Search

In (st)age-structured populations, the long-run population growth rate is negatively affected by temporal variation in vital rates. In most cases, natural selection should minimize temporal variation in the vital rates to which the long-run population growth is most sensitive, resulting in demographic buffering. By reviewing empirical studies on demographic buffering in wild populations, we found overall support for this hypothesis. However, we also identified issues when testing for demographic buffering. In particular, solving scaling problems for decomposing, measuring, and comparing stochastic variation in vital rates and accounting for density dependence are required in future tests of demographic buffering. In the current context of climate change, demographic buffering may mitigate the negative impact of environmental variation and help populations to persist in an increasingly variable environment. This article is available under the Creative Commons CC-BY-NC-ND license and permits non-commercial use of the work as published, without adaptation or alteration provided the work is fully attributed.

Translocation of conspecific individuals to reduce extinction risk of small, isolated populations and prevent genetic depletion is a powerful tool in conservation biology. An important question is how the translocated individuals influence the long-term genetic composition of the recipient population. Here, we experimentally reinforced a house sparrow (Passer domesticus) population, and examined the impact of this translocation on allele frequencies, levels of heterozygosity and genetic differentiation over six cohorts. We found no permanent increase in the mean number of alleles across loci or levels of observed heterozygosity, but a few alleles private to the translocated individuals remained in the population and we found a short-term increase in heterozygosity. Consequently, genetic differentiation of the recipient population compared to the genetic composition prior to reinforcement was small. The limited genetic impact was due to combined effects of a small probability of establishment and low mating success for the translocated individuals, together with increased genetic drift in the recipient population. Our findings emphasize the importance of selection and genetic drift as forces that may decrease the genetic contribution of reinforcement, especially in small populations. Conservation managers should aim to improve habitat quality in the recipient population to reduce genetic drift following translocation and thereby avoid the need for continued reinforcement. Furthermore, by facilitating establishment success and selecting individuals expected to have high mating success, possibly indicated by sexually selected traits, genetic contribution of released individuals is increased which in turn will decrease reproductive skew and genetic drift.

The ‘Moran effect’ predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large‐scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high‐Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain‐on‐snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8–324 km apart suggested that density‐dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one ‘continental’ reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density‐dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift—with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity—led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales., Spatially autocorrelated weather and climate may cause population co‐fluctuations over large distances. We show that increasingly frequent rain‐on‐snow (ROS) and icing events in winter synchronize the annual dynamics of Svalbard reindeer populations, while, paradoxically, spatial variation in ROS trends and density‐dependent weather effects cause diverging local population trajectories in the long run. Such decoupling of population dynamics increases species viability under a rapidly warming high‐Arctic climate.

Density regulation of the population growth rate occurs through negative feedbacks on underlying vital rates, in response to increasing population size. Here, we examine in a capital breeder how vital rates of different life-history stages, their elasticities and population growth rates are affected by changes in population size. We developed an integrated population model for a local population of Svalbard barnacle geese, Branta leucopsis, using counts, reproductive data and individual-based mark-recapture data (1990-2017) to model age class-specific survival, reproduction and number of individuals. Based on these estimates, we quantified the changes in demographic structure and the effect of population size on age class-specific vital rates and elasticities, as well as the population growth rate. Local density regulation at the breeding grounds acted to reduce population growth through negative effects on reproduction; however, population size could not explain substantial variation in survival rates, although there was some support for density-dependent first-year survival. With the use of prospective perturbation analysis of the density-dependent projection matrix, we show that the elasticities to different vital rates changed as population size increased. As population size approached carrying capacity, the influence of reproductive rates and early-life survival on the population growth rate was reduced, whereas the influence of adult survival increased. A retrospective perturbation analysis revealed that density dependence resulted in a positive contribution of reproductive rates, and a negative contribution of the numbers of individuals in the adult age class, to the realised population growth rate. The patterns of density dependence in this population of barnacle geese were different from those recorded in income breeding birds, where density regulation mainly occurs through an effect on early-life survival. This indicates that the population dynamics of capital breeders, such as the barnacle goose, are likely to be more reproduction-driven than is the case for income breeders.

Body size plays a key role in the ecology and evolution of all organisms. Therefore, quantifying the sources of morphological (co)variation, dependent and independent of body size, is of key importance when trying to understand and predict responses to selection. We combine structural equation modeling with quantitative genetics analyses to study morphological (co)variation in a meta-population of house sparrows (Passer domesticus). As expected, we found evidence of a latent variable "body size," causing genetic and environmental covariation between morphological traits. Estimates of conditional evolvability show that allometric relationships constrain the independent evolution of house sparrow morphology. We also found spatial differences in general body size and its allometric relationships. On islands where birds are more dispersive and mobile, individuals were smaller and had proportionally longer wings for their body size. Although on islands where sparrows are more sedentary and nest in dense colonies, individuals were larger and had proportionally longer tarsi for their body size. We corroborated these results using simulations and show that our analyses produce unbiased allometric slope estimates. This study highlights that in the short term allometric relationships may constrain phenotypic evolution, but that in the long term selection pressures can also shape allometric relationships.

Despite their importance in shaping life history tactics and population dynamics, individual growth trajectories have only been rarely explored in the wild because their analysis requires multiple measurements of individuals throughout their lifetime and some knowledge of age, a key timer of body growth. The availability of long‐term longitudinal studies of two wild boar populations subjected to contrasting environments (rich vs. poor) provided an opportunity to analyze individual growth trajectories. We quantified wild boar growth trajectories at both the population and the individual levels using standard growth models (i.e., Gompertz, logistic, and monomolecular models) that encompass the expected range of growth shapes in determinate growers. Wild boar is a rather altricial species, with a polygynous mating system and is strongly sexually dimorphic in size. According to current theories of life history evolution, we thus expect wild boar to display a sex‐specific Gompertz type growth trajectory and lower sexual size dimorphism in the poorer environment. While wild boar displayed the expected Gompertz type trajectory in the rich site at the population level, we found some evidence for potential differences in growth shapes between populations and individuals. Asymptotic body mass, growth rate and timing of maximum growth rate differed as well, which indicates a high flexibility of growth in wild boar. We also found a cohort effect on asymptotic body mass, which suggests that environmental conditions early in life shape body mass at adulthood in this species. Our findings demonstrate that body growth trajectories in wild boar are highly diverse in relation to differences of environmental context, sex and year of birth. Whether the intermediate ranking of wild boar along the precocial–altricial continuum of development at birth may explain the ability of this species to exhibit this high diversity of growth patterns remains to be investigated., There is a relative rarity of long‐term studies documenting lifetime body growth trajectories. Using long‐term longitudinal data on two wild boar populations subjected to contrasting environments (rich vs. poor), we demonstrate body growth trajectories in wild boar are context‐, sex‐, and cohort‐specific, differing between populations and among individuals within a population. These findings are novel as they demonstrate that it may be difficult to generalize the shape of a species’ body growth trajectory.

