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.     

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.     

Scale-dependent proximity of wildlife habitat in a spatially-neutral Bayesian model

Organisms may be constrained by the energetic costs incurred while obtaining resources in fragmented landscapes. We used a spatially neutral model of deer wintering habitat to evaluate the effects of landscape fragmentation on the aggregation of deer habitat. The spatially neutral model used Bayesian probabilities to predict where deer wintering areas occurred. The probabilities were conditional on 12 landscape variables measured at 22,750 contiguous 0.4 ha locations. The model predicted deer habitat at each location independently, thereby enabling a comparison of habitat aggregation in observed, simulated, and random distributions of deer habitat. The predictions of the neutral model exhibited greater fragmentation than observed in nature, suggesting that suitable, yet isolated, locations were not visited by deer. The most suitable sites for deer were clumped in the neutral model, regardless of scale. The inclusion of less suitable sites preserved significant aggregation at fine scales but not at broad scales. Species operate at different scales within a landscape, so ecologists, nature reserve designers and natural resource planners may benefit from models that focus on the proximity of habitat sites as a function of both spatial scale and habitat quality.     

Landscape context and selection for forest edge by breeding Brown-headed Cowbirds

We evaluated support for four alternate hypotheses explaining the distribution of breeding Brown-headed Cowbirds (Molothrus ater) in forests at varying distances from the forest edge in three Midwestern USA landscapes with varying amounts of forest fragmentation (core forest area ranged from 5 to 70%). We focused on breeding cowbirds’ use of forest because of the risk of nest parasitism to forest-dwelling hosts and to identify factors affecting breeding cowbird habitat selection. We compared distances of cowbird locations in the forest from the forest edge (“edge distances”) to distances of random forest locations in the entire landscape or within individual cowbird home ranges. We analyzed 1322 locations of 84 cowbirds across three landscapes. We found support for the landscape context hypothesis that breeding cowbird preference for forest edge varied with landscape context. Ninety percent of cowbird locations were within 150–350 m of forest edge, despite the overall availability of forest at greater distances from edge (as far as 500–1450 m) both within cowbird home ranges and the entire forested landscape. Cowbird preference for edge varied by landscape context largely due to differences in the availability of forest edge. In a highly fragmented forest cowbirds utilized the entire forest and likely viewed it as “all edge.” In less fragmented forests, cowbirds preferred edge. We consider how variation in cowbird edge preference might relate to patterns in host abundance, host diversity, and host quality because cowbird movements indicate they are capable of using forest farther from edges.     

Models based on individual level movement predict spatial patterns of genetic relatedness for two Australian forest birds

Fine-scale landscape change can alter dispersal patterns of animals, thus influencing connectivity or gene flow within a population. Furthermore, dispersal patterns of different species may be influenced by the landscape in varying ways. Our research first aimed to examine whether the spatial genetic structure within populations of closely related bird species differs in response to the same landscape. Second, we examined whether individual-level movement characteristics are a mechanistic driver of these differences. We generated a priori predictions of how landscape features will influence dispersal (particularly the response of individuals to habitat boundaries both natural and human-induced) based on a movement model developed by Fahrig (Funct Ecol 21:1003–1015, 2007). This model allowed us to predict genetic relatedness patterns in populations of two passerine bird species with different life-history traits from Queensland, Australia (yellow-throated scrubwren Sericornis citreogularis, a habitat specialist; white-browed scrubwren Sericornis frontalis, a habitat generalist). We quantified our predictions using cost-distance modelling and compared these to observed pairwise genetic distances (a _r ) between individuals as calculated from microsatellite markers. Mantel tests showed that our a priori models correlated with genetic distance. Euclidean distance was most closely correlated to genetic distance for the generalist species (r = 0.093, P = 0.002), and landscape models that included the avoidance of unsuitable habitat were best for the specialist species (r = 0.107, P = 0.001). Our study showed that predictable movement characteristics may be the mechanism driving differences in genetic relatedness patterns within populations of different bird species.     

