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The Asiatic black bear (Ursus thibetanus), classified as a vulnerable species on the IUCN Red List, is an important mammal species found in the state of Sikkim, India. Studies carried out in Khangchendzonga National Park have documented the presence of these bears, highlighting their crucial conservation importance in the region. The population of Black bears are restricted to small habitat patches, which over the years have become fragmented by road networks and urban settlements. In such fragmented landscapes, connecting corridors play a crucial role in maintaining wildlife movement and genetic diversity. We assessed connectivity between eight protected areas in Sikkim using MaxENT and Circuitscape. 65 black bear presence locations (collected through Camera traps and sign surveys) and 24 environmental variables were used to model the corridors. Habitat suitability map was generated through MaxENT modelling approach. Our analysis suggests that there are multiple options to maintain connectivity for black bears in Sikkim. We mapped seven corridors and five pinch points (bottlenecks in connectivity), and calculated metrics to estimate their quality and importance. Our model output was supported by high AUC value (0.921) and field validation by questionnaire surveys and sign surveys to assess black bear presence and habitat use. Our results showed that 300 km² of the suitable regions are within the protected areas in Sikkim. The highest quality linkages as measured by the ratio of cost-weighted distance to Euclidean distance (CWD:EucD) and cost-weighted distance to least-cost path (CWD:LCP) were Khangchendzonga and Barsey, suggesting that these protected areas (National Parks and Wildlife Sanctuaries) and the developed corridors play important role in maintaining connectivity. We mapped pinch-points which are habitat where black bear movement is restricted due to unfavorable environments, linear infrastructures, built up/settlements or a combination of factors and our model predicted pinch points near few settlement areas; Mangan, Dikchu, Pangthang, Kabi, Yuksum and Lachen. Ground truthing confirmed that these areas also coincide with Black bear conflict zones in Sikkim. [ABSTRACT FROM AUTHOR]

Climate change poses a significant threat to biodiversity. Predicting the impacts of climate change on species distribution and dispersal through computational models and big data analysis can provide valuable insights. These predictions are crucial for developing effective strategies to mitigate the threats that climate change poses to biodiversity. Our study investigated the potential impact of climate change on an umbrella species (Ursus arctos pruinosus) in Western Sichuan Province, China. We employed the MaxEnt and Circuit Theory to assess both the current and potential future shifts in the distribution and migration corridors. The results indicated that climate and environmental factors had the greatest influence on species distribution, with bioclimatic variables bio12, bio3, and elevation contributing 22.1%, 21.5%, and 19.3%, respectively. Under current climatic conditions, the total suitable habitat area for the species was 70,969.78 km2, with the largest suitable habitats located in Shiqu and Litang, accounting for 24.39% and 15.86% of the total area, respectively. However, under future climate scenarios, predictions for RCP 2.6, RCP 4.5, and RCP 8.5 showed a significant reduction in suitable habitat area, ranging from 7789.26 km2 to 16,678.85 km2. The Yajiang and Xinlong counties experienced the most severe habitat reductions, with declines exceeding 50%. Additionally, the altitudinal distribution of suitable habitats shifted, with suitable habitats gradually moving to higher elevations under future climate scenarios. Our study also analyzed the species' dispersal paths. Under current climatic conditions, the dispersal paths predominantly followed a northwest-to-southeast orientation. However, by the 2070s, under all three RCPs, dispersal resistance is projected to significantly increase, the density of dispersal paths will decrease, and the connectivity of these paths will be reduced. In the most extreme RCP 8.5 scenario, southern dispersal paths nearly disappeared, and the dispersal paths contracted towards the northwest. These findings highlight potential threats posed by climate change to the species' habitats and dispersal corridors, emphasizing the importance of considering both current and future climate change in conservation strategies to protect this vulnerable species and its ecosystem. [ABSTRACT FROM AUTHOR]

The Upper Paraguay Basin (BAP) is one of the largest river basins in South America, covering three countries: Brazil, Bolivia and Paraguay. In Brazil, one of the main risks to BAP conservation is the loss of native vegetation. In the floodplain region of the BAP, more than 13% of native vegetation was converted, while in the surrounding highlands the loss of native vegetation reached over 61% of the area. These values tend to increase, highlighting the importance of territorial planning for sustainable development in the region. In this sense, we mapped the ecological corridors in the Upper Paraguay Basin, in Brazil, to support conservation strategies focused on maintaining connectivity on a regional scale. To achieve this, we use the Least Cost Path and Circuitscape methods, based on a multispecies approach. As a result, we identified 303 fragments of native vegetation or conservation units that can be considered nodes and 859 ecological corridors. Of all the ecological corridors identified, around 288 were lost in just 3 years, due to the conversion of native vegetation. In general, our results were an extensive network of corridors, which can be applied in UPRB territorial planning, aiming to reduce the impacts of loss of connectivity in the region. Our results highlight the importance of territorial planning and quick and effective decision‐making to mitigate the effects of native vegetation loss for biodiversity conservation in the UPRB. [ABSTRACT FROM AUTHOR]

Context: Ecological corridors are one of the most recommended ways to mitigate biodiversity loss. With growing recognition of corridor importance, corridor modeling lags others in the development of robust, quantitative validation methods. Objective: We propose a post-hoc corridor validation framework, considering the range of methods across data needs and statistical intensity. We demonstrate the importance of post-hoc corridor validation by testing several validation methods on different corridor model outputs. Methods: We used three different transformations on a Florida black bear (Ursus americanus floidanus) habitat suitability model to create different resistance grids, independent GPS collar data from a case study population, and Circuitscape to create corridor models. We used several validation methods, including a novel method, to compare resulting corridors. Results: Transformed resistance grids were all correlated, yet differing validation and resistance grids resulted in different recommended corridors. The use of one resistance surface and one validation type can result in the selection of inefficient or ineffective corridors. At a minimum, modelers should determine what proportion of an independent population falls within resulting corridors and should move towards more robust, documented methods as resources allow. The use of multiple validation methods can ensure greater confidence of modeling results. Conclusions: We encourage the use and further development of the framework presented here to drive the corridor modeling field towards more effective corridor creation and improved conservation outcomes. If validation methods are not improved, the ecological and economic cost of poor corridor science will continue to increase with increasing biodiversity loss. [ABSTRACT FROM AUTHOR]

The Asiatic black bear (Ursus thibetanus), classified as a vulnerable species on the IUCN Red List, is an important mammal species found in the state of Sikkim, India. Studies carried out in Khangchendzonga National Park have documented the presence of these bears, highlighting their crucial conservation importance in the region. The population of Black bears are restricted to small habitat patches, which over the years have become fragmented by road networks and urban settlements. In such fragmented landscapes, connecting corridors play a crucial role in maintaining wildlife movement and genetic diversity. We assessed connectivity between eight protected areas in Sikkim using MaxENT and Circuitscape. 65 black bear presence locations (collected through Camera traps and sign surveys) and 24 environmental variables were used to model the corridors. Habitat suitability map was generated through MaxENT modelling approach. Our analysis suggests that there are multiple options to maintain connectivity for black bears in Sikkim. We mapped seven corridors and five pinch points (bottlenecks in connectivity), and calculated metrics to estimate their quality and importance. Our model output was supported by high AUC value (0.921) and field validation by questionnaire surveys and sign surveys to assess black bear presence and habitat use. Our results showed that 300 km² of the suitable regions are within the protected areas in Sikkim. The highest quality linkages as measured by the ratio of cost-weighted distance to Euclidean distance (CWD:EucD) and cost-weighted distance to least-cost path (CWD:LCP) were Khangchendzonga and Barsey, suggesting that these protected areas (National Parks and Wildlife Sanctuaries) and the developed corridors play important role in maintaining connectivity. We mapped pinch-points which are habitat where black bear movement is restricted due to unfavorable environments, linear infrastructures, built up/settlements or a combination of factors and our model predicted pinch points near few settlement areas; Mangan, Dikchu, Pangthang, Kabi, Yuksum and Lachen. Ground truthing confirmed that these areas also coincide with Black bear conflict zones in Sikkim.

Construction and paving of road infrastructures is on the rise globally. Roads have many negative impacts on the environment, including changes and damages to landscape connectivity, fragmentation and disrupting of ecological corridors, loss of habitats, air pollution, noise pollution and light pollution . Here we aimed to examine the impacts of the construction of a major road (national Highway 6 in Israel, 188 km long) on landscape fragmentation. To this end we mapped the land cover at three-time steps: 1997 (before the construction of the road began), 2009 and 2019, quantifying both patch-based metrics (using Frgastats), the continuous metrics of landscape connectivity (using Circuitscape) and landscape continuity, adapting a before-after-control-impact methodology. Analyzing changes in those metrics for sections of the road based on their time of construction and on the distance from the highway, we found that most changes took place within a distance of up to 1 km from the new highway, starting after road construction began. We also found that the patch-based metrics and the continuous metrics were weakly correlated. We conclude that each of those different approaches has its merits and limitations, that they are complementary and that jointly they provide us with better understanding of landscape changes.

