Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.     

Graph theory as a proxy for spatially explicit population models in conservation planning.

Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.     

The Application of Neutral Landscape Models in Conservation Biology

Neutral landscape models, derived from percolation theory in the field of landscape ecology, are grid-based maps in which complex habitat distributions are generated by random or fractal algorithms. This grid-based representation of landscape structure is compatible with the raster-based format of geographical information systems (GIS), which facilitates comparisons between theoretical and real landscapes. Neutral landscape models permit the identification of critical thresholds in connectivity, which can be used to predict when landscapes will become fragmented. The coupling of neutral landscape models with generalized population models, such as metapopulation theory, provides a null model for generating predictions about population dynamics in fragmented landscapes. Neutral landscape models can contribute to the following applications in conservation: (1) incorporation of complex spatial patterns in (meta)population models; (2) identification of species' perceptions of landscape structure; (3) determination of landscape connectivity; (4) evaluation of the consequences of habitat fragmentation for population subdivision; (5) identification of the domain of metapopulation dynamics; (6) prediction of the occurrence of extinction thresholds; ( 7) determination of the genetic consequences of habitat fragmentation; and (8) reserve design and ecosystem management. This generalized, spatially explicit framework bridges the gap between spatially implicit, patch-based models and spatially realistic GIS applications which are usually parameterized for a single species in a specific landscape. Development of a generalized, spatially explicit framework is essential in conservation biology because we will not be able to develop individual models for every species of management concern.     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

The spatial links tool: Automated mapping of habitat linkages in variegated landscapes

The removal, alteration and fragmentation of habitat in many parts of the world has led to a loss of biodiversity. Within the prevailing societal limitations the process is not easily reversed. Attempts are being made to minimise the fragmentation of remaining habitat by strategically reversing or managing habitat loss. Although their relative usefulness is a topic of debate among ecologists, habitat corridors are seen as one way of maintaining spatially dependent ecological processes within landscapes where habitat has been seriously depleted. Corridors can only be effective if they significantly contribute to the species sustaining processes of gene flow, resource access or the colonisation of vacant patches. We present a spatial habitat modelling methodology for evaluating the contribution and potential contribution of connecting paths to landscape connectivity. We have developed the spatial links tool (SLT), which maps link value across a region. The SLT combines connectivity measures from metapopulation ecology with the least cost path algorithm from graph theory, and can be applied to continuously variable landscape data. Combined with expert judgement, link value maps can be used to delineate habitat corridors. The approach capitalises on some synergies between ecological relevance and computational efficiency to produce an easily applied heuristic tool that has been successfully applied in NSW Australia.     

The effects of habitat loss, fragmentation, and community homogenization on resilience in estuaries.

When changes in the frequency and extent of disturbance outstrip the recovery potential of resident communities, the selective removal of species contributes to habitat loss and fragmentation across landscapes. The degree to which habitat change is likely to influence community resilience will depend on metacommunity structure and connectivity. Thus ecological connectivity is central to understanding the potential for cumulative effects to impact upon diversity. The importance of these issues to coastal marine communities, where the prevailing concept of open communities composed of highly dispersive species is being challenged, indicates that these systems may be more sensitive to cumulative impacts than previously thought. We conducted a disturbance-recovery experiment across gradients of community type and environmental conditions to assess the roles of ecological connectivity and regional variations in community structure on the recovery of species richness, total abundance, and community composition in Mahurangi Harbour, New Zealand. After 394 days, significant differences in recovery between sites were apparent. Statistical models explaining a high proportion of the variability (R2 > 0.92) suggested that community recovery rates were controlled by a combination of physical and ecological features operating across spatial scales, affecting successional processes. The dynamic and complex interplay of ecological and environmental processes we observed driving patch recovery across the estuarine landscape are integral to recovery from disturbances in heterogeneous environments. This link between succession/recovery, disturbance, and heterogeneity confirms the utility of disturbance-recovery experiments as assays for cumulative change due to fragmentation and habitat change in estuaries.     

