Search Results (23,978)

Concerns regarding the safety, environmental impacts, and long-term sustainability of pesticide-dependent crop protection have intensified interest in biological control, which suppresses pest populations using natural enemies (predators, parasitoids, and pathogens) within integrated pest management (IPM) programs. This bibliometric study maps the development of biological control research from 2000 to 2025 using records retrieved from the Web of Science Core Collection. The publication trends, collaboration structures, leading countries and institutions, core journals, keyword co-occurrence and clustering, citation bursts, and influential cited references were examined using CiteSpace and VOSviewer. The results show a pronounced increase in publication output after 2011, indicating rapid expansion and consolidation of the field in the last decade. Keyword analyses reveal a thematic shift toward ecosystem-based framing, reflected by the growing prominence of terms such as ecosystem services, habitat management, and ecological intensification, which emphasize landscape- and management-oriented approaches to enhancing pest suppression. Cited-reference patterns highlight the persistent influence of the foundational literature on habitat manipulation, landscape complexity, and conservation biological control. Despite the field’s growth, research gaps remain in integrating biological control with emerging bioengineering tools and explicitly accounting for climate-driven variability across regions and production systems. Full article

This study assesses the impacts of climate change (CC) on maize production in Bosnia and Herzegovina, comparing ten maize-producing municipalities and using Gradiška as a case study. Agroclimatic indicators and ISAREG-based soil water balance simulations were used to evaluate regional suitability for future maize production. Projections indicate substantial increases in average temperatures of 2 to 6 Celsius by the end of the century, depending on the RCP scenario, together with important reductions in accumulated mean precipitation, particularly during summer. Rising temperatures accelerate maize phenology, shortening growth cycles and enabling double-cropping opportunities for short-season cycles. Medium-season cycles may become feasible in most regions, while long-season cycles remain constrained in high-altitude areas due to thermal requirements. Rainfed maize in Gradiška is expected to face increased relative evapotranspiration deficits under future ‘hot & dry’ conditions, with potential relative yield losses due to water deficit of up to 12%. Irrigated maize shows a variation in irrigation requirements from −26% to +8% relative to the baseline, which reflects the combined effect of a shortened crop growth cycle under higher temperatures and increased evapotranspiration demand under drier conditions. Regions with high soil water-holding capacity are the most resilient, while areas with shallow soils or Mediterranean climates are more vulnerable under future conditions. The findings underscore the need for agronomic adaptation measures to the projected CC impacts, including supplemental irrigation, drought-tolerant cultivars, and potential adjustment of sowing. Full article

Frequent extreme heatwaves (HWs) have significantly exacerbated urban thermal risks, yet the regulatory mechanisms of urban morphology remain poorly understood. This study focuses on the core urban areas of Beijing and develops a Local Climate Zone (LCZ)-constrained spatiotemporal data fusion model (LCZ-FSDAF) to generate high-resolution Land Surface Temperature (LST) datasets from 2015 to 2024. By integrating urban–rural gradient analysis with the XGBoost-SHAP model, this study quantitatively resolves the spatiotemporal evolution of land surface temperature during heatwaves and the nonlinear threshold effects of urban morphological parameters, using a representative extreme heatwave event in July 2023 as a case study. The results indicate that the LCZ-FSDAF model achieves high precision across complex urban underlying surfaces (up to 0.946, RMSE as low as 0.762 K), effectively capturing the spatial heterogeneity of the urban thermal environment. Over the past decade, heatwave events in Beijing have exhibited a significant trend of increasing frequency, duration, and intensity. During these events, LST displays a concentric core-high, periphery-low structure; however, the peak temperature shifts toward high-density built-up areas in the sub-core, manifesting a distinct heat island core shift phenomenon. Furthermore, the impact of urban morphology on LST is characterized by significant nonlinearity, with the Normalized Difference Vegetation Index (NDVI) and Mean Building Height (MBH) identified as dominant factors. Notably, Building Coverage (BC) and Sky View Factor (SVF) exhibit pronounced threshold effects across different thermal indicators. Findings of this study are useful for guiding urban planning, optimizing spatial configurations, formulating urban heat island mitigation policies under heatwaves, and promoting the Sustainable Development Goals (SDGs) of cities and communities. Full article

