Pervasive soil phosphorus losses in terrestrial ecosystems in China.

Future phosphorus (P) shortages could seriously affect terrestrial productivity and food security. We investigated the changes in topsoil available P (AP) and total P (TP) in China's forests, grasslands, paddy fields, and upland croplands during the 1980s-2010s based on substantial repeated soil P measurements (63,220 samples in the 1980s, 2000s, and 2010s) and machine learning techniques. Between the 1980s and 2010s, total soil AP stock increased with a small but significant rate of 0.13 kg P ha-1 year-1 , but total soil TP stock declined substantially (4.5 kg P ha-1 year-1 ) in the four ecosystems. We quantified the P budgets of soil-plant systems by harmonizing P fluxes from various sources for this period. Matching trends of soil contents over the decades with P budgets and fluxes, we found that the P-surplus in cultivated soils (especially in upland croplands) might be overestimated due to the great soil TP pool compared to fertilization and the substantial soil P losses through plant uptake and water erosion that offset the P additions. Our findings of P-deficit in China raise the alarm on the sustainability of future biomass production (especially in forests), highlight the urgency of P recycling in croplands, and emphasize the critical role of country-level basic data in guiding sound policies to tackle the global P crises.

Deforestation as an Anthropogenic Driver of Mercury Pollution.

Deforestation reduces the capacity of the terrestrial biosphere to take up toxic pollutant mercury (Hg) and enhances the release of secondary Hg from soils. The consequences of deforestation for Hg cycling are not currently considered by anthropogenic emission inventories or specifically addressed under the global Minamata Convention on Mercury. Using global Hg modeling constrained by field observations, we estimate that net Hg fluxes to the atmosphere due to deforestation are 217 Mg year-1 (95% confidence interval (CI): 134-1650 Mg year-1) for 2015, approximately 10% of global primary anthropogenic emissions. If deforestation of the Amazon rainforest continues at business-as-usual rates, net Hg emissions from the region will increase by 153 Mg year-1 by 2050 (CI: 97-418 Mg year-1), enhancing the transport and subsequent deposition of Hg to aquatic ecosystems. Substantial Hg emissions reductions are found for two potential cases of land use policies: conservation of the Amazon rainforest (92 Mg year-1, 95% CI: 59-234 Mg year-1) and global reforestation (98 Mg year-1, 95% CI: 64-449 Mg year-1). We conclude that deforestation-related emissions should be incorporated as an anthropogenic source in Hg inventories and that land use policy could be leveraged to address global Hg pollution.

How the EU Soil Observatory contributes to a stronger soil erosion community.

New policy developments have emerged in relation to soil conservation after 2020. The Common Agricultural Policy (CAP) 2023-2027, the proposal for a Soil Monitoring Law and the mission 'A Soil Deal for Europe' have shaped a new policy framework at EU level, which requires updated assessments on soil erosion and land degradation. The EU Soil Observatory (EUSO) successfully organised a scientific workshop on 'Soil erosion for the EU' in June 2022. The event has seen the participation of more than 330 people from 63 countries, addressing important topics such as (i) management practices, (ii) large scale modelling, (iii) the importance of sediments in nutrient cycle, (vi) the role of landslides and (v) laying the foundations for early career scientists. As a follow up, among the 120 abstracts submitted in the workshop, we received fifteen manuscripts, out of which nine were selected for publication in the present special issue. In this editorial, we summarize the major challenges that the soil erosion research community faces in relation to supporting the increasing role of soils in the EU Green Deal.

Retaining natural vegetation to safeguard biodiversity and humanity.

