Search

River networks represent the largest biogeochemical nexus between the continents, ocean and atmosphere. Our current understanding of the role of rivers in the global carbon cycle remains limited, which makes it difficult to predict how global change may alter the timing and spatial distribution of riverine carbon sequestration and greenhouse gas emissions. Here we review the state of river ecosystem metabolism research and synthesize the current best available estimates of river ecosystem metabolism. We quantify the organic and inorganic carbon flux from land to global rivers and show that their net ecosystem production and carbon dioxide emissions shift the organic to inorganic carbon balance en route from land to the coastal ocean. Furthermore, we discuss how global change may affect river ecosystem metabolism and related carbon fluxes and identify research directions that can help to develop better predictions of the effects of global change on riverine ecosystem processes. We argue that a global river observing system will play a key role in understanding river networks and their future evolution in the context of the global carbon budget.

The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). Major advances have improved our understanding of the coastal air-sea exchanges of these three gasses since the first phase of the Regional Carbon Cycle Assessment and Processes (RECCAP in 2013), but a comprehensive view that integrates the three gasses at the global scale is still lacking. In this second phase (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ~60% larger in models (-0.72 vs. -0.44 PgC/yr, 1998-2018, coastal ocean area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e /yr in observational product and +0.54 PgCO2-e /yr in model median) and of CH4 (+0.21 PgCO2-e /yr in observational product), which offsets a substantial proportion of the net radiative effect of coastal \co uptake (35-58% in CO2-equivalents). Data products and models need improvement to better resolve the spatio-temporal variability and long term trends in CO2, N2O and CH4 in the global coastal ocean.

A research highlight about the modelling of land-to-ocean aquatic continuum carbon fluxes. Based on the publication: Regnier, P., Resplandy, L., Najjar, R.G. et al. (2022) The land-to-ocean loops of the global carbon cycle. Nature 603, 401–410 . https://doi.org/10.1038/s41586-021-04339-9

Regional land carbon budgets provide insights into the spatial distribution of the land uptake of atmospheric carbon dioxide and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields, or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions due to different definitions and component fluxes being reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers that connect CO2 uptake in one area with its release in another also requires better definitions and protocols to reach harmonized regional budgets that can be summed up to a globe scale and compared with the atmospheric CO2 growth rate and inversion results. In this study, using the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims to be an update to regional carbon budgets over the last 2 decades based on observations for 10 regions covering the globe with a better harmonization than the precursor project, we provide recommendations for using atmospheric inversion results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes, and land use fluxes.

Leaching of dissolved organic carbon (DOC) from soils into the river network is an important component of the land carbon (C) budget. At regional to global scales, its significance has been estimated through simple mass budgets, often using multi-year averages of observed fluvial DOC fluxes as a proxy of DOC leaching due to the limited availability of observations of the leaching flux itself. This procedure leads to a systematic underestimation of the leaching flux because of the decay of DOC during fluvial transport. Moreover, this procedure does not allow for revealing spatiotemporal variability in DOC leaching from soils, which is vital to better understand the drivers of DOC leaching and its impact on the local soil C budget. In this study, we use the land surface model (LSM) ORCHILEAK to simulate the terrestrial C budget, including leaching of DOC from the soil and its subsequent reactive transport through the river network of Europe. The model performance is evaluated not only against the sparse observations of the soil DOC leaching rate, but also against the more abundant observations of fluxes and reactivity of DOC in rivers, providing further evidence that our simulated DOC fluxes are realistic. The model is then used to simulate the spatiotemporal patterns of DOC leaching across Europe over the period 1972–2012, quantifying both the environmental drivers of these patterns and the impact of DOC leaching on the land C budget. Over the simulation period, we find that, on average, 14.3 Tg C yr−1 of DOC is leached from land into European rivers, which is about 0.6 % of the terrestrial net primary production (NPP), a fraction significantly lower than that reported for tropical river networks. On average, 12.3 Tg C yr−1 of the leached DOC is finally exported to the coast via the river network, and the rest is respired during transit. DOC leaching presents a large seasonal variability, with the maximum occurring in winter and the minimum in summer, except for most parts of northern Europe, where the maximum occurs in spring due to snowmelt. The DOC leaching rate is generally low in warm and dry regions, and high in the cold and wet regions of Europe. Furthermore, runoff and the ratio between runoff from shallower flow paths on one hand and deep drainage and groundwater flow on the other hand are the main drivers of the spatiotemporal variation of DOC leaching. Temperature, as a major control of DOC production and decomposition rates in the soils, plays only a secondary role.

