Hotter is not (always) better: Embracing unimodal scaling of biological rates with temperature.

Rate-temperature scaling relationships have fascinated biologists for nearly two centuries and are increasingly important in our era of global climate change. These relationships are hypothesized to originate from the temperature-dependent kinetics of rate-limiting biochemical reactions of metabolism. Several prominent theories have formalized this hypothesis using the Arrhenius model, which characterizes a monotonic temperature dependence using an activation energy E. However, the ubiquitous unimodal nature of biological temperature responses presents important theoretical, methodological, and conceptual challenges that restrict the promise for insight, prediction, and progress. Here we review the development of key hypotheses and methods for the temperature-scaling of biological rates. Using simulations, we examine the constraints of monotonic models, illustrating their sensitivity to data nuances such as temperature range and noise, and their tendency to yield variable and underestimated E, with critical consequences for climate change predictions. We also evaluate the behaviour of two prominent unimodal models when applied to incomplete and noisy datasets. We conclude with recommendations for resolving these challenges in future research, and advocate for a shift to unimodal models that better characterize the full range of biological temperature responses.

Maintenance of Behavioral Variation under Predation Risk: Effects on Personality, Plasticity, and Predictability.

AbstractClassic 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 (∼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.

GIS-based G × E modeling of maize hybrids through enviromic markers engineering.

Through enviromics, precision breeding leverages innovative geotechnologies to customize crop varieties to specific environments, potentially improving both crop yield and genetic selection gains. In Brazil's four southernmost states, data from 183 distinct geographic field trials (also accounting for 2017-2021) covered information on 164 genotypes: 79 phenotyped maize hybrid genotypes for grain yield and their 85 nonphenotyped parents. Additionally, 1342 envirotypic covariates from weather, soil, sensor-based, and satellite sources were collected to engineer 10 K synthetic enviromic markers via machine learning. Soil, radiation light, and surface temperature variations remarkably affect differential genotype yield, hinting at ecophysiological adjustments including evapotranspiration and photosynthesis. The enviromic ensemble-based random regression model showcases superior predictive performance and efficiency compared to the baseline and kernel models, matching the best genotypes to specific geographic coordinates. Clustering analysis has identified regions that minimize genotype-environment (G × E) interactions. These findings underscore the potential of enviromics in crafting specific parental combinations to breed new, higher-yielding hybrid crops. The adequate use of envirotypic information can enhance the precision and efficiency of maize breeding by providing important inputs about the environmental factors that affect the average crop performance. Generating enviromic markers associated with grain yield can enable a better selection of hybrids for specific environments.

The evolution of developmental thresholds and reaction norms for age and size at maturity.

Developing organisms typically mature earlier and at larger sizes in favorable growth conditions, while in rarer cases, maturity is delayed. The rarer reaction norm is easily accommodated by general life history models, whereas the common pattern is not. Theory suggests that a solution to this paradox lies in the existence of critical size thresholds at which maturation or metamorphosis can commence, and in the evolution of these threshold sizes in response to environmental variation. For example, ephemeral environments might favor the evolution of smaller thresholds, enabling earlier maturation. The threshold model makes two unique and untested predictions. First, reaction norms for age and size should steepen, and even change sign, with decreases in threshold size; second, food reductions at sizes below the threshold should delay maturation, while those occurring after the threshold should accelerate maturation. We test these predictions through food manipulations in five damselfly species that theory suggests should differ in threshold size. The results provide strong support for the threshold model's predictions. In all species, early food reductions delayed maturation, while late reductions accelerated maturation. Reaction norms were steeper, and the effect of food reductions changed from decelerating to accelerating at a much smaller size in species from ephemeral habitats. These results support the view that developmental thresholds can account for the widespread observation of negative correlations between age and size at maturity. Moreover, evolution of the threshold appears to be both predictable and central to the observed diversity of reaction norms for age and size at maturity.

