Prairie Pothole wetlands have large temporal changes in water status. The wetlands are often flooded, with water above the soil surface during the early growing season, while becoming dry during the later growing season or for years under strong drought. We used the eddy covariance technique to assess the potential for ecosystem carbon sequestration as a natural climate solution in a large Prairie Pothole wetland in southern Alberta (Frank Lake wetland complex) that was dominated by the emergent macrophyte, Schoenoplectus acutus L. (bulrush). We made ecosystem-scale measurements of CO2 and CH4 exchange over two growing seasons during a time-period with environmental conditions that were warmer and drier than the climate normal. In particular, the study was conducted while the wetland had been experiencing a decade-long drought based on the Standardized Precipitation Evapotranspiration Index. To provide perspective on the longer-term temporal variability of ecosystem carbon exchange processes, we also used LandSat NDVI measurements of vegetation greenness, calibrated with eddy covariance measurements of ecosystem CO2 exchange during 2022-23, to estimate carbon sequestration capacity during 1984-2023, a period that included several wet-dry cycles. Our measured growing season-integrated net CO2 uptake values were 47 and 70 g C m-2 season-1 in 2022 and 2023, respectively. Including the measured low methane emissions (converted to CO2 equivalents based on a Sustained Global Warming Potential) only changed the net sink to 40 and 67 g C m-2 season-1 in 2022 and 2023, respectively. Despite drought conditions over the last decade, measured ecosystem carbon sequestration values were close to average values during 1984-2023, based on NDVI measurements and model carbon flux calculations. Our results demonstrated net carbon sequestration as a natural climate solution in a Prairie Pothole wetland, even during a time-period that was not expected to be favourable for carbon sequestration because of the drought conditions.

The Tiaozini wetland is an important part of the Yancheng Coastal Wetland, which is a World Natural Heritage Site. With the invasion of Spartina alterniflora, the ecology of the wetland has been severely damaged. The local government has carried out an ecological project to remove Spartina alterniflora, but the long-term influence of ecological projects is unknown. In order to explore the overall impact of ecological restoration projects, the soil at different depths (0 similar to 20 cm, 20 similar to 40 cm, 40 similar to 60 cm) was collected in the plowing area, flooding area, and suaeda area of the Tiaozini wetland. Then, the physicochemical properties and the microbial community of the soil were comprehensively analyzed. The Tiaozini wetland has made satisfactory progress in controlling Spartina alterniflora. And the results show that Tiaozini wetland still plays an important role in carbon sequestration, with the soil organic carbon density ranging from 34.23 +/- 0.02 kg/m(2) to 56.07 +/- 0.04 kg/m(2), which makes it an important blue carbon sink. The high salinity and invasion of Spartina alterniflora inhibit soil nitrogen, phosphorus cycling, and soil enzyme activities. In addition, plowing destroys the microbial structure and reduces the biodiversity of the soil. While the integrated management method has little negative impact on the microbial communities of soil, the invasion of Spartina alterniflora can lead to the accumulation of heavy metals in the environment. Accordingly, this paper further reveals that regional heavy metals are all lower than the background value, but the E-r (potential ecological risk factor of heavy metals) of Cd reached 21.35, indicating a high risk. Furthermore, this paper provides a scientific basis for the government to control Spartina alterniflora, as well as focusing on the overall impact of treatment methods on environmental factors and microorganisms.

Reducing carbon emissions and increasing carbon sinks have become the core issues of the international community. Although coastal blue carbon ecosystems (such as mangroves, seagrass beds, coastal salt marshes and large algae) account for less than 0.5% of the seafloor area, they contain more than 50% of marine carbon reserves, occupying an important position in the global carbon cycle. However, with the rapid development of the economy and the continuous expansion of human activities, coastal wetlands have suffered serious damage, and their carbon sequestration capacity has been greatly limited. Ecological restoration has emerged as a key measure to reverse this trend. Through a series of measures, including restoring the hydrological conditions of damaged wetlands, cultivating suitable plant species, effectively managing invasive species and rebuilding habitats, ecological restoration is committed to restoring the ecological functions of wetlands and increasing their ecological service value. Therefore, this paper first reviews the research status and influencing factors of coastal wetland carbon sinks, discusses the objectives, types and measures of various coastal wetland ecological restoration projects, analyzes the impact of these ecological restoration projects on wetland carbon sink function, and proposes suggestions for incorporating carbon sink enhancement into wetland ecological restoration.

In order to improve the regional environment in light of the socioeconomic development that has taken place in China's coastal regions, ecological engineering construction projects must be designed and implemented, including (but not limited to) (1) the use of artificial beach restoration technology, (2) the construction of coastal protective forest belts, (3) the development of a shoreline farmland shelterbelt network, (4) the establishment of new mangrove forest areas, and (5) the restoration and protection of wetlands. The implementation of such projects can help prevent and mitigate against natural disasters, whilst at the same time protecting the environment, sheltering the land against wind and sand damage, conserving water and soil, preventing aquatic pollution, ensuring waterway security, purifying the atmosphere, and conserving biodiversity, ultimately forming an ecological barrier to achieve regional ecosystem balance. Therefore, the construction of coastal ecological engineering projects is crucial to securing ecological safety and improving the environmental status of coastal areas; plus, it is of great importance to the promotion of coordinated socioeconomic development in these regions.

