Search Results (49,144)

Populus euphratica is a key community-building species in the desert riparian forests of Northwest China, exhibiting exceptional resistance to stress and playing a vital role in soil and water conservation as well as maintaining ecological balance in arid regions. To investigate the ecological processes underlying the composition of P. euphratica communities and to identify their community construction mechanisms, this study analyses the species diversity and phylogenetic diversity of 58 P. euphratica communities, exploring their assembly processes and key influencing factors. This research aims to elucidate the relationship between community structure from the perspective of species evolution and analyse the construction mechanisms of P. euphratica communities across different clusters in arid environments. The results show that the species diversity of P. euphratica clusters in Northwest China is relatively low, and a significant correlation is noted with phylogenetic diversity (PD). The Shannon–Wiener and Margalef indices exhibit similar trends, whereas Simpson’s index show the opposite trends. Pielou’s index range from 0.7 to 0.85. Notably, the PD and species diversity of the P. euphratica–Haloxylon ammodendron association group (Group 4) is significantly higher (p < 0.05) compared to that of the other groups. Additionally, net relatedness index (NRI) and nearest taxon index (NTI) peaked in the P. euphratica–H. ammodendron association group (Group 4) and the Populus pruinosa–Tamarix ramosissima–Phragmites australis association group (Group 1) (p < 0.05). A Pearson correlation analysis indicated that PD was significantly positively correlated with Margalef’s index, Shannon–Wiener’s index, and Pielou’s index, but was significantly negatively correlated with Simpson’s index, while also being associated with environmental factors. Key factors influencing the diversity of P. euphratica communities in Northwest China include total phosphorus, pH, soil moisture content, total potassium, the mean temperature of the coldest quarter, precipitation of the wettest month, and precipitation seasonality. Soil factors primarily affected the Pielou and Simpson indices of species diversity, whereas climatic factors mainly influenced the Margalef and Shannon–Wiener indices. PD and structure were mainly influenced by climatic factors. The combined effects of soil and climatic factors play a crucial role in sustaining the diversity and ecological adaptation of these plant communities. In summary, P. euphratica communities may exhibit a significant ecological niche conservation in response to environmental changes, and competitive exclusion might be the primary process shaping community structure. Climatic factors were shown to be important regulators of community diversity and phylogenetic structure. Full article

Straw returning into the soil is a crucial method for boosting soil carbon levels. To research the influence of straw return practices on soil aggregates and organic matter content within the farmlands of the Northeast Black Soil Region, the objective was to clarify the varying impacts of these practices on soil carbon enhancement. In this study, 89 pertinent papers were acquired through a rigorous literature compilation. Meta-analysis and the linear regression method were employed to analyze the influence of field return methods, their duration on soil water-stable aggregates, and their organic matter content. Furthermore, the study delved into the trends in the variation of aggregates and organic matter in relation to mean annual temperature and precipitation. Our results showed that the straw-returning method has been discovered to predominantly bolster soil organic matter by altering the proportions of macro-aggregate content. Specifically, straw incorporation has led to a notable enhancement in the content of macro-aggregates (57.14%) and micro-aggregates (20.29%), in addition to augmenting the content of macro-, small, and micro-aggregate organic matter by 13.22%, 16.43%, and 15.08%, respectively. The most significant increase in large agglomerates was witnessed in straw return over a period of more than 5 years (115.17%), as well as shallow mixing return (87.32%). Meanwhile, the highest increase in the organic matter content of large agglomerates was recorded in straw return over 5 years (12.60%) and deep mixing return (8.72%). In the field validation experiment, a period of seven years of straw return significantly boosted the macro-aggregate content across various soil layers, ranging from 11.78% to 116.21%. Furthermore, among the various climatic factors, the primary determinants of disparities in study outcomes were the average annual temperature and average annual precipitation. Specifically, lower precipitation and higher temperatures were conducive to the enhancement of macro-aggregate formation and organic matter content. Full article

