A network approach to modeling population aggregation and genetic control of pest insects

Historically, models of the invasion and biological control of insect pests have omitted heterogeneities in the spatial structure of the targeted populations. In this study, we use stochastic network simulations to examine explicitly population heterogeneity as a function of landscape structure and insect behavior. We show that when insects are distributed non-randomly across a heterogeneous landscape, control can be significantly hindered. However, when insect populations are clustered as a result of limited dispersal, genetic control efficiency can be enhanced. In developing the model, we relax a key assumption of previous theoretical studies of genetic control: that released genetic control insects remain homogenously distributed irrespective of the spatial structure of the wild type populations. Here, this behavior (termed the ‘coverage proportion’) is parameterized and its properties are explored. We show that landscape heterogeneity and limited dispersal have little effect on the critical coverage proportion necessary for control.     

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.     

Spatial heterogeneity in landscape structure influences dispersal and genetic structure: empirical evidence from a grasshopper in an agricultural landscape

Dispersal may be strongly influenced by landscape and habitat characteristics that could either enhance or restrict movements of organisms. Therefore, spatial heterogeneity in landscape structure could influence gene flow and the spatial structure of populations. In the past decades, agricultural intensification has led to the reduction in grassland surfaces, their fragmentation and intensification. As these changes are not homogeneously distributed in landscapes, they have resulted in spatial heterogeneity with generally less intensified hedged farmland areas remaining alongside streams and rivers. In this study, we assessed spatial pattern of abundance and population genetic structure of a flightless grasshopper species, Pezotettix giornae, based on the surveys of 363 grasslands in a 430‐km² agricultural landscape of western France. Data were analysed using geostatistics and landscape genetics based on microsatellites markers and computer simulations. Results suggested that small‐scale intense dispersal allows this species to survive in intensive agricultural landscapes. A complex spatial genetic structure related to landscape and habitat characteristics was also detected. Two P. giornae genetic clusters bisected by a linear hedged farmland were inferred from clustering analyses. This linear hedged farmland was characterized by high hedgerow and grassland density as well as higher grassland temporal stability that were suspected to slow down dispersal. Computer simulations demonstrated that a linear‐shaped landscape feature limiting dispersal could be detected as a barrier to gene flow and generate the observed genetic pattern. This study illustrates the relevance of using computer simulations to test hypotheses in landscape genetics studies.     

Landscape configuration determines gene flow and phenotype in a flightless forest-edge ground-dwelling bush-cricket, Pholidoptera griseoaptera

Spatial configuration of habitats influences genetic structure and population fitness whereas it affects mainly species with limited dispersal ability. To reveal how habitat fragmentation determines dispersal and dispersal-related morphology in a ground-dispersing insect species we used a bush-cricket (Pholidoptera griseoaptera) which is associated with forest-edge habitat. We analysed spatial genetic patterns together with variability of the phenotype in two forested landscapes with different levels of fragmentation. While spatial configuration of forest habitats did not negatively affect genetic characteristics related to the fitness of sampled populations, genetic differentiation was found higher among populations from an extensive forest. Compared to an agricultural matrix between forest patches, the matrix of extensive forest had lower permeability and posed barriers for the dispersal of this species. Landscape configuration significantly affected also morphological traits that are supposed to account for species dispersal potential; individuals from fragmented forest patches had longer hind femurs and a higher femur to pronotum ratio. This result suggests that selection pressure act differently on populations from both landscape types since dispersal-related morphology was related to the level of habitat fragmentation. Thus observed patterns may be explained as plastic according to the level of landscape configuration; while anthropogenic fragmentation of habitats for this species can lead to homogenization of spatial genetic structure.     

