European Journal of Soil Science最新文献

Soil inorganic carbon (SIC) plays a critical role in the global carbon cycle, particularly in arid and semi-arid regions in which SIC reserves are substantial. However, the mechanisms governing SIC migration and transformation remain poorly understood. This study comprehensively reviews the influence of soil weathering, respiration, depth, precipitation, and acidity on SIC dynamics. We highlight the role of vegetation restoration in enhancing SIC storage and shifting the interactions of soil organic carbon (SOC) with SIC. The solubility changes of CO₂ and carbonates, mineral surface adsorption, and soil chemical reactions are regulated by various environmental factors, substantially affecting CO₂ flux. Yet the carbonate crystals left behind by evaporation during the downward migration of SIC in the soil solution can lead to soil stratification. Furthermore, vegetation restoration boosts carbon storage by adding organic matter through humus and potentially increasing SIC. Our findings reveal that SIC contributes significantly to carbon sequestration, with implications for mitigating climate change. This review provides a framework for better understanding SIC dynamics and its potential for enhancing soil carbon storage in arid ecosystems.

Accurately describing bi- or multi-modal soil hydraulic properties (SHPs) is essential for understanding soil water flow processes. Traditional bimodal models, based on capillary theory, often require numerous empirical parameters and fail to adequately represent macropore flow driven by gravity and film flow held by adsorption forces. In this study, we introduce a novel framework to describe bimodal SHPs by shifting from a reference unimodal model. We propose a new bimodal soil hydraulic model based on the widely used unimodal van Genuchten–Mualem (VGM) model and incorporate the additional effects of adsorption forces. The so-called VGM-Bi model introduces two additional parameters, which can be easily derived or constrained from the measured soil water retention curve (SWRC), enhancing its usability. We further propose a modified version, the VGM-Bi-Macro model, to account for macropore effects by using a hydraulic conductivity value at a slightly negative matric potential as a new matching point. Evaluation with 25 soil samples shows that the VGM-Bi model accurately captures bimodal SWRCs but struggles with bimodal hydraulic conductivity curves (HCCs) for a few samples. In contrast, the VGM-Bi-Macro model effectively captures both. Specifically, the VGM-Bi-Macro model achieves a slightly lower mean root-mean-square error (RMSE) of 0.200 in estimating HCCs and nearly half the RMSE (0.008 cm³ cm⁻³) in estimating SWRCs compared to the VGM-Bi model (0.229 and 0.014 cm³ cm⁻³) and an existing bimodal model (0.262 and 0.015 cm³ cm⁻³), underscoring the importance of gravity-driven macropore flow. These models offer a physically meaningful and efficient tool for simulating water flow in structured soils.

Despite being key indicators of soil fertility and quality, microbial enzyme activities are rarely assessed spatially due to the high number of samples required and labour-intensive assays. This study aimed to evaluate the potential of on-the-go visible–near infrared (vis–NIR) spectroscopy to predict and map the spatial distribution of β-1,4-glucosidase (BG), acid phosphatase (ACP), alkaline phosphatase (ALP), and arylsulphatase (ARS) activities. An on-the-go (tractor-pulled sensor platform) vis–NIR spectroscopy sensor, coupled with partial least squares regression (PLSR), was used to estimate microbial enzyme activities in two fields, namely, Cayenne and Mortier, Belgium. Spatial maps were developed for both measured and predicted enzyme activities and analyzed using Local Moran's I and Bivariate Moran's I spatial statistics. Results showed strong correlations between total organic carbon (TOC), pH, and enzyme activities for samples from these two sites. A notable negative correlation existed between soil pH and TOC. PLSR model prediction accuracy varied by enzyme, with the highest for ARS (R² = 0.70, ratio of performance to interquartile distance [RPIQ] = 2.79), followed by BG (R² = 0.69, RPIQ = 2.93), ACP (R² = 0.64, RPIQ = 2.95), and ALP (R² = 0.60, RPIQ = 1.81). Spatial analysis demonstrated a strong agreement between measured and predicted enzyme activity maps, except for ARS in the Mortier field. Bivariate Moran's Iindicated positive spatial correlations between observed and predicted enzyme activities. In the Cayenne field, the highest Bivariate Moran's I was 0.64 for ACP, while in the Mortier field, the highest value was 0.58 for ALP. Overall, PLSR models performed better in the Cayenne field; hence, spatial predictions of enzyme activities were generally reliable, except for ARS in the Mortier field. These findings demonstrate that on-the-go line vis–NIR spectroscopy can provide reliable, high-resolution maps of soil microbial activities, offering a practical tool for guiding precision fertilizer recommendations.

