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.

AbstractAbstract

Animal migrations represent the regular movements of trillions of individuals. The scale of these movements has inspired human intrigue for millennia and has been intensively studied by biologists.
This research has highlighted the diversity of migratory strategies seen across and within migratory taxa: while some migrants temporarily express phenotypes dedicated to travel, others show little or no phenotypic flexibility in association with migration. However, a vocabulary for describing these contrasting solutions to the performance trade‐offs inherent to the highly dynamic lifestyle of migrants (and strategies intermediate between these two extremes) is currently missing.
We propose a taxon‐independent organising framework based on energetics, distinguishing between migrants that forage as they travel (income migrants) and those that fuel migration using energy acquired before departure (capital migrants).
Not only does our capital:income continuum of migratory energetics account for the variable extent of phenotypic flexibility within and across migrant populations, but it also aligns with theoreticians' treatment of migration and clarifies how migration impacts other phases of the life cycle. As such, it provides a unifying scale and common vacabulary for comparing the migratory strategies of divergent taxa.

Temporal variation in natural selection is predicted to strongly impact the evolution and demography of natural populations, with consequences for the rate of adaptation, evolution of plasticity, and extinction risk. Most of the theory underlying these predictions assumes a moving optimum phenotype, with predictions expressed in terms of the temporal variance and autocorrelation of this optimum. However, empirical studies seldom estimate patterns of fluctuations of an optimum phenotype, precluding further progress in connecting theory with observations. To bridge this gap, we assess the evidence for temporal variation in selection on breeding date by modeling a fitness function with a fluctuating optimum, across 39 populations of 21 wild animals, one of the largest compilations of long-term datasets with individual measurements of trait and fitness components. We find compelling evidence for fluctuations in the fitness function, causing temporal variation in the magnitude, but not the direction of selection. However, fluctuations of the optimum phenotype need not directly translate into variation in selection gradients, because their impact can be buffered by partial tracking of the optimum by the mean phenotype. Analyzing individuals that reproduce in consecutive years, we find that plastic changes track movements of the optimum phenotype across years, especially in bird species, reducing temporal variation in directional selection. This suggests that phenological plasticity has evolved to cope with fluctuations in the optimum, despite their currently modest contribution to variation in selection.

Access to analytical code is essential for transparent and reproducible research. We review the state of code availability in ecology using a random sample of 346 nonmolecular articles published between 2015 and 2019 under mandatory or encouraged code-sharing policies. Our results call for urgent action to increase code availability: only 27% of eligible articles were accompanied by code. In contrast, data were available for 79% of eligible articles, highlighting that code availability is an important limiting factor for computational reproducibility in ecology. Although the percentage of ecological journals with mandatory or encouraged code-sharing policies has increased considerably, from 15% in 2015 to 75% in 2020, our results show that code-sharing policies are not adhered to by most authors. We hope these results will encourage journals, institutions, funding agencies, and researchers to address this alarming situation.

Sexual reproduction is inherently interactive, especially in animal species such as humans that exhibit extended pair bonding. Yet we have little knowledge of the role of male characteristics and their evolutionary impact on reproductive behavioural phenotypes, to the extent that biologists typically consider component traits (e.g. reproductive timing) as female-specific. Based on extensive genealogical data detailing the life-histories of 6,435 human mothers born across four centuries of modern history, we use an animal modelling approach to estimate the indirect genetic effect of men on the reproductive phenotype of their partners. These analyses show that a woman’s reproductive timing (age at first birth) is influenced by her partner’s genotype. This indirect genetic effect is positively correlated with the direct genetic effect expressed in women, such that total heritable variance in this trait is doubled when heritable partner effects are considered. Our study thus suggests that much of the heritable variation in women’s reproductive timing is mediated via partner effects, and that the evolutionary potential of this trait is far greater than previously appreciated.

It was recently proposed that long-term population studies be exempted from the expectation that authors publicly archive the primary data underlying published articles. Such studies are valuable to many areas of ecological and evolutionary biological research, and multiple risks to their viability were anticipated as a result of public data archiving (PDA), ultimately all stemming from independent reuse of archived data. However, empirical assessment was missing, making it difficult to determine whether such fears are realistic. I addressed this by surveying data packages from long-term population studies archived in the Dryad Digital Repository. I found no evidence that PDA results in reuse of data by independent parties, suggesting the purported costs of PDA for long-term population studies have been overstated.