Search Results (139)

Background/Objectives: Global warming and rising CO₂ concentrations pose significant challenges to plant systems. Amid these pressures, this study contributes to understanding how tropical species respond by simultaneously evaluating reproductive and genetic traits. It specifically investigates the effects of maternal exposure to warming and elevated CO₂ on progeny physiology, genetic diversity, and population structure in Stylosanthes capitata, a resilient forage legume native to Brazil. Methods: Maternal plants were cultivated under controlled treatments, including ambient conditions (control), elevated CO₂ at 600 ppm (eCO₂), elevated temperature at +2 °C (eTE), and their combined exposure (eTEeCO₂), within a Trop-T-FACE field facility (Temperature Free-Air Controlled Enhancement and Free-Air Carbon Dioxide Enrichment). Seed traits (seeds per inflorescence, hundred-seed mass, abortion, non-viable seeds, coat color, germination at 32, 40, 71 weeks) and abnormal seedling rates were quantified. Genetic diversity metrics included the average (A) and effective (Ae) number of alleles, observed (Ho) and expected (He) heterozygosity, and inbreeding coefficient (Fis). Population structure was assessed using Principal Coordinates Analysis (PCoA), Analysis of Molecular Variance (AMOVA), number of migrants per generation (Nm), and genetic differentiation index (Fst). Two- and three-way Analysis of Variance (ANOVA) were used to evaluate factor effects. Results: Compared to control conditions, warming increased seeds per inflorescence (+46%), reduced abortion (−42.9%), non-viable seeds (−57%), and altered coat color. The germination speed index (GSI +23.5%) and germination rate (Gr +11%) improved with warming; combined treatments decreased germination time (GT −9.6%). Storage preserved germination traits, with warming enhancing performance over time and reducing abnormal seedlings (−54.5%). Conversely, elevated CO₂ shortened GSI in late stages, impairing germination efficiency. Warming reduced Ae (−35%), He (−20%), and raised Fis (maternal 0.50, progeny 0.58), consistent with the species’ mixed mating system; A and Ho were unaffected. Allele frequency shifts suggested selective pressure under eTE. Warming induced slight structure in PCoA, and AMOVA detected 1% (maternal) and 9% (progeny) variation. Fst = 0.06 and Nm = 3.8 imply environmental influence without isolation. Conclusions: Warming significantly shapes seed quality, reproductive success, and genetic diversity in S. capitata. Improved reproduction and germination suggest adaptive advantages, but higher inbreeding and reduced diversity may constrain long-term resilience. The findings underscore the need for genetic monitoring and broader genetic bases in cultivars confronting environmental stressors. Full article

Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin. Full article

South Korea is one of the world’s major centers for marine shellfish aquaculture. Since the industry’s rapid expansion began in the 1980s, concerns have grown regarding its environmental impacts on coastal marine ecosystems. Evaluating the benthic ecological quality status (EcoQs) of shellfish farms using benthic indices provides a scientific foundation for the sustainable management of aquaculture areas. In our study, five benthic indices (AZTI’s marine biotic index, BENTIX, benthic opportunistic polychaeta amphipoda index, benthic pollution index, and multivariate AMBI) and one composite index were selected to assess EcoQs of shellfish farms in Gangjin Bay, South Korea. Our results revealed significant differences in macrobenthic community structure and EcoQs between November and December in Gangjin Bay. Spearman correlation analysis and principal coordinates analysis (PCoA) demonstrated that the multivariate AMBI (M-AMBI) exhibited the best overall performance among indices. However, considering the ecological complexity, variability in farming practices, and site-specific conditions typical of shellfish aquaculture environments, the use of five benthic indices and a composite index is recommended to ensure a more comprehensive and robust evaluation of EcoQs in Korean shellfish farms. Full article

