Abstract

Conservation planning of a threatened species essentially requires information on its present population and extent of distribution. Ecological niche modeling (ENM) is a suitable machine learning technique to predict potential distribution of a species enabling to identify suitable habitat for conservation action. The present study undertook distribution modeling of Vanda thwaitesii, a notified endangered orchid species of the Indian Western Ghats and Sri Lanka using maxent software. Geographical coordinates of 54 occurrence points at 1 km resolutions gathered during the study were utilized for modeling. A total of 37 variables including bioclimatic, topographical, and seasonal climate subjected to principal component analysis extracted into three components based on temperature and precipitation. Four representative variables from each component in all possible combinations resulted consistent output showing distribution of the species extending from Gavi in Periyar Tiger Reserve of Kerala to Chikkamagalur of Karnataka. Habitat suitability was confined to the cooler regions receiving an average 3,400 mm annual mean precipitation, 22.70C annual mean temperature, and 290 mm summer precipitation. A total of 2,557 km2 in Kerala and Karnataka mostly outside protected forests demonstrated as the highly suitable habitats. Silent Valley National Park, Idukki Wildlife Sanctuary, Periyar Tiger Reserve, and Brahmagiri Wildlife Sanctuary in addition to a few reserve forests hold sufficient area for reinforcement of diversity of V. thwaitesii from vulnerable locations. The present study revealed niche modeling as a useful tool to find suitable habitats for V. thwaitesii in the Western Ghats.

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