Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution.

Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.

Increasing calcium scarcity along Afrotropical forest succession.

Secondary forests constitute an increasingly important component of tropical forests worldwide. Although cycling of essential nutrients affects recovery trajectories of secondary forests, the effect of nutrient limitation on forest regrowth is poorly constrained. Here we use three lines of evidence from secondary forest succession sequences in central Africa to identify potential nutrient limitation in regrowing forests. First, we show that atmospheric phosphorus supply exceeds demand along forest succession, whereas forests rely on soil stocks to meet their base cation demands. Second, soil nutrient metrics indicate that available phosphorus increases along the succession, whereas available cations decrease. Finally, fine root, foliar and litter stoichiometry show that tissue calcium concentrations decline relative to those of nitrogen and phosphorus during succession. Taken together, these observations suggest that calcium becomes an increasingly scarce resource in central African forests during secondary succession. Furthermore, ecosystem calcium storage shifts from soil to woody biomass over succession, making it a vulnerable nutrient in the wake of land-use change scenarios that involve woody biomass export. Our results thus call for a broadened focus on elements other than nitrogen and phosphorus regarding tropical forest biogeochemical cycles and identify calcium as a scarce and potentially limiting nutrient in an increasingly disturbed and dynamic tropical forest landscape.

Low N2O and variable CH4 fluxes from tropical forest soils of the Congo Basin.

Globally, tropical forests are assumed to be an important source of atmospheric nitrous oxide (N2O) and sink for methane (CH4). Yet, although the Congo Basin comprises the second largest tropical forest and is considered the most pristine large basin left on Earth, in situ N2O and CH4 flux measurements are scarce. Here, we provide multi-year data derived from on-ground soil flux (n = 1558) and riverine dissolved gas concentration (n = 332) measurements spanning montane, swamp, and lowland forests. Each forest type core monitoring site was sampled at least for one hydrological year between 2016 - 2020 at a frequency of 7-14 days. We estimate a terrestrial CH4 uptake (in kg CH4-C ha-1 yr-1) for montane (-4.28) and lowland forests (-3.52) and a massive CH4 release from swamp forests (non-inundated 2.68; inundated 341). All investigated forest types were a N2O source (except for inundated swamp forest) with 0.93, 1.56, 3.5, and -0.19 kg N2O-N ha-1 yr-1 for montane, lowland, non-inundated swamp, and inundated swamp forests, respectively.

Fire-derived phosphorus fertilization of African tropical forests.

Central African tropical forests face increasing anthropogenic pressures, particularly in the form of deforestation and land-use conversion to agriculture. The long-term effects of this transformation of pristine forests to fallow-based agroecosystems and secondary forests on biogeochemical cycles that drive forest functioning are poorly understood. Here, we show that biomass burning on the African continent results in high phosphorus (P) deposition on an equatorial forest via fire-derived atmospheric emissions. Furthermore, we show that deposition loads increase with forest regrowth age, likely due to increasing canopy complexity, ranging from 0.4 kg P ha-1 yr-1 on agricultural fields to 3.1 kg P ha-1 yr-1 on old secondary forests. In forest systems, canopy wash-off of dry P deposition increases with rainfall amount, highlighting how tropical forest canopies act as dynamic reservoirs for enhanced addition of this essential plant nutrient. Overall, the observed P deposition load at the study site is substantial and demonstrates the importance of canopy trapping as a pathway for nutrient input into forest ecosystems.

Towards Mapping of Soil Crust Using Multispectral Imaging.

Soil crusts and surface roughness are properties which are highly dynamic in both space and time that change in response to biotic processes, meteorological conditions and farming operations. These factors, however, are difficult to quantify and are usually described using simplified expert-based classes. This hampers a clear identification of the controlling factors and their relation to soil erosion and sediment generation processes. The availability of new small portable multispectral cameras offers the potential to study soil surface dynamics at a high spatial and temporal resolution. The objective of this study was to analyse the relationship between soil crusting, represented by cumulative rainfall kinetic energy, and soil surface reflectance, as derived from vis-NIR multispectral imaging. We designed a series of rainfall-soil surface experiments to disentangle the effects of soil crusting on spectral reflectance factors from those related to surface micro-scale roughness. Partial least squared regression (PLSR) models were developed to predict both kinetic energy and roughness from multispectral images. We evaluated different roughness removal methods which were based on the transformation of reflectance through standard normal variate (SNV) and roughness thresholding using high resolution digital elevation models. Furthermore, we assigned the light scattering effect related to roughness in the multispectral spatial domain by calculating the inter-quantile range of the reflectance values in a kernel. Our experiments and workflow demonstrate that it is possible to model crust development, using rainfall kinetic energy as a proxy, from vis-NIR based multispectral imaging.

