Increases in average global temperatures have caused researchers to revisit how species and populations are expected to respond to changing temperatures. Allen's rule and Bergmann's rule describe two ecogeographic patterns where species in high (cold) latitudes have shorter limbs and larger bodies, respectively, than species at low (warm) latitudes. This pattern is purported to be due to the improved heat retention of short-limbed, large bodies, and improved heat dissipation of long-limbed, small bodies. While Allen's and Bergmann's rules are generally assumed to reflect adaptive outcomes, we sought to investigate the role of developmental plasticity in response to rearing temperature in producing these expected morphologies. To do so, we conducted a systematic review and meta-analysis to test the hypotheses that body shape and size will change plastically in response to experimentally manipulated thermal rearing environments and conform to the patterns predicted by Allen's and Bergmann's rules. Via a phylogenetic meta-analysis, we examined the relationship between temperature experienced by subjects during early life and subsequent body shape and size metrics. Our analysis of 40 studies included 243 estimates from 4 mammal species and 21 bird species, with some species contributing multiple estimates. Developmental plasticity generally produced morphologies in line with Allen's rule, though not Bergmann's rule. Changes in morphology were more prominent under artificially cold conditions than warm conditions. Mammals were generally more responsive than birds, though birds were better-represented in our final dataset. These results suggest that developmental plasticity may contribute to the ability of populations to respond to climate change and that broader biogeographical patterns may emerge from plastic responses.

Meta-analysis is a powerful tool for synthesizing behavioural research and identifying general patterns. However, we should consider if the conclusions we draw from these analyses are truly representative across animal groups, or whether our conclusions are shaped by taxonomic biases in the underlying research. For example, in animal behaviour, vertebrates are over-represented in the research we conduct. The occurrence of this taxonomic imbalance raises concerns about the validity of generalizations drawn in the field. To study this issue, we examined the meta-analyses published in Animal Behaviour, Behavioral Ecology and Behavioral Ecology and Sociobiology from 2000-2024. We then conducted a 'meta-meta-analysis' to calculate the degree to which overall effects in prior meta-analytical results may have been misestimated owing to taxonomic bias. We found that taxonomic biases in the primary research strongly influence effect size estimates in meta-analyses and may lead to improper inferences and generalizations. On average, meta-analytical averages are significantly misestimated and taxonomic bias also results in apparent changes in statistical significance. Because meta-analyses aggregate data, they propagate the biases present in an area of research, leading to potentially incorrect generalizations. Addressing this taxonomic bias is critical for generalizations that describe the true richness of animal behaviour. (c) 2026 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Urbanization causes fundamental changes to natural environments, causing rapid and substantial adaptive phenotypic change in wild populations. While many studies have investigated how urbanization may shape interspecific behavioural variation, for example, via urban environmental filtering, no study has yet quantitatively assessed broad, global patterns of urban-associated intraspecific behavioural variation. Here, we conducted a phylogenetic meta-analysis to assess urban-associated behavioural differences in wild populations of birds, mammals, amphibians, reptiles and insects. We focused on four commonly measured behaviours (boldness, aggressiveness, activity, exploration) and extracted paired urban-nonurban effect size estimates for behavioural means and variances (k = 279), repeatability (k = 13) and correlations (k = 14) from 81 unique studies. We found evidence that urban populations exhibited heightened average boldness, aggressiveness, exploration and activity compared to nonurban conspecifics, a result that was robust across geographic regions and ecological niches. However, avian species were strongly overrepresented in our meta-analysis (N = 49 studies) compared to other taxa (Mammalia, N = 20; Reptilia, N = 7; Insecta, N = 3; Amphibia, N = 2). Consequently, most behaviours in non-avian taxa were under-sampled, and effect sizes were generally not statistically significant: among non-avian species, only boldness differed significantly between urban and nonurban populations. This strong taxonomic bias potentially affects our other inferences as well. We did not find strong evidence linking urbanization to changes in behavioural variation, repeatability or correlations. Our results summarize data from the rapidly growing field of urban evolutionary ecology and demonstrate geographically widespread differences in behaviour between urban and nonurban populations. These patterns suggest that urban populations experience parallel directional selection or that urban invaders experience environmental filtering by common urban conditions that favour certain behavioural types. Taxonomic biases and methodological heterogeneity continue to limit inference in the field, constraining our ability to test preregistered hypotheses in this study. Broadening research to include understudied taxa such as invertebrates, herpetofauna and nocturnal species; incorporating common-garden approaches; and emphasizing clearer definitions for behaviour and urbanization will yield a more comprehensive understanding of how urbanization shapes animal behaviour and other ecologically meaningful phenotypes.