Global efforts to deliver internationally agreed goals to reduce carbon emissions, halt biodiversity loss, and retain essential ecosystem services have been poorly integrated. These goals rely in part on preserving natural (e.g., native, largely unmodified) and seminatural (e.g., low intensity or sustainable human use) forests, woodlands, and grasslands. To show how to unify these goals, we empirically derived spatially explicit, quantitative, area-based targets for the retention of natural and seminatural (e.g., native) terrestrial vegetation worldwide. We used a 250-m-resolution map of natural and seminatural vegetation cover and, from this, selected areas identified under different international agreements as being important for achieving global biodiversity, carbon, soil, and water targets. At least 67 million km2 of Earth's terrestrial vegetation (∼79% of the area of vegetation remaining) required retention to contribute to biodiversity, climate, soil, and freshwater conservation objectives under 4 United Nations' resolutions. This equates to retaining natural and seminatural vegetation across at least 50% of the total terrestrial (excluding Antarctica) surface of Earth. Retention efforts could contribute to multiple goals simultaneously, especially where natural and seminatural vegetation can be managed to achieve cobenefits for biodiversity, carbon storage, and ecosystem service provision. Such management can and should co-occur and be driven by people who live in and rely on places where natural and sustainably managed vegetation remains in situ and must be complemented by restoration and appropriate management of more human-modified environments if global goals are to be realized.

Retención de la vegetación natural para salvaguardar la biodiversidad y la humanidad Resumen Hoy en día hay muy poca integración de los esfuerzos mundiales para alcanzar los objetivos internacionales de reducción de las emisiones de carbono, impedimento de la pérdida de biodiversidad y conservación de los servicios ambientales esenciales. Estos objetivos dependen parcialmente de la conservación de los bosques, selvas y praderas naturales (por ejemplo, nativos y en su mayoría sin alteraciones) y seminaturales (por ejemplo, de uso humano sostenible o de baja intensidad). Obtuvimos de manera empírica objetivos espacialmente explícitos, cuantitativos y basados en áreas para la conservación de la vegetación terrestre natural y seminatural (por ejemplo, nativa) en todo el mundo para mostrar cómo unificar los objetivos internacionales. Usamos un mapa de 250 m de resolución de la cubierta vegetal natural y seminatural y, a partir de él, seleccionamos las áreas identificadas como importantes en diferentes acuerdos internacionales para alcanzar los objetivos globales de biodiversidad, carbono, suelo y agua. Al menos 67 millones de km2 de la vegetación terrestre de la Tierra (∼79% de la superficie de vegetación restante) requieren ser conservados para contribuir a los objetivos de conservación de la biodiversidad, el clima, el suelo y el agua dulce en virtud de cuatro de las resoluciones de las Naciones Unidas. Esto equivale a conservar la vegetación natural y seminatural en al menos el 50% de la superficie terrestre total de la Tierra (sin contar a la Antártida). Los esfuerzos de retención podrían contribuir a alcanzar múltiples objetivos simultáneamente, especialmente en donde la vegetación natural y seminatural puede gestionarse para lograr beneficios colaterales para la biodiversidad, el almacenamiento de carbono y la provisión de servicios ambientales. Esta gestión puede y debe ser impulsada y llevada a cabo por las personas que viven en y dependen de los lugares donde la vegetación natural y gestionada de forma sostenible permanece in situ y debe complementarse con la restauración y la gestión adecuada de entornos modificados por el hombre si se quieren alcanzar los objetivos globales.

Land use and climate change impacts on global soil erosion by water (2015-2070).

Soil erosion is a major global soil degradation threat to land, freshwater, and oceans. Wind and water are the major drivers, with water erosion over land being the focus of this work; excluding gullying and river bank erosion. Improving knowledge of the probable future rates of soil erosion, accelerated by human activity, is important both for policy makers engaged in land use decision-making and for earth-system modelers seeking to reduce uncertainty on global predictions. Here we predict future rates of erosion by modeling change in potential global soil erosion by water using three alternative (2.6, 4.5, and 8.5) Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. Global predictions rely on a high spatial resolution Revised Universal Soil Loss Equation (RUSLE)-based semiempirical modeling approach (GloSEM). The baseline model (2015) predicts global potential soil erosion rates of [Formula: see text] Pg yr-1, with current conservation agriculture (CA) practices estimated to reduce this by ∼5%. Our future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6-10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. Climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Accepting some degrees of uncertainty, our findings provide insights into how possible future socioeconomic development will affect soil erosion by water using a globally consistent approach. This preliminary evidence seeks to inform efforts such as those of the United Nations to assess global soil erosion and inform decision makers developing national strategies for soil conservation.

