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Sea level rise and intensifying storms cause salinization and freshwater inundation of coastal forest soils which can result in tree mortality and altered ecosystem carbon (C) cycling. However, it is not yet clear if increased salinity and inundation will affect greenhouse gas (GHG) emissions to feed back with climate change. To assess the impacts of in situ chronic and pulsed salinity on GHG fluxes from coastal forests, we made continuous measurements of carbon dioxide and methane fluxes from intact soil cores collected in 1) an upland forest dominated by loblolly pine (Pinus taeda) and a freshwater swamp dominated by baldcypress (Taxodium distichum) 2) adjacent forest stands within forest types experiencing high versus low salinization and associated tree mortality and 3) before and after pulsed salinity from a hurricane related storm surge. In lab mesocosms, all soil cores were exposed to three levels of rainwater addition to assess potential interactive effects between salinization and inundation. We found that chronic salinization and associated tree mortality decreased soil CO2 fluxes in loblolly, but not baldcypress forest with in situ soil inundation patterns potentially driving the site effect. Additionally, in an upland loblolly forest, pulsed salinity from a storm surge exhibited the potential to increase CH4 fluxes. Finally, the effect of rainwater inundation on CH4 fluxes was greater in low compared to high salinity stands suggesting that salinization may have suppressed the effects of rainwater inundation on CH4 fluxes. Overall, we show that complex interactions between biotic and abiotic conditions in stressed coastal forests can alter GHG emissions, highlighting a need for future research focused on understanding the mechanisms driving GHG fluxes from coastal forests under changing environmental conditions. 

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under- sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups. 

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.