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Abstract

In captivity, personality types differ in behavioral flexibility: "fast" (neophilic, exploratory, and aggressive) types quickly form routines, whereas "slow" types continually adjust their behavior with environmental changes. If these differences extend to pertinent natural environmental changes, which indicate changing predation or starvation threat, then personality may reflect important variation in how animals manage risk. We examined whether personality traits classified in captivity would predict the behavioral flexibility of blue tits Cyanistes caeruleus as they foraged in the wild. Behavioral flexibility was defined as the tendency to adjust feeder use with changing winter air temperature, an indicator of starvation risk. At the population level, birds reduced their feeder use on warm days. Individuals, though, varied widely, with some instead using feeders at a relatively fixed, temperature-independent rate. Sex and size, correlates of dominance in blue tits, did not predict behavioral flexibility. Instead, behavioral flexibility was predicted by age and 2 personality traits: old, neophobic, and exploratory birds were more behaviorally flexible than young, neophilic, and nonexploratory birds. Our findings suggest that personality types differ in how they use information about their environments and hence cope with environmental change.

INTRODUCTION

The term "personality" describes behavioral differences among individuals that are consistent over time or contexts, for example, in the tendency to approach novel objects or predators, explore new environments, or interact with conspecifics ( Gosling 2001). Such variation may reflect underlying differences in responsiveness of hypothalamic-pituitary-adrenal axis that regulates hormonal response to environmental stimuli ( Groothuis and Carere 2005; Cockrem 2013). Within the same environment, individuals differing in personality often differ also in their fitness and condition ( Dingemanse and Réale 2005; Herborn et al. 2011). In a few studies comparing fitness of personality types over multiple years, there is evidence that "slow" personality types, that is, less exploratory, neophobic, less active, or passive animals are less successful than "fast" (exploratory, neophilic, active, or aggressive) types in relatively stable environments but that this is reversed in changeable environments ( Dingemanse and Réale 2005). Two observations in captive studies suggest a mechanism for this environment-specific advantage: 1) fast types learn novel associations or habituate to novel or risky stimuli more quickly than slow types ( Marchetti and Drent 2000; Dugatkin and Alfieri 2003; Rodriguez-Prieto et al. 2010) and 2) once formed, fast types tend to stick to routines, using old information to predict the environment, whereas slow types continually gather and use new information ( Benus et al. 1987, 1988; Guillette et al. 2010). These attributes may allow fast types to quickly monopolize resources in stable environments. In contrast, slow types may be relatively "behaviorally flexible," that is, able to adjust their behavior in response to changing environmental stimuli ( Coppens et al. 2010; Sih and Del Giudice 2012). Extra time or energy spent on information gathering may allow slow, behaviorally flexible types to "keep pace" in changeable environments ( Dall and Johnstone 2002).

However, these predictions on personality and behavioral flexibility come from studies of captive animals. In captivity, fast-exploring great tits ( Parus major) continue to visit feeders for a period after they are emptied, whereas slow explorers extend their search to new sites ( Marchetti and Drent 2000). Comparing range location after emptying artificial feeding stations in the wild, however, van Overveld and Matthysen (2009) found the opposite. Reliance on old information may have limited fast explorers to the emptied feeders in the simple captive environment but, equally, channelled them to recalled, distant natural sites in the wild. A few other recent studies have compared the behavior of personality types between captivity and the wild ( Dingemanse and de Goede 2004; Herborn et al. 2010; Minderman et al. 2010; Schuett et al. 2012) or the behavior of captive-bred to wild-caught animals ( Mason et al. 2013). These studies raise an important point: to understand the mechanisms underlying fitness variation among personality types, predictions must be explored in the greater complexity of the natural environment ( Archard and Braithwaite 2010). Therefore, we aimed to test the prediction that personality types differ in behavioral flexibility in free-living birds.

Moreover, we aimed to quantify behavioral flexibility in relation to a pertinent, natural environmental cue. To this end, behavioral flexibility was defined as the change in foraging behavior, specifically artificial feeder use, with changing air temperature in winter. In winter, when food is scarce and thermoregulatory costs high, birds use feeders more often ( Chamberlain et al. 2005) and gain mass earlier in the day ( Macleod et al. 2005) than under more benign conditions. These activities not only increase body reserves, providing a buffer against starvation, but also incur costs in terms of increased exposure to predators while foraging and increased mass-specific predation risk ( Metcalfe and Ure 1995; Macleod et al. 2005). Thus, Parids may use air temperature as a cue to predict starvation risk and, hence, optimize foraging rate ( Fitzpatrick 1997) or fat storage ( Gosler 2002).

Our study species was the blue tit ( Cyanistes caeruleus). The personality traits were exploratory tendency and neophobia, which describe responses to novel environments and to resources near novel objects, respectively ( Verbeek et al. 1994; Greenberg 1995). Although in many species these traits are positively correlated, hence considered aspects of a single proactive-reactive trait ( Groothuis and Carere 2005; le Vin et al. 2011), they are independent in blue tits ( Herborn et al. 2010). Previously, in a larger sample of individuals of which this study uses a subset, we demonstrated that a blue tit's novel environment activity and neophobia in captivity predicted analogous behaviors in the wild and that these behaviors were repeatable in both contexts ( Herborn et al. 2010). In addition, we compared 2 aspects of exploration behavior: activity specifically in novel parts of a cage and total activity in a cage. Only novel environment activity predicted wild behavior ( Herborn et al. 2010).

Here, we provide a novel test of whether an individual's personality predicts their response to a fluctuating environmental cue. At the population level, we anticipated that individuals would spend more time foraging at feeders when the air temperature was colder, to maintain body reserves. However, we predicted that this response would vary among individuals and that birds that were more behaviorally flexible (i.e., more neophobic and less exploratory) would adjust their behavior in response to fluctuating air temperature, whereas less behaviorally flexible birds (i.e., less neophobic and more exploratory) would not alter their behavior in response to temperature. Additionally, we examined whether sex and size, correlates of dominance in Parids ( Braillet et al. 2002; Krams et al. 2010), and age influenced behavioral flexibility and/or average feeder use.

