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Grasslands absorb and release carbon dioxide (CO 2 ), emit methane (CH 4 ) from grazing livestock, and emit nitrous oxide (N 2 O) from soils. Little is known about how the fluxes of these three greenhouse gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO 2 and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of greenhouse gas, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO 2 and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce greenhouse gas emissions from managed grasslands. Grasslands, and the livestock that live there, are dynamic sources and sinks of greenhouse gases, but what controls these fluxes remains poorly characterized. Here the authors show that on the global level, grasslands are climate neutral owing to the cancelling effects of managed vs. natural systems.

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 availability of phosphorus (P) and nitrogen (N) constrains the ability of ecosystems to use resources such as light, water and carbon. In turn, nutrients impact the distribution of productivity, ecosystem carbon turnovers and their net exchange of CO2 with the atmosphere in response to variation of environmental conditions in both space and time. In this study, we evaluated the performance of the global version of the land surface model ORCHIDEE-CNP (v1.2), which explicitly simulates N and P biogeochemistry in terrestrial ecosystems coupled with carbon, water and energy transfers. We used data from remote sensing, ground-based measurement networks and ecological databases. Components of the N and P cycle at different levels of aggregation (from local to global) are in good agreement with data-driven estimates. When integrated for the period 1850 to 2017 forced with variable climate, rising CO2 and land use change, we show that ORCHIDEE-CNP underestimates the land carbon sink in the Northern Hemisphere (NH) during recent decades despite an a priori realistic gross primary productivity (GPP) response to rising CO2. This result suggests either that processes other than CO2 fertilization, which are omitted in ORCHIDEE-CNP such as changes in biomass turnover, are predominant drivers of the northern land sink and/or that the model parameterizations produce emerging nutrient limitations on biomass growth that are too strict in northern areas. In line with the latter, we identified biases in the simulated large-scale patterns of leaf and soil stoichiometry as well as plant P use efficiency, pointing towards P limitations that are too severe towards the poles. Based on our analysis of ecosystem resource use efficiencies and nutrient cycling, we propose ways to address the model biases by giving priority to better representing processes of soil organic P mineralization and soil inorganic P transformation, followed by refining the biomass production efficiency under increasing atmospheric CO2, phenology dynamics and canopy light absorption.

Global water erosion strongly affects the terrestrial carbon balance. However, this process is currently ignored by most global land surface models (LSMs) that are used to project the responses of terrestrial carbon storage to climate and land use changes. One of the main obstacles to implement erosion processes in LSMs is the high spatial resolution needed to accurately represent the effect of topography on soil erosion and sediment delivery to rivers. In this study, we present an upscaling scheme for including erosion‐induced lateral soil organic carbon (SOC) movements into the ORCHIDEE LSM. This upscaling scheme integrates information from high‐resolution (3″) topographic and soil erodibility data into a LSM forcing file at 0.5° spatial resolution. Evaluation of our model for the Rhine catchment indicates that it reproduces well the observed spatial and temporal (both seasonal and interannual) variations in river runoff and the sediment delivery from uplands to the river network. Although the average annual lateral SOC flux from uplands to the Rhine River network only amounts to 0.5% of the annual net primary production and 0.01% of the total SOC stock in the whole catchment, SOC loss caused by soil erosion over a long period (e.g., thousands of years) has the potential to cause a 12% reduction in the simulated equilibrium SOC stocks. Overall, this study presents a promising approach for including the erosion‐induced lateral carbon flux from the land to aquatic systems into LSMs and highlights the important role of erosion processes in the terrestrial carbon balance. Plain Language Summary Global land surface models (LSMs) are the main tools used to simulate the terrestrial carbon (C) cycle and to predict its response to climate and land cover changes. Currently, the processes of vertical C fluxes between soils, plants, and the atmosphere (e.g., photosynthesis, plant growth, and litter and soil organic matter decomposition) has been well represented in many LSMs; however, the lateral soil C delivery through the river network caused by water erosion is still missing in most LSMs. This study introduces a LSM approach which is suitable to simulate the large‐scale soil C delivery from upland soils to inland waters at high temporal resolution (daily) and accounting for the small‐scale (~90 m) spatial variability in topography and soil properties. Evaluation of our model in the Rhine catchment demonstrates a good performance with regard to reproducing the spatial and temporal (daily, seasonal, and interannual) variability of soil C delivery rate from uplands to river networks at large spatial scale and for exploring the impacts of changes in vegetation cover (land use change) and climate (e.g., changes in rainfall amounts and regimes) on the regional soil C balance. Key Points We presented an upscaling scheme for including erosion‐induced lateral soil and carbon transfers into a global land surface model Our model is a useful tool to estimate the impacts of climate and land cover changes on erosion‐induced soil carbon loss at large scale Model application for the Rhine basin demonstrates that erosion‐induced soil carbon losses substantially reduce soil carbon stocks

