Search Results (220)

The vertical migration of soil nitrogen (N) losses in sloped farmlands under natural rainfall conditions remains inadequately understood. This study conducted a two-year (March 2023–February 2025) in situ runoff field monitoring experiment on purple loam slopes in Chongqing, China, systematically investigating the effects of different rainfall patterns (TR, HR, MR, LR) and planting stages (CPS, SFS, MPS, WFS) on the vertical migration of nitrogen at four depths (0, 20, 40, and 60 cm) under natural rainfall conditions. The results demonstrate that rainfall is the key driver of vertical nitrogen migration. The migration loads of total nitrogen (TN), total dissolved nitrogen (TDN), and nitrate nitrogen (NO₃⁻-N) all increased significantly with increasing rainfall intensity (p < 0.01), showing the strongest correlation with rainfall amount in the shallow soil layer (L₁). Nitrogen migration loads exhibited a clear decreasing trend with increasing soil depth, declining progressively from the surface (L₁) to deeper layers (L₃). However, higher loads of nitrate nitrogen were maintained in deeper layers, given its strong mobility. The study found that although extreme rainfall events (TR and HR) accounted for only 6.05% of total rainfall events, they contributed to more than 60% of the total nitrogen migration load, highlighting extreme rainfall as the primary driver of nutrient loss. Over 70% of nitrogen loss occurred during the corn planting stage (CPS) with high fertilizer demand, highlighting that this period is critical for nitrogen loss and represents a key window for risk management. The increased soil depth functions as a “sink”, exhibiting certain nitrogen retention and filtration effects. The total nitrogen content in deeper soil layers (L₂, L₃) shows cumulative accumulation, confirming the nitrogen migration pattern from sources (surface layers) to sinks (deep layers) within the soil profile. This study elucidates the core driving mechanisms and critical risk periods for vertical nitrogen migration in purple soil on sloped farmland, providing crucial scientific evidence for precise regional nitrogen fertilizer management and non-point source pollution control. Full article

Tropical forests of the Amazon support exceptional biodiversity while sustaining the livelihoods, cultures, and food systems of Indigenous communities. In Loreto, Peru, hunting remains central to both subsistence and market economies, yet its sustainability depends on ecological dynamics and sociocultural systems that shape harvest behavior. Here, we evaluate the potential for sustainable wildlife management in the Maijuna–Kichwa Regional Conservation Area (MKRCA) by integrating a spatially explicit biodemographic model of hunting with a targeted review of Maijuna hunting practices, governance, and economic context. Using participatory mapping data from 19 hunters in the community of Sucusari, we parameterized a model to estimate species-specific depletion under current and projected hunting scenarios. Model results suggest that current harvest rates are largely sustainable, with localized depletion near settlements but relatively intact populations across the broader landscape, supported by access to remote hunting areas and nearby source populations. The literature review reveals that Maijuna sociocultural systems, including territorial hunting norms, seasonal mobility, food-sharing practices, and species-specific taboos, may function as informal management institutions that distribute hunting pressure and limit overexploitation. Together, these findings suggest that both ecological conditions and sociocultural institutions in Sucusari are conducive to sustainable wildlife management if supported by adaptive co-management approaches. However, external pressures, particularly a proposed highway, may fragment existing source–sink dynamics and pose a significant risk to long-term sustainability. Full article

The excavation of deep shafts using Vertical Shaft Sinking Machine (VSM) technology in stratified soft soils involves complex soil-structure interaction (SSI) mechanisms that are often oversimplified by conventional numerical approaches. This study develops a robust three-dimensional numerical framework to investigate ground deformation induced by VSM operations, explicitly incorporating the phased construction sequence, segmental lining installation, and site-specific stratigraphy. The model is calibrated and validated against high-resolution field monitoring data, employing a prediction envelope approach and statistical performance metrics (RMSE and $R^2$). The results suggest that ground response during VSM excavation is predominantly stiffness-controlled under the investigated conditions. Mobilized shear stresses remain significantly below the available soil capacity, indicating that deformation under serviceability conditions is driven by progressive strain accumulation. Horizontal displacement profiles suggest a relatively stable depth of influence, indicating that the excavation process amplifies deformations within a pre-established domain without significant deep-seated propagation. Sensitivity analyses indicate soil stiffness modules ($E_{50},E_{oed},E_{ur})$ and the SSI interface factor ($R_{inter}$) as the primary drivers of deformation magnitude. Furthermore, stratigraphic contrasts specifically clay-sand sequences, act as a mechanical filter, concentrating strains in soft layers while limiting vertical propagation through stiffer strata. The proposed framework provides a mechanically coherent basis for serviceability-oriented design, deformation prediction, and risk-mitigation strategies for mechanized shafts in saturated soft ground. Full article