Metapopulation genetic structure and migration pathways in the land snail Helix aspersa: influence of landscape heterogeneity

The spatial genetic structuring of the land snail Helix aspersa was investigated for 32 colonies within an intensive agricultural area, the polders of the Bay of Mont-Saint-Michel (France). Given the habitat patchiness and environmental instability, the setting of H. aspersa colonies meets the broader view of a metapopulation structure. The identification of extrinsic barriers to migration and their impact on the genetic distribution was addressed through the genotyping of 580 individuals using a combined set of enzyme and microsatellite loci. To evaluate the distance as well as the direction over which the spatial genetic arrangement occurs, two-dimensional spatial autocorrelation analyses, Mantel tests of association and multivariate Mantel correlograms were used. Different connectivity networks and geographical distances based on landscape features were constructed to evaluate the effect of environmental heterogeneity and to test the adequacy of an isolation by distance model on the distribution of the genetic variability. Genetic divergence was assessed using either classical IAM-based statistics, or SMM-based genetic distances specifically designed to accommodate the mutational processes thought to fit microsatellite evolution (IAM: Infinite Allele Model; SMM: Stepwise Mutation Model). Genetic distances based only on genetic drift yielded the most plausible biologically meaningful interpretation of the observed spatial structure. Applying a landscape-based geographical distance which postulates that migration arises along roadside verges, hedges or irrigation canal embankments gave a better fit to an isolation by distance model than did a simple Euclidean distance. The progressive decline of genetic similarity with physical distance appeared to be environmentally induced, leading to functional migration pathways.This revised version was published online in May 2005 with corrections to the Cover Date.     

Landscape cohesion: an index for the conservation potential of landscapes for biodiversity

In urbanising landscapes, planning for sustainable biodiversity occurs in a context of multifunctional land use. Important conditions for species persistence are habitat quality, the amount and configuration of habitat and the permeability of the landscape matrix. For planning purposes, these determinants should be integrated into simple indicators for spatial conditions of persistence probability. We propose a framework of three related indices. The cohesion index is based on the ecology of metapopulations in a habitat network. We discuss how an indicator for species persistence in such a network could be developed. To translate this network index into an area index, we propose the concept of spatial cohesion. Habitat cohesion and spatial cohesion are defined and measured for single species or, at best, for species profiles. Since species differ in their perception of the same landscape, different species will rate different values of these indices for the same landscape. Because landscapes are rarely planned for single species, we further propose the index of landscape cohesion, which integrates the spatial cohesion indices of different species. Indices based on these concepts can be built into GIS tools for landscape assessment. We illustrate different applications of these indices, and emphasise the distinction between ecological and political decisions in developing and applying such tools. This revised version was published online in August 2006 with corrections to the Cover Date.     

Can landscape indices predict ecological processes consistently?

The ecological interpretation of landscape patterns is one of the major objectives in landscape ecology. Both landscape patterns and ecological processes need to be quantified before statistical relationships between these variables can be examined. Landscape indices provide quantitative information about landscape pattern. Response variables or process rates quantify the outcome of ecological processes (e.g., dispersal success for landscape connectivity or Morisita's index for the spatial distribution of individuals). While the principal potential of this approach has been demonstrated in several studies, the robustness of the statistical relationships against variations in landscape structure or against variations of the ecological process itself has never been explicitly investigated. This paper investigates the consistency of correlations between a set of landscape indices (calculated with Fragstats) and three response variables from a simulated dispersal process across heterogeneous landscapes (cell immigration, dispersal success and search time) against variation in three experimental treatments (control variables): habitat amount, habitat fragmentation and dispersal behavior. I found strong correlations between some landscape indices and all three response variables. However, 68% of the statistical relationships were highly inconsistent and sometimes ambiguous for different landscape structures and for differences in dispersal behavior. Correlations between one landscape index and one response variable could range from highly positive to highly negative when derived from different spatial patterns. I furthermore compared correlation coefficients obtained from artificially generated (neutral) landscape models with those obtained from Landsat TM images. Both landscape representations produced equally strong and weak statistical relationships between landscape indices and response variables. This result supports the use of neutral landscape models in theoretical analyses of pattern-process relationships.     

Separating the effects of habitat area,fragmentation and matrix resistance on genetic differentiation in complex landscapes

Little is known about how variation in landscape mosaics affects genetic differentiation. The goal of this paper is to quantify the relative importance of habitat area and configuration, as well as the contrast in resistance between habitat and non-habitat, on genetic differentiation. We hypothesized that habitat configuration would be more influential than habitat area in influencing genetic differentiation. Population size is positively related to habitat area, and therefore habitat area should affect genetic drift, but not gene flow. In contrast, differential rates and patterns of gene flow across a landscape should be related to habitat configuration. Using spatially explicit, individual-based simulation modeling, we found that habitat configuration had stronger relationships with genetic differentiation than did habitat area, but there was a high degree of confounding between the effects of habitat area and configuration. We evaluated the predictive ability of six widely used landscape metrics and found that patch cohesion and correlation length of habitat are among the strongest individual predictors of genetic differentiation. Correlation length, patch density and clumpy are the most parsimonious set of variables to predict the magnitude of genetic differentiation in complex landscapes.     

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.     

