2025-02-14 マサチューセッツ大学アマースト校
＜関連情報＞
- https://www.umass.edu/news/article/new-englands-salt-marshes-store-10-million-cars-worth-carbon-and-add-another-15000
- https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024JG008254
時間的に最適化された衛星リモートセンシング画像を用いたブルーカーボンマッピング： 米国北東部塩性湿地の地域研究 Blue Carbon Mapping Using Temporally Optimized Satellite Remote Sensing Imagery: A Regional Study of Northeast US Salt Marshes
Wenxiu Teng, Qian Yu, Brian Yellen, Bonnie Turek, Jonathan D. Woodruff
Journal of Geophysical Research: Biogeosciences Published: 11 February 2025
DOI:https://doi.org/10.1029/2024JG008254
Abstract
Coastal wetlands store three to five times more carbon per unit area than tropical rainforests in continually accreting peat soils, collectively referred to as “Blue Carbon.” However, variability in soil carbon density within and between sites leads to large uncertainty when estimating carbon stocks and sequestration rates. Salt marsh carbon sequestration is mainly driven by nonlinear ecogeomorphic feedback between tidal inundation, bioproductivity, and sediment supply—all of which can be observed by satellites. In this study, we used soil bulk density and soil organic content from 410 soil samples collected across 15 sites in the Northeast US to relate soil properties to remotely sensed spectral observations. We tested model fits using Landsat 5, 7, 8, and Sentinel 2 images from 1984 to 2022 to determine the optimal season and tidal conditions for relating remote sensing indices to soil properties. We explored the roles of sediment supply and tidal range in regional prediction models. The study found that (a) spatial patterns of remote sensing indices correlate well with soil properties; (b) at the marsh scale, remote sensing indices capture the spatial variability of soil properties with image acquired at high tide and vegetation phenology specific to geomorphic setting; (c) at the regional scale, tidal range improves the prediction model in barrier marshes, while sediment supply improves the prediction model in fluvial marshes. The considerable spatial variation of SOC within marshes and across regional gradients highlights the need for high resolution maps of salt marsh soil properties.
Plain Language Summary
Salt marshes are vibrant coastal ecosystems that play a crucial role in biodiversity, shoreline stabilization, and climate change mitigation. These marshes are particularly effective at storing carbon in their continuously growing soils, which helps reduce atmospheric carbon dioxide levels. However, the variability in soil carbon density both within and across sites makes it difficult to accurately assess how much carbon these ecosystems store. To address this, we collected 410 soil samples from 15 locations in the Northeast US to measure soil bulk density and organic content. These two properties are key indicators of carbon density in soils. By linking these soil properties with satellite-derived spectral data, particularly the Normalized Difference Water Index (NDWI), we observed that NDWI trends align closely with ground-based measurements of soil properties. This correlation is due to the ability of satellite images, acquired during peak growth seasons and high tides, to capture key ecogeomorphic drivers like tidal inundation and bioproductivity, which influence carbon sequestration. We then map soil organic carbon across Northeast US salt marshes at 10 m resolution. This precise mapping provides insights into the carbon storage potential of tidal marshes and offers essential data to guide restoration efforts, including estimating sediment demands before restoration projects.
Key Points
- Optical remote sensing captures ecogeomorphic drivers of soil organic carbon (SOC) spatial variability in salt marshes
- Remote sensing indices capture SOC variability with image acquired at high tide and vegetation phenology specific to geomorphic setting
- Tidal range improves the SOC prediction model in barrier marshes, while sediment supply improves the prediction model in fluvial marshes