Simulating Erosion-Induced Soil and Carbon Delivery From Uplands to Rivers in a Global Land Surface Model.

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.

Plutonium aided reconstruction of caesium atmospheric fallout in European topsoils.

Global nuclear weapon testing and the Chernobyl accident have released large amounts of radionuclides into the environment. However, to date, the spatial patterns of these fallout sources remain poorly constrained. Fallout radionuclides (137Cs, 239Pu, 240Pu) were measured in soil samples (n = 160) collected at flat, undisturbed grasslands in Western Europe in the framework of a harmonised European soil survey. We show that both fallout sources left a specific radionuclide imprint in European soils. Accordingly, we used plutonium to quantify contributions of global versus Chernobyl fallout to 137Cs found in European soils. Spatial prediction models allowed for a first assessment of the global versus Chernobyl fallout pattern across national boundaries. Understanding the magnitude of these fallout sources is crucial not only to establish a baseline in case of future radionuclide fallout but also to define a baseline for geomorphological reconstructions of soil redistribution due to soil erosion processes.

Mobilization of aged and biolabile soil carbon by tropical deforestation.

In the mostly pristine Congo Basin, agricultural land-use change has intensified in recent years. One potential and understudied consequence of this deforestation and conversion to agriculture is the mobilization and loss of organic matter from soils to rivers as dissolved organic matter. Here, we quantify and characterize dissolved organic matter sampled from 19 catchments of varying deforestation extent near Lake Kivu over a two-week period during the wet season. Dissolved organic carbon from deforested, agriculturally-dominated catchments was older (14C age: ~1.5kyr) and more biolabile than from pristine forest catchments. Ultrahigh-resolution mass spectrometry revealed that this aged organic matter from deforested catchments was energy-rich and chemodiverse, with higher proportions of nitrogen- and sulfur-containing formulae. Given the molecular composition and biolability, we suggest that organic matter from deforested landscapes is preferentially respired upon disturbance, resulting in elevated in-stream concentrations of carbon dioxide. We estimate that while deforestation reduces the overall flux of dissolved organic carbon by ~56%, it does not significantly change the yield of biolabile dissolved organic carbon. Ultimately, the exposure of deeper soil horizons through deforestation and agricultural expansion releases old, previously stable, and biolabile soil organic carbon into the modern carbon cycle via the aquatic pathway.

Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion.

The main purpose was to compare discrimination and reliability of four machine learning models to create gully erosion susceptibility map (GESM) in a part of Ekbatan Dam Basin, Hamedan, western Iran. Extensive field surveys using GPS, and the visual interpretation of satellite images, used to prepare a digital map of the spatial distribution of gullies. 130 locations were sampled to elucidate the spatial distribution of the soil surface properties. Topographic attributes were provided from digital elevation model (DEM). The land use and normalized difference vegetation index (NDVI) maps were created by satellite imagery. The functional relationships between gully erosion and controlling factors were calculated using the random forest (RF), support vector machine (SVM), Naïve Bayes (NB), and generalized additive model (GAM) models. The performance of models was evaluated by 10-fold cross-validation based on efficiency, Kappa coefficient, receiver operating characteristic curve (ROC), mean absolute error (MAE), and root mean square error (RMSE). The results showed that the RF model had the highest amount of efficiency, Kappa coefficient, and AUC and the lowest amounts of MAE and RMSE compared with SVM, NB, and GAM. The RF model showed the highest predictive performance (mean AUC = 92.4%), followed by SVM (mean AUC = 90.9%), GAM (mean AUC = 89.9%), and NB (mean AUC = 87.2%) models. Overall accuracy of the models ranged from excellent (NB, GAM) to outstanding (RF, SVM) classes. The capacity of all models for creating GESM was quite stable when the calibration and validation samples were changed through10-fold cross-validation technique. According to variable importance analysis performed by RF model, the most important variables are distance from rivers, calcium carbonate equivalent (CCE), and topographic position index (TPI). The obtained maps can help identifying areas at risk of gully erosion and facilitate the implementation of plans for soil conservation and sustainable management.

Global rainfall erosivity assessment based on high-temporal resolution rainfall records.

The exposure of the Earth's surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha-1 h-1 yr-1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

Phosphorus in agricultural soils: drivers of its distribution at the global scale.