METHODS

Overview of study system

Over 2 winters, we collected feeder use data at 8 feeding stations in woodland around the Scottish Centre for Ecology and the Natural Environment (SCENE; 56°08′N; 4°37′W). For detailed description of the study system and captive methods, see Herborn et al. (2010). Briefly, each feeding station had 2 opaque feeders, baited with peanut granules. One bird could access each feeder at a time, from a small perch fitted with an antenna. Feeders were baited for 1 month prior to the study, so that all birds were familiar with using the feeders prior to collecting behavioral data. Each winter, we then mist-netted on 2 or 3 mornings, spaced through the winter, at each feeding station to capture feeder-using birds. On capture, each bird was fitted with a leg-ring mounted passively integrated transponder ("PIT" tag; 11.5mm × 2.1mm, <0.1g, Trovan Unique™). When on a feeder perch, within the electromagnetic field of the antenna, this PIT tag allowed identification of the bird by a connected electronic reader (Trovan™ LID665). On capture, we also measured wing length and determined age (juvenile/adult) from plumage traits. Birds were then taken to SCENE for personality testing. They were returned after 1 or 2 nights in captivity. PIT tag records, from which we derived feeder use, were collected thereafter. We used these records to determine also which feeding stations each bird used. All birds were detected at their feeding station of capture on the first day of PIT tag recording after release; thus, capture did not cause the birds to change feeding site.

Feeder use data

We were interested in feeder use relative to air temperature. Where readily available, artificial food makes up on average 15% of the diet of blue tit nestlings and 21% of the adult winter diet of the closely related black-capped chickadees ( Poecile atricapillus) and scales with total food intake that varies with energetic demands ( Cowie and Hinsley 1988; Brittingham and Temple 1992). Changes in feeder use are, therefore, likely to represent changes in total food intake.

Maximum daily air temperature (henceforth "air temperature") was collated from Met Office records for Gartocharn (56°03′N; 4°34′W), which ranged between 1.2 and 12.1 °C. Maximum daily air temperature in the previous day ("previous day air temperature") may alter birds' body reserves on entering trials and changing day length their total foraging opportunity. Both variables may, therefore, alter perceived starvation risk (Gosler 2002), hence feeder use, so were collated to control when comparing among individuals sampled on different days. At the end of the study, we used the average air temperature across study days (7.8 °C) to identify 68 focal individuals that had feeder use data for at least one above and one below average air temperature.

Feeder use was measured in the 4h following sunrise in winter (22 December 2007 and 25 February 2008, and 12 January 2009 and 26 February 2009). To collect the feeder use data, we rotated 4 PIT tag readers around the 8 feeding stations throughout the winter, obtaining between 8 and 14 mornings of readings per feeding station per year. PIT tag readers recorded the identity of feeder users at 2-s intervals. Thus, the number of detections per bird was our score of their total feeder use on a given morning (mean number of mornings = 6.5 per bird, range = 2-14). We summed feeder use over the whole morning rather than the most competitive early feeds because we wanted to compare total food intake among birds rather than intake under competition. We scored birds a 0 whenever their PIT tag was not recorded on the focal feeding station during the morning but was recorded later that day; thus, they were in the area. Of 68 birds, 51 used 1 feeding station and 17 used 2 feeding stations. In those 17 birds, feeder use data were excluded when they were detected at both within the same week, in case they had divided their time between the focal feeding station and another not currently connected to the PIT tag readers. On the 68 birds, we collected 441 feeder use measurements in total, of which 20 were 0 scores.

Personality trials

Personality tests were conducted more than 2 days in captivity (see also Herborn et al. 2010). Each bird was tested only once in one of the study years. On arrival, the focal bird was enclosed within one half of a 150cm × 50cm × 50cm cage. Food and water were provided ad libitum and the bird undisturbed for at least 2h. The first trial was the exploration trial, after which the bird had access to the entire cage. Neophobia trials were conducted during the afternoon of day 1 and repeated on the morning of day 2. In 2007-2008, birds were then blood sampled for genetic sexing and released at the capture site. In 2008-2009, birds were released after a second exploration trial on the morning of day 3.

Exploratory tendency

By initially enclosing birds within one cage half, we aimed to create a "familiar" and, behind the divider, a "novel" environment. We removed food 1h and water 30min prior to the trial to motivate birds to forage. The trial started when the observer removed the cage divider. The focal bird was observed for 10min, during which we recorded the number of movements (hops or flights between perches or covering >50cm), and the endpoint of each movement: novel or familiar.

To assay exploration independently of neophobia, the arrangement of 3 plastic vine-covered perches was the same in each cage half, that is, the novel half was novel only in that it was unexplored. To determine whether activity per se or specifically activity directed toward the novel environment predicted behavioral flexibility, we extracted 2 measures from the trial. First, we regressed day 1 activity in the novel environment against day 1 activity in the familiar environment, after log-transforming both values. The residuals of this model were our measure of "novel environment activity," with positive values indicating highly exploratory birds that were relatively active in the novel environment, and vice versa. Novel environment activity was, therefore, independent of the summed activity in the novel and familiar environments: "total activity."

The repeatability of novel environment activity was 0.27 and total activity was 0.42 in a previous study of individuals from this population, of which these 68 are a subset ( Herborn et al. 2010). In that study and here, novel environment activity was independent of sex, mass, wing length, and age (analysis of variance [Anova]: F 4,63 = 0.46, P = 0.77).

Neophobia

Neophobia is measured using the extent to which approaching a resource, here food, is delayed by the presence of a novel object (Greenberg 1995). Food and water were removed for 30min prior to the trial. To start, the observer returned the food bowl with 1 of 2 similarly sized novel objects placed inside: a pink plastic frog and a half of a purple rubber ball. Latency to approach the bowl was recorded. After 10min, the object was removed and water returned. Birds underwent 2 trials, one per day, with the order of objects randomized per bird.

Independent of differences in neophobia, individuals may also differ in their motivation to feed or their response to disturbance by the observer. To isolate neophobia, we performed the same procedure but without a novel object, returning the food bowl only. This disturbance control phase was performed 1h either before or after each novel object phase, with the order randomized on each day. After log-transformation, mean novel object latency was regressed against mean disturbance latency. The residuals of this model were our measure of neophobia, with positive values indicating birds that were more neophobic (Herborn et al. 2011).

