Search Results (881)

This paper presents an Industrial–Ecological Symbiosis Framework that enables industrial operations to achieve quantifiable ecological gains without compromising operational efficiency. The model integrates Mixed-Integer Linear Programming (MILP) with AI-optimised forecasting to allow real-time adjustments to production and resource use. It was tested across the apparel manufacturing, metalworking, and mining sectors using publicly available benchmark datasets. The framework delivered consistent improvements: fabric waste was reduced by 10.8%, energy efficiency increased by 15%, and carbon emissions decreased by 14%. These gains were statistically validated and quantified using ecological equivalence metrics, including forest carbon sequestration rates and wetland restoration values. Outputs align with national carbon accounting systems, SDG reporting, and policy frameworks—specifically contributing to SDGs 6, 9, and 11–13. By linking industrial decisions directly to verified environmental outcomes, this study demonstrates how adaptive optimisation can support climate goals while maintaining productivity. The framework offers a reproducible, cross-sectoral solution for sustainable industrial development. Full article

The scientific literature currently lacks studies that evaluate the nutritional composition of the tissues of cattle raised in different systems, so that the nutritional effects can be known and used to enhance consumption and use in the diet. The aim was therefore to assess whether the mineral content of muscle tissue (longissimus lumborum) in cattle finished during the rainy season in the Eastern Amazon is influenced by different farming systems. The treatments consisted of four systems (three pasture production systems and one feedlot system). 1. native wetland pasture in Santa Cruz do Arari (Mesoregion of Marajó); 2. native wetland pasture in Monte Alegre (Mesoregion of Baixo Amazonas); 3. cultivated dryland pasture in São Miguel do Guamá (Mesoregion of Nordeste Paraense); and 4. Confinement in Santa Izabel do Pará (Metropolitan Region of Belém). The analyses were carried out on samples of the longissimus lumborum muscle tissue of 48 male, castrated, crossbred Nelore cattle, twelve per breeding system, from commercial farms, destined for meat production, finished during the rainiest period of the year (between January and June). In systems 1 and 2, the animals were slaughtered in licensed slaughterhouses; the animals in systems 3 and 4 were slaughtered in commercial slaughterhouses. Food sampling and chemical analysis, soil sample collection and analysis, longissimus lumborum muscle tissue collection, sample preparation and digestion, and inductively coupled plasma optical emission spectrometry were evaluated. The experimental design was completely randomized in a linear model with four rearing systems and one period (rainy). The data was compared using the Statistical Analysis Systems (SAS) program. All analyses were carried out considering a significance level of 0.05. Samples of the diets offered (pasture and concentrate) were also collected. The Amazon systems influenced the macro- and micromineral content in the muscles of cattle (p < 0.05). The interaction between pasture systems vs. confinement showed differences in the minerals calcium (Ca), magnesium (Mg), phosphorus (P), copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn) (p < 0.05). However, there was no difference in the values of sodium (Na), potassium (K), and sulfur (S) between the rearing systems (p > 0.05). By contrast, the cultivated pasture system vs. extensive pasture showed differences in all the elements evaluated (p < 0.05). The rearing systems of the Eastern Amazon influenced the mineral content of beef, which continues to be an excellent source of macro- and microminerals and can compose the human diet. Full article

The Gahai wetland in Gansu, China, is a key wetland for nationally and globally threatened bird species. This research aims to quantify the economic value of wetland birds by the method of contingent valuation questionnaire, thereby providing a foundation for conservation of avian species. The result indicated that residents were willing to pay between 208 and 230 CNY (29–32 USD $) annually for bird protection, a total annual value of wetland birds in Luqu County ranging from 7.9 M to 8.8 M CNY (1.1–1.3 M USD $). Men, locals, and older individuals were more inclined to contribute and offered higher payments, albeit non-significant correlation between education level and annual income with the willingness to pay. While the depth of understanding of wetland pressures did not significantly influence the willingness to pay, it did show a positive correlation; those with more profound understanding tended to be more generous in their payments. Tibetan male residents were more likely to prioritize ecological and environmental protection due to their religious beliefs and cultural customs, which emphasize the reverence for and compassion towards birds. This research not only complemented and validated the applicability of the contingent valuation method in China but also underscores the considerations that should be taken into account when employing this method. Full article

