Assessing the viability of tiger subpopulations in a fragmented landscape

Abstract

Summary: Conservation managers require accurate and timely information on the occurrence, size and viability of populations, but this is often difficult for cryptic species living at low densities over large areas. This study aimed to provide such information for tigers in the 36 400‐km 2 Kerinci Seblat (KS) region, Sumatra, by identifying and assessing subpopulation viability under different management strategies. Tiger occurrence was mapped within a geographical information system (GIS) using repeat detection–non‐detection surveys to incorporate a function of detection probability into a logistic regression model. The landscape variables that influenced tiger occupancy were then used to construct a spatially explicit habitat model to identify core areas. The number of tigers within each core area was estimated by calculating the area of different forest types and their respective tiger densities as determined through camera trapping. The viability of each subpopulation was then assessed under different management scenarios using a population viability analysis (PVA). Tiger occurrence was negatively correlated with distance to public roads. Four core tiger areas were identified, all predominantly located within KS National Park, estimated to support subpopulations of 21, 105, 16 and three adult tigers, respectively. PVA showed that the three larger subpopulations could be demographically viable if well protected. However, if poaching removed ≥ 3 tigers per year, then only the largest subpopulation would not reach extinction within 50 years. Connectivity to this large subpopulation would ensure survival of the smaller subpopulations, through providing a source of tigers to offset poaching losses. Synthesis and applications. Our key management recommendations for tigers in the Kerinci Seblat region of Sumatra stress the importance of maintaining connectivity between the smaller areas and the larger area, and minimizing poaching within these smaller areas. More widely, our research has shown the feasibility of using detection–non‐detection surveys combined with spatial modelling to provide timely information for conservation management.