Mechanistic home range models capture spatial patterns and dynamics of coyote territories in Yellowstone

Patterns of space-use by individuals are fundamental to the ecology of animal populations influencing their social organization, mating systems, demography and the spatial distribution of prey and competitors. To date, the principal method used to analyse the underlying determinants of animal home range patterns has been resource selection analysis (RSA), a spatially implicit approach that examines the relative frequencies of animal relocations in relation to landscape attributes. In this analysis, we adopt an alternative approach, using a series of mechanistic home range models to analyse observed patterns of territorial space-use by coyote packs in the heterogeneous landscape of Yellowstone National Park. Unlike RSAs, mechanistic home range models are derived from underlying correlated random walk models of individual movement behaviour, and yield spatially explicit predictions for patterns of space-use by individuals. As we show here, mechanistic home range models can be used to determine the underlying determinants of animal home range patterns, incorporating both movement responses to underlying landscape heterogeneities and the effects of behavioural interactions between individuals. Our analysis indicates that the spatial arrangement of coyote territories in Yellowstone is determined by the spatial distribution of prey resources and an avoidance response to the presence of neighbouring packs. We then show how the fitted mechanistic home range model can be used to correctly predict observed shifts in the patterns of coyote space-use in response to perturbation.     

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad‐scale spatial‐temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter‐annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi‐scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter‐annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 10⁶ tortoise re‐locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio‐temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non‐migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large‐scale predictions for movement strategies, based on environmental structuring, with finer‐scale analysis of space‐use. Integrating different organizational levels of analysis provides a deeper understanding of the eco‐evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.     

Physiologically structured models – from versatile technique to ecological theory

A ubiquitous feature of natural communities is the variation in size that can be observed between organisms, a variation that to a substantial degree is intraspecific. Size variation within species by necessity implies that ecological interactions vary both in intensity and type over the life cycle of an individual. Physiologically structured population models (PSPMs) constitute a modelling approach especially designed to analyse these size‐dependent interactions as they explicitly link individual level processes such as consumption and growth to population dynamics. We discuss two cases where PSPMs have been used to analyse the dynamics of size‐structured populations. In the first case, a model of a size‐structured consumer population feeding on a non‐structured prey was successful in predicting both qualitative (mechanisms) and quantitative (individual growth, survival, cycle amplitude) aspects of the population dynamics of a planktivorous fish population. We conclude that single generation cycles as a result of intercohort competition is a general outcome of size‐structured consumer–resource interactions. In the second case, involving both cohort competition and cannibalism, we show that PSPMs may predict double asymptotic growth trajectories with individuals ending up as giants. These growth trajectories, which have also been observed in field data, could not be predicted from individual level information, but are emergent properties of the population feedback on individual processes. In contrast to the size‐structured consumer–resource model, the dynamics in this case cannot be reduced to simpler lumped stage‐based models, but can only be analysed within the domain of PSPMs. Parameter values used in PSPMs adhere to the individual level and are derived independently from the system at focus, whereas model predictions involve both population level processes and individual level processes under conditions of population feedback. This leads to an increased ability to test model predictions but also to a larger set of variables that is predicted at both the individual and population level. The results turn out to be relatively robust to specific model assumptions and thus render a higher degree of generality than purely individual‐based models. At the same time, PSPMs offer a much higher degree of realism, precision and testing ability than lumped stage‐based or non‐structured models. The results of our analyses so far suggest that also in more complex species configurations only a limited set of mechanisms determines the dynamics of PSPMs. We therefore conclude that there is a high potential for developing an individual‐based, size‐dependent community theory using PSPMs.     