The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage connects wilderness areas in the northeastern United States with southeastern Canada. However, land conversion is putting wolf habitat amount and functional connectivity at risk. With the exception of protected areas, hunting and trapping of wolves and coyotes are permitted within the Québec and Ontario portions, while hunting and trapping coyotes are permitted within the New York portion where wolves have been extirpated. Thus, the fear of humans strongly influences wolf habitat selection in this region. We assessed the impact of land conversion on wolf habitat amount, habitat fragmentation, and functional connectivity in the A2L between 2000 and 2015 and identified potential suitable habitat patches and corridors for protection. Suitable habitat patch area decreased by 18,245 km2 (27%), with losses of 28% in the Québec portion, 95% in the Ontario portion, but only 0.3% in the New York portion. Habitat fragmentation, as measured by the effective mesh size, substantially increased in the Québec and Ontario portions, but only slightly in the New York portion. Functional connectivity significantly decreased, with mean distances and the cost of traveling these distances more than doubling. We propose nine recommendations centered on extensive habitat restoration and protected area expansion in the Québec and Ontario portions of the study area. Wolf recovery within the A2L will require collaborative and coordinated transboundary conservation and the protection of suitable habitat patches and corridors, or the legal protection of both wolves and coyotes within the suitable habitat patches and corridors, to ensure that wolves are not harvested as they disperse and colonize new locations. [ABSTRACT FROM AUTHOR]

Across Africa, space for conservation is sometimes limited to formally protected areas that have become progressively more isolated. There is a need for targeted conservation initiatives such as the demarcation of landscape connections, defined as areas that encompass environmental variables that promote the natural movement of individuals between populations, which can facilitate gene flow. Landscape connections can mitigate genetic isolation, genetic drift, and inbreeding, which can occur in isolated populations in protected areas. Promoting gene flow can reduce the risk of extirpation often associated with isolated populations. Here we develop and test models for identifying landscape connections among African savannah elephant (Loxodonta africana) populations by combining habitat suitability modeling with gene flow estimates across a large region including seven countries. We find a pronounced non-linear response to unsuitable habitat, consistent with previous studies showing that non-transformed habitat models are poor predictors of gene flow. We generated a landscape connections map that considers both suitable habitats based on telemetry occurrence data and gene flow estimated as the inverse of individual genetic distance, delineating areas that are important for maintaining elephant population connectivity. Our approach represents a novel framework for developing spatially and genetically informed conservation strategies for elephants and many other taxa distributed across heterogeneous and fragmented landscapes. [ABSTRACT FROM AUTHOR]

Giraffe populations have declined by around 40% in the last three decades. Climate change, poaching, habitat loss, and increasing human pressures are confining giraffes to smaller and more isolated patches of habitats. Masai giraffes (Giraffa tippelskirchi) have been subjected to habitat loss and fragmentation, diseases, poaching, and unpredictable calamities such as wildfires and climate change. In this study, we aimed to identify (1) suitable Masai giraffe habitats within the transboundary landscape of Tsavo‐Mkomazi in Southern Kenya and Northern Tanzania; and (2) key connecting corridors in a multiple‐use landscape for conservation prioritization. We combined Masai giraffe presence data collected through a total aerial survey with moderate resolution satellite data to model habitat suitability at 250 m resolution using species distribution models (SDMs) implemented in Google Earth Engine (GEE). Model accuracy was assessed using area under precision recall curve (AUC‐PR). We then used the habitat suitability index as a resistance surface to model functional connectivity using Circuitscape theory and cost‐weighted distance pairwise methods. Human habitat modification, rainfall, and elevation were the main model predictors of Masai giraffe habitat and corridors. On average, our 10‐fold model fitting attained a good predictive performance with an average AUC‐PR = 0.80 (SD = 0.01, range = 0.79–0.83). The model predicted an area of 15,002 km2 as potential suitable Masai giraffe habitat with over 17% outside protected areas within the landscape. Although Tsavo West National Park formed a key habitat and a key connecting corridor, nonprotected community ranches connecting Tsavo West and Tsavo East National Parks are equally important in maintaining landscape connectivity joining more than two Masai giraffe core areas with low resistance and high permeability. To maintain critical Masai giraffe's habitats and landscape functional connectivity, especially in multiple‐use landscapes, conservation‐compatible land use practices, capacity building, and land use planning should be considered at the outset of any new infrastructure development and land use changes. This modeling shows the potential of utilizing remotely sensed information and ground surveys to guide the management of habitats and their connecting corridors across important African landscapes, complementing existing efforts to identify, conserve, and protect wildlife habitats and their linkage zones. [ABSTRACT FROM AUTHOR]

This study provides the first comprehensive assessment of habitat connectivity for the Mongolian saiga, a species endemic to Western Mongolia. We utilized a resource selection function (RSF) to identify core habitats (CHs) throughout the saiga's entire range. Additionally, the Circuitscape approach was employed to map the least-cost paths (LCPs) among these core habitats. The RSF models revealed a strong preference for high productivity areas, while avoiding disturbed regions. Through a spatially explicit model, 34 CHs covering an area of 12,480 km2 (30.7% of the saiga's range) were identified. The connectivity models identified 68 LCPs between various pairs of CHs, totaling 1700 km in length across the entire saiga range. The core habitat in the center of the saiga range displayed the highest centrality scores, highlighting their critical importance in maintaining their habitat interconnectedness. Furthermore, the presence of pinch points was observed in several CH pairs within the northwest region, suggesting potential bottlenecks that may hinder movement between these habitats. It is imperative to implement measures aimed at addressing these pinch points and establishing secure corridors to facilitate the saiga movement between the CHs. To ensure the survival of the saiga, it is also crucial to mitigate the impact of existing and planned linear infrastructures, as well as other human disturbances that have the potential to fragment habitats and disrupt connectivity. These findings serve as valuable insights for targeted conservation efforts and the formulation of effective management strategies geared toward safeguarding this iconic species in Western Mongolia. [ABSTRACT FROM AUTHOR]

Ecological connectivity is key for the long-term viability of species and is necessary when facing disturbance or global change, and geospatial analysis tools are key to exploring it with conservation aims. The vicuña is an ungulate endemic from South American highlands that faced extinction risk fifty years ago and is now slowly expanding and increasing in numbers. At present, it has a patchy distribution that may partially reflect connectivity limitations, an issue which can be key for its conservation under climate change. We developed a habitat suitability model using MaxEnt and location data of vicuñas in the Tarapacá region (Northern Chile), combined with spatial layers derived from remotely sensed imagery. We then used these results as the basis for a cost surface layer, and we examined habitat connectivity using least-cost and graph theory methods. Results showed the relevance for the species of habitat patches in the Southern part of the study area, out of protected areas, and the fact that ecological connectivity relies mainly on the intra-patch and flux components. These results should guide conservation actions for the species in the area and exemplify the relevance of remote sensing and geospatial models in the study of remote areas. [ABSTRACT FROM AUTHOR]

Abstract Giraffe populations have declined by around 40% in the last three decades. Climate change, poaching, habitat loss, and increasing human pressures are confining giraffes to smaller and more isolated patches of habitats. Masai giraffes (Giraffa tippelskirchi) have been subjected to habitat loss and fragmentation, diseases, poaching, and unpredictable calamities such as wildfires and climate change. In this study, we aimed to identify (1) suitable Masai giraffe habitats within the transboundary landscape of Tsavo‐Mkomazi in Southern Kenya and Northern Tanzania; and (2) key connecting corridors in a multiple‐use landscape for conservation prioritization. We combined Masai giraffe presence data collected through a total aerial survey with moderate resolution satellite data to model habitat suitability at 250 m resolution using species distribution models (SDMs) implemented in Google Earth Engine (GEE). Model accuracy was assessed using area under precision recall curve (AUC‐PR). We then used the habitat suitability index as a resistance surface to model functional connectivity using Circuitscape theory and cost‐weighted distance pairwise methods. Human habitat modification, rainfall, and elevation were the main model predictors of Masai giraffe habitat and corridors. On average, our 10‐fold model fitting attained a good predictive performance with an average AUC‐PR = 0.80 (SD = 0.01, range = 0.79–0.83). The model predicted an area of 15,002 km2 as potential suitable Masai giraffe habitat with over 17% outside protected areas within the landscape. Although Tsavo West National Park formed a key habitat and a key connecting corridor, nonprotected community ranches connecting Tsavo West and Tsavo East National Parks are equally important in maintaining landscape connectivity joining more than two Masai giraffe core areas with low resistance and high permeability. To maintain critical Masai giraffe's habitats and landscape functional connectivity, especially in multiple‐use landscapes, conservation‐compatible land use practices, capacity building, and land use planning should be considered at the outset of any new infrastructure development and land use changes. This modeling shows the potential of utilizing remotely sensed information and ground surveys to guide the management of habitats and their connecting corridors across important African landscapes, complementing existing efforts to identify, conserve, and protect wildlife habitats and their linkage zones.

