Particle morphology and soil properties affect the retention of copper oxide nanoparticles in agricultural soils.

The interaction between nanoscale copper oxides (nano-CuOs) and soil matrix significantly affects their fate and transport in soils. This study investigates the retention of nano-CuOs and Cu2+ ions in ten typical agricultural soils by employing the Freundlich adsorption model. Retention of nano-CuOs and Cu2+ in soils was well fitted by the Freundlich model. The retention parameters (KD, KF, and N) followed an order of CuO NTs > CuO NPs > Cu2+, highlighting significant impact of nano-CuOs morphology. The KF and N values of CuO NPs/Cu2+ were positively correlated with soil pH and electrical conductivity (EC), but exhibited a weaker correlation for CuO NTs. Soil pH and/or EC could be used to predict KF and N values of CuO NPs or CuO NTs, with additional clay content should be included for Cu2+.The different relationship between retention parameters and soil properties may suggest that CuO NTs retention mainly caused by agglomeration, whereas adsorption and agglomeration were of equal importance to CuO NPs. The amendment of Ca2+ at low and medium concentration promoted retention of nano-CuOs in alkaline soils, but reduced at high concentration. These findings provided critical insights into the fate of nano-CuOs in soil environments, with significant implications for environmental risk assessment and soil remediation strategies.

Multi-criteria GIS-based land suitability analysis for rice cultivation: a case study in Guilan Province, Iran.

Ensuring food security and sustainable resource management has become a paramount global concern, prompting significant attention to land suitability analysis for enhancing agricultural production. In this study, an AHP-weighted overlay method was employed to delineate rice cultivation suitability in Guilan province, Iran, a central hub for rice production. Sixteen climatic, topographic, and soil variables were integrated, and individual maps were reclassified to align with the specific requisites for rice production. The results revealed three suitability classes: including 'very suitable,' 'suitable,' and 'moderately suitable', covering 91%, 6%, and 3% of the land, respectively. Soil attributes, particularly organic matter, significantly influenced suitability (weight value of 0.745), with topographic and soil factors outweighing climate in assessment. While salinity is generally absent, organic matter deficiency affects 44% of the land. Phosphorus imbalances are prevalent, with potassium toxicity observed in 10%. Microelement deficiencies, especially in iron and zinc, are noted. Additionally, the results indicated that topographic and soil attributes played a more significant role than climate-related factors in assessing land suitability for rice cultivation within the study area. This research provides a comprehensive spatial analysis of all variables in the study region, shedding light on the complexities of land suitability for rice cultivation. These findings contribute to the understanding of agricultural sustainability and resource management strategies in the context of food security.

Exploring main soil drivers of vegetation succession in abandoned croplands of Minqin Oasis, China.

Background: The Minqin Oasis, which is located in Wuwei City, Gansu Province, China, faces a very serious land desertification problem, with about 94.5% of its total area desertified. Accordingly, it is crucial to implement ecological restoration policies such as cropland abandonment in this region. In abandoned croplands, abiotic factors such as soil properties may become more important than biotic factors in driving vegetation succession. However, the connections between soil properties and vegetation succession remain unclear. To fill this knowledge gap, this study investigated these connections to explore major factors that affected vegetation succession, which is meaningful to designing management measures to restore these degraded ecosystems. Methods: This study investigated seven 1-29-year-old abandoned croplands using the "space for time" method in Minqin Oasis. Vegetation succession was classified into different stages using a canonical correlation analysis (CCA) and two-way indicator species analysis (Twinspan). The link between soil properties and vegetation succession was analyzed using CCA. The primary factors shaping community patterns of vegetation succession were chosen by the "Forward selection" in CCA. The responses of dominant species to soil properties were analyzed using generalized additive models (GAMs). Results: Dominant species turnover occurred obviously after cropland abandonment. Vegetation succession can be classified into three stages (i.e., early, intermediate, and late successional stages) with markedly different community composition and diversity. The main drivers of vegetation succession among soil properties were soil salinity and saturated soil water content and they had led to different responses of the dominant species in early and late successional stages. During the development of vegetation succession, community composition became simpler, and species diversity decreased significantly, which was a type of regressive succession. Therefore, measures should be adopted to manage these degraded, abandoned croplands.

