Knowledge Management System Of Guangzhou Institute of Geochemistry，CAS
| Tian, Jie1,2; Yang, Xueqin1,2,3,4; Yuan, Wenping5; Lin, Shangrong6; Han, Liusheng7; Zheng, Yi1,2; Xia, Xiaosheng1,2; Liu, Liyang8; Wang, Mei1,2; Zheng, Wei1,2; Fan, Lei9; Yan, Kai10; Chen, Xiuzhi1,2 | |
| A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests | |
| Source Publication | GLOBAL CHANGE BIOLOGY
 |
| ISSN | 1354-1013 |
| 2024-08-01 | |
| Volume | 30Issue:8Pages:17 |
| DOI | 10.1111/gcb.17454 |
| Language | 英语 |
| WOS Research Area | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| Abstract | Tropical and subtropical evergreen broadleaved forests (TEFs) contribute more than one-third of terrestrial gross primary productivity (GPP). However, the continental-scale leaf phenology-photosynthesis nexus over TEFs is still poorly understood to date. This knowledge gap hinders most light use efficiency (LUE) models from accurately simulating the GPP seasonality in TEFs. Leaf age is the crucial plant trait to link the dynamics of leaf phenology with GPP seasonality. Thus, here we incorporated the seasonal leaf area index of different leaf age cohorts into a widely used LUE model (i.e., EC-LUE) and proposed a novel leaf age-dependent LUE model (denoted as LA-LUE model). At the site level, the LA-LUE model (average R2 = .59, average root-mean-square error [RMSE] = 1.23 gC m-2 day-1) performs better than the EC-LUE model in simulating the GPP seasonality across the nine TEFs sites (average R2 = .18; average RMSE = 1.87 gC m-2 day-1). At the continental scale, the monthly GPP estimates from the LA-LUE model are consistent with FLUXCOM GPP data (R2 = .80; average RMSE = 1.74 gC m-2 day-1), and satellite-based GPP data retrieved from the global Orbiting Carbon Observatory-2 (OCO-2) based solar-induced chlorophyll fluorescence (SIF) product (GOSIF) (R2 = .64; average RMSE = 1.90 gC m-2 day-1) and the reconstructed TROPOspheric Monitoring Instrument SIF dataset using machine learning algorithms (RTSIF) (R2 = .78; average RMSE = 1.88 gC m-2 day-1). Typically, the estimated monthly GPP not only successfully represents the unimodal GPP seasonality near the Tropics of Cancer and Capricorn, but also captures well the bimodal GPP seasonality near the Equator. Overall, this study for the first time integrates the leaf age information into the satellite-based LUE model and provides a feasible implementation for mapping the continental-scale GPP seasonality over the entire TEFs. This study incorporated leaf age information into a widely used light use efficiency (LUE) model (i.e., EC-LUE) and proposed a novel leaf age-dependent LUE model (i.e., LA-LUE model) to estimate the monthly gross primary productivity (GPP) over pantropical evergreen broadleaved forests. The GPP estimations from the LA-LUE model showed superior performance than the EC-LUE model against in situ measurements. The new model also demonstrated good capacity in representing both the unimodal GPP seasonality near the Tropics of Cancer and Capricorn and the bimodal GPP seasonality near the Equator. The new model provides a feasible implementation for predicting the future continental-scale GPP seasonality.image |
| Keyword | gross primary productivity leaf age light use efficiency model photosynthetic seasonality tropical and subtropical evergreen broadleaved forests |
| WOS ID | WOS:001288550900001 |
| Indexed By | SCI |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.gig.ac.cn/handle/344008/78676 |
| Collection | 中国科学院广州地球化学研究所 |
| Corresponding Author | Chen, Xiuzhi |
| Affiliation | 1.Sun Yat Sen Univ, Sch Atmospher Sci, Guangdong Prov Data Ctr Terr & Marine Ecosyst Carb, Guangdong Prov Key Lab Climate Change & Nat Disast, Zhuhai 519082, Peoples R China 2.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China 3.Chinese Acad Sci, Guangzhou Inst Geochem, Guangzhou, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Peking Univ, Inst Carbon Neutral, Sino French Inst Earth Syst Sci, Coll Urban & Environm Sci, Beijing, Peoples R China 6.Sun Yat Sen Univ, Sch Geog & Planning, Carbon Water Res Stn Karst Reg Northern Guangdong, Guangzhou, Peoples R China 7.Shandong Univ Technol, Sch Civil Engn & Geomat, Zibo, Peoples R China 8.Univ Paris Saclay, CNRS, UVSQ, IPSL,CEA,Lab Sci Climat & Environm, Gif Sur Yvette, France 9.Southwest Univ, Sch Geog Sci, Chongqing Jinfo Mt Karst Ecosyst Natl Observat & R, Natl Observat & Res Stn, Chongqing, Peoples R China 10.Beijing Normal Univ, Fac Geog Sci, Innovat Res Ctr Satellite Applicat IRCSA, State Key Lab Remote Sensing Sci, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | Tian, Jie,Yang, Xueqin,Yuan, Wenping,et al. A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests[J]. GLOBAL CHANGE BIOLOGY,2024,30(8):17. |
| APA | Tian, Jie.,Yang, Xueqin.,Yuan, Wenping.,Lin, Shangrong.,Han, Liusheng.,...&Chen, Xiuzhi.(2024).A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests.GLOBAL CHANGE BIOLOGY,30(8),17. |
| MLA | Tian, Jie,et al."A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests".GLOBAL CHANGE BIOLOGY 30.8(2024):17. |
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