New microbial model explains observed relationship between heterotrophic respiration and temperature.
This study developed a new model of microbial soil decomposition that successfully captured the changing relationship between temperature and microbial respiration during the growing season. We showed that the soil microbial response to plant inputs depends on the nitrogen content of the added plant material.
We developed a new model for predicting soil response to changes in soil temperature, moisture, plant inputs and stoichiometry. This model is simple and based on well-defined physical and biological properties, and could be developed to model microbial activity at larger scales.
Microorganisms that grow in the soil, like bacteria and fungi, affect how much carbon resides in the soil and how much is released to the atmosphere as CO2. Mathematical models used to make climate change predictions often struggle to capture the activity of soil microbes in realistic ways. This study uses well-established descriptions of water and temperature effects on soil microbes to predict rate of carbon and nitrogen cycling in the soil. The new model (called the Dual Arrhenius Michaelis-Menten-Microbial Carbon and Nitrogen Physiology, or DAMM-MCNiP), reproduces the changing relationship between temperature and microbial respiration during the growing season. The study also shows using a theoretical addition of root secretions that the microbial response depends on the nitrogen content of the added plant material. This model is simple and based on well-defined physical and biological properties, and could be developed to model microbial activity at larger scales.
Adrien Finzi / Rose Abramoff
Boston University / Lawrence Berkeley National Lab
email@example.com / firstname.lastname@example.org
U.S. Department of Energy, grants DE-SC0006916, DE-SC0012288, and DE-AC02-05CH11231; the National Science Foundation (DEB 1237491); U.S. Department of Agriculture grant 2014-67003-22073; and the American Association of University Women Doctoral Dissertation Fellowship.
R.Z. Abramoff, E.A. Davidson, A.C. Finzi. 2017. “A Parsimonious Modular Approach to Building a Mechanistic Belowground Carbon and Nitrogen Model,” JGR Biogeosciences, 122. 10.1002/2017JG003796
SC-23.1 Climate and Environmental Sciences Division, BER
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...]
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...]
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...]
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...]
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)