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Enhancing Assessments Of Blue Carbon Stocks In Marsh Soils Using Bayesian Mixed-Effects Modeling With Spatial Autocorrelation — Proof Of Concept Using Proxy Data, Grace S. Chiu, Molly Mitchell, Julie Herman, Christian Longo, Kate Davis
Enhancing Assessments Of Blue Carbon Stocks In Marsh Soils Using Bayesian Mixed-Effects Modeling With Spatial Autocorrelation — Proof Of Concept Using Proxy Data, Grace S. Chiu, Molly Mitchell, Julie Herman, Christian Longo, Kate Davis
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Our paper showcases the potential gain in scientific insights about blue carbon stocks (or total organic carbon) when additional rigor, in the form of a spatial autocorrelation component, is formally incorporated into the statistical model for assessing the variability in carbon stocks. Organic carbon stored in marsh soils, or blue carbon (BC), is important for sequestering carbon from the atmosphere. The potential for marshes to store carbon dioxide, mitigating anthropogenic contributions to the atmosphere, makes them a critical conservation target, but efforts have been hampered by the current lack of robust methods for assessing the variability of BC stocks at …