DOI: 10.1016/j.ecolind.2020.106224
论文题名: Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis
作者: Xie X. ; Li A. ; Tan J. ; Lei G. ; Jin H. ; Zhang Z.
刊名: Ecological Indicators
ISSN: 1470160X
出版年: 2020
卷: 113 语种: 英语
英文关键词: Global GPP datasets
; Lagged effect of drought
; LUE-based models
; ML-based models
; Photosynthesis
; Process-based models
Scopus关键词: Climate change
; Drought
; Photosynthesis
; Tropical engineering
; Tropics
; Global climate changes
; Global GPP datasets
; Gross primary productivity
; Light use efficiency
; Probability analysis
; Process-based models
; Standard deviation
; Tropical climates
; Uncertainty analysis
; climate change
; data set
; drought
; global climate
; light use efficiency
; machine learning
; numerical model
; photosynthesis
; tropical region
; uncertainty analysis
英文摘要: Understanding the lagged effect of drought on photosynthesis is essential in global climate change research. Various gross primary productivity (GPP) datasets have been used to assess the drought effect on photosynthesis. However, discrepancies have been found in these GPP datasets, and whether the GPP discrepancies can cause uncertainties in understanding the lagged effect of drought on photosynthesis remains unclear. Here, twenty-six global GPP datasets from light use efficiency (LUE)-, machine learning (ML)-, and process-based models during 2001–2010, were used to evaluate the role of GPP discrepancies in characterizing the lagged effect of drought on photosynthesis. Based on probability analysis, a relatively reliable pattern about the lagged effect of drought on global photosynthesis was derived from multiple GPP datasets. Results showed that these 26 GPP datasets existed obvious discrepancies across the globe, with a standard deviation (SD) value of 42 g C m−2 month−1. Moreover, the area presenting the lagged effect of drought on photosynthesis was found to range between 32% and 69% of the global vegetated lands, confirming the obvious differences in drought patterns derived from different GPP datasets. Our results also indicated that the tropical region (20°N–20°S) presented lower reliabilities of lagged effect than other regions, indicating that the assessment of drought effect on photosynthesis in the tropical region should be more cautious. Furthermore, the probability-based lagged effect of drought on global photosynthesis showed that the lagged effect of drought on photosynthesis existed in 50% of the vegetated lands, with dominant lagged months being less than 8 months, suggesting that the water deficiency in preceding months probably influences vegetation growth. Our study highlights the need to better constrain the carbon modelling under tropical climate and demonstrates that uncertainties caused by GPP datasets should be considered when assessing drought effect on photosynthesis. © 2020 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158104
Appears in Collections: 气候变化与战略
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作者单位: Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China; University of Chinese Academy of Sciences, Beijing, 100049, China; School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha, 410114, China
Recommended Citation:
Xie X.,Li A.,Tan J.,et al. Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis[J]. Ecological Indicators,2020-01-01,113