Bacterial community in the buckwheat rhizosphere responds more sensitively to single microplastics in lead-contaminated soil compared to the arbuscular mycorrhizal fungi community.

Soil pollution by microplastics (MPs), defined as plastic particles <5 mm, and heavy metals is a significant environmental issue. However, studies on the co-contamination effects of MPs and heavy metals on buckwheat rhizosphere microorganisms, especially on the arbuscular mycorrhizal fungi (AMF) community, are limited. We introduced low (0.01 g kg-1) and high doses of lead (Pb) (2 g kg-1) along with polyethylene (PE) and polylactic acid (PLA) MPs, both individually and in combination, into soil and assessed soil properties, buckwheat growth, and rhizosphere bacterial and AMF communities in a 40-day pot experiment. Notable alterations were observed in soil properties such as pH, alkaline hydrolyzable nitrogen (AN), and the available Pb (APb). High-dose Pb combined with PLA-MPs hindered buckwheat growth. Compared to the control, bacterial Chao1 richness and Shannon diversity were lower in the high dose Pb with PLA treatment, and differentially abundant bacteria were mainly detected in the high Pb dose treatments. Variations in bacterial communities correlated with APb, pH and AN. Overall, the AMF community composition remained largely consistent across all treatments. This phenomenon may be due to fungi having lower nutritional demands than bacteria. Stochastic processes played a relatively important role in the assembly of both bacterial and AMF communities. In summary, MPs appeared to amplify both the positive and negative effects of high Pb doses on the buckwheat rhizosphere bacteria.

Remediation of phenanthrene contaminated soil by persulphate coupled with Pseudomonas aeruginosa GZ7 based on oxidation prediction model.

Chemical oxidation coupled with microbial remediation has attracted widespread attention for the removal of polycyclic aromatic hydrocarbons (PAHs). Among them, the precise evaluation of the feasible oxidant concentration of PAH-contaminated soil is the key to achieving the goal of soil functional ecological remediation. In this study, phenanthrene (PHE) was used as the target pollutant, and Fe2+-activated persulphate (PS) was used to remediate four types of soils. Linear regression analysis identified the following important factors influencing remediation: PS dosage and soil PHE content for PHE degradation, Fe2+ dosage, hydrolysable nitrogen (HN), and available phosphorus for PS decomposition. A comprehensive model of "soil characteristics-oxidation conditions-remediation effect" with a high predictive accuracy was constructed. Based on model identification, Pseudomonas aeruginosa GZ7, which had high PAHs degrading ability after domestication, was further applied to coupling repair remediation. The results showed that the optimal PS dose was 0.75% (w/w). The response relationship between soil physical, chemical, and biological indicators at the intermediate interface and oxidation conditions was analysed. Coupled remediation effects were clarified using microbial diversity sequencing. The introduction of Pseudomonas aeruginosa GZ7 stimulated the relative abundance of Cohnella, Enterobacter, Paenibacillus, and Bacillus, which can promote material metabolism and energy transformation during remediation.

Artificial neural networks in soil quality prediction: Significance for sustainable tea cultivation.

In today's era artificial intelligence is quite popular, one of the most effective algorithms used is Artificial Neural Networks (ANN). In this study, the determination of soil quality using the Soil Management Assessment Framework (SMAF) model in areas where tea cultivation is carried out at the micro-watershed scale and the predictability of soil quality using ANN were evaluated. According to the results, the soil quality indices of tea-growing areas were generally classified as "medium" between 55 and 70 %. Among the evaluated features for determining soil quality, the highest relative importance value was for soil organic carbon content (13 %) and potential mineralizable nitrogen (13 %), whereas the lowest values were for exchangeable potassium (4 %) and sodium adsorption ratio (SAR) (4 %). In addition, when comparing the actual and predicted values for soil quality prediction using ANN, the Lin's concordance correlation coefficient (LCCC), ratio of performance to deviation (RPD), and R2 values were found to be 0.93, 2.95, and 0.89, respectively. Significant properties for the determined values within a 90 % predicted interval were found to be organic matter, microbial biomass carbon, bulk density, and aggregate stability of the soils. Moreover, the uncertainty values (standard deviation) in the model predictions were determined to be within the range of 1.01-4.56 %. Consequently, the Soil Quality Index (SQI) obtained from the SMAF model using 12 soil properties in tea-growing areas could be accurately predicted using ANN. As a result of this study, digital maps showing the spatial distribution of SQI and the predicted uncertainties can help monitor SQI levels in this area.

