The Agasthyamalai and Periyar-Srivilliputhur hills constitute the southernmost ranges of the Western Ghats. They contain unique ecosystems and species, and are acknowledged as high priority areas for conservation. These areas were historically part of a single, wildlife-rich forested landscape, but human pressure has reduced both animal numbers and connectivity, especially around the Shencottah gap. Large mammal movement between these ranges is increasingly rare owing to the rapid pace of habitat degradation and alteration in the intervening mosaic of multiple-use forests, estates and small settlements.
In these areas of low animal density, preserving connectivity between populations can help ensure long-term population viability. Small populations, which are at a higher risk of extinction due to chance events, (for example, an outbreak of disease, increase in hunting, etc) can be buffered against these if animals are able to move from other areas into the affected parts. Further, the natural movement of individuals and groups for foraging, mating or migration can also be restored. In the long term, the genetic effects of isolation can be mitigated.
In August 2008, we initiated a long-term research and conservation programme aimed at assessing and preserving connectivity between large mammal populations in this region. We are assessing large mammal distribution, habitat use and movement patterns. We will relate these to both ecological variables (such as habitat composition) and disturbance variables (such as resource extraction or linear barriers). This data will be used to identify movement corridors at both the local and landscape level. A key component of this study will be the use of a multi-species approach, so that the needs of a wide range of species can be incorporated into future conservation initiatives. Further, the surveys make use of appropriate methods to evaluate the efficacy of our interventions in achieving our conservation objectives. Our surveys are data intensive and are conducted within a robust analytical framework to ensure the reliability of inferences made from them.