Urbanization is commonly associated with biodiversity loss and habitat fragmentation. However, urban environments often have greenspaces that can support wildlife populations, including rare species. The challenge for conservation planners working in these systems is identifying priority habitats and corridors for protection before they are lost. In a rapidly changing urban environment, this requires prompt decisions informed by accurate spatial information. Here, we combine several approaches to map habitat and assess connectivity for a diverse set of rare species in seven urban study areas across southern Michigan, USA. We incorporated multiple connectivity tools for a comprehensive appraisal of species‐habitat patterns across these urban landscapes. We observed distinct differences in connectivity by taxonomic group and site. The three turtle species (Blanding's, Eastern Box, and Spotted) consistently had more habitat predicted to be suitable per site than other evaluated species. This is promising for this at‐risk taxonomic group and allows conservation efforts to focus on mitigating threats such as road mortality. Grassland and prairie‐associated species (American Bumble Bee, Black and Gold Bumble Bee, and Henslow's Sparrow) had the least amount of habitat on a site‐by‐site basis. Kalamazoo and the northern Detroit sites had the highest levels of multi‐species connectivity across the entire study area based on the least cost paths. These connectivity results have direct applications in urban planning. Kalamazoo, one of the focal urban regions, has implemented a Natural Features Protection (NFP) plan to bolster natural area protections within the city. We compared our connectivity results to the NFP area and show where this plan will have an immediate positive impact and additional areas for potential consideration in future expansions of the protection network. Our results show that conservation opportunities exist within each of the assessed urban areas for maintaining rare species, a key benefit of this multi‐species and multi‐site approach. [ABSTRACT FROM AUTHOR]

Context: The successful dispersal of an animal depends, partly, on landscape connectivity. Urbanization poses risks to dispersal activities by increasing hostile land cover types. Objectives: We investigated how connectivity of urban ponds impacted Odonata communities (dragonflies and damselflies), an order of semi-aquatic insects that actively disperse. Methods: We sampled 41 constructed stormwater ponds and 8 natural ponds in a metropolitan area. The effect of connectivity and the quantity of available adjacent habitats was tested at different scales for dragonflies (900 m) and damselflies (300 m), determined by a literature analysis, to account for differences in suborder dispersal capabilities. Results: Lower levels of connectivity and fewer nearest neighbours negatively impacted abundance, species richness, and composition of dragonflies (p values < 0.01, R2 = 0.18–0.70). Adult dragonfly abundance had a stronger positive relationship with connectivity than species richness. In particular, the abundance of adult dragonfly Leucorrhinia frigida, found almost exclusively at natural ponds, had a positive relationship with connectivity. Connectivity and the number of nearest neighbours had no significant impact on damselflies apart from a slight negative relationship between connectivity and species richness (p value = 0.02, R2 = 0.11). Natural ponds had significantly higher levels of connectivity when compared to stormwater ponds. Conclusions: Our results suggest that dragonflies are positively affected by increased connectivity in an urban landscape, with no benefit of connectivity to damselflies at the scale measured. We recommend intentional planning of urban stormwater pond networks, where individual ponds can act as stepping stones, incorporated with strategic inclusion of beneficial land cover types. [ABSTRACT FROM AUTHOR]

Restoring landscape connectivity is a key strategy for sustaining biodiversity and ecosystem services. We developed a decision‐focused process that moves from opportunistic siting of restoration to strategic prioritization by incorporating connectivity enhancement in the Appalachian Mountains, USA. Our approach builds from a recent national‐scale assessment identifying a Resilient and Connected Network (RCN) to inform land protection priorities under climate change. In three high‐ranking study areas within the Appalachians, we demonstrated a circuit‐theory based approach simulating the connectivity value of restoring natural vegetation at sites with high human modification. Our methods were co‐developed by scientists and local decision‐makers. This emphasis on study area‐specific decisions led to differences in how model inputs were defined, for instance using feasible potential restoration sites instead of pixels to define opportunities. Similarly, landscape context influenced our process and in fragmented study areas we added a step that considered additional potential restoration sites outside of the current land protection‐based boundaries. To help interpretation of the results, and link back to the broader network of conservation priorities, we mapped connectivity values in current flow categories that matched the RCN product. Our innovative approach and the decision‐relevant framing, can inform a broad range of connectivity science applications. [ABSTRACT FROM AUTHOR]

Maintaining and restoring ecological connectivity is considered a global imperative to help reverse the decline of biodiversity. To be successful, practitioners need to be guided by connectivity modeling research that is rigorous and reliable for the task at hand. However, the methods and workflows within this rapidly growing field are diverse and few have been carefully scrutinized. We propose four steps that should be consistently undertaken in connectivity modeling studies in order to improve rigour and utility: 1) describe the type of connectivity being modeled, 2) assess the uncertainty and sensitivity of model parameters, 3) validate the model outputs, ideally with independent data and 4) make non‐sensitive raw data and code openly available to enhance computational reproducibility. We reviewed the literature to determine the extent to which studies included these four steps. We focused on studies that generated novel landscape connectivity outputs using circuit theory and restricted our assessment to studies concerning terrestrial mammals. Among 181 studies meeting our search criteria, 39% communicated the type of connectivity being modeled, 18% conducted some form of sensitivity or uncertainty analysis (or both), 18% of studies attempted to validate their connectivity model outputs and only 7% used fully independent data to do so. Lastly, 13% of the studies made all raw data available, 2% provided all required code and only two studies provided both. Our findings highlight a clear need and opportunity to improve the reliability, reproducibility and utility of connectivity modeling research. We provide a checklist that researchers can consult and include with outputs. This will help practitioners make more informed decisions and ensure limited resources for connectivity conservation and restoration are allocated appropriately. [ABSTRACT FROM AUTHOR]

Hindrance in the ecological connectivity and gene transfer in the ecosystem affects numerous animals from large mammals to small invertebrates. For foraging, mating, and dispersal, many animal species need wide-ranging habitats such as ungulates—deer, elk, as well as bears, wolves, mountain lions, elephants and tigers. Their access to suitable habitats might be restricted by fragmented landscapes, which can also block essential movement corridors. Moreover, increased human inhabitants and population shift towards the edge of forests provides animals with very less or no scope of living in the wilderness thereby isolating the population. As a result, ecological connectivity analysis and landscape planning are integral part of one another. This paper gives a scoping review of the modelling techniques used to address the ecological connectivity in a landscape. The literature on existing modelling technique, highlighting its uses, advantages, limitations, and developments, is analysed and summarised in the paper. An exhaustive discussion on modelling techniques such as graph theoretic approaches (least cost path analysis, network analysis, etc.), circuit theoretic approaches, agent-based models and machine learning-based approach is compiled for improved decision-making. This review paper aims to support evidence-based decision-making by synthesising the current state of knowledge, identifying research gaps, and providing insights into future directions for advancing connectivity modelling. [ABSTRACT FROM AUTHOR]

Context: The Adirondack-to-Laurentians (A2L) transboundary wildlife linkage is one of three north–south movement linkages that connect natural areas in northeastern USA and southeastern Canada. This region still retains habitats of high ecological integrity and biodiversity; however, anthropogenic land transformation may be putting transboundary connectivity at risk. Objectives: We measured the impacts of anthropogenic land transformation on species-specific habitat amount, fragmentation, and connectivity in the A2L between 2000 and 2015. Methods: We developed suitable habitat and resistance models for the American black bear (Ursus americanus), fisher (Pekania pennanti), moose (Alces alces), and white-tailed deer (Odocoileus virginianus) to identify suitable and optimal habitat patches for each species. We quantified habitat amount, fragmentation, and connectivity, and used Linkage Mapper and Circuitscape to map corridors and pinch-points important for connectivity. Results: In the A2L between 2000 and 2015, suitable and optimal habitat patch area declined considerably, fragmentation increased, and inter-patch connectivity decreased for each species. Moose and black bear habitat patches experienced the greatest habitat loss, fragmentation, and decline in inter-patch connectivity. The majority of habitat patch area loss and fragmentation occurred in the southern Québec and Ontario portions. Conclusions: To achieve long-term functionality of the A2L, collaborative and coordinated measures will be necessary to preserve the integrity of the Québec mega-patch, restore extensive habitat in eastern Ontario, and reestablish or maintain connectivity throughout the linkage. Left unaddressed, continued anthropogenic land transformation is likely to have detrimental effects on the ability of the A2L to function as a transboundary wildlife linkage. [ABSTRACT FROM AUTHOR]

Abstract Increasingly precise spatial data (e.g. high‐resolution imagery from remote sensing) allow for improved representations of the landscape network for assessing the combined effects of habitat loss and connectivity declines on biodiversity. However, evaluating large landscape networks presents a major computational challenge both in terms of working memory and computation time. We present the ConScape (i.e. “connected landscapes”) software library implemented in the high‐performance open‐source Julia language to compute metrics for connected habitat and movement flow on high‐resolution landscapes. The combination of Julia's ‘just‐in‐time’ compiler, efficient algorithms and ‘landmarks’ to reduce the computational load allows ConScape to compute landscape ecological metrics—originally developed in metapopulation ecology (such as ‘metapopulation capacity’ and ‘probability of connectivity’)—for large landscapes. An additional major innovation in ConScape is the adoption of the randomized shortest paths framework to represent connectivity along the continuum from optimal to random movements, instead of only those extremes. We demonstrate ConScape's potential for using large datasets in sustainable land planning by modelling landscape connectivity based on remote‐sensing data paired with GPS tracking of wild reindeer in Norway. To guide users, we discuss other applications, and provide a series of worked examples to showcase all ConScape's functionalities in Supplementary Material. Built by a team of ecologists, network scientists and software developers, ConScape is able to efficiently compute landscape metrics for high‐resolution landscape representations to leverage the availability of large data for sustainable land use and biodiversity conservation. As a Julia implementation, ConScape combines computational efficiency with a transparent code base, which facilitates continued innovation through contributions from the rapidly growing community of landscape and connectivity modellers using Julia.

