In this paper we review recent models that provide adaptive explanations for animal personalities: individual differences in behaviour (or suites of correlated behaviours) that are consistent over ...time or contexts. We start by briefly discussing patterns of variation in behaviour that have been documented in natural populations. In the main part of the paper we discuss models for personality differences that (i) explain animal personalities as adaptive behavioural responses to differences in state, (ii) investigate how feedbacks between state and behaviour can stabilize initial differences among individuals and (iii) provide adaptive explanations for animal personalities that are not based on state differences. Throughout, we focus on two basic questions. First, what is the basic conceptual idea underlying the model? Second, what are the key assumptions and predictions of the model? We conclude by discussing empirical features of personalities that have not yet been addressed by formal modelling. While this paper is primarily intended to guide empiricists through current adaptive theory, thereby stimulating empirical tests of these models, we hope it also inspires theoreticians to address aspects of personalities that have received little attention up to now.
Behavioural traits are characterized by their labile expression: behavioural responses can, in principle, be up- and down-regulated in response to moment-to-moment changes in environmental ...conditions. Evidence is accumulating that individuals from the same population differ in the degree and extent of this form of phenotypic plasticity. We here discuss how such between-individual differences in behavioural plasticity can result from additive and interactive effects of genetic make-up and past environmental conditions, and under which conditions natural selection might favour this form of between-individual variation. We highlight how spatial or temporal variation in the environment, in combination with competition among individuals, can promote adaptive individual differences in plasticity; and we detail how differences in plasticity can emerge as a result of selection pressures induced by social interactions or as a response to between-individual differences in state. We further discuss both ecological and evolutionary consequences of individual differences in plasticity. We outline, for example, how individual differences in plasticity can have knock-on effects on the rate of evolution; and how such differences can enhance the stability and persistence of populations.
► Individual differences in responsiveness need an evolutionary explanation. ► We review the proximate and ultimate causation of variation in responsiveness. ► We propose evolutionary and ecological consequences of variation in responsiveness. ► Individual variation in responsiveness likely affects responses to human-induced rapid environmental change.
•A growing number of studies investigate links between metabolic rate and behavior.•A common assumption is that metabolic rate is a proxy for energetic constraints.•We outline why this is false and ...provide guidelines for testing this assumption.•We conclude by highlighting exciting directions for future work in this field.
The number of studies investigating links between among-individual differences in metabolic rate (MR) and behavior has grown dramatically in the past several years. A major and often untested assumption of these studies is that the selected measure of MR is a valid proxy for energetic constraints. We argue that without explicitly testing this assumption, observed patterns between MR and behavior are uninterpretable. We provide guidelines for evaluating how a given measure of MR relates to constraints on the acquisition or expenditure of energy. The approach we advocate will allow researchers to develop and test a priori predictions relating energy metabolism and behavior. We conclude by highlighting several exciting directions for future work in this rapidly growing field.
The ecological factors responsible for the evolution of individual differences in animal personality (consistent individual differences in the same behaviour across time and contexts) are currently ...the subject of intense debate. A limited number of ecological factors have been investigated to date, with most attention focusing on the roles of resource competition and predation. We suggest here that parasitism may play a potentially important, but largely overlooked, role in the evolution of animal personalities. We identify two major routes by which parasites might influence the evolution of animal personality. First, because the risk of acquiring parasites can be influenced by an individual's behavioural type, local parasite regimes may impose selection on personality traits and behavioural syndromes (correlations between personality traits). Second, because parasite infections have consequences for aspects of host ‘state’, parasites might induce the evolution of individual differences in certain types of host behaviour in populations with endemic infections. Also, because infection often leads to specific changes in axes of personality, parasite infections have the potential to decouple behavioural syndromes. Host–parasite systems therefore provide researchers with valuable tools to study personality variation and behavioural syndromes from a proximate and ultimate perspective.
Understanding the evolution of coral endosymbiosis requires a predictive framework that integrates life-history theory and ecology with cell biology. The time has come to bridge disciplines and use a ...model systems approach to achieve this aim.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Growing interest in proximate and ultimate causes and consequences of between‐ and within‐individual variation in labile components of the phenotype – such as behaviour or physiology – characterizes ...current research in evolutionary ecology. The study of individual variation requires tools for quantification and decomposition of phenotypic variation into between‐ and within‐individual components. This is essential as variance components differ in their ecological and evolutionary implications. We provide an overview of how mixed‐effect models can be used to partition variation in, and correlations among, phenotypic attributes into between‐ and within‐individual variance components. Optimal sampling schemes to accurately estimate (with sufficient power) a wide range of repeatabilities and key (co)variance components, such as between‐ and within‐individual correlations, are detailed. Mixed‐effect models enable the usage of unambiguous terminology for patterns of biological variation that currently lack a formal statistical definition (e.g. ‘animal personality’ or ‘behavioural syndromes’), and facilitate cross‐fertilisation between disciplines such as behavioural ecology, ecological physiology and quantitative genetics.
