Classic evolutionary theory predicts that predation will shift trait means and erode variance within prey species; however, several studies indicate higher behavioral trait variance and trait integration in high-predation populations. These results come predominately from field-sampled animals comparing low- and high-predation sites and thus cannot isolate the role of predation from other ecological factors, including density effects arising from higher predation. Here, we study the role of predation on behavioral trait (co)variation in experimental populations of guppies (Poecilia reticulata) living with and without a benthic ambush predator (Jaguar cichlid) to better evaluate the role of predation and where density was equalized among replicates twice per year. At 2.5 years after introduction of the predators (similar to 10 overlapping generations), 40 males were sampled from each of the six replicate populations and extensively assayed for activity rates, water column use, and latency to feed following disturbance. Individual variation was pronounced in both treatments, with substantial individual variation in means, temporal plasticity, and predictability (inverse residual variance). Predators had little effect on mean behavior, although there was some evidence for greater use of the upper water column in predator-exposed fish. There was greater variance among individuals in water column use in predator-exposed fish, and they habituated more quickly over time; individuals higher in the water column fed slower and had a reduced positive correlation with activity, although again this effect was time specific. Predators also affected the integration of personality and plasticity-among-individual variances in water column use increased, and those in activity decreased, through time-which was absent in controls. Our results contrast with the extensive guppy literature showing rapid evolution in trait means, demonstrating either increases or maintenance of behavioral variance under predation.

Wildlife is increasingly exposed to sublethal transient cancer risk factors, including mutagenic substances, which activates their anti-cancer defences, promotes tumourigenesis, and may negatively impact populations. Little is known about how exposure to cancer risk factors impacts the behaviour of wildlife. Here, we investigated the effects of a sublethal, short-term exposure to a carcinogen at environmentally relevant concentrations on the activity patterns of wild Girardia tigrina planaria during a two-phase experiment, consisting of a 7-day exposure to cadmium period followed by a 7-day recovery period. To comprehensively explore the effects of the exposure on activity patterns, we employed the double hierarchical generalized linear model framework which explicitly models residual intraindividual variability in addition to the mean and variance of the population. We found that exposed planaria were less active compared to unexposed individuals and were able to recover to pre-exposure activity levels albeit with a reduced variance in activity at the start of the recovery phase. Planaria showing high activity levels were less predictable with larger daily activity variations and higher residual variance. Thus, the shift in behavioural variability induced by an exposure to a cancer risk factor can be quantified using advanced tools from the field of behavioural ecology. This is required to understand how tumourous processes affect the ecology of species.

In recent years, many studies have investigated the potential state dependence of individual differences in behaviour, with the aim to understand the proximate and ultimate causes and consequences of animal personality. Among the potential state variables that could affect behavioural expression is size and mass, but few studies have found associations at the among-individual levels. Insufficient sampling and incorrect analysis of data are cited as impediments to detecting correlations, if they exist. Here, we conducted a study using 100 pillbugs ( Armadillidium vulgare ) and assayed their defensive behaviour 24 times each over time and across familiarity contexts, to test the asset protection hypothesis that predicts a negative correlation between boldness and mass, and with increases in mass over time. Multivariate mixed models revealed that despite mostly consistent individual behavioural differences over time (modest slope variance) and across contexts (near-parallel reaction norms), and 18-fold range in starting mass, there was no correlation between individual mean mass and boldness. However, individuals that gained more mass over time may have been more ‘shy’ compared to those gaining less mass, but the correlation was weak and observed variation in mass gain was small. There was also a mean level trend of increasing shyness over time that was coincident with mean level mass increases over time. Together, our study provides weak evidence for the asset protection hypothesis, whereby individuals that accumulate more resources are thought to protect them through risk averse behaviour. Significance statement Individual variation in ‘state’, such as mass or energy reserves, is thought to be a predictor of individual differences in behaviour that are consistent over time. However, few studies reveal such links, and several studies suggest insufficient sampling may explain null results in most studies. We studied 100 animals sampled 24 times each in a controlled setting to reveal stable individual differences in mean behaviour over time and across contexts; however, individual behaviour was unrelated to large differences in individual mass but weakly related to increases in mass through time whereby individuals became more shy and those growing faster were somewhat more shy. Our results provide little evidence for the asset protection hypothesis.

