Advancing projections of phytoplankton responses to climate change through ensemble modelling

被引:76
|
作者
Trolle, Dennis [1 ,2 ]
Elliott, J. Alex [3 ]
Mooij, Wolf M. [4 ,5 ]
Janse, Jan H. [4 ,6 ]
Bolding, Karsten [1 ,7 ]
Hamilton, David P. [8 ]
Jeppesen, Erik [1 ,2 ,9 ]
机构
[1] Aarhus Univ, Dept Biosci, DK-8600 Silkeborg, Denmark
[2] Sino Danish Ctr Educ & Res, Beijing, Peoples R China
[3] Ctr Ecol & Hydrol, Algal Modelling Unit, Lake Ecosystem Grp, Lancaster LA1 4AP, England
[4] Netherlands Inst Ecol, NIOO KNAW, Dept Aquat Ecol, NL-6700 AB Wageningen, Netherlands
[5] Wageningen Univ, Dept Aquat Ecol & Water Qual Management, NL-6700 AA Wageningen, Netherlands
[6] PBL Netherlands Environm Assessment Agcy, NL-3720 AH Bilthoven, Netherlands
[7] Bolding & Burchard ApS, DK-5466 Asperup, Denmark
[8] Univ Waikato, Environm Res Inst, Hamilton 3240, New Zealand
[9] Greenland Inst Nat Resources, GCRC, Nuuk 3900, Greenland
关键词
Future climate; Cyanobacteria; Water resources; Ecosystem modelling; SHALLOW LAKES; MULTIMODEL ENSEMBLES; ENVIRONMENTAL-CHANGE; COMMUNITY STRUCTURE; CYANOBACTERIA; RESTORATION; PREDICTIONS; FRAMEWORK; DYNAMICS; BLOOMS;
D O I
10.1016/j.envsoft.2014.01.032
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A global trend of increasing health hazards associated with proliferation of toxin-producing cyanobacteria makes the ability to project phytoplankton dynamics of paramount importance. Whilst ensemble (multi-)modelling approaches have been used for a number of years to improve the robustness of weather forecasts this approach has until now never been adopted for ecosystem modelling. We show that the average simulated phytoplankton biomass derived from three different aquatic ecosystem models is generally superior to any of the three individual models in describing observed phytoplankton biomass in a typical temperate lake ecosystem, and we simulate a series of climate change projections. While this is the first multi-model ensemble approach applied for some of the most complex aquatic ecosystem models available, we consider it sets a precedent for what will become commonplace methodology in the future, as it enables increased robustness of model projections, and scenario uncertainty estimation due to differences in model structures. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:371 / 379
页数:9
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