FINE‐SCALE GENETIC STRUCTURE IN A WILD BIRD POPULATION: THE ROLE OF LIMITED DISPERSAL AND ENVIRONMENTALLY BASED SELECTION AS CAUSAL FACTORS

Individuals are typically not randomly distributed in space; consequently ecological and evolutionary theory depends heavily on understanding the spatial structure of populations. The central challenge of landscape genetics is therefore to link spatial heterogeneity of environments to population genetic structure. Here, we employ multivariate spatial analyses to identify environmentally induced genetic structures in a single breeding population of 1174 great tits Parus major genotyped at 4701 single‐nucleotide polymorphism (SNP) loci. Despite the small spatial scale of the study relative to natal dispersal, we found multiple axes of genetic structure. We built distance‐based Moran's eigenvector maps to identify axes of pure spatial variation, which we used for spatial correction of regressions between SNPs and various external traits known to be related to fitness components (avian malaria infection risk, local density of conspecifics, oak tree density, and altitude). We found clear evidence of fine‐scale genetic structure, with 21, seven, and nine significant SNPs, respectively, associated with infection risk by two species of avian malaria (Plasmodium circumflexum and P. relictum) and local conspecific density. Such fine‐scale genetic structure relative to dispersal capabilities suggests ecological and evolutionary mechanisms maintain within‐population genetic diversity in this population with the potential to drive microevolutionary change.     

Scale-Dependent Effects of a Heterogeneous Landscape on Genetic Differentiation in the Central American Squirrel Monkey (Saimiri oerstedii)

Landscape genetic studies offer a fine-scale understanding of how habitat heterogeneity influences population genetic structure. We examined population genetic structure and conducted a landscape genetic analysis for the endangered Central American Squirrel Monkey (Saimiri oerstedii) that lives in the fragmented, human-modified habitats of the Central Pacific region of Costa Rica. We analyzed non-invasively collected fecal samples from 244 individuals from 14 groups for 16 microsatellite markers. We found two geographically separate genetic clusters in the Central Pacific region with evidence of recent gene flow among them. We also found significant differentiation among groups of S. o. citrinellus using pairwise F(ST) comparisons. These groups are in fragments of secondary forest separated by unsuitable "matrix" habitats such as cattle pasture, commercial African oil palm plantations, and human residential areas. We used an individual-based landscape genetic approach to measure spatial patterns of genetic variance while taking into account landscape heterogeneity. We found that large, commercial oil palm plantations represent moderate barriers to gene flow between populations, but cattle pastures, rivers, and residential areas do not. However, the influence of oil palm plantations on genetic variance was diminished when we restricted analyses to within population pairs, suggesting that their effect is scale-dependent and manifests during longer dispersal events among populations. We show that when landscape genetic methods are applied rigorously and at the right scale, they are sensitive enough to track population processes even in species with long, overlapping generations such as primates. Thus landscape genetic approaches are extremely valuable for the conservation management of a diverse array of endangered species in heterogeneous, human-modified habitats. Our results also stress the importance of explicitly considering the heterogeneity of matrix habitats in landscape genetic studies, instead of assuming that all matrix habitats have a uniform effect on population genetic processes.     

Identification of subpopulations from connectivity matrices

Dispersal on the landscape/seascape scale may lead to complex spatial population structure with non‐synchronous demography and genetic divergence. In this study we present a novel approach to identify subpopulations and dispersal barriers based on estimates of dispersal probabilities on the landscape scale. A theoretical framework is presented where the landscape connectivity matrix is analyzed for clusters as a signature of partially isolated subpopulations. Identification of subpopulations is formulated as a minimization problem with a tuneable penalty term that makes it possible to generate population subdivisions with varying degree of dispersal restrictions. We show that this approach produces superior results compared to alternative standard methods. We apply this theory to a dataset of modeled dispersal probabilities for a sessile marine invertebrate with free‐swimming larvae in the Baltic Sea. For a range of critical connectivities we produce a hierarchical partitioning into subpopulations spanning dispersal probabilities that are typical for both genetic divergence and demographic independence. The mapping of subpopulations suggests that the Baltic Sea includes a fine‐scale (100–600 km) mosaic of invisible dispersal barriers. An analysis of the present network of marine protected areas reveal that protection is very unevenly distributed among the suggested subpopulations. Our approach can be used to assess the location and strength of dispersal barriers in the landscape, and identify conservation units when extensive genotyping is prohibitively costly to cover necessary spatial and temporal scales, e.g. in spatial management of marine populations.     

