Geoderma最新文献

{"title":"Mapping clay fraction oxides in Brazil using Earth observation strategy","authors":"Jorge Tadeu Fim Rosas ,&nbsp;José A.M. Demattê ,&nbsp;Nícolas Augusto Rosin ,&nbsp;Raul Roberto Poppiel ,&nbsp;Nélida E.Q. Silvero ,&nbsp;Merilyn Taynara Accorsi Amorim ,&nbsp;Heidy S. Rodríguez-Albarracín ,&nbsp;Letícia Guadagnin Vogel ,&nbsp;Bruno dos Anjos Bartsch ,&nbsp;José João Lelis Leal de Souza ,&nbsp;Lucas de Carvalho Gomes ,&nbsp;Danilo César de Mello","doi":"10.1016/j.geoderma.2025.117425","DOIUrl":"10.1016/j.geoderma.2025.117425","url":null,"abstract":"<div><div>The major oxides in the clay fraction of tropical soils are iron (Fe2O3), aluminum (Al2O3), and silicon (SiO2) oxides, which are responsible for the soil’s capacity to provide multiple ecosystem services. Therefore, they are used to classify the soils into different pedological classes. Despite their importance of these oxides, quantifying them on a large scale presents significant challenges. The most common method is laboratory sulfuric acid digestion, which is expensive, complex, and environmentally detrimental. To overcome these issues and provide faster results, we developed a satellite technique associated with machine learning (ML) to map Fe₂O₃, Al₂O₃, and SiO₂ in all agricultural areas in Brazil at 30 m resolution. Additionally, we tested the feasibility of the generated maps to infer soil weathering, and assist in the construction of pedological maps. A dataset, comprising 5,330 sites (0–20 cm and 80–100 cm) across all 27 states was employed in prediction. Six spectral variables obtained from the historical Landsat series (bare soil) and seven terrain attributes derived from a digital elevation model were employed to generate the Fe₂O₃, Al₂O₃, and SiO₂ maps, using the Random Forest algorithm. The predicted maps of oxides covered nearly 3.48 million km² (∼40 % of the national territory). The best predictions were observed for Fe₂O₃ in the 0–20 cm layer (RMSE = 49.8 <span><span>g.kg</span><svg><path></path></svg></span>⁻¹, RPIQ = 1.82, and R² = 0.62), while the worst predictions were for SiO₂ in the 80–100 cm layer (RMSE = 65.3 <span><span>g.kg</span><svg><path></path></svg></span>⁻¹, RPIQ = 1.50 and R² = 0.22). It was possible to infer soil weathering using the Ki index. Despite the models not showing such high R² values, the results are aligned with legacy maps, highly weathered soils were observed in the plateaus of the Cerrado biome, while younger soils were observed in the arid Caatinga biome and waterlogged soils in the Pantanal biome. The generated maps also demonstrated a high potential for grouping pedological soil classes. They also revealed a relationship between oxide contents and the NDVI of sugarcane crops, indicating potential applications in crop management. Moreover, this satellite-based technique, supported by ML, presents a plausible approach to predict oxide fraction at high spatial resolution for large areas.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117425"},"PeriodicalIF":5.6,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Limited impact of organic fertilizers on soil phosphorus accumulation in a long-term field experiment with excess fertilization","authors":"M. Álvarez Salas ,&nbsp;Jakob Magid ,&nbsp;Dorette Müller-Stöver ,&nbsp;Beatriz Gómez-Muñoz ,&nbsp;Federica Tamburini ,&nbsp;Astrid Oberson","doi":"10.1016/j.geoderma.2025.117426","DOIUrl":"10.1016/j.geoderma.2025.117426","url":null,"abstract":"<div><div>Understanding how fertilizer phosphorus (P) interacts with soils is necessary in order to use it efficiently. In the long-term field experiment CRUCIAL (Closing the Rural-Urban Nutrient Cycle − Investigations through Agronomic Long-term experiments), organic fertilizers were intentionally overapplied to test soil ecotoxicological limits. This has resulted in yearly P inputs of up to 463 kg·ha⁻¹ and positive P balances (input after crop offtake) for over 20 years. These inputs have occurred in sandy loam soils. Fertilization treatments included sewage sludge, compost, cattle manure, other organic fertilizers, and mineral NPK. We hypothesized that, given the high fertilizer P inputs, P accumulation in the topsoil (0–0.2 m), along with its distribution into sequentially extractable fractions, would vary depending on P fractions in the fertilizers. We measured P fractions and total P concentrations in both organic fertilizers and topsoils, and calculated two P budgets. The first budget compared topsoil total P concentrations from 2003 with those from 2022, considering the total fertilizer P inputs and crop offtake over that time. The second is a fractional P budget that uses P fractions in topsoils treated with NPK as a baseline to assess fertilization induced changes. Treatments with