土壤水分主导中亚严重干旱期间总初级生产力的变化

IF 5.8 2区 环境科学与生态学 Q1 ECOLOGY
Tao Yu , Guli Jiapaer , Anming Bao , Ye Yuan , Jiayu Bao , Tim Van de Voorde
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引用次数: 0

摘要

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Soil moisture dominates gross primary productivity variation during severe droughts in Central Asia
The onset of severe drought is usually accompanied by anomalies in soil moisture (SM) and climatic factors such as temperature (Tem), solar radiation (Srad), and vapor pressure defict (VPD). These factors are critical for gross primary productivity (GPP) as they directly influence photosynthesis. Central Asia (CA), characterized by a dry climate and water scarcity, frequently experiences severe droughts, leading to a decrease in GPP. However, how anomalies in SM and climatic factors affect GPP in CA, and the dominant factors causing the decline in GPP during severe droughts, remain unclear. Here we first identified severe droughts in CA from 2000 to 2021 using the self-calibrated Palmer Drought Severity Index (scPDSI) and then investigated the effects of anomalies in SM, Tem, Srad, and VPD on solar-induced chlorophyll fluorescence (SIF) and GPP under severe drought conditions by light-use efficiency P-model and the Random Forest (RF) algorithm. The results show that the severe droughts in CA from 2000 to 2021 occurred in 2008 and 2021, with scPDSI values of −3.26 and − 3.94, respectively. In 2008 and 2021, SIF and GPP showed significant decreases: the area of negative anomalies in SIF and GPP was more than 70 % of CA. The spatial pattern of SM anomalies is consistent with that of SIF and GPP. P-model simulations indicate that SM deficits dominated the decline in GPP in 2008 and 2021, affecting regions covering 31 % and 17 % of CA, respectively, with GPP reductions exceeding 5 %. RF predictions also indicated that during severe drought, SM had a significant effect on GPP, while Srad, Tem, and VPD had a slight effect on GPP.
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来源期刊
Ecological Informatics
Ecological Informatics 环境科学-生态学
CiteScore
8.30
自引率
11.80%
发文量
346
审稿时长
46 days
期刊介绍: The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.
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