Search

Understanding the origins of diversity and the factors that drive some clades to be more diverse than others are important issues in evolutionary biology. Sophisticated SSE (state-dependent speciation and extinction) models provide insights into the association between diversification rates and the evolution of a trait. The empirical data used in SSE models and other methods is normally imperfect, yet little is known about how this can affect these models. Here, we evaluate the impact of common phylogenetic issues on inferences drawn from SSE models. Using simulated phylogenetic trees and trait information, we fitted SSE models to determine the effects of sampling fraction (phylogenetic tree completeness) and sampling fraction mis-specification on model selection and parameter estimation (speciation, extinction, and transition rates) under two sampling regimes (random and taxonomically biased). As expected, we found that both model selection and parameter estimate accuracies are reduced at lower sampling fractions (i.e., low tree completeness). Furthermore, when sampling of the tree is imbalanced across sub-clades and tree completeness is ≤ 60%, rates of false positives increase and parameter estimates are less accurate, compared to when sampling is random. Thus, when applying SSE methods to empirical datasets, there are increased risks of false inferences of trait dependent diversification when some sub-clades are heavily under-sampled. Mis-specifying the sampling fraction severely affected the accuracy of parameter estimates: parameter values were over-estimated when the sampling fraction was specified as lower than its true value, and under-estimated when the sampling fraction was specified as higher than its true value. Our results suggest that it is better to cautiously under-estimate sampling efforts, as false positives increased when the sampling fraction was over-estimated. We encourage SSE studies where the sampling fraction can be reasonably estimated and provide recommended best practices for SSE modeling. [Trait dependent diversification; SSE models; phylogenetic tree completeness; sampling fraction.]

The distribution of fitness effects is a key property in evolutionary genetics as it has implications for several evolutionary phenomena including the evolution of sex and mating systems, the rate of adaptive evolution, and the prevalence of deleterious mutations. Despite the distribution of fitness effects being extensively studied, the effects of strongly deleterious mutations are difficult to infer since such mutations are unlikely to be present in samples of haplotypes, so genetic data may contain very little information about them. Recent work has attempted to correct for this issue by expanding the classic gamma-distributed model to explicitly account for strongly deleterious mutations. Here, we use simulations to investigate one such method, adding a parameter (plth) to capture the proportion of strongly deleterious mutations. We show thatplthcan improve the model fit when applied to individual species but can underestimate the true proportion of strongly deleterious mutations. The parameter can also artificially maximize the likelihood when used to jointly infer a distribution of fitness effects from multiple species. Asplthand related parameters are used in current inference algorithms, our results are relevant with respect to avoiding model artifacts and improving future tools for inferring the distribution of fitness effects.

1. Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative dispersal strategies and tradeoffs, and testing the repeatability of evolutionary outcomes. 2. Practical constraints restrict experimental evolution studies of dispersal to a set of typically small, short-lived organisms reared in artificial laboratory conditions. Here, we argue that despite these restrictions, inferences from these studies can reinforce links between theoretical predictions and empirical observations and advance our understanding of the eco-evolutionary consequences of dispersal. 3. We illustrate how applying an integrative framework of theory, experimental evolution and natural systems can improve our understanding of dispersal evolution under more complex and realistic biological scenarios, such as the role of biotic interactions and complex dispersal syndromes.

Nuptial gift-giving occurs in several taxonomic groups including insects, snails, birds, squid, arachnids and humans. Although this trait has evolved many times independently, no general framework has been developed to predict the conditions necessary for nuptial gift-giving to evolve. We use a time-in time-out model to derive analytical results describing the requirements necessary for selection to favour nuptial gift-giving. Specifically, selection will favour nuptial gift-giving if the fitness increase caused by gift-giving exceeds the product of expected gift search time and encounter rate of the opposite sex. Selection will favour choosiness in the opposite sex if the value of a nuptial gift exceeds the inverse of offspring processing time multiplied by the rate at which mates with nuptial gifts are encountered. Importantly, selection can differ between the sexes, potentially causing sexual conflict. We test these results using an individual-based model applied to a system of nuptial gift-giving spiders,Pisaura mirabilis, by estimating parameter values using experimental data from several studies. Our results provide a general framework for understanding when the evolution of nuptial gift-giving can occur, and also provide novel insight into the evolution of worthless nuptial gifts, which occur in multiple taxonomic groups with implications for understanding parental investment.

Time is running out to limit further devastating losses of biodiversity and nature's contributions to humans. Addressing this crisis requires accurate predictions about which species and ecosystems are most at risk to ensure efficient use of limited conservation and management resources. We review existing biodiversity projection models and discover problematic gaps. Current models usually cannot easily be reconfigured for other species or systems, omit key biological processes, and cannot accommodate feedbacks with Earth system dynamics. To fill these gaps, we envision an adaptable, accessible, and universal biodiversity modeling platform that can project essential biodiversity variables, explore the implications of divergent socioeconomic scenarios, and compare conservation and management strategies. We design a roadmap for implementing this vision and demonstrate that building this biodiversity forecasting platform is possible and practical.

