Many regions are experiencing unprecedented change in their climatic conditions. Temperature and precipitation are the major determinants of vegetation structure and biomass. Understanding how vegetation respond to change in temperature and precipitation will be key for predicting the status of the terrestrial Carbon sink and many interconnected ecosystem responses under future climate scenarios. In my study, I analyze long-term data sets at different spatial scales to identify patterns and processes of interactions between climate and vegetation.

In my first chapter, I address growing concerns of vegetation degradation in the Trans-Himalayas. This cold-arid ecosystem is a climate-change hotspot because it is experiencing rapid rise in temperature, and is also getting progressively wetter. While warmer and wetter conditions may favor plant growth, yet, there are widespread concerns of degradation in this ecosystem. I evaluated whether long-term trends in vegetation change, i.e., greening or browning, can inform management concerns over degradation. I analyzed satellite-derived vegetation datasets (NDVI) at six spatial scales: MODIS (250 m, 500 m, 1 km, and 5.5 km), SPOT (1 km), and GIMMS (8 km). Results indicate browning (degradation) in the spring and greening in late summer. This pattern was consistent across all spatial scales. The timing and location of degradation did not coincide with human land-use (livestock grazing), suggesting vegetation trends may be more strongly related to climate than to human land use. Overall, the results show the importance of evaluating the consistency of inter- and intra-annual vegetation trends across different spatial/temporal scales for interpreting degradation.

In my second chapter, I address how spatial and temporal variation in climatic factors can influence vegetation phenology across the greater Trans-Himalayan landscape. Global warming has caused relaxation of thermal constraints for plant growth in cold regions, which include both high-altitude and high-latitude landscapes. However, this hypothesis has found poor support globally, including the Trans-Himalayas where temperature alone could not explain the long-term greening/browning patterns. An alternate hypothesis is to examine the effect of water limitation across the Trans-Himalayan landscape. I investigated this by analyzing the plant phenological response in terms of change in shape of the annual growth pattern – a unimodal curve that is represented mathematically by a double-logistic function. I analyzed long-term changes in geometric properties of vegetation phenology, e.g., skewness and kurtosis of the double-logistic curve. This long-term phenological analysis showed that the plants are reaching their peak biomass earlier in the growth season, and also attaining a higher peak biomass. These changes were explained by variation in snowfall and rainfall. This study shows the differential effect of snow and rain in determining the phenological trends in mountain ecosystems.

In my last chapter, I explore whether long-term trends in global vegetation change is linked to thermal constraints on the biochemical steps in photosynthesis. A key aspect is temperature-sensitivity of net photosynthesis, which declines above 32 oC due to thermal sensitivity of participant enzymes, particularly Rubisco Activase. I find that warming over the past four decades has altered the window of thermally suitable days for photosynthesis and plant growth, through effects attributable to this enzyme’s thermal-sensitivity. This explains satellite-records of long-term vegetation trends during 1982-2015 (greening/browning) for nearly 80-million km2 across the world Change in temperature was more successful in explaining vegetation trends than simultaneous change in water-stress over the same period. This match (Bayesian probability) between thermal-sensitivity of enzymes and vegetation response could not be achieved by random chance. Comparatively, match against browning was lower than for greening, due to confounding effects (pests, fire, logging). However, I found that the water-stress could reverse the trends expected from temperature, especially in the warm regions. These results can help improve our understanding and prediction of future changes in terrestrial productivity, and the fate of the terrestrial carbon-sink, as they link processes occurring at molecular and planetary scales.