Spatial cognitive abilities allow individuals to remember the location of food patches, predator hide-outs, or shelters. Animals typically incorporate learnt spatial information or use external environmental cues to navigate their surroundings. A spectacular example of how some fishes move is through aerial jumping. For instance, fish that are trapped within isolated pools, cut off from the main body of water during dry periods, may jump over obstacles and direct their jumps to return to safe locations. However, what information such re-orientation behaviour during jumping is based on remains enigmatic. Here we combine a lab and field experiment to test if guppies ( Poecilia reticulata ) incorporate learnt spatial information and external environmental cues (visual and auditory) to determine where to jump. In a spatial memory assay we found that guppies were more likely to jump towards deeper areas, hence incorporating past spatial information to jump to safety. In a matched vs. mismatched spatial cue experiment in the field, we found that animals only showed directed jumping when visual and auditory cues matched. We show that in unfamiliar entrapments guppies direct their jumps by combining visual and auditory cues, while in familiar entrapments they use a cognitive map. We hence conclude that jumping behaviour is a goal-directed behaviour, guided by different sources of information and involving important spatial cognitive skills.

Behavioural studies have shown that even after accounting for individual differences in contextual and temporal plasticity, considerable unexplained (residual) variation remains. Recent studies show that individuals differ in the magnitude of residual variation (=their predictability), but hardly any studies exist that assess whether this individual attribute itself is repeatable and potentially subject to selection, and whether predictability is related to aspects of different underlying state variables. Using data on the latency to emerge after disturbance of 100 pill bugs, Armadillidium vulgare, measured 24 times each over time and across contexts, we found substantial among-individual variation in mean boldness (latency) and in their behavioural predictability. Individual mean boldness across weeks was highly consistent over time, as was individual predictability; by contrast, unadjusted repeatability of boldness scores (the familiar ‘intraclass correlation’) and repeatability adjusted for time-related behavioural changes were low to moderate, indicating substantial residual variation. Individual mean boldness was not related to individual predictability, indicating that while selection can potentially act on individual means and individual variances, correlated selection is unlikely, for the traits assessed. Neither boldness nor predictability in boldness was related to mass or to sex, nor did they vary over time concurrent with gains in mass under ad libitum food conditions and in experience with the behavioural assay, indicating they were not clearly related to these potentially important life history and state variables.

Cognitive and sensory abilities are vital in affecting survival under predation risk, leading to selection on brain anatomy. However, how exactly predation and brain evolution are linked has not yet been resolved, as current empirical evidence is inconclusive. This may be due to predation pressure having different effects across life stages and/or due to confounding factors in ecological comparisons of predation pressure. Here, we used adult guppies ( Poecilia reticulata ) to experimentally test how direct predation during adulthood would impact the relative brain size and brain anatomy of surviving individuals to examine if predators selectively remove individuals with specific brain morphology. To this end, we compared fish surviving predation to control fish, which were exposed to visual and olfactory predator cues but could not be predated on. We found that predation impacted the relative size of female brains. However, this effect was dependent on body size, as larger female survivors showed relatively larger brains, while smaller survivors showed relatively smaller brains when compared to control females. We found no differences in male relative brain size between survivors and controls, nor for any specific relative brain region sizes for either sex. Our results corroborate the important, yet complex, role of predation as an important driver of variation in brain size.

Behavioral and physiological ecologists have long been interested in explaining the causes and consequences of trait variation, with a focus on individual differences in mean values. However, the majority of phenotypic variation typically occurs within individuals, rather than among individuals (as indicated by average repeatability being less than 0.5). Recent studies have further shown that individuals can also differ in the magnitude of variation that is unexplained by individual variation or environmental factors (i.e., residual variation). The significance of residual variation, or why individuals differ, is largely unexplained, but is important from evolutionary, methodological, and statistical perspectives. Here, we broadly reviewed literature on individual variation in behavior and physiology, and located 39 datasets with sufficient repeated measures to evaluate individual differences in residual variance. We then analyzed these datasets using methods that permit direct comparisons of parameters across studies. This revealed substantial and widespread individual differences in residual variance. The magnitude of individual variation appeared larger in behavioral traits than in physiological traits, and heterogeneity was greater in more controlled situations. We discuss potential ecological and evolutionary implications of individual differences in residual variance and suggest productive future research directions.

In the evolutionary transition from solitary to group living, it should be adaptive for animals to respond to the environment and choose when to socialize to reduce conflict and maximize access to resources. Due to the associated proximate mechanisms (e.g. neural network, endocrine system), it is likely that this behavior varies between individuals according to genetic and non-genetic factors. We used long-term behavioral and genetic data from a population of eastern water dragons (Intellagama lesueurii) to explore variation in plasticity of social behavior, in response to sex ratio and density. To do so, we modeled individual variation in social reaction norms, which describe individuals' mean behavior and behavioral responses to changes in their environment, and partitioned variance into genetic and non-genetic components. We found that reaction norms were repeatable over multiple years, suggesting that individuals consistently differed in their behavioral responses to changes in the social environment. Despite high repeatability of reaction norm components, trait heritability was below our limit of detection based on power analyses (h2 < 0.12), leading to very little power to detect heritability of plasticity. This was in contrast to a relatively greater amount of variance associated with environmental effects. This could suggest that mechanisms such as social learning and frequency-dependence may shape variance in reaction norms, which will be testable as the dataset grows.

