植物功能性状对动态全球植被模型改进研究进展
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摘要
动态全球植被模型(dynamic global vegetation models,DGVMs)在模拟和预测陆地生态系统对气候变化响应中表现出很大的不确定性,重要原因之一在于动态全球植被模型将定义植物功能型的性状值设置为常数,忽略了植物功能性状对环境变化的响应.动态全球植被模型现有的植物功能型框架已经严重地阻碍了其发展,因此迫切需要一种新的方法来克服这种局限性.植物功能性状不仅可以反映植物对环境连续变化的响应,而且与生态系统的结构和功能密切相关,可提升当前动态全球植被模型对生态系统过程的模拟和功能的预测.本文从动态全球植被模型发展和植物功能型局限性入手,详细介绍了植物功能性状发展现状及其对动态全球植被模型改进的重要价值,归纳总结了植物功能性状对动态全球植被模型改进的主要方法,并指明植物功能性状对动态全球植被模型改进的发展方向.以期通过凝练植物功能性状在构建下一代动态全球植被模型中发挥作用,推动动态全球植被模型在我国的发展和应用.
Dynamic global vegetation models(DGVMs) are key components of earth system models(ESMs), which aim to understand ecosystem processes and their interactions with the atmosphere. DGVMs are designed to simulate the structural and functional responses of global vegetation to changes in climate and atmospheric CO_2 concentration with the coexistence of plant functional types(PFTs). PFTs are groups of plant species with similar functions based on morphological, physiological, biochemical, reproductive, and demographic characteristics. DGVMs typically assign each PFT with fixed parameters representing the above characteristics, consequently ignoring their variations within PFT and their responses to environmental changes. This parameterization scheme can simplify plant species represented in DGVMs but inevitably result in large uncertainties in model predictions on ecosystem processes. Therefore, a new generation of DGVMs are urgently needed to overcome the limitations of PFTs by replacing the PFTs parameterization scheme with continuous variation in plant functional traits. Plant functional traits(FTs) are defined as morphological, physiological, and phenological characteristics that affect plants via their effects on the growth, reproduction, and survival. Plant FTs that mediate the structure and function of ecosystems can be implemented into DGVMs as variables rather than PFT-specific parameters with fixed values. The plant FT scheme not only provides a widely applicable approach for forecasting ecosystem shifts and changes in ecosystem structure, but can also be linked with ecosystem functions under a changing climate. This holds great potentials for predicting possible responses of terrestrial ecosystems to environmental changes. This review first introduces the state-of-the-art DGVMs based on PFTs. PFTs represent most of the world's vegetation types and characteristics through their functional behaviors and attributes. Although PFT-based DGVMs play a pivotal role in simulating atmosphere-land interactions by quantifying the processes of global carbon, nitrogen, and water cycles, uncertainties arise from inadequate PFT parameters and incomplete PFT classification. For example, many traits vary more within PFTs than between PFTs. Moreover, the values assigned to different PFTs often do not differ much—so little is gained(and much uncertainty is added) compared to a generic model where all plants behave identically. This paper also reviews the recent progress in plant FTs for developing new generations of DGVMs, which includes:(1) descripting adaption strategies of plants to the changing environment,(2) revealing the mechanisms of coexistence between plant species,(3) highlighting the close relationship with the structures and processes of ecosystems, and(4) summarizing their application in the parameterization of vegetation models. We also summarize the main approaches to improve current or build new DGVMs based on FTs, such as building a transitional framework for a PFT-FT hybrid DGVM and building a completely FT-based DGVM. Based on those discussions, several future research directions are recommended for developing a new-generation DGVMs, such as improving the prediction power of traits within the PFTs, building the mechanism expressions between plant adaptations and environments, and standardizing of the data sharing for FTs. We argue that constructing next generation of DGVMs is not simply a matter of incorporating trait-climate relationships, but more importantly to combine optimality concepts and classical vegetation dynamic theories making vegetation modelling more reliable and robust. Botanists, geographers, vegetation modelers, and other relevant scientists should cooperate and share the trait data to elucidate the huge potential of plant FTs in constructing the next generation of more reliable, robust and realistic DGVMs. We hope this review will promote the developments and applications of new generation DGVMs in China.
Dynamic global vegetation models(DGVMs) are key components of earth system models(ESMs), which aim to understand ecosystem processes and their interactions with the atmosphere. DGVMs are designed to simulate the structural and functional responses of global vegetation to changes in climate and atmospheric CO_2 concentration with the coexistence of plant functional types(PFTs). PFTs are groups of plant species with similar functions based on morphological, physiological, biochemical, reproductive, and demographic characteristics. DGVMs typically assign each PFT with fixed parameters representing the above characteristics, consequently ignoring their variations within PFT and their responses to environmental changes. This parameterization scheme can simplify plant species represented in DGVMs but inevitably result in large uncertainties in model predictions on ecosystem processes. Therefore, a new generation of DGVMs are urgently needed to overcome the limitations of PFTs by replacing the PFTs parameterization scheme with continuous variation in plant functional traits. Plant functional traits(FTs) are defined as morphological, physiological, and phenological characteristics that affect plants via their effects on the growth, reproduction, and survival. Plant FTs that mediate the structure and function of ecosystems can be implemented into DGVMs as variables rather than PFT-specific parameters with fixed values. The plant FT scheme not only provides a widely applicable approach for forecasting ecosystem shifts and changes in ecosystem structure, but can also be linked with ecosystem functions under a changing climate. This holds great potentials for predicting possible responses of terrestrial ecosystems to environmental changes. This review first introduces the state-of-the-art DGVMs based on PFTs. PFTs represent most of the world's vegetation types and characteristics through their functional behaviors and attributes. Although PFT-based DGVMs play a pivotal role in simulating atmosphere-land interactions by quantifying the processes of global carbon, nitrogen, and water cycles, uncertainties arise from inadequate PFT parameters and incomplete PFT classification. For example, many traits vary more within PFTs than between PFTs. Moreover, the values assigned to different PFTs often do not differ much—so little is gained(and much uncertainty is added) compared to a generic model where all plants behave identically. This paper also reviews the recent progress in plant FTs for developing new generations of DGVMs, which includes:(1) descripting adaption strategies of plants to the changing environment,(2) revealing the mechanisms of coexistence between plant species,(3) highlighting the close relationship with the structures and processes of ecosystems, and(4) summarizing their application in the parameterization of vegetation models. We also summarize the main approaches to improve current or build new DGVMs based on FTs, such as building a transitional framework for a PFT-FT hybrid DGVM and building a completely FT-based DGVM. Based on those discussions, several future research directions are recommended for developing a new-generation DGVMs, such as improving the prediction power of traits within the PFTs, building the mechanism expressions between plant adaptations and environments, and standardizing of the data sharing for FTs. We argue that constructing next generation of DGVMs is not simply a matter of incorporating trait-climate relationships, but more importantly to combine optimality concepts and classical vegetation dynamic theories making vegetation modelling more reliable and robust. Botanists, geographers, vegetation modelers, and other relevant scientists should cooperate and share the trait data to elucidate the huge potential of plant FTs in constructing the next generation of more reliable, robust and realistic DGVMs. We hope this review will promote the developments and applications of new generation DGVMs in China.