Spatiotemporal food web dynamics along a desert riparian–upland transition

Increased awareness of spatiotemporal variation in species interactions has motivated the study of temporally-resolved food web dynamics at the landscape level. Empiricists have focused attention on cross-habitat flows of materials, nutrients, and prey, largely ignoring the movement of predators between habitats that differ in productivity (and how predators integrate pulses in resource availability over time). We set out to study seasonal variation in food web interactions between mammalian carnivores and their rodent prey along a riparian–upland gradient in semi-arid southeastern Arizona which features both spatial and temporal heterogeneity in resource availability. Specifically, we tested whether mammalian carnivores spill over from productive, near-river habitats into adjacent, desert-scrub habitats; and if they do, to document the effects of this spillover on rodent communities. Furthermore, we examined seasonal variation in top-down effects by measuring changes in carnivore diet and distribution patterns and rodent populations over time. The results indicate that carnivores track seasonally-abundant resources across the landscape, varying both their diet and movement patterns. In turn, desert-scrub rodent population dynamics track seasonal shifts in carnivore habitat use but not resource availability, suggesting that predation plays a role in structuring rodent communities along the San Pedro River. Further evidence comes from data on rodent community composition, which differs between desert-scrub habitats near and far from the river, despite similarities in resource availability. Our data also suggest that seasonal omnivory helps predators survive lean times, increasing their effects on prey populations. Taken together, these results underscore the importance of spatiotemporal variation in species interactions, highlighting the complexity of natural systems and the need for further detailed studies of food web dynamics.     

Spatial population structure of a specialist leaf-mining moth

1. The spatial structure of natural populations may profoundly influence their dynamics. Depending on the frequency of movements among local populations and the consequent balance between local and regional population processes, earlier work has attempted to classify metapopulations into clear-cut categories, ranging from patchy populations to sets of remnant populations. In an alternative, dichotomous scheme, local populations have been classified as self-sustaining populations generating a surplus of individuals (sources) and those depending on immigration for persistence (sinks). 2. In this paper, we describe the spatial population structure of the leaf-mining moth Tischeria ekebladella, a specialist herbivore of the pedunculate oak Quercus robur. We relate moth dispersal to the distribution of oaks on Wattkast, a small island (5 km(2)) off the south-western coast of Finland. 3. We build a spatially realistic metapopulation model derived from assumptions concerning the behaviour of individual moths, and show that the model is able to explain part of the variation in observed patterns of occurrence and colonization. 4. While the species was always present on large trees, a considerable proportion of the local populations associated with small oaks showed extinction-recolonization dynamics. The vast majority of moth individuals occur on large trees. 5. According to model predictions, the dominance of local vs. regional processes in tree-specific moth dynamics varies drastically across the landscape. Most local populations may be defined broadly as 'sinks', as model simulations suggest that in the absence of immigration, only the largest oaks will sustain viable moth populations. Large trees in areas of high oak density will contribute most to the overall persistence of the metapopulation by acting as sources of moths colonizing other trees. 6. No single 'metapopulation type' will suffice to describe the oak-moth system. Instead, our study supports the notion that real populations are often a mix of earlier identified categories. The level to which local populations may persist after landscape modification will vary across the landscape, and sweeping classifications of metapopulations into single categories will contribute little to understanding how individual local populations contribute to the overall persistence of the system.     

From local interactions to population dynamics in site-based models of ecology

A central problem in ecology is relating the interactions of individuals-described in terms of competition, predation, interference, etc.-to the dynamics of the populations of these individuals-in terms of change in numbers of individuals over time. Here, we address this problem for a class of site-based ecological models, where local interactions between individuals take place at a finite number of discrete resource sites over non-overlapping generations and, between generations, individuals move randomly between sites over the entire system. Such site-based models have previously been applied to a wide range of ecological systems: from those involving contest or scramble competition for resources to host-parasite interactions and meta-populations. We show how the population dynamics of site-based models can be accurately approximated by and understood through deterministic and stochastic difference equations. Conversely, we use the inverse of this approximation to show what implicit assumptions are made about individual interactions by modelling of population dynamics in terms of difference equations. To this end, we prove a useful and general theorem: that any model in our class of site-based models has a corresponding stochastic difference equation population model, by which it can be approximated. This theorem allows us to calculate long-term population dynamics, evolutionary stable strategies and, by extending our theory to account for large deviations, extinction probabilities for a wide range of site-based systems. Our methodology is then illustrated to various examples of between species competition, predator-prey interactions and co-operation.     

Movement can mediate temporal mismatches between resource availability and biological events in host–pathogen interactions

Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species’ populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host–pathogen systems. We adapted an established individual‐based model of host–pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host''s explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life‐history events affect host–pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts’ biological events. However, a temporal mismatch reduced host–pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat‐dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host–pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.     