Predation risk during early ontogeny can impact developmental trajectories and permanently alter adult phenotypes. Such phenotypic plasticity often leads to adaptive changes in traits involved in anti-predator responses. While plastic changes in cognition may increase survival, it remains unclear whether early predation experience shapes cognitive investment and drives developmental plasticity in cognitive abilities. Here, we show that predation risk during early ontogeny induces developmental plasticity in two cognitive domains. We reared female guppies (Poecilia reticulata) with and without predator cues and tested their adult cognitive abilities. We found that females reared under simulated predation took longer to learn a simple association task, yet outperformed animals reared without predation threat in a reversal learning task testing cognitive flexibility. These results show that predation pressure during ontogeny shapes adult cognitive abilities, which we argue is likely to be adaptive. Our study highlights the important role of predator-mediated developmental plasticity on cognitive investment in natural populations and the general role of plasticity in cognitive performance.

Quantifying individual variation in labile physiological or behavioral traits often involves repeated measures through time, so as to test for consistency of individual differences (often using repeatability, "R") and/or individual differences in trendlines over time. Another form of temporal change in behavior is temporal autocorrelation, which predicts observations taken closely together in time to be correlated, leading to nonrandom residuals about individual temporal trendlines. Temporal autocorrelation may result from slowly changing internal states (e.g., hormone or energy levels), leading to slowly changing behavior. Autocorrelation is a well-known phenomenon, but has been largely neglected by those studying individual variation in behavior. Here, we provide two worked examples which show substantial temporal autocorrelation (r > 0.4) is present in spontaneous activity rates of guppies (Poecilia reticulata) and house mice (Mus domesticus) in stable laboratory conditions, even after accounting for temporal plasticity of individuals. Second, we show that ignoring autocorrelation does bias estimates of R and temporal reaction norm variances upwards, both in our worked examples and in separate simulations. This bias occurs due to the misestimation of individual-specific means and slopes. Given the increasing use of technologies that generate behavioral and physiological data at high sampling rates, we can now study among- and within-individual changes in behavior in more detailed ways, including autocorrelation, which we discuss from biological and methodological perspectives and provide recommendations and annotated R code to help researchers implement these models on their data.

The study of behavioral syndromes aims to understand among-individual correlations of behavior, yielding insights into the ecological factors and proximate constraints that shape behavior. In parallel, interest has been growing in behavioral plasticity, with results commonly showing that animals vary in their behavioral response to environmental change. These two phenomena are inextricably linked-behavioral syndromes describe cross-trait or cross-context correlations, while variation in behavioral plasticity describes variation in response to changing context. However, they are often discussed separately, with plasticity analyses typically considering a single trait (univariate) across environments, while behavioral trait correlations are studied as multiple traits (multivariate) under one environmental context. Here, we argue that such separation represents a missed opportunity to integrate these concepts. Through observations of multiple traits while manipulating environmental conditions, we can quantify how the environment shapes behavioral correlations, thus quantifying how phenotypes are differentially constrained or integrated under different environmental conditions. Two analytical options exist which enable us to evaluate the context dependence of behavioral syndromes-multivariate reaction norms and character state models. These models are largely two sides of the same coin, but through careful interpretation we can use either to shift our focus to test how the contextual environment shapes trait covariances.

1.Phenotypic plasticity requires animals to acquire reliable environmental information. When multiple sources of information agree, cues should be perceived as reliable and induce a relatively strong response. Conversely, where stimuli conflict, animals must weigh the accuracy of the sources of information and responses should be reduced. 2.Availability of reliable information is often considered a limitation on plasticity, yet how animals integrate seemingly contradictory or incomplete information remains enigmatic, as empirical tests are scarce. 3.We tested how incomplete information determines phenotypic plasticity by simulating predation risk during early ontogeny of guppies (Poecilia reticulata). We exposed guppy fry to a combination of visual and/or olfactory cues of the predatory pike cichlid (Crenicichla alta), and monitored growth of the body and brain. After five weeks of exposure, guppies were returned to common no-risk conditions and their activity rates were monitored for four weeks post-treatment. 4.Visual predator exposure more strongly affected development; reducing body size of adult males and increasing brain size in females. However, there was little evidence for the hypothesised additive effect, with the combined treatment not inducing a larger effect than when only receiving olfactory or visual treatments. 5.While there was consistent individual variation in activity rates, this was unaffected by developmental risk and uncorrelated with the growth parameters. 6.Our results demonstrate the differential reliability of cues during development. Visual exposure to a predator was a highly reliable environmental cue, while environmental certainty was unaffected by combined stimuli.