The repeatability of neophobia was 0.28 in a previous study of individuals from the population, of which these 68 are a subset ( Herborn et al. 2010). In that study and here, novel environment activity was independent of sex, mass, wing length, age, novel environment activity, and total activity (Anova: F 6,61 = 0.78, P = 0.59).

STATISTICAL METHODS

Analyses were conducted using R 2.15.1 ( R Development Core Team 2012), with glmmADMB_0.7.2.12 ( Skuag et al. 2006). We had 3 objectives:

1) To test whether, at the population level, feeder use declined with increasing air temperature. We employed a generalized linear mixed model (GLMM) with feeder use per morning per individual as the response variable and air temperature as a fixed variable. A negative binomial error structure accounted for overdispersion in the response variable and individual identity was a random effect to account for repeated measures. Previous day air temperature and day length were fixed effects. To reduce collinearity between the 2 air temperature measurements, previous day air temperature was expressed as high or low relative to air temperature, by taking the residual of a regression with air temperature. As the feeding stations were also the capture sites, in case birds altered feeder use immediately postrelease from captivity, a factor "new release" describing whether a given measurement was the first after release (yes or no) was also a fixed effect.

2) We aimed to test whether individuals differed in their tendency to reduce feeder use with increasing air temperature, that is, in their "behavioral flexibility" with respect to air temperature. We also tested whether individuals differed in "average feeder use." To the GLMM, we added the random slope of interaction: individual identity × air temperature, which then represented individuals' behavioral flexibility. The random intercept for individual identity represented individuals' average feeder use. We used likelihood ratio tests (LRTs) to compare between models including and excluding those random effects.

3) We tested whether average feeder use or behavioral flexibility was related to novel environment activity, neophobia, total activity, age, sex, or wing length. To identify correlates of average feeder use, these traits were added to the original GLMM as fixed effects. We compared between consecutive nested models using LRT. To identify correlates of behavioral flexibility, we followed the same procedure but starting with all 2-way interactions between traits and air temperature. Significant trait × air temperature interactions would indicate variation in the relationship between feeder use and air temperature among individuals differing in that trait, hence within-trait variation in behavioral flexibility. Equally, we would expect "behaviorally flexible" individuals to attend to current rather than old information and, hence, to temperature on the day of testing rather than the temperature of the previous day. To test this possibility also, we include all 2-way interactions of traits × previous day air temperature, with the expectation of no or opposite relationships to those found in traits × air temperature.

Ethical note

Work was licensed by the UK Home Office, Scottish Natural Heritage, and the British Trust for Ornithology. Studies met the Association for the Study of Animal Behaviour ethical guidelines on animal research and were subject to review by Waltham Centre for Pet Nutrition and the University of Glasgow. No birds died, were injured, or lost more than 10% body mass while in captivity.

RESULTS

Does feeder use decline with increasing air temperature at the population level?

As predicted, at the population level, feeder use declined with increasing air temperature (Table 1i). Also, birds used feeders most intensively when day length, and hence the opportunity to forage, was shortest. Finally, previous day air temperature correlated negatively to feeder use, so birds used the feeders more when the temperature on the previous day was relatively cold and vice versa. The new release variable was not significant, so recent experience of captivity did not alter feeder use. Day length, previous day air temperature, and the new release factor were controlled as fixed effects in subsequent analyses.

(i) Population-level environmental predictors of average feeder use

(ii) Individual-level predictors of average feeder use

(iii) Individual-level predictors of behavioral flexibility

Do individuals differ in average feeder use or behavioral flexibility?

Removal of the random intercept term significantly reduced the model fit (LRT: χ ² = 108.92, P < 0.001), so average feeder use differed between individuals. Removal of the random slope term significantly reduced the model fit (LRT: χ ² = 7.38, P = 0.007). Therefore, individuals differed in behavioral flexibility in terms of their change in feeder use with changing air temperature.

Do personality and other traits predict average feeder use or behavioral flexibility?

Adult birds (>1 year old) used feeders more than juveniles (<1 year old) ( Table 1ii). Behavioral flexibility was predicted by age, neophobia, and novel environment activity: adults, neophobic birds, and those that were highly active in novel environments were most responsive to temperature ( Table 1i ii). Juveniles, less neophobic birds, and those that were less active in novel environments fed at a constant rate irrespective of air temperature. There were no significant interactions between traits and previous air temperature. Sex, wing length, and total activity did not predict average feeder use or behavioral flexibility.

DISCUSSION

We provide a rare demonstration that personality types differ in behavioral flexibility in a seminatural and ecologically relevant context (see also Quinn et al. 2011; Betini and Norris 2012). At the population level, feeder use declined with increasing air temperature. At the individual level, this response differed between birds: some showed a steep decline, whereas others used feeders at a relatively fixed, temperature-independent level. Old, neophobic, and, contrary to expectation from captive studies ( Coppens et al. 2010), exploratory individuals were more behaviorally flexible than young, neophilic, and nonexploratory individuals. Feeder use also correlated negatively with temperature in the previous day, suggesting some carryover of expectations and/or an energy deficit. However, there were no interactions between traits and previous day air temperature, indicating that birds differed in their response to current but not old temperature information. Behavioral flexibility was not explained by sex or wing length: 2 correlates of dominance in blue tits ( Braillet et al. 2002; Krams et al. 2010).

To respond flexibly suggests an individual must first incur costs in terms of time and energy expended on information gathering or learning ( Coppens et al. 2010). The benefits of behavioral flexibility will, therefore, be context dependent. For example, personality variation appears to be maintained in one great tit population by fluctuating selection on personality-specific responses to large, interannual changes in food availability, with beech mast years ( Dingemanse and Réale 2005). However, our study shows that personality differences are expressed even when food availability, in artificial feeders, is constant. And in a great tit population lacking such beech mast years, there is no fluctuating selection and evidence of directional selection away from "slow" traits in that more constant foraging environment ( Quinn et al. 2009).

Our findings with the neophobia trait fit the expectation from captive studies that slow types should be behaviorally flexible ( Coppens et al. 2010). Previously, we have shown that this captive measure of neophobia in blue tits also predicts their neophobia in the wild ( Herborn et al. 2010). A third study on blue tits from our population showed that nestling diets associated with poor foraging environment were associated with development of neophilic personality ( Arnold et al. 2007). The authors suggested that this may equip birds to "take risks" on fledging into an impoverished environment. Taken together, these studies suggest neophobia measured in captivity may reflect a range of strategies, fixed and plastic, for coping with environmental change.