引文
1 Prentice I C,Cramer W,Harrison S P,et al.A global biome model based on plant physiology and dominance,soil properties and climate.J Biogeogr,1992,19:117-134
2 Ciais P,Reichstein M,Viovy N,et al.Europe-wide reduction in primary productivity caused by the heat and drought in 2003.Nature,2005,437:529-533
3 Piao S L,Fang J Y,Ciais P,et al.The carbon balance of terrestrial ecosystems in China.Nature,2009,458:1009
4 Purves D,Pacala S.Predictive models of forest dynamics.Science,2008,320:1452
5 Heimann M,Reichstein M.Terrestrial ecosystem carbon dynamics and climate feedbacks.Nature,2008,451:289-292
6 Guiot J,Cramer W.Climate change:The 2015 paris agreement thresholds and mediterranean basin ecosystems.Science,2016,354:465-468
7 Sitch S,Huntingford C,Gedney N,et al.Evaluation of the terrestrial carbon cycle,future plant geography and climate-Carbon cycle feedbacks using five dynamic global vegetation models(DGVMs).Glob Change Biol,2008,14:2015-2039
8 Box E O.Plant functional types and climate at the global scale.J Veg Sci,1996,7:309-320
9 Cramer W,Bondeau A,Woodward F I,et al.Global response of terrestrial ecosystem structure and function to CO2 and climate change:Results from six dynamic global vegetation models.Glob Change Biol,2001,7:357-373
10 Yu G R,Wang Q F,Zhu X J.Methods and uncertaintiesin evaluating the carbon budgets of regional terrestrial ecosystems(in Chinese).Prog Geogr,2011,30:103-113[于贵瑞,王秋凤,朱先进.区域尺度陆地生态系统碳收支评估方法及其不确定性.地理科学进展,2011,30:103-113]
11 Piao S L,Ciais P,Lomas M,et al.Contribution of climate change and rising CO2 to terrestrial carbon balance in east asia:A multi-model analysis.Glob Planet Change,2011,75:133-142
12 Chapin F S III,Zavaleta E S,Eviner V T,et al.Consequences of changing biodiversity.Nature,2000,405:234-242
13 Bodegom P M V,Douma J C,Witte J P M,et al.Going beyond limitations of plant functional types when predicting global ecosystem-atmosphere fluxes:Exploring the merits of traits-based approaches.Glob Ecol Biogeogr,2012,21:625-636
14 Yang Y Z,Zhu Q A,Peng C H,et al.From plant functional types to plant functional traits:A new paradigm in modelling global vegetation dynamics.Prog Phys Geogr,2015,39:1-22
15 Peng C H.From static biogeographical model to dynamic global vegetation model:A global perspective on modelling vegetation dynamics.Ecol Model,2000,135:33-54
16 Lavorel S,Díaz S,Cornelissen J H C,et al.Plant functional types:Are we getting any closer to the holy grail?In:Terrestrial Ecosystems in a Changing World.Berlin,Heidelberg:Springer,2007
17 Mao J F,Wang B,Dai Y J.Perspective on terrestrial ecosystem models and their coupling with climate system models(in Chinese).Clima Environ Res,2006,11:763-771[毛嘉富,王斌,戴永久.陆地生态系统模型及其与气候模式耦合的回顾.气候与环境研究,2006,11:763-771]
18 Wang X F,Ma M G,Yao H.Advance in dynamic global vegetation model(in Chinese).Remote Sens Tech Appl,2009,24:246-251[王旭峰,马明国,姚辉.动态全球植被模型的研究进展.遥感技术与应用,2009,24:246-251]
19 Le QuéréC,Andrew R M,Friedlingstein P,et al.Global carbon budget 2017.Earth Syst Sci Data Diss,2017,1-79
20 Saunois M,Bousquet P,Poulter B,et al.The global methane budget 2000-2012.Earth Syst Sci Data,2016,8:697
21 Jones C D,John J G,Randerson J T.C4MIP-the coupled climate-carbon cycle model intercomparison project:Experimental protocol for CMIP6.Geosci Model Dev,2016,9:2853
22 Potter C S,Klooster S A.Dynamic global vegetation modelling for prediction of plant functional types and biogenic trace gas fluxes.Glob Ecol Biogeogr,1999,8:473-488
23 Sitch S,Smith B,Prentice I C,et al.Evaluation of ecosystem dynamics,plant geography and terrestrial carbon cycling in the LPJdynamic global vegetation model.Glob Change Biol,2003,9:161-185
24 Smith B,Prentice I C,Sykes M T.Representation of vegetation dynamics in the modelling of terrestrial ecosystems:Comparing two contrasting approaches within European climate space.Glob Ecol Biogeogr,2001,10:621-637
25 Bondeau A,Smith P C,Zaehle S,et al.Modelling the role of agriculture for the 20th century global terrestrial carbon balance.Glob Change Biol,2007,13:679-706
26 Foley J A,Prentice I C,Ramankutty N,et al.An integrated biosphere model of land surface processes,terrestrial carbon balance,and vegetation dynamics.Glob Biogeochem Cycle,1996,10:603-628
27 Kucharik C J,Foley J A,Delire C,et al.Testing the performance of a dynamic global ecosystem model:Water balance,carbon balance,and vegetation structure.Glob Biogeochem Cycle,2000,14:795-825
28 Levis S,Bonan B,Vertenstein M,et al.The community land model’s dynamic global vegetation model(CLM-DGVM).Colorado:Technical Description and User’s Guide.2004
29 Sato H,Itoh A,Kohyama T.SEIB-DGVM:A new dynamic global vegetation model using a spatially explicit individual-based approach.Ecol Model,2007,200:279-307
30 Best M,Pryor M,Clark D,et al.The joint uk land environment simulator(JULES),model description-part 1:Energy and water fluxes.Geosci Model Dev,2011,4:677-699
31 Zeng X,Li F,Song X.Development of the iap dynamic global vegetation model.Adv Atmos Sci,2014,31:505-514