Ecological importance evaluation can clearly identify the ecological service functions and ecological values of a region. This paper takes the Yanshan-Taihang Mountain area in Hebei Province as the research area, utilizing 2020 land use data. With the help of various analytical models and GIS spatial analysis methods, this paper selects water conservation, soil and water conservation, biodiversity, carbon sequestration and oxygen release to evaluate the importance of ecosystem services, and selects soil and water loss sensitivity and land desertification sensitivity to evaluate the ecological sensitivity, so as to identify the important areas of ecological protection in the study area, analyze their spatial change characteristics and divide the leading ecological functions according to the results. The results show that the moderately important and highly important areas in the Yanshan-Taihang region of Hebei Province account for more than 70% of the total study area. Based on the importance evaluation results, three types of dominant ecological function zones were obtained using self-organized feature mapping neural network analysis in the R language, and control measures were proposed. The research results can provide strategic support for local ecological protection and regional ecological restoration, as well as serving as a reference for the optimization of land spatial development patterns. Full article

Soil health is essential for sustainable agricultural operations, as it supports farm production and ecosystem services. The adoption of sustainable agriculture practices such as conservation tillage, cover cropping, and crop rotation provides significant benefits for both crop productivity and environmental sustainability. These practices can increase soil biodiversity, nutrient cycling, and organic matter, which increase the resilience of agroecosystems. This narrative review synthesizes the insights of the soil health practices adoption literature, with a focus on common farming practices that can improve soil health and enhance crop yields, reviewing the results of various approaches and pointing out the challenges and opportunities for implementing sustainable agriculture on a larger scale. This paper discusses the effects of various tillage and cropping system approaches on soil health, including no-till and conventional tillage systems, crop rotation, cover cropping, cultivator combinations, and fertilizer application. This study found that conservation tillage is more beneficial to soil health than conventional tillage—which is still debated among scientists and farmers—and that different tillage methods interact differently. In contrast, agricultural yields increase more with intercropping, crop rotation, and cover crops than monocropping. For maintaining soil fertility, this study shows that agricultural yields could be increased by implementing zero tillage. This review identifies the most suitable farming practices for improving soil health while boosting crop production with minimal negative impact on the soil. It also highlights the benefits of these practices in maintaining soil quality. Full article

Soil moisture (SM) is a crucial factor in land-atmosphere interactions and climate systems, affecting surface energy, water budgets, and weather extremes. In the Three-River-Source Region (TRSR) of China, rapid climate change necessitates precise SM monitoring. This study employs a novel UNet-Gan model to integrate and downscale SM data from 17 CMIP6 models, producing a high-resolution (0.1°) dataset called CMIP6_UNet-Gan. This dataset includes SM data for five depth layers (0–10 cm, 10–30 cm, 30–50 cm, 50–80 cm, 80–110 cm), four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). The UNet-Gan model demonstrates strong performance in data fusion and downscaling, especially in shallow soil layers. Analysis of the CMIP6_UNet-Gan dataset reveals an overall increasing trend in SM across all layers, with higher rates under more intense emission scenarios. Spatially, moisture increases vary, with significant trends in the western Yangtze and northeastern Yellow River regions. Deeper soils show a slower response to climate change, and seasonal variations indicate that moisture increases are most pronounced in spring and winter, followed by autumn, with the least increase observed in summer. Future projections suggest higher moisture increase rates in the early and late 21st century compared to the mid-century. By the end of this century (2071–2100), compared to the Historical period (1995–2014), the increase in SM across the five depth layers ranges from: 5.5% to 11.5%, 4.6% to 9.2%, 4.3% to 7.5%, 4.5% to 7.5%, and 3.3% to 6.5%, respectively. Full article

