Oral Presentation Society for Freshwater Science 2026 Annual Meeting

Spatial Drivers of Soil Organic Carbon and Carbon Sequestration Rates within estuarine marsh plains along the California Coast. (136144)

Jessica Turner 1 , Adina Paytan 2 , Kevin O'Connor 3 , John Olson 1
  1. CSU Monterey Bay, Marina, CALIFORNIA, United States
  2. UC Santa Cruz, Santa Cruz
  3. Central Coast Wetlands Group, Moss Landing

Coastal wetlands provide many ecosystem services including storm and erosion control, water quality benefits, and important wildlife habitats, but among their most important benefits is their role in carbon sequestration. Despite only covering 0.3% of land, coastal wetlands are responsible for 1%-2% of carbon sequestered within the U.S.. While wetland Soil Organic Carbon (SOC) data are available in California, the California Air Resources Board (CARB) reports an uncertainty range of at least +\- 90% in existing SOC estimates. These large uncertainties are due to a lack of estimation of carbon storage, export or sequestration rates within California that are specific to each site including species specific vegetation. The CARB recommends improved vegetation classification and mapping where samples are taken to increase the accuracy of SOC estimates. Carbon concentration can vary within a single wetland type as microclimates cause changes in precipitation and temperature leading to differences in vegetation composition and geomorphology, all of which are important when predicting carbon storage potential. We collected sediment cores at 13 sites along the California coast that were within Estuarine Marine Protected Area Monitoring Program areas. We selected sites with marsh plains and additional sites to fill longitudinal gaps within existing data. These cores were analyzed in 1cm increments for SOC at all sites. 210Pb dating was used to estimate C sequestration rate in sites that have not had earth moving. Our measurements of carbon content will establish baseline carbon stocks for future monitoring. In addition, we will combine our SOC data with existing data from the Coastal Carbon Network to model the spatial patterns of SOC concentration and C sequestration rates. The carbon content and sequestration rate of these coastal wetlands was modeled with potential spatial drivers such as, land use, temperature, precipitation, vegetation species, and mean high tides. Using the Random Forest machine learning algorithm, we identified which spatial drivers of SOC and C sequestration rates are the most influential. Understanding the spatial patterns of C sequestration and what environmental factors increase rates will inform decisions for wetland management and help prioritize restoration and conservation of carbon sinks.