The temporal variability of the sea surface partial pressure of CO2 (pCO2) and the underlying processes driving this variability are poorly understood in the coastal ocean. In this study, we tailor an existing method that quantifies the effects of thermal changes, biological activity, ocean circulation and freshwater fluxes to examine seasonal pCO2 changes in highly variable coastal environments. We first use the Modular Ocean Model version 6 (MOM6) and biogeochemical module Carbon Ocean Biogeochemistry And Lower Trophics version 2 (COBALTv2) at a half-degree resolution to simulate coastal CO2 dynamics and evaluate them against pCO2 from the Surface Ocean CO2 Atlas database (SOCAT) and from the continuous coastal pCO2 product generated from SOCAT by a two-step neuronal network interpolation method (coastal Self-Organizing Map Feed-Forward neural Network SOM-FFN, Laruelle et al., 2017). The MOM6-COBALT model reproduces the observed spatiotemporal variability not only in pCO2 but also in sea surface temperature, salinity and nutrients in most coastal environments, except in a few specific regions such as marginal seas. Based on this evaluation, we identify coastal regions of “high” and “medium” agreement between model and coastal SOM-FFN where the drivers of coastal pCO2 seasonal changes can be examined with reasonable confidence. Second, we apply our decomposition method in three contrasted coastal regions: an eastern (US East Coast) and a western (the Californian Current) boundary current and a polar coastal region (the Norwegian Basin). Results show that differences in pCO2 seasonality in the three regions are controlled by the balance between ocean circulation and biological and thermal changes. Circulation controls the pCO2 seasonality in the Californian Current; biological activity controls pCO2 in the Norwegian Basin; and the interplay between biological processes and thermal and circulation changes is key on the US East Coast. The refined approach presented here allows the attribution of pCO2 changes with small residual biases in the coastal ocean, allowing for future work on the mechanisms controlling coastal air–sea CO2 exchanges and how they are likely to be affected by future changes in sea surface temperature, hydrodynamics and biological dynamics.

Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) fluxes and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021b). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven sectoral model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with European National Greenhouse Gas Inventories (NGHGIs) reported by Parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 3392 ± 49 Tg CO2 yr-1 (926 ± 13 Tg C yr-1), while eight other BU sources report a mean value of 3340 [3238,3401] [25th,75th percentile] Tg CO2 yr-1 (948 [937,961] Tg C yr-1). The sole top-down inversion of fossil emissions currently available accounts for 3800 Tg CO2 yr-1 (1038 Tg C yr-1), a value close to that of the NGHGI, but for which uncertainty estimates are not yet available. For the net CO2 land fluxes, during the most recent five-year period including the NGHGI estimates, the NGHGI accounted for -91 ± 32 Tg C yr-1 while six other BU approaches reported a mean sink of -62 [-117,-49] Tg C yr-1 and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported -69 [-152,-5] Tg C yr-1. The five-year mean of three TD regional ensembles combined with one non-ensemble inversion of -73 Tg C yr-1 has a slightly smaller spread (0th–100th percentile of [-135,45] Tg C yr-1), and was calculated after removing land-atmosphere CO2 fluxes caused by lateral transport of carbon (crops, wood trade and inland waters) resulting in increased agreement with the the NGHGI and bottom-up approaches. Results at the sub-sector level (Forestland, Cropland, Grassland) show generally good agreement between the NGHGI and sub-sector-specific models, but results for a DGVM are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while large uncertainties on net uptake of CO2 by the land surface prevent trend identification. In addition, a gap on the order of 1000 Tg C yr-1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.7365863.

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).

Knowledge of the spatial distribution of the fluxes of greenhouse gases and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its Global Stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27+UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results, inverse modelling estimates, and extends the previous period 1990–2017 to 2020. BU and TD products are compared with European National GHG Inventories (NGHGI) reported by Parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. The uncertainties of NGHGIs were evaluated using the standard deviation obtained by varying parameters of inventory calculations, reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates e.g. anthropogenic and natural fluxes, which, in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGAR v5v6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, 2015), close to the NGHGI estimates of 17.5 ± 2.1 Tg CH4 yr−1. TD inversions estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 Tg CH4 yr−1 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soils emissions from the JSBACH-HIMMELI model, natural rivers, lakes and reservoirs emissions, geological sources and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGAR v5v6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8 ± 55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT which reported no data). The TD and BU comparison method defined in this study can be "operationalized" for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27+UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, of great importance for CH4 and N2O, which may help identify sector contributions to divergence between prior and posterior estimates at the annual/inter-annual scale. Even if currently comparison between CH4 and N2O inversions estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modelling and observations, as well as modelling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emissions inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.6992472 (Petrescu et al., 2022).