Process-based models are becoming increasingly used tools for understanding how species are likely to respond to environmental changes and to potential management options. RangeShifter is one such modelling platform, which has been used to address a range of questions including identifying effective reintroduction strategies, understanding patterns of range expansion and assessing population viability of species across complex landscapes.Here we introduce a new version, RangeShifter 2.0, which incorporates important new functionality. It is now possible to simulate dynamics over user-specified, temporally changing landscapes. Additionally, the genetic and evolutionary capabilities have been strengthened, notably by introducing an explicit genetic modelling architecture, which allows for simulation of neutral and adaptive genetic processes. Furthermore, emigration, transfer and settlement rules can now all evolve, allowing for sophisticated simulation of the evolution of dispersal. We illustrate the potential application of RangeShifter 2.0’s new functionality by two examples. The first illustrates the range expansion of a virtual species across a dynamically changing UK landscape. The second demonstrates how the software can be used to explore the concept of evolving connectivity in response to land-use modification, by examining how movement rules come under selection over landscapes of different structure and composition.RangeShifter 2.0 is built using object-oriented C++ providing computationally efficient simulation of complex individual-based, eco-evolutionary models. The code has been redeveloped to enable use across operating systems, including on high performance computing clusters, and the Windows GUI has been enhanced. Furthermore, the recoding of the package has supported the development of a new version running under the R platform, RangeShiftR.RangeShifter 2.0 will facilitate the development of in-silico assessments of how species will respond to environmental changes and to potential management options for conserving or controlling them. By making the code available open source, we hope to inspire further collaborations and extensions by the ecological community.

Open Access via the Wiley Jisc Agreeement Funding – This work was funded by MarCRef, a collaboration between the Univ. of Aberdeen [grant number CF10434‐53] and Marine Scotland [grant number RG14645‐10], as part of Rebekka Allgayer's PhD program and Research Councils UK, Natural Environment Research Council, NE/T006935/1. The code for the model is available in a GitHub repository: .

Empirical studies have documented both positive and negative density-dependent dispersal, yet most theoretical models predict positive density dependence as a mechanism to avoid competition. Several hypotheses have been proposed to explain the occurrence of negative density-dependent dispersal, but few of these have been formally modeled. Here, we developed an individual-based model of the evolution of density-dependent dispersal. This model is novel in that it considers the effects of density on dispersal directly, and indirectly through effects on individual condition. Body condition is determined mechanistically, by having juveniles compete for resources in their natal patch. We found that the evolved dispersal strategy was a steep, increasing function of both density and condition. Interestingly, although populations evolved a positive density-dependent dispersal strategy, the simulated metapopulations exhibited negative density-dependent dispersal. This occurred because of the negative relationship between density and body condition: high density sites produced low-condition individuals that lacked the resources required for dispersal. Our model, therefore, generates the novel hypothesis that observed negative density-dependent dispersal can occur when high density limits the ability of organisms to disperse. We suggest that future studies consider how phenotype is linked to the environment when investigating the evolution of dispersal.

Understanding how genetic and ecological effects can interact to shape genetic loads within and across local populations is key to understanding ongoing persistence of systems that should otherwise be susceptible to extinction through mutational meltdown. Classic theory predicts short persistence times for metapopulations comprising small local populations with low connectivity, due to accumulation of deleterious mutations. Yet, some such systems have persisted over evolutionary time, implying the existence of mechanisms that allow metapopulations to avoid mutational meltdown. We first hypothesize a mechanism by which the combination of stochasticity in the numbers and types of mutations arising locally (genetic stochasticity), resulting local extinction, and recolonization through evolving dispersal facilitates metapopulation persistence. We then test this mechanism using a spatially and genetically explicit individual-based model. We show that genetic stochasticity in highly structured metapopulations can result in local extinctions, which can favor increased dispersal, thus allowing recolonization of empty habitat patches. This causes fluctuations in metapopulation size and transient gene flow, which reduces genetic load and increases metapopulation persistence over evolutionary time. Our suggested mechanism and simulation results provide an explanation for the conundrum presented by the continued persistence of highly structured populations with inbreeding mating systems that occur in diverse taxa.

Defining appropriate null expectations for species distribution hypotheses is important because sampling bias and spatial autocorrelation can produce realistic, but ecologically meaningless, geographic patterns. Generating null species occurrences with similar spatial structure to observed data can help overcome these problems, but existing methods focus on single or pairs of species and do not incorporate between-species spatial structure that may occlude comparative biogeographic analyses. Here, we describe an algorithm for generating randomised species occurrence points that mimic the within- and between-species spatial structure of real datasets and implement it in a new R package - fauxcurrence. The algorithm can be implemented on any geographic domain for any number of species, limited only by computing power. To demonstrate its utility, we apply the algorithm to two common analysis-types: testing the fit of species distribution models (SDMs) and evaluating niche-overlap. The method works well on all tested datasets within reasonable timescales. We found that many SDMs, despite a good fit to the data, were not significantly better than null expectations and identified only two cases (out of a possible 32) of significantly higher niche divergence than expected by chance. The package is user-friendly, flexible and has many potential applications beyond those tested here, such as joint SDM evaluation and species co-occurrence analysis, spanning the areas of ecology, evolutionary biology and biogeography.

