3/7/2023 0 Comments Slender lorisThus current management practices need to concern these issues for the future survival of the Overall study clearly shows available habitat for the Montane Slender Loris is critically small Making to identify suitable hotspots for habitats of Montane Slender Loris in the HSNR. Possibility of using spatial and geographical features for effective analysis and decision Habitat suitability factors, along with related topographic data through GIS and discover the The objective of this research is to map the Lanka using GIS and Remote sensing techniques. Suitability analysis for Montane Slender Loris in Hakgala Strict Nature Reserve (HSNR) in Sri This research study is an attempt to explore the application of habitat Slender Loris is endangered primate subspecies and found only in the Montane rainforest Geographic Information Systems and Remote sensing are treated as powerfulĪnalysis and decision making tool used in a spectrum of applications in different fields. The presence of an undescribed subspecies of slender loris demonstrates an urgent need for a detailed exploration within the range modeled by the present study. malabaricus corresponds with wetter climates, ranging from deciduous to evergreen forest types. lydekkerianus corresponds with a relatively drier climate, largely occupying deciduous and open-scrub forest types, whereas the modeled potential distribution of L. Among the 2 known subspecies, the modeled potential distribution of L. The potential geographic distribution of this subspecies appears to occupy a distinct and intermediate climate region running along the eastern fringe of the southern Western Ghats. Results indicate that the modeled potential distribution of a morphologically different and hitherto undescribed subspecies of slender loris is noticeably different in geographic space from the 2 known subspecies found within peninsular India. We utilized occurrence records of more than 300 confirmed sightings of slender lorises to model the species' potential geographic distribution by applying an ecological niche modeling (ENM) framework using a desktop genetic algorithm for rule-set prediction (GARP) algorithm.
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