Ecological connectivity is key for the long-term viability of species and is necessary when facing disturbance or global change, and geospatial analysis tools are key to exploring it with conservation aims. The vicuña is an ungulate endemic from South American highlands that faced extinction risk fifty years ago and is now slowly expanding and increasing in numbers. At present, it has a patchy distribution that may partially reflect connectivity limitations, an issue which can be key for its conservation under climate change. We developed a habitat suitability model using MaxEnt and location data of vicuñas in the Tarapacá region (Northern Chile), combined with spatial layers derived from remotely sensed imagery. We then used these results as the basis for a cost surface layer, and we examined habitat connectivity using least-cost and graph theory methods. Results showed the relevance for the species of habitat patches in the Southern part of the study area, out of protected areas, and the fact that ecological connectivity relies mainly on the intra-patch and flux components. These results should guide conservation actions for the species in the area and exemplify the relevance of remote sensing and geospatial models in the study of remote areas.

The sagebrush biome within the western United States has been reshaped by disturbances, management, and changing environmental conditions. As a result, sagebrush cover and configuration have varied over space and time, influencing processes and species that rely on contiguous, connected sagebrush. Previous studies have documented changes in sagebrush cover, but we know little about how the connectivity of sagebrush has changed over time and across the sagebrush biome. We investigated temporal connectivity patterns for sagebrush using a time series (1985–2020) of fractional sagebrush cover and used an omnidirectional circuit algorithm to assess the density of connections among areas with abundant sagebrush. By comparing connectivity patterns over time, we found that most of the biome experienced moderate change; the amount and type of change varied spatially, indicating that areas differ in the trend direction and magnitude of change. Two different types of designated areas of conservation and management interest had relatively high proportions of stable, high-connectivity patterns over time and stable connectivity trends on average. These results provide ecological information on sagebrush connectivity persistence across spatial and temporal scales that can support targeted actions to address changing structural connectivity and to maintain functioning, connected ecosystems. [ABSTRACT FROM AUTHOR]

Context: Habitat connectivity can stabilise animal populations by facilitating immigration and genetic exchange, but it increases the risk of infectious diseases being spread by hosts. Chytridiomycosis caused by Batrachochytrium salamandrivorans (Bsal) threatens European salamander diversity. The extent to which the connectivity of populations of fire salamanders (Salamandra salamandra) contributes to the spread of Bsal remains unclear. Objectives: We analysed the impact of habitat connectivity of fire salamanders on the spread of Bsal. Moreover, we show how local salamander abundance is associated with habitat connectivity over a five-year period. Methods: We developed fire salamander habitat suitability models (HSMs) for the Eifel area (Germany), currently considered the core of the range of Bsal in Europe. Habitat models were used to calculate pairwise resistance between salamander occurrences to test whether Bsal presence and salamander abundance were associated with habitat connectivity. Results: Fire salamanders are widely distributed in the Eifel. Solid bedrock and topographic positioning were important predictors of stream suitability as breeding habitats, while deciduous forests and grassland cover determined overall fire salamander habitat suitability along with breeding habitat suitability. Bsal-positive salamander occurrences were better-connected than Bsal-negative or untested occurrences. Nevertheless, fire salamander larvae were more abundant in well-connected sites. Conclusion: The connection of salamander populations by suitable habitat seems to support local salamander abundance while facilitating the spread of Bsal. In situ conservation measures counteracting host species connectivity to interrupt Bsal transmission pathways must be implemented with caution, as they may weaken the demographic advantages of connectivity. [ABSTRACT FROM AUTHOR]

Summary: The Atlantic Forest of South America has undergone major changes due to urban and agriculture/pasture extension, resulting in a highly fragmented biome. Protected areas, created to ensure the biodiversity conservation of this biome, need to be connected for long-term landscape integrity. We aimed to quantify connectivity among protected areas in the south-east Atlantic Forest using two species with different environmental requirements: a threatened species with high requirements, the jaguar Panthera onca ; and an exotic species with low requirements, the wild pig Sus scrofa. Our methods included expert opinion, and Circuitscape and least-cost-path analyses. We hypothesized that the patchy and altered landscape would not support the connectivity of jaguars but would allow wild pigs to transit. In fact, we found connectivity for both species, but there were more connectivity opportunities for wild pigs. The connection between Serra do Mar (and Serra do Mar state park) and Serra da Mantiqueira (Mantiqueira Mosaic) is narrow but possible to traverse through some protected areas of sustainable use and private reserves, highlighting the importance of these to structural landscape connectivity for the studied species in this region. The same connectivity that allows the transit of the native jaguar with high environmental requirements also allows the invasive wild pig to move through the landscape, which is worrisome. [ABSTRACT FROM AUTHOR]

Increasingly precise spatial data (e.g. high‐resolution imagery from remote sensing) allow for improved representations of the landscape network for assessing the combined effects of habitat loss and connectivity declines on biodiversity. However, evaluating large landscape networks presents a major computational challenge both in terms of working memory and computation time. We present the ConScape (i.e. "connected landscapes") software library implemented in the high‐performance open‐source Julia language to compute metrics for connected habitat and movement flow on high‐resolution landscapes.The combination of Julia's 'just‐in‐time' compiler, efficient algorithms and 'landmarks' to reduce the computational load allows ConScape to compute landscape ecological metrics—originally developed in metapopulation ecology (such as 'metapopulation capacity' and 'probability of connectivity')—for large landscapes. An additional major innovation in ConScape is the adoption of the randomized shortest paths framework to represent connectivity along the continuum from optimal to random movements, instead of only those extremes.We demonstrate ConScape's potential for using large datasets in sustainable land planning by modelling landscape connectivity based on remote‐sensing data paired with GPS tracking of wild reindeer in Norway. To guide users, we discuss other applications, and provide a series of worked examples to showcase all ConScape's functionalities in Supplementary Material.Built by a team of ecologists, network scientists and software developers, ConScape is able to efficiently compute landscape metrics for high‐resolution landscape representations to leverage the availability of large data for sustainable land use and biodiversity conservation. As a Julia implementation, ConScape combines computational efficiency with a transparent code base, which facilitates continued innovation through contributions from the rapidly growing community of landscape and connectivity modellers using Julia. [ABSTRACT FROM AUTHOR]

Fencing is one of the most widely utilized tools for reducing human-wildlife conflict in agricultural landscapes. However, the increasing global footprint of fencing exceeds millions of kilometers and has unintended consequences for wildlife, including habitat fragmentation, movement restriction, entanglement, and mortality. Here, we present a novel and quantitative approach to prioritize fence removal within historic migratory pathways of white-bearded wildebeest (Connochaetes taurinus) across Kenya's Greater Masai Mara Ecosystem. Our approach first assesses historic and contemporary landscape connectivity of wildebeest between seasonal ranges by incorporating two sets of GPS tracking data and fine-scale fencing data. We then predict connectivity gains from simulated fence removal and evaluate the impact of different corridor widths and locations on connectivity and removal costs derived from locally implemented interventions. Within the study system, we found that modest levels of fence removal resulted in substantial connectivity gains (39%-54% improvement in connectivity for 15-140 km of fence line removed). By identifying the most suitable corridor site, we show that strategically placed narrow corridors outperform larger, more expensive interventions. Our results demonstrate how and where targeted fence removal can enhance connectivity for wildlife. Our framework can aid in identifying suitable and cost-effective corridor restoration sites to guide decision-makers on the removal of fences and other linear barriers. Our approach is transferable to other landscapes where the removal or modification of fences or similar barriers is a feasible mitigation strategy to restore habitat and migratory connectivity., (© 2025 The Author(s). Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

IntroductionThe maintenance of habitat connections between fragmented habitat patches is vital for the conservation of wildlife populations and ecosystem functioning. The awareness of connectivity issues for species conservation has resulted in a growth of connectivity modeling and the application of these results in conservation planning. Such connectivity modeling efforts can include several decisions or data limitations, which could influence the connectivity results and ultimately a systematic conservation plan (SCP). However, there has been little investigation of how these different decisions on species, scale, and extent influence the ultimate conservation planning outcomes.MethodsWe modeled the connectivity of northern bobwhite (Colinus virginianus), North American river otter (Lontra canadensis), and black bear (Ursus americanus), three species with varying ecological requirements, through the Congaree Biosphere Region, South Carolina, USA. We modeled habitat suitability for each species using boosted regression trees and converted these results into resistance layers for the connectivity analyses. We compared models for each species at multistate regional and local extents using directional and omnidirectional circuit theory approaches. We then used the results from each modeling combination as conservation goals for three different SCPs to determine how connectivity modeling decisions may influence geographic conservation decisions.ResultsThere was substantial positive spatial correlation between the three connectivity models of each species, and there appeared to be general agreement among mammals as to most important primary corridors. Across all species, the greatest agreement was between the omnidirectional and local directional models as compared with the regional directional plan, which highlighted a unique corridor. The omnidirectional conservation plan required the least amount of planning units to achieve its conservation goals, followed by the local and then regional directional plans that required over 200 km2 more land area to be conserved.DiscussionOur results indicate that overall variations in connectivity modeling decisions may have only a moderate impact on the identification of important movement corridors for conservation at the local scale. Practitioners should base modeling decisions on the ecology of the study region, conservation question, and available computing resource.

