Many species experience heterogeneous environments and adapt genetically to local conditions. The extent of such local adaptation depends on a balance between divergent selection and gene flow but also on other factors such as phenotypic plasticity or the genetic architecture of traits. Here, we explore the role of life history in this process. We develop a quantitative genetics model and run individual-based simulations to contrast the evolution of local adaptation between short- and long-lived species. We show that local adaptation varies with a species' life cycle and how this cycle modulates the scheduling of selection and dispersal among stages. When a longer generation time is associated with more frequent events of selection than dispersal, local adaptation is more pronounced in long-lived than in short-lived species. Contrastingly, if dispersal occurs more frequently than selection, long-lived species evolve weaker local adaptation. Our simulations confirm these findings and further show how longevity shapes additive genetic variance, effective dispersal between patches, and the genetic response at quantitative trait loci. Taken together, our results suggest that the effect of longevity on local adaptation depends on the specifics of a species' life cycle, potentially explaining why current meta-analyses have not consistently detected this effect.

In patch- or habitat-structured populations, different processes can favor adaptive polymorphism at different scales. While spatial heterogeneity can generate spatially disruptive selection favoring variation between patches, local competition can lead to locally disruptive selection promoting variation within patches. So far, almost all theory has studied these two processes in isolation. Here, we use mathematical modeling to investigate how resource variation within and between habitats influences the evolution of variation in a consumer population where individuals compete in finite patches connected by dispersal. We find that locally and spatially disruptive selection typically act in concert, favoring polymorphism under a wider range of conditions than when in isolation. But when patches are small and dispersal between them is low, kin competition inhibits the emergence of polymorphism, especially when the latter is driven by local competition for resources. We further use our model to clarify what comparisons between trait and neutral genetic differentiation (QST/FST comparisons) can tell about the nature of selection. Overall, our results help us understand the interaction between two major drivers of polymorphism: locally and spatially disruptive selection, and how this interaction is modulated by the unavoidable effects of kin selection under limited dispersal.

We adopted a landscape-scale approach to analyze the genetic patterns (diversity, structure, and differentiation) of the Marbled White ( Melanargia galathea ). This butterfly species is characteristic of semi-dry grasslands, which have substantially declined in Switzerland during past decades. We sampled individuals on a regular grid of the established Biodiversity Monitoring program of Switzerland over five consecutive years, obtaining 1639 genotyped individuals from 185 locations. Results showed that M. galathea populations cluster into five spatially aggregated clusters that largely coincide with the biogeographic regions of Switzerland. Genetic diversity (allelic richness) was higher in the South of the Alps, likely related to immigration dynamics that suggest recolonisation from the South after the last glaciation. Demographic history resulted in distinct isolation by distance (IBD) and by cumulative elevational difference (isolation by altitude, IBA) at large scale, while regional IBD and IBA were less pronounced. This pattern was likely induced by the barrier effect of the high mountains of the Alps impeding continuous northward migration after the last glacial maximum. A temporal analysis revealed that regional genetic diversity did not change strongly during the five sampling years. This result indicates that the genetic diversity pattern in M. galathea has not been noticeably affected by historical land-use change or that the sampling period of five years is too short to detect any changes. Our findings highlight the regionally, topography-induced distinct genetic clusters, relevant for consideration as conservation units and likely reflecting genetic structures similar to those found in other butterfly species of conservation concern.

In patch- or habitat-structured populations different processes can lead to diversity at different scales. While spatial heterogeneity generates spatially disruptive selection favoring variation between patches, local competition can lead to locally disruptive selection promoting variation within patches. So far, almost all theory has studied these two processes in isolation. Here, we use mathematical modelling to investigate how resource variation within and between habitats influences the evolution of variation in a consumer population where individuals compete in finite patches connected by dispersal. We find that locally and spatially disruptive selection typically act in concert, favoring polymorphism under a significantly wider range of conditions than when in isolation. But when patches are small and dispersal between them is low, kin competition inhibits the emergence of polymorphism, especially when driven by local competition. We further use our model to clarify what comparisons between trait and neutral genetic differentiation ( Q st / F st comparisons) can tell about the nature of selection. Overall, our results help understand the interaction between two major drivers of diversity: locally and spatially disruptive selection; and how this interaction is modulated by the unavoidable effects of kin selection under limited dispersal.

