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Context: The accurate estimation of landscape resistance to movement is important for ecological understanding and conservation applications. Rigorous estimation of resistance requires validation and optimization. One approach uses genetic data for the optimization or validation of resistance models. Objectives: We used a genetic dataset of snow leopards from China to evaluate how landscape genetics resistance models varied across genetic distances and spatial scales of analysis. We evaluated whether landscape genetics models were superior to models of resistance derived from habitat suitability or isolation-by-distance. Methods: We regressed genetically optimized, habitat-based, and isolation-by-distance hypotheses against genetic distances using mixed effect models. We explored all subset combinations of genetically optimized variables to find the most supported resistance scenario for each genetic distance. Results: Genetically optimized models always outperformed habitat-based and isolation-by-distance hypotheses. The choice of genetic distances influenced the apparent influence of variables, their spatial scales and their functional response shapes, producing divergent resistance scenarios. Gene flow in snow leopards was largely facilitated by areas of intermediate ruggedness at intermediate elevations corresponding to small-to-large valleys within and between the mountain ranges. Conclusions: This study highlights that landscape genetics models provide superior estimation of functional dispersal than habitat surrogates and suggests that optimization of genetic distance should be included as an optimization routine in landscape genetics, along with variables, scales, effect size and functional response shape. Furthermore, our study provides new insights on the ecological conditions that promote gene flow in snow leopards, which expands ecological knowledge, and we hope will improve conservation planning. [ABSTRACT FROM AUTHOR]

Understanding landscape connectivity and population genetic parameters is imperative for threatened species management. However, such information is lacking for the snow leopard (Panthera uncia). This study sought to explore hierarchical snow leopard gene flow patterns and drivers of genetic structure in Mongolia and China. A total of 97 individuals from across Mongolia and from the north-eastern edge of the Qinghai-Tibetan Plateau in Gansu Province to the middle of Qinghai Province in China were genotyped across 24 microsatellite loci. Distance-based frameworks were used to determine a landscape scenario best explaining observed genetic structure. Spatial and non-spatial methods were used to investigate fine-scale autocorrelation and similarity patterns as well as genetic structure and admixture. A genetic macro-division between populations in China and Mongolia was observed, suggesting that the Gobi Desert is a substantial barrier to gene flow. However, admixture and support for a resistance-based mode of isolation suggests connective routes that could facilitate movement. Populations in Mongolia had greater connectivity, indicative of more continuous habitat. Drivers of genetic structure in China were difficult to discern, and fine-scale sampling is needed. This study elucidates snow leopard landscape connectivity and helps to prioritize conservation areas. Although contact zones may have existed and occasional crossings can occur, establishing corridors to connect these areas should not be a priority. Focus should be placed on maintaining the relatively high connectivity for snow leopard populations within Mongolia and increasing research efforts in China. [ABSTRACT FROM AUTHOR]

Identification of the effect of anthropogenic threats on ecosystem is crucial. We used molecular tools and remote sensing to evaluate the population status of an isolated Asian elephant population in southwestern China in response to changes in habitat suitability between 1989 and 2019. A total of 22 unique genotypes were identified from 117 dung samples collected between March and June 2018 using microsatellite DNA analysis, including 13 males and 9 females. Based on the size of fecal boli, 1 animal was a juvenile, 9 were subadults, and 12 were adults, indicating that recruitment was limited. The effective population size was small (15.3) but there was no signature of a recent population bottleneck. We observed a low genetic diversity (He = 0.46 ± 0.05) and a high level of inbreeding (Fis of 0.43 ± 0.11), suggesting low population viability and high risk of extinction. In total, these elephants lost nearly two thirds (62%) of their habitat in 3 decades. The expansion of agriculture and rubber plantations followed by an increase in human settlements after 1989 increased the isolation of this population. We recommend that resettlement of 800 inhabitants of 2 villages and the abandonment of associated farmland and rubber plantations would make an additional 20 km2 of suitable habitat available. This could allow a population increase of 14 elephants, possibly by translocating individuals from elsewhere in China. Our findings can be applied to the management and conservation of other fragmented populations in China or in other range countries of Asian elephants. [ABSTRACT FROM AUTHOR]

Conservation interventions for threatened species must be based on accurate assessments of the effects of anthropogenic pressures on habitat suitability. We used multiscale multivariable species‐distribution modeling to evaluate habitat suitability for an Asian elephant (Elephas maximus) population in Shangyong Reserve, Yunnan Province, southwestern China. We investigated the scales at which measurements of environmental variables best reflected elephant habitat selection, and examined whether these responses changed over 2 decades (2000–2010 and 2011–2020) in response to 20 environmental variables, including 14 variables reflecting landscape fragmentation, the extent of buildings, and transport infrastructure. Elephant presence was sensitive to the scale of each variable, and the effects differed among variables within and between decades. More than half of the variables influenced elephant presence at coarse scales of 8 or 16 km, including 12 variables reflecting anthropogenic pressures in 2000–2010 and 10 in 2011–2020. Overall, multivariate models with variables at their optimal scales had higher discrimination than models at uniformly fine scales of 1 km or 2 km. The extent of suitable habitat for elephants declined by 24% over 2 decades. Less than half of elephant habitat was located within Shangyong Reserve (49% in 2000–2010, 40% in 2011–2020), indicating the importance of managing suitable habitat beyond reserve boundaries. Roads and buildings reduced the probability of elephant presence, with effects that extended beyond their immediate footprint. We advocate that infrastructure be planned with buffers, ≥8 km wide, between roads or buildings and core elephant habitat. Multiscale multivariable species‐distribution modeling should be employed to ensure that all suitable habitat for the remaining fragmented elephant populations in Yunnan is identified, mapped, and protected. [ABSTRACT FROM AUTHOR]

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi‐scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape‐specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles' overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape‐specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low‐contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi‐scale response of snow leopards to environmental attributes and confirms the role of meta‐replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction. [ABSTRACT FROM AUTHOR]

Understanding the spatial structure of genetic diversity provides insights into a populations' genetic status and enables assessment of its capacity to counteract the effects of genetic drift. Such knowledge is particularly scarce for the snow leopard, a conservation flagship species of Central Asia mountains. Focusing on a snow leopard population in the Qilian mountains of Gansu Province, China, we characterised the spatial genetic patterns by incorporating spatially explicit indices of diversity and multivariate analyses, based on different inertia levels of Principal Component Analysis (PCA). We compared two datasets differing in the number of loci and individuals. We found that genetic patterns were significantly spatially structured and were characterised by a broad geographical division coupled with a fine-scale cline of differentiation. Genetic admixture was detected in two adjoining core areas characterised by higher effective population size and allelic diversity, compared to peripheral localities. The power to detect significant spatial relationships depended primarily on the number of loci, and secondarily on the number of PCA axes. Spatial patterns and indices of diversity highlighted the cryptic structure of snow leopard genetic diversity, likely driven by its ability to disperse over large distances. In combination, the species' low allelic richness and large dispersal ability result in weak genetic differentiation related to major geographical features and isolation by distance. This study illustrates how cryptic genetic patterns can be investigated and analysed at a fine spatial scale, providing insights into the spatially variable isolation effects of both geographic distance and landscape resistance., (© 2021. The Author(s), under exclusive licence to The Genetics Society.)