Ecological connectivity across landscapes is vital for the maintenance of biodiversity and the processes that enable life on earth. Despite this, environmental planning decisions are usually made at the scale of individual projects, failing to account for landscape-scale impacts. Incorporating habitat connectivity analysis in Environmental Impact Assessments (EIAs) could provide an opportunity to address this gap. We present a novel approach to model habitat connectivity in an EIA undertaken for the Heathrow Third Runway Expansion Project, a proposed development in south-east England. Drawing on field data, remote sensing, and species-specific literature reviews, a circuit theory approach was used to assess functional connectivity across the project landscape for grass snakes Natrix helvetica and soprano pipistrelles Pipistrellus pygmaeus. Results indicated key areas for species movement and potential 'pinch-points' vulnerable to development impacts. We discuss lessons learnt, potential applications to inform impact assessment, mitigation design, and biodiversity net gain approaches, and further work required to mainstream connectivity analyses in EIA and decision-making. [ABSTRACT FROM AUTHOR]

Context: Agricultural land-use conversion has fragmented prairie wetland habitats in the Prairie Pothole Region (PPR), an area with one of the most wetland dense regions in the world. This fragmentation can lead to negative consequences for wetland obligate organisms, heightening risk of local extinction and reducing evolutionary potential for populations to adapt to changing environments. Objectives: This study models biotic connectivity of prairie-pothole wetlands using landscape genetic analyses of the northern leopard frog (Rana pipiens) to (1) identify population structure and (2) determine landscape factors driving genetic differentiation and possibly leading to population fragmentation. Methods: Frogs from 22 sites in the James River and Lake Oahe river basins in North Dakota were genotyped using Best-RAD sequencing at 2868 bi-allelic single nucleotide polymorphisms (SNPs). Population structure was assessed using STRUCTURE, DAPC, and fineSTRUCTURE. Circuitscape was used to model resistance values for ten landscape variables that could affect habitat connectivity. Results: STRUCTURE results suggested a panmictic population, but other more sensitive clustering methods identified six spatially organized clusters. Circuit theory-based landscape resistance analysis suggested land use, including cultivated crop agriculture, and topography were the primary influences on genetic differentiation. Conclusion: While the R. pipiens populations appear to have high gene flow, we found a difference in the patterns of connectivity between the eastern portion of our study area which was dominated by cultivated crop agriculture, versus the western portion where topographic roughness played a greater role. This information can help identify amphibian dispersal corridors and prioritize lands for conservation or restoration. [ABSTRACT FROM AUTHOR]

• Given the wide application of connectivity modelling tools in applied conservation planning, it is crucial to broadly evaluate how these models perform across resistance, movement, and population structure conditions in predicting genetic diversity patterns. • Our goal was to investigate how the predictions of three connectivity models were related to spatial patterns of genetic diversity complex landscapes, considering factors such as population structure, resistance, genetic drift, genetic disequilibrium, and organism movement abilities. • We used CDPOP, an individual-based, spatially explicit population and genetic simulation model, to simulate genetic diversity across these resistance surfaces. We then simulated landscape connectivity with several popular connectivity methods, including resistant kernels, Circuitscape, and Pathwalker, and evaluated how well they were able to predict spatial patterns of genetic diversity. • Resistant kernel outperformed other connectivity methods in predicting landscape patterns of genetic diversity. The strongest relationships occurred when the population process has created spatial structure but has not yet led to significant genetic diversity loss due to drift. • Our results confirm the strong relationship between genetic diversity and population connectivity, and suggest that computationally efficient incidence function algorithms, such as resistant kernel methods, are well suited to predicting functional connectivity. There have been few evaluations of how well different connectivity modelling methods are able to predict the spatial genetic structure and genetic diversity of populations residing in complex landscapes. Given the wide application of connectivity modelling tools in applied conservation planning, it is crucial to broadly evaluate how these models perform across resistance, movement, and population structure conditions in predicting genetic diversity patterns. Such evaluations are critical to provide rigorous, biologically based guidance for conservation and management applications. Our goal was to investigate how the predictions of three connectivity models were related to spatial patterns of genetic diversity complex landscapes, considering factors such as population structure, resistance, genetic drift, genetic disequilibrium, and organism movement abilities. We evaluated the performance of several connectivity methods across seven a priori landscape resistance surfaces to provide a broad assessment of their performance. We used CDPOP, an individual-based, spatially explicit population and genetic simulation model, to simulate genetic diversity across these resistance surfaces. This provided a pool of genetic diversity patterns that were the response factor in our simulation experiment. We then simulated landscape connectivity with several popular connectivity methods, including resistant kernels, Circuitscape, and Pathwalker, and evaluated how well they were able to predict spatial patterns of genetic diversity. Resistant kernel outperformed other connectivity methods in predicting landscape patterns of genetic diversity. The strongest relationships occurred when the population process has created spatial structure but has not yet led to significant genetic diversity loss due to drift. The time lag disequilibrium was relatively short. Long simulation times resulted in severe reduction in prediction ability due to drift. Resistant kernel predictions were much more strongly related to spatial patterns of genetic diversity than were predictions produced by Circuitscape and Pathwalker, across a large combination of population structures. Strong relationships exist between functional connectivity and genetic diversity, with clearer and stronger associations seen in spatial patterns of allelic richness compared to heterozygosity or spatial effective population size. Our results confirm the strong relationship between genetic diversity and population connectivity, and suggest that computationally efficient incidence function algorithms, such as resistant kernel methods, are well suited to predicting functional connectivity. [Display omitted] [ABSTRACT FROM AUTHOR]

Preserving the genetic diversity of endangered species is fundamental to their conservation and requires an understanding of genetic structure. In turn, identification of landscape features that impede gene flow can facilitate management to mitigate such obstacles and help with identifying isolated populations. We conducted a landscape genetic study of the endangered salt marsh harvest mouse (Reithrodontomys raviventris), a species endemic to the coastal marshes of the San Francisco Estuary of California. We collected and genotyped > 500 samples from across the marshes of Suisun Bay which contain the largest remaining tracts of habitat for the species. Cluster analyses and a population tree identified three geographically discrete populations. Next, we conducted landscape genetic analyses at two scales (the entire study area and across the Northern Marshes) where we tested 65 univariate models of landscape features and used the best supported to test multivariable analyses. Our analysis of the entire study area indicated that open water and elevation (> 2 m) constrained gene flow. Analysis of the Northern Marshes, where low elevation marsh habitat is more continuous, indicated that geographic distance was the only significant predictor of genetic distance at this scale. The identification of a large, connected population across Northern Marshes achieves a number of recovery targets for this stronghold of the species. The identification of landscape features that act as barriers to dispersal enables the identification of isolated and vulnerable populations more broadly across the species range, thus aiding conservation prioritization. [ABSTRACT FROM AUTHOR]

Protecting or restoring habitat connectivity in landscapes undergoing rapid environmental change requires multiple conservation and restoration strategies. These strategies have different risk profiles, costs, and require various types of technical expertise to conduct. This diversity in landscape context and strategic approach requires more nuance and flexibility than traditional connectivity conservation plans have supported. We present a novel, spatially‐explicit framework for developing connectivity conservation priorities and strategies based on Omniscape, an adaptation of Circuitscape, a common tool for mapping habitat connectivity. Using California (USA) as a case study, we mapped structural connectivity and developed a classification of connectivity conservation and restoration categories across the gradient of land use intensities, as well as by land ownership. The most constrained areas with highly concentrated flow (movement potential) make up 3% of the state and occur primarily on private lands. Conversely, intact areas with diffuse flow that indicate multiple connectivity options cover 55% of the state, including the majority of the desert and mountain ecoregions. This "strategy mapping" approach can be used to identify priority areas for conservation investment and suites of potential implementation mechanisms and partners, which in turn may improve the efficiency and effectiveness of connectivity conservation in this era of global change. [ABSTRACT FROM AUTHOR]

