Search Results (1,701)

To investigate the spatiotemporal evolution characteristics and primary driving factors of Gross Primary Productivity (GPP) on the Qinghai-Tibet Plateau, we employed an enhanced MODIS-PSN model. Utilizing the fifth-generation global climate reanalysis dataset (ECMWF ERA5), we generated GPP remote sensing products by integrating six natural factors. Through correlation analysis and geographical detector modeling, we quantitatively analyzed the spatiotemporal dynamics and key drivers of vegetation GPP across the Qinghai-Tibet Plateau from 2001 to 2022. The results demonstrate that GPP changes across the Qinghai-Tibet Plateau display pronounced spatial heterogeneity. The humid northeastern and southeastern regions exhibit significantly positive change rates, primarily distributed across wetland and forest ecosystems, with a maximum mean annual change rate of 12.40 gC/m²/year. In contrast, the central and southern regions display a decreasing trend, with the minimum change rate reaching −1.61 gC/m²/year, predominantly concentrated in alpine grasslands and desert areas. Vegetation GPP on the Qinghai-Tibet Plateau shows significant correlations with temperature, vapor pressure deficit (VPD), evapotranspiration (ET), leaf area index (LAI), precipitation, and radiation. Among the factors analyzed, LAI demonstrates the strongest explanatory power for spatial variations in vegetation GPP across the Qinghai-Tibet Plateau. The dominant factors influencing vegetation GPP on the Qinghai-Tibet Plateau are LAI, ET, and precipitation. The pairwise interactions between these factors exhibit linear enhancement effects, demonstrating synergistic multifactor interactions. This study systematically analyzed the response mechanisms and variations of vegetation GPP to multiple driving factors across the Qinghai-Tibet Plateau from a spatial heterogeneity perspective. The findings provide both a critical theoretical framework and practical insights for better understanding ecosystem response dynamics and drought conditions on the plateau. Full article

In plateau wetlands, the interactions of herbaceous roots with ectorhizosphere soil microorganisms represent an important way to realize their ecological functions. Global change-induced aridification of plateau wetlands has altered long-established functional synergistic relationships between plant roots and ectorhizosphere soil microbes, but we still know little about this phenomenon. In this context, nine typical wetlands with three different moisture statuses were selected from the eastern Tibetan Plateau in this study to analyze the relationships among herbaceous plant root traits and microbial communities and functions. The results revealed that drought significantly inhibited the accumulation of root biomass and surface area as well as the development of root volumes and diameters. Similarly, drought significantly reduced the diversity of ectorhizosphere soil microbial communities and the relative abundances of key phyla of archaea and bacteria. Redundancy analysis revealed that plant root traits and ectorhizosphere soil microbes were equally regulated by soil physicochemical properties. Functional genes related to carbohydrate metabolism were significantly associated with functional traits related to plant root elongation and nutrient uptake. Functional genes related to carbon and energy metabolism were significantly associated with traits related to plant root support and storage. Key genes such as CS,gltA, and G6PD,zwf help to improve the drought resistance and barrenness resistance of plant roots. This study helps to elucidate the synergistic mechanism of plant and soil microbial functions in plateau wetlands under drought stress, and provides a basis for evolutionary research and conservation of wetland ecosystems in the context of global change. Full article

Abiotic processes have ramifications in wastewater treatment, in situ degradation of organic matter, and cycling of nutrients in wetland ecosystems. Experiments were conducted to investigate abiotic oxidation of organic compounds (lactate) as a function of electron acceptors (ferric citrate and hydrous ferric oxide (HFO), media composition, and pH under anaerobic conditions, using sodium bicarbonate as the buffering agent. Dissolved inorganic carbon (DIC) was used as a proxy for the oxidation of substrates. HFO media generated more DIC compared to ferric citrate containing media. Light and pH had major roles in the oxidation of lactate in the presence of ferric iron. Under dark conditions in the presence or absence of Fe(III), the DIC produced was low in all pH conditions. Inhibition of DIC production was also observed upon photo exposure when Fe (III) was absent. Isotopically, the system showed initial mixing between the bicarbonate and the carbon dioxide produced from oxidation later being dominated by carbon isotope value of lactate used. These redox conditions align with previous studies suggesting cleavage of organic compounds by hydroxyl radicals. The slower redox processes observed here, compared to previous studies, could be due to the scavenging effect of chloride ion on the hydroxyl radical. Full article

