Spatial scale affects landscape genetic analysis of a wetland grasshopper

Most landscape genetic studies assess the impact of landscape elements on species' dispersal and gene flow. Many of these studies perform their analysis on all possible population pairs in a study area and do not explicitly consider the effects of spatial scale and population network topology on their results. Here, we examined the effects of spatial scale and population network topology on the outcome of a landscape genetic analysis. Additionally, we tested whether the relevant spatial scale of landscape genetic analysis could be defined by population network topology or by isolation‐by‐distance (IBD) patterns. A data set of the wetland grasshopper Stethophyma grossum, collected in a fragmented agricultural landscape, was used to analyse population network topology, IBD patterns and dispersal habitats, using least‐cost transect analysis. Landscape genetic analyses neglecting spatial scale and population network topology resulted in models with low fits, with which a most likely dispersal habitat could not be identified. In contrast, analyses considering spatial scale and population network topology resulted in high model fits by restricting landscape genetic analysis to smaller scales (0–3 km) and neighbouring populations, as represented by a Gabriel graph. These models also successfully identified a likely dispersal habitat of S. grossum. The above results suggest that spatial scale and potentially population network topology should be more explicitly considered in future landscape genetic analyses.     

Genetic differentiation and gene flow among populations of the alpine butterfly, Parnassius smintheus, vary with landscape connectivity

Levels of gene flow among populations vary both inter- and intraspecifically, and understanding the ecological bases of variation in levels of gene flow represents an important link between the ecological and evolutionary dynamics of populations. The effects of habitat spatial structure on gene flow have received considerable attention; however, most studies have been conducted at a single spatial scale and without background data on how individual movement is affected by landscape features. We examined the influence of habitat connectivity on inferred levels of gene flow in a high-altitude, meadow-dwelling butterfly, Parnassius smintheus. For this species, we had background data on the effects of landscape structure on both individual movement and on small-scale population genetic differentiation. We compared genetic differentiation and patterns of isolation by distance, based on variation at seven microsatellite loci, among three regions representing two levels of connectivity of high-altitude, nonforested habitats. We found that reduced connectivity of habitats, resulting from more forest cover at high altitudes, was associated with greater genetic differentiation among populations (higher estimated FST), a breakdown of isolation by distance, and overall lower levels of inferred gene flow. These observed differences were consistent with expectations based on our knowledge of the movement behaviour of this species and on previous population genetic analyses conducted at the smaller spatial scale. Our results indicate that the role of gene flow may vary among groups of populations depending on the interplay between individual movement and the structure of the surrounding landscape.     

Effects of landscape and history on diversification of a montane, stream-breeding amphibian

Aim The aim of this study was to understand the roles of landscape features in shaping patterns of contemporary and historical genetic diversification among populations of the Andean tree frog (Hypsiboas andinus) across spatial scales. Location Andes mountains, north‐western Argentina, South America. Methods Mitochondrial DNA control region sequences were utilized to assess genetic differentiation among populations and calculate population pair‐wise genetic distances. Three models of movement, namely traditional straight‐line distance and two effective distances based on habitat classification, were examined to determine which of these explained the most variation in pair‐wise population genetic differentiation. The two habitat classifications were based on digital vegetation and hydrology layers that were generated from a 90‐m resolution digital elevation model (DEM) and known relationships between elevation and habitat. Mantel tests were conducted to test for correlations between geographic and genetic distance matrices and to estimate the percentage variation explained by each type of geographic distance. To investigate the location of possible barriers to gene flow, we used Monmonier’s maximum difference algorithm as implemented in barrier 2.2. Results At both geographic scales, effective distances explained more variation in genetic differentiation than did straight‐line distance. The least‐cost distances based on the simple classification performed better than the more detailed habitat classification. We controlled for the effects of historical range fragmentation determined from previous nested clade analyses, and therefore evaluated the effect of different distances on the genetic variation attributable to more recent factors. Effective distances identified populations that were highly divergent as a result of isolation in unsuitable habitats. The proposed locations of barriers to gene flow identified using Monmonier’s maximum difference algorithm corresponded well with earlier analyses and supported findings from our partial Mantel tests. Main conclusions Our results indicate that landscape features have been important in both historical and contemporary genetic structuring of populations of H. andinus at both large and small spatial scales. A landscape genetic perspective offers novel insights not provided by traditional phylogeographic studies: (1) effective distances can better explain patterns of differentiation in populations, especially in heterogeneous landscapes where barriers to dispersal may be common; and (2) least‐cost path analysis can help to identify corridors of movement between populations that are biologically more realistic.     