The underground plastic vertical drains (PVDs) are a significant problem for shield machines in tunneling construction. At present, the main method to deal with PVDs is to manually adjust the parameters of the shield machine. To ensure that a shield machine autonomously recognizes and adjusts the control in soil layers containing PVDs, this study constructs a shield machine advance and rotation state-space model utilizing Bayesian decision theory for the judgment of excavation conditions. A Bayesian model predictive control (Bayes-MPC) method for the shield machine is proposed, followed by a simulation analysis. Finally, a validation experiment is conducted based on a Singapore subway project. Compared with traditional methods, the method proposed in this paper has better performance in the simulation, and it also has demonstrated effectiveness and accuracy in experiments. The research outcomes can provide a reference for the adaptive assistance system of shield machines excavating underground obstacles. Full article

In the global context of biodiversity and ecosystem services loss, the integration of agriculture with ecological restoration is crucial.. This study presents the biodiversity value (Bv) index for the first time as a tool for decision-making and securing funding for future restoration projects. The Bv index was used to assess biodiversity values in both restored natural habitats and agricultural areas in the saline lagoon of El Hito, a natural reserve located within an agricultural landscape in central Spain. Additionally, we estimated biodiversity gains from habitat transitions and explored the relationship between biodiversity, soil pH, and salinity. Sustainable agricultural practices, combined with ecological restoration methods, can lead to synergistic actions that reduce the potential detrimental effects of agriculture. Our results show that transitioning from agricultural to natural habitats consistently increases biodiversity. Among agricultural practices, multiannual vegetated fallows had the highest Bv values. Restoration led to a continuous biodiversity improvement, with the exception of the final transition from permanent pastures to Elymus 1410, which showed a slight decline in biodiversity. We also found that higher soil salinity and pH were associated with greater biodiversity values, likely due to historical agricultural practices that favored areas with lower salinity and pH for higher productivity. Salinity and pH act as limiting factors for biodiversity; therefore, agricultural plots with lower salinity and pH, particularly those adjacent to natural habitats, are expected to yield greater biodiversity gains if restored. Full article

Pokkah Boeng disease has been observed in nearly all countries where sugarcane is commercially cultivated. The disease was considered a minor concern in earlier times, but due to climate change, it has now become a major issue. It is caused by fungi, specifically the Fusarium fungal complex. Fusarium fujikuroi, F. sacchari, F. oxysporum, F. verticillioides, F. proliferatum, and F. subglutinans are the major species causing the disease in sugarcane. The disease spreads rapidly, and unpredictable environmental conditions, along with the overlap of crop stages with biotic factors, contributed to its increased severity and varied symptom patterns. This disease is primarily airborne, spreading through air currents. Secondary transmission occurs via infected setts, irrigation water, splashed rain, and soil. It typically emerges during hot and humid conditions, particularly when the sugarcane is experiencing rapid growth. The most effective way to control Pokkah Boeng is by cultivating resistant varieties and removing canes exhibiting ‘top rot’ or ‘knife cut’ symptoms. Apply 0.1% carbendazim, 0.2% copper oxychloride, or 0.3% mancozeb for two to three sprayings at 15-day intervals. Using biological methods to control plant pathogens presents a promising alternative to the heavy reliance on chemical fungicides in modern agriculture, which can lead to environmental pollution and the development of resistant strains. Full article

Soil loss due to wind erosion and dust deposition has become a growing concern, particularly in arid regions like Al-Baha, Saudi Arabia. The aim of this study was to quantitatively assess soil loss and dust deposition using three different dust collection methods across 20 sites during the summer of 2022. The methods include Big Spring Number Eight (BSNE), which measures airborne dust particles using passive samplers; Surface Dust Collector (SDC), designed to collect dust settling on the ground surface; and Marble Dust Collector (MDCO), which utilizes marble-coated surfaces to trap and measure dust deposition. These methods collectively provide a comprehensive evaluation of dust dynamics in the study area. The objective was to evaluate the effects of wind erosion and dust deposition on soil properties, offering insights into the mechanisms of soil loss in arid environments. The study revealed significant variations in soil characteristics, including low organic matter content (<1%), high calcite (up to 19.62%), and increased salinity levels, with notable quantities of Cl⁻ (211.58 meq kg⁻¹) and Na^⁺ (165.98 meq kg⁻¹). July showed the highest dust deposition (0.0133 ton ha⁻¹), particularly at site S11, while soil loss was lowest at site S5. This research offers novel insights into the nonlinear relationship between soil loss and time, contributing to sustainable soil management strategies. By aligning with Saudi Arabia’s Vision 2030 and the Sustainable Development Goals (SDGs), the findings underscore the need to mitigate soil loss to enhance environmental sustainability, prevent desertification, and promote long-term resilience in arid regions. Full article

