| Summary: | In this thesis, I tried to understand the patterns and processes of vegetation trends at different spatial scales and resolution. The spatial variability in vegetation trends was related to inter and intra-annual changes in climate, mainly, temperature and precipitation. In this thesis, I applied non-parameteric linear regression (Sen’s slope) to calculate trends in vegetation and climatic variables. The relationship between long-term vegetation trends and climate shifted between seasons in Trans-Himalaya. Phenological response to climate change can determine the strength and direction of feedback between the biosphere and the earth’s climate system. I evaluated the influence of changes in temperature and precipitation on vegetation phenology in the Central Asian highlands. The Central Asian highlands consists of arid and tundra climatic regions. Arid regions experience higher evapo-transpirational stress compared to tundra regions. Therefore, vegetation response to changes in climate can differ between arid and tundra regions. The changes in phenology was calculated by analyzing the changes in shape of uni-modal curve, which represents the vegetation annual biomass. Long-term changes in peak, skewness and kurtosis of the uni-modal curve correspond to peak biomass, timing of the peak biomass and length of the vegetation period respectively. Overall, arid regions showed higher changes in plant phenology compared to tundra with higher increase in peak biomass, earlier peaking and shorter vegetation period. Arid regions experienced higher temperature rise, but tundra regions experienced increase in snow and rain. The vegetation-climate relationship was evaluated using multiple linear regression and Cannonical Correlation Analysis. Both these analysis showed that the temperature and precipitation had an opposite effect on vegetation phenology. Warming conditions were related to earlier peaking and shortening the length of the vegetation period; while increase in precipitation was related to delayed peaking and ...
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