An increasing number of empirical studies aim to quantify individual variation in demographic parameters because these patterns are key for evolutionary and ecological processes. Advanced approaches to estimate individual heterogeneity are now using a multivariate normal distribution with correlated individual random effects to account for the latent correlations among different demographic parameters occurring within individuals. Despite the frequent use of multivariate mixed models, we lack an assessment of their reliability when applied to Bernoulli variables. Using simulations, we estimated the reliability of multivariate mixed effect models for estimating correlated fixed individual heterogeneity in demographic parameters modelled with a Bernoulli distribution. We evaluated both bias and precision of the estimates across a range of scenarios that investigate the effects of life-history strategy, levels of individual heterogeneity and presence of temporal variation and state dependence. We also compared estimates across different sampling designs to assess the importance of study duration, number of individuals monitored and detection probability. In many simulated scenarios, the estimates for the correlated random effects were biased and imprecise, which highlight the challenge in estimating correlated random effects for Bernoulli variables. The amount of fixed among-individual heterogeneity was frequently overestimated, and the absolute value of the correlation between random effects was almost always underestimated. Simulations also showed contrasting performances of mixed models depending on the scenario considered. Generally, estimation bias decreases and precision increases with slower pace of life, large fixed individual heterogeneity and large sample size. We provide guidelines for the empirical investigation of individual heterogeneity using correlated random effects according to the life-history strategy of the species, as well as, the volume and structure of the data available to the researcher. Caution is warranted when interpreting results regarding correlated individual random effects in demographic parameters modelled with a Bernoulli distribution. Because bias varies with sampling design and life history, comparisons of individual heterogeneity among species is challenging. The issue addressed here is not specific to demography, making this warning relevant for all research areas, including behavioural and evolutionary studies.

Environmental variation in time and space affects biological processes such as extinction risk and speed of adaptation to environmental change. The spatial structure of environmental variation may vary among ecosystems, for instance due to differences in the flow of nutrients, genes and individuals. However, inferences about ecosystem spatial scale should also include spatial autocorrelation in environmental stochasticity, such as fluctuations in weather or climate. We used spatially structured time series (19-36 yr) on temperature from 4 different ecosystems (terrestrial, limnic, coastal sea and open ocean) to assess the spatiotemporal patterns of environmental variation over large geographical scales (up to 1900 km) during summer and winter. The distance of positive spatial autocorrelation in mean temperature was greatest for the terrestrial system (range: 592-622 km), and shorter for the open ocean (range: 472-414 km), coastal sea (range: 155-814 km) and the limnic systems (range: 51-324 km), suggesting a stronger spatial structure in environmental variation in the terrestrial system. The terrestrial system had high spatial synchrony in temperature (mean correlation: winter = 0.82, summer = 0.66) with a great spatial scaling (>650 km). Consequently, populations of terrestrial species experience similar environmental fluctuations even at distances up to 1000 km, compared to species in the aquatic systems (

International audience; The effects of harvest and fluctuating environment on interdependent predators and prey are complex and not well-known. We define a stochastic model where the predators and prey dynamically interact. The novelty of the model holds on the fact that predators and prey dynamics are simultaneously affected by correlated environmental noises. Interacting predators and prey are harvested using a proportional threshold harvesting strategy that accounts for stochastic population dynamics. Optimal yield of prey can be obtained with identical harvesting strategies when the predators and prey responded to the environment similarly (i.e., synchrony between species) and differently (i.e., asynchrony between species). Remarkably, our study demonstrates that two different harvesting strategies, the proportional harvesting strategy for the prey and the proportional threshold harvesting strategy for the predators, are needed to optimize the annual yield of predators and prey when both species are harvested simultaneously. Our study finds optimal strategies for harvesting interacting species affected by environmental variations (i.e., correlated noises) with parameters representing the joint dynamics of predators and prey at a stable state.

Understanding components of interspecific competition has long been a major goal in ecological studies. Classical models of competition typically consider equal responses of all individuals to the density of competitors, however responses may differ both among individuals from the same population, and between populations. Based on individual long-term monitoring of two chamois populations in sympatry with red deer, we built a multi-event capture-recapture model to assess how vital rates of the smaller chamois are affected by competition from the larger red deer. In both populations, mortality and breeding probabilities of female chamois depend on age and in most cases, breeding status the preceding year. Successful breeders always performed better the next year, indicating that some females are of high quality. In one population where there was high spatial overlap between the two species, the survival of old female chamois that were successful breeders the preceding year (high-quality) was negatively related to an index of red deer population size suggesting that they tend to skip reproduction instead of jeopardizing their own survival when the number of competitors increases. The breeding probability of young breeders (ages 2 and 3) was similarly affected by red deer population size. In contrast, in the second site with low spatial overlap between the two species, the vital rates of female chamois were not related to red deer population size. We provide evidence for population-specific responses to interspecific competition and more generally, for context-, age- and state-dependent effects of interspecific competition. Our results also suggest that the classical assumption of equal responses of all individuals to interspecific competition should be relaxed, and emphasize the need to move towards more mechanistic approaches to better understand how natural populations respond to changes in their environment.

Weather conditions and population density individuals experience at birth influence their life‐history traits and thereby population dynamics. Early‐life individual growth is a key fitness‐related trait; however, how it is affected by such conditions at birth remains to be explored. Taking advantage of long‐term monitoring of three wild boar (Sus scrofa) populations living in contrasting ecological contexts, we assess how weather conditions (temperature and precipitation) and the number of removed individuals at birth influence early‐life growth rates. We found that the number of individuals removed before the early‐growth period had a positive effect on early‐life growth rate across sites. This might be interpreted as a density‐dependent response involving an increase in food availability per capita that favors faster growth. Alternatively, if the number of removed individuals increases with population density, this result might be attributable to decreasing litter sizes at high density, leading mothers to allocate more resources to individual offspring, which favors higher juvenile growth rates. Early‐life growth rates also increased with springtime temperature and decreasing precipitation. Thus, early‐life growth is expected to increase in response to warmer and drier springs, which should become more frequent in the future under current climate change. We found that conditions at birth explained very little among‐year variation in early‐life growth rates (i.e., weak cohort effects) and that within‐year variation in early‐life growth rates was more likely caused by strong individual differences.

