2017
DOI: 10.1111/gcb.13874
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Assessment of ecosystem resilience to hydroclimatic disturbances in India

Abstract: Recent studies have shown an increasing trend in hydroclimatic disturbances like droughts, which are anticipated to become more frequent and intense under global warming and climate change. Droughts adversely affect the vegetation growth and crop yield, which enhances the risks to food security for a country like India with over 1.2 billion people to feed. Here, we compared the response of terrestrial net primary productivity (NPP) to hydroclimatic disturbances in India at different scales (i.e., at river basi… Show more

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Cited by 80 publications
(44 citation statements)
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“…The value of Rd can be classified into four categories [29]: if Rd was greater than or equal to 1, the grid cell was considered to have resilience and it meant that the ecosystem can sustain its productivity…”
Section: Resilience Analysismentioning
confidence: 99%
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“…The value of Rd can be classified into four categories [29]: if Rd was greater than or equal to 1, the grid cell was considered to have resilience and it meant that the ecosystem can sustain its productivity…”
Section: Resilience Analysismentioning
confidence: 99%
“…The ecosystem resilience was considered as the ability of an ecosystem which could resist external disturbances (such as drought) and sustain the same structure and functions under changing conditions [19,49]. In this study, we used a dimensionless index (R d ) defined by Sharma et al [29,50] to quantify terrestrial ecosystem resilience to drought on a per-pixel basis:…”
Section: Resilience Analysismentioning
confidence: 99%
See 2 more Smart Citations
“…The collected data were manually examined to ensure that the coverage of cloud and snow was lower than 10%. Land cover classification map was obtained from 500-m MODIS land cover data (MCD12Q1) [37], which has been used in many studies to stratify vegetation types [38,39]. The terrain information was represented by the 30-m Shuttle Radar Topography Mission (SRTM) digital terrain model (DTM) data collected from the United States Geological Survey.…”
Section: Ancillary Datasetsmentioning
confidence: 99%