Wetlands in northeastern Algeria’s Numidia region provide vital ecosystem services, yet their cultural and intangible values (e.g., spiritual or aesthetic benefits) remain under-recognized in policy and practice. This study explores how gender, education, occupation, and wetland protection status influence local perceptions of provisioning, regulating, and cultural ecosystem services. Based on surveys (n = 552) across 12 wetland communities, results show that women place greater importance on cultural services, while those with higher education display more ecological awareness but less connection to traditional practices. Occupation and residence in protected areas also significantly shape valuation. These findings highlight the need for inclusive conservation strategies that integrate gender perspectives and local knowledge, promoting community-driven stewardship. This research supports more equitable and resilient environmental governance. Full article

Ecological security underpins sustainable regional development and human well-being. Tianjin is in the eastern coastal area of China and features coastal wetlands and river systems. Over the past decade, Tianjin has undergone rapid urbanization. Tianjin faces the dual challenges of maintaining ecological security with economic growth, making it crucial to assess Tianjin’s ecological security status. This study constructed a comprehensive framework incorporating ecosystem health, services, and risk data to evaluate the ecological security status of Tianjin in 2012, 2017, and 2022. The results show the following: (1) Land use transfer mainly shows other land use types transferred to construction land. (2) The ecological security index of Tianjin ranges from 0.003 to 0.865, and the annual average values from 2012 to 2022 are 0.496, 0.493, and 0.499, with security levels dominated by medium, medium-high, and high security levels, respectively. The change in ecological security was relatively stable and was dominated by areas with unchanged levels, accounting for 63.72% of the total area. (3) The natural environment, human activities, and ecosystem status jointly influence Tianjin’s ecological security level. Shannon diversity, Shannon evenness, vegetation type, elevation, and mean annual temperature were the main factors affecting changes in ecological security in Tianjin, among which the interaction of Shannon diversity and vegetation type had the most significant influence. This study combines positive and negative aspects to assess ecological security, providing a reference for other regions to conduct ecological security assessments and a scientific basis for ecological management and urban planning decisions in similar regions. Full article

This study focuses on the Dongting Lake region in China and evaluates ecological vulnerability using the Sensitivity–Resilience–Pressure (SRP) framework, integrated with Spatial Principal Component Analysis (SPCA) to calculate the Ecological Vulnerability Index (EVI). The EVI values were classified into five levels using the Natural Breaks (Jenks) method, and spatial autocorrelation analysis was applied to reveal spatial differentiation patterns. The Geodetector model was used to analyze the driving mechanisms of natural and socioeconomic factors on EVI, identifying key influencing variables. Furthermore, the LightGBM algorithm was used for feature optimization, followed by the construction of six machine learning models—Multilayer Perceptron (MLP), Extremely Randomized Trees (ET), Decision Tree (DT), Random Forest (RF), LightGBM, and K-Nearest Neighbors (KNN)—to conduct multi-class classification of ecological vulnerability. Model performance was assessed using ROC–AUC, accuracy, recall, confusion matrix, and Kappa coefficient, and the best-performing model was interpreted using SHAP (SHapley Additive exPlanations). The results indicate that: ① ecological vulnerability increased progressively from the core wetlands and riparian corridors to the transitional zones in the surrounding hills and mountains; ② a significant spatial clustering of ecological vulnerability was observed, with a Moran’s I index of 0.78; ③ Geodetector analysis identified the interaction between NPP (q = 0.329) and precipitation (PRE, q = 0.268) as the dominant factor (q = 0.50) influencing spatial variation of EVI; ④ the Random Forest model achieved the best classification performance (AUC = 0.954, F1 score = 0.78), and SHAP analysis showed that NPP and PRE made the most significant contributions to model predictions. This study proposes a multi-method integrated decision support framework for assessing ecological vulnerability in lake wetland ecosystems. Full article