Coupling urban 3-D information and circuit theory to advance the development of urban ecological networks

Ongoing, rapid urban growth accompanied by habitat fragmentation and loss challenges biodiversity conservation and leads to decreases in ecosystem services. Application of the concept of ecological networks in the preservation and restoration of connections among isolated patches of natural areas is a powerful conservation strategy. However, previous approaches often failed to objectively consider the impacts of complex 3-D city environments on ecological niches. We used airborne lidar-derived information on the 3-D structure of the built environment and vegetation and detailed land use and cover data to characterize habitat quality, niche diversity, and human disturbance and to predict habitat connectivity among 38 identified habitat core areas (HCAs) in Nanjing, China. We used circuit theory and Linkage Mapper to create a landscape resistance layer, simulate habitat connectivity, and identify and prioritize important corridors. We mapped 64 links by using current flow centrality to evaluate each HCA's contribution and the links that facilitate intact connectivity. Values were highest for HCA links located in the west, south, and northeast of the study area, where natural forests with complex 3-D structures predominate. Two smaller HCA areas had high centrality scores relative to their extents, which means they could act as important stepping stones in connectivity planning. The mapped pinch-point regions had narrow and fragile links among the HCAs, suggesting they require special protection. The barriers with the highest impact scores were mainly located at the HCA connections to Purple Mountain and, based on these high scores, are more likely to indicate important locations that can be restored to improve potential connections. Our novel framework allowed us to sufficiently convey spatially explicit information to identify targets for habitat restoration and potential pathways for species movement and dispersal. Such information is critical for assessing existing or potential habitats and corridors and developing strategic plans to balance habitat conservation and other land uses based on scientifically informed connectivity planning and implementation.     

Genes and song: genetic and social connections in fragmented habitat in a woodland bird with limited dispersal

Understanding the processes leading to population declines in fragmented landscapes is essential for successful conservation management. However, isolating the influence of disparate processes, and dispersal in particular, is challenging. The Grey Shrike-thrush, Colluricincla harmonica, is a sedentary woodland-dependent songbird, with learned vocalizations whose incidence in suitable habitat patches falls disproportionally with decline in tree cover in the landscape. Although it has been suggested that gaps in tree cover might act as barriers to its dispersal, the species remains in many remnants of native vegetation in agricultural landscapes, suggesting that it may have responded to habitat removal and fragmentation by maintaining or even increasing dispersal distances. We quantified population connectivity of the Grey Shrike-thrush in a system fragmented over more than 120 years using genetic (microsatellites) and acoustic (song types) data. First, we tested for population genetic and acoustic structure at regional and local scales in search of barriers to dispersal or gene flow and signals of local spatial structuring indicative of restricted dispersal or localized acoustic similarity. Then we tested for effects of habitat loss and fragmentation on genetic and acoustic connectivity by fitting alternative models of mobility (isolation-by-distance [the null model] and reduced and increased movement models) across treeless vs. treed areas. Birds within -5 km of each other had more similar genotypes and song types than those farther away, suggesting that dispersal and song matching are limited in the region. Despite restricted dispersal detected for females (but not males), populations appeared to be connected by gene flow and displayed some cultural (acoustic) connectivity across the region. Fragmentation did not appear to impact greatly the dispersal of the Grey Shrike-thrush: none of the mobility models fit the genetic distances of males, whereas for females, an isolation-by-distance model could not be rejected in favor of the models of reduced or increased movement through treeless gaps. However, dissimilarities of the song types were more consistent with the model of reduced cultural connectivity through treeless areas, suggesting that fragmentation impedes song type sharing in the Grey Shrike-thrush. Our paper demonstrates that habitat fragmentation hinders important population processes in an Australian woodland bird even though its dispersal is not detectably impacted.     

Toward Best Practices for Developing Regional Connectivity Maps

Abstract: To conserve ecological connectivity (the ability to support animal movement, gene flow, range shifts, and other ecological and evolutionary processes that require large areas), conservation professionals need coarse‐grained maps to serve as decision‐support tools or vision statements and fine‐grained maps to prescribe site‐specific interventions. To date, research has focused primarily on fine‐grained maps (linkage designs) covering small areas. In contrast, we devised 7 steps to coarsely map dozens to hundreds of linkages over a large area, such as a nation, province, or ecoregion. We provide recommendations on how to perform each step on the basis of our experiences with 6 projects: California Missing Linkages (2001), Arizona Wildlife Linkage Assessment (2006), California Essential Habitat Connectivity (2010), Two Countries, One Forest (northeastern United States and southeastern Canada) (2010), Washington State Connected Landscapes (2010), and the Bhutan Biological Corridor Complex (2010). The 2 most difficult steps are mapping natural landscape blocks (areas whose conservation value derives from the species and ecological processes within them) and determining which pairs of blocks can feasibly be connected in a way that promotes conservation. Decision rules for mapping natural landscape blocks and determining which pairs of blocks to connect must reflect not only technical criteria, but also the values and priorities of stakeholders. We recommend blocks be mapped on the basis of a combination of naturalness, protection status, linear barriers, and habitat quality for selected species. We describe manual and automated procedures to identify currently functioning or restorable linkages. Once pairs of blocks have been identified, linkage polygons can be mapped by least‐cost modeling, other approaches from graph theory, or individual‐based movement models. The approaches we outline make assumptions explicit, have outputs that can be improved as underlying data are improved, and help implementers focus strictly on ecological connectivity.     

