Utilization patterns strongly dominated the dynamics of CO₂ and CH₄ emissions from small artificial lakes

Small lakes are significant sources of CO₂ and CH₄ emissions to atmosphere. The dynamics and controls of CO₂ and CH₄ emissions from human-dominated small lakes with diverse functions remain poorly understood. We investigated the spatiotemporal dynamics of CO₂ and CH₄ concentrations and fluxes in 33 small lakes around the urban area with different landscape properties and utilization patterns, to clarify the impact of human-dominated functional shift on their greenhouse gas emissions. Meanwhile, we used microcosm cultivation methods to assess the CO₂ and CH₄ production rates of sediments in these lakes. The results indicated that the utilization ways significantly influence the CO₂ and CH₄ emissions in these lakes, with urban landscape lakes and aquaculture lakes showing significantly higher emissions compared to irrigation water-supplying lakes and drinking-water lakes. Extensive urbanization and aquaculture practices could increase the risk of that small lakes turn into hotspots of CO₂ and CH₄ emissions, and further complicate their spatial heterogeneity. Meanwhile, the production potential of CO₂ and CH₄ in sediments, as well as gas fluxes in small lakes, exhibited consistent functional differentiation across different utilization patterns. They were mainly driven by changes in sediment organic carbon and microbial carbon. Additionally, the difference of organic carbon and nitrogen loads were another drives for the variability in CO₂ and CH₄ emissions. We highlighted that the continuous accumulation of nutrient loads in water and sediments in human-dominated small lakes has greatly enhanced the potential for carbon gas emissions. We also found that utilization ways can significantly affect the key controls of CO₂ and CH₄ emission from small lakes, and also influence the reliability of carbon emission prediction models based on water chemistry parameters. To accurately estimate the contribution of small lakes to the global greenhouse gas inventory, it is essential to establish adaptive predictive models that consider the uncertainties in lake carbon emissions resulting from human utilization patterns.