32 Zhu Q A,Liu J X,Peng C H,et al.Modelling methane emissions from natural wetlands by development and application of the TRIPLEX-GHG model.Geosci Model Dev,2014,7:981-999
33 Yuan Q Z,Zhao D S,Wu S H,et al.Validation of the integrated biosphere simulator in simulating the potential natural vegetation map of China.Ecol Res,2011,26:917-929
34 Sun G D.Simulati on of potential vegetation distribution and estimation of carbon flux in China from 1981 to 1998 with LPJ dynamic global vegetation model(in Chinese).Clim Environ Res,2009,(4):341-351[孙国栋.LPJ模型对1981~1998年中国区域潜在植被分布和碳通量的模拟.气候与环境研究,2009,(4):341-351]
35 Yu M.Improvement of a dynamic vegetation model(ICM)and assesesment of its impactes on global climate simulation(in Chinese).Doctor Dissertation.Nanjing:Nanjing University of Information Science&Technolgy,2010[俞淼.动态植被模型ICM的改进及其对全球气候模拟的影响评估.博士学位论文.南京:南京信息工程大学,2010]
36 Zeng X,Zeng X,Shen S S,et al.Vegetation-soil water interaction within a dynamical ecosystem model of grassland in semi-Arid areas.Tellus Ser B-Chem Phys Meteorol,2005,57:189-202
37 Ma R,Zhang L,Tian X,et al.Assimilation of remotely-sensed leaf area index into a dynamic vegetation model for gross primary productivity estimation.Remote Sens,2017,9:188
38 Luo Y,Ogle K,Tucker C,et al.Ecological forecasting and data assimilation in a data-rich era.Ecol Appl,2011,21:1429
39 Li F,Zeng X,Levis S.A process-based fire parameterization of intermediate complexity in a dynamic global vegetation model.Biogeosciences,2012,9:2761-2780
40 Reich P B,Wright I J,Lusk C H.Predicting leaf physiology from simple plant and climate attributes:A global glopnet analysis.Ecol Appl,2007,17:1982-1988
41 Cunningham S,Read J.Comparison of temperate and tropical rainforest tree species:Photosynthetic responses to growth temperature.Oecologia,2002,133:112-119
42 Kunstler G,Falster D,Coomes D A,et al.Plant functional traits have globally consistent effects on competition.Nature,2015,529:204-207
43 Prentice I C,Dong N,Gleason S M,et al.Balancing the costs of carbon gain and water transport:Testing a new theoretical framework for plant functional ecology.Ecol Lett,2014,17:82-91
44 Violle C,Navas M L,Vile D,et al.Let the concept of trait be functional!Oikos,2007,116:882-892
45 Liu X J,Ma K P.Plant functional traits:Concepts,applications and future directions(in Chinese).Sci China Life Sci,2015,45:325-339[刘晓娟,马克平.植物功能性状研究进展.中国科学:生命科学,2015,45:325-339]
46 Yao T T,Meng T T,Ni J,et al.Leaf functional trait variation and its relationship with plant phylogenic background and the climate in Xinjiang Junggar Basin,NW China(in Chinese).Biodivers Sci,2010,18:188-197[尧婷婷,孟婷婷,倪健,等.新疆准噶尔荒漠植物叶片功能性状的进化和环境驱动机制初探.生物多样性,2010,18:188-197]
47 Feng Q H,Shi Z M,Dong L L,et al.Relationships among functional traits of Quercus species and their response to meteorological factors in the temperate zone of the north-south transect of eastern China(in Chinese).Chin J Plant Ecol,2010,34:619-627[冯秋红,史作民,董莉莉,等.南北样带温带区栎属树种功能性状间的关系及其对气象因子的响应.植物生态学报,2010,34:619-627]
48 Meng T T,Ni J,Wang G H.Plant functional traits,environments and ecosystem functioning(in Chinese).J Plant Ecol,2007,(1):150-165[孟婷婷,倪健,王国宏.植物功能性状与环境和生态系统功能.植物生态学报,2007,(1):150-165]
49 Xiao Y,Xie G D,An K.A research framework of ecosystem services based on functional traits(in Chinese).Chin J Plant Ecol,2012,36:353-362[肖玉,谢高地,安凯,等.基于功能性状的生态系统服务研究框架.植物生态学报,2012,36:353-362]
50 Webb C T,Hoeting J A,Ames G M,et al.A structured and dynamic framework to advance traits-based theory and prediction in ecology.Ecol Lett,2010,13:267-283
51 Wright I,Reich P,Johannes H C,et al.Modulation of leaf economic traits and trait relationships by climate.Glob Ecol Biogeogr,2005,14:411-421
52 Reich P B,Oleksyn J.Global patterns of plant leaf n and p in relation to temperature and latitude.Proc Natl Acad Sci USA,2004,101:11001-11006
53 He N,Liu C,Tian M,et al.Variation in leaf anatomical traits from tropical to cold-Temperate forests and linkage to ecosystem functions.Funct Ecol,2018,32:1175-1181
54 Liu C,He N,Zhang J,et al.Variation of stomatal traits from cold temperate to tropical forests and association with water use efficiency.Funct Ecol,2018,32:20-28
55 Soudzilovskaia N A,Elumeeva T G,Onipchenko V G,et al.Functional traits predict relationship between plant abundance dynamic and long-term climate warming.Proc Natl Acad Sci USA,2013,110:18180-18184
56 Wright I J,Reich P B,Westoby M,et al.The worldwide leaf economics spectrum.Nature,2004,428:821
57 Song G,Wen Z M,Zheng Y,et al.Relatisionships between plnatfunctioanl traits on Robinia Pseudoacacia and meteological factors in Loess Plateau,North Shaanxi,China(in Chinese).Res Soil Water Conserv,2013,(3):125-130[宋光,温仲明,郑颖,等.陕北黄土高原刺槐植物功能性状与气象因子的关系.水土保持学报,2013,(3):125-130]
58 Westoby M,Falster D S,Moles A T,et al.Plant ecological strategies:Some leading dimensions of variation between species.Annu Rev Ecol Syst,2002,33:125-159
59 Kraft N J,Godoy O,Levine J M.Plant functional traits and the multidimensional nature of species coexistence.Proc Natl Acad Sci USA,2015,112:797