Divergent effects of single and combined stress of drought and salinity on the physiological traits and soil properties of Platycladus orientalis saplings.

Drought and salinity are two abiotic stresses that affect plant productivity. We exposed 2-year-old Platycladus orientalis saplings to single and combined stress of drought and salinity. Subsequently, the responses of physiological traits and soil properties were investigated. Biochemical traits such as leaf and root phytohormone content significantly increased under most stress conditions. Single drought stress resulted in significantly decreased nonstructural carbohydrate (NSC) content in stems and roots, while single salt stress and combined stress resulted in diverse response of NSC content. Xylem water potential of P. orientalis decreased significantly under both single drought and single salt stress, as well as the combined stress. Under the combined stress of drought and severe salt, xylem hydraulic conductivity significantly decreased while NSC content was unaffected, demonstrating that the risk of xylem hydraulic failure may be greater than carbon starvation. The tracheid lumen diameter and the tracheid double wall thickness of root and stem xylem was hardly affected by any stress, except for the stem tracheid lumen diameter, which was significantly increased under the combined stress. Soil ammonium nitrogen, nitrate nitrogen and available potassium content was only significantly affected by single salt stress, while soil available phosphorus content was not affected by any stress. Single drought stress had a stronger effect on the alpha diversity of rhizobacteria communities, and single salt stress had a stronger effect on soil nutrient availability, while combined stress showed relatively limited effect on these soil properties. Regarding physiological traits, responses of P. orientalis saplings under single and combined stress of drought and salt were diverse, and effects of combined stress could not be directly extrapolated from any single stress. Compared to single stress, the effect of combined stress on phytohormone content and hydraulic traits was negative to P. orientalis saplings, while the combined stress offset the negative effects of single drought stress on NSC content. Our study provided more comprehensive information on the response of the physiological traits and soil properties of P. orientalis saplings under single and combined stress of drought and salt, which would be helpful to understand the adapting mechanism of woody plants to abiotic stress.

[Effects of Rosa roxburghii Pomace Biochar on Yield and Quality of Chinese Cabbage and Soil Properties].

In order to explore the effect of Rosa roxburghii pomace biochar on the yield and quality of Chinese cabbage and soil properties and realize the resource utilization of R. roxburghii pomace, a pot experiment was conducted to study the effect of R. roxburghii pomace biochar on the yield and quality of Chinese cabbage and soil properties by setting five biochar application rates of 0 % (CK), 1 % (T1), 3 % (T2), 5 % (T3), and 7 % (T4). The results showed that:① The application of R. roxburghii pomace biochar could significantly improve the yield and quality of Chinese cabbage, and the effect was the best at a 5 % biochar application rate. The yield, soluble solids, soluble sugar, vitamin C, total nitrogen, total phosphorus, and total potassium content of Chinese cabbage increased by 71.51 %, 40.14 %, 33.65 %, 38.08 %, 9.03 %, 28.85 %, and 35.38 %, respectively, compared with those in CK. ② The application of biochar from R. roxburghii pomace could significantly improve soil properties and increase soil nutrient content and availability. The effect was better at a 5 % biochar application rate. The soil pH, organic matter, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium content increased by 41.06 %, 134.84 %, 157.48 %, 140.79 %, 341.75 %, and 627.13 %, respectively, compared with those in CK. The contents of available Fe, Mn, Cu, and Zn and exchangeable Ca and Mg increased by 37.68 %, 61.69 %, 400.00 %, 4 648.84 %, 617.17 %, and 351.42 %, respectively, compared with those in CK. ③ The application of biochar from R. roxburghii pomace could significantly enhance soil enzyme activity. Compared with those in the CK treatment, soil urease, acid phosphatase, catalase, and sucrase increased by 51.43 %-362.86 %, 90.63 %-134.14 %, 21.40 %-85.12 %, and 82.92 %-218.43 %, respectively. ④ Redundancy analysis showed that soil AK; exchangeable Ca, SOM, and AP; and available Zn were the main factors affecting the yield and quality of Chinese cabbage, and there was a significant positive correlation between them. In summary, the application of R. roxburghii pomace biochar can significantly increase the yield and quality of Chinese cabbage and improve soil properties. The preparation of R. roxburghii pomace into biochar can provide a theoretical reference for the rational utilization of R. roxburghii pomace resources.

