, Reznick J S, Snidman N. 1988. Biological ecology. Trends in Ecology & Evolution 8:133–137. bases of childhood shyness. Science 240:167–171. Loehlin J C, McCrae R R, Costa P T, John O P. 1998. Kawecki T J, Stearns S C. 1993. The evolution of life Heritabilities of common and measure-specific histories in spatially heterogeneous environments: components of the big five personality factors. Jour- optimal reaction norms revisited. Evolutionary Ecol- nal of Research in Personality 32:431–453. ogy 7:155–174. Lubchenco J. 1978. Plant species diversity in a marine Ketterson E D, Nolan V, Cawthorn M J, Parker P G, intertidal community: importance of herbivore Ziegenfus C. 1996. Phenotypic engineering: using food preference and algal competitive abilities. hormones to explore the mechanistic and func- American Naturalist 112:23–39. tional bases of phenotypic variation in nature. Ibis Lubinski D. 2000. Scientific and social significance of 138:70–86. assessing individual differences: “sinking shafts at Ketterson E D, Nolan V. 1999. Adaptation, exaptation, a few critical points.” Annual Review of Psychology and constraint: a hormonal perspective. American 51:405–444. Naturalist 154: S4-S25. Luttbeg B, Warner R R. 1999. Reproductive decision- Klingenberg C P, Leamy L J, Routman E J, Cheverud making by female peacock wrasses: flexible versus J M. 2001. Genetic architecture of mandible shape fixed behavioral rules in variable environments. in mice: effects of quantitative trait loci analyzed Behavioral Ecology 10:666–674. by geometric morphometrics. Genetics 157:785– Lynch M, Walsh B. 1998. Genetics and Analysis of Quan- 802. titative Traits. Sunderland (MA): Sinauer Associ- Kolar C S, Lodge D M. 2001. Progress in invasion biol- ates. ogy: predicting invaders. Trends in Ecology & Evo- Lyons D M, Price E O, Moberg G P. 1988. Individual lution 16:199–204. differences in temperament of domestic dairy Koolhaas J M, de Boer S F, Bohus B. 1997. Motivational goats: constancy and change. Animal Behaviour systems or motivational states: behavioural and 36:1323–1333. physiological evidence. Applied Animal Behavior Sci- MacArthur R H. 1972. Geographical Ecology: Patterns in ence 53:131–143. the Distribution of Species. New York: Harper & Row. Koolhaas J M, Korte S M, De Boer S F, Van Der Vegt MacDonald K. 1983. Stability of individual differences B J, Van Reenen C G, Hopster H, De Jong I C, Ruis in behavior in a litter of wolf cubs, (Canis lupus). M A W, Blokhuis H J. 1999. Coping styles in ani- Journal of Comparative Psychology 97:99–106. 274 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Mack R N, Simberloff D, Lonsdale W M, Evans H, of time delays in a stochastic environment. Evolu- Clout M, Bazzaz F A. 2000. Biotic invasions: causes, tionary Ecology 10:105–117. epidemiology, global consequences, and control. Palmer J O, Dingle H. 1989. Responses to selection on Ecological Applications 10:689–710. flight behavior in a migratory population of milk- Magurran A E. 1990. The inheritance and develop- weed bug (Oncopeltus fasciatus). Evolution 43:1805– ment of minnow anti-predator behaviour. Animal 1808. Behaviour 39:834–842. Partridge L. 1994. Genetic and nongenetic Mangel M, Stamps J. 2001. Trade-offs between growth approaches to questions about sexual selection. and mortality and the maintenance of individual Pages 126–141 in Quantitative Genetic Studies of variation in growth. Evolutionary Ecology Research Behavioral Evolution, edited by C R B Boake. Chi- 3:583–593. cago (IL): University of Chicago Press. Marchetti C, Drent P J. 2000. Individual differences in Pedhazur E J. 1982. Multiple Regression in Behavioral the use of social information in foraging by captive Research: Explanation and Prediction. New York: Holt, great tits. Animal Behaviour 60:131–140. Rinehart and Winston. Marler C A, Moore M C. 1988. Evolutionary costs of Pereira H S, Sokolowski M B. 1993. Mutations in the aggression revealed by testosterone manipulations larval foraging gene affect adult locomotory in free-living male lizards. Behavioral Ecology and behavior after feeding in Drosophila melanogaster. Sociobiology 23:21–26. Proceedings of the National Academy of Sciences USA Maupin J L, Riechert S E. 2001. Superfluous killing in 90:5044–5046. spiders: a consequence of adaptation to food-lim- Pervin L, John O P, editors. 