Phenotypic plasticity and thermal efficiency of temperature responses in two conspecific springtail populations from contrasting climates.

Temperature drives adaptation in life-history traits through direct effects on physiological processes. However, multiple life-history traits co-evolve as a life-history strategy. Therefore, physiological limitations constraining the evolution of trait means and phenotypic plasticity can be larger for some traits than the others. Comparisons of thermal responses across life-history traits can improve our understanding of the mechanisms determining the life-history strategies. In the present study, we focused on a soil microarthropod species abundant across the Northern Hemisphere, Folsomia quadrioculata (Collembola), with previously known effects of macroclimate. We selected an arctic and a temperate population from areas with highly contrasting climates - the arctic tundra and a coniferous forest floor, respectively - and compared them for thermal plasticity and thermal efficiency in growth, development, fecundity, and survival across four temperatures for a major part of their life cycle. We intended to understand the mechanisms by which temperature drives the evolution of life-history strategies. We found that the temperate population maximized performance at 10-15 °C, whereas the arctic population maintained its thermal efficiency across a wider temperature range (10-20 °C). Thermal plasticity varied in a trait-specific manner, and when considered together with differences in thermal efficiency, indicated that stochasticity in temperature conditions may be important in shaping the life-history strategies. Our study suggests that adopting a whole-organism approach and including physiological time considerations while analysing thermal adaptation will markedly improve our understanding of plausible links between thermal adaptation and responses to global climate change.

The dynamic response of quorum sensing to density is robust to signal supplementation and individual signal synthase knockouts.

Quorum sensing (QS) is a widespread mechanism of environment sensing and behavioural coordination in bacteria. At its core, QS is based on the production, sensing and response to small signalling molecules. Previous work with Pseudomonas aeruginosa shows that QS can be used to achieve quantitative resolution and deliver a dosed response to the bacteria's density environment, implying a sophisticated mechanism of control. To shed light on how the mechanistic signal components contribute to graded responses to density, we assess the impact of genetic (AHL signal synthase deletion) and/or signal supplementation (exogenous AHL addition) perturbations on lasB reaction-norms to changes in density. Our approach condenses data from 2000 timeseries (over 74 000 individual observations) into a comprehensive view of QS-controlled gene expression across variation in genetic, environmental and signal determinants of lasB expression. We first confirm that deleting either (∆lasI, ∆rhlI) or both (∆lasIrhlI) AHL signal synthase gene attenuates QS response to density. In the ∆rhlI background we show persistent yet attenuated density-dependent lasB expression due to native 3-oxo-C12-HSL signalling. We then test if density-independent quantities of AHL signal (3-oxo-C12-HSL, C4-HSL) added to the WT either flatten or increase responsiveness to density and find that the WT response is robust to all tested concentrations of signal, alone or in combination. We then move to progressively supplementing the genetic knockouts and find that cognate signal supplementation of a single AHL signal (∆lasI +3-oxo-C12-HSL, ∆rhlI +C4HSL) is sufficient to restore the ability to respond in a density-dependent manner to increasing density. We also find that dual signal supplementation of the double AHL synthase knockout restores the ability to produce a graded response to increasing density, despite adding a density-independent amount of signal. Only the addition of high concentrations of both AHLs and PQS can force maximal lasB expression and ablate responsiveness to density. Our results show that density-dependent control of lasB expression is robust to multiple combinations of QS gene deletion and density-independent signal supplementation. Our work develops a modular approach to query the robustness and mechanistic bases of the central environmental sensing phenotype of quorum sensing.

Spring temperature drives phenotypic selection on plasticity of flowering time.