Scale Mismatches,Conservation Planning,and the Value of Social‐Network Analyses

Many of the challenges conservation professionals face can be framed as scale mismatches. The problem of scale mismatch occurs when the planning for and implementation of conservation actions is at a scale that does not reflect the scale of the conservation problem. The challenges in conservation planning related to scale mismatch include ecosystem or ecological process transcendence of governance boundaries; limited availability of fine‐resolution data; lack of operational capacity for implementation; lack of understanding of social‐ecological system components; threats to ecological diversity that operate at diverse spatial and temporal scales; mismatch between funding and the long‐term nature of ecological processes; rate of action implementation that does not reflect the rate of change of the ecological system; lack of appropriate indicators for monitoring activities; and occurrence of ecological change at scales smaller or larger than the scale of implementation or monitoring. Not recognizing and accounting for these challenges when planning for conservation can result in actions that do not address the multiscale nature of conservation problems and that do not achieve conservation objectives. Social networks link organizations and individuals across space and time and determine the scale of conservation actions; thus, an understanding of the social networks associated with conservation planning will help determine the potential for implementing conservation actions at the required scales. Social‐network analyses can be used to explore whether these networks constrain or enable key social processes and how multiple scales of action are linked. Results of network analyses can be used to mitigate scale mismatches in assessing, planning, implementing, and monitoring conservation projects. Discordancia de Escalas, Planificación de la Conservación y el Valor del Análisis de Redes Sociales     

Connecting today's climates to future climate analogs to facilitate movement of species under climate change

Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate‐induced species’ movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species’ movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving‐window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species’ dispersal capabilities. We compared connectivity maps generated with our climate‐change‐informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present‐day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate.     

A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning

Abstract:  Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A).^. We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.     

Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model

Abstract:  Organisms respond to their surroundings at multiple spatial scales, and different organisms respond differently to the same environment. Existing landscape models, such as the "fragmentation model" (or patch-matrix-corridor model) and the "variegation model," can be limited in their ability to explain complex patterns for different species and across multiple scales. An alternative approach is to conceptualize landscapes as overlaid species-specific habitat contour maps. Key characteristics of this approach are that different species may respond differently to the same environmental conditions and at different spatial scales. Although similar approaches are being used in ecological modeling, there is much room for habitat contours as a useful conceptual tool. By providing an alternative view of landscapes, a contour model may stimulate more field investigations stratified on the basis of ecological variables other than human-defined patches and patch boundaries. A conceptual model of habitat contours may also help to communicate ecological complexity to land managers. Finally, by incorporating additional ecological complexity, a conceptual model based on habitat contours may help to bridge the perceived gap between pattern and process in landscape ecology. Habitat contours do not preclude the use of existing landscape models and should be seen as a complementary approach most suited to heterogeneous human-modified landscapes.     

Preface to the selected papers on spatially explicit landscape modelling: Current practices and challenges

In the past 30 years, the notion of landscape has emerged in ecology as a result of both theoretical strategies and practical aspects of land use. This has generated a variety of computerized models addressing both objectives and techniques. Scientists model landscapes for at least two reasons: to better understand the landscape dynamics themselves (called intrinsic needs) and to offer a realistic frame to support other ecological processes (extrinsic needs). This special issue concerns both needs and illustrates the way socioeconomic and/or ecological mechanisms of various landscapes have been understood through modelling approaches. It outlines the links between landscape and model concepts, focusing on one hand on several landscape types (agricultural, forested and aquatic) and on the other hand on several landscape model characteristics (explicit or neutral, dynamic or static, patchy or continuous and multi- or mono-scale). The patterns and processes of each landscape model presented in this issue, in particular, should be analysed in order to highlight the way they are contributing to the landscape ecology discipline. We finally argue that the discipline can now offer a theoretical dimension to landscape dynamics, aiming at understanding the possible mechanism unity underlying this complex object.     

