This study was conducted in the Al-Kawtha Agricultural Project, Babil Governorate, Iraq (874 km²), with the aim of evaluating the spatial distribution of major soil nutrients. Four land-use types were considered: wheat, maize, eggplant, and uncultivated land. Soil samples were collected from two depths (0–30 cm and 30–60 cm) and analyzed to determine nitrogen, phosphorus, potassium, iron, and zinc.as well as key physical and chemical properties.The results showed substantial variation in nutrient levels among the different land uses, while soil pH remained relatively stable. Nitrogen concentrations ranged from 18.90 to 38.9 mg kg⁻¹, phosphorus from 4.30 to 11.27 mg kg⁻¹, potassium from 97.60 to 145.3 mg kg⁻¹, iron from 3.58 to 7.58 mg kg⁻¹, and zinc from 0.31 to 0.46 mg kg⁻¹. The highest nutrient concentrations were observed in uncultivated areas, reflecting minimal nutrient removal, whereas cultivated fields—especially maize—showed lower nitrogen and organic matter content. Phosphorus was more abundant in deeper layers, while other nutrients were concentrated in the topsoil .Statistical analysis (p ≤ 0.05) confirmed that Findings revealed that soil nutrient distribution was significantly influenced by both land-use type and soil depth. These findings emphasize the long-term impact of cultivation on soil nutrient depletion and highlight the necessity of sustainable management strategies, including organic fertilization and crop rotation, to preserve soil fertility and productivity.

Tourism village development through Village-Owned Enterprises (BUMDes) serves as a key strategy for rural economic empowerment. Klampitan Village, Purwoasri District, Kediri Regency, encounters several obstacles including limited human resource capacity, weak digital promotion, and lack of systematic spatial planning for BUMDes development. The community service program aimed to design a BUMDes site plan as a guideline for physical tourism area development and to enhance digital promotion capacity. A qualitative participatory approach was employed through the Asset-Based Community Development (ABCD) framework for village asset mapping, complemented by SWOT analysis for strategy formulation. Implementation took place from July to August 2025, involving 10 key informants through observation, interviews, and Focus Group Discussions (FGDs). Data validation was conducted using source triangulation and member checking. The program produced a conceptual BUMDes site plan comprising 11 main sections with economic, social, educational, and recreational functions. Additionally, official BUMDes social media accounts were established as digital promotion channels. Evaluation showed 92% community participation and improved capabilities of MSME actors in utilizing social media for product marketing. These achievements demonstrate that the program not only generated initial plans and facilitation but also established institutional foundations and human resource capacity for sustainable BUMDes management. The resulting site plan and digital enhancement function as initial instruments supporting the acceleration of Klampitan Village toward becoming a tourism village in 2026.

Low levels of financial literacy and poor financial management practices are still the main problems faced by micro, small and medium enterprises that are based on community and religious organizations. Problems with unorganized financial recording systems, in addition to the inability to separate business from personal finances, are obstacles to obtaining financing as well as making appropriate business decisions. The community service program is intended to improve the financial management capacity of micro, small and medium enterprises based at the Al-Muhajirat Mosque Taklim Assembly in Biring Romang Village, Makassar City through practical training on basic accounting. The method used is lectures, tutorials, and discussions tailored to the needs of partners with a participatory approach. The evaluation was carried out using participatory observation, case studies as well as post-training assessments to measure the effectiveness of the program. The results showed a significant increase in participants' ability to record transactions, implement a simple accounting cycle, and separate business from personal finances. Participants can also prepare basic financial reports for decision-making purposes. This program strengthens MSMEs' readiness for more accountable, transparent, and sustainable financial management.

ABSTRACT The study focuses on using remote sensing methods for geotechnical monitoring and disaster management in Saudi Arabia. Surface changes were analysed through satellite image processing, Light Detection and Ranging (LiDAR) surveys, and Unmanned Aerial Vehicle (UAV) assessments, revealing significant landform alterations and ground subsidence. High-resolution LiDAR data enabled precise terrain and elevation measurements, while statistical analyses quantified movement rates across three designated hazard zones (Zones A, B, and C based on deformation characteristics), identifying Zone C as the most active. Temporal trend analysis showed seasonal fluctuations and stability concerns. Geographic Information System (GIS)-based spatial analysis produced slope stability maps that support land use planning and hazard mitigation. Integrating Wireless Sensor Networks (WSNs) enhanced real-time monitoring, with simulations confirming their reliability. The study underscores the vital role of continuous remote sensing and data integration for disaster preparedness, resilient infrastructure, and sustainable risk management in Saudi Arabia.

Phage therapy under multiple abiotic stresses: Systematic review on mechanisms of plant disease control

Making waves: One Water quality standardization concept – A leap for sustainable water management

Predicting coastal subsidence and sea-level scenarios in the Sundarbans Delta using InSAR and artificial intelligence for sustainable coastal management.