Population spread in patchy landscapes under a strong Allee effect

Many species of invasive insects establish and spread in regions around the world, causing enormous economical and environmental damage, in particular in forests. Some of these insects are subject to an Allee effect whereby the population must surpass a certain threshold in order to establish. Recent studies have examined the possibility of exploiting an Allee effect to improve existing control strategies. Forests and most other ecosystems show natural spatial variation, and human activities frequently increase the degree of spatial heterogeneity. It is therefore imperative to understand how the interplay between this spatial variation and individual movement behavior affects the overall speed of spread of an invasion. To this end, we study an integrodifference equation model in a patchy landscape and with Allee growth dynamics. Movement behavior of individuals varies according to landscape quality. Our study focuses on how the speed of the resulting traveling periodic wave depends on the interaction between landscape fragmentation, patch-dependent dispersal, and Allee population dynamics.     

Spatial genetic structure of a small rodent in a heterogeneous landscape

Gene flow in natural populations may be strongly influenced by landscape features. The integration of landscape characteristics in population genetic studies may thus improve our understanding of population functioning. In this study, we investigated the population genetic structure and gene flow pattern for the common vole, Microtus arvalis, in a heterogeneous landscape characterised by strong spatial and temporal variation. The studied area is an intensive agricultural zone of approximately 500 km² crossed by a motorway. We used individual-based Bayesian methods to define the number of population units and their spatial borders without prior delimitation of such units. Unexpectedly, we determined a single genetic unit that covered the entire area studied. In particular, the motorway considered as a likely barrier to dispersal was not associated with any spatial genetic discontinuity. Using computer simulations, we demonstrated that recent anthropogenic barriers to effective dispersal are difficult to detect through analysis of genetic variation for species with large effective population sizes. We observed a slight, but significant, pattern of isolation by distance over the whole study site. Spatial autocorrelation analyses detected genetic structuring on a local scale, most probably due to the social organisation of the study species. Overall, our analysis suggests intense small-scale dispersal associated with a large effective population size. High dispersal rates may be imposed by the strong spatio-temporal heterogeneity of habitat quality, which characterises intensive agroecosystems.     

Do landscape processes predict phylogeographic patterns in the wood frog?

Understanding factors that influence population connectivity and the spatial distribution of genetic variation is a major goal in molecular ecology. Improvements in the availability of high-resolution geographic data have made it increasingly possible to quantify the effects of landscape features on dispersal and genetic structure. However, most studies examining such landscape effects have been conducted at very fine (e.g. landscape genetics) or broad (e.g. phylogeography) spatial scales. Thus, the extent to which processes operating at fine spatial scales are linked to patterns at larger scales remains unclear. Here, we test whether factors impacting wood frog dispersal at fine spatial scales are correlated with genetic structure at regional scales. Using recently developed methods borrowed from electrical circuit theory, we generated landscape resistance matrices among wood frog populations in eastern North America based on slope, a wetness index, land cover and absolute barriers to wood frog dispersal. We then determined whether these matrices are correlated with genetic structure based on six microsatellite markers and whether such correlations outperform a landscape-free model of isolation by resistance. We observed significant genetic structure at regional spatial scales. However, topography and landscape variables associated with the intervening habitat between sites provide little explanation for patterns of genetic structure. Instead, absolute dispersal barriers appear to be the best predictor of regional genetic structure in this species. Our results suggest that landscape variables that influence dispersal, microhabitat selection and population structure at fine spatial scales do not necessarily explain patterns of genetic structure at broader scales.     

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.     