Repeatability, more generally known as intraclass correlation, represents an important quantity of interest in many scientific fields. It represents a metric for summarizing variance decomposition to identify sources of variation in an outcome of interest (e.g. organismal traits). The estimation of variance components is often achieved through linear mixed-effects models or their extension, generalized linear mixed-effects models. Here, we review variants of calculating repeatabilities from mixed-effects models for a variety of conditions and applications. We also recommend which variant might be appropriate under what conditions, focusing on behavioural biology/ecology examples. However, the decision is ultimately with the researcher, since it depends upon their research question, and there is no one-size-fits-all solution. We also highlight the importance of the scope of inference, which affects how repeatabilities are used and interpreted. We recommend transparent reporting of statistical results, including all variance components, which are the building blocks of repeatability. This review aims to assist empiricists in choosing an appropriate repeatability variant and interpretation concerning their questions and the scope of inference.

Abstract The ability of prey to eavesdrop on predator vocalizations is expected to increase survival by reducing detection and capture. Unfortunately, most research has been conducted in vertebrates, and little is known about this ability in invertebrates. We measured latency to emerge, overall activity, and shelter visits in wild-caught fall field crickets ( Gryllus pennsylvanicus ) in response to acoustic playback. Stimuli included multiple predator vocalizations, non-predator vocalizations, white noise, and a control. We predicted that crickets would reduce activity, spend more time in shelter, and freeze in response to stimuli representing greater risk. Contrary to our predictions, crickets traveled greater distances, spent more time moving, and spent less time in shelter in response to predator vocalizations versus controls. We did not, however, find clear differences in responses between predator vocalizations and other treatments. Our results suggest that crickets may not differentiate between the vocalizations of predators, non-predators, and other abrupt sounds. Consequently, eavesdropping may not be a viable method of assessing predation risk for this species and its general use remains unclear.

1. Animal ecologists frequently quantify variance in hierarchically structured traits in wild populations. Importantly, phenotypic plasticity within the period of measurement can modify the trait of interest in response to various unmeasured, temporally or spatially changeable, environmental conditions. Non-random sampling among units of the random effect (e.g. individuals) regarding the environment at issue may lead to estimates of the variance among (partial derivative(2)(I)) or within (partial derivative(2)(W)) such units that conflate several types of processes. This mixing of underlying biology can affect interpretations of the random effect variance. Here, we explore the conditions leading to this situation and assess potential solutions when relevant information is missing. 2. We simulated a trait's phenotypic values that depended on the environmental variable, and individuals that differed in their deviation to the mean population phenotype (random intercepts). We also simulated different types of variation in an environmental variable that was either shared or specific to each individual. We then varied the repeatability in the timing of sampling (R-IS(2)) and analysed simulated datasets using linear mixed-effect models with different fixed-and random-effect structures. 3. In the presence of unmeasured environmental factors, the estimated among-individual variance (partial derivative(2)(I)) contained a larger signature of the current environment as the strength of the temporal autocorrelation and the repeatability in the timing of sampling (R-IS(2)) increased. For low to moderate values of R-IS(2)(e.g. <60% of the total variance in our simulations) the risk of pre-study and within-study effects conflating estimates of variance components was low and could easily be corrected with a model including period or individual-period combination as random effects. Higher R(IS)(2)led to an increase in conflating effects that were difficult to correct. 4. Our study shows the importance of limiting the variance among individuals in the timing structure of sampling (R-IS(2)). We recommend researchers estimate R(IS)(2)and report it in papers. Finally, R(IS)(2)can be limited by sampling all individuals in the same period, or sensitivity analyses could be conducted by removing extreme sampling dates at the analysis stage to reduce R-IS(2).