Inbreeding may increase the extinction risk of small populations. Yet, studies using modern genomic tools to investigate inbreeding depression in nature have been limited to single populations, and little is known about the dynamics of inbreeding depression in subdivided populations over time. Natural populations often experience different environmental conditions and differ in demographic history and genetic composition, characteristics that can affect the severity of inbreeding depression. We utilized extensive long-term data on more than 3,100 individuals from eight islands in an insular house sparrow metapopulation to examine the generality of inbreeding effects. Using genomic estimates of realized inbreeding, we discovered that inbred individuals had lower survival probabilities and produced fewer recruiting offspring than noninbred individuals. Inbreeding depression, measured as the decline in fitness-related traits per unit inbreeding, did not vary appreciably among populations or with time. As a consequence, populations with more resident inbreeding (due to their demographic history) paid a higher total fitness cost, evidenced by a larger variance in fitness explained by inbreeding within these populations. Our results are in contrast to the idea that effects of inbreeding generally depend on ecological factors and genetic differences among populations, and expand the understanding of inbreeding depression in natural subdivided populations.

Classical theory in population genetics includes derivation of the stationary distribution of allele frequencies under balance between selection, genetic drift, and mutation. Here we investigate the simplest generalization of these single locus models to quantitative genetics with many loci, assuming simple additive effects on a set of phenotypes and a linear approximation to the fitness function. Genetic effects and pleiotropy are simulated by a prescribed stochastic model. Our goal is to analyze the structure of the G-matrix at stasis when the model is not very close to being neutral. The smallest eigenvalue of the G-matrix is practically zero by Fisher's fundamental theorem for natural selection and the fitness function is approximately a linear function of the corresponding eigenvector. Evolution of genetic trade-offs is closely linked to the fitness function. If a single locus never codes for more than two traits, then additive genetic covariance between two phenotype components always has the opposite sign of the product of their coefficients in the fitness function under no mutation, a pattern that is likely to occur frequently also in more complex models. In our major examples only 1-2 percent of the loci are over-dominant for fitness, but they still account for practically all dominance variance in fitness as well as all contributions to the G-matrix. These analyses show that the structure of the G-matrix reveals important information about the contribution of different traits to fitness.

1. Landscape changes are happening at an unprecedented pace, and together with high levels of wildlife harvesting humans have a large effect on wildlife populations. A thorough knowledge of their combined influence on individual fitness is important to understand factors affecting population dynamics. 2. The goal of the study was to assess the individual consistency in the use of risky habitat types, and how habitat use was related to fitness components and life‐history strategies. 3. Using data from a closely monitored and harvested population of moose Alces alces, we examined how individual variation in offspring size, reproduction and survival was related to the use of open grasslands; a habitat type that offers high‐quality forage during summer, but at the cost of being more exposed to hunters in autumn. The use of this habitat type may therefore involve a trade‐off between high mortality risk and forage maximization. 4. There was a high repeatability in habitat use, which suggests consistent behaviour within individuals. Offspring number and weight were positively related to the mothers' use of open grasslands, whereas the probability of surviving the subsequent harvest season was negatively related to the use of the same habitat type. As a consequence, we found a nonsignificant relationship between habitat use and lifetime fitness. 5. The study suggests that harvesting, even if intended to be nonselective with regard to phenotypes, may be selective towards animals with specific behaviour and life‐history strategies. As a consequence, harvesting can alter the life‐history composition of the population and target life‐history strategies that would be beneficial for individual fitness and population growth in the absence of hunting. © 2020 The Author. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Many species show synchronous fluctuations in population size over large geographical areas, which are likely to increase their regional extinction risk. Here we examine how the degree of spatial synchrony in population dynamics is affected by trophic interactions using a two-species predator-prey model with spatially correlated environmental noise. We show that the predator has a larger spatial scale of population synchrony than the prey if the population fluctuations of both species are mainly determined by the direct effect of stochastic environmental variations in the prey. This result implies that in ecosystems regulated from the bottom up, the spatial scale of synchrony of the predator population increases beyond the scale of the spatial autocorrelation in the environmental noise and in the prey fluctuations. Harvesting the prey increases the spatial scale of population synchrony of the predator, while harvesting the predator reduces the spatial scale of the population fluctuations of its prey. Hence, the development of sustainable harvesting strategies should also consider the impact on unharvested species at other trophic levels as well as human perturbations of ecosystems, whether the result of exploitation or an effect on dispersal processes, as they can affect food web structures and trophic interactions over large geographical areas.

