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The present study aimed at predicting the potential habitat of Western Hoolock Gibbon ( Hoolock hoolock ) in the upper Brahmaputra River Valley, Assam, India, and identifying priority conservation areas for the species, taking canopy cover into account. We used the maximum entropy algorithm for the prediction of the potential habitat of the gibbon using its current distribution with 19 environmental parameters as primary predictors. Spatio-temporal analyses of the habitat were carried out using satellite-based remote sensing and GIS techniques for two decades (1998–2018) along with Terra Modis Vegetation Continuous Field product to examine land use land cover (LULC), habitat fragmentation, Normalized Difference Vegetation Index (NDVI) and tree cover percentage of the study area. To identify the conservation priority area, we applied a cost-effective decision-making analysis using systematic conservation prioritization in R programming. The model predicted an area of 6025 km 2  under high potential habitat, a major part of which was found to overlap with dense forest (80%), followed by moderately open forest (74%) and open forest (66%). The LULC change matrix showed a reduction of forest area in the predicted high potential habitat during the study period, while agricultural class showed an increasing trend. The fragmentation analysis indicated that the number of patches and patch density increased from 2008 to 2018 in the ‘very dense’ and ‘dense’ canopy regions of the gibbon habitat. Based on the conservation priority analysis, a 640 km 2  area has been proposed to conserve a minimum of 10% of gibbon habitat. The current analysis revealed that in the upper Brahmaputra Valley most areas under dense forest and dense canopy have remained intact over the last two decades, at least within the high potential habitat zone of gibbons independent of the degree of area change in forest, agriculture and plantation.

Habitat monitoring and conservation prioritization of Western Hoolock Gibbon in upper Brahmaputra Valley, Assam, India