Predation is a near ubiquitous factor of nature and a powerful selective force on prey. Moreover, it has recently emerged as an important driver in the evolution of brain anatomy, though population comparisons show ambiguous results with considerable unexplained variation. Here, we test the reproducibility of reduced predation on evolutionary trajectories of brain evolution. We make use of an introduction experiment, whereby guppies (Poecilia reticulata) from a single high predation stream were introduced to four low predation streams. After 8–9 years of natural selection in the wild and two generations of common garden conditions in the laboratory, we quantified brain anatomy. Relative brain region sizes did not differ between populations. However, we found a general increase and striking variation in relative brain size of introduced populations, which varied from no change to a 12.5% increase in relative brain weight, relative to the ancestral high predation population. We interpret this as evidence for non-parallel evolution, which implies a weak or inconsistent association of relative brain size with fitness in low predation sites. The evolution of brain anatomy appears sensitive to unknown environmental factors, or contingent on either chance events or historical legacies of environmental change.

Interactions between genotypes and environments are central to evolutionary genetics, but such interactions are typically described, rather than predicted from theory. Recent Bayesian models of development generate specific predictions about genotypic differences in developmental plasticity (changes in the value of a given trait as a result of a given experience) based on genotypic differences in the value of the trait that is expressed by naïve subjects. We used these models to make a priori predictions about the effects of an aversive olfactory conditioning regime on the response of Drosophila melanogaster larvae to the odor of ethyl acetate. As predicted, across 116 genotypes initial trait values were related to plasticity. Genotypes most strongly attracted to the odor of ethyl acetate when naïve reduced their attraction scores more as a result of the aversive training regime than those less attracted to the same odor when naïve. Thus, as predicted, the variance across genotypes in attraction scores was higher before than after the shared experience. These results support predictions generated by Bayesian models of development and indicate that such models can be successfully used to investigate how variation across genotypes in information derived from ancestors combines with personal experience to differentially affect developmental plasticity in response to specific types of experience.

This study focuses on the fine scale, moment to moment changes in behaviour of animals. It shows that individuals commonly vary in the extent of their behavioural predictability, and explores potential sources of this variance.

Despite accumulating evidence for individual variation in behavioural plasticity, there is currently little understanding of the causes and consequences of this variation. An outstanding question is whether individual reaction norm (RN) slopes are consistent across different environmental variables—that is, whether an individual that is highly responsive to one environmental variable will be equally responsive to a second variable. Another important and related question is whether RNs are themselves consistently expressed through time or whether they are simply state dependent. Here, we quantified individual activity rates of zebrafish in response to independent manipulations of temperature and food availability that were repeated in discrete ‘bursts’ of sampling through time. Individuals that were thermally responsive were not more responsive to food deprivation, but they did exhibit greater unexplained variation. Individual RN slopes were consistent (repeatable) over time for both temperature (Rslope = 0.92) and food deprivation responses (Rslope = 0.4), as were mean activity rates in the standard environment (Rintercept = 0.83). Despite the high potential lability of behaviour, we have demonstrated consistency of behavioural RN components and identified potential energetic constraints leading to high consistency of thermal RNs and low consistency of food deprivation RNs.

There is a long-standing interest in behavioural ecology, exploring the causes and correlates of consistent individual differences in mean behavioural traits ('personality') and the response to the environment ('plasticity'). Recently, it has been observed that individuals also consistently differ in their residual intraindividual variability (rIIV). This variation will probably have broad biological and methodological implications to the study of trait variation in labile traits, such as behaviour and physiology, though we currently need studies to quantify variation in rIIV, using more standardized and powerful methodology. Focusing on activity rates in guppies (Poecilia reticulata), we provide a model example, from sampling design to data analysis, in how to quantify rIIV in labile traits. Building on the doubly hierarchical generalized linear model recently used to quantify individual differences in rIIV, we extend the model to evaluate the covariance between individual mean values and their rIIV. After accounting for time-related change in behaviour, our guppies substantially differed in rIIV, and it was the active individuals that tended to be more consistent (lower rIIV). We provide annotated data analysis code to implement these complex models, and discuss how to further generalize the model to evaluate covariances with other aspects of phenotypic variation.