From individual behavior to metapopulation dynamics: unifying the patchy population and classic metapopulation models

Spatially structured populations in patchy habitats show much variation in migration rate, from patchy populations in which individuals move repeatedly among habitat patches to classic metapopulations with infrequent migration among discrete populations. To establish a common framework for population dynamics in patchy habitats, we describe an individual-based model (IBM) involving a diffusion approximation of correlated random walk of individual movements. As an example, we apply the model to the Glanville fritillary butterfly (Melitaea cinxia) inhabiting a highly fragmented landscape. We derive stochastic patch occupancy model (SPOM) approximations for the IBMs assuming pure demographic stochasticity, uncorrelated environmental stochasticity, or completely correlated environmental stochasticity in local dynamics. Using realistic parameter values for the Glanville fritillary, we show that the SPOMs mimic the behavior of the IBMs well. The SPOMs derived from IBMs have parameters that relate directly to the life history and behavior of individuals, which is an advantage for model interpretation and parameter estimation. The modeling approach that we describe here provides a unified framework for patchy populations with much movements among habitat patches and classic metapopulations with infrequent movements.     

Joint Effects of Habitat Heterogeneity and Species’ Life-History Traits on Population Dynamics in Spatially Structured Landscapes

Both habitat heterogeneity and species’ life-history traits play important roles in driving population dynamics, yet there is little scientific consensus around the combined effect of these two factors on populations in complex landscapes. Using a spatially explicit agent-based model, we explored how interactions between habitat spatial structure (defined here as the scale of spatial autocorrelation in habitat quality) and species life-history strategies (defined here by species environmental tolerance and movement capacity) affect population dynamics in spatially heterogeneous landscapes. We compared the responses of four hypothetical species with different life-history traits to four landscape scenarios differing in the scale of spatial autocorrelation in habitat quality. The results showed that the population size of all hypothetical species exhibited a substantial increase as the scale of spatial autocorrelation in habitat quality increased, yet the pattern of population increase was shaped by species’ movement capacity. The increasing scale of spatial autocorrelation in habitat quality promoted the resource share of individuals, but had little effect on the mean mortality rate of individuals. Species’ movement capacity also determined the proportion of individuals in high-quality cells as well as the proportion of individuals experiencing competition in response to increased spatial autocorrelation in habitat quality. Positive correlations between the resource share of individuals and the proportion of individuals experiencing competition indicate that large-scale spatial autocorrelation in habitat quality may mask the density-dependent effect on populations through increasing the resource share of individuals, especially for species with low mobility. These findings suggest that low-mobility species may be more sensitive to habitat spatial heterogeneity in spatially structured landscapes. In addition, localized movement in combination with spatial autocorrelation may increase the population size, despite increased density effects.     

Between‐individual variation drives the seasonal dynamics in the trophic niche of a Neotropical marsupial

The dynamics of population niches result from the variation in resource use within individuals and also from the variation between individuals. The prevalence of one mechanism or the other leads to competing hypotheses about the major mechanisms underlying the empirical observations of the contraction/expansion dynamics of the trophic niche in natural populations. In this study, we investigated how within‐ and between‐individual variation in resource use shapes the food niche dynamics of the woolly mouse opossum, Marmosa paraguayana (Didelphimorphia: Didelphidae), in a remnant of the highly seasonal Cerrado in south‐eastern Brazil. To do so, we analysed the faecal samples of live‐trapped individuals to determine their diets within the wet and dry seasons. In addition to a seasonal shift in the composition of the diet, the population trophic niche was significantly wider during the dry season than the wet season. This expansion resulted from larger between‐individual variation in the dry season that was not related to sex preferences, whereas the individual niche widths did not significantly increase from the wet to the dry seasons. Our findings add to the growing list of animal populations that show individual‐level variation in resource use. Furthermore, these results represent a pattern of individual‐level response to seasonal changes that is different from patterns reported for other organisms. We suggest that a pathway to build more realistic foraging models and produce more accurate predictions on population and community dynamics is to consider between‐individual variation and short‐term niche dynamics.     

Genetic structure and dispersal in a small South African rodent. Is dispersal female-biased?

Dispersal greatly determines genetic structure of populations, although it is influenced by landscape heterogeneity, quality of the matrix, resource distribution and local population densities and dynamics. To get insights into some of those processes we analysed the genetic structure of the hairy-footed gerbil Gerbillurus paeba (Rodentia, Murinae, Gerbillinae) in the southern Kalahari (South Africa). Samples were taken from 20 populations covering an area of about 2200 km². Genetic data were related to landscape characters and population dynamics. We used newly developed microsatellites and found at all loci some indication for the presence of null alleles. However, null alleles seem to have little influence on the general results of our analyses. Altogether we found even nearby populations of G. paeba to be significantly differentiated, although assignment tests revealed 24% of individuals as immigrants. Genetic structure was independent of landscape heterogeneities at all spatial scales. Autocorrelation analyses (range 50–90 km) revealed significant genetic structure within populations on distances <3 km. We found some indication for female-biased dispersal. Our study suggests that dispersing individuals have little influence on the long-term genetic structure and that drift is the major cause of genetic diversity. The observed genetic pattern likely derives from strong population fluctuations of G. paeba. The landscape structure has little influence on the genetic differentiation between populations.     

