ORCID Profile
0000-0003-2997-6368
Current Organisation
University of California, Irvine
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Publisher: IOP Publishing
Date: 13-09-2018
Publisher: Wiley
Date: 08-05-2018
DOI: 10.1111/GCB.14274
Abstract: Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.
Publisher: Wiley
Date: 08-01-2015
DOI: 10.1111/GCB.12795
Abstract: The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr(-1), ranging from 0.0035 yr(-1) to 0.0127 yr(-1)), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai-Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.
Publisher: Springer Science and Business Media LLC
Date: 29-06-2018
Publisher: Springer Science and Business Media LLC
Date: 25-04-2016
DOI: 10.1038/NCLIMATE3004
Publisher: Springer Science and Business Media LLC
Date: 22-05-2017
DOI: 10.1038/NCLIMATE3299
Publisher: American Association for the Advancement of Science (AAAS)
Date: 03-01-2020
Abstract: Extra water loss from earlier spring greening dries soils locally in summer, but can moisten soils in areas downwind.
No related grants have been discovered for Yue Li.