1. Among-individual and within-individual variation in expression of seasonal migration versus residence is widespread in nature and could substantially affect the dynamics of partially migratory metapopulations inhabiting seasonally and spatially structured environments. However, such variation has rarely been explicitly incorporated into metapopulation dynamic models for partially migratory systems. We, therefore, lack general frameworks that can identify how variable seasonal movements, and associated season- and location-specific vital rates, can control system persistence. 2. We constructed a novel conceptual framework that captures full-annual-cycle dynamics and key dimensions of metapopulation structure for partially migratory species inhabiting seasonal environments. We conceptualize among-individual variation in seasonal migration as two variable vital rates: seasonal movement probability and associated movement survival probability. We conceptualize three levels of within-individual variation (i.e. plasticity), representing seasonal or annual variation in seasonal migration or lifelong fixed strategies. We formulate these concepts as a general matrix model, which is customizable for diverse life-histories and seasonal landscapes. 3. To illustrate how variable seasonal migration can affect metapopulation growth rate, demographic structure and vital rate elasticities, we parameterize our general models for hypothetical short- and longer-lived species. Analyses illustrate that elasticities of seasonal movement probability and associated survival probability can sometimes equal or exceed those of vital rates typically understood to substantially influence metapopulation dynamics (i.e. seasonal survival probability or fecundity), that elasticities can vary non-linearly, and that metapopulation outcomes depend on the level of within-individual plasticity. 4. We illustrate how our general framework can be applied to evaluate the consequences of variable and changing seasonal movement probability by parameterizing our models for a real partially migratory metapopulation of European shags Gulosus aristotelis assuming lifelong fixed strategies. Given observed conditions, metapopulation growth rate was most elastic to breeding season adult survival of the resident fraction in the dominant population. However, given doubled seasonal movement probability, variation in survival during movement would become the primary driver of metapopulation dynamics. 5. Our general conceptual and matrix model frameworks, and illustrative analyses, thereby highlight complex ways in which structured variation in seasonal migration can influence dynamics of partially migratory metapopulations, and pave the way for diverse future theoretical and empirical advances.

Female mating preferences for exaggerated male display traits are commonplace. Yet, comprehensive understanding of the evolution and persistence of costly female preference through indirect (Fisherian) selection in finite populations requires some explanation for the persistence of additive genetic variance (V

There is increasing evidence that life-history traits can evolve rapidly during range expansion and that this evolution can impact the ecological dynamics of population spread. While dispersal evolution during range expansion has received substantial attention, dormancy (dispersal in time) has not. Here, we use an individual-based model to investigate the evolution of seed dormancy during range expansion. When a population is at spatial equilibrium our model produces results that are consistent with previous theoretical studies: seed dormancy evolves due to kin competition and the degree of dormancy increases as temporal environmental variation increases. During range expansions we consistently observe evolution towards reduced rates of dormancy at the front. Behind the front there is selection for higher rates of dormancy. Notably, the decreased dormancy towards the expanding margin reduces the regional resilience of recently expanded populations to a series of harsh years. We discuss how dormancy evolution during range expansion, and its consequences for spatial population dynamics, may impact other evolutionary responses to environmental change. We end with suggestions for future theoretical and empirical work.

Understanding evolution of complex life-histories requires explicitly considering their multiple interactions, feedbacks, and shared drivers. Inbreeding depression is hypothesized to drive evolution of two life-histories which have far-reaching ecological and evolutionary consequence: dispersal and polyandry. Yet, the role of inbreeding depression in the separate evolution of these key life-histories is still debated, while the possibility for their joint evolution and consequent covariation has not been considered. I propose that dispersal and polyandry might be competing means of inbreeding avoidance which negatively feedback on each other’s evolution. Using a genetically explicit individual-based model, I first demonstrate that inbreeding depression can drive the separate evolution of dispersal and polyandry. Although this is largely known for dispersal, it is not as well established for polyandry evolution, which generally remains an evolutionary puzzle. Here, I show that polyandry can indeed evolve as means of indirect inbreeding avoidance in spatially structured populations. Second, when dispersal and polyandry can evolve jointly, a negative feedback emerges, such that they evolve as alternative inbreeding avoidance strategies across replicate systems, especially if there are fitness costs associated. Finally, although both dispersal and polyandry might be expected to shape the level of inbreeding depression, this is mainly affected by dispersal, while polyandry has a much more limited effect. These results emphasize the need to consider the potential joint evolution of dispersal and mating system in general, together with their genetic effects, to further our understanding of life-history evolution in spatially structured systems, and provide theoretical expectations for new empirical testing.

Female mating preferences for exaggerated male display traits are commonplace. Yet, comprehensive understanding of the evolution and persistence of costly female preference through indirect (Fisherian) selection in finite populations requires some explanation for the persistence of additive genetic variance (Va) underlying sexual traits, given that directional preference is expected to deplete Va in display and hence halt preference evolution. However, the degree to which Va, and hence preference-display coevolution, may be prolonged by spatially variable sexual selection arising solely from limited gene flow and genetic drift within spatially structured populations has not been examined. Our genetically and spatially explicit model shows that spatial population structure arising in an ecologically homogeneous environment can facilitate evolution and long-term persistence of costly preference given small subpopulations and low dispersal probabilities. Here, genetic drift initially creates spatial variation in female preference, leading to persistence of Va in display through “migration-bias” of genotypes maladapted to emerging local sexual selection, thus fuelling coevolution of costly preference and display. However, costs of sexual selection increased the probability of subpopulation extinction, limiting persistence of high preference-display genotypes. Understanding long-term dynamics of sexual selection systems therefore requires joint consideration of coevolution of sexual traits and metapopulation dynamics.

