Connecting mountains and desert valleys for black bears in northern Mexico

Context

Black bear connectivity studies are scarce in the southern distribution where the species is endangered. The identification of corridors is a strategy to promote conservation in human-modified landscapes.

Objectives

Assess and validate long-distance corridors in the southern black bear distribution using resistance models, occurrence records, and radio-telemetry of an individual that dispersed between the Sierras Madres of Mexico.

Methods

We acquired black bear occurrence records from several sources and telemetry records from one dispersal individual in northern Mexico. We generated ensemble habitat suitability models and resistance landscape surfaces to generate cumulative resistant kernel and least-cost paths to identify connectivity core areas and corridors of importance through Natural Protected Areas. Finally, we assessed long-distance corridors.

Results

We developed three habitat suitability models for black bears southern range; one matches the current distribution of the species. When including radio-tracking records, the landscape resistance is reduced to arid sites with low habitat suitability. We used least resistance connectivity surfaces to merge subpopulations within each Sierra Madre. The long-distance corridor models indicate narrow routes that require individuals with plastic behavioral dispersal capacity. Almost 20% of the connectivity core areas are within Natural Protected Areas. These are the first large-scale corridors using resistance layers in the southern black bear distribution.

Conclusions

Corridors can be functional for a range of temperate and dry habitat species. Landscape connectivity models should include the monitoring of dispersal individuals to identify the plasticity of organisms and the tangible barriers for them.

     

Estimating landscape resistance from habitat suitability: effects of data source and nonlinearities

Context

Conservation corridors must facilitate long-distance dispersal movements to promote gene flow, prevent inbreeding, and allow animals to shift ranges with climate change. Least-cost models are used to identify areas that support long-distance movement. These models rely on estimates of landscape resistance, which are typically derived from habitat suitability.

Objectives

We examine two key steps in estimating resistance from habitat suitability: choosing a procedure to estimate habitat suitability, and choosing a transformation function to translate habitat suitability into resistance.

Methods

We used linear and nonlinear functions to convert three types of habitat suitability estimates (from expert opinion, resource selection functions, and step selection functions) into resistances for elk (Cervus canadensis) and desert bighorn sheep (Ovis canadensis nelsoni). We evaluated the resulting resistance maps on an independent set of observed long-distance, prospecting movements.

Results

A negative exponential function best described the relationship between resistance values and habitat suitability for desert bighorn sheep indicating long-distance movers readily travel through moderately-suitable areas and avoid only the least suitable habitat. For desert bighorn sheep, all three suitability estimates performed better than chance, and resource and step selection functions outperformed expert opinion. For elk, all three suitability estimates performed the same as chance.

Conclusions

When designing corridors to facilitate long-distance movements of mobile animals, we recommend transforming habitat suitability into resistance with a negative exponential function. Use of an exponential transformation means that larger fractions of the landscape offer low resistance, allowing greater flexibility in where a corridor is located.

     

Circuit theory emphasizes the importance of edge-crossing decisions in dispersal-scale movements of a forest passerine

Measuring landscape connectivity in ways that reflect an animal’s propensity or reluctance to move across a given landscape is key for planning effective conservation strategies. Resistance distance, based on circuit theory, is one such measure relevant for modeling how broad-scale animal movements over long time periods may lead to gene flow across the landscape. Despite the success of circuit theory in landscape genetic studies, its applicability to model finer-scale processes such as the movement patterns of individual animals within their breeding grounds (e.g., while prospecting for territories) has yet to be tested. Here, we applied both circuit models and least-cost models to understand the relationship between landscape connectivity and return time of Ovenbirds (Seiurus aurocapilla) that had been translocated at least 20 km from their home territory near Québec City, Canada. Using an iterative optimization process, we derived resistance values for three cover types (forest, edge, and open) that resulted in resistance distance values that best explained Ovenbird return times. We also identified the cover-type resistance values that yielded length of least-cost path estimates that best explained return times of the translocated birds. The circuit theory and least-cost path methods were equally supported by the data despite being based on different sets of resistance values. The optimal resistance values for calculating resistance distance indicated that for Ovenbirds, traversing a given distance of edge habitat presented a substantially greater resistance than that of open areas. On the other hand, optimized resistances of edge and open were very similar for calculating length of least-cost path. The circuit theory approach suggested that for an Ovenbird moving through fragmented habitat, the number of forest-open transitions (i.e., edge-crossings) that an individual must make is critical to understanding return times after translocation. The least-cost path approach, on the other hand, suggested that the birds strongly avoid all open areas, regardless of size. Circuit theory offers an important new approach for understanding landscapes from the perspective of individuals moving within their breeding range, at finer spatial scales and shorter time scales than have been previously considered.     