In this study, we present the first combined open and coastal ocean pCO2 mapped monthly climatology (Landschützer et al. (2020), doi:10.25921/qb25-f418, https://www.nodc.noaa.gov/ocads/oceans/MPI-ULB-SOM_FFN_clim.html) constructed from observations collected between 1998 and 2015 extracted from the Surface Ocean CO2 Atlas (SOCAT) database. We combine two neural network-based pCO2 products, one from the open ocean and the other from the coastal ocean, and investigate their consistency along their common overlap areas. While the difference between open and coastal ocean estimates along the overlap area increases with latitude, it remains close to 0 μatm globally. Stronger discrepancies, however, exist on the regional level resulting in differences that exceed 10 % of the climatological mean pCO2, or an order of magnitude larger than the uncertainty from state of the art measurements. This also illustrates the potential of such analysis to inform the measurement community about the locations where additional measurements are essential to better represent the aquatic continuum and improve our understanding of the carbon exchange at the air water interface. A regional analysis further shows that the seasonal carbon dynamics at the coast-open interface are well represented in our climatology. While our combined product is only a first step towards a true representation of both the open ocean and the coastal ocean air-sea CO2 flux in marine carbon budgets, we show it is a feasible task and the present data product already constitutes a valuable tool to investigate and quantify the dynamics of the air-sea CO2 exchange consistently for oceanic regions regardless of its distance to the coast.

International audience; Carbon storage by the ocean and by the land is usually quantified separately, and does not fully take into account the land-to-ocean transport of carbon through inland waters, estuaries, tidal wetlands and continental shelf waters—the `land-to-ocean aquatic continuum' (LOAC). Here we assess LOAC carbon cycling before the industrial period and perturbed by direct human interventions, including climate change. In our view of the global carbon cycle, the traditional `long-range loop', which carries carbon from terrestrial ecosystems to the open ocean through rivers, is reinforced by two `short-range loops' that carry carbon from terrestrial ecosystems to inland waters and from tidal wetlands to the open ocean. Using a mass-balance approach, we find that the pre-industrial uptake of atmospheric carbon dioxide by terrestrial ecosystems transferred to the ocean and outgassed back to the atmosphere amounts to 0.65 ± 0.30 petagrams of carbon per year (±2 sigma). Humans have accelerated the cycling of carbon between terrestrial ecosystems, inland waters and the atmosphere, and decreased the uptake of atmospheric carbon dioxide from tidal wetlands and submerged vegetation. Ignoring these changing LOAC carbon fluxes results in an overestimation of carbon storage in terrestrial ecosystems by 0.6 ± 0.4 petagrams of carbon per year, and an underestimation of sedimentary and oceanic carbon storage. We identify knowledge gaps that are key to reduce uncertainties in future assessments of LOAC fluxes.

The temporal variability of the sea surface partial pressure of CO2 (pCO2) and the underlying processes driving this variability are poorly understood in the coastal ocean. In this study, we tailor an existing method that quantifies the effects of thermal changes, biological activity, ocean circulation and fresh water fluxes to examine seasonal pCO2 changes in highly-variable coastal environments. We first use the Modular Ocean Model version 6 (MOM6) and biogeochemical module Carbon Ocean Biogeochemistry And Lower Trophics version 2 (COBALTv2) at a half degree resolution to simulate the coastal CO2 dynamics and evaluate it against pCO2 from the Surface Ocean CO2 Atlas database (SOCAT) and from the continuous coastal pCO2 product generated from SOCAT by a two-step neuronal network interpolation method (coastal-SOM-FFN, Laruelle et al., 2017). The MOM6-COBALT model not only reproduces the observed spatio-temporal variability in pCO2 but also in sea surface temperature, salinity, nutrients, in most coastal environments except in a few specific regions such as marginal seas. Based on this evaluation, we identify coastal regions of ‘high’ and ‘medium’ model skill where the drivers of coastal pCO2 seasonal changes can be examined with reasonable confidence. Second, we apply our decomposition method in three contrasted coastal regions: an Eastern (East coast of the U.S) and a Western (the Californian Current) boundary current and a polar coastal region (the Norwegian Basin). Results show that differences in pCO2 seasonality in the three regions are controlled by the balance between ocean circulation, biological and thermal changes. Circulation controls the pCO2 seasonality in the Californian Current, biological activity controls pCO2 in the Norwegian Basin, while the interplay between biology, thermal and circulation changes is key in the East coast of the U.S. The refined approach presented here allows the attribution of pCO2 changes with small residual biases in the coastal ocean, allowing future work on the mechanisms controlling coastal air-sea CO2 exchanges and how they are likely to be affected by future changes in sea surface temperature, hydrodynamics and biological dynamics.