Agricultural waste-based modified biochars differentially affected the soil properties, growth, and nutrient accumulation by maize (Zea mays L.) plants.

Biochar (BC) is an organic compound formed by the pyrolysis of organic wastes. Application of BCs as soil amendments has many benefits including carbon sequestration, enhanced soil fertility and sustainable agriculture production. In the present study, we acidified the different BCs prepared from rice straw, rice husk, wheat straw, cotton stalk, poultry manure, sugarcane press mud and vegetable waste; following which, we applied them in a series of pot experiments. Comparisons were made between acidified and non- acidified BCs for their effects on seed germination, soil properties (EC, pH) nutrient contents (P, K, Na) and organic matter. The treatments comprised of a control, and all above-described BCs (acidified as well as non-acidified) applied to soil at the rate of 1% (w/w). The maize crop was selected as a test crop. The results showed that acidified poultry manure BC significantly improved germination percentage, shoot length, and biomass of maize seedlings as compared to other BCs and their respective control plants. However, acidified BCs caused a significant decrease in nutrient contents (P, K, Na) of soil,maize seedlings, and the soil organic matter contents as compared to non- acidified BCs. But when compared with control treatments, all BCs treatments (acidified and non-acidified) delivered higher levels of nutrients and organic matter contents. It was concluded that none of the BCs (acidified and non-acidified) had caused negative effect on soil conditions and growth of maize. In addition, the acidification of BC prior to its application to alkaline soils might had altered soil chemistry and delivered better maize growth. Moving forward, more research is needed to understand the long-term effects of modified BCs on nutrient dynamics in different soils. In addition, the possible effects of BC application timings, application rates, particle size, and crop species have to be evaluated systemtically.

Effects of aeolian deposition on soil properties and microbial carbon metabolism function in farmland of Songnen Plain, China.

The effects of wind erosion, one of the crucial causes of soil desertification in the world, on the terrestrial ecosystem are well known. However, ecosystem responses regarding soil microbial carbon metabolism to sand deposition caused by wind erosion, a crucial driver of biogeochemical cycles, remain largely unclear. In this study, we collected soil samples from typical aeolian deposition farmland in the Songnen Plain of China to evaluate the effects of sand deposition on soil properties, microbial communities, and carbon metabolism function. We also determined the reads number of carbon metabolism-related genes by high-throughput sequencing technologies and evaluated the association between sand deposition and them. The results showed that long-term sand deposition resulted in soil infertile, roughness, and dryness. The impacts of sand deposition on topsoil were more severe than on deep soil. The diversity of soil microbial communities was significantly reduced due to sand deposition. The relative abundances of Nitrobacteraceae, Burkholderiaceae, and Rhodanobacteraceae belonging to α-Proteobacteria significantly decreased, while the relative abundances of Streptomycetaceae and Geodermatophilaceae belonging to Actinobacteria increased. The results of the metagenomic analysis showed that the gene abundances of carbohydrate metabolism and carbohydrate-activity enzyme (GH and CBM) significantly decreased with the increase of sand deposition amount. The changes in soil microbial community structure and carbon metabolism decreased soil carbon emissions and carbon cycling in aeolian deposition farmland, which may be the essential reasons for land degradation in aeolian deposition farmland.

Aridity regulates the impacts of multiple dimensional plant diversity on soil properties in the drylands of northern China.