sludge, compost, or manure had positive P balances between 2152 and 2664 kg·ha⁻¹ over 20 years. Total P stocks in the topsoil increased by at least 869 kg·ha⁻¹ in treatments with sludge or compost compared to only 278 kg·ha⁻¹ with manure. Treatments supplying less resin extractable-P and more NaHCO₃-P or NaOH-P retained a higher proportion of the fertilizer P, even in topsoils already saturated with P. Consequently, specific organic fertilizers have caused increases in soil P fractions corresponding to their own P fraction compositions. Still, between 59–87 % of the excess P applied could not be accounted for in topsoils after considering crop P offtake. Consequently, regardless of the fertilizer type, overfertilization led to excess P movement out of the topsoil layer, which is detrimental for the environment.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117426"},"PeriodicalIF":5.6,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of tree plantation-driven forest fragmentation on native soil bacteria and fungi: similar patterns, but contrasting mechanisms","authors":"Mengli Li ,&nbsp;Chaoyou Jiang ,&nbsp;Shucun Sun ,&nbsp;Fengqun Meng","doi":"10.1016/j.geoderma.2025.117423","DOIUrl":"10.1016/j.geoderma.2025.117423","url":null,"abstract":"<div><div>A global expansion of tree plantations, particularly in developing tropical and subtropical countries, has fragmented natural forests. Despite the importance of microorganisms in ecosystem services, it remains unclear whether plantation-driven fragmentation threatens microbial biodiversity. We hypothesize that bacterial and fungal diversity patterns on remnant forest “islands” surrounded by a “sea” of tree plantations follow the traditional island species–area relationship (SAR), i.e., larger fragments harbor more species. We examined the SAR patterns of soil bacteria and fungi and explored the mechanisms underlying the observed SAR using a cluster of 17 remnant natural forest fragments scattered across a “sea” of tree plantations in Yachang Forest Farm, Guangxi, China. As expected, both fragment-scale bacterial and fungal diversity increased with fragment area; however, neither bacterial nor fungal diversity was influenced by fragment isolation. The positive SARs for both bacteria and fungi were characterized by greater heterogeneity in community composition among localities on larger fragments. However, the mechanisms underlying the positive SARs differ between bacteria and fungi. The greater heterogeneity of bacterial community composition on larger fragments was associated with higher levels of soil pH heterogeneity, while the greater heterogeneity of fungal community composition was linked to increased geographic distances among localities on larger fragments. Our results suggest that the SAR for bacteria is primarily driven by habitat heterogeneity, whereas the SAR for fungi is primarily driven by dispersal limitation. These findings highlight urgent need for conservation efforts to maintain large, continuous remnant natural forest fragments to mitigate fragmentation-induced biodiversity loss.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117423"},"PeriodicalIF":5.6,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-based fertilizers typically deliver on either high nutrient release or soil health parameters","authors":"Tine Engedal,&nbsp;Bianca Messmer,&nbsp;Jakob Magid,&nbsp;Lars Stoumann Jensen,&nbsp;Veronika Hansen","doi":"10.1016/j.geoderma.2025.117424","DOIUrl":"10.1016/j.geoderma.2025.117424","url":null,"abstract":"<div><div>The transition to a circular and bio-based economy requires nutrient recycling from agricultural, industrial, and societal by-products and wastes. Beyond their role in nutrient supply for crop production, bio-based fertilizers (BBFs) also have the potential to improve soil health by contributing organic matter. However, as the legal framework evolves and a broader range of BBFs becomes available, a key challenge for implementation and adaptation lies in the great variability of their nutritional value and effects on soil health. Therefore, the aim of this study was to examine the effects of a diverse sample of BBFs on both nutrient release (nitrogen, sulfur and phosphorus) and a range of soil health parameters. In an 11-month incubation study, we evaluated eleven different bio-based fertilizers: four digestates, two composts, insect frass, and by-products from animal, medicinal, and plant production and processing. The results revealed a trade-off between high nutrient release and soil health improvements. High N availability was significantly and negatively correlated to all examined soil health parameters, while most soil health parameters were positively linked to the amount of added carbon (C). To overcome the trade-off between nutrient availability and soil health, customized BBF blends with optimized nutrient and C profiles tailored to specific field needs may offer a practical solution for farmers. Further research, particularly under field conditions, is needed to fully understand the long-term effects of BBFs on soil properties and crop growth.