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A Novel Large-Scale Temperature Dominated Model for Predicting the End of the Growing Season
Fu, Yang1,2; Zheng, Zeyu1,2; Shi, Haibo1,2; Xiao, Rui3
Corresponding AuthorZheng, Zeyu(zhengzeyu@sia.cn)
2016-11-28
Source PublicationPLOS ONE
ISSN1932-6203
Volume11Issue:11Pages:13
AbstractVegetation phenology regulates many ecosystem processes and is an indicator of the biological responses to climate change. It is important to model the timing of leaf senescence accurately, since the canopy duration and carbon assimilation are strongly determined by the timings of leaf senescence. However, the existing phenology models are unlikely to accurately predict the end of the growing season (EGS) on large scales, resulting in the misrepresentation of the seasonality and interannual variability of biosphere-atmosphere feedbacks and interactions in coupled global climate models. In this paper, we presented a novel large-scale temperature dominated model integrated with the physiological adaptation of plants to the local temperature to assess the spatial pattern and interannual variability of the EGS. Our model was validated in all temperate vegetation types over the Northern Hemisphere. The results indicated that our model showed better performance in representing the spatial and interannual variability of leaf senescence, compared with the original phenology model in the Integrated Biosphere Simulator (IBIS). Our model explained approximately 63% of the EGS variations, whereas the original model explained much lower variations (coefficient of determination R-2 = 0.01-0.18). In addition, the differences between the EGS reproduced by our model and the MODIS EGS at 71.3% of the pixels were within 10 days. For the original model, it is only 26.1%. We also found that the temperature threshold (TcritTm) of grassland was lower than that of woody species in the same latitudinal zone.
Funding OrganizationProgram for One-hundred Talent Program of the Chinese Academy of Sciences
DOI10.1371/journal.pone.0167302
Indexed BySCI
Language英语
Funding ProjectProgram for One-hundred Talent Program of the Chinese Academy of Sciences[Y5AA100A01]
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000389472400110
PublisherPUBLIC LIBRARY SCIENCE
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/126975
Collection中国科学院金属研究所
Corresponding AuthorZheng, Zeyu
Affiliation1.Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Peoples R China
2.Chinese Acad Sci, Key Lab Network Control Syst, Shenyang, Peoples R China
3.Univ Penn, Dept Biostat & Epidemiol, Perelman Sch Med, Philadelphia, PA 19104 USA
Recommended Citation
GB/T 7714
Fu, Yang,Zheng, Zeyu,Shi, Haibo,et al. A Novel Large-Scale Temperature Dominated Model for Predicting the End of the Growing Season[J]. PLOS ONE,2016,11(11):13.
APA Fu, Yang,Zheng, Zeyu,Shi, Haibo,&Xiao, Rui.(2016).A Novel Large-Scale Temperature Dominated Model for Predicting the End of the Growing Season.PLOS ONE,11(11),13.
MLA Fu, Yang,et al."A Novel Large-Scale Temperature Dominated Model for Predicting the End of the Growing Season".PLOS ONE 11.11(2016):13.
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