Stabilizing selection is thought to be common in wild populations and act as one of the main evolutionary mechanisms, which constrain phenotypic variation. When multiple traits interact to create a combined phenotype, correlational selection may be an important process driving adaptive evolution. Here, we report on phenotypic selection and evolutionary changes in two natal traits in a semidomestic population of reindeer (Rangifer tarandus) in northern Finland. The population has been closely monitored since 1969, and detailed data have been collected on individuals since they were born. Over the length of the study period (1969–2015), we found directional and stabilizing selection toward a combination of earlier birth date and heavier birth mass with an intermediate optimum along the major axis of the selection surface. In addition, we demonstrate significant changes in mean traits toward earlier birth date and heavier birth mass, with corresponding genetic changes in breeding values during the study period. Our results demonstrate evolutionary changes in a combination of two traits, which agree closely with estimated patterns of phenotypic selection. Knowledge of the selective surface for combinations of genetically correlated traits are vital to predict how population mean phenotypes and fitness are affected when environments change. © 2019 The Authors. Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Levels of random genetic drift are influenced by demographic factors, such as mating system, sex ratio and age structure. The effective population size (Ne) is a useful measure for quantifying genetic drift. Evaluating relative contributions of different demographic factors to Ne is therefore important to identify what makes a population vulnerable to loss of genetic variation. Until recently, models for estimating Ne have required many simplifying assumptions, making them unsuitable for this task. Here, using data from a small, harvested moose population, we demonstrate the use of a stochastic demographic framework allowing for fluctuations in both population size and age distribution to estimate and decompose the total demographic variance and hence the ratio of effective to total population size (Ne/N) into components originating from sex, age, survival and reproduction. We not only show which components contribute most to Ne/N currently, but also which components have the greatest potential for changing Ne/N. In this relatively long‐lived polygynous system we show that Ne/N is most sensitive to the demographic variance of older males, and that both reproductive autocorrelations (i.e., a tendency for the same individuals to be successful several years in a row) and covariance between survival and reproduction contribute to decreasing Ne/N (increasing genetic drift). These conditions are common in nature and can be caused by common hunting strategies. Thus, the framework presented here has great potential to increase our understanding of the demographic processes that contribute to genetic drift and viability of populations, and to inform management decisions. © 2019 The Authors. Molecular Ecology published by John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and eco-logical processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change)., To solve data integration issues and enable a new scale of ecological and evolution-ary research based on long-term studies of birds, we have created the SPI-Birds Network and Database (www.spibirds.org)—a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting., SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collab-oration and synthesis. We provide community-derived data and meta-data stand-ards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata lan-guages (e.g. ecological meta-data language)., The encouraging community involvement stems from SPI-Bird's decentralized ap-proach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demogra-phy, etc.) will aid much-needed large-scale ecological data integration., The SPI-Birds have been supported by an NWO personal grant (grant number 016.Veni.181.054) to A.C., and a Research Council of Norway grant: 223257 (SFF-III) and 267511 (EVOCLIM).

Age at first reproduction is an important determinant of individual variation in reproductive success in ungulates, but few studies have examined its relationship with later fitness‐related traits in males. We used a long‐term individual based study of a harvested moose population to quantify the individual reproductive performance and survival of males, as well as to examine the determinants of age at first reproduction and consequences of age at first reproduction on lifetime breeding success. The probability that a male successfully reproduced at the age of two was negatively related to the mean age of adult males in the population, but the relationship weakened with increasing population size. Large antlers and large body mass relative to other males in the population increased the number of calves sired at their first successful mating season. In addition, those that successfully reproduced as two year‐olds were more likely to sire calves the next year, making them more productive at a given age compared to those that first reproduced at the age of three or older. We emphasize the importance for males to start reproducing as soon as possible in a harvested population to gain lifetime fitness benefits, as surviving the hunt is a major determinant of reproductive success in this population. We found no costs of early reproduction in males, hence leading to high individual heterogeneity in male reproductive performance. The apparent lack of reproductive costs could partly be explained by the age distribution in the population, individual variation in early‐life body mass and antler size, and differences in probabilities of being hunted of successful and unsuccessful males. Locked until 3 September 2019 due to copyright restrictions. This is the peer reviewed version of an article, which has been published in final form at https://doi.org/10.1111/oik.05494. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

In changing environments, phenotypic traits are shaped by numerous agents of selection. The optimal phenotypic value maximizing the fitness of an individual thus varies through time and space with various environmental covariates. Selection may differ between different life-cycle stages and act on correlated traits inducing changes in the distribution of several traits simultaneously. Despite increasing interests in environmental sensitivity of phenotypic selection, estimating varying selective optima on various traits throughout the life cycle, while considering (a)biotic factors as potential selective agents has remained challenging. Here, we provide a statistical model to measure varying selective optima from longitudinal data. We apply our approach to analyze environmental sensitivity of phenotypic selection on egg-laying date and clutch size throughout the life cycle of a white-throated dipper population. We show the presence of a joint optimal phenotype that varies over the 35-year period, being dependent on altitude and temperature. We also find that optimal laying date is density-dependent, with high population density favoring earlier laying dates. By providing a flexible approach, widely applicable to free-ranging populations for which long-term data on individual phenotypes, fitness, and environmental factors are available, our study improves the understanding of phenotypic selection in varying environments.

Harvesting in space affects, in general, the spatial scale of the synchrony in the population fluctuations, which determines the size of the areas subjected to simultaneous quasi-extinction risk. Here we show that harvesting reduces the population synchrony scale if it depends more strongly on population fluctuations than the density dependence of the growth rate in the absence of harvesting. We show that constant and proportional harvesting always increases the spatial scale, using a theta-logistic model for density regulation. We also provide exact scaling results under harvesting for the Beverton–Holt and the Ricker stock-recruitment models that are commonly applied, e.g. in fisheries. Our results indicate that harvest in areas with large abundances should be encouraged to avoid increase of the spatial scale of synchrony in the population fluctuations that can lead to unexpected quasi-extinction of populations over large areas. Our results quantify this harvesting impact giving the resulting scales of spatial synchrony of population fluctuations. This emphasizes the importance of estimating the form of density dependence as well as the dependency of harvest upon population density of exploited populations, in order to get reliable predictions of the size of areas that can undergo simultaneous quasi-extinction.

We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities.

Significance We derive a univariate approximation for the growth of a density-dependent age-structured population in a fluctuating environment. Its accuracy is demonstrated by comparison with simulations of the age-structured model under assumptions applicable to many vertebrate populations. This facilitates extension to age-structured populations of recent theory on the evolution of stochastic population dynamics, showing that evolution tends to maximize a simple function of three key population parameters: the maximum population growth rate and carrying capacity in the average environment, r 0 and K , and the variance of population growth rate, σ e 2 . Regardless of the complexity of trade-offs among these parameters, for the classical logistic model of population growth, evolution in a fluctuating environment tends to maximize the average population size.

Evolutionary adaptations following environmental deterioration can sometimes rescue populations from extinction. Here we provide a scenario in which such evolutionary rescue will be difficult. Using a rather general model for fluctuating r- and K-selection in a density-dependent population, we show that reduction of available resources will not necessarily induce evolution of adaptations to counteract such changes provided that density regulation acts through available resources per individual. In large populations, resource depletion may induce a change in stationary distribution of population size while the optimal phenotype remains unchanged. Under a period of continuous reduction in available resources, increased strength of K-selection will occur in the sense that individuals are able to live and reproduce under less favorable conditions. Smaller growth rates as a consequence of K-selection and trade-offs between intrinsic growth rate r and carrying capacity K may then have a considerable negative effect on the persistence of the population even after the reduction of available resources is stopped. This negative effect comes in addition to the purely ecological effect of reduced time to extinction because of a reduction in K and increased demographic stochasticity. Continuous reduction in the available area or in available resources per individual may result in long-run maladaptation even if demographic noise increases and, finally but too late, induces r-selection.