Understanding how a species' life history affects its capacity to cope with environmental changes is important in the context of rapid climate changes. Reinterpreting previous results from a well-developed theoretical framework, we show that a trade-off exists between a species' ability to genetically adapt to long-term gradual environmental changes and its ability to demographically resist short-term environmental perturbations, causing variation in its vital rates. Surprisingly, this important insight has not been made formally explicit before. Choosing archetypal life histories along the fast-slow pace-of-life continuum and modeling their eco-evolutionary dynamics, we further show that long-lived species have larger demographic robustness to interannual fluctuations but limited trait evolutionary responses in gradually changing environments. In contrast, short-lived species had larger evolvability but reduced demographic robustness. This trade-off bears heavily on extinction probabilities of populations tracking fast trait changes in stochastic environments. Faster trait evolution in short-lived species came at the expense of their higher sensitivity to short-term fluctuations, causing higher extinction rates than for long-lived species. Long-lived species persisted better on short timescales but built maladaptation and an extinction debt over time. This work shows how modeling species' eco-evolutionary dynamics can help to assess species vulnerability to environmental changes.

The ongoing increase in global temperature affects biodiversity, especially in mountain regions where climate change is exacerbated. As sessile, long-lived organisms, trees are especially challenged in terms of adapting to rapid climate change. Here, we show that low rates of allele frequency shifts in Swiss stone pine (Pinus cembra) occurring near the treeline result in high genomic vulnerability to future climate warming, presumably due to the species' long generation time. Using exome sequencing data from adult and juvenile cohorts in the Swiss Alps, we found an average rate of allele frequency shift of 1.23 x 10(-2)/generation (i.e. 40 years) at presumably neutral loci, with similar rates for putatively adaptive loci associated with temperature (0.96 x 10(-2)/generation) and precipitation (0.91 x 10(-2)/generation). These recent shifts were corroborated by forward-in-time simulations at neutral and adaptive loci. Additionally, in juvenile trees at the colonisation front we detected alleles putatively beneficial under a future warmer and drier climate. Notably, the observed past rate of allele frequency shift in temperature-associated loci was decidedly lower than the estimated average rate of 6.29 x 10(-2)/generation needed to match a moderate future climate scenario (RCP4.5). Our findings suggest that species with long generation times may have difficulty keeping up with the rapid climate change occurring in high mountain areas and thus are prone to local extinction in their current main elevation range.

One of the largest causes of fluctuations in the size and structure of populations is changes in the environment. In nature, these changes are often temporally autocorrelated and the strength and direction of the autocorrelation can affect population dynamics. These effects are mediated by complex, simultaneously occurring ecological and evolutionary processes, such as phenotypic plasticity and selection. Determining how these processes interact to affect responses of different life histories to autocorrelated environmental fluctuations is of paramount importance to infer which taxa are likely to go extinct or become invasive under global change. Here, we assessed the effect of autocorrelation in environmental states on the trait and population dynamics of different life histories using an evolutionary explicit individual-based modeling approach. We found that, in general, higher positive temporal autocorrelation caused more variation in population size. Fast life histories were more affected than slow ones as they were able to adapt more quickly to varying environmental optima and therefore experienced larger initial decreases in population size when optima changed. Including adaptive phenotypic plasticity buffered the effects of autocorrelation on population dynamics while nonadaptive plasticity amplified them, especially for slow life histories, which recovered less from maladaptation. This study highlights that integration of phenotypic plasticity, selection, and population dynamics is important to improve our understanding of how different life histories deal with autocorrelated climate variability.