Relationships between plant diversity and soil properties are important for restoring ecosystem function to adapt climate change in drylands. Taxonomic, functional and phylogenetic diversity are widely used for understanding community assembly and the responses of plant communities to environmental change. However, one dimension of diversity index is difficult to reflect the multiple dimensional plant diversity, and their effects on soil properties (i.e., moisture, nutrients, and texture characteristics) along aridity gradient in drylands are limitedly understood. In this study, we proposed a holistic biodiversity (HB) index to integrate all the characteristics of plant diversity, and investigated the relationships between plant diversity and soil properties across 41 sites along aridity gradient (from hyperarid to arid and semiarid levels) in drylands of northern China. The results showed that the taxonomic diversity and phylogenetic diversity increased significantly while most of functional diversity indices did not differ significantly along the aridity gradient. The functional diversity was more important than taxonomic and phylogenetic diversity to plant communities, and the importance of taxonomic and phylogenetic diversity varied greatly and inversely along the aridity gradient. The HB index could much better reflect the positive or negative exponential relationships with soil properties compared to the single diversity index. Further, the aridity weakened the positive effects of plant diversity on several soil properties (including soil water content, soil organic carbon and soil total nitrogen), and indirectly strengthened the accumulation of soil total phosphorus, as well as intensified the soil coarsening by limiting the negative effects of plant diversity on soil sand content. Our findings suggest that the holistic biodiversity index can represent the overall traits of plant diversity in drylands, and guide a further step to understand the role of plant diversity in plant-soil relationships of dryland ecosystems.

Changes in the Arbuscular Mycorrhizal Fungal Community in the Roots of Eucalyptus grandis Plantations at Different Ages in Southern Jiangxi, China.

Eucalyptus roots form symbiotic relationships with arbuscular mycorrhizal (AM) fungi in soil to enhance adaptation in challenging environments. However, the evolution of the AM fungal community along a chronosequence of eucalypt plantations and its relationship with soil properties remain unclear. In this study, we evaluated the tree growth, soil properties, and root AM fungal colonization of Eucalyptus grandis W. Hill ex Maiden plantations at different ages, identified the AM fungal community composition by high-throughput sequencing, and developed a structural equation model among trees, soil, and AM fungi. Key findings include the following: (1) The total phosphorus (P) and total potassium (K) in the soil underwent an initial reduction followed by a rise with different stand ages. (2) The rate of AM colonization decreased first and then increased. (3) The composition of the AM fungal community changed significantly with different stand ages, but there was no significant change in diversity. (4) Paraglomus and Glomus were the dominant genera, accounting for 70.1% and 21.8% of the relative abundance, respectively. (5) The dominant genera were mainly influenced by soil P, the N content, and bulk density, but the main factors were different with stand ages. The results can provide a reference for fertilizer management and microbial formulation manufacture for eucalyptus plantations.

Optimizing Soil Health and Sorghum Productivity through Crop Rotation with Quinoa.

Crop rotation has been considered a potential solution to mitigate the negative effects of the continuous cropping of sorghum, including soil quality issues, inadequate plant development, and diminished yield and quality. A two-year field experiment was conducted to compare the effects of sorghum-sorghum continuous cropping and quinoa-sorghum rotation on soil properties and sorghum yield. The treatments were arranged in a randomized complete block design with three replicates. Sorghum seeds (Jinza 22) and quinoa seeds ('Jiaqi 1' variety) were used. Soil samples were collected before and during the experiment for the analysis of physicochemical properties. The yield traits of sorghum were measured at maturity. The results showed that soil nutrients and organic matter were higher in the top 0-20 cm soil depth compared to 20-40 cm depth, with significant differences observed between cropping systems. Sorghum-quinoa cropping increased soil total N and organic matter, particularly at the jointing and maturity stages of sorghum. However, the available phosphorus was higher under continuous cropping at all growth stages. Crop rotation significantly improved sorghum yield traits, including spike fresh weight, spike dry weight, grain weight per spike, and grain yield per hectare. A correlation analysis revealed positive relationships between soil total N, organic matter, and sorghum yield. Overall, sorghum-quinoa rotation demonstrated potential for improving soil fertility and enhancing crop productivity compared to continuous cropping, although further studies are needed to explore the long-term effects and optimize management practices.