The ability of individuals to leave a current breeding area and select a future one is important, because such decisions can have multiple consequences for individual fitness, but also for metapopulation dynamics, structure, and long‐term persistence through non‐random dispersal patterns. In the wild, many colonial and territorial animal species display informed dispersal strategies, where individuals use information, such as conspecific breeding success gathered during prospecting, to decide whether and where to disperse. Understanding informed dispersal strategies is essential for relating individual behavior to subsequent movements and then determining how emigration and settlement decisions affect individual fitness and demography. Although numerous theoretical studies have explored the eco‐evolutionary dynamics of dispersal, very few have integrated prospecting and public information use in both emigration and settlement phases. Here, we develop an individual‐based model that fills this gap and use it to explore the eco‐evolutionary dynamics of informed dispersal. In a first experiment, in which only prospecting evolves, we demonstrate that selection always favors informed dispersal based on a low number of prospected patches relative to random dispersal or fully informed dispersal, except when individuals fail to discriminate better patches from worse ones. In a second experiment, which allows the concomitant evolution of both emigration probability and prospecting, we show the same prospecting strategy evolving. However, a plastic emigration strategy evolves, where individuals that breed successfully are always philopatric, while failed breeders are more likely to emigrate, especially when conspecific breeding success is low. Embedding information use and prospecting behavior in eco‐evolutionary models will provide new fundamental understanding of informed dispersal and its consequences for spatial population dynamics., Information use affects the evolution of emigration probability and the number of prospected patches. It has to be considered when addressing dispersal as a response of individuals and populations to environmental changes.

In Focus: Li, X-Y., & H. Kokko. (2021). Sexual dimorphism driven by intersexual resource competition: Why is it rare, and where to look for it? Journal of Animal Ecology, 00, 1-13. Ecological sexual dimorphism, that is differences between the sexes in traits that are naturally selected as opposed to sexually selected, is gaining increasing attention after having often been dismissed as the 'less-parsimonious' explanation for differences between sexes. One potential driver of ecological sexual dimorphism is intersexual resource competition, in a process analogous to ecological character displacement between species; yet, clear empirical examples are scarce. Li and Kokko present mathematical models that introduce novel pieces to the puzzle: the role of the scale of mating competition and the spatial variation in resource availability. They show that ecological sexual dimorphism evolves when local mating groups are small (e.g. monogamous pairs) and when different resources are homogeneously available across habitats. Counterintuitively, larger mating groups (e.g. polygyny), and consequently higher intralocus sexual conflict, lead to sexual monomorphism. Habitat heterogeneity also leads to overlapping niches, although it can sometimes drive polymorphism within sexes. This study highlights why the conditions for intrasexual resource competition to drive evolution of sexual dimorphism are stringent, even in the absence of genetic constraints or competing species. Crucially, it highlights the importance of considering the mating system and the spatial scale of resource competition for understanding the occurrence of ecological sexual dimorphism, showing a large potential for future work considering different aspects of species' life histories and spatial dynamics.

Large carnivores are currently disappearing from many world regions because of habitat loss, prey depletion, and persecution. Ensuring large carnivore persistence requires safeguarding and sometimes facilitating the expansion of their populations. Understanding which conservation strategies, such as reducing persecution or restoring prey, are most effective to help carnivores to reclaim their former ranges is therefore important. Here, we systematically explored such alternative strategies for the endangered Persian leopard (Panthera pardus saxicolor) in the Caucasus. We combined a rule-based habitat suitability map and a spatially explicit leopard population model to identify potential leopard subpopulations (i.e., breeding patches), and to test the effect of different levels of persecution reduction and prey restoration on leopard population viability across the entire Caucasus ecoregion and northern Iran (about 737,000 km2). We identified substantial areas of potentially suitable leopard habitat (~120,000 km2), most of which is currently unoccupied. Our model revealed that leopards could potentially recolonize these patches and increase to a population of >1,000 individuals in 100 yr, but only in scenarios of medium to high persecution reduction and prey restoration. Overall, reducing persecution had a more pronounced effect on leopard metapopulation viability than prey restoration: Without conservation strategies to reduce persecution, leopards went extinct from the Caucasus in all scenarios tested. Our study highlights the importance of persecution reduction in small populations, which should hence be prioritized when resources for conservation are limited. We show how individual-based, spatially explicit metapopulation models can help in quantifying the recolonization potential of large carnivores in unoccupied habitat, designing adequate conservation strategies to foster such recolonizations, and anticipating the long-term prospects of carnivore populations under alternative scenarios. Our study also outlines how data scarcity, which is typical for threatened range-expanding species, can be overcome with a rule-based habitat map. For Persian leopards, our projections clearly suggest that there is a large potential for a viable metapopulation in the Caucasus, but only if major conservation actions are taken towards reducing persecution and restoring prey. Federal State of Berlin, Germany German Research Foundation http://dx.doi.org/10.13039/501100001659

Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species’ distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses.We present RangeShiftR, an R package that provides flexible and fast simulations of spatial eco-evolutionary dynamics and species’ responses to environmental changes. It implements the individual-based simulation software RangeShifter for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package’s functionality, describe the underlying model structure with its main components and present a short example.RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with comprehensive documentation and elaborate tutorials to provide a low entry level. Thanks to the implementation of the core code in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible.The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification, and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.

