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Managing soils to increase organic carbon storage presents a potential opportunity to mitigate and adapt to global change challenges, while providing numerous co-benefits and ecosystem services. However, soils differ widely in their potential for carbon sequestration, and knowledge of biophysical limits to carbon accumulation may aid in informing priority regions. Consequently, there is great interest in assessing whether soils exhibit a maximum capacity for storing organic carbon, particularly within organo–mineral associations given the finite nature of reactive minerals in a soil. While the concept of soil carbon saturation has existed for over 25 years, recent studies have argued for and against its importance. Here, we summarize the conceptual understanding of soil carbon saturation at both micro- and macro-scales, define key terminology, and address common concerns and misconceptions.

Loss of soil organic carbon (SOC) from farmland is a key threat to the capacity of soils to provide ecosystem services and exacerbates climate change. In alignment with a published protocol, we conducted a review and meta-analysis of time series of SOC measurements in long-term agricultural experiments to study absolute SOC changes under different agricultural management regimes.

Shifting towards healthy, plant-based diets is widely recognized as a strategy to reduce greenhouse gas emissions (GHG) from food systems, primarily through reduced methane emissions from livestock. However, the implications of this transition for soil-based GHG emissions, a major contributor to climate change, remain uncertain. We used the MAGNET economic model and the DayCent biogeochemical model to assess the impacts of dietary shifts aligned with the EAT-Lancet guidelines on soil organic carbon (SOC), nitrous oxide (N2O) emissions, and the soil GHG balance across the European Union and the United Kingdom. Adopting the EAT-Lancet diet reduced livestock production, organic carbon (C) and organic nitrogen (N) inputs from manure, and permanent grassland areas for agricultural use. This results in potential SOC losses of an EU average of 14 Mg CO2e ha−1 and reaching up to 50 Mg CO2e ha−1 in livestock-intensive regions by 2100. However, afforestation of land released from production could offset approximately half of the diet-induced soil C losses by 2100. When above-ground biomass from afforestation is factored in, this could yield an additional 65 Mg C ha−1 in afforested areas, resulting in net CO2 removal at the European scale. N2O emissions exhibited more moderate and heterogeneous changes by 2100, ranging from 10 to −13 Mg CO2e ha−1 across the continent, and dependent on land use change (LUC) and increased synthetic N inputs. The changes in SOC were driven by LUC, lower organic inputs, soil types and, to a lesser degree, climatic zones. This study's findings underscore the importance of dietary changes in tackling climate change. However, practitioners and policymakers should carefully consider potential soil-related trade-offs by supporting and implementing appropriate soil conservation practices, such as no-tilling or afforestation, to realize the full co-benefits of more sustainable diets.

The Amazon rainforest is crucial for the global carbon cycle, yet annual changes in its aboveground biomass carbon (AGC) stock remain highly uncertain. Natural and local anthropogenic drivers such as deforestation, forest degradation, and regrowth following deforestation interact with large-scale climate variability to determine AGC dynamics. Here, we propose an approach to disaggregate low-frequency passive L-band microwave data over 2010-2020 and reconstruct maps of annual change. We show that the Amazon lost −0.37 ± 0.17 PgC, with gains by undisturbed (0.33 ± 0.13 PgC) and secondary forest growth (0.33 ± 0.05 PgC) outweighed by losses by deforestation (−0.55 ± 0.04 PgC), degradation (−0.42 ± 0.08 PgC), and agricultural areas (−0.06 ± 0.03 PgC). Losses in human-influenced land intensified over time and amounted to 60% of all gross losses in El Niño years. Our study reinforces the need for stronger implementation of policies and effective actions to control forest degradation.

The European Union's strategic agenda for 2024–2029 prioritizes a prosperous and competitive Europe, with soil health potentially playing a role in achieving this goal. However, the current state of European soils is of concern, with over 60 % of soils not in healthy condition, as reported by the European Union’s Soil Mission Board and the EU Soil Observatory. This results not only in environmental issues, but also economic ones, as the costs of soil degradation in the EU are estimated to be higher than €50 billion per year, underscoring the need for soil health to be placed more prominently on the political agenda. Soil-related business models, including biotechnology, remediation of contaminated sites, carbon removals and farming, regenerative agriculture, and agritech solutions, can contribute to EU competitiveness. These business models may help address most of the challenges posed by soil degradation, climate change, and biodiversity loss, while promoting sustainable agriculture practices and improving ecosystem functioning. The EU's soil remediation market is valued at €8.5 billion, with an annual growth rate of 5 %. The EU Carbon Removals and Carbon Farming Regulation provides a framework for certifying carbon removals, with potential revenue of €6 billion per year. Regenerative agriculture, which prioritises soil health and ecosystem services, can increase crop yields, reduce dependency on synthetic fertilisers and pesticides, and promote biodiversity. Agritech solutions, such as precision agriculture and artificial intelligence, can optimize farming practices, reduce costs, and improve environmental sustainability. Here we present the potential of soil-related business models to contribute to EU competitiveness, while addressing environmental and societal challenges. However, a number of challenges remain and need to be addressed as the need for acceleration, a clear policy framework, a closer collaboration of different actors in the food supply chain and a digital transformation are still needed.

Over 60% of European soils are unhealthy according to the Soil Mission board estimates and the indicators presented in the European Union (EU) Soil degradation dashboard. The situation may worsen if no policy interventions are taken. The unsustainable use of natural resources, in particular the degradation of soils, precipitates biodiversity loss, exacerbated by the climate crisis. In particular, in the EU alone, soil degradation costs over €50 billion per year due to the loss of essential services they provide and to the impact on human health. Here a more precise estimation of the soil degradation cost related to a set of soil degradation processes, ranging between €40.9 and 72.7 billion per year is presented. This newly updated estimate compared to the Impact assessment of the Soil Monitoring Law takes into account the costs of soil erosion, contamination, phosphorus losses, soil carbon losses, nitrogen losses, soil compaction, and soil sealing. However, this estimation might double if it is added to the costs of soil biodiversity loss, floods, droughts, off-site effects of soil erosion, and health consequences of soil contamination. Therefore, further research is needed to address this knowledge gap and estimate the missing costs. Soil degradation is a critical issue with transboundary implications that requires urgent attention and action at the EU level. The costs of soil degradation are substantial, both in terms of environmental impacts and economic consequences, highlighting the importance of investing in sustainable soil management practices and a harmonized EU soil monitoring system. By addressing soil degradation through the proposed Soil Monitoring Law, investing significant amounts for research and innovation in the Soil Mission, and promoting international cooperation, the EU can take solid steps toward protecting its soil resources and achieving a sustainable future for all.

Soil Electrical conductivity (EC) is a measure of the ability of soil to conduct an electric current, which is primarily influenced by the concentration of soluble salts in the soil solution that takes place principally through water-filled pores. Ions (Ca2+, Mg 2+, K +, Na +, and NH 4+, SO42-, Cl-, NO3–, and HCO3–) from soluble salts dissolved in soil water carry electrical charges and conduct the electrical current. EC is considered a proxy of soil salinity and other soil characteristics, whose monitoring is much needed in the context of climate change, increasing irrigation in agricultural areas and sea level rise. The pan-European LUCAS soil monitoring scheme, established in 2009, provided EC1:5 in the topsoil (0–20 cm) in the surveys of the years 2015 and 2018 for almost 20,000 samples. In this work, using the LUCAS 2018 dataset, we provide an empirically-derivedpedotransfer function to convert diluted EC1:5 to saturated ECe using the LUCAS soil texture and soil organic carbon, and a framework for ECe mapping with a machine-learning algorithm named Quantile Regression Forest. The final model resulted in an R2 of 0.302 with an RMSE of 0.265 dS m−1 for soil samples not used for model calibration. The results are presented as predicted ECe in the topsoil, and they reveal that in Atlantic and Northern Europe, salts may accumulate in soils through several natural processes, i.e., primary salinization, but in Mediterranean and Southern Europe, they accumulate because of human interventions on the soil water and solute regimes. 

Soil pollution poses a significant threat to human health and the environment in the Western Balkans. It contaminates food and water sources with potentially toxic elements and degrades ecosystems by reducing soil functions and biodiversity. Industrialization over the past century has made soil pollution a widespread issue in the region. This study aims to summarize the status of point source soil pollution, identify knowledge gaps, and support the implementation of the Green Agenda for the Western Balkans, with a focus on soil remediation priorities.

Conservation benefits from dietary change are commonly assessed without accounting for different conservation objectives. By representing fine-scale habitat and landscape change within a dynamic land-system model, we assess how a partial or full transition to healthier diets would affect indicators across the ‘Nature for Nature’ and ‘Nature for Society’ conservation value perspectives. We find that most diet-related conservation benefits are already achieved by a partial shift to healthier diets. This is because, particularly in many countries in tropical Africa and Asia, adopting healthier diets would mainly involve substituting staple foods with more varied plant-based foods rather than replacing resource-intensive livestock products. Conservation action in line with the Global Biodiversity Framework, by contrast, most consistently improves outcomes across both value perspectives, even under current demand trends, showing that spatial planning is central for decoupling conservation outcomes from food demand. However, any progress towards healthier diets not only lowers greenhouse gas emissions but also reduces barriers to effective conservation, such as higher food prices and imports.

Evaluating heavy metals bioavailable is crucial for comprehensive soil contamination assessment but challenging at large scales due to complex and resource-intensive analytical procedures, and the amount of dissolved metal in soils represents the relative solubility and potential mobility of cadmium, which is a key factor determining bioavailability. Here, we developed a geochemical-integrated machine learning framework using multi-source data to predict cadmium speciation distribution in European and Chinese non-industrial topsoils.

Soil pH indicates the level of acidity or alkalinity in the soil environment, influencing various biogeochemical and physical processes. Additionally, soil pH levels are crucial in determining the bioavailability of elements such as iron, aluminium, and heavy metals which can be harmful. As such, pH is an important soil health and degradation indicator. Although there is a well-established understanding of soil pH at localized levels, the spatial and temporal variations, as well as significant thresholds at national and continental scales, are not sufficiently documented. Here we analyse the European topsoil pH data (LUCAS) in combination with other soil properties from the LUCAS survey, to identify thresholds and spatial patterns of soil pH across Europe in relation to soil health and degradation.

The increasing threat of soil degradation presents significant challenges to soil health, especially within agroecosystems that are vital for food security, climate regulation, and economic stability. This growing concern arises from intricate interactions between land use practices and climatic conditions, which, if not addressed, could jeopardize sustainable development and environmental resilience. This review offers a comprehensive examination of soil degradation, including its definitions, global prevalence, underlying mechanisms, and methods of measurement. It underscores the connections between soil degradation and land use, with a focus on socio-economic consequences. Current assessment methods frequently depend on insufficient data, concentrate on singular factors, and utilize arbitrary thresholds, potentially resulting in misclassification and misguided decisions. We analyze these shortcomings and investigate emerging methodologies that provide scalable and objective evaluations, offering a more accurate representation of soil vulnerability. Additionally, the review assesses both physical and biological indicators, as well as the potential of technologies such as remote sensing, artificial intelligence, and big data analytics for enhanced monitoring and forecasting. Key factors driving soil degradation, including unsustainable agricultural practices, deforestation, industrial activities, and extreme climate events, are thoroughly examined. The review emphasizes the importance of healthy soils in achieving the United Nations Sustainable Development Goals, particularly concerning food and water security, ecosystem health, poverty alleviation, and climate action. It suggests future research directions that prioritize standardized metrics, interdisciplinary collaboration, and predictive modeling to facilitate more integrated and effective management of soil degradation in the context of global environmental changes.

Soil health is critical for sustaining ecosystem functions and addressing environmental challenges. Effective soil health management requires reliable methods for assessing soil properties. Soil spectroscopy may allow resource-effective assessment of soil properties, but more knowledge is needed to transfer knowledge from laboratory-grade spectrometers to in-field data acquisition. This study explores the predictive potential of selected spectral subsets from the full visible and near-infrared (VIS–NIR) range, using various machine learning algorithms (MLAs), as a theoretical exercise to support the design of practical soil sensing tools. Specifically, we evaluated whether narrower spectral ranges can provide predictions comparable to those achieved with the full VIS–NIR spectrum. The ranges are chosen to emulate the spectral coverage and resolution of commercially available sensors which are candidates for widespread and resource-effective data collection. We used the VIS–NIR spectral data (400–2500 nm) alongside laboratory analyses of several soil properties to be predicted from the pan-European LUCAS dataset. We employed four different MLAs for estimating soil properties: support vector regression (SVR), cubist, random forest (RF), and multi-layer perceptron (MLP), which were benchmarked against ordinary least squares regression. Our results showed that spectral subset ranges of 1000–2500 nm and 1350–2500 nm (emulating Trinamix and NeoSpectra sensors, respectively) yielded prediction accuracies similar to the full spectrum. Spectral subsets limited to the visible and early NIR range (350–1000 nm) were less effective. The most informative spectral features were found in wavelengths above approximately 1750 nm. Among MLAs, MLP consistently delivered the best performance, particularly when estimating organic carbon, nitrogen, pH and clay, which were predicted with greater accuracy compared to potassium (K), phosphorus (P) and coarse fragments (CF) which cannot yet be robustly predicted from spectral data alone. This study provides preliminary insight into the spectral regions most relevant for soil property prediction. These findings may inform future development and optimisation of real-world soil sensors. Validation with actual sensor data, both on dried and in situ samples, remains an important next step.

Heavy rainfall is the main driver of water-induced soil erosion, necessitating accurate spatial and temporal predictions of rainfall erosivity to predict the soil erosion response. This study evaluates the ground radar-based EUropean RADar CLIMatology (EURADCLIM) precipitation grids to quantify rainfall erosivity across European countries. Compared to Global Rainfall Erosivity Database (GloREDa) gauge-based interpolations, EURADCLIM overpredicts rainfall erosivity, principally due to residual artefacts in some regions which inflate the instantaneous rainfall rates. Overprediction is most pronounced in European regions with lower radar antenna coverage and complex topography, whereas flatter regions with lower erosivity and better radar coverage are better predicted spatially but with a tendency towards underprediction. Disagreement attributes to the input radar quality in EURADCLIM (derived from OPERA) and to a lesser extent the uncertainty in GloREDa due to its limited gauge records in some regions. Event (EI30) time series analysis showed reasonably good performance (Kling-Gupta Efficiency (KGE) > 0.4) in 50 % of the evaluated gauge locations, although significant overprediction by EURADCLIM was evident in the upper quantiles in some countries. To account for the propagation of these remaining single-hour rainfall artefacts, which have a large impact on the temporally-aggregated R-factor, applying a 80 mm h−1 threshold to limit the maximum I30 value (i.e., less than 0.1 % of GloREDa events exceed this threshold) during the calculation of rainfall erosivity significantly improves the performance of the EURADCLIM dataset at annual, monthly and event time scale. Following adjustment, EURADCLIM best agrees with GloREDa across Europe in July and August, while bigger differences were observed in June and winter in general. Annually, the spatially aggregated rainfall erosivity per country had a percent bias below 10 %. While applying simple I30 thresholds is promising, radar artefacts remain significant in areas with lower quality rainfall retrievals. In the absence of spatiotemporally continuous, high-quality ground-radar retrievals across Europe, we show the value of ensemble R-factor layers of EURADCLIM with three other rainfall erosivity grids (e.g., satellite retrievals) and discuss the possibility of ground radar to offer unique spatial detail in such ensembles.