Mapping Soil Properties in the Haihun River Sub-Watershed, Yangtze River Basin, China, by Integrating Machine Learning and Variable Selection.

Mapping soil properties in sub-watersheds is critical for agricultural productivity, land management, and ecological security. Machine learning has been widely applied to digital soil mapping due to a rapidly increasing number of environmental covariates. However, the inclusion of many environmental covariates in machine learning models leads to the problem of multicollinearity, with poorly understood consequences for prediction performance. Here, we explored the effects of variable selection on the prediction performance of two machine learning models for multiple soil properties in the Haihun River sub-watershed, Jiangxi Province, China. Surface soils (0-20 cm) were collected from a total of 180 sample points in 2022. The optimal covariates were selected from 40 environmental covariates using a recursive feature elimination algorithm. Compared to all-variable models, the random forest (RF) and extreme gradient boosting (XGBoost) models with variable selection improved in prediction accuracy. The R2 values of the RF and XGBoost models increased by 0.34 and 0.47 for the soil organic carbon, by 0.67 and 0.62 for the total phosphorus, and by 0.43 and 0.62 for the available phosphorus, respectively. The models with variable selection presented reduced global uncertainty, and the overall uncertainty of the RF model was lower than that of the XGBoost model. The soil properties showed high spatial heterogeneity based on the models with variable selection. Remote sensing covariates (particularly principal component 2) were the major factors controlling the distribution of the soil organic carbon. Human activity covariates (mainly land use) and organism covariates (mainly potential evapotranspiration) played a predominant role in driving the distribution of the soil total and soil available phosphorus, respectively. This study indicates the importance of variable selection for predicting multiple soil properties and mapping their spatial distribution in sub-watersheds.

[Meta-analysis of plant restoration impacts on soil microbial community structure in mining areas]. / 植被恢复对矿区土壤微生物群落结构影响的整合分析.

Mining causes severe damage to soil ecosystems. Vegetation restoration in abandoned mine areas is an inevitable requirement for sustainable development. Soil microbes, as the most active component of soil organic matter, play a crucial role in the transformation of carbon, nitrogen, phosphorus, and other elements. They are often used as indicators to assess the extent of vegetation restoration in ecologically fragile areas. However, the impacts of vegetation restoration on soil microbial community structure in mining areas at the global scale remains largely unknown. Based on 310 paired observations from 44 papers, we employed the meta-analysis approach to examine the influence of vegetation restoration on soil microbial abundance and biomass in mining area. The results indicated that vegetation restoration significantly promotes soil microbial biomass in mining areas. In comparison to bare soil, vegetation restoration leads to a significant 95.1% increase in soil microbial biomass carbon and a 87.8% increase in soil microbial biomass nitrogen. The abundance of soil bacteria, fungi, and actinomycetes are significantly increased by 1005.4%, 472.4%, and 177.7%, respectively. Among various vegetation restoration types, the exclusive plan-ting of trees exhibits the most pronounced promotion effect on soil microbial biomass and population, which results in a significant increase of 540.3% in soil fungi and 104.5% in actinomycetes, along with a respective enhancement of 110.3% and 106.4% in microbial biomass carbon and nitrogen. Model selection results revealed that soil satura-ted water content and vegetation restoration history contribute most significantly to the abundance of soil bacteria and fungi. Soil available nitrogen has the most significant impact on the abundance of actinomycetes and microbial biomass carbon, while soil available phosphorus emerges as a crucial factor affecting microbial biomass nitrogen. This research could contribute to understanding the relationship between vegetation restoration and the structure of soil microbial communities in mining areas, and providing scientific support for determining appropriate vegetation restoration types in mining areas.

The mechanism of using magnetized-ionized water in combination with organic fertilizer to enhance soil health and cotton yield.

