Search Results (10,392)

In response to the ‘zero carbon’ goal, the development of renewable energy has become a global consensus. Among the array of renewable energy sources, wind energy is distinguished by its considerable installed capacity on a global scale. Accurate wind power prediction provides a fundamental basis for power grid dispatching, unit combination operation, and wind farm operation and maintenance. This study establishes a framework to bridge theoretical innovations with practical implementation challenges in wind power prediction. This work uses a narrative method to synthesize and discuss wind power prediction methods. Common classification angles of wind power prediction methods are outlined. By synthesizing existing approaches through multi-time scales, from the ultra-short term and short term to mid-long term, the review further deconstructs methods by model characteristics, input data types, spatial scales, and evaluation metrics. The analysis reveals that the data-driven prediction model dominates ultra-short-term predictions through rapid response to volatility, while the hybrid method enhances short-term precision. Mid-term predictions increasingly integrate climate dynamics to address seasonal variability. A key contribution lies in unifying fragmented methodologies into a decision support framework that prioritizes the time scale, model adaptability, and spatial constraints. This work enables practitioners to systematically select optimal strategies and advance the development of forecasting systems that are critical for highly renewable energy systems. Full article

Plant nitrogen (N), phosphorus (P), and potassium (K) concentrations and ratios serve as critical indicators of nutrient constraints in coastal ecosystems. However, the response of leaf–soil N-P-K stoichiometry in tropical coastal shelterbelt forests to seasonal rainfall variations remains poorly understood. This study measured total N, P, and K contents in leaves and soils of three typical tropical coastal shelterbelt forests in Wenchang, China—Casuarina equisetifolia L., Cocos nucifera L., and Pinus elliottii × caribaea—during August 2022 (wet season) and February 2023 (dry season). Key findings are as follows: (1) All three forests exhibited low N-P-K contents in both leaves and soils, with significant stand-specific variations. Soil N:P ratios were consistently below 14, indicating chronic N limitation for plant growth. (2) Wet seasons significantly altered leaf–soil N-P-K contents and stoichiometric ratios. (3) Leaf and soil stoichiometric traits exhibited strong correlations, but these relationships diverged under seasonal transitions. (4) Shifts from wet to dry seasons increased the sensitivity of N-P-K stoichiometric homeostasis, reflecting weakened nutrient buffering capacity. This study reveals stand-specific nutrient cycling patterns in tropical coastal shelterbelts, with seasonal rainfall modulating soil–leaf nutrient coupling and stoichiometric stability. These findings provide a theoretical basis for optimizing nutrient management and species configuration in tropical coastal ecosystems under climate variability. Full article

Polynyas play a crucial role in polar ecosystems, influencing biodiversity, climate regulation, and oceanic processes. This study employs Synthetic Aperture Radar (SAR) data to determine the optimal sea ice concentration threshold for polynya identification, which is established at 75%. We present a dataset of daily polynya distribution in the Arctic and Antarctic from 2013 to 2022, analyzing their spatial patterns, interannual variability, and seasonal dynamics. Our results indicate that coastal polynyas, primarily located near landmasses, dominate both polar regions. The total polynya area in the Antarctic remained relatively stable, averaging approximately 1.86 × 10⁸ km² per year, with an interannual fluctuation of −3.1 × 10⁵ km² per year. In the Arctic, the average polynya area is around 1.59 × 10⁸ km² per year, with an interannual fluctuation of −7.1 × 10⁵ km² per year. Both regions exhibit distinct seasonal cycles: Arctic polynyas peak in May and reach their minimum in September, whereas Antarctic polynyas expand in November and contract to their smallest extent in February. The polynya formation and development result from a complex interplay of multiple factors, with no single variable fully explaining variations in polynyas’ extent. Additionally, the polynya area in the NOW, and Weddell Sea polynyas, exhibit consistent trends with chlorophyll-a concentration, highlighting their role as critical habitats for primary productivity in polar regions. These findings provide key insights into polynya dynamics and their broader implications for climate and ecological processes in polar regions Full article