60 Wang R,Wang Q,Zhao N,et al.Different phylogenetic and environmental controls of first-order root morphological and nutrient traits:Evidence of multidimensional root traits.Funct Ecol,2018,32:29-39
61 Ackerly D D,Cornwell W K.A trait-based approach to community assembly:Partitioning of species trait values into within-and among-community components.Ecol Lett,2007,10:135-145
62 Ding M,Wen Z M,Zheng Y.Scale change and dependence of plant functional traits in hilly areas of the loess region,Shaanxi Province,China(in Chinese).Acta Ecol Sin,2014,9:2308-2315[丁曼,温仲明,郑颖.黄土丘陵区植物功能性状的尺度变化与依赖.生态学报,2014,9:2308-2315]
63 Suding K N,Lavorel S,Chapin F S III,et al.Scaling environmental change through the community-level:A trait-based responseand-effect framework for plants.Glob Change Biol,2008,14:1125-1140
64 Klumpp K,Soussana J F.Using functional traits to predict grassland ecosystem change:A mathematical test of the response-and-effect trait approach.Glob Change Biol,2010,15:2921-2934
65 Wright I J,Dong N,Maire V,et al.Global climatic drivers of leaf size.Science,2017,357:917-921
66 Wright I J,Reich P B,Westoby M.Least-cost input mixtures of water and nitrogen for photosynthesis.Am Nat,2003,161:98-111
67 Poorter L,Bongers F.Leaf traits are good predictors of plant performance across 53 rain forest species.Ecology,2006,87:1733-1743
68 Reichstein M,Bahn M,Mahecha M D,et al.Linking plant and ecosystem functional biogeography.Proc Natl Acad Sci USA,2014,111:13697-13702
69 Pavlick R,Drewry D T,Bohn K,et al.The jena diversity-dynamic global vegetation model(Je Di-DGVM):A diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs.Biogeosciences,2013,10:4137-4177
70 Scheiter S,Langan L,Higgins S I.Next-generation dynamic global vegetation models:Learning from community ecology.New Phytol,2013,198:957-969
71 Fisher R,Muszala S,Verteinstein M,et al.Taking off the training wheels:The properties of a dynamic vegetation model without climate envelopes,CLM4.5(ED).Geosci Model Dev,2015,8:3593
72 Zhu Y J,Gao Q,Liu J S,et al.Aggregation of plant functional types based on model of stomatal conductance and photosynthesis(in Chinese).J Plant Ecol,2007,31:873-882[朱玉洁,高琼,刘峻杉,等.基于气孔导度和光合模型的植物功能类群合并问题.植物生态学报,2007,31:873-882]
73 van Bodegom P M,Douma J C,Verheijen L M.A fully traits-based approach to modeling global vegetation distribution.Proc Natl Acad Sci USA,2014,111:13733-13738
74 Verheijen L M,Brovkin V,Aerts R,et al.Impacts of trait variation through observed trait-climate relationships on performance of an earth system model:A conceptual analysis.Biogeosci Dis,2012,9:18907-18950
75 Lu X,Wang Y P,Wright I J,et al.Incorporation of plant traits in a land surface model helps explain the global biogeographical distribution of major forest functional types.Glob Ecol Biogeogr,2017,26:304-317
76 Yang Y Z,Zhu Q A,Peng C H,et al.A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China.Sci Rep,2016,6:24110
77 Woodward F I,Diament A D.Functional approaches to predicting the ecological effects of global change.Funct Ecol,1991,5:202
78 Keddy P A.Assembly and response rules:Two goals for predictive community ecology.J Veg Sci,1992,3:157-164
79 Lavorel S,Garnier E.Predicting changes in community composition and ecosystem functioning from plant traits:Revisiting the holy grail.Funct Ecol,2002,16:545-556
80 Shipley B,Vile D,Garnieré.From plant traits to plant communities:A statistical mechanistic approach to biodiversity.Science,2006,314:812-814
81 Laughlin D C,Joshi C,Bodegom P M,et al.A predictive model of community assembly that incorporates intraspecific trait variation.Ecol Lett,2012,15:1291-1299
82 Ali A A,Medlyn B E,Crous K Y,et al.A trait-based ecosystem model suggests that long-term responsiveness to rising atmospheric CO2concentration is greater in slow-growing than fast-growing plants.Funct Ecol,2013,27:1011-1022
83 Higgins S I,Langan L,Scheiter S.Progress in DGVMs:A comment on“impacts of trait variation through observed trait-climate relationships on performance of an earth system model:A conceptual analysis”by Verheijen et al.(2013).Biogeosciences,2014,11:4357-4360
84 Wang H,Prentice I C,Davis T W,et al.Photosynthetic responses to altitude:An explanation based on optimality principles.New Phytol,2017,213:976-982
85 Wang H,Prentice I C,Keenan T F,et al.Towards a universal model for carbon dioxide uptake by plants.Nat Plants,2017,3:734-741
86 Reich P B,Rich R L,Lu X,et al.Biogeographic variation in evergreen conifer needle longevity and impacts on boreal forest carbon cycle projections.Proc Natl Acad Sci USA,2014,111:13703-13708
87 HomolováL,MalenovskyZ,Clevers J G P W,et al.Review of optical-based remote sensing for plant trait mapping.Ecol Complex,2013,15:1-16
88 Asner G P,Martin R E,Knapp D,et al.Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation.Science,2017,355:385-389
89 Asner G P,Martin R E,Anderson C B,et al.Scale dependence of canopy trait distributions along a tropical forest elevation gradient.New Phytol,2017,214:973-988
