Multi‐scale habitat modelling identifies spatial conservation priorities for mainland clouded leopards ( Neofelis nebulosa )

Assessing Global Efforts in the Selection of Vertebrates as Umbrella Species for Conservation

The umbrella-species strategy has been proposed as an attainable tool to achieve multi-species and community conservation with limited investment. There have been many umbrella-related studies since the concept's inception; thus, a summary of global study efforts and recommended umbrella species is important for understanding advances in the field and facilitating conservation applications. Here, we collated 213 recommended umbrella species of terrestrial vertebrates from 242 scientific articles published during 1984-2021 and analyzed their geographic patterns, biological features, and conservation statuses to identify global trends in the selection of umbrella species. We found a considerable geographic bias: most studies and, consequently, recommended umbrella species are from the Northern Hemisphere. There is also a strong taxonomic bias, with grouses (order Galliformes) and large carnivores being the most popular umbrella species and amphibians and reptiles being largely overlooked. In addition, wide-ranging and non-threatened species were frequently recommended as umbrella species. Given the observed biases and trends, we caution that appropriate species need to be chosen for each location, and it is important to confirm that popular, wide-ranging species are effective umbrella species. Moreover, amphibians and reptiles should be investigated for their potential as umbrella species. The umbrella-species strategy has many strengths and, if applied appropriately, may be one of the best options in today's conservation research and funding landscape.

Does scale or method matter for conservation? Application of directional and omnidirectional connectivity models in spatial prioritizations

Introduction

The 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.

Methods

We 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.

Results

There 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.

Discussion

Our 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.

Influence of land use changes on landscape connectivity for North China leopard (Panthera pardus japonensis)

North China leopard (Panthera pardus japonensis) is the most widespread subspecies of leopard and one of the rare and endangered species in China. It is currently confined to several isolated natural reserves, and little is known about its habitat network connectivity with land use changes. This study was conducted to assess the impacts of land use changes on landscape connectivity for North China leopard in the Great Taihang Region. Circuit theory‐based connectivity models and least‐cost path analyses were used to delineate pathways suitable for species movement, and evaluate the impacts of land use changes on landscape connectivity. The results revealed that there were 37 least‐cost paths in 1990 and 38 in 2020. The area of forest land increased from 57,142.74 km² to 74,836.64 km², with the percentage increasing from 26.61% to 34.85%. In general, the increase in forest land area promoted the landscape connectivity for North China leopard at broad spatial scales. The improvement of landscape connectivity was not always consistent with the land use changes, and there was a slightly decreasing trend on connectivity in some key movement barrier areas with high intensity of human activities. Improving landscape connectivity at broad spatial scales is as important as protecting the habitats (natural reserves) where the species lives. Our study can serve as an example of exploring the relationships between land use changes and landscape connectivity for species conservation at broad spatial scales with limited movement pattern data. This information is proved to be critical for enhancing landscape connectivity for the conservation concern of North China leopard and planning of natural reserves network.

Structural Connectivity of Asia’s Protected Areas Network: Identifying the Potential of Transboundary Conservation and Cost-Effective Zones

Human activities can degrade landscape connectivity and disrupt ecological flows, jeopardising the functional integrity of processes. This study presents a quantitative assessment of Asia’s protected areas’ (PAs) structural connectivity using landscape metrics, as well as analyses of the Cost-Effective Zones’ (CEZs). Using nine landscape metrics, we assessed connectivity at zonal (country borders and interior), national, regional, and geographical (islands and continent) levels. The results showed that the structural connectivity of Asia’s PAs network measured by a Connectance index was very low (0.08% without country borders and 9.06% for the average country analysis). In general, connectivity was higher within borders (0.36%) than within the countries (0.22%). Islands exhibited significantly higher Area-weighted mean patch area, Proximity index and Largest patch index, suggesting more integrity and connectiveness. When comparing Asian regions, Western Asia presented the lowest values for Percentage of landscape and Proximity index. We found that only 15% of the CEZs in Asia were under PAs designation, and more CEZs are located in the interior, but the majority with the highest priority was in the borders (9%). We advocate that expanding PAs coverage, specifically targeting areas that increase connectivity (e.g., through transboundary PAs), should be a priority to maintain their ecological function.