High-resolution images captured by Unmanned Aerial Vehicles (UAVs) play a vital role in precision agriculture, particularly in evaluating crop health and detecting weeds. However, the detailed pixel information in these images makes classification a time-consuming and resource-intensive process. Despite these challenges, UAV imagery is increasingly utilized for various agricultural classification tasks. This study introduces an automatic classification method designed to streamline the process, specifically targeting cassava plants, weeds, and soil classification. The approach combines K-means unsupervised classification with spectral trend-based labeling, significantly reducing the need for manual intervention. The method ensures reliable and accurate classification results by leveraging color indices derived from RGB data and applying mean-shift filtering parameters. Key findings reveal that the combination of the blue (B) channel, Visible Atmospherically Resistant Index (VARI), and color index (CI) with filtering parameters, including a spatial radius (sp) = 5 and a color radius (sr) = 10, effectively differentiates soil from vegetation. Notably, using the green (G) channel, excess red (ExR), and excess green (ExG) with filtering parameters (sp = 10, sr = 20) successfully distinguishes cassava from weeds. The classification maps generated by this method achieved high kappa coefficients of 0.96, with accuracy levels comparable to supervised methods like Random Forest classification. This technique offers significant reductions in processing time compared to traditional methods and does not require training data, making it adaptable to different cassava fields captured by various UAV-mounted optical sensors. Ultimately, the proposed classification process minimizes manual intervention by incorporating efficient pre-processing steps into the classification workflow, making it a valuable tool for precision agriculture. Full article

The aim of the present research was the efficient degradation of industrial textile wastewater dyes using a very active cloned laccase enzyme. For this purpose, potent laccase-producing bacteria were isolated from soil samples collected from wastewater-replenished textile sites in Punjab, Pakistan. The laccase gene from locally isolated strain LI-81, identified as Bacillus megaterium, was cloned into vector pET21a, which was further transformed into E. coli BL21 codon plus. The optimized conditions for the increased production of laccase include fermentation in a 2% glucose, 5% yeast extract and 250 mg/L CuSO₄ medium with pH 7.5; inoculation with 5% inoculum; induction with 0.1 mM IPTG at 0.5 O.D.; and incubation for 36 h at 37 °C. The crude enzyme produced was employed for the removal of commercially used textile dyes. The dyes were quickly precipitated under optimized reaction conditions. Rose bengal, brilliant green, brilliant blue G, Coomassie brilliant blue R and methylene blue were precipitated at rates of 10.69, 54.47, 84.04, 78.99 and 7.40%, respectively. The FTIR and UV–Vis spectroscopic analyses of dyes before and after confirmed the chemical changes brought about by the cloned laccase that led to the dye removal. Full article

Microplastics have become a ubiquitous pollutant that permeates every aspect of our environment—from the oceans to the soil to the elementary foundations of human life. New findings demonstrate that microplastic particles not only pose a latent threat to adult populations, but also play a serious role even before birth during the fetal stages of human development. Exposure to microplastics during the early childhood stages is another source of risk that is almost impossible to prevent. This comprehensive review examines the multiple aspects associated with microplastics during early human development, detailing the mechanisms by which these particles enter the adult body, their bioaccumulation in tissues throughout life and the inevitable re-entry of these particles into different ecosystems after death. Full article

