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基于卫星观测的太阳诱导叶绿素荧光监测中国北方草原对干旱的响应。

Grassland productivity response to droughts in northern China monitored by satellite-based solar-induced chlorophyll fluorescence.

机构信息

School of Ecology and Environmental Sciences, Ningxia University, Yinchuan, Ningxia 750021, China; Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration of Northwest China, Ningxia University, Yinchuan, Ningxia 750021, China; Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwestern China of Ministry of Education, Ningxia University, Yinchuan, Ningxia 750021, China; Key Lab. for Restoration of Degraded Ecosystems in Ningxia Province, Ningxia University, Yinchuan, Ningxia 750021, China; International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA.

International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA.

出版信息

Sci Total Environ. 2022 Jul 15;830:154550. doi: 10.1016/j.scitotenv.2022.154550. Epub 2022 Mar 15.

Abstract

Solar-induced chlorophyll fluorescence (SIF) has been applied to a wide range of ecological studies, such as monitoring and assessing drought, vegetation productivity, and crop yield. Previous studies have shown that SIF is highly related to gross primary production (GPP), but its correlation with aboveground biomass (AGB) still needs further exploration. In this study, we explored the potential of SIF for monitoring and assessing the effects of climate change and meteorological drought on grassland AGB changes in the northern grassland of China. By examining the relationship between the Orbiting Carbon Observatory 2 (OCO-2) SIF and drought indices, we assessed the response of northern grassland productivity to meteorological drought conditions. The results show that SIF is very sensitive to meteorological drought and can capture drought events and the dynamics of grassland growth in different grassland types. The correlation between SIF, drought indices, and AGB varied with grassland type. A gradient boosting decision tree (GBDT) was used to explore the relationships between SIF and the impact variables in the grassland ecosystem. We found that climatic factors (e.g., annual mean growing season precipitation, annual mean growing season temperature, and annual mean vapor pressure deficit) and human activity (e.g., grazing intensity) significantly impacted the interannual variability of grassland productivity. Our results indicate that SIF changes can reflect the seasonal dynamics of vegetation growth in the northern grassland of China. Therefore, SIF can be used as benchmark data for evaluating the performance of terrestrial ecosystem models in simulating ecosystem productivity in this region. The high sensitivity of SIF to drought suggests that it is a useful tool for monitoring and assessing drought events.

摘要

太阳诱导叶绿素荧光 (SIF) 已广泛应用于生态研究,例如监测和评估干旱、植被生产力和作物产量。先前的研究表明,SIF 与总初级生产力 (GPP) 高度相关,但它与地上生物量 (AGB) 的相关性仍需进一步探索。本研究旨在探讨 SIF 监测和评估气候变化和气象干旱对中国北方草原 AGB 变化影响的潜力。通过检查轨道碳观测站 2 (OCO-2) SIF 与干旱指数之间的关系,评估了北方草原生产力对气象干旱条件的响应。结果表明,SIF 对气象干旱非常敏感,能够捕捉不同草原类型中干旱事件和草原生长的动态。SIF、干旱指数和 AGB 之间的相关性随草原类型而变化。梯度提升决策树 (GBDT) 用于探索 SIF 与草原生态系统中影响变量之间的关系。结果表明,气候因素(如年平均生长季降水量、年平均生长季温度和年平均蒸气压亏缺)和人类活动(如放牧强度)显著影响草原生产力的年际变化。研究结果表明,SIF 变化可以反映中国北方草原植被生长的季节性动态。因此,SIF 可作为评估该地区陆地生态系统模型模拟生态系统生产力性能的基准数据。SIF 对干旱的高敏感性表明,它是监测和评估干旱事件的有用工具。

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