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Dog in the matrix: Envisioning countrywide connectivity conservation for an endangered carnivore

Dog in the matrix: Envisioning countrywide connectivity conservation for an endangered carnivore Elevated rates of anthropogenic impacts on land‐use regimes have pushed terrestrial megafauna to the brink of extinction. Consequently, it is critical to adopt conservation approaches that safeguard individual populations while retaining connectivity among these populations. Conserving spatially structured populations of imperiled species at large scales is often complex; and the past decades have therefore seen a rise in spatial conservation prioritization exercises aimed at shaping landscape‐scale conservation programmes. We present a framework for informing nationwide connectivity conservation, linking ecological and administrative scales, to maximize relevance for management. We assessed connectivity of the endangered dhole Cuon alpinus among 155 potential source populations across India using a data‐driven approach combined with graph and circuit theory. We used clustering algorithms to identify ecologically meaningful conservation landscapes; within each landscape, we identified priority source populations based on their connectedness and quantified pixel‐specific habitat accessibility. We superimposed administrative boundaries on our findings to provide conservation recommendations at this management‐relevant scale. We first mapped potential dhole movement across India. Dhole populations fell within three primary clusters—Western and Eastern Ghats (WEG), Central Indian Landscape (CIL) and North‐East India (NEI)—of which NEI had the highest forest cover, most diffuse connectivity and lowest human density, while WEG had the highest protected area coverage and overall connectedness. Within each conservation landscape, we evaluated the relative importance of Protected Areas and accessibility to high‐quality patches. Parts of the Eastern Ghats had low habitat accessibility, yet high potential for dhole landscape connectivity. In 114 identified administrative units of priority for habitat restoration, we highlight those with low accessibility, that is, areas where restoration needs to be spatially targeted for maximum benefits. Synthesis and applications. We make recommendations for spatially informed habitat restoration to enhance dhole connectivity in India, highlighting the importance of improving matrix permeability where dhole movement is currently restricted. More broadly, the framework we present is useful across species and management contexts, as it combines spatial and administrative scales to make ecologically informed assessments of high relevance to management. Synergistically integrating species ecology, threats and administrative considerations in connectivity conservation plans can enhance success of species conservation programmes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Ecology Wiley

Dog in the matrix: Envisioning countrywide connectivity conservation for an endangered carnivore

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References (33)

Publisher
Wiley
Copyright
© 2022 British Ecological Society
ISSN
0021-8901
eISSN
1365-2664
DOI
10.1111/1365-2664.14048
Publisher site
See Article on Publisher Site

Abstract

Elevated rates of anthropogenic impacts on land‐use regimes have pushed terrestrial megafauna to the brink of extinction. Consequently, it is critical to adopt conservation approaches that safeguard individual populations while retaining connectivity among these populations. Conserving spatially structured populations of imperiled species at large scales is often complex; and the past decades have therefore seen a rise in spatial conservation prioritization exercises aimed at shaping landscape‐scale conservation programmes. We present a framework for informing nationwide connectivity conservation, linking ecological and administrative scales, to maximize relevance for management. We assessed connectivity of the endangered dhole Cuon alpinus among 155 potential source populations across India using a data‐driven approach combined with graph and circuit theory. We used clustering algorithms to identify ecologically meaningful conservation landscapes; within each landscape, we identified priority source populations based on their connectedness and quantified pixel‐specific habitat accessibility. We superimposed administrative boundaries on our findings to provide conservation recommendations at this management‐relevant scale. We first mapped potential dhole movement across India. Dhole populations fell within three primary clusters—Western and Eastern Ghats (WEG), Central Indian Landscape (CIL) and North‐East India (NEI)—of which NEI had the highest forest cover, most diffuse connectivity and lowest human density, while WEG had the highest protected area coverage and overall connectedness. Within each conservation landscape, we evaluated the relative importance of Protected Areas and accessibility to high‐quality patches. Parts of the Eastern Ghats had low habitat accessibility, yet high potential for dhole landscape connectivity. In 114 identified administrative units of priority for habitat restoration, we highlight those with low accessibility, that is, areas where restoration needs to be spatially targeted for maximum benefits. Synthesis and applications. We make recommendations for spatially informed habitat restoration to enhance dhole connectivity in India, highlighting the importance of improving matrix permeability where dhole movement is currently restricted. More broadly, the framework we present is useful across species and management contexts, as it combines spatial and administrative scales to make ecologically informed assessments of high relevance to management. Synergistically integrating species ecology, threats and administrative considerations in connectivity conservation plans can enhance success of species conservation programmes.

Journal

Journal of Applied Ecology – Wiley

Published: Jan 1, 2022

Keywords: circuit theory; connectivity; conservation landscapes; dhole; India; management; modularity; spatial prioritization

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