1999. Handbook of Person- ited environments? Behavioral Ecology 12:569–576. ality: Theory and Research. Second Edition. New Maurer E F, Sih A. 1996. Ephemeral habitats and vari- York: Guilford. ation in behavior and life history: comparisons of Petranka J W. 1983. Fish predation: a factor affecting sibling salamander species. Oikos 76:337–349. the spatial distribution of a stream-breeding sala- Maynard Smith J. 1982. Evolution and the Theory of mander. Copeia 1983:624–628. Games. Cambridge: Cambridge University Press. Petranka J W, Sih A. 1987. Habitat duration, length of McLaughlin R L. 1989. Search modes of birds and liz- the larval period, and the evolution of a complex ards: evidence for alternative movement patterns. life cycle of a salamander, Ambystoma texanum. Evo- American Naturalist 133:654–670. lution 41:1347–1356. Meaney M J. 2001. Maternal care, gene expression, Pianka E R. 1981. Competition and niche theory. and the transmission of individual differences in Pages 167–196 in Theoretical Ecology: Principles and stress reactivity across generations. Annual Review Applications, Second Edition, edited by R M May. of Neuroscience 24:1161–1192. Oxford: Blackwell Scientific Publications. Mezey J G, Cheverud J M, Wagner G P. 2000. Is the Pianka E R, Parker W S. 1975. Age-specific reproduc- genotype-phenotype map modular?: a statistical tive tactics. American Naturalist 109:453–464. approach using mouse quantitative trait loci data. Price T, Langen T. 1992. Evolution of correlated char- Genetics 156:305–311. acters. Trends in Ecology & Evolution 7:307–310. Mischel W, Shoda Y. 1998. Reconciling processing Proctor H C. 1991. Courtship in the water mite Neu- dynamics and personality dispositions. Annual mania papillator: males capitalize on female adap- Review of Psychology 49:229–258. tations for predation. Animal Behaviour 42:589– Moore M C, Hews D K, Knapp R. 1998. Hormonal 598. control and evolution of alternative male pheno- Re´ale D, Gallant B Y, Leblanc M, Festa-Bianchet M. types: generalizations of models for sexual differ- 2000. Consistency of temperament in bighorn entiation. American Zoologist 38:133–151. ewes and correlates with behaviour and life history. Moran N A. 1992. The evolutionary maintenance of Animal Behaviour 60:589–597. alternative phenotypes. American Naturalist Renger J J, Yao W-D, Sokolowski M B, Wu C-F. 1999. 139:971–989. Neuronal polymorphism among natural alleles of Orzack S H, Tuljapurkar S. 2001. Reproductive effort a cGMP-dependent kinase gene, foraging, in Dro- in variable environments, or environmental varia- sophila. Journal of Neuroscience 19:A1-A8. tion is for the birds. Ecology 82:2659–2665. Revelle W. 1995. Personality processes. Annual Review Osborne K A, Robichon A, Burgess E, Butland S, Shaw of Psychology 46:295–328. R A, Coulthard A, Pereira H S, Greenspan R J, Richardson J M L. 2001. A comparative study of activity Sokolowski M B. 1997. Natural behavior polymor- levels in larval anurans and response to the pres- phism due to a cGMP-dependent protein kinase of ence of different predators. Behavioral Ecology Drosophila. Science 277:834–836. 12:51–58. Padilla D K, Adolph S C. 1996. Plastic inducible mor- Riechert S E. 1993. The evolution of behavioral phe- phologies are not always adaptive: the importance notypes: lessons learned from divergent spider September 2004BEHAVIORAL SYNDROMES 275