Contrary to several captive studies ( Coppens et al. 2010), highly exploratory blue tits proved more behaviorally flexible than less exploratory individuals. Comparison of a captive and a wild study of great tits, which found exploratory birds to be least ( Marchetti and Drent 2000) versus most ( van Overveld and Matthysen 2009) behaviorally flexible, respectively, in terms of their tendency to move away from unprofitable situations, suggests that a naturalistic context may be important. Differences in how "exploratory tendency" is defined from otherwise similar behavioral trials, however, as activity level ( van Overveld and Matthysen 2009) or time taken to explore ( Marchetti and Drent 2000), or indeed space use ( Minderman et al. 2010), may also be important ( van Dongen et al. 2010). If aspects of exploration behavior vary in state dependency, the interval between captive and wild testing may also be important, with captive trials typically repeated within days but wild data collected over months ( Bell et al. 2009). Here, total activity did not predict behavioral flexibility. Activity in a novel environment, however, which combined space use with activity, predicted both the birds' propensity to find new, short-lived feeding sites over months in the wild ( Herborn et al. 2010) and also, here, behavioral flexibility in the use of known feeding sites.

Total activity was also independent of average feeder use. Although this is surprising, given that highly active individuals may be expected to require more energy, as we did not test whether total activity in the exploration trial correlated to activity levels in general, we cannot speculate on this possibility. The independence of average feeder use and all 3 personality traits, however, is encouraging for studies using artificial feeding sites to assay behavior in the wild ( Echeverría and Vassallo 2008; van Overveld and Matthysen 2009; Herborn et al. 2010), where variation in feeder use per se could bias results.

As expected, feeder use was highest on short and cold days, when the opportunity to forage was brief and urgent, giving ecological resonance to our results. However, we also expected, but did not find, small and female birds to use feeders at a high rate to maintain body reserves as an "insurance policy" against starvation under risk of competitive exclusion by male and large birds ( Dall and Johnstone 2002). In turn, we expected male and large birds to avoid costs associated with carrying body reserves ( Metcalfe and Ure 1995) by monopolizing feeders on cold days, hence to be behaviorally flexible. However, it is possible that dominance patterns were lost by summing feeder use across the morning rather than comparing the exact times of feeding: Cole and Quinn (2011) found that great tits defined as poor competitors employed alternative strategies at feeders to gain similar total access despite competitive exclusion. That subdominant groups did not have lower average feeder use, nor show the opposite patterns in behavioral flexibility by using feeders most under the low competition of warm days, supports this possibility.

Interestingly, old birds were more behaviorally flexible than young birds. As such, the predation-starvation risk trade-off may differ with age, with young birds at greater predation risk than older birds when it is warm, but old birds lacking the body reserves for a sudden cold snap ( Dall and Johnstone 2002). Age-specific patterns arise by selective mortality, but also when traits are plastic and either learnt or have age-specific costs ( Komers 1997). This raises the intriguing possibility that, rather than a fixed characteristic of particular personality types, personality differences in behavioral flexibility may be plastic, arising within environments that would promote behavioral flexibility ( Wright et al. 2010). Indeed, there is some evidence that the expression of personality traits themselves may be plastic, varying with context ( Kluen and Brommer 2013) and experience ( Bell and Sih 2007). It has been suggested that personality, in particular behavioral and hormonal responsiveness to novel cues or opportunities, may play an important role in population-level adaptation to new or shifting environments ( Greenberg 1995; Bell and Sih 2007; Echeverría and Vassallo 2008; Cockrem 2013; Sih 2013). To understand the mechanisms, it will be important to determine how personality differences develop and are expressed as the environment changes ( Visser 2008; Kluen and Brommer 2013).

FUNDING

K.H. was funded by a Biotechnology and Biological Sciences Research Council Industrial Case studentship with WALTHAM® (BBS/S/M/2006/13139) and K.E.A. by a Royal Society University Research Fellowship.

We thank R. Macleod, A. Schofield, W. Miles, B. Zonfrillo, E. Leat, L. Henderson, M. Gastañaga, S. Wilson, D. Fettes, and R. Brennan for field support and N. Mirzai and T. Wallis for electronic support. Genetic sexing was conducted by A. Adam and K. Stift.

REFERENCES

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Personality predicts behavioral flexibility in a fluctuating, natural environment | Behavioral Ecology | Oxford Academic

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In captivity, personality types differ in behavioral flexibility: "fast" (neophilic, exploratory, and aggressive) types quickly form routines, whereas "slow" types continually adjust their behavior with environmental changes. If these differences extend to pertinent natural environmental changes, which indicate changing predation or starvation threat, then personality may reflect important variation in how animals manage risk.

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Centre for Ecology and Conservation, Biosciences, College of Life and Environmental Sciences, University of Exeter, Penryn, Exeter, UK

Department of Biological Sciences, Macquarie University, Sydney, NSW, Australia

The study of animal personality variation promises to provide significant new insight into the way that behavior evolves in animals, along with its ecological and evolutionary influences. We strongly advocate more empirical work in this exciting and rapidly expanding research area, but hope that new studies adopt a more hypothesis-driven and/or experimental approach than seems to be usual at the moment. Here we outline what we feel is "good practice" to the many empiricists that are keen on pursuing work in this field. We highlight the substantial body of theoretical work that exists for providing well-reasoned hypotheses, which new empirical studies should be designed to test. Furthermore, using a brief review of existing work on the behavioral ecology of animal personality variation in the zebra finch-one of the more widely used model systems in this field-we stress the importance of understanding the ecology of the chosen study animal, and the problems that are likely to arise by neglecting to identify or account for the structure of behavioral variation that is often likely to occur.