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117424"},"PeriodicalIF":5.6,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying spatial and vertical variations in soil C:N relationships in permafrost-affected landscapes","authors":"Joshua O. Minai ,&nbsp;Julie D. Jastrow ,&nbsp;Roser Matamala ,&nbsp;Chien-Lu Ping ,&nbsp;Gary J. Michaelson ,&nbsp;Nicolas A. Jelinski","doi":"10.1016/j.geoderma.2025.117418","DOIUrl":"10.1016/j.geoderma.2025.117418","url":null,"abstract":"<div><div>Permafrost regions are experiencing rapid changes that affect carbon (C) and nitrogen (N) cycles, with implications for vegetation dynamics and gas exchanges with the atmosphere. Soil C:N ratio is a key indicator of organic matter quality, yet spatial estimates of N stocks and C:N ratios lag behind those for C. We used quantile regression forests to compare direct and indirect digital soil mapping approaches for predicting soil C:N ratios at 0–30, 30–60, and 60–100 cm depths across a latitudinal transect in Alaska. The indirect approach – deriving C:N from separately predicted C and N stocks – outperformed direct mapping for the surface layer (0–30 cm), while direct mapping was marginally better at greater depths. However, prediction accuracy decreased with depth for both methods. Temperature and topography were the most important predictors. Both approaches overestimated low and underestimated high C:N ratios, with direct mapping showing greater bias. Our results underscore the challenges of modeling C:N ratios in heterogeneous, data-sparse permafrost soils, but also suggest that indirect mapping holds promise if supported by more extensive datasets.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117418"},"PeriodicalIF":5.6,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active motility and chemotactic movement regulate the microbial early-colonization and biodiversity","authors":"Yan Wang ,&nbsp;Ali Ebrahimi ,&nbsp;Guowei Chen ,&nbsp;Zi Zhang ,&nbsp;Kun Zhu ,&nbsp;Shane Franklin ,&nbsp;Yan Jin ,&nbsp;Ying Liu ,&nbsp;Gang Wang","doi":"10.1016/j.geoderma.2025.117419","DOIUrl":"10.1016/j.geoderma.2025.117419","url":null,"abstract":"<div><div>Microbial dispersal and subsequent colonization of new niches are fundamental processes in microbial ecology, particularly in patchy environments like soil. However, the heterogeneity of soil pore spaces and the resulting fragmented aqueous habitats are known to significantly impede microbial dispersal rates and ranges. Despite this, the strategies microbes employ to overcome these abiotic constraints remain poorly understood. To address this, we developed a novel experimental system using porous ceramic surfaces to simulate hydrated soil environments, enabling direct quantification of early-stage bacterial colonization. Our findings reveal that distinct taxonomic and functional bacterial populations successfully colonized the porous ceramic surfaces, differing significantly from the original soil communities. Active motility and chemotaxis emerged as two key traits facilitating early-stage colonization. However, the advantages conferred by motility and chemotaxis were significantly reduced under drier soil conditions, typically at water contents below 25% (v/v). Under such conditions, non-motile bacteria relied on passive dispersal mechanisms or physical adhesion to colonize the porous surfaces. Furthermore, functional metagenomic profiling of the colonizing microbial populations uncovered a trade-off between growth and dispersal rates. This observed trade-off was incorporated into an agent-based model simulating microbial activity in soil, which explored how correlations between microbial functional genes influence community dynamics during early colonization. The simulations demonstrated that the growth-dispersal trade-off is crucial for enhancing and maintaining microbial diversity during colonization of new niches. Our study elucidates the key biophysical mechanisms driving microbial early-stage colonization dynamics from bulk soil to new environments, highlighting this process as a core ecological phenomenon in soil ecosystems.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117419"},"PeriodicalIF":5.