Context: Regional conservation efforts should incorporate fine scale landscape genetic and habitat suitability data for management decisions. This information permits conservation measures to be tailored to a specific landscape. Objectives: We investigated the landscape determinants of gene flow and habitat suitability for the state-threatened Blanding's turtle (Emydoidea blandingii) in northeastern New York (NNY). We applied the results from each to examine their complementary contributions to local connectivity and genetic structuring. Methods: We conducted population and individual-based genetic analyses with microsatellite data to evaluate genetic structuring and landscape genetics in NNY. We coupled these genetic analyses with species distribution modeling (SDM) to estimate the extent of suitable habitat across this important region for species persistence in the state. Results: Gene flow was strongly associated with open water and cultivated land, indicating the role open water channels play in connecting neighboring activity centers, and the propensity of females to select cultivated land to nest. Species distribution models based on Landsat-derived vegetation indices and percentage of scrub-shrub wetlands accurately identified Blanding's turtle habitat. Connectivity estimates from our NNY focal area using landscape genetic and SDM resistance surfaces showed potential movement constraints between the two genetic clusters. Conclusions: Land cover better explained genetic distance data than geographic distance for Blanding's turtles in our focal area. Accurate SDMs were developed for our focal area with a small number of occurrences (< 50). Using both gene flow and habitat-informed resistance surfaces revealed localized connectivity constraints associated with each, permitting more comprehensive landscape planning. [ABSTRACT FROM AUTHOR]

The sagebrush biome within the western United States has been reshaped by disturbances, management, and changing environmental conditions. As a result, sagebrush cover and configuration have varied over space and time, influencing processes and species that rely on contiguous, connected sagebrush. Previous studies have documented changes in sagebrush cover, but we know little about how the connectivity of sagebrush has changed over time and across the sagebrush biome. We investigated temporal connectivity patterns for sagebrush using a time series (1985–2020) of fractional sagebrush cover and used an omnidirectional circuit algorithm to assess the density of connections among areas with abundant sagebrush. By comparing connectivity patterns over time, we found that most of the biome experienced moderate change; the amount and type of change varied spatially, indicating that areas differ in the trend direction and magnitude of change. Two different types of designated areas of conservation and management interest had relatively high proportions of stable, high-connectivity patterns over time and stable connectivity trends on average. These results provide ecological information on sagebrush connectivity persistence across spatial and temporal scales that can support targeted actions to address changing structural connectivity and to maintain functioning, connected ecosystems.

As both plant and animal species shift their ranges in response to a changing climate, maintaining connectivity between present habitat and suitable habitat in the future will become increasingly important to ensure lasting protection for biodiversity. Because the temporal period commensurate with planning for mid‐century change is multi‐generational for most species, connectivity designed to facilitate climate adaptation requires pathways with 'stepping‐stones' between current and future habitat. These areas should have habitats suitable not only for dispersal, but for all aspects of species lifecycles. We integrated present‐day land use, topographic diversity, and projections of shifting climate regimes into a single connectivity modeling approach to identify pathways for mid‐century shifts in species ranges. Using Omniscape we identified climate linkages, or areas important for climate change‐driven movement, as the areas with more current flow than would be expected in the absence of climate considerations. This approach identified connectivity potential between natural lands in the present climate and natural lands with future analogous climate following topo‐climatically diverse routes. We then translated the model output into a strategic framework to improve interpretation and to facilitate a more direct connection with conservation action. Across modified landscapes, pathways important to climate‐driven movement were highly coincident with the last remaining present‐day linkages, reinforcing their importance. Across unfragmented lands, the presence of climate‐adapted pathways helped inform the prioritization of conservation actions in areas where multiple connectivity options still exist. Many climate linkages follow major watercourses along elevational gradients, highlighting the importance of protecting or managing for these natural linear pathways that provide movement routes for climate adaptation. By integrating enduring landscape features with climate projections and present‐day land uses, our approach reveals "no‐regrets" pathways to plan for a connected landscape in an uncertain future. [ABSTRACT FROM AUTHOR]

Terrestrial carnivores are among the most imperiled species worldwide, yet some species are resilient and are recovering in human-dominated landscapes after decades or centuries of absence. Bobcat (Lynx rufus) populations were extirpated from much of Midwestern US in the mid-1800’s, and are currently expanding and recolonizing their former range. In this study, we investigated multi-scale habitat selection for Ohio’s expanding bobcat population, and examined habitat connectivity in order to evaluate the conduits for dispersal statewide. We used citizen observations collected between 1978 and 2019 and logistic regression to evaluate population-level habitat selection, and GPS telemetry data for 20 individuals collected between 2012 and 2014 and a distribution-weighted exponential Resource Selection Function to evaluate individual-level habitat selection within home ranges. At the population level, bobcats selected for higher amounts of forest and pasture (at a 50 km2 scale) and herbaceous vegetation (at 15–50 50 km2 scales), thus overall heterogeneous forested habitat. At individual (home range) level, bobcats selected for forested habitats with low road density and farther away from high traffic roads; they also showed weak selection for open habitat at the home range level. Male home ranges were significantly greater than female home ranges. Lastly, we used the population-level spatial outputs (i.e. habitat suitability map) to parameterize habitat connectivity models using circuit theory in the program Circuitscape. We tested three relationships between habitat suitability and resistance to movement and used a subset of data on potential dispersing individuals to evaluate which relationship performed best. All three relationships performed almost equally well, and we calculated a weighted averaged connectivity map as our final map. Habitat was highly permeable to movements between core areas of two genetically distinct subpopulations located in southeastern Ohio. We also identified potential dispersal corridors from the core areas to other regions of Ohio dominated by agriculture and suburban development via forested riparian corridors. Overall, our analysis offers new information on habitat selection and connectivity in a rebounding felid population and offers important ecological information for wildlife management strategies. We recommend that the suitability and connectivity models should be periodically updated until the population reaches an equilibrium, and be integrated with data from neighboring states for a comprehensive assessment of a conservation success story.

Aim: The ongoing global change makes landscape planning and management of ecological corridors crucial to preserve biodiversity. We propose a workflow optimizing the use of different data sources to convert ecological niche models (ENMs) into landscape‐focused species distribution models (SDMs), using these latter to compute ecological corridors. We infer corridors connecting present occurrence localities to future climatic refugia as well as to localities where extinct populations occurred. Also, a continuous connectivity change index is proposed to assess current–future differences. Finally, we discuss possible applications of our workflow to conservation, assessing the capability of established protected areas to preserve ecological corridors. Location: Europe. Methods: As case study to illustrate our framework, we use a database comprising occurrence localities of Vipera ursinii, one of the most endangered European reptiles. We obtain weighted SDMs for each of the four V. ursinii subspecies by coupling climate‐based ENMs with standardized occurrence frequencies along land use and altitude gradients through weighted averaging in GIS. We calculate current and future landscape connectivity for each subspecies based on the corresponding weighted SDM. We compare predictive performance of "traditional" ENMs, including climate, land use and topography as predictors and weighted SDMs. Results: Weighted SDMs outperform ENMs, according to Boyce index. SDMs are used to infer connectivity, predicted to decrease in all future scenarios for V. ursinii, and assess where connections may favour movements of individuals to, for example, future suitable areas. Generally, protected areas are predicted to cover low‐connectivity territories. Main conclusions: The proposed "couple‐and‐weigh" approach could represent a helpful tool to investigate biogeography, conservation and landscape planning topics, as it permits to capitalize on occurrence records and accessible environmental predictors by narrowing the target species' potential distribution, estimated within "traditional" ENMs, to the realized one through post‐modelling GIS analyses, which in turn improves estimation of friction maps used to infer connectivity. [ABSTRACT FROM AUTHOR]

Biofuel production in Sub-Saharan Africa is an important part of local low-income countries. Among many plant species, Jatropha curcas gained popularity in this area, as it can be grown even where crops of agricultural interest cannot. A natural African pest of J. curcas is the Aphthona cookei species group, for which future climatic suitability is predicted to favor areas of co-occurrence. In this research, we identify the possible climatic corridors in which the colonization of J. curcas crops may occur through a circuit theory-based landscape connectivity software at a country scale. Additionally, we use the standardized connectivity change index to predict possible variations in future scenarios. Starting from ecological niche models calibrated on current and 2050 conditions (two different RCP scenarios), we found several countries currently showing high connectivity. Ghana, Zambia and Ivory Coast host both high connectivity and a high number of J. curcas cultivations, which is also predicted to increase in the future. On the other side, Burundi and Rwanda reported a future increase of connectivity, possibly acting as "connectivity bridges" among neighboring countries. Considering the economic relevance of the topic analyzed, our spatially explicit predictions can support stakeholders and policymakers at a country scale in informed territorial management. [ABSTRACT FROM AUTHOR]