To address complex challenges and help advance a systems theory for soils requires soil scientists to be able to engage with knowledges outside the discipline of soil science. However, there is a lack of examples and guidance available to support different ways of producing new knowledge. Drawing on our experience as a transdisciplinary team, we present a roadmap comprising five key steps for undertaking transdisciplinary, soil-centred research. The five steps are: addressing complex challenges, building relationships, weaving knowledges and building connectivity, developing holistic understandings and moving beyond knowledge translation. The central tenet of the roadmap is connectivity, with soil health at the core of the interrelationships of people, soil and food. To illustrate the application of this roadmap, we share learnings from two case studies that focused on understanding connections between people and soil, through food production in an Aotearoa New Zealand context. These case studies weave together mātauraka Māori (Māori Indigenous knowledge) and soil science, guided by social science framings, providing examples of how to undertake Transdisciplinary Research (TDR) and guidance for others looking to extend the boundaries of our field by connecting and applying new approaches to knowledge creation, and in so doing advance the development of a soil systems approach.

Long-term conventional cultivation leads to soil structural degradation, greatly limiting the sustainable development of agriculture. Conservation agriculture (CA) has been demonstrated to be a promising sustainable agriculture approach that improves soil structure by regulating the formation and turnover of soil aggregates, consequently mediating key soil processes and multifunctionality. Although research on the impacts of CA on soil aggregates is extensive, there is an urgent need to synthesize and systematize the current body of knowledge. Accordingly, we reviewed CA's impacts on soil aggregates to explore the development trends, major advancements, and future perspectives in this field. We clarified formation, turnover, and stability of soil aggregates under CA. Moreover, we revealed the intricate relationships among soil aggregates, organic carbon, and microorganisms under CA, and explored the current state of the hotspot of soil aggregates and multifunctionality. In addition, we proposed a CA framework and four critical considerations for future research directions, emphasizing the integration of cross-disciplinary approaches and the convergence of multiple technologies. These directions include: (1) strengthening of long-term monitoring of soil aggregate dynamics, (2) elucidating fundamental microbial mechanisms, (3) establishing an integrated evaluation platform, and (4) enhancing climate resilience within agricultural systems. These recommendations provide valuable insights into the complex interactions between CA and soil aggregate dynamics, thereby contributing significantly to the advancement of soil health and sustainable agriculture.

Ridge-furrow planting with plastic film (RP) is rarely used as an efficient precipitation harvesting tillage practice in humid and subhumid areas, and its effect on precipitation infiltration remains poorly understood. Given the growing demand for water-saving agriculture under climate change, exploring RP's potential to optimize precipitation use efficiency is critical for advancing sustainable cropping systems in these regions. Therefore, we investigated the infiltration processes of 10 typical precipitation events in wheat fields under flat planting (FP) and RP from 2022 to 2024 in the Guanzhong Plain, China. Hydrogen and oxygen stable isotope technology was used to quantify precipitation loss and contribution proportion (f) of precipitation to soil water in different soil layers. The f values were then applied to determine the infiltration depth (ID) and effective contribution time (ECT) of precipitation. Ridge regression analysis was employed to further reveal the sensitivity of ID, f, and precipitation loss to precipitation amount (Pr). This study suggests that compared to FP, RP reduced the average precipitation loss by 56.9% on the first day after precipitation. The depth-weighted average f values of precipitation to 0–120 cm soil layer under RP significantly increased by 12.0%–20.7% versus FP within 5 days after precipitation. Furthermore, RP extended the ID by 10–20 cm and maintained an ECT of 1–3 days in soil layers where no infiltration occurred under FP. In response to a 100 mm increase in Pr, RP demonstrated a clear advantage over FP, with a 60.9% and 59.9% reduction in precipitation loss, a 24.6% and 27.0% increase in f, and a 22.6% and 18.7% increase in ID, respectively, in wet and normal years. As a result, the 2-year average grain yield and water use efficiency of winter wheat under RP increased significantly by 19.1% and 21.6% in comparison to FP, respectively. This study fills the knowledge gap on the infiltration process of precipitation under RP, and provides empirical support for adopting it as a water-saving practice for wheat cultivation over FP in subhumid regions.