Addressing critical challenges in sustainable agriculture, notably water scarcity and soil degradation, necessitates innovative irrigation and fertilization methods. This investigation thoroughly assessed the effects of combining inorganic and organic fertilizers under brackish water irrigation, particularly focusing on magnetized-ionized brackish water-a promising solution for these challenges. The study shows that the integration of inorganic and organic fertilizers notably enhances soil water retention and salt leaching when applied with magnetized-ionized brackish water irrigation (MIBIO treatment), with water storage rate and salt accumulation rate observed at -0.454 and -0.075, respectively. Additionally, soil microbial diversity and uniformity witnessed significant improvement, positively influencing cotton growth rates, particularly noting a dry matter accumulation rate of 9.3262 kg·(ha·°C)-1. Transcriptomic analysis revealed that the MIBIO treatment elevated gene expression during the boll period, with notable enrichment in pathways such as the MAPK signaling pathway-plant and amino sugar and nucleotide sugar metabolism. Furthermore, the partial least squares path modeling indicated that soil alkali-hydrolyzed nitrogen (AN) and available potassium (AK) positively impact cotton leaf transcription and yield, with path coefficients of 0.613 and 0.428, respectively. Specifically, AN and AK contribute to enhancing cotton growth and affect the expression of metabolism genes in cotton leaves, thereby increasing cotton yield. Our study highlights the crucial role of irrigation and fertilization in influencing the soil environment and cotton growth. We recommend the use of magnetized-ionized water irrigation in combination with organic fertilizers as a strategy to boost agricultural productivity. Through the development of these strategies, our goal is to offer farmers practical guidance that can be readily implemented to enhance crop production efficiency, reduce environmental impact, and adhere to the principles of sustainable agriculture.

Fires in the face of climate change: Indicators of fire disturbance in heath areas - Inference from military training lands.

Global warming significantly affects the frequency and intensity of wildfires in many fire-prone areas of the world and fire disturbance regimes are changing rapidly. Alongside this, controlled burning is often considered or implemented as an alternative method for nature protection. Here, we studied the post-fire secondary succession in dry heath habitat located in military training grounds to recognise the impact of fire on the effectiveness and rate of ecosystem recovery. We focus particularly on identifying indicator species for a given successional phase of Central European dry heath habitats and assessing their value for dating the last fire disturbance. The research involved 60 vegetation patches (plots of 25 m2), which were assigned to four post-fire age classes, namely: 1-5 years (Class A), 6-10 years (Class B), 11-15 years (Class C), and >15 years (Class D). In each study plot, species diversity and coverage of lichens, bryophytes and vascular plants were examined in addition to the physicochemical properties of the soil substrate. Cryptogams and vascular plants clearly differ in terms of the secondary succession pattern; specific sets of cryptogams correspond well to particular post-fire classes and are therefore good determinants of the post-fire succession stage. Spontaneous succession of plant vegetation eventually leads to complete recovery of the heath in a relatively short time. Nevertheless, great vegetation dynamics in the first years after a fire disturbance may result in seemingly different directions of succession. Post-fire classes did not differ noticeably in terms of soil properties, it follows that the effects of fire on soil conditions are negligible; though, a significant upward trend was observed for exchangeable form of K throughout the succession process. Our results indicate that sporadic fires reduce the undesirable overgrowth of heathlands or psamophilous grasslands and generally have a little negative side-effect on the ecosystem. The revealed succession patterns and defined sets of species characteristic for subsequent post-fire age classes are applicable to dating fire disturbances, regardless of whether the fire was planned or spontaneous.

Positive role of plateau pika (Ochotona coronae) on environmental quality at low and moderate density on the Tibetan plateau: Evidence from a meta-analysis.

