Assessing the viability of tiger subpopulations in a fragmented landscape

Abstract

Summary1. 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. 2. 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. 3. 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). 4. 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. 5. 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 detectionnon-detection surveys combined with spatial modelling to provide timely information for conservation management.

Threatened predator on the equator: multi-point abundance estimates of the tiger Panthera tigris in central Sumatra

“…Compared to other studies using similar techniques our estimates of tiger densities in Sumatra are lower than expected, often , 1 tiger per 100 km 2 , even compared to similar habitat elsewhere (Karanth & Nichols, 1998;Kawanishi & Sunquist, 2004;Karanth et al, 2006;Linkie et al, 2006;Rayan & Mohamad, 2009; Table 5). Using spatially explicit capture-recapture models our estimates of tiger density were almost 50% lower compared to densities estimated with traditional capture-recapture models, a finding noted in other studies (Tredick & Vaughan, 2009;Obbard et al, 2010;Sharma et al, 2010;Gerber et al, 2012).…”

What are the roles of species distribution models in conservation planning?

“…For the conservation community focused on endangered species, these future SDMs are analogous to population habitat viability analysis (PHVA), where population parameters are used to determine the current population growth rate and then are projected into future generations in the presence of known stressors (Akçakaya & Sjögren-Gulve 2000;Linkie et al 2006;Redford et al 2011). PHVA workshops for stakeholders then explore the minimum and maximum levels for each stressor that allow population persistence over the projected time span.…”

Active adaptive conservation of threatened species in the face of uncertainty

“…Many threatened species now only persist in a small number of relatively isolated subpopulations (Harrison and Bruna 1999) and numerous management programs worldwide distribute resources between subpopulations in an attempt to ensure the persistence of threatened species (e.g., Sumatran tiger, Panthera tigris sumatrae [Linkie et al 2006]; Gunnison's Sage Grouse, Centrocerus minimus [Oyler-McCance et al 2001]; the golden lion tamarin, Leontopithecus rosalia [Pinto and Rylands 1997]; Caribbean staghorn coral, Acropora cervicornis [Vollmer and Palumbi 2007]; and Japanese woodland primula, Primula sieboldii [Washitani et al 2005]). Predictably, the number of subpopulations or areas available to implement management actions affects how learning can take place.…”