Permafrost, a major component of the cryosphere, is undergoing rapid degradation due to climate change, human activities, and other external disturbances, profoundly impacting ecosystems, hydroclimate, engineering geological stability, and infrastructure. In Northeast China, the thermal dynamics of Xing'an permafrost (XAP) are particularly complex, complicating the accurate assessment of its spatial extent. Many earlier mapping efforts, despite significant progress, fall short in accounting for some key local geo-environmental factors. Thus, this study introduces a new approach that incorporates four key driving factors-biotic, climatic, physiographic, and anthropogenic-by integrating multisource datasets and in situ observations. Four machine learning (ML) models [random forest (RF), support vector machine (SVM), logistic regression (LR), and extreme gradient boosting (XGB)] are applied to simulate permafrost distribution and probability, as well as to evaluate their performance. The results indicate that models' accuracy, ranked from highest to lowest, is as follows: RF (area under the curve (AUC) =0.88 and accuracy =0.81), XGB (0.86 and 0.77), LR (0.81 and 0.73), and SVM (0.76 and 0.66), with RF emerging as the most effective model for permafrost mapping in Northeast China. Analysis of the relationships between predictors and permafrost occurrence probability (POP) indicates that vegetation and snow cover exert nonlinear effects on permafrost, while human activities significantly reduce POP. Additionally, finer soil textures and higher soil organic matter content are positively correlated with increased POP. The modeling results, combined with field survey data, also show that permafrost is more prevalent in lowlands than in uplands, confirming the symbiotic relationship between permafrost and wetlands in Northeast China. This spatial variation is influenced by local microclimates, runoff patterns, and soil thermal properties. The primary sources of model error are uncertainties in the accuracy of multisource datasets at different scales and the reliability of observational data. Overall, ML models demonstrate great potential for mapping permafrost in Northeast China.

This study aims to explore the effects of arbuscular mycorrhizal fungi (AMF) on the growth of Iris pseudacorus L. and treatment efficacy in constructed wetlands (CWs) subjected to stress from per-and poly-fluoroalkyl substances (PFASs). The findings reveal that PFASs exposure induces oxidative damage and inhibits the growth of I . pseudacorus. However, AMF symbiosis enhances plant tolerance to PFAS stress by modulating oxidative responses. AMF treatment not only promoted plant growth but also improved photosynthetic efficiency under PFAS exposure. Compared to non-AMF treatment, those with AMF treatment exhibited significantly increased levels of peroxidases and antioxidant enzymes, including peroxidase and superoxide dismutase, along with a notable reduction in lipid peroxidation. Additionally, AM symbiosis markedly enhanced the efficacy of CWs in the remediation of wastewater under PFASs-induced stress, with removal efficiencies for COD, TP, TN, and NH4+- N increasing by 19-34%, 67-180%, 106-137%, and 25-95%, respectively, compared to the AMF- treatments. In addition, the metabolic pathways of PFASs appeared to be influenced by their carbon chain length, with long- chain PFASs like perfluorooctanoic acid (PFOA) and perfluoro anionic acid (PFNA) exhibiting more complex pathways compared to short-chain PFASs such as perfluoro acetic acid (PFPeA), and perfluoro hexanoic acid (PFHpA). These results suggest that AMF-plant symbiosis can enhance plant resilience against PFAS-induced stress and improve the pollutant removal efficiency of CWs. This study highlights the significant potential of AMF in enhancing environmental remediation strategies, providing new insights for the more effective management of PFAS-contaminated ecosystems.

Ground freeze-thaw processes have significant impacts on infiltration, runoff and evapotranspiration. However, there are still critical knowledge gaps in understanding of hydrological processes in permafrost regions, especially of the interactions among permafrost, ecology, and hydrology. In this study, an alpine permafrost basin on the northeastern Qinghai-Tibet Plateau was selected to conduct hydrological and meteorological observations. We analyzed the annual variations in runoff, precipitation, evapotranspiration, and changes in water storage, as well as the mechanisms for runoff generation in the basin from May 2014 to December 2015. The annual flow curve in the basin exhibited peaks both in spring and autumn floods. The high ratio of evapotranspiration to annual precipitation (>1.0) in the investigated wetland is mainly due to the considerably underestimated 'observed' precipitation caused by the wind-induced instrumental error and the neglect of snow sublimation. The stream flow from early May to late October probably came from the lateral discharge of subsurface flow in alpine wetlands. This study can provide data support and validation for hydrological model simulation and prediction, as well as water resource assessment, in the upper Yellow River Basin, especially for the headwater area. The results also provide case support for permafrost hydrology modeling in ungauged or poorly gauged watersheds in the High Mountain Asia.