Diet and prey selection of clouded leopards and tigers in Laos

In Southeast Asia, conservation of ‘Vulnerable’ clouded leopards (Neofelis nebulosa) and ‘Endangered’ tigers (Panthera tigris) might depend on the management of their preferred prey because large felid populations are limited by the availability of suitable prey. However, the diet of clouded leopards has never been determined, so the preferred prey of this felid remains unknown. The diet of tigers in the region has been studied only from one protected‐area complex in western Thailand, but prey preferences were not determined. To better understand the primary and preferred prey of threatened felids, we used DNA‐confirmed scats and prey surveys to determine the diet and prey selection of clouded leopards and tigers in a hilly evergreen forest in northern Laos. For clouded leopards, the primary prey was wild pig (Sus scrofa; 33% biomass consumed), followed by greater hog badger (Arctonyx collaris; 28%), small rodents (15%), and mainland serow (Capricornis sumatraensis; 13%; hereafter, serow). For tigers, the primary prey was wild pig (44%), followed by serow (18%), sambar (Rusa unicolor; 12%), and Asiatic black bear (Ursus thibetanus; 10%). Compared to availability, serow was positively selected by both clouded leopards (D = 0.69) and tigers (0.61), whereas all other ungulate species were consumed in proportion to the availability or avoided. Our results indicate that clouded leopards are generalist predators with a wide prey spectrum. Nonetheless, mid‐sized ungulates (50–150 kg) comprised nearly half of their diet, and were the preferred prey, supporting a previous hypothesis that the enlarged gape and elongated canines of clouded leopards are adaptations for killing large prey. Because serow was the only ungulate preferred by both felids, we recommend that serow populations be monitored and managed to help conservation efforts for clouded leopards and tigers, at least in hilly evergreen forests of Southeast Asia.

Conservation Prioritization in a Tiger Landscape: Is Umbrella Species Enough?

Conservation approaches in tiger landscapes have focused on single species and their habitat. Further, the limited extent of the existing protected area network in India lacks representativeness, habitat connectivity, and integration in the larger landscape. Our objective was to identify sites important for connected tiger habitat and biodiversity potential in the Greater Panna Landscape, central India. Further, we aimed to set targets at the landscape level for conservation and prioritize these sites within each district in the landscape as specific management/conservation zones. We used earth observation data to derive an index of biodiversity potential. Marxan was used to identify sites that met tiger and biodiversity conservation targets with minimum costs. We found that to protect 50% of the tiger habitat with connectivity, 20% of the landscape area must be conserved. To conserve 100% of high biodiversity potential, 50% moderate biodiversity potential, and 25% low biodiversity potential, 55% of the landscape area must be conserved. To represent both tiger habitat and biodiversity, 62% of the total landscape area requires conservation or restoration intervention. The prioritized zones can prove significant for hierarchical decision making, involving multiple stakeholders in the landscape, including other tiger range areas.

Accounting for geographic variation in species-habitat associations during habitat suitability modeling

Range-wide species conservation efforts are facilitated by spatially explicit estimates of habitat suitability. However, species-environment relationships often vary geographically and models assuming geographically constant relationships may result in misleading inferences. We present the first range-wide habitat suitability model (HSM) for the federally threatened eastern indigo snake (Drymarchon couperi) as a case study illustrating an approach to account for known latitudinal variation in habitat associations. Specifically, we modeled habitat suitability using interactive relationships between minimum winter temperature and several a priori environmental covariates and compared our results to those from models assuming geographically constant relationships. We found that multi-scale models including interactive effects with winter temperature outperformed single-scale models and models not including interactive effects with winter temperature. Our top-ranked model had suitable range-wide predictive performance and identified numerous large (i.e., ≥1000 ha) potential habitat patches throughout the indigo snake range. Predictive performance was greatest in southern Georgia and northern Florida likely reflecting more restrictive indigo snake habitat associations in these regions. This study illustrates how modeling interactive effects between temperature and environmental covariates can improve the performance of HSMs across geographically varying environmental gradients.

Combining multiscale niche modeling, landscape connectivity, and gap analysis to prioritize habitats for conservation of striped hyaena (Hyaena hyaena)

Identifying spatial gaps in conservation networks requires information on species-environment relationships, and prioritization of habitats and corridors. We combined multi-extent niche modeling, landscape connectivity, and gap analysis to investigate scale-dependent environmental relationships, and identify core habitats and corridors for a little-known carnivore in Iran, the striped hyaena (Hyaena hyaena). This species is threatened in Iran by road vehicle collisions and direct killing. Therefore, understanding the factors that affect its habitat suitability, spatial pattern of distribution, and connectivity among them are prerequisite steps to delineate strategies aiming at human-striped hyaena co-existence. The results showed that the highest predictive power and extent of habitats was obtained at the extent sizes of 4 and 2 km, respectively. Also, connectivity analysis revealed that the extent and number of core habitats and corridors changed with increasing dispersal distance, and approximately 21% of the landscape was found to support corridors. The results of gap analysis showed that 15–17% of the core habitats overlapped with conservation areas. Given the body size of the species, its mobility, and lack of significant habitat specialization we conclude that this species would be more strongly influenced by changes in habitat amount rather than landscape configuration. Our approach showed that the scale of variables and dispersal ability must be accounted for in conservation efforts to prioritize habitats and corridors, and designing conservation areas. Our results could facilitate the conservation of striped hyaena through the identification and prioritization of habitats, establishment of conservation areas, and mitigating conflicts in corridors.

