Impact of Phylogenetic Tree Completeness and Mis-specification of Sampling Fractions on Trait Dependent Diversification Models.

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.].

Environmental variance in male mating success modulates the positive versus negative impacts of sexual selection on genetic load.

Sexual selection on males is predicted to increase population fitness, and delay population extinction, when mating success negatively covaries with genetic load across individuals. However, such benefits of sexual selection could be counteracted by simultaneous increases in genome-wide drift resulting from reduced effective population size caused by increased variance in fitness. Resulting fixation of deleterious mutations could be greatest in small populations, and when environmental variation in mating traits partially decouples sexual selection from underlying genetic variation. The net consequences of sexual selection for genetic load and population persistence are therefore likely to be context dependent, but such variation has not been examined. We use a genetically explicit individual-based model to show that weak sexual selection can increase population persistence time compared to random mating. However, for stronger sexual selection such positive effects can be overturned by the detrimental effects of increased genome-wide drift. Furthermore, the relative strengths of mutation-purging and drift critically depend on the environmental variance in the male mating trait. Specifically, increasing environmental variance caused stronger sexual selection to elevate deleterious mutation fixation rate and mean selection coefficient, driving rapid accumulation of drift load and decreasing population persistence times. These results highlight an intricate balance between conflicting positive and negative consequences of sexual selection on genetic load, even in the absence of sexually antagonistic selection. They imply that environmental variances in key mating traits, and intrinsic genetic drift, should be properly factored into future theoretical and empirical studies of the evolution of population fitness under sexual selection.

Experimental evolution of dispersal: Unifying theory, experiments and natural systems.

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 trade-offs, and testing the repeatability of evolutionary outcomes. 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. 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.

Modelling the responses of partially migratory metapopulations to changing seasonal migration rates: From theory to data.

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. 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. 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. 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. 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.

Reducing persecution is more effective for restoring large carnivores than restoring their prey.

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.

Ecological sexual dimorphism is modulated by the spatial scale of intersexual resource competition.

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.

Maladapted Prey Subsidize Predators and Facilitate Range Expansion.

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.

Coevolutionary Feedbacks between Female Mating Interval and Male Allocation to Competing Sperm Traits Can Drive Evolution of Costly Polyandry.

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.

Models of Dispersal Evolution Highlight Several Important Issues in Evolutionary and Ecological Modeling.

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.

A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?

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.

Between migration load and evolutionary rescue: dispersal, adaptation and the response of spatially structured populations to environmental change.

The evolutionary potential of populations is mainly determined by population size and available genetic variance. However, the adaptability of spatially structured populations may also be affected by dispersal: positively by spreading beneficial mutations across sub-populations, but negatively by moving locally adapted alleles between demes. We develop an individual-based, two-patch, allelic model to investigate the balance between these opposing effects on a population's evolutionary response to rapid climate change. Individual fitness is controlled by two polygenic traits coding for local adaptation either to the environment or to climate. Under conditions of selection that favour the evolution of a generalist phenotype (i.e. weak divergent selection between patches) dispersal has an overall positive effect on the persistence of the population. However, when selection favours locally adapted specialists, the beneficial effects of dispersal outweigh the associated increase in maladaptation for a narrow range of parameter space only (intermediate selection strength and low linkage among loci), where the spread of beneficial climate alleles is not strongly hampered by selection against non-specialists. Given that local selection across heterogeneous and fragmented landscapes is common, the complex effect of dispersal that we describe will play an important role in determining the evolutionary dynamics of many species under rapidly changing climate.

Sexual selection and mate limitation shape evolution of species' range limits.

Understanding what processes shape the formation of species' geographic range limits is one central objective linking ecology and evolutionary biology. One potentially key process is sexual selection; yet, theory examining how sexual selection could shape eco-evolutionary dynamics in marginal populations is still lacking. In species with separate sexes, range limits could be shaped by limitations in encountering mates at low densities. Sexual selection could therefore modulate mate limitation and resulting extinction-colonization dynamics at range margins, through evolution of mate encounter ability and/or mate competition traits, and their demographic consequences. We use a spatially explicit eco-genetic model to reveal how different forms of sexual selection can variably affect emerging range limits. Larger ranges emerged when sexual selection acted exclusively on traits increasing mate encounter probability, thus reducing female's mate limitation toward the range margins. In contrast, sexual selection via mate competition narrowed range limits due to increased trait-dependent mortality in males and elevated mate limitation for females. When mate encounter coevolved with mate competition, their combined effects on range limits depended on the mating system (polygyny vs. monogamy). Our results demonstrate that evolution of species' ranges may be importantly shaped by feedbacks between sexual selection and spatial population demography and dynamics.

Eco-evolutionary dynamics of range shifts: elastic margins and critical thresholds.

It is widely recognised that the response of a population to environmental change will be determined by the eco-evolutionary dynamics of dispersal. Here, modelling the evolution of dispersal distance within a species structured across an environmental gradient yields some important general insights. First, it demonstrates that 'elastic' ranges are more likely features of range-shifting dynamics than has been recently reported; when dispersal distance, rather than simply emigration rate, is modelled elastic ranges occur regardless of the nature of the environmental gradient. Second, we start to identify critical survival thresholds beyond which even the evolution of greater dispersal distance is unlikely to rescue a population. The position of such thresholds depends on a combination of genetic, demographic and environmental parameters. We find simulated species rarely survive if the location of the range front of a range-shift falls behind the optimal environmental conditions of the species. Should similar thresholds exist for real species aggressive conservation actions such as assisted colonisation are likely to be required to reduce the risk of extinction. We believe simple models, such as the one presented in this study, will be essential for providing a theoretical underpinning for more tactical eco-evolutionary models and informing conservation strategies to be employed under rapid climate change.

Inferring the distributions of fitness effects and proportions of strongly deleterious mutations.

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 a sample 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 that plth can improve the model fit when applied to individual species but underestimates 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. As plth and 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.

Uncertainty and the role of information acquisition in the evolution of context-dependent emigration.

There is increasing empirical evidence that individuals utilize social and environmental cues in making decisions as to whether or not to disperse. However, we lack theory exploring the influence of information acquisition and use on the evolution of dispersal strategies and metapopulation dynamics. We used an individual-based, spatially explicit simulation model to explore the evolution of emigration strategies under varying precision of information about the natal patch, cost of information acquisition, and environmental predictability. Our findings show an interesting interplay between information use and the evolved emigration propensity. Lack of information led to higher emigration probabilities in more unpredictable environments but to lower emigration probabilities in constant or highly predictable scenarios. Somewhat-informed dispersal strategies were selected for in most cases, even when the acquisition of information was associated with a moderate reproductive cost. Notably, selection rarely favored investment in acquisition of high-precision information, and the tendency to invest in information acquisition was greatest in predictable environments when the associated cost was low. Our results highlight that information use can affect dispersal in a complex manner and also emphasize that information-acquisition behaviors can themselves come under strong selection, resulting in evolutionary dynamics that are tightly coupled to those of context-dependent behaviors.

Strong spatial population structure shapes the temporal coevolutionary dynamics of costly female preference and male display.

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 fueling 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.

Eco-evolutionary extinction and recolonization dynamics reduce genetic load and increase time to extinction in highly inbred populations.

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.

Prospecting and informed dispersal: Understanding and predicting their joint eco-evolutionary 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.

Negative density-dependent dispersal emerges from the joint evolution of density- and body condition-dependent dispersal strategies.

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.

Genetics of dispersal.

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.