Uncertainty propagation in reinforcement bond performance of 3D-printed concrete via generative-augmented ensemble learning

Assessment of soil quality properties and crop yield after long-term implementation of sustainable management practices in semiarid rainfed conditions

We demonstrate a near-real time forest disturbance alerting system for Europe using Sentinel-1 radar data. Sentinel-1 radar can penetrate clouds and offers high spatial (∼20 m) and temporal (3- to 6-day) detail. We directly integrated near-real time ERA5-Land temperature and Copernicus forest type data into the disturbance detection framework to address freezing temperatures and seasonal phenology, both of which influence the Sentinel-1 backscatter signal and thus need to be accounted for. This facilitates year-round monitoring across a range of environmental conditions (sub-zero, wet and dry) and forest types (coniferous, deciduous) throughout the boreal, temperate, and Mediterranean forests of Europe. Validation across Europe showed high accuracy, with a user accuracy of 91.2% (±1.3%) and producer accuracy of 74.5% (±6.0%). User accuracy increased to 99% (±0.4%) when excluding errors in the European-scale forest cover mask primarily caused by local overestimation of forest height and density. Disturbances were detected with a median delay of 27 days relative to the first high-resolution optical Planet reference image, which can further be reduced to 1 day through retrospective event-based correction of late detection bias. Compared to existing annual optical-based products, our method improves the detection of small-scale disturbances such as group fellings in Romania. We generated European-scale estimates of intra-annual disturbance seasonality, capturing variation in forest management practices and disturbance regimes such as winter harvesting in northern Europe, spring sanitation cutting in central Europe, and summer wildfires in southern Europe. Overall, this alerting system provides timely and detailed forest disturbance information in support of sustainable forest management, biodiversity conservation, carbon accounting, and law enforcement efforts across Europe. The alerts are available at https://wurnrt-raddeurope.projects.earthengine.app/view/radd-europe. • Near-real time Sentinel-1 forest disturbance alerting demonstrated across Europe. • Direct integration of ERA5-Land temperature data enabled year-round monitoring. • User accuracy of 91%, up to 99% with forest mask errors excluded; producer accuracy of 75%. • Median relative detection delays of 27 days and 1 day after event-based bias-correction. • First European-scale estimates of intra-annual forest disturbance seasonality.

Distribution, source, and pollution risk assessment of heavy metals in the coastal sediments of the northern South China sea.

Machine learning assisted-hyperspectral imaging for in-situ evaluation of compost maturity.

A novel spatiotemporal and machine learning framework for sustainable groundwater monitoring and management

Mining activities can significantly alter surface and groundwater systems. Therefore, sustainable water resources management has become a central requirement and strategic necessity for responsible mining. This requires tools capable of characterizing water sources, flow paths, and contaminant dynamics to support informed and responsible decision-making. Stable and radioactive isotopes are powerful tracers of the origin, age, movement, and transport of water and its constituents, as well as indicators of the water-rock interactions affecting groundwater and surface water quality. This paper reviews publications from 2022 to 2024 that discuss advancements in isotopic techniques and their applications, with the goal to promote the adoption of integrated isotopic and geochemical methods in mining-related assessments. The review is organized into three sections: 1) the understanding of hydro(geo)logical circuits: water sources and circulation, mixing processes, hydro(geo)logical alteration, river-groundwater interactions and groundwater age; 2) the assessment of mining-related contamination processes: contamination by S or by N compounds, discrimination between mining and other contamination sources, the use of minor and trace element isotopes, the salinity issues, and the identification of gas production and exchange; and 3) the application of isotope approaches for monitoring the impact of mining and assessing remediation measures, whether natural or engineered. Finally, the intrinsic strengths and weaknesses, as well as the external opportunities and limitations to the application of isotopic approaches are discussed. The review summarizes the commonly encountered sources and processes in mining settings and provides graphical outputs to assist with interpreting new experimental data, highlighting environmental isotopes as “sustainable investigation tools”. • Isotopic approaches in mining-related settings are assessed with a SWOT analysis • Graphical outputs to assist with interpreting new experimental data are provided • Environmental isotopes represent fully-fledged “sustainable investigation tools”