Soil degradation threatens agricultural productivity and ecosystem resilience across Europe, yet spatially consistent assessments of its intensity and drivers remain limited. In this study, we used Soil Degradation Proxy (SDP), that integrates four key indicators of soil degradation, including erosion rate, soil pH, electrical conductivity, and organic carbon content, to quantify soil degradation risk. Using over 38,000 LUCAS topsoil observations and a machine learning model trained on climate, land cover, topographic, soil parent material properties, and spectral variables, we map annual SDP values between years 2000 to 2022 across Europe. Results show soil degradation risk is highest in southern Europe, especially in intensively managed and sparsely vegetated landscapes. Over the past two decades, approximately 7.1% of land area across the EU and the UK has experienced increasing degradation risk (most notably across Eastern Europe), with rainfed croplands emerging as the most affected land cover type. Land cover is the most influential driver, modulating effects of climatic variables such as precipitation and temperature on SDP. This data-driven framework provides a consistent and scalable approach for monitoring soil degradation risk and offers actionable insights to support targeted conservation and EU-wide policy implementation.

Ecosystem functioning is potentially dependent on the relationships between soil microbial diversity and biomass. Yet, it remains unclear how land use and climate influence these relationships. Here, we (i) analysed relationships and ratios between richness and biomass of bacteria and fungi in ~500 soils across Europe, including three land-use types (woodlands, grasslands and croplands) and climates (cold, temperate and arid) and (ii) identified the driving factors of changes in richness:biomass (R:B) ratios.

Erosion models simulating the intra-annual effects of hydrometeorological drivers and disturbances (e.g. vegetation clearcutting, tillage events, wildfires) need to represent temporal variability at time scales below the long-term annual average (e.g. the native timescale of the (Revised) Universal Soil Loss Equation). Here, we test a low-complexity, spatially distributed model (WaTEM/SEDEM: W/S), to simulate 15-day erosion and sediment dynamics. A standardised modelling routine was applied to four monitored and well-studied catchments in North-West Europe with open-access discharge (Q) and suspended sediment load (SSL) data, creating a model workflow implementable with predominantly pan-European Union data.

Effective implementation of Sustainable Land Management (SLM) remains a major challenge worldwide because of its weak integration within the domains of science, policy, and development practice. Based on global analyses of soil erosion risk and the degree of implementation of SLM research, policies, and practices at the country level, we propose a transdisciplinary framework to address soil erosion through SLM. In the analysis, we used indices of the policy–development, science–policy, and science–development interfaces to evaluate the overall science–policy–development interface (SPDI) in 236 countries.

Rainfall erosivity maps for (near) real-time soil erosion predictions require the integration of (combinations of) reanalysis products and satellite-retrievals of rainfall, and the overcoming of potential bias related to their simplified spatial and temporal scale. Across Europe, we evaluate: 1) the European Meteorological Observations (EMO) dataset to simulate the localised characteristics of rainfall erosivity at the event scale (EI30), and 2) different implementations of quantile delta mapping (QDM) bias correction to improve the prediction skill. Between 1990 and 2014, evaluations were made at several spatial (location-specific, climatic zone and pan-European) and temporal (event, annual and long-term annual average) scales. The uncorrected EMO predictions demonstrated: 1) a slight overprediction of the number of EI30 events, 2) a reduced coefficient of variation in the EI30 (CV EMO = 1.57, CV REDES = 2.5), and 3) a relatively low (R2 = 0.22, n = 139,306) location-specific predictive skill, with higher discrepancies in all cases in Southern Europe. Following QDM, the EI30 predictions significantly better represented the large-sample variability of EI30 per climate region and improved the monthly correspondence. 

Physical and chemical erosion associated with water both affect land–atmosphere carbon exchanges. However, previous studies have often addressed these processes separately or used oversimplified mechanisms, leading to ongoing debates and uncertainties about erosion-induced carbon fluxes. We provide an overview of the on-site carbon uptake fluxes induced by physical erosion (0.05–0.29 Pg C yr−1, globally) and chemical erosion (0.26–0.48 Pg C yr−1). Then, we discuss off-site carbon dynamics (during transport, deposition, and burial). Soil organic carbon mineralization during transport is nearly 0.37–1.20 Pg C yr−1 on the globe. We also summarize the overall carbon fluxes into estuaries (0.71–1.06 Pg C yr−1) and identify the sources of different types of carbon within them, most of which are associated with land erosion.

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains limited. Here, we present the first global assessment of gully density's spatial patterns. Using mapped observations from over 17,000 representative study sites worldwide, we trained random forest models that simulate both the susceptibility to gullying at a 1 km2 resolution and the corresponding gully head density (GHD).map

The global increase in pesticide use has raised concerns about its impact on biodiversity, ecosystems, and human health, in particular of people living near agricultural areas. This study explores the assessment of pesticide exposure and risks to residents at a high spatial granularity using plant protection product data. Our objective was to develop an indicator to monitor pesticide risk levels faced by residents in France by integrating spatial datasets and exposure assessment methodologies. Using spatialized pesticide sales data based on crop authorizations, we mapped potential pesticide loads at the parcel level.

Comparability of soil data derived from different sources is crucial to obtain consistent results when evaluating the soil health status. Discrepancies may arise due to various factors, including uncertainties resulting from different sampling methods. In this study, we compared various soil Physicochemical properties (ST)—pH, organic carbon, texture, cation exchange capacity, nutrients, heavy metals—and microbial diversity (BIO) of samples collected following both the LUCAS Soil (performed by the European Commission Joint Research Centre, JRC) and the Italian (performed by two regional agencies) procedures. The aim was to evaluate the effect of applying different soil sampling protocols on ST and BIO data. Soil samples from 58 LUCAS Soil 2022 sampling sites located in northern Italy were collected following both sampling protocols. 

The special issue “From data to Fork” gathered 15 papers from all over the world in cross-cutting areas of Smart Agriculture Research, including new algorithm development for the agricultural sector, food security, and ecosystem well-being and several study cases. We promoted the concept of reviews and original research papers reporting applications of smart farming from field to fork. The editorial proposed some main groups of papers in the following sections: i) Advances in Precision Agriculture and Crop Monitoring; ii) Technological Innovation for Farm Management and Infrastructure; iii) Digital Outreach and Decision Support Systems.

The effect of fire on plants and soils cannot be viewed in isolation. Plant-soil interactions, and their role in determining the response of ecosystem to fire, has been a widely debated topic. Most studies describe patterns rather than the mechanisms that may lead to variable effects on soils across ecosystems.

Fires can alter soil properties via downward heat transfer. Numerous studies have examined effects of wildfires and prescribed burns on soils, yet knowledge of the soil temperatures and durations reached is limited. This can lead to erroneous assumptions regarding fire impacts, especially when laboratory heating results are extrapolated to field conditions.

Poster with six key facts reveal Europe's soil crisis—erosion, contamination, sealing, biodiversity loss, carbon decline, poor health and the overall cost —highlighting the urgent need for sustainable soil management and protection.

This report addresses soil pollution in the EU, supporting the implementation of the EU's Soil Monitoring Law (SML) and Zero Pollution Action Plan. This document presents the outcomes of workshop with several EU Mission projects on soil pollution, including the SoilWise, ISLANDR, EDAPHOS, ARAGORN, and BENCHMARKS projects. The report provides a comprehensive approach to harmonization and standardization of soil pollution data, essential for effective policy-making and decision-support. The report also provides information on the development of new policy measures, such as the EU's Soil Strategy and proposed Directive on Soil Monitoring and Resilience. This report hopes to serve ongoing and future Soil Mission projects with data harmonization for a higher dissemination and policy impact. The harmonization of the data will help EU and national/regional policymakers to have a clear view on the state of the soil pollution and therefore reinforce their regulation on soils (e.g., Soil Monitoring Law).

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Healthy soils are essential for providing healthy food and achieving climate neutrality. The publication of the EU Soil Strategy for 2030, the proposed Soil Monitoring and Resilience Directive and the Mission Soil marked major milestones for soil protection and restoration in the EU. Given this context, the EU Soil Observatory (EUSO) aims to be the principal provider of knowledge and data on soils at the EU-level and to underpin EU policies related to soils. This report highlights the main activities and outcomes of the EUSO in 2024. During this period, the EUSO provided policy support to a wide range of soil related areas, including the proposed Soil Monitoring and Resilience Directive, the Carbon Removal Certification Framework and the Mission Soil. A highlight was the launch of the science for policy report ‘The state of soils in Europe’, in collaboration with the European Environment Agency, providing an in-depth examination of the pressures affecting soils across Europe. Furthermore, the EUSO updated its Soil Degradation Dashboard and launched a novel EU Soil Strategy Actions Tracker. The latter shows that almost 70% of the policy actions listed in the EU Soil Strategy for 2030 are completed. Next, the European Soil Data Centre, the leading web platform for sharing data and knowledge about EU soils, has grown significantly with 15 new datasets and a 20% increase in requests for datasets. Additionally, the EUSO contributed directly to advanced scientific knowledge on soils with the publication of 47 scientific papers, 10 technical reports, and 3 science-for-policy reports. Finally, the EUSO organised and contributed to activities to support stakeholder interactions and citizen engagement regarding soils. Highlights include the fourth EUSO Stakeholders Forum, the second Young Soil Researchers Forum, the European Mission Soil Week and the activities of the EUSO Working Groups. During 2025, the EUSO will continue to be the principal provider of soil-related data and knowledge while supporting the implementation of EU policy objectives in relation to soils.

Download the Report: https://esdac.jrc.ec.europa.eu/public_path//shared_folder/doc_pub/JRC141262.pdf

Soil pollution is a significant environmental and health concern in Europe, with potential links to cancer incidence. The Exploratory Research project “Understanding the links between SOil pollution and CancEr” (SOLACE)” aimed to investigate the complex relationships between soil properties, pollution, land use and human health, providing a foundation for further research and policy development, as part of the Joint Research Centre's (JRC) strategic scientific development.. The scoping review of the existing studies linking soil pollution and cancer identified the knowledge gaps in the fields. We also performed an ecological study across 26 EU countries, which releaved associations between the regional rates of lung cancer mortality and soil pollution with arsenic and cadmium. The SOLACE project underscores the importance of comprehensive soil monitoring to safeguard environmental and human health and emphasizes the need for continued investment in research, monitoring, and policy development to address the complex issues surrounding soil pollution and its impact on human health The SOLACE project achievements contribute to the goals of the JRC by supporting soil-related directives like the Soil Monitoring Law and the Zero Pollution Action Plan.

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Healthy soils are essential for our environment and society, as soils deliver crucial ecosystem services. The publication of the EU Soil Strategy for 2030 and the Soil Monitoring Law marked
major milestones for soil protection and restoration in the EU. In parallel, the Mission Soil aims to advance knowledge on healthy soils and establish 100 Living Labs and Lighthouses to co-create innovations for soil health. Contributing to a better EU soil health monitoring and a complete set of indicators at the EU-level are crucial components of the Mission Soil’s objectives. This report proposes a list of indicators for soil health in the EU, together with targets and thresholds for these indicators. Nineteen indicators are presented, representing the main soil degradation processes and monitoring the state of soil health at EU scale. The EUSO Soil Degradation Dashboard is proposed as the main platform for presenting these indicators, together with key results and statistics. The dashboards shows that, based on the proposed indicators, more than 60% of EU soils are currently unhealthy. Planned updates on the proposed indicator framework include: (i) refining, updating and adding new datasets for indicators, (ii) refining thresholds for the indicators, and (iii) developing a composite Soil Health Index. For these planned activities, close collaboration with the Mission Soil projects will be crucial.

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Land degradation is a complex socio-environmental threat, which generally occurs as multiple concurrent pathways that remain largely unexplored in Europe. Here we present an unprecedented analysis of land multi-degradation in 40 continental countries, using twelve dataset-based processes that were modelled as land degradation convergence and combination pathways in Europe’s agricultural (and arable) environments. Using a Land Multi-degradation Index, we find that up to 27%, 35% and 22% of continental agricultural (~2 million km2) and arable (~1.1 million km2) lands are currently threatened by one, two, and three drivers of degradation, while 10–11% of pan-European agricultural/arable landscapes are cumulatively affected by four and at least five concurrent processes. We also explore the complex pattern of spatially interacting processes, emphasizing the major combinations of land degradation pathways across continental and national boundaries. Our results will enable policymakers to develop knowledge-based strategies for land degradation mitigation and other critical European sustainable development goals..

A unifying modelling of multiple land degradation pathways in Europe | Nature Communications

Soil health is expected to be of key importance for plant growth and ecosystem functioning. However, whether soil health is linked to primary productivity across environmental gradients and land-use types remains poorly understood. To address this gap, we conducted a pan-European field study including 588 sites from 27 countries to investigate the link between soil health and primary productivity across three major land-use types: woodlands, grasslands and croplands. We found that mean soil health (a composite index based on soil properties, biodiversity and plant disease control) in woodlands was 31.4% higher than in grasslands and 76.1% higher than in croplands. Soil health was positively linked to cropland and grassland productivity at the continental scale, whereas climate best explained woodland productivity. Among microbial diversity indicators, we observed a positive association between the richness of Acidobacteria, Firmicutes and Proteobacteria and primary productivity. Among microbial functional groups, we found that primary productivity in croplands and grasslands was positively related to nitrogen-fixing bacteria and mycorrhizal fungi and negatively related to plant pathogens. Together, our results point to the importance of soil biodiversity and soil health for maintaining primary productivity across contrasting land-use types.