In seasonal environments, a high responsiveness of development to increasing temperatures in spring can infer benefits in terms of a longer growing season, but also costs in terms of an increased risk of facing unfavourable weather conditions. Still, we know little about how climatic conditions influence the optimal plastic response. Using 22 years of field observations for the perennial forest herb Lathyrus vernus, we assessed phenotypic selection on among-individual variation in reaction norms of flowering time to spring temperature, and examined if among-year variation in selection on plasticity was associated with spring temperature conditions. We found significant among-individual variation in mean flowering time and flowering time plasticity, and that plants that flowered earlier also had a more plastic flowering time. Selection favoured individuals with an earlier mean flowering time and a lower thermal plasticity of flowering time. Less plastic individuals were more strongly favoured in colder springs, indicating that spring temperature influenced optimal flowering time plasticity. Our results show how selection on plasticity can be linked to climatic conditions, and illustrate how we can understand and predict evolutionary responses of organisms to changing environmental conditions.

Predicting effects of multiple interacting global change drivers across trophic levels.

Global change encompasses many co-occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction-norm perspective can improve our ability to make predictions of interactions at higher levels of organization-that is, community and food web. Building on the framework of consumer-resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof-of-concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

Inferring temperature adaptation from thermal performance curves of somatic growth rate: The importance of growth measurements and mortality.

When comparing somatic growth thermal performance curves (TPCs), higher somatic growth across experimental temperatures is often observed for populations originating from colder environments. Such countergradient variation has been suggested to represent adaptation to seasonality, or shorter favourable seasons in colder climates. Alternatively, populations from cold climates may outgrow those from warmer climates at low temperature, and vice versa at high temperature, representing adaptation to temperature. Using modelling, we show that distinguishing between these two types of adaptation based on TPCs requires knowledge about (i) the relationship between somatic growth rate and population growth rate, which in turn depends on the scale of somatic growth (absolute or proportional), and (ii) the relationship between somatic growth rate and mortality rate in the wild. We illustrate this by quantifying somatic growth rate TPCs for three populations of Daphnia magna where population growth scales linearly with proportional somatic growth. For absolute somatic growth, the northern population outperformed the two more southern populations across temperatures, and more so at higher temperatures, consistent with adaptation to seasonality. In contrast, for the proportional somatic growth TPCs, and hence population growth rate, TPCs tended to converge towards the highest temperatures. Thus, if the northern population pays an ecological mortality cost of rapid growth in the wild, this may create crossing population growth TPCs consistent with adaptation to temperature. Future studies within this field should be more explicit in how they extrapolate from somatic growth in the lab to fitness in the wild.

The Role of Information in Evolutionary Biology.

The Modern Synthesis has received criticism for its purported gene-centrism. That criticism relies on a concept of the gene as a unit of instructional information. In this paper I discuss information concepts and endorse one, developed from Floridi, that sees information as a functional relationship between data and context. I use this concept to inspect developmental criticisms of the Modern Synthesis and argue that the instructional gene arose as an idealization practice when evolutionary biologists made comment on development. However, a closer inspection of key claims shows that at least some associated with the Modern Synthesis were in fact adopting the data led definition I favour and made clear arguments for the role of developmental processes beyond genetic input. There was no instructional gene.

Past history shapes evolution of reproductive success in a global warming scenario.

Adaptive evolution is critical for animal populations to thrive in the fast-changing natural environments. Ectotherms are particularly vulnerable to global warming and, although their limited coping ability has been suggested, few real-time evolution experiments have directly accessed their evolutionary potential. Here, we report a long-term experimental evolution study addressing the evolution of Drosophila thermal reaction norms, after ∼30 generations under different dynamic thermal regimes: fluctuating (daily variation between 15 and 21 °C) or warming (daily fluctuation with increases in both thermal mean and variance across generations). We analyzed the evolutionary dynamics of Drosophila subobscura populations as a function of the thermally variable environments in which they evolved and their distinct background. Our results showed clear differences between the historically differentiated populations: high latitude D. subobscura populations responded to selection, improving their reproductive success at higher temperatures whereas their low latitude counterparts did not. This suggests population variation in the amount of genetic variation available for thermal adaptation, an aspect that needs to be considered to allow for better predictions of future climate change responses. Our results highlight the complex nature of thermal responses in face of environmental heterogeneity and emphasize the importance of considering inter-population variation in thermal evolution studies.

