The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO
2 growth rate, fossil fuel emissions, and modeled (bottom‐up) land and ocean fluxes cannot be fully closed, leading to a ...“budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom‐up and top‐down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO
2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high‐resolution remote‐sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.
Key Points
Top‐down and bottom‐up estimates of net land‐atmosphere CO
2 fluxes agree well globally but show important mismatches at regional scales
Regional mismatches are dominated by differences between inversions and interannual variability in CO
2 fluxes
Mismatches between top‐down and bottom‐up data sets are explained by sensitivity to climate and by uncertainty in land use change forcing
Past characterizations of the land–ocean continuum were constructed either from a continental perspective through an analysis of watershed river basin properties (COSCATs: COastal Segmentation and ...related CATchments) or from an oceanic perspective, through a regionalization of the proximal and distal continental margins (LMEs: large marine ecosystems). Here, we present a global-scale coastal segmentation, composed of three consistent levels, that includes the whole aquatic continuum with its riverine, estuarine and shelf sea components. Our work delineates comprehensive ensembles by harmonizing previous segmentations and typologies in order to retain the most important physical characteristics of both the land and shelf areas. The proposed multi-scale segmentation results in a distribution of global exorheic watersheds, estuaries and continental shelf seas among 45 major zones (MARCATS: MARgins and CATchments Segmentation) and 149 sub-units (COSCATs). Geographic and hydrologic parameters such as the surface area, volume and freshwater residence time are calculated for each coastal unit as well as different hypsometric profiles. Our analysis provides detailed insights into the distributions of coastal and continental shelf areas and how they connect with incoming riverine fluxes. The segmentation is also used to re-evaluate the global estuarine CO2 flux at the air–water interface combining global and regional average emission rates derived from local studies.
Natural lakes and reservoirs are important yet not well‐constrained sources of greenhouse gasses to the atmosphere. In particular for N2O emissions, a huge variability is observed in the few, ...observation‐driven flux estimates that have been published so far. Recently, a process‐based, spatially explicit model has been used to estimate global N2O emissions from more than 6,000 reservoirs based on nitrogen (N) and phosphorous inflows and water residence time. Here we extend the model to a data set of 1.4 million standing water bodies comprising natural lakes and reservoirs. For validation, we normalized the simulated N2O emissions by the surface area of each water body and compared them against regional averages of N2O emission rates taken from the literature or estimated based on observed N2O concentrations. We estimate that natural lakes and reservoirs together emit 4.5 ± 2.9 Gmol N2O‐N year−1 globally. Our global‐scale estimate falls in the far lower end of existing, observation‐driven estimates. Natural lakes contribute only about half of this flux, although they contribute 91% of the total surface area of standing water bodies. Hence, the mean N2O emission rates per surface area are substantially lower for natural lakes than for reservoirs with 0.8 ± 0.5 versus 9.6 ± 6.0 mmol N·m−2·year−1, respectively. This finding can be explained by on average lower external N inputs to natural lakes. We conclude that upscaling‐based estimates, which do not distinguish natural lakes from reservoirs, are prone to important biases.
Key Points
Global N2O emission from natural lakes and reservoirs estimated at 4.5 ± 2.9 Gmol N year‐1
Natural lakes emit less N2O than reservoirs
North America and Europe contribute nearly half of global N2O emission from natural lakes and reservoirs
This regional study quantifies the CO2 exchange at the air-water interface along the land-ocean aquatic continuum (LOAC) of the northeast North American coast, from streams to the shelf break. Our ...analysis explicitly accounts for spatial and seasonal variability in the CO2 fluxes. The yearly integrated budget reveals the gradual change in the intensity of the CO2 exchange at the air-water interface, from a strong source towards the atmosphere in streams and rivers (3.0 ± 0.5 TgC yr-1) and estuaries (0.8 ± 0.5 TgC yr-1) to a net sink in continental shelf waters (-1.7 ± 0.3 TgC yr-1). Significant differences in flux intensity and their seasonal response to climate variations is observed between the North and South sections of the study area, both in rivers and coastal waters. Ice cover, snowmelt, and intensity of the carbon removal efficiency through the estuarine filter are identified as important control factors of the observed spatiotemporal variability in CO2 exchange along the LOAC.
•France, Italy, Romania and Hungary could dominate soybean expansion in EU.•Avg. crop water deficit for soybean lower in France than in Italy, Romania, Hungary.•Maize-soybean conversion increases ...avg. crop water deficit by 49.0±22.1 mm season−1.•Model results are sensitive to choice of crop calendars and assumed root depth.•In general, later planting dates appear to reduce crop water deficit.