populations. Advances in the Study of Animal Behavior and Theory: A Festschrift Honoring Donald W. Fiske. 22:103–134. Hillsdale (NJ): Lawrence Erlbaum. Riechert S E, Hedrick A V. 1993. A test for correlations Shuster S M, Wade M J. 2003. Mating Systems and Strat- among fitness-linked behavioural traits in the spi- egies. Princeton (NJ): Princeton University Press. der, Agelenopsis aperta (Araneae, Agelenidae). Ani- Sibly R M. 1995. Life-history evolution in spatially het- mal Behavior 46:669–675. erogeneous environments, with and without phe- Riechert S E, Maynard Smith J. 1989. Genetic analyses notypic plasticity. Evolutionary Ecology 9:242–257. of two behavioural traits linked to individual fitness Sibly R M. 1996. Life history evolution in heteroge- in the desert spider, Agelenopsis aperta. Animal neous environments: a review of theory. Philosoph- Behaviour 37:624–637. ical Transactions of the Royal Society London B Robins R W, John O P, Caspi A, Moffitt T E, Stou- 351:1349–1359. thamer-Loeber M. 1996. Resilient, overcontrolled, Sih A. 1980. Optimal behavior: can foragers balance and undercontrolled boys: three replicable per- two conflicting demands? Science 210:1041–1043. sonality types. Journal of Personality and Social Psy- Sih A. 1987. Predators and prey lifestyles: an evolu- chology 70:157–171. tionary and ecological overview. Pages 203–224 in Rodd F H, Sokolowski M B. 1995. Complex origins of Predation: Direct and Indirect Impacts on Aquatic Com- variation in the sexual behaviour of male Trinida- munities, edited by W C Kerfoot and A Sih. Hano- dian guppies, Poecilia reticulata: interactions ver (NH): University Press of New England. between social environment, heredity, body size Sih A. 1992. Prey uncertainty and the balancing of and age. Animal Behaviour 49:1139–1159. antipredator and feeding needs. American Natural- Roff D A. 1992. The Evolution of Life Histories: Theory ist 139:1052–1069. and Analysis. London: Chapman & Hall. Sih A, Kats L B, Moore R D. 1992. Effects of predatory Roff D A. 1997. Evolutionary Quantitative Genetics. New sunfish on the density, drift, and refuge use of York: Chapman & Hall. stream salamander larvae. Ecology 73:1418–1430. Rutter M, Silberg J. 2002. Gene-environment interplay Sih A, Gleeson S K. 1995. A limits-oriented approach in relation to emotional and behavioral distur- to evolutionary ecology. Trends in Ecology & Evolu- bance. Annual Review of Psychology 53:463–490. tion 10:378–382. Ryan M J, Rand A S. 1993. Sexual selection and signal Sih A, Kats L B, Maurer E F. 2000. Does phylogenetic evolution: the ghost of biases past. Philosophical inertia explain the evolution of ineffective antipre- Transactions of the Royal Society of London B 340:187– dator behavior in a sunfish-salamander system? 195. Behavioral Ecology and Sociobiology 49:48–56. Scarr S. 1992. Developmental theories for the 1990s: Sih A, Lauer M, Krupa J J. 2002. Path analysis and the developmental and individual differences. Child relative importance of male-female conflict, Development 63:1–19. female choice and male-male competition in water Scheiner S M. 1993. Genetics and evolution of phe- striders. Animal Behaviour 63:1079–1089. notypic plasticity. Annual Review of Ecology and Sys- Sih A, Kats L B, Maurer E F. 2003. Behavioural cor- tematics 24:35–68. Scheiner S M, Callahan H S. 1999. Measuring natural relations across situations and the evolution of selection on phenotypic plasticity. Evolution antipredator behaviour in a sunfish-salamander 53:1704–1713. system. Animal Behaviour 65:29–44. Schlichting C D, Pigliucci M. 1995. Gene regulation, Sinervo B, Huey R B. 1990. Allometric engineering: quantitative genetics and the evolution of reaction an experimental test of the causes of interpopula- norms. Evolutionary Ecology 9:154–168. tional differences in performance. Science Schlichting C, Pigliucci M. 1998. Phenotypic Evolution: 248:1106–1109. A