Using network theory to prioritize management in a desert bighorn sheep metapopulation

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.     

Habitat suitability modelling to correlate gene flow with landscape connectivity

Landscape connectivity is important in designing corridor and reserve networks. Combining genetic distances among individuals with least-cost path (LCP) modelling helps to correlate indirect measures of gene flow with landscape connectivity. Applicability of LCP modelling, however, is reduced if knowledge on dispersal pathways or routes is lacking. Therefore, we integrated habitat suitability modelling into LCP analysis to avoid the subjectivity common in LCP analyses lacking knowledge on dispersal pathways or routes. We used presence-only data and ecological niche factor analysis to model habitat suitability for the spiny rat, Niviventer coninga, in a fragmented landscape of western Taiwan. We adapted the resultant habitat suitability map for incorporation into LCP analyses. Slightly increased Mantel correlations indicated that a class-weighted suitability map better explained genetic distances among individuals than did geographical distances. The integration of habitat suitability modelling into LCP analysis can thus generate information on distribution of suitable habitats, on potential routes of dispersal, for placement of corridors, and evaluate landscape connectivity. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Influence of separating home range and dispersal movements on characterizing corridors and effective distances

Context

Corridors are usually delineated as areas of minimum cumulative resistance to movement through a resistance surface and characterized by their effective distance (accumulated resistance along the least-cost path). The results of these assessments depend on resistance values, which are typically derived from the inverse of habitat suitability models or from presence data of individuals within their home ranges, rather than from data on dispersal or exploratory movements.

Objective

Evaluate the extent to which corridor delineation and effective distance estimates may vary depending on whether home range locations or dispersal data are used to characterize species habitat selection and landscape resistance to movement.

Methods

We analyzed a large telemetry dataset (GPS collars) for the endangered Iberian lynx. We modeled corridors and effective distances three ways: (1) considering only GPS locations within home ranges, (2) considering only locations in dispersal or exploratory movements outside home ranges, and (3) considering all locations together.

Results

Delineated least-cost corridors followed similar trajectories and sometimes overlapped in the three models. The estimated effective distances were 42 % lower in the dispersal-based model than in the model based solely on home range use.

Conclusions

Models derived exclusively from locations within home ranges may provide lower connectivity estimates than models derived from dispersal locations, affecting estimates of resistance to move between habitat areas, even when the most likely movement routes are similar. Although dispersal data are costly to gather, they potentially provide more realistic assessments of the actual isolation of populations in heterogeneous landscapes.

     

Movement behavior explains genetic differentiation in American black bears

Individual-based landscape genetic analyses provide empirically based models of gene flow. It would be valuable to verify the predictions of these models using independent data of a different type. Analyses using different data sources that produce consistent results provide strong support for the generality of the findings. Mating and dispersal movements are the mechanisms through which gene flow operates in animal populations. The best means to verify landscape genetic predictions would be to use movement data to independently predict landscape resistance. We used path-level, conditional logistic regression to predict landscape resistance for American black bear (Ursus americanus) in a landscape in which previous work predicted population connectivity using individual-based landscape genetics. We found consistent landscape factors influence genetic differentiation and movement path selection, with strong similarities between the predicted landscape resistance surfaces. Genetic differentiation in American black bear is driven by spring movement (mating and dispersal) in relation to residential development, roads, elevation and forest cover. Given the limited periods of the year when gene flow events primarily occur, models of landscape connectivity should carefully consider temporal changes in functional landscape resistance.     

