Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (4 results)

  • Thesis
  • Peer Reviewed
UC Davis Electronic Theses and Dissertations (2022)

Methane (CH4) emissions from Arctic polygonal tundra are spatially heterogeneous due to the complex soil hydrology. This spatial heterogeneity in CH4 emissions requires a reliable upscaling approach to reach accurate regional CH4 budgets in the Arctic tundra. Additionally, Arctic regions have been warming two to four times faster than the global average in recent decades. CH4 emission from the Arctic is increasing under climate warming. However, interactions among temperature, soil water table and vegetation complicate a full understanding of emission rates and their magnitude in a changing climate. In this dissertation, I applied the CLM‐Microbe model to examine microtopographic impacts on CH4 and CO2 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low‐centered polygon (LCP) center, LCP transition, LCP rim, high‐centered polygon (HCP) center, HCP transition, and HCP rim. Low‐elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high‐elevation and drier landscape types (rims and HCP center). Substrate availability for methanogenesis was identified as the most important factor determining CH4 emission. Upscaled CH4 emissions at the eddy covariance (EC) domain using an area‐weighted approach were underestimated by 20% and 25% at daily and hourly time steps. Combined with three footprint algorithms, I upscaled CH4 fluxes from a plot level to EC domains (200 m × 200 m) for three sites in Utqiaġvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo). Three footprint algorithms are the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. DF performed better than HF and GF algorithms in capturing the temporal variation in daily CH4 flux in each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH4 flux during 2013-2015 were predominately explained by air temperature (67-74%), followed by precipitation (22-36%). Spatial heterogeneities in vegetation and elevation dominated spatial variations in CH4 flux for all EC domains despite relatively weak differences in simulated CH4 flux among three footprint algorithms. Finally, I projected CH4 emissions during 2016-2100 for all these five sites under three Shared Socioeconomic Pathways (SSP) scenarios derived from three climate models. CH4 emission exhibited a stronger response (630 - 850% increase) under SSP5-8.5 than under SPP1-2.6 and SSP2-4.5, likely supported by a simultaneous enhanced precipitation-induced expansion of anoxic conditions for methanogenesis. All three CH4 transport pathways (i.e. diffusion, ebullition, and plant-mediated transport) are increasing by 2100, and ebullition contributed most to CH4 emissions under three SSP scenarios across five sites. Temperature sensitivity for CH4 emission differed using three climate models (i.e., BCC-CSM2-MR, CESM2, and EC-Earth3) with a Q10 range of 2.7-60.9 under SSP1-2.6, 3.8-17.6 under SSP2-4.5, and 5.7-17.2 under SSP5-8.5. This study advanced our understanding of the mechanisms of current and future CH4 emissions in the highly heterogeneous Arctic landscape. The CLM-Microbe model was testified as a powerful tool that can simulate CH4 flux at both plot and landscape scales at a high temporal resolution, upscale terrestrial CH4 flux integrated with an appropriate algorithm, and project future CH4 emissions in Arctic landscapes under different climate scenarios.

    Cover page: Multi-scale Modeling of Arctic Methane Cycling Using the CLM-Microbe Model
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2024)
    The positive Arctic–methane (CH 4 ) feedback forms when more CH 4 is released from the Arctic tundra to warm the climate, further stimulating the Arctic to emit CH 4 . This study utilized the CLM-Microbe model to project CH 4 emissions across five distinct Arctic tundra ecosystems on the Alaska North Slope, considering three Shared Socioeconomic Pathway (SSP) scenarios using climate data from three climate models from 2016 to 2100. Employing a hyper-resolution of 5 m × 5 m within 40,000 m 2 domains accounted for the Arctic tundra’s high spatial heterogeneity; three sites were near Utqiaġvik (US-Beo, US-Bes, and US-Brw), with one each in Atqasuk (US-Atq) and Ivotuk (US-Ivo). Simulated CH 4 emissions substantially increased by a factor of 5.3 to 7.5 under the SSP5–8.5 scenario compared to the SSP1–2.6 and SSP2–4.5 scenarios. The projected CH 4 emissions exhibited a stronger response to rising temperature under the SSP5–8.5 scenario than under the SSP1–2.6 and SSP2–4.5 scenarios, primarily due to strong temperature dependence and the enhanced precipitation-induced expansion of anoxic conditions that promoted methanogenesis. The CH 4 transport via ebullition and plant-mediated transport is projected to increase under all three SSP scenarios, and ebullition dominated CH 4 transport by 2100 across five sites. Projected CH 4 emissions varied in temperature sensitivity, with a Q 10 range of 2.7 to 60.9 under SSP1–2.6, 3.8 to 17.6 under SSP2–4.5, and 5.7 to 17.2 under SSP5–8.5. Compared with the other three sites, US-Atq and US-Ivo were estimated to have greater increases in CH 4 emissions due to warmer temperatures and higher precipitation. The fact that warmer sites and warmer climate scenarios had higher CH 4 emissions suggests an intensified positive Arctic–CH 4 feedback in the 21st century. Microbial physiology and substrate availability dominated the enhanced CH 4 production. The simulated intensified positive feedback underscores the urgent need for a more mechanistic understanding of CH 4 dynamics and the development of strategies to mitigate CH 4 across the Arctic.
      Cover page: Intensified Positive Arctic–Methane Feedback under IPCC Climate Scenarios in the 21st Century
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2019)
      Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.
        Cover page: Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2019)
        Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.
          Cover page: Large loss of CO2 in winter observed across the northern permafrost region
          Top