90 Prentice I C,Liang X,Medlyn B E,et al.Reliable,robust and realistic:The three R’s of next-generation land-surface modelling.Atmos Chem Phys,2015,15:5987-6005
91 Maire V,Martre P,Kattge J,et al.The coordination of leaf photosynthesis links C and N fluxes in C3 plant species.PLo S One,2012,7:e38345
92 Dong N,Prentice I C,Evans B J,et al.Leaf nitrogen from first principles:Field evidence for adaptive variation with climate.Biogeosciences,2017,14:481-495
93 He J S,Wang X,Schmid B,et al.Taxonomic identity,phylogeny,climate and soil fertility as drivers of leaf traits across Chinese grassland biomes.J Plant Res,2010,123:551-561
94 Han W X,Fang J Y,Reich P B,et al.Biogeography and variability of eleven mineral elements in plant leaves across gradients of climate,soil and plant functional type in China.Ecol Lett,2011,14:788-796
95 Ackerly D.Conservatism and diversification of plant functional traits:Evolutionary rates versus phylogenetic signal.Proc Natl Acad Sci USA.2009,106:19699-19706
96 Keenan T F,Niinemetsü.Global leaf trait estimates biased due to plasticity in the shade.Nat plants,2017,3:16201
97 Kattge J,Díaz S,Lavorel S,et al.Try-A global database of plant traits.Glob Change Biol,2011,17:2905-2935
98 Kleyer M,Bekker R M,Knevel I C,et al.The leda traitbase:A database of life-history traits of the northwest european flora.J Ecol,2008,96:1266-1274
99 Wang H,Harrison S P,Prentice I C,et al.The China plant trait database:Towards a comprehensive regional compilation of functional traits for land plants.Ecology,2018,99:500
100 Cornwell W K,Wright I,Turner J,et al.A global dataset of leaf delta 13C values.Dryad Digital Repository:10.5061/dryad.3jh61
101 De Kauwe M G,Lin Y S,Wright I J,et al.A test of the‘one-point method’for estimating maximum carboxylation capacity from fieldmeasured,light-saturated photosynthesis.New Phytol,2016,210:1130
102 Walker A P,Beckerman A P,Gu L,et al.The relationship of leaf photosynthetic traits-vcmax and jmax-to leaf nitrogen,leaf phosphorus,and specific leaf area:A meta-analysis and modeling study.Ecol Evol,2014,4:3218-3235
103 Cornelissen J H C,Lavorel S,Garnier E,et al.A handbook of protocols for standardised and easy measurement of plant functional traits worldwide.Aust J Bot,2003,51:335-380
104 Pérez-Harguindeguy N,Garnier E,Lavorel S,et al.New handbook for standardised measurement of plant functional traits worldwide.Aust J Bot,2013,61:167-234
105 Geng Y,Ma W,Wang L,et al.Linking above-and belowground traits to soil and climate variables:An integrated database on China’s grassland species.Ecology,2017,98:1471
2 Ciais P,Reichstein M,Viovy N,et al.Europe-wide reduction in primary productivity caused by the heat and drought in 2003.Nature,2005,437:529-533
3 Piao S L,Fang J Y,Ciais P,et al.The carbon balance of terrestrial ecosystems in China.Nature,2009,458:1009
4 Purves D,Pacala S.Predictive models of forest dynamics.Science,2008,320:1452
5 Heimann M,Reichstein M.Terrestrial ecosystem carbon dynamics and climate feedbacks.Nature,2008,451:289-292
6 Guiot J,Cramer W.Climate change:The 2015 paris agreement thresholds and mediterranean basin ecosystems.Science,2016,354:465-468
7 Sitch S,Huntingford C,Gedney N,et al.Evaluation of the terrestrial carbon cycle,future plant geography and climate-Carbon cycle feedbacks using five dynamic global vegetation models(DGVMs).Glob Change Biol,2008,14:2015-2039
8 Box E O.Plant functional types and climate at the global scale.J Veg Sci,1996,7:309-320
9 Cramer W,Bondeau A,Woodward F I,et al.Global response of terrestrial ecosystem structure and function to CO2 and climate change:Results from six dynamic global vegetation models.Glob Change Biol,2001,7:357-373
10 Yu G R,Wang Q F,Zhu X J.Methods and uncertaintiesin evaluating the carbon budgets of regional terrestrial ecosystems(in Chinese).Prog Geogr,2011,30:103-113[于贵瑞,王秋凤,朱先进.区域尺度陆地生态系统碳收支评估方法及其不确定性.地理科学进展,2011,30:103-113]
11 Piao S L,Ciais P,Lomas M,et al.Contribution of climate change and rising CO2 to terrestrial carbon balance in east asia:A multi-model analysis.Glob Planet Change,2011,75:133-142
12 Chapin F S III,Zavaleta E S,Eviner V T,et al.Consequences of changing biodiversity.Nature,2000,405:234-242
13 Bodegom P M V,Douma J C,Witte J P M,et al.Going beyond limitations of plant functional types when predicting global ecosystem-atmosphere fluxes:Exploring the merits of traits-based approaches.Glob Ecol Biogeogr,2012,21:625-636
14 Yang Y Z,Zhu Q A,Peng C H,et al.From plant functional types to plant functional traits:A new paradigm in modelling global vegetation dynamics.Prog Phys Geogr,2015,39:1-22
15 Peng C H.From static biogeographical model to dynamic global vegetation model:A global perspective on modelling vegetation dynamics.Ecol Model,2000,135:33-54
16 Lavorel S,Díaz S,Cornelissen J H C,et al.Plant functional types:Are we getting any closer to the holy grail?In:Terrestrial Ecosystems in a Changing World.Berlin,Heidelberg:Springer,2007