Estimating landscape resistance to dispersal

Dispersal is an inherently spatial process that can be affected by habitat conditions in sites encountered by dispersers. Understanding landscape resistance to dispersal is important in connectivity studies and reserve design, but most existing methods use resistance functions with cost parameters that are subjectively chosen by the investigator. We develop an analytic approach allowing for direct estimation of resistance parameters that folds least cost path methods typically used in simulation approaches into a formal statistical model of dispersal distributions. The core of our model is a frequency distribution of dispersal distances expressed as least cost distance rather than Euclidean distance, and which includes terms for feature-specific costs to dispersal and sex (or other traits) of the disperser. The model requires only origin and settlement locations for multiple individuals, such as might be obtained from mark–recapture studies or parentage analyses, and maps of the relevant habitat features. To evaluate whether the model can estimate parameters correctly, we fit our model to data from simulated dispersers in three kinds of landscapes (in which resistance of environmental variables was categorical, continuous with a patchy configuration, or continuous in a trend pattern). We found maximum likelihood estimators of resistance and individual trait parameters to be approximately unbiased with moderate sample sizes. We applied the model to a small grizzly bear dataset to demonstrate how this approach could be used when the primary interest is in the prediction of costs and found that estimates were consistent with expectations based on bear ecology. Our method has important practical applications for testing hypotheses about dispersal ecology and can be used to inform connectivity planning efforts, via the resistance estimates and confidence intervals, which can be used to create a data-driven resistance surface.     

Where do we go from here? Dispersal simulations shed light on the role of landscape structure in determining animal redistribution after reintroduction

Reintroduction projects represent viable options for animal conservation. They allow the establishment of new local populations and may contribute to recreating functional networks within a metapopulation. In the latter case, landscape connectivity may be a major determinant of the phase of spread of the reintroduced populations. Here, we deal with an example of a red deer (Cervus elaphus) translocation planned to enable the connection among existing isolated populations of the species in the Italian Alps. Our aim was to assess whether the analysis of landscape suitability and the simulation of dispersal of released individuals could shed light on the actual process of population spread. For these purposes, we adopted a modelling approach using radiotracking data to develop a habitat suitability map. On the basis of this map, we simulated the dispersal of the animals after release and we then compared the simulation results with the outcome of null models and with the observed population redistribution. The results suggest that the spread of the subpopulation was easier north-westward than southward. Taking into account landscape suitability, our simulations produced a reliable estimate of the ease of colonization of the valleys neighbouring the release-site and they allowed the identification and validation of a potential pathway for animal dispersal. The suitability model based on the monitoring of individuals in the earliest phase of establishment shed light on the spread of the population and on its potential connections with other deer subpopulations.     

Exploring dispersal barriers using landscape genetic resistance modelling in scarlet macaws of the Peruvian Amazon

Context

Dispersal is essential for species persistence and landscape genetic studies are valuable tools for identifying potential barriers to dispersal. Macaws have been studied for decades in their natural habitat, but we still have no knowledge of how natural landscape features influence their dispersal.

Objectives

We tested for correlations between landscape resistance models and the current population genetic structure of macaws in continuous rainforest to explore natural barriers to their dispersal.

Methods

We studied scarlet macaws (Ara macao) over a 13,000 km² area of continuous primary Amazon rainforest in south-eastern Peru. Using remote sensing imagery from the Carnegie Airborne Observatory, we constructed landscape resistance surfaces in CIRCUITSCAPE based on elevation, canopy height and above-ground carbon distribution. We then used individual- and population-level genetic analyses to examine which landscape features influenced gene flow (genetic distance between individuals and populations).

Results

Across the lowland rainforest we found limited population genetic differentiation. However, a population from an intermountain valley of the Andes (Candamo) showed detectable genetic differentiation from two other populations (Tambopata) located 20–60 km away (F _ST = 0.008, P = 0.001–0.003). Landscape resistance models revealed that genetic distance between individuals was significantly positively related to elevation.

Conclusions

Our landscape resistance analysis suggests that mountain ridges between Candamo and Tambopata may limit gene flow in scarlet macaws. These results serve as baseline data for continued landscape studies of parrots, and will be useful for understanding the impacts of anthropogenic dispersal barriers in the future.

     

Testing assumptions of cost surface analysis—a tool for invasive species management

Applied ecology could benefit from new tools that identify potential movement pathways of invasive species, particularly where data are sparse. Cost surface analysis (CSA) estimates the permeability (friction) across a landscape and can be applied to dispersal modelling. Increasingly used in a diversity of applications, several fundamental assumptions that might influence the outputs of CSA (cost surfaces and least-cost pathways) have yet to be systematically examined. Thus, we explore two issues: the presumed relationship between habitat preferences and dispersal behaviour as well as the degree of landscape fragmentation through which an organism moves by modelling a total of 18 sensitivity and dispersal scenarios. We explored the effect of fragmentation by altering the friction values (generally assigned using expert opinion) associated with patch and linear features. We compared these sensitivity scenarios in two sites that differed in fragmentation. We also used eastern grey squirrels (Sciurus carolinensis) as an example invading species and compared diffusion models and two contrasting cost surface dispersal scenarios. The diffusion model underestimated spread because squirrels did not move randomly through the landscape. Despite contrasting assumptions regarding dispersal behaviour, the two cost surfaces were strikingly similar while the least-cost paths differed. Furthermore, while the cost surfaces were insensitive to changes in friction values for linear features, they were sensitive to assumptions made for patch features. Our results suggest that movement in fragmented landscapes may be more sensitive to assumptions regarding friction values than contiguous landscapes. Thus, the reliability of CSA may depend not only on the range of friction values used for patches but also the degree of contiguity in the landscape.     