Methodological approaches for estimating populations of the endangered dhole Cuon alpinus

Large carnivores are important for maintaining ecosystem integrity and attract much research and conservation interest. For most carnivore species, estimating population density or abundance is challenging because they do not have unique markings for individual identification. This hinders status assessments for many threatened species, and calls for testing new methodological approaches. We examined past efforts to assess the population status of the endangered dhole (Cuon alpinus), and explored the application of a suite of recently developed models for estimating their populations using camera-trap data from India's Western Ghats. We compared the performance of Site-Based Abundance (SBA), Space-to-Event (STE), and Time-to-Event (TTE) models against current knowledge of their population size in the area. We also applied two of these models (TTE and STE) to the co-occurring leopard (Panthera pardus), for which density estimates were available from Spatially Explicit Capture-Recapture (SECR) models, so as to simultaneously validate the accuracy of estimates for one marked and one unmarked species. Our review of literature (n = 38) showed that most assessments of dhole populations involved crude indices (relative abundance index; RAI) or estimates of occupancy and area of suitable habitat; very few studies attempted to estimate populations. Based on empirical data from our field surveys, the TTE and SBA models overestimated dhole population size beyond ecologically plausible limits, but the STE model produced reliable estimates for both the species. Our findings suggest that it is difficult to estimate population sizes of unmarked species when model assumptions are not fully met and data are sparse, which are commonplace for most ecological surveys in the tropics. Based on our assessment, we propose that practitioners who have access to photo-encounter data on dholes across Asia test old and new analytical approaches to increase the overall knowledge-base on the species, and contribute towards conservation monitoring of this endangered carnivore.

Identifying core habitats and corridors for giant pandas by combining multiscale random forest and connectivity analysis

Habitat loss and fragmentation are widely acknowledged as the main driver of the decline of giant panda populations. The Chinese government has made great efforts to protect this charming species and has made remarkable achievements, such as population growth and habitat expansion. However, habitat fragmentation has not been reversed. Protecting giant pandas in a large spatial extent needs to identify core habitat patches and corridors connecting them. This study used an equal-sampling multiscale random forest habitat model to predict a habitat suitability map for the giant panda. Then, we applied the resistant kernel method and factorial least-cost path analysis to identify core habitats connected by panda dispersal and corridors among panda occurrences, respectively. Finally, we evaluated the effectiveness of current protected areas in representing core habitats and corridors. Our results showed high scale dependence of giant panda habitat selection. Giant pandas strongly respond to bamboo percentage and elevation at a relatively fine scale (1 km), whereas they respond to anthropogenic factors at a coarse scale (≥2 km). Dispersal ability has significant effects on core habitats extent and population fragmentation evaluation. Under medium and high dispersal ability scenarios (12,000 and 20,000 cost units), most giant panda habitats in the Qionglai mountain are predicted to be well connected by dispersal. The proportion of core habitats covered by protected areas varied between 38% and 43% under different dispersal ability scenarios, highlighting significant gaps in the protected area network. Similarly, only 43% of corridors that connect giant panda occurrences were protected. Our results can provide crucial information for conservation managers to develop wise strategies to safeguard the long-term viability of the giant panda population.

Investigating Carnivore Guild Structure: Spatial and Temporal Relationships amongst Threatened Felids in Myanmar

The co-occurrence of felid species in Southeast Asia provides an unusual opportunity to investigate guild structure and the factors controlling it. Using camera-trap data, we quantified the space use, temporal activity, and multi-dimensional niche overlap of the tiger, clouded leopard, Asiatic golden cat, marbled cat, and leopard cat in the Htamanthi Wildlife Sanctuary, Myanmar. We hypothesised that the spatio-temporal behaviour of smaller cats would reflect the avoidance of the larger cats, and similar-sized guild members would partition their niches in space or time to reduce resource competition. Our approach involved modelling single-species occupancy, pairwise spatial overlap using Bayesian inference, activity overlap with kernel density estimation, and multivariate analyses. The felid assembly appeared to be partitioned mainly on a spatial rather than temporal dimension, and no significant evidence of mesopredator release was observed. Nonetheless, the temporal association between the three mesopredators was inversely related to the similarity in their body sizes. The largest niche differences in the use of space and time occurred between the three smallest species. This study offers new insight into carnivore guild assembly and adds substantially to knowledge of five of the least known felids of conservation concern.

