Patterns and drivers of tree carbon stocks in Kashmir Himalayan forests: implications for climate change mitigation

Abstract

BackgroundTemperate forests are major carbon sinks because of their high storage potential and low decomposition processes. We quantified tree carbon (TC) storage from 143 plots distributed across three major forest types of Kashmir Himalaya, relative to differences in ecological factors. Combined regression and Random Forest (RF) analysis were used to examine the distribution of TC stock along ecological gradients and recognize the role of driving factors on TC stocks.ResultsAmong the three forest types, sub-alpine (SA) forest was the primary TC sink, accounting for 228.73 t ha−1 of carbon, followed by mixed conifer (MC; 181.29 t C ha−1) and blue pine (BP; 133.04 t C ha−1) forests. The distribution of TC stocks among the three forest types differed significantly (χ2 = 18.87; P = 0.000). Relative carbon stock analysis demonstrated that Abies pindrow and Pinus wallichiana accounted 91% of TC stocks across the landscape. Basal area, mean diameter at breast height (DBH), elevation, disturbance and precipitation had significant effects on TC stocks in bivariate regression models. The RF model explained 86% of the variation; basal area interpreted 30.15%, followed by mean DBH (17.96%), disturbance complex (10.64%), precipitation (8.00%) and elevation (7.34%).ConclusionsKashmir Himalayan forests are significant carbon sinks as they store a substantial quantum of carbon in trees. Forest carbon, an essential climatic indicator, is determined by a complex interaction of other ecological variables, particularly stand structural features. The study provides insights into the role of these natural forests in climate change mitigation and in REDD+/national commitments to offset the carbon.