Prolonged inundations are altering coastal forest ecosystems of the southeastern US, causing extensive tree die-offs and the development of ghost forests. This hydrological stressor also alters carbon fluxes, threatening the stability of coastal carbon sinks. This study was conducted to investigate the interactions between hydrological drivers and ecosystem responses by analyzing daily eddy covariance flux data from a wetland forest in North Carolina, USA, spanning 2009–2019. We analyzed temporal patterns of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RE) under both flooded and non-flooded conditions and evaluated their relationships with observed tree mortality. Generalized Additive Modeling (GAM) revealed that groundwater table depth (GWT), leaf area index (LAI), NEE, and net radiation (Rn) were key predictors of mortality transitions (R² = 0.98). Elevated GWT induces root anoxia; declining LAI reduces productivity; elevated NEE signals physiological breakdown; and higher Rn may amplify evapotranspiration stress. Receiver Operating Characteristic (ROC) analysis revealed critical early warning thresholds for tree mortality: GWT = 2.23 cm, LAI = 2.99, NEE = 1.27 g C m⁻² d⁻¹, and Rn = 167.54 W m⁻². These values offer a basis for forecasting forest mortality risk and guiding early warning systems. Our findings highlight the dominant role of hydrological variability in ecosystem degradation and offer a threshold-based framework for early detection of mortality risks. This approach provides insights into managing coastal forest resilience amid accelerating sea level rise. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

Global antibiotic use saturates ecosystems with selective pressure, driving mobile genetic element (MGE)-mediated antibiotic resistance gene (ARG) dissemination that destabilizes ecological integrity and breaches public health defenses. This review synthesizes the sources, environmental distribution, and ecological risks of antibiotics and ARGs, emphasizing the mechanisms of horizontal gene transfer (HGT) driven by MGEs such as plasmids, transposons, and integrons. We further conduct a comparative critical analysis of the effectiveness and limitations of antibiotics and ARGs remediation strategies for adsorption (biochar, activated carbon, carbon nanotubes), chemical degradation (advanced oxidation processes, Fenton-based systems), and biological treatment (microbial degradation, constructed wetlands). To effectively curb the spread of antimicrobial resistance and safeguard the sustainability of ecosystems, we propose an integrated “One Health” framework encompassing enhanced global surveillance (antibiotic residues and ARGs dissemination) as well as public education. Full article

(1) Background: Wetlands are ecologically significant ecosystems that support biodiversity and contribute to essential environmental functions such as water purification, carbon storage and flood regulation. However, these ecosystems face increasing pressures from land-use change and degradation, prompting the need for scalable and accurate classification methods to support conservation and policy efforts. In this research, our motivation was to test whether high-spatial-resolution PlanetScope imagery can be used with pixel-based machine learning to support the mapping and monitoring of wetlands at a national scale. (2) Methods: This study compared four machine learning classification models—Random Forest (RF), XGBoost (XGB), Histogram-Based Gradient Boosting (HGB) and a Multi-Layer Perceptron Classifier (MLPC)—to detect and map wetland areas across New Zealand. All models were trained using eight-band SuperDove satellite imagery from PlanetScope, with a spatial resolution of ~3 m, and ancillary geospatial datasets representing topography and soil drainage characteristics, each of which is available globally. (3) Results: All four machine learning models performed well in detecting wetlands from SuperDove imagery and environmental covariates, with varying strengths. The highest accuracy was achieved using all eight image bands alongside features created from supporting geospatial data. For binary wetland classification, the highest F1 scores were recorded by XGB (0.73) and RF/HGB (both 0.72) when including all covariates. MLPC also showed competitive performance (wetland F1 score of 0.71), despite its relatively lower spatial consistency. However, each model over-predicts total wetland area at a national level, an issue which was able to be reduced by increasing the classification probability threshold and spatial filtering. (4) Conclusions: The comparative analysis highlights the strengths and trade-offs of RF, XGB, HGB and MLPC models for wetland classification. While all four methods are viable, RF offers some key advantages, including ease of deployment and transferability, positioning it as a promising candidate for scalable, high-resolution wetland monitoring across diverse ecological settings. Further work is required for verification of small-scale wetlands (<~0.5 ha) and the addition of fine-spatial-scale covariates. Full article