A priori prediction of disease invasion dynamics in a novel environment

Directly transmitted infectious diseases spread through wildlife populations as travelling waves away from the sites of original introduction. These waves often become distorted through their interaction with environmental and population heterogeneities and by long-distance translocation of infected individuals. Accurate a priori predictions of travelling waves of infection depend upon understanding and quantifying these distorting factors. We assess the effects of anisotropies arising from the orientation of rivers in relation to the direction of disease-front propagation and the damming effect of mountains on disease movement in natural populations. The model successfully predicts the local and large-scale prevaccination spread of raccoon rabies through New York State, based on a previous spatially heterogeneous model of raccoon-rabies invasion across the state of Connecticut. Use of this model provides a rare example of a priori prediction of an epidemic invasion over a naturally heterogeneous landscape. Model predictions matched to data can also be used to evaluate the most likely points of disease introduction. These results have general implications for predicting future pathogen invasions and evaluating potential containment strategies.     

How interactions between animal movement and landscape processes modify local range dynamics and extinction risk

Forecasts of range dynamics now incorporate many of the mechanisms and interactions that drive species distributions. However, connectivity continues to be simulated using overly simple distance-based dispersal models with little consideration of how the individual behaviour of dispersing organisms interacts with landscape structure (functional connectivity). Here, we link an individual-based model to a niche-population model to test the implications of this omission. We apply this novel approach to a turtle species inhabiting wetlands which are patchily distributed across a tropical savannah, and whose persistence is threatened by two important synergistic drivers of global change: predation by invasive species and overexploitation. We show that projections of local range dynamics in this study system change substantially when functional connectivity is modelled explicitly. Accounting for functional connectivity in model simulations causes the estimate of extinction risk to increase, and predictions of range contraction to slow. We conclude that models of range dynamics that simulate functional connectivity can reduce an important source of bias in predictions of shifts in species distributions and abundances, especially for organisms whose dispersal behaviours are strongly affected by landscape structure.     

An empirical test of a diffusion model: predicting clouded apollo movements in a novel environment

Functional connectivity is a fundamental concept in conservation biology because it sets the level of migration and gene flow among local populations. However, functional connectivity is difficult to measure, largely because it is hard to acquire and analyze movement data from heterogeneous landscapes. Here we apply a Bayesian state-space framework to parameterize a diffusion-based movement model using capture-recapture data on the endangered clouded apollo butterfly. We test whether the model is able to disentangle the inherent movement behavior of the species from landscape structure and sampling artifacts, which is a necessity if the model is to be used to examine how movements depend on landscape structure. We show that this is the case by demonstrating that the model, parameterized with data from a reference landscape, correctly predicts movements in a structurally different landscape. In particular, the model helps to explain why a movement corridor that was constructed as a management measure failed to increase movement among local populations. We illustrate how the parameterized model can be used to derive biologically relevant measures of functional connectivity, thus linking movement data with models of spatial population dynamics.     

Demographic stochasticity and resource autocorrelation control biological invasions in heterogeneous landscapes

Mounting theoretical evidence suggests that demographic stochasticity, environmental heterogeneity and biased movement of organisms individually affect the dynamics of biological invasions and range expansions. Studies of species spread in heterogeneous landscapes have traditionally characterized invasion velocities as functions of the mean resource density throughout the landscape, thus neglecting higher‐order moments of the spatial resource distribution. Here, we show theoretically that different spatial arrangements of resources lead to different spread velocities even if the mean resource density throughout the landscape is kept constant. Specifically, we find that increasing the resource autocorrelation length causes a reduction in the speed of species spread. The model shows that demographic stochasticity plays a key role in the slowdown, which is strengthened when individuals can actively move towards resources. We then experimentally corroborated the theoretically predicted reduction in propagation speed in microcosm experiments with the protist Euglena gracilis by comparing spread in landscapes with different resource autocorrelation lengths. Our work identifies the resource autocorrelation length as a key modulator and a simple measure of landscape susceptibility to biological invasions, which needs to be considered for predicting invasion dynamics within naturally heterogeneous environmental corridors.     

