B23J-03
Terrestrial carbon storage dynamics: Chasing a moving target

Tuesday, 15 December 2015: 14:10
2010 (Moscone West)
Yiqi Luo, University of Oklahoma Norman Campus, Norman, OK, United States and NIMBioS Carbon working group and OU Eco-Lab
Abstract:
Terrestrial ecosystems have been estimated to absorb roughly 30% of anthropogenic CO2 emissions. Past studies have identified myriad drivers of terrestrial carbon storage changes, such as fire, climate change, and land use changes. Those drivers influence the carbon storage change via diverse mechanisms, which have not been unified into a general theory so as to identify what control the direction and rate of terrestrial carbon storage dynamics. Here we propose a theoretical framework to quantitatively determine the response of terrestrial carbon storage to different exogenous drivers. With a combination of conceptual reasoning, mathematical analysis, and numeric experiments, we demonstrated that the maximal capacity of an ecosystem to store carbon is time-dependent and equals carbon input (i.e., net primary production, NPP) multiplying by residence time. The capacity is a moving target toward which carbon storage approaches (i.e., the direction of carbon storage change) but usually does not attain. The difference between the capacity and the carbon storage at a given time t is the unrealized carbon storage potential. The rate of the storage change is proportional to the magnitude of the unrealized potential. We also demonstrated that a parameter space of NPP, residence time, and carbon storage potential can well characterize carbon storage dynamics quantified at six sites ranging from tropical forests to tundra and simulated by two versions (carbon-only and coupled carbon-nitrogen) of the Australian Community Atmosphere-Biosphere Land Ecosystem (CABLE) Model under three climate change scenarios (CO2 rising only, climate warming only, and RCP8.5). Overall this study reveals the unified mechanism unerlying terrestrial carbon storage dynamics to guide transient traceability analysis of global land models and synthesis of empirical studies.