Numerous factors, such as soil fertility, climatic conditions, human activity, pests, and diseases, limit agricultural yields. Pesticides and fertilizers have become indispensable tools to satisfy the global food demand. However, its adverse environmental effects have led to the search for more sustainable and ethical techniques. Biofertilizers and biopesticides based on plant- growth-promoting rhizobacteria (PGPRs) are efficient and ecological treatments that promote plant growth and protection against pathogens and abiotic stresses. In this study, twelve rhizobacterial strains with plant-growth-promoting attributes were selected to evaluate their plant-growth-promoting effect on tomato plants (Solanum lycopersicum L. var Robin). Soil inoculation with these strains resulted in a significant increase in shoot length, up to 50% when compared with control plants. Regarding fresh biomass, rhizobacterial treatments significantly improved seedlings’ fresh aerial weight with a maximum increase of 77%. Root biomass also demonstrated a substantial improvement, yielding 62.26% greater fresh root weight compared to the control. Finally, dry root weights exhibited the most remarkable enhancements, with values between 49 and 124%, when compared to the control plants. Concerning the nutritional status, the strains inoculation increased the macronutrients and micronutrients content in the aerial and root parts of the plants. All these findings suggest that rhizobacteria from different ecosystems and agriculture soils of the Canary Islands could be used as fertilizer inoculants to increase crop yield and promote more sustainable practices in modern agriculture. Full article

Understory terrain plays a multi-faceted role in ecosystems, biodiversity, and productivity in forests by influencing different major factors, such as hydrological processes, soils, climate, and light conditions. Strong illuminants (e.g., sunlight) from ground surfaces and atmosphere can introduce additional photons into the ATLAS system. These photons can, consequently, be mistakenly identified as laser photons reflected from ground surfaces. The presence of such ambient light, particularly under low-photon-count conditions, can significantly increase elevation measurement errors. In this context, this study aims to propose a method for extracting reliable understory elevation control points under varying forest conditions, based on the parameter attributes of ICESat-2/ATLAS data. The overall filtered data resulted in a coefficient of determination (R²), root mean square error (RMSE), and standard deviation (STD) of 0.99, 2.77 m, and 2.42 m, respectively. The greatest accuracy improvement was found in the Puerto Rico study area, showing decreases in the RMSE and STD values by 2.68 and 2.67 m, respectively. On the other hand, canopy heights and slopes exhibited relatively large impacts on noise interferences. In addition, there were decreases in the RMSE and STD values by 4.57 and 4.64 m, respectively, under the very tall canopy category, whereas under steep slope conditions, the RMSE and STD values of the filtering results decreased by 4.59 and 4.34 m, respectively. The proposed method can enhance the overall accuracy of elevation data, allowing for the significant extraction of understory elevation control points, ultimately optimizing forest management practices and improving ecological assessments. Full article

There are many examples in nature in which the ability to detect is combined with decision-making, such as the basic survival instinct of plants and animals to search for food. We can technically translate this innate function via the use of robotics with integrated sensors and artificial intelligence. However, the integration of sensing capabilities into robotics has traditionally been neglected due to the significant associated technical challenges. Inspired by plant-root chemotropism, we present a miniaturized electrochemical array integrated into a robotic tip, embedding a customized micro-potentiometer. The system contains solid-state sensors fitted to the tip of the robotic root to three-dimensionally monitor potassium and pH changes in a moist, soil-like environment, providing an integrated electronic readout. The sensors measure a range of parameters compatible with realistic soil conditions. The sensors’ response can trigger the movement of the robotic root with a control algorithm inspired by the behavior of the plant root that determines the optimal path toward root growth, simulating the decision-making process of a plant. This nature-inspired technology may lead, in the future, to the realization of robotic devices with the potential for monitoring and exploring the soil autonomously. Full article