植物生态学报 ›› 2023, Vol. 47 ›› Issue (2): 145-169.DOI: 10.17521/cjpe.2022.0245
• 综述 • 下一篇
收稿日期:
2022-06-13
接受日期:
2022-09-08
出版日期:
2023-02-20
发布日期:
2023-02-28
通讯作者:
ORCID: *王志恒: 0000-0003-0808-7780(zhiheng.wang@pku.edu.cn)
作者简介:
李耀琪: ORCID:0000-0001-6540-395X
基金资助:
LI Yao-Qi1,2, WANG Zhi-Heng1,*()
Received:
2022-06-13
Accepted:
2022-09-08
Online:
2023-02-20
Published:
2023-02-28
Contact:
*(Supported by:
摘要:
功能生物地理学研究性状及其多样性的时空分布变化、生态成因及其对生态系统功能的影响。近十来年, 功能生物地理学领域发展迅速, 性状数据呈指数增长, 基于性状探索物种分布、群落结构和组成以及生态系统功能对环境变化响应的研究取得了重要进展。该文综述了植物功能生物地理学的核心内涵、发展历史、主要研究进展和未来展望。性状是功能生物地理学的研究核心, 该文先总结了植物叶、茎、根、花、果实和种子等器官和整株关键性状的地理格局及其与环境间的关系, 表明性状变异是植物适应进化和环境筛选的结果; 概述了功能多样性的常用指标、地理分布与生态成因; 介绍了性状数据的主要来源与性状缺失值的填充方法。随后, 综述了植物性状间的关联与权衡, 重点介绍了叶经济谱和植物经济谱的发展, 指出其反映了植物对关键资源(如碳、养分和水分)的获取与分配策略; 概述了基于性状预测物种分布的依据与进展, 以及性状多样性与生态系统功能间的关系。在此基础上, 提出了功能生物地理学研究所面临的挑战, 强调未来研究要关注多性状在种内和种间的协同与权衡关系, 将研究精度从物种水平推进到个体水平, 采用性状网络等方法定量化性状间的关系及其对环境变化的响应, 关注植物跨尺度的适应; 并指出如何将现有的研究进展应用于新一代植被模型的改进, 指导基于功能的植物多样性保护等是未来研究的重点和难点。
李耀琪, 王志恒. 植物功能生物地理学的研究进展与展望. 植物生态学报, 2023, 47(2): 145-169. DOI: 10.17521/cjpe.2022.0245
LI Yao-Qi, WANG Zhi-Heng. Functional biogeography of plants: research progresses and challenges. Chinese Journal of Plant Ecology, 2023, 47(2): 145-169. DOI: 10.17521/cjpe.2022.0245
图1 功能生物地理学的定义、主要目标与相关领域。根据Violle等(2014)中图1改编。
Fig. 1 Functional biogeography: definition, main objectives and related fields. Modified from Figure 1 in Violle et al. (2014).
图3 自1900年以来功能生物地理学领域论文发表数量的变化趋势。以“functional biogeography”或(“function*” + “biogeograph*”)为主题关键词在Web of Science核心合集数据库(WoS)中进行主题搜索。*表征所有可能的字母组合, 例如“biogeograph*”包括“biogeography” “biogeographic”等词。
Fig. 3 Number of papers published as the topic of functional biogeography since 1900. Searched through Web of Science core collection using a search query as TS = (“functional biogeography”) OR TS = (“function*” AND “biogeograph*”). TS, topic searching; * represents all possible combination of letters, for example, “biogeograph*” included words like “biogeography” and “biogeographic”.
图4 功能生物地理学研究领域发表的文章数量与质量在不同类群(A)、国家(B)和生态系统(C)间的对比。
Fig. 4 Comparisons of the numbers and quality of publications in the field of functional biogeography across different taxa (A), countries (B), and ecosystems (C).
图5 功能生物地理学研究领域的关键词词云(A、C)和主题图(B、D)。A、B为全部类群。C、D为植物类群。词云来自图3在Web of Science中搜索到的所有论文的标题、摘要和关联关键词。主题图基于共词网络分析划分4个象限, 代表该领域内各个主题的重要性(即中心度)和发展情况(即密度)。圆形上的标记代表该主题下最重要的关键词, 圆形的大小反映了包含对应关键词的文章数量。方法参考Codo等(2011)。
Fig. 5 Word cloud (A, C) and thematic map (B, D) in the field of functional biogeography. A, B for all taxa. C, D for plants. Word cloud was generated from the titles, abstracts and key words plus of all publications searched by Fig. 3. Thematic map was divided into four regions using co-word network analysis, which represents the importance (i.e. centrality) and development (i.e. density) of detecting themes in this field. Circles were labelled by the most significant key word in that theme, and the size of circles were scaled to the number of publications including that key word. See Codo et al. (2011) for details.