The EU imports large quantities of soybeans, mainly for livestock feed. However, there is a trend to increase domestic soybean production and reduce imports. In this study, we investigate the potential impact of an increased EU soybean cultivation on evapotranspiration (ET), water deficit, and irrigation needs. We focus on the consequences of replacing maize with soybeans, as both crops have similar cropping periods and high water demands. We implement a simple, well established crop water model that estimates crop water deficit (ETd) as the difference between simulated potential (ETc) and actual (ETa) ET. We apply this model over the EU from 2001 to 2020, using data on daily reference ET and precipitation, soil hydrological properties and three different crop calendars. Results indicate that a maize-to-soybean conversion would result in an average ETd increase of 49.0±22.1 mm season−1 across the EU. In the four countries of France, Italy, Hungary and Romania, where most of the additional soybean production would be allocated, crop water deficits would increase on average by 21-34% compared to that of maize, following an increased ETc and/or decreased ETa. However, the decrease in ETa is largely due to an assumed shorter root depth for soybean, while recent empirical results suggest that both crops may actually have comparable root depths. Using the same root depth for maize and soybean, the simulated average increase in ETd amounts to only 28.2±18.3 mm season−1. Our results are sensitive to the choice of crop calendar, with reduced ETd for later sowing dates .
Erosion is an Earth system process that transports carbon laterally across the land surface and is currently accelerated by anthropogenic activities. Anthropogenic land cover change has accelerated ...soil erosion rates by rainfall and runoff substantially, mobilizing vast quantities of soil organic carbon (SOC) globally. At timescales of decennia to millennia this mobilized SOC can significantly alter previously estimated carbon emissions from land use change (LUC). However, a full understanding of the impact of erosion on land–atmosphere carbon exchange is still missing. The aim of this study is to better constrain the terrestrial carbon fluxes by developing methods compatible with land surface models (LSMs) in order to explicitly represent the links between soil erosion by rainfall and runoff and carbon dynamics. For this we use an emulator that represents the carbon cycle of a LSM, in combination with the Revised Universal Soil Loss Equation (RUSLE) model. We applied this modeling framework at the global scale to evaluate the effects of potential soil erosion (soil removal only) in the presence of other perturbations of the carbon cycle: elevated atmospheric CO2, climate variability, and LUC. We find that over the period AD 1850–2005 acceleration of soil erosion leads to a total potential SOC removal flux of 74±18 Pg C, of which 79 %–85 % occurs on agricultural land and grassland. Using our best estimates for soil erosion we find that including soil erosion in the SOC-dynamics scheme results in an increase of 62 % of the cumulative loss of SOC over 1850–2005 due to the combined effects of climate variability, increasing atmospheric CO2 and LUC. This additional erosional loss decreases the cumulative global carbon sink on land by 2 Pg of carbon for this specific period, with the largest effects found for the tropics, where deforestation and agricultural expansion increased soil erosion rates significantly. We conclude that the potential effect of soil erosion on the global SOC stock is comparable to the effects of climate or LUC. It is thus necessary to include soil erosion in assessments of LUC and evaluations of the terrestrial carbon cycle.
The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these ...latitudes, two carbon pools of planetary significance – those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest – are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.
Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires ...detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed.
Soil erosion by rainfall and runoff is an important process behind the redistribution of soil organic carbon (SOC) over land, thereby impacting the exchange of carbon (C) between land, atmosphere, ...and rivers. However, the net role of soil erosion in the global C cycle is still unclear as it involves small-scale SOC removal, transport, and redeposition processes that can only be addressed over selected small regions with complex models and measurements. This leads to uncertainties in future projections of SOC stocks and complicates the evaluation of strategies to mitigate climate change through increased SOC sequestration.
As the second largest area of contiguous tropical rainforest and second
largest river basin in the world, the Congo Basin has a significant role to
play in the global carbon (C) cycle. For the ...present day, it has been shown
that a significant proportion of global terrestrial net primary productivity (NPP) is transferred laterally to the land–ocean aquatic continuum (LOAC) as dissolved CO2, dissolved organic carbon (DOC), and particulate organic carbon (POC). Whilst the importance of LOAC fluxes in the Congo Basin has been demonstrated for the present day, it is not known to what extent these fluxes have been perturbed historically, how they are likely to change under future climate change and land use scenarios, and in turn what impact these changes might have on the overall C cycle of the basin. Here we apply the ORCHILEAK model to the Congo Basin and estimate that 4 % of terrestrial NPP (NPP = 5800±166 Tg C yr−1) is currently exported from soils and vegetation to inland waters. Further, our results suggest that aquatic C fluxes may have undergone considerable perturbation since 1861 to
the present day, with aquatic CO2 evasion and C export to the coast increasing by 26 % (186±41 to 235±54 Tg C yr−1) and 25 % (12±3 to 15±4 Tg C yr−1), respectively, largely because of rising atmospheric CO2 concentrations. Moreover, under climate scenario RCP6.0 we predict that this perturbation could continue; over the full simulation period (1861–2099), we estimate that aquatic CO2 evasion and C export to the coast could increase by 79 % and 67 %, respectively. Finally, we show that the proportion of terrestrial NPP lost to the LOAC could increase from approximately 3 % to 5 % from 1861–2099 as a result of increasing atmospheric CO2 concentrations and climate change. However, our future projections of the Congo Basin C fluxes in particular need to be interpreted with some caution due to model limitations. We discuss these limitations, including the wider challenges associated with applying the current generation of land surface models which ignore nutrient dynamics to make future projections of the tropical C cycle, along with potential next steps.
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