Linking microscale processes and macroscale fluxes using soil properties in a process-rich simulation.
Researchers from Pacific Northwest National Laboratory (PNNL) coupled fundamental soil properties with microbial physiology in a pore-scale simulation to predict how microbial respiration will vary under different moisture conditions.
By modeling soil microbial respiration response to moisture using a more fundamental understanding of the system, scientists from PNNL can improve our predictions of how different soils will respond biogeochemically to drought and inundation events like floods and extreme weather.
DOE’s PNNL researchers have observed for a long time a “sweet spot” where soils respire the most carbon dioxide when they aren’t too wet or too dry. However, the location of this zone seemed to vary across different soil types and it was difficult to predict.
In this study, scientists captured the underlying physical controls and microbial physiology in a computer simulation and generated a range of different respiration-moisture curves across different soil types. This demonstrated the distribution of these different moisture responses across soils and how those differences can be explained by specific soil properties. The findings will help us develop better models for soil biogeochemistry.
Contacts (BER PM)
Terrestrial Ecosystems Program, DOE BER
Pacific Northwest National Lab
This research was supported by the National Key R&D Program of China and DOE’s Office of Science, Biological and Environmental Research (BER) Division through the Terrestrial Ecosystem Science (TES) program.
Yan, Z., B. Bond-Lamberty, K. Todd-Brown, V. Bailey, S. Li, C. Liu, C Liu, “A moisture function of soil heterorophic respiration incorporating microscale processes.” Nature Communications volume 9(1) Article number: 2562 (2018). [DOI:10.1038/s41467-018-04971-6]
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]
May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]
May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]
May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]
Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]
List all highlights (possible long download time)