Traditional intensive agricultural system impedes ecological functions, such as nutrient cycling and biodiversity conservation, resulting in excessive nitrogen discharge, CH₄ emission, and ecosystem service losses. To enhance critical ecosystem services and mitigate environmental externalities in paddy fields, we developed a multi-objective agricultural system (MIA system), which combines two eco-functional units: paddy wetlands and Beitang (irrigation water collection pond). Pilot study results demonstrated that the MIA system enhanced biodiversity and inhibited pest outbreak, with only a marginal reduction in rice production compared with the control. Additionally, the paddy wetland effectively removed nitrogen, with removal rates of total nitrogen and dissolved inorganic nitrogen ranging from 0.06 to 0.65 g N m⁻² d⁻¹ and from 0.02 to 0.22 g N m⁻² d⁻¹, respectively. Continuous water flow in the paddy wetland reduced the CH₄ emission by 84.4% compared with the static water conditions. Furthermore, a simulation experiment indicated that tide flow was more effective in mitigating CH₄ emission, with a 68.3% reduction compared with the drying–wetting cycle treatment. The emergy evaluation demonstrated that the MIA system outperformed the ordinary paddy field when considering both critical ecosystem services and environmental externalities. The MIA system exhibited higher emergy self-sufficiency ratio, emergy yield ratio, and emergy sustainable index, along with a lower environmental load ratio. Additionally, the system required minimal transformation, thus a modest investment. By presenting the case of the MIA system, we provide a theoretical foundation for comprehensive management and assessment of agricultural ecosystems, highlighting its significant potential for widespread application. Full article

The Ichubamba Yasepan wetlands, in the Andean páramos of Ecuador, suffer heavy metal contamination due to anthropogenic activities and volcanic ash from Sangay, impacting biodiversity and ecosystem services. This quasi-experimental study evaluated the bioaccumulation and tolerance of metals in high Andean species through stratified random sampling and linear transects in two altitudinal ranges. Concentrations of Cr, Pb, Hg, As, and Fe in water and the tissues of eight dominant plant species were analyzed using atomic absorption spectrophotometry, calculating bioaccumulation indices (BAIs) and applying principal component analysis (PCA), clustering, and linear discriminant analysis (LDA). Twenty-five species from 14 families were identified, predominantly Poaceae and Cyperaceae, with Calamagrostis intermedia as the most relevant (IVI = 12.74). The water exceeded regulatory limits for As, Cr, Fe, and Pb, indicating severe contamination. Carex bonplandii showed a high BAI for Cr (47.8), Taraxacum officinale and Plantago australis for Pb, and Lachemilla orbiculata for Hg, while Fe was widely accumulated. The LDA highlighted differences based on As and Pb, suggesting physiological adaptations. Pollution threatens biodiversity and human health, but C. bonplandii and L. orbiculata have phytoremediation potential. Full article

