Ecological modelling for the conservation of Gluta travancorica Bedd. - An endemic tree species of southern Western Ghats, India

Abstract

Endemic species are highly adapted to grow exclusively in a specific geographical area. The goal of the current study is to determine the probable habitat distribution range of the narrowly endemic species Gluta travancorica. An ecological niche modelling is carried out, using four different models viz., BioClim, MaxEnt, Random Forest and Deep Neural Networks (DNN). A total of 506 G. travancorica cluster locations were surveyed and used for this study with thirty different ecogeographic, edaphic and bioclimatic environmental parameters. After a preliminary investigation using multi-collinearity analysis, soil parameter variables like pH, cation exchange capacity (CEC), silt and clay content are used for final modelling. Factor analysis of ecological niche revealed the soil parameters like pH, CEC, silt and clay content as the key predictors. The result is validated using true skill statistics, sensitivity, specificity, kappa statistic and AUC-ROC. Results of the present study show that DNN have exceptional prediction performance, demonstrated by its AUC score of 0.959. DNN model projected 32.37% (938.18 km2) of the study region to have a ‘highly suitable habitat’, whereas 67.63% (1960.82 km2) was classified as having ‘low habitat suitability’. Besides, back-to-field assessments have also proven DNN's potential in predicting the habitat suitability of G. travancorica. The study results will facilitate the prioritization of conservation and seedling restoration strategies. The forest range explored in this work is a component of one of the most important global biodiversity hotspots, and it has significant implications for regional biodiversity conservation.