排序 Order | 发表期刊 Journals for publications | 引用期刊 Journals for cited publications |
---|---|---|
1 | Journal of Biogeography | Proceedings of the National Academy of Sciences of the United States of America (PNAS) |
2 | Global Ecology and Biogeography | Ecology |
3 | PLoS ONE | Science |
4 | Frontiers in Microbiology | Nature |
5 | Ecography | Ecology Letters |
6 | Ecology | PLoS ONE |
7 | PNAS | Journal of Biogeography |
8 | Diversity and Distributions | ISME Journal |
9 | Ecology and Evolution | Applied and Environmental Microbiology |
10 | Scientific Reports | Trends in Ecology and Evolution |
表1 功能生物地理学研究领域发文量和被引次数最多的前10个期刊名称
Table 1 Top ten most relevant and frequently-cited journals in the field of functional biogeography
排序 Order | 发表期刊 Journals for publications | 引用期刊 Journals for cited publications |
---|---|---|
1 | Journal of Biogeography | Proceedings of the National Academy of Sciences of the United States of America (PNAS) |
2 | Global Ecology and Biogeography | Ecology |
3 | PLoS ONE | Science |
4 | Frontiers in Microbiology | Nature |
5 | Ecography | Ecology Letters |
6 | Ecology | PLoS ONE |
7 | PNAS | Journal of Biogeography |
8 | Diversity and Distributions | ISME Journal |
9 | Ecology and Evolution | Applied and Environmental Microbiology |
10 | Scientific Reports | Trends in Ecology and Evolution |
[1] | Ackerly DD (2003). Community assembly, niche conservatism, and adaptive evolution in changing environments. International Journal of Plant Sciences, 164, S165-S184. |
[2] |
Ackerly DD, Knight CA, Weiss SB, Barton K, Starmer KP (2002). Leaf size, specific leaf area and microhabitat distribution of chaparral woody plants: contrasting patterns in species level and community level analyses. Oecologia, 130, 449-457.
DOI PMID |
[3] |
Adler PB, Salguero-Gómez R, Compagnoni A, Hsu JS, Ray-Mukherjee J, Mbeau-Ache C, Franco M (2014). Functional traits explain variation in plant life history strategies. Proceedings of the National Academy of Sciences of the United States of America, 111, 740-745.
DOI PMID |
[4] |
Albert CH, Grassein F, Schurr FM, Vieilledent G, Violle C (2011). When and how should intraspecific variability be considered in trait-based plant ecology? Perspectives in Plant Ecology, Evolution and Systematics, 13, 217-225.
DOI URL |
[5] |
Ameztegui A, Paquette A, Shipley B, Heym M, Messier C, Gravel D (2017). Shade tolerance and the functional trait: demography relationship in temperate and boreal forests. Functional Ecology, 31, 821-830.
DOI URL |
[6] |
Aria M, Cuccurullo C (2017). Bibliometrix: an R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11, 959-975.
DOI URL |
[7] |
Arnan X, Cerdá X, Retana J (2017). Relationships among taxonomic, functional, and phylogenetic ant diversity across the biogeographic regions of Europe. Ecography, 40, 448-457.
DOI URL |
[8] | Asner GP, Knapp DE, Anderson CB, Martin RE, Vaughn N (2016). Large-scale climatic and geophysical controls on the leaf economics spectrum. Proceedings of the National Academy of Sciences of the United States of America, 113, E4043-E4051. |
[9] |
Baraloto C, Timothy Paine CE, Poorter L, Beauchene J, Bonal D, Domenach AM, Hérault B, Patiño S, Roggy JC, Chave J (2010). Decoupled leaf and stem economics in rain forest trees. Ecology Letters, 13, 1338-1347.
DOI PMID |
[10] |
Bergmann J, Weigelt A, van der Plas F, Laughlin DC, Kuyper TW, Guerrero-Ramirez NR, Valverde-Barrantes OJ, Bruelheide H, Freschet GT, Iversen CM, Kattge J, McCormack ML, Meier IC, Rillig MC, Roumet C, et al. (2020). The fungal collaboration gradient dominates the root economics space in plants. Science Advances, 6, eaba3756. DOI: 10.1126/sciadv.aba3756.
DOI |
[11] |
Blomberg SP, Garland T, Ives AR (2003). Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution, 57, 717-745.
DOI PMID |
[12] |
Blonder B, Violle C, Enquist BJ (2013). Assessing the causes and scales of the leaf economics spectrum using venation networks in Populus tremuloides. Journal of Ecology, 101, 981-989.
DOI URL |
[13] |
Borgy B, Violle C, Choler P, Garnier E, Kattge J, Loranger J, Amiaud B, Cellier P, Debarros G, Denelle P, Diquélou S, Gachet S, Jolivet C, Lavorel S, Lemauviel-Lavenant S, et al. (2017). Sensitivity of community-level trait-environment relationships to data representativeness: a test for functional biogeography. Global Ecology and Biogeography, 26, 729-739.
DOI URL |
[14] |
Bourgeois B, Munoz F, Gaba S, Denelle P, Fried G, Storkey J, Violle C (2021). Functional biogeography of weeds reveals how anthropogenic management blurs trait-climate relationships. Journal of Vegetation Science, 32, e12999. DOI: 10.1111/jvs.12999.
