Earlier events :: 2014 :: STUDENT Poster

Distribution of a Caenophidian Snake, Xylophis captaini (Gower & Winkler, 2007) in the Western Ghats, India.

Presented by
Jins V J
Salim Ali Centre For Ornithology And Natural History
Authors
Subramanian Bhupathy, V. J. Jins, Santhanakrishanan Babu And Joyce Jose

Introduction: What conservation problem or question does your study address?

Spatial distribution pattern, range of species and the factors that regulate them are prerequisite for developing conservation plan. We update the distribution of little known Captain’s Wood Snake (Xylophis captaini) using ecological niche model based on new observations in the Western Ghats and collation of literature. The habitat and extent of its distribution across elevation of the hill range, and the conservation status of this species are also assessed.

Methods: What were the main research methods you used?

We surveyed along the south-western slopes of the Agasthyamalai Biosphere Reserve (ABR) from March 2012 to December 2013 using Time constrained visual encounter survey. Known localities of X.captaini from literature and primary data obtained during the present study in ABR were considered for analysis. The Maximum Entropy (MAXENT) algorithm was applied to predict the extent of geographic distribution of the species using presence only data. Twenty-five environmental variables, which are biologically meaningful to the study species, were considered for analysis including 19 bioclimatic variable (WorldClim dataset), elevation, slope and aspect, and MODIS tree, bare and herb cover. MAXENT has been applied to predict and quantify the extent of suitable habitats available for the species and to estimate the probable distribution of this species across the area of interest, especially the areas not covered during the survey.

Results: What are your most important results?

The MAXENT model showed that the predicted distribution of X. captaini as south of Thodupuzha (09o58’N, 76o38’) of the Kerala State. The precipitation seasonality has highest predictive gain when used in isolation and it appears to be the most important variable for the predicted model.The area of occurrence and occupancy of the species is estimated to be 3153 sq km and 1800 sq km respectively, which qualifies for listing under ‘Vulnerable category’ of the IUCN Redlist.

Discussion: What are your important discussion points and what is the relevance of your results to conservation (if any)?

Pending data on the sub-criteria such as fragmentation and decline in area of its occurrence and occupancy, we propose for ‘Near-Threatened’ category. More surveys are essential for validating the model and predicted distribution of the species. The present study highlights the utility of niche models in assessing the distribution of cryptic and little known species in biodiversity rich areas such as the Western Ghats.