A general assumption in quantitative genetics is the existence of an intermediate phenotype with higher mean individual fitness in the average environment than more extreme phenotypes. Here, we investigate the evolvability and presence of such a phenotype in wild bird populations from an eleven-year experiment with four years of artificial selection for long and short tarsus length, a proxy for body size. The experiment resulted in strong selection in the imposed directions. However, artificial selection was counteracted by reduced production of recruits in offspring of artificially selected parents. This resulted in weak natural selection against extreme trait values. Significant responses to artificial selection were observed at both the phenotypic and genetic level, followed by a significant return toward preexperimental means. During artificial selection, the annual observed phenotypic response closely followed the predicted response from quantitative genetic theory (ryears = 0.96, rcohorts = 0.56). The rapid return to preexperimental means was induced by three interacting mechanisms: selection for an intermediate phenotype, immigration, and recombination between selected and unselected individuals. The results of this study demonstrates the evolvability of phenotypes and that selection may favor an intermediate phenotype in wild populations.

Translocation of individuals from source populations to augment small populations facing risk of extinction is an important conservation tool. Here we examine sex-specific differences between resident and translocated house sparrows Passer domesticus in reproductive success and survival, and the contribution of translocated individuals to the growth of a local population. We found evidence for assortative mating based on origin revealed by fewer parentages between translocated males and resident females than expected, and the total number of fledglings produced by such pairs was lower. The reproductive success of translocated males was positively related to the size of the throat badge (a sexual ornament), such that only translocated males with a large badge size were as successful as resident males. However, offspring with parents of different origin had higher survival than offspring with parents of the same origin, which suggests hybrid vigour. The contribution of resident and translocated individuals to the stochastic component of the long-run growth rate of the population was similar; neither the mean individual contributions in fitness nor the demographic variance differed between the two groups. Thus, this experiment shows that translocated individuals may have a similar demographic influence on the growth of local populations as resident individuals. Still, the intermixing of translocated and resident individuals was low, and fitness differed according to origin in relation to individual differences in a sexually selected trait. In addition, hybrid vigour with respect to offspring recruitment seemed to partially decrease the negative fitness consequences of the assortative mating based on origin. This is the peer reviewed version of the following article: [Demographic influences of translocated individuals on a resident population of house sparrows], which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/oik.04065/abstract. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Locked until 24.4.2018 due to copyright restrictions.

Understanding how environmental variation affects phenotypic evolution requires models based on ecologically realistic assumptions that include variation in population size and specific mechanisms by which environmental fluctuations affect selection. Here we generalize quantitative genetic theory for environmentally induced stochastic selection to include general forms of frequency- and density-dependent selection. We show how the relevant fitness measure under stochastic selection relates to Fisher's fundamental theorem of natural selection, and present a general class of models in which density regulation acts through total use of resources rather than just population size. In this model, there is a constant adaptive topography for expected evolution, and the function maximized in the long run is the expected factor restricting population growth. This allows us to generalize several previous results and to explain why apparently " K -selected" species with slow life histories often have low carrying capacities. Our joint analysis of density- and frequency-dependent selection reveals more clearly the relationship between population dynamics and phenotypic evolution, enabling a broader range of eco-evolutionary analyses of some of the most interesting problems in evolution in the face of environmental variation.

International audience; Understanding species coexistence has long been a major goal of ecology. Coexistence theory for two competing species posits that intraspecific density dependence should be stronger than interspecific density dependence. Great tits and blue tits are two bird species that compete for food resources and nesting cavities. On the basis of long-term monitoring of these two competing species at sites across Europe, combining observational and manipulative approaches, we show that the strength of density regulation is similar for both species, and that individuals have contrasting abilities to compete depending on their age. For great tits, density regulation is driven mainly by intraspecific competition. In contrast, for blue tits, interspecific competition contributes as much as intraspecific competition, consistent with asymmetric competition between the two species. In addition, including age-specific effects of intra-and interspecific competition in density-dependence models improves predictions of fluctuations in population size by up to three times.

Understanding how stochastic fluctuations in the environment influence population dynamics is crucial for sustainable management of biological diversity. However, because species do not live in isolation, this requires knowledge of how species interactions influence population dynamics. In addition, spatial processes play an important role in shaping population dynamics. It is therefore important to improve our understanding of how these different factors act together to shape patterns of abundance across space within and among species. Here, we present a new analytical model for understanding patterns of covariation in space between interacting species in a stochastic environment. We show that the correlation between two species in how they experience the same environmental conditions determines how correlated fluctuations in their densities would be in the absence of competition. In other words, without competition, synchrony between the species is driven by the environment, similar to the Moran effect within a species. Competition between the two species causes their abundances to become less positively or more negatively correlated. The same strength of competition has a greater negative effect on the correlation between species when one of them has a more variable growth rate than the other. In addition, dispersal or other movement weakens the effect of competition on the interspecific correlation. Finally, we show that movement increases the distance over which the species are (positively or negatively) correlated, an effect that is stronger when the species are competitors, and that there is a close connection between the spatial scaling of population synchrony within a species and between species. Our results show that the relationships between the different factors influencing interspecific correlations in abundance are not simple linear ones, but this model allows us to disentangle them and predict how they will affect population fluctuations in different situations. © 2019 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Climate and weather conditions may have substantial effects on the ecology of both parasites and hosts in natural populations. The strength and shape of the effects of weather on parasites and hosts are likely to change as global warming affects local climate. These changes may in turn alter fundamental elements of parasite–host dynamics. We explored the influence of temperature and precipitation on parasite prevalence in a metapopulation of avian hosts in northern Norway. We also investigated if annual change in parasite prevalence was related to winter climate, as described by the North Atlantic Oscillation (NAO). We found that parasite prevalence increased with temperature within-years and decreased slightly with increasing precipitation. We also found that a mild winter (positive winter NAO index) was associated with higher mean parasite prevalence the following year. Our results indicate that both local and large scale weather conditions may affect the proportion of hosts that become infected by parasites in natural populations. Understanding the effect of climate and weather on parasite–host relationships in natural populations is vital in order to predict the full consequence of global warming.