Coastal wetlands are critical ecosystems that require effective monitoring to support conservation and restoration efforts. This study evaluates the use of small unmanned aerial systems (sUAS) and multispectral imagery to estimate aboveground biomass (AGB) in tidal marshes, comparing models calibrated with destructive versus non-destructive in situ sampling methods. Imagery was collected over South Carolina’s North Inlet-Winyah Bay National Estuarine Research Reserve, and vegetation indices (VIs) were derived from sUAS imagery to model biomass. Stepwise linear regression was used to develop and validate models based on both sampling approaches. Destructive sampling models, particularly those using the Normalized Difference Vegetation Index (NDVI) and Difference Vegetation Index (DVI), achieved the lowest root mean square error (RMSE) values (as low as 70.91 g/m²), indicating higher predictive accuracy. Non-destructive models, while less accurate (minimum RMSE of 214.86 g/m²), demonstrated higher R² values (0.44 and 0.61), suggesting the potential for broader application with further refinement. These findings highlight the trade-offs between ecological impact and model performance, and support the viability of non-destructive methods for biomass estimation in sensitive wetland environments. Future work should explore machine learning approaches and improved temporal alignment of data collection to enhance model robustness. Full article

Open habitats in forests perform several important functions. In addition to enriching biodiversity, they have an impact on the diversification of the forest landscape, and through complex processes and trophic relationships, they provide greater sustainability in forest communities. It turns out that they are also important not only for the functioning of nature, but also due to their regenerative properties, through which people can improve their well-being and recover their mental balance. The purpose of this study was to determine whether and to what extent mid-forest open dunes and wetlands are able to provide people with feelings of relaxation and mental renewal. The study was conducted in June 2024 in one of the forest complexes located in the suburban zone of Warsaw. The experiment was conducted with the participation of 52 young adult volunteers. The experiment used a pre–posttest method. The subjects’ mood and well-being were determined using four psychological questionnaires: the Positive and Negative Affect Schedule (PANAS), Restorative Outcome Scale (ROS), Subjective Vitality Scale (SVS), and Profile of Mood States (POMSs). The key findings from the research conducted are as follows: compared to the control sample (before entering the forest), exposure to all three variants of greenery had a restorative effect on the experimental participants; the water environment had the most favorable effect compared to the control sample (before entering the forest); and exposure to this environment provided the greatest increase in positive feelings and the greatest decrease in negative feelings. Research has shown that areas important for preserving forest biodiversity are also important for humans because of their high restorative properties. Preserving non-forest enclaves in forests and promoting their regenerative values for humans can be one nature-based solution to improve people’s health and well-being, especially for people living in urban areas. Full article

[Background] Brasenia schreberi is a perennial floating leaf aquatic plant with high ecological protection value and potential for economic development, and thus, its endangered mechanisms are of great concern. The rapid endangerment of this species in modern times may be primarily attributed to the deterioration of water and soil environmental conditions, as its growth relies on high-quality water and soil. [Objective] Exploring the responses of B. schreberi to water and soil conditions from the perspective of functional traits is of great significance for understanding its endangered mechanisms and implementing effective conservation strategies. [Methods] This study was conducted in the Tengchong Beihai Wetland, which has the largest natural habitat of B. schreberi in China. By measuring the key functional traits of B. schreberi and detecting the water and soil parameters at the collecting sites, the responses of these functional traits to the water and soil conditions have been investigated. [Results] (1) The growth status of B. schreberi affects the expression of its functional traits. Compared with sporadic distribution, B. schreberi in continuous patches have significantly higher stomatal conductance, intercellular CO₂ concentration, transpiration rate, and vein density, while these plants have significantly smaller leaf area and perimeter. (2) Good water quality directly promotes photosynthetic, morphological, and structural traits. However, high soil carbon, nitrogen, and phosphorus contents can inhibit the photosynthetic rate. The net photosynthetic rate is significantly positively correlated with dissolved oxygen content, pH value, ammonia nitrogen, and nitrate nitrogen contents in the water, as well as the magnesium, zinc, and silicon contents in the soil. In contrast, the net photosynthetic rate is significantly negatively correlated with the total phosphorus content in water and the total carbon, total nitrogen, and total phosphorus content in the soil. (3) Leaf area and perimeter show positive correlations with various water parameters, including the depth, temperature, pH value, dissolved oxygen content, ammonium nitrogen, and nitrate nitrogen content, yet they are negatively correlated with total phosphorus content, chemical oxygen demand, biological oxygen demand, and permanganate index of water. [Conclusions] This study supports the idea that B. schreberi thrives in oligotrophic water environments, while the notion that fertile soil is required for its growth still needs to be investigated more thoroughly. Full article