Wild animals typically organize activity around a 24-h day and daily timing across the year is optimized for both survival and reproductive success. Among-individual variation in chronotype, where individuals differ in when they begin or end their active day relative to a cue such as photoperiod, often exists within a population. Both intrinsic and extrinsic factors contribute to this variation and activity patterns may change across and within different life-history stages as energetic investment changes. Here we describe population level changes in free-living female great tit (Parus major) activity patterns of onset and offset of activity as well as assess variation and repeatability in daily activity both within- and across-breeding stages. We fitted individual females with accelerometers to track activity prior to nest building through chick rearing. Prior to clutch initiation females began their active day before sunrise, however, in the days prior to laying their first egg, activity was delayed until after sunrise. Females ended activity prior to sunset across the monitoring period and earliest during egg laying and incubation. In addition, females exhibited greater among- and within-individual variance in activity during parental care. Female daily activity was moderately repeatable within breeding stages and strongly covaried across several breeding stages. These findings expand our understanding of individual variation in activity patterns during reproduction and the potential fitness implications of chronotype in wild animals. Breeding birds experience differing priorities as they transition through nest building, mating, egg laying, and caring for young. Using accelerometer data loggers, we show that individual female Great Tits change their daily activity patterns across the reproductive season. However, early birds remain earlier relative to others. During the pre-breeding season and before laying eggs, females begin their daily activity before sunrise, while they delay activity onset during subsequent reproductive stages as they engage in parental care.

In many species, males produce signals to attract females. However, in some species and populations, only some males produce these signals, with other males competing for and intercepting reproductive opportunities. In these systems, at least three tactics are expected: Always Signal, signal only when others are not (Assess) and Never Signal. The expected representation of these tactics within a population is frequently unknown in part because the costs of signalling (C) and the fitness value of a single reproductive bout (V) are difficult to quantify. Using a game-theoretic model, we predicted that the Always Signal strategy should only be present in a population if the fitness value of calling is greater than twice the cost (2C < V). We found that males that Always Signal are apparently absent in decorated crickets, Gryllodes sigillatus, at least in our sampling of a laboratory-housed population. Moreover, males were not strict assessors and instead signalled infrequently (30% of the time) when signalling by others was constant. Males also exhibited substantial among-individual variation in the propensity to call when other males were not signalling (t 1/4 0.3). Our results indicate a high relative cost of signalling (2C > V). The presence of among-individual variation in propensity to call is also suggestive of underlying genetic variation and a mixed evolutionarily stable strategy. More generally, the apparent high cost of signalling and the presence of variation in calling propensity suggest that reduced-cost strategies should spread quickly in populations. (c) 2024 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Many biological features are expressed as 'time-to-event' traits, such as time to first reproduction or time to first response to some stimulus. The analysis of these traits frequently produces right-censored data in cases where no event has occurred within a certain time frame. The Cox proportional hazards (CPH) model, a type of survival analysis, accounts for censored data by estimating the hazard of an event occurring at each time point. While random effect variances can be estimated in CPH models, it is currently not possible to estimate within-cluster variance. Consequently, we lack a general method for calculating ecologically and evolutionary relevant variances and metrics like repeatability from time-toevent data. We here present a solution to this issue. We first describe the characteristics of CPH models and introduce repeatability as an intraclass correlation coefficient (ICC). We demonstrate how CPH models with discrete time intervals are comparable to binomial generalized linear mixed-effects models (GLMMs) with the complementary log-log link. Through this equivalence, we show how to estimate an ICC using the estimates of the random effects variance component(s) resulting from CPH models and the distribution-specific variance (within-cluster variance) from the binomial GLMM. We provide a case study and online materials to demonstrate how our new method for ICC for time-to-event data can be implemented and used. We conclude that the proposed method will not only generate a standard way to quantify consistent individual differences (ICC) from time-to-event data, but also broaden the use of survival analysis outside of the typical implementation for survivorship studies. (c) 2025 The Authors. Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour. This is an open access article under the CC BY license (http://creativecommons.org/licenses/ by/4.0/).