International audience; In marine and terrestrial ecosystems, organisms are affected by environmental variations that cause fluctuations in population size. The harvest–interaction hypothesis predicts that environmentally induced fluctuations in population size are magnified by harvesting. Empirical evidence is urgently needed in the context of global change because greater fluctuations will increase extinction risk.Here, we review theoretical and empirical work that has addressed the harvest–interaction hypothesis in fish, birds and mammals. We identify the mechanisms by which harvesting might make population size more variable over time and thereby increase the risk of extinction.Theoretical models show that harvest can modify population structure in time and space, and that changes in the amplitude and synchrony of population dynamics both increase extinction risk. Empirical evidence indicates that fishing amplifies the effects of environmental changes on the population variability, but no empirical study of terrestrial species has tested for amplified environmentally induced fluctuations due to hunting.Synthesis and applications. In terrestrial species, theoretical studies have evaluated how environmentally induced fluctuations in population size are magnified by different harvest strategies, but there is now an urgent need for an empirical evaluation of this hypothesis. Future research is needed to explore how hunting and climate interact and to test whether hunting enhances environmentally induced fluctuations in population numbers of terrestrial species

Theoretical models pertaining to feedbacks between ecological and evolutionary processes are prevalent in multiple biological fields. An integrative overview is currently lacking, due to little crosstalk between the fields and the use of different methodological approaches. Here, we review a wide range of models of eco‐evolutionary feedbacks and highlight their underlying assumptions. We discuss models where feedbacks occur both within and between hierarchical levels of ecosystems, including populations, communities and abiotic environments, and consider feedbacks across spatial scales. Identifying the commonalities among feedback models, and the underlying assumptions, helps us better understand the mechanistic basis of eco‐evolutionary feedbacks. Eco‐evolutionary feedbacks can be readily modelled by coupling demographic and evolutionary formalisms. We provide an overview of these approaches and suggest future integrative modelling avenues. Our overview highlights that eco‐evolutionary feedbacks have been incorporated in theoretical work for nearly a century. Yet, this work does not always include the notion of rapid evolution or concurrent ecological and evolutionary time scales. We show the importance of density‐ and frequency‐dependent selection for feedbacks, as well as the importance of dispersal as a central linking trait between ecology and evolution in a spatial context. A plain language summary is available for this article.

The synchrony of population dynamics in space has important implications for ecological processes, for example affecting the spread of diseases, spatial distributions and risk of extinction. Here, we studied the relationship between spatial scaling in population dynamics and species position along the slow‐fast continuum of life history variation. Specifically, we explored how generation time, growth rate and mortality rate predicted the spatial scaling of abundance and yearly changes in abundance of eight marine fish species. Our results show that population dynamics of species' with ‘slow’ life histories are synchronised over greater distances than those of species with ‘fast’ life histories. These findings provide evidence for a relationship between the position of the species along the life history continuum and population dynamics in space, showing that the spatial distribution of abundance may be related to life history characteristics. This is the peer reviewed version of an article, which has been published in final form at [https://doi.org/10.1111/ele.13360]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. "

In a stable environment, evolution maximizes growth rates in populations that are not density regulated and the carrying capacity in the case of density regulation. In a fluctuating environment, evolution maximizes a function of growth rate, carrying capacity and environmental variance, tending to r-selection and K-selection under large and small environmental noise, respectively. Here we analyze a model in which birth and death rates depend on density through the same function but with independent strength of density dependence. As a special case, both functions may be linear, corresponding to logistic dynamics. It is shown that evolution maximizes a function of the deterministic growth rate r0 and the lifetime reproductive success (LRS) R0 , both defined at small densities, as well as the environmental variance. Under large noise this function is dominated by r0 and average lifetimes are small, whereas R0 dominates and lifetimes are larger under small noise. Thus, K-selection is closely linked to selection for large R0 so that evolution tends to maximize LRS in a stable environment. Consequently, different quantities (r0 and R0 ) tend to be maximized at low and high densities, respectively, favoring density-dependent changes in the optimal life history.

Reliable estimates of effective population size Ne are of central importance in population genetics and evolutionary biology. For populations that fluctuate in size, harmonic mean population size is commonly used as a proxy for (multi-) generational effective size. This assumes no effects of density dependence on the ratio between effective and actual population size, which limits its potential application. Here, we introduce density dependence on vital rates in a demographic model of variance effective size. We derive an expression for the ratio Ne/N in a density-regulated population in a fluctuating environment. We show by simulations that yearly genetic drift is accurately predicted by our model, and not proportional to 1/(2N) as assumed by the harmonic mean model, where N is the total population size of mature individuals. We find a negative relationship between Ne/N and N. For a given N, the ratio depends on variance in reproductive success and the degree of resource limitation acting on the population growth rate. Finally, our model indicate that environmental stochasticity may affect Ne/N not only through fluctuations in N, but also for a given N at a given time. Our results show that estimates of effective population size must include effects of density dependence and environmental stochasticity.

International audience; Classical approaches for the analyses of density dependence assume that all the individuals in a population equally respond and equally contribute to density dependence. However, in age-structured populations, individuals of different ages may differ in their responses to changes in population size and how they contribute to density dependence affecting the growth rate of the whole population. Here we apply the concept of critical age classes, i.e., a specific scalar function that describes how one or a combination of several age classes affect the demographic rates negatively, in order to examine how total density dependence acting on the population growth rate depends on the age-specific population sizes. In a 38-yr dataset of an age-structured great tit (Parus major) population, we find that the age classes, including the youngest breeding females, were the critical age classes for density regulation. These age classes correspond to new breeders that attempt to take a territory and that have the strongest competitive effect on other breeding females. They strongly affected population growth rate and reduced recruitment and survival rates of all breeding females. We also show that depending on their age class, females may differently respond to varying density. In particular, the negative effect of the number of breeding females was stronger on recruitment rate of the youngest breeding females. These findings question the classical assumptions that all the individuals of a population can be treated as having an equal contribution to density regulation and that the effect of the number of individuals is age independent. Our results improve our understanding of density regulation in natural populations.

