Academic Journal

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

التفاصيل البيبلوغرافية
العنوان: Cohort Marsh Equilibrium Model (CMEM): History, Mathematics, and Implementation.
المؤلفون: Vahsen, M. L., Todd-Brown, K. E. O., Hicks, J., Pilyugin, S. S., Morris, J. T., Holmquist, J. R.
المصدر: Journal of Geophysical Research. Biogeosciences; Apr2024, Vol. 129 Issue 4, p1-19, 19p
مستخلص: Marsh 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. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
تدمد:21698953
DOI:10.1029/2023JG007823