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.

Climate change is expected to induce many ecological and evolutionary changes. Among these is the hypothesis that climate warming will cause a reduction in body size. This hypothesis stems from Bergmann's rule, a trend whereby species exhibit a smaller body size in warmer climates, and larger body size under colder conditions in endotherms. The mechanisms behind this rule are still debated, and it is not clear whether Bergmann's rule can be extended to predict the effects of climate change through time. We reviewed the primary literature for evidence (i) of a decrease in body size in response to climate warming, (ii) that changing body size is an adaptive response and (iii) that these responses are evolutionary or plastic. We found weak evidence for changes in body size through time as predicted by Bergmann's rule. Only three studies investigated the adaptive nature of these size decreases. Of these, none reported evidence of selection for smaller size or of a genetic basis for the size change, suggesting that size decreases could be due to nonadaptive plasticity in response to changing environmental conditions. More studies are needed before firm conclusions can be drawn about the underlying causes of these changes in body size in response to a warming climate.

Ecological responses to on-going climate change are numerous, diverse, and taxonomically widespread. However, with one exception, the relative roles of phenotypic plasticity and microevolution as mechanisms in explaining these responses are largely unknown. Several recent studies have uncovered evidence for temporal declines in mean body sizes of birds and mammals, and these responses have been interpreted as evidence for microevolution in the context of Bergmann's rule—an ecogeographic rule predicting an inverse correlation between temperature and mean body size in endothermic animals. We used a dataset of individually marked red-billed gulls ( Larus novaehollandiae scopulinus ) from New Zealand to document phenotypic and genetic changes in mean body mass over a 47-year (1958–2004) period. We found that, whereas the mean body mass had decreased over time as ambient temperatures increased, analyses of breeding values estimated with an “animal model” approach showed no evidence for any genetic change. These results indicate that the frequently observed climate-change-related responses in mean body size of animal populations might be due to phenotypic plasticity, rather than to genetic microevolutionary responses.

The rate of adaptive evolution, the contribution of selection to genetic changes that increase mean fitness, is determined by the additive genetic variance in individual relative fitness. To date, there are few robust estimates of this parameter for natural populations, and it is therefore unclear whether adaptive evolution can play a meaningful role in short-term population dynamics. We developed and applied quantitative genetic methods to long-term datasets from 19 wild bird and mammal populations and found that, while estimates vary between populations, additive genetic variance in relative fitness is often substantial and, on average, twice that of previous estimates. We show that these rates of contemporary adaptive evolution can affect population dynamics and hence that natural selection has the potential to partly mitigate effects of current environmental change.

Lower visibility of female scientists, compared to male scientists, is a potential reason for the under‐representation of women among senior academic ranks. Visibility in the scientific community stems partly from presenting research as an invited speaker at organized meetings. We analysed the sex ratio of presenters at the European Society for Evolutionary Biology (ESEB) Congress 2011, where all abstract submissions were accepted for presentation. Women were under‐represented among invited speakers at symposia (15% women) compared to all presenters (46%), regular oral presenters (41%) and plenary speakers (25%). At the ESEB congresses in 2001–2011, 9–23% of invited speakers were women. This under‐representation of women is partly attributable to a larger proportion of women, than men, declining invitations: in 2011, 50% of women declined an invitation to speak compared to 26% of men. We expect invited speakers to be scientists from top ranked institutions or authors of recent papers in high‐impact journals. Considering all invited speakers (including declined invitations), 23% were women. This was lower than the baseline sex ratios of early‐mid career stage scientists, but was similar to senior scientists and authors that have published in high‐impact journals. High‐quality science by women therefore has low exposure at international meetings, which will constrain Evolutionary Biology from reaching its full potential. We wish to highlight the wider implications of turning down invitations to speak, and encourage conference organizers to implement steps to increase acceptance rates of invited talks.