Unravelling the causes and consequences of dispersal syndromes in a wild passerine.

Evidence accumulates that dispersal is correlated with individual behavioural phenotype (dispersal syndrome). The evolutionary causes and consequences of such covariation depend on the degree of plasticity versus inheritance of the traits, which requires challenging experiments to implement in mobile organisms. Here, we combine a forced dispersal experiment, natural colonization and longitudinal data to establish if dispersal and aggression levels are integrated and to test their adaptive nature in pied flycatchers (Ficedula hypoleuca). We found that (forced) dispersers behaved more aggressively in their first breeding year after dispersal and decreased their aggression in following years. Strength of dispersal syndrome and direction of fecundity selection on aggression in newly colonized areas varied between years. We propose that the net benefits of aggression for dispersers increase under harsh conditions (e.g. low food abundance). This hypothesis now warrants further testing. Overall, this study provides unprecedented experimental evidence that dispersal syndromes can be remodelled via adaptive plasticity depending on the individuals' local breeding experience and/or year-specific ecological conditions. It highlights the importance of individual behavioural variation in population dynamics.

Evidence for evolutionary adaptation of mixotrophic nanoflagellates to warmer temperatures.

Mixotrophs, organisms that combine photosynthesis and heterotrophy to gain energy, play an important role in global biogeochemical cycles. Metabolic theory predicts that mixotrophs will become more heterotrophic with rising temperatures, potentially creating a positive feedback loop that accelerates carbon dioxide accumulation in the atmosphere. Studies testing this theory have focused on phenotypically plastic (short-term, non-evolutionary) thermal responses of mixotrophs. However, as small organisms with short generation times and large population sizes, mixotrophs may rapidly evolve in response to climate change. Here, we present data from a 3-year experiment quantifying the evolutionary response of two mixotrophic nanoflagellates to temperature. We found evidence for adaptive evolution (increased growth rates in evolved relative to acclimated lineages) in the obligately phototrophic strain, but not in the facultative phototroph. All lineages showed trends of increased carbon use efficiency, flattening of thermal reaction norms, and a return to homeostatic gene expression. Generally, mixotrophs evolved reduced photosynthesis and higher grazing with increased temperatures, suggesting that evolution may act to exacerbate mixotrophs' effects on global carbon cycling.

Genomic selection in tropical perennial crops and plantation trees: a review.

To overcome the multiple challenges currently faced by agriculture, such as climate change and soil deterioration, more efficient plant breeding strategies are required. Genomic selection (GS) is crucial for the genetic improvement of quantitative traits, as it can increase selection intensity, shorten the generation interval, and improve selection accuracy for traits that are difficult to phenotype. Tropical perennial crops and plantation trees are of major economic importance and have consequently been the subject of many GS articles. In this review, we discuss the factors that affect GS accuracy (statistical models, linkage disequilibrium, information concerning markers, relatedness between training and target populations, the size of the training population, and trait heritability) and the genetic gain expected in these species. The impact of GS will be particularly strong in tropical perennial crops and plantation trees as they have long breeding cycles and constrained selection intensity. Future GS prospects are also discussed. High-throughput phenotyping will allow constructing of large training populations and implementing of phenomic selection. Optimized modeling is needed for longitudinal traits and multi-environment trials. The use of multi-omics, haploblocks, and structural variants will enable going beyond single-locus genotype data. Innovative statistical approaches, like artificial neural networks, are expected to efficiently handle the increasing amounts of heterogeneous multi-scale data. Targeted recombinations on sites identified from profiles of marker effects have the potential to further increase genetic gain. GS can also aid re-domestication and introgression breeding. Finally, GS consortia will play an important role in making the best of these opportunities. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01326-4.

Phenotypic variation in Xenopus laevis tadpoles from contrasting climatic regimes is the result of adaptation and plasticity.