Soil health is associated with higher primary productivity across Europe | Nature Ecology & Evolution

Fire-induced geomorphic changes, such as enhanced erosion and debris-flow activity, are expected to increase with climate change owing to increases in fire activity and rainfall intensification. In this Review, we summarize how landscape attributes, rainfall and burn severity influence post-fire geomorphic responses over a range of temporal and spatial scales. Sub-hourly rainfall intensity and burn severity control the magnitude of many post-fire geomorphic process rates through their influence on ground cover and rainfall-runoff partitioning. Post-fire debris flows (PFDFs) make a substantial contribution to the post-fire sediment cascade, transporting sediment from hillslopes to channels, adjacent floodplains and alluvial fans. By the late twenty-first century, PFDF activity is estimated to increase in 68% of areas in which PFDFs have occurred in the past and decrease in only 2% of locations. Once altered by fire, geomorphic state variables — such as infiltration capacity, canopy cover, ground cover and sediment availability — can recover to their pre-fire value or be shifted to a new value. Improved understanding of the factors that influence these post-fire trajectories could support targeted management and intervention strategies. Additionally, monitoring that extends beyond the first 1–3 years after fire and deeper integration of ecohydrological processes into geomorphic models are needed to improve forecasts of post-fire geomorphic responses.

Fire effects on geomorphic processes | Nature Reviews Earth & Environment

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.

GloRESatE: A dataset for global rainfall erosivity derived from multi-source data | Scientific Data

Modeling monthly rainfall erosivity is vital to the optimization of measures to control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing rainfall erosivity estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach to model global monthly rainfall erosivity. The framework integrates long-term (2001–2020) mean annual rainfall erosivity estimates from IMERG (Global Precipitation Measurement (GPM) mission’s Integrated Multi-satellitE Retrievals for GPM) with station data from GloREDa (Global Rainfall Erosivity Database, n = 3,286 stations). The merged mean annual rainfall erosivity was disaggregated into mean monthly values based on monthly rainfall erosivity fractions derived from the original IMERG data. Global mean monthly rainfall erosivity was distinctly seasonal; erosivity peaked at ~ 200 MJ mm ha−1 h−1 month−1 in June–August over the Northern Hemisphere and ~ 700 MJ mm ha−1 h−1 month−1 in December–February over the Southern Hemisphere, contributing to over 60% of the annual rainfall erosivity over large areas in each hemisphere. Rainfall erosivity was ~ 4 times higher during the most erosive months than the least erosive months (December–February and June–August in the Northern and Southern Hemisphere, respectively). The latitudinal distributions of monthly and seasonal rainfall erosivity were highly heterogeneous, with the tropics showing the greatest erosivity. The intra-annual variability of monthly rainfall erosivity was particularly high within 10–30° latitude in both hemispheres. The monthly rainfall erosivity maps can be used for improving spatiotemporal modeling of soil erosion and planning of soil conservation measures.

An integrated modeling approach for estimating monthly global rainfall erosivity | Scientific Reports

Increasing soil organic carbon (SOC) confers benefits to soil health, biodiversity, underpins carbon sequestration and ameliorates land degradation. One recommendation is to increase SOC such that the SOC to clay ratio (SOC/clay) exceeds 1/13, yet normalising SOC levels based on clay alone gives misleading indications of soil structure and the potential to store additional carbon. Building on work by Poeplau & Don (2023) to benchmark observed against predicted SOC, we advance an alternative indicator: the ratio between observed and “typical” SOC (O/T SOC) for pan-European application. Here, “typical” SOC is the average concentration in different pedo-climate zones, PCZs (which, unlike existing SOC indicators, incorporate land cover and climate, alongside soil texture) across Europe, determined from mineral (<20 % organic matter) topsoils (0–20 cm) sampled during 2009–2018 in LUCAS, Europe's largest soil monitoring scheme (n = 19,855). Regression tree modelling derived 12 PCZs, with typical SOC values ranging 5.99–39.65 g kg−1. New index classes for comparison with SOC/clay grades were established from the quartiles of each PCZ's O/T SOC distribution; these were termed: “Low” (below the 25th percentile), “Intermediate” (between the 25th and 50th percentiles), “High” (between the 50th and 75th percentiles), and “Very high” (above the 75th percentile). Compared with SOC/clay, O/T SOC was less sensitive to clay content, land cover, and climate, less geographically skewed, and better reflected differences in soil porosity and SOC stock, supporting 2 EU Soil Health Mission objectives (consolidating SOC stocks; improving soil structure for crops and biota). These patterns held for 2 independent datasets, and O/T SOC grades were sensitive enough to reflect land management differences across several long-term field experiments. O/T SOC used in conjunction with several other physical, chemical and biological soil health indicators can help support the EU Soil Monitoring Law and achieve several United Nations Sustainable Development Goals.

Benchmarking soil organic carbon (SOC) concentration provides more robust soil health assessment than the SOC/clay ratio at European scale - ScienceDirect

The present European Union (EU) Sewage Sludge Directive (86/278/EEC) is undergoing modifications aimed at enhancing its applicability in the agricultural sector. The Directive's existing limit values for heavy metal concentrations in soils are in the process of being revised. However, to comprehensively understand their effects on EU agricultural lands, additional evaluations are necessary. This is particularly important given that ecological risk assessments are often performed on a site-specific basis, potentially overlooking broader regional implications. The main objective of the current work is to introduce a methodological approach to quantify the impact of sewage sludge (SS) application on agricultural soils in the EU and the United Kingdom. Concentrations of heavy metals (HMs) (Cd, Cu, Hg, Ni, Pb and Zn) in agricultural land from Land Use/Land Cover Area Frame Survey (LUCAS) 2009 topsoil database were used as a baseline. Maximum quantities of SS that can be safely applied to agricultural lands were obtained by a modeling procedure was used to determine the maximum safe quantities of SS that can be applied to agricultural lands for each country within the European Member States and the United Kingdom. Accumulation of HMs in soils was modelled by using a representative SS composition, distributed over 10 successive years at 5 Mg ha−1 year−1 rate. Ecological risk impact was assessed by using both the single ecological risk index (Er) and the integrated potential ecological risk index (RI). Maximum quantities of SS applied on agricultural soils in EU + UK were estimated to be 45 Mg ha−1 at the country level. We found that 19% of agricultural land (around 28,471,900 ha) in the EU + UK shows a higher RI than moderate risk after long time application of the representative SS. We show that the combination of the HM concentrations from the LUCAS topsoil survey and assumptions on the SS composition and soil HM partitioning can be used to define the actual and potential soil pollution rate in EU + UK. We demonstrate that the proposed methodology can be used by policymakers, farmers, regional authorities and other stakeholders, with possible adaptions based on local in-depth soil and SS knowledge.

Ecological risk assessment of heavy metals from application of sewage sludge on agricultural soils in Europe - Yunta - 2024 - European Journal of Soil Science - Wiley Online Library

Soil protists have vital roles as major microbiome predators in soil functioning and plant performance. Protists are also suggested to be the most responsive microbial group to external changes, such as anthropogenic land use types. While protists were long used as models for biogeography such as to investigate if ‘everything is everywhere’ among microbes, their biogeography at the taxonomic level has never been explored in depth at the continental scale and linked to anthropogenic drivers. Here we evaluated how land-use types affect the diversity and structure of soil protist communities across 885 locations in Europe based on the European Commission's Land Use and Coverage Area frame Survey (LUCAS). We observed higher α-diversity of soil protists but lower community structure dissimilarity (β-diversity) in croplands compared with woodlands, with grasslands in an intermediate position. The diversity of protist groups with a broader spatial niche was higher in croplands, whereas taxa with a narrower niche increased in woodlands. The importance of climate factors on α-diversity variations reduced as land use intensity increased, but the opposite trend was observed for the effect of soil properties. Our study suggests that there is an interaction between land use type, environmental effects, and spatial niche attributes of soil protist groups, highlighting the importance of land-use type on the dynamics of protist communities.

https://www.sciencedirect.com/science/article/pii/S0038071724001482

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions.

Connections between soil microbes, land use and European climate: Insights for management practices - ScienceDirect

Soil loss by water erosion represents a key threat to land degradation worldwide. This study employs an integrated quantitative modelling approach to estimate the long-term global sustainability impacts of soil erosion. The global biophysical model estimates a mean increase of soil erosion rates of between 30-66% over the period 2015-2070 under alternative climate-economic scenarios, assuming different greenhouse gas concentration trajectories. In a subsequent step, projected soil erosion rates are converted into land productivity losses and inputted into an economic global simulation model to identify those regional hotspots where the greatest market tensions are expected to occur.The headline result is that soil erosion presents a major challenge to food security in vulnerable regions (Africa and some tropical regions). Indeed, for certain crops (particularly oilseeds) the threat of shortages is potentially significant. Secondly, exploring different long-term socioeconomic-environmental pathways quantitatively confirms the merits of sustainable management practises in coping with anticipated market and environmental stresses arising from soil erosion. Finally, free (and fair) trade is essential to allow less affected regions to expand (marginally) their production, thereby cushioning the market tensions that are expected to occur in more acutely affected areas of the world.

Remaining Loyal to Our Soil: A Prospective Integrated Assessment of Soil Erosion on Global Food Security by Martina Sartori, Emanuele Ferrari, Robert M'Barek, G. Philippidis, Kirsten Boysen-Urban, Pasquale Borrelli, Luca Montanarella, Panos Panagos :: SSRN

The use of cover crops (CCs) is a promising cropland management practice with multiple benefits, notably in reducing soil erosion and increasing soil organic carbon (SOC) storage. However, the current ability to represent these factors in land surface models remains limited to small scales or simplified and lumped approaches due to the lack of a sediment-carbon erosion displacement scheme. This precludes a thorough understanding of the consequences of introducing a CC into agricultural systems. In this work, this problem was addressed in two steps with the spatially distributed CE-DYNAM model.First, the historical effect of soil erosion, transport, and deposition on the soil carbon budget at a continental scale in Europe was characterized since the early industrial era, using reconstructed climate and land use forcings. Then, the impact of two distinct policy-oriented scenarios for the introduction of CCs were evaluated, covering the European cropping systems where surface erosion rates or nitrate susceptibility are critical. The evaluation focused on the increase in SOC storage and the export of particulate organic carbon (POC) to the oceans, compiling a continental-scale carbon budget. The results indicated that Europe exported 1.95 TgC/year of POC to the oceans in the last decade, and that CCs can contribute to reducing this amount while increasing SOC storage. Compared to the simulation without CCs, the additional rate of SOC storage induced by CCs peaked after 10 years of their adoption, followed by a decrease, and the cumulative POC export reduction stabilized after around 13 years. The findings indicate that the impacts of CCs on SOC and reduced POC export are persistent regardless of their spatial allocation adopted in the scenarios. Together, the results highlight the importance of taking the temporal aspect of CC adoption into account and indicate that CCs alone are not sufficient to meet the targets of the 4‰ initiative. Despite some known model limitations, which include the lack of feedback of erosion on the net primary productivity and the representation of carbon fluxes with an emulator, the current work constitutes the first approach to successfully couple a distributed routing scheme of eroded carbon to a land carbon model emulator at a reasonably high resolution and continental scale. SHORT ABSTRACT: A spatially distributed model coupling erosion, transport, and deposition to the carbon cycle was developed. Then, it was used to simulate the impact of cover crops on both erosion and carbon, to show that cover crops can simultaneously increase organic carbon storage and reduce particulate organic carbon export to the oceans. The results seemed persistent regardless of the spatial distribution of cover crops.

Including land management in a European carbon model with lateral transfer to the oceans - PubMed

Nowadays, there is contrasting evidence between the ongoing continuing and widespread environmental degradation and the many means to implement environmental sustainability actions starting from good policies (e.g. EU New Green Deal, CAP), powerful technologies (e.g. new satellites, drones, IoT sensors), large databases and large stakeholder engagement (e.g. EIP-AGRI, living labs). Here, we argue that to tackle the above contrasting issues dealing with land degradation, it is very much required to develop and use friendly and freely available web-based operational tools to support both the implementation of environmental and agriculture policies and enable to take positive environmental sustainability actions by all stakeholders. Our solution is the S-DSS LANDSUPPORT platform, consisting of a free web-based smart Geospatial CyberInfrastructure containing 15 macro-tools (and more than 100 elementary tools), co-designed with different types of stakeholders and their different needs, dealing with sustainability in agriculture, forestry and spatial planning. LANDSUPPORT condenses many features into one system, the main ones of which were (i) Web-GIS facilities, connection with (ii) satellite data, (iii) Earth Critical Zone data and (iv) climate datasets including climate change and weather forecast data, (v) data cube technology enabling us to read/write when dealing with very large datasets (e.g. daily climatic data obtained in real time for any region in Europe), (vi) a large set of static and dynamic modelling engines (e.g. crop growth, water balance, rural integrity, etc.) allowing uncertainty analysis and what if modelling and (vii) HPC (both CPU and GPU) to run simulation modelling ‘on-the-fly’ in real time. Two case studies (a third case is reported in the Supplementary materials), with their results and stats, covering different regions and spatial extents and using three distinct operational tools all connected to lower land degradation processes (Crop growth, Machine Learning Forest Simulator and GeOC), are featured in this paper to highlight the platform's functioning. Landsupport is used by a large community of stakeholders and will remain operational, open and free long after the project ends. This position is rooted in the evidence showing that we need to leave these tools as open as possible and engage as much as possible with a large community of users to protect soils and land.

Land Degradation & Development | Environmental & Soil Science Journal | Wiley Online Journal

In the European Union (EU), a common understanding of the potential harmful effect of sewage sludge (SS) on the environment is regulated by the Sewage Sludge Directive 86/278/EEC (SSD). Limit values (LVs) for concentrations of heavy metals in soil are listed in Impact Assessment of this directive, and they were transposed by EU member states using different criteria. Member states adopted either single limit values or based on soil factors such as pH and texture to define the maximum limit values for concentrations of heavy metals in soils. Our work presents the first quantitative analysis of the SSD at the European level by using the Land Use and Coverage Area Frame Survey (LUCAS) 2009 topsoil database. The reference values at the European level were arranged taking into account the upper value (EU_UL) and the lower value (EU_LL) for each heavy metal (arsenic, cadmium, copper, chromium, mercury, nickel, lead, and zinc) as well as taking into account the pH of the soil (cadmium, copper, mercury, nickel, lead, and zinc) as introduced in the SSD Annex IA. Single and integrated contamination rate indices were developed to identify those agricultural soils that exceeded the reference values for each heavy metal. In total, 10%, 36%, and 19% of the LUCAS 2009 topsoil samples exceeded the limit values. Additionally, 12% and 16% of agricultural soils exceeded the concentration of at least one single heavy metal when European LVs were fixed following the soil pH in Strategy II compared to those national ones in Strategy I. Generally, all member states apply similar or stricter limit values than those laid down in the SSD. Our work indicates that choosing LVs quantitatively affects further actions such as monitoring and remediation of contaminated soils. The actual soil parameters, such as heavy metal concentrations and soil pH values from the LUCAS 2009 topsoil database, could be used by SSD-involved policy stakeholders not only to lay down the LVs for concentrations of heavy metal in soils but also for monitoring the SSD compliance grade by using the LUCAS surveys over time (past and upcoming LUCAS datasets).

https://link.springer.com/article/10.1007/s11356-024-31835-y

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.