Integrative approach for landscape-based graph connectivity analysis: a case study with the common frog (Rana temporaria) in human-dominated landscapes

Graph-based analysis is a promising approach for analyzing the functional and structural connectivity of landscapes. In human-shaped landscapes, species have become vulnerable to land degradation and connectivity loss between habitat patches. Movement across the landscape is a key process for species survival that needs to be further investigated for heterogeneous human-dominated landscapes. The common frog (Rana temporaria) was used as a case study to explore and provide a graph connectivity analysis framework that integrates habitat suitability and dispersal responses to landscape permeability. The main habitat patches influencing habitat availability and connectivity were highlighted by using the software Conefor Sensinode 2.2. One of the main advantages of the presented graph-theoretical approach is its ability to provide a large choice of variables to be used based on the study’s assumptions and knowledge about target species. Based on dispersal simulation modelling in potential suitable habitat corridors, three distinct patterns of nodes connections of differing importance were revealed. These patterns are locally influenced by anthropogenic barriers, landscape permeability, and habitat suitability. And they are affected by different suitability and availability gradients to maximize the best possible settlement by the common frog within a terrestrial habitat continuum. The study determined the key role of landscape-based approaches for identifying the “availability-suitability-connectivity” patterns from a local to regional approach to provide an operational tool for landscape planning.     

Beyond the least-cost path: evaluating corridor redundancy using a graph-theoretic approach

The impact of the landscape matrix on patterns of animal movement and population dynamics has been widely recognized by ecologists. However, few tools are available to model the matrix’s influence on the length, relative quality, and redundancy of dispersal routes connecting habitat patches. Many GIS software packages can use land use/land cover maps to identify the route of least resistance between two points—the least-cost path. The limitation of this type of analysis is that only a single path is identified, even though alternative paths with comparable costs might exist. In this paper, we implemented two graph theory methods that extend the least-cost path approach: the Conditional Minimum Transit Cost (CMTC) tool and the Multiple Shortest Paths (MSPs) tool. Both methods enable the visualization of multiple dispersal routes that, together, are assumed to form a corridor. We show that corridors containing alternative dispersal routes emerge when favorable habitat is randomly distributed in space. As clusters of favorable habitat start forming, corridors become less redundant and dispersal bottlenecks become visible. Our approach is illustrated using data from a real landscape in the Brazilian Atlantic forest. We explored the effect of small, localized disturbance on dispersal routes linking conservation units. Simulated habitat destruction caused the appearance of alternative dispersal routes, or caused existing corridors to become narrower. These changes were observed even in the absence of significant differences in the length or cost of least-cost paths. Last, we discuss applications to animal movement studies and conservation initiatives.     

Constraints and time lags for recovery of a keystone species (Dipodomys spectabilis) after landscape restoration

Habitat restoration is typically focused on reestablishing suitable conditions at a local scale, but landscape constraints may be important for keystone species with limited dispersal. We tested for time lags and examined the relative importance of local and landscape constraints on the response of the banner-tailed kangaroo rat (Dipodomys spectabilis) to restoration of Chihuahuan Desert grasslands in New Mexico, USA. Dipodomys spectabilis is a keystone species that creates habitat heterogeneity and modifies the structure of plant and animal communities. We selected 21 sites and compared density of D. spectabilis between areas treated with herbicide to control shrubs (treated areas) and paired untreated areas. We evaluated whether density of D. spectabilis depended on treatment age, local habitat quality (vegetation and soil structure), and landscape factors (treatment area and spatial connectivity). Density was greater at treated areas than at untreated areas due to a direct effect of reduced shrub cover. However, the response of D. spectabilis to restoration was lagged by a decade or more. Structural equation modeling indicated the time lag reflected a dispersal constraint as opposed to a temporal change in habitat quality. This inference was corroborated by a positive relationship between density at treated areas and connectivity to source populations. Our results indicate that density of D. spectabilis depended strongly on the spatial configuration of treated areas, which supports a landscape mosaic approach to restoration. If keystone species commonly exhibit limited dispersal ability, landscape constraints may be broadly important for shaping ecosystem structure and function after habitat restoration.     

