Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km2 of forest habitat was found to be only 21,290 km2. After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (F ST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost.

Data from: Prioritizing tiger conservation through landscape genetics and habitat linkages

The threat of habitat fragmentation and population isolation looms large over much of biodiversity in this human-dominated epoch. Species-rich South Asia is made particularly vulnerable by its high human density and anthropogenic habitat modification. Therefore, reliably estimating wildlife connectivity and the factors underpinning it become crucial in mitigating extinction risk due to isolation. We analysed peer-reviewed literature on connectivity and corridors for terrestrial mammals in South Asia to identify trends in connectivity research. We identify key research gaps and highlight future directions that may aid efforts to robustly study connectivity. We found a significant bias towards charismatic megafauna and their habitats. Methodologically, although we observed a range of approaches reflecting some of the advances and innovations in the field, several studies lacked data on animal movement/behaviour, leading to potentially biased inferences of how species disperse through human-modified landscapes. New avenues for connectivity research, though currently under-explored in South Asia, offer alternatives to the heavily used but less-reliable habitat suitability models. We highlight the advantages of landscape genetic methods that reflect effective dispersal and are made feasible through non-invasive and increasingly more cost-effective sampling methods. We also identify important gaps or areas of focus that need to be addressed going forward, including accounting for animal movement/behaviour, human impacts and landscape change for dynamic and adaptive connectivity planning for the future.

Trends in Wildlife Connectivity Science from the Biodiverse and Human-Dominated South Asia

Graph theory (GT) is extensively applied in the ecological network analysis. This review study aimed to examine GT in the field of ecological network analysis based on the following questions: In what areas are the articles focused?, what indexes or graph-based indicators have been thus far utilized in ecological network analysis?, and what aspects of ecological network analysis have been less considered in terms of the use of the GT indicators? To address these questions, a systematic literature review was conducted and the results showed that most of the articles in this field had been fulfilled in China, the United States, and France. This theory could have implications for more research on plants and mammals. In addition, 118 indicators were identified in the field of GT in the ecological network analysis. Among these indicators, the probability of connectivity (PC) and an integral index of connectivity (IIC) had been consistently exploited in most articles. Moreover, the results revealed the increasing trend of introducing the new indicators of GT to ecological network analysis, suggesting the applicability of GT in this context. Despite the importance of ecological network resilience, it has been less reflected from the GT perspective while it can be useful and efficient in analyzing the sustainability of ecological networks within this framework. The current trend of exploiting the GT indicators delineates three future lines of development, viz. (1) the GT use more widely in ecological network analysis, (2) emerging new and more precise indexes, and (3) new concerns mainly examining ecological network resilience. 

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Amit Aggarwal

Papers

A graph theoretic approach for modelling tiger corridor network in Central India-Eastern Ghats landscape complex, India