兰州大学机构库
Improved modeling of canopy transpiration for temperate forests by incorporating a LAI-based dynamic parametrization scheme of stomatal slope
Jin, Jiaxin1,2; Yan, Tao1; Wang, Han3; Ma, Xuanlong4; He, Mingzhu5; Wang, Ying6; Wang, Weifeng7; Guo, Fengsheng8; Cai, Yulong1; Zhu, Qiuan1; Wu, Jin9,10
2022-11-15
Online publication date2022-09
Source PublicationAGRICULTURAL AND FOREST METEOROLOGY   Impact Factor & Quartile
ISSN0168-1923
EISSN1873-2240
Volume326
page numbers13
AbstractThe ecosystem-level conductance-photosynthesis models, which represent a linearly coupled relationship between canopy stomatal conductance (G(s)) and CO2 assimilation, have been increasingly used for modeling transpiration (T-c). As a key parameter in these models, the slope parameter (G(1)) has been observed to vary considerably over the seasons in the field, but is often parametrized with a biome-specific temporally constant G(1), resulting in large potential uncertainty. Here we hypothesized that G(1 )varies with leaf area index (LAI) phenology and soil water content (SWC) seasonality, and accurate characterization of G(1) seasonality offers an avenue to improve T-c modelling. To test these hypotheses, we first investigated the seasonality of Eddy flux-derived G(1) and then explored its relationship with satellite-derived LAI and field-observed SWC seasonality at 12 temperate forest FLUXNET sites across the Northern Hemisphere. Last, we cross-compared the two schemes of model parameterization of G(1) for modeling T-c: (1) a constant G(1 )(FIX) and (2) a dynamic G(1) parameterized using the selected variables (DYN). Our results show G(1) displays considerable seasonal variations across all sites, with a minimum value in mid-summer. Further variance partitioning analysis demonstrates that the seasonal variations in G(1) show direct linkages with LAI phenology rather than SWC seasonality likely associated with leaf aging and ontogeny development. Last, we found relative to the FIX model, the DYN model (using LAI for G(1) parameterization) significantly reduced the model uncertainty in terms of RMSE by 24.6 +/- 11.8% and 32.0 +/- 8.7%, respectively for G(s) and T-c at a daily scale. These results collectively improve our understanding of the dynamic pattern and proximate controls of G(1) seasonality, and highlight the effectiveness of using remote sensing-derived LAI phenology for improved characterization of G(1) seasonality that ultimately contributes to the improved process model simulations of the seasonal dynamics of G(s )and T-c across temperate forest landscapes.
KeywordStomatal conductance model Stomatal slope Leaf area index Transpiration Phenology Temperate forest
PublisherELSEVIER
DOI10.1016/j.agrformet.2022.109157
Indexed BySCIE
Language英语
WOS Research AreaAgriculture ; Forestry ; Meteorology & Atmospheric Sciences
WOS SubjectAgronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS IDWOS:000855552900001
Original Document TypeArticle
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/488977
Collection兰州大学
Corresponding AuthorJin, Jiaxin; Wu, Jin
Affiliation
1.Hohai Univ, Coll Hydrol & Water Resources, Nanjing, Peoples R China;
2.Natl Earth Syst Sci Data Ctr, Natl Sci & Technol Infrastruct China, Beijing, Peoples R China;
3.Tsinghua Univ, Dept Earth Syst Sci, Beijing, Peoples R China;
4.Lanzhou Univ, Sch Earth & Environm Sci, Lanzhou, Peoples R China;
5.Peking Univ, Coll Urban & Environm Sci, Beijing, Peoples R China;
6.NanJing XiaoZhuang Univ, Tourism & Social Adm Coll, Nanjing, Peoples R China;
7.Nanjing Forestry Univ, Coll Biol & Environm, Nanjing, Peoples R China;
8.PowerChina Zhongnan Engn Corp Ltd, Changsha, Peoples R China;
9.Univ Hong Kong, Sch Biol Sci, Hong Kong, Peoples R China;
10.Chinese Univ Hong Kong, State Key Lab Agrobiotechnol, Shatin, Hong Kong, Peoples R China
Recommended Citation
GB/T 7714
Jin, Jiaxin,Yan, Tao,Wang, Han,et al. Improved modeling of canopy transpiration for temperate forests by incorporating a LAI-based dynamic parametrization scheme of stomatal slope[J]. AGRICULTURAL AND FOREST METEOROLOGY,2022,326.
APA Jin, Jiaxin.,Yan, Tao.,Wang, Han.,Ma, Xuanlong.,He, Mingzhu.,...&Wu, Jin.(2022).Improved modeling of canopy transpiration for temperate forests by incorporating a LAI-based dynamic parametrization scheme of stomatal slope.AGRICULTURAL AND FOREST METEOROLOGY,326.
MLA Jin, Jiaxin,et al."Improved modeling of canopy transpiration for temperate forests by incorporating a LAI-based dynamic parametrization scheme of stomatal slope".AGRICULTURAL AND FOREST METEOROLOGY 326(2022).
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