Leaching of dissolved organic carbon (DOC) from soils to the river network is an important component of the land carbon (C) budget. At regional to global scales, its significance has been estimated through simple mass budgets, often using multi-year averages of observed fluvial DOC fluxes as proxy of DOC leaching due to the limited availability of observations of the leaching flux itself. This procedure leads to a systematic underestimation of the leaching flux because of the reactivity of DOC during fluvial transport. Moreover, this procedure does not allow to reveal spatio-temporal variability in DOC leaching from soils, which is needed to better understand the drivers of DOC leaching and its impact on the local soil C budget. In this study, we use the land surface model ORCHILEAK to simulate the terrestrial C budget including leaching of DOC from the soil and its subsequent reactive transport through the river network of Europe. The model performance is not only evaluated against the sparse observations of DOC leaching, but also against the more abundant observations of fluxes and reactivity of DOC in rivers, providing further evidence that our simulated DOC leaching fluxes are realistic. The model is then used to simulate the spatio-temporal patterns of DOC leaching across Europe over the period 1972 to 2012, quantifying both the environmental drivers of these patterns as well as the impact of DOC leaching on the land C budget. Over the simulation period, we find that on average 14.3 TgC yr−1 of DOC is leached from land to European rivers, which is only about 0.6 % of the terrestrial net primary production, a fraction about one order of magnitude lower than reported for tropical river networks. Of the DOC leaching, on average 12.3 TgC yr−1 is exported to the coast via the river network, the rest being respired in transit. DOC leaching presents a large seasonal variability, with a maximum occurring in winter and a minimum in summer, except for the Northern most part of Europe where the maximum occurs in spring due to the snow melt. DOC leaching rate is generally lower in warm and dry regions, and higher in cold and wet regions of Europe. Furthermore, runoff, and the ratio between runoff from shallower flow paths vs. deep drainage and groundwater flow, is the main driver of the spatial variation of DOC leaching. Temperature, as a major control of DOC production and decomposition rates in the soils, plays only a secondary role.

Changes in winter and spring temperatures have been widely used to explain the diverse responses of spring phenology to climate change. However, our understanding of their respective roles remain incomplete. Using >300,000 in situ observations of leaf unfolding date (LUD) in Europe, we show that the advancement of LUD since 1950 is due both to accelerated spring thermal accumulation and changes in winter chilling which explain 61% and 39% of the LUD shifts, respectively. Winter warming did not substantially retard the releasing of bud dormancy, but increased the thermal requirement to reach leaf unfolding. The increase of thermal requirement and decreased efficiency of spring warming on accelerating thermal accumulation partly explained the temporally (1950s-2010s) decreasing response of LUD to warming. Our study stresses the need to better assess the antagonistic and heterogeneous effects of winter and spring warming on leaf phenology, which is key to projection of future vegetation-climate feedbacks.

Accurate monitoring of vegetation stress is required for better modelling and forecasting of primary production, in a world where heatwaves and droughts are expected to become increasingly prevalent. Variability in formaldehyde (HCHO) concentrations in the troposphere is dominated by local emissions of short-lived biogenic (BVOC) and pyrogenic volatile organic compounds. BVOCs are emitted by plants in a rapid protective response to abiotic stress, mediated by the energetic status of leaves (the excess of reducing power when photosynthetic light and dark reactions are decoupled, as occurs when stomata close in response to water stress). Emissions also increase exponentially with leaf temperature. New analytical methods for the detection of spatiotemporally contiguous extremes in remote-sensing data are applied here to satellite-derived atmospheric HCHO columns. BVOC emissions are shown to play a central role in the formation of the largest positive HCHO anomalies. Although vegetation stress can be captured by various remotely sensed quantities, spaceborne HCHO emerges as the most consistent recorder of vegetation responses to the largest climate extremes, especially in forested regions.

