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Biology subjects

Goswami, V. R.

Publications and source records attributed to Goswami, V. R..

2 recordsLinked to original sources

Tiger diet in Ranthambore Tiger Reserve: how do metabarcoding and mechanical sorting compare?

Accurately describing large carnivore diets is critical for understanding trophic interactions and identifying targeted conservation strategies. Most studies have relied on traditional dietary analysis based on mechanical sorting and identification of undigested prey remains, a method known to be error-prone and ecologically biased. Here, we compare the diet of tigers using non-invasively collected scats from Ranthambore Tiger Reserve in India, analysed using mechanical sorting and DNA metabarcoding. We found that DNA metabarcoding outperformed mechanical sorting in detecting higher overall prey and rare prey species occurrences, uncovering higher prey diversity. The study revealed that tigers were subsisting mainly on wild prey such as sambar and chital. However, domestic cattle contributed the highest relative prey biomass to their diet. Our findings demonstrate that DNA metabarcoding is an efficient, effective and powerful approach that overcomes several of the previously identified biases of the mechanical sorting approach and provides an accessible and particularly useful tool for carnivore dietary studies based on non-invasive samples. The increased frequency of livestock depredation relative to previous studies highlights the need for active mitigation measures to secure this population.

ecology↗

Identifying the potential for sustainable human wildlife coexistence by integrating willingness to coexist with habitat suitability models

Persistence of large mammals in the Anthropocene depends on human willingness to coexist with them, but this is rarely incorporated into habitat suitability or conservation priority assessments. We propose a framework that integrates human willingness-to-coexist with habitat suitability assessments to identify areas of high potential for sustainable coexistence. We demonstrate its applicability for elephants and rhinos in the socio-ecological system of Maasai Mara, Kenya, by integrating spatial distributions of peoples willingness-to-coexist based on Bayesian hierarchical models using 556 household interviews, with socio-ecological habitat suitability mapping validated with long-term elephant observations from aerial surveys. Willingness-to-coexist was higher if people had little personal experience with a species, and strongly reduced by experiencing a species as a threat to humans. The sustainable coexistence potential framework highlights areas of low socio-ecological suitability, and areas that require more effort to increase positive stakeholder engagement to achieve long-term persistence of large herbivores in human-dominated landscapes.

ecology↗