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The utilization of satellite images in conservation research is becoming more prevalent due to advancements in remote sensing technologies. To achieve accurate classification of wildlife habitats, it is important to consider the different capabilities of spectral and spatial resolution. Our study aimed to develop a method for accurately classifying habitat types of the Himalayan ibex (Capra sibirica) using satellite data. We used LISS IV and Sentinel 2A data to address both spectral and spatial issues. Furthermore, we integrated the LISS IV data with the Sentinel 2A data, considering their individual geometric information. The Random Forest approach outperformed other algorithms in supervised classification techniques. The integrated image had the highest level of accuracy, with an overall accuracy of 86.17% and a Kappa coefficient of 0.84. Furthermore, to delineate the suitable habitat for the Himalayan ibex, we employed ensemble modelling techniques that incorporated Land Cover Land Use data from LISS IV, Sentinel 2A, and Integrated image, separately. Additionally, we incorporated other predictors including topographical features, soil and water radiometric indices. The integrated image demonstrated superior accuracy in predicting the suitable habitat for the species. The identification of suitable habitats was found to be contingent upon the consideration of two key factors: the Soil Adjusted Vegetation Index and elevation. The study findings are important for advancing conservation measures. Using accurate classification methods helps identify important landscape components. This study offers a novel and important approach to conservation planning by accurately categorising Land Cover Land Use and identifying critical habitats for the species., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 Dutta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Landscape features can impede dispersal, gene flow, and population demography, resulting in the formation of several meta-populations within a continuous landscape. Understanding a species' ability to overcome these barriers is critical for predicting genetic connectivity and population persistence, and implementing effective conservation strategies. In the present study, we conducted a fine-scale spatial genetic analysis to understand the contemporary gene flow within red panda populations in the Eastern Himalayas. Employing geometric aspects of reserve design, we delineated the critical core habitats for red pandas, which comprise 14.5 % of the landscape (12,189.75 Km 2 ), with only a mere 443 Km 2 falling within the protected areas. We identified corridors among the core habitats, which may be vital for the species' long-term genetic viability. Furthermore, we identified substantial landscape barriers, including Sela Pass in the western region, Siang river in the central region, and the Dibang river, Lohit river, along with Dihang, Dipher, and Kumjawng passes in the eastern region, which hinder gene flow. We suggest managing red panda populations through the creation of Community Conservation Reserves in the identified core habitats, following landscape-level management planning based on the core principles of geometric reserve design. This includes a specific emphasis on identified core habitats of red panda (CH-RP 5 and CH-RP 8) to facilitate corridors and implement meta-population dynamics. We propose the development of a comprehensive, long-term conservation and management plan for red pandas in the transboundary landscape, covering China, Nepal, and Bhutan., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The trans-Himalayan region of India, although have xeric features, still supports a unique assemblage of biodiversity, including some of the charismatic and endemic species. In the present study, we studied blue sheep (Pseudois nayaur) across the distribution range in the Western trans Himalayas of India and found about 18,775 km 2 area suitable for blue sheep. The explicit Bayesian based spatial and non-spatial population structure analysis assigned blue sheep into two genetic populations, i.e., Ladakh and Lahaul-Spiti. We found relatively high genetic divergence in blue sheep which is also supported by the low current flow in Circuitscape model. With the multiple evidences, we explain landscape resistance facilitated by the landscape heterogeneity, and large patches of unsuitable habitats forced population divergence and poor functional connectivity. We found that blue sheep population has been demographically stable in the past, but showed a slight decline within the last few decades. This study is the first range-wide attempt to exhibit landscape features in shaping the spatial distribution, genetic structure and demography patterns of blue sheep in Western Himalayas, and will be of use in the conservation and management planning of blue sheep., (© 2023. Springer Nature Limited.)