Understanding the distribution of bushmeat hunting effort across landscapes by testing hypotheses about human foraging

Mitigating the massive impacts of defaunation on natural ecosystems requires understanding and predicting hunting effort across the landscape. But such understanding has been hindered by the difficulty of assessing the movement patterns of hunters in thick forests and across complex terrain. We statistically tested hypotheses about the spatial distribution of hunting with circuit theory and structural equation models. We used a data set of >7000 known kill locations in Guyana and hunter movement models to test these methods. Comparing models with different resistance layers (i.e., different estimates of how terrain and land cover influence human movement speed) showed that rivers, on average, limited movement rather than serving as transport arteries. Moreover, far more kills occurred close to villages than in remote areas. This, combined with the lack of support for structural equation models that included latent terms for prey depletion driven by past overhunting, suggests that kill locations in this system tended to be driven by where hunters were currently foraging rather than by influences of historical harvest. These analyses are generalizable to a variety of ecosystems, species, and data types, providing a powerful way of enhancing maps and predictions of hunting effort across complex landscapes.     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.     

Incorporating behaviour into simple models of dispersal using the biological control agent Dicyphus hesperus

We explored the utility of incorporating easily measured, biologically realistic movement rules into simple models of dispersal. We depart from traditional random walk models by designing an individual-based simulation model where we decompose animal movement into three separate processes: emigration, between-patch movement, and immigration behaviour. These processes were quantified using experiments on the omnivorous insect Dicyphus hesperus moving through a tomato greenhouse. We compare the predictions of the individual-based model, along with a series of biased random walk models, against an independent experimental release of D. hesperus. We find that in this system, the short-term dispersal of these insects is described well by our individual-based model, but can also be described by a 2D grid-based biased random walk model when mortality is accounted for.     

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

Importance of dispersal routes that minimize open‐ocean movement to the genetic structure of island populations

Islands present a unique scenario in conservation biology, offering refuge yet imposing limitations on insular populations. The Kimberley region of northwestern Australia has more than 2500 islands that have recently come into focus as substantial conservation resources. It is therefore of great interest for managers to understand the driving forces of genetic structure of species within these island archipelagos. We used the ubiquitous bar‐shouldered skink (Ctenotus inornatus) as a model species to represent the influence of landscape factors on genetic structure across the Kimberley islands. On 41 islands and 4 mainland locations in a remote area of Australia, we genotyped individuals across 18 nuclear (microsatellite) markers. Measures of genetic differentiation and diversity were used in two complementary analyses. We used circuit theory and Mantel tests to examine the influence of the landscape matrix on population connectivity and linear regression and model selection based on Akaike's information criterion to investigate landscape controls on genetic diversity. Genetic differentiation between islands was best predicted with circuit‐theory models that accounted for the large difference in resistance to dispersal between land and ocean. In contrast, straight‐line distances were unrelated to either resistance distances or genetic differentiation. Instead, connectivity was determined by island‐hopping routes that allow organisms to minimize the distance of difficult ocean passages. Island populations of C. inornatus retained varying degrees of genetic diversity (N_A = 1.83 – 7.39), but it was greatest on islands closer to the mainland, in terms of resistance‐distance units. In contrast, genetic diversity was unrelated to island size. Our results highlight the potential for islands to contribute to both theoretical and applied conservation, provide strong evidence of the driving forces of population structure within undisturbed landscapes, and identify the islands most valuable for conservation based on their contributions to gene flow and genetic diversity.     

Use of Empirically Derived Source-Destination Models to Map Regional Conservation Corridors

Abstract:  The ability of populations to be connected across large landscapes via dispersal is critical to long-term viability for many species. One means to mitigate population isolation is the protection of movement corridors among habitat patches. Nevertheless, the utility of small, narrow, linear features as habitat corridors has been hotly debated. Here, we argue that analysis of movement across continuously resistant landscapes allows a shift to a broader consideration of how landscape patterns influence connectivity at scales relevant to conservation. We further argue that this change in scale and definition of the connectivity problem improves one's ability to find solutions and may help resolve long-standing disputes regarding scale and definition of movement corridors and their importance to population connectivity. We used a new method that combines empirically derived landscape-resistance maps and least-cost path analysis between multiple source and destination locations to assess habitat isolation and identify corridors and barriers to organism movement. Specifically, we used a genetically based landscape resistance model for American black bears ( Ursus americanus ) to identify major movement corridors and barriers to population connectivity between Yellowstone National Park and the Canadian border. Even though western Montana and northern Idaho contain abundant public lands and the largest wilderness areas in the contiguous United States, moving from the Canadian border to Yellowstone Park along those paths indicated by modeled gene flow required bears to cross at least 6 potential barriers. Our methods are generic and can be applied to virtually any species for which reliable maps of landscape resistance can be developed.