The study of animal personality variation has been the focus of a burgeoning research effort over the past decade, with the realization that the consistent individual differences in behavior that characterize it are the target of different forms of selection ( Dingemanse and Wolf, 2010; Schuett et al., 2010; Wolf and Weissing, 2010), and can be substantial drivers of a range of important ecological and evolutionary processes ( Sih et al., 2012; Wolf and Weissing, 2012). In keeping with the broad consensus in the evolutionary and behavioral ecology literature, we use the term personality variation to refer here to the existence of substantial variation in behavior among individuals within a population, with at least some individuals showing behavior that is consistent (i.e., individual differences remain stable) across time and/or contexts. Empirical studies of animal personality in the context of ecology and evolution, have been influenced by the long-established body of research conducted in the fields of animal and human psychology that is typically focused on characterizing inter-individual variation in behavior from ratings (by either the focal subjects or expert observers of focal subjects) derived from questionnaires ( Gosling, 2001).

An accessible way of entering this new and exciting field of research has been to adopt standardized tools for measuring individual variation in response to controlled environments and stimuli. It has been advocated that the widespread adoption of a very general framework and standardized methodologies such as the open-field test (where individual behavior is assayed in unfamiliar, "open" spaces: Archer, 1973) provides a useful framework for addressing the ecology and evolution of animal personality variation ( Reale et al., 2007). However, perhaps as a consequence, most of the recent empirical studies of animal personality published in the fields of evolution or ecology have been almost entirely descriptive and "question free." Despite requiring the capture and handling of animals, the assays of personality using, for example, open field tests, the presentation of novel objects, or startle responses are simply standardized tools for assaying variation, rather than being true manipulative experiments in themselves. Studies of natural variation are currently still useful in a field in which relatively few species have yet been the focus of more than a single study of personality variation. However, the interpretation of such observational findings will remain ambiguous without widespread experimental manipulations to test a priori hypotheses about the evolutionary and ecological factors underpinning behavioral variation of this type. Therefore, it is important that any observational studies that are attempted are designed with specific hypotheses in mind based on the ecology of the study species and theoretically-derived predictions (e.g., Table 1).

Table 1. Some empirical questions derived from theoretical models of the evolution and maintenance of animal personality variation (individuals that differ consistently in their behavior from one another within populations).

Given this backdrop, we would like to present a road map for those keen to enter this area of research, which will increase the insight provided by new empirical studies, and help newcomers avoid some of the pitfalls that have limited the conclusions and interpretations of many of the studies conducted to date.

The two most important principles we advocate, the reasons for which we will discuss further below, are:

1. Consider the ecology and evolutionary context of your species carefully and explore the theoretical literature from the perspective of that species. Focus on the personality variation in suites of behavioral traits likely to be most ecologically relevant to that particular species, and design assays that are best able to capture that appropriately.

2. Adopt an experimental and/or hypothesis-driven approach designed around a temporal framework that adequately captures the important variation in repeatability within and amongst individuals.

Theoretical Background and Experimental Tests

Although the study of animal personality variation in the context of ecology and evolution is less than 10 years old, there is a relatively rich theoretical literature that has already been well reviewed (e.g., Dingemanse and Wolf, 2010; Wolf and Weissing, 2010). However, for a newcomer, an inconsistent and developing terminology can be somewhat difficult to navigate. The dearth of incisive experimental work also suggests that there is a need for some simple guidance about the approaches that should be followed in conducting good empirical work tackling a priori (theoretically-derived) predictions. There are two main branches of theory that have explored the drivers of (selection pressures on) animal personality variation, which are ready for empirical hypothesis testing at the behavioral level (see Wolf and Weissing, 2012 for a summary of theoretical predictions about the ecological and evolutionary consequences of personality variation). This work has focussed on identifying the key ecological factors that can select for both substantial inter-individual variation AND individual consistency to coevolve within populations (see Dingemanse and Wolf, 2010; Wolf and Weissing, 2010 for more detail). A number of theoretical papers have explored the role of individual life-history and metabolic trade-offs and the way in which they can drive consistent variation in suites of behaviors (e.g., Stamps, 2007; Wolf et al., 2007; Houston, 2010; Careau and Garland, 2012; Wolf and McNamara, 2012). These ideas are best summarized and encapsulated in the recent work defining "Pace of Life Syndromes" ( Reale et al., 2010), and are focussed on the role that resource-acquisition/assimilation trade offs play in driving the evolution and maintenance of personality variation.

The other important theoretical perspective is that the among-individual variation in consistent patterns of behaving can be selected for directly in social (including sexual) contexts, where an individual's behavioral responses are determined by the interactions of other conspecifics and the consistent responses that they make ( Dall et al., 2004; McNamara et al., 2009; Bergmüller and Taborsky, 2010; Schuett et al., 2010; Wolf et al., 2011). The basic idea is that, when animals interact socially, they can pay attention to each other's behavior to make better decisions. Once individuals are using such basic social information, it changes selection on how to pattern behavior over time in the presence of audiences. In some contexts (e.g., when competing aggressively for resources or interacting cooperatively) this can select for individual behavioral differentiation ( Dall et al., 2004; McNamara et al., 2009; Wolf et al., 2011) or it can create negative frequency dependent selection on being adaptively flexible ( Wolf et al., 2008).

Together, these non-mutually exclusive sets of theoretical work provide an excellent framework for approaching the study of variation in animal personality, although, to date, very few of the predictions that they make for understanding the variation across and within animal populations have been directly tested. Table 1 summarizes some empirical research questions derived from this theoretical work so far (see Dingemanse and Wolf, 2010; Wolf and Weissing, 2010 for more details). Trade-offs and state-dependent feedback loops have been proposed as common features driving patterns of variation within populations across both sets of theoretical work ( Dall et al., 2004; Luttbeg and Sih, 2010), and therefore, well designed manipulations of key metabolic, life-history, environmental, or social variables should readily test the strength of theoretical predictions (Table 1).