Making molehills out of mountains: landscape genetics of the Mojave desert tortoise

Heterogeneity in habitat often influences how organisms traverse the landscape matrix that connects populations. Understanding landscape connectivity is important to determine the ecological processes that influence those movements, which lead to evolutionary change due to gene flow. Here, we used landscape genetics and statistical models to evaluate hypotheses that could explain isolation among locations of the threatened Mojave desert tortoise (Gopherus agassizii). Within a causal modeling framework, we investigated three factors that can influence landscape connectivity: geographic distance, barriers to dispersal, and landscape friction. A statistical model of habitat suitability for the Mojave desert tortoise, based on topography, vegetation, and climate variables, was used as a proxy for landscape friction and barriers to dispersal. We quantified landscape friction with least-cost distances and with resistance distances among sampling locations. A set of diagnostic partial Mantel tests statistically separated the hypotheses of potential causes of genetic isolation. The best-supported model varied depending upon how landscape friction was quantified. Patterns of genetic structure were related to a combination of geographic distance and barriers as defined by least-cost distances, suggesting that mountain ranges and extremely low-elevation valleys influence connectivity at the regional scale beyond the tortoises’ ability to disperse. However, geographic distance was the only influence detected using resistance distances, which we attributed to fundamental differences between the two ways of quantifying friction. Landscape friction, as we measured it, did not influence the observed patterns of genetic distances using either quantification. Barriers and distance may be more valuable predictors of observed population structure for species like the desert tortoise, which has high dispersal capability and a long generation time.     

Patterns of habitat occupancy, genetic variation and predicted movement of a flightless bush cricket, Pholidoptera griseoaptera, in an agricultural mosaic landscape

Habitat fragmentation has been generally regarded detrimental to the persistence of many species, especially those with limited dispersal abilities. Yet, when exactly habitat elements become functionally disconnected very much depends on the dispersal ability of a species in combination with the landscape’s composition in which it occurs. Surprisingly, for many small and ground-walking generalists knowledge at what spatial scale and to what extent landscape structure affects dispersal is very scarce. Because it is flightless, the bush cricket Pholidoptera griseoaptera may be regarded susceptible to fragmentation. We applied habitat occupancy surveys, population genetic analyses and movement modelling to investigate the performance of P. griseoaptera in an agricultural mosaic landscape with suitable habitat patches of varying size and isolation. Despite its presumed dispersal limitation we could show that P. griseoaptera occupied the majority of suitable habitats, including small and isolated patches, showed a very low and non-significant genetic differentiation (F _ST = 0.0072) and, in the model, managed to colonize around 73% of all suitable habitat patches within one generation under weak and strong landscape-effect scenarios. We conclude that P. griseoaptera possesses the behavioural attributes (frequent inter-patch dispersal) necessary to persist in this landscape characterized by a patchy distribution of habitat elements. Yet, sound recommendations to landscape planning and conservation require more research to determine whether this represents a general behaviour of the species or a behavioural adaptation to this particular landscape.     

Landscape genetics matches with behavioral ecology and brings new insight on the functional connectivity in Mediterranean mouflon

Context

In natural populations, gene flow often represents a key factor in determining and maintaining genetic diversity. In a worldwide context of habitat fragmentation, assessing the relative contribution of landscape features to gene flow thus appears crucial for sustainable management of species.

Objective

We addressed this issue in Mediterranean mouflon (Ovis gmelini musimon?×?Ovis sp.) by combining previous knowledge on behavioral ecology with landscape genetics. We also assessed how sex-specific behavioral differences translated in term of functional connectivity in both sexes.

Methods

We relied on 239 individuals genotyped at 16 microsatellite markers. We applied a model optimization approach in a causal modeling framework of landscape genetics to test for the effects on gene flow of habitat types and linear landscape features previously identified as important for movements and habitat selection in both sexes. Five resistance values were alternately assigned to these landscape characteristics leading to a comprehensive set of resistance surfaces.

