Integrating Soil Microbes and Large Perennial Grasses in a New Model
A new model called DayCent-CABBI has been developed by a research team to integrate soil microbes and the distinct physiological traits of large perennial grasses into the DayCent model. This new model aims to improve the representation of ecosystem dynamics and evaluate the sustainability of growing various bioenergy crops.
Soils play a crucial role in storing carbon, with about half of the carbon stored in ecosystems worldwide found in soils. Depending on factors such as climate, vegetation, and management practices, soils can act as either a source or sink of carbon. Natural climate solutions (NCS) offer a promising way to achieve net-zero emissions goals by removing carbon dioxide from the atmosphere and storing it in plant biomass and soil. Bioenergy feedstocks like large perennial grasses have the potential to build soil carbon and produce carbon-neutral biofuels and bioproducts, making them ideal candidates for NCS.
The DayCent model has been a valuable tool for researchers over the past 40 years to understand how climate, disturbances, and land management influence carbon and other fluxes in ecosystems. However, previous versions of the model did not explicitly account for soil microbes or the unique traits of large perennial grasses like miscanthus and switchgrass, limiting its ability to project the potential of these bioenergy crops as NCS.
By developing DayCent-CABBI, researchers have addressed these limitations and enhanced the model’s ability to simulate daily fluxes of carbon, nitrogen, and water between the atmosphere, vegetation, and soil. The new model now includes a live microbial biomass pool and a dead microbial biomass pool to better represent carbon cycling in soil. It also models different parts of perennial plants separately, allowing for more accurate simulation of carbon, nitrogen, and lignin content, as well as realistic litter chemistry and harvest options.
The research team tested DayCent-CABBI by simulating switchgrass and miscanthus at the University of Illinois Energy Farm from 2008 to 2049. The model demonstrated better agreement with historical data and showed a plateau in soil carbon by 2049, indicating its improved ability to assess the potential of perennial grasses as NCS. These advances are not only beneficial for the research team but also for stakeholders interested in estimating the carbon intensity of growing high-yielding perennial grasses for biofuel and bioproduct production.
Overall, the integration of soil microbes and refined plant traits in the DayCent-CABBI model represents a significant step forward in modeling ecosystem carbon dynamics and evaluating the sustainability of bioenergy crops.