Coastal wetlands are extremely vulnerable to both marine damage and human activities. In order to protect these wetlands, many artificial seawalls have been constructed. However, studies are required to understand how coastal wetlands will evolve under the influence of artificial seawalls. Therefore, to understand this succession process of plants and their adaptation to habitats divided by seawalls, two different habitats inside and outside the seawalls were selected in Laizhou Bay, China. The results showed that there were 5 plant species outside the seawalls that were lower than the 13 species inside. Additionally, the dominant plant species were varied between the two habitats, with mostly annual herbs observed outside the seawalls and perennial shrubs inside. Soil salinity was higher outside the seawalls, which was the key impact factor of soil nutrient differences. The distribution of annual and perennial species may be constrained by spatial differences in soil stoichiometry. Therefore, the plants in coastal wetlands vary significantly at a small scale in response to the disturbance of artificial seawalls. The differences in soil and plants between the two habitats divided by the artificial seawalls provide a new insight for evaluating the artificial coastal projects. The only way to reduce the effects of seawalls on natural coastal wetland vegetation and ecosystem functions is to restore connectivity of tidal flow inside and outside the seawalls.

Petroleum pollution in soil is very damaging to the areas affected by the accidental release of petroleum hydrocarbons and has destructive impacts on natural resources and environmental health. Therefore, its monitoring and analysis are critical, however, due to the cost and time associated with chemical approaches, finding a quick and cost-effective analytical method is valuable. This study was conducted to evaluate the potential of using visible near infrared (Vis-NIR) spectroscopy to predict total petroleum hydrocarbons (TPH) in polluted soils around the Shadegan ponds, in southern Iran. One hundred soil samples showing various degrees of pollution were randomly collected from topsoil (0-10 cm). The soil samples were analyzed for TPH using Vis-NIR reflectance spectroscopy in the laboratory and then following application of preprocessing transformation, partial least squares PLS regression as well as two machine learning models including random forest (RF), and support vector machine (SVM) were examined. The results showed that the reflectance values at 1725 nm and 2311 nm, respectively, served as indicative TPH reflectance features, exhibiting weaker reflection with rising TPH. Among the preprocessing methods, the baseline correction method indicated the highest performance than the others. According to the evaluation model criteria in the validation dataset, the efficiency of the three selected models was observed in the following order SVM > RF > PLS regression. The SVM model provided the best performance in the validation dataset with r(2) = 0.85, root mean of square (RMSEP = 1.59 %, and the ratio of prediction to deviation (RPD) = 2.6. Overall, this study provided strong evidence supporting the considerable potential of Visible-NIR spectroscopy as a rapid and cost-effective technique for estimating TPH levels in oil-contaminated soils, surpassing traditional chemical analytical methods. Applying the mid-infrared spectrum (MIR) in combination with Visible-NIR data is expected to provide more comprehensive and accurate results when assessing soils in polluted areas, thereby enhancing the accuracy and reliability of the results across a diverse range of soil types.

Introduction Wetlands are ecosystems that have a significant impact on ecological services and are essential for the environment. With the impacts of rapid population growth, wetland reclamation, urbanization, and land use change, wetlands have undergo severe degradation or loss. However, the response of soil fungal communities to wetland degradation remains unknown. It is crucial to comprehend how the diversity and population dynamics of soil fungi respond to varying levels of degradation and ecological progression in the wetlands of the Songnen Plain.Methods In this study, high- throughput sequencing technology to analyze the variety and abundance of soil fungi in the undegraded (UD), light degraded (LD), moderate degraded (MD), and severe degraded (SD) conditions in the Halahai Nature Reserve of Songnen Plain. This study also explored how these fungi are related to the soil's physicochemical properties in wetlands at various degradation levels.Results The findings indicated that Basidiomycota and Ascomycota were the primary phyla in the Songnen Plain, with Ascomycota increasing and Basidiomycota decreasing as wetland degradation progressed. Significant differences were observed in soil organic carbon (SOC), total nitrogen (TN),and soil total potassium (TK) among the succession degradation stages. With the deterioration of the wetland, there was a pattern of the Shannon and Chao1 indices increasing and then decreasing. Non-metric Multidimensional Scaling (NMDS) analysis indicated that the fungal community structures of UD and LD were quite similar, whereas MD and SD exhibited more distinct differences in their fungal community compositions. Redundancy analysis (RDA) results indicated that Soil Water content (SWC) and total nitrogen (TN) were the primary environmental factors influencing the dominant fungal phylum. According to the FUNGuild prediction, Ectomycorrhizal and plant pathogens gradually declining with wetland degradation.Discussion In general, our findings can offer theoretical support develop effective solutions for the preservation and rehabilitation of damaged wetlands.