Cohort Marsh Equilibrium Model (CMEM): History, Mathematics, and Implementation

Author:

Vahsen M. L.12ORCID,Todd‐Brown K. E. O.3ORCID,Hicks J.3,Pilyugin S. S.4ORCID,Morris J. T.5ORCID,Holmquist J. R.6ORCID

Affiliation:

1. Department of Biological Sciences University of Notre Dame Notre Dame IN USA

2. Department of Wildland Resources Utah State University Logan UT USA

3. Department of Environmental Engineering Sciences University of Florida Gainesville FL USA

4. Department of Mathematics University of Florida Gainesville FL USA

5. Department of Biological Sciences University of South Carolina Columbia SC USA

6. Smithsonian Environmental Research Center Edgewater MD USA

Abstract

AbstractMarsh accretion models predict the resiliency of coastal wetlands and their ability to store carbon in the face of accelerating sea level rise. Most existing marsh accretion models are derived from two parent models: the Marsh Equilibrium Model, which formalizes the biophysical relationships between sea level rise, dominant macrophyte growth, and elevation change; and the Cohort Theory Model, which formalizes how carbon mass pools belowground contribute to soil volume expansion over time. While there are several existing marsh accretion models, the application of these models by a broader base of researchers and practitioners is hindered because of (a) limited descriptions of how empirically derived ecological mechanism informed the development of these models, (b) limitations in the ability to apply models to geographies with variable tidal regimes, and (c) a lack of open‐source code to apply models. Here, we provide for the first time an explicit description of a mathematical version of the Cohort Theory Model and a numerical version of a combined model: the Cohort Marsh Equilibrium Model (CMEM) with an accompanying open‐source R package, rCMEM. We show that, through this “depth‐aware” model, we can capture how tidal variation impacts broad patterns of marsh accretion and carbon sequestration across the United States. The application of this model will likely be imperative in predicting the fate and state of coastal wetlands and the ecosystem services they provide in an era of rapid environmental change.

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

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