European Journal of Soil Science最新文献

Across Europe, increasingly more soil-related data is being collected. Soil organic carbon (SOC) is one of the most frequently collected parameters from soil monitoring networks due to the connections between SOC and many soil health indicators and ecosystem functions. Furthermore, SOC changes are also related to CO₂ emissions and sinks, thus influencing climate change. SOC-related data is therefore also fundamental for greenhouse gas emission reporting in the sector land use, land use change and forestry. Much of the SOC data at continent-, country-, and regional-level scale in Europe come from soil monitoring networks (SMNs) that are highly diverse and scattered. In this review, we gather results from European SMNs covering agricultural land with more than one completed sampling campaign in order to compare changes in SOC content and stock from SMNs across Europe. Sixteen countries and regions are represented in the review, representing 24% of the agricultural land (cropland and grassland) of the European Union, United Kingdom and Switzerland. The results and data included in this review were collected between 1955 and 2024. While both gains and losses in SOC are found from European croplands and grasslands, a loss of SOC was found for 56% of the agricultural area covered by the included studies. In cropland areas and general agricultural land, SOC loss and gain were found equally frequently, while SOC loss was found for the majority of the grassland areas surveyed. Given the prevalence of SOC loss, soil health appears under pressure, and improved and harmonized soil monitoring data are needed to quantify SOC changes and their consequences for soil health at the continental scale.

Estimating the soil particle size distribution (PSD) from visible–near infrared (vis–NIR) reflectance spectra is conventionally limited to predicting discrete soil fractions (e.g., sand, silt, and clay). This approach presents significant challenges: it requires the harmonization of data from different classification systems and, by reducing the PSD to a few values, fails to reflect the entire variation in soil texture. To address these gaps, we present a novel physics-informed neural network (PINN) for the direct estimation of the continuous PSD from vis–NIR reflectance measurements. The PINN learns a continuous, differentiable, and non-parametric representation of the cumulative PSD by integrating both measurements and physical constraints imposed during training. This approach eliminates the need for harmonization and interpolation of measurements originating from different soil texture classification systems and allows the model to be trained on datasets with varying numbers of measurements per sample. Performance evaluation on 30% of the 2777 studied samples showed that the PINN achieved an RMSE of 6.77% and an R² of 0.97 in predicting the cumulative PSD fraction. For the texture fractions, the model achieved RMSE values of 4.72%, 3.06%, and 2.75% for sand, silt, and clay, respectively. A comparison with a physics-agnostic (i.e., physics-uninformed) version of the model revealed that both approaches performed similarly in terms of RMSE and R². However, the physics-agnostic model violated physical constraints even in data-rich scenarios. In contrast, the PSD obtained from the PINN maintained its physical integrity even under data sparsity conditions and consistently produced non-negative, monotonically increasing predictions that sum to 100% at the largest particle size.

Exogenous organic materials (EOMs) are increasingly used as substitutes for mineral fertilizers and as tools to restore soil health within a circular bioeconomy context. However, the great diversity of EOMs in terms of origin, composition, chemical properties, and contaminant concentrations challenges their safe and efficient use in agriculture. The aim of the study was to establish a framework for the clustering of EOMs properties from several EU countries, enabling their categorisation according to their origin, characteristics, and chemical properties and trace elements (TE) profile. For that purpose, a dataset with chemical characteristics and TE concentrations from 118 EOMs was constructed from a database previously published. The EOMs included a wide range of organic residues and waste streams from agricultural, industrial, and urban origins representative of the diversity of European EOMs. Clustering analyses were carried out to distribute EOMs among clusters (i) of chemical properties based on their characteristics (dry mass, C-to-N ratio, pH, and concentrations of organic C, N, NNH₄, P, K, Ca, and Mg), and (ii) of TE profile based on their concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. Five practical scenarios of EOMs applications mixing amending and fertilizing EOMs were considered to estimate input fluxes of C, N, P, K, and TEs over a period of 10 years in contrasted areas (agricultural settings and peri-urban areas). The present study clustered the EOMs according to their soil improver characteristics that is, from NK fertilizing to liming and organic amending properties. The clustering analysis on TEs classified EOMs according to their TE profiles, with (i) smaller concentration of TEs (i.e., three quarters of EOMs), and (ii) larger concentration of all TEs and especially for Cu and Zn. The various practical scenarios simulating the repeated applications of local EOMs from contrasted areas showed that input fluxes were in line with commercial organic fertilizer inputs and below the goal of 170 kg N per hectare per year, while TE input fluxes respected the French regulation thresholds, even in the scenarios including EOMs containing also greater TE levels.

