Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Observation and Research Station on Eco-Environment of Frozen Ground in the Qilian Mountains, Lanzhou University, Lanzhou, China.
Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China.
Glob Chang Biol. 2023 May;29(10):2732-2745. doi: 10.1111/gcb.16658. Epub 2023 Mar 13.
Thermokarst lakes are potentially important sources of methane (CH ) and carbon dioxide (CO ). However, considerable uncertainty exists regarding carbon emissions from thermokarst lakes owing to a limited understanding of their patterns and motivators. In this study, we measured CH and CO diffusive fluxes in 163 thermokarst lakes in the Qinghai-Tibet Plateau (QTP) over 3 years from May to October. The median carbon emissions from the QTP thermokarst lakes were 1440 mg CO m day and 60 mg CH m day , respectively. The diffusive rates of CO and CH are related to the catchment land cover type. Sediment microbial abundance and hydrochemistry explain 51.9% and 38.3% of the total variance in CH diffusive emissions, respectively, while CO emissions show no significant relationship with environmental factors. When upscaling carbon emissions from the QTP thermokarst lakes, the annual average CH release per lake area is equal to that of the pan-Arctic region. Our findings highlight the importance of incorporating in situ observation data with different emission pathways for different land cover types in predicting carbon emissions from thermokarst lakes in the future.
热喀斯特湖是甲烷 (CH) 和二氧化碳 (CO) 的潜在重要来源。然而，由于对其模式和驱动因素的了解有限，热喀斯特湖的碳排放量存在相当大的不确定性。在这项研究中，我们在 3 年的时间里（从 5 月到 10 月）测量了青藏高原（QTP）163 个热喀斯特湖的 CH 和 CO 扩散通量。青藏高原热喀斯特湖的碳排放量中位数分别为 1440mg CO m day 和 60mg CH m day 。CO 和 CH 的扩散率与集水区土地覆盖类型有关。沉积物微生物丰度和水化学分别解释了 CH 扩散排放总量方差的 51.9%和 38.3%，而 CO 排放与环境因素没有显著关系。在将青藏高原热喀斯特湖的碳排放量外推时，每个湖泊面积的年平均 CH 释放量与整个北极地区相当。我们的研究结果强调了在未来预测热喀斯特湖碳排放量时，将不同土地覆盖类型的原位观测数据与不同排放途径相结合的重要性。