The field production of tomato faces challenges regarding abiotic stress factors, which unfavorably impact fruit quality traits. Hedgerows, a form of agroforestry, offer a climate-resilient strategy to buffer temperatures and reduce the impact of direct wind stress on crop production. This study assessed the impact of hedgerow microclimate modulation effects on open-field tomato fruit quality, employing three genotypes (Roma, Ace55, and Szentlőrinckáta). Key quality traits (Total Soluble Solids (TSS), Titratable Acidity (TA), Sugar–Acid Ratio (SAR), Ferric-Reducing Antioxidant Power (FRAP), Total Phenolic Content (TPC), Chroma (C*), and Hue (h^o)) were measured over two harvests per season, in two consecutive years (2023–2024). Plots were positioned at five distances (3, 6, 9, 12, and 15 m from the hedge) on both windy and protected sides (W1–W5 and P1–P5, respectively, with 1 showing the closest position). We observed that the microclimate of the protected side was consistently warmer, with an average deviation from the reference temperature of +3.54 °C at mid-distances and +0.38 °C higher overall across both growing seasons. Results show that mid-distance zones (P3–P4, W3–W4) consistently exhibited the highest C* (up to 39.44) at W4 and TSS values at W1 (7.00 °Bx). Protected sides favored higher TA at P3 (0.70%) and Hue (h^o) values at P3 with (53.06 ± 0.30) with Ace55 and SAR at P3 (16.35) with Szentlőrinckáta. Windy sides significantly enhanced FRAP and TPC, with the Szentlőrinckáta genotype exhibiting the highest antioxidant capacity at W1 (23.67 mg AAE 100 g⁻¹, FRAP) and TPC (244.17 mg GAE 100 g⁻¹). At W4, Roma showed a 9.4% increase in TPC in the second harvest, while Ace55 showed the highest FRAP values during late-season sampling, highlighting genotype-specific antioxidant resilience under contrasting microclimates. These findings suggest that mid-distance zones and microclimatic variation between windy and protected sides remarkably influence fruit quality traits and antioxidant profiles. Full article

This paper assesses the role of nature-based solutions as a way to scale sustainability goals, focusing on the use of carbon credits in voluntary corporate climate commitments. To accomplish this, we adapt the DICE23 model by incorporating a demand function for voluntary corporate carbon abatement and by including the costs of supplying nature-based and non-CO₂ credits to that market. Through scenario analysis, we examine how likely current and proposed new commitments are to meet 1.5 °C and 2 °C climate thresholds by 2030 and 2050 with and without the use of nature-based carbon credits. We find that the inclusion of nature-based credits would increase the probability of meeting a 2 °C threshold by 2030 by lowering costs and significantly increasing overall mitigation. A key result of this paper is that allowing companies to utilize nature-based credits to deliver on near-term mitigation targets can provide the same number of emission reductions as efforts to expand corporate commitments three-fold, but is limited to reductions in the energy sector alone. Overall, incorporating forests and other nature-based credits into corporate commitments could provide immediate and substantial climate benefits while also supporting people and nature impacts today, enabling companies to better achieve multiple social and sustainability goals simultaneously. Full article

Extreme hydrological events fundamentally alter sediment transport dynamics across grain, reach, and watershed scales, rendering classical equilibrium-based transport formulations inadequate. This review synthesizes recent advances in multiscale sediment transport modeling under highly unsteady and high-magnitude forcing conditions. At the grain scale, particle-resolved simulations demonstrate that sediment entrainment is governed by turbulence intermittency and transient force exceedance rather than mean bed shear stress thresholds, particularly when the hydrograph rise timescale (T_h) becomes comparable to particle response times (T_p). At the reach scale, non-equilibrium transport emerges when the unsteadiness ratio T_h/T_a∼O(1), where T_a is the sediment adaptation timescale representing the time required for sediment flux to adjust toward transport capacity. Under these conditions, pronounced hysteresis between discharge and sediment flux is observed, requiring relaxation-based transport formulations instead of instantaneous equilibrium laws. At the watershed scale, the sediment delivery ratio (SDR), defined as the ratio of sediment yield at the basin outlet to total hillslope erosion, becomes highly time-dependent. Extreme precipitation events can activate hillslope-channel connectivity, increasing SDR by orders of magnitude relative to baseline conditions. A unified dimensionless scaling framework is presented based on mobility intensity (θ/θ_c, where θ is the Shields parameter and θ_c is its critical value for incipient motion), unsteadiness ratio (T_h/T_a), and morphodynamic coupling (T_f/T_m, where T_f is the hydraulic advection timescale and T_m is the morphodynamic adjustment timescale). This framework enables classification of sediment transport regimes ranging from quasi-equilibrium to cascade-dominated states. The synthesis demonstrates that predictive uncertainty increases nonlinearly across scales due to timescale compression, threshold activation, and feedback between flow hydraulics and evolving morphology. Recent developments in hybrid physics-AI approaches show promise in improving predictive capability by enabling dynamic transport closures, surrogate modeling of computationally expensive microscale processes, and data assimilation for real-time forecasting. However, these approaches remain limited by extrapolation uncertainty and the need to enforce physical constraints. Overall, this review concludes that regime-aware multiscale coupling, combined with uncertainty quantification and adaptive modeling strategies, is essential for robust sediment hazard prediction and climate-resilient infrastructure design under intensifying hydrological extremes. Full article