Anticipating and preparing for the effect of environmental changes on biodiversity requires to understand and predict both the ecological and evolutionary responses of populations. Tools and methods to efficiently integrate these complex processes are lacking. We present the genetically and spatially explicit individual‐based simulation software Nemo‐age combining ecological and evolutionary processes. Nemo‐age has a strong emphasis on modelling complex life histories. We here provide a methodology to predict changes in species distribution for given climate projections using Nemo‐age . Modelling complex life histories, spatial distribution and evolutionary processes unravel possible eco‐evolutionary mechanisms that have been previously overlooked when populations endure rapid environmental changes. The interface of Nemo‐age is designed to integrate species' data from different fields, from demography to genetic architecture and spatial distributions, thus representing a versatile tool to model a variety of applied and theoretical scenarios.

While clines in environmental tolerance and phenotypic plasticity along a single species' range have been reported repeatedly and are of special interest in the context of adaptation to environmental changes, we know little about their evolution. Recent empirical findings in ectotherms suggest that processes underlying dynamic species' ranges can give rise to spatial differences in environmental tolerance and phenotypic plasticity within species. We used individual-based simulations to investigate how plasticity and tolerance evolve in the course of three scenarios of species' range shifts and range expansions on environmental gradients. We found that regions of a species' range that experienced a longer history or larger extent of environmental change generally exhibited increased plasticity or tolerance. Such regions may be at the trailing edge when a species is tracking its ecological niche in space (e.g., in a climate change scenario) or at the front edge when a species expands into a new habitat (e.g., in an expansion/invasion scenario). Elevated tolerance and plasticity in the distribution center was detected when asymmetric environmental change (e.g., polar amplification) led to a range expansion. However, tolerance and plasticity clines were transient and slowly flattened out after range dynamics because of genetic assimilation.

BACKGROUND AND PURPOSE:Birth cohort effects have greatly shaped long-term trends in multiple sclerosis (MS). This study examined whether birth cohort effects have also determined trends in the sex ratio.METHODS:Age-period-cohort analyses were applied to Swiss mortality data, 1901-2010, using logit models. Sex was introduced as an additional main effect (overall effect) and in interaction terms with A, P and C.RESULTS:Birth cohort effects strongly impacted the trends of MS risk in Switzerland, with a peak in cohorts born in the 1910s and 1920s. Similarly, birth cohort effects accounted for the change in the sex ratios during the 20th century. The balanced sex ratio at the beginning of the 20th century has been superseded by a ratio with a preponderance of women. Despite similarities in timing, the patterns of overall and sex-specific birth cohort estimates were not congruent.CONCLUSION:The change in the sex ratio in MS is driven by birth cohort related factors. Overall and sex-specific trends indicate that the appearance of MS has changed dramatically in the 20th century. The driving force behind these trends is related to yet unknown environmental factors.

Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.

Several evolutionary processes shape the genetic and phenotypic differentiation of populations. Among them, the joint effects of gene flow, selection and phenotypic plasticity are poorly known, especially when trying to understand how maladaptive plasticity affects population divergence. We extended a quantitative genetic model of Hendry et al. (2001) to describe these joint effects on phenotypic and additive genetic divergence between two populations, and their phenotypic and genetic differentiation (PST and QST). With individual-based simulations, we tested our model predictions and further modeled allelic differentiation at neutral (FST) and adaptive (FSTQ) loci. While adaptive phenotypic plasticity allows for large phenotypic divergence and differentiation despite high gene flow, maladaptive plasticity promotes genetic divergence and generates countergradient variation, under extensive migration with phenotypic differences sometimes opposed to genetic differences. Maladaptive plasticity can also promote adaptive phenotypic divergence by reducing the effective gene flow. Overall, plasticity decouples genetic from phenotypic differences between populations, and blurs the correlation between phenotypic divergence and local adaptation. By deriving models of population differentiation for three different life cycles, we further describe the effect of a species' ecology on evolution in structured populations.