Making the connection: expanding the role of restoration genetics in restoring and evaluating connectivity

The success of restoration activities is affected by connectivity with the surrounding landscape. From a genetic perspective, landscape connectivity can influence gene flow, effective size, and genetic diversity of populations, which in turn have impacts on the fitness and adaptive potential of species in restored areas. Researchers and practitioners are increasingly using genetic data to incorporate elements of connectivity into restoration planning and evaluation. We show that genetic studies of connectivity can improve restoration planning in three main ways. First, by comparing genetic estimates of contemporary and historical gene flow and population size, practitioners can establish historical baselines that may provide targets for restoration of connectivity. Second, empirical estimates of dispersal, landscape resistance to movement, and adaptive genetic variance can be derived from genetic data and used to parameterize existing restoration planning tools. Finally, restoration actions can also be targeted to remove barriers to gene flow or mitigate pinch‐points in corridors. We also discuss appropriate methods for evaluating the restoration of gene flow over timescales required by practitioners. Collaboration between restoration geneticists, ecologists, and practitioners is needed to develop practical and innovative ways to further incorporate connectivity into restoration practice.     

Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change

Landscape genetics seeks to determine the effect of landscape features on gene flow and genetic structure. Often, such analyses are intended to inform conservation and management. However, depending on the many factors that influence the time to reach equilibrium, genetic structure may more strongly represent past rather than contemporary landscapes. This well‐known lag between current demographic processes and population genetic structure often makes it challenging to interpret how contemporary landscapes and anthropogenic activity shape gene flow. Here, we review the theoretical framework for factors that influence time lags, summarize approaches to address this temporal disconnect in landscape genetic studies, and evaluate ways to make inferences about landscape change and its effects on species using genetic data alone or in combination with other data. Those approaches include comparing correlation of genetic structure with historical versus contemporary landscapes, using molecular markers with different rates of evolution, contrasting metrics of genetic structure and gene flow that reflect population genetic processes operating at different temporal scales, comparing historical and contemporary samples, combining genetic data with contemporary estimates of species distribution or movement, and controlling for phylogeographic history. We recommend using simulated data sets to explore time lags in genetic structure, and argue that time lags should be explicitly considered both when designing and interpreting landscape genetic studies. We conclude that the time lag problem can be exploited to strengthen inferences about recent landscape changes and to establish conservation baselines, particularly when genetic data are combined with other data.     

The influence of landscape on gene flow in the eastern massasauga rattlesnake (Sistrurus c. catenatus): insight from computer simulations

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation‐by‐distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation‐by‐distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long‐standing natural features (e.g. water bodies) co‐exist on the landscape.     

NONSTATIONARY PATTERNS OF ISOLATION‐BY‐DISTANCE: INFERRING MEASURES OF LOCAL GENETIC DIFFERENTIATION WITH BAYESIAN KRIGING

Patterns of isolation‐by‐distance (IBD) arise when population differentiation increases with increasing geographic distances. Patterns of IBD are usually caused by local spatial dispersal, which explains why differences of allele frequencies between populations accumulate with distance. However, spatial variations of demographic parameters such as migration rate or population density can generate nonstationary patterns of IBD where the rate at which genetic differentiation accumulates varies across space. To characterize nonstationary patterns of IBD, we infer local genetic differentiation based on Bayesian kriging. Local genetic differentiation for a sampled population is defined as the average genetic differentiation between the sampled population and fictive neighboring populations. To avoid defining populations in advance, the method can also be applied at the scale of individuals making it relevant for landscape genetics. Inference of local genetic differentiation relies on a matrix of pairwise similarity or dissimilarity between populations or individuals such as matrices of between pairs of populations. Simulation studies show that maps of local genetic differentiation can reveal barriers to gene flow but also other patterns such as continuous variations of gene flow across habitat. The potential of the method is illustrated with two datasets: single nucleotide polymorphisms from human Swedish populations and dominant markers for alpine plant species.     

EXAMINING THE FULL EFFECTS OF LANDSCAPE HETEROGENEITY ON SPATIAL GENETIC VARIATION: A MULTIPLE MATRIX REGRESSION APPROACH FOR QUANTIFYING GEOGRAPHIC AND ECOLOGICAL ISOLATION

Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual‐based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real‐world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.     