A methodological roadmap to quantify animal-vectored spatial ecosystem subsidies

Energy, nutrients and organisms move over landscapes, connecting ecosystems across space and time. Meta-ecosystem theory investigates the emerging properties of local ecosystems coupled spatially by these movements of organisms and matter, by explicitly tracking exchanges of multiple substances across ecosystem borders. To date, meta-ecosystem research has focused mostly on abiotic flows-neglecting biotic nutrient flows. However, recent work has indicated animals act as spatial nutrient vectors when they transport nutrients across landscapes in the form of excreta, egesta and their own bodies. Partly due to its high level of abstraction, there are few empirical tests of meta-ecosystem theory. Furthermore, while animals may be viewed as important mediators of ecosystem functions, better integration of tools is needed to develop predictive insights of their relative roles and impacts on diverse ecosystems. We present a methodological roadmap that explains how to do such integration by discussing how to combine insights from movement, foraging and ecosystem ecology to develop a coherent understanding of animal-vectored nutrient transport on meta-ecosystems processes. We discuss how the slate of newly developed technologies and methods-tracking devices, mechanistic movement models, diet reconstruction techniques and remote sensing-that when integrated have the potential to advance the quantification of animal-vectored nutrient flows and increase the predictive power of meta-ecosystem theory. We demonstrate that by integrating novel and established tools of animal ecology, ecosystem ecology and remote sensing, we can begin to identify and quantify animal-mediated nutrient translocation by large animals. We also provide conceptual examples that show how our proposed integration of methodologies can help investigate ecosystem impacts of large animal movement. We conclude by describing practical advancements to understanding cross-ecosystem contributions of animals on the move. Understanding the mechanisms by which animals shape ecosystem dynamics is important for ongoing conservation, rewilding and restoration initiatives around the world, and for developing more accurate models of ecosystem nutrient budgets. Our roadmap will enable ecologists to better qualify and quantify animal-mediated nutrient translocation for animals on the move.

Small cats in big trouble? Diet, activity, and habitat use of jungle cats and leopard cats in threatened dry deciduous forests, Cambodia

Dry deciduous dipterocarp forests (DDF) cover about 15%-20% of Southeast Asia and are the most threatened forest type in the region. The jungle cat (Felis chaus) is a DDF specialist that occurs only in small isolated populations in Southeast Asia. Despite being one of the rarest felids in the region, almost nothing is known about its ecology. We investigated the ecology of jungle cats and their resource partitioning with the more common leopard cats (Prionailurus bengalensis) in a DDF-dominated landscape in Srepok Wildlife Sanctuary, Cambodia. We used camera-trap data collected from 2009 to 2019 and DNA-confirmed scats to determine the temporal, dietary and spatial overlap between jungle cats and leopard cats. The diet of jungle cats was relatively diverse and consisted of murids (56% biomass consumed), sciurids (15%), hares (Lepus peguensis; 12%), birds (8%), and reptiles (8%), whereas leopard cats had a narrower niche breadth and a diet dominated by smaller prey, primarily murids (73%). Nonetheless, dietary overlap was high because both felid species consumed predominantly small rodents. Both species were primarily nocturnal and had high temporal overlap. Two-species occupancy modelling suggested jungle cats were restricted to DDF and had low occupancy, whereas leopard cats had higher occupancy and were habitat generalists. Our study confirmed that jungle cats are DDF specialists that likely persist in low numbers due to the harsh conditions of the dry season in this habitat, including annual fires and substantial decreases in small vertebrate prey. The lower occupancy and more diverse diet of jungle cats, together with the broader habitat use of leopard cats, likely facilitated the coexistence of these species. The low occupancy of jungle cats in DDF suggests that protection of large areas of DDF will be required for the long-term conservation of this rare felid in Southeast Asia.

