Predicting landscape connectivity for the Asian elephant in its largest remaining subpopulation

摘要: Landscape connectivity between protected areas is crucial for the conservation of megafauna. But often, corridor identification relies on expert knowledge that subjective and not spatially synoptic. analysis allows generalization when satellite tracking or genetic data are available. The Nilgiri Biosphere Reserve in southern India supports largest wild populations endangered Asian elephant Elephas maximus. Current understanding this region based corridors identified by experts, which empirically validated incongruent with each other. To more rigorously assess population elephant, we evaluated a combination three resistance layers dispersal abilities. models were combined contributions land cover, topographical slope, elevation, roads buildings. A explicit modeling tool predicted optimal movement as function factorial least-cost routes across maps. resistant kernel approach produced maps expected frequency through cell to define core areas. We conducted sensitivity determine influence dispersal. selected surface ability highest correlation observed densities. optimality using path randomization method. Eleven out 24 had values significantly higher than chance, while only two congruent teams. Areas corresponded well priority conservationists density model correlated surveys (Spearman's ρ = 0.85, n = 500, P ≪ 0.001). results provide first rigorous, synoptic evaluation reserve.