The spatio-temporal variability and the underlying drivers of the carbon dioxide (CO2) exchange at the air-water interface (FCO2) of the global coastal ocean are still poorly understood and their quantification remains highly uncertain. Here, we present an analysis of the spatial and seasonal variability of FCO2 using a high-resolution (0.25 degree) monthly climatology (1998-2015 period) for coastal sea surface partial pressure in CO2 (pCO2), globally.Overall, a clear latitudinal pattern emerges from our analysis regarding sources/sinks distribution of atmospheric CO2 and we find that in most regions, annual mean CO2 flux densities are comparable in sign and magnitude to those of the adjacent open ocean except for river dominated systems. Globally, coastal regions act as a CO2 sink with a more intense uptake occurring in summer because of the disproportionate influence of high latitude coastal seas in the Northern Hemisphere. The majority of the coastal seasonal FCO2 variations stems from the air-sea pCO2 gradient, although changes in wind speed and sea-ice cover can also be significant regionally. To investigate further the drivers of the spatio-seasonal variability, our observation-based pCO2 climatology is used in conjunction with global ocean biogeochemistry model MOM6-COBALT. The model outputs allow us to quantify the respective contributions of thermal effects, biology, and non-thermal physical processes (circulation and freshwater inputs) to seasonal variations in coastal pCO2. Generally, biological activity is the dominant driver of the pCO2 seasonal variability in temperate and high latitudes while thermal and non-thermal physical processes dominate in low latitudes.

Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land–atmospheric carbon exchange (NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global ‘bottom-up’ NEE for net land anthropogenic CO2 uptake of –2.2 ± 0.6 PgC yr−1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000–09. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2 of 39 PgC yr−1 with an interquartile of 33–46 PgC yr−1—a much smaller portion of net primary productivity than previously reported., info:eu-repo/semantics/published

International audience; We synthesized N2O emissions over North America using 17 bottom-up (BU) estimates from 1980–2016 and five top-down (TD) estimates from 1998 to 2016. The BU-based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007–2016, North American N2O emissions are estimated at 1.7 (1.0–3.0) Tg N yr−1 (BU) and 1.3 (0.9–1.5) Tg N yr−1 (TD). Anthropogenic emissions were twice as large as natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process-based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories.Nitrous oxide (N2O) is the third most important greenhouse gase (GHG) after CO2 and CH4 causing global warming. Among world regions, North America (defined herein as U.S., Canada, and Mexico) is the second largest source of N2O emissions globally, and previous source estimates for this region vary widely. This study aims to provide a comprehensive N2O assessment over North America including all available estimates based on a number of approaches. We report total emissions, and emissions from four anthropogenic source sectors, over the past four decades. Agriculture and industry are two major N2O sources in North America. Our results show a minor increase in the total N2O emission due to agricultural trends in the U.S. Our bottom-up estimate of U.S. agricultural N2O emissions are close to those in the EPA national GHG inventory that includes both empirical and model results. The high consistency suggests the need to take process-based modeling results into account for future national GHG inventories.

The contribution of continental shelves to the marine carbon cycle is still poorly understood. Their preindustrial state is, for one, essentially unknown, which strongly limits the quantitative assessment of their anthropogenic perturbation. To date, approaches developed to investigate and quantify carbon fluxes on continental shelves have strongly simplified their physical and biogeochemical features. In this study, we enhance the global ocean biogeochemistry model HAMburg Ocean Carbon Cycle by explicitly representing riverine loads of carbon and nutrients, as well as improving the representation of organic matter dynamics in the coastal ocean. Our simulations, at a resolution of similar to 0.4 degrees, reveal a globally averaged shelf water residence time (RT) of 12-17 months, which is much shorter than the global RTs previously assumed in benchmark studies (>4 years). This shorter global RT, induced primarily through outer shelf regions with large oceanic inflows, promotes an efficient offshore transport of terrestrial and marine organic carbon (0.44 PgCyr(-1)) and a dissolved inorganic carbon sink from the organic cycling of carbon on the global shelf (net ecosystem productivity [NEP] equal to +0.20 PgCyr(-1)). In turn, this autotrophic state of continental shelves contributes to a weak global preindustrial sink of atmospheric CO2 (0.04 PgCyr(-1)), dominated by extensive regions with large oceanic inflows and positive NEPs, such as the Patagonian shelf, the East China Sea and the outer North Sea. The contemporary global shelf CO2 uptake of 0.15 PgCyr(-1) furthermoresuggests that the anthropogenic CO2 uptake (0.11 PgCyr(-1)) on the global continental shelf is less efficient with respect to the open ocean.