17 Mao J F,Wang B,Dai Y J.Perspective on terrestrial ecosystem models and their coupling with climate system models(in Chinese).Clima Environ Res,2006,11:763-771[毛嘉富,王斌,戴永久.陆地生态系统模型及其与气候模式耦合的回顾.气候与环境研究,2006,11:763-771]
18 Wang X F,Ma M G,Yao H.Advance in dynamic global vegetation model(in Chinese).Remote Sens Tech Appl,2009,24:246-251[王旭峰,马明国,姚辉.动态全球植被模型的研究进展.遥感技术与应用,2009,24:246-251]
19 Le QuéréC,Andrew R M,Friedlingstein P,et al.Global carbon budget 2017.Earth Syst Sci Data Diss,2017,1-79
20 Saunois M,Bousquet P,Poulter B,et al.The global methane budget 2000-2012.Earth Syst Sci Data,2016,8:697
21 Jones C D,John J G,Randerson J T.C4MIP-the coupled climate-carbon cycle model intercomparison project:Experimental protocol for CMIP6.Geosci Model Dev,2016,9:2853
22 Potter C S,Klooster S A.Dynamic global vegetation modelling for prediction of plant functional types and biogenic trace gas fluxes.Glob Ecol Biogeogr,1999,8:473-488
23 Sitch S,Smith B,Prentice I C,et al.Evaluation of ecosystem dynamics,plant geography and terrestrial carbon cycling in the LPJdynamic global vegetation model.Glob Change Biol,2003,9:161-185
24 Smith B,Prentice I C,Sykes M T.Representation of vegetation dynamics in the modelling of terrestrial ecosystems:Comparing two contrasting approaches within European climate space.Glob Ecol Biogeogr,2001,10:621-637
25 Bondeau A,Smith P C,Zaehle S,et al.Modelling the role of agriculture for the 20th century global terrestrial carbon balance.Glob Change Biol,2007,13:679-706
26 Foley J A,Prentice I C,Ramankutty N,et al.An integrated biosphere model of land surface processes,terrestrial carbon balance,and vegetation dynamics.Glob Biogeochem Cycle,1996,10:603-628
27 Kucharik C J,Foley J A,Delire C,et al.Testing the performance of a dynamic global ecosystem model:Water balance,carbon balance,and vegetation structure.Glob Biogeochem Cycle,2000,14:795-825
28 Levis S,Bonan B,Vertenstein M,et al.The community land model’s dynamic global vegetation model(CLM-DGVM).Colorado:Technical Description and User’s Guide.2004
29 Sato H,Itoh A,Kohyama T.SEIB-DGVM:A new dynamic global vegetation model using a spatially explicit individual-based approach.Ecol Model,2007,200:279-307
30 Best M,Pryor M,Clark D,et al.The joint uk land environment simulator(JULES),model description-part 1:Energy and water fluxes.Geosci Model Dev,2011,4:677-699
31 Zeng X,Li F,Song X.Development of the iap dynamic global vegetation model.Adv Atmos Sci,2014,31:505-514
32 Zhu Q A,Liu J X,Peng C H,et al.Modelling methane emissions from natural wetlands by development and application of the TRIPLEX-GHG model.Geosci Model Dev,2014,7:981-999
33 Yuan Q Z,Zhao D S,Wu S H,et al.Validation of the integrated biosphere simulator in simulating the potential natural vegetation map of China.Ecol Res,2011,26:917-929
34 Sun G D.Simulati on of potential vegetation distribution and estimation of carbon flux in China from 1981 to 1998 with LPJ dynamic global vegetation model(in Chinese).Clim Environ Res,2009,(4):341-351[孙国栋.LPJ模型对1981~1998年中国区域潜在植被分布和碳通量的模拟.气候与环境研究,2009,(4):341-351]
35 Yu M.Improvement of a dynamic vegetation model(ICM)and assesesment of its impactes on global climate simulation(in Chinese).Doctor Dissertation.Nanjing:Nanjing University of Information Science&Technolgy,2010[俞淼.动态植被模型ICM的改进及其对全球气候模拟的影响评估.博士学位论文.南京:南京信息工程大学,2010]
36 Zeng X,Zeng X,Shen S S,et al.Vegetation-soil water interaction within a dynamical ecosystem model of grassland in semi-Arid areas.Tellus Ser B-Chem Phys Meteorol,2005,57:189-202
37 Ma R,Zhang L,Tian X,et al.Assimilation of remotely-sensed leaf area index into a dynamic vegetation model for gross primary productivity estimation.Remote Sens,2017,9:188
38 Luo Y,Ogle K,Tucker C,et al.Ecological forecasting and data assimilation in a data-rich era.Ecol Appl,2011,21:1429
39 Li F,Zeng X,Levis S.A process-based fire parameterization of intermediate complexity in a dynamic global vegetation model.Biogeosciences,2012,9:2761-2780
40 Reich P B,Wright I J,Lusk C H.Predicting leaf physiology from simple plant and climate attributes:A global glopnet analysis.Ecol Appl,2007,17:1982-1988
41 Cunningham S,Read J.Comparison of temperate and tropical rainforest tree species:Photosynthetic responses to growth temperature.Oecologia,2002,133:112-119
42 Kunstler G,Falster D,Coomes D A,et al.Plant functional traits have globally consistent effects on competition.Nature,2015,529:204-207
43 Prentice I C,Dong N,Gleason S M,et al.Balancing the costs of carbon gain and water transport:Testing a new theoretical framework for plant functional ecology.Ecol Lett,2014,17:82-91
44 Violle C,Navas M L,Vile D,et al.Let the concept of trait be functional!Oikos,2007,116:882-892
45 Liu X J,Ma K P.Plant functional traits:Concepts,applications and future directions(in Chinese).Sci China Life Sci,2015,45:325-339[刘晓娟,马克平.植物功能性状研究进展.中国科学:生命科学,2015,45:325-339]
46 Yao T T,Meng T T,Ni J,et al.Leaf functional trait variation and its relationship with plant phylogenic background and the climate in Xinjiang Junggar Basin,NW China(in Chinese).Biodivers Sci,2010,18:188-197[尧婷婷,孟婷婷,倪健,等.新疆准噶尔荒漠植物叶片功能性状的进化和环境驱动机制初探.生物多样性,2010,18:188-197]
