Modeling the Impacts of Changes in Soil Microbes and Mosses on Arctic Terrestrial Ecosystem Carbon Dynamics
thesisposted on 16.08.2019 by Junrong Zha
In order to distinguish essays and pre-prints from academic theses, we have a separate category. These are often much longer text based documents than a paper.
The land ecosystems in northern high latitudes (>45° N) occupy 22% of the global surface and store more than 1600 Pg soil organic carbon. Warming in this region has been documented during the past decades. Warming-induced changes in regional carbon dynamics are expected to loom large in the global carbon cycle and exert large feedbacks to the global climate system. Numerous Earth System Models have been widely used to quantify the response of terrestrial ecosystem carbon dynamics to climatic changes. However, predictions of terrestrial ecosystem carbon responses to increasing levels of atmospheric carbon dioxide (CO2) and climate change is still uncertain due to model limitations. The limitations include relatively low levels of representation of ecosystem processes that determine the exchanges of water, energy, and carbon between land ecosystems and the atmosphere and omitting some key biogeochemical mechanisms. To improve model realism and provide a better projection of the Arctic carbon dynamics, this dissertation developed three new versions of a process-based biogeochemistry models that involve more fundamental processes of terrestrial ecosystems. First, microbial dynamics and enzyme kinetics that catalyze soil carbon decomposition have been incorporated into the extant terrestrial ecosystem model TEM to remedy the inadequate representation of soil decomposition process. Furthermore, a vital microbial life-history trait, microbial dormancy, has been implemented into previous microbial-based model to consider the impacts of microbial dormancy in modeling. Additionally, the role of moss in the Arctic terrestrial ecosystem carbon quantification was also demonstrated by incorporating moss and higher plant interactions in modelling.