The implications of climate change and other human perturbations on the oceanic carbon cycle are still associated with large uncertainties. Global-scale modelling studies are essential to investigate anthropogenic perturbations of oceanic carbon fluxes but, until now, they have not considered the impacts of temporal changes in riverine and atmospheric inputs of P and N on the marine net biological productivity (NPP) and air–sea CO2 exchange (FCO2). To address this, we perform a series of simulations using an enhanced version of the global ocean biogeochemistry model HAMOCC to isolate effects arising from (1) increasing atmospheric CO2 levels, (2) a changing physical climate and (3) alterations in inputs of terrigenous P and N on marine carbon cycling over the 1905–2010 period. Our simulations reveal that our first-order approximation of increased terrigenous nutrient inputs causes an enhancement of 2.15 Pg C year−1 of the global marine NPP, a relative increase of +5% over the simulation period. This increase completely compensates the simulated NPP decrease as a result of increased upper ocean stratification of −3% in relative terms. The coastal ocean undergoes a global relative increase of 14% in NPP arising largely from increased riverine inputs, with regional increases exceeding 100%, for instance on the shelves of the Bay of Bengal. The imprint of enhanced terrigenous nutrient inputs is also simulated further offshore, inducing a 1.75 Pg C year−1 (+4%) enhancement of the NPP in the open ocean. This finding implies that the perturbation of carbon fluxes through coastal eutrophication may extend further offshore than that was previously assumed. While increased nutrient inputs are the largest driver of change for the CO2 uptake at the regional scale and enhance the global coastal ocean CO2 uptake by 0.02 Pg C year−1, they only marginally affect the FCO2 of the open ocean over our study's timeline., SCOPUS: ar.j, info:eu-repo/semantics/published

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO 2 ), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO 2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO 2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO 2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO 2 emissions (including cement production) account for 2624 Tg CO 2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 ( ± 463 Tg CO 2 ). The inversion reports 2700 Tg CO 2 ( ± 480 Tg CO 2 ), which is well in line with the national inventories. Over 2011–2015, the CO 2 land sources and sinks from NGHGI estimates report −90 Tg C yr −1 ± 30 Tg C yr −1 while all other BU approaches report a mean sink of −98 Tg C yr −1 ( ± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr −1 ± 400 Tg C yr −1 ). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO 2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr-1 (EDGAR v5.0) and 19.0 Tg CH4 yr-1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr-1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr-1. Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4 yr-1) and surface network (24.4 Tg CH4 yr-1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 Tg CH4 yr-1. For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr-1, respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr-1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr-1, respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU+UK scale and at the national scale. The referenced datasets related to figures are visualized at. (Petrescu et al. 2020b)., SCOPUS: re.j, info:eu-repo/semantics/published

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results, and inverse modelling estimates, over the period 1990–2018. BU and TD products are compared with European national GHG inventories (NGHGI) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGI, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGI with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGI and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), well in line with the national inventories. Over 2011–2015, the CO2 land sources/sinks from NGHGI estimates report −90 Tg C yr−1 ± 30 Tg C while all other BU approaches report a mean sink of −98 Tg yr−1 (± 362 Tg C from DGVMs only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 T g C yr−1). This concludes that a) current independent approaches are consistent with NGHGI b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of CO2 flux obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288883 (Petrescu et al., 2020).

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).

Terrestrial ecosystems absorb, at present, about one-fourth of anthropogenic CO2 emissions, which is accumulating in the carbon (C) stocks of vegetation and soils. Land-surface models are used to project the 21st century evolution of this CO2 sink, which mitigates the expected increase in atmospheric CO2 concentration and, thus, climate change. However, classical land-surface models neglect that a fraction of the anthropogenic C absorbed by terrestrial ecosystems is not accumulating on land but is instead exported through the river network. Using the Amazon basin as a case study and a novel land-surface model that represents C exports through rivers, we prove that classical land-surface models such as those used for the Assessment Reports of the IPCC underestimate the CO2 uptake by terrestrial ecosystems and overestimate the amount of anthropogenic C sequestered within vegetation and soils. We provide reasons justifying that similar biases are to be expected at global scale., SCOPUS: ar.j, info:eu-repo/semantics/published