A 'debt' based approach to land degradation as an indicator of global change.

We propose a way to synthesize different approaches to globally map land degradation by combining vegetation and soil indicators into a consistent framework for assessing land degradation as an environmental 'debt'. our combined approach reveals a broader lens for land degradation through global change, in particular, identifying hot-spots for the different kinds of land degradation.

Global forest restoration opportunities to foster coral reef conservation.

Sediment runoff from disturbed coastal catchments is a major threat to marine ecosystems. Understanding where sediments are produced and where they are delivered enables managers to design more effective strategies for improving water quality. A management strategy is targeted restoration of degraded terrestrial areas, as it provides opportunities to reduce land-based runoff from coastal areas and consequently foster coral reef conservation. To do this strategically, a systematic approach is needed to identify watersheds where restoration actions will provide the highest conservation benefits for coral reefs. Here, we develop a systematic approach for identifying global forest restoration opportunities that would also result in large decreases in the flux of sediments to coral reefs. We estimate how land-use change affects sediment runoff globally using high-resolution spatial data and determine the subsequent risk of sediment exposure on coral reefs using a diffusion-based ocean transport model. Our results reveal that sediment export is a major issue affecting 41% of coral reefs globally. The main coastal watersheds with the highest sediment export are predominantly located in Southeast Asian countries, with Indonesia and the Philippines accounting for 52% of the sediment export in coastal areas near coral reefs. We show how restoring forest across multiple watersheds could help to reduce sediment export to 63,000 km2 of coral reefs. Although reforestation opportunities in areas that discharge onto coral reefs are relatively small across watersheds, it is possible to achieve large sediment reduction benefits by strategically targeting watersheds located in regions with a high density of corals near to the coast. Thus, reforestation benefits on coral reefs do not necessarily come from the watersheds that produce the highest sediment export. These analyses are key for generating informed action to support both international conservation policy and national restoration activities.

Copper Content and Export in European Vineyard Soils Influenced by Climate and Soil Properties.

Copper-based fungicides (Cuf) are used in European (EU) vineyards to prevent fungal diseases. Soil physicochemical properties locally govern the variation of the total copper content (Cut) in EU vineyards. However, variables controlling Cut distribution at a larger scale are poorly known. Here, machine learning techniques were used to identify governing variables and to predict the Cut distribution in EU vineyards. Precipitation, aridity and soil organic carbon are key variables explaining together 45% of Cut distribution across EU vineyards. This underlines the effect of both climate and soil properties on Cut distribution. The average net export of Cu at the EU scale is 0.29 kg Cu ha-1, which is 2 orders of magnitude less than the net accumulation of Cu (24.8 kg Cu ha-1). Four scenarios of Cuf application were compared. The current EU regulation with a maximum of 4 kg Cu ha-1 year-1 may increase by 2% of the EU vineyard area, exceeding the predicted no-effect concentration (PNEC) in soil in the next 100 years. Overall, our results highlight the vineyard areas requiring specific remediation measures and strategies of Cuf use to manage a trade-off between pest control and soil and water contamination.

Mercury in European topsoils: Anthropogenic sources, stocks and fluxes.

Mercury (Hg) is one of the most dangerous pollutants worldwide. In the European Union (EU), we recently estimated the Hg distribution in topsoil using 21,591 samples and a series of geo-physical inputs. In this manuscript, we investigate the impact of mining activities, chrol-alkali industries and other diffuse pollution sources as primary anthropogenic sources of Hg hotspots in the EU. Based on Hg measured soil samples, we modelled the Hg pool in EU topsoils, which totals about 44.8 Gg, with an average density of 103 g ha-1. As a following step, we coupled the estimated Hg stocks in topsoil with the pan-European assessment of soil loss due to water erosion and sediment distribution. In the European Union and UK, we estimated that about 43 Mg Hg yr-1 are displaced by water erosion and c. a. 6 Mg Hg yr-1 are transferred with sediments to river basins and eventually released to coastal Oceans. The Mediterranean Sea receives almost half (2.94 Mg yr-1) of the Hg fluxes to coastal oceans and it records the highest quantity of Hg sediments. This is the result of elevated soil Hg concentration and high erosion rates in the catchments draining into the Mediterranean Sea. This work contributes to new knowledge in support of the policy development in the EU on the Zero Pollution Action Plan and the Sustainable Development Goal (SDGs) 3.9 and 14.1, which both have as an objective to reduce soil pollution by 2030.

