This study aims to map and discriminate rangeland degradation from the effects of precipitation variability and thereby identify the driving forces of degradation in the grazing areas of Ghiling in Upper Mustang, Nepal. Landsat MSS, TM, ETM, and SPOT images covering the years 1976-2008 were analyzed. 8. km resolution NOAA NDVI from 1981to 2006 were used to identify the long term interrelationship between vegetation greenness and precipitation variability. The use of time series residual of the NDVI/precipitation linear regression to normalize the precipitation effect on vegetation productivity and identify the long term degradation was extended at the local scale. A weighted grazing pressure surface model was developed combining information from satellite images, topography, forage availability and detailed field work data on points of livestock concentration, herders' ranking of forage quality and grazing pattern in each pasture unit. The grazing pressure of a given site was defined as the product of annual net stocking density and the inverse of the total friction of livestock movement. While annual precipitation was found as the dominant factor for the interannual vegetation variability, degradation in Upper Mustang was the result of grazing induced change and some localized natural processes. ?? 2010 Elsevier Inc.
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