Currently, the anthropogenic perturbation of the biogeochemical cycles remains unquantified due to the poor representation of lateral fluxes of carbon and nutrients in Earth system models (ESMs). This lateral transport of carbon and nutrients between terrestrial ecosystems is strongly affected by accelerated soil erosion rates. However, the quantification of global soil erosion by rainfall and runoff, and the resulting redistribution is missing. This study aims at developing new tools and methods to estimate global soil erosion and redistribution by presenting and evaluating a new large-scale coarse-resolution sediment budget model that is compatible with ESMs. This model can simulate spatial patterns and long-term trends of soil redistribution in floodplains and on hillslopes, resulting from external forces such as climate and land use change. We applied the model to the Rhine catchment using climate and land cover data from the Max Planck Institute Earth System Model (MPI-ESM) for the last millennium (here AD 850–2005). Validation is done using observed Holocene sediment storage data and observed scaling between sediment storage and catchment area. We find that the model reproduces the spatial distribution of floodplain sediment storage and the scaling behavior for floodplains and hillslopes as found in observations. After analyzing the dependence of the scaling behavior on the main parameters of the model, we argue that the scaling is an emergent feature of the model and mainly dependent on the underlying topography. Furthermore, we find that land use change is the main contributor to the change in sediment storage in the Rhine catchment during the last millennium. Land use change also explains most of the temporal variability in sediment storage in floodplains and on hillslopes.

The construction of terraces is a key soil conservation practice on agricultural land in China providing multiple valuable ecosystem services. Accurate spatial information on terraces is needed for both management and research. In this study, the first 30 m resolution terracing map of the entire territory of China is produced by a supervised pixel-based classification using multisource and multi-temporal data based on the Google Earth Engine (GEE) platform. We extracted time-series spectral features and topographic features from Landsat 8 images and the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) data, classifying cropland area (cultivated land of Globeland30) into terraced and non-terraced types through a random forest classifier. The overall accuracy and kappa coefficient were evaluated by 10 875 test samples and achieved values of 94 % and 0.72, respectively. For terrace class, the producer's accuracy (PA) was 79.945 %, and the user's accuracy (UA) was 71.149 %. The classification performed best in the Loess Plateau and southwestern China, where terraces are most numerous. Some northeastern, eastern-central, and southern areas had relatively high uncertainty. Typical errors in the mapping results are from the sloping cropland (non-terrace cropland with a slope of ≥ 5∘), low-slope terraces, and non-crop vegetation. Terraces are widely distributed in China, and the total terraced area was estimated to be 53.55 Mha (i.e., 26.43 % of China's cropland area) by pixel counting (PC) method and 58.46 ± 2.99 Mha (i.e., 28.85 % ± 1.48 % of China's cropland area) by error-matrix-based model-assisted estimation (EM) method. Elevation and slope were identified as the main features in the terrace/non-terrace classification, and multi-temporal spectral features (such as percentiles of NDVI, TIRS2, and BSI) were also essential. Terraces are more challenging to identify than other land use types because of the intra-class feature heterogeneity, interclass feature similarity, and fragmented patches, which should be the focus of future research. Our terrace mapping algorithm can be used to map large-scale terraces in other regions globally, and our terrace map will serve as a landmark for studies on multiple ecosystem service assessments including erosion control, carbon sequestration, and biodiversity conservation. The China terrace map is available to the public at https://doi.org/10.5281/zenodo.3895585 (Cao et al., 2020).