Phenotypic variations between populations often correlate with climatic variables. Determining the presence of phenotypic plasticity and local adaptation of a species to different environments over a large spatial scale can provide insight on the persistence of a species across its range. Amphibians, and in particular their larvae, are good models for studies of phenotypic variation as they are especially sensitive to their immediate environment. Few studies have attempted to determine the mechanisms that drive phenotypic variation between populations of a single amphibian species over a large spatial scale especially across contrasting climatic regimes. The African clawed frog, Xenopus laevis, occurs in two regions with contrasting rainfall regimes in southern Africa. We hypothesised that the phenotypic variation of life-history traits of X. laevis tadpoles emerges from a combination of plastic and genetic responses. We predicted that plasticity would allow the development of tadpoles from both regions in each environment. We also predicted that local adaptation of larval traits would drive the differentiation of reaction norms between populations and lower survival in tadpoles reared away from their home environment. We measured growth, time to metamorphosis, and survival in a reciprocal transplant experiment using outdoor mesocosms. Supporting our prediction, we found that the measured variation of all traits was explained by both adaptation and plasticity. However, the reaction norms differed between populations suggesting adaptive and asymmetric plasticity. All tadpoles experienced lower survival when translocated, but only translocated tadpoles from the winter rainfall region matched survival of local tadpoles. This has implications for the dynamics of translocated X. laevis into novel environments, especially from the winter rainfall region. Our discovery of their asymmetric capacity to overcome novel environmental conditions by phenotypic plasticity alone provides insight into their invasion success.

Individual differences in habitat selection mediate landscape level predictions of a functional response.

Predicting future space use by animals requires models that consider both habitat availability and individual differences in habitat selection. The functional response in habitat selection posits animals adjust their habitat selection to availability, but population-level responses to availability may differ from individual responses. Generalized functional response (GFR) models account for functional responses by including fixed effect interactions between habitat availability and selection. Population-level resource selection functions instead account for individual selection responses to availability with random effects. We compared predictive performance of both approaches using a functional response in elk (Cervus canadensis) selection for mixed forest in response to road proximity, and avoidance of roads in response to mixed forest availability. We also investigated how performance changed when individuals responded differently to availability from the rest of the population. Individual variation in road avoidance decreased performance of both models (random effects: ß = 0.69, 95% CI 0.47, 0.91; GFR: ß = 0.38, 95% CI 0.05, 0.71). Changes in individual road and forest availability affected performance of neither model, suggesting individual responses to availability different from the functional response mediated performance. We also found that overall, both models performed similarly for predicting mixed forest selection (F1, 58 = 0.14, p = 0.71) and road avoidance (F1, 58 = 0.28, p = 0.60). GFR estimates were slightly better, but its larger number of covariates produced greater variance than the random effects model. Given this bias-variance trade-off, we conclude that neither model performs better for future space use predictions.

Phenotypic plasticity as a cause and consequence of population dynamics.

Predicting complex species-environment interactions is crucial for guiding conservation and mitigation strategies in a dynamically changing world. Phenotypic plasticity is a mechanism of trait variation that determines how individuals and populations adapt to changing and novel environments. For individuals, the effects of phenotypic plasticity can be quantified by measuring environment-trait relationships, but it is often difficult to predict how phenotypic plasticity affects populations. The assumption that environment-trait relationships validated for individuals indicate how populations respond to environmental change is commonly made without sufficient justification. Here we derive a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics. Applying the framework to the classical example of Nicholson's blowflies, we show how seemingly sensible predictions made from environment-trait relationships do not generalise to population responses. As a consequence, trait-based analyses that do not incorporate population feedbacks risk mischaracterising the effect of environmental change on populations.

Ovotestes suggest cryptic genetic influence in a reptile model for temperature-dependent sex determination.

