Coastal salt marshes (CSMs) are vital blue carbon (BC) reservoirs, yet accurately quantifying their gross primary productivity (GPP) remains challenging due to limitations in terrestrial biosphere models (TBMs), which often overlook coastal-specific processes. Here, we present SAL-GPP, a process-based model that incorporates coastal-specific modules to capture the effects of salinity and temperature stress on photosynthesis, as well as light-use efficiency across salinity gradients in diverse CSM plant species. Model validation showed strong agreement with observations, with R2 of 0.82 and model efficiencies of 0.82 and 0.74 for daily and seasonal GPP, respectively. Driven with global inputs, SAL-GPP produced high-resolution global simulations, yielding a mean annual GPP of 66.89 ± 11.68 TgC yr-1 (2011-2020), with 64% concentrated in key hotspots across the southeastern United States, western Europe, southeastern China, and Australia. From 2011 to 2016, global CSM GPP increased by 1.56 TgC yr-1, then declined, rebounded after 2018, and peaked at 71.45 ± 12.02 TgC yr-1 in 2020. Model evaluation showed that SAL-GPP outperformed existing remote sensing-based GPP products and TBMs at both site and grid levels. By explicitly incorporating coastal ecosystem dynamics, SAL-GPP supports global BC accounting and climate mitigation strategies aligned with nature-based solutions for carbon neutrality.
Zhou et al. (Fri,) studied this question.