Terrestrial carnivores are among the most imperiled species worldwide, yet some species are resilient and are recovering in human-dominated landscapes after decades or centuries of absence. Bobcat (Lynx rufus) populations were extirpated from much of Midwestern US in the mid-1800’s, and are currently expanding and recolonizing their former range. In this study, we investigated multi-scale habitat selection for Ohio’s expanding bobcat population, and examined habitat connectivity in order to evaluate the conduits for dispersal statewide. We used citizen observations collected between 1978 and 2019 and logistic regression to evaluate populationlevel habitat selection, and GPS telemetry data for 20 individuals collected between 2012 and 2014 and a distribution-weighted exponential Resource Selection Function to evaluate individual-level habitat selection within home ranges. At the population level, bobcats selected for higher amounts of forest and pasture (at a 50 km2 scale) and herbaceous vegetation (at 15–50 50 km2 scales), thus overall heterogeneous forested habitat. At individual (home range) level, bobcats selected for forested habitats with low road density and farther away from high traffic roads; they also showed weak selection for open habitat at the home range level. Male home ranges were significantly greater than female home ranges. Lastly, we used the population-level spatial outputs (i.e. habitat suitability map) to parameterize habitat connectivity models using circuit theory in the program Circuitscape. We tested three relationships between habitat suitability and resistance to movement and used a subset of data on potential dispersing individuals to evaluate which relationship performed best. All three relationships performed almost equally well, and we calculated a weighted averaged connectivity map as our final map. Habitat was highly permeable to movements between core areas of two genetically distinct subpopulations located in southeastern Ohio. We also identified potential dispersal corridors from the core areas to other regions of Ohio dominated by agriculture and suburban development via forested riparian corridors. Overall, our analysis offers new information on habitat selection and connectivity in a rebounding felid population and offers important ecological information for wildlife management strategies. We recommend that the suitability and connectivity models should be periodically updated until the population reaches an equilibrium, and be integrated with data from neighboring states for a comprehensive assessment of a conservation success story. [ABSTRACT FROM AUTHOR]

Context: Maintaining landscape connectivity for large felids by preserving and restoring corridors between core habitats is crucial to their long-term conservation. Tiger, leopard, and clouded leopard populations occur in isolated habitat patches across the Dawna-Tanintharyi Landscape (DTL) of Kawthoolei (all Karen National Union administrative areas in Myanmar) and Thailand. Objectives: We analyzed connectivity among 18 habitat patches in this transboundary region based on large felid presence and expert opinion of large felid dispersal requirements. Methods: Least-cost corridor and circuit theory analyses were used to identify corridors, determine corridor quality and their relative importance to connectivity in the landscape, and pinpoint bottlenecks to movement. Results: Forty-eight corridors were identified. Lower resistances to dispersal were in forested montane areas. High-quality corridors remained in the northern DTL and south of Tanintharyi Nature Reserve in Kawthoolei based on cost-weighted distance to least-cost path ratio. Pairwise current pinch point analyses revealed a possible landscape level bottleneck to movement north of Thailand's Western Forest Complex. Area corrected centrality scores indicated smaller habitat patches disproportionately contributed to landscape connectivity. Conclusions: The DTL may retain connectivity across the landscape if conservation actions are taken to protect integral habitats and corridors. Conservation efforts that expand the protected area network in Kawthoolei, either by increasing the size of current protected area habitats or by demarcating new protected areas in regions with confirmed felid presence, will aid DTL connectivity. The DTL should be managed to preserve connectivity on both sides of the border, entailing international governmental, indigenous community, and non-governmental collaboration. [ABSTRACT FROM AUTHOR]

Context: Conserving or restoring connectivity is a common objective of landscape-scale conservation initiatives. However, precise species occurrence or movement data to inform or validate spatial models are often lacking. Objectives: Our objectives were to (1) produce the first approximation of country-wide connectivity for Andean bears (Tremarctos ornatus) in Colombia and (2) demonstrate a novel approach for model validation which uses publicly available web and social media records of a flagship species. Methods: We used general knowledge about Andean bear habitat associations and indices of ecological integrity to construct a resistance surface across the Colombian Andes. We used this resistance surface to model omnidirectional connectivity using circuit theory. We validated our model with coarse location data acquired from local news stories and social media posts. Results: Our model was most sensitive to changes in the resistance values of agricultural landcover and the mid-elevational zone, but uncertainty analysis demonstrated these changes had little impact on our conclusions regarding the municipalities most conducive to Andean bear movement. Just over one-third of those areas most conducive to Andean bear movement were within protected areas, while 8% coincided with agricultural landcover. Conclusions: We constructed a model of connectivity that did not rely on independent, empirically derived location data. Our model is coarse (1 km resolution) but can still provide useful information to practitioners in Colombia who are working with scarce ecological data. More information about how Andean bears move through agricultural landscapes would help improve our understanding of connectivity for this species in Colombia. [ABSTRACT FROM AUTHOR]

Starting in 2010, rapid fire salamander (Salamandra salamandra) population declines in northwestern Europe heralded the emergence of Batrachochytrium salamandrivorans (Bsal), a salamander‐pathogenic chytrid fungus. Bsal poses an imminent threat to global salamander diversity owing to its wide host range, high pathogenicity, and long‐term persistence in ecosystems. While there is a pressing need to develop further research and conservation actions, data limitations inherent to recent pathogen emergence obscure necessary insights into Bsal disease ecology. Here, we use a hierarchical modeling framework to describe Bsal landscape epidemiology of outbreak sites in light of these methodological challenges. Using model selection and machine learning, we find that Bsal presence is associated with humid and relatively cool, stable climates. Outbreaks are generally located in areas characterized by low landscape heterogeneity and low steepness of slope. We further find an association between Bsal presence and high trail density, suggesting that human‐mediated spread may increase risk for spillover between populations. We then use distribution modeling to show that favorable conditions occur in lowlands influenced by the North Sea, where increased survey effort is needed to determine how Bsal impacts local newt populations, but also in hill‐ and mountain ranges in northeastern France and the lower half of Germany. Finally, connectivity analyses suggest that these hill‐ and mountain ranges may act as stepping stones for further spread southward. Our results provide initial insight into regional environmental conditions underlying Bsal epizootics, present updated invasibility predictions for northwestern Europe, and lead us to discuss a wide variety of potential survey and research actions needed to advance future conservation and mitigation efforts. [ABSTRACT FROM AUTHOR]

Ecosystem functioning depends on multiple successful interactions, many supported by individual movements. The degree to which the landscape allows these interactions to take place has been referred to as 'effective connectivity' (EC). Many of the cumulative impacts of anthropogenic activities on ecosystem functioning arise from changes in EC. Therefore, a coherent framework to quantify EC is urgently needed. Recent theoretical developments propose that studying EC requires the simultaneous consideration of spatial, environmental and species intrinsic characteristics (SEI framework). In this paper we further expand the SEI framework by integrating advances in geographic information science, ecological niche modelling, movement ecology, island biogeography and network sciences to develop a comprehensive three‐step methodological approach for quantifying EC. First, using niche modelling and movement ecology, we quantify the species movement probabilities with respect to local environmental conditions. Second, we quantify ecological distances between non‐adjacent locations by integrating species movement responses to the local environment with the spatial configuration of the landscape using the expected cost obtained from the randomized shortest paths (RSP) framework. This expected cost generalizes the two most frequently used ecological distance metrics, i.e. least‐cost distance and resistance distance. Moreover the 'absorbing random walk' properties of RSP allow the integration of new developments in connectivity research, i.e. spatial absorbing Markov chains, to account for movement‐related mortality. Third, drawing from island biogeography and metapopulation ecology, we scale ecological distances by relevant species‐ and area‐specific parameters to estimate EC for the ecological process of interest, e.g. migration, dispersal or gene flow. The integrative and highly interdisciplinary approach we propose can lead to increasingly more realistic measures of EC at different organizational levels. Moreover efficient computation allows its application to large‐scale high‐resolution landscapes for theoretical studies, conservation planning and sustainable management of real landscapes. [ABSTRACT FROM AUTHOR]

Context: Maintaining and improving ecological connectivity is an important component of wildlife conservation. Omnidirectional circuit theory algorithms model the flow of electric current across a resistance grid from all directions, making them particularly useful for modeling connectivity of multiple or widespread species, or when source and destination sites are not specified, such as in the case of continuously distributed species. Objectives: We compared three published omnidirectional connectivity methods—the point-based method, the wall-to-wall method, and the Omniscape method. Methods: We compared the three omnidirectional connectivity methods using ten simulated resistance grids, representing commonly encountered landscape features. We then used three Canada lynx (Lynx canadensis) snow-track datasets from Ontario, Canada to validate the ability of each method to detect landscape use. Results: Current density maps generated by all three methods were highly correlated for most simulated landscapes, with the exception of uniform resistance grids. In uniform grids, without landscape features to guide current, each method revealed unique node-placement biases. All three methods produced similar connectivity maps for lynx, showing higher current at lynx presence locations compared to absence locations. The main differences between methods were not in their output, but in their implementation and use of computational resources. Conclusions: Our findings suggest that all three currently published omnidirectional connectivity models produce similar current density maps and can accurately map landscape connectivity. We provide guidelines for selecting a method based on factors such as computational resources, study area, and project goals. [ABSTRACT FROM AUTHOR]

Background Conservation practitioners are often interested in developing land use plans that increase landscape connectivity, which is defined as the degree to which the landscape facilitates or impedes movement among resource patches. Landscape connectivity is often estimated with a cost surface that indicates the varying costs experienced by an organism in moving across a landscape. True, or absolute costs are rarely known however, and therefore assigning costs to different landscape elements is often a challenge in creating cost surface maps. As such, we consider it important to understand the sensitivity of connectivity estimates to uncertainty in cost estimates. Methods We used simulated landscapes to test the sensitivity of current density estimates from circuit theory to varying relative cost values, fragmentation, and number of cost classes (i.e., thematic resolution). Current density is proportional to the probability of use during a random walk. Using Circuitscape software, we simulated electrical current between pairs of nodes to create current density maps. We then measured the correlation of the current density values across scenarios. Results In general, we found that cost values were highly correlated across scenarios with different cost weights (mean correlation ranged from 0.87 to 0.92). Changing the spatial configuration of landscape elements by varying the degree of fragmentation reduced correlation in current density across maps. We also found that correlations were more variable when the range of cost values in a map was high. Discussion The low sensitivity of current density estimates to relative cost weights suggests that the measure may be reliable for land use applications even when there is uncertainty about absolute cost values, provided that the user has the costs correctly ranked. This finding should facilitate the use of cost surfaces by conservation practitioners interested in estimating connectivity and planning linkages and corridors.