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.In this study we present the parsimonious process-based Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the C cycle along a cascade of hillslopes, floodplains, and rivers. The model simulates horizontal soil and C transfers triggered by erosion across landscapes and the resulting changes in land–atmosphereCO2 fluxes at a resolution of about 8 km at the catchment scale. CE-DYNAM is the result of the coupling of a previously developed coarse-resolution sediment budget model and the ecosystem C cycle and erosion removal model derived from the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model. CE-DYNAM is driven by spatially explicit historical land use change, climate forcing, and global atmospheric CO2 concentrations, affecting ecosystem productivity, erosion rates, and residence times of sediment and C in deposition sites. The main features of CE-DYNAM are (1) the spatially explicit simulation of sediment and C fluxes linking hillslopes and floodplains, (2) the relatively low number of parameters that allow for running the model at large spatial scales and over long timescales, and (3) its compatibility with global land surface models, thereby providing opportunities to study the effect of soil erosion under global changes.We present the model structure, concepts, limitations, and evaluation at the scale of the Rhine catchment for the period 1850–2005 CE (Common Era). Model results are validated against independent estimates of gross and net soil and C erosion rates and the spatial variability of SOC stocks from high-resolution modeling studies and observational datasets. We show that despite local differences, the resulting soil and C erosion rates, as well as SOC stocks from CE-DYNAM, are comparable to high-resolution estimates and observations at subbasin level.We find that soil erosion mobilized around 66±28 Tg (1012 g) of C under changing climate and land use over the non-Alpine region of the Rhine catchment over the entire period, assuming that the erosion loop of the C cycle was nearly steady state by 1850. This caused a net C sink equal to 2.1 %–2.7 % of the net primary productivity of the non-Alpine region over 1850–2005 CE. This sink is a result of the dynamic replacement of C on eroding sites that increases in this period due to rising atmosphericCO2 concentrations enhancing the litter C input to the soil from primary production.

Lateral carbon transport from soils to the ocean through rivers has been acknowledged as a key component of the global carbon cycle, but it is still neglected in most global land surface models (LSMs). Fluvial transport of dissolved organic carbon (DOC) and CO 2 has been implemented in the ORCHIDEE LSM, while erosion-induced delivery of sediment and particulate organic carbon (POC) from land to river was implemented in another version of the model. Based on these two developments, we take the final step towards the full representation of biospheric carbon transport through the land-river continuum. The newly developed model, called ORCHIDEE-C lateral , simulates the complete lateral transport of water, sediment, POC, DOC, and CO 2 from land to sea through the river network, the deposition of sediment and POC in the river channel and floodplains, and the decomposition of POC and DOC in transit. We parameterized and evaluated ORCHIDEE-C lateral using observation data in Europe. The model explains 94 %, 75 %, and 83 % of the spatial variations of observed riverine water discharges, bankfull water flows, and riverine sediment discharges in Europe, respectively. The simulated long-term average total organic carbon concentrations and DOC concentrations in river flows are comparable to the observations in major European rivers, although our model generally overestimates the seasonal variation of riverine organic carbon concentrations. Application of ORCHIDEE-C lateral for Europe reveals that the lateral carbon transfer affects land carbon dynamics in multiple ways, and omission of this process in LSMs may lead to an overestimation of 4.5 % in the simulated annual net terrestrial carbon uptake over Europe. Overall, this study presents a useful tool for simulating large-scale lateral carbon transfer and for predicting the feedbacks between lateral carbon transfer and future climate and land use changes.

Lateral carbon transport from soils to the ocean through rivers has been acknowledged as a key component of the global carbon cycle, but it is still neglected in most global land surface models (LSMs). Fluvial transport of dissolved organic carbon (DOC) and CO 2 has been implemented in the ORCHIDEE LSM, while erosion-induced delivery of sediment and particulate organic carbon (POC) from land to river was implemented in another version of the model. Based on these two developments, we take the final step towards the full representation of biospheric carbon transport through the land-river continuum. The newly developed model, called ORCHIDEE-C lateral , simulates the complete lateral transport of water, sediment, POC, DOC, and CO 2 from land to sea through the river network, the deposition of sediment and POC in the river channel and floodplains, and the decomposition of POC and DOC in transit. We parameterized and evaluated ORCHIDEE-C lateral using observation data in Europe. The model explains 94 %, 75 %, and 83 % of the spatial variations of observed riverine water discharges, bankfull water flows, and riverine sediment discharges in Europe, respectively. The simulated long-term average total organic carbon concentrations and DOC concentrations in river flows are comparable to the observations in major European rivers, although our model generally overestimates the seasonal variation of riverine organic carbon concentrations. Application of ORCHIDEE-C lateral for Europe reveals that the lateral carbon transfer affects land carbon dynamics in multiple ways, and omission of this process in LSMs may lead to an overestimation of 4.5 % in the simulated annual net terrestrial carbon uptake over Europe. Overall, this study presents a useful tool for simulating large-scale lateral carbon transfer and for predicting the feedbacks between lateral carbon transfer and future climate and land use changes.