There are a multitude of raspberry and blackberry varieties, and each of them develops differently depending on environmental factors and cultivation technology, so much research is needed to see which variety has the best yield in a desired area. This paper studied the growth under natural soil and specific climate conditions in the Bucharest–Ilfov region of Romania of a raspberry plantation and a blackberry plantation, both in their first year of vegetation. The studied interval, the period of June to October 2024, was established from the beginning of the ripening of the first fruits to the late ripening of the fruits. The study analyzed the correlations between the vegetative and productive parameters of the raspberry variety “Delniwa” and the blackberry variety “Thornfree” on productivity per plant. During the study period, good shoot formation was observed, with an average height of 1400 mm for raspberries and 3474 mm for blackberries (r = 0.99 to raspberries and r = 0.98 to blackberries); a good development of the average stem diameter of 8.54 mm for raspberries and 12.78 mm for blackberries (r = 0.96 la zmeur si r = 0.89 la mur), of the number of ripe fruits harvested (r = 0.68 to raspberries and r = 0.58 to blackberries), all of which are correlated with increased productivity of 820 g/plant for raspberries and 2050 g/plant for blackberries. The experimental data were statistically analyzed using linearized, polynomial and hyperbolic models to identify the relationships between the studied variables and to highlight growth variations and fruit production in raspberries and blackberries throughout the season. In the first year of vegetation, both crops recorded constant growth but with different rhythms: raspberries showed constant fruit production, with a peak in June–July and a slight resumption in September, while blackberries had high production at the beginning of summer, followed by a significant decrease in August. The results obtained support farmers who grow raspberries and blackberries under similar natural pedo-climatic conditions, contributing to crop planning and production optimization. Full article

This study introduces a novel one-dimensional Fractional Time–Space Stochastic Advection–Diffusion Equation that revolutionizes the modeling of moisture transport within atmospheric boundary layers adjacent to oceanic surfaces. By synthesizing fractional calculus, advective transport mechanisms, and pink noise stochasticity, the proposed model captures the intricate interplay between temporal memory effects, non-local turbulent diffusion, and the correlated-fluctuations characteristic of complex ocean–atmosphere interactions. The framework employs the Caputo fractional derivative to represent temporal persistence and the fractional Laplacian to model non-local turbulent diffusion, and incorporates a stochastic term with a $1/f$ power spectral density to simulate environmental variability. An efficient numerical solution methodology is derived utilizing complementary Fourier and Laplace transforms, which elegantly converts spatial fractional operators into algebraic expressions and yields closed-form solutions via Mittag–Leffler functions. This method’s application to a benchmark coastal domain demonstrates that stronger advection significantly increases the spatial extent of conditions exceeding fog formation thresholds, revealing advection’s critical role in moisture transport dynamics. Numerical simulations demonstrate the model’s capacity to reproduce both anomalous diffusion phenomena and realistic stochastic variability, while convergence analysis confirms the numerical scheme’s robustness against varying noise intensities. This integrated fractional stochastic framework substantially advances atmospheric moisture modeling capabilities, with direct applications to meteorological forecasting, coastal climate assessment, and environmental engineering. Full article

Ribbon waterfront parks in hot summer and cold winter regions play a crucial role in microclimate regulation and thermal comfort enhancement due to the combined effects of water bodies and vegetation. This study focuses on ribbon waterfront parks in Hefei. This study investigates the influence of park environmental factors (e.g., plant community characteristics, spatial configuration of water bodies, and plaza layouts) on the summer thermal environment through field measurements and ENVI-met numerical simulations. Based on field studies and a literature review, five environmental factors were selected as test variables: water body direction (S), tree planting density and arrangement (A), square distribution form (B), square location (C), and pavement material (D). Using orthogonal testing, 64 different environmental scenarios under four distinct water body orientations were designed and simulated using ENVI-met (Version 5.6.1), followed by a quantitative analysis of the simulation results. The findings reveal that the interaction between water body orientation and prevailing wind direction significantly influences the cooling efficiency in both the upwind and downwind regions. In addition, through orthogonal testing, Range Analysis (RA), and analysis of variance (ANOVA), the order of magnitude of the effect of each experimental factor on the Universal Thermal Climate Index (UTCI) can be derived: density and form of tree planting (A) > pavement material (D) > location of the square in the park (C) > forms of distribution of squares in the park (B). Finally, this study suggests various environmental factor-setting schemes for ribbon waterfront parks that are tailored to distinct microclimatic requirements. It also provides design recommendations to improve thermal comfort in parks based on the orientation of different water bodies. Furthermore, it offers specific references and foundations for planning, designing, optimising, and renovating waterfront parks of similar scales. Full article