47 Feng Q H,Shi Z M,Dong L L,et al.Relationships among functional traits of Quercus species and their response to meteorological factors in the temperate zone of the north-south transect of eastern China(in Chinese).Chin J Plant Ecol,2010,34:619-627[冯秋红,史作民,董莉莉,等.南北样带温带区栎属树种功能性状间的关系及其对气象因子的响应.植物生态学报,2010,34:619-627]
48 Meng T T,Ni J,Wang G H.Plant functional traits,environments and ecosystem functioning(in Chinese).J Plant Ecol,2007,(1):150-165[孟婷婷,倪健,王国宏.植物功能性状与环境和生态系统功能.植物生态学报,2007,(1):150-165]
49 Xiao Y,Xie G D,An K.A research framework of ecosystem services based on functional traits(in Chinese).Chin J Plant Ecol,2012,36:353-362[肖玉,谢高地,安凯,等.基于功能性状的生态系统服务研究框架.植物生态学报,2012,36:353-362]
50 Webb C T,Hoeting J A,Ames G M,et al.A structured and dynamic framework to advance traits-based theory and prediction in ecology.Ecol Lett,2010,13:267-283
51 Wright I,Reich P,Johannes H C,et al.Modulation of leaf economic traits and trait relationships by climate.Glob Ecol Biogeogr,2005,14:411-421
52 Reich P B,Oleksyn J.Global patterns of plant leaf n and p in relation to temperature and latitude.Proc Natl Acad Sci USA,2004,101:11001-11006
53 He N,Liu C,Tian M,et al.Variation in leaf anatomical traits from tropical to cold-Temperate forests and linkage to ecosystem functions.Funct Ecol,2018,32:1175-1181
54 Liu C,He N,Zhang J,et al.Variation of stomatal traits from cold temperate to tropical forests and association with water use efficiency.Funct Ecol,2018,32:20-28
55 Soudzilovskaia N A,Elumeeva T G,Onipchenko V G,et al.Functional traits predict relationship between plant abundance dynamic and long-term climate warming.Proc Natl Acad Sci USA,2013,110:18180-18184
56 Wright I J,Reich P B,Westoby M,et al.The worldwide leaf economics spectrum.Nature,2004,428:821
57 Song G,Wen Z M,Zheng Y,et al.Relatisionships between plnatfunctioanl traits on Robinia Pseudoacacia and meteological factors in Loess Plateau,North Shaanxi,China(in Chinese).Res Soil Water Conserv,2013,(3):125-130[宋光,温仲明,郑颖,等.陕北黄土高原刺槐植物功能性状与气象因子的关系.水土保持学报,2013,(3):125-130]
58 Westoby M,Falster D S,Moles A T,et al.Plant ecological strategies:Some leading dimensions of variation between species.Annu Rev Ecol Syst,2002,33:125-159
59 Kraft N J,Godoy O,Levine J M.Plant functional traits and the multidimensional nature of species coexistence.Proc Natl Acad Sci USA,2015,112:797
60 Wang R,Wang Q,Zhao N,et al.Different phylogenetic and environmental controls of first-order root morphological and nutrient traits:Evidence of multidimensional root traits.Funct Ecol,2018,32:29-39
61 Ackerly D D,Cornwell W K.A trait-based approach to community assembly:Partitioning of species trait values into within-and among-community components.Ecol Lett,2007,10:135-145
62 Ding M,Wen Z M,Zheng Y.Scale change and dependence of plant functional traits in hilly areas of the loess region,Shaanxi Province,China(in Chinese).Acta Ecol Sin,2014,9:2308-2315[丁曼,温仲明,郑颖.黄土丘陵区植物功能性状的尺度变化与依赖.生态学报,2014,9:2308-2315]
63 Suding K N,Lavorel S,Chapin F S III,et al.Scaling environmental change through the community-level:A trait-based responseand-effect framework for plants.Glob Change Biol,2008,14:1125-1140
64 Klumpp K,Soussana J F.Using functional traits to predict grassland ecosystem change:A mathematical test of the response-and-effect trait approach.Glob Change Biol,2010,15:2921-2934
65 Wright I J,Dong N,Maire V,et al.Global climatic drivers of leaf size.Science,2017,357:917-921
66 Wright I J,Reich P B,Westoby M.Least-cost input mixtures of water and nitrogen for photosynthesis.Am Nat,2003,161:98-111
67 Poorter L,Bongers F.Leaf traits are good predictors of plant performance across 53 rain forest species.Ecology,2006,87:1733-1743
68 Reichstein M,Bahn M,Mahecha M D,et al.Linking plant and ecosystem functional biogeography.Proc Natl Acad Sci USA,2014,111:13697-13702
69 Pavlick R,Drewry D T,Bohn K,et al.The jena diversity-dynamic global vegetation model(Je Di-DGVM):A diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs.Biogeosciences,2013,10:4137-4177
70 Scheiter S,Langan L,Higgins S I.Next-generation dynamic global vegetation models:Learning from community ecology.New Phytol,2013,198:957-969
71 Fisher R,Muszala S,Verteinstein M,et al.Taking off the training wheels:The properties of a dynamic vegetation model without climate envelopes,CLM4.5(ED).Geosci Model Dev,2015,8:3593
72 Zhu Y J,Gao Q,Liu J S,et al.Aggregation of plant functional types based on model of stomatal conductance and photosynthesis(in Chinese).J Plant Ecol,2007,31:873-882[朱玉洁,高琼,刘峻杉,等.基于气孔导度和光合模型的植物功能类群合并问题.植物生态学报,2007,31:873-882]
73 van Bodegom P M,Douma J C,Verheijen L M.A fully traits-based approach to modeling global vegetation distribution.Proc Natl Acad Sci USA,2014,111:13733-13738
74 Verheijen L M,Brovkin V,Aerts R,et al.Impacts of trait variation through observed trait-climate relationships on performance of an earth system model:A conceptual analysis.Biogeosci Dis,2012,9:18907-18950
