IB-CAS  > 植被与环境变化国家重点实验室
Benchmark estimates for aboveground litterfall data derived from ecosystem models
Li, Shihua1; Yuan, Wenping1; Ciais, Philippe2; Viovy, Nicolas2; Ito, Akihiko3; Jia, Bingrui4; Zhu, Dan2
2019
发表期刊ENVIRONMENTAL RESEARCH LETTERS
ISSN1748-9326
卷号14期号:8
摘要Litter production is a fundamental ecosystem process, which plays an important role in regulating terrestrial carbon and nitrogen cycles. However, there are substantial differences in the litter production simulations among ecosystem models, and a global benchmarking evaluation to measure the performance of these models is still lacking. In this study, we generated a global dataset of aboveground litterfall production (i.e. cLitter), a benchmark as the defined reference to test model performance, by combining systematic measurements taken from a substantial number of surveys (1079 sites) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is an effective tool for upscaling local litterfall production observations to the global scale. On average, the model predicted 23.15 Pg Cyr(-1) of aboveground litterfall production. Our results revealed substantial differences in the aboveground litterfall production simulations among the five investigated ecosystem models. Compared to the reference data at the global scale, most of models could reproduce the spatial patterns of aboveground litterfall production, but the magnitude of simulations differed substantially from the reference data. Overall, ORCHIDEE-MICT performed the best among the five investigated ecosystem models.
关键词aboveground litterfall production leaf area index random forest ecosystem model
学科领域Environmental Sciences ; Meteorology & Atmospheric Sciences
DOI10.1088/1748-9326/ab2ee4
收录类别SCI
语种英语
WOS关键词CARBON-CYCLE ; LAND MODEL ; DECOMPOSITION ; FORESTS ; FLUXES ; STANDS ; RETURN
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号WOS:000490599700002
出版者IOP PUBLISHING LTD
文献子类Article
出版地BRISTOL
资助机构National Key Basic Research Program of ChinaNational Basic Research Program of China [2018YFA0606104] ; National Youth Top-Notch Talent Support Program [2015-48] ; Changjiang Young Scholars Program of China [Q2016161] ; Training Project of Sun Yat-sen University [16lgjc53] ; European Research CouncilEuropean Research Council (ERC)European Commission [SyG-2013-610028 IMBALANCE-P] ; ANR CLAND Convergence InstituteFrench National Research Agency (ANR)
作者邮箱yuanwp3@mail.sysu.edu.cn
作品OA属性Green Published, gold
引用统计
被引频次:17[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ibcas.ac.cn/handle/2S10CLM1/19689
专题植被与环境变化国家重点实验室
作者单位1.Sun Yat Sen Univ, Zhuhai Key Lab Dynam Urban Climate & Ecol, Sch Atmospher Sci, Zhuhai 519082, Guangdong, Peoples R China
2.Southern Marine Sci & Engn Guangdong Lab, Zhuhai 519082, Guangdong, Peoples R China
3.UVSQ, CNRS, CEA, LSCE, F-91191 Gif Sur Yvette, France
4.Natl Inst Environm Studies, Tsukuba, Ibaraki 3058506, Japan
5.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
推荐引用方式
GB/T 7714
Li, Shihua,Yuan, Wenping,Ciais, Philippe,et al. Benchmark estimates for aboveground litterfall data derived from ecosystem models[J]. ENVIRONMENTAL RESEARCH LETTERS,2019,14(8).
APA Li, Shihua.,Yuan, Wenping.,Ciais, Philippe.,Viovy, Nicolas.,Ito, Akihiko.,...&Zhu, Dan.(2019).Benchmark estimates for aboveground litterfall data derived from ecosystem models.ENVIRONMENTAL RESEARCH LETTERS,14(8).
MLA Li, Shihua,et al."Benchmark estimates for aboveground litterfall data derived from ecosystem models".ENVIRONMENTAL RESEARCH LETTERS 14.8(2019).
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Li-2019-Benchmark es(4912KB)期刊论文出版稿开放获取CC BY-NC-SA浏览 请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Li, Shihua]的文章
[Yuan, Wenping]的文章
[Ciais, Philippe]的文章
百度学术
百度学术中相似的文章
[Li, Shihua]的文章
[Yuan, Wenping]的文章
[Ciais, Philippe]的文章
必应学术
必应学术中相似的文章
[Li, Shihua]的文章
[Yuan, Wenping]的文章
[Ciais, Philippe]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Li-2019-Benchmark estimates for aboveground li.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。