Ongoing ambitions are to understand the evolution of costly polyandry and its consequences for species ecology and evolution. Emerging patterns could stem from feed-back dynamics between the evolving mating system and its genetic environment, defined by interactions among kin including inbreeding. However, such feed-backs are rarely considered in non-selfing systems. We use a genetically-explicit model to demonstrate a mechanism by which inbreeding depression can select for polyandry to mitigate the negative consequences of mating with inbred males rather than avoiding inbreeding. Specifically, given inbreeding depression in sperm traits, costly polyandry evolved to ensure female fertility, without requiring explicit inbreeding avoidance. We show the mechanisms behind two main feed-backs. First, resulting sperm competition caused evolution of sperm traits and further mitigated the negative effect of inbreeding depression on female fertility. Second, the evolving mating system fed back to decrease population-wide homozygosity, and hence inbreeding. However, net overall reduction was small due to compound effects on the variances in sex-specific reproductive success and paternity skew. Purging of deleterious mutations did not eliminate inbreeding depression in sperm traits and hence selection for polyandry. Polyandry evolution, both directly and through sperm competition, might consequently facilitate evolutionary rescue for populations experiencing sudden increases in inbreeding. This article is protected by copyright. All rights reserved

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

Dispersal of prey from predator-free patches frequently supplies a trophic subsidy to predators by providing more prey than are produced locally. Prey arriving from predator-free patches might also have evolved weaker defenses against predators and thus enhance trophic subsidies by providing easily captured prey. Using local models assuming a linear or accelerating trade-off between defense and population growth rate, we demonstrate that immigration of undefended prey increased predator abundances and decreased defended prey through eco-evolutionary apparent competition. In individual-based models with spatial structure, explicit genetics, and gene flow along an environmental gradient, prey became maladapted to predators at the predator's range edge, and greater gene flow enhanced this maladaptation. The predator gained a subsidy from these easily captured prey, which enhanced its abundance, facilitated its persistence in marginal habitats, extended its range extent, and enhanced range shifts during environmental changes, such as climate change. Once the predator expanded, prey adapted to it and the advantage disappeared, resulting in an elastic predator range margin driven by eco-evolutionary dynamics. Overall, the results indicate a need to consider gene flow-induced maladaptation and species interactions as mutual forces that frequently determine ecological and evolutionary dynamics and patterns in nature.

Understanding the dynamics of socio-ecological systems is crucial to the development of environmentally sustainable practices. Models of social or ecological sub-systems have greatly enhanced such understanding, but at the risk of obscuring important feedbacks and emergent effects. Integrated modelling approaches have the potential to address this shortcoming by explicitly representing linked socio-ecological dynamics. We developed a socio-ecological system model by coupling an existing agent-based model of land-use dynamics and an individual-based model of demography and dispersal. A hypothetical case-study was established to simulate the interaction of crops and their pollinators in a changing agricultural landscape, initialised from a spatially random distribution of natural assets. The bi-directional coupled model predicted larger changes in crop yield and pollinator populations than a unidirectional uncoupled version. The spatial properties of the system also differed, the coupled version revealing the emergence of spatial land-use clusters that neither supported nor required pollinators. These findings suggest that important dynamics may be missed by uncoupled modelling approaches, but that these can be captured through the combination of currently-available, compatible model frameworks. Such model integrations are required to further fundamental understanding of socio-ecological dynamics and thus improve management of socio-ecological systems.

Summary 1.Nature conservation policies need to deliver on multiple criteria, including genetic diversity, population viability and species richness as well as ecosystem services. The challenge of integrating these may be addressed by simulation modelling. 2.We used four models (MetaConnect, SPOMSIM, a community model and InVEST) to assess a variety of spatial habitat patterns with two levels of total habitat cover and realised at two spatial scales, exploring which landscape structures performed best according to five different conservation criteria assessed for four functional types of organisms (approximately representing trees, butterflies, small mammals and birds). 3.The results display both synergies and trade-offs: population size and pollination services generally benefitted more from fragmentation than did genetic heterozygosity, and species richness more than allelic richness, although the latter two varied considerably among the functional types. 4 No single landscape performed best across all conservation criteria, but averaging over criteria and functional types, overall performance improved with greater levels of habitat cover and intermediate fragmentation (or less fragmentation in cases with lower habitat cover). 5.Policy implications. Using four simulation models we show that different conservation objectives must be traded off in spatial conservation planning, and that considering only a single taxon or criterion may result in sub-optimal choices when planning reserve networks. Nevertheless, heterogeneous spatial patterns of habitat can provide reasonable compromises for multiple criteria. This article is protected by copyright. All rights reserved.

Aim We still lack a comprehensive understanding of the relative importance of demographic, dispersal and landscape characteristics on species’ rates of range expansion (RRE) and on how these factors interact. Here, we provide an analysis of these effects for passive dispersers, by investigating how habitat characteristics, such as habitat quality, availability and fragmentation, interplay with species’ dispersal characteristics in determining species’ RRE. In addition, we assessed the predictability of RRE in cases where we have the knowledge of a species’ demography, dispersal and habitat availability. Methods Using the newly available individual-based modelling platform, RangeShifter we simulated the range expansion of species with different dispersal abilities, by varying mean dispersal distance and number of emigrants, on various landscapes. Landscapes varied in habitat quality (in terms of carrying capacity and species’ growth rates) and in habitat availability (in terms of the proportion of suitable habitat and its degree of fragmentation). Results Our results show that 55% of the total variation in RRE was explained by our six main effects, being considerably faster in landscapes with more suitable habitat, but only slightly affected by the degree of habitat fragmentation. Also, synergies between the amount of suitable habitat and species dispersal characteristics had significant positive effects on range expansion. Notably, however, 33% of variation in RRE was not explained by any of the tested factors or interactions between them and can be considered inherent and irreducible uncertainty. Main conclusions Simulation-based approaches provide important insights into the drivers of RRE that are relevant for conservation planning. For instance, our results indicate when it is likely to be better to allocate resources to improve existing habitat rather than creating new habitat, and vice versa. Additionally, our results emphasize that there will often be substantial uncertainty in the RRE, which needs to be taken into account for ecological management.

