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Incorporating water availability into autumn phenological model improved China's terrestrial gross primary productivity (GPP) simulation
Peng, Jie1,2; Wu, Chaoyang1,2; Zhang, Xiaoyang3; Ju, Weimin4; Wang, Xiaoyue1,2; Lu, Linlin5; Liu, Yibo6
2021-09-01
Source PublicationENVIRONMENTAL RESEARCH LETTERS
ISSN1748-9326
Volume16Issue:9Pages:16
Corresponding AuthorWu, Chaoyang(wucy@igsnrr.ac.cn)
AbstractEcosystem models provide an effective approach to quantify the terrestrial carbon cycle, but the lack of accurate phenological information prevents them from better simulations of the physical processes. Compared with spring phenology (i.e. the start of the growing season, SOS), the vegetation phenology in autumn (the end of the growing season, EOS) is not well-simulated and it is challenging to incorporate vegetation phenology into ecosystem models. The simulation of EOS based on temperature and photoperiod was widely accepted, such as Delpierre et al (2009 Agric. For. Meteorol. 149 938-48)'s model (DM), yet its accuracy has not been fully discussed at a regional scale. Here, we developed a regional autumn phenological model (DMS) with inputs of temperature, photoperiod, and water availability for China's terrestrial ecosystems. The new DMS model significantly improved the representation of EOS in terms of the lower root mean square error (RMSE), higher model efficiency, and a higher percentage of significant correlation with the referenced EOS. We observed widespread delaying trends of EOS with an average rate of 0.1 d yr(-1) for vegetated areas over 2001-2018. We further incorporated the improved EOS into the boreal ecosystem productivity simulator (BEPS) and found that the phenology-modified BEPS model had better performances in predicting annual gross primary productivity (GPP) with similar to 28% lower RMSE than the original model when testing against GPP measurements from flux tower sites. From 2001 to 2017, the interannual GPP simulated by the modified BEPS model showed an increasing trend with a rate of 6.0 g C m(-2) yr(-2). In conclusion, our study proves that water availability is of great significance for modeling autumn phenology, and the incorporation of phenological dates into an ecosystem model is helpful for productivity simulation.
Keywordphenological model autumn phenology gross primary productivity BEPS model
DOI10.1088/1748-9326/ac1a3b
WOS KeywordNET ECOSYSTEM PRODUCTIVITY ; CARBON FLUX PHENOLOGY ; LEAF SENESCENCE ; SEASONAL GROWTH ; CLIMATE-CHANGE ; PHOTOPERIODIC CONTROL ; NORTHERN-HEMISPHERE ; MEDIATED CONTROL ; TIBETAN PLATEAU ; VEGETATION
Indexed BySCI
Language英语
Funding ProjectNational Key R& D program of China[2018YFA0606101] ; National Natural Science Foundation of China[4212500048] ; Key Research Program of Frontier Sciences, CAS[QYZDB-SSW-DQC011] ; CAS Interdisciplinary Innovation Team[JCTD-2020-05]
Funding OrganizationNational Key R& D program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; CAS Interdisciplinary Innovation Team
WOS Research AreaEnvironmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS SubjectEnvironmental Sciences ; Meteorology & Atmospheric Sciences
WOS IDWOS:000685898500001
PublisherIOP PUBLISHING LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/164562
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWu, Chaoyang
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.South Dakota State Univ, Dept Geog, Geospatial Sci Ctr Excellence GSCE, 1021 Medary Ave,Wecota Hall 506B, Brookings, SD 57007 USA
4.Nanjing Univ, Int Inst Earth Syst Sci, 22 Hankou Rd, Nanjing 210093, Peoples R China
5.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
6.Nanjing Univ Informat Sci & Technol, Sch Appl Meteorol, Jiangsu Key Lab Agr Meteorol, Nanjing 210044, Peoples R China
Recommended Citation
GB/T 7714
Peng, Jie,Wu, Chaoyang,Zhang, Xiaoyang,et al. Incorporating water availability into autumn phenological model improved China's terrestrial gross primary productivity (GPP) simulation[J]. ENVIRONMENTAL RESEARCH LETTERS,2021,16(9):16.
APA Peng, Jie.,Wu, Chaoyang.,Zhang, Xiaoyang.,Ju, Weimin.,Wang, Xiaoyue.,...&Liu, Yibo.(2021).Incorporating water availability into autumn phenological model improved China's terrestrial gross primary productivity (GPP) simulation.ENVIRONMENTAL RESEARCH LETTERS,16(9),16.
MLA Peng, Jie,et al."Incorporating water availability into autumn phenological model improved China's terrestrial gross primary productivity (GPP) simulation".ENVIRONMENTAL RESEARCH LETTERS 16.9(2021):16.
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