Here we analyze how dispersal, genetic drift, and adaptation to the local environment affect the geographical differentiation of a quantitative character through natural selection using a spatial dynamic model for the evolution of the distribution of mean breeding values in space and time. The variation in optimal phenotype is described by local Ornstein-Uhlenbeck processes with a given spatial autocorrelation. Selection and drift are assumed to be governed by phenotypic variation within areas with a given mean breeding value and constant additive genetic variance. Between such neighboring areas there will be white noise variation in mean breeding values, while the variation at larger distances has a spatial structure and a spatial scale that we investigate. The model is analyzed by solving balance equations for the stationary distribution of mean breeding values. We also present scaling results for the spatial autocovariance function for mean breeding values as well as that for the covariance between mean breeding value and the optimal phenotype expressing local adaption. Our results show in particular how these spatial scales depend on population density. For large densities the spatial scale of fluctuations in mean breeding values have similarities with corresponding results in population dynamics, where the effect of migration on spatial scales may be large if the local strength of density regulation is small. In our evolutionary model strength of density regulation corresponds to strength of local selection so that weak local selection may produce large spatial scales of autocovariances. Genetic drift and stochastic migration are shown to act through the population size within a characteristic area with much smaller variation in optimal phenotypes than in the whole population.

Empirical evidence strongly indicates that human exploitation has frequently led to rapid evolutionary changes in wild populations, yet the mechanisms involved are often poorly understood. Here, we applied a recently developed demographic framework for analyzing selection to data from a 20-year study of a wild population of moose, Alces alces. In this population, a genetic pedigree has been established all the way back to founders. We demonstrate harvest-induced directional selection for delayed birth dates in males and reduced body mass as calf in females. During the study period, birth date was delayed by 0.81 days per year for both sexes, whereas no significant changes occurred in calf body mass. Quantitative genetic analyses indicated that both traits harbored significant additive genetic variance. These results show that selective harvesting can induce strong selection that oppose natural selection. This may cause evolution of less favorable phenotypes that become maladaptive once harvesting ceases.

Investigating factors which affect the decline in survival with age, i.e. actuarial senescence, is important in order to understand how demographic rates vary in wild populations. Although the evidence for the occurrence of actuarial senescence in wild populations is growing, very few studies have compared actuarial senescence rates between wild populations of the same species. We used data from a long-time study of demography of house sparrows (Passer domesticus) to investigate differences in rates of actuarial senescence between habitats and sub-populations. We also investigated whether rates of actuarial senescence differed between males and females. We found that rates of actuarial senescence showed large spatial variation. We also found that the onset of actuarial senescence varied between sub-populations. However, these differences were not significantly explained by a general difference in habitat type. We also found no significant difference in actuarial senescence rates between males and females. This study shows that senescence rates in natural populations may vary significantly between sub-populations and that failing to account for such differences may give a biased estimate of senescence rates of a species. © Springer Verlag. The final publication is available at https://link.springer.com/article/10.1007%2Fs00442-016-3615-4. This is the authors' manuscript to the article.

During pregnancy, littermates compete to extract maternal resources from the placenta. Unequal extraction of resources leads to developmental differences among offspring and thus within-litter variation in offspring mass. Because competition among littermates can be stronger among half-sibs, multiple paternity may represent an adaptive strategy allowing females to increase within-litter phenotypic variation among offspring when facing variable environments. Wild boar (Sus scrofa) females produce large litters with diversified offspring in terms of body mass. Additionally, multiple paternities within a litter have been observed in this promiscuous species. One can hypothesize that multiple paternity represents the mechanism by which females increase within-litter phenotypic variation. Combining long-term monitoring data with paternity analyses in a wild boar population, we tested whether the increase in the number of fathers within a litter explained the increase in within-litter variation in offspring mass observed in large litters. We showed that heavy females mated earlier during the rut, produced larger litters with a higher number of fathers and more variable fetus mass than lighter females. Within-litter variation of offspring mass increased with gestation stage and litter size, suggesting differential allocation of maternal resource among offspring “in utero.” However, we found only a weak paternal effect on offspring mass and no direct effect of the number of fathers on the within-litter variation in offspring mass. These results indicate that differential maternal allocation to offspring during pregnancy is unlikely related to paternal identity in this species. This is a pre-copyedited, author-produced version of an article accepted for publication in Behavioral Ecology following peer review. The version of record is available online at: https://doi.org/10.1093/beheco/ary056

Trade-offs between fitness-related traits are predicted from the principle of resource allocation, where increased fecundity or parental investment leads to reduced future reproduction or survival. However, fitness traits can also be positively correlated due to individual differences (e.g. body mass). Age at primiparity could potentially explain variation in individual fitness either because early primiparity is costly, or it may lead to higher lifetime reproductive success. Based on long-term monitoring and genetic parentage assignment of an island population of moose, we quantified reproductive performance and survival, and examined whether early maturing females have higher total calf production than late maturing females. We explored if harvesting of calves affected the subsequent reproductive success of their mothers, i.e. also due to a post-weaning cost of reproduction, and whether there are any intergenerational effects of female reproductive success. There was a positive relationship between current and future reproduction. The probability to reproduce was lower for females that were unsuccessful the year before, indicating a strong quality effect on productivity. Females that started to reproduce as 2-year olds had a slightly higher total calf production compared to those starting at age three or four. High-performing mothers were also correlated with daughters that performed well in terms of reproductive success. Our results suggest that the observed individual heterogeneity in fitness could be associated with differences in age at primiparity. This heterogeneity was not affected by reproductive costs associated with tending for a calf post-weaning.

