January 20 2016

12:00 LSB 2320

Uma Ramakrishnan
National Centre for Biological Sciences, Tata Institute of Fundamental Research

Why numbers are not enough: evaluating tiger survival through a genetic lens Why numbers are not enough: evaluating tiger survival through a genetic lens


Tigers are emblematic of conservation, and India harboring around 60% of the world’s wild tigers. We have used genetic data from wild populations to understand their relatively recent past and current connectivity in a hope to predict future trajectories. We explored population genetic variation in wild tigers and showed that 60-70% of global genetic variation is retained by India tigers, making it a stronghold for their conservation. This is despite a precipitous bottleneck 200 or so years ago. Data from historical skins supports this bottleneck, and also suggests a decrease in connectivity in the last 150 years. Recent genomic data help identify ‘tiger landscapes’ that could be targets of conservation action.
While the total numbers of tigers in India have increased due to focused conservation efforts, only 10 populations have more than 50 individuals, and the median population size is 19. Future survival is critically dependent on exchange between these fragmented populations. But is such connectivity possible given current models of economic development in India? I will spend most of my talk focusing on this question. In recent analyses, we used genetic data from 116 individuals from the Central Indian tiger landscape to infer how human footprints, agriculture and forests impact connectivity. We modeled landscapes 100 years into the future, and assessed impacts of different development scenarios on connectivity and extinction using spatially explicit landscape genetics simulations. Our results suggest that connectivity between populations will decrease with high risk of local extinction in many small and/or isolated populations. Decreasing extinction will require stepping-stone populations that act as corridors between larger populations. Our results can prioritize mitigation efforts associated with development activities, providing a link between science and policy.















































































































































































































































































































































































































































































































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