Eco-evolutionary optimality as a means to improve vegetation and land-surface models

被引:107
作者
Harrison, Sandy P. [1 ,2 ]
Cramer, Wolfgang [3 ]
Franklin, Oskar [4 ,5 ]
Prentice, Iain Colin [2 ,6 ,7 ]
Wang, Han [2 ]
Brannstrom, Ake [4 ,8 ]
de Boer, Hugo [9 ]
Dieckmann, Ulf [4 ,10 ]
Joshi, Jaideep [4 ]
Keenan, Trevor F. [11 ,12 ]
Lavergne, Alienor [13 ]
Manzoni, Stefano [14 ,15 ]
Mengoli, Giulia [6 ]
Morfopoulos, Catherine [6 ]
Penuelas, Josep [16 ,17 ]
Pietsch, Stephan [4 ,18 ]
Rebel, Karin T. [9 ]
Ryu, Youngryel [19 ]
Smith, Nicholas G. [20 ]
Stocker, Benjamin D. [21 ,22 ]
Wright, Ian J. [7 ]
机构
[1] Univ Reading, Dept Geog & Environm Sci, Reading RG6 6AB, Berks, England
[2] Tsinghua Univ, Dept Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China
[3] Avignon Univ, Aix Marseille Univ, CNRS, IRD,Inst Mediterraneen Biodivers & Ecol Marine &, Technopole Arbois Mediterranee, F-13545 Aix En Provence, France
[4] Int Inst Appl Syst Anal, Schlosspl 1, A-2361 Laxenburg, Austria
[5] Swedish Univ Agr Sci, Dept Forest Ecol & Management, S-90183 Umea, Sweden
[6] Imperial Coll London, Dept Life Sci, Silwood Pk Campus,Buckhurst Rd, Ascot SL5 7PY, Berks, England
[7] Macquarie Univ, Dept Biol Sci, N Ryde, NSW 2109, Australia
[8] Umea Univ, Dept Math & Math Stat, S-90187 Umea, Sweden
[9] Univ Utrecht, Fac Geosci, Copernicus Inst Sustainable Dev, Environm Sci, Vening Meinesz Bldg,Princetonlaan 8a, NL-3584 CB Utrecht, Netherlands
[10] Grad Univ Adv Studies Sokendai, Dept Evolutionary Studies Biosyst, Hayama, Kanagawa 2400193, Japan
[11] Lawrence Berkeley Natl Lab, Climate & Ecosyst Sci Div, 1 Cyclotron Rd, Berkeley, CA 94720 USA
[12] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA
[13] Imperial Coll London, Dept Phys, South Kensington Campus, London SW7 2AZ, England
[14] Stockholm Univ, Dept Phys Geog, SE-10691 Stockholm, Sweden
[15] Stockholm Univ, Bolin Ctr Climate Res, SE-10691 Stockholm, Sweden
[16] UAB, CSIC, CREAF, Global Ecol, Barcelona 08193, Catalonia, Spain
[17] CREAF, Cerdanyola Valles Barcel 08193, Catalonia, Spain
[18] BOKU Univ Life Sci & Nat Resources, Gregor Medel Str 33, A-1180 Vienna, Austria
[19] Seoul Natl Univ, Dept Landscape Architecture & Rural Syst Engn, Seoul 08826, South Korea
[20] Texas Tech Univ, Dept Biol Sci, 2901 Main St, Lubbock, TX 79409 USA
[21] ETH, Dept Environm Syst Sci, Univ Str 2, CH-8092 Zurich, Switzerland
[22] Swiss Fed Inst Forest Snow & Landscape Res WSL, Zrcherstr 111, CH-8903 Birmensdorf, Switzerland
基金
瑞典研究理事会; 欧洲研究理事会; 中国国家自然科学基金; 澳大利亚研究理事会; 新加坡国家研究基金会;
关键词
acclimation; eco-evolutionary optimality; global vegetation model; land-surface model; leaf economics spectrum; plant functional ecology; stomatal behaviour; water and carbon trade-offs; TROPICAL MOIST FORESTS; PLANT FUNCTIONAL TYPES; ISOPRENE EMISSIONS; STOMATAL CONDUCTANCE; TRAIT VARIATION; USE EFFICIENCY; CLIMATE-CHANGE; QUANTUM YIELD; CARBON GAIN; TRADE-OFFS;
D O I
10.1111/nph.17558
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.
引用
收藏
页码:2125 / 2141
页数:17
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