Integrating leaf functional traits improves modelled estimates of carbon and water fluxes at a subtropical evergreen conifer forest
文献类型：期刊论文
| 作者 | Chen, Bin; Li, Yue6; Wang, Shaoqiang4,5; Chen, Jinghua; Zhang, Xuanze3; Liu, Zhenhai5; Croft, Holly2 |
| 刊名 | ECOLOGICAL MODELLING
 |
| 出版日期 | 2024-02-01 |
| 卷号 | 488页码:110593 |
| 关键词 | Leaf maximum carboxylation rate Leaf maximum electron transport rate Gross primary productivity Evapotranspiration Sunlit and shaded leaves |
| DOI | 10.1016/j.ecolmodel.2023.110593 |
| 文献子类 | Article |
| 英文摘要 | Simulations of gross primary productivity (GPP) and evapotranspiration (ET) by terrestrial biosphere models (TBMs) are subject to significant uncertainty, in part due to the spatiotemporal variability in leaf photosynthetic capacity, which is not well represented in models. Recent studies have shown the potential for using leaf chlorophyll content (Chl(leaf)) to constrain GPP and ET modeling in deciduous vegetation with a strong seasonal phenology. However, little is known about how integrating physiological trait information affects modelled GPP and ET in evergreen plants. In this study, we investigated the feasibility of incorporating Chl(leaf) and leaf age into a TBM, as a proxy for leaf maximum carboxylation rate at 25 degrees C (V-cmax25) for improving GPP and ET simulations. Measurements of Chl(leaf) and V-cmax25 from different leaf age classes (current-year and 1-year-old) for Masson pine and Slash pine species, and leaf area index (LAI) were made in a subtropical Evergreen Needleleaf Forest (ENF) eddy covariance flux tower site. The parameterization of V-cmax25 using combined information on Chl(leaf) and leaf age considerably reduced the biases in simulated GPP and ET, relative to the cases of i) constant V-cmax25 and ii) Chl(leaf) based V-cmax25. The largest improvements in GPP and ET simulations were found in growing season (May to August), when monthly absolute errors (AEs) of modeled GPP were similar to 40 % reduced, from 120.5 to 71.2 g C m(-2) mon(-1), with a 25 % decrease of monthly AEs of modeled ET from 52.3 to 39.1 mm mon(-1). Chl(leaf) plays a different role in modelled photosynthesis and transpiration between sunlit and shaded leaves. The modeled water use efficiency (WUE) and light use efficiency (LUE) of the shaded leaves were both higher than those of sunlit leaves. This study presents the newly use of Chl(leaf) and leaf age as a proxy for improving V-cmax25 modeling at an ENF stand, which highlights the importance of using plant physiological traits and leaf age for improving ecosystem carbon-water coupling simulations. |
| WOS关键词 | PHOTOSYNTHETIC CAPACITY ; ECOSYSTEM RESPIRATION ; STOMATAL CONDUCTANCE ; CHLOROPHYLL CONTENT ; USE EFFICIENCY ; NITROGEN ; LEAVES ; CO2 ; SUN ; ASSIMILATION |
| WOS研究方向 | Environmental Sciences & Ecology |
| WOS记录号 | WOS:001137874700001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201562]  |
| 专题 | 生态系统网络观测与模拟院重点实验室_外文论文 |
| 作者单位 | 1.Univ Sheffield, Sch Biosci, Western Bank, Sheffield S10 2TN, England 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 3.China Univ Geosci, Coll Geog & Informat Engn, Wuhan, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 5.Hebei Univ Engn, Sch Earth Sci & Engn, Handan, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Bin,Li, Yue,Wang, Shaoqiang,et al. Integrating leaf functional traits improves modelled estimates of carbon and water fluxes at a subtropical evergreen conifer forest[J]. ECOLOGICAL MODELLING,2024,488:110593. |
| APA | Chen, Bin.,Li, Yue.,Wang, Shaoqiang.,Chen, Jinghua.,Zhang, Xuanze.,...&Croft, Holly.(2024).Integrating leaf functional traits improves modelled estimates of carbon and water fluxes at a subtropical evergreen conifer forest.ECOLOGICAL MODELLING,488,110593. |
| MLA | Chen, Bin,et al."Integrating leaf functional traits improves modelled estimates of carbon and water fluxes at a subtropical evergreen conifer forest".ECOLOGICAL MODELLING 488(2024):110593. |
入库方式： OAI收割
来源：地理科学与资源研究所
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