ABSTRACT
Phenotypes vary hierarchically among taxa and populations, among genotypes within populations, among individuals within genotypes, and also within individuals for repeatedly expressed, ...labile phenotypic traits. This hierarchy produces some fundamental challenges to clearly defining biological phenomena and constructing a consistent explanatory framework. We use a heuristic statistical model to explore two consequences of this hierarchy. First, although the variation existing among individuals within populations has long been of interest to evolutionary biologists, within‐individual variation has been much less emphasized. Within‐individual variance occurs when labile phenotypes (behaviour, physiology, and sometimes morphology) exhibit phenotypic plasticity or deviate from a norm‐of‐reaction within the same individual. A statistical partitioning of phenotypic variance leads us to explore an array of ideas about residual within‐individual variation. We use this approach to draw attention to additional processes that may influence within‐individual phenotypic variance, including interactions among environmental factors, ecological effects on the fitness consequences of plasticity, and various types of adaptive variance. Second, our framework for investigating variation in phenotypic variance reveals that interactions between levels of the hierarchy form the preconditions for the evolution of all types of plasticity, and we extend this idea to the residual level within individuals, where both adaptive plasticity in residuals and canalization‐like processes (stability) can evolve. With the statistical tools now available to examine heterogeneous residual variance, an array of novel questions linking phenotype to environment can be usefully addressed.
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve ...complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to accurate and unbiased estimation.
Here we address the consequences of violations in distributional assumptions and the impact of missing random effect components on model estimates. In particular, we evaluate the effects of skewed, bimodal and heteroscedastic random effect and residual variances, of missing random effect terms and of correlated fixed effect predictors. We focus on bias and prediction error on estimates of fixed and random effects.
Model estimates were usually robust to violations of assumptions, with the exception of slight upward biases in estimates of random effect variance if the generating distribution was bimodal but was modelled by Gaussian error distributions. Further, estimates for (random effect) components that violated distributional assumptions became less precise but remained unbiased. However, this particular problem did not affect other parameters of the model. The same pattern was found for strongly correlated fixed effects, which led to imprecise, but unbiased estimates, with uncertainty estimates reflecting imprecision.
Unmodelled sources of random effect variance had predictable effects on variance component estimates. The pattern is best viewed as a cascade of hierarchical grouping factors. Variances trickle down the hierarchy such that missing higher‐level random effect variances pool at lower levels and missing lower‐level and crossed random effect variances manifest as residual variance.
Overall, our results show remarkable robustness of mixed‐effects models that should allow researchers to use mixed‐effects models even if the distributional assumptions are objectively violated. However, this does not free researchers from careful evaluation of the model. Estimates that are based on data that show clear violations of key assumptions should be treated with caution because individual datasets might give highly imprecise estimates, even if they will be unbiased on average across datasets.
ABSTRACT
Energy metabolism has received much attention as a potential driver of repeatable among‐individual differences in behaviour (animal personality). Several factors have been hypothesized to ...mediate this relationship. We performed a systematic review with a meta‐analysis of >70 studies comprised of >8000 individuals reporting relationships between measures of maintenance metabolic rates (i.e. basal metabolic rate, resting metabolic rate, and standard metabolic rate) and behaviour. We evaluated support for three hypothesized mediators: (i) type of behaviour, (ii) opportunities for energy re‐allocation, and (iii) magnitude of energetic constraints. Relationships between measures of maintenance metabolic rate (MR) and behaviour are predicted to be strongest for behaviours with strong consequences for energy turnover (acquisition or expenditure). Consistent with this, we found that behaviours with known consequences for energy gain (e.g. foraging, dominance, boldness) or expenditure (e.g. maximum sprint speed, sustained running speed, maximum distance travelled, etc.) had strong positive correlations with MR, while behaviours with putatively weak and/or inconsistent associations with net energy gain or loss (e.g. exploration, activity, sociability) were not correlated with MR. Greater opportunities for energy reallocation are predicted to weaken relationships between MR and behaviour by creating alternative pathways to balance energy budgets. We tested this by contrasting relationships between MR and behaviour in ectotherms versus endotherms, as thermoregulation in endotherms creates additional opportunities for energy reallocation compared with ectotherms. As predicted, the relationship between behaviour and MR was stronger in ectotherms compared with endotherms. However, statistical analyses of heterogeneity among effect sizes from different species did not support energy re‐allocation as the main driver of these differences. Finally, we tested whether conditions where animals face greater constraints in meeting their energy budgets (e.g. field versus laboratory, breeding versus non‐breeding) increased the strength of the relationship between MR and behaviour. We found that the relationship between MR and behaviour was unaffected by either of these modifiers. This meta‐analysis provides two key insights. First, we observed positive relationships of similar magnitude between MR and behaviours that bring in net energy, and behaviours that cost net energy. This result is only consistent with a performance energy‐management model. Given that the studies included in our meta‐analysis represent a wide range of taxa, this suggests that the performance model may be the most common model in general. Second, we found that behaviours with putatively weak or inconsistent consequences for net energy gain or expenditure (exploration, activity, sociability) show no relationship with MR. The lack of relationship between MR and behavioural traits with weak and/or inconsistent consequences for energy turnover provides the first systematic demonstration of the central importance of the ecological function of traits in mediating relationships between MR and behaviour.
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