Although a landscape is a single environmental system, human systems of governance at the landscape scale are often fragmented across jurisdictions and diverse stakeholders, impeding coordinated planning to maintain ecological connectivity. We sought solutions to overcome this challenge for wildlife corridor conservation in a rapidly developing, multifunctional landscape in one of North America’s most endangered ecoregions. Circuitscape modelling was used to identify key wildlife movement corridors through our study area. We then describe how the results of this modelling have informed a collaborative multi-stakeholder process leading to shared conservation objectives across scales of governance and illustrate its success with our case study. We conclude that achieving landscape-scale conservation objectives requires ongoing and coordinated collaboration facilitated by a dedicated group of individuals and informed by science.EDITED BY Davide Geneletti

Wetlands, like East Kolkata Wetlands (EKW) in present study, are vulnerable to habitat alteration and other anthropogenic threats affecting avifauna. Consequently, prioritizing avifaunal conservation based on suitable habitats and their connectivity is essential. White-breasted waterhen (WBW, Amaurornis phoenicurus) and bronze-winged jacana (BWJ, Metopidius indicus) are two resident birds of EKW. We used MaxEnt for habitat suitability maps; assessed habitat connectivity in Circuitscape and mapped top 10% conservation priority areas in Zonation softwares. Both species had similar niche breadth and high niche overlap. The high suitability and moderate suitability areas for WBW was 0.02 km2 and 13.06 km2 respectively, while high suitability area for BWJ was absent and moderate suitability areas covered 6.73 km2. But, these suitable habitats mostly showed low and least connectivity. Finally, we found banks and dikes of wetlands, small vegetations therein and cropfields are important land-use classes in their projected suitable habitats and also in top 10% conservation priority areas. Use of chemical fertilizers and pesticides in the cropfields and clearing of bushes on the banks and dikes, as well as, the floating and emergent macrophytes in waterbodies with intensive commercial pisciculture are recorded as potential anthropogenic threats. Also ~80% of this top 10% conservation priority area are prone to moderate to high habitat transformation. Protection of remaining suitable habitats and their connectivity identified in this study, as well as, restoration of degraded habitats, and reduction of threats will ensure the conservation of WBW and BWJ in EKW and also in other wetlands in human-dominated landscapes. [ABSTRACT FROM AUTHOR]

Migration is common worldwide as species access spatiotemporally varying resources and avoid predators and parasites. However, long‐distance migrations are increasingly imperiled due to development and habitat fragmentation. Improved understanding of migratory behavior has implications for conservation and management of migratory species, allowing identification and protection of seasonal ranges and migration corridors. We present a technique that applies circuit theory to predict future effects of development by analyzing season‐specific resistance to movement from anthropogenic and natural environmental features across an entire migratory path. We demonstrate the utility of our approach by examining potential effects of a proposed road system on barren ground caribou (Rangifer tarandus granti) and subsistence hunters in northern Alaska. Resource selection functions revealed migratory selection by caribou. We tested five scenarios relating habitat selection to landscape resistance using Circuitscape and GPS telemetry data. To examine the effect of potential roads on connectivity of migrating animals and human hunters, we compared current flow values near communities in the presence of proposed roads. Caribou avoided dense vegetation, rugged terrain, major rivers, and existing roads in both spring and fall. A negative linear relationship between resource selection and landscape resistance was strongly supported for fall migration while spring migration featured a negative logarithmic relationship. Overall patterns of caribou connectivity remained similar in the presence of proposed roads, though reduced current flow was predicted for communities near the center of current migration areas. Such data can inform decisions to allow or disallow projects or to select among alternative development proposals and mitigation measures, though consideration of cumulative effects of development is needed. Our approach is flexible and can easily be adapted to other species, locations and development scenarios to expand understanding of movement behavior and to evaluate proposed developments. Such information is vital to inform policy decisions that balance new development, resource user needs, and preservation of ecosystem function. [ABSTRACT FROM AUTHOR]

Survival of endangered Himalayan red panda is threatened by ever‐growing anthropogenic activities leading to an unprecedented rate of habitat degradation and loss. However, limited studies have been conducted in the context of the spatial distribution of habitats and habitat connectivity for the species in the landscape of Sakteng Wildlife Sanctuary (SWS). Lack of such information remains a challenge while implementing effective and holistic conservation initiatives. Therefore, this study identifies the distribution of potential habitats and their connectivity using maxent and linkage mapper, respectively. Precipitation‐related predictor variables exhibited a significant influence on the prediction of habitat distribution. The model predicted 27.7% of the SWS as a potential habitat (fundamental niche). More than 75% of the predicted habitats fall outside the existing core zones where anthropogenic disturbance is relatively high, indicating the need to reassess existing management options. In SWS, 15 core habitats (CH) are predicted which are connected by a least‐cost corridor (length µ = 2.91 km) with several pinch points in it. Centrally located CH5 and CH11 are identified as the most important habitat in maintaining overall connectivity within SWS. However, CH located in the peripheries could be equally important in facilitating the transboundary movement of the species. Overall, SWS can play a critical role as a connecting link between the larger landscape of Bhutan and the adjacent Indian state of Arunachal Pradesh in the conservation of Himalayan red panda that exhibits narrow dispersal with special habitat needs. Based on our findings, we recommend initiating GPS/satellite telemetry of the species to enable SWS to understand the precise interaction of Himalayan red panda to widespread herder communities, livestock, and free‐roaming dogs dwelling in the same landscape. It will also help to evaluate the functionality of the predicted habitats, linkages, and feasibility of transboundary conservation initiatives. [ABSTRACT FROM AUTHOR]

Understanding how landscape features affect gene flow has implications for numerous fields including molecular and evolutionary ecology. Despite this, modelling landscape resistance surfaces has remained a significant challenge. The R package resistancega was developed to provide a framework for optimizing landscape resistance surfaces. In this study, we assessed ResistanceGA's ability to recover the true resistance surface under a variety of scenarios, including when the underlying surface: (a) had different levels of spatial autocorrelation and (b) was transformed into a resistance surface using different functional transformations. These scenarios were evaluated with regard to varying sample size and varying levels of variance in the measure of genetic distance. We also assessed the ability of ResistanceGA to identify the true resistance surface among alternative correlated surfaces. In univariate simulations, correlation between the true and optimized resistance surfaces remained high with increased variance in genetic distance, but only when sample size was moderate to high (≥50). Model selection error was also driven by sample size with low type I error when simulations had moderate to high sample sizes, even with moderate to high variance in genetic distance and correlated alternative surfaces. ResistanceGA also performed well in multivariate simulationsbut had more difficulty identifying the true data generating surfaces when genetic data were simulated using an agent‐based approach (especially with individual‐based genetic data). Overall, our simulations highlight the ability of ResistanceGA to accurately optimize resistance surfaces but also underscore challenges in optimizing landscape resistance surfaces, especially with highly stochastic individual‐based data. [ABSTRACT FROM AUTHOR]

Aim: Central part of Iran harbours populations of wild ungulates that are threatened or extinct over large parts of the region, and are likely to be impacted by climate change. In this study, we predicted the impact of climate change on the distribution of three vulnerable ungulates in central Iran. We then evaluated future suitability of corridors connecting the protected areas for movement of the ungulates in response to climate change. Location: Central Iran. Methods: Impact of climate change on distribution of goitered gazelle (Gazella subgutturosa), wild sheep (Ovis spp) and wild goat (Capra aegagrus) was predicted adapting an ensemble modelling approach and under the RCP 8.5 emission scenario. We then used CIRCUITSCAPE software with current and future distribution maps to identify corridors for movement of the three ungulates, and evaluate likely changes in their suitability under climate change. Results: Our results revealed that climate change might result in loss of 55%, 69% and 76% of suitable habitats for goitered gazelle, wild sheep and wild goat by 2070, respectively. These losses also resulted in some protected areas to become unsuitable for the ungulates. However, we identified key protected areas with the potential for future protection of these ungulates. For the three species, we also identified corridors which would persist into the future, allowing the impacted populations to move in response to climate change. Main conclusions: Conservation of ungulate populations in Iran mainly depends on the protected areas. To maintain the role of the protected areas in conserving these mammals under climate change, we recommend the incorporation of their potential future distribution into conservation plans, increasing protection status of the key protected areas, and maintain critical corridors. In this regard, combining results of distribution and connectivity models provides useful information for effective management of these ungulates in the future. [ABSTRACT FROM AUTHOR]