Towards a Comprehensive Understanding: Unveiling the Impact of Trait Variation on Plant-Microbe Interactions in Estuarine Marsh Carbon Cycling Models

Estuarine marshes, essential and intricate ecosystems, provide crucial services such as carbon sequestration, coastal protection, and habitat support for diverse species. The role of plant-microbe interactions in the carbon cycling and storage of estuarine marshes is pivotal. Despite recent advancements in mechanistic understanding, there remains a research gap regarding the specific impacts of these biotic interactions compared to abiotic factors on carbon cycling within estuarine marsh ecosystems, hindering a comprehensive understanding. Recent studies emphasize the usefulness of process-based models in representing dynamics between plants and microbes in estuarine marshes. Specifically, trait-based models prove instrumental in quantifying the influence of different plant functional types on carbon sequestration rates. While current models often use average trait values to parametrize plant functional types, emerging research suggests that incorporating a range of trait values, reflecting natural variation, could enhance predictive accuracy. To address this, we compare the predictions of a process-based model of soil organic matter decomposition that includes plant type-specific effects using average trait values versus trait ranges. Based on this example, we propose an innovative process-based marsh ecosystem model that explicitly considers the influence of trait variation on complex interactions among plants, soil microbes, and abiotic factors.Our study outlines the systematic evaluation of this model against field observations spanning a salinity and water level gradient in estuarine marshes. The outcomes of this study contribute significantly to advancing our understanding of these dynamic ecosystems, addressing research gaps, and refining the predictive capabilities of ecosystem models in estuarine environments.