Reliable prediction of climate change and its impact on and feedbacks from terrestrial carbon cycles requires realistic representation of physiological and ecological processes in coupled climate-carbon models. This is hampered by various deficiencies in model structures and parameters. The goal of my study is to improve model realism by incorporating latest advances of fundamental eco-physiological processes and further to use such improved models to investigate climate-carbon interactions at regional to global scales. I focus on the CO₂ diffusion within leaves (a key plant physiological process) and large-scale disturbances (a fundamental ecological process) as extremely important but not yet in current models. The CO₂ diffusion within plant leaves is characterized by mesophyll conductance (g[subscript m]), which strongly influences photosynthesis. I developed a g[subscript m] model by synthesizing new advances in plant-physiological studies and incorporated this model into the Community Land Model (CLM), a state-of-art climate-carbon model. I updated associated photosynthetic parameters based on a large dataset of leaf gas exchange measurements. Major findings are: (1) omission of g[subscript m] underestimates the maximum carboxylation rate and distorts its relationships with other parameters, leading to an incomplete understanding of leaf-level photosynthesis machinery; (2) proper representation of g[subscript m] is necessary for climate-carbon models to realistically predict carbon fluxes and their responsiveness to CO₂ fertilization; (3) fine tuning of parameters may compensate for model structural errors in contemporary simulations but introduce large biases in future predictions. Further, I have corrected a numerical deficiency of CLM in its calculation of carbon/water fluxes, which otherwise can bias model simulations. Large-scale disturbances of terrestrial ecosystems strongly affect their carbon sink strength. To provide insights for modeling these processes, I used satellite products to examine the temporal-spatial patterns of greenness after a massive ice storm. I found that the greenness of impacted vegetation recovered rapidly, especially in lightly and severely impacted regions. The slowest rebound occurred over moderately impacted areas. This nonlinear pattern was caused by an integrated effect of natural regrowth and human interventions. My results demonstrate mechanisms by which terrestrial carbon sinks could be significantly affected and help determine how these sinks will behave and so affect future climate. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/21525 |
| Date | 10 October 2013 |
| Creators | Sun, Ying, active 2013 |
| Source Sets | University of Texas |
| Language | en_US |
| Detected Language | English |
| Format | application/pdf |
Page generated in 0.0021 seconds