Dispersal ability and habitat requirements determine landscape‐level genetic patterns in desert aquatic insects

Species occupying the same geographic range can exhibit remarkably different population structures across the landscape, ranging from highly diversified to panmictic. Given limitations on collecting population‐level data for large numbers of species, ecologists seek to identify proximate organismal traits—such as dispersal ability, habitat preference and life history—that are strong predictors of realized population structure. We examined how dispersal ability and habitat structure affect the regional balance of gene flow and genetic drift within three aquatic insects that represent the range of dispersal abilities and habitat requirements observed in desert stream insect communities. For each species, we tested for linear relationships between genetic distances and geographic distances using Euclidean and landscape‐based metrics of resistance. We found that the moderate‐disperser Mesocapnia arizonensis (Plecoptera: Capniidae) has a strong isolation‐by‐distance pattern, suggesting migration–drift equilibrium. By contrast, population structure in the flightless Abedus herberti (Hemiptera: Belostomatidae) is influenced by genetic drift, while gene flow is the dominant force in the strong‐flying Boreonectes aequinoctialis (Coleoptera: Dytiscidae). The best‐fitting landscape model for M. arizonensis was based on Euclidean distance. Analyses also identified a strong spatial scale‐dependence, where landscape genetic methods only performed well for species that were intermediate in dispersal ability. Our results highlight the fact that when either gene flow or genetic drift dominates in shaping population structure, no detectable relationship between genetic and geographic distances is expected at certain spatial scales. This study provides insight into how gene flow and drift interact at the regional scale for these insects as well as the organisms that share similar habitats and dispersal abilities.     

A plea for simultaneously considering matrix quality and local environmental conditions when analysing landscape impacts on effective dispersal

Landscape genetics has tremendous potential for enhancing our understanding about landscape effects on effective dispersal and resulting genetic structures. However, the vast majority of landscape genetic studies focus on effects of the landscape among sampling locations on dispersal (i.e. matrix quality), while effects of local environmental conditions are rather neglected. Such local environmental conditions include patch size, habitat type or resource availability and are commonly used in (meta‐) population ecology and population genetics. In our opinion, landscape genetic studies would greatly benefit from simultaneously incorporating both matrix quality and local environmental conditions when assessing landscape effects on effective dispersal. To illustrate this point, we first outline the various ways in which environmental heterogeneity can influence different stages of the dispersal process. We then propose a three‐step approach for assessing local and matrix effects on effective dispersal and review how both types of effects can be considered in landscape genetic analyses. Using simulated data, we show that it is possible to correctly disentangle the relative importance of matrix quality vs. local environmental conditions for effective dispersal. We argue that differentiating local and matrix effects in such a way is crucial for predicting future species distribution and persistence, and for optimal conservation decisions that are based on landscape genetics. In sum, we think it is timely to move beyond purely statistical, pattern‐oriented analyses in landscape genetics and towards process‐oriented approaches that consider the full range of possible landscape effects on dispersal behaviour and resulting gene flow.     

Genetic differentiation that is exceptionally high and unexpectedly sensitive to geographic distance in the absence of gene flow: Insights from the genus Eranthis in East Asian regions

Genetic differentiation between populations is determined by various factors, including gene flow, selection, mutation, and genetic drift. Among these, gene flow is known to counter genetic differentiation. The genus Eranthis, an early flowering perennial herb, can serve as a good model to study genetic differentiation and gene flow due to its easily detectable population characteristics and known reproductive strategies, which can be associated with gene flow patterns. Eranthis populations are typically small and geographically separated from the others. Moreover, previous studies and our own observations suggest that seed and pollen dispersal between Eranthis populations is highly unlikely and therefore, currently, gene flow may not be probable in this genus. Based on these premises, we hypothesized that the genetic differentiation between the Eranthis populations would be significant, and that the genetic differentiation would not sensitively reflect geographic distance in the absence of gene flow. To test these hypotheses, genetic differentiation, genetic distance, isolation by distance, historical gene flow, and bottlenecks were analyzed in four species of this genus. Genetic differentiation was significantly high, and in many cases, extremely high. Moreover, genetic differentiation and geographic distance were positively correlated in most cases. We provide possible explanations for these observations. First, we suggest that the combination of the marker type used in our study (chloroplast microsatellites), genetic drift, and possibly selection might have resulted in the extremely high genetic differentiation observed herein. Additionally, we provide the possibility that genetic distance reflects geographic distance through historical gene flow, or adaptation in the absence of historical gene flow. Nevertheless, our explanations can be more rigorously examined and further refined through additional observations and various population genetic analyses. In particular, we suggest that other accessible populations of the genus Eranthis should be included in future studies to better characterize the intriguing population dynamics of this genus.     