Soils are increasingly affected by microplastic (MP) contamination, mainly coming from industrial activities, agricultural practices, atmospheric or waterborne transport, and improper waste disposal. Despite the increasing attention to the fate of MPs in soil over the last few years, research in this area is still limited compared to aquatic ecosystems. The introduction of MPs into the soil environment can modify not only the soil properties but also the interactions among soil components, plants, and microorganisms, thus affecting the mobility and availability of other contaminants, such as potentially toxic elements (PTEs). This review critically examines the complex dynamics between MPs and PTEs in the soil ecosystem, with a focus on the conditions under which MPs can act as a source or a sink of PTEs. Indeed, on the one hand, MPs can adsorb or complex PTEs on their surfaces (similarly to natural soil colloids), thus reducing their mobility and availability; on the other hand, they can release/mobilize PTEs after MP degradation or act as micro-/nano-vectors of PTEs. Understanding such mechanisms is relevant when evaluating the environmental risks associated with the co-presence of MPs and PTEs in soil, a situation likely to occur in most contaminated sites and in many agricultural soils. Full article

Underwater Wireless Sensor Networks (UWSNs) play a vital role in ocean monitoring and exploration. However, harsh underwater conditions and frequent topology changes caused by node and sink mobility pose significant challenges for reliable routing. Conventional routing protocols that depend on global route reconstruction and static paths generate excessive control overhead and degrade performance in large-scale underwater environments. In this paper, we propose an energy-efficient virtual cell-based mobile-sink adaptive routing (VC-MAR) protocol for UWSNs. The sensing field is logically partitioned into a three-dimensional grid of virtual cells, where a cell-gateway is elected in each cell to construct a low-overhead routing backbone. To support sink mobility, VC-MAR introduces a localized route-adjustment mechanism that updates only the affected backbone segments rather than reconstructing the entire routing structure. By confining routing updates to neighboring cells influenced by sink movement, the proposed protocol significantly reduces control packet exchanges while ensuring stable and reliable data delivery. Simulation results show that the proposed VC-MAR improves the packet delivery ratio by up to 20% and reduces routing control overhead by about 34% compared with traditional grid-based routing methods. These results confirm the suitability of VC-MAR for dynamic and realistic underwater sensing scenarios. Full article

Wireless Sensor Networks (WSNs) enable energy-efficient data collection in dynamic environments but continue to face the dual challenges of severely constrained node energy and the spatiotemporal heterogeneity of data traffic. Inspired by honeybee foraging behavior, this paper proposes a hybrid optimization framework that integrates mixed-integer linear programming (MILP) and Markov decision processes (MDP), utilizing Q-learning for adaptive decision-making. The proposed framework systematically maps the dual-layer decision-making mechanism of honeybee foraging onto a synergistic architecture combining MILP-based global planning and MDP-based local adaptation, offering a novel bio-inspired solution for mobile sink trajectory planning and adaptive routing. Specifically, the upper-level MILP module simulates a colony-level global assessment of distant nectar sources, generating an initial global trajectory by determining the optimal access sequence of cluster heads to minimize the movement cost of the mobile sink. The lower-level Q-learning module simulates the individual-level local adaptation, where bees adjust harvesting behavior in real-time based on nectar quality and distance. This module continuously optimizes routing parameters based on real-time network states, including residual energy, the ratio of surviving nodes, data queue lengths, and cluster head density. The algorithm employs an $ϵ$-greedy strategy to balance exploration and exploitation, while a periodic decision-update mechanism is introduced to harmonize computational efficiency with learning stability. Furthermore, a multi-objective reward function is designed to jointly optimize energy efficiency, network lifetime, end-to-end latency, and path length. Extensive simulation results demonstrate that the proposed MILP-MDP hybrid framework significantly outperforms several representative baseline algorithms in terms of network lifetime extension and energy balance. These findings validate that the integration of bio-inspired foraging strategies and reinforcement learning provides an efficient and robust solution for trajectory planning and adaptive routing in dynamic WSNs. Full article

