Comprehensive analysis of greenhouse gases emissions and microbial dynamics in glacier-fed lakes across various ablation stages

Abstract

Glacier melting, a direct consequence of global climate change, significantly influences lake ecosystem structures and greenhouse gases (GHGs) emission in the glacier-fed lake. As glaciers release substantial meltwater containing nitrogen and carbon into lakes, microbial communities and their GHGs emissions could also evolve accordingly. So far, studies on seasonal and diel GHGs emission characteristics and their driving mechanism at high-altitude (> 5000 m) glacier-fed lakes remains relatively constrained. This study has focused on the Lhasa Valley Glacier, a typical continental-type glacier on the Tibetan Plateau, to explore the GHGs characteristics in the three newly formed glacier-fed lakes during distinct periods of glacier melting (i.e., initial ablation, peak ablation and end of ablation stage). A combination of techniques including multi-point continuous sampling, physicochemical characteristic analysis, 16S rRNA sequencing, and machine learning models had been utilized. Our results indicated that the annual average CH₄, N₂O, and CO₂ emission rates were 0.76±1.00, 0.02±0.08, and -5.19±50.16 mmol·m^-2·d^-1, respectively, demonstrating that glacier-fed lakes were significant CH₄ and N₂O source to the atmosphere. We found substantial seasonal variation of GHGs emissions from lakes, particularly for CH₄, with the maximum fluxes 104 times as high as the minimum value. Diurnal monitoring showed that GHGs emission were primarily concentrated during the daytime. Based on the 16S RNA sequencing results, we also observed seasonal variation of the microbial communities and their roles in driving GHGs emissions. Using Partial Least Squares Path Modeling, we further quantified complex relations among GHGs emissions, microorganism communities, and environmental factors. We found that the impact of microorganisms on GHGs emission could be further regulated by environmental factors such as water temperature and NO₃^--N. The Tibetan Plateau plays a critical role in global climate system. This study characterizes the GHGs emissions in glacier-fed lakes that has been less considered. Characterizing the GHGs emissions from this region could provide insights into how emissions contribute to global warming and climate change.

Keywords: Glacier-fed lakes; Greenhouse gases (GHGs) emission; Machine learning model; Microorganism; Seasonal and diel patterns; Tibetan Plateau.