Arid and semi-arid regions serve as crucial ecological barriers in China, making the spatiotemporal evolution of their ecological environmental quality (EEQ) scientifically significant. This study developed a Modified Remote Sensing Ecological Index (MRSEI) by innovatively integrating the Comprehensive Salinity Indicator (CSI) into the Remote Sensing Ecological Index (RSEI) and applied it to systematically evaluate the spatiotemporal evolution of EEQ (2014–2023) in Yinchuan City, a typical arid region of northwest China along the upper Yellow River. The study revealed the spatiotemporal evolution patterns through the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test, and adopted the Light Gradient Boosting Machine (LightGBM) combined with the Shapley Additive Explanation (SHAP) to quantify the contributions of ten natural and anthropogenic driving factors. The results suggest that (1) the MRSEI outperformed the RSEI, showing 0.41% higher entropy and 5.63% greater contrast, better characterizing the arid region’s heterogeneity. (2) The EEQ showed marked spatial heterogeneity. High-quality areas are concentrated in the Helan Mountains and the integrated urban/rural development demonstration zone, while the core functional zone of the provincial capital, the Helan Mountains ecological corridor, and the eastern eco-economic pilot zone showed lower EEQ. (3) A total of 87.92% of the area (7609.23 km²) remained stable with no significant changes. Notably, degraded areas (934.52 km², 10.80%) exceeded improved zones (111.04 km², 1.28%), demonstrating an overall ecological deterioration trend. (4) This study applied LightGBM with SHAP to analyze the driving factors of EEQ. The results demonstrated that Land Use/Land Cover (LULC) was the predominant driver, contributing 41.52%, followed by the Digital Elevation Model (DEM, 18.26%) and Net Primary Productivity (NPP, 12.63%). This study offers a novel framework for arid ecological monitoring, supporting evidence-based conservation and sustainable development in the Yellow River Basin. Full article

The Hindu Kush–Himalaya (HKH) region is an essential component of the global ecosystem, playing a crucial role in global climate regulation and ecological balance. This study employed a remote sensing ecological index (RSEI) with Geodetector to evaluate the eco-environmental quality and its driving factors within the HKH region. Results revealed a statistically significant upward trend (p < 0.05) in eco-environmental quality across the HKH region during 2001–2023, with the average RSEI value increasing by 23.9%. Areas classified as the Good/Excellent grades (RSEI > 0.6) expanded by ~12%, while areas at the Very Poor grade (RSEI ≤ 0.2) shrunk by ~20%. However, areas classified as the Poor (0.2 < RSEI ≤ 0.4) and Moderate (0.4 < RSEI ≤ 0.6) grades increased by ~11% and ~5%, respectively. This resulted in ~11% of the total area degraded across the HKH. Spatially, the highest ecological quality occurred in the southern Himalayan countries (sub-region R2), followed by China’s Tibetan Plateau (sub-region R3), while the northwestern HKH region (sub-region R3) exhibited the lowest ecological quality. Notably, the sub-region R3 and eastern sub-region R1 had the most pronounced improvement. Precipitation and land cover type were the dominant driving factors, exhibiting nonlinear enhancement effects in their interactions, whereas topographic factors (e.g., elevation) had limited but stable influences. These findings elucidate the spatiotemporal dynamics of HKH’s eco-environmental quality and underscore the combined effects of climatic and geomorphic factors, offering a scientific basis for targeted conservation and sustainable development strategies. Full article

Assessing the ecological environmental quality (EEQ) is crucial for protecting the environment. Dhaka’s rapid, unplanned urbanization, driven by economic and social growth, poses significant eco-environmental challenges. Spatiotemporal ecological and environmental quality changes were assessed using remote sensing based ecological index (RSEI) maps derived from Landsat images (1993, 2003, 2013, and 2023). RSEI was based on four indicators—greenness (NDVI), heat index (LST), dryness (NDBSI), and wetness (LSM). Landsat 5 TM and 8 OLI/TIRS images were processed on Google Earth Engine (GEE), with principal component analysis (PCA) applied to determine RSEI. The findings showed a decline in the overall RSEI (1993–2023), with low- and very low-quality areas increasing by about 39% and high- and very high-quality areas decreasing by 24% of the total area. NDBSI and LST were negatively correlated with RSEI, except in 1993, while NDVI and LSM were generally positive but negative in 1993. The global Moran’s I (0.88–0.93) indicated strong spatial correlation in the distribution of EEQ across Dhaka. LISA cluster maps showed high-high clusters in the northeast and east, while low-low clusters were concentrated in the northwest. This research examines the degradation of ecological conditions over time in Dhaka and provides valuable insights for policymakers to address environmental issues and improve future ecological management. Full article