Anthropogenic polymers have become an increasingly important class of emerging contaminants in terrestrial ecosystems. While extensive research has focused on microplastics in aquatic environments, their interactions with soil systems and particularly with soil organic matter (SOM) remain insufficiently understood. Soil represents a major environmental sink for polymer residues originating from agricultural practices, urban activities, and atmospheric deposition. Accordingly, associations between polymers and SOM, including humic substances, may significantly influence the retention, mobility, and transformation of carbon in soil systems. This review synthesizes current knowledge on the influence of synthetic polymers on soil organic matter dynamics. A bibliometric and qualitative literature analysis based on publications indexed in Web of Science and Scopus from 1979 to 2025 was conducted to identify major research trends and knowledge gaps. The results indicate that polymer particles can alter soil structure, microbial activity, and sorption processes, thereby affecting the stability and cycling of soil organic carbon. Interactions between polymer surfaces and humic substances may modify aggregation processes and influence the persistence and mobility of both polymers and organic carbon compounds. Despite the rapid growth of research on microplastics, studies addressing polymer–SOM interactions remain limited and methodologically heterogeneous. Greater integration between polymer research, soil science, and land use studies is necessary to better understand the implications of polymer contamination for soil quality and carbon cycling. The findings highlight the need for standardized analytical approaches and interdisciplinary research frameworks to assess the long-term effects of polymers in soil ecosystems. Full article

This study quantified nutrient accumulation and partitioning among the kernel, shell, husk, rachis, and leaves during fruit development in three macadamia cultivars. Racemes and leaves were sampled at biweekly intervals until kernel maturity. The shell and rachis ceased to accumulate biomass earlier in the season than the husk or kernel. Nitrogen (N) and potassium (K) were the dominant nutrients accumulated in the fruit. Despite declining concentrations between 80 and 140 DAF, total kernel nutrient content continued to increase, indicating sustained nutrient import during this critical period. The kernel was the primary sink for N, phosphorus (P), sulfur (S), and magnesium (Mg), with peak accumulation occurring during rapid kernel growth at 80–175 days after flowering (DAF). In contrast, the accumulation of calcium (Ca) and manganese (Mn) into the kernel ceased earlier, suggesting limited late-stage mobility. The husk accumulated more K than the kernel and remained an active sink for K, S, Mg, Ca, and Mn until maturity, while N, P, and boron (B) accumulation slowed after ~107 DAF. The shell contributed minimally to nutrient demand, with N, zinc (Zn), and B accumulation ceasing after shell hardening (90–110 DAF). The cultivars exhibited consistent temporal patterns, differing mainly in magnitude. Nutrient partitioning efficiency among-the fruit components was highest for cv. A38. The rachis acted as a transient sink early in development before declining in mobile nutrients, while leaf nutrient dynamics did not reflect fruit demand. Full article

Potentially toxic element (PTE) co-contamination in farmland severely threatens global food safety. To identify effective remediation strategies, large-scale field trials were conducted in two karst regions of Southwest China highly co-contaminated with Cd, Pb, As, Cr, and Hg. The efficacy of seven commercial soil amendments (biochar (BC), fused calcium–magnesium phosphate (FCMP), humic acid (HA), potassium humate (KH), oyster shell powder (OS), composite passivator (PA), and quicklime (QL)) on soil physicochemical properties, PTE bioavailability, maize (Zea mays L.) yield, and plant tissue distribution was systematically evaluated. The results indicated that organic amendments, specifically BC, HA, and KH, consistently outperformed inorganic treatments. These organic materials significantly decreased the diethylenetriaminepentaacetic acid (DTPA)-extractable fractions of cationic PTEs (e.g., Cd and Pb decreased by up to 39.5% under KH treatment) without inadvertently mobilizing As, unlike the alkaline inorganic amendments. This reduction in soil bioavailability closely correlated with improved plant performance, leading to maximum increases in root biomass (up to 130% with BC) and grain yield (up to 27.6% with HA). Furthermore, BC and humic substances effectively restricted PTE accumulation in grains (Cd and Pb reduced by up to 42.1%). Tissue distribution analysis revealed a consistently low root-to-stem translocation factor (TF < 0.2), indicating that roots acted as the primary sink for absorbed PTEs. This study indicates that commercial organic amendments support the use of a superior, broad-spectrum strategy for mitigating multi-PTE risks and ensuring safe agricultural utilization in severely co-contaminated areas. Full article

