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1. High rates of daytime river metabolism are an underestimated component of carbon cycling

   https://doi.org/10.1038/s43247-022-00607-2  

   Tromboni, Flavia; Hotchkiss, Erin R.; Schechner, Anne E.; Dodds, Walter K.; Poulson, Simon R.; Chandra, Sudeep (December 2022, Communications Earth & Environment)

   Abstract River metabolism and, thus, carbon cycling are governed by gross primary production and ecosystem respiration. Traditionally river metabolism is derived from diel dissolved oxygen concentrations, which cannot resolve diel changes in ecosystem respiration. Here, we compare river metabolism derived from oxygen concentrations with estimates from stable oxygen isotope signatures (δ 18 O 2 ) from 14 sites in rivers across three biomes using Bayesian inverse modeling. We find isotopically derived ecosystem respiration was greater in the day than night for all rivers (maximum change of 113 g O 2  m −2  d −1 , minimum of 1 g O 2  m −2  d −1 ). Temperature (20 °C) normalized rates of ecosystem respiration and gross primary production were 1.1 to 87 and 1.5 to 22-fold higher when derived from oxygen isotope data compared to concentration data. Through accounting for diel variation in ecosystem respiration, our isotopically-derived rates suggest that ecosystem respiration and microbial carbon cycling in rivers is more rapid than predicted by traditional methods. 

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2. Quantifying the impacts of land cover change on gross primary productivity globally

   https://doi.org/10.1038/s41598-022-23120-0  

   Krause, Andreas; Papastefanou, Phillip; Gregor, Konstantin; Layritz, Lucia S.; Zang, Christian S.; Buras, Allan; Li, Xing; Xiao, Jingfeng; Rammig, Anja (December 2022, Scientific Reports)

   Abstract Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satellite-derived GPP and environmental predictor variables to estimate the potential GPP of forests, grasslands, and croplands around the globe. With a mean GPP of 2.0 kg C m −2  yr −1 forests represent the most productive land cover on two thirds of the total area suitable for any of these land cover types, while grasslands and croplands on average reach 1.5 and 1.8 kg C m −2  yr −1 , respectively. Combining our potential GPP maps with a historical land-use reconstruction indicates a 4.4% reduction in global GPP from agricultural expansion. This land-use-induced GPP reduction is amplified in some future scenarios as a result of ongoing deforestation (e.g., the large-scale bioenergy scenario SSP4-3.4) but partly reversed in other scenarios (e.g., the sustainability scenario SSP1-1.9) due to agricultural abandonment. Comparing our results to simulations from state-of-the-art Earth System Models, we find that all investigated models deviate substantially from our estimates and from each other. Our maps could be used as a benchmark to reduce this inconsistency, thereby improving projections of land-based climate mitigation potentials. 

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3. Constrained Carbon Partitioning: A Self‐Trained Physics‐Informed Machine Learning Model Refines GPP Estimates From Eddy Covariance Measurements

   https://doi.org/10.1111/gcb.70886  

   Ranjbar, Sadegh; Desai, Ankur R; Hoffman, Sophie; Zahn, Einara; Bou‐Zeid, Elie; Stoy, Paul C (May 2026, Global Change Biology)

   Gross primary productivity (GPP) is the largest term in the global carbon budget but cannot be directly observed. We present a knowledge‐guided machine learning (KGML) framework that partitions eddy covariance‐measured net ecosystem exchange (NEE) into gross primary production (GPP) and ecosystem respiration (RECO) with partitioned water vapor fluxes and CO₂flux source areas from 36 U.S. National Ecological Observatory Network (NEON) towers. The KGML is guided by hard physical constraints that enforce mass balance and ‘soft’ theoretical expectations including optimal stomatal response to vapor pressure deficit (VPD) and links between GPP and transpiration (T) through stomatal function. The model achieves strong physical consistency (NEER² = 0.99) while capturing expected ecophysiological relationships including GPP‐T coupling (R² = 0.58) and stomatal responses to light and VPD. Compared to conventional partitioning methods, KGML infers lower GPP and RECO estimates on average, with the largest negative biases occurring at low light levels (0–200 μmol photons m⁻² s⁻¹). These differences likely reflect a combination of mechanisms including light‐induced respiration suppression consistent with the Kok effect, stomatal‐transpiration coupling constraints, and dynamic allocation between respiration components. The flux differences vary across plant functional types (PFTs), where forested ecosystems (deciduous broadleaf, evergreen needleleaf, and mixed), savannas and grasslands show the largest negative annual GPP deviations (−10% to −18% versus nighttime partitioning), while croplands and open shrublands show moderate negative deviations (−5% to −10%). The lower GPP estimates by PFT are closer to those inferred by Keenan et al. that explicitly considers limitations on RECO from the Kok effect. We discuss implications for our understanding of ecosystem and global carbon cycle processes, as well as ways to further benefit from the full information content of eddy covariance observations by combining physics with knowledge of biological processes. 

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4. X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

   https://doi.org/10.5194/bg-21-5079-2024  

   Nelson, Jacob A; Walther, Sophia; Gans, Fabian; Kraft, Basil; Weber, Ulrich; Novick, Kimberly; Buchmann, Nina; Migliavacca, Mirco; Wohlfahrt, Georg; Šigut, Ladislav; et al (January 2024, Biogeosciences)

   Abstract. Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr−1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr−1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×103 ± 0.9×103 km3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates. 

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5. Metabolism of a subtidal rocky mussel reef in a high-temperate setting: pathways of organic C flow

   https://doi.org/10.3354/meps13372  

   Attard, KM; Rodil, IF; Berg, P; Mogg, AOM; Westerbom, M; Norkko, A; Glud, RN (July 2020, Marine Ecology Progress Series)

   null (Ed.)

   Mytilid mussels form abundant, species-rich reefs on rocky substrates, but the role of this key habitat in carbon (C) cycling remains poorly understood. We performed a seasonal study on a 5 m deep photic Mytilus trossulus reef in the Central Baltic Sea to investigate pathways and rates of organic C flow. Reef gross primary production (GPP) and respiration ( R ) were estimated seasonally using underwater O 2 eddy covariance on hourly and daily timescales. Photogrammetry and biotic sampling were used to quantify reef rugosity and mussel coverage, and to derive mussel filtration and biodeposition. Mussels were highly abundant, reaching ~50000 ind. m -2 , and the reef structure increased the seabed surface area by 44%. GPP hourly was up to 20 mmol O 2 m -2 h -1 and GPP daily was up to 107 mmol O 2 m -2 d -1 , comparable to a nearby seagrass canopy. Hourly eddy fluxes responded linearly to light intensity and flow velocity, with higher velocities enhancing reef O 2 uptake at night. Reef R daily exceeded GPP daily on 12 of 13 measurement days, and R annual (29 mol O 2 m -2 yr -1 ) was 3-fold larger than GPP annual . The reef sustained a productive community of microbes and fauna whose activities accounted for ~50% of R annual . Horizontal water advection promoted food supply to the reef and likely facilitated substantial lateral C export of mussel biodeposits. Our analyses suggest that a reduction in mussel reef extent due to ongoing environmental change will have major implications for the transport and transformation of C and nutrients within the coastal Baltic Sea. 

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