Socio-environmental vulnerability to climate change in mountain landscapes depends upon multiple factors that can vary across altitude zones. However, there is limited knowledge on specific indicators suitable for assessing socio-environmental vulnerability that address altitude-related variations. This study systematically analysed important components of vulnerability and mapped them by weight for four altitude zones in the Indian Himalayas. Indices focusing on components of the three different dimensions of vulnerability (adaptive capacity, exposure, sensitivity) were identified based on the literature. Data on these different indices were then collected through a pre-tested questionnaire-based survey of 403 randomly selected households in the four altitude zones (<1000 (low), 1000–1500 (middle), 1500–2000 (high), >2000 m a.s.l. (very high)) in the Garhwal Himalaya, India. Components of vulnerability dimensions were assessed and significantly contributing components were identified by Principal Component Analysis (PCA). An entropy method was used to weight the dimensions of vulnerability for the different altitude zones. Vulnerability was estimated based on the Manush approach of human development index. The data were used to produce a spatial map based on a proposed Spatial Social Vulnerability Index (SSEVI). SSEVI was proposed based on social and environmental indicators of vulnerability with a mix of spatial indicators to generate spatially bound vulnerability. The results indicated that communities in the middle and high altitude zones (1000–2000 m a.s.l.) were more vulnerable (score 0.32 and 0.31, respectively) than those in the low and very high zones (score 0.29 and 0.30, respectively). Greater vulnerability was mainly due to high exposure to extreme events and less adaptive capacity, which can affect agricultural production negatively, in combination with high population density in middle-altitude communities. There was lower pressure on natural resources and better connectivity in the low altitude zone (<1000 m a.s.l.), reducing vulnerability. The spatial SSVI map clearly revealed vulnerable hotspots, suggesting that government supported adaptation measures should not be similar across the altitude gradient in the Indian Himalayas, but should be based on available resources, pressure and livelihood options for achieving sustainability under climate change.

Mapping socio-environmental vulnerability to climate change in different altitude zones in the Indian Himalayas

Donatella Valente
Writing – Review & Editing
;
Irene Petrosillo
Writing – Original Draft Preparation
;
2020-01-01

Abstract

Socio-environmental vulnerability to climate change in mountain landscapes depends upon multiple factors that can vary across altitude zones. However, there is limited knowledge on specific indicators suitable for assessing socio-environmental vulnerability that address altitude-related variations. This study systematically analysed important components of vulnerability and mapped them by weight for four altitude zones in the Indian Himalayas. Indices focusing on components of the three different dimensions of vulnerability (adaptive capacity, exposure, sensitivity) were identified based on the literature. Data on these different indices were then collected through a pre-tested questionnaire-based survey of 403 randomly selected households in the four altitude zones (<1000 (low), 1000–1500 (middle), 1500–2000 (high), >2000 m a.s.l. (very high)) in the Garhwal Himalaya, India. Components of vulnerability dimensions were assessed and significantly contributing components were identified by Principal Component Analysis (PCA). An entropy method was used to weight the dimensions of vulnerability for the different altitude zones. Vulnerability was estimated based on the Manush approach of human development index. The data were used to produce a spatial map based on a proposed Spatial Social Vulnerability Index (SSEVI). SSEVI was proposed based on social and environmental indicators of vulnerability with a mix of spatial indicators to generate spatially bound vulnerability. The results indicated that communities in the middle and high altitude zones (1000–2000 m a.s.l.) were more vulnerable (score 0.32 and 0.31, respectively) than those in the low and very high zones (score 0.29 and 0.30, respectively). Greater vulnerability was mainly due to high exposure to extreme events and less adaptive capacity, which can affect agricultural production negatively, in combination with high population density in middle-altitude communities. There was lower pressure on natural resources and better connectivity in the low altitude zone (<1000 m a.s.l.), reducing vulnerability. The spatial SSVI map clearly revealed vulnerable hotspots, suggesting that government supported adaptation measures should not be similar across the altitude gradient in the Indian Himalayas, but should be based on available resources, pressure and livelihood options for achieving sustainability under climate change.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/441139
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