Geoderma Regional最新文献

Soil sealing has been recognised as one of the main causes of urban soil degradation in Europe. To tackle this issue, de-sealing measures have recently been promoted in cities to increase the sustainability of soil ecosystem services. To our knowledge, very few evaluations of de-sealing projects have as yet been done to assess the current framework of these urban planning practices. Therefore, we conducted an online survey to collect and analyse soil de-sealing projects throughout mainland France. A 60-question survey was run over a 4-month-period, and data about 57 projects were collected. The answers covered a diversity of projects, structures and stakeholders and included data such as the location / objectives / costs and benefits of the projects implemented in cities of various sizes. A typology of urban land-uses before and after de-sealing was defined. Among the diverse objectives of de-sealing, rainwater management, reducing urban heat, and greening were most frequent. More than half of the respondents (64%) indicated that ecosystem services were used to drive their de-sealing project. The methods usually required excavation of the sealing cover and road layers being replaced by newly imported fertile materials. Recent de-sealing projects have reused derelict materials from the site (soil-material inventory) and/or local urban waste for soil construction, which can help minimise both the economic and environmental costs of urban greening projects. The results of this study provide quite an exhaustive view of current French de-sealing practices and could provide guidelines for improving soil functions by applying soil engineering processes to construct sustainable fertile soils for urban greening.

The visible-near infrared (Vis-NIR) reflectance technique is a powerful tool, particularly for obtaining faster information about soil texture, organic matter, and calcium carbonate content. However, there is limited research on the characterization of soil horizons using Vis-NIR data in profiles of different soil series. This study investigated the relationship between soil properties and spectral reflectance (Vis-NIR) in eight soil profiles with varying genetic properties from Harran Plain, Türkiye, focusing on variations within profiles (A, B, and C horizons) and across different soil series. A total of 36 soil samples were collected from the A, B, and C horizons, and spectral reflectance was measured along with calcium carbonate, organic matter, and particle size distribution. High variability was observed in calcium carbonate (11.58–52.50%) and organic matter content (0.60–3.71%), reflecting complex soil composition influenced by parent material and land management. Distinct reflectance patterns were observed within profiles, reflecting variations in soil composition. Ap horizons with higher organic matter content often exhibited lower reflectance (visible region). Clay content influenced NIR reflectance, with higher absorption in clay-rich profiles. The Kaynakli series (Fine-loamy, mixed, mesic Typic Calcixerepts) showed differentiation in reflectance between A and B horizons after 700 nm due to horizon formation and clay/carbonate accumulation. Increasing calcium carbonate content in Ck horizons led to higher reflectance compared to other layers. Confirmed that Vis-NIR reflectance could explain a significant portion of the variance in soil properties (A: 87.7%, B: 88.3%, and C: 90.6%). PCA results supported the notion that spectral signatures captured by Vis-NIR reflectance measurements are indicative of inherent differences between A, B, and C horizons. This study contributes to the growing body of knowledge on the application of Vis-NIR spectroscopy for soil assessment and monitoring. However, future research should focus on understanding spectral reflectance variations under diverse soil and environmental conditions.

In the context of a changing climate and the increasing occurrences of extreme events, including droughts, field evidence, and models suggest that cases of forest decline and migration of tree species to more suitable climates will augment in the 21st century. In northeastern North America, an expansion of American beech at the expense of maples has been observed since the 1970s and has been associated to several causes. Through an analysis of time series leveraging thousands of data collected in a temperate forest in southern Quebec, Canada, dynamics of soil water potential were analyzed in interaction with soil temperature, meteorological variables and forest types, including hardwoods (mostly maple) with a large presence of beech trees (hardwood-beech stands), hardwoods (maple and birch) and mixedwoods (maple and fir). During flash drought events with a net precipitation deficit and water stress, the presence of beech led to a decrease in soil temperature and favored the maintenance of low soil water potential and faster restoration of water reserves compared to mixedwoods. Using machine learning-based approaches, distinct critical soil temperature thresholds in regard to water potential were identified for the various forest types, and the temporality in soil water regime changes was more favorable under hardwood-beech stands. The presence of beech appears to render greater resilience in regard to water stress in this forest. A greater capacity of beech to preserve and restore soil water not only offers an additional explanation for its establishment in hardwoods in the last decades, but greater water conservation in the presence of beech, assuming it remains in the landscape, could also help local plant species adapt to climate change and to the predicted increased water deficits, as well as species migrating northward to find more suitable environmental envelopes.