Arable lands under the pressure of multiple land degradation processes. A global perspective.

While agricultural systems are a major pillar in global food security, their productivity is currently threatened by many environmental issues triggered by anthropogenic climate change and human activities, such as land degradation. However, the planetary spatial footprint of land degradation processes on arable lands, which can be considered a major component of global agricultural systems, is still insufficiently well understood. This study analyzes the land degradation footprint on global arable lands, using complex geospatial data on certain major degradation processes, i.e. aridity, soil erosion, vegetation decline, soil salinization and soil organic carbon decline. By applying geostatistical techniques that are representative for identifying the incidence of the five land degradation processes in global arable lands, results showed that aridity is by far the largest singular pressure for these agricultural systems, affecting ~40% of the arable lands' area, which cover approximately 14 million km2 globally. It was found that soil erosion is another major degradation process, the unilateral impact of which affects ~20% of global arable systems. The results also showed that the two degradation processes simultaneously affect an additional ~7% of global arable lands, which makes this synergy the most common form of multiple pressure of land degradative conditions across the world's arable areas. The absolute statistical data showed that India, the United States, China, Brazil, Argentina, Russia and Australia are the most vulnerable countries in the world to the various pathways of arable land degradation. Also, in terms of percentages, statistical observations showed that African countries are the most heavily affected by arable system degradation. This study's findings can be useful for prioritizing agricultural management actions that can mitigate the negative effects of the two degradation processes or of others that currently affect many arable systems across the planet.

Soil erosion modelling: A bibliometric analysis.

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Mapping LUCAS topsoil chemical properties at European scale using Gaussian process regression.

This paper presents the second part of the mapping of topsoil properties based on the Land Use and Cover Area frame Survey (LUCAS). The first part described the physical properties (Ballabio et al., 2016) while this second part includes the following chemical properties: pH, Cation Exchange Capacity (CEC), calcium carbonates (CaCO3), C:N ratio, nitrogen (N), phosphorus (P) and potassium (K). The LUCAS survey collected harmonised data on changes in land cover and the state of land use for the European Union (EU). Among the 270,000 land use and cover observations selected for field visit, approximately 20,000 soil samples were collected in 24 EU Member States in 2009 together with more than 2000 samples from Bulgaria and Romania in 2012. The chemical properties maps for the European Union were produced using Gaussian process regression (GPR) models. GPR was selected for its capacity to assess model uncertainty and the possibility of adding prior knowledge in the form of covariance functions to the model. The derived maps will establish baselines that will help monitor soil quality and provide guidance to agro-environmental research and policy developments in the European Union.

Lateral carbon transfer from erosion in noncroplands matters.

This study combines two unprecedentedly high resolution (250 × 250 m) maps of soil erosion (inter-rill and rill processes) and soil organic carbon to calculate a global estimate of erosion-induced organic carbon (C) displacement. The results indicate a gross C displacement by soil erosion of 2.5-0.3+0.5 Pg C/year. The greatest share of displaced C (64%) comes from seminatural lands and forests. This suggests that lateral C transfer from erosion in noncroplands may play a more important role than previously assumed.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets.

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha-1 h-1 yr-1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Quantifying the erosion effect on current carbon budget of European agricultural soils at high spatial resolution.

