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Grassland productivity response to droughts in northern China monitored by satellite-based solar-induced chlorophyll fluorescence.
Wang, Xinyun; Pan, Shufen; Pan, Naiqing; Pan, Peipei.
Afiliação
  • Wang X; 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 Reconst
  • Pan S; International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA.
  • Pan N; International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36830, USA; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Pan P; College of Resources and Environmental Science, Hebei Normal University, Shijiazhuang, Hebei 050024, China. Electronic address: panpeipei626@163.com.
Sci Total Environ ; 830: 154550, 2022 Jul 15.
Article em En | MEDLINE | ID: mdl-35302027
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecossistema / Secas Tipo de estudo: Prognostic_studies Limite: Humans País como assunto: Asia Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ecossistema / Secas Tipo de estudo: Prognostic_studies Limite: Humans País como assunto: Asia Idioma: En Ano de publicação: 2022 Tipo de documento: Article