Uranium mining generates complex multi-element contamination that affects interconnected ecosystem components, posing long-term ecological and sanitary risks; this review places these impacts in a broad environmental context and aims to synthesize current knowledge on the distribution, migration, and accumulation of uranium and associated heavy metals in water, soil, and plants. A structured analysis of international peer-reviewed literature was conducted, focusing on documented pathways of metal release from tailings and waste dumps, geochemical controls on mobility, and biological uptake by vegetation. The reviewed studies consistently show that tailings and disturbed ore-bearing strata act as persistent sources of uranium and heavy metals (e.g., Cd, Pb, Cr, Ni, Zn, Mn, As), which migrate through infiltration, acid mine drainage, and atmospheric dispersion, leading to elevated concentrations in surface and groundwater and long-term accumulation in soils. Soils function as the principal sink controlling metal bioavailability, while vegetation reflects the bioavailable fraction and exhibits pronounced species-specific accumulation patterns. These processes establish an active “soil–water–plant” transfer chain that facilitates entry of contaminants into food webs. The synthesis indicates that combined uranium and heavy metal contamination represents a sustained ecological and public health concern in uranium-mining regions and underscores the need for integrated monitoring of soils, waters, and vegetation, along with quantitative risk assessment and scientifically grounded remediation strategies. Full article

Microplastics (MPs) persist in wastewater treatment systems owing to their durability and mobility. As critical interception points, wastewater treatment plants (WWTPs) receive MPs from diverse domestic and industrial sources. This review synthesizes peer-reviewed studies (2009–2026) to evaluate MP mass flux, in-plant transformation, and elimination across primary, secondary, and tertiary stages. While conventional processes typically remove 60–90% of MPs, advanced tertiary technologies, such as membrane bioreactors and rapid sand filtration, can achieve efficiencies exceeding 95%. The fate of MPs is governed by density-driven settling and biological aggregation; however, the significant accumulation of MPs in sewage sludge represents a critical pathway for environmental re-entry. This review highlights key knowledge gaps, including inconsistent analytical methodologies, evidence of in-plant fragmentation generating nanoplastics (NPs), and uncertainties regarding full-scale mass flows. Furthermore, the review synthesizes mass flux data to clarify the partitioning of MPs between the effluent and sludge, identifying biosolids as a primary sink. The review concludes by proposing a transition from physical separation to elimination technologies (e.g., AOPs), alongside standardized monitoring and regulatory frameworks, to achieve sustainable reductions in MP emissions. Full article

Additively manufactured (AM) and wrought 316L stainless steels were irradiated with 2 MeV protons at 360 °C. Depth-resolved void swelling was quantified using cross-sectional transmission electron microscopy, with a safe-zone analysis applied to exclude near-surface and proton-range artifacts. The AM 316L exhibits significantly lower swelling than the wrought alloy. Swelling in the AM material is characterized by larger voids but a much lower void number density, whereas the wrought alloy develops smaller voids at a substantially higher density. The two alloys also display distinct dependences on local damage: in AM 316L, void size increases with local dpa while the void density remains nearly constant, whereas in wrought 316L, the void size is approximately constant and the void density increases with local dpa. These trends indicate that AM 316L has already entered a void growth-dominated regime, while wrought 316L remains in a void-nucleation-dominated regime. The reduced swelling in the AM alloy is attributed to more effective defect-recombination sinks and/or reduced vacancy mobility associated with the AM microstructure. These findings provide important insight for the evaluation and optimization of AM 316L alloys for nuclear industry applications. Full article