In this second part of a two-part study, we performed a simulation of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. The model results are evaluated for their ability to reproduce the fluxes of DOC and carbon dioxide (CO2) along the soil-inland-water continuum and the exchange of CO2 with the atmosphere, including the evasion outgassing of CO2 from inland waters. We present simulation results over the years 1901-2007 and show that the model is able to broadly reproduce observed state variables and their emergent properties across a range of interacting physical and biogeochemical processes. These include (1) net primary production (NPP), respiration and riverine hydrologic amplitude, seasonality, and inter-annual variation; (2) DOC concentrations, bulk annual flow, and their volumetric attribution at the sub-catchment level; (3) high headwater versus downstream CO2 evasion, an emergent phenomenon consistent with observations over a spectrum of high-latitude observational studies. These quantities obey emergent relationships with environmental variables like air temperature and topographic slope that have been described in the literature. This gives us confidence in reporting the following additional findings: of the ĝ'1/434TgCyr-1 left over as input to soil matter after NPP is diminished by heterotrophic respiration, 7TgCyr-1 is leached and transported into the aquatic system. Of this, over half (3.6TgCyr-1) is evaded from the inland water surface back into the atmosphere and the remainder (3.4TgCyr-1) flushed out into the Arctic Ocean, mirroring empirically derived studies. These riverine DOC exports represent ĝ'1/41.5% of NPP. DOC exported from the floodplains is dominantly sourced from recent more "labile" terrestrial production in contrast to DOC leached from the rest of the watershed with runoff and drainage, which is mostly sourced from recalcitrant soil and litter. All else equal, both historical climate change (a spring-summer warming of 1.8ĝ' C over the catchment) and rising atmospheric CO2 (+85.6ppm) are diagnosed from factorial simulations to contribute similar significant increases in DOC transport via primary production, although this similarity may not hold in the future., SCOPUS: ar.j, info:eu-repo/semantics/published

In contrast to the open ocean, the sources and sinks for atmospheric carbon dioxide (CO2) in the coastal seas are poorly constrained and understood. Here we address this knowledge gap by analyzing the spatial and temporal variability of the coastal air-sea flux of CO2 (FCO2) using a recent high-resolution (0.25°) monthly climatology for coastal sea surface partial pressure in CO2 (pCO2). Coastal regions are characterized by CO2 sinks at temperate and high latitudes and by CO2 sources at low latitude and in the tropics, with annual mean CO2 flux densities comparable in magnitude and pattern to those of the adjacent open ocean with the exception of river-dominated systems. The seasonal variations in FCO2 are large, often exceeding 2 mol C m−2 year−1, a magnitude similar to the variations exhibited across latitudes. The majority of these seasonal variations stems from the air-sea pCO2 difference, although changes in wind speed and sea ice cover can also be significant regionally. Globally integrated, the coastal seas act currently as a CO2 sink of −0.20 ± 0.02 Pg C year−1, with a more intense uptake occurring in summer because of the disproportionate influence of high-latitude shelves in the Northern Hemisphere. Combined with estimates of the carbon sinks in the open ocean and the Arctic, this gives for the global ocean, averaged over the 1998 to 2015 period an annual net CO2 uptake of −1.7 ± 0.3 Pg C year−1., SCOPUS: ar.j, info:eu-repo/semantics/published