Exchangeable aluminum (Exc-Al), an often overlooked yet indispensable soil parameter, predominantly contributes to soil exchangeable acidity. In this study, we utilized data from 53 sets of surface and subsurface black soil characteristics, including Exc-Al, exchangeable acid (Exc-acid), pH, soil organic matter (SOM), and available and total nutrient levels, to develop a neural network prediction model for estimating Exc-Al and Exc-acid in the black soil area of northeast China. The deterministic neural network model (NNM) was employed to predict Exc-Al and Exc-acid contents in 690 sets of surface and subsurface farmland soil samples with unknown Exc-Al and Exc-acid values. Subsequently, a black soil exchangeable acidity map for northeast China was generated through spatial interpolation. Our results revealed that the average Exc-Al and Exc-acid contents in the 53 surface soils were 0.82 and 0.93 cmol kg⁻¹, respectively, while those in the corresponding subsurface soils were 0.58 and 0.70 cmol kg⁻¹, respectively. Multi-layer perceptron (MLP) neural networks effectively simulated Exc-Al and Exc-acid contents in the surface and subsurface black soils, with calibrated determination coefficients (R_adj²) of 0.95–0.96, relative root mean square errors (rRMSE) of 17.3%–24.8%, and statistical significance α at 0.001. The MLP estimations and spatial interpolations revealed that 2.0% and 17.6% of the surface black soil area, and 0% and 3.7% of the subsurface soil area exhibited Exc-Al content exceeding 2.0 and 1.0 cmol kg⁻¹, respectively. Furthermore, 6.7% and 24.9% of the surface black soil area, and 0% and 6.3% of the subsurface soil area showed Exc-acid content exceeding 2.0 and 1.0 cmol kg⁻¹, respectively. These findings break the limitation of relying solely on soil pH as the unique indicator, enrich our knowledge of black soil exchangeable acidity, and enhance our understanding of the black soil acidity status in northeast China.

Soil organic carbon (C) and nitrogen (N) are profoundly affected by changes in land use and land cover (LULC), especially by farming in riparian zones. The five LULC classes were selected in contiguous order, i.e., undisturbed forest (CAL_ref), conventional agriculture lands (CAL), reservoir riparian zones (RSRZ), river riparian zones (RRZ), and undisturbed riparian zones (RZ_ref) in the Ganga River basin to study the C storage and emission trends at a landscape scale. The riparian soils showed higher moisture, temperature, and bulk density than the upland soils, strongly determining the spatial variations in the CO₂ equivalent (CO₂e), C:N ratio, and CO₂ efflux. Riparian CO₂e was more bulk density-dependent, while upland CO₂e showed greater dependence on TOC. The C:N ratio showed a higher mean value in the reference soils (CAL_ref and RZ_ref) than in the other soils (P < 0.05). The total nitrogen (TN), total protein (TP), and NH₄-N (ammonium‑nitrogen) showed the following trend: RSRZ > CAL > RRZ > RZ_ref > CAL_ref. The stepwise multiple regression models illustrated that soil moisture was the primary regulator of the C:N ratio and CO₂ efflux in the upland soils while the temperature in the riparian soils. These intrinsic soil variables resulted in 1.15 to 2.26 times higher CO₂ efflux from the cultivated soils (CAL, RSRZ, and RRZ) than from the reference soils. Hence, the present study revealed how agricultural practices tangibly increase the riparian system's carbon footprint while offering unsustainable livelihood options to farmers.

Shallow soils (i.e., Lithic Entisols) cover about 20% of Brazilian drylands. Inherent soil characteristics (i.e., shallow depths) and water scarcity restrict plant growth and carbon (C) inputs in these soils. In such a sensitive ecosystem, sustainable land management options are key to promoting socio-economic development and ensuring food security. Here, we use a dataset of 50 Lithic Entisol profiles distributed within the Brazilian drylands (northeastern region) to: (i) investigate the effects of land-use (cropland, grassland, and native forest), climate (semi-arid and dry sub-humid), and slope classes (0–3%, 3–8%, 8–20% and 20–45%) on soil C accumulation; and (ii) evaluate how understanding multiple drivers C accumulation can support the identification of sustainable land management options. The results suggested that land use does not affect C stock and C/N ratio, nevertheless, they were affected by climate. Under dry sub-humid climate conditions, C stocks were 41.7 Mg ha⁻¹, 44% higher than under semi-arid climate (28.9 Mg ha⁻¹), a result that reflects the effect of higher biomass production in wetter environments. Under slopes of 20–45%, C stocks were 54.3 Mg ha⁻¹, 172% higher than under slopes of 0–3% (19.9 Mg ha⁻¹), because of the higher altitudes and wetter conditions under steeper slopes. Our results showed that areas under lower slopes have lower C stocks and lower aridity index. These drier conditions reduce the productive potential of annual crops and grasslands but enable the cultivation of high-yielding Crassulacean Acid Metabolism (CAM) crops, such as Agave spp, which have a high potential for biofuel production. Furthermore, the possibility of reintroducing organic residues from ethanol production can promote an increase in C stocks, contributing to climate change mitigation. Ultimately, our study provides insights from a holistic view of SOC accumulation drivers, supporting land use planning of highly sensitive environments in tropical drylands around the world.