Landscape genetics in the subterranean rodent <Emphasis Type="Italic">Ctenomys</Emphasis> “<Emphasis Type="Italic">chasiquensis</Emphasis>” associated with highly disturbed habitats from the southeastern Pampas region,Argentina

Studies of genetic differentiation in fragmented environments help us to identify those landscape features that most affect gene flow and dispersal patterns. Particularly, the assessment of the relative significance of intrinsic biological and environmental factors affecting the genetic structure of populations becomes crucial. In this work, we assess the current dispersal patterns and population structure of Ctenomys “chasiquensis”, a vulnerable and endemic subterranean rodent distributed on a small area in Central Argentina, using 9 polymorphic microsatellite loci. We use landscape genetics approaches to assess the relationship between genetic connectivity among populations and environmental attributes. Our analyses show that populations of C. “chasiquensis” are moderately to highly structured at a regional level. This pattern is most likely the outcome of substantial gene flow on the more homogeneous sand dune habitat of the Northwest of its distributional range, in conjunction with an important degree of isolation of eastern and southwestern populations, where the optimal habitat is surrounded by a highly fragmented landscape. Landscape genetics analysis suggests that habitat quality and longitude were the environmental factors most strongly associated with genetic differentiation/uniqueness of populations. In conclusion, our results indicate an important genetic structure in this species, even at a small spatial scale, suggesting that contemporary habitat fragmentation increases population differentiation.     

Genetic spatial autocorrelation can readily detect sex-biased dispersal

Sex-biased dispersal is expected to generate differences in the fine-scale genetic structure of males and females. Therefore, spatial analyses of multilocus genotypes may offer a powerful approach for detecting sex-biased dispersal in natural populations. However, the effects of sex-biased dispersal on fine-scale genetic structure have not been explored. We used simulations and multilocus spatial autocorrelation analysis to investigate how sex-biased dispersal influences fine-scale genetic structure. We evaluated three statistical tests for detecting sex-biased dispersal: bootstrap confidence intervals about autocorrelation r values and recently developed heterogeneity tests at the distance class and whole correlogram levels. Even modest sex bias in dispersal resulted in significantly different fine-scale spatial autocorrelation patterns between the sexes. This was particularly evident when dispersal was strongly restricted in the less-dispersing sex (mean distance <200 m), when differences between the sexes were readily detected over short distances. All tests had high power to detect sex-biased dispersal with large sample sizes (n ≥ 250). However, there was variation in type I error rates among the tests, for which we offer specific recommendations. We found congruence between simulation predictions and empirical data from the agile antechinus, a species that exhibits male-biased dispersal, confirming the power of individual-based genetic analysis to provide insights into asymmetries in male and female dispersal. Our key recommendations for using multilocus spatial autocorrelation analyses to test for sex-biased dispersal are: (i) maximize sample size, not locus number; (ii) concentrate sampling within the scale of positive structure; (iii) evaluate several distance class sizes; (iv) use appropriate methods when combining data from multiple populations; (v) compare the appropriate groups of individuals.     

Apparent widespread gene flow in the predominantly flightless planthopper Tumidagena minuta

1. To determine whether dispersal biology can predict the pattern of population‐genetic variation among insect populations accurately, allozyme variation was assayed for populations of a saltmarsh planthopper, Tumidagena minuta, in which > 99% of the adults are flightless. 2. The pattern of genetic isolation by distance in T. minuta was compared with that in other insects, to determine whether it was similar to isolation by distance in other sedentary insects. 3. In contrast to predictions, the pattern of isolation by distance in T. minuta was most similar to that seen in the most mobile insects in a recent review of population‐genetic variation in insects. Furthermore, population‐genetic subdivision over a spatial scale of > 400 km was weak. 4. Possible causes of the apparent contradiction between dispersal biology and population‐genetic structure in this species are discussed. The results for T. minuta highlight the fact that although mobility is generally correlated with gene flow in insects, studies of population‐genetic variation must be combined with direct studies of dispersal to understand fully the degree to which populations exchange individuals.     

