Addressing methodological issues in the study of tiger metapopulation dynamics in Western Ghats, India
Keywords: tiger ecology
statistical ecology
Bayesian methods
population ecology
tiger
statistical methods
tiger conservation
spatial capture-recapture

The tiger (Panthera tigris) is a globally endangered large carnivore of high conservation importance. It is cryptic, wide-ranging and naturally occurs at low population densities. Any study of its metapopulation in real landscapes is faced with a suite of methodological constraints because the temporal and spatial scale of study is large. The scope presented for developing, testing and reviewing methods, whether they are analytical, practical or conceptual, in such a context is wide: ranging from statistical methods to laboratory techniques to field methodologies to software products and methods, all relevant to tiger research and conservation endeavours.
Framed within the ecological theme of assessing population dynamics of species within patchy environments, and with the source-sink view of tiger metapopulations, this thesis investigates the abundance estimation question of tigers and their prey at multiple scales within a 38,000 square kilometre tiger landscape in the Western Ghats, India.
While the emphasis is firmly rooted in the development of statistical methods, software products and field methodologies, it also brings in research in laboratory techniques to bear on the abundance and distribution questions on hand. In specific, this thesis:
1. Advances our understanding of spatial capture-recapture methods - a statistical methodology being widely used over the last five years for density estimation.
2. Develops a new field-based method for estimating the density of tiger prey, specifically when they occur at low densities, using an occupancy-based approach. The results of this exercise show much promise and offers a way of tackling the abundance estimation question in unmarked, rare species.
3. Develops a software product called SPACECAP to make novel spatial capture-recapture methods accessible to wildlife biologists, ecologists and park managers. The software is adequately tested and provides users with the necessary summary statistics of density and related parameters, along with the necessary diagnostic tools in order facilitate accurate interpretation of parameters.
4. Develops a Bayesian inferential approach to estimating tiger density in areas of low abundance by bringing together data sets from multiple sources (camera trapping images and faecal DNA samples, in our case) to strengthen inference about tiger density. Results from this approach suggests that it takes a relatively small increase in sampling effort to bring about large reductions in the variance of density estimates.
5. Investigates a long-standing controversy of index-calibration experiments at large scales. The theoretical models and the empirical testing with tiger sign-encounter data at macroecological scales demonstrate the relative futility in employing simplified and direct linear models using the R-squared statistics, because there are latent sampling process parameters which considerably weaken inference.
6. Develops a spatial capture-recapture model that facilitates investigation of unanswered questions lying at the interface between behavioural and population ecology of carnivores. This is done by introducing the attraction-repulsion spatial arrangements of carnivores into spatial capture-recapture models.
Nearly 70 percent of the world’s tigers remain in less than 100,000 square kilometres of habitat today. Yet, we lack sufficient methodological tools to reliably estimate their population dynamic parameters. This thesis provides a toolbox of advanced methods to make these assessments more reliable and, more importantly, accessible. It is envisioned that researchers and practical conservation managers will both benefit with this toolbox.