The roles of plateau pika (Ochotona coronae) in the Tibetan Plateau are often controversial, because it is often regarded as a destructive pest or an ecosystem engineer. Here a meta-analysis using 72 paired observations was conducted to examine whether the impacts of plateau pika on environmental quality (i.e., plant and soil properties) depend on population density in the Tibetan Plateau. Pika population density was used as a proxy for disturbance intensity. The pika disturbance intensity was divided into five groups based on the number of burrows, including low disturbance intensity (LD) (9-30 burrows per ha), medium disturbance intensity (MD) (31-100 burrows per ha), high disturbance intensity (HD) (101-170 burrows per ha), extreme disturbance intensity (ED) (171-240 burrows per ha) and uncontrolled (or excessive) disturbance intensity (UD) (>241 burrows per ha). Given that sample sizes in some of the groups are small (especially for the HD), we further pooled the disturbance groups including the LD-MD and HD-UD. Overall, relative to control (i.e., no disturbing), there was a great increase (80.3%) in aboveground biomass under the LD-MD, whereas a decrease of 41.1% occurred under the HD-UD. At the same time, plant coverage, species richness, height, and belowground biomass greatly decreased only in the HD-UD. Furthermore, the effect size of plant coverage, species richness, and aboveground biomass also declined with pika burrow density significantly. With regard to soil properties, there was a significant increase in soil organic carbon, ammonium nitrogen, and soil organic carbon stock under the LD-MD, whereas a decrease under the HD-UD. In addition, soil total nitrogen, total potassium, and nitrate nitrogen increased at the LD-MD and HD-UD. Nevertheless, the effect size of these soil properties (with >20 observations) was not related to pika burrow density. In summary, there is an implication that the low and moderate disturbance of pikas is beneficial to maintain and promote ecosystem functioning in the Tibetan grasslands. In the future pikas' eradication policy should be reconsidered in alpine grassland management.

Soil Microbial Community Characteristics and Their Effect on Tea Quality under Different Fertilization Treatments in Two Tea Plantations.

Fertilization is an essential aspect of tea plantation management that supports a sustainable tea production and drastically influences soil microbial communities. However, few research studies have focused on the differences of microbial communities and the variation in tea quality in response to different fertilization treatments. In this work, the soil fertility, tea quality, and soil microbial communities were investigated in two domestic tea plantations following the application of chemical and organic fertilizers. We determined the content of mineral elements in the soil, including nitrogen, phosphorus, and potassium, and found that the supplementation of chemical fertilizer directly increased the content of mineral elements. However, the application of organic fertilizer significantly improved the accumulation of tea polyphenols and reduced the content of caffeine. Furthermore, amplicon sequencing results showed that the different ways of applying fertilizer have limited effect on the alpha diversity of the microbial community in the soil while the beta diversity was remarkably influenced. This work also suggests that the bacterial community structure and abundance were also relatively constant while the fungal community structure and abundance were dramatically influenced; for example, Chaetomiaceae at the family level, Hypocreaceae at the order level, Trichoderma at the genus level, and Fusarium oxysporum at the species level were predominantly enriched in the tea plantation applying organic fertilizer. Moreover, the bacterial and fungal biomarkers were also analyzed and it was found that Proteobacteria and Gammaproteobacteria (bacteria) and Tremellomycetes (fungi) were potentially characterized as biomarkers in the plantation under organic fertilization. These results provide a valuable basis for the application of organic fertilizer to improve the soil of tea plantations in the future.

Development and application of machine learning models for prediction of soil available cadmium based on soil properties and climate features.

Identifying the key influencing factors in soil available cadmium (Cd) is crucial for preventing the Cd accumulation in the food chain. However, current experimental methods and traditional prediction models for assessing available Cd are time-consuming and ineffective. In this study, machine learning (ML) models were developed to investigate the intricate interactions among soil properties, climate features, and available Cd, aiming to identify the key influencing factors. The optimal model was obtained through a combination of stratified sampling, Bayesian optimization, and 10-fold cross-validation. It was further explained through the utilization of permutation feature importance, 2D partial dependence plot, and 3D interaction plot. The findings revealed that pH, surface pressure, sensible heat net flux and organic matter content significantly influenced the Cd accumulation in the soil. By utilizing historical soil surveys and climate change data from China, this study predicted the spatial distribution trend of available Cd in the Chinese region, highlighting the primary areas with heightened Cd activity. These areas were primarily located in the eastern, southern, central, and northeastern China. This study introduces a novel methodology for comprehending the process of available Cd accumulation in soil. Furthermore, it provides recommendations and directions for the remediation and control of soil Cd pollution.