The very few examples of experimental work (including "natural experiments") in this field illustrate some of the approaches that can be taken. An example of what we would consider "good practice" involved experiments on captive zebra finches that directly tested hypotheses about the role of sexual selection on personality variation ( Schuett et al., 2010). Schuett et al. (2011a, b) showed that personality variation impacted both the fitness consequences of pairing up according to behavioral type (via a forced-pairing, cross-fostering experiment: Schuett et al., 2011a) and mate choice decisions (by manipulating the apparent behavioral type of males in a standardized mate choice protocol: Schuett et al., 2011b) in captive zebra finch populations. There are a number of other studies that similarly manipulate personality variation to assess its impact on measures of fitness (e.g., Sih and Watters, 2005; Riebli et al., 2012; Sweeney et al., 2013). Most impressive, though, are the very few studies that have isolated the effects of specific factors that were hypothesized a priori to influence the structure of personality variation within populations. These include a comparison across multiple populations that has taken the "natural experiment" approach to investigate a purported relationship between predation or parasite intensity and the distribution of personality variation in three-spined sticklebacks ( Dingemanse et al., 2007). Moreover, Bell and Sih (2007) went on to manipulate predation intensity on captive stickleback populations and demonstrated the hypothesized (causal) effect of predation intensity on selection for boldness-aggression syndromes. Finally, Laskowski and Bell (2013) manipulated intraspecific competition over access to food in captive sticklebacks and corroborated theoretically-derived predictions (Table 1) that heightened competition levels should promote stronger personality variation.

The Importance of Measuring Behavior Repeatedly

A pretty fundamental problem facing researchers interested in studying animal personality variation is that, as humans, we effortlessly cue in on individuality and individual patterns behavior. Perhaps as a consequence, we have been too ready to dismiss the evolutionary importance of such behavior (e.g., its functional significance in non-human animals) and so human-centerd (psychological) definitions of personality range from the vaguely broad: "individual differences within species" ( Gosling and John, 1999), to the idiosyncratically human-specific: "those characteristics of individuals that describe and account for consistent patterns of feeling, thinking and behaving" ( Pervin and John, 1997). Indeed, both extremes are of limited value when investigating measurable patterns of individual variation in an evolutionary and ecological context (e.g., across species). Clearly further elucidation is needed. There are two distinct components that must be included within the scope of animal personality variation from an evolutionarily and ecologically functional standpoint (see Stamps and Groothuis, 2010; Kight et al., 2013 for a more exhaustive discussions of the issue). First and foremost, investigators must consider behavioral variation amongst individuals within otherwise homogenous populations or groups of the same species when they study animal personality. Crucially, however, researchers must simultaneously consider the patterns of behavior that individuals exhibit over some portion of their lifetimes and/or across the different biological contexts they face (e.g., foraging, mating, socializing etc.), since a hallmark of personality is the relative stability or consistency of individual behavior over some portion of a life history. Indeed, the vast majority of existing studies on animal personality variation fall within this scope. Moreover, by adopting this stance, we do not restrict ourselves to studying inter individual variation that is generated by any specific proximate mechanisms (e.g., coded for genetically), thus avoiding potential confusion over levels of explanation ( Tinbergen, 1963) by focusing on observable patterns of behavior per se. In this way, animal personality studies can encompass variation that is genetically driven, while also considering inter individual variation that involves substantial behavioral plasticity, need not be stable for a lifetime and depends on social status or condition.

Given this emphasis on patterns of variation and consistency, it is necessary to structure measurements of behavior in such a way to be able to quantify this class of variation at biologically significant scales for the species in question. The basic approach must therefore involve taking repeated measurements of behavior from the same individuals across multiple ecologically important time periods and/or contexts (e.g., within vs. among breeding seasons; while breeding vs. not breeding etc.: see Bell, 2012 for more details). It is also important to ensure that you get estimates of behavioral repeatabilities (i.e., you get repeated measures) for ALL of the individuals in your study population. This is because theory suggests that individual differences in the consistency or flexibility of behavior can evolve in certain contexts (e.g., Wolf et al., 2008). Therefore a single population-representative repeatability (e.g., mean repeatability) may not be biologically meaningful and quantifying the full-range of individual-level patterns of behavioral variation will be necessary to critically test theoretical predictions. Dingemanse et al. (2010) have described the 'reaction norm' approach that provides an excellent framework for structuring and analysing data sets in a way that will capture the variation within and between individuals in behavioral traits over time and across different ecological, or life-history contexts. As such it relies heavily on mixed-effect statistical modeling approaches ( Dingemanse and Dochtermann, 2013). Researchers that follow the detailed recommendations made in these reviews will maximize their abilities to fully-quantify personality variation within their study populations, if it is present.

A Species-Specific Approach to the Study of Variation in Personality

As in all other areas of biology, the starting point for good research should be the choice of a species that is appropriate for the particular question that you wish to address. There is nothing inherently wrong with studying systems that are readily accessible, and it is perhaps no surprise, for instance, that more research has been conducted on existing research populations of tits ( Cyanistes caeruleus or Parus major), or the domesticated zebra finch ( Taeniopygia guttata), than other avian species. However, to date, most of the work on these species has focused on demonstrating the existence of personality, methods for measuring personality ( Herborn et al., 2010; Kluen et al., 2012), and correlates of particular personality traits that have been explored in the absence of clear a priori theoretically driven predictions (e.g., David et al., 2012; Patrick et al., 2012), with highly variable methodologies and sample sizes ( Garamszegi et al., 2012).

The difficulty of non-manipulative studies (or observational studies that are not designed to test a specific hypothesis) is that the interpretation of results can be very difficult, if not impossible in the absence of a proper understanding of a species. For example, one of the more widely used assay of personality variation is the "candidate behavior" approach ( Reale et al., 2007), which focuses on assay-derived categories of behavior that are difficult to interpret and define across and within populations. A relevant example here is to consider the open field test ( Archer, 1973), in which an animal is released into an unfamiliar cage/ box and the degree of movement in a set period of time is assessed (e.g., Dingemanse et al., 2004; Schuett and Dall, 2009). Many researchers interpret this test as assaying "boldness" or exploratory behavior. However, this may not be the correct interpretation for species that have evolved with ambush predators (i.e., take refuge in open areas) and forage under cover, or are highly social ( Carter et al., 2013). Indeed, Carter et al. (2013) detail the problems that arise from the widespread use of such standardized "personality assays" without careful consideration of how well they assay what you think they assay in your study species, and the ecological relevance of any given assay for different animal systems. We agree with many of their recommendations to deal with the first issue, especially that multiple tests should be designed for each functional category of behavior that has been identified a priori as being of interest, and that individual tests should be validated against each other to ensure personality variation within the functional domain of interest can be reliably quantified. However, we differ somewhat in our recommendations about how researchers should design assays in the first place. As we have stated all along, we feel that, as with any study of animal behavior from an ecological or evolutionary perspective, assays should be designed to capture variation in behavioral responses to key ecological trade-offs that have been identified a priori as likely influencing animal personality variation. So, for instance, if you are attempting to test the hypothesis that strong trade-offs between mortality and resource acquisition are likely to favor individual differences in attitudes to risk while foraging (Table 1), you should design (or customize) assays to probe, in a standardized way, the willingness to look for food in situations that are perceived as posing a significant risk of mortality for your focal species.