We present the first version of OMEN-SED (Organic Matter ENabled SEDiment model), a new, onedimensional analytical early diagenetic model resolving organic matter cycling and the associated biogeochemical dynamics in marine sediments designed to be coupled to Earth system models. OMEN-SED explicitly describes organic matter (OM) cycling and the associated dynamics of the most important terminal electron acceptors (i.e. O2, NO3, SO4) and methane (CH4), related reduced substances (NH4, H2S), macronutrients (PO4) and associated pore water quantities (ALK, DIC). Its reaction network accounts for the most important primary and secondary redox reactions, equilibrium reactions, mineral dissolution and precipitation, as well as adsorption and desorption processes associated with OM dynamics that affect the dissolved and solid species explicitly resolved in the model. To represent a redox-dependent sedimentary P cycle we also include a representation of the formation and burial of Fe-bound P and authigenic Ca-P minerals. Thus, OMEN-SED is able to capture the main features of diagenetic dynamics in marine sediments and therefore offers similar predictive abilities as a complex, numerical diagenetic model. Yet, its computational efficiency allows for its coupling to global Earth system models and therefore the investigation of coupled global biogeochemical dynamics over a wide range of climate-relevant timescales. This paper provides a detailed description of the new sediment model, an extensive sensitivity analysis and an evaluation of OMEN-SED's performance through comprehensive comparisons with observations and results from a more complex numerical model. We find that solid-phase and dissolved pore water profiles for different ocean depths are reproduced with good accuracy and simulated terminal electron acceptor fluxes fall well within the range of globally observed fluxes. Finally, we illustrate its application in an Earth system model framework by coupling OMEN-SED to the Earth system model cGENIE and tune the OM degradation rate constants to optimise the fit of simulated benthic OM contents to global observations. We find that the simulated sediment characteristics of the coupled model framework, such as OM degradation rates, oxygen penetration depths and sediment-water interface fluxes, are generally in good agreement with observations and in line with what one would expect on a global scale. Coupled to an Earth system model, OMENSED is thus a powerful tool that will not only help elucidate the role of benthic-pelagic exchange processes in the evolution and the termination of a wide range of climate events, but will also allow for a direct comparison of model output with the sedimentary record - the most important climate archive on Earth., SCOPUS: ar.j, info:eu-repo/semantics/published

Constraints of temperature on spring plant phenology are closely related to plant growth, vegetation dynamics, and ecosystem carbon cycle. However, the effects of temperature on leaf onset, especially for winter chilling, are still not well understood. Using long-term, widespread in situ phenology observations collected over China for multiple plant species, this study analyzes the quantitative response of leaf onset to temperature, and compares empirical findings with existing theories and modeling approaches, as implemented in 18 phenology algorithms. Results show that the growing degree days (GDD) required for leaf onset vary distinctly among plant species and geographical locations as well as at organizational levels (species and community), pointing to diverse adaptation strategies. Chilling durations (CHD) needed for releasing bud dormancy decline monotonously from cold to warm areas with very limited interspecies variations. Results also reveal that winter chilling is a crucial component of phenology models, and its effect is better captured with an index that accounts for the inhomogeneous effectiveness of low temperature to chilling rate than with the conventional CHD index. The impact of spring warming on leaf onset is nonlinear, better represented by a logistical function of temperature than by the linear function currently implemented in biosphere models. The optimized base temperatures for thermal accumulation and the optimal chilling temperatures are species-dependent and average at 6.9 and 0.2°C, respectively. Overall, plants' chilling requirement is not a constant, and more chilling generally results in less requirement of thermal accumulation for leaf onset. Our results clearly demonstrate multiple deficiencies of the parameters (e.g., base temperature) and algorithms (e.g., method for calculating GDD) in conventional phenology models to represent leaf onset. Therefore, this study not only advances our mechanistic and quantitative understanding of temperature controls on leaf onset but also provides critical information for improving existing phenology models.

The river‐floodplain network plays an important role in the carbon (C) cycle of the Amazon basin, as it transports and processes a significant fraction of the C fixed by terrestrial vegetation, most of which evades as CO2 from rivers and floodplains back to the atmosphere. There is empirical evidence that exceptionally dry or wet years have an impact on the net C balance in the Amazon. While seasonal and interannual variations in hydrology have a direct impact on the amounts of C transferred through the river‐floodplain system, it is not known how far the variation of these fluxes affects the overall Amazon C balance. Here, we introduce a new wetland forcing file for the ORCHILEAK model, which improves the representation of floodplain dynamics and allows us to closely reproduce data‐driven estimates of net C exports through the river–floodplain network. Based on this new wetland forcing and two climate forcing datasets, we show that across the Amazon, the percentage of net primary productivity (NPP) lost to the river–floodplain system is highly variable at the interannual timescale, and wet years fuel aquatic CO2 evasion. However, at the same time overall net ecosystem productivity (NEP) and C sequestration are highest during wet years, partly due to reduced decomposition rates in water‐logged floodplain soils. It is years with the lowest discharge and floodplain inundation, often associated with El Nino events, that have the lowest NEP and the highest total (terrestrial plus aquatic) CO2 emissions back to atmosphere. Furthermore, we find that aquatic C fluxes display greater variation than terrestrial C fluxes, and that this variation significantly dampens the interannual variability in NEP of the Amazon basin. These results call for a more integrative view of the C fluxes through the vegetation‐soil‐river‐floodplain continuum, which directly places aquatic C fluxes into the overall C budget of the Amazon basin.