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1. Controls on Seasonal Atmosphere‐Ecosystem Carbon Dioxide Exchanges in a Temperate Salt Marsh

   https://doi.org/10.1111/gcb.70740  

   Ruiz‐Plancarte, Jesus; Fuentes, Jose D; McGlathery, Karen J (February 2026, Global Change Biology)

   ABSTRACT Salt marshes play a vital role in the biogeochemistry of coastal zones, yet the biophysical controls on CO₂exchange with the atmosphere, or net ecosystem exchange (NEE, positive upwards) remain poorly quantified. We investigated aSpartina alternifloramonoculture salt marsh on the eastern shore of Virginia, United States, by estimating half‐hourly NEE from March 2016 to February 2017 using the eddy‐covariance method. Maximum marsh–atmosphere CO₂exchanges occurred during June and July when hourly averaged NEE values reached −10.0 ± 2.5 μmol CO₂m⁻² s⁻¹(mean ±1 standard deviation). During the most productive time of the year, a tidal inundation of 0.7 m reduced daytime CO₂assimilation and nighttime CO₂release to the atmosphere by 5.0 ± 1.2 μmol CO₂m⁻² s⁻¹and 3.0 ± 0.7 μmol CO₂m⁻² s⁻¹, respectively. Diffuse photosynthetically active radiation (PAR) conditions promoted quantum use efficiencies (α) of the ecosystem that were approximately three times greater than under direct PAR conditions (α_Cloudy = 0.012 ± 0.004 versusα_Clear = 0.004 ± 0.001 mol CO₂per (mol photons)). Under diffuse light, NEE increased more rapidly with PAR and photo‐saturation occurred at higher PAR levels compared to clear‐sky conditions. On average, under the influence of diffuse light, the assimilation of CO₂increased by 30% relative to equivalent PAR levels under direct sunlight. During March 2016 to February 2017 the marsh exchanged −269.1 ± 9.1 g of carbon per m²with the atmosphere. The findings demonstrate that tides and light quality are key regulators of carbon cycling in tidal marshes. These factors should be incorporated into models of tidal marsh biogeochemistry, particularly as both are undergoing rapid changes due to sea level rise and atmospheric warming. 

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2. Eddy covariance (EC) vertical carbon fluxes from a Georgia tidal salt marsh from 2014 to 2024

   https://doi.org/10.6073/pasta/796a1d1461efd426a3b5d3c7d8109eda  

   Project, Georgia_Coastal_Ecosystems LTER; Hawman, Peter (January 2025, Environmental Data Initiative)

   We present our methodology and data for science ready vertical carbon fluxes from a Spartina alterniflora tidal salt marsh as part of the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) site on Sapelo Island, Georgia, USA. Vertical carbon fluxes were measured through the eddy covariance (EC) method from 2014 to 2024. The EC flux tower was located on the western side of Sapelo Island bounded by the Duplin River and Barn Creek. The proportional influence of marsh habitats on the flux measurements were 4% tall, 38% short, and 58% medium height form Spartina alterniflora. We present the net ecosystem exchange (NEE), ecosystem respiration (ER), and gross primary production (GPP) at 30-minute fluxes (μmol CO2 m-2 s-1), daily averages (μmol CO2 m-2 s-1) and totals (g C m-2 day-1), and annual (g C m-2 year-1) quantities. We provide estimated uncertainty for each flux at each integrated timescale as 95% confidence intervals. Providing open access to 10-year carbon flux datasets can facilitate collaboration for advancing regional and global blue carbon synthesis and scale-up studies. 

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3. Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

   https://doi.org/10.1029/2024MS004342  

   Xia, Yushu; Sanderman, Jonathan; Watts, Jennifer D; Machmuller, Megan B; Mullen, Andrew L; Rivard, Charlotte; Endsley, Arthur; Hernandez, Haydee; Kimball, John; Ewing, Stephanie A; et al (March 2025, Journal of Advances in Modeling Earth Systems)

   Abstract Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long‐term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C‐cycle processes. Bayesian calibration was conducted using quality‐controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass‐shrub mixture, and grass‐tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R² > 0.6, RMSE <390 g C m⁻²) relative to net ecosystem exchange of CO₂(NEE) (R² > 0.4, RMSE <180 g C m⁻²). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks withR² = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long‐term network‐based monitoring of vegetation biomass, C fluxes, and SOC stocks. 

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4. Temporal patterns and causal drivers of aboveground plant biomass in a coastal wetland: Insights from time-series analyses

   https://doi.org/10.3389/fmars.2023.1130958  

   Biçe, Kadir; Schalles, John; Sheldon, Joan E.; Alber, Merryl; Meile, Christof (April 2023, Frontiers in Marine Science)

   Salt marshes play a crucial role in coastal biogeochemical cycles and provide unique ecosystem services. Salt marsh biomass, which can strongly influence such services, varies over time in response to hydrologic conditions and other environmental drivers. We used gap-filled monthly observations ofSpartina alternifloraaboveground biomass derived from Landsat 5 and Landsat 8 satellite imagery from 1984-2018 to analyze temporal patterns in biomass in comparison to air temperature, precipitation, river discharge, nutrient input, sea level, and drought index for a southeastern US salt marsh. Wavelet analysis and ensemble empirical mode decomposition identified month to multi-year periodicities in both plant biomass and environmental drivers. Wavelet coherence detected cross-correlations between annual biomass cycles and precipitation, temperature, river discharge, nutrient concentrations (NO_xand PO₄^3–) and sea level. At longer periods we detected coherence between biomass and all variables except precipitation. Through empirical dynamic modeling we showed that temperature, river discharge, drought, sea level, and river nutrient concentrations were causally connected to salt marsh biomass and exceeded the confounding effect of seasonality. This study demonstrated the insights into biomass dynamics and causal connections that can be gained through the analysis of long-term data. 

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5. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO₂, water, and energy fluxes on daily to annual scales

   https://doi.org/10.5194/gmd-11-497-2018  

   Qiu, Chunjing; Zhu, Dan; Ciais, Philippe; Guenet, Bertrand; Krinner, Gerhard; Peng, Shushi; Aurela, Mika; Bernhofer, Christian; Brümmer, Christian; Bret-Harte, Syndonia; et al (January 2018, Geoscientific Model Development)

   Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO₂ fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (V_cmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r² =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r² =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r² =  0.42, MEF  =  0.14) and and net ecosystem CO₂ exchange (NEE, r² =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r² values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r² values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r² &lt; 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V_cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V_cmax value. 

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