Global Change Biology | Environmental Change Journal | Wiley Online Library

The EU Soil Strategy 2030 aims to increase soil organic carbon (SOC) in agricultural land to enhance soil health and support biodiversity as well as to offset greenhouse gas emissions through soil carbon sequestration. Therefore, the quantification of current SOC stocks and the spatial identification of the main drivers of SOC changes is paramount in the preparation of agricultural policies aimed at enhancing the resilience of agricultural systems in the EU. In this context, changes of SOC stocks (Δ SOCs) for the EU + UK between 2009 and 2018 were estimated by fitting a quantile generalized additive model (qGAM) on data obtained from the revisited points of the Land Use/Land Cover Area Frame Survey (LUCAS) performed in 2009, 2015 and 2018. The analysis of the partial effects derived from the fitted qGAM model shows that land use and land use change observed in the 2009, 2015 and 2018 LUCAS campaigns (i.e. continuous grassland [GGG] or cropland [CCC], conversion grassland to cropland (GGC or GCC) and vice versa [CGG or CCG]) was one of the main drivers of SOC changes. The CCC was the factor that contributed to the lowest negative change on Δ SOC with an estimated partial effect of −0.04 ± 0.01 g C kg−1 year−1, while the GGG the highest positive change with an estimated partial effect of 0.49 ± 0.02 g C kg−1 year−1. This confirms the C sequestration potential of converting cropland to grassland. However, it is important to consider that local soil and environmental conditions may either diminish or enhance the grassland's positive effect on soil C storage. In the EU + UK, the estimated current (2018) topsoil (0–20 cm) SOC stock in agricultural land below 1000 m a.s.l was 9.3 Gt, with a Δ SOC of −0.75% in the period 2009–2018. The highest estimated SOC losses were concentrated in central-northern countries, while marginal losses were observed in the southeast.

Global Change Biology | Environmental Change Journal | Wiley Online Library

Phosphorus (P) is an essential nutrient for all crops, yet its excess negatively affects public health, the environment, and the economy. At the same time, rock P is a critical raw material due to its importance for food production, the finite geological deposits, and its unequal regional distribution. As a consequence, nutrient management is addressed by numerous environmental policies. Process-based biogeochemical models are valuable instruments to monitor the P cycle and predict the effect of agricultural management policies. In this study, we upscale the calibrated DayCent model at European level using data-derived soil properties, advanced input data sets, and representative management practices. Our results depicted a P budget with an average P surplus (0.11 kg P ha−1 year−1), a total soil P (2240.0 kg P ha−1), and available P content (77.4 kg P ha−1) consistent with literature and national statistics. Through agricultural management scenarios, we revealed a range of potential changes in the P budget by 2030 and 2050, influenced by the interlink of P with biogeochemical carbon and nitrogen cycles. Thus, we developed a powerful assessment tool capable of i) identifying areas with P surplus or deficit at high spatial resolution of 1 km2, (ii) pinpointing areas where a change in agricultural management would be most urgent to reach policy goals in terms of environmental pollution, food security and resource efficiency of a critical raw material, and iii) assessing the response of the P cycle to modifications in agricultural management.

https://www.sciencedirect.com/science/article/pii/S0048969723057704

Excavated soil and rock (ESR) and dredging spoils (DDS) account for 23 % of the total EU waste generation in 2020. This study performs a life cycle assessment and life cycle costing to quantify the potential environmental and cost savings resulting from increasing the level of ESR and DDS prepared for reuse and recycled in comparison to the business-as-usual practice. Scenarios for the waste management pathways based on the status quo, technical feasibility or normative impositions are assessed, including the potential contribution to achieving the European Green Deal goals. Results show that promoting preparing for reuse and recycling could lead to non-negligible GHG reductions (up to 3.6 Mt. CO2 eq.) and economic savings (EUR 12.3 billion) annually. Depending upon the scenario, 0.2 % to 1 % of the net annual GHG emissions reductions sought by the European Green Deal could be facilitated by scaling up improved circular management of ESR and DDS at the EU level. Finally, the study highlights the main barriers to scaling up to more circular (i.e., preparing for reuse and recycling) and better performing management options in Europe. The results provide new insights for the European Green Deal and circular economy policymaking for CDW.

Management of excavated soil and dredging spoil waste from construction and demolition within the EU: Practices, impacts and perspectives - ScienceDirect

The so-called soil-landscape model is the central paradigm which relates soil types to their forming factors through the visionary Jenny’s equation. This is a formal mathematical expression that would permit to infer which soil should be found in a specific geographical location if the involved relationship was sufficiently known. Unfortunately, Jenny’s is only a conceptual expression, where the intervening variables are of qualitative nature, not being then possible to work it out with standard mathematical tools. In this work, we take a first step to unlock this expression, showing how Machine Learning can be used to predictably relate soil types and environmental factors. Our method outperforms other conventional statistical analyses that can be carried out on the same forming factors defined by measurable environmental variables.

Disentangling Jenny’s equation by machine learning | Scientific Reports

Editorial of the Special Issue Digital Soil Mapping, Decision Support Tools and Soil Monitoring Systems in the Mediterranean

Fertilization and soil management machine learning based sustainable agronomic prescriptions for durum wheat in Italy | Precision Agriculture

As urban agriculture increasingly becomes part of our regional food systems, its role in sustainable urban development grows. Urban agriculture can sustain food demand and contribute to food security, environmental sustainability, and community health. However, soil-related factors in urban agricultural systems pose unique challenges not found in more rural environments, and issues such as soil fertility, soil biodiversity, soil contamination, and existing policy demand further investigation to deepen and enhance the potential contribution of urban agriculture to livability in urban areas. This special issue collects studies to support the need for sustainable soil management, crop diversification, and management strategies for optimal soil health and good crop yield and quality. In addition, the issue examines recent advances in remote sensing technologies and deep learning techniques that offer potential tools for soil health monitoring and plant disease detection related to existing plant-based contamination, providing a way forward to make informed decisions for policy stakeholders and land planners. Combining these initiatives into urban planning and public health policies could have a considerable impact on urban well-being and resilience.

Urban Agriculture & Regional Food Systems Special Section: Improving Livability in Urban Areas: Examining Urban and Peri‐Urban Soil and Plant Management - Bulgari - 2024 - Urban Agriculture & Regional Food Systems - Wiley Online Library

Soil bulk density (BD) serves as a fundamental indicator of soil health and quality, exerting a significant influence on critical factors such as plant growth, nutrient availability, and water retention. Due to its limited availability in soil databases, the application of pedotransfer functions (PTFs) has emerged as a potent tool for predicting BD using other easily measurable soil properties, while the impact of these PTFs' performance on soil organic carbon (SOC) stock calculation has been rarely explored. In this study, we proposed an innovative local modeling approach for predicting BD of fine earth (BDfine) across Europe using the recently released BDfine data from the LUCAS Soil (Land Use and Coverage Area Frame Survey Soil) 2018 (0–20 cm) and relevant predictors. Our approach involved a combination of neighbor sample search, forward recursive feature selection (FRFS), and random forest (RF) models (local-RFFRFS). The results showed that local-RFFRFS had a good performance in predicting BDfine (R2 of 0.58, root mean square error (RMSE) of 0.19 g cm−3, relative error (RE) of 16.27 %), surpassing the earlier-published PTFs (R2 of 0.40–0.45, RMSE of 0.22 g cm−3, RE of 19.11 %–21.18 %) and global PTFs using RF models with and without FRFS (R2 of 0.56–0.57, RMSE of 0.19 g cm−3, RE of 16.47 %–16.74 %). Interestingly, we found that the best earlier-published PTF (R2 = 0.84, RMSE = 1.39 kg m−2, RE of 17.57 %) performed close to the local-RFFRFS (R2 = 0.85, RMSE = 1.32 kg m−2, RE of 15.01 %) in SOC stock calculation using BDfine predictions. However, the local-RFFRFS still performed better (ΔR2 > 0.2) for soil samples with low SOC stocks (< 3 kg m−2). Therefore, we suggest that the local-RFFRFS is a promising method for BDfine prediction, while earlier-published PTFs would be more efficient when BDfine is subsequently utilized for calculating SOC stock. Finally, we produced two topsoil BDfine and SOC stock datasets (18 945 and 15 389 soil samples) at 0–20 cm for LUCAS Soil 2018 using the best earlier-published PTF and local-RFFRFS, respectively. This dataset is archived on the Zenodo platform at https://doi.org/10.5281/zenodo.10211884 (S. Chen et al., 2023). The outcomes of this study present a meaningful advancement in enhancing the predictive accuracy of BDfine, and the resultant BDfine and SOC stock datasets for topsoil across the Europe enable more precise soil hydrological and biological modeling.

ESSD - European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions

The 2018 LUCAS (Land Use and Coverage Area frame Survey) Soil Pesticides survey provides a European Union (EU)‐scale assessment of 118 pesticide residues in more than 3473 soil sites. This study responds to the policy need to develop risk‐based indicators for pesticides in the environment. Two mixture risk indicators are presented for soil based, respectively, on the lowest and the median of available No Observed Effect Concentration (NOECsoil,min and NOECsoil,50) from publicly available toxicity datasets. Two further indicators were developed based on the corresponding equilibrium concentration in the aqueous phase and aquatic toxicity data, which are available as species sensitivity distributions. Pesticides were quantified in 74.5% of the sites. The mixture risk indicator based on the NOECsoil,min exceeds 1 in 14% of the sites and 0.1 in 23%. The insecticides imidacloprid and chlorpyrifos and the fungicide epoxiconazole are the largest contributors to the overall risk. At each site, one or a few substances drive mixture risk. Modes of actions most likely associated with mixture effects include modulation of acetylcholine metabolism (neonicotinoids and organophosphate substances) and sterol biosynthesis inhibition (triazole fungicides). Several pesticides driving the risk have been phased out since 2018. Following LUCAS surveys will determine the effectiveness of substance‐specific risk management and the overall progress toward risk reduction targets established by EU and UN policies. Newly generated data and knowledge will stimulate needed future research on pesticides, soil health, and biodiversity protection. Integr Environ Assess Manag 2024;20:1639–1653. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Evaluation of the ecological risk of pesticide residues from the European LUCAS Soil monitoring 2018 survey | Integrated Environmental Assessment and Management | Oxford Academic

This report delves into the intricate interplay between drivers, pressures and impacts on soil in the 32 Member States of the European Environment Agency (EEA), along with six cooperating countries from the West Balkans, Ukraine and UK, shedding light on the multifaceted challenges facing soil conservation efforts. Our analysis shows the complex interactions among various factors, both anthropogenic and natural, shaping soil degradation processes and their subsequent consequences. We highlight key findings, including the significant impacts of soil degradation on agriculture, ecosystem resilience, water quality, biodiversity, and human health, underscoring the urgent need for comprehensive soil management strategies. Moreover, our examination of citizen science initiatives underlines the importance of engaging the public in soil monitoring and conservation efforts. This work emphasises the policy relevance of promoting sustainable soil governance frameworks, supported by research, innovation, and robust soil monitoring schemes, to safeguard soil health and ensure the long-term resilience of ecosystems.

Direct link: /public_path//JRC137600_State_of_Soils_in_Europe_Report_2024_online.pdf

Clay minerals are a key factor in mineral soils as they are controlling physic, chemical and biological soil properties. The X-ray diffraction (XRD) analysis has been widely used to identify and quantify minerals in earth science The aim of this research is to describe the clay minerals in soils of Europe and United Kingdom by using soil samples from the Land Use/Cover Area Frame Survey (LUCAS) topsoil database sampled in 2015. A subset of 388 soil samples were selected from LUCAS 2015 topsoil survey. The clay fraction (<2 µm) was separated by sedimentation in distilled water. X-ray powder diffraction (XRPD) measurements have been carried out with a Siemens D5000 diffractometer with a graphite monochromator, using CuKα radiation at 40 kV and 40 mA. Clay mineralogy has been studied by measurement of basal spacing parameters on the clay fraction oriented in glass slides: 3 to 13 °2θ range 0.02 °2θ step size. The study involved the measurement of the 1. air-dried sample, 2. ethylene glycol solvated sample, 3. heat treatment at 110, 350 and 550 °C. Identification of clay minerals were based on the d-spacing value of their 00l (mainly 001) reflections after different diagnostic treatment. The semiquantitative composition of <2 µm fractions was estimated by using integrated areas of 00l reflections. Brief description of the clay mineralogy of all samples and semi quantitative mineral composition was performed at country level. The X-ray diffractograms after the different treatment (black = untreated, blue = ethylene glycol solvated, green = 110 °C, dark red = 350 °C, red = 550 °C) for each soil sample were analyzed. Majority clay minerals were compared to soils properties such as CEC, soil pH, soil organic carbon (SOC), and clay and sand content. Current descriptive analysis can be used to identify the most relevant clay minerals in soils of Europe. Monitoring over time can be used as soil health indicator to establish potential correlations between clay minerals and relevant threats as soil degradation, soil erosion, and soil pollution.

Download PDF: Clay mineral inventory in soils of Europe based on LUCAS 2015 survey soil samples

The objectives of the ‘IACS65 data sharing project’ performed by the JRC were to make: IACS data more visible and accessible through the INSPIRE geoportal by the production and publication of discovery metadata for datasets and services, improve interoperability with other relevant data sets for the interest of public administration (LULUCF, crop classification, landscape features), ensure effective re-use through use cases, with a specific focus on soil, explore IACS data when it is integrated with third data bases, collaboration with the Member States (Paying agencies). Substantial progress has been made in the 30 months for the project thanks to AGRI/JRC efforts to facilitate IACS data sharing with Member States, even though data are not yet available for all Member States. Good results have been obtained and the positive trend along time was possible thanks to different EC actions, notably: publication of technical guidelines for the data discovery metadata and datasets metadata, adaptation of INSPIRE geoportal for better visibility of LPIS and GSA(A) (In line with the implementation action on High Value data sets) and trainings for the paying agencies, leading to exchange during workshops and conferences. Nevertheless, the efforts should continue.