This study constructs an index system based on provincial data from 2012 to 2023 for forestry industry agglomeration and eco-efficiency. Using methods such as the Coupling Coordination Degree and Relative Development Degree, the study explores the relationship between the coupled and coordinated development of forestry industry agglomeration and eco-efficiency at the provincial level, and introduces a balanced interval to regulate the coupling and coordination process between forestry industry agglomeration and eco-efficiency. The results indicate that: (1) During the study period, the overall coupled and coordinated development of China’s forestry industry agglomeration and eco-efficiency was in an antagonistic stage, with the development of forestry industry agglomeration lagging behind the level of eco-efficiency. (2) The Relative Development Degree of forestry industry agglomeration and eco-efficiency shifted from a “ladder” pattern to an “hourglass” pattern. (3) The process of coupling and coordinating the development of forestry industry agglomeration and eco-efficiency exhibited fluctuations, indicating that future efforts should focus on improving the quality of both forestry industry agglomeration and eco-efficiency to promote coordinated development. (4) During the period from 2012 to 2023, China’s forestry industry agglomeration and eco-efficiency generally failed to simultaneously reach a reasonably balanced state, with notable regional differences. Factors such as the number of non-forestry employees, geographic location, and environmental conditions significantly impacted the balance between forestry industry agglomeration and eco-efficiency. Full article

Scientific and rational monitoring of eco-environmental effects induced by mining activities is a prerequisite for optimizing mining planning and contributes to the advancement of ecological civilization. Remote sensing and multi-source data provide advanced methods for long-term dynamic evaluation of mining-induced eco-environmental effects. This study systematically constructs eco-environmental effect indicators tailored to mining characteristics and establishes quantitative extraction methods based on Landsat data and spectral indices. The Mine Eco-environmental Effect Index (MEEI) was developed using kernel principal component analysis (KPCA). The Heidaigou Open-pit Coal Mine in Jungar Banner was selected as the study area to validate the MEEI’s performance and analyze ecological dynamics across five key temporal phases. Results indicate the following: (1) the KPCA-based MEEI effectively integrates multi-indicator features, offering an objective representation of comprehensive eco-environmental impacts; (2) from 1990 to 2020, the ecological trajectory of the coal mine followed a pattern of “sharp deterioration → gradual slowdown → relative stabilization”, with post-mining restoration and management measures significantly mitigating negative impacts and improving regional ecological quality. This study provides a methodological framework for dynamic evaluation of mining-related eco-environmental effects, supporting sustainable mining practices and ecological governance. Full article

Taking the upper reaches of Huaihe River (UHR) as a research area, based on land use types data with 30 m resolution from 1980 to 2020, the changes in “production–living–ecological space” (PLE) and eco-environmental quality (EQ) in UHR from 1980 to 2020 were analyzed by using the eco-environmental effect evaluation method. Meanwhile, the PLUS model was applied to simulate and forecast the future scenarios for the data of 2010 and 2020, and the data for 2030–2050 under three situations of business as usual, ecological protection, and production priority were obtained, and the changing pattern of PLE and the change in EQ under each scenario were analyzed. Results: (1) From 1980 to 2020, the production and ecological space area in UHR presented a downward–upward–downward tendency and the living space area continued to increase. (2) From 1980 to 2020, the eco-environmental quality index (EV) presented a down–up tendency, and the expansion of lower eco-quality areas was obvious. The conversion of agricultural production (AP) and forest ecological (FE) is the main factor affecting environmental quality change. (3) Under the business as usual and production priority scenarios, the production and ecological space continues to reduce, and the living space continues to augment, but the production space area in the production priority situation is the least in three scenarios. Under the ecological protection scenario, the production space keeps reducing, and the ecological and living space keep increasing. (4) The ecological protection situation has the uppermost EV in three scenarios. The research can provide a scientific basis for territorial spatial planning and sustainable development of UHR. Full article