Spatial population genomics of the brown rat (Rattus norvegicus) in New York City

Human commensal species such as rodent pests are often widely distributed across cities and threaten both infrastructure and public health. Spatially explicit population genomic methods provide insights into movements for cryptic pests that drive evolutionary connectivity across multiple spatial scales. We examined spatial patterns of neutral genomewide variation in brown rats (Rattus norvegicus) across Manhattan, New York City (NYC), using 262 samples and 61,401 SNPs to understand (i) relatedness among nearby individuals and the extent of spatial genetic structure in a discrete urban landscape; (ii) the geographic origin of NYC rats, using a large, previously published data set of global rat genotypes; and (iii) heterogeneity in gene flow across the city, particularly deviations from isolation by distance. We found that rats separated by ≤200 m exhibit strong spatial autocorrelation (r = .3, p = .001) and the effects of localized genetic drift extend to a range of 1,400 m. Across Manhattan, rats exhibited a homogeneous population origin from rats that likely invaded from Great Britain. While traditional approaches identified a single evolutionary cluster with clinal structure across Manhattan, recently developed methods (e.g., fineSTRUCTURE, sPCA, EEMS) provided evidence of reduced dispersal across the island's less residential Midtown region resulting in fine‐scale genetic structuring (F_ST = 0.01) and two evolutionary clusters (Uptown and Downtown Manhattan). Thus, while some urban populations of human commensals may appear to be continuously distributed, landscape heterogeneity within cities can drive differences in habitat quality and dispersal, with implications for the spatial distribution of genomic variation, population management and the study of widely distributed pests.     

Sex-Biased Dispersal at Different Geographical Scales in a Cooperative Breeder from Fragmented Rainforest

Dispersal affects both social behavior and population structure and is therefore a key determinant of long-term population persistence. However, dispersal strategies and responses to spatial habitat alteration may differ between sexes. Here we analyzed spatial and temporal variation in ten polymorphic microsatellite DNA loci of male and female Cabanis’s greenbuls ( Phyllastrephus cabanisi ), a cooperative breeder of Afrotropical rainforest, to quantify rates of gene flow and fine-grained genetic structuring within and among fragmented populations. We found genetic evidence for female-biased dispersal at small spatial scales, but not at the landscape level. Local autocorrelation analysis provided evidence of positive genetic structure within 300 m distance ranges, which is consistent with behavioral observations of short-distance natal dispersal. At a landscape scale, individual-based autocorrelation values decreased over time while levels of admixture increased, possibly indicating increased gene flow over the past decade.     

Spatial genetic structure and dispersal of giant pandas on a mountain-range scale

Understanding the spatial genetic structure of populations can provide insight into the ecological or evolutionary processes of the species, and enable wise conservation decisions. We examined the spatial genetic structure of a giant panda (Ailuropoda melanoleuca) population in a heterogeneous mountainous landscape using noninvasive genetic sampling and 12 microsatellite loci. Nonrandom genetic structure was detected through spatial autocorrelation analysis, demonstrating a significantly positive autocorrelation over closer distances. Additional spatial analyses showed significantly positive genetic correlation among spatially-proximate males, and no correlation among females and among male–female pairs. These findings suggest a female-biased dispersal pattern and cryptic family grouping among giant pandas on a large mountain-range scale. The spatial extent of genetic structure occurred within 12.5 km, measured by a least-cost path distance model integrating information of habitat quality and habitat preferences of this species. Using the bearing analysis of PASSAGE, we found that directional genetic autocorrelations were in agreement with habitat structure, and habitat heterogeneity may affect the direction of giant panda dispersal. The characterization of spatial genetic structure can provide potentially valuable information for the conservation and management of giant pandas and their habitat.     

