B035
New Mechanisms, Feedbacks, and Approaches for Predicting Global Biogeochemical Cycles under Climate Change and Intervention
Session ID#: 160067
Session Description:
Predictions of future atmospheric CO2 levels, an essential objective of Earth system science, are influenced by global carbon and nutrient cycles, climate interactions, and feedbacks to the Earth system. Relevant processes operate at different spatial and temporal scales and vary across terrestrial, coastal, and marine ecosystems. Biogeochemical feedbacks may be altered by anthropogenic and natural disturbances, including tropospheric O3, changes in nutrient and hydrological cycles, eutrophication, acidification, land cover/land use change, prescribed and wildland fires, and potential climate intervention strategies. This session focuses on integrated understanding of terrestrial and marine feedback mechanisms that impact the predictability of all aspects of the Earth system, methods for evaluating and benchmarking process representations in Earth system models, approaches for constraining future climate projections (e.g., emergent constraints), and novel applications of artificial intelligence and machine learning to improve predictive understanding of global biogeochemical cycles.
Co-Sponsor(s):
Index Terms:
0428 Carbon cycling [BIOGEOSCIENCES]
0439 Ecosystems, structure and dynamics [BIOGEOSCIENCES]
1615 Biogeochemical cycles, processes, and modeling [GLOBAL CHANGE]
1622 Earth system modeling [GLOBAL CHANGE]
Primary Convener: Forrest M. Hoffman, Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States
Conveners: Cheng-En Yang, University of Tennessee, Civil and Environmental Engineering, Knoxville, TN, United States, Jessica Fay Needham, Lawrence Berkeley National Laboratory, Climate Sciences, Berkeley, CA, United States and Enhui Liao, Princeton University, Department of Geosciences, Princeton, NJ, United States
Student/Early Career Convener: Jessica Fay Needham, Lawrence Berkeley National Laboratory, Climate Sciences, Berkeley, CA, United States
Disentangling abiotic and biotic drivers of plant nutrient resorption efficiencies at global scales (1047611)
Gabriela Sophia1, Silvia Caldararu2, Benjamin Stocker3 and Sönke Zaehle1, (1)Max Planck Institute for Biogeochemistry, Jena, Germany, (2)Trinity College Dublin, Dublin, Ireland, (3)ETH Zürich, Department of Environmental System Science, Zürich, Switzerland
Microbial roles in the terrestrial carbon dynamics during 1901-2016 as simulated by the CLM-Microbe model (1049136)
Liyuan He1, Jorge L. Mazza Rodrigues2, Melanie A Mayes3, Chun-Ta Lai4, David Lipson1 and Xiaofeng Xu1, (1)San Diego State University, Department of Biology, San Diego, CA, United States, (2)University of California Davis, Department of Land, Air and Water Resources, Davis, CA, United States, (3)ORNL, Oak Ridge, TN, United States, (4)San Diego State University, San Diego, CA, United States
Climate and Carbon Responses to a Restoration Scenario of Idealized CO2 Emissions Reversal (1059666)
Charles D Koven, Lawrence Berkeley National Laboratory, Berkeley, CA, United States, Benjamin M Sanderson, Center for International Climate and Environmental Research Oslo, Oslo, Norway and Abigail L. S. Swann, University of Washington, Atmospheric Sciences and Biology, Seattle, United States
Aboveground Plant-Herbivore Interactions Drive Root Decomposition in the Sub-Arctic (1063900)
Emily Chavez1, Trisha Atwood2, Bonnie G Waring3, Karen H. Beard4 and Jaron Adkins1, (1)Utah State University, Logan, UT, United States, (2)Utah State University, Department of Watershed Sciences and The Ecology Center, Logan, United States, (3)Imperial College Lodon, Lodon, United Kingdom, (4)University of Alaska Anchorage, Anchorage, United States
Machine learning–based observation-constrained global wildfire projections (1072475)
Jiafu Mao1, Yan Yu2, Stan Wullschleger1, Anping Chen3, Xiaoying Shi1, Yaoping Wang1, Forrest M. Hoffman4, Yulong Zhang5 and Eric M Pierce1, (1)Oak Ridge National Laboratory, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge, United States, (2)Peking University, Atmospheric and Oceanic Sciences, Beijing, China, (3)Colorado State University, Fort Collins, United States, (4)Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States, (5)University of Tennessee, Institute for a Secure & Sustainable Environment, Knoxville, United States
Using causal analysis and machine learning to evaluate the CO2 fertilization of global photosynthesis (1074423)
Yanghui Kang1, Maoya Bassiouni1, Max Gaber1,2, Xinchen Lu1,3 and Trevor F Keenan1,3, (1)University of California, Berkeley, Department of Environmental Science, Policy, and Management, Berkeley, United States, (2)University of Copenhagen, Department of Geosciences and Natural Resource Management, Copenhagen, Denmark, (3)Lawrence Berkeley National Laboratory, Climate and Ecosystem Sciences Division, Berkeley, United States
Goose Herbivory Controls Greenhouse Gas Fluxes by Altering Soil Conditions in Sub-Arctic Wetlands (1079194)
Jaron Adkins, Utah State University, Logan, UT, United States, Bonnie G Waring, Imperial College Lodon, Lodon, United Kingdom, Karen H. Beard, University of Alaska Anchorage, Anchorage, United States and Trisha Atwood, Utah State University, Department of Watershed Sciences and The Ecology Center, Logan, United States
Quantifying Extremes in Net Biospheric Production and Attribution to Compound Climate Drivers (1081438)
Bharat Sharma, Northeastern University, Civil and Environmental Engineering Department, Boston, MA, United States, Jitendra Kumar, Oak Ridge National Laboratory, Oak Ridge, TN, United States, Auroop Ganguly, Northeastern University, Boston, MA, United States and Forrest M. Hoffman, Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States