Attention has been drawn internationally to the carbon footprint of the healthcare sector, its impact upon climate change and promises that have been made to reduce carbon emissions. Even so, there are, as yet, not many reports about steps that have been taken in the practical setting to bring about the promised reductions. This review is intended to provide some guidance on actions that could prove beneficial. It includes examples of steps that have been undertaken and shown to be viable options in the practical setting and that now need to be implemented more widely. Certain types of medical textiles contribute more substantially to the carbon footprint of healthcare than others. To achieve significant reductions, attention needs to be focused on reducing the environmental impact of hospital and care centre linen, textile filter components of HVAC systems and PPE, such as gowns, drapes and facemasks, rather than on implantable items and specialist medical devices. Policy makers, those officials responsible for procurement and healthcare practitioners all need to become more involved in ensuring that the correct guidance and resulting actions are implemented in a coordinated fashion. Full article

Accurate measurement of streamflow is fundamental for water resources management, ecological conservation, flash flood early warning, and climate change impact studies. This study presents a proof of concept on the usage of Internet of Things (IoT) for automatic streamflow measurements using commercial off-the-shelf (COTS) hardware. The system is designed, implemented, and experimentally evaluated as a low-cost, solar-powered IoT device tailored to small-order streams and headwater tributaries. At its core is the Hall-effect YF-S201 flow sensor. Although primarily designed for closed-conduit applications, the sensor was tested in a controlled setup where stream water was diverted into a short pipe section, enabling continuous monitoring and calibration. This paper provides details on the design and validation of a low-cost (approximately 24 Euros), solar-powered streamflow measurement system based on a water flow sensor, using wireless communications, and cloud storage based on an ESP32 board, PostgreSQL, and a web interface. The device was tested in a simulated environment. Results indicate the proposed device reliably tracks flow variability, while offering portability, energy autonomy, and cost efficiency, and may serve as a feasible alternative for low-infrastructure, temporary deployments. Full article

High-temperature stress severely reduces the photosynthetic efficiency of radish (Raphanus sativus L.), a cool-season crop. This study evaluated five nitrogen (N) levels {0 N, 0.5 N, 1 N (234 kg urea ha⁻¹, based on RDA), 2 N, and 4 N} through an open-field experiment under high-temperature stress conditions. Analysis of OJIP transients revealed that high temperatures severely inhibited photosynthetic capacity in the 0 N, 0.5 N, and 4 N treatment groups. These groups exhibited a simultaneous increase in K and J-steps, signifying electron transport bottlenecks and structural damage to the oxygen-evolving complex (OEC). Consequently, energy absorption and trapping decreased, while heat dissipation increased. In contrast, the 2 N treatment maintained superior F_m(maximum fluorescence) and energy flux, demonstrating enhanced photosynthetic resilience. However, despite improved photosynthetic stability, the 2 N group did not show a significant increase in yield compared to the 0.5 N or 1 N treatment groups. These results suggest that photosynthetic protection under heat stress does not necessarily guarantee higher yields, highlighting the need to identify optimal fertilization points for sustainable production. Overall, the findings of this study provide fundamental data for strategic nitrogen management in open-field radish cultivation to mitigate the impacts of increasing climatic instability. Full article

The genus Trollius L. remains insufficiently studied in Kazakhstan, necessitating comprehensive monitoring of its distribution and population status assessments. In Kazakhstan, this genus is represented by the following five species: T. asiaticus, T. altaicus, T. dschungaricus, T. lilacinus and T. komarovii. Of those, T. altaicus and T. dschungaricus are the most widely distributed. This study focuses on analyzing the population structure of Trollius altaicus and Trollius dschungaricus in relation to varying ecological and geographical conditions within Kazakhstan, along with conducting a comprehensive morphometric assessment. To study plant communities with Trollius L. species, classical geobotanical methods were applied, including the route-reconnaissance method to determine the species’ range and carry out a detailed population survey which involved the assessment of the age structure of populations and species composition of associated vegetation. Population structure analysis showed that the majority of T. altaicus plants were in the generative stage, with the right skewed age spectrum suggesting a decline in population size. Meanwhile, populations of T. dschungaricus were dominated by juvenile and virginal individuals, with the left skewed age spectrum suggesting a high regenerative potential. The morphometric analysis revealed high variability of plant height, number of leaves, flower diameter, diameter of generative bushes, number of basal leaves, and leaf length and width. The obtained results can serve as a basis for developing effective conservation and management strategies for T. altaicus and T. dschungaricus under ongoing climate change and anthropogenic impact. This research demonstrates that a detailed assessment of phenotypic characteristics is vital for formulating preservation frameworks and managing biological resources sustainably. Full article