Life‐stage differences in spatial genetic structure in an irruptive forest insect: implications for dispersal and spatial synchrony

Dispersal determines the flux of individuals, energy and information and is therefore a key determinant of ecological and evolutionary dynamics. Yet, it remains difficult to quantify its importance relative to other factors. This is particularly true in cyclic populations in which demography, drift and dispersal contribute to spatio‐temporal variability in genetic structure. Improved understanding of how dispersal influences spatial genetic structure is needed to disentangle the multiple processes that give rise to spatial synchrony in irruptive species. In this study, we examined spatial genetic structure in an economically important irruptive forest insect, the spruce budworm (Choristoneura fumiferana) to better characterize how dispersal, demography and ecological context interact to influence spatial synchrony in a localized outbreak. We characterized spatial variation in microsatellite allele frequencies using 231 individuals and seven geographic locations. We show that (i) gene flow among populations is likely very high (F_st ≈ 0); (ii) despite an overall low level of genetic structure, important differences exist between adult (moth) and juvenile (larvae) life stages; and (iii) the localized outbreak is the likely source of moths captured elsewhere in our study area. This study demonstrates the potential of using molecular methods to distinguish residents from migrants and for understanding how dispersal contributes to spatial synchronization. In irruptive populations, the strength of genetic structure depends on the timing of data collection (e.g. trough vs. peak), location and dispersal. Taking into account this ecological context allows us to make more general characterizations of how dispersal can affect spatial synchrony in irruptive populations.     

Spatial genetic structure among and within populations of Primula sieboldii growing beside separate streams

We investigated the hierarchical genetic structure of SSR (simple sequence repeats) and cpDNA (chloroplast DNA) polymorphisms among and within populations of Primula sieboldii, a heterostylous clonal herb. Seven out of eight populations at the study site, located in a mountainous region of Nagano Prefecture, had each developed alongside a different stream, and the other occurred on a flat area 70 m from the nearest stream. The magnitude of genetic differentiation among streamside populations in maternally inherited cpDNA (Phi = 0.341) was much higher than that in biparentally inherited SSRs (Phi = 0.011). This result suggests that seed dispersal among streams was restricted, and pollen was the primary agent of gene flow among streamside populations. In contrast, genetic differentiation among subpopulations within streams were low at both markers (Phi = 0.053 for cpDNA, Phi = 0.025 for SSR). This low differentiation among subpopulations in cpDNA compared with that among streamside populations suggest that seed dispersal occur along the stream probably during flooding. This hypothesis was supported by the fact that in cpDNA haplotypes, no clear genetic structure was detected within the streamside population, while a significant genetic structure was found within 20 m in the nonstreamside population. Furthermore, within the streamside populations, two pairs of ramets with identical multilocus genotypes for eight SSR loci were distantly (> 50 m) distributed along the same streamside, suggesting dispersal of clonal propagule. Our study showed that the heterogeneity of the landscape can influence gene flow and hence spatial genetic structure.     

Spatial genetic patterns indicate mechanism and consequences of large carnivore cohabitation within development

Patterns of human development are shifting from concentrated housing toward sprawled housing intermixed with natural land cover, and wildlife species increasingly persist in close proximity to housing, roads, and other anthropogenic features. These associations can alter population dynamics and evolutionary trajectories. Large carnivores increasingly occupy urban peripheries, yet the ecological consequences for populations established entirely within urban and exurban landscapes are largely unknown. We applied a spatial and landscape genetics approach, using noninvasively collected genetic data, to identify differences in black bear spatial genetic patterns across a rural‐to‐urban gradient and quantify how development affects spatial genetic processes. We quantified differences in black bear dispersal, spatial genetic structure, and migration between differing levels of development within a population primarily occupying areas with >6 houses/km² in western Connecticut. Increased development disrupted spatial genetic structure, and we found an association between increased housing densities and longer dispersal. We also found evidence that roads limited gene flow among bears in more rural areas, yet had no effect among bears in more developed ones. These results suggest dispersal behavior is condition‐dependent and indicate the potential for landscapes intermixing development and natural land cover to facilitate shifts toward increased dispersal. These changes can affect patterns of range expansion and the phenotypic and genetic composition of surrounding populations. We found evidence that subpopulations occupying more developed landscapes may be sustained by male‐biased immigration, creating potentially detrimental demographic shifts.