Fine-scale population structure in a desert amphibian: landscape genetics of the black toad (Bufo exsul)

Environmental variables can strongly influence a variety of intra- and inter-population processes, including demography, population structure and gene flow. When environmental conditions are particularly harsh for a certain species, investigating these effects is important to understanding how populations persist under difficult conditions. Furthermore, species inhabiting challenging environments present excellent opportunities to examine the effects of complex landscapes on population processes because these effects will often be more pronounced. In this study, I use 16 microsatellite loci to examine population structure, gene flow and demographic history in the black toad, Bufo exsul , which has one of the most restricted natural ranges of any amphibian. Bufo exsul inhabits four springs in the Deep Springs Valley high desert basin and has never been observed more than several meters from any source of water. My results reveal limited gene flow and moderately high levels of population structure ( F _ST = 0.051–0.063) between all but the two closest springs. I found that the geographic distance across the arid scrub habitat between springs is significantly correlated with genetic structure when distance accounts for topography and barriers to dispersal. I also found very low effective population sizes ( N _e = 7–30) and substantial evidence for historical population bottlenecks in all four populations. Together, these results suggest that the desert landscape and B.   exsul 's high habitat specificity contribute significantly to population structure and demography in this species and emphasize the importance of considering behavioural and landscape data in conservation genetic studies of natural systems.     

A comparison of individual‐based genetic distance metrics for landscape genetics

A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual‐based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (although several other metrics performed similarly), but only when they were derived from multiple principal components axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.     

Microsatellites reveal regional population differentiation and isolation in Lobaria pulmonaria, an epiphytic lichen

Many lichen species produce both sexual and asexual propagules, but, aside from being minute, these diaspores lack special adaptations for long-distance dispersal. So far, molecular studies have not directly addressed isolation and genetic differentiation of lichen populations, both being affected by gene flow, at a regional scale. We used six mycobiont-specific microsatellite loci to investigate the population genetic structure of the epiphytic lichen Lobaria pulmonaria in two regions that strongly differed with respect to anthropogenic impact. In British Columbia, L. pulmonaria grows in continuous old-growth forests, while its populations in the old cultural landscape of Switzerland are comparably small and fragmented. Populations from both British Columbia and Switzerland were genetically diverse at the loci. Geographically restricted alleles, low historical gene flow, and analyses of genetic distance (upgma tree) and of differentiation (amova) indicated that populations from Vancouver Island and from the Canadian mainland were separated from each other, except for one, geographically intermediate population. This differentiation was attributed to different glacial and postglacial histories of coastal and inland populations in British Columbia. In contrast to expectations, the three investigated Swiss populations were genetically neither isolated nor differentiated from each other despite the long-lasting negative human impact on the lichen's range size in Central Europe. We propose that detailed studies integrating local landscape and regional scales are now needed to understand the processes of dispersal and gene flow in lichens.     

Surprisingly little population genetic structure in a fungus‐associated beetle despite its exploitation of multiple hosts

In heterogeneous environments, landscape features directly affect the structure of genetic variation among populations by functioning as barriers to gene flow. Resource‐associated population genetic structure, in which populations that use different resources (e.g., host plants) are genetically distinct, is a well‐studied example of how environmental heterogeneity structures populations. However, the pattern that emerges in a given landscape should depend on its particular combination of resources. If resources constitute barriers to gene flow, population differentiation should be lowest in homogeneous landscapes, and highest where resources exist in equal proportions. In this study, we tested whether host community diversity affects population genetic structure in a beetle (Bolitotherus cornutus) that exploits three sympatric host fungi. We collected B. cornutus from plots containing the three host fungi in different proportions and quantified population genetic structure in each plot using a panel of microsatellite loci. We found no relationship between host community diversity and population differentiation in this species; however, we also found no evidence of resource‐associated differentiation, suggesting that host fungi are not substantial barriers to gene flow. Moreover, we detected no genetic differentiation among B. cornutus populations separated by several kilometers, even though a previous study demonstrated moderate genetic structure on the scale of a few hundred meters. Although we found no effect of community diversity on population genetic structure in this study, the role of host communities in the structuring of genetic variation in heterogeneous landscapes should be further explored in a species that exhibits resource‐associated population genetic structure.     