Download the Report

EU Soil Observatory 2022

This report presents the activities of the EU Soil Observatory (EUSO) that took place during 2021. Through its five main objectives, the EUSO contributes to improving the monitoring of soils, to creating and sharing knowledge and data about EU soils, in particular producing tailored outputs in support of policy development and to the wider public. These activities feed into the overarching knowledge management objective under which the EUSO provided extensive policy support to a range of policy areas, notably the upcoming Soil Health Law and the Horizon Europe’s Soil Mission.

A key element of the EU Soil Observatory are the six EUSO Working Groups (WG) that aim to discuss policy or technical advances on a particular topic. Their activities in 2022 were diverse and ranged from providing policy support (Soil Monitoring, Soil Pollution WGs), technical progress on integration of soil data (Soil Data WG) or advancing scientific knowledge about soils (Soil Erosion WG).

This report also highlights the developments to be expected in 2023. In particular, the EUSO will produce reports on soil pollution, soil organic carbon trends, pesticides in soils, land degradation and a soil fertility index and work on the state of soil health in the EU. A key development will be the publication of the EUSO soil health dashboard. The EUSO will support dedicated Soil Mission research projects and will continue to provide support for the upcoming Soil Health Law proposal. The EUSO is also planning a 2023 EU Soil Week.

Link: https://esdac.jrc.ec.europa.eu/public_path//shared_folder/doc_pub/JRC133346.pdf

Factors driving microbial community composition and diversity are well established but the relationship with microbial functioning is poorly understood, especially at large scales. We analysed microbial biodiversity metrics and distribution of potential functional groups along a gradient of increasing land-use perturbation, detecting over 79,000 bacterial and 25,000 fungal OTUs in 715 sites across 24 European countries. We found the lowest bacterial and fungal diversity in less-disturbed environments (woodlands) compared to grasslands and highly-disturbed environments (croplands). Highly-disturbed environments contain significantly more bacterial chemoheterotrophs, harbour a higher proportion of fungal plant pathogens and saprotrophs, and have less beneficial fungal plant symbionts compared to woodlands and extensively-managed grasslands. Spatial patterns of microbial communities and predicted functions are best explained when interactions among the major determinants (vegetation cover, climate, soil properties) are considered. We propose guidelines for environmental policy actions and argue that taxonomical and functional diversity should be considered simultaneously for monitoring purposes.

Link: https://www.nature.com/articles/s41467-023-37937-4

Intensive vegetable production is characterised by high nitrogen (N) application rates and frequent irrigations, promoting elevated nitrous oxide (N₂O) emissions, a powerful greenhouse gas indicative for the low N use efficiency (NUE) in these systems. The use of nitrification inhibitors (NI) has been promoted as an effective strategy to increase NUE and decrease N₂O emissions in N-intensive agricultural systems. This study investigated the effect of two NIs, 3,4-dimethylpyrazole phosphate (DMPP) and 3-methylpyrazole 1,2,4-triazole (Piadin), on N₂O emissions and 15N fertiliser recovery in a field experiment in sweet corn. The trial compared the conventional fertiliser N rate to a 20% reduced rate combined with either DMPP or Piadin. The use of NI-coated urea at a 20% reduced application rate decreased cumulative N2O emissions by 51% without yield penalty. More than 25% of applied N was lost from the conventional treatment, while a reduced N rate in combination with the use of a NI significantly decreased N fertiliser losses (by up to 98%). Across treatments, between 30 and 50% of applied N fertiliser remained in the soil, highlighting the need to account for residual N to optimise fertilisation in the following crop. The reduction of overall N losses without yield penalties suggests that the extra cost of using NIs can be compensated by reduced fertiliser application rates, making the use of NIs an economically viable management strategy for growers while minimising environmentally harmful N losses from vegetable growing systems.

https://doi.org/10.1007/s10705-021-10185-y

Land degradation is the persistent reduction in the capacity of the land to support human and other life on Earth (IPBES, 2018). This process jeopardizes the provision of ecosystem services. The Sustainable Development Goal (SDG) 15, ‘Life on Land’, includes efforts to sustainably manage and recover natural ecosystems and restore degraded land and soil. Under the umbrella of SDG 15, the United Nations Convention to Combat Desertification (UNCCD) has defined an indicator framework to monitor progress toward ‘land degradation neutrality’. We evaluated the performance of SDG 15.3.1, focusing on “…proportion of land that is degraded over the total land area” for the European Union (EU) using the TRENDS.EARTH software. We assessed the impact of alternative datasets at different spatial resolutions and policy-relevant data sources for land cover (CORINE) and soil organic carbon (SOC) stock (LUCAS). Our hypothesis was that higher spatial resolution sub-indicators would better identify the total share of degraded land and provide a clearer picture of the extent of degraded land for the target period. Land productivity trajectories were adjusted using the Water Use Efficiency index that revealed the high share of improving land reported by the NDVI trends. Therefore, it is advisable to use always a climate correction to assess land productivity trends. Replacing default datasets with alternative sub-indicators allowed the detection of 25–40% more degraded areas. Additionally, the integration with a combined proxy of land degradation (soil erosion >10 Mg ha⁻¹ yr⁻¹, and SOC concentration <1%) identified an additional 50% land degradation and revealed that a large extent of the EU needs restoration measures.

Pheomelanin is a pigment responsible for yellowish-to-reddish colours of vertebrate teguments. Its biosynthesis is favoured under high concentration of intracellular thiols, which, in turn, can depend on the environmental exposure to sulphur. Thus, pheomelanin production should be more intense and frequent in environments characterized by high level of sulphur, such as volcanic regions. In this study, we aimed at addressing this hypothesis by investigating variation in plumage colour of insular populations of the cosmopolitan barn owl (Tyto alba species complex) according to the presence of soils of volcanic origin (i.e. andosols) and recent volcanic activity.

https://doi.org/10.1111/jbi.14596

https://doi.org/10.1029/2023JG007391

Conservation agriculture (CA) is an agronomic system based on minimum soil disturbance (no-tillage, NT), permanent soil cover, and species diversification. The effects of NT on soil organic carbon (SOC) changes have been widely studied, showing somewhat inconsistent conclusions, especially in relation to the Mediterranean and humid subtropical climates. These areas are highly vulnerable and predicted climate change is expected to accentuate desertification and, for these reasons, there is a need for clear agricultural guidelines to preserve or increment SOC. We quantitively summarized the results of 47 studies all around the world in these climates investigating the sources of variation in SOC responses to CA, such as soil characteristics, agricultural management, climate, and geography. Within the climatic area considered, the overall effect of CA on SOC accumulation in the plough layer (0–0.3 m) was 12% greater in comparison to conventional agriculture. On average, this result corresponds to a carbon increase of 0.48 Mg C ha⁻¹ year⁻¹. However, the effect was variable depending on the SOC content under conventional agriculture: it was 20% in soils which had ≤ 40 Mg C ha⁻¹, while it was only 7% in soils that had > 40 Mg C ha⁻¹. We proved that 10 years of CA impact the most on soil with SOC ≤ 40 Mg C ha⁻¹. For soils with less than 40 Mg C ha⁻¹, increasing the proportion of crops with bigger residue biomasses in a CA rotation was a solution to increase SOC. The effect of CA on SOC depended on clay content only in soils with more than 40 Mg C ha⁻¹ and become null with a SOC/clay index of 3.2. Annual rainfall (that ranged between 331–1850 mm y⁻¹) and geography had specific effects on SOC depending on its content under conventional agriculture. In conclusion, SOC increments due to CA application can be achieved especially in agricultural soils with less than 40 Mg C ha⁻¹ and located in the middle latitudes or in the dry conditions of Mediterranean and humid subtropical climates.

https://doi.org/10.1111/ejss.13338

The so-called soil-landscape model is the central paradigm which relates soil types to their forming factors through the visionary Jenny’s equation. This is a formal mathematical expression that would permit to infer which soil should be found in a specific geographical location if the involved relationship was sufficiently known. Unfortunately, Jenny’s is only a conceptual expression, where the intervening variables are of qualitative nature, not being then possible to work it out with standard mathematical tools. In this work, we take a first step to unlock this expression, showing how Machine Learning can be used to predictably relate soil types and environmental factors. Our method outperforms other conventional statistical analyses that can be carried out on the same forming factors defined by measurable environmental variables.

https://doi.org/10.1038/s41598-023-44171-x

https://doi.org/10.1016/j.jenvman.2023.117478

Rural fires are now a major societal concern across the world, especially where fire regimes have (apparently) intensified in terms of burnt area, intensity and recurrency. Among the indirect fire effects, fire-enhanced runoff and erosion have been an important focus of post-fire land and water management, in particular through emergency stabilization of hillslopes using a range of erosion mitigation measures. The most widely applied and – scientifically tested – measure is that of mulching with agricultural straw, in spite of concerns of introducing exogenous organic material and especially seeds of non-native higher plant species, including the straw species it- or themselves. So far, field studies in the present study region of north-central Portugal have preferred using endogenous forest residues but these studies concerned forest types for which such residues are easily available. The latter, however, is not the case for strawberry tree stands, so that straw mulch was selected in this study as a cheaper alternative to eucalypt or pine residues. This - apparently, first – post-fire erosion mitigation study in a strawberry tree (Arbutus unedo L.) stand aimed to compare post-fire sediment and organic matter losses as well as ground vegetation recovery without and with applying barley (Hordeum vulgare L.) straw mulch at a low rate of 2 Mg ha−1. The experimental set-up involved a randomized block design with a total of six geotextile-bounded erosion plots of 2 m by 5 m that were organized in three blocks, were installed and mulched roughly one month after the 17-October-2017 M-fire in inland Central Portugal, and monitored at 12 irregular intervals during the first two post-fire years. The principal findings were that: (i) especially the specific sediment losses without mulching over the first post-fire year were notably higher than those reported by the prior field studies in the region, in eucalypt and maritime pine plantations; and that the - low - mulching rate: (ii) was extremely effective in reducing these first-post-fire-year losses; but (iii) did not result in changes in the cover or floristic composition of the ground vegetation cover that were noteworthy and longer-lived than the first post-fire year.

https://doi.org/10.1016/j.ecoleng.2023.107074

In recent years there has been an increased demand for digital soil mapping (DSM) products. DSM has become the ultimate soil spatial representation framework due to its quantitative results, replicability, and uncertainty analysis. The present study aimed to map the probability distribution of the derived soil profiles (DSPs) of soil typological units (STUs). DSPs are statistical representation of the properties of the soil profiles belonging to STUs. STUs aggregate individual profiles into a group. The criteria used for grouping were homogeneity for World Reference Base (WRB) reference soil group (WRB-RSG), qualifiers (WRB-qu), and Soil Taxonomy particle size for the family classification (USDA-PS), and the belonging to a specific Soil Region. The European Soil Regions have been suggested as the primary grouping criteria for soil mapping at the European continental scale since they define continental-scale soilscapes, distinguished mainly by their climate and geology. To map DSPs, we firstly mapped STUs. The grouping criteria of STUs were mapped at 500 m spatial resolution, using a Neural Network trained on 18,707 georeferenced and analyzed soil profiles selected from the Italian national soil database. A 10% of the soil profiles were randomly sampled using a stratified sampling approach for validation. In particular, the procedure consisted of: i) mapping the grouping criteria WRB-RSG, WRB-qu, and USDA-PS, on a 500 m national grid, through Neural Network; ii) grouping soil profiles on the base of the combinations of grouping criteria (WRB-RSG, WRB-qu, USDA-PS, and Soil Regions) as mapped with the first step at each grid node, to produce a map of Soil Typological Units (STUs); iii) calculating statistics for the soil parameters of the groups of soil profiles created, to produce a map of Derived Soil Profiles (DSPs). DSPs statistics (average, standard deviation, and sample numerosity) were elaborated for the following parameters: soil rooting depth, pH (in water), soil organic carbon, clay, silt, sand, coarse fragments, and cation exchange capacity. The maps obtained were validated against the test set. The same test set was used for the comparison with the National benchmark map (Soils Map of Italy 1:1,000,000) and with the global scale SoilGrids at 250 m spatial resolution. The overall accuracy was 45.98% for the WRB-RSG map compared with the 30.74% of WRB-RSG as mapped with the Soil Map of Italy, and 28.79% as mapped with SoilGrids; 33.07% for WRB-qu compared with the 15.69% of WRB-qu as mapped with the Soil Map of Italy, and 12.45% as mapped with SoilGrids, and 45.48% for USDA-PS, not comparable with the National and Global benchmarks. Tau statistics showed a higher accuracy Kappa of our approach than in others, due to the unbalanced classes numerosity. The predictive ability in the validation of DSPs parameters resulted in a R2 of 0.35 for clay (0.16 with SoilGrids), 0.28 for sand (0.08 with SoilGrids), 0.18 for pH in water (0.21 with SoilGrids). The proposed approach produced harmonized soil type maps with higher accuracy than the previous generation of conventional field-based soil maps for the national benchmark and the calculation of the uncertainty. The STUs express variability of soil properties between groups so their knowledge might improve our understanding of the soil distribution, the planning of their management, monitoring, and the decisions for further surveys. A future challenge will be including more dynamic parameters in the criteria used to create STU, to help monitoring soil management effects.

https://doi.org/10.1016/j.geodrs.2023.e00619

The European fan palm (Chamaerops humilis, Arecaceae) is the only native palm in continental Europe, providing ecosystem services that are hard to obtain from other species. However, its populations are declining in some areas due to anthropogenic effects including climate change. Knowledge of genetic variability among natural populations is needed to establish conservation plans, to prevent genetic contamination of native stands by cultivated germplasm and to exploit it as an ornamental species. However, information on the genetic similarities among C. humilis populations is scarce. The aims of this work were to study genetic structure in C. humilis using a set of specifically designed genetic markers and to highlight genetic similarities and their relationships with geographical proximity. We sampled 301 specimens from 42 natural populations throughout the distribution area and analysed these with ten di-, tri- and tetra-nucleotide simple sequence repeats. Relationships between genetic similarities and geographical distances were analysed and populations grouped according to a genetic, geographical or national clustering. We found lower variability in populations from the eastern half of the distribution, and this lower variability was accompanied by a stronger relationship between genetic differences and spatial proximity. In addition, we found that C. humilis probably showed two patterns of spread and further differentiation: one from Morocco to southern continental Spain and then to Portugal and the Balearic Islands, and one from Morocco to Algeria, Tunisia, Sicily and continental Italy. Populations from Sardinia and France showed similarities to those from Spain and Tunisia, respectively, and may have arisen from multiple colonization events. Our results support the hypothesis that isolation on large islands may have increased diversification of the species even if all populations shared the same founder. These results have important implications for both the ecological management and the conservation of the species.