Understanding the genetic architecture of quantitative traits can provide insights into the mechanisms driving phenotypic evolution. Bill morphology is an ecologically important and phenotypically variable trait, which is highly heritable and closely linked to individual fitness. Thus, bill morphology traits are suitable candidates for gene mapping analyses. Previous studies have revealed several genes that may influence bill morphology, but the similarity of gene and allele effects between species and populations is unknown. Here, we develop a custom 200K SNP array and use it to examine the genetic basis of bill morphology in 1857 house sparrow individuals from a large‐scale, island metapopulation off the coast of Northern Norway. We found high genomic heritabilities for bill depth and length, which were comparable with previous pedigree estimates. Candidate gene and genomewide association analyses yielded six significant loci, four of which have previously been associated with craniofacial development. Three of these loci are involved in bone morphogenic protein (BMP) signalling, suggesting a role for BMP genes in regulating bill morphology. However, these loci individually explain a small amount of variance. In combination with results from genome partitioning analyses, this indicates that bill morphology is a polygenic trait. Any studies of eco‐evolutionary processes in bill morphology are therefore dependent on methods that can accommodate polygenic inheritance of the phenotype and molecular‐scale evolution of genetic architecture. Publisher embargo applies until July 24, 2019

In nature, individual reproductive success is seldom independent from year to year, due to factors such as reproductive costs and individual heterogeneity. However, population projection models that incorporate temporal autocorrelations in individual reproduction can be difficult to parameterise, particularly when data are sparse. We therefore examine whether such models are necessary to avoid biased estimates of stochastic population growth and extinction risk, by comparing output from a matrix population model that incorporates reproductive autocorrelations to output from a standard age‐structured matrix model that does not. We use a range of parameterisations, including a case study using moose data, treating probabilities of switching reproductive class as either fixed or fluctuating. Expected time to extinction from the two models is found to differ by only small amounts (under 10%) for most parameterisations, indicating that explicitly accounting for individual reproductive autocorrelations is in most cases not necessary to avoid bias in extinction estimates. This is the peer reviewed version of an article, which has been published in final form at [https://doi.org/10.1111/ele.12834]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. "

Experimental evolution studies can be used to explore genomic response to artificial and natural selection. In such studies, loci that display larger allele frequency change than expected by genetic drift alone are assumed to be directly or indirectly associated with traits under selection. However, such studies report surprisingly many loci under selection, suggesting that current tests for allele frequency change may be subject to P-value inflation and hence be anticonservative. One factor known from genomewide association (GWA) studies to cause P-value inflation is population stratification, such as relatedness among individuals. Here, we suggest that by treating presence of an individual in a population after selection as a binary response variable, existing GWA methods can be used to account for relatedness when estimating allele frequency change. We show that accounting for relatedness like this effectively reduces false-positives in tests for allele frequency change in simulated data with varying levels of population structure. However, once relatedness has been accounted for, the power to detect causal loci under selection is low. Finally, we demonstrate the presence of P-value inflation in allele frequency change in empirical data spanning multiple generations from an artificial selection experiment on tarsus length in two free-living populations of house sparrow and correct for this using genomic control. Our results indicate that since allele frequencies in large parts of the genome may change when selection acts on a heritable trait, such selection is likely to have considerable and immediate consequences for the eco-evolutionary dynamics of the affected populations. This is the peer reviewed version of the following article: [Controlling for P-value inflation in allele frequency change in experimental evolution and artificial selection experiments], which has been published in final form at [http://onlinelibrary.wiley.com/doi/10.1111/1755-0998.12631/abstract]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Locked until 25.11.2017 due to copyright restrictions.

Peeters, B., V. Veiberg, A. Ø. Pedersen, A. Stien, R. J. Irvine, R. Aanes, B.-E. Sæther, O. Strand, and B. B. Hansen. 2017. Climate and density dependence cause changes in adult sex ratio in a large Arctic herbivore. Ecosphere 8(2):e01699. 10.1002/ecs2.1699 Variation in adult sex ratio (ASR) affects population demography and dynamics of large mammals. The mechanisms behind this variation are largely unclear, but may be partly related to climatic drivers and density dependence operating differently on the adult male and female segments of the population. Here, we examine such drivers of annual changes in ASR in the predator-free wild Svalbard reindeer (Rangifer tarandus platyrhynchus), a high Arctic subspecies whose population dynamics are shaped by climate. Using up to 35 year long time-series of population count data from two populations, we disentangle drivers of fluctuations in ASR by first analyzing how climate and density dependence affect sex-specific adult population growth rates through effects on mortality. There were a positive population size trend and an overall female bias in ASR throughout the study period. Increased winter precipitation, a proxy for the harshness of winter feeding conditions, was found to significantly reduce adult population growth rates through reduced survival in males, but not in females. However, increased population size tended to cause a stronger immediate decline in female than in male adult population growth rates. As a consequence, the female bias in ASR increased with harsher winter conditions and declined with higher population size. As expected from the increased frequency of rainy and icy winters due to climate warming, a recent trend toward increased female bias in ASR was evident. This demonstrates that climatic drivers of both short-term fluctuations and long-term trends in demography need to be accounted for in the management and population dynamic predictions of Arctic ungulates.

Warmer winters alter the dynamics of a local bird population and reduce immigration rate due to density-dependent feedback., Climate change will affect the population dynamics of many species, yet the consequences for the long-term persistence of populations are poorly understood. A major reason for this is that density-dependent feedback effects caused by fluctuations in population size are considered independent of stochastic variation in the environment. We show that an interplay between winter temperature and population density can influence the persistence of a small passerine population under global warming. Although warmer winters favor an increased mean population size, density-dependent feedback can cause the local population to be less buffered against occasional poor environmental conditions (cold winters). This shows that it is essential to go beyond the population size and explore climate effects on the full dynamics to elaborate targeted management actions.

1.Environmental variation can induce life history changes that can last over a large part of the lifetime of an organism. If multiple demographic traits are affected, expected changes in climate may influence environmental covariances among traits in a complex manner. Thus, examining the consequences of environmental fluctuations requires that individual information at multiple life stages are available, which is particularly challenging in long-lived species. 2.Here we analyse how variation in climatic conditions occurring in the year of hatching of female goshawks Accipiter gentilis (L.) affects age-specific variation in demographic traits and lifetime reproductive success (LRS). LRS decreased with increasing temperature in April in the year of hatching, due to lower breeding frequency and shorter reproductive lifespan. In contrast, the probability for a female to successfully breed was higher in years with a warm April, but lower LRS of the offspring in these years generated a negative covariance among fecundity rates among generations. 3.The mechanism by which climatic conditions generated cohort effects was likely through influencing the quality of the breeding segment of the population in a given year, as the proportion of pigeons in the diet during the breeding period was positively related to annual and lifetime reproductive success, and the diet of adult females that hatched in warm years contained fewer pigeons. 4.Climatic conditions experienced during different stages of individual life histories caused complex patterns of environmental covariance among demographic traits even across generations. Such environmental covariances may either buffer or amplify impacts of climate change on population growth, emphasizing the importance of considering demographic changes during the complete life history of individuals when predicting the effect of climatic change on population dynamics of long-lived species. This article is protected by copyright. All rights reserved.