Mangrove forests are widely recognized for their effectiveness as carbon sinks and serve as critical ecosystems for mitigating the effects of climate change. Current research lacks comprehensive, large-scale carbon storage datasets for wetland ecosystems, particularly across Mexico and other understudied regions worldwide. Therefore, the objective of this study was to develop a high spatial resolution map of carbon stocks, encompassing both aboveground and belowground components, within the Marismas Nacionales system, which is the largest mangrove complex in northeastern Pacific Mexico. Our approach integrates primary field data collected during 2023–2024 and incorporates some historical plot measurements (2011–present) to enhance spatial coverage. These were combined with contemporary remote sensing data, including Sentinel-1, Sentinel-2, and LiDAR, analyzed using Random Forest algorithms. Our spatial models achieved strong predictive accuracy (R² = 0.94–0.95), effectively resolving fine-scale variations driven by canopy structure, hydrologic regime, and spectral heterogeneity. The application of Local Indicators of Spatial Association (LISA) revealed the presence of carbon “hotspots,” which encompass 33% of the total area but contribute to 46% of the overall carbon stocks, amounting to 21.5 Tg C. Notably, elevated concentrations of carbon stocks are observed in the central regions, including the Agua Brava Lagoon and at the southern portion of the study area, where pristine mangrove stands thrive. Also, our analysis reveals that 74.6% of these carbon hotspots fall within existing protected areas, demonstrating relatively effective—though incomplete—conservation coverage across the Marismas Nacionales wetlands. We further identified important cold spots and ecotones that represent priority areas for rehabilitation and adaptive management. These findings establish a transferable framework for enhancing national carbon accounting while advancing nature-based solutions that support both climate mitigation and adaptation goals. Full article

Urban wetlands are increasingly recognized for their ecological and cultural benefits, yet remain underutilized due to limited public awareness and environmental literacy. This study investigates how visitors’ perceptions of wetland ecosystem services influence their motivations to engage with a constructed wetland in Putrajaya, Malaysia. By integrating the ecosystem services framework with push-pull motivation theory, the research aims to bridge knowledge gaps and inform sustainable wetland tourism planning. A structured questionnaire was administered to 420 visitors, with 385 valid responses (response rate: 91.7%). Data were analyzed using non-parametric tests (Kruskal–Wallis, Spearman correlation) and multiple regression analysis. Results show that cultural and regulating services are perceived most positively, while emotional restoration and aesthetic appreciation emerged as key motivational drivers. Regression findings reveal that push factors are stronger predictors of ecosystem service engagement than pull factors. These insights highlight the importance of emotional and psychological connections to nature, offering practical implications for urban wetland management, visitor education and environmental communication strategies. Full article

Every year, a large amount of antibiotics enter aquatic environments globally through discharging of pharmaceutical wastewater and domestic sewage, emissions from agriculture, and livestock, posing a severe threat to ecosystems and human health. Therefore, it is essential to develop efficient adsorption materials for rapid removal of antibiotics in water. In this study, abundant and renewable wetland plants (lotus leaves, Arundo donax, and canna lilies) were utilized as raw materials to prepare biochar through slow pyrolysis combined with KOH chemical activation. The prepared biochar was employed to adsorb typical tetracycline (TC) antibiotics (TC-HCl, CTC-HCl, OTC-HCl) from water. The results showed that the optimum biochar (LBC-600 (1:3)) was prepared at a pyrolysis temperature of 600 °C with the mass ratio of KOH to lotus leaf of 1:3. The optimum pH for the adsorption of the three antibiotics were 5, 4, and 3, respectively. The highest adsorption rates reached 93.32%, 81.44%, and 83.76% for TC-HCl, CTC-HCl, and OTC-HCl with 0.6 g/L of biochar, respectively. At an initial antibiotic concentration of 80 mg·L⁻¹, the maximum adsorption capacities achieved 40.17, 27.76, and 24.6 mg·g⁻¹ for TC-HCl, CTC-HCl, and OTC-HCl, respectively. The adsorption process conformed to the pseudo-second-order kinetic and Langmuir isotherm models, indicating that it was a spontaneous endothermic process and primarily involved monolayer chemical adsorption. This study transformed wetland plant waste into adsorbent and applied it for antibiotic removal, providing a valuable resource utilization strategy and technical support for recycling wetland plant residues and antibiotic removal from water environments. Full article

Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the spatiotemporal dynamics and driving mechanisms of carbon sinks from 2000 to 2022, utilizing the Theil-Sen median trend, Mann-Kendall test, and attribution based on the differentiating equation (ADE). Results showed that (1) the annual mean spatial NEP was 50.24 g C/m²/a, which first increased and then decreased, with an overall trend of −1.5 g C/m²/a. The carbon sink was strongest in spring, declined in summer, and shifted to a carbon source in autumn and winter. (2) Climate variability and human activities contributed +2.17 and −3.73 g C/m²/a to NEP, respectively. Human activities were the primary driver of carbon sink degradation (74.30%), whereas climate change mainly promoted carbon sequestration (25.70%). However, from 2000–2011 to 2011–2022, climate change shifted from enhancing to limiting carbon sequestration, mainly due to the transition from water storage and lake reclamation to ecological restoration policies and intensified climate anomalies. (3) NEP was negatively correlated with precipitation and water level. Land use adjustments, such as forest expansion and conversion of cropland and reed to sedge, alongside maintaining growing season water levels between 24.06~26.44 m, are recommended to sustain and enhance wetland carbon sinks. Despite inherent uncertainties in model parameterization and the lack of sufficient in situ flux validation, these findings could provide valuable scientific insights for wetland carbon management and policy-making. Full article

Groundwater systems are intrinsically linked to climate, with changing conditions significantly altering recharge, storage, and discharge processes, thereby impacting water availability and ecosystem integrity. Critical knowledge gaps persist regarding groundwater equilibrium timescales, water table dynamics, and their governing factors. This study develops a novel remote sensing framework to quantify factor controls on groundwater–climate interaction characteristics in the Heihe River Basin (HRB). High-resolution (0.005° × 0.005°) maps of groundwater response time (GRT) and water table ratio (WTR) were generated using multi-source geospatial data. Employing Geographical Convergent Cross Mapping (GCCM), we established causal relationships between GRT/WTR and their drivers, identifying key influences on groundwater dynamics. Generalized Additive Models (GAM) further quantified the relative contributions of climatic (precipitation, temperature), topographic (DEM, TWI), geologic (hydraulic conductivity, porosity, vadose zone thickness), and vegetative (NDVI, root depth, soil water) factors to GRT/WTR variability. Results indicate an average GRT of ~6.5 × 10⁸ years, with 7.36% of HRB exhibiting sub-century response times and 85.23% exceeding 1000 years. Recharge control dominates shrublands, wetlands, and croplands (WTR < 1), while topography control prevails in forests and barelands (WTR > 1). Key factors collectively explain 86.7% (GRT) and 75.9% (WTR) of observed variance, with spatial GRT variability driven primarily by hydraulic conductivity (34.3%), vadose zone thickness (13.5%), and precipitation (10.8%), while WTR variation is controlled by vadose zone thickness (19.2%), topographic wetness index (16.0%), and temperature (9.6%). These findings provide a scientifically rigorous basis for prioritizing groundwater conservation zones and designing climate-resilient water management policies in arid endorheic basins, with our high-resolution causal attribution framework offering transferable methodologies for global groundwater vulnerability assessments. Full article

Aquatic fungi serve as core ecological engines in freshwater ecosystems, driving organic matter decomposition and energy flow to sustain environmental balance. Wetlands, with their distinct hydrological dynamics and nutrient-rich matrices, serve as critical habitats for these microorganisms. As an internationally designated Ramsar Site, Yunnan Dashanbao Black-Necked Crane National Nature Reserve in China not only sustains endangered black-necked cranes but also harbors a cryptic reservoir of aquatic fungi within its peat marshes and alpine lakes. This study employed high-throughput sequencing to characterize fungal diversity and community structure across 12 understudied wetland sites in the reserve, while analyzing key environmental parameters (dissolved oxygen, pH, total nitrogen, and total phosphorus). A total of 5829 fungal operational taxonomic units (OTUs) spanning 649 genera and 15 phyla were identified, with Tausonia (4.17%) and Cladosporium (1.89%) as dominant genera. Environmental correlations revealed 19 genera significantly linked to abiotic factors. FUNGuild functional profiling highlighted saprotrophs (organic decomposers) and pathogens as predominant trophic guilds. Saprotrophs exhibited strong associations with pH, total nitrogen, and phosphorus, whereas pathogens correlated primarily with pH. These findings unveil the hidden diversity and ecological roles of aquatic fungi in alpine wetlands, emphasizing their sensitivity to environmental gradients. By establishing baseline data on fungal community dynamics, this work advances the understanding of wetland microbial ecology and informs conservation strategies for Ramsar sites. Full article