Prediction of Potential Areas of Crop Damage by Wild Animals in Nilambur Forest Divisions, Southern Western Ghats, India
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Supplementary Files

Correlation matrix
Questionnaire survey sheet
PDF

Keywords

Crop Damage
Ordinary Kriging
Conflict Hotspots.

How to Cite

Nair, R. P., & Jayson, E. A. (2021). Prediction of Potential Areas of Crop Damage by Wild Animals in Nilambur Forest Divisions, Southern Western Ghats, India. Journal of the Bombay Natural History Society (JBNHS), 118, 125–130. https://doi.org/10.17087/jbnhs/2021/v118/149970

Abstract

Department of Statistics and Mathematics, Vertebrate Pest Management, College of Agriculture, Professor Jayashankar Telangana State Agricultural University (PJTSAU), Rajendranagar, Hyderabad 500030, Telengana Crop damage by wild animals is a major problem for conservation management in forest fringes. Studies of humanwildlife interactions encompass recognizing the affected areas and understanding the magnitude of the conflict. In this research study, ordinary kriging (spherical model) in the spatial analyst tool of ArcMap v.10, GIS Software Package, was used to predict the areas of crop damage by wild animals in Nilambur Forest Divisions, Kerala, India. Baseline data for the analysis was collected using a structured questionnaire survey of 300 households. Statistical models were prepared by logistic regression analysis using seven explanatory variables, which are supposed to influence the prediction of potential areas of crop loss in Nilambur Forest Divisions. The best models (cumulative weight>0.95) were selected to estimate the probabilities of crop loss with the help of Corrected Akaike Information Criterion (AICC). The number of crop-damaging animal species (β = 14.71, 95% CI [12.799, 16.621]) and duration of residence (β = -0.031, 95% CI [0.086, 0.148]), reported in the survey are the two variables that have a strong effect on the prediction of crop loss. The conflict hotspots in terms of crop loss to wild animals and its magnitude were identified on the map to plan and improve management efforts for mitigation.
https://doi.org/10.17087/jbnhs/2021/v118/149970

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