A thorough understanding of the consequences of urbanization can be significantly advanced by examining urban environmental dynamics at high spatial and temporal resolutions. This study evaluates eco-environmental quality and investigates the underlying drivers of urban greening within the functional units of Haikou, a tropical coastal city located on Hainan Island, China, using advanced techniques from Landsat and Google Earth imagery. Ecological index and land use change analyses were conducted using Landsat 5 (TM) imagery for 2010 and Landsat 8 (OLI) imagery for 2020. In addition, Google Earth imagery was used to interpret the driving factors influencing urban functional units (UFUs) in 2010 and 2020. Spatial and temporal environmental changes were quantitatively assessed. Multi-spectral Landsat 8 data at a 30 m resolution were used to construct a remote sensing ecological index (RSEI) to assess Haikou’s ecological condition. Land use impacts on eco-environmental quality were evaluated through RSEI values from 2010 to 2020, showing that eco-environmental quality improved over time, revealing a gradual improvement over time. Land use across 190 UFUs from 2010 to 2020 was categorized into five types: trees and shrubs, herbs, built-up areas, sandy lands, and water bodies. The primary drivers of greening percentage in each UFU were identified as housing prices, maintenance duration, and construction age. The most significant changes in land cover type were observed in the herb areas. Similarly, maintenance duration emerged as the most influential factor driving changes in urban green space (UGS). In conclusion, this study offers valuable insights for future urban planning and improvements in eco-environmental quality in Haikou, Hainan Island, China. Full article

The impact of energy consumption on sustainable development remains a critical global concern that is deeply influenced by the progress and effectiveness of the ongoing energy transition. The primary objective of this study is to examine the impact of the energy transition (ET) an institutional quality index (IQI) on sustainable development (SD), along with other control variables, including globalization (GLOB), trade openness (TO), gross domestic product per capita (GDP), and economic structure (EcoStru), in E-7 economies from 1990 to 2022. To fulfill this objective, we employ the cross-sectional autoregressive distributive lags (CS-ARDL) technique to tackle issues such as heteroscedasticity, cross-sectional dependence, and interaction across sections caused by variations in slope. Similarly, for the robustness analysis and based on the results of cointegration tests, we employed the Fully Modified Ordinary Least Square (FMOLS) and Canonical Cointegrating Regression (CCR) cointegration models. The empirical findings reveal that the ET, TO, and IQI significantly influence improving sustainable development in the E-7 countries. Meanwhile, GLOB and GDP have been shown to have a detrimental environmental impact. To move toward truly sustainable development, E-7 countries should emphasize the transition to renewable energy and reinforce institutional governance to lessen their dependence on fossil fuels. Full article

The rapid expansion of urban spaces driven by accelerating urbanization has profoundly impacted the eco-environmental quality. However, the dynamic relationship between urbanization and eco-environmental quality remains insufficiently understood. This study quantifies urbanization intensity and eco-environmental quality using the impervious surface distribution density (ISDD) and Remote Sensing-based Ecological Index (RSEI). By examining the spatiotemporal dynamics and evolutionary relationships of these indicators in Hangzhou from 1985 to 2020, we found that urban expansion drove ecological degradation in expansion areas, whereas ecological quality in the old city significantly improved. The ecological response to urbanization intensity exhibited spatial variation: in low-intensity urbanized expansion areas, ecological quality declined with increasing urbanization, whereas in the high-intensity urbanized old city, ecological quality improved. Additionally, the degree of coupling coordination between urbanization and ecological quality steadily increased over time, underscoring the importance of rational urban planning and ecological management in achieving sustainable development. This study provides a scientific foundation for urban ecological environment management and offers practical insights for fostering green development in rapidly urbanizing regions. Full article