Results

Isolation by resistance shaped female gene flow, supporting the central role of linear landscape features as behavioral barriers for animal movements. Conversely, no isolation by resistance was detected in males. Although a lack of statistical power cannot be discarded to explain this result, it tended to confirm that males are less influenced by landscape structures during the mating period.

Conclusions

Combining previous knowledge on behavioral ecology with results from landscape genetics was decisive in assessing functional landscape connectivity in both sexes. These results highlighted the need to perform sex-specific studies for management and conservation of dimorphic species.

     

Estimating density of a territorial species in a dynamic landscape

Context

Conservation planning for at-risk species requires understanding of where species are likely to occur, how many individuals are likely to be supported on a given landscape, and the ability to monitor those changes through time.

Objectives

We developed a distribution model for northern spotted owls that incorporates both habitat suitability and probability of territory occupancy while accounting for interspecies competition.

Methods

We developed range-wide habitat suitability maps for two time periods (1993 and 2012) for northern spotted owls that accounted for regional differences in habitat use and home range size. We used these maps for a long-term demographic monitoring study area to assess habitat change and estimate the number of potential territories based on available habitat for both time periods. We adjusted the number of potential territories using known occupancy rates to estimate owl densities for both time periods. We evaluated our range-wide habitat suitability model using independent survey data.

Results

Our range-wide habitat maps predicted areas suitable for territorial spotted owl presence well. On the demographic study area, the amount of habitat declined 19.7% between 1993 and 2012, while our estimate of the habitat-based carrying capacity declined from 150 to 146 territories. Estimated number of occupied territories declined from 94 to 57.

Conclusions

Conservation and recovery of at-risk species depends on understanding how habitat changes over time in response to factors such as wildfire, climate change, biological invasions, and interspecies competition, and how these changes influence species distribution. We demonstrate a model-based approach that provides an effective planning tool.

     

Genetic isolation by distance and landscape connectivity in the American marten (Martes americana)

Empirical studies of landscape connectivity are limited by the difficulty of directly measuring animal movement. ‘Indirect’ approaches involving genetic analyses provide a complementary tool to ‘direct’ methods such as capture–recapture or radio-tracking. Here the effect of landscape on dispersal was investigated in a forest-dwelling species, the American marten (Martes americana) using the genetic model of isolation by distance (IBD). This model assumes isotropic dispersal in a homogeneous environment and is characterized by increasing genetic differentiation among individuals separated by increasing geographic distances. The effect of landscape features on this genetic pattern was used to test for a departure from spatially homogeneous dispersal. This study was conducted on two populations in homogeneous vs. heterogeneous habitat in a harvested boreal forest in Ontario (Canada). A pattern of IBD was evidenced in the homogeneous landscape whereas no such pattern was found in the near-by harvested forest. To test whether landscape structure may be accountable for this difference, we used effective distances that take into account the effect of landscape features on marten movement instead of Euclidean distances in the model of isolation by distance. Effective distances computed using least-cost modeling were better correlated to genetic distances in both landscapes, thereby showing that the interaction between landscape features and dispersal in Martes americana may be detected through individual-based analyses of spatial genetic structure. However, the simplifying assumptions of genetic models and the low proportions in genetic differentiation explained by these models may limit their utility in quantifying the effect of landscape structure.     

Movements of cactus bugs: Patch transfers,matrix resistance,and edge permeability

Individual movement is a key process affecting the distribution of animals in heterogeneous landscapes. For specialist species in patchy habitat, a central issue is how dispersal distances are related to landscape structure. We compared dispersal distances for cactus bugs (Chelinidea vittiger) on two naturally fragmented landscapes (≤ 4% suitable habitat) with different matrix structures (i.e., vegetation height of nonsuitable habitat between suitable patches). Using mark-release-recapture studies, we determined that most transfers between cactus patches occurred during the mating season. Dispersal distances were reduced by > 50% on the landscape that had reduced structural connectivity due to relatively high matrix structure and low patch density. An experiment with detailed movement pathways demonstrated that greater matrix structure decreased mean step lengths, reduced directionality, and thus decreased net displacement by > 60%. However, habitat edges between two matrix elements that differed substantially in resistance to movement were completely permeable. Therefore, the difference in distributions of dispersal distances between the two landscapes mainly reflected the average resistance of matrix habitat and not the level of matrix heterogeneity per se. Our study highlights the merits of combining estimates of dispersal distances with insights on mechanisms from detailed movement pathways, and emphasizes the difficulty of treating dispersal distances of species as fixed traits independent of landscape structure.