This study investigates the determinants of timber trade from 21 Latin American countries to global markets over the period 1996–2023 using a gravity model framework. We focus in particular on roundwood, that is the dominant primary forest product in international trade, and we address the high prevalence of zero trade flows by estimating a Negative Binomial hurdle gravity model in a Bayesian setting, with posterior inference obtained via the Integrated Nested Laplace Approximation. Our study contributes to the literature by proposing a novel statistical methodology for gravity models and by providing insights into Latin America’s bidirectional timber trade. The results show that importer countries’ economic size significantly increases both the probability and the volume of roundwood trade, while exporter-side production capacity and forest endowments are key drivers of export intensity. Managed forestry plays an important role: a higher share of planted forests is positively associated with export volumes, suggesting scope for trade expansion without increasing pressure on natural forests. Climate-related natural disasters in importing countries increase the probability of trade, indicating growing demand for timber following extreme events. Institutional quality consistently enhances trade on both the extensive and intensive margins, while currency appreciation in exporter countries reduces competitiveness and trade flows. Finally, participation in selected trade agreements, particularly APEC, ITTA, and MERCOSUR, positively affects trade outcomes. These findings highlight the importance of sustainable forest management, institutional quality, macroeconomic stability, and context-specific trade agreements in strengthening Latin America’s position in global timber markets, while mitigating deforestation risks and increasing resilience to climate-related shocks. • First comprehensive study of Latin American roundwood trade (1996–2023). • Bayesian Negative Binomial hurdle gravity model with INLA in timber trade. • Importer demand, exporter capacity, forest endowments, and management drive intensity. • Institutions, exchange rates, disasters, and trade deals shape trade margins.

• Comparative LCA of biological EoL options for rPC-PLA waste under ISO standards. • Anaerobic digestion outperformed other EoL routes due to efficient energy recovery. • Evaluates uncertainty propagation from data reliability and process variability. • Provides Australia’s key challenges in expanding biological treatment of PLA waste. • Offers policy insights to support sustainable and circular bioplastic management. Bioplastics are increasingly promoted as sustainable alternatives to conventional polymers, yet their environmental performance strongly depends on end-of-life (EoL) treatment. For polylactic acid (PLA), the most widely used biodegradable bioplastic, repeated recycling leads to progressive polymer degradation, leaving residual fractions that can no longer be recovered. These residual streams require biological disposal, but their climate implications remain poorly quantified and inconsistently compared. We present a comprehensive, process-based life cycle assessment of three biological EoL pathways for residual post-consumer PLA (rPC-PLA), such as industrial composting, anaerobic digestion (AD), and landfilling, conducted under ISO 14040/14044 standards and coupled with uncertainty modelling via Monte Carlo simulation and pedigree-matrix parameterization. AD demonstrates a net-negative climate impact (-134 kg CO 2 eq per tonne of rPC-PLA) through biogas recovery and fossil-energy substitution, whereas composting generates substantially higher emissions (1932 kg CO 2 eq per tonne) due to rapid biogenic CO 2 release and high aeration energy demand. Landfilling delivers moderate impacts in engineered facilities with optimized gas capture, but uncontrolled disposal leads to markedly higher emissions over a 100-year time horizon. These findings show that not all biodegradable waste pathways deliver environmental benefits and that AD uniquely converts unavoidable rPC-PLA into climate-beneficial energy. The work provides quantitative evidence to guide bioplastic waste policy and demonstrates that realizing the sustainability promise of PLA depends not only on its material design but on aligning waste infrastructure with circular bioeconomy goals.

Functional analysis of Sirt5 in the effect of azadirachtin on the intestinal injury of Spodoptera litura.

Assessing the role of gridded evapotranspiration products in improving streamflow simulation and reducing hydrological modeling uncertainty

Green roofs play a vital role in urban climate adaptation by reducing heat stress and stormwater runoff. However, their effectiveness is highly dependent on substrate moisture. During dry periods, extensive green roofs rapidly dry out, significantly diminishing their cooling capacity. This restricts plant selection to drought-tolerant species such as succulents, which offer only limited evaporative cooling potential and biodiversity benefits. Supplemental irrigation can enhance green roof cooling performance and may allow the cultivation of more diverse and transpiring vegetation. However, excessive or poorly timed irrigation may reduce the system's capacity to retain stormwater. In this study, a novel smart irrigation system was developed, which is based on the assimilation of weather forecast data into a hydrological model to allow for demand-driven water supply. The aim of the smart irrigation management is to avoid water stress for plants and provide cooling only on warm days, while targeting to maximize the retention capacity before rainfall events to achieve the effective interaction of multiple ecosystem services. The performance of the smart irrigation system is compared to conventional irrigation approaches relying on fixed intervals or simple soil-moisture threshold controls. Irrigation substantially enhanced daytime surface cooling, reducing surface temperatures by up to 6.85K compared to the non-irrigated roof. While irrigated green roofs offered thermal regulation on warm days, the non-irrigated green roof tended to exhibit even higher surface temperatures than a conventional gravel roof. Hydrologically, the smart irrigation system required lower amounts of irrigation compared to timer and sensor-based irrigation regimes (reduction by 46.3% and 23.5%, respectively) without negatively affecting plant vitality and showed notably better average runoff reduction performance for heavy precipitation events (86.3% vs. 68.4% and 79.5%) This study demonstrates that novel smart irrigation routines for extensive green roofs have the potential to enhance the contribution to urban microclimate regulation and sustainable water management.

Role of nutrient and runoff retention in reducing nutrient export and runoff: a comprehensive framework for sustainable basin-scale water management