Understanding the Carbon Cycle in the Complex Terrain at Shale Hills Critical Zone Observatory
Open Access
- Author:
- He, Yuting
- Graduate Program:
- Meteorology and Atmospheric Science
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- July 16, 2019
- Committee Members:
- Kenneth Davis, Dissertation Advisor/Co-Advisor
Kenneth Davis, Committee Chair/Co-Chair
David Eissenstat, Outside Member
Chris Eliot Forest, Committee Member
Yuning Shi, Special Member
Chaopeng Shen, Committee Member
David Jonathan Stensrud, Program Head/Chair - Keywords:
- terrestrial carbon cycle
complex terrain
critical zone observatory
Biome-BGC
ecosystem modeling - Abstract:
- The terrestrial carbon (C) cycle remains the least constrained component in the global C cycle, partly due to the difficulty in quantifying C sources and sinks in complex terrain. Here I used observations at the Shale Hills Critical Zone Observatory and a biogeochemistry model, Biome-BGC, to study the spatial distribution of C stocks and fluxes in a first-order watershed. The model simulated the average C pools and fluxes in the watershed after constraining three model parameters (i.e. whole-plant mortality rate, N deposition and maximum decomposition rates of soil C pools) with observations. The model was also able to generate the observed spatial patterns of C pools in the watershed, with higher biomass and soil C in the valley and lower values on the ridgetop, though the model underestimated the ridgetop to valley differences. To improve the simulation of the spatial pattern of C stocks, I used a global sensitivity analysis (Sobol’) to target the most important model parameters that affect the C stocks and fluxes in complex terrain. Sensitivity analysis of the model Biome-BGC revealed that both the carbon pools and the spatial contrast of the carbon pools are sensitive to a small number of the ecophysiological parameters (e.g. Specific leaf area and C allocation ratio between stem C and leaf C). I then incorporated available measurements (i.e. automated soil respiration data) at Shale Hills CZO to constrain the important model parameters and thus improved the simulation of C fluxes in Shale Hills by about 26% (mean absolute difference).