Search

Climate and land use change are among the main drivers affecting virtually all species on earth. There were extensive studies projecting impacts of climate and land use changes on habitat loss and fragmentation but few on connectivity loss, and those that investigated connectivity did not disentangle the combined effects between climate change and land use change. This study uses the Himalayan brown bear (Ursus arctos isabellinus) as a case study to illustrate an approach for disentangling the effects of climate change and human land use on population connectivity in the future. First, we assessed the current spatial pattern of population connectivity by simulating cumulative resistant kernels and factorial least‐cost paths with empirical field data. Then, we simulated the changes in connectivity due to future climate change under alternative emission scenarios (RCP 2.6 and RCP 8.5) in mid (2041–2060) and late (2061–2080) 21st century, which served as baseline scenarios of future connectivity. Finally, we estimated the changes in future connectivity due to human land use changes by adding a low and a high human land use activity scenario to the baseline climate change scenarios in our simulations. Alarmingly, all high emission scenarios, with or without human land use change, were projected to result in >99% reduction in current core areas of connectivity by the end of 21st century at 50th percentile threshold or above. This study demonstrates a spatially explicit scenario modeling approach to examine the interplay between future climate change and human land use on species connectivity. Our results suggest that regional land use regulations may be insufficient to conserve connectivity for HBB if nothing is done to reduce climate change at a global scale. [ABSTRACT FROM AUTHOR]

Multiple studies have used species distribution models to identify human–wildlife conflict drivers. An important application of these models is spatial conflict resolution by accounting for habitat suitability and corridors. We used distribution and connectivity models to identify habitats and corridors for brown bear Ursus arctos in southwestern Iran with high risk of bear damages, and evaluated the effects of landscape composition and configuration on the predicted conflict hotspots. We used 154 locations of bear damage incidents along with a suit of predictors to develop risk models. To prepare predictive variables, we used brown bear occurrence data and a number of covariates to develop a suitability model. We then converted the suitability map into a resistance surface and used a connectivity model to predict corridors. Finally, the bear damages risk map, habitats and corridors were overlaid to prioritize conflict hotspots, corridors and habitats, and conflict‐prone corridors. Proportion of suitable habitats, distance to village, density of forest patches, conservation areas and corridor bottlenecks were the main predictors contributing to bear damages risk. A total of 38.73% of habitats, and 6.24% of corridors across the 124 000‐km2 study area were identified as areas with high risk of bear damages. The risk of bear damage was also spatially associated with forests fragmentation and patchiness of habitat. Our results highlight the importance of landscape configuration and corridors when investigating the spatial patterns of bear damages. Our findings showed how the combination of distribution models and connectivity analysis can guide carnivore conservation planning aiming at reducing the risk of carnivore‐inflicted damages. [ABSTRACT FROM AUTHOR]

Habitat loss and fragmentation are key drivers of biodiversity loss. However, they are usually confounded, making it difficult to separate fragmentation effects from those of habitat loss. In addition, it has been shown that often fragmentation negatively affects biodiversity only below a certain threshold of habitat amount. We investigated the separate and interactive effects of habitat amount and fragmentation on habitat selection of the woodlark at 10 spatial scales. In southern Switzerland this passerine mainly breeds in ground‐vegetated vineyards, which therefore represent the focal habitat type in this study. Additionally, we investigated land cover, topographic and climatic variables at the same 10 scales to obtain a holistic picture of species‐habitat associations. Habitat selection was analyzed at two hierarchical levels: home range selection within the study area and habitat use within home ranges. Home range selection was strongly driven by an interactive effect of habitat amount and fragmentation: woodlarks avoided fragmented areas if habitat amount was below 20% but exhibited a preference for fragmented areas if habitat amount exceeded this threshold. Both habitat amount and fragmentation most strongly affected habitat use at the 100 m scale. We did not find such interactive effects for habitat use within home ranges. At this level, habitat amount at a 50 m scale influenced woodlark presence positively with no significant effects of fragmentation. Furthermore, woodlarks preferred evenly sloped landscape mosaics interspersed with steppes and groves. Two main insights emerge from our study. First, these results highlight the necessity of studying scale explicit and interactive effects of habitat amount and fragmentation when addressing ecological questions, such as habitat selection in birds. Second, we provide management recommendations for farmers: more vineyards should be vegetated and arranged as disjunct patches where their surface covers more than 20% of the landscape but be aggregated where vegetated area is lower. [ABSTRACT FROM AUTHOR]

Landscape connectivity between protected areas is crucial for the conservation of megafauna. But often, corridor identification relies on expert knowledge that is subjective and not spatially synoptic. Landscape analysis allows generalization of expert knowledge when satellite tracking or genetic data are not available. The Nilgiri Biosphere Reserve in southern India supports the largest wild populations of the endangered Asian elephant Elephas maximus. Current understanding of connectivity in this region is based on corridors identified by experts, which are not empirically validated and incongruent with each other. To more rigorously assess population connectivity for the Asian elephant, we evaluated a combination of three resistance layers and three dispersal abilities. The resistance models were based on the combined contributions of land cover, topographical slope, elevation, roads and buildings. A spatially explicit connectivity modeling tool predicted optimal movement corridors as a function of factorial least-cost routes across the resistance maps. A resistant kernel approach produced maps of the expected frequency of elephant movement through each cell to define core areas. We conducted a sensitivity analysis to determine the influence of resistance and dispersal. We selected the resistance surface and dispersal ability that produced the highest correlation with observed elephant densities. We evaluated the optimality of expert corridors by using a path randomization method. Eleven out of 24 expert corridors had connectivity values significantly higher than expected by chance, while only two corridors were spatially congruent between expert teams. Areas with the highest connectivity corresponded well with priority areas identified by conservationists and elephant density predicted by the resistant kernel connectivity model correlated significantly with surveys (Spearman's ρ = 0.85, n = 500, P ≪ 0.001). The results provide the first rigorous, spatially synoptic and empirically validated evaluation of the connectivity of the elephant population across the reserve. [ABSTRACT FROM AUTHOR]

Effective conservation solutions for small and isolated wildlife populations depend on identifying and preserving critical biological corridors and dispersal routes. With a worldwide population of ≤70 individuals, the critically endangered Asiatic cheetah Acinonyx jubatus venaticus persists in several fragmented nuclei in Iran. Connectivity between nuclei is crucial for the survival of this subspecies, but detailed information to guide conservation actions is lacking. We developed a resistance surface that predicted cost of cheetah movement as functions of topographical complexity, human development, surface water and landscape protection level. We predicted alternative models for the landscape connectivity of Asiatic cheetahs, considering the combination of relative landscape resistance and different dispersal ability scenarios. We predicted that core connected habitat patches are concentrated in three sub-regions, and within these sub-regions, populations were predicted to be broken up into two to eight isolated patches, depending on the dispersal ability scenario. Despite the achievements of recent conservation initiatives, long-term survival of the Asiatic cheetah in Iran is threatened by the combination of its small population size and fragmented distribution. We propose that conservation of the Asiatic cheetah urgently requires integrated landscape-level management to reduce mortality risk, protect core areas and corridors, and ultimately establish stepping-stone populations to integrate this fragmented population. [ABSTRACT FROM AUTHOR]