Predicting Carbon Stocks in Tidal Marsh Soils

Author

Fidaa Janoudi, University of Rhode IslandFollow

Date of Award

1-1-2022

Degree Type

Thesis

Degree Name

Master of Science in Biological and Environmental Sciences (MSBES)

Specialization

Environmental and Earth Sciences

Department

Natural Resources Science

First Advisor

Jason Parent

Abstract

Tidal marsh soils serve as important blue carbon storage sink ecosystems which are currently being threatened by rising sea levels. Previous studies have suggested that exist-ing estimates of tidal marsh blue carbon stocks may be inaccurate and overestimated. Currently, we do not have a clear quantification of how much soil organic carbon (SOC), also referred to as blue carbon in coastal ecosystems, is being stored in tidal marsh soils, and how influential geomorphic factors could be on soil carbon stocks. In this study, our goal was to use geographic information systems (GIS) and remote sensing tools to model soil organic carbon stocks in tidal marshes across three regions along the Atlantic Coast: southern New England (i.e. Rhode Island, Massachusetts, Connecticut), the Mid Atlantic (i.e. Maryland, New Jersey, Delaware), and Southeastern Atlantic (i.e. North Carolina). We determined marsh geomorphic predictors for all tidal marshes within our study area and used field sampled soil organic carbon stock values at 50, 100, and 200 cm soil depths to train Random Forest models and determine which geomorphic predictors are important for blue carbon stocks. Models performed well for the 100 and 200 cm soil depths of the southeastern Atlantic carbon stocks (r² = 0.86 and r² = 0.77 for 100 and 200 cm, respectively) but failed completely for the 50 cm southern New England and Mid-Atlantic study sites (r² = 0.01). Fetch, upland/marsh boundary elevation, mean upland elevation, slope, elevation, and distance to open water were the most significant geomorphic predictors for these models. Further work is needed to develop more accurate models for various marsh settings in order to help accurately predict car-bon stock values in unsampled locations and aid tidal marsh management and preservation efforts.

Recommended Citation

Janoudi, Fidaa, "Predicting Carbon Stocks in Tidal Marsh Soils" (2022). Open Access Master's Theses. Paper 2280.
https://digitalcommons.uri.edu/theses/2280