Intercontinental long‐distance seed dispersal across the Mediterranean Basin explains population genetic structure of a bird‐dispersed shrub

Long‐distance dispersal (LDD) is a pivotal process for plants determining their range of distribution and promoting gene flow among distant populations. Most fleshy‐fruited species rely on frugivorous vertebrates to disperse their seeds across the landscape. While LDD events are difficult to record, a few ecological studies have shown that birds move a sizeable number of ingested seeds across geographic barriers, such as sea straits. The foraging movements of migrant frugivores across distant populations, including those separated by geographic barriers, creates a constant flow of propagules that in turn shapes the spatial distributions of the genetic variation in populations. Here, we have analysed the genetic diversity and structure of 74 populations of Pistacia lentiscus, a fleshy‐fruited shrub widely distributed in the Mediterranean Basin, to elucidate whether the Mediterranean Sea acts as a geographic barrier or alternatively whether migratory frugivorous birds promote gene flow among populations located on both sides of the sea. Our results show reduced genetic distances among populations, including intercontinental populations, and they show a significant genetic structure across an eastern‐western axis. These findings are consistent with known bird migratory routes that connect the European and African continents following a north‐southwards direction during the fruiting season of many fleshy‐fruited plants. Further, approximate Bayesian analysis failed to explain the observed patterns as a result of historical population migrations at the end of Last Glacial Maximum. Therefore, anthropic and/or climatic changes that would disrupt the migratory routes of frugivorous birds might have genetic consequences for the plant species they feed upon.     

Nonequilibrium conditions following landscape rearrangement: the relative contribution of past and current hydrological landscapes on the genetic structure of a stream-dwelling fish

Interpreting patterns of population structure in nature is often challenging, especially in dynamic landscapes where population genetic connectivity evolves over time. In this study, we document the absence of migration-drift equilibrium in a stream-dwelling euryhaline fish resulting from past fine-scale drainage rearrangements and evaluate the relative contribution of past and current hydrological landscapes on observed population structure. Based on allelic variation at nine microsatellite loci, genetic relationships among 12 populations of brook charr, Salvelinus fontinalis, from Gros Morne National Park of Canada (GMNP, Newfoundland, Canada) did not reflect current stream hierarchical structure. In addition, we observed no correlation between population differentiation and contemporary landscape features (waterway distance and sums of altitudinal differences). Instead, population relationships were consistent with historical hydrological structure predicted a priori based on geomorphological and biogeographical evidences. Also, population differentiation was strongly correlated with inferred historical landscape features. Contemporary barriers have apparently preserved the signature of past genetic connectivity by constraining gene flow. Based on the relationships between population differentiation and current and past landscape features at various spatial scales, we suggest that brook charr genetic diversity in GMNP is mostly the result of small distance migrations at the time of colonization and subsequent differentiation through drift. This study highlights the potential of approaching landscapes from a combination of contemporary and historical perspectives when interpreting nonequilibrium population structures resulting from landscape rearrangement.     

Disentangling the effects of historic vs. contemporary landscape structure on population genetic divergence

Increasing habitat fragmentation poses an immediate threat to population viability, as gene flow patterns are changed in these altered landscapes. Patterns of genetic divergence can potentially reveal the impact of these shifts in landscape connectivity. However, divergence patterns not only carry the signature of altered contemporary landscapes, but also historical ones. When considered separately, both recent and historical landscape structure appear to significantly affect connectivity among 51 wood frog ( Rana sylvatica ) populations. However, by controlling for correlations among landscape structure from multiple time periods, we show that patterns of genetic divergence reflect recent landscape structure as opposed to landscape structure prior to European settlement of the region (before 1850s). At the same time, within-population genetic diversities remain high and a genetic signature of population bottlenecks is lacking. Together, these results suggest that metapopulation processes – not drift-induced divergence associated with strong demographic bottlenecks following habitat loss – underlie the strikingly rapid consequences of temporally shifting landscape structure on these amphibians. We discuss the implications of these results in the context of understanding the role of population demography in the adaptive variation observed in wood frog populations.     

Alleles versus mutations: Understanding the evolution of genetic architecture requires a molecular perspective on allelic origins

Perspectives on the role of large‐effect quantitative trait loci (QTL) in the evolution of complex traits have shifted back and forth over the past few decades. Different sets of studies have produced contradictory insights on the evolution of genetic architecture. I argue that much of the confusion results from a failure to distinguish mutational and allelic effects, a limitation of using the Fisherian model of adaptive evolution as the lens through which the evolution of adaptive variation is examined. A molecular‐based perspective reveals that allelic differences can involve the cumulative effects of many mutations plus intragenic recombination, a model that is supported by extensive empirical evidence. I discuss how different selection regimes could produce very different architectures of allelic effects under a molecular‐based model, which may explain conflicting insights on genetic architecture from studies of variation within populations versus between divergently selected populations. I address shortcomings of genome‐wide association study (GWAS) practices in light of more suitable models of allelic evolution, and suggest alternate GWAS strategies to generate more valid inferences about genetic architecture. Finally, I discuss how adopting more suitable models of allelic evolution could help redirect research on complex trait evolution toward addressing more meaningful questions in evolutionary biology.