Phosphorus (P) availability in soils limits crop yields in many regions of the World, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global data sets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analysed both the labile inorganic P (PILAB ), a proxy of the pool involved in plant nutrition and the total soil P (PTOT ). We found that the soil biogeochemical background corresponding to P inherited from natural soils at the conversion to agriculture (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between PTOT vs. PILAB . When the spatial variability was computed between grid cells at half-degree resolution, we found that almost all of the PTOT spatial variability could be explained by BIOG, while BIOG and FARM explained 38% and 63% of PILAB spatial variability, respectively. Our work also showed that the driver contribution was sensitive to the spatial scale characterizing the variability (grid cell vs. continent) and to the region of interest (global vs. tropics for instance). In particular, the heterogeneity of farming practices between continents was large enough to make FARM contribute to the variability in PTOT at that scale. We thus demonstrated how the different drivers were combined to explain the global distribution of agricultural soil P. Our study is also a promising approach to investigate the potential effect of P as a limiting factor for agroecosystems at the global scale.

Lateral transport of soil carbon and land-atmosphere CO2 flux induced by water erosion in China.

Soil erosion by water impacts soil organic carbon stocks and alters CO2 fluxes exchanged with the atmosphere. The role of erosion as a net sink or source of atmospheric CO2 remains highly debated, and little information is available at scales larger than small catchments or regions. This study attempts to quantify the lateral transport of soil carbon and consequent land-atmosphere CO2 fluxes at the scale of China, where severe erosion has occurred for several decades. Based on the distribution of soil erosion rates derived from detailed national surveys and soil carbon inventories, here we show that water erosion in China displaced 180 ± 80 Mt C⋅y(-1) of soil organic carbon during the last two decades, and this resulted a net land sink for atmospheric CO2 of 45 ± 25 Mt C⋅y(-1), equivalent to 8-37% of the terrestrial carbon sink previously assessed in China. Interestingly, the "hotspots," largely distributed in mountainous regions in the most intensive sink areas (>40 g C⋅m(-2)⋅y(-1)), occupy only 1.5% of the total area suffering water erosion, but contribute 19.3% to the national erosion-induced CO2 sink. The erosion-induced CO2 sink underwent a remarkable reduction of about 16% from the middle 1990s to the early 2010s, due to diminishing erosion after the implementation of large-scale soil conservation programs. These findings demonstrate the necessity of including erosion-induced CO2 in the terrestrial budget, hence reducing the level of uncertainty.

Modelling the impact of agricultural management on soil carbon stocks at the regional scale: the role of lateral fluxes.

Agricultural management has received increased attention over the last decades due to its central role in carbon (C) sequestration and greenhouse gas mitigation. Yet, regardless of the large body of literature on the effects of soil erosion by tillage and water on soil organic carbon (SOC) stocks in agricultural landscapes, the significance of soil redistribution for the overall C budget and the C sequestration potential of land management options remains poorly quantified. In this study, we explore the role of lateral SOC fluxes in regional scale modelling of SOC stocks under three different agricultural management practices in central Belgium: conventional tillage (CT), reduced tillage (RT) and reduced tillage with additional carbon input (RT+i). We assessed each management scenario twice: using a conventional approach that did not account for lateral fluxes and an alternative approach that included soil erosion-induced lateral SOC fluxes. The results show that accounting for lateral fluxes increased C sequestration rates by 2.7, 2.5 and 1.5 g C m(-2)  yr(-1) for CT, RT and RT+i, respectively, relative to the conventional approach. Soil redistribution also led to a reduction of SOC concentration in the plough layer and increased the spatial variability of SOC stocks, suggesting that C sequestration studies relying on changes in the plough layer may underestimate the soil's C sequestration potential due to the effects of soil erosion. Additionally, lateral C export from cropland was in the same of order of magnitude as C sequestration; hence, the fate of C exported from cropland into other land uses is crucial to determine the ultimate impact of management and erosion on the landscape C balance. Consequently, soil management strategies targeting C sequestration will be most effective when accompanied by measures that reduce soil erosion given that erosion loss can balance potential C uptake, particularly in sloping areas.

Legacy of human-induced C erosion and burial on soil-atmosphere C exchange.

Carbon exchange associated with accelerated erosion following land cover change is an important component of the global C cycle. In current assessments, however, this component is not accounted for. Here, we integrate the effects of accelerated C erosion across point, hillslope, and catchment scale for the 780-km(2) Dijle River catchment over the period 4000 B.C. to A.D. 2000 to demonstrate that accelerated erosion results in a net C sink. We found this long-term C sink to be equivalent to 43% of the eroded C and to have offset 39% (17-66%) of the C emissions due to anthropogenic land cover change since the advent of agriculture. Nevertheless, the erosion-induced C sink strength is limited by a significant loss of buried C in terrestrial depositional stores, which lagged the burial. The time lag between burial and subsequent loss at this study site implies that the C buried in eroded terrestrial deposits during the agricultural expansion of the last 150 y cannot be assumed to be inert to further destabilization, and indeed might become a significant C source. Our analysis exemplifies that accounting for the non-steady-state C dynamics in geomorphic active systems is pertinent to understanding both past and future anthropogenic global change.