MSA: Self-organizing principles for upscaling ecosystem water and heterotrophic carbon fluxes

Texas A&M Agrilife Research, College Station TX

Investigators

Abstract

Climate change and land management are affecting soils globally, with detrimental consequences for soil health and biodiversity, plant productivity, and climate regulation. However, the loss of soil organic carbon and its emission as carbon dioxide, which is a major input of carbon to the atmosphere regulated by soil microorganisms (known as heterotrophic respiration), remains one of the most uncertain terrestrial carbon fluxes. This research aims to understand how heterotrophic respiration varies across biomes and climates depending on macroscopic environmental variables (for example, rainfall and vegetation productivity) and from the ecosystem to continental scale, by combining experimental data from multiple observational networks and mathematical models of microbial growth and metabolism. This analysis is helping to map heterotrophic respiration at regional to continental scales and assess the potential impact of climate change on soils and ecosystems by enabling more accurate estimates of soil organic carbon losses. The effort allows environmental policymakers working on ecosystem management and sustainability to plan effective conservation strategies, especially for those regions that are most sensitive to climate change. The project will train diverse students and will support the development of new interdisciplinary curricular material at the intersection of microbiology, hydrology, and environmental science and engineering. This research is guided by the hypothesis that at the ecosystem scale the ratio of annual heterotrophic respiration to plant productivity (a dimensionless measure related to the soil carbon budget) is primarily correlated with the aridity index (a dimensionless measure of wetness/dryness). The project combines process-based microbial growth modeling with flux tower datasets and field-based measurements of soil and ecosystem carbon fluxes from NEON and other regional and global networks to explore, guided by the π theorem of dimensional analysis, the existence of fundamental laws explaining the variability in water and carbon fluxes across biomes. A parsimonious process-based microbial model is being used to analyze observations and statistically link microbial parameters to macroscopic environmental drivers and identify key dimensionless groups governing the large-scale dynamics. The macroscopic relations between heterotrophic respiration and environmental drivers are then used to reconstruct large-scale carbon fluxes based on the spatial structure of primary environmental drivers. 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.