Social partners frequently resemble each other. These correlations between the phenotypes of interacting individuals (e.g., social partners, group members, etc.) can be caused by multiple processes. These processes include joint plasticity in response to shared environments, plasticity in response to partner phenotype, and genetic similarity arising from nonrandom assortment due to clustered relatives, spatiotemporal stratification, and partner choice. Although social plasticity and nonrandom assortment can influence evolutionary dynamics, these two processes have most often been studied separately, and disentangling the causes of partner resemblance in observational datasets can be challenging. Furthermore, standard statistical models of social plasticity do not allow for potential social feedback between partners' phenotypes, and estimating joint plasticity to shared environmental effects requires environmental data that is rarely available. We assessed the performance of several statistical models to estimate nonrandom assortment and social plasticity in observational datasets, using simulations of a socially monogamous species, in which nonrandom mating, social plasticity (with or without feedback) and joint plasticity occurred alone or simultaneously. Standard "variance-partitioning approaches" retrieved biased estimates except when the process they aimed to estimate occurred on its own. By contrast, a recently proposed statistical model explicitly including social plasticity as a dynamic process generating feedback between partners' phenotypes (the so-called social animal model) performed best even in scenarios with multiple co-occurring processes. While we recommend empiricists use this latter approach, we also highlight the importance of appropriate sampling designs given the study question and system, and using simulations to assess model performance in realistic scenarios.

Behavioral variation is typically assumed to arise from the combination and interaction of genetic and environmental variation. However, recent work with genetically identical individuals has found that substantial behavioral individuality is expressed even when genetic and environmental variation are negligible. This surprising result requires direct testing of our standard model for the sources of behavioral individuality. Here, we tested the standard model by comparing among-individual variation in highly inbred crickets versus outbred crickets. Comparing inbred and outbred lines allows for direct testing of the standard model by contrasting the magnitude of among-individual variation in a uniform versus varied genetic background. We found substantial and significant differences in among-individual variances, with among-individual variances being roughly three times greater in outbred versus inbred crickets (posterior probability, p = 0.974). Repeatability was also significantly different between inbred and outbred crickets (0.15 versus 0.41, respectively; p = 0.984). This result supports our standard model and suggests that the surprising expression of behavioral variation in clonal and parthenogenic species may represent an important but unique pathway for the expression of behavioral individuality. ### Competing Interest Statement The authors have declared no competing interest. U.S. National Science Foundation, https://ror.org/021nxhr62, 1557951, 2216605

Urbanization is causing fundamental changes to natural environments, effecting rapid and substantial adaptive phenotypic change in wild populations. While a large body of work has investigated how urbanization may shape interspecific variation in behavioral traits, such as via urban environmental filtering, no study has yet quantitatively assessed global patterns of urban-associated intraspecific behavioral variation. Here, we conducted a phylogenetic meta-analysis to assess urban-associated behavioral differences in wild populations of birds, mammals, amphibians, reptiles, and insects. We focused on four commonly measured behaviors (boldness, aggression, activity, and exploration) and extracted paired urban-nonurban effect size estimates for phenotypic means and variances ( k = 278), behavioral repeatability ( k = 13), and behavioral correlations ( k = 14) from 80 studies. We found clear evidence that urban populations exhibit heightened average boldness, aggression, exploration, and activity compared to nonurban conspecifics, a result that was robust among species, geographic region, and ecological niche. Further, our results suggested that “generalist” species have the strongest behavioral responses. Conversely, we did not find strong evidence linking urbanization to changes in phenotypic variation, behavioral repeatability, or behavioral correlations. Our results summarize data from a rapidly evolving field in urban ecology and demonstrate geographically and taxonomically widespread differences in behavior between urban and nonurban populations, suggesting parallel natural selection across urban species and populations.### Competing Interest StatementThe authors have declared no competing interest.