The idea of offsetting anthropogenic CO2 emissions by increasing global soil organic carbon (SOC), as recently proposed by French authorities ahead of COP21 in the 'four per mil' initiative, is notable. However, a high uncertainty still exits on land C balance components. In particular, the role of erosion in the global C cycle is not totally disentangled, leading to disagreement whether this process induces lands to be a source or sink of CO2. To investigate this issue, we coupled soil erosion into a biogeochemistry model, running at 1 km(2) resolution across the agricultural soils of the European Union (EU). Based on data-driven assumptions, the simulation took into account also soil deposition within grid cells and the potential C export to riverine systems, in a way to be conservative in a mass balance. We estimated that 143 of 187 Mha have C erosion rates <0.05 Mg C ha(-1) yr(-1), although some hot-spot areas showed eroded SOC >0.45 Mg C ha(-1) yr(-1). In comparison with a baseline without erosion, the model suggested an erosion-induced sink of atmospheric C consistent with previous empirical-based studies. Integrating all C fluxes for the EU agricultural soils, we estimated a net C loss or gain of -2.28 and +0.79 Tg yr(-1) of CO2 eq, respectively, depending on the value for the short-term enhancement of soil C mineralization due to soil disruption and displacement/transport with erosion. We concluded that erosion fluxes were in the same order of current carbon gains from improved management. Even if erosion could potentially induce a sink for atmospheric CO2, strong agricultural policies are needed to prevent or reduce soil erosion, in order to maintain soil health and productivity.

In vivo dentate nucleus MRI relaxometry correlates with previous administration of Gadolinium-based contrast agents.

OBJECTIVES: To evaluate changes in T1 and T2* relaxometry of dentate nuclei (DN) with respect to the number of previous administrations of Gadolinium-based contrast agents (GBCA). METHODS: In 74 relapsing-remitting multiple sclerosis (RR-MS) patients with variable disease duration (9.8±6.8 years) and severity (Expanded Disability Status Scale scores:3.1±0.9), the DN R1 (1/T1) and R2* (1/T2*) relaxation rates were measured using two unenhanced 3D Dual-Echo spoiled Gradient-Echo sequences with different flip angles. Correlations of the number of previous GBCA administrations with DN R1 and R2* relaxation rates were tested, including gender and age effect, in a multivariate regression analysis. RESULTS: The DN R1 (normalized by brainstem) significantly correlated with the number of GBCA administrations (p<0.001), maintaining the same significance even when including MS-related factors. Instead, the DN R2* values correlated only with age (p=0.003), and not with GBCA administrations (p=0.67). In a subgroup of 35 patients for whom the administered GBCA subtype was known, the effect of GBCA on DN R1 appeared mainly related to linear GBCA. CONCLUSIONS: In RR-MS patients, the number of previous GBCA administrations correlates with R1 relaxation rates of DN, while R2* values remain unaffected, suggesting that T1-shortening in these patients is related to the amount of Gadolinium given. KEY POINTS: • In multiple sclerosis, previous Gadolinium administrations correlate with dentate nuclei T1 relaxometry. • Such correlation is linked to linear Gadolinium chelates and unrelated to disease duration or severity. • Dentate nuclei T2* relaxometry is age-related and independent of previous Gadolinium administrations. • Changes in dentate nuclei T1 relaxometry are not determined by iron accumulation. • MR relaxometry can quantitatively assess Gadolinium accumulation in dentate nuclei.

Mapping regional patterns of large forest fires in Wildland-Urban Interface areas in Europe.

