The pace-of-life syndrome (POLS) hypothesis specifies that closely related species or populations experiencing different ecological conditions should differ in a suite of metabolic, hormonal and immunity traits that have coevolved with the life-history particularities related to these conditions. Surprisingly, two important dimensions of the POLS concept have been neglected: (i) despite increasing evidence for numerous connections between behavioural, physiological and life-history traits, behaviours have rarely been considered in the POLS yet; (ii) the POLS could easily be applied to the study of covariation among traits between individuals within a population. In this paper, we propose that consistent behavioural differences among individuals, or personality, covary with life history and physiological differences at the within-population, interpopulation and interspecific levels. We discuss how the POLS provides a heuristic framework in which personality studies can be integrated to address how variation in personality traits is maintained within populations.

Summary1. Dispersal and gene flow can have a variety of interacting effects on evolution. These effects can either promote or constrain adaptive divergence through either genetic or demographic routes. The relative importance of these effects is unknown because few attempts have been made to conceptually integrate and test them. 2. We draw a broad distinction between situations with vs. without strong coevolutionary dynamics. This distinction is important because the adaptive peak for a given population is more mobile in the former than in the latter. This difference makes ongoing evolutionary potential more important in the presence of strong coevolutionary dynamics than in their absence. 3. We advance a conceptual integration of the various effects of gene flow and dispersal on adaptive divergence. In line with other authors, but not necessarily for the same reasons, we suggest that an intermediate level of gene flow will allow the greatest adaptive divergence. 4. When dispersal is quite low, we predict that an increase will have positive effects on adaptive divergence, owing to genetic/demographic rescue and 'reinforcement.' The rescue effect may be more important in small populations and in homogeneous environments. The reinforcement effect may be more common in large populations and in heterogeneous environments. 5. Once a certain level of dispersal is reached, we predict that a further increase may have negative effects on adaptive divergence. These effects may arise if carrying capacity is exceeded or maladaptive genes are introduced. 6. Many additional effects remain to be integrated into this framework, and doing so may yield novel insights into the factors influencing evolution on ecological time-scales.

An essential requirement to determine a population's potential for evolutionary change is to quantify the amount of genetic variability expressed for traits under selection. Early investigations in laboratory conditions showed that the magnitude of the genetic and environmental components of phenotypic variation can change with environmental conditions. However, there is no consensus as to how the expression of genetic variation is sensitive to different environmental conditions. Recently, the study of quantitative genetics in the wild has been revitalized by new pedigree analyses based on restricted maximum likelihood, resulting in a number of studies investigating these questions in wild populations. Experimental manipulation of environmental quality in the wild, as well as the use of naturally occurring favourable or stressful environments, has broadened the treatment of different taxa and traits. Here, we conduct a meta-analysis on recent studies comparing heritability in favourable versus unfavourable conditions in non-domestic and non-laboratory animals. The results provide evidence for increased heritability in more favourable conditions, significantly so for morphometric traits but not for traits more closely related to fitness. We discuss how these results are explained by underlying changes in variance components, and how they represent a major step in our understanding of evolutionary processes in wild populations. We also show how these trends contrast with the prevailing view resulting mainly from laboratory experiments on Drosophila. Finally, we underline the importance of taking into account the environmental variation in models predicting quantitative trait evolution.

Evolutionary ecologists and population biologists have recently considered that ecological and evolutionary changes are intimately linked and can occur on the same time-scale. Recent theoretical developments have shown how the feedback between ecological and evolutionary dynamics can be linked, and there are now empirical demonstrations showing that ecological change can lead to rapid evolutionary change. We also have evidence that microevolutionary change can leave an ecological signature. We are at a stage where the integration of ecology and evolution is a necessary step towards major advances in our understanding of the processes that shape and maintain biodiversity. This special feature about 'eco-evolutionary dynamics' brings together biologists from empirical and theoretical backgrounds to bridge the gap between ecology and evolution and provide a series of contributions aimed at quantifying the interactions between these fundamental processes.