In addition to the issue of reliably assaying behavior in an ecologically meaningful manner, it is also important to design personality testing to capture hidden structure to variation measured along a continuum that can be predicted theoretically. For instance, in open field tests it is typically assumed by many of the empirical studies that individual variation will be distributed along a continuum from individuals that move around lots, and are "exploratory" to those that are "non-exploratory" and essentially don't move around. It is often believed, for example, that this exploratory aspect of personality will be related to dispersal ability and inversely related to the risk of predation that an individual exposes itself to. However, theoretical work often predicts that the variation in stable individual behavior across a population will not be so continuous, and this can start to make clear interpretations very difficult. For example, in their recent study of the great tit, Titulaer et al. (2012) found that the relationship between exploratory behavior and flexible learning abilities was discontinuous across the population: it manifest in opposite directions in males and females. In this study, the sex-specific personality variation was relatively easy to identify and account for in both experimental design and analyses, because sex was easy to assign and is an obvious feature of individuals to record in any study of behavior. However, a more interesting, and problematic situation arises where we have a similar degree of structuring amongst the individuals within a population that is not so readily identified, or accounted for. Behavioral polymorphisms can often be very cryptic (driven by hidden "state variables" like reputation or energy levels), and indeed many of the theoretical models have predicted the emergence of multiple stable personalities (e.g., Wolf et al., 2007). Where such polymorphism occurs within populations, we would not necessarily expect a simple linear or continuous pattern of variation, and this makes interpretation of datasets very difficult without having assayed the relevant state-variables from the outset of data collection. For example, if individuals within a population follow different strategies then the relationship between a particular behavioral type or syndrome and other variables (e.g., lifetime reproductive success) is likely to vary dependent upon the polymorphism. Counter-acting relationships exhibited in different morphs or subsets of a population would make it very difficult to determine or examine relationships in a population-wide sample in the absence of a structured data collection protocol designed a priori to assign individuals to their biologically-relevant categories.

Personality Variation of a Model System in an Ecological Context

To help illustrate the pitfalls we have highlighted so far, along with some of the approaches we are advocating as "good practice," we now provide a brief review of the behavioral ecology of zebra finches from an animal personality perspective. Although studies of the zebra finch have made a disproportionate contribution to a number of fields in animal behavior and evolutionary biology ( Griffith and Buchanan, 2010), and have already been the focus of around 15 publications relating to variation in personality in captive populations, we are only recently developing an understanding of the ecology of wild populations. There are a number of aspects of the life-history and behavior of the wild zebra finch that have the potential to influence the way that studies of personality variation in this species are approached and interpreted. A brief review of some of these issues, for a bird that has already been the focus of more empirical work than almost any other single species in the field of animal personality variation, should help to focus attention on the importance of a careful consideration of species ecology and behavior for future studies in any species from this perspective. The contrast between recent work on personality in this captive model species (largely conducted on individually assayed zebra finches in a relatively simple and predator-free captive environment), with the complex social ecology of the wild bird highlights issues that are likely to be common to many species that have been, or will become, the focus of further work in this area. Whilst the differences will not perhaps as extreme as those between captive domesticated zebra finches and their wild free-living counterparts, it is still very easy to lose sight of the way that free-living individuals operate, when we are capturing them and assaying them in isolation. Specifically we identify two important considerations in the extent to which individuals operate on their own or in a social context, and the pattern of variation in behavioral traits across a population.

The Effect of Social Isolation

In the wild, zebra finches pair for life (probably shortly after reaching sexual maturity) and are almost always in close proximity to their partner, both during reproductive cycles and throughout non-breeding periods ( Mariette and Griffith, 2012a), and have a very low level of infidelity for a passerine ( Griffith et al., 2010). One of the few periods when the pair is out of immediate contact with one another is during the incubation period (when the male and female take turns to separately incubate the eggs). Pairs perform regular and characteristic acoustic duetting behavior ( Elie et al., 2010), and become physiologically stressed when socially isolated, moderating their vocalizations accordingly ( Perez et al., 2012). Above the level of the pair bond, zebra finches will often form associations with other pairs and coordinate their reproductive activity in small colonies with between 1 and 10 other pairs in close proximity ( Mariette and Griffith, 2012b). Given the highly social nature of the wild zebra finch, it is not clear what persistent effects might be caused on domesticated zebra finches by keeping them, or assaying personality variation in social isolation. However, it is interesting that in their study Mainwaring et al. (2011), found birds to have a reduced level of exploratory behavior in social groups than when assayed in isolation. It will be interesting to follow up on these observational findings to test whether, for example this difference may have been driven be anxiety in isolated birds, or the social feedback dynamics that occur in small groups.

The strong pair bond of the wild zebra finch and the level of synchronized behavior between the pair ( Mariette and Griffith, 2012a), also help to place the findings of Schuett and Dall (2009) in a better context. In their study they found that the exploratory behavior of individuals became more similar (coordinated) when birds foraged together in opposite sex pairs (compared to when such behavior was assayed repeatedly on isolated individuals), and this does make sense in a species in which behavior is so tightly integrated between a male and female.

Typically, candidate behavior tests are conducted on individuals held in unfamiliar surroundings and isolated from other conspecifics. This approach does present some challenges for species such as the zebra finch in which individuals are rarely alone, or even more social species such as cooperatively breeding species, that also are rarely alone and have highly coordinated group behavior on a daily basis in, or out of the breeding season (e.g., Sorato et al., 2012). Further work is required to determine the effect of social isolation, or isolation from strongly affiliated individuals, on personality assays and whether this might be introducing persistent or non-random biases across populations. Future studies should certainly consider such effects when designing assays and experimental procedures.