Microsatellite DNA families (MDF) are stretches of DNA that share similar or identical sequences beside nuclear simple‐sequence repeat (nSSR) motifs, potentially causing problems during nSSR marker development. Primers positioned within MDFs can bind several times within the genome and might result in multiple banding patterns. It is therefore common practice to exclude MDF loci in the course of marker development. Here, we propose an approach to deal with multiple primer‐binding sites by purposefully positioning primers within the detected repetitive element. We developed a new protocol to determine the family type and the primer position in relation to MDFs using the software packages repark and repeatmasker together with an in‐house R script. We re‐evaluated newly developed nSSR markers for the lepidopteran Marbled White (Melanargia galathea) and explored the implications of our results with regard to published data sets of the butterfly Euphydryas aurinia, the grasshopper Stethophyma grossum, the conifer Pinus cembra and the crucifer Arabis alpina. For M. galathea, we show that it is not only possible to develop reliable nSSR markers for MDF loci, but even to benefit from their presence in some cases: We used one unlabelled primer, successfully binding within an MDF, for two different loci in a multiplex PCR, combining this family primer with uniquely binding and fluorescently labelled primers outside of MDFs, respectively. As MDFs are abundant in many taxa, we propose to consider these during nSSR marker development in taxa concerned. Our new approach might help in reducing the number of tested primers during nSSR marker development.

Douglas fir (Pseudotsuga menziesii (Mirb.) Franco) was first introduced to Europe from North America more than 150 years ago, was then planted on a large scale and is now the economically most important exotic tree species in European forests. This literature review summarizes the current knowledge on the effects of Douglas fir on soil chemistry, plants, arthropods and fungi. Douglas fir shapes its abiotic environment similarly to native tree species such as Norway spruce, silver fir or European beech. In general, many organisms have been shown to be able to live together with Douglas fir and in some cases even benefit from its presence. Although the number of species of the ground vegetation and that of arthropod communities is similar to those of native conifer species, fungal diversity is reduced by Douglas fir. Special microclimatic conditions in the crown of Douglas fir can lead to reduced arthropod densities during winter with possible negative consequences for birds. The ecological impacts of Douglas fir are in general not as severe as those of other exotic tree species, e.g., Pinus spp. in South Africa and Ailanthus altissima, Prunus serotina and Robinia pseudoacacia in Europe. Nonetheless, Douglas fir can negatively impact single groups of organisms or species and is now regenerating itself naturally in Europe. Although Douglas fir has not been the subject of large-scale outbreaks of pests in Europe so far, the further introduction of exotic organisms associated with Douglas fir in its native range could be more problematic than the introduction of Douglas fir itself.

Background and purpose: Many hypotheses on the etiopathogenesis of multiple sclerosis (MS) focus on risk factors occurring early in life. This study examined the variability of birth cohort trends in international MS data by means of age-period-cohort (APC) analysis.Methods: The data from 25 countries were taken from the WHO mortality database. Data were encoded according to the International Classification of Diseases and covered slightly varying periods between 1951 and 2009. The APC analyses were based on logit models applied to cohort tables with 5-year age- and period intervals.Results: In most countries, the birth cohort estimates peaked in those born in the first half of the 20th century. In countries from Central and Western Europe, the peak concerned those born before and around 1920. A second group of countries (Denmark, Sweden, Italy, Ireland, Scotland) shared a later peak amongst cohorts born in the 1920s and 1930s. Group 3 included Commonwealth countries, the USA and Norway, with a double or extended peak starting in the 1910s or 1920s, and ending by the 1950s. The fourth group, consisting of Mediterranean countries and Finland, was characterized by a steady increase in the birth cohort estimates until the 1950s. The fifth group with countries from Eastern Europe and Japan showed no particular pattern.Conclusions: Birth cohort trends have influenced the change in MS risk across the 20th century in many Western countries. This silent epidemic points to a most important but unknown latent risk factor in MS.