Abstract

Carbon-water cycle represents a fundamental material cycle within urban ecosystems, characterized by interdependence and inseparability. Based on flux measurements in Shenzhen, we analyzed periodical dynamics of carbon and water fluxes and simulated their variations using four machine learning models. The results indicated that hourly carbon fluxes exhibited a typical U-shaped trend, while water fluxes showed an inverse trend. Seasonal carbon sink capacity was strongest in spring and winter and lowest in summer. Human activities influenced carbon and water fluxes, evidenced by shorter duration of carbon sequestration at suburban station (10 h) compared to exurban station (10.5 h). Seasonal mean carbon fluxes ranged from −5.285 to −2.514 μmol m−2∙s−1 at exurban station and from −2.197 to −1.352 μmol m−2∙s−1 at suburban station, while seasonal mean water fluxes of the above stations ranged from −3.454 to −1.136 μmol m−2∙s−1 and from −1.436 to −0.322 μmol m−2∙s−1, respectively. Exurban station demonstrated a greater carbon sequestration capacity and a higher transpiration intensity than suburban station. The environmental factors influencing carbon and water fluxes of the two stations were generally similar and with some differences. At the exurban station, there was a weak negative correlation between photo-synthetic active radiation and carbon flux, whereas at the suburban station, it was weakly positively correlated. Carbon fluxes at both stations displayed a positive correlation with temperature and relative humidity, while exhibiting a significant negative correlation with saturation vapor pressure deficit. The comparative studies are important for revealing the regularities, influencing factors, and mechanisms of carbon and water cycling in subtropical urban ecosystems.

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