As an ecological transition zone, the ecosystem of the Qin River Basin in the middle reaches of the Yellow River is of great significance to the regional ecological balance. With the rapid socio-economic development, land use changes are significant, and the spatial and temporal patterns of ecosystems are evolving. Exploring its dynamics and driving mechanisms is crucial to the ecological protection and sustainable development of watersheds. This research systematically examines the spatiotemporal dynamics and driving mechanisms of ecosystem patterns in the middle Yellow River’s Qin River Basin (1990–2020). Quantitative assessments integrating ecosystem transition metrics and redundancy analysis reveal three critical insights: (1) dominance of agricultural land and woodland (74.81% combined coverage), with grassland (18.58%) and other land types (6.61%) constituting secondary components; (2) dynamic interconversion between woodland and grassland accompanied by urban encroachment on agricultural land, manifesting as net reductions in woodland (−13.74%), farmland (−6.60%), and wetland (−38.64%) contrasting with grassland (+43.34%) and built-up area (+116.63%) expansion; (3) quantified anthropogenic drivers showing agricultural intensification (45.03%) and ecological protection measures (36.50%) as primary forces, while urbanization account for 18.47% of observed changes. The first two RDA ordination axes significantly (p < 0.01) explain 68.3% of the variance in ecosystem evolution, particularly linking land-use changes to socioeconomic indicators. Based on these findings, the study proposes integrated watershed management strategies emphasizing scientific land-use optimization, controlled urban expansion, and systematic ecological rehabilitation to enhance landscape stability in this ecologically sensitive region. The conclusions of this study have important reference value for other ecologically sensitive watersheds in land use planning, ecological protection policy making, and ecological restoration practice, which can provide a theoretical basis and practical guidance. Full article

Under the context of global climate change, sea-level rise and frequent storm surge events pose significant challenges to coastal areas. Protecting coastlines from erosion, mitigating socio-economic losses, and maintaining ecosystem balance are critical for the sustainable development of coastal zones. The concept of “living shorelines” based on Nature-based Solutions (NbS) employs near-natural ecological restoration and protection measures. In low-energy coastal segments, natural materials are prioritized, while high-energy segments are supplemented with artificial structures. This approach not only enhances disaster resilience but also preserves coastal ecosystem stability and ecological functionality. This study constructs a coastal vitality evaluation system for Fujian Province, China, using the entropy weight method, integrating three dimensions: protective safety, ecological resilience, and economic vitality. Data from 2010 and 2020 were analyzed to assess the spatiotemporal evolution of coastal vitality. Results indicate that coastal vitality initially exhibited a spatial pattern of “low in the north, high in the center, and low in the south,” with vitality values ranging from 0.20 to 0.67 (higher values indicate stronger vitality). Over the past decade, ecological restoration projects have significantly improved coastal vitality, particularly in central and southern regions, where high-vitality segments increased markedly. Key factors influencing coastal vitality include water quality, cyclone intensity, biological shoreline length, and wetland area. NbS-aligned coastal management strategies and soft revetment practices have generated substantial ecological and economic benefits. To further enhance coastal vitality, region-specific approaches are recommended, emphasizing rational resource utilization, optimization of ecological and economic values, and the establishment of a sustainable evaluation framework. This study provides scientific insights for improving coastal protection capacity, ecological resilience, and economic potential. Full article

A key challenge is how to effectively conserve habitats and biodiversity amid widespread habitat fragmentation and loss caused by global urbanization. Despite growing attention to this issue, knowledge of the seasonal dynamics of habitats remains limited, and conservation gaps are still inadequately identified. This study proposes a novel integrated framework, “Habitat Suitability–Risk–Quality”, to improve the assessment of the seasonal bird habitat quality and to identify priority conservation habitats in urban landscapes. The framework was implemented in Wuhan, China, a critical stopover site along the East Asian–Australasian Flyway. It combines the Maximum Entropy (MaxEnt) model to predict the seasonal habitat suitability, the Habitat Risk Assessment (HRA) model to quantify habitat sensitivity to multiple anthropogenic threats, and a refined Habitat Quality (HQ) model to evaluate the seasonal habitat quality. K-means clustering was then applied to group habitats based on seasonal quality dynamics, enabling the identification of priority areas and the development of differentiated conservation strategies. The results show significant seasonal variation in habitat suitability and quality. Wetlands provided the highest-quality habitats in autumn and winter, grasslands exhibited moderate seasonal quality, and forests showed the least seasonal fluctuation. The spatial analysis revealed that high-quality wetland habitats form an ecological belt along the urban–suburban fringe. Four habitat clusters with distinct seasonal characteristics were then identified. However, spatial mismatches were found between existing protected areas and habitats of high ecological value. Notably, Cluster 1 maintained high habitat quality year round, spanning 99.38 km², yet only 46.51% of its area is currently protected. The remaining 53.16 km², mostly situated in urban–suburban transitional zones, remain unprotected. This study provides valuable insights for identifying priority habitats and developing season-specific conservation strategies in rapidly urbanizing regions, thereby supporting the sustainable management of urban biodiversity and the development of resilient ecological systems. Full article