Polyandry is often hypothesized to evolve to allow females to adjust the degree to which they inbreed. Multiple factors might affect such evolution, including inbreeding depression, direct costs, constraints on male availability, and the nature of polyandry as a threshold trait. Complex models are required to evaluate when evolution of polyandry to adjust inbreeding is predicted to arise. We used a genetically explicit individual-based model to track the joint evolution of inbreeding strategy and polyandry defined as a polygenic threshold trait. Evolution of polyandry to avoid inbreeding only occurred given strong inbreeding depression, low direct costs, and severe restrictions on initial versus additional male availability. Evolution of polyandry to prefer inbreeding only occurred given zero inbreeding depression and direct costs, and given similarly severe restrictions on male availability. However, due to its threshold nature, phenotypic polyandry was frequently expressed even when strongly selected against and hence maladaptive. Further, the degree to which females adjusted inbreeding through polyandry was typically very small, and often reflected constraints on male availability rather than adaptive reproductive strategy. Evolution of polyandry solely to adjust inbreeding might consequently be highly restricted in nature, and such evolution cannot necessarily be directly inferred from observed magnitudes of inbreeding adjustment.

Female extra-pair reproduction in socially monogamous systems is predicted to cause cuckolded socially-paired males to conditionally reduce paternal care, causing selection against extra-pair reproduction and underlying polyandry. However, existing models and empirical studies have not explicitly considered that cuckolded males might be related to their socially-paired female and/or to her extra-pair mate, and therefore be related to extra-pair offspring that they did not sire but could rear. Selection against paternal care, and hence against extra-pair reproduction, might then be weakened. We derive metrics that quantify allele-sharing between within-pair and extra-pair offspring and their mother and her socially-paired male in terms of coefficients of kinship and inbreeding. We use song sparrow (Melospiza melodia) paternity and pedigree data to quantify these metrics, and thereby quantify the joint effects of extra-pair reproduction and inbreeding on a brood's total allelic value to its socially-paired parents. Cuckolded male song sparrows were almost always detectably related to extra-pair offspring they reared. Consequently, although brood allelic value decreased substantially following female extra-pair reproduction, this decrease was reduced by within-pair and extra-pair reproduction among relatives. Such complex variation in kinship within nuclear families should be incorporated into models considering coevolutionary dynamics of extra-pair reproduction, parental care, and inbreeding.

Dispersal and migration are superficially similar large-scale movements, but which appear to differ in terms of inter-individual behavioural synchronization. Seasonal migration is a striking example of coordinated behaviour, enabling animal populations to track spatio-temporal variation in ecological conditions. By contrast, for dispersal, while social context may influence an individual's emigration and settlement decisions, transience is believed to be mostly a solitary behaviour. Here, we review differences in drivers that may explain why migration appears to be more synchronized than dispersal. We derive the prediction that the contrast in the importance of behavioural synchronization between dispersal and migration is linked to differences in the selection pressures that drive their respective evolution. Although documented examples of collective dispersal are rare, this behaviour may be more common than currently believed, with important consequences for eco-evolutionary dynamics. Crucially, to date, there is little available theory for predicting when we should expect collective dispersal to evolve, and we also lack empirical data to test predictions across species. By reviewing the state of the art in research on migration and collective movements, we identify how we can harness these advances, both in terms of theory and data collection, to broaden our understanding of synchronized dispersal and its importance in the context of global change.

The interacting impacts of habitat fragmentation and climate change present a substantial threat for biodiversity, constituting a ‘deadly anthropogenic cocktail’. A range of conservation actions has been proposed to allow biodiversity to respond to those environmental changes. However, determining the relative effectiveness of these actions has been hampered by incomplete evidence. Empirical studies have provided important insights to inform conservation, but the challenge of considering multiple actions at large spatial and temporal scales is considerable. We adopt an individual-based modelling approach to qualitatively assess the effectiveness of alternative conservation actions in facilitating range expansion and patch occupancy for eight virtual species. We test actions to: (i) improve the quality of existing habitat patches, (ii) increase the permeability of the surrounding matrix, (iii) restore degraded habitat, (iv) create new habitat patches to form stepping-stones or (v) create new habitat to enlarge existing habitat patches. These actions are systematically applied to six real landscapes of the UK, which differ in their degree of habitat fragmentation and availability. Creating new habitat close to existing patches typically provides the strongest benefits for both range expansion and patch occupancy across species and landscapes. However, some landscapes may be so degraded that even under unrealistically high levels of management action, species' performances cannot be rescued. We identify that it is possible to develop a triage of conservation actions at the landscape, species and investment level, thereby providing timely evidence to inform action on the ground to lessen the hangover from the deadly anthropogenic cocktail.

Complex coevolutionary feedbacks between female mating interval and male sperm traits have been hypothesized to explain the evolution and persistence of costly polyandry. Such feedbacks could potentially arise because polyandry creates sperm competition and consequent selection on male allocation to sperm traits, while the emerging sperm traits could create female sperm limitation and, hence, impose selection for increased polyandry. However, the hypothesis that costly polyandry could coevolve with male sperm dynamics has not been tested. We built a genetically explicit individual-based model to simulate simultaneous evolution of female mating interval and male allocation to sperm number versus longevity, where these two sperm traits trade off. We show that evolution of competing sperm traits under polyandry can indeed cause female sperm limitation and, hence, promote further evolution and persistence of costly polyandry, particularly when sperm are costly relative to the degree of female sperm limitation. These feedbacks were stronger, and greater polyandry evolved, when postcopulatory competition for paternity followed a loaded rather than fair raffle and when sperm traits had realistically low heritability. We therefore demonstrate that the evolution of allocation to sperm traits driven by sperm competition can prevent males from overcoming female sperm limitation, thereby driving ongoing evolution of costly polyandry.