Boron (B) is an essential but narrow-range micronutrient for citrus, with toxicity risks heightened in dry regions due to potentially high-B irrigation water and limited soil leaching. ‘Forner-Alcaide 5’ (FA5) is a promising rootstock for enhancing B-tolerance of sweet orange, but it had not been sufficiently tested before this study, specifically considering soil texture. Therefore, this greenhouse study investigated the effects on B absorption and biomass buildup of irrigating navel orange seedlings (cv. Navelina) grafted onto ‘Carrizo’ citrange (CC) and FA5 rootstocks, with 0.11, 2, or 5 mg B L⁻¹ waters and grown in clay loam or sandy loam soils. The results of this complete three-factor trial revealed that leaves are the primary sink for B (24–1300 mg kg⁻¹), indicating passive, transpiration-driven uptake and limited phloem redistribution. The presumed absence of sugar alcohols, and the weak binding affinity of B to the abundant sucrose, may account for the restricted phloem mobility of B in citrus, consistent with the mechanistic interpretation proposed in this study. FA5 rootstock showed greater B tolerance, sustaining 28% higher biomass than CC at 2 mg L⁻¹ B. Plant B uptake was found to be more related to soil soluble B than adsorbed B. Interestingly, the relationship followed a diminishing-returns pattern, thereby suggesting a balancing feedback mechanism, potentially based on B-induced stomatal closure. This analytical link between irrigation B and plant accumulation offers a framework for managing B toxicity, pending field validation. Full article

Autonomous Underwater Vehicles (AUVs) play a central role in marine observation, inspection, and monitoring missions, where effective trajectory planning is essential for ensuring safe operation, reliable sensing, and efficient data transfer. In realistic underwater environments, uneven seafloor geometry, limited acoustic communication, navigation uncertainty, and sensing visibility constraints significantly influence mission performance and challenge classical planar planning formulations. This survey reviews trajectory planning methods for AUVs operating in uneven environments, with a focus on two major classes of underwater sensing missions: underwater area coverage using onboard sensors and underwater sensor data collection within underwater acoustic sensor networks (UASNs) supporting the Internet of Underwater Things (IoUT). For area coverage, the survey examines the progression from classical planar coverage strategies to terrain-aware, occlusion-aware, multi-AUV, and online planning frameworks designed to address uneven terrain and sensing visibility. For underwater sensor data collection, it reviews mobile sink-based trajectory planning strategies, including energy-aware, channel-aware, and information-based formulations based on metrics such as Age of Information (AoI) and Value of Information (VoI), as well as cooperative architectures involving unmanned surface vehicles (USVs). By synthesizing these two bodies of literature, the survey clarifies current capabilities and limitations of trajectory planning methods for AUVs operating in uneven underwater environments. Full article

Currently, wireless sensor networks (WSNs) have been mutually applied to environmental monitoring and industrial control due to their low-cost and low-energy sensor nodes. However, WSNs are composed of a large number of energy-limited sensor nodes, which requires balancing the relationship among energy consumption, transmission delay, and network lifetime simultaneously to avoid the formation of energy holes. In nature, gregarious herbivores, such as the white-bearded wildebeest on the African savanna, employ a “fast-transit and selective-dwell” strategy when searching for water; they cross low-value regions quickly and prolong their stay in nutrient-rich pastures, thereby minimizing energy cost while maximizing nutrient gain. Ants, meanwhile, dynamically evaluate the “energy-to-reward” ratio of a path through pheromone concentration and its evaporation rate, achieving globally optimal foraging. Inspired by these two complementary biological mechanisms, our study proposes a novel ACO-conceptualized optimization model formulated via mixedinteger linear programming (MILP). By mapping the pheromone intensity and evaporation rate into the MILP energy constraints and cost functions, the model integrates discrete decision-making (path selection) and continuous variables (dwell time) by dynamic path planning and energy optimization of mobile sink, constituting multi-objective optimization. Firstly, we can achieve flexible trade-offs between multiple objectives such as data transmission delay and energy consumption balance through adjustable weight coefficients of the MILP model. Secondly, the method transforms complex path planning and scheduling problems into deterministic optimization models with theoretical global optimality guarantees. Finally, experimental results show that the model can effectively optimize network performance, significantly improve energy efficiency, while ensuring real-time performance and extended network lifetime. Full article