This study investigates the salinization processes affecting the coastal aquifer within the Torre Guaceto State Nature Reserve, a Mediterranean coastal area characterized by a unique ecological value of a brackish wetland threatened by water-intensive agricultural activities. Groundwater salinization threatens biodiversity, agriculture, and water resource sustainability. This work integrates hydrogeological monitoring, geochemical and isotopic analyses, and geophysical surveys to understand salinity dynamics and identify key drivers, such as seawater intrusion, irrigation practices, and climate change. Data collected during monitoring campaigns from 2022 to 2024 reveal significant seasonal and spatial variations in groundwater salinity influenced by natural and human-induced factors. The results indicate that salt recycling from irrigation and marine spray deposition are important local contributors to groundwater salinity, in addition to seawater intrusion. These findings highlight the urgent need for integrated groundwater management approaches considering the combined effects of agricultural practices, irrigation water quality, and climate variability tailored to Mediterranean coastal ecosystems. Full article

Unmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of Suaeda salsa using UAV-based visible-light imagery combined with hue angle inversion modeling. By integrating diffuse reflectance standard plates into the flight protocol, we converted RGB pixel values into reflectance and derived hue angle metrics with enhanced radiometric accuracy. A hue angle cutoff threshold of 249.01° was identified as the optimal cutoff to distinguish Suaeda salsa from the surrounding land cover types with high confidence. To estimate biomass, we developed an exponential inversion model based on hue angle data calibrated through extensive field measurements. The resulting model—Biomass = 3.57639 × 10⁻¹⁵ × e^0.12201×α—achieved exceptional performance (R² = 0.99696; MAPE = 3.616%; RMSE = 0.02183 kg/m²), indicating strong predictive accuracy and robustness. This study highlights a cost-effective, non-destructive, and scalable method for the real-time monitoring of coastal vegetation, offering a significant advancement in remote sensing applications for wetland ecosystem management. Full article

Potamogeton crispus (P. crispus), with strong nitrogen uptake capacity, plays an important ecological role during winter and early spring when most aquatic plants are inactive. Its presence can also influence microbial denitrification in sediments by regulating oxygen levels and organic carbon availability. In this study, an indoor hydroponic simulation system was used to systematically evaluate the effects of P. crispus under different nitrogen-loading conditions on nitrogen removal from water, changes in sediment carbon and nitrogen fractions, microbial community structure, and greenhouse gas fluxes. The results showed that P. crispus effectively removed TN, NH₄⁺-N, NO₃⁻-N, and NO₂⁻-N, maintaining strong denitrification capacity even under high-nitrogen loading. Under all nitrogen conditions, TN removal exceeded 80%, while NH₄⁺-N and NO₃⁻-N removal efficiencies surpassed 90%, with effective suppression of NO₂⁻-N accumulation. Rhizosphere-mediated regulation by P. crispus enhanced the transformation and stabilization of DOC and NO₃⁻-N in sediments, while also mitigating nitrogen-induced disturbances to carbon–nitrogen balance. The plant also exhibited strong CO₂ uptake capacity, low CH₄ emissions with a slight increase under higher nitrogen loading, and N₂O fluxes that were significantly affected by nitrogen levels—showing negative values under low nitrogen and sharp increases under high-nitrogen conditions. Correlation analyses indicated that CO₂ and N₂O emissions were mainly regulated by microbial taxa involved in carbon and nitrogen transformation, while CH₄ emissions were primarily driven by methanogenic archaea and showed weaker correlations with environmental factors. These findings highlight the importance of water restoration during low-temperature seasons and provide a theoretical basis for integrated wetland management strategies aimed at coordinated pollution reduction and carbon mitigation. Full article