Quantifying Arctic Terrestrial Ecosystem Carbon Dynamics Using Mechanistically-Based Biogeochemistry Models and In Situ and Satellite Data
Date of Award
Doctor of Philosophy (PhD)
Earth, Atmospheric, and Planetary Sciences
Committee Member 1
Melba M. Crawford
Committee Member 2
Laura C Bowling
Committee Member 3
Terrestrial ecosystems of northern mid-to-high latitudes (45°-90°N) play a critical role in global carbon cycling and climate system feedbacks, given the massive carbon storage in the region and the amplification effects due to year-round and seasonal snow covering. This region has vast area of peatlands with a large amount of soil organic carbon. It has experienced dramatic climatic and environmental changes in recent decades, and the changes are expected to continue. This dissertation aims to quantify the Arctic carbon dynamics under these changes using mechanistically-based biogeochemistry models and in situ and remotely sensed data.
In the Arctic, snow pack modifies soil and carbon dynamics in the region due to its insulation effects. This dissertation first incorporated these effects by introducing a snow model into an existing soil thermal model in a biogeochemistry modeling framework, the Terrestrial Ecosystem Model (TEM). The coupled model was then used to quantify snow insulation effects on carbon (C) and soil thermal dynamics in the 45°-90°N region for the historical period of 2003-2010 and the future period of 2017-2099 under two future climate scenarios. The revised model captured the snow insulation effects and improved the estimates of soil thermal dynamics and the land freeze-thaw as well as terrestrial ecosystem carbon dynamics. Historical mean cold-season soil temperature at 5cm depth driven with satellite-based snow data was 6.4℃ warmer in comparison with the original model simulation. Frozen area in late spring was estimated to shrink mainly over eastern Siberia, in central to eastern Europe, and along southern Canada in November. During each non-growing season in the historical period, 0.41 Pg more soil C was released due to warmer soil temperature estimated using the new model. During 2003-2010, the revised model estimated that the region accumulated 0.86 Pg less C due to weaker gross primary production, leading to a regional C loss at 0.19 PgC/yr. The revised model projected that the region will lose 38-51% of its permafrost area by 2100 and continue to be a C source under the low emission scenario (RCP2.6), but to be gradually transitioning into a weak sink in the latter half of the 21st century under the high emission scenario (RCP8.5).
In the Arctic, wetlands cover relatively large area, especially in the state of Alaska. Wetlands terrestrial ecosystems in Alaska cover ~177,000 km2, an area greater than all the wetlands in the remainder of the United States. They are important to carbon dynamics of Alaska terrestrial ecosystem as a whole as well as regional warming potential. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO2) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1 km-resolution for the historical period (1950-2009) and future projection period (2010-2099). Simulations estimated that wetland ecosystems of Alaska lost 175 TgC in the historical period. Ecosystem C storage in 2009 was 5556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO2 and biogenic methane (CH4) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 TgC/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 TgC/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO2 fertilization (~5% per 100 ppmv increase) and by increases in air temperature (~1% per oC increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH4 emissions among the simulations (~15% per oC increase). Ecosystem CO2 sequestration offset the increase in CH4 emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, this forcing will be expected to ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO2, (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH4 emissions to increases in soil temperature.
Ecosystem models are widely used to quantify CH4 dynamics from natural wetlands. However, recent model inter-comparison projects suggested that there have been large disagreements among model simulations, particularly disagreements that came from uncertain model algorithms. My dissertation research also evaluated the performance of different algorithms of CH4 production, consumption and transport in reproducing the measured CH4 fluxes at northern peatland sites. A set of different algorithms were integrated into a methane biogeochemistry model within the Terrestrial Ecosystem Model. The ensemble of CH4 production algorithm simulations indicated that methanogenesis based on soil organic matter content represented by NPP yielded the largest daily variation and tended to over-estimate CH4 emissions, while simulation based on the amount of heterotrophic respiration represented by different soil litter pools provided the best fit of estimates at the two sites investigated. Estimates based on soil CH4 concentration were in between the other two approaches. The two methanotrophy algorithms differed in whether oxygen supply is a limiting factor in soils, and yielded similar CH4 consumptions. Ebullition events estimated with the two CH4 ebullition algorithms were comparable in their timing and duration, with higher ebullition CH4 fluxes yielded from algorithm considering pressure effects than CH4 concentration based algorithm. This study highlights the need to refine algorithms to quantify methane cycling in northern peatland ecosystems.
Lyu, Zhou, "Quantifying Arctic Terrestrial Ecosystem Carbon Dynamics Using Mechanistically-Based Biogeochemistry Models and In Situ and Satellite Data" (2018). Open Access Dissertations. 2012.