Over recent decades, Land Use and Cover Change (LUCC) trends in many regions of Europe have reconfigured the landscape structures around many urban areas. In these areas, the proximity to landscape elements with high forest fuels has increased the fire risk to people and property. These Wildland-Urban Interface areas (WUI) can be defined as landscapes where anthropogenic urban land use and forest fuel mass come into contact. Mapping their extent is needed to prioritize fire risk control and inform local forest fire risk management strategies. This study proposes a method to map the extent and spatial patterns of the European WUI areas at continental scale. Using the European map of WUI areas, the hypothesis is tested that the distance from the nearest WUI area is related to the forest fire probability. Statistical relationships between the distance from the nearest WUI area, and large forest fire incidents from satellite remote sensing were subsequently modelled by logistic regression analysis. The first European scale map of the WUI extent and locations is presented. Country-specific positive and negative relationships of large fires and the proximity to the nearest WUI area are found. A regional-scale analysis shows a strong influence of the WUI zones on large fires in parts of the Mediterranean regions. Results indicate that the probability of large burned surfaces increases with diminishing WUI distance in touristic regions like Sardinia, Provence-Alpes-Côte d'Azur, or in regions with a strong peri-urban component as Catalunya, Comunidad de Madrid, Comunidad Valenciana. For the above regions, probability curves of large burned surfaces show statistical relationships (ROC value > 0.5) inside a 5000 m buffer of the nearest WUI. Wise land management can provide a valuable ecosystem service of fire risk reduction that is currently not explicitly included in ecosystem service valuations. The results re-emphasise the importance of including this ecosystem service in landscape valuations to account for the significant landscape function of reducing the risk of catastrophic large fires.

An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques.

Spatial accurate mapping of land susceptibility to wind erosion is necessary to mitigate its destructive consequences. In this research, for the first time, we developed a novel methodology based on deep learning (DL) and active learning (AL) models, their combination (e.g., recurrent neural network (RNN), RNN-AL, gated recurrent units (GRU), and GRU-AL) and three interpretation techniques (e.g., synergy matrix, SHapley Additive exPlanations (SHAP) decision plot, and accumulated local effects (ALE) plot) to map global land susceptibility to wind erosion. In this respect, 13 variables were explored as controlling factors to wind erosion, and eight of them (e.g., wind speed, topsoil carbon content, topsoil clay content, elevation, topsoil gravel fragment, precipitation, topsoil sand content and soil moisture) were selected as important factors via the Harris Hawk Optimization (HHO) feature selection algorithm. The four models were applied to map land susceptibility to wind erosion, and their performance was assessed by three measures consisting of area under of receiver operating characteristic (AUROC) curve, cumulative gain and Kolmogorov Smirnov (KS) statistic plots. The results revealed that GRU-AL model was considered as the most accurate, revealing that 38.5%, 12.6%, 10.3%, 12.5% and 26.1% of the global lands are grouped at very low, low, moderate, high and very high susceptibility classes to wind erosion hazard, respectively. Interpretation techniques were applied to interpret the contribution and impact of the eight input variables on the model's output. Synergy plot revealed that the soil carbon content exhibited high synergy with DEM and soil moisture on the model's predictions. ALE plot showed that soil carbon content and precipitation had negative feedback on the prediction of land susceptibility to wind erosion. Based on SHAP decision plot, soil moisture and DEM presented the highest contribution on the model's output. Results highlighted new regions at high latitudes (southern Greenland coast, hotspots in Alaska and Siberia), which exhibited high and very high land susceptibility to wind erosion.

GloRESatE: A dataset for global rainfall erosivity derived from multi-source data.

Numerous hydrological applications, such as soil erosion estimation, water resource management, and rain driven damage assessment, demand accurate and reliable rainfall erosivity data. However, the scarcity of gauge rainfall records and the inherent uncertainty in satellite and reanalysis-based rainfall datasets limit rainfall erosivity assessment globally. Here, we present a new global rainfall erosivity dataset (0.1° × 0.1° spatial resolution) integrating satellite (CMORPH and IMERG) and reanalysis (ERA5-Land) derived rainfall erosivity estimates with gauge rainfall erosivity observations collected from approximately 6,200 locations across the globe. We used a machine learning-based Gaussian Process Regression (GPR) model to assimilate multi-source rainfall erosivity estimates alongside geoclimatic covariates to prepare a unified high-resolution mean annual rainfall erosivity product. It has been shown that the proposed rainfall erosivity product performs well during cross-validation with gauge records and inter-comparison with the existing global rainfall erosivity datasets. Furthermore, this dataset offers a new global rainfall erosivity perspective, addressing the limitations of existing datasets and facilitating large-scale hydrological modelling and soil erosion assessments.