European Journal of Soil Science最新文献

Soil organic carbon (SOC) content plays an important role in modulating atmospheric CO₂. Visible and near-infrared spectroscopy (VISNIRS) has been proven to be a suitable method for SOC prediction in the laboratory. However, several soil properties such as soil moisture (SM), bulk density, compactness, texture, and temperature affect the near-infrared spectra obtained under field conditions. Among these factors, SM variation is the most significant challenge for SOC measurement. Soil is a composition of fractions, especially minerals and organic matter, whose contents are expressed in relative and interdependent quantities, belonging to simplex spaces. These are known as compositional data (CoDa) and require specific mathematical methods. This study proposes methods to predict SOC along with other soil components, rather than using solely one soil feature. Several predictive models using VISNIRS by considering different soil compositions were evaluated. All models included SM to mitigate its interference in SOC prediction, which would otherwise occur when using only VISNIRS-based methods. The analyzed soil components included soil organic matter (SOM, calculated as SOM = 1.724 × SOC), SM, soil inorganic carbon (SIC), and the textural fractions: “Clay,” “Silt,” and the remainder of the soil sample classified as “Other.” The 4-parts model including the clay content provided SOM prediction with Lin's concordance correlation coefficient = 0.84 and Pearson r = 0.87. Important is to note that the predictions stated with the different CoDa approaches showed similar trends, from the 6-Parts to the 2-Parts compositions, this fact highlighting the consistency of the method. The performance of all the CoDa models obtained, and in particular the 4-part “Clay” model, was superior to that obtained with the traditional PLS calibration. The results highlighted that CoDa methods for estimating SOM or SOC provided an improvement over traditional partial least square (PLS) calibration. Future software solutions could integrate routines for using these methods in the field.

Transitioning towards soil health-oriented farming systems is fundamental to mitigate future challenges such as climate change, soil degradation, and increasing global food demands. In this study, we evaluated soil health, crop yields, and greenhouse gas (GHG) emissions at a long-term experimental site in Central Europe that comprised two cropping systems: a conventional system with regular tillage, low-diversity crop rotation, and minimal cover cropping, and a conservation system with shallow tillage, diverse crop rotation, and extensive cover cropping. We assessed soil health using 13 physico-chemical and biological parameters, calculated field-scale GHG emissions, and analysed yield dynamics over an eight-year period to evaluate potential crop yield penalties under conservation farming. We observed significant soil health advances (+7%) and reductions in GHG emissions (−43%) with conservation farming, while crop yields for all cultivated crops remained stable. Improvements in soil health were particularly pronounced for nitrogen cycling and microbial-driven processes. For several measured soil health parameters, we found a larger effect of crop species compared to farming system. Further, positive management effects on soil were apparent particularly for winter wheat and to a lesser extent for maize and sugar beet, strongly emphasizing the need for standardized soil health assessments that take crop species into account. Our study demonstrates that easily implementable conservation farming measures such as reduced tillage, increased crop diversity, and enhanced cover cropping can substantially improve soil health and long-term agricultural sustainability without compromising crop yields. Conservation farming thus emerges as a viable strategy to support resilient crop production in temperate regions.

Heller, O., A. Chervet, F. Durand-Maniclas, et al. 2025. “SoilManageR—An R Package for Deriving Soil Management Indicators to Harmonise Agricultural Practice Assessments.” European Journal of Soil Science 76: e70102. https://doi.org/10.1111/ejss.70102.

The error was limited to the manuscript and did not occur in the underlying calculations and the software package. Therefore, the correction of Equation (3) does not affect any of the presented data, results or interpretations.

We apologize for this error.

Soils are under multiple threats, with varying levels of intensity and nature across different areas. It is therefore important to assess the soil threat level. To do so, scientific indicators have been developed, but their implementation at the country level can be challenging. As stakeholders have good knowledge of soil conditions, stakeholders' perceptions on soil threats could be used as a complementary indicator. The objective of this paper is to explore this possibility focusing on the five soil threats considered by stakeholders as the most important at the European level: erosion, artificialisation, compaction, soil organic carbon (SOC) loss and contamination. A participatory stakeholder consultation conducted in France in 2021 yielded 1444 responses. We elaborated stakeholders' perception maps at the departmental scale, which we compared with scientific indicator maps per soil threat. Our findings indicate that stakeholders consider artificialisation the most important soil threat in France. The spatial distribution of soil threats based on stakeholders' perceptions and scientific indicators matches in 43% of the departments for SOC loss, and in over half of the departments for erosion (50%), compaction (51%), artificialisation (63%) and contamination (74%). The differences can be attributed to higher stakeholders' perception compared to scientific indicators for erosion, SOC loss and contamination. Conversely, for artificialisation and compaction, these differences can be attributed to lower stakeholders' perception than the scientific indicators. Moreover, certain scientific indicators assess the threat only partially, whereas stakeholders may perceive the threat differently or as a whole. When biases in the scientific assessment, stakeholders' perception or comparison are taken into consideration, stakeholders' perceptions can be used as a tool to complement existing scientific indicators.