75 Lu X,Wang Y P,Wright I J,et al.Incorporation of plant traits in a land surface model helps explain the global biogeographical distribution of major forest functional types.Glob Ecol Biogeogr,2017,26:304-317
76 Yang Y Z,Zhu Q A,Peng C H,et al.A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China.Sci Rep,2016,6:24110
77 Woodward F I,Diament A D.Functional approaches to predicting the ecological effects of global change.Funct Ecol,1991,5:202
78 Keddy P A.Assembly and response rules:Two goals for predictive community ecology.J Veg Sci,1992,3:157-164
79 Lavorel S,Garnier E.Predicting changes in community composition and ecosystem functioning from plant traits:Revisiting the holy grail.Funct Ecol,2002,16:545-556
80 Shipley B,Vile D,Garnieré.From plant traits to plant communities:A statistical mechanistic approach to biodiversity.Science,2006,314:812-814
81 Laughlin D C,Joshi C,Bodegom P M,et al.A predictive model of community assembly that incorporates intraspecific trait variation.Ecol Lett,2012,15:1291-1299
82 Ali A A,Medlyn B E,Crous K Y,et al.A trait-based ecosystem model suggests that long-term responsiveness to rising atmospheric CO2concentration is greater in slow-growing than fast-growing plants.Funct Ecol,2013,27:1011-1022
83 Higgins S I,Langan L,Scheiter S.Progress in DGVMs:A comment on“impacts of trait variation through observed trait-climate relationships on performance of an earth system model:A conceptual analysis”by Verheijen et al.(2013).Biogeosciences,2014,11:4357-4360
84 Wang H,Prentice I C,Davis T W,et al.Photosynthetic responses to altitude:An explanation based on optimality principles.New Phytol,2017,213:976-982
85 Wang H,Prentice I C,Keenan T F,et al.Towards a universal model for carbon dioxide uptake by plants.Nat Plants,2017,3:734-741
86 Reich P B,Rich R L,Lu X,et al.Biogeographic variation in evergreen conifer needle longevity and impacts on boreal forest carbon cycle projections.Proc Natl Acad Sci USA,2014,111:13703-13708
87 HomolováL,MalenovskyZ,Clevers J G P W,et al.Review of optical-based remote sensing for plant trait mapping.Ecol Complex,2013,15:1-16
88 Asner G P,Martin R E,Knapp D,et al.Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation.Science,2017,355:385-389
89 Asner G P,Martin R E,Anderson C B,et al.Scale dependence of canopy trait distributions along a tropical forest elevation gradient.New Phytol,2017,214:973-988
90 Prentice I C,Liang X,Medlyn B E,et al.Reliable,robust and realistic:The three R’s of next-generation land-surface modelling.Atmos Chem Phys,2015,15:5987-6005
91 Maire V,Martre P,Kattge J,et al.The coordination of leaf photosynthesis links C and N fluxes in C3 plant species.PLo S One,2012,7:e38345
92 Dong N,Prentice I C,Evans B J,et al.Leaf nitrogen from first principles:Field evidence for adaptive variation with climate.Biogeosciences,2017,14:481-495
93 He J S,Wang X,Schmid B,et al.Taxonomic identity,phylogeny,climate and soil fertility as drivers of leaf traits across Chinese grassland biomes.J Plant Res,2010,123:551-561
94 Han W X,Fang J Y,Reich P B,et al.Biogeography and variability of eleven mineral elements in plant leaves across gradients of climate,soil and plant functional type in China.Ecol Lett,2011,14:788-796
95 Ackerly D.Conservatism and diversification of plant functional traits:Evolutionary rates versus phylogenetic signal.Proc Natl Acad Sci USA.2009,106:19699-19706
96 Keenan T F,Niinemetsü.Global leaf trait estimates biased due to plasticity in the shade.Nat plants,2017,3:16201
97 Kattge J,Díaz S,Lavorel S,et al.Try-A global database of plant traits.Glob Change Biol,2011,17:2905-2935
98 Kleyer M,Bekker R M,Knevel I C,et al.The leda traitbase:A database of life-history traits of the northwest european flora.J Ecol,2008,96:1266-1274
99 Wang H,Harrison S P,Prentice I C,et al.The China plant trait database:Towards a comprehensive regional compilation of functional traits for land plants.Ecology,2018,99:500
100 Cornwell W K,Wright I,Turner J,et al.A global dataset of leaf delta 13C values.Dryad Digital Repository:10.5061/dryad.3jh61
101 De Kauwe M G,Lin Y S,Wright I J,et al.A test of the‘one-point method’for estimating maximum carboxylation capacity from fieldmeasured,light-saturated photosynthesis.New Phytol,2016,210:1130
102 Walker A P,Beckerman A P,Gu L,et al.The relationship of leaf photosynthetic traits-vcmax and jmax-to leaf nitrogen,leaf phosphorus,and specific leaf area:A meta-analysis and modeling study.Ecol Evol,2014,4:3218-3235
103 Cornelissen J H C,Lavorel S,Garnier E,et al.A handbook of protocols for standardised and easy measurement of plant functional traits worldwide.Aust J Bot,2003,51:335-380
104 Pérez-Harguindeguy N,Garnier E,Lavorel S,et al.New handbook for standardised measurement of plant functional traits worldwide.Aust J Bot,2013,61:167-234
105 Geng Y,Ma W,Wang L,et al.Linking above-and belowground traits to soil and climate variables:An integrated database on China’s grassland species.Ecology,2017,98:1471