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gemmatirosa adaptations to arid and low soil organic carbon conditions worldwide","authors":"Yuanyuan Bao ,&nbsp;Tadeo Sáez-Sandino ,&nbsp;Youzhi Feng ,&nbsp;Xuebin Yan ,&nbsp;Shiying He ,&nbsp;Shilun Feng ,&nbsp;Ruirui Chen ,&nbsp;Hui Guo ,&nbsp;Manuel Delgado-Baquerizo","doi":"10.1016/j.geoderma.2025.117420","DOIUrl":"10.1016/j.geoderma.2025.117420","url":null,"abstract":"<div><div>Aridity and warming accelerate soil organic carbon (SOC) loss, thereby compromising essential functions of soil health, such as nutrient retention and microbial diversity. However, the mechanisms by which microbes adapt to arid and low SOC conditions remain poorly understood. Here, using data from an 8-y field-scale manipulation experiment, we found that the largely undescribed <em>Gemmatimonadetes</em> could be among the well-adapted bacterial taxa for thriving under low SOC content and arid ecosystems. Their enhanced ability to tolerate drought stress—mediated by metabolic pathways for the synthesis of osmolytes (e.g., glycine, betaine, choline, ectoine, and histidine)—and their capacity to acquire carbon resource through glycoside hydrolase genes involved in organic matter decomposition (41.6 % and 11.8 % higher than those in the total bacterial community, respectively), could explain this pattern. Further analyses based on a global-scale standardized field survey covering all continents and major ecosystem types further confirmed that <em>Gemmatimonadetes</em>—and, at a finer resolution, <em>Gemmatirosa</em>—predominated in arid (with a peak relative abundance of <em>Gemmatimonadetes</em> reaching 3.8 % in dry grasslands) and warm regions (peaking at 4.5 % in Africa) of the planet, where the SOC content is low. Our work provides new insights into how a largely neglected microbial group, such as <em>Gemmatimonadetes/Gemmatirosa</em>, can adapt to increasing environmental stress in arid and low-carbon environments in a changing world.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117420"},"PeriodicalIF":5.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting soil organic matter using corrected field spectra and stacking ensemble learning","authors":"Yu Wang ,&nbsp;Xuhui Yan ,&nbsp;Rongyanting Huo ,&nbsp;Longcai Zhao ,&nbsp;Jie Peng ,&nbsp;Yongsheng Hong ,&nbsp;Jing Liu","doi":"10.1016/j.geoderma.2025.117417","DOIUrl":"10.1016/j.geoderma.2025.117417","url":null,"abstract":"<div><div>Soil organic matter (SOM), as a key indicator of soil fertility and the carbon cycle, its field rapid and precise quantification is of great scientific significance for precise agricultural management. Visible near-infrared (Vis-NIR) spectroscopy technology is a rapid and highly accurate SOM quantification method. While the laboratory spectra measurement requires a series of processing procedures. Compared with laboratory spectra, field spectra measurement has the advantages of being faster and more convenient. However, achieving high-precision estimation of SOM based on field spectra poses significant challenges, primarily in mitigating the effects of interfering factors, such as soil moisture and developing a highly robust spectra prediction model. In the practical application of field spectroscopy, eliminating interference through spectra correction methods is an effective strategy. The field prediction of SOM using spectra correction algorithms in conjunction with ensemble learning remains a significant and unresolved challenge. In this study, we gathered 180 soil samples from Hancheng City, Shaanxi Province, China, and built Stacking models using field spectra, field corrected spectra, and lab spectra, respectively, and comprehensively compared their predictive abilities. The study aims to assess the ability of spectra correction methods, including non-negative matrix decomposition (NMF), and generalized least squares weight (GLSW), when combined with the Stacking model, to predict SOM. The results showed that it was difficult challenging to accurately predict SOM using models calibrated with field spectra. However, spectra data corrected by NMF and GLSW could effectively mitigate the influence of environmental interference factors and significantly enhance the model’s predictive performance. The GLSW (R² = 0.85, RMSE = 3.74 g kg⁻¹) outperformed the NMF method (R² = 0.69, RMSE = 5.14 g kg⁻¹) and was close to the laboratory spectra model (R² = 0.89, RMSE = 3.81 g kg⁻¹). Combining spectra correction and stacking improves field SOM prediction accuracy, increasing R² value by 0.1 and 0.26, and decreasing RMSE by 1.16 and 2.56 g kg⁻¹. The performance of all Stacking models was superior to that of the best single model. The stacking model could effectively improve the accuracy of SOM model.