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生态学杂志 ›› 2020, Vol. 39 ›› Issue (9): 2821-2831.doi: 10.13292/j.1000-4890.202009.004

• 研究报告 • 上一篇    下一篇

隆宝滩保护区不同生态系统CH4和CO2通量差异及其影响因素

何方杰1,2, 韩辉邦3, 马学谦3, 张劲松1,2, 孙守家1,2*   

  1. (1中国林业科学研究院林业研究所/国家林业局林木培育重点实验室, 北京 100091;2南京林业大学南方现代林业协同创新中心, 南京 210037;3青海省人工影响天气办公室, 西宁 810001)
  • 出版日期:2020-09-10 发布日期:2021-03-10

CH4 and CO2 fluxes and their influencing factors in different ecosystems in Longbaotanreserve.

HE Fang-jie1,2, HAN Hui-bang3, MA Xue-qian3, ZHANG Jin-song1,2, SUN Shou-jia1,2*#br#   

  1. (1Key Laboratory of Tree Breeding and Cultivation of the State Forestry Administration/Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China; 2Collaborative Innovation Center of Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; 3Qinghai Province Weather Modification Office, Xining 810001, China).
  • Online:2020-09-10 Published:2021-03-10

摘要: 以位于青藏高原中部的隆宝滩自然保护区为对象,在2017—2018年生长季节使用便携式温室气体分析仪对高寒草地、沼泽化草甸和高寒沼泽的CH4和CO2通量进行原位观测,结合环境因子确定不同生态系统的CH4和CO2通量差异及其影响因素。结果表明,2个生长季节中沼泽化草甸和高寒沼泽排放CH4,峰值出现在7—9月,高寒草地吸收CH4,峰值出现在8月,沼泽化草甸和高寒沼泽CH4通量与高寒草地差异显著(P<0.05)。3种生态系统的CO2通量均为正值,峰值出现在6—8月,高寒草地CO2通量年均值最大,高寒沼泽最小,二者差异显著(P<0.05)。统计显示,高寒草地和高寒沼泽CO2与CH4通量之间呈极显著负相关(P<0.01),而在沼泽化草甸中二者呈显著正相关(P=0.02)。CH4、CO2与环境因子关系的主成分分析结果显示,第1主成分是土壤因子,第2主成分是生物因子,第3主成分是温度因子。逐步回归结果显示,土壤温度是影响月尺度CH4通量的关键因子,土壤温度和湿度是影响月尺度CO2通量的关键因子。Pearson相关分析表明,3种生态系统的CO2通量均与土温呈极显著正相关(P<0.01),与土壤水分呈显著负相关(P<0.05),CH4通量则与土壤水分呈极显著正相关(P<0.01)。受温度、土壤水分以及土壤有机质和氮等因素影响,高寒草地、沼泽化草甸和高寒沼泽CH4和CO2通量存在明显的异质性。因此,在估算青藏高原CH4和CO2排放时,需考虑不同生态系统碳排放的差异。

关键词: 青藏高原中部, 高寒草甸, 高寒沼泽, CH4通量, CO2通量

Abstract: We measured in situ CH4 and CO2 fluxes of alpine grassland, marsh meadow, and alpine marsh using portable greenhouse gas analyzer in Longbaotan, a nature reserve located in the middle of Qinghai-Tibet Plateau, in two growing seasons from 2017 to 2018. Our objectives were to determine the differences in CH4 and CO2 fluxes among the three ecosystems and their influencing factors. The results showed that marsh meadow and alpine marsh were CH4 sources in both growing seasons, with an emission peak in July-September. The alpine grassland was a CH4 sink, with an absorption peak in August. CH4 flux in alpine grassland significantly differed from that in marsh meadow and alpine marsh (P<0.05). All the three ecosystems were the sources of CO2 and the emission peak appeared from June to August. The annual mean value of CO2 flux was the largest in alpine grassland and the lowest in alpine marsh (P<0.05). CO2 fluxes in alpine grassland and alpine marsh were significantly negatively correlated with CH4 fluxes (P<0.01), and a positive correlation was found in marsh meadow (P=0.02). Results of principal component analysis showed that the first principal component was soil factor, the second was biological factor, and the third was temperature factor. Results from stepwise regression showed that soil temperature was the key factor affecting CH4 flux, and soil temperature and humidity were the key factors of CO2 flux on monthly scale. Results from Pearson correlation analysis showed that the CO2 flux of the three ecosystems was significantly positively correlated with soil temperature (P<0.01), negatively correlated with soil moisture (P<0.05). The CH4 flux was significantly positively correlated with soil moisture (P<0.01). The heterogeneity of CH4 and CO2 fluxes in alpine grassland, marsh meadow and alpine marsh was caused by temperature, soil moisture, soil organic matter and nitrogen. When estimating CH4 and CO2 emissions in the Qinghai-Tibet Plateau, the difference of carbon emissions from different ecosystems should be considered.

Key words: central Qinghai-Tibet Plateau, alpine grassland, alpine marsh, CH4 flux, CO2 flux.