Reaction Norm Perspective. Sunderland: Sinauer Sluyter F, Bult A, Lynch C B, van Oortmerssen G A, Associates. Koolhaas J M. 1995. A comparison between house Schwabl H. 1993. Yolk is a source of maternal testos- mouse lines selected for attack latency or nest- terone for developing birds. Proceedings of the building: evidence for a genetic basis of alternative National Academy of Sciences USA 90:11446–11450. behavioral strategies. Behavior Genetics 25:247–252. Schwabl H. 1996. Environment modifies the testoster- Smith T B, Sku´lason S. 1996. Evolutionary significance one levels of a female bird and its eggs. Journal of of resource polymorphisms in fishes, amphibians Experimental Zoology 276:157–163. and birds. Annual Review of Ecology and Systematics Seferta A, Guay P-J, Marzinotto E, Lefebvre L. 2001. 27:111–133. Learning differences between feral pigeons and Sokolowski M B, Pereira H S, Hughes K. 1997. Evo- Zenaida doves: the role of neophobia and human lution of foraging behavior in Drosophila by density- proximity. Ethology 107:281–293. dependent selection. Proceedings of the National Shrout P, Fiske S T. 1995. Personality Research, Methods, Academy of Science USA 94:7373–7377. 276 THE QUARTERLY REVIEW OF BIOLOGY Volume 79

Sokolowski M B. 2001. Drosophila: genetics meets Trut L N. 1999. Early canid domestication: the farm- behaviour. Nature Reviews Genetics 2:879–892. fox experiment. American Scientist 87:160–169. Sol D, Lefebvre L. 2000. Behavioural flexibility pre- Tufto J. 2000. The evolution of plasticity and nonplas- dicts invasion success in birds introduced to New tic spatial and temporal adaptations in the pres- Zealand. Oikos 90:599–605. ence of imperfect environmental cues. American Sol D, Timmermans S, Lefebvre L. 2002. Behavioral Naturalist:156:121–130. flexibility and invasion success in birds. Animal Turri M G, Datta S R, DeFries J, Henderson N D, Flint Behaviour 63:495–502. J. 2001. QTL analysis identifies multiple behavioral Soldz S, Villant G E. 1999. The big five personality dimensions in ethological tests of anxiety in labo- traits and the life course: a 45-year longitudinal ratory mice. Current Biology 11:725–734. study. Journal of Research in Personality 33:208–232. van Oers K, Drent P J, de Goede P, van Noordwijk A Soma K K, Tramontin A D, Wingfield J C. 2000. Oes- J. 2004. Realized heritability and repeatability of trogen regulates male aggression in the non-breed- risk-taking behaviour in relation to avian person- ing season. Proceedings of the Royal Society Biological alities. Proceedings of the Royal Society of London B Sciences B 267:1089–1096. 271:65–73. Stamps J. 2003. Behavioural processes affecting devel- van Tienderen P H. 1997. Generalists, specialists, and opment: Tinbergen’s fourth question comes of the evolution of phenotypic plasticity in sympatric age. Animal Behaviour 66:1–13. populations of distinct species. Evolution 51:1372– Stearns S C. 1992. The Evolution of Life Histories. 1380. Oxford: Oxford University Press. Verbeek M E M, Drent P J, Wiepkema P R. 1994. Con- Steppan S J, Phillips P C, Houle D. 2002. Comparative sistent individual differences in early exploratory quantitative genetics: evolution of the G matrix. behaviour of male great tits. Animal Behaviour Trends in Ecology & Evolution 17:320–327. 