Wetland health assessment provides important basis for wetland restoration and management. However, it is quite tricky to select proper indicators from multiple assessment indicators that can truly reflect the health state of urban wetlands. In an attempt to address these problems, a pressure-state-response (PSR) and back propagation artificial neural network (BP) conjoined model was established for health assessment of several plateau urban wetlands in Xining City, China. The model was driven and verified through field monitoring and social questionnaire data for 4 consecutive years from 2016 to 2019. Results indicate that: (1) Eight health evaluation indexes, including population density, eutrophication level, increasing humidity, carbon dioxide absorption, air purifying, recreation, wetland management level and investment in ecological construction and protection were selected from 45 input indexes. (2) The health index of Huangshui National Wetland Park has been increasing year by year, with an average of comprehensive health score of 0.746, 0.790, 0.884, and 0.877, respectively. The indicators that contributed the most to the restoration effect were leisure and entertainment service value (2016), carbon dioxide absorption service value (2017), eutrophication (2018), and wetland management level (2019), respecially. (3) Compared with the single PSR method, the advantages of this method include; There are fewer evaluation indicators, more accurate results (excluding the interference of some highly variable indicators) and more sensitive to environmental changes. The current study proposed a novel method that may provide additional accurate and refined indicators for urban wetland health assessment.

Nowadays, an increasing shortage of water resources intensifies the contradiction among different water-using sectors in the social-economic-ecological complex system. To adjust water used configuration in a holistic framework, a water use system (WUS) model was constructed with inclusive five water-using sectors including aquatic systems, primary industry, secondary industry, tertiary industry and resident consumption. The Baiyangdian Basin in Northern China was used as a case area. Six years data from 2008 to 2013 were used to quantify the model. By introducing the ecological network analysis (EAN), we holistically assessed the WUS under different water use configuration. System organization, activities and development degree, etc. were used to character the prosperities of the water use system. Results indicate that the WUS encountered a lasting degradation in system organization (AMI index decreased in an annual rate of 0.6%) and development degree though with an ascending system activities in the studies periods (with an annual growth rate of 11.3%). Scenario analysis results suggest several potential ways to achieve a better water use configuration in this basin, such as environmental and ecological restoration, water-saving technology and water recycling rate, etc. The current study may provide ways to optimize water use structure to balance the interests of different sectors both ecologically and economically.

Algal blooms significantly affect microbial community in wetland ecosystems. However, little is known about the succession of sediment microbial community during algal blooms. This study aimed to investigate the temporal patterns of sediment bacterial community structure and function succession during algal blooms (March to May, 2022) with high-throughput sequencing technology. To this end, algal blooms were divided into the bloom stage (BS), decomposition stage (DS) and end stage (ES). The results showed that: (1) The algal blooms were dominated by Microcystis species within Cyanobacteria. Both phytoplankton abundance and biomass reached the peak in the BS, with 45.78×10⁵ cells/L and 5.97 mg/L, respectively. (2) The alpha diversity indices of sediment bacterial community showed a monotonically increasing trend, with the lowest value in the BS. Cyanobacterial blooms reduced the relative abundance of Actinobacteria and Chloroflexi, and raised that of Firmicutes, Proteobacteria and Bacteroidetes. (3) Cyanobacterial blooms remarkably decreased the complexity of the co-occurrence network of the sediment bacterial community, which resisted extreme environmental conditions in the BS and DS by increasing positive relationships. (4) Mantel test showed that phytoplankton biomass, T, DO, and OC had significant effects on the sediment bacterial community. The results of this study are important for the ecological management of algal blooms through microorganisms.

Urban wetlands on the Qinghai–Tibetan Plateau are increasingly recognized as potentially important components of city-scale carbon budgets; however, their CO₂ flux dynamics and associated environmental drivers remain insufficiently quantified, particularly under high-altitude urban conditions. In this study, we addressed this knowledge gap by conducting continuous eddy covariance observations at Haihu Wetland Park in Xining City, China. Carbon fluxes were monitored throughout 2023 using the Huangshui Park Station flux tower. We quantified the temporal dynamics of gross primary productivity (GPP), ecosystem respiration (Re), and net ecosystem exchange (NEE), and systematically assessed their responses to key environmental drivers across multiple temporal scales. GPP and Re exhibited unimodal seasonal patterns, with substantially higher values during the growing season. NEE showed pronounced diel cycling, with nighttime CO₂ release and daytime uptake, and shifted seasonally between net source and net sink states. At the daily scale (n = 365), Pearson correlations showed that air temperature (T_a), 5 cm soil temperature (T_s5) and volumetric soil water content (SWC) exhibited the strongest associations with the flux components, whereas photosynthetic photon flux density (PPFD) showed moderate associations and precipitation was weak. At the monthly scale (n = 12), Mantel tests further highlighted a dominant thermal control on GPP and Re (T_a and T_s5), whereas precipitation showed additional associations with Re and NEE. Overall, the ecosystem acted as a net CO₂ sink in 2023 (annual NEE = −292.25 g C m⁻² yr⁻¹ under our sign convention), with uptake concentrated in the first eight months of the year. Under the combined effects of multiple environmental factors, plateau urban wetlands functioned as a strong carbon sink, and the results of this study provide a data basis for improving the accuracy of carbon budget estimates for this type of ecosystem.