Sex determination and differentiation in reptiles is complex. Temperature-dependent sex determination (TSD), genetic sex determination (GSD) and the interaction of both environmental and genetic cues (sex reversal) can drive the development of sexual phenotypes. The jacky dragon (Amphibolurus muricatus) is an attractive model species for the study of gene-environment interactions because it displays a form of Type II TSD, where female-biased sex ratios are observed at extreme incubation temperatures and approximately 50 : 50 sex ratios occur at intermediate temperatures. This response to temperature has been proposed to occur due to underlying sex determining loci, the influence of which is overridden at extreme temperatures. Thus, sex reversal at extreme temperatures is predicted to produce the female-biased sex ratios observed in A. muricatus. The occurrence of ovotestes during development is a cellular marker of temperature sex reversal in a closely related species Pogona vitticeps. Here, we present the first developmental data for A. muricatus, and show that ovotestes occur at frequencies consistent with a mode of sex determination that is intermediate between GSD and TSD. This is the first evidence suggestive of underlying unidentified sex determining loci in a species that has long been used as a model for TSD.

Parasitism and host dispersal plasticity in an aquatic model system.

Dispersal is a central determinant of spatial dynamics in communities and ecosystems, and various ecological factors can shape the evolution of constitutive and plastic dispersal behaviours. One important driver of dispersal plasticity is the biotic environment. Parasites, for example, influence the internal condition of infected hosts and define external patch quality. Thus, state-dependent dispersal may be determined by infection status and context-dependent dispersal by the abundance of infected hosts in the population. A prerequisite for such dispersal plasticity to evolve is a genetic basis on which natural selection can act. Using interconnected microcosms, we investigated dispersal in experimental populations of the freshwater protist Paramecium caudatum in response to the bacterial parasite Holospora undulata. For a collection of 20 natural host strains, we found substantial variation in constitutive dispersal and to a lesser degree in dispersal plasticity. First, infection tended to increase or decrease dispersal relative to uninfected controls, depending on strain identity, indicative of state-dependent dispersal plasticity. Infection additionally decreased host swimming speed compared to the uninfected counterparts. Second, for certain strains, there was a weak negative association between dispersal and infection prevalence, such that uninfected hosts dispersed less when infection was more frequent in the population, indicating context-dependent dispersal plasticity. Future experiments may test whether the observed differences in dispersal plasticity are sufficiently strong to be picked up by natural selection. The evolution of dispersal plasticity as a strategy to mitigate parasite effects spatially may have important implications for epidemiological dynamics.

State dependence explains individual variation in nest defence behaviour in a long-lived bird.

Parental care, such as nest or offspring defence, is crucial for offspring survival in many species. Yet, despite its obvious fitness benefits, the level of defence can consistently vary between individuals of the same species. One prominent adaptive explanation for consistent individual differences in behaviours involves state dependency: relatively stable differences in individual state should lead to the emergence of repeatable behavioural variation whereas changes in state should lead to a readjustment of behaviour. Therefore, empirical testing of adaptive state dependence requires longitudinal data where behaviour and state of individuals of the same population are repeatedly measured. Here, we test if variation in states predicts nest defence behaviour (a 'risky' behaviour) in a long-lived species, the barnacle goose Branta leucopsis. Adaptive models have predicted that an individual's residual reproductive value or 'asset' is an important state variable underlying variation in risk-taking behaviour. Hence, we investigate how nest defence varies as a function of time of the season and individual age, two state variables that can vary between and within individuals and determine asset. Repeated measures of nest defence towards a human intruder (flight initiation distance or FID) of females of known age were collected during 15 breeding seasons. Increasing values of FID represent increasing shyness. We found that females strongly and consistently differed in FID within- and between-years. As predicted by theory, females adjusted their behaviour to state by decreasing their FID with season and age. Decomposing these population patterns into within- and between-individual effects showed that the state-dependent change in FID was driven by individual plasticity in FID and that bolder females were more plastic than shyer females. This study shows that nest defence behaviour differs consistently among individuals and is adjusted to individual state in a direction predicted by adaptive personality theory.