Influence of Covariates:
The null model that did not include any covariates for detection or occupancy performed poorly and ranked the lowest (AIC=175.48). Model performance improved after we included the covariates alone or in combination according to our priori hypothesis. Summed AIC weight of covariates from the most competitive models was highest for termite followed by fruit, disturbance, tree cover and equal for EVI Wi =0.12 and TRI (Figure 3). Average model specific β-coefficient value from the top competitive models for termites, fruit, disturbance, terrain ruggedness and vegetation productivity indicated their positive influence on sloth bear occupancy whereas negative beta coefficient for tree cover indicated its negative association with sloth bear habitat occupancy (Figure 4) .