Spatiotemporal Characteristics of Carbon Fluxes and Their Environmental Drivers in a Plateau Urban Wetlands Ecosystem Based on Eddy Covariance Observations

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 (Ta), 5 cm soil temperature (Ts5) 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 (Ta and Ts5), 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.