Blows and Hoffmann (2005) and others have suggested that low levels of genetic variation in some dimensions of an additive genetic variance-covariance matrix (G) will be detectable as eigenvalues approaching zero. These dimensions may be indicative of trade-offs (Blows and Hoffmann 2005) or, potentially, of "holes" in fitness landscapes (Dochtermann et al. 2023). However, because the estimation of G typically constrains variances to be positive, and matrices to therefore be positive definite, "approaching zero" is challenging to statistically define. It is, therefore, not currently clear how to statistically identify dimensions with effectively zero variances. Being able to identify dimensions of G with variances approaching zero would improve our ability to understand trade-offs which, typically and inappropriately, focus on the signs of bivariate correlations (Houle 1991). Viable approaches would also allow better understanding of the structure of G and the evolutionary processes that have shaped G across taxa. Mezey and Houle (2005) and Kirkpatrick and Lofsvold (1992) used matrix rank to determine if there were dimensions lacking variation. Rank is the number of eigenvalues for a matrix that are greater than zero. If a G's rank is less than its dimensionality, this would be evidence that there are dimensions without variation. However, most contemporary analysis procedures force estimates of G to be positive semi-definite. Consequently, estimated Gs will not have eigenvalues of 0 or negative. Therefore, the estimated eigenvalues on their own will not allow the identification of absolute constraints (sensu Houle 2001) or more generally dimensions lacking variation. One alternative would be to compare the eigenvalues of observed matrices to those of random matrices and, if there were dimensions with less variation than expected by chance, this comparison could be used to identify dimensions in which evolution is constrained. If trade-offs or landscape holes result in dimensions of G that have minimal variance, we would expect that the associated eigenvalues exhibit less variation than expected by chance. Here, I tested whether the distribution of eigenvalues from randomly generated correlated matrices can be used for such testing. ### Competing Interest Statement The authors have declared no competing interest.

Assessing the biological relevance of variance components estimated using MCMC-based mixed-effects models is not straightforward. Variance estimates are constrained to be greater than zero and their posterior distributions are often asymmetric. Different measures of central tendency for these distributions can therefore be very different, and credible intervals cannot overlap zero, making it difficult to assess the the size and statistical support for among-group variance. This is often done through visual inspection of the whole posterior distribution, and so relies on subjective decisions for interpretation. We use simulations to demonstrate the difficulties of summarising the posterior distributions of variance estimates from MCMC-based models. We compare commonly used summary statistics of posterior distributions of variance components showing that the posterior median is predominantly the least biased. We also describe different methods for generating null distributions (i.e. a distribution of effect sizes that would be obtained if there was no among-group variance) that can be used to aid in the interpretation of variance estimates. We further show how null distributions could be used to derive a p-value that provides complimentary information to the commonly presented measures of central tendency and uncertainty and also facilitates the implementation of power analyses within an MCMC framework.

Plasticity is a major feature of behavior and particularly important for how animals respond to predators. While animals frequently show plastic responses when directly exposed to predators, with these exposures even leading to permanent behavioral changes and transgenerational effects, whether indirect cues of predator presence can elicit similarly severe responses is unclear. We exposed banded crickets ( Gryllodes siglattus ) to cues of predator presence throughout development and compared their behavior—as well as the behavior of their offspring—to individuals who had not been reared in the presence of predator cues. Contrary to findings in both G. sigilattus and related species, we did not detect either developmental plasticity in the form of differences between adult behavior or differences in offspring behavior. These findings suggest that chronic exposure to cues of predator presence have a substantially different affect on behaviors than does direct exposure to predators. How habituation might interact with developmental plasticity and transgenerational effects requires further investigation.Significance Statement Previous research has established that exposure to predators elicits behavioral plasticity, including life-long effects, as well as transgenerational effects. Here we show that chronic exposure to cues of predator presence throughout development, with a resulting potential for habituation, results in neither differences in adult behavior or transgenerational effects. This suggests an important role for habituation in how plasticity manifests within and between generations### Competing Interest StatementThe authors have declared no competing interest.

