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若尔盖高寒湿地—大气间碳交换特征及驱动机制研究

Characteristics and Driving Mechanism of Carbon Exchange between the Zoige Alpine Wetland and Atmosphere

  • 摘要: 在全球变暖背景下,高寒湿地生态系统的碳过程是复杂且敏感。然而,高寒湿地生态系统碳收支的长期动态及其驱动机制尚不清楚。本研究利用涡度协方差技术测量的二氧化碳(CO2)通量,分析了若尔盖高寒湿地2017~2021年间的CO2交换通量,以及CO2交换通量的动态变化和驱动机制。结果显示,在植被生长季(6~10月),若尔盖高寒湿地的年均生态系统总初级生产力(Gross Primary Productivity,简称GPP)和生态系统呼吸(Ecosystem Respiration,简称Re)呈现出单峰型分布,而年均净生态系统碳交换((Net Ecosystem Exchange,简称NEE)则呈现V型趋势。若尔盖高寒湿地生态系统在生长季节是一个碳汇,即一个吸收比释放更多的陆—气间碳交换过程。多年日平均NEE、GPP和Re分别达到−3.10±4.61、4.78±5.61和1.65±1.56 μmol m−2 s−1。在月度尺度上,回归分析了气温、土壤温度、光合光子通量密度、降水量、空气相对湿度和水汽压差分别对NEE、GPP和Re的影响,结果显示,气温、土壤温度和水汽压差是月度NEE变化的主要决定因素,NEE与它们都呈负相关。土壤温度和气温在很大程度上决定了每月GPP的变化,GPP与其呈正相关,土壤温度、气温和PPT是月度Re变化的主要决定因素,Re与它们都呈正相关。利用分类回归树算法分析了日尺度上各个要素对碳交换通量的影响,结果表明:土壤温度对日GPP和Re具有较大影响,气温是每日NEE的主要控制因素。本研究结果为理解高寒湿地生态系统碳收支提供了重要数据和参考依据。

     

    Abstract: In the context of global warming, the carbon process of alpine wetland ecosystems is complex and sensitive; however, the long-term dynamics and driving mechanisms of the carbon balance in alpine wetland ecosystems remain unclear. In this study, the carbon dioxide (CO2) flux measured by the eddy covariance technique was used to analyze the CO2 exchange flux in the Zoige alpine wetland from 2017 to 2021, as well as the dynamics and driving mechanisms of the CO2 exchange flux were determined. The results showed that during the vegetation growing season (June–October), the annual gross primary productivity (GPP) and ecosystem respiration (Re) of the ecosystem displayed a unimodal pattern, while the annual average net ecosystem carbon exchange (NEE) of CO2 displayed a V-shaped trend. The Zoige alpine wetland ecosystem is a carbon sink during the growing season; as such, it absorbs more carbon from the air than it releases. The daily average NEE, GPP, and Re over the years reached −3.10±4.61, 4.78±5.61, and 1.65±1.56 μmol m−2 s−1, respectively. The effects of air temperature, soil temperature, photosynthetic photon flux density, precipitation, air relative humidity, and vapor pressure deficit on NEE, GPP, and Re were analyzed on a monthly scale using regression analysis. The results of regression analysis showed that air temperature, soil temperature, and precipitation were the main determinants of monthly NEE changes, and NEE was negatively correlated with these effects. soil temperature and air temperature largely determined the monthly variation in GPP, and they were positively correlated with GPP; soil temperature, air temperature, and precipitation were the main determinants of monthly Re variation, and they were positively correlated with Re. The Classification and Regression Tree algorithm was used to analyze the effects of various factors on carbon exchange flux on a daily scale. The results showed that soil temperature had a strong influence on daily GPP and Re, and temperature was the main factor controlling daily NEE. The results of this study provide important data and reference for understanding the carbon budget of alpine wetland ecosystems.

     

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