https://doi.org/10.1093/botlinnean/boac053

https://doi.org/10.1002/sae2.12041

Micro- and nanoplastics (MNPs) emissions and pollution are a growing concern due to their potential impact on ecosystems and human health, particularly in soil. This study conducts a comprehensive bibliometric analysis of 2,451 publications spanning from 2006 to 2023. The aim is to assess the research landscape, trends, contributors, and collaborative efforts related to MNPs in soil. Moreover, it examines the extensive research on the effects of MNPs on soil organisms, including earthworms, nematodes, and other fauna as well as the physical–chemical impacts, nanoscale interactions, and ecotoxicological effects on soil microorganisms. Utilizing network analysis, this study explores the global distribution of research across countries, institutions, authors, and keywords, shedding light on the interconnected scientific exploration. The findings reveal a consistent rise in research output over the past decade, reflecting worldwide interest in soil MNPs pollution. It also identifies influential authors and interdisciplinary clusters, highlighting their significant collaborations. Moreover, it pinpoints key institutions and leading journals in this area. Keyword co-occurrence and time-series analysis uncover seven significant research clusters. All provide insights into crucial MNPs aspects and their environmental and health implications. Our findings guide future research and inform strategies to combat MNPs pollution in soils, underscore the need for interdisciplinary approaches to address this complex challenge. In essence, our comprehensive bibliometric analysis serves as a valuable resource, it benefits researchers, policy stakeholders by promoting further research and guiding strategies to mitigate MNPs pollution in soils, in support of ecosystem preservation and human health protection.

https://doi.org/10.1016/j.ecolind.2023.111109

Elucidating contents and drivers of soil bacterial and fungal biomass in contrasting land uses and climates at European scale is useful to define appropriate policies for the conservation of the ecosystem services that soil microorganisms provide. Here, we aimed to (i) quantify and compare bacterial and fungal biomass in 513 European soils collected from three different land uses (forests, grasslands, and croplands) and climates (arid, temperate, and cold) through analysis of fatty acid methyl esters; (ii) model the factors controlling soil bacterial and fungal biomass; and (iii) investigating levels of bacterial and fungal biomass in cropland soils cultivated with three important crop types in Europe: cereals, oil-producing crops, and orchards. Bacterial biomass decreased with land use in the following order: grasslands > croplands > forests and was found to be the highest in temperate environments. Similar patterns were found for biomass of Gram-positive and Gram-negative bacteria and Actinobacteria. Soil fungal biomass was greater in forests than in croplands and grasslands and was favoured by colder environments. The fungi to bacteria ratio (F/B) decreased as follows: forests > croplands > grasslands, with soils in colder climates showing greater F/B ratios in croplands and forests. Soil texture, soil organic carbon, and nitrogen were shown to directly drive bacterial and fungal biomass. The biomass of the different microbial groups was not influenced by the crop type when only croplands were considered. Fungi appear to be more susceptible to agricultural soil use than bacteria. Moreover, agricultural use of soil seems to buffer the effect of harsh climatic conditions on soil bacterial biomass. The present study improves our understanding of the combined effects of land use and climate on soil bacterial and fungal biomass across Europe.

https://doi.org/10.1016/j.geoderma.2023.116474

Sustainable land management (SLM) is widely recognized as the key to reducing rates of land degradation, and preventing desertification. Many efforts have been made worldwide by various stakeholders to adopt and/or develop various SLM practices. Nevertheless, a comprehensive review on the spatial distribution, prospects, and challenges of SLM practices and research is lacking. To address this gap, we gathered information from a global SLM database provided by the World Overview of Conservation Approaches and Technologies (WOCAT) and two bibliographic databases of academic research. Over 1900 SLM practices and 1181 academic research papers from 129 and 90 countries were compiled and analyzed. Relatively better SLM dissemination was observed in dry subhumid countries and countries with medium scores on the Human Development Index (HDI), whereas dissemination and research were both lower in humid countries with low HDI values. Cropland was the main land use type targeted in both dissemination and research; degradation caused by water erosion and mitigation aimed at water erosion were also the main focus areas. Other dominant land use types (e.g., grazing) and SLM purposes (e.g., economic benefits) have received relatively less research attention compared to their dissemination. Overall, over 75 % of the 60 countries experiencing high soil erosion rates (>10 t ha⁻¹ yr⁻¹) also have low HDI scores, as well as poor SLM dissemination and research implying the limited evidence-based SLM dissemination in these countries. The limitation of research evidence can be addressed in the short term through integrating existing scientific research and SLM databases by adopting the proposed Research Evidence for SLM framework. There is, however, a great need for additional detailed studies of country-specific SLM challenges and prospects to create appropriate evidence-based SLM dissemination strategies to achieve multiple SLM benefits.

https://doi.org/10.1016/j.scitotenv.2022.160027

Phosphorus (P) is a non-renewable geological macronutrient that plays an essential role in food security. The excessive use of P as a fertilizer and its subsequent diffuse loss leads to the deterioration of water quality, eutrophication, and loss of biodiversity. Ecosystem process-based models are a powerful tool to depict the P cycle, investigate the effects of management practices and climate change, and ultimately assess policy interventions that affect biogeochemical cycles. Of the limited number of P models in agricultural production systems, none have been tested in temperate conditions for periods of decades using long-term field experiments.

https://doi.org/10.1016/j.agsy.2022.103595

During the International Workshop on Soil Erosion and Riverine Sediment in Mountainous Regions held in November 2022, scientists from many countries shared their state-of-the-art knowledge and brainstormed to improve scientific understanding for coping with climate change and anthropogenic impacts. Information summarized in this discussion includes proposed key scientific questions and suggested joint actions to reduce soil erosion and riverine sediment problems in mountainous regions.

https://doi.org/10.1016/j.iswcr.2023.04.006

Rainfall erosivity is a key factor that influences soil erosion by water. Rain-gauge measurements are commonly used to estimate rainfall erosivity. However, long-term gauge records with sub-hourly resolutions are lacking in large parts of the world. Satellite observations provide spatially continuous estimates of rainfall, but they are subject to biases that affect estimates of rainfall erosivity. We employed a novel approach to map global rainfall erosivity based on a high-temporal-resolution (30-min), long-term (2001–2020) satellite-based precipitation product—the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG)—and mean annual rainfall erosivity from the Global Rainfall Erosivity Database (GloREDa) stations (n = 3286). We used a residual-based merging scheme to integrate GPM-IMERG-based rainfall erosivity with GloREDa using Geographically Weighted Regression (GWR). The accuracy of the GWR-based merging scheme was evaluated with a 10-fold cross-validation against GloREDa stations. Based on GPM-IMERG-only, the global mean annual rainfall erosivity was estimated to be 1173 MJ mm ha⁻¹ h⁻¹ yr⁻¹ with a standard deviation of 1736 MJ mm ha⁻¹ h⁻¹ yr⁻¹. The mean value estimated via GPM-IMERG merged with GloREDa was 2020 MJ mm ha⁻¹ h⁻¹ yr⁻¹ with a standard deviation of 3415 MJ mm ha⁻¹ h⁻¹ yr⁻¹. Overall, GPM-IMERG-only estimates underestimated rainfall erosivity. The underestimations were greatest in areas of high rainfall erosivity. The accuracy of rainfall erosivity estimates from GPM-IMERG merged with GloREDa substantially improved (Nash-Sutcliffe efficiency = 0.83, percent bias = −2.4%, and root mean square error = 1122 MJ mm ha⁻¹ h⁻¹ yr⁻¹) compared to estimates by GPM-IMERG-only (Nash-Sutcliffe efficiency = 0.51, percent bias = 27.8%, and root mean square error = 1730 MJ mm ha⁻¹ h⁻¹ yr⁻¹). Improving satellite-based global rainfall erosivity estimates through integrating with gauge data is relevant as it can contribute to enhancing soil erosion modeling and, in turn, support land degradation neutrality programs.

https://doi.org/10.1016/j.jhydrol.2023.129555

The European Green Deal with its high ambition has set the European Union (EU) on a promising path towards greater soil protection. The EU Soil Strategy 2030, the Biodiversity Strategy 2030, the Farm to Fork Strategy, the Zero Pollution, the Nature Restoration Law and the European Climate Law, among others, include actions to protect our soils. Research and Innovation (R&I) will play a key role in developing new knowledge and tools enabling the transition to healthy soils. The main aim of this paper is to analyse past and near-future trends in EU's funding for R&I on soil-related issues. For this purpose, a review of EU-funded soil projects was conducted based on the data available in the Community Research and Development Information Service and the official portal for European data. Our analysis shows that over the past 40 years, the EU has invested significantly in developing integrated knowledge about the relationships between soil functions and ecosystem services and how human-induced pressures affect soil health. Following the adoption of the EU Soil Thematic Strategy in 2006, there was an increase in research funding for soil-related research. Furthermore, our analysis also illustrates an interesting interplay of permanent and changing soil themes. The Horizon Europe Mission ‘A Soil Deal for Europe’, which aims to establish a network of 100 living labs and lighthouses to lead the transition towards healthy soils and safeguard human and planetary health by 2030, provides a further incentive for soil research. Together with the EU Soil Strategy 2030 and the new proposal for a Directive on Soil Monitoring and Resilience (Soil Monitoring Law), and the EU Soil Observatory (EUSO), the three instruments set up the political framework, concrete measures, and a monitoring system needed for the protection, restoration and sustainable use of soils.

https://bsssjournals.onlinelibrary.wiley.com/doi/10.1111/ejss.13423

Soil erosion is a complex process involving multiple natural and anthropic agents, causing the deterioration of multiple components comprising soil health. Here, we provide an estimate of the spatial patterns of cropland susceptibility to erosion by sheet and rill, gully, wind, tillage, and root crops harvesting and report the co-occurrence of these processes using a multi-model approach. In addition, to give a global overview of potential future changes, we identify the locations where these multiple concurrent soil erosion processes may be expected to intersect with projected dry/wet climate changes by 2070. Of a modelled 1.48 billion hectares (B ha) of global cropland, our results indicate that 0.56 B ha (∼36% of the total area) are highly susceptible (classes 4 and 5) to a single erosion process, 0.27 B ha (∼18% of the total area) to two processes and 0.02 B ha (1.4% of the total area) to three or more processes. An estimated 0.82 B ha of croplands are susceptible to possible increases in water (0.68 B ha) and wind (0.14 B ha) erosion. We contend that the presented set of estimates represents a basis for enhancing our foundational knowledge on the geography of soil erosion at the global scale. The generated insight on multiple erosion processes can be a useful starting point for decision-makers working with ex-post and ex-ante policy evaluation of the UN Sustainable Development Goal 15 (Life on Land) activities. Scientifically, this work provides the hitherto most comprehensive assessment of soil erosion risks at the global scale, based on state-of-the-art models.

https://www.sciencedirect.com/science/article/pii/S209563392300062X?via%3Dihub

The original version of this Article contained an error in Fig. 1a, in which part of the ‘LUCAS Vegetation cover’ legend was omitted. This has now been corrected in the PDF and HTML versions of the Article.

https://www.nature.com/articles/s41467-023-39596-x

In the version of this article originally published, there was a plotting error in the presentation of Extended Data Fig. 5

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Diagnostic horizons, properties and materials are commonly applied building units of national and international soil classification systems. The presence, depth or absence of diagnostic information supports the process of objective soil classification, such as the World Reference Base (WRB). While the diagnostic units and associated descriptive qualifiers convey information that reflect pedogenesis, they also indicate important, and often complex properties that are related to soil fertility and other soil functions. The spatial extent or the continuum of diagnostic information is often different from the spatial extent of the mapping units in general soil maps (mostly reflecting soil types). This paper presents the spatial distribution of selected diagnostic units and qualifiers for the European Union and describes their significance for key soil functions. The derivation of selected diagnostics was performed based on the information provided in the European Soil Database and by taking into consideration the definitions, rules and allocation procedure of soils to the appropriate Reference Soil Group (RSG) defined by the WRB key. The definition of the presence/absence of the diagnostic units were performed by extracting information related to the first level of the WRB classification and to the qualifiers provided by the ESDB on the Soil Taxonomic Units (STU) level. The areal percentage of the STUs (thus, the derived diagnostics) within Soil Mapping Units (SMUs) was calculated and was visualized on separate maps. The study demonstrated the importance of the spatial information that the diagnostic elements convey, especially related to soil functions.

10.15201/hungeobull.71.4.1

Dryland soils provide different societal and environmental services, such as food supply and biodiversity support. In Europe, most of the dryland areas are devoted to agriculture. In the next decades, both European and worldwide drylands are expected to suffer with increased intensity due to the expected climate change-derived rise in aridity. Many studies have focussed on aridity-induced changes in major nutrients in drylands, but little is known of the impact of environmental and biogeochemical factors on micronutrients with critical roles in life, and as inorganic contaminants with ecotoxicological implications. We analysed and explored drivers of total and available concentrations of micronutrients (Co, Cu, Fe, Mo, Mn, Ni and Zn) and contaminants (As, Cd and Pb) in 148 soil samples collected from European drylands covering a wide range of aridity and of other geochemical parameters. The availability of micronutrients increased with their total content, decreased with pH and was enhanced by organic C content. Aridity decreased the availability of Fe, a key element in human diet. Our findings also highlight the scarcity of this micronutrient in European drylands, as well as of some other important micronutrients like Zn and Mo in agricultural soils. Total content was the main driver of the availability of Cd and Pb, and organic matter exerted synergistic effects on contaminant release. Our data show the need for precise management practices to be incentivised by agricultural and environmental policies in order to ensure micronutrient supply and avoid contamination, thus maintaining adequate levels of agricultural productivity and simultaneously preserving dryland ecosystems.