The coordinated relationship of new-type urbanization (NU) and the eco-environment (EE) is of great significance for high-quality and healthy development. A multi-dimensional index system of NU and EE was established to measure and compare the coordinated level of 30 Chinese provinces from 2009 to 2020 by the entropy method, coupling coordination degree model, and Markov chain. Furthermore, the regional differences in and distribution dynamic evolution of the coordination level of the four east, west, central, and northeast regions in China were analyzed using the Dagum Gini coefficient and the kernel density estimation method. The results showed that China’s NU and EE was in the low coordination state, and the distribution was uneven. In addition, the coordinated evolution was continuous. The study also revealed that intra-regional differences in coordination level were small and stable in China, and the overall difference in NU and EE coordination was mainly ascribed to inter-regional difference. The national coordination level rose, and the polarization phenomenon gradually disappeared. In the process of NU, the environmental capacity in China should be considered to promote the coordinated development of regions and fully reflect the sustainable development requirements of NU. Full article

The Yellow River Basin (YRB) serves as a critical ecological functional and economic zone in China. However, due to the rapid economic and social development, the YRB has encountered dual pressure from the anthropogenic disturbances and climate change, leading to intensified conflicts among production, living, and ecological spaces (PLES). In this study, we examined the spatiotemporal evolution pattern and transition mode of the PLES from 1980 to 2020 at the county level, evaluated the eco-environmental effects, and identified the key driving factors. The results indicate that land-use changes in the YRB are marked by a continuous increase in living space, while ecological spaces initially decreased before increasing, and production spaces initially increased before decreasing, with the year 2000 serving as a pivotal point in these transitions. At the county level, land-use transformations in the YRB have significant spatial differentiation. The north region of the Hu Line is predominantly characterized by a reduction in ecological space, whereas the south primarily exhibits declines in production space and increases in living space in the downstream region. Consequently, the environmental quality index (EQI) also exhibits a trend of an initial decline followed by an increase. Frequent mutual conversions between production and ecological spaces influenced by major national ecological conservation policies after 2000, as well as pressure from living spaces on production spaces influenced by population and GDP growth, have been the primary manifestations of spatial transformation in the region. These findings suggest that with the implementation of appropriate governance measures, exploring the transformation of PLES at a finer county level can provide a clearer pattern of spatiotemporal changes, supporting detailed basin management for sustainable development. Full article

Soybean oil is the second most consumed vegetable oil worldwide and is recognized as a source of heart-healthy polyunsaturated fatty acids. Optimizing the extraction process in the oil industry is essential for both economic and environmental sustainability. This research aimed to determine the optimal conditions for various extraction parameters—stripper temperature (110–140 °C), stripper pressure (150–210 mbar), and dryer pressure (60–120 mbar)—and their effects on the physicochemical properties of soybean oil. These properties include oil-insoluble fine substances, acidity, the color index, peroxide value, oxidative stability, and moisture content. The results indicated that the stripper temperature significantly influenced oil-insoluble fine substances, acidity, the color index, and peroxide value (p < 0.05). The optimal conditions for oil extraction were found to be a stripper temperature of 110 °C, a stripper pressure of 150 mbar, and a dryer pressure of 120 mbar. Under these conditions, the oil-insoluble fine substances, acidity, the color index, peroxide value, oxidative stability, and moisture content of soybean oil were in the ranges of 0.2–0.58%, 0.63–1.15%, 4.3–5.5, 0.67–1.23 meqO₂/kg, 3–5.5, and 0.05–0.11%, respectively. These findings provide valuable insight for optimizing soybean oil extraction processes to enhance quality and efficiency. Future advancements in industrial oil extraction are expected to focus on integrating efficient, eco-friendly technologies and enhancing precision through automation and data analytics to optimize yield and minimize waste. Full article