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EESA Researchers Develop Open-Source Code for Modeling Soil Biogeochemistry2 min read

by Christina Procopiou on April 22, 2022

Climate and Ecosystem Sciences Division

Figure 11.2. The seven soil biogeochemical network subunits (S1, S2, S3, S4, S5, S6, S7) connect the seven classes of processes described above (P1–P7) via transport and substrate competition. MS is “mineral surface,” MOM is “monomeric organic molecule,” E is “enzyme,” POM is “polymeric organic molecule,” X is “microbial exudate,” and Z is a “complementary substrate.

 

Senior scientist William Riley and several EESA collaborators have published a chapter of a new book on soil biogeochemistry. Published in March, the book Multi-Scale Biogeochemical Processes in Soil Ecosystems: Critical Reactions and Resilience to Climate Changes was developed to provide a state-of-the-art overview of research in soil biogeochemical processes and strategies for greenhouse gas mitigation under climate change.

The EESA contributors authored chapter 11, Next-Generation Soil Biogeochemistry Model Representations: A Proposed Community Open-Source Model Farm (BeTR-S), to provide an open-source software package designed to simulate the processes that they consider to be among the most important in soil biogeochemistry. Riley explained that their contributions mark an important development in being able to accurately portray soil biogeochemical processes that play an important role in the global climate. 

“The system is very complex and until now there has been no universally available software to analyze these interactions,” said Riley. “In the real world, microbial processes in the soil and mineral surface interaction processes are happening all the time but it’s difficult and time consuming for scientists to incorporate them in a numerical model. With this open-source model that we have developed, we have made it easier for scientists to explore their own hypotheses on how soil biogeochemical processes affect soil carbon cycling, and ultimately how those processes interact with climate.”

EESA Staff Scientist Jinyun Tang developed the open-source code, and Riley, EESA research scientists Qing Zhu and Nick Bouskill, and former postdoc fellow Rose Abramoff contributed to the chapter. Carlos Sierra from the Max Planck Institute in Jena, Germany is also a co-author. This code is being applied by the Belowground Biogeochemistry Scientific Focus Area project led by EESA Senior Scientist Margaret Torn and by EESA scientists involved in the global land model ELM, which is a component of E3SM. 

 

News & Events

Chun Chang Places Second in Annual Berkeley Lab Pitch Competition3 min read

January 18, 2023

Commercializing Berkeley Lab inventions is an important part of the Lab’s mission, and one that requires strong communication skills. For example, Lab inventors need to be able to pitch their ideas to external partners and potential funders.  The annual Berkeley Lab Pitch Competition occurred on October 27, 2022 and is a part of an entrepreneurship…

EESA Scientists Collaborate With Universities to bring Environmental Science Research Opportunities and Training to Students Underrepresented in STEM3 min read

January 13, 2023

  EESA researchers are collaborators in three of the 41 projects awarded in December by DOE through its Reaching a New Energy Sciences Workforce (RENEW) initiative.  RENEW aims to build foundations for research at institutions that have been historically underrepresented in the Office of Science (SC) research portfolio. The initiative provides opportunities for undergraduate and…

New Report Explores Revolutionary Environmental Artificial Intelligence Infrastructure5 min read

January 10, 2023

In a collaborative effort between the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) and DOE’s Advanced Scientific Computing Research (ASCR) program, as well as with community experts, the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop was held from October through December 2021. BER developed the process as the Model-Experiment paradigm, or ModEx, and a report released this fall outlines the key takeaways of last year’s event.

A Q&A With Postdoc Kunxiaoja Yuan3 min read

January 4, 2023

  Kunxiaojia Yuan received her Bachelor’s of Engineering in remote sensing and Ph.D. in geographic information engineering from Wuhan University. She is a postdoctoral researcher in EESA, with a research focus on global carbon, energy, and water cycle analysis and model evaluation using machine learning and causal inference. What motivated you to pursue a postdoc…

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