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Abstract Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO₂) and methane (CH₄) in tidal wetlands are highly uncertain. While several biogeochemical models can operate in tidal wetlands, they have yet to be parameterized and validated against high‐frequency, ecosystem‐scale CO₂and CH₄flux measurements across diverse sites. We paired the Cohort Marsh Equilibrium Model (CMEM) with a version of the PEPRMT model called PEPRMT‐Tidal, which considers the effects of water table height, sulfate, and nitrate availability on CO₂and CH₄emissions. Using a model‐data fusion approach, we parameterized the model with three sites and validated it with two independent sites, with representation from the three marine coasts of North America. Gross primary productivity (GPP) and ecosystem respiration (R_eco) modules explained, on average, 73% of the variation in CO₂exchange with low model error (normalized root mean square error (nRMSE) <1). The CH₄module also explained the majority of variance in CH₄emissions in validation sites (R² = 0.54; nRMSE = 1.15). The PEPRMT‐Tidal‐CMEM model coupling is a key advance toward constraining estimates of greenhouse gas emissions across diverse North American tidal wetlands. Further analyses of model error and case studies during changing salinity conditions guide future modeling efforts regarding four main processes: (a) the influence of salinity and nitrate on GPP, (b) the influence of laterally transported dissolved inorganic C on R_eco, (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH₄emissions, and (d) CH₄responses to non‐periodic changes in salinity. 

Abstract Due to their large carbon storage capacity and ability to exchange subterranean CO₂with the atmosphere, soils are key components in the carbon balance in semi‐arid ecosystems. Most studies have focused on shallow (e.g., <30 cm depth) soil CO₂dynamics neglecting processes in deeper soil layers where highly CO₂‐enriched air can be stored or transported through soil pores and fissures. Here, we examine the relationship among variations in subterranean CO₂molar fraction, volumetric water content, soil temperature and atmospheric pressure during three years within soil profiles (0.15, 0.50, and 1.50 m depths) in two semi‐arid grasslands located in southeastern Spain. We applied a wavelet coherence analysis to study the temporal variability and temporal correlation between the CO₂molar fraction and its covariates (soil temperature, soil moisture and atmospheric pressure). Our results show that CO₂dynamics are strongly influenced by changes in atmospheric pressure from semidiurnal, diurnal and synoptic to monthly time‐scales for all soil depths. In contrast, only weak daily dependencies were found at the surface level (0.15 m) regarding soil temperature and volumetric water content. Atmospheric pressure changes substantially influence variations in the CO₂content (with daily fluctuations of up to 2000 ppm) denoting transportation through soil layers. These results provide insights into the importance of subterranean storage and non‐diffusive gas transport that could influence soil CO₂efflux rates, processes that are not considered when applying the flux‐gradient approach and, which can be especially important in ecosystems with high air permeability between the unsaturated porous media and the atmosphere. 

Abstract We mapped tidal wetland gross primary production (GPP) with unprecedented detail for multiple wetland types across the continental United States (CONUS) at 16‐day intervals for the years 2000–2019. To accomplish this task, we developed the spatially explicit Blue Carbon (BC) model, which combined tidal wetland cover and field‐based eddy covariance tower data into a single Bayesian framework, and used a super computer network and remote sensing imagery (Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index). We found a strong fit between the BC model and eddy covariance data from 10 different towers (r²= 0.83,p< 0.001, root‐mean‐square error = 1.22 g C/m²/day, average error was 7% with a mean bias of nearly zero). When compared with NASA's MOD17 GPP product, which uses a generalized terrestrial algorithm, the BC model reduced error by approximately half (MOD17 hadr²= 0.45,p< 0.001, root‐mean‐square error of 3.38 g C/m²/day, average error of 15%). The BC model also included mixed pixels in areas not covered by MOD17, which comprised approximately 16.8% of CONUS tidal wetland GPP. Results showed that across CONUS between 2000 and 2019, the average daily GPP per m²was 4.32 ± 2.45 g C/m²/day. The total annual GPP for the CONUS was 39.65 ± 0.89 Tg C/year. GPP for the Gulf Coast was nearly double that of the Atlantic and Pacific Coasts combined. Louisiana alone accounted for 15.78 ± 0.75 Tg C/year, with its Atchafalaya/Vermillion Bay basin at 4.72 ± 0.14 Tg C/year. The BC model provides a robust platform for integrating data from disparate sources and exploring regional trends in GPP across tidal wetlands.