LAUSR

Simple Summary The objective of our study was to gain a deep understanding about the role of predicted climate change on the range restricted and high-mountain dwelling animal species like the Himalayan goral (HG). To achieve this, we conducted species distribution modeling of the target species under present and predicted future climate change scenarios. Our focus was on identifying the potential suitable microhabitats of the target species using a predictive modeling and maximum entropy algorithm under current climate, and any possible range variation and shift under future climate change scenarios. Annual precipitation and elevation are important factors that affect goral distribution; the elevation between 2000 and 3000 m is thought to be the most suitable for the goral’s habitat. Additionally, a general slight range shift toward northern latitudes and along the higher elevations is observed. Our analysis shows that the suitability of the Himalayan goral’s habitat can change dramatically depending on the forecast. This work might fill the existing knowledge gap about the target species distribution in the study area and predict suitable habitats necessary for species conservation. This study might also be helpful in future planning, management, and sustainable use of available resources, and to mitigate the possible negative effects of climate change in the Himalayan region. Abstract The distribution of large ungulates is more often negatively impacted by the changing climate, especially global warming and species with limited distributional zones. While developing conservation action plans for the threatened species such as the Himalayan goral (Naemorhedus goral Hardwicke 1825; a mountain goat that mostly inhabits rocky cliffs), it is imperative to comprehend how future distributions might vary based on predicted climate change. In this work, MaxEnt modeling was employed to assess the habitat suitability of the target species under varying climate scenarios. Such studies have provided highly useful information but to date no such research work has been conducted that considers this endemic animal species of the Himalayas. A total of 81 species presence points, 19 bioclimatic and 3 topographic variables were employed in the species distribution modeling (SDM), and MaxEnt calibration and optimization were performed to select the best candidate model. For predicted climate scenarios, the future data is drawn from SSPs 245 and SSPs 585 of the 2050s and 2070s. Out of total 20 variables, annual precipitation, elevation, precipitation of driest month, slope aspect, minimum temperature of coldest month, slope, precipitation of warmest quarter, and temperature annual range (in order) were detected as the most influential drivers. A high accuracy value (AUC-ROC > 0.9) was observed for all the predicted scenarios. The habitat suitability of the targeted species might expand (about 3.7 to 13%) under all the future climate change scenarios. The same is evident according to local residents as species which are locally considered extinct in most of the area, might be shifting northwards along the elevation gradient away from human settlements. This study recommends additional research is conducted to prevent potential population collapses, and to identify other possible causes of local extinction events. Our findings will aid in formulating conservation plans for the Himalayan goral in a changing climate and serve as a basis for future monitoring of the species.