According to the United Nations International Children's Emergency Fund (UNICEF) assessment report released in 2021, South Asian countries were among the most vulnerable in the world to the effects of climate change on future generations. Hence it is become crucial to assess how resilient the ecosystems are to these changes. The current study incorporated a novel approach, the Combined Ecological Resiliency Indices Approach (CERIA), to assess ecological resiliency status at various scales during hydroclimatic disturbances. Water and carbon use efficiency (WUE and CUE, respectively) were used as indicators for the examination of ecological resilience. The standardized Precipitation Index (SPI) was adopted to assess the initial stage of hydroclimatic disturbances (meteorological drought). A resiliency analysis based on combined R d and R d ' indices (derived from WUE and CUE, respectively) revealed that just 1.87% land cover area of the entire SAARC (South Asian Association for Regional Cooperation) region's total 17 land cover classes was resilient to meteorological drought. At the river basin scale, only 16.58% of the total 62 river basins were found resilient. Only 11 (27.46%) of the 21 climate classes on the Koppen climate classification scale were resilient to the hydro-climatic disturbance period. To achieve the United Nations sustainable development goals (SDGs goal-2 and goal-13) of 'No Hunger' and 'Protect the Planet', the Joint Ecosystem Resiliency Enhancement Programme (JEREP) should be adopted in land cover, river basins, or climatic classes of the SAARC region that were highly affected., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Large forested landscapes often harbour significant amount of biodiversity and support mankind by rendering various livelihood opportunities and ecosystem services. Their periodic assessment for health and ecological integrity is essential for timely mitigation of any negative impact of human use due to over harvesting of natural resources or unsustainable developmental activities. In this context, monitoring of mega fauna may provide reasonable insights about the connectivity and quality of forested habitats. In the present study, we conducted a largest non-invasive genetic survey to explore mammalian diversity and genetically characterized 13 mammals from the Indian Himalayan Region (IHR). We analyzed 4806 faecal samples using 103 autosomal microsatellites and with three mitochondrial genes, we identified 37 species of mammal. We observed low to moderate level of genetic variability and most species exhibited stable demographic history. We estimated an unbiased population genetic account (PGA unbias ) for 13 species that may be monitored after a fixed time interval to understand species performance in response to the landscape changes. The present study has been evident to show pragmatic permeability with the representative sampling in the IHR in order to facilitate the development of species-oriented conservation and management programmes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Species with sympatric distribution influence ecosystem dynamics and are impacted by the presence of other co-existing species. Assessing the coexistence and the role of interspecific interactions with the landscape variables is necessary to know the species co-occurrence in space. In the Indian Himalayan region, such studies are completely lacking due to limited efforts being made, mainly because of complex terrains and inaccessible landscape features. We used camera trapping and sign survey in a multi-species occupancy framework to understand the influence of environmental variables on occupancy and detection probability of species-specific and pair-wise interaction of the three ungulates in Uttarkashi. Our results concluded that individual species' occupancy probabilities were related both to the environmental variables and the presence or absence of other interacting species. Our top model showed evidence of interspecific interaction among species pairs, and the occupancy probability of species one varied in the presence or absence of another species. The overall activity patterns were similar among all the three species and were found active throughout the day. The activity overlap between sambar-barking deer (Dhat1 value = 0.85) was considerably higher than barking deer-goral (Dhat1 value = 0.78). The findings of the present study will be useful for the conservation and management of ungulates in the Indian Himalayan and adjoining regions., (© 2022. The Author(s).)

Wildlife management in rapid changing landscapes requires critical planning through cross cutting networks, and understanding of landscape features, often affected by the anthropogenic activities. The present study demonstrates fine-scale spatial patterns of genetic variation and contemporary gene flow of red panda (Ailurus fulgens) populations with respect to landscape connectivity in Kangchenjunga Landscape (KL), India. The study found about 1,309.54 km 2 area suitable for red panda in KL-India, of which 62.21% area fell under the Protected Area network. We identified 24 unique individuals from 234 feces collected at nine microsatellite loci. The spatially explicit and non-explicit Bayesian clustering algorithms evident to exhibit population structuring and supported red panda populations to exist in meta-population frame work. In concurrence to the habitat suitability and landscape connectivity models, gene flow results supported a contemporary asymmetric movement of red panda by connecting KL-India in a crescent arc. We demonstrate the structural-operational connectivity of corridors in KL-India that facilitated red panda movement in the past. We also seek for cooperation in Nepal, Bhutan and China to aid in preparing for a comprehensive monitoring plan for the long-term conservation and management of red panda in trans-boundary landscapes.

Different Biogeographic provinces and environmental factors are known to influence the dispersibility of long-ranging carnivores over the landscape. However, lack of empirical data on long-ranging carnivores may lead to erroneous decisions in formulating management plans. The Indian Grey wolf (Canis lupus pallipes) is known to be distributed in the vast areas of the Indian subcontinent. However, the actual population estimates are available only for Gujarat, Karnataka, Rajasthan and Bihar. Whereas, its distribution, population and habitat ecology is poorly known from the eastern region. Hence, this article aimed to evaluate the habitat suitability along with landscape connectivity for the species over the two major biogeographic provinces of India, i.e., Lower Gangetic Plains (7b) and Chhota Nagpur Plateau (6b). The present model with significantly higher Area under the curve (AUC) value of 0.981, indicates its accuracy in predicting the suitable habitats and identifying biological corridors by using environmental, topological and anthropogenic variables. Precipitation of the driest quarter and the precipitation of seasonality were the two best performing variables in our model, capable of explaining about 26% and 22.4% variation in the data respectively. Out of the total area i.e. 4,16,665 Km2, about 18,237 Km2 (4.37%) was found to be highly suitable area and about 3,16,803 Km2 (76.03%) areas as least suitable. The corridor analysis indicated that the habitat connectivity was highest in the border line area of the two biotic provinces located in the south-eastern zone via districts of Purba Singhbhum and Paschim Singhbhum of Jharkhand state and Bankura and West Midnapore districts of West Bengal state. Among the Protected Areas (PAs), natural corridors exist connecting the Simlipal National Park (NP)-Satkosia Wildlife Santuray (WLS), Dalma ranges of Chotta Nagpur plateau along with Badrama WLS, Khulasuni WLS and Debrigarh WLS. Differential management through landscape level planning may be helpful in securing the future of the species in the landscape., Competing Interests: The authors have declared that no competing interests exist.