Indicator-based vulnerability assessment of forest ecosystem in the Indian Western Himalayas: An analytical hierarchy process integrated approach

Manoj Kumar,Naveen Kalra,Hukum Singh,Subrat Sharma,Praveen Singh Rawat,Ram Kumar Singh,Ajay Kumar Gupta,Pavan Kumar,N.H Ravindranath

doi:10.1016/j.ecolind.2021.107568

Abstract

Understanding the vulnerability of forests and its associated factors is crucial for the sustainable management of forested landscapes. The assessment of vulnerability of forests in the Indian Western Himalayan (IWH) region comprising the states of Jammu & Kashmir (J&K), Himachal Pradesh (HP) and Uttarakhand (UK) was done using six indicators of vulnerability in the form of biological richness index, disturbance index, forest canopy density, fire point intensity and forest extraction intensity of fringe forests. We express this assessment as the “indicator-based vulnerability”. The indicators were allocated weights by multi criteria analysis using analytical hierarchy process. The spatial extent of all of the selected indicators was mapped for the IWH region at a pixel resolution of 24 m and was integrated to find out the vulnerability for each pixel in a GIS environment. The study area was divided into 172 grids of size 0.5°, equivalent to the grid size of available climatic projections, out of which 67 grids were identified as the forest grids. The grids that have at least 5% forest cover were designated as the forest grids and the vulnerability assessment was done only for these grids. The final representation of vulnerability across forested grids of the IWH was done at a spatial resolution of 5' and 0.5° to categorise as low, medium, high and very high class. It was observed that the highest concentration of “very high” and “high” vulnerable grids of 5' size lies in the state of UK, comprising 32 and 31%, respectively. The aggregated values at 0.5° indicate that most of the grids of UK fall under very high vulnerability except for the few uppermost and lowermost grids falling under other categories. In J&K, most of the 5' grids fall under low vulnerability (41%), while medium, high and very high categories are 27, 25 and 7%, respectively. Similarly, out of total 28 grids of size 0.5°, only one grid is categorized as very high vulnerable, while 11 grids fall under high vulnerability. In HP, none of the grids of either size is categorized as very high vulnerable. It was observed that most of the high and very high vulnerable grids in the IWH are in the lower altitudes while higher altitudes have lesser magnitude of vulnerability. Forests occurring at a higher elevation such as the Alpine forests (dry, moist and sub-alpine) is the least vulnerable forests compared to other forest type groups of the IWH.

Highlights

The vulnerability assessment has been one of the most discussed topics in recent era for the physical, biological and social systems (Cuevas, 2011; Jurgilevich et al, 2017; Nguyen et al, 2017)
Having discussed facts in mind, we present an assessment for measuring vulnerability of a forest ecosystem with the objectives of (1) identification of the most prominent indicators of vulnerability, (2) assigning weights to selected indicators using analyt ical hierarchy process (AHP) and (3) integration of the indicators to map the spatial extent of vulnerability for a forest ecosystem in the Indian Western Himalayas (IWH)
As most of the climate change projections are available at 0.5◦ spatial resolution (Ahlstrom et al, 2012; Dufresne et al, 2013; Rogelj et al, 2012), authors have studied the vulnerability of forests under projected climate change scenarios at 0.5◦ spatial resolution (Upgupta et al, 2015)

Summary

Introduction

The vulnerability assessment has been one of the most discussed topics in recent era for the physical, biological and social systems (Cuevas, 2011; Jurgilevich et al, 2017; Nguyen et al, 2017). It has become a central concept in research and policy documents of climate change (Hinkel, 2011). Vulnera bility assessment has become the central theme of scholars to examine where, how and why a system would be vulnerable (McDowell et al, 2016; Smit and Wandel, 2006). The vulnerability literature is vast (Giupponi and Biscaro, 2015) and there is a growing interest for assessing vulnerability for environmental and socio-economic disci plines (Gupta et al, 2020; Kalra and Kumar, 2019; Kumar et al, 2019a, 2018a, 2018b, 2020a, 2020b, 2020c; Pokhriyal et al, 2020; Singh et al, 2020)

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