Urban green spaces play a crucial role in mitigating the effects of urban microclimates. This study quantitatively explored how the spatial structural parameters of plant communities regulate microclimates during the hot summer in Zhuji City, Zhejiang Province. Field measurements and ENVI-met simulations were conducted to evaluate the microclimatic effects of different plant communities, including broadleaf and coniferous tree communities. Microclimatic variables, such as air temperature, relative humidity, and solar radiation, were analyzed. The results revealed that spatial structural parameters, such as Acanopy/H, sky view factor (SVF), and canopy density, significantly affected temperature reduction and humidity increase. Among these, the canopy-to-height ratio (Acanopy/H) was a promising potential factor influencing cooling. Simulations revealed that with a constant tree height, cooling and humidification benefits increased as Acanopy/H increased. However, with a constant canopy area, these benefits were greater when Acanopy/H ratio decreased. This study emphasizes the importance of spatial structural parameters in optimizing summer microclimatic regulation, providing key insights into urban green space design to enhance thermal comfort. These findings can guide the planning of climate-resilient plant landscapes in subtropical cities. Full article

The discourse around ‘nature-based solutions’ (NBSs) is quite recent, but this paper contends that, as knowledge and practice, the notion of NBS is not novel. Indigenous and rural communities are known to work closely with nature to fulfil their water needs, eke out sustainable livelihoods, and cope with climate variability and the impacts of natural disasters. India is a country where NBS has been a tradition for millennia. Water has been sustainably managed here and related societal challenges successfully met through the use of nature, natural systems, or natural processes within rural as well as urban settings. However, despite the merits, in recent times, many of the old NBSs have come to be neglected and degraded, being increasingly replaced by gray infrastructure. These changes are deepening the water crisis in the country, with the rapidly transforming peri-urban locations being an important area of concern. This paper outlines some of the major NBS forms traditionally established and used in different parts of India. Thereafter, using an integrated analytical framework for assessing sustainability of NBS (developed under project NATWIP), the value of the NBS legacy in India will be analyzed. Finally, the paper proposes important lessons as a way forward for enhancing water sustainability in peri-urban India that is based on the adoption and rejuvenation of the disappearing NBS science in the country. Full article

Stormwater runoff containing road deicing salts has led to the increasing salinization of surface waters in northern climates, and urban municipalities are increasingly being mandated to manage stormwater runoff to improve water quality. We assessed chloride concentrations in runoff from late-winter snowmelt and rainfall events flowing into an urban Minnesota, USA, lake during two different years, predicting that specific stormwater drainages with greater concentrations of roadways and parking lots would produce higher chloride loads during runoff than other drainages with fewer impervious surfaces. Chloride levels were measured in runoff draining into Lake Winona via 11 stormwater outfalls, a single channelized creek inlet, and two in-lake locations during each snowmelt or rainfall event from mid-February through early April in 2021 and 2023. In total, 33% of outfall runoff samples entering the lake collected over two years had chloride concentrations exceeding the 230 ppm chronic standard for aquatic life in USA surface waters, but no sample exceeded the 860 ppm acute standard. Chloride concentrations in outfall runoff (mean ± SD; 190 ± 191 ppm, n = 143) were significantly higher than in-lake concentrations (43 ± 14 ppm, n = 25), but chloride levels did not differ significantly between snowmelt and rainfall runoff events. Runoff from highway locations had higher chloride concentrations than runoff from residential areas. Site-specific chloride levels were highly variable both within and between years, with only a single monitored outfall displaying high chloride levels in both years. There are several possible avenues available within the city to reduce deicer use, capture and treat salt-laden runoff, and prevent or reduce the delivery of chlorides to the lake. Full article

