Assessing the adequacy of a protected area network in conserving a wide‐ranging apex predator: The case for tiger ( Panthera tigris ) conservation in Bhutan

Comparing wildlife habitat suitability models based on expert opinion with camera trap detections

Expert knowledge is used in the development of wildlife habitat suitability models (HSMs) for management and conservation decisions. However, the consistency of such models has been questioned. Focusing on 1 method for elicitation, the analytic hierarchy process, we generated expert-based HSMs for 4 felid species: 2 forest specialists (ocelot [Leopardus pardalis] and margay [Leopardus wiedii]) and 2 habitat generalist species (Pampas cat [Leopardus colocola] and puma [Puma concolor]). Using these HSMs, species detections from camera-trap surveys, and generalized linear models, we assessed the effect of study species and expert attributes on the correspondence between expert models and camera-trap detections. We also examined whether aggregation of participant responses and iterative feedback improved model performance. We ran 160 HSMs and found that models for specialist species showed higher correspondence with camera-trap detections (AUC [area under the receiver operating characteristic curve] >0.7) than those for generalists (AUC < 0.7). Model correspondence increased as participant years of experience in the study area increased, but only for the understudied generalist species, Pampas cat (β = 0.024 [SE 0.007]). No other participant attribute was associated with model correspondence. Feedback and revision of models improved model correspondence, and aggregating judgments across multiple participants improved correspondence only for specialist species. The average correspondence of aggregated judgments increased as group size increased but leveled off after 5 experts for all species. Our results suggest that correspondence between expert models and empirical surveys increases as habitat specialization increases. We encourage inclusion of participants knowledgeable of the study area and model validation for expert-based modeling of understudied and generalist species.

Modeling Distribution and Habitat Suitability for the Snow Leopard in Bhutan

The snow leopard (Panthera uncia) is one of the world's most elusive felids. In Bhutan, which is one of the 12 countries where the species still persists, reliable information on its distribution and habitat suitability is lacking, thus impeding effective conservation planning for the species. To fill this knowledge gap, we created a country-wide species distribution model using “presence-only” data from 420 snow leopard occurrences (345 from a sign survey and 77 from a camera-trapping survey) and 12 environmental covariates consisting of biophysical and anthropogenic factors. We analyzed the data in an ensemble model framework which combines the outputs from several species distribution models. To assess the adequacy of Bhutan's network of protected areas and their potential contribution toward the conservation of the species, we overlaid the output of the ensemble model on the spatial layers of protected areas and biological corridors. The ensemble model identified 7,206 km2 of Bhutan as suitable for the snow leopard: 3,647 km2 as highly suitable, 2,681 km2 as moderately suitable, and 878 km2 as marginally suitable. Forty percent of the total suitable habitat consisted of protected areas and a further 8% of biological corridors. These suitable habitats were characterized by a mean livestock density of 1.3 individuals per hectare, and a mean slope of 25°; they closely match the distribution of the snow leopard's main wild prey, the bharal (Pseudois nayaur). Our study shows that Bhutan's northern protected areas are a centre for snow leopard conservation both at the national and regional scale.

Predictively modelling the distribution of the threatened brush-tailed rock-wallaby (

Abstract Context Species Distribution Models (SDM) can be used to investigate and understand relationships between species occurrence and environmental variables, so as to predict potential distribution. These predictions can facilitate conservation actions and management decisions. Oxley Wild Rivers National Park (OWRNP) is regarded as an important stronghold for the threatened brush-tailed rock-wallaby (Petrogale penicillata), on the basis of the presence of the largest known metapopulation of the species. Adequate knowledge of the species’ ecology and distribution in OWRNP is a key objective in the national recovery plan for the species occurring in the Park. Aims To model distribution using key GIS-derived environmental factors for the brush-tailed rock-wallaby in OWRNP and to ground-truth its presence through field surveys in areas of high habitat suitability. Methods We used Maxent to model the distribution of the brush-tailed rock-wallaby within OWRNP on the basis of 282 occurrence records collected from an online database, elicitation of informal records from experts, helicopter surveys and historic records. Environmental variables used in the analysis were aspect, distance to water, elevation, geology type, slope and vegetation type. Key results Vegetation type (37.9%) was the highest contributing predictor of suitable habitat, whereas aspect (4.8%) contributed the least. The model produced an area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.780. The model was able to discriminate between suitable and non-suitable habitat for brush-tailed rock-wallabies. Areas identified in our model as being highly suitable yielded eight new occurrence records during subsequent ground-truthing field surveys. Conclusions Brush-tailed rock-wallaby distribution in OWRNP is primarily associated with vegetation type, followed by distance to water, elevation, geology, slope and aspect. Field surveys indicated that the model was able to identify areas of high habitat suitability. Implications This model represents the first predicted distribution of brush-tailed rock-wallaby in OWRNP. By identifying areas of high habitat suitability, it can be used to survey and monitor the species in OWRNP, and, thus, contribute to its management and conservation within the Park.

Conserving an Endangered Canid: Assessing Distribution, Habitat Protection, and Connectivity for the Dhole (Cuon alpinus) in Bhutan

Most canids face population declines and range contractions worldwide. Although the dhole (Cuon alpinus) is widely distributed across 10 countries in South and Southeast Asia, limited studies exist on this species. Despite its globally “Endangered” status and ecological role as an apex predator, assessments on its distribution are limited to a few landscapes and countries. This explains the lack of a dhole-specific species conservation plan in most range countries, including Bhutan where no current population estimate exists. The species has also recovered from a country-wide poisoning campaign in the 1970s and 80s. In this study, we determine the dhole's distribution pattern and assess the protection and connectivity of dhole habitat in Bhutan. We anticipated dholes to be extant within their habitat well-represented in protected areas (PAs) and biological corridors (BCs). We used 721 georeferenced dhole occurrence records and eight environmental variables in MaxEnt software to model potential dhole distribution and habitat suitability. The model output was overlaid on the spatial layers of PAs and BCs to assess habitat protection and connectivity. As anticipated, we found the dhole widely distributed in all districts, PAs, and BCs in Bhutan. Dholes were recorded at the highest elevation range limit of 4,980 m above sea level, which overlapped with the “Vulnerable” snow leopard (Panthera uncia). Our model identified 72% (27,634 km2) of the country as suitable areas for dholes, of which, 31% (11,899 km2) was highly suitable and 41% (15,735 km2) was moderately suitable. Contrary to our expectation, PAs and BCs encompassed only 29% (8,046 km2) and 12% (3,185 km2) of suitable areas for dholes, respectively. A vast majority of the areas we deemed suitable for dholes currently remain unprotected, thus making dholes more vulnerable to human persecution and local extermination. We recommend adjusting PA boundaries to fully encompass suitable dhole habitat, and also advocate improved livestock husbandry to reduce dhole related livestock predation and minimize conflict, thereby ensuring its long-term survival in Bhutan.