Accurate determination of the soil particle size distribution (PSD) is critical for a wide range of environmental, agronomic, and geotechnical applications. Laser diffraction method (LDM) has gained popularity because of its speed and reproducibility; however, it remains sensitive to sample preparation and introduction methods. This study evaluated the impact of three manual dosing techniques on PSD results obtained via laser diffraction for seven USDA-classified soil types, with the pipette method used as a reference. Each technique (A: pipetted suspension; B: semiliquid paste; C: dried material) was applied to 1050 measurements. The results revealed a systematic underestimation of clay and overestimation of silt fractions across all LDM techniques, with Technique A yielding the highest relative standard deviation (average RSD for clay: 16.8%; sand: 26.9%). Techniques B and C showed markedly better repeatability (clay RSDs: 7.1% and 10.2%, respectively), with silt exhibiting the highest measurement precision overall (mean RSD: 6.7%). One-way analysis of variance (ANOVA) confirmed that the choice of dosing technique significantly affected the measured clay fraction (p < 0.001), whereas no statistically significant differences were found for silt or sand. All the laser-based techniques misclassified the soil texture in the USDA triangle, with most samples shifting to silt-dominated groups regardless of the true origin. These findings highlight that while LDM itself introduces systematic biases in PSD estimation, the choice of manual dosing technique—particularly uncontrolled suspension pipetting (Technique A)—further amplifies measurement variability, rendering it unsuitable for high-precision applications. These findings highlight the strong influence of manual dosing on LDM outcomes and confirm the unsuitability of uncontrolled suspension pipetting (Technique A) in precision analysis. Recommendations are provided for standardized manual procedures that can improve reproducibility and classification accuracy in soil laboratories.

The issues of both soil health and climate change can be characterised as a so called ‘wicked problem’. We adopt this shared characteristic as a rationale for applying lessons from climate change communications to suggest an appropriate ‘language of soil’ that should be deployed to effectively communicate the pertinent issue(s) of soil health. Using six recognised examples of climate change communication pitfalls, we illustrate why inciting a sense of dread around soil and why setting ‘soil health’ deadlines are not helpful strategies to promote positive action on soils. We also discuss the value-action gap and the way in which it applies to soil communication and why it is important to avoid the ‘trap’ of the knowledge deficit model. Finally, we stress the importance of communicating actions rather than knowledge as well as the importance of ‘credible’ soil health communicators.

Protected areas are often thought of as pristine natural environments. Practically however, protected areas are often degraded. In Africa, protected areas are mostly funded through game viewing tourism, where development of the road network to enable game viewing often leads to land degradation. Furthermore, off-road driving is common in such game parks, leading to soil compaction and crusting. Guidelines for sustainable road network development and off-road driving exist but are impossible to apply without a soil map of the game reserve. This paper shows how a digital soil map can be used to create spatial off-road driving guidelines for the Phinda Game Reserve in South Africa. Phinda has a very high road density and therefore an additional aim was to designate roads for closure and rehabilitation, without decreasing the opportunity to view predators. A soil class map with a Kappa value of 0.8 was created using the multinomial logistic regression algorithm and 133 soil observations. A soil sensitivity rating was assigned to each soil class based on the soil properties of the class. The off-driving guideline map showed that off-road driving should be prohibited on 6.7% of the area and can only be practised on 41% of the area when not bare or overgrazed. Using the soil sensitivity map and the locations of accommodation camps and predator sighting hotspots, roads were designated for closure and rehabilitation. In total, 207 km of 17% of roads were designated for closure. These roads were outside of predator hotspot areas and would therefore not negatively affect the touristic experience. This paper gives a blueprint to develop spatial off-road driving guidelines and sustainable road network design in game reserves using digital soil mapping and could be applied to similar game parks throughout Africa.