CAREER: Scaling Complexities in Soil Biogeochemistry

University Of Florida, Gainesville FL

Investigators

Abstract

This NSF CAREER award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Too much carbon (C) in the atmosphere causes the Earth to warm, while C in the soil improves water retention and nutrient availability. C in the atmosphere is produced through burning fossil fuels and also as a byproduct of decomposition of plant matter by microorganisms in soil. As a result, soil C is directly connected to that in the atmosphere. Earth system models (computer simulations) struggle to predict whether soil C will increase or decrease over the next 100 years. Some simulations predict huge increases in soil C, leading researchers to hope that soils will help to mitigate continued CO2 emissions. By contrast, other simulations predict that soils will release more C, leading to a feedback loop that will cause atmospheric C to increase even if CO2 emissions are greatly reduced. Research in this NSF CAREER project will improve predictive understanding of the C cycle and global warming by adding details to the simulations about how C moves through soil, as well as by pulling together more data to help calibrate and validate simulations. The project will also develop and promote a useful terminology to more accurately describe the detailed processes to be modeled in computer simulations, as well as provide research training for graduate and undergraduate students. This project will expand predictive understanding of soil C dynamics by connecting traditional soil C models to a process-rich understanding via a new multi-scale modeling framework. Traditional soil C models divide soil C into pools; C then leaves a pool at a rate proportional to the C in that pool. While this captures the observed dynamics in incubation studies, the parameterization remains difficult to predict, a priori, for a given soil type, relying on soil organic C stocks and incubated respiration rates for both parameterization and validation. By representing processes like microbial dynamics and mineral-organic interactions more explicitly in non-linear models, and linking these process-explicit models to the traditional linear soil C models via numerical experiments and mathematical analysis, this work will be able to incorporate non-traditional measurements to inform traditional model parameterizations. In this project, soil measurements will be interconnected from primary open data archives in repositories and held by U.S. government agencies to support an expanded predictive understanding of soil carbon dynamics. This project will also spearhead development of shared language (ontology) with a democratized governance structure via data-centered communities of practice linking researchers across soil projects internationally. Training opportunities for graduate and undergraduate students will be integrated with the research and outreach activities. By linking established and new understanding of soil C dynamics with the rich legacy of soil data, results from this project will help policy makers to better manage activities related to C stocks and emissions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.