10.1111/ejss.13163

Soils form the basis for agricultural production and other ecosystem services, and soil management should aim at improving their quality and resilience. Within the SoilCare project, the concept of soil-improving cropping systems (SICS) was developed as a holistic approach to facilitate the adoption of soil management that is sustainable and profitable. SICS selected with stakeholders were monitored and evaluated for environmental, sociocultural, and economic effects to determine profitability and sustainability. Monitoring results were upscaled to European level using modelling and Europe-wide data, and a mapping tool was developed to assist in selection of appropriate SICS across Europe. Furthermore, biophysical, sociocultural, economic, and policy reasons for (non)adoption were studied. Results at the plot/farm scale showed a small positive impact of SICS on environment and soil, no effect on sustainability, and small negative impacts on economic and sociocultural dimensions. Modelling showed that different SICS had different impacts across Europe—indicating the importance of understanding local dynamics in Europe-wide assessments. Work on adoption of SICS confirmed the role economic considerations play in the uptake of SICS, but also highlighted social factors such as trust. The project’s results underlined the need for policies that support and enable a transition to more sustainable agricultural practices in a coherent way

10.3390/land11060780

Recently burnt areas typically reveal strong to extreme hydrological responses, as a consequence of loss of protective soil cover and heating-induced changes in topsoil properties. Soil water repellency (SWR) has frequently been referred to as one of the explanatory variables for fire-enhanced surface runoff generation but this has been poorly demonstrated, especially at the catchment scale. This study employs a process-based modelling approach to better understand the relevance of SWR in the hydrological response of a small, entirely burnt catchment in central Portugal, in particular by comparing hydrological events under contrasting initial conditions of dry vs wet soils. The OpenLISEM model was applied to a selection of 16 major rainfall runoff events that occurred during the first 2 post-fire years. The automatic calibration procedure resulted in good model performance, but it worsened for validation events. Furthermore, uncertainty analysis revealed an elevated sensitivity of OpenLISEM to event-specific conditions, especially for predicting the events’ total and peak flows. Also, predicted spatial patterns in runoff poorly agreed with the runoff observed in microplots. Model performance improved when events were separated by dry and wet initial moisture conditions, particularly for wet conditions, suggesting the role of variables other than initial soil moisture.

10.1071/WF21005

The importance of soils to society has gained increasing recognition over the past decade, with the potential to contribute to most of the United Nations’ Sustainable Development Goals (SDGs). With unprecedented and growing demands for food, water and energy, there is an urgent need for a global effort to address the challenges of climate change and land degradation, whilst protecting soil as a natural resource. In this paper, we identify the contribution of soil science over the past decade to addressing gaps in our knowledge regarding major environmental challenges: climate change, food security, water security, urban development, and ecosystem functioning and biodiversity. Continuing to address knowledge gaps in soil science is essential for the achievement of the SDGs. However, with limited time and budget, it is also pertinent to identify effective methods of working that ensure the research carried out leads to real-world impact. Here, we suggest three strategies for the next decade of soil science, comprising a greater implementation of research into policy, interdisciplinary partnerships to evaluate function trade-offs and synergies between soils and other environmental domains, and integrating monitoring and modelling methods to ensure soil-based policies can withstand the uncertainties of the future.

10.1111/ejss.13145

The forecasting of crop yield is one of the most critical research areas in crop science, which allows for the development of decision support systems, optimization of nitrogen fertilization, and food safety. Many tested modeling approaches can be differentiated according to the models and data used. The models used are traditional crop models that require data that are often difficult to measure. New modeling approaches based on artificial intelligence algorithms have proven to be of high performance, flexible, and can be tested based on available data. In this study, four independent field experiments conducted on Triticum turgidum subsp. durum Desf. in central–southern Italy were used to train a set of machine learning (ML) algorithms to predict the yield using 16 variables: fertilization, nitrogen management, pedoclimatic, and remote sensing data. Four ML algorithms were calibrated and validated over two independent sites, and a linear regression model was used as a control. The calibrated models can predict the grain yield in the two regions by using ancillary data, topsoil physical and chemical properties, multispectral drone imagery, climatic data, and nitrogen fertilizer applied at the site. Among the four ML algorithms, stochastic gradient boosting (root-mean-square error  = 0.58 t ha−1) outperformed others during calibration and transferability. Nitrogen application rate, seasonal precipitation, and temperature are the most important features for predicting wheat yield.

10.1002/agj2.21279

Back in the 1930s, the aphorism “publish or perish” first appeared in an academic context. Today, this phrase is becoming a harsh reality in several academic environments, and scientists are giving increasing attention to publishing and disseminating their scientific work. Soil erosion modelers make no exception. With the introduction of the bibliometric field, the evaluation of the impact of a piece of scientific work becomes more articulated. The post-publication impact of the research became an important aspect too. In this study, we analyse the outreach and the impact of the literature on soil erosion modelling using the altmetric database, i.e., Altmetric. In our analysis, we use only a small fraction (around 15%) of Global Applications of Soil Erosion Modelling Tracker (GASEMT) papers because only 257 papers out of 1697 had an Altmetric Score (AS) larger than 0. We observed that media and policy documents mentioned more frequently literature dealing with global-scale assessments and future projection studies than local-scale ones. Papers that are frequently cited by researchers do not necessarily also yield high media and policy outreach. The GASEMT papers that had an AS larger than 0 were, on average, mentioned by one policy document and five Twitter users and had 100 Mendeley readers. Only around 5% and 9% of papers with AS > 0 appeared in news articles and blogs, respectively. However, this percentage was around 45% for Twitter and policy mentions. The top GASEMT paper’s upper bound was around 1 million Twitter followers, while this number was around 10,000 for the 10th ranked GASEMT paper. The exponentially increasing trend for erosion modelling papers having an AS has been confirmed, as during the last 3 years (2014–2017), we estimated that the number of entries had doubled compared to 2011–2014 and quadrupled if we compare it with 2008–2011.

DOI: 10.3390/su14031342

Conservation agriculture (CA) is an agronomic system based on minimum soil disturbance (no-tillage, NT), permanent soil cover, and species diversification. The effects of NT on soil organic carbon (SOC) changes have been widely studied, showing somewhat inconsistent conclusions, especially in relation to the Mediterranean and humid subtropical climates. These areas are highly vulnerable and predicted climate change is expected to accentuate desertification and, for these reasons, there is a need for clear agricultural guidelines to preserve or increment SOC. We quantitively summarized the results of 47 studies all around the world in these climates investigating the sources of variation in SOC responses to CA, such as soil characteristics, agricultural management, climate, and geography. Within the climatic area considered, the overall effect of CA on SOC accumulation in the plough layer (0–0.3 m) was 12% greater in comparison to conventional agriculture. On average, this result corresponds to a carbon increase of 0.48 Mg C ha−1 year−1. However, the effect was variable depending on the SOC content under conventional agriculture: it was 20% in soils which had ≤ 40 Mg C ha−1, while it was only 7% in soils that had > 40 Mg C ha−1. We proved that 10 years of CA impact the most on soil with SOC ≤ 40 Mg C ha−1. For soils with less than 40 Mg C ha−1, increasing the proportion of crops with bigger residue biomasses in a CA rotation was a solution to increase SOC. The effect of CA on SOC depended on clay content only in soils with more than 40 Mg C ha−1 and become null with a SOC/clay index of 3.2. Annual rainfall (that ranged between 331–1850 mm y−1) and geography had specific effects on SOC depending on its content under conventional agriculture. In conclusion, SOC increments due to CA application can be achieved especially in agricultural soils with less than 40 Mg C ha−1 and located in the middle latitudes or in the dry conditions of Mediterranean and humid subtropical climates.

DOI: 10.1111/ejss.13338

We present the developments on soil erosion modelling at European scale to respond to the policy needs. The Joint Research Centre (JRC) of the European Commission has developed the European Soil Erosion Modelling Platform (EUSEMP) to support the agro-environmental policies in the European Union (EU). The major component of EUSEMP is an hybrid soil erosion model named RUSLE2015 (RUSLE-based) to estimate soil loss by water erosion. The model runs with updated input layers (years: 2000, 2010 and 2016) and provides baselines for evaluating the current status of agricultural soils in the EU, evaluating the impact of agri-environmental policies on land management and making projections of soil loss by water erosion in 2050. In addition, EUSEMP includes also the Revised Wind Erosion Equation (RWEQ) to access wind erosion in EU arable lands and another component to access soil loss due to harvesting crops. Another component of EUSEMP is the sediment delivery model WaTEM/SEDEM to estimate net soil loss. Finally, the erosion models are coupled with the biogeochemical CENTURY model to estimate soil organic carbon losses by water erosion. EUSEMP targets to integrate the sediments transfer datasets with soil pollution data (e.g. mercury, copper) and nutrient losses (e.g. phoshorus).

DOI: 10.1007/978-981-16-7916-2_21

10.1016/j.catena.2021.105957

Despite recent developments in modeling global soil erosion by water, to date, no substantial progress has been made towards more dynamic inter- and intra-annual assessments. In this regard, the main challenge is still represented by the limited availability of high temporal resolution rainfall data needed to estimate rainfall erosivity. As the availability of high temporal resolution rainfall data will most likely not increase in future decades since the monitoring networks have been declining since the 1980s, the suitability of alternative approaches to estimate global rainfall erosivity using satellite-based rainfall data was explored in this study. For this purpose, we used the high spatial and temporal resolution global precipitation estimates obtained with the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) Climate Prediction Center MORPHing (CMORPH) technique. Such high spatial and temporal (30 min) resolution data have not yet been used for the estimation of rainfall erosivity on a global scale. Alternatively, the erosivity density (ED) concept was also used to estimate global rainfall erosivity. The obtained global estimates of rainfall erosivity were validated against the pluviograph data included in the Global Rainfall Erosivity Database (GloREDa). Overall, results indicated that the CMORPH estimates have a marked tendency to underestimate rainfall erosivity when compared to the GloREDa estimates. The most substantial underestimations were observed in areas with the highest rainfall erosivity values. At the continental level, the best agreement between annual CMORPH and interpolated GloREDa rainfall erosivity maps was observed in Europe, while the worst agreement was detected in Africa and South America. Further analyses conducted at the monthly scale for Europe revealed seasonal misalignments, with the occurrence of underestimation of the CMORPH estimates in the summer period and overestimation in the winter period compared to GloREDa. The best agreement between the two approaches to estimate rainfall erosivity was found for fall, especially in central and eastern Europe. Conducted analysis suggested that satellite-based approaches for estimation of rainfall erosivity appear to be more suitable for low-erosivity regions, while in high-erosivity regions (> 1000–2000 MJ mm ha−1 h−1 yr−1) and seasons (> 150–250 MJ mm ha−1 h−1 month−1), the agreement with estimates obtained from pluviographs (GloREDa) is lower. Concerning the ED estimates, this second approach to estimate rainfall erosivity yielded better agreement with GloREDa estimates compared to CMORPH, which could be regarded as an expected result since this approach indirectly uses the GloREDa data. The application of a simple-linear function correction of the CMORPH data was applied to provide a better fit to GloREDa and correct systematic underestimation. This correction improved the performance of CMORPH, but in areas with the highest rainfall erosivity rates, the underestimation was still observed. A preliminary trend analysis of the CMORPH rainfall erosivity estimates was also performed for the 1998–2019 period to investigate possible changes in the rainfall erosivity at a global scale, which has not yet been conducted using high-frequency data such as CMORPH. According to this trend analysis, an increasing and statistically significant trend was more frequently observed than a decreasing trend.

10.5194/hess-26-1907-2022

Healthy soil is the foundation underpinning global agriculture and food security. Soil erosion is currently the most serious threat to soil health, leading to yield decline, ecosystem degradation and economic impacts. Here, we provide high-resolution (ca. 100 × 100 m) global estimates of soil displacement by water erosion obtained using the Revised-Universal-Soil-Loss-Equation-based Global Soil Erosion Modelling (GloSEM) platform under present (2019) and future (2070) climate scenarios (i.e. Shared Socioeconomic Pathway [SSP]1–Representative Concentration Pathway [RCP]2.6, SSP2–RCP4.5 and SSP5–RCP8.5). GloSEM is the first global modelling platform to take into account regional farming systems, the mitigation effects of conservation agriculture (CA), and climate change projections. We provide a set of data, maps and descriptive statistics to support researchers and decision-makers in exploring the extent and geography of soil erosion, identifying probable hotspots, and exploring (with stakeholders) appropriate actions for mitigating impacts. In this regard, we have also provided an Excel spreadsheet that can provide useful insights into the potential mitigating effects of present and future alternative CA scenarios at the country level.

10.1038/s41597-022-01489-x

The cover management factor (C-factor) calculation requires the assessment of the intra‐annual spatiotemporal variability of biomass cover, owed to the natural growth cycle of vegetation and the impact of agriculture on land cover. However, this is frequently omitted, and the vegetation conditions are approximated by assigning constant values to static classified Land Use/Land Cover (LULC) maps, such as the Coordination of Information on the Environment (CORINE) Land Cover (CLC). Using as test site the Sperchios River catchment, Central Greece, this study introduces a new approach to estimate C-factor in a spatiotemporally exhaustive manner. The goal is to increase estimation accuracy in erosion modelling applications. The C-factor computations are performed on monthly scale, based on LULC maps that portray the basin’s agricultural areas in unprecedented detail. The methodology involves the use of a biophysical index, namely Fraction of Vegetation Cover (Fcover) and empirical literature data on crop types. Fcover was developed from Sentinel-2 (S2) imagery in 10-m analysis. Such analysis (compared to the 300-m one provided by the EU) is a major improvement towards a more precise estimation of C-factor. The study identified the monthly C-factor fluctuation at basin scale, and the most susceptible months seasons at localities in terms of land cover/soil loss potential. The higher C-factor values were acquired in October and the lower in May. Mean annual (numerical) C-factor complies with the value of July. All monthly values are significantly higher – almost double – than the mean annual stationary one. The revealed patterns would not have been detected in a lower temporal (e.g., annual) resolution without the incorporation of vegetation density seasonality. The study shows high reproducibility and upscaling potential, as the utilized datasets are available in all European Union (EU) Member States, having similar structure, thus they can be harmonized towards a unified continental approach.

10.1016/j.catena.2022.106149

Advances in climate change research contribute to improved forecasts of hydrological extremes with potentially severe impacts on human societies and natural landscapes. Rainfall erosivity density (RED), i.e. rainfall erosivity (MJ mm hm-2 h-1 yr-1) per rainfall unit (mm), is a measure of rainstorm aggressiveness and a proxy indicator of damaging hydrological events. Here, using downscaled RED data from 3,625 raingauges worldwide and log-normal ordinary kriging with probability mapping, we identify damaging hydrological hazard-prone areas that exceed warning and alert thresholds (1.5 and 3.0 MJ hm-2 h-1, respectively). Applying exceedance probabilities in a geographical information system shows that, under current climate conditions, hazard-prone areas exceeding a 50% probability cover ~31% and ~19% of the world’s land at warning and alert states, respectively. RED is identified as a key driver behind the spatial growth of environmental disruption worldwide (with tropical Latin America, South Africa, India and the Indian Archipelago most affected).

10.1371/journal.pone.0272161
 

The European Green Deal puts a healthy environment at the core of policy-making initiatives in the European Union (EU). Soil, due to its nature, is a central actor to be considered when developing and implementing actions in many areas, from biodiversity and agriculture to climate and pollution. New means for monitoring the impact of decisions taken in these sectors are needed. The Land Use and Coverage Area frame Survey (LUCAS modules of Soil Biodiversity and Pesticides provide both policy-makers and the research community with tools in this direction. The first component corresponds to the largest analysis of soil biodiversity across the EU through molecular biology techniques. The second component is the most extensive harmonised pan-European assessment of pesticide residues in agricultural soils. Specific features, together with policy and research potential of these instruments for achieving Green Deals targets under the Biodiversity 2030 Strategy, the Farm to Fork Strategy and the Zero Pollution Action Plan, are presented. All generated data are made available to the public through the EU Soil Observatory and European Soil Data Centre.

