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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., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Factors regulating the diversity and composition of soil microbial communities include soil properties, land cover and climate. How these factors interact at large scale remains poorly investigated. Here, we used an extensive dataset including 715 locations from 24 European countries to investigate the interactive effects of climatic region, land cover and pH on soil bacteria and fungi. We found that differences in microbial diversity and community composition between land cover types depended on the climatic region. In Atlantic, Boreal and Continental regions, microbial richness was higher in croplands and grasslands than woodlands while richness in Mediterranean areas did not vary significantly among land cover types. These differences were further related to soil pH, as a driver of bacterial and fungal richness in most climatic regions, but the interaction of pH with land cover depended on the region. Microbial community composition differed the most between croplands and woodlands in all regions, mainly due to differences in pH. In the Mediterranean region, bacterial communities in woodlands and grasslands were the most similar, whereas in other regions, grassland and cropland-associated bacteria showed more similarity. Overall, we showed that key factors interact in shaping soil microbial communities in a climate-dependent way at large scale., (© 2024 The Authors. Environmental Microbiology published by Applied Microbiology International and John Wiley & Sons Ltd.)

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., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

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., (© 2023. the European Union.)

Despite phosphorus (P) being crucial for plant nutrition and thus food security, excessive P fertilization harms soil and aquatic ecosystems. Accordingly, the European Green Deal and derived strategies aim to reduce P losses and fertilizer consumption in agricultural soils. The objective of this study is to calculate a soil P budget, allowing the quantification of the P surpluses/deficits in the European Union (EU) and the UK, considering the major inputs (inorganic fertilizers, manure, atmospheric deposition, and chemical weathering) and outputs (crop production, plant residues removal, losses by erosion) for the period 2011-2019. The Land Use/Cover Area frame Survey (LUCAS) topsoil data include measured values for almost 22,000 samples for both available and total P. With advanced machine learning models, we developed maps for both attributes at 500 m resolution. We estimated the available P for crops at a mean value of 83 kg ha -1 with a clear distinction between North and South. The ratio of available P to the total P is about 1:17. The inorganic fertilizers and manure contribute almost equally as P inputs (mean 16 ± 2 kg P ha -1 yr -1 at 90 % confidence level) to agricultural soils, with high regional variations depending on farming practices, livestock density, and cropping systems. The P outputs came mainly from the exportation by the harvest of crop products and residues (97.5 %) and, secondly, by erosion. Using a sediment distribution model, we quantified the P fluxes to river basins and sea outlets. In the EU and UK, we estimated an average surplus of 0.8 kg P ha -1 yr -1 with high variability between countries with some regional variations. The P annual budget at regional scale showed ample possibility to improve P management by both reducing inputs in regions with high surplus (and P soil available) and rebalancing fertilization in those at risk of soil fertility depletion., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics. One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor, which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content, soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25 Member States of the European Union. The aim of this study is the generation of a harmonised high-resolution soil erodibility map (with a grid cell size of 500 m) for the 25 EU Member States. Soil erodibility was calculated for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated at 0.032 thahha(-1)MJ(-1)mm(-1) with a standard deviation of 0.009 thahha(-1)MJ(-1)mm(-1). The yielded soil erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation of the protective effect of surface stone cover, which is usually not considered for the soil erodibility calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where highest percentages of surface stone cover were observed., (Copyright © 2014. Published by Elsevier B.V.)

A reliable spatial assessment of the POPs contamination in soils is essential for burden studies and flux evaluations. Soil characteristics and properties vary enormously even within small spatial scale and over time; therefore soil capacity of accumulating POPs varies greatly. In order to include this very high spatial and temporal variability, models can be used for assessing soil accumulation capacity in a specific time and space and, from it, the spatial distribution and temporal trends of POPs concentrations. In this work, predictive contamination maps of the accumulation capacity of soils were developed at a space resolution of 1×1m with a time frame of one day, in a study area located in the central Alps. Physical algorithms for temperature and organic carbon estimation along the soil profile and across the year were fitted to estimate the horizontal, vertical and seasonal distribution of the contamination potential for PCBs in soil (Ksa maps). The resulting maps were cross-validated with an independent set of PCB contamination data, showing very good agreement (e.g. for CB-153, R(2)=0.80, p-value≤2.2·10(-06)). Slopes of the regression between predicted Ksa and experimental concentrations were used to map the soil contamination for the whole area, taking into account soil characteristics and temperature conditions. These maps offer the opportunity to evaluate burden (concentration maps) and fluxes (emission maps) with highly resolved temporal and spatial detail. In addition, in order to explain the observed low autumn PCB concentrations in soil related to the high Ksa values of this period, a dynamic model of seasonal variation of soil concentrations was developed basing on rate parameters fitted on measured concentrations. The model was able to describe, at least partially, the observed different behavior between the quite rapid discharge phase in summer and the slow recharge phase in autumn., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Under the European Union Thematic Strategy for Soil Protection, the European Commission Directorate-General for the Environment and the European Environmental Agency (EEA) identified a decline in soil organic carbon and soil losses by erosion as priorities for the collection of policy relevant soil data at European scale. Moreover, the estimation of soil organic carbon content is of crucial importance for soil protection and for climate change mitigation strategies. Soil organic carbon is one of the attributes of the recently developed LUCAS soil database. The request for data on soil organic carbon and other soil attributes arose from an on-going debate about efforts to establish harmonized datasets for all EU countries with data on soil threats in order to support modeling activities and display variations in these soil conditions across Europe. In 2009, the European Commission's Joint Research Centre conducted the LUCAS soil survey, sampling ca. 20,000 points across 23 EU member states. This article describes the results obtained from analyzing the soil organic carbon data in the LUCAS soil database. The collected data were compared with the modeled European topsoil organic carbon content data developed at the JRC. The best fitted comparison was performed at NUTS2 level and showed underestimation of modeled data in southern Europe and overestimation in the new central eastern member states. There is a good correlation in certain regions for countries such as the United Kingdom, Slovenia, Italy, Ireland, and France. Here we assess the feasibility of producing comparable estimates of the soil organic carbon content at NUTS2 regional level for the European Union (EU27) and draw a comparison with existing modeled data. In addition to the data analysis, we suggest how the modeled data can be improved in future updates with better calibration of the model., (Copyright © 2012 Elsevier B.V. All rights reserved.)