Long-term monitoring of margays (Leopardus wiedii): Implications for understanding low detection rates

Population assessments of wide-ranging, cryptic, terrestrial mammals rely on camera trap surveys. While camera trapping is a powerful method of detecting presence, it is difficult distinguishing rarity from low detection rate. The margay (Leopardus wiedii) is an example of a species considered rare based on its low detection rates across its range. Although margays have a wide distribution, detection rates with camera traps are universally low; consequently, the species is listed as Near Threatened. Our 12-year camera trap study of margays in protected broadleaf forest in Belize suggests that while margays have low detection rate, they do not seem to be rare, rather that they are difficult to detect with camera traps. We detected a maximum of 187 individuals, all with few or no recaptures over the years (mean = 2.0 captures/individual ± SD 2.1), with two-thirds of individuals detected only once. The few individuals that were recaptured across years exhibited long tenures up to 9 years and were at least 10 years old at their final detection. We detected multiple individuals of both sexes at the same locations during the same survey, suggesting overlapping ranges with non-exclusive territories, providing further evidence of a high-density population. By studying the sparse annual datasets across multiple years, we found evidence of an abundant margay population in the forest of the Cockscomb Basin, which might have been deemed low density and rare, if studied in the short term. We encourage more long-term camera trap studies to assess population status of semi-arboreal carnivore species that have hitherto been considered rare based on low detection rates.

The role of the environment in the spatial dynamics of an extensive hybrid zone between two neotropical cats

Identifying factors that create and maintain a hybrid zone is of great interest to ecology, evolution and, more recently, conservation biology. Here, we investigated the role of environmental features in shaping the spatial dynamics of a hybrid zone between the southern tigrina, Leopardus guttulus, and Geoffroy's cat, L. geoffroyi, testing for exogenous selection as the main force acting on its maintenance. These Neotropical felid species are mainly allopatric, with a restricted area of sympatry in the ecotone between the Atlantic Forest and Pampa biomes. As both biomes have experienced high rates of anthropogenic habitat alteration, we also analysed the influence of habitat conversion on the hybrid zone structure. To do this, we used 13 microsatellite loci to identify potential hybrids and generated ecological niche models for them and their parental species. We compared the influence of variables on parental species and hybrid occurrence and calculated the amount of niche overlap among them. Parental species showed different habitat requirements and predicted co-occurrence was restricted to the forest-grassland mosaic of the ecotone. However, hybrids were found beyond this area, mainly in the range of L. geoffroyi. Hybrids demonstrated higher tolerance to habitat alteration than parental types, with a probability of occurrence that was positively related with mosaics of cropland areas and remnants of natural vegetation. These results indicate that exogenous selection alone does not drive the dynamics of the hybrid zone, and that habitat conversion influences its structure, potentially favouring hybrids over parental species.

Identifying priority core habitats and corridors for effective conservation of brown bears in Iran

Iran lies at the southernmost range limit of brown bears globally. Therefore, understanding the habitat associations and patterns of population connectivity for brown bears in Iran is relevant for the species’ conservation. We applied species distribution modeling to predict habitat suitability and connectivity modeling to identify population core areas and corridors. Our results showed that forest density, topographical roughness, NDVI and human footprint were the most influential variables in predicting brown bear distribution. The most crucial core areas and corridor networks for brown bear are concentrated in the Alborz and Zagros Mountains. These two core areas were predicted to be fragmented into a total of fifteen isolated patches if dispersal of brown bear across the landscape is limited to 50,000 cost units, and aggregates into two isolated habitat patches if the species is capable of dispersing 400,000 cost units. We found low overlap between corridors, and core habitats with protected areas, suggesting that the existing protected area network may not be adequate for the conservation of brown bear in Iran. Our results suggest that effective conservation of brown bears in Iran requires protection of both core habitats and the corridors between them, especially outside Iran’s network of protected areas.

Projected Impacts of Climate Change on the Protected Areas of Myanmar

Protected areas are the backbone of biodiversity conservation but are fixed in space and vulnerable to anthropogenic climate change. Myanmar is exceptionally rich in biodiversity but has a small protected area system. This study aimed to assess the potential vulnerability of this system to climate change. In the absence of good biodiversity data, we used a spatial modeling approach based on a statistically derived bioclimatic stratification (the Global Environmental Stratification, GEnS) to understand the spatial implications of projected climate change for Myanmar’s protected area system by 2050 and 2070. Nine bioclimatic zones and 41 strata were recognized in Myanmar, but their representation in the protected area system varied greatly, with the driest zones especially underrepresented. Under climate change, most zones will shift upslope, with some protected areas projected to change entirely to a new bioclimate. Potential impacts on biodiversity include mountaintop extinctions of species endemic to isolated peaks, loss of climate specialists from small protected areas and those with little elevational range, and woody encroachment into savannas and open forests as a result of both climate change and rising atmospheric CO2. Myanmar needs larger, better connected, and more representative protected areas, but political, social, and economic problems make this difficult.

Meta-replication, sampling bias, and multi-scale model selection: A case study on snow leopard (Panthera uncia) in western China

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.