Network metrics reveal differences in social organization between two fission–fusion species, Grevy’s zebra and onager

For species in which group membership frequently changes, it has been a challenge to characterize variation in individual interactions and social structure. Quantifying this variation is necessary to test hypotheses about ecological determinants of social patterns and to make predictions about how group dynamics affect the development of cooperative relationships and transmission processes. Network models have recently become popular for analyzing individual contacts within a population context. We use network metrics to compare populations of Grevy’s zebra (Equus grevyi) and onagers (Equus hemionus khur). These closely related equids, previously described as having the same social system, inhabit environments differing in the distribution of food, water, and predators. Grevy’s zebra and onagers are one example of many sets of coarsely similar fission–fusion species and populations, observed elsewhere in other ungulates, primates, and cetaceans. Our analysis of the population association networks reveals contrasts consistent with their distinctive environments. Grevy’s zebra individuals are more selective in their association choices. Grevy’s zebra form stable cliques, while onager associations are more fluid. We find evidence that females associate assortatively by reproductive state in Grevy’s zebra but not in onagers. The current approach demonstrates the utility of network metrics for identifying fine-grained variation among individuals and populations in association patterns. From our analysis, we can make testable predictions about behavioral mechanisms underlying social structure and its effects on transmission processes.     

Synchronization in ecological systems by weak dispersal coupling with time delay

One of the most salient spatiotemporal patterns in population ecology is the synchronization of fluctuating local populations across vast spatial extent. Synchronization of abundance has been widely observed across a range of spatial scales in relation to the rate of dispersal among discrete populations. However, the dependence of synchrony on patterns of among-patch movement across heterogeneous landscapes has been largely ignored. Here, we consider the duration of movement between two predator–prey communities connected by weak dispersal and its effect on population synchrony. More specifically, we introduce time-delayed dispersal to incorporate the finite transmission time between discrete populations across a continuous landscape. Reducing the system to a phase model using weakly connected network theory, it is found that the time delay is an important factor determining the nature and stability of phase-locked states. Our analysis predicts enhanced convergence to stable synchronous fluctuations in general and a decreased ability of systems to produce in-phase synchronization dynamics in the presence of delayed dispersal. These results introduce delayed dispersal as a tool for understanding the importance of dispersal time across a landscape matrix in affecting metacommunity dynamics. They further highlight the importance of landscape and dispersal patterns for predicting the onset of synchrony between weakly coupled populations.     

Implications from Monitoring Gopher Tortoises at Two Spatial Scales

Conservation biologists need to effectively monitor species given resource limitations and the inherent challenges of assessing long-term demographic processes. We assessed gopher tortoise (Gopherus polyphemus) abundance at a landscape scale and at the scale of 3 local populations within the Conecuh National Forest (CNF), Alabama, USA, between 1991 and 2017. We collected landscape-level data from line transect distance sampling arranged uniformly across the CNF during a single season (2011); we obtained data for local populations from long-term mark-recapture of individuals at 3 sites selected based on prior knowledge of high density at each. At a landscape scale, we estimated 5,242 (95% CI = 3,538–7,768) tortoises occurred across the approximately 34,000-ha forest, yielding a density of 0.14–0.32 tortoises/ha. These low densities across the landscape suggest that, on average, management activities across the property have not allowed tortoise populations to retain the social structure needed for long-term persistence. The 3 local populations, however, contained 25–60 individuals and densities of 1.9–6.9 tortoises/ha. Over the study period, populations at 2 sites were stable and the third experienced significant population growth. Mean annual survival of individuals was 0.89 and invariant across size classes. Overall, line transect distance sampling is important for assessing landscape-scale abundance of tortoises but may fail to detect local clusters of high-density sites important for population persistence. Our mark-recapture efforts at the local scale revealed that small populations on these high-density sites can exhibit long-term stability or growth even though they do not meet current established criteria for viability. Improved models that incorporate immigration and emigration and better reflect the dynamics of peripheral populations would assist in determining how such populations best contribute to species recovery and regional conservation targets. © 2020 The Wildlife Society.     

The walk is never random: subtle landscape effects shape gene flow in a continuous white-tailed deer population in the Midwestern United States

One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.     

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.