48:1113–1121. Stevenson-Hinde J, Stillwell-Barnes R, Zunz M. 1980. Verbeek M E M, Boon A, Drent P J. 1996. Exploration, Individual differences in young rhesus monkeys: aggressive behavior and dominance in pair-wise consistency and change. Primates 21:498–509. confrontations of juvenile male great tits. Behaviour Storfer A, Sih A. 1998. Gene flow and ineffective anti- 133:945–963. predator behavior in a stream-breeding salaman- Verbeek M E M, de Goede P, Drent P J, Wiepkema P der. Evolution 52:558–565. R. 1999. Individual behavioural characteristics and Suomi S J. 1987. Genetic and maternal contributions dominance in aviary groups of great tits. Behaviour to individual differences in rhesus monkey biobe- 136:23–48. havioral development. Pages 397–420 in Perinatal Via S, Lande R. 1985. Genotype-environment inter- Development: A Psychobiological Perspective, edited by action and the evolution of phenotypic plasticity. N A Krasnegor. New York: Academic Press. Evolution 39:505–522. Suomi S J, Novak M A, Well A. 1996. Aging in rhesus Via S, Lande R. 1987. Evolution of genetic variability monkeys: different windows on behavioral conti- in a spatially heterogeneous environment: effects nuity and change. Developmental Psychology 32:1116– of genotype-environment interaction. Genetical 1128. Research 49:147–156. Tett R P, Jackson D N, Rothstein M. 1991. Personality Via S, Gomulkiewicz R, De Jong G, Scheiner S M, measures as predictors of job performance: a meta- Schlichting C D, Van Tienderen P H. 1995. Adap- analytic review. Personnel Psychology 44:703–742. tive phenotypic plasticity: consensus and contro- Tett R P, Guterman H A. 2000. Situation trait rele- versy. Trends in Ecology & Evolution 10:212–217. vance, trait expression and cross-situational consis- Wagner G P, Chiu C-h, Laubichler M. 2000. Develop- tency: testing a principle of trait activation. Journal mental evolution as a mechanistic science: the of Research in Personality 34:397–423. inference from developmental mechanisms to evo- Tilman D. 1988. Plant Strategies and the Dynamics and lutionary processes. American Zoologist 40:819–831. Structure of Plant Communities. Princeton (NJ): Wainwright P C, Osenberg C W, Mittelbach G G. 1991. Princeton University Press. Trophic polymorphisms in the pumpkinseed sun- Tollrian R, Harvell C D. 1999. The Ecology and Evolution fish (Lepomis gibbosus Linnaeus): effects of environ- of Inducible Defense. Princeton (NJ): Princeton Uni- ment on ontogeny. Functional Ecology 5:40–55. versity Press. Wcislo W T. 1989. Behavioral environments and evo- Toye A A, Cox R. 2001. Behavioral genetics: anxiety lutionary change. Annual Review of Ecology and Sys- under interrogation. Current Biology 26:June, 2001, tematics 20:137–169. 11, R473-R476. Webster S J, Lefebvre L. 2001. Problem solving and Tramontin A D, Brenowitz E A. 2000. Seasonal plastic- neophobia in a columbiform-passeriform assem- ity in the adult brain. Trends in Neurosciences blage in Barbados. Animal Behaviour 62:23–32. 23:251–258. Werner E E, Anholt B R. 1993. Ecological conse- September 2004BEHAVIORAL SYNDROMES 277

quences of the trade-off between growth and mor- Wilson D S, Clark A B, Coleman K, Dearstyne T. 1994. tality rates mediated by foraging activity. American Shyness and boldness in humans and other ani- Naturalist 142:242–272. mals. Trends in Ecology & Evolution 9:442–446. White D J, King A P, West M J. 2002. Facultative devel- Wingfield J C, Hegner R E, Dufty A M, Ball G F. 1990. opment of courtship and communication in juve- The “challenge hypothesis”: theoretical implica- nile male cowbirds (Molothrus ater). Behavioral Ecol- tions for patterns of testosterone secretion, mating ogy 13:487–496. systems, and breeding strategies. American Natural- Wilson D S. 1998. Adaptive individual differences ist 136:829–846. within single populations. Philosophical Transactions Zera A J, Denno R F. 1997. Physiology and ecology of of the Royal Society of London B 353:199–205. dispersal polymorphism in insects. Annual Review Wilson D S, Coleman K, Clark A B, Biederman L. of Entomology 42:207–230. 1993. Shy-bold continuum in pumpkinseed sunfish Zhivotovsky L A, Feldman M W, Bergman A. 1996. On (Lepomis gibbosus): an ecological study of a psycho- the evolution of phenotypic plasticity in a spatially logical trait. Journal of Comparative Psychology heterogeneous environment. Evolution 50:547– 107:250–260. 558.

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