Previous results showing that lack of information on local population density leads to higher emigration probabilities in unpredictable environments but to lower emigration probabilities in constant or highly predictable scenarios have recently been challenged by Poethke et al. By reimplementing both our model and that of Poethke and colleagues, we demonstrate that our original results indeed hold to the presented critiques and do not contradict previous findings. The comment by Poethke and colleagues does, however, present potentially intriguing results suggesting that negative density-dependent dispersal evolves under white noise for some model formulations. Here, through intermodel comparison, we seek to better understand the source of the differences in results obtained in our study and theirs. We conclude that the apparent negative density dependence reported by Poethke et al. is effectively density independence and that the shape of the reaction norm they obtain is a model artefact. Further,...

Success rates for conservation translocations of species are low and there is a need for increased understanding of how this activity is best applied. Here, using static species distribution models and a spatially-explicit dynamic simulation model, RangeShifter, we examine the impacts of habitat cover in recipient landscapes, allocation of individuals into multiple sites and species trait characteristics on the long-term fate of hypothetical translocations of a grassland specialist butterfly, Maniola jurtina, in Finland. While persistence of populations introduced to climatically suitable locations northwards of the current range can be increased by selecting sites with increasing habitat cover and by allocation of individuals to multiple release sites, local population growth rate is shown to be the key parameter in determining likely translocation success. We conclude that the long-term persistence of translocated habitat specialist butterflies, particularly with low growth rates, appears to be uncertain in modern-day fragmented grassland networks and that translocation activities should prioritize management that improves local growth rate.

Inbreeding avoidance among interacting females and males is not always observed despite inbreeding depression in offspring fitness, creating an apparent "inbreeding paradox." This paradox could be resolved if selection against inbreeding was in fact weak, despite inbreeding depression. However, the net magnitude and direction of selection on the degree to which females and males inbreed by pairing with relatives has not been explicitly estimated. We used long-term pedigree data to estimate phenotypic selection gradients on the degree of inbreeding that female and male song sparrows (Melospiza melodia) expressed by forming socially persistent breeding pairs with relatives. Fitness was measured as the total numbers of offspring and grand offspring contributed to the population, and as corresponding expected numbers of identical-by-descent allele copies, thereby accounting for variation in offspring survival, reproduction, and relatedness associated with variation in parental inbreeding. Estimated selection gradients on the degree to which individuals paired with relatives were weakly positive in females, but negative in males that formed at least one socially persistent pairing. However, males that paired had higher mean fitness than males that remained socially unpaired. These analyses suggest that net selection against inbreeding may be weak in both sexes despite strong inbreeding depression, thereby resolving the "inbreeding paradox."

Inbreeding depression is widely hypothesised to drive adaptive evolution of pre-copulatory and post-copulatory mechanisms of inbreeding avoidance, which in turn are hypothesised to affect evolution of polyandry (i.e., female multiple mating). However, surprisingly little theory or modelling critically examines selection for pre-copulatory or post-copulatory inbreeding avoidance, or both strategies, given evolutionary constraints and direct costs, or examines how evolution of inbreeding avoidance strategies might feed back to affect evolution of polyandry. Selection for post-copulatory inbreeding avoidance, but not for pre-copulatory inbreeding avoidance, requires polyandry, while interactions between pre-copulatory and post-copulatory inbreeding avoidance might cause functional redundancy (i.e., ‘degeneracy’) potentially generating complex evolutionary dynamics among inbreeding strategies and polyandry. We used individual-based modelling to quantify evolution of interacting pre-copulatory and post-copulatory inbreeding avoidance and associated polyandry given strong inbreeding depression and different evolutionary constraints and direct costs. We found that evolution of post-copulatory inbreeding avoidance increased selection for initially rare polyandry, and that evolution of a costly inbreeding avoidance strategy became negligible over time given a lower cost alternative strategy. Further, fixed pre-copulatory inbreeding avoidance often completely precluded evolution of polyandry and hence post-copulatory inbreeding avoidance, but fixed post-copulatory inbreeding avoidance did not preclude evolution of pre-copulatory inbreeding avoidance. Evolution of inbreeding avoidance phenotypes and associated polyandry are therefore affected by evolutionary feedbacks and degeneracy. All else being equal, evolution of pre-copulatory inbreeding avoidance and resulting low polyandry is more likely when post-copulatory inbreeding avoidance is precluded or costly, and evolution of post-copulatory inbreeding avoidance greatly facilitates evolution of costly polyandry.

Summary Rapid environmental changes are threatening biodiversity and exposing species to novel ecological and evolutionary pressures. The scientific community increasingly recognizes the need for dynamic models integrating sufficient complexity both to improve our understanding of species' responses to environmental changes and to inform effective management strategies. Using three illustrative examples, we introduce a novel modelling platform, RangeShifter, which integrates complex population dynamics and dispersal behaviour, includes plastic and evolutionary processes and simulates scenarios on spatially explicit landscapes. The software provides functionality for a wide variety of modelling applications ranging from applied questions, where it can be parameterized for real landscapes and species to compare alternative potential management interventions, to purely theoretical studies of species' eco-evolutionary dynamics and responses to different environmental pressures. RangeShifter provides an important tool for facilitating the advancement of ecological theory on species' spatial dynamics in response to environmental changes, and linking it directly to application in biodiversity conservation.

