Browsing by Subject "Carbon cycle"
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Item Dissolved organic matter in major rivers across the Pan-Arctic from remote sensing(2016-05) Griffin, Claire Genevieve; McClelland, James W.; Frey, Karen E; Gardner, Wayne S; Liu, Zhanfei; Shank, Gerald CClimate-driven changes in Arctic hydrology and biogeochemistry are impacting transport of water and water-borne material from land to ocean. This includes massive amounts of organic matter that are mobilized and exported from the pan-Arctic watershed via rivers each year. Dissolved organic matter (DOM), an important part of the Arctic carbon cycle, has received growing attention in recent years, yet long-term studies of riverine biogeochemistry remain rare in these remote and logistically challenging regions. Remote sensing of chromophoric dissolved organic matter (CDOM, the portion of the DOM pool that absorbs light), provides a unique opportunity to investigate variations in DOM in major Arctic rivers over multiple decades. CDOM is a useful proxy for dissolved organic carbon (DOC) and is essential to photochemical processes in surface waters. This dissertation presents the development and application of remote sensing regression models across six major Arctic rivers: the Kolyma, Lena, Mackenzie, Ob’, Yenisey and Yukon. Frozen, archival samples of CDOM were used to develop calibration data for remote sensing regressions. Remote sensing methods estimated CDOM with R2 of 85% across all rivers, although individual rivers varied in their predictability in association with sediment loading and hydrology. As with previous studies of Arctic systems, concentrations and export of CDOM and DOC were highest during spring freshet in most of these rivers. Interannual variability in DOM export may be linked to the Arctic Oscillation. Within the Mackenzie, Ob’, and Yenisey rivers, observations of DOM concentration and export were extended back to the 1980s, the first known empirical records of this length for Arctic rivers that span both continents. Although no pan-Arctic trends in CDOM export were detected, there is some evidence of long-term changes in riverine DOM. For example, discharge-specific CDOM concentrations decreased in the Yenisey River and increased in the Ob’ River. Additionally, CDOM concentrations increased over the past ~30 years within the Mackenzie River. This dissertation also includes results from experiments used to quantify the effects of cryopreservation on CDOM analyses, and potential approaches for ameliorating freezing effects. These experiments showed that freezing for preservation introduces some error into CDOM measurements, although these effects vary between river systems. Sonication may improve CDOM measurements in some river systems, but the effects of both cryopreservation and sonication should be quantified on a case-by-case basis. Overall, this dissertation work demonstrates that 1) remote sensing of CDOM is a viable tool for tracking fluvial DOM in the major Arctic rivers, 2) only the Mackenzie River showed significant increases in CDOM concentration from the 1980s to present and 3) long-term changes in discharge-specific CDOM concentrations have occurred in the Yenisey and Ob’ rivers. These long-term trends cannot be definitively linked to climate change, but may be related to effects of warming on permafrost, hydrology, and biogeochemistry within in Arctic watersheds with consequences for carbon cycling on both regional and global scales.Item Role of mesophyll CO₂ diffusion and large-scale disturbances in the interactions between climate and carbon cycles(2013-05) Sun, Ying, active 2013; Dickinson, Robert E. (Robert Earl), 1940-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.Item Simulating and quantifying land-surface biogeochemical, hydrological, and biogeophysical processes using the Community Land Model version 4(2013-08) Shi, Mingjie; Yang, Zong-liangCarbon and nitrogen cycles, the energy cycle, and the hydrological cycle interact with each other; all are crucial to atmosphere–land studies. Carbon and nitrogen cycle from the atmosphere to vegetation communities and soil micro-organisms through their transformation in inorganic and organic pools. Ecosystem equilibrium, which is usually disturbed by extreme events (e.g., fires or drought), depends on the speeds of carbon and nitrogen uptake and decomposition. Terrestrial biogeochemistry models typically require hundreds to thousands of years for carbon and nitrogen in various pools to reach steady-state solutions, which are generally a function of soil temperature and soil water. Hydrological processes such as the root transpiration/water removal and the cold-region infiltration with the soil ice freeze/thaw status involved affect soil water content and soil temperature, and regulate carbon- and nitrogen-stock variations. Last but not least, mineral dust, a type of atmospheric aerosol, alters surface radiation/energy balance, and may act as cloud condensation nuclei to modify precipitation rates and eventually the hydrological cycle. Therefore, we were motivated to investigate these processes in different ecosystems. Specifically, this research aims to 1) to elucidate the carbon- and nitrogen-pool adjustment processes in different ecosystems, 2) to evaluate how the root transpiration process affects ecosystem carbon exchange patterns in Amazonia, 3) to analyze the influence of soil impermeability, which is affected by the landscape freeze/thaw status in cold regions, on hydrological cycles at high latitudes, and 4) to explore the effects of surface vegetation distribution and model resolution on surface dust emissions. The Community Land Model version 4 (CLM4) was used in this study. We did numerical experiments in three environments: forest and grassland ecosystems, river basins in cold regions, and the Arabian Peninsula. Our main scientific findings are: 1) the adjustment time of the biogeochemistry components in CLM4 is longer for boreal forests than for other ecosystems, 2) with more water is lifted from deep soil, Amazonia ecosystems start to take up carbon during dry seasons, 3) the timing of boreal spring runoff simulations is improved by reducing the impermeable area underneath the snowpack, and 4) model-simulated dust emissions increase with model resolution as a result of the heterogeneities of vegetation cover and wind speed.