Modelling forest resilience in Hindu Kush Himalaya using geoinformation

Abstract

Resilience is the capacity of an ecosystem to absorb disturbance and undergo change while maintaining its essential structure, functions, identity and feedbacks. The forests of the Hindu Kush Himalayan (HKH) region are vulnerable to both natural and anthropogenic changes, and the forest land conversion and degradation. Using satellite-derived tree canopy cover percent data and precipitation as the explaining variable, we studied the forest cover resilience in a geospatial framework employing the logistic regression and polynomial equation fitting. Out of the 4.3millionkm2 geographical areas, 873,650km2 (20.20%) was under the forest in 2000 and experienced loss of 11,250km2 during 2000–2010. We could model the forest cover and treeless areas fairly than the scrub and grassland owing to the variation in precipitation pattern. The majority of the forest cover (59.3%) has been estimated to have less resilience owing to the receipt of <1650 mm of total annual precipitation, whereas only 375km2 forest area could change to scrub that shows the least resilience. About 94.4% of treeless areas were estimated to be stable, while only 1% (25,200km2) area could accommodate the grassland. The resilient forest areas estimated and observed, owing to the mapping and modelling protocols used in this study, shall be useful in conservation planning in the HKH region.