Dispersal is fundamental in determining biodiversity responses to rapid climate change, but recently acquired ecological and evolutionary knowledge is seldom accounted for in either predictive methods or conservation planning. We emphasise the accumulating evidence for direct and indirect impacts of climate change on dispersal. Additionally, evolutionary theory predicts increases in dispersal at expanding range margins, and this has been observed in a number of species. This multitude of ecological and evolutionary processes is likely to lead to complex responses of dispersal to climate change. As a result, improvement of models of species’ range changes will require greater realism in the representation of dispersal. Placing dispersal at the heart of our thinking will facilitate development of conservation strategies that are resilient to climate change, including landscape management and assisted colonisation

Previous results showing that lack of information on local population density leads to higher emigration probabilities in unpredictable environments but to lower emigration probabilities in constant or highly predictable scenarios have recently been challenged by Poethke et al. By reimplementing both our model and that of Poethke and colleagues, we demonstrate that our original results indeed hold to the presented critiques and do not contradict previous findings. The comment by Poethke and colleagues does, however, present potentially intriguing results suggesting that negative density-dependent dispersal evolves under white noise for some model formulations. Here, through intermodel comparison, we seek to better understand the source of the differences in results obtained in our study and theirs. We conclude that the apparent negative density dependence reported by Poethke et al. is effectively density independence and that the shape of the reaction norm they obtain is a model artefact. Further, this response provides an opportunity to elaborate on some important issues in evolutionary and ecological modeling regarding (i) the importance of carefully considering different models' assumptions in comparisons among models, (ii) the need to consider the role of stochasticity and uncertainty when presenting and interpreting results from stochastic individual-based models, (iii) the adequate choice of the underlying ecological model that creates the selective pressures determining the evolution of behavioral reaction norms, and (iv) the appropriate choice of mutation models.

Summary 1. Dynamic simulation models are a promising tool for assessing how species respond to habitat fragmentation and climate change. However, sensitivity of their outputs to impacts of spatial resolution is insufficiently known. 2. Using an individual-based dynamic model for species’ range expansion, we demonstrate an inherent risk of substantial biases resulting from choices relating to the resolution at which key patterns and processes are modelled. 3. Increasing cell size leads to overestimating dispersal distances, the extent of the range shift and population size. Overestimation accelerates with cell size for species with short dispersal capacity and is particularly severe in highly fragmented landscapes. 4. The overestimation results from three main interacting sources: homogenisation of spatial information, alteration of dispersal kernels and stabilisation/aggregation of population dynamics. 5. We urge for caution in selecting the spatial resolution used in dynamic simulations and other predictive models and highlight the urgent need to develop upscaling methods that maintain important patterns and processes at fine scales.

Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait-based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life-history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life-history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait-space-demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability.

Female extra‐pair reproduction in socially monogamous systems is predicted to cause cuckolded socially‐paired males to conditionally reduce paternal care, causing selection against extra‐pair reproduction and underlying polyandry. However, existing models and empirical studies have not explicitly considered that cuckolded males might be related to their socially‐paired female and/or to her extra‐pair mate, and therefore be related to extra‐pair offspring that they did not sire but could rear. Selection against paternal care, and hence against extra‐pair reproduction, might then be weakened. We derive metrics that quantify allele‐sharing between within‐pair and extra‐pair offspring and their mother and her socially‐paired male in terms of coefficients of kinship and inbreeding. We use song sparrow (Melospiza melodia) paternity and pedigree data to quantify these metrics, and thereby quantify the joint effects of extra‐pair reproduction and inbreeding on a brood's total allelic value to its socially‐paired parents. Cuckolded male song sparrows were almost always detectably related to extra‐pair offspring they reared. Consequently, although brood allelic value decreased substantially following female extra‐pair reproduction, this decrease was reduced by within‐pair and extra‐pair reproduction among relatives. Such complex variation in kinship within nuclear families should be incorporated into models considering coevolutionary dynamics of extra‐pair reproduction, parental care, and inbreeding.

Inbreeding avoidance among interacting females and males is not always observed despite inbreeding depression in offspring fitness, creating an apparent “inbreeding paradox.” This paradox could be resolved if selection against inbreeding was in fact weak, despite inbreeding depression. However, the net magnitude and direction of selection on the degree to which females and males inbreed by pairing with relatives has not been explicitly estimated. We used long‐term pedigree data to estimate phenotypic selection gradients on the degree of inbreeding that female and male song sparrows (Melospiza melodia) expressed by forming socially persistent breeding pairs with relatives. Fitness was measured as the total numbers of offspring and grand offspring contributed to the population, and as corresponding expected numbers of identical‐by‐descent allele copies, thereby accounting for variation in offspring survival, reproduction, and relatedness associated with variation in parental inbreeding. Estimated selection gradients on the degree to which individuals paired with relatives were weakly positive in females, but negative in males that formed at least one socially persistent pairing. However, males that paired had higher mean fitness than males that remained socially unpaired. These analyses suggest that net selection against inbreeding may be weak in both sexes despite strong inbreeding depression, thereby resolving the “inbreeding paradox.”