Spectral representation of neutral landscapes

Pattern in ecological landscapes is often the result of different processes operating at different scales. Neutral landscape models were introduced in landscape ecology to differentiate patterns that are the result of simple random processes from patterns that arise from more complex ecological processes. Recent studies have used increasingly complex neutral models that incorporate contagion and other constraints on random patterns, as well as using neutral landscapes as input to spatial simulation models. Here, I consider a common mathematical framework based on spectral transforms that represents all neutral landscape models in terms of sets of spectral basis functions. Fractal and multi-fractal models are considered, as well as models with multiple scaling regions and anisotropy. All of the models considered are shown to be variations on a basic theme: a scaling relation between frequency and amplitude of spectral components. Two example landscapes examined showed long-range correlations (distances up to 1000 km) consistent with fractal scaling.     

Dispersal success on fractal landscapes: a consequence of lacunarity thresholds

Habitat fragmentation is expected to disrupt dispersal, and thus we explored how patch metrics of landscape structure, such as percolation thresholds used to define landscape connectivity, corresponded with dispersal success on neutral landscapes. We simulated dispersal as either a purely random process (random direction and random step lengths) or as an area-limited random walk (random direction, but movement limited to an adjacent cell at each dispersal step) and quantified dispersal success for 1000 individuals on random and fractal landscape maps across a range of habitat abundance and fragmentation. Dispersal success increased with the number of cells a disperser could search (m), but poor dispersers (m<5) searching via area-limited dispersal on fractal landscapes were more successful at locating suitable habitat than random dispersers on either random or fractal landscapes. Dispersal success was enhanced on fractal landscapes relative to random ones because of the greater spatial contagion of habitat. Dispersal success decreased proportionate to habitat loss for poor dispersers (m=1) on random landscapes, but exhibited an abrupt threshold at low levels of habitat abundance (p<0.1) for area-limited dispersers (m<10) on fractal landscapes. Conventional metrics of patch structure, including percolation, did not exhibit threshold behavior in the region of the dispersal threshold. A lacunarity analysis of the gap structure of landscape patterns, however, revealed a strong threshold in the variability of gap sizes at low levels of habitat abundance (p<0.1) in fractal landscapes, the same region in which abrupt declines in dispersal success were observed. The interpatch distances or gaps across which dispersers must move in search of suitable habitat should influence dispersal success, and our results suggest that there is a critical gap-size structure to fractal landscapes that interferes with the ability of dispersers to locate suitable habitat when habitat is rare. We suggest that the gap structure of landscapes is a more important determinant of dispersal than patch structure, although both are ultimately required to predict the ecological consequences of habitat fragmentation.     

Linking movement behavior and fine-scale genetic structure to model landscape connectivity for bobcats (Lynx rufus)

Spatial heterogeneity can constrain the movement of individuals and consequently genes across a landscape, influencing demographic and genetic processes. In this study, we linked information on landscape composition, movement behavior, and genetic differentiation to gain a mechanistic understanding of how spatial heterogeneity may influence movement and gene flow of bobcats in the agricultural landscape of Iowa (USA). We analyzed movement paths of 23 animals to parameterize landscape resistance surfaces, applied least cost path analysis to generate measures of effective geographic distance between DNA collection locations of 625 bobcats, and tested the correlation between genetic distance and the different models of geographic distance. We found that bobcats showed a strong preference for forest over any other habitat type, and that incorporating information on habitat composition both along the path and in the surrounding landscape provided the best model of movement. Measures of effective geographic distance were significantly correlated with genetic distance, but not once the effects of Euclidean distance were accounted for. Thus, despite the impact of habitat composition on movement behavior, we did not detect a signature of a landscape effect in genetic structure. Our results are consistent with the issue of limiting factors: the high uniformity of forest fragmentation across southern Iowa, the primary study area, results in a landscape resistance pattern virtually indistinguishable from the isolation-by-distance pattern. The northern portion of the state, however, is predicted to pose a high level of resistance to bobcat movement, which may impede the regional genetic connectivity of populations across the Midwest.     

Effect of historic landscape change on the genetic structure of the bush-cricket Metrioptera roeseli

This study investigates the impact of past and present landscape structure on the current genetic structure of the bush-cricket Metrioptera roeseli (Orthoptera, Tettigoniidae) in a rural landscape in Germany. Assuming that land-use types, such as grassland, arable land and forest, as well as linear structures, mainly roads, differentially affect the connectivity of the bush-cricket's habitat and therefore migration and gene flow, we correlated landscape parameters between sampling locations as derived from GIS-maps with genetic similarities between individual bush-crickets as estimated by RAPD-PCR. Fifty bush-crickets were sampled with distances between sampling locations varying between 15 m and 2 km. Corresponding landscape configurations were recorded in 8 years between 1945 and 1998. Landscape configuration 50 years ago appeared to have influenced the present genetic structure of the bush-cricket (R ² = 0.18). Crossing roads and land use other than grassland along the transect between sampling locations tended to decrease genetic similarity, whereas grassland and parallel roads tended to increase genetic similarity between bush-crickets. Following shifts in land use during 1953–1973 the correlation between landscape and present genetic structure decreased gradually. Our study suggests that it needs time for the landscape to build a visible effect on the genetic structure of the bush-cricket population, and that this effect cannot be detected if the landscape changes faster than the genetic structure responds to it.     