Contemporary Climate-Fire Feedbacks and the Potential Amplification of Future Fire Emissions (Invited) (1109984)
Douglas C Morton1, Yang Chen2, Niels Andela3, Louis Giglio4, Melanie B Follette-Cook5, Lesley Ott6, Pam Wales7, Robert D Field8, Elizabeth Brooke Wiggins9,10, Yue Li2 and James T. Randerson11, (1)NASA Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD, United States, (2)University of California Irvine, Department of Earth System Science, Irvine, United States, (3)BeZero Carbon, London, United Kingdom, (4)University of Maryland College Park, Geographical Sciences, College Park, MD, United States, (5)NASA GSFC, Greenbelt, United States, (6)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (7)University of Maryland College Park, College Park, MD, United States, (8)University of Aizu, Aizu-Wakamatsu, Japan, (9)NASA Langley Research Center, Hampton, VA, United States, (10)University of California, Earth System Science, Irvine, United States, (11)University of California Irvine, Earth System Science, Irvine, United States
Climate change may increase both plant drought stress and productivity (Invited) (1124108)
Anna T Trugman, University of California Santa Barbara, Department of Geography, Santa Barbara, CA, United States and Gregory Ross Quetin, Stanford University, Department of Earth System Science, Stanford, CA, United States
Atmospheric Feedbacks Modulate Land Parameters’ Influence on Land Surface Fluxes (1126032)
Claire Zarakas1, Abigail L. S. Swann2, Amy Liu3, Daniel Kennedy4, Katherine Dagon4, David M Lawrence4, Gordon B Bonan4, Danica L. Lombardozzi4 and Charles Koven5, (1)University of Washington, Atmospheric Sciences, Seattle, WA, United States, (2)University of Washington, Atmospheric Sciences and Biology, Seattle, United States, (3)University of Washington, Atmospheric Sciences, Seattle, United States, (4)National Center for Atmospheric Research, Boulder, CO, United States, (5)University of California Berkeley, Energy and Resources Group, Berkeley, United States
Understanding and predicting the interannual variability (IAV) of the global terrestrial carbon cycle (1129330)
Jiaming Wen, Cornell University, School of Integrative Plant Science, Soil and Crop Sciences Section, Ithaca, NY, United States, Jakob Runge, German Aerospace Center DLR Jena, Institute of Data Science, Jena, Germany, Andreas Gerhardus, German Aerospace Center, Institute of Data Science, Jena, Germany and Ying SUN, Cornell University, School of Integrative Plant Science, Soil and Crop Sciences Section, Ithaca, United States
Using Statistical Learning Methods to Accelerate Model Parameter Sensitivity Experiments (1132559)
Shamik Bhattacharya, North Carolina State University Raleigh, Raleigh, NC, United States, Forrest M. Hoffman, Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States, Bharat Sharma, Northeastern University, Civil and Environmental Engineering Department, Boston, MA, United States, Gaurab Kc, Oak Ridge National Lab, Oak Ridge, United States and Nathan Collier, Oak Ridge National Laboratory, Oak Ridge, United States
Compound marine heatwaves and ocean acidity extremes (1147776)
Thomas L. Frolicher1, Friedrich Burger2 and Jens Terhaar2, (1)University of Bern, Oeschger Center for Climate Change Research, Bern, Switzerland, (2)University of Bern, Climate and Environmental Physics, Bern, Switzerland
Improving Seasonal Patterns of Carbon Fluxes in a Dynamic Vegetation Model Using Carbon Isotopes (1147829)
Brenden Fischer-Femal, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Benjamin Poulter, NASA Goddard Space Flight Center, Greenbelt, United States, Sourish Basu, NASA Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, United States, John B Miller, NOAA, Global Monitoring Laboratory, Boulder, United States, Scott Lehman, Institute for Arctic and Alpine Research, University of Colorado, Boulder, CO, United States, Ashley Ballantyne, University of Montana, Missoula, MT, United States and Leonardo Calle, Regrow Ag, Durham, United States
Integrating omics, machine learning, and process-based land surface model to predict environmental feedbacks of microbial functions and its implication for soil carbon emission (1166451)
Yang Song1, Changpeng Fan1 and Xiaojuan Yang2, (1)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (2)Oak Ridge National Laboratory, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge, United States
A Differentiable Ecosystem Modeling Framework for Highly Efficient Forward and Inverse Problems (1173600)
Doaa Aboelyazeed1, Chaopeng Shen1, Chonggang Xu2 and Forrest M Hoffman3, (1)Pennsylvania State University Main Campus, Department of Civil and Environmental Engineering, University Park, United States, (2)Los Alamos National Laboratory, Earth and Environmental Sciences Division, Los Alamos, NM, United States, (3)Oak Ridge National Lab, Oak Ridge, United States
Proposed changes to the ILAMB Scoring Methodology (1192249)
Nathan Collier, Oak Ridge National Laboratory, Oak Ridge, United States, Forrest M. Hoffman, Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States and David M Lawrence, National Center for Atmospheric Research, Boulder, CO, United States
Impact of a northward migration of the ITCZ on terrestrial ecosystem function in North Africa (1197600)
Mingquan Mu1, James Tremper Randerson1 and Forrest M. Hoffman2, (1)University of California Irvine, Department of Earth System Science, Irvine, United States, (2)Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States
