GSTDTAP  > 气候变化
DOI10.1111/gcb.13965
Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions
Ehrhardt, Fiona1; Soussana, Jean-Francois1; Bellocchi, Gianni2; Grace, Peter3; McAuliffe, Russel4; Recous, Sylvie5; Sandor, Renata2,6; Smith, Pete7; Snow, Val4; Migliorati, Massimiliano de Antoni; Basso, Bruno8; Bhatia, Arti9; Brilli, Lorenzo10; Doltra, Jordi11; Dorich, Christopher D.12; Doro, Luca13; Fitton, Nuala7; Giacomini, Sandro J.14; Grant, Brian15; Harrison, Matthew T.16; Jones, Stephanie K.17; Kirschbaum, Miko U. F.18; Klumpp, Katja2; Laville, Patricia19; Leonard, Joel20; Liebig, Mark21; Lieffering, Mark22; Martin, Raphael2; Massad, Raia S.19; Meier, Elizabeth23; Merbold, Lutz24,25; Moore, Andrew D.26; Myrgiotis, Vasileios17; Newton, Paul22; Pattey, Elizabeth15; Rolinski, Susanne27; Sharp, Joanna28; Smith, Ward N.15; Wu, Lianhai29; Zhang, Qing30
2018-02-01
发表期刊GLOBAL CHANGE BIOLOGY
ISSN1354-1013
EISSN1365-2486
出版年2018
卷号24期号:2页码:E603-E616
文章类型Article
语种英语
国家France; Australia; New Zealand; Hungary; Scotland; USA; India; Italy; Spain; Brazil; Canada; Switzerland; Kenya; Germany; England; Peoples R China
英文摘要

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield-scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed.


英文关键词agriculture benchmarking biogeochemical models climate change greenhouse gases nitrous oxide soil yield
领域气候变化 ; 资源环境
收录类别SCI-E
WOS记录号WOS:000423994700019
WOS关键词GREENHOUSE-GAS MITIGATION ; NITROUS-OXIDE EMISSIONS ; GRAZING MANAGEMENT ; CLIMATE ; WHEAT ; SYSTEMS ; CARBON ; YIELD ; GRASSLAND ; BUDGET
WOS类目Biodiversity Conservation ; Ecology ; Environmental Sciences
WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/16978
专题气候变化
资源环境科学
作者单位1.INRA, Paris, France;
2.INRA, UMR Ecosyst Prairial, Clermont Ferrand, France;
3.Queensland Univ Technol, Brisbane, Qld, Australia;
4.Lincoln Res Ctr, AgRes, Lincoln, New Zealand;
5.INRA, UMR FARE, Reims, France;
6.Inst Agr, CAR, HAS, Martonvasar, Hungary;
7.Univ Aberdeen, Inst Biol & Environm Sci, Aberdeen, Scotland;
8.Michigan State Univ, Dept Geol Sci, E Lansing, MI 48824 USA;
9.Indian Agr Res Inst, New Delhi, India;
10.Univ Florence, DISPAA, Florence, Italy;
11.Cantabrian Agr Res & Training Ctr CIFA, Muriedas, Spain;
12.Colorado State Univ, NREL, Ft Collins, CO USA;
13.Univ Sassari, Desertificat Res Ctr, Sassari, Italy;
14.Fed Univ Santa Maria UFSM, Soil Dept, Santa Maria, RS, Brazil;
15.Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON, Canada;
16.Tasmanian Inst Agr, Burnie, Tas, Australia;
17.SRUC, Edinburgh, Midlothian, Scotland;
18.Landcare Res, Palmerston North, New Zealand;
19.Univ Paris Saclay, INRA, UMR ECOSYS, Thiverval Grignon, France;
20.INRA, UR AgroImpact, Laon, France;
21.USDA ARS, Mandan, ND USA;
22.Grasslands Res Ctr, AgRes, Palmerston North, New Zealand;
23.CSIRO, Agr & Food, St Lucia, Qld, Australia;
24.Inst Agr Sci, ETH Zurich, Zurich, Switzerland;
25.Mazingira Ctr, ILRI, Nairobi, Kenya;
26.CSIRO, Black Mt Sci & Innovat Precinct, Agr & Food, Canberra, ACT, Australia;
27.Potsdam Inst Climate Impact Res PIK, Potsdam, Germany;
28.New Zealand Inst Plant & Food Res, Christchurch, New Zealand;
29.Rothamsted Res, Sustainable Soils & Grassland Syst, Harpenden, Devon, England;
30.Chinese Acad Sci, Inst Atmospher Phys, LAPC, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Ehrhardt, Fiona,Soussana, Jean-Francois,Bellocchi, Gianni,et al. Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions[J]. GLOBAL CHANGE BIOLOGY,2018,24(2):E603-E616.
APA Ehrhardt, Fiona.,Soussana, Jean-Francois.,Bellocchi, Gianni.,Grace, Peter.,McAuliffe, Russel.,...&Zhang, Qing.(2018).Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions.GLOBAL CHANGE BIOLOGY,24(2),E603-E616.
MLA Ehrhardt, Fiona,et al."Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions".GLOBAL CHANGE BIOLOGY 24.2(2018):E603-E616.
条目包含的文件
条目无相关文件。
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
[Ehrhardt, Fiona]的文章
[Soussana, Jean-Francois]的文章
[Bellocchi, Gianni]的文章
百度学术
百度学术中相似的文章
[Ehrhardt, Fiona]的文章
[Soussana, Jean-Francois]的文章
[Bellocchi, Gianni]的文章
必应学术
必应学术中相似的文章
[Ehrhardt, Fiona]的文章
[Soussana, Jean-Francois]的文章
[Bellocchi, Gianni]的文章
相关权益政策
暂无数据
收藏/分享
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。