How behaviors vary among individuals and covary with other behaviors has been a major topic of interest over the last two decades, particularly in research on animal personality, behavioral syndromes, and trade-offs with life-history traits. Unfortunately, proposed theoretical and conceptual frameworks explaining the seemingly ubiquitous observation of behavioral (co)variation have rarely successfully generalized. For example, the “pace-of-life syndrome hypothesis” proposes that behaviors, life-history, and physiological traits should be correlated in a predictable manner. However, these predictions are not consistently upheld. Two observations perhaps explain this failure: First, phenotypic correlations between behaviors are more strongly influenced by correlated and reversible plastic changes in behavior than by among-individual correlations which stem from the joint effects of genetics and developmental plasticity. Second, while trait correlations are frequently assumed to arise via trade-offs, the observed pattern of correlations is not consistent with simple pair-wise trade-offs. A possible resolution to the apparent inconsistency between observed correlations and a role for trade-offs is provided by state-behavior feedbacks. This is critical because the inconsistency between data and theory represents a major failure in our understanding of behavioral evolution. These two primary observations emphasize the importance of an increased research focus on correlated reversible plasticity in behavior—frequently estimated and then disregarded as within-individual covariances.

An organism’s phenotype has been shaped by evolution but the specific processes have to be indirectly inferred for most species. For example, correlations among traits imply the historical action of correlated selection and, more generally, the expression and distribution of traits is expected to be reflective of the adaptive landscapes that have shaped a population. However, our expectations about how quantitative traits—like most behaviors, physiological processes, and life-history traits—should be distributed under different evolutionary processes are not clear. Here, we show that genetic variation in quantitative traits is not distributed as would be expected under dominant evolutionary models. Instead, we found that genetic variation in quantitative traits across six phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high-dimensional “holey landscapes.” This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped and that traits are integrated in a manner contrary to predictions of dominant evolutionary theory. Our results demonstrate that our understanding of how evolution has shaped phenotypes remains incomplete and these results provide a starting point for reassessing the relevance of existing evolutionary models.

ABSTRACT The influence of a changing climate on the phenology of organisms in a region is dependent on how regional climate cues or modifies the timing of local life history events and how those cues are changing over time. There is extensive evidence of phenolological shifts in flowering time over the past 50 years in response to increasing temperatures in temperate regions, but far less is known about tropical regions where seasonality is less temperature driven. We examined historical datasets of flowering patterns in two guilds of ornithophilous plants in the montane cloud forests of Monteverde, Costa Rica in order to identify environmental cues for flowering in nine species of plant that are important resources for hummingbirds. Bimonthly censuses of flower production were used to quantify flower production during two sampling periods:1981-1983, 1986-1991., the species studied here appear to cue flowering patterns to either accumulated drought units or a combination of accumulated drought units and chill units prior to flowering. These results have implications for how tropical cloud forest plants will respond to climate change to the extent that drought and chill patterns are changing with time.

Individuals frequently differ consistently from one another in their average behaviours (i.e. 'animal personality') and in correlated suites of consistent behavioural responses (i.e. 'behavioural syndromes'). However, understanding the evolutionary basis of this (co)variation has lagged behind demonstrations of its presence. This lag partially stems from comparative methods rarely being used in the field. Consequently, much of the research on animal personality has relied on 'adaptive stories' focused on single species and populations. Here, we used a comparative approach to examine the role of phylogeny in shaping patterns of average behaviours, behavioural variation and behavioural correlations. In comparing the behaviours and behavioural variation for five species of Gryllid crickets, we found that phylogeny shaped average behaviours and behavioural (co)variation. Despite differences among species, behavioural responses and variation were most similar among more closely related species. These results suggest that phylogenetic constraints play an important role in the expression of animal personalities and behavioural syndromes and emphasize the importance of examining evolutionary explanations within a comparative framework.