Assessment of inherent vulnerability of forests at landscape level: a case study from Western Ghats in India

Jagmohan Sharma (), Sujata Upgupta (), Rajesh Kumar (), Rajiv Kumar Chaturvedi (), G. Bala () and N H Ravindranath ()
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Jagmohan Sharma: Indian Institute of Science
Sujata Upgupta: Indian Institute of Science
Rajesh Kumar: Forest Survey of India
Rajiv Kumar Chaturvedi: Indian Institute of Science
G. Bala: Indian Institute of Science
N H Ravindranath: Indian Institute of Science

Mitigation and Adaptation Strategies for Global Change, 2017, vol. 22, issue 1, No 3, 29-44

Abstract: Abstract Assessment of vulnerability is an important step in building long-term resilience in the forestry sector. The objective of this paper is to present a methodological approach to assess inherent vulnerability of forests at landscape level. The approach involves use of vulnerability indicators, the pairwise comparison method, and geographic information system (GIS) tools. We apply this approach to assess the inherent vulnerability of forests of the Western Ghats Karnataka (WGK) landscape, which is a part of the Western Ghats biodiversity hotspot in India. Four vulnerability indicators, namely biological richness, disturbance index, canopy cover, and slope, are selected. We find that forests in 30, 36, 19, and 15 % grid points in this region show low, medium, high, and very high inherent vulnerability, respectively. The forest showing high and very high inherent vulnerability are mostly dry deciduous forests and plantations located largely on the eastern side of the landscape. We also find that canopy cover is one of the key indicators that determine the inherent vulnerability of forests, and natural forests are inherently less vulnerable than man-made plantations. Spatial assessment of inherent vulnerability of forests at landscape level is particularly useful for developing strategies to build resilience to current stressors and climate change in future.

Keywords: Forest; Indicators; Inherent vulnerability; Plantation; Resilience; Vulnerability assessment (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11027-015-9659-7

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