10.1111/ejss.13299

Since soil biodiversity sustains above-ground life, the European Union (EU) has recently announced its new Soil Strategy to better protect soil ecosystems as part of the Biodiversity Strategy for 2030. Also, the EU's Farm to Fork Strategy and the Zero Pollution Action Plan aim for soil protection. However, the status of soil biodiversity protection has not been comprehensively assessed. Therefore, we explored regulatory, incentive-based and knowledge-based instruments and strategic policy documents at the EU and national levels to determine whether they adequately protect soil biodiversity. Our review of 507 literature references concluded that only eight EU member states explicitly address threats to soil biodiversity in 14 regulatory instruments while 13 countries mainly focus on implicit threats to soil biodiversity, whereas six countries do not consider soil biodiversity. At the EU level, current directives and regulations only tackle individual threats to soil biodiversity. An EU-wide, legally binding protection could ensure a standardised minimum level of soil biodiversity protection while preventing surging costs of not acting. The EU Soil Health Law foreseen for 2023 could couple land management practices beneficial for soil biodiversity with incentive-based instruments. Simultaneously, models should be designed to predict soil biodiversity, considering soil biodiversity's spatial and temporal heterogeneity.

10.1016/j.biocon.2022.109475

Phosphorus (P) is an important nutrient for all plant growth and it has become a critical and often imbalanced element in modern agriculture. A proper crop fertilization is crucial for production, farmer profits, and also for ensuring sustainable agriculture. The European Commission has published the Farm to Fork (F2F) Strategy in May 2020, in which the reduction of the use of fertilizers by at least 20% is among one of the main objectives. Therefore, it is important to look for the optimal use of P in order to reduce its pollution effects but also ensure future agricultural production and food security. It is essential to estimate the P budget with the best available data at the highest possible spatial resolution. In this study, we focused on estimating the P removal from soils by crop harvest and removal of crop residues. Specifically, we attempted to estimate the P removal by taking into account the production area and productivity rates of 37 crops for 220 regions in the European Union (EU) and the UK. To estimate the P removal by crops, we included the P concentrations in plant tissues (%), the crop humidity rates, the crop residues production, and the removal rates of the crop residues. The total P removal was about 2.55 million tonnes (Mt) (± 0.23 Mt), with crop harvesting having the larger contribution (ca. 94%) compared to the crop residues removal. A Monte-Carlo analysis estimated a ± 9% uncertainty. In addition, we performed a projection of P removal from agricultural fields in 2030. By providing this picture, we aim to improve the current P balances in the EU and explore the feasibility of F2F objectives.

10.1007/s00003-022-01363-3

To assess carbon sequestration in the agricultural and natural systems, it is usually required to report soil organic carbon (SOC) as mass per unit area (Mg ha-1) for a single soil layer (e.g., the 0-0.3 m ploughing layer). However, if the SOC data are reported as relative concentration (g kg-1 or %), it is required to compute the SOC stock and its standard deviation (SD) for a given layer as the product of SOC concentration and bulk density (BD). For a proper computation, it is required to consider that these two variables are correlated. Moreover, if the data are already reported as SOC stock for multiple sub-layers (e.g., 0-0.15 m, 0.15-0.3 m) it is necessary to compute the SOC stock and its SD for a single soil layer (e.g., 0-0.3 m). The correlation between stocks values from adjacent and non-adjacent soil sub-layers must be accounted to compute the SD of the single soil layer.

The present work illustrates the methodology to compute SOC stock and its SD for a single soil layer based on SOC concentration and BD also from multiple sub-layers. An Excel workbook automatically computes the means of stocks and SD saving the results in a ready-to-use database.
•Computation of a carbon (SOC) stock and its standard deviation (SD) from the product between SOC concentration and bulk density (BD), being correlated variables.
•Computation of a SOC stock and its SD from the sum of SOC stocks of multiple correlated sub-layers.
•An Excel workbook automatically computes the means of SOC stocks and SD and saves the results in a ready-to-use database.

10.1016/j.mex.2022.101662

The agricultural uses of the Coordination of Information on the Environment Land Cover (CLC) dataset suffer from limitations such as temporal stationarity, low spatial resolution, broad and rather simplified grouping of classes. The study attempts to address these shortcomings, using as test site the Sperchios River catchment, Central Greece. The Greek ‘branch’ of the Land Parcel Identification System, Beneficiaries’ Declarations (BD) and CLC inventories were utilized to develop hybrid layers, deriving from their harmonization, sequential incorporation and progressive update (BD → BD-ilot → BD-ilot-CLC). The final layer constitutes the new object-oriented Land Use/Land Cover map. Remote sensing data (Sentinel-2) was used to validate the accuracy of the BD, subject to the most frequent errors. The new map retains the key advantages of CLC yet is now characterized by highly detailed spatial resolution and the explicit description of the different cultivated farmlands included.

10.1080/10106049.2022.2041107

The scope of this document is to provide a synthesis of the achievements of the EU Soil Observatory (EUSO) during its first year of existence. The EUSO aims to become the principal provider of reference data and knowledge at EU-level for all matters relating to soil. The EUSO will be a dynamic and inclusive platform that supports EU soil-related policymaking by providing its stakeholder base with the knowledge and data flows needed to safeguard and restore soils.
Since its launch on December 4th 2020, most efforts have focused on defining and developing concepts associated with the main tasks of the Observatory (monitoring, dashboard, support to R&I, citizen engagement). Efforts have also been made to consolidate and enhance the capacity and functionality of the European Soil Data Centre (ESDAC), which is at the heart of the Observatory.
Major developments for 2021 included the establishment of an interservice Steering Committee (chaired by the Director of JRC Sustainable Resources Directorate), the support to the EU Mission “A Soil Deal for Europe", the development of the knowledge base on soil through research at the JRC, and the organisation of the 1st EUSO Stakeholder Forum.
The EUSO Stakeholder Forum was attended by over 1 000 participants over a three-day period in October 2021. In this sense, it succeeded in bringing a EUSO community together and in establishing a two-way dialogue with its user base. A summary of the event is presented in this report. EUSO activities will intensify in 2022.

Soils provide crucial ecosystem services such as the provision of food, carbon sequestration and water purification. Soil is the largest terrestrial pool of carbon, hosts more than 25% of all biodiversity and provides 95–99% of food to 8 billion people. The European Union (EU) puts the concept of healthy soils at the core of the European Green Deal to achieve climate neutrality, zero pollution, sustainable food provision and a resilient environment.

Given the European Union's objective to become the first climate neutral continent by 2050, the European Commission adopted a series of communications for a greener Europe. In 2020, an ambitious package of measures were presented within the Biodiversity 2030, Farm to Fork and Chemicals Strategies, as well as the Circular Economy Action Plan and the European Climate Law, which included actions to protect soils (Montanarella and Panagos, 2021). In 2021, these were followed by the Fit for 55 package, the Zero Pollution Action Plan and the EU Soil Strategy for 2030. All these policies include provisions relevant to soils to achieve the ambitious objectives of the EU Green Deal.

10.1016/j.geodrs.2022.e00510

Provides an overview of the entire nitrate cycle and the processes influencing nitrate transformation, and clearly identifies its role as an essential nutrient in plant growth, food preservation, and human health. It explains the discrepancies between public perceptions on nitrate harm versus the beneficial effects on human health.

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Soil security has emerged during the recent years as a new paradigm for addressing sustainable soil management. Soil security was first presented in the literature in 2013–2014 (Koch et al., 2013; McBratney et al., 2014). Both publications defined soil security as the maintenance and improvement of the world's soil resources so that they can continue to provide food and fresh water, make major contributions to energy and climate sustainability, and help maintaining biodiversity and the overall protection of ecosystem goods and services. After the first publications on soil security, some regional studies addressed the subject in Australia (Bennett et al., 2019) and Tasmania (Kidd et al., 2018). Meanwhile, soil security starts to gain the momentum as it is linked to crop production and global climate (Beerling et al., 2018), soil contamination and human health (Carre et al., 2017; Brevik et al., 2017), farming and ecosystem services (Dazzi et al., 2019) and with the Sustainable Development Goals (Bouma, 2020).

Therefore, soil security is developed as a concept in analogy with the other six existential global environmental challenges (e.g. provision of food, fresh water, energy, climate sustainability, maintenance of biodiversity, protection of ecosystem goods and services). Soil security is described by five dimensions known as 5Cs: soil Capability, Condition, Capital, Connectivity & Codification (Koch et al., 2013; McBratney et al., 2014). Here, we discuss the implications of soil security for the European Union's sustainability.

Link: 10.1016/j.soisec.2021.100009

Soil loss by water erosion is a major land degradation processes that can locally reduce crop productivity and cause off-site negative effects such as siltation, eutrophication of waterways, flooding and terrestrial and aquatic biodiversity loss. The major driver of water erosion is the erosive power of rainfall. Using the detailed erosive events of the Rainfall Erosivity Database at European Scale (REDES), we study the characteristics and patterns of rainfall erosivity in Europe introducing the Rainfall Erosivity Synchrony Scale (Rsync). Rsync expresses the maximum radius in kilometers around a given meteorological station within which at least half of the other meteorological stations in the database also detect an erosive event. In this study we correlate the Rsync and the annual erosivity with annual number of thunderstorm days, convective and large-scale precipitation and multiple geo-morphological features such as topographic position index and terrain ruggedness index. Our analysis shows an inverse relationship between the Rsync and rainfall erosivity values in Europe. Different spatial patterns of synchrony scale are detected in Europe, which enables us to delineate areas where severe soil erosion can simultaneously occur at larger scales, e.g., large sectors of Italy, Spain, Croatia and Slovenia. Furthermore, we observe a tendency of the Rsync to decrease with convective precipitation, annual number of thunderstorm days and increase with the large-scale precipitation. On the contrary, annual rainfall erosivity increases with convective precipitation and annual number of thunderstorm days and decreases with large-scale precipitation.

10.1016/j.catena.2020.105060

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.

10.1021/acs.est.0c02093

There is increasing recognition that soils fulfil many functions for society. Each soil can deliver a range of functions, but some soils are more effective at some functions than others due to their intrinsic properties. In this study we mapped four different soil functions on agricultural lands across the European Union. For each soil function, indicators were developed to evaluate their performance. To calculate the indicators and assess the interdependencies between the soil functions, data from continental long-term simulation with the DayCent model were used to build crop-specific Bayesian networks. These Bayesian Networks were then used to calculate the soil functions' performance and trade-offs between the soil functions under current conditions. For each soil function the maximum potential was estimated across the European Union and changes in trade-offs were assessed. By deriving current and potential soil function delivery from Bayesian networks a better understanding is gained of how different soil functions and their interdependencies can differ depending on soil, climate and management.

10.1111/ejss.13039

Changes in future soil erosion rates are driven by climatic conditions, land use patterns, socio-economic development, farmers’ choices, and importantly modified by agro-environmental policies. This study simulates the impact of expected climatic and land use change projections on future rates of soil erosion by water (sheet and rill processes) in 2050 within the agricultural areas of the European Union and the UK, compared to a current representative baseline (2016). We used the Revised Universal Soil Loss Equation (RUSLE) adjusted at continental scale with projections of future rainfall erosivity and land use change. Future rainfall erosivity is predicted using an average composite of 19 Global Climate Models (GCMs) from the Coupled Model Inter-comparison Projects (CMIP5) WorldClim dataset across three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Concerning future land use change and crop dynamics, we used the projections provided by the Common Agricultural Policy Regional Impact Analysis (CAPRI) model.

Depending on the RCP scenario, we estimate a +13 %-22.5 % increase in the mean soil erosion rate in the EU and UK, rising from an estimated 3.07 t ha−1 yr−1 (2016) to between 3.46 t ha−1 yr−1 (RCP2.6 scenario) and 3.76 t ha−1 yr−1 (RCP8.5 scenario). Here, we disentangle the impact of land use change and climate change in relation to future soil losses. Projected land use change in the EU and UK indicates an overall increase of pasture coverage in place of croplands. This land use change is estimated to reduce soil erosion rates (-3%). In contrast, the increases in future rainfall erosivity (+15.7 %–25.5 %) will force important increases of soil erosion requiring further targeted intervention measures. Given that agro-environmental policies will be the most effective mechanisms to offset this future increase in soil erosion rates, this study proposes soil conservation instruments foreseen in the EU Common Agricultural Policy (CAP) to run policy scenarios. A targeted application of cover crops in soil erosion hotspots combined with limited soil disturbance measures can partially or completely mitigate the effect of climate change on soil losses. Effective mitigation of future soil losses requires policy measures for soil conservation on at least 50 % of agricultural land with erosion rates above 5 t ha−1 yr−1.


10.1016/j.envsci.2021.07.012

Heavy rainstorms play a central role in the water-driving soil erosion processes. An in-depth knowledge about temporal and spatial erosivity of rainfall events is required to gain a better understanding of soil erosion processes and optimize soil protection measures efficiency. In this study, the spatiotemporal distribution of more than 300,000 erosive events measured at 1181 locations, part of the Rainfall Erosivity Database at European Scale (REDES) database, is studied to shed some new light on the rainfall erosivity in Europe. Rainfall erosive events are statistically investigated through the Lorenz curve and derived coefficients such as the Gini coefficient (G). Additionally, seasonal characteristics of the most and the less erosive events are compared to investigate seasonal characteristics of rainstorms across Europe. The G shows largest values of inequality of the inter-annual temporal distribution of the rainfall erosive events in the Alpine region, mostly due to the large number of rainfall events with smaller rainfall erosivity. While for other parts of Europe, the inequality described by the G is mostly due to a small number of high erosive events. The G slightly decreases from south to north while no clear regional patterns can be detected. Additionally, in Europe, on average 11% (ranging from 1 to 24%) of all erosive events contribute to form 50% of the total rainfall erosivity. Furthermore, higher erosive rainfall events tend to occur later in the year compared to less erosive events that take place earlier. To our knowledge, this study is the first one addressing event scale rainfall erosivity distribution using more than 300,000 rainfall erosivity events and covering almost a whole continent. Scientifically our findings represent a major step towards large-scale process-based erosion modelling while, practically, they provide new elements that can support national and local soil erosion monitoring programs.

10.1016/j.catena.2021.105577