Behavior of class-level landscape metrics across gradients of class aggregation and area

Habitat loss and fragmentation processes strongly affect biodiversity conservation in landscapes undergoing anthropogenic land use changes. Many attempts have been made to use landscape structure metrics to quantify the independent and joint effects of these processes. Unfortunately, ecological interpretation of those metrics has been plagued by lack of thorough understanding of their theoretical behavior. We explored behavior of 50 metrics in neutral landscapes across a 21-step gradient in aggregation and a 19-step gradient in area using a full factorial design with 100 replicates of each of the 399 combinations of the two factors to assess how well metrics reflected changes in landscape structure. Metric values from real landscapes were used to determine the extent of neutral landscape space that is represented in real landscapes. We grouped metrics into three major behavioral classes: strongly related to focal class area (n=15), strongly related to aggregation (n=7), and jointly responding to area and aggregation (n=28). Metrics strongly related to class area exhibited a variety of distinct behaviors, and many of these metrics have unique interpretations that make each of them particularly useful in certain applications. Metrics strongly related to aggregation, independent of class area, are particularly useful in assessing effects of fragmentation. Moreover, metrics in this group exhibited a range of specific behaviors, highlighting subtle but different aspects of landscape aggregation even though we controlled only one aspect of aggregation. The non-linear behavior exhibited by many metrics renders interpretation difficult and use of linear analytical techniques inappropriate under many circumstances. Ultimately, comprehensive characterization of landscapes undergoing habitat loss and fragmentation will require using several metrics distributed across behavioral groups.This revised version was published online in May 2005 with corrections to the Cover Date.     

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.     

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.     

Linking life history traits to pollinator loss in fragmented calcareous grasslands

To gain insight into the drivers of pollinator loss, a holistic approach to land-use change including habitat size, isolation, habitat quality and the surrounding landscape matrix is necessary. Moreover, species’ responses to land-use change may differ depending on their life history traits such as dispersal ability, trophic level, or sociality. We assessed species richness and life history traits of wild bees in 32 calcareous grasslands in central Germany that differ in size, connectivity, resource availability and landscape context. Declining habitat area and, to a lesser degree, reduced diversity of the surrounding landscape were the key factors negatively influencing species richness. In the community-wide analysis, small body size and solitary reproduction were traits that made species particularly vulnerable to habitat loss. Contrary to our expectations, cleptoparasitic species were not more affected by reduced habitat area and landscape diversity than nest-building species. We performed further detailed trait analyses within the family Halictidae to prevent possible confounding effects due to trait correlations across families. Here, social as opposed to solitary species were more affected by habitat loss. We conclude that the opposite pattern observed for all social bees was mainly caused by large-sized social bumblebee species with high mobility and large foraging distances. Our results demonstrate the risks of concealed trait interference when analyzing community-wide patterns of life history traits. As a consequence, conservation requirements of small social bee species might be overlooked by generalizations from community responses.     

野生桂花的遗传多样性和遗传结构研究

 利用细胞核微卫星（nuclear microsatellite,nSSR）标记对中国4 个省的7 个野生桂花[Osmanthus fragrans（Thunb.）Lour.]群体139 个个体的遗传多样性和遗传结构进行了研究。11 个微卫星位点揭示了 野生桂花等位基因多样性（A）平均为6.039,有效等位基因数（Ne）平均为3.769,平均预期杂合度（He） 为0.673。所有群体均显著偏离哈温平衡,近交系数FIS 介于0.313 ~ 0.580 之间。群体间遗传分化系数FST = 0.143,AMOVA 分析表明群体间遗传分化占总遗传变异的12.69%,群体内的遗传变异为87.31%。Mantel 检验表明野生桂花群体间遗传距离与地理距离不存在相关性（r =–0.277,P = 0.214）。STRUCTURE 聚类 分析显示,所有个体被划分为3 个理论群体,庐山群体和浏阳群体中谱系较为单纯,而其他群体则存在 一定程度的遗传混杂。瓶颈效应分析显示,除浏阳群体外所有群体经历了种群衰退。