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117417"},"PeriodicalIF":5.6,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144500913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of soil thickness in karst landforms using a quantile regression forests approach","authors":"Fayong Fang ,&nbsp;Ruyi Zi ,&nbsp;Zhen Han ,&nbsp;Qian Fang ,&nbsp;Rui Hou ,&nbsp;Longshan Zhao","doi":"10.1016/j.geoderma.2025.117416","DOIUrl":"10.1016/j.geoderma.2025.117416","url":null,"abstract":"<div><div>Soil thickness is a basic feature of the earth’s land surface. Accurately representing the spatial distribution of soil thickness is important for various models of earth surface processes. However, mapping soil thickness in karst landforms is highly uncertain. To address this challenge, this study analyzed the correlation between 906 soil thickness measurements and 376 environmental characteristics in a typical karst landscape covering 54,000 km². We employed a quantile regression forests (QRF) approach to estimate soil thickness and evaluate the associated uncertainty in the predicted results. We found that, like other regional scale soil mapping models, climate and topographic data were key factors influencing soil thickness. Specific for karst landscapes, we found that the characteristics of karst rocky desertification play a key role in predicting soil thickness. The rocky desertification information indexes (RIs), which use exposure rate of bedrock to represent the degree of karst rocky desertification, showed relatively high importance in the variable importance assessment. The developed model explained 40 % of the spatial variability of soil thickness across the study area, with an RMSE (37.3 cm) of 50–60 % of the mean thickness. This indicates that the model, and environmental factors evaluated within, explained a little less than half of the spatial variability. The prediction results reveal the distribution pattern of soil thickness at both regional and local scales within karst landforms. Thick soil was commonly found in low-lying landscape features like depressions and foothills, whereas areas with steep slopes, ridges, and peaks tended to have thin soil, following a typical toposequence. In areas with relatively deep soil or severe rocky desertification, the uncertainty of predicting soil thickness is relatively high. The results of uncertainty analysis, as a supplement to the prediction results, have improved the usability of the predictions to a certain extent. This study has, to some extent, addressed the challenges of predicting soil thickness in karst areas and has also provided transferable methods for other complex regions.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117416"},"PeriodicalIF":5.6,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in water characteristics and pore distributions in loam soil under the coexistence of microplastics and salts","authors":"Xuguang Xing ,&nbsp;Liuchang Su ,&nbsp;Dongwei Li ,&nbsp;Fengyue Zhao ,&nbsp;Weihua Wang","doi":"10.1016/j.geoderma.2025.117415","DOIUrl":"10.1016/j.geoderma.2025.117415","url":null,"abstract":"<div><div>Farmland salinization and microplastics (MPs) pollution are increasing worldwide, posing threats to environmental health and accelerating land degradation. In the context of the global ecological challenges of land degradation and pollution, clarifying the interactions between MPs and salts is beneficial for land development and sustainable management. We measured the hydraulic parameters and calculated the water characteristics and pore distributions of the soils with different salinities (i.e., 0, 1, 3, and 5 g/kg) and MPs mixing contents (i.e., 0, 5, 10, and 30 g/kg). Results indicated that MPs generally reduced the soil saturated hydraulic conductivity, but the increased soil salinity weakened the effects of MPs on it. According to the soil water retention curves, MPs weakened the water-holding capacity, with a greater impact in non-saline soil than in saline soil. In non-saline soil, MPs caused the saturated water content to decrease by 4.6 %–8.1 %. In addition, MPs reduced the field capacity and wilting coefficient of both soils. The effect of MPs on available water was greater in non-saline soil than in saline soil. Furthermore, MPs reduced the total porosity of both soils. However, MPs had no significant effect on pore distribution in non-saline soil, whereas, in saline soil, MPs increased the proportion of micro pores and small pores but decreased the proportion of macro pores and voids. We determined that, in addition to changing the pore distribution, MPs and salts changed the water characteristics through hydrophobicity and ionic interactions, respectively. Our findings provide evidence of the influence of MPs on the physical properties of saline soil, highlighting the need for improved regulation and land management in plastic-polluted soil–crop systems.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117415"},"PeriodicalIF":5.6,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}