The article addresses the current and future potential distribution of Drosophila suzukii (Diptera: Drosophilidae), commonly known as spotted wing Drosophila (SWD). This invasive pest affects various fruit crops worldwide. Native to Southeast Asia, the species has rapidly expanded due to its high adaptability to climates and ability to infest ripe fruits. SWD occurrence data were collected from multiple databases, pseudo-absences were selected from the background area, and climatic variables were downloaded from WorldClim. The Random Forest algorithm was employed to model the current distribution and project future scenarios, categorizing environmental suitability into high, moderate, and low levels. The analysis of bioclimatic variables indicated that factors such as isothermality, maximum temperature of the warmest month, and precipitation of the driest month are the most significant for pest distribution. The results revealed high climatic suitability for the species in North America, Europe, and Asia, with projections indicating expansion under climate change scenarios in the Northern Hemisphere, including new areas in Europe and North America. Regions with higher suitability are expected to require management and monitoring strategies, particularly in vulnerable agricultural areas. Furthermore, the study underscores the importance of climatic data in predicting pest distribution and formulating effective control and mitigation policies. Full article

Under the dual pressures of climate change and rapid urbanization, a comprehensive analysis of vegetation’s spatiotemporal patterns and their driving forces plays a pivotal role for addressing global ecological challenges. However, systematic bibliometric analyses in this field remain limited. This study involved a comprehensive bibliometric analysis of 18,270 related publications from 1989 to 2024 retrieved from the Web of Science SCI-Expanded database, elucidating research trends, methodologies, and key thematic areas. Utilizing the bibliometrix and biblioshiny tools, the results reveal an annual average growth rate of 17.62% in the number of published research articles, indicating rapid research expansion. Climate change emerged as the core driving force, with high-frequency keywords such as “vegetation”, “dynamics”, and “variability”. China (18,687 papers), the United States (14,502 papers), and Germany (3394 papers) are the leading contributors in this domain, with China showing the fastest growth in research output, albeit with relatively lower average citation rates. Core journals, including Remote Sensing of Environment and Global Change Biology, have played pivotal roles in advancing vegetation dynamics research, with remote sensing techniques dominating the field. The study highlights a shift in vegetation dynamics research from single-variable analyses (e.g., temperature, precipitation) to multi-scale and multidimensional approaches around 2010. Regional studies, such as those focusing on the Loess Plateau, are gaining importance, while advancements in remote sensing and machine learning technologies have enhanced the precision and scalability of research. This study provides a comprehensive summary of the current state and development trends in vegetation spatiotemporal dynamics and their driving forces, offering valuable insights for future research in the field. Full article

This study investigates the anatomical adaptations and ecological plasticity of C. ambiguus in extreme environmental conditions by analyzing the structural characteristics of its leaves and annual shoots collected from 12 populations in the arid regions of Mangystau, including Western Karatau, Northern Aktau, and the Tyubkaragan Peninsula. Microscopic and statistical analyses revealed significant variability in key anatomical traits, including epidermal thickness, collenchyma, primary cortex, and vascular bundle area, highlighting the species’ adaptive responses to drought, high solar radiation, and limited water availability. The epidermal thickness ranged from 14.85 µm (Pop_12 Botakan) to 22.51 µm (Pop_6 Samal), demonstrating xeromorphic adaptations for reducing transpiration. At the same time, the vascular bundle area varied from 286.06 × 10⁻³ mm² (Pop_3 Emdikorgan) to 528.51 × 10⁻³ mm² (Samal), indicating differences in water transport efficiency across populations. Despite substantial anatomical variation, the low coefficients of variation (0.31%–6.31%) suggested structural stability, reinforcing C. ambigua’s ability to maintain functional integrity under environmental stress. Canonical Correlation Analysis (CCA) confirmed that environmental factors such as soil type, elevation, and water availability significantly influenced anatomical traits. Floristic analysis revealed distinct patterns of species richness, with the highest diversity recorded in Pop_4 and Pop_7, while Pop_12 and Pop_9 exhibited lower diversity, indicating potential vulnerability. Furthermore, the identified anatomical traits could serve as key markers for selecting drought-resistant genotypes in afforestation and restoration programs. This study also highlighted the need for the long-term monitoring of C. ambigua populations to assess the impact of climate change on structural adaptations. These findings offer a framework for integrating ecological and genetic studies to refine conservation strategies for xerophytic species. Full article