The utilization of biochar as a soil amendment holds promise for long-term carbon sequestration due to its elevated carbon content and persistent chemical structure. This characteristic has positioned biochar as a proposed nature-based solution for climate change mitigation. Nevertheless, the impact of biochar on soil greenhouse gas (GHG) emissions remains a subject of ongoing debate. In the present investigation, we evaluated the influence of conifer wood biochar on the fluxes of three GHGs, namely carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄), in a vineyard soil subjected to biochar-alone treatments (at rates of 25 and 50 t ha⁻¹) and in combination with green waste compost (at a rate of 45 t ha⁻¹). The experimental field was situated in northern Italy and was organized in a randomized block design. Soil GHG fluxes were monitored for two and a half years. Monthly flux measurements were conducted using a high-resolution multi-gas analyzer for 24 hours. Fluxes were, therefore, correlated with soil temperature to assess the influence of treatments on the sensitivity of GHG emissions to this pivotal environmental parameter. The findings demonstrated diminished temperature sensitivity in the initial experimental year across all GHG fluxes in soils amended with biochar and biochar-compost combination, in contrast to treatments lacking biochar (i.e., control and compost-alone treatments). Notably, the attenuation was most pronounced for N₂O emissions, suggesting a potential role of biochar in mitigating the release of this gas. However, this effect did not persist in the second and third years of the experiment. Overall, biochar significantly contributed to a reduction in N₂O fluxes and an increase in CO₂ fluxes, but the effect was limited and temporary. Furthermore, biochar had no impact on CH₄ fluxes. The discerned fluctuation in the impact of biochar over time can be attributed to the processes of biochar aging and/or the interannual variability in soil moisture.

The current investigation examines the effects of LULC variation on soil erosion and soil organic carbon at the basin of Çorum Stream of Çorum city in the Central Black Sea Region characterized by semi-humid environmental conditions, for the years 1990, 2001, 2010 and 2021. The research employed a GIS application based on Revised Universal Soil Loss Equation (RUSLE) modeling approach, geostatistics, and remote sensing techniques. The findings revealed significant relative changes in LULC types over the study period, relatively 41.1% increase in artificial area. Spatial changes were minimal in agricultural areas and pasturelands. Despite the slight changes observed in soil erosion rates classified by RUSLE, with areas mainly falling into the Very Low–Low erosion rate categories (20.0 ton ha⁻¹ year⁻¹), it is recommended to expand soil conservation practices, particularly in agricultural and pasture areas, to make sure the long-period sustainability of the production system. In addition, When examining the distribution of SOC stocks in the study area according to both LULC and rates of soil erosion, it was found that forested areas exhibited the highest distribution of both low and very low SOC rates as well as very high and high SOC rates, while agricultural and artificial areas showed the lowest distribution.

Rare earth elements (REEs) are becoming increasingly interesting as indicators of soil processes, and modelling their spatial distribution has become a fundamental requirement for this purpose. This study aims to model and quantify the spatial distribution of soil REEs taking into account their compositional nature in their mapping, and to assess the associated spatial uncertainty. In particular, the cerium anomaly (Ce^⁎) and the ratio of the sum (Σ) of light to heavy REEs (ΣLREEs/ΣHREEs) were calculated and analysed. The study was carried out in Sicily (Italy), one of the largest (25,832 km²) and most populous island in the Mediterranean Sea. Soil REE data were obtained from the soil database of Sicily region. Soil REEs were transformed into a vector of isometric log-ratio (ilr) coordinates and analysed using a geostatistical approach for predicting their values at unsampled locations and generating 100 REEs realizations using turning bands simulation. Each REE element and Ce^⁎ were mapped as well as the ΣLREEs/ΣHREEs ratio. The joint variability of the investigated REEs and the ΣLREEs/ΣHREEs ratio provided insights into their abundance and distribution patterns. From the simulated realizations, standard deviation maps were calculated for the Ce^⁎ and the ΣLREEs/ΣHREEs ratio, providing a measure of their spatial uncertainty. Although with some limitations, the study established a first baseline of the Ce^⁎ and the ΣLREEs/ΣHREEs ratio. The maps of spatial uncertainty may be a useful tool for planning future soil sampling and optimise the choice of new sampling locations.