EAR-PF: Integrating scale-dependency of geomicrobial controls on soil C dynamics in predictive models

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Dr. Katherine Shek has been awarded an NSF EAR Postdoctoral Fellowship to carry out research and education plans at the University of New Hampshire under the mentorship of Dr. Adam Wymore. This study will improve our understanding of soil carbon dynamics under global change through identifying patterns in microbial composition and function. Current models aiming to predict soil carbon dynamics do not effectively represent the small-scale processes controlling emergent large-scale processes such as CO2 gas flux and organic carbon storage, because the small-scale processes are performed by complex microbial communities that can change across environmental gradients. Dr. Shek will address this discrepancy through a synthesis of large datasets available through ecological and Earth system monitoring networks describing geomicrobiome structure and emergent functions related to the carbon cycle. From this data synthesis, cross-scale patterns in geomicrobial processes will be integrated to improve the predictive power of carbon dynamics in Earth Systems Models. Better understanding of cross-scale interactions between geomicrobiome variability and carbon cycle processes will connect several research programs and disciplines addressing urgent challenges under climate change. For instance, characterizing general patterns linking geomicrobial processes with carbon cycling under different environmental contexts could inform policy makers, land managers and scientists aiming to predict the consequences of climate variability and change on carbon dynamics. Dr. Shek’s research and professional development plan includes application of machine learning techniques and training in biogeochemistry and data science, while presenting findings and communicating science with diverse audiences including both nonscientists and fellow researchers.Interactions between ecosystem structure and climate are difficult to characterize across environmental gradients due to the scale-dependency of ecological processes governing emergent biogeochemical outcomes, especially those acting on the micro scale. Earth’s largest terrestrial carbon pool is in soils, where diverse consortia of microorganisms control the turnover and stability of organic carbon through micro scale differences in metabolic activity, directly influencing Earth’s climate. Despite geomicrobial controls determining shifts in soil organic carbon distribution and stability, Earth Systems Models (ESMs) aiming to predict soil carbon dynamics under global change do not adequately represent these fine scale processes. Building an understanding of cross-scale interactions among factors controlling macro scale differences in soil carbon dynamics requires process-based modeling of geomicrobial functional profiles and how they change across environmental gradients. This project will leverage the robust microbial metagenomic and environmental datasets available through programs such as NEON, LTER and CZnet to build process-based microbial models that will improve our ability to predict soil carbon under global change. Dr. Shek will use machine learning algorithms to distill complex cross-scale geomicrobial and environmental patterns to characterize geomicrobiome-soil carbon dynamics across environmental gradients, and then integrate these patterns to improve soil carbon projections in process-based ESMs. This fellowship will enable Dr. Shek to synthesize an open-source, cross-network database linking biogeochemical measurements with metagenomic data for fellow Earth system and ecological researchers to utilize in future studies. This research contributes broadly to society’s general ability to project the stability and behavior of Earth’s ecosystems under global change by directly improving ESMs.This project is jointly funded by the Critical-Zone Collaborative Network Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.