Hippophae neurocarpa is a relatively new member of the Rhamnus genus that has various potential edible and medicinal values, but still needs to be further developed. To better develop H. neurocarpa, it is crucial to determine its current and future population distribution. This study utilized the “Biomod2” package in R to integrate five individual models and investigate the effects of climate change on the potential distribution of H. neurocarpa, as well as the key climatic factors influencing its distribution. The results indicated that, under the current scenario, the potential distribution of H. neurocarpa is mainly concentrated in the eastern parts of the Loess Plateau and the Qinghai–Tibet Plateau. In the future, its potential suitable habitats will undergo varying degrees of change: the area of medium/low suitability will decrease, while the area of high suitability will shift westward and increase. In the analysis of area changes, it was found that some potential suitable habitats in Sichuan and Shaanxi will directly transition from highly suitable to unsuitable areas. Key environmental variable analysis showed that temperature, particularly low temperature, is a crucial factor affecting the distribution of H. neurocarpa. Additionally, altitude also has a significant impact on its distribution. This study predicted the potential suitable habitats of H. neurocarpa, which will aid in its future development and provide reference for selecting regions suitable for its cultivation. Full article

Climate change is increasing variability in environmental conditions and the frequency and severity of natural hazards such as hurricanes, floods, and wildfires. In this paper, we use general systems theory to describe how disaster management systems are composed of four types of system regulators (aggregation, passive, error control, and anticipation) that are deployed to provide protection from natural hazards. We argue that climate change, by changing causal relationships in the environment and thereby reducing the predictability of related hazards and altering exposure to them, is likely to require that disaster management systems be restructured by changing the combinations of system regulators that are employed to prevent or mitigate disasters. This leads to the conclusion that one of the keys to developing effective policies to support adaptation to climate change and to promote sustainability hinges on understanding how disaster management systems can be interpreted as mechanisms for regulating exposure and vulnerability to minimise the threats from natural hazards. Consequently, developing methods for interpreting and modelling system regulators in disaster management systems is an important next step. Full article

Wildfires represent an increasing threat to ecosystems and communities, driven by climate change, fuel dynamics, and human activities. In Ambato, Ecuador, a city in the Andean highlands, these risks are exacerbated by prolonged droughts, vegetation dryness, and urban expansion into fire-prone areas within the Wildland–Urban Interface (WUI). This study integrates climatic, ecological, and socio-economic data from 2017 to 2023 to assess wildfire risks, employing advanced geospatial tools, thematic mapping, and machine learning models, including Multinomial Logistic Regression (MLR), Random Forest, and XGBoost. By segmenting the study area into 1 km² grid cells, microscale risk variations were captured, enabling classification into five categories: ‘Very Low’, ‘Low’, ‘Moderate’, ‘High’, and ‘Very High’. Results indicate that temperature anomalies, reduced fuel moisture, and anthropogenic factors such as waste burning and unregulated land-use changes significantly increase fire susceptibility. Predictive models achieved accuracies of 76.04% (MLR), 77.6% (Random Forest), and 76.5% (XGBoost), effectively identifying high-risk zones. The highest-risk areas were found in Izamba, Pasa, and San Fernando, where over 884.9 ha were burned between 2017 and 2023. The year 2020 recorded the most severe wildfire season (1500 ha burned), coinciding with extended droughts and COVID-19 lockdowns. Findings emphasize the urgent need for enhanced land-use regulations, improved firefighting infrastructure, and community-driven prevention strategies. This research provides a replicable framework for wildfire risk assessment, applicable to other Andean regions and beyond. By integrating data-driven methodologies with policy recommendations, this study contributes to evidence-based wildfire mitigation and resilience planning in climate-sensitive environments. Full article