Fine-grained, sulphide-bearing marine clays are found along the Finnish coastline. When excavated and exposed to air, the sulphides within these soils react with oxygen to form sulfuric acid. Such soils are classified as hypersulphidic soils. The acid can then lower the soil's pH, causing harmful elements to be released into the environment through runoff water. Once the oxidation process has been initiated, these soils are classified as sulphuric soils, and together with hypersulphidic soils, they form subgroups of acid sulphate (AS) soils. Stabilising the soils (i.e., hypersulphidic soils) can prevent the leaching of metals and metalloids. Clay-rich AS (AS clay) and non-AS (non-AS clay) soil materials were collected from different areas in the city of Turku in Southwestern Finland. The aim was to find solutions for stabilising urban fine-grained sulphide-bearing clays to enable a safe beneficial use. Another objective was to study possible differences in strength development between AS clays and non-AS clays. Stabilisation formulations for the soils were systematically developed using cement, blast furnace slag, quicklime and ash. Different levels of binders mixed with the clays were pressed into cylindrical samples, and the unconfined compressive strength was measured after 7, 28 and 91 days. The leaching of elements was determined on the stabilised samples. The morphology of the stabilised samples was analysed using SEM/EDS. Industrial side streams were successfully utilised for the stabilisation of the clays. Up to 65% of cement could be replaced with blast furnace slag without decreasing the long-term strength values, suggesting a significant reduction in carbon footprint, calculated as CO₂ emissions. The compressive strength was significantly lower for the stabilised AS clay samples, implying more binders are needed to achieve the same strength as for the non-AS clays. It should be noted that water content and particle size also influenced the compressive strength. When the AS soil samples were incubated, harmful metals were leached out as expected. However, stabilising the soils prevented the decrease in pH, effectively immobilising harmful elements in AS soils and making them suitable as building ground material.

Although land-use change in post-socialist countries has been widely studied, most research has focused on the post-1990 transition period, emphasizing socio-economic and institutional drivers. In contrast, limited attention has been given to land-use dynamics during the Soviet period and their lasting impacts on landscape structure and soil properties. This gap is particularly relevant for understanding long-term ecological processes in areas affected by early agricultural abandonment. This study aims to analyse the political, environmental, and spatial drivers of land-use change from 1954 to 2021 in a marginal rural area and to assess how these changes have influenced soil properties under different land-use scenarios. Over the past 67 years, substantial land-use changes in marginal regions have been driven primarily by agricultural extensification, land abandonment, and subsequent natural afforestation, processes shaped by both natural factors and targeted land management policies. The development of forest is influenced by environmental and spatial factors, particularly land quality and proximity to forest edge. In our study, forested areas were characterized by lower soil pH and reduced levels of organic carbon, nitrogen, and exchangeable cations compared to grasslands, reflecting both inherent soil properties and the legacy of past land use. These findings underscore that forest encroachment predominantly occurs on less fertile soils, highlighting the need for land management and policy approaches that integrate historical context, soil properties, and the conflicting priorities of conservation and afforestation to ensure sustainable land use and biodiversity protection.

Plants and soil microbes are intricately linked, and agricultural production relies heavily on microbially mediated ecosystem services. However, the effects of plant diversity (richness, relative abundance and composition) on soil microbial community diversity and function are still unclear. To better inform agricultural grassland management, it is essential to understand these relationships in intensively managed systems. Between May and September 2019, we conducted a field experiment on an established, intensively managed agricultural grassland to investigate the effect of plant diversity on soil microbial abundance, community composition and nitrogen cycling functional capacity. We systematically manipulated sown plant diversity comprising six forage species at a lower level of chemical nitrogen application, and we included a high chemical N treatment on an L. perenne monoculture as a reference level for conventional productive grassland management. Using Diversity-Interactions (DI) modelling, we measured the effects of plant richness, relative abundance and composition on soil microbial community gene abundance and nitrogen cycling functional capacities, finding limited effects of plant identity and even weaker effects of interspecific interactions. Where differences in identity effects occurred, the plant species involved were not consistent across responses. In a separate multivariate community analysis, soil microbial community composition was found to be significantly affected by plant species composition, and this was more evident in fungal communities than in prokaryotic communities. There were no differences in microbial community composition between L. perenne monocultures receiving a high and lower nitrogen application; however, the high nitrogen L. perenne had a different microbial community structure than some other plant communities at lower nitrogen. Overall, our study found weak effects of plant diversity on several measures of microbial diversity and function in intensively managed agricultural grasslands.

Adsorption to minerals is a key mechanism in stabilizing organic carbon in soils. We used isothermal titration calorimetry (ITC) to quantify the thermodynamics of binding of citric acid, oxalic acid, and salicylic acid to four goethites with different specific surface areas (SSA, 14–120 m² g⁻¹). Thermodynamic parameters could be determined for sorption of citric and salicylic acids, while flocculation of particles prevented their quantification for sorption of oxalic acid. For citric acid adsorption, ∆H shifted from −23.5 ± 0.57 to −27.0 ± 0.47 kJ mol⁻¹ and ∆S from −8.8 ± 1.54 to −29.9 ± 0.13 J mol⁻¹ K⁻¹ with increasing SSA and broader (110) diffraction peaks of goethite, thus reducing ∆G from −20.7 ± 0.02 to −18.0 ± 0.03 kJ mol⁻¹. Salicylic acid adsorption was more exothermic (∆H −40.53 ± 1.93 kJ mol⁻¹) and accompanied by a larger loss of entropy (∆S −65.1 ± 1.91 J mol⁻¹ K⁻¹), possibly due to chelation of its ortho hydroxyl and carboxyl groups to single iron atoms on the mineral surface. These results demonstrate that ITC can decipher adsorption thermodynamics of organic ligands to mineral surfaces, but ligand-induced flocculation can render the interpretation of results difficult. Crystallite size and lattice defects of adsorbent minerals influence the thermodynamics of sorption by determining the conformation of organic molecules sorbed to goethite surfaces.