Aviation emissions significantly contribute to climate change, with both CO₂ and non-CO₂ effects, such as contrails and nitrogen oxides. The aim of this paper was to develop a machine learning-based model to predict the climate impact of flights using atmospheric and emissions data. The proposed model, an LGMB Regressor algorithm, was trained on a dataset of atmospheric variables and algorithmic Climate Change Functions to forecast the cumulative impact of these emissions measured via the total average temperature response at 20 years (ATR20). In a test on five months of data pertaining to the North Atlantic Corridor, the LGBM Regressor model exhibited strong predictive performance, with an $R^2$ score between 0.41 and 0.55 and a Mean Absolute Percentage Error between 2.68% and 5.11% depending on the month. This study shows the potential of machine learning to provide efficient, accurate climate impact assessments for aviation. Full article

In the context of occupational environments and sustainable employment, this review explores the effects of declining workers’ health, environmental degradation, and the depletion of marine resources on workers’ psychological well-being. As seas and oceans are increasingly exploited and used as dumping sites for both solid and liquid waste, marine ecosystems are severely degraded, with negative impacts on biodiversity, water quality, and ecosystem processes. Marine biodiversity is crucial to maintaining global food security and supporting the livelihoods of millions of people worldwide. Moreover, this study examines the role of digital technology in the marine industry in safeguarding workers’ sustainable well-being. It emphasizes the complementary roles of law and technology in promoting it. The risks to the health and well-being of marine workers are greatly increased by the occupational consequences of climate change on the sustainable environment and the effects of working in marine environments. Working conditions, incomes, and even unemployment among marine workers have been directly affected by the degradation of marine environments and the depletion of marine resources. Anxiety, panic, depression, rage, and other unpleasant emotions that affect workers’ health and pose mental health risks are detrimental to the psychological well-being of marine workers. The challenges of employment in the marine industry adversely affect the physical and mental well-being of marine employees and hinder economic growth. However, digital technology in marine environments has fundamentally altered the regulations governing marine operations. Full article

Coastal erosion poses a growing threat to natural systems and critical infrastructures, particularly in touristic coastal areas where beaches represent both ecological assets and economic resources. Beyond shoreline retreat, erosion processes progressively reduce emerged beach surfaces and increase the exposure and vulnerability of coastal roads, railways, and urban settlements, with cascading socio-economic consequences. This study presents an integrated geomorphological and economic assessment of coastal erosion impacts. The Coastal Degradation Calculator (CoDeC) is applied along the Tyrrhenian coast of southern Italy, focusing on the municipality of San Lucido. Shoreline variations are quantified to reconstruct long-term changes in the Surface of the Emerged Beach (SEB) before and after major coastal defense interventions using multi-temporal remote sensing data (1954–2018). Simple, science-based box models are implemented to estimate sediment deficits, restoration needs, and associated economic damages, expressed in both €/m² and €/year. Results highlight a reduction in SEB area exceeding 60%, significant downdrift erosion linked to hard defenses and additional losses caused by coastal urbanization. The methodology proved effective in supporting damage quantification and informed the resolution of a long-standing legal dispute between public authorities. Owing to its transparency and reproducibility, the proposed framework offers a transferable tool for coastal risk assessment and management under increasing climate-driven pressures. Full article

Climate change will impact the distribution of daily deaths in Austria until the end of the century. This study examines the net effects of fewer cold and more-frequent hot days on daily mortality under different climate and demographic scenarios. Projected district-level mortality data and daily temperatures based on Representative Concentration Pathways (RCP4.5 and RCP8.5) are analyzed to estimate the number of attributable deaths for every fifth year due to heat and cold using district-wise temperature–effect estimates from a previous analysis. While the overall shape of the time course of temperature-attributable deaths depends mostly on the demographic developments (with the highest numbers of daily mortality mid-century), under all climate scenarios investigated, the increase in heat-attributable deaths will be more pronounced than the decrease in cold-attributable deaths. Contrary to common claims, shift in temperatures due to climate change already has a net negative effect on population health in Austria now. Full article