Climate change has severely impacted many species, causing rapid declines or extinctions within their essential ecological niches. This deterioration is expected to worsen, particularly in remote high-altitude regions like the Himalayas, which are home to diverse flora and fauna, including many mountainous ungulates. Unfortunately, many of these species lack adaptive strategies to cope with novel climatic conditions. The Red Goral (Naemorhedus baileyi) is a cliff-dwelling species classified as “Vulnerable” by the IUCN due to its small population and restricted range extent. This species has the most restricted range of all goral species, residing in the temperate mountains of northeastern India, northern Myanmar, and China. Given its restricted range and small population, this species is highly threatened by climate change and habitat disruptions, making habitat mapping and modeling crucial for effective conservation. This study employs an ensemble approach (BRT, GLM, MARS, and MaxEnt) in species distribution modeling to assess the distribution, habitat suitability, and connectivity of this species, addressing critical gaps in its understanding. The findings reveal deeply concerning trends, as the model identified only 21,363 km² (13.01%) of the total IUCN extent as suitable habitat under current conditions. This limited extent is alarming, as it leaves the species with very little refuge to thrive. Furthermore, this situation is compounded by the fact that only around 22.29% of this identified suitable habitat falls within protected areas (PAs), further constraining the species’ ability to survive in a protected landscape. The future projections paint even degraded scenarios, with a predicted decline of over 34% and excessive fragmentation in suitable habitat extent. In addition, the present study identifies precipitation seasonality and elevation as the primary contributing predictors to the distribution of this species. Furthermore, the study identifies nine designated transboundary PAs within the IUCN extent of the Red Goral and the connectivity among them to highlight the crucial role in supporting the species’ survival over time. Moreover, the Dibang Wildlife Sanctuary (DWLS) and Hkakaborazi National Park are revealed as the PAs with the largest extent of suitable habitat in the present scenario. Furthermore, the highest mean connectivity was found between DWLS and Mehao Wildlife Sanctuary (0.0583), while the lowest connectivity was observed between Kamlang Wildlife Sanctuary and Namdapha National Park (0.0172). The study also suggests strategic management planning that is a vital foundation for future research and conservation initiatives, aiming to ensure the long-term survival of the species in its natural habitat.

In recent years, global warming has become a major driver of biodiversity loss, significantly impacting various vertebrate species, including mammals. Consequently, numerous smaller species face extinction risks due to anthropogenic factors as well as inadequate assessments and conservation planning. Thus, this study focuses on two recently described endemic giant flying squirrel species under the Petaurista genus—Petaurista mishmiensis and Petaurista mechukaensis—found in Arunachal Pradesh, India. Using an ensemble species distribution model (SDM), this research delineates suitable habitats for these lesser-known species and evaluates the effects of climate change and habitat fragmentation on these areas. This analysis aims to inform a comprehensive management plan for their conservation. The ensemble model identified suitable habitat patches for the two species, extending beyond their current IUCN-designated ranges in Arunachal Pradesh. Under present conditions, P. mishmiensis has the largest predicted suitable area (9213 sq. km), followed by P. mechukaensis (6754 sq. km). However, future projections reveal alarming habitat losses ranging from 13.45% to 55.86% across the study area. This study also highlights severe habitat fragmentation throughout the state as viable patches for P. mishmiensis are drastically reduced in size, resulting in many being completely lost and the remaining areas being closer together. However, the P. mechukaensis experiences significant disintegration, resulting in numerous smaller, more dispersed patches within Arunachal Pradesh. Hence, to address these challenges, this study recommends several actions such as genetic assessments to confirm evolutionary relationships, evaluations of corridor connectivity, and comprehensive field studies. Furthermore, establishing joint forest conservation committees involving local communities, forest personnel, defense forces, naturalists, and scientists are also encouraged. Ultimately, this research provides critical insights for guiding future field studies across Arunachal Pradesh’s vast landscapes and supports the development of detailed species management plans to protect these endemic flying squirrels.

In recent years, remote sensing and geographic information systems (GISs) have become essential tools for effective landscape management. This study utilizes these technologies to analyze land use and land cover (LULC) changes in Dibru-Saikhowa National Park, a riverine ecosystem in Assam, India, from its designation as a national park in 2000 through 2024. The satellite imagery was used to classify LULC types and track landscape changes over time. In 2000, grasslands were the dominant land cover (28.78%), followed by semi-evergreen forests (25.58%). By 2013, shrubland became the most prominent class (81.31 km²), and degraded forest expanded to 75.56 km². During this period, substantial areas of grassland (29.94 km²), degraded forest (10.87 km²), semi-evergreen forest (12.33 km²), and bareland (10.50 km²) were converted to shrubland. In 2024, degraded forest further increased, covering 80.52 km² (23.47%). This change resulted since numerous areas of shrubland (11.46 km²) and semi-evergreen forest (27.48 km²) were converted into degraded forest. Furthermore, significant shifts were observed in grassland, shrubland, and degraded forest, indicating a substantial and consistent decline in grassland. These changes are largely attributed to recurring Brahmaputra River floods and increasing anthropogenic pressures. This study recommends a targeted Grassland Recovery Project, control of invasive species, improved surveillance, increased staffing, and the relocation of forest villages to reduce human impact and support community-based conservation efforts. Hence, protecting the landscape through informed LULC-based management can help maintain critical habitat patches, mitigate anthropogenic degradation, and enhance the survival prospects of native floral and faunal assemblages in DSNP.