Best linear unbiased prediction (BLUP) is a method for obtaining point estimates of a random effect in a mixed effect model. Over the past decade it has been used extensively in ecology and evolutionary biology to predict individual breeding values and reaction norms. These predictions have been used to infer natural selection, evolutionary change, spatial-genetic patterns, individual reaction norms, and frailties. In this article we show analytically and through simulation and example why BLUP often gives anticonservative and biased estimates of evolutionary and ecological parameters. Although some concerns with BLUP methodology have been voiced before, the scale and breadth of the problems have probably not been widely appreciated. Bias arises because BLUPs are often used to estimate effects that are not explicitly accounted for in the model used to make the predictions. In these cases, predicted breeding values will often say more about phenotypic patterns than the genetic patterns of interest. An additional problem is that BLUPs are point estimates of quantities that are usually known with little certainty. Failure to account for this uncertainty in subsequent tests can lead to both bias and extreme anticonservatism. We demonstrate that restricted maximum likelihood and Bayesian solutions exist for these problems and show how unbiased and powerful tests can be derived that adequately quantify uncertainty. Of particular utility is a new test for detecting evolutionary change that not only accounts for prediction error in breeding values but also accounts for drift. To illustrate the problem, we apply these tests to long-term data on the Soay sheep (Ovis aries) and the great tit (Parus major) and show that previously reported temporal trends in breeding values are not supported.

According to the theory of mate choice based on heterozygosity, mates should choose each other in order to increase the heterozygosity of their offspring. In this study, we tested the 'good genes as heterozygosity' hypothesis of mate choice by documenting the mating patterns of wild Atlantic salmon (Salmo salar) using both major histocompatibility complex (MHC) and microsatellite loci. Specifically, we tested the null hypotheses that mate choice in Atlantic salmon is not dependent on the relatedness between potential partners or on the MHC similarity between mates. Three parameters were assessed: (i) the number of shared alleles between partners (x and y) at the MHC (M(xy)), (ii) the MHC amino-acid genotypic distance between mates' genotypes (AA(xy)), and (iii) genetic relatedness between mates (r(xy)). We found that Atlantic salmon choose their mates in order to increase the heterozygosity of their offspring at the MHC and, more specifically, at the peptide-binding region, presumably in order to provide them with better defence against parasites and pathogens. This was supported by a significant difference between the observed and expected AA(xy) (p = 0.0486). Furthermore, mate choice was not a mechanism of overall inbreeding avoidance as genetic relatedness supported a random mating scheme (p = 0.445). This study provides the first evidence that MHC genes influence mate choice in fish.

Evolutionary theory predicts that local population divergence will depend on the balance between the diversifying effect of selection and the homogenizing effect of gene flow. However, spatial variation in the expression of genetic variation will also generate differential evolutionary responses. Furthermore, if dispersal is non-random it may actually reinforce, rather than counteract, evolutionary differentiation. Here we document the evolution of differences in body mass within a population of great tits, Parus major, inhabiting a single continuous woodland, over a 36-year period. We show that genetic variance for nestling body mass is spatially variable, that this generates different potential responses to selection, and that this diversifying effect is reinforced by non-random dispersal. Matching the patterns of variation, selection and evolution with population ecological data, we argue that the small-scale differentiation is driven by density-related differences in habitat quality affecting settlement decisions. Our data show that when gene flow is not homogeneous, evolutionary differentiation can be rapid and can occur over surprisingly small spatial scales. Our findings have important implications for questions of the scale of adaptation and speciation, and challenge the usual treatment of dispersal as a force opposing evolutionary differentiation.

A gene diversity analysis was performed using microsatellite loci in order to (i) describe the extent and pattern of population structure in Atlantic salmon (Salmo salar L.) within a river system; (ii) establish the importance of quantifying the signal:noise ratio in accurately estimating population structure; and (iii) assess the potential usefulness of two evolutionary models in explaining within-river population structure from the ecological and habitat characteristics of Atlantic salmon. We found weak, yet highly significant microscale spatial patterning after accounting for variance among temporal replicates within sites. Lower genetic distances were observed among temporal samples at four sampling sites whereas no evidence for temporal stability was observed at the other three locations. The component of genetic variance attributable to either temporal instability and/or random sampling errors was almost three times more important than the pure spatial component. This indicates that not considering signal:noise ratio may lead to an important overestimation of genetic substructuring in situations of weak genetic differentiation. This study also illustrates the usefulness of the member-vagrant hypothesis to generate a priori predictions regarding the number of subpopulations that should compose a species, given its life-history characteristics and habitat structure. On the other hand, a metapopulation model appears better suited to explain the extent of genetic divergence among subpopulations, as well as its temporal persistence, given the reality of habitat patchiness and environment instability. We thus conclude that the combined use of both models may offer a promising avenue for studies aiming to understand the dynamics of genetic structure of species found in unstable environments.