A likely way forward here would be to use ongoing behavioral assays (perhaps conducted on free-living animals: e.g., behavior on artificial food patches), which could be conducted on individuals across a variety of social contexts, to be analyzed with a mixed model approach that would enable researchers to partition out the effects of social context on the repeatability of behavior (e.g., Nakagawa and Schielzeth, 2010). For example, to ask questions such as how does an individual's pattern of exploratory behavior change when it is: (a) with its sexual partner; (b) amongst a group of familiar conspecifics; (c) unfamiliar conspecifics; (d) a potential new sexual partner?

Behavioral and Genetic Structuring within Populations

Zebra finches are opportunistic breeders in the wild and individuals can breed over extended periods of the year, and at a variety of different breeding densities ( Zann, 1996). Recent work has identified two strategies within wild populations, with many birds coordinating and aggregating their reproductive attempts both temporally and spatially with a number of con-specifics in high density colonies, but a notable proportion of the same population choosing to nest singly in very isolated patches ( Mariette and Griffith, 2012b). Pairs nesting in solitary nests were better at finding experimental foraging patches, and were better at adjusting parental care to experimentally enlarged broods than birds following a more colonial nesting strategy ( Mariette and Griffith, 2013). The extent to which these different reproductive strategies are state-dependent (e.g., dependent on condition when first encountering a suitable breeding habitat) is currently unclear however there are no obvious genetic or morphological predictors of the strategy that an individual will follow. These colonial and solitary birds appear to have different information about the environment, and different patterns of sociality and foraging behavior, which are likely to expose them to different risks and adaptive trade-offs. For instance, if high density aggregations of breeding finches attract the nomadic, and opportunistic raptors that occur in the Australian arid zone ( Marchant and Higgins, 1993), solitary breeders may experience lower levels of predation risk, which may encourage higher rates of resource acquisition and better information about local resources. It is difficult to identify whether an individual is a solitary or colonial bird by morphological or molecular markers and therefore it is very difficult to account for, or explore the relationship between this behavioral strategy and personality variation, even though we might anticipate some dependencies. For example, colonial birds might be expected to be highly socially tolerant and be less likely to explore novel habitats asocially, while solitary birds are likely to show lower levels of socialization, be more aggressive, value asocial information more etc.

Furthermore, developing an understanding of these two strategies and how they operate in wild birds can completely switch around the interpretation of observed patterns of personality variation. For example, most of the work on personality variation in captive zebra finches has interpreted variation in performance on open field tests (novel environment assays) as reflecting individual differences in the tendency to take risks: i.e., individual differences in the fitness value of taking a gamble on potential novel opportunities in unfamiliar environments (e.g., Schuett and Dall, 2009; Schuett et al., 2011a, b). However, recognizing that there are these two different lifestyles in wild zebra finches suggests that a more ecologically realistic interpretation might be that "highly exploratory" individuals (i.e., those that move around a novel environment more when alone) are those individuals that perceive the world as less risky (whose prior expectation of risk is lower) and therefore place higher value on local information about resources etc. ( Dall, 2010). By contrast, highly social individuals may not rely on their own acquired knowledge of an environment and be more dependent on the acquisition of social information to identify current ecological opportunities. The challenge here is how we can interpret our results on personality in the absence of such ecological knowledge. For example an individual might be a very poor explorer in it's own right and have a very poor skill set at finding food alone in the environment. However if such low explorers are highly sensitive to social cues, and only ever operate as part of a larger social group then their poor exploratory personality is not necessarily the fitness disadvantage we might initially expect. We need to understand the extent to which individuals operate alone or as part of a larger social structure, and integrate that knowledge as part of the study of animal personality variation. We need to understand how reliant individuals are on each other, and how that relates to personality traits with respect to other aspects of ecology and behavior. There is lots of interesting variation in the degree of individual sociality across and within species with some excellent recent breakthroughs in understanding the neuronal and molecular basis for some of that variation (e.g., Goodson et al., 2009; Goodson and Kingsbury, 2011). Furthermore, the timely emergence of interest in the analyses of animal social networks ( Krause et al., 2009), will allow future studies to integrate the study of personality variation with the social context, or strategies that different individuals within populations take. Such integrative studies will provide excellent opportunities to test some of the ideas proposed by the theoretical literature focused on the effects of social interactions on personality variation (e.g., Dall et al., 2004; McNamara et al., 2009; Schuett et al., 2010; Wolf et al., 2011).

Conclusions

It is of paramount importance to properly understand the species with which you are working before designing a study of personality variation from an evolutionary or behavioral ecology perspective. Personality variation is likely to be there, but it's very easy to overlook if you don't measure it correctly, or are unable to account for behavioral polymorphisms within your species. These might be driven by sex-, or phenotype dependent variation, that may be easy to evaluate, or they might result from cryptic behavioral polymorphisms that are very difficult to identify without a reasonably good understanding of species ecology and evolution. This is a very good reason to follow the approach we advocate here (explicitly based on ecology context), and work with species for which we have a reasonable understanding of basic ecology and behavior, and to think about how we might expect that to affect selection on patterns of personality variation.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Dall, S. R. X. (2010). "Managing risk: the perils of uncertainty," in Evolutionary Behavioral Ecology, ed D. F. Westneat and C. W. Fox (New York, NY: Oxford University Press), 194-206.

Mangel, M., and Stamps, J. (2001). Trade-offs between growth and mortality and the maintenance of individual variation in growth. Evol. Ecol. Res. 3, 583-593.

Pervin, L. A., and John, O. P. (1997). Personality: Theory and Research. New York, NY: Guildford Press.

Zann, R. A. (1996). The Zebra Finch. Oxford: Oxford University Press.

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An empiricist guide to animal personality variation in ecology and evolution

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The study of animal personality variation promises to provide significant new insight into the way that behaviour evolves in animals, along with its ecological and evolutionary influences. We strongly advocate more empirical work in this exciting and rapidly expanding research area, but hope that new studies adopt a more hypothesis-driven and/or experimental approach than seems to be usual at the moment.

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Do opposites attract? Effects of personality matching in breeding pairs of captive giant pandas on reproductive success - ScienceDirect

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Based on novel object tests: 1) pairs similar for Neophobic and dissimilar for Food anticipatory were more likely to have intromission success and produce cubs, 2) dyads composed of males ranked higher on Inactive-Communicative trait than females had significantly more intromission success and cub production than dyads composed of males having lower scores.