DOI |
[15] |
Braga J ter Braak CJF, Thuiller W, Dray S (2018). Integrating spatial and phylogenetic information in the fourth-corner analysis to test trait-environment relationships. Ecology, 99, 2667-2674.
DOI PMID |
[16] |
Brooks TM, Mittermeier RA, da Fonseca GAB, Gerlach J, Hoffmann M, Lamoreux JF, Mittermeier CG, Pilgrim JD, Rodrigues ASL (2006). Global biodiversity conservation priorities. Science, 313, 58-61.
DOI PMID |
[17] |
Brown AM, Warton DI, Andrew NR, Binns M, Cassis G, Gibb H (2014). The fourth-corner solution—Using predictive models to understand how species traits interact with the environment. Methods in Ecology and Evolution, 5, 344-352.
DOI URL |
[18] | Bruelheide H, Dengler J, Purschke O, Lenoir J, Jiménez-Alfaro B, Hennekens SM, Botta-Dukát Z, Chytrý M, Field R, Jansen F, Kattge J, Pillar VD, Schrodt F, Mahecha MD, Peet RK, et al. (2018). Global trait—Environment relationships of plant communities. Nature Ecology & Evolution, 2, 1906-1917. |
[19] | Bruggeman J, Heringa J, Brandt BW (2009). PhyloPars: estimation of missing parameter values using phylogeny. Nucleic Acids Research, 37, W179-W184. |
[20] |
Brum FT, Graham CH, Costa GC, Hedges SB, Penone C, Radeloff VC, Rondinini C, Loyola R, Davidson AD (2017). Global priorities for conservation across multiple dimensions of mammalian diversity. Proceedings of the National Academy of Sciences of the United States of America, 114, 7641-7646.
DOI PMID |
[21] | Butler EE, Datta A, Flores-Moreno H, Chen M, Wythers KR, Fazayeli F, Banerjee A, Atkin OK, Kattge J, Amiaud B, Blonder B, Boenisch G, Bond-Lamberty B, Brown KA, Byun C, et al. (2017). Mapping local and global variability in plant trait distributions. Proceedings of the National Academy of Sciences of the United States of America, 114, E10937-E10946. |
[22] |
Cadotte MW, Carscadden K, Mirotchnick N (2011). Beyond species: functional diversity and the maintenance of ecological processes and services. Journal of Applied Ecology, 48, 1079-1087.
DOI URL |
[23] |
Cadotte MW, Cavender-Bares J, Tilman D, Oakley TH (2009). Using phylogenetic, functional and trait diversity to understand patterns of plant community productivity. PLoS ONE, 4, e5695. DOI: 10.1371/journal.pone.0005695.
DOI |
[24] |
Carmona CP, de Bello F, Mason NWH, Lepš J (2019). Trait probability density (TPD): measuring functional diversity across scales based on TPD with R. Ecology, 100, e02876. DOI: 10.1002/ecy.2876.
DOI |
[25] |
Carmona CP, Tamme R, Pärtel M, de Bello F, Brosse S, Capdevila P, González-M R, González-Suárez M, Salguero-Gómez R, Vásquez-Valderrama M, Toussaint A (2021). Erosion of global functional diversity across the tree of life. Science Advances, 7, eabf2675. DOI: 10.1126/sciadv.abf2675.
DOI |
[26] |
Cernansky R (2017). Biodiversity moves beyond counting species. Nature, 546, 22-24.
DOI URL |
[27] |
Chamberlain SA, Hovick SM, Dibble CJ, Rasmussen NL, van Allen BG, Maitner BS, Ahern JR, Bell-Dereske LP, Roy CL, Meza-Lopez M, Carrillo J, Siemann E, Lajeunesse MJ, Whitney KD (2012). Does phylogeny matter? Assessing the impact of phylogenetic information in ecological meta-analysis. Ecology Letters, 15, 627-636.
DOI PMID |
[28] | Chapin III FS, Autumn K, Pugnaire F (1993). Evolution of suites of traits in response to environmental stress. The American Naturalist, 142, S78-S92. |
[29] |
Chardon NI, Pironon S, Peterson ML, Doak DF (2020). Incorporating intraspecific variation into species distribution models improves distribution predictions, but cannot predict species traits for a wide-spread plant species. Ecography, 43, 60-74.
DOI URL |
[30] |
Chave J, Coomes D, Jansen S, Lewis SL, Swenson NG, Zanne AE (2009). Towards a worldwide wood economics spectrum. Ecology Letters, 12, 351-366.
DOI PMID |
[31] |
Chen SC, Cornwell WK, Zhang HX, Moles AT (2017). Plants show more flesh in the tropics: variation in fruit type along latitudinal and climatic gradients. Ecography, 40, 531-538.
DOI URL |
[32] | Chen XY, Zhang ST, Niu KC (2022). Scaling-up trait covariation: coordination and trade-offs within and among plant species in alpine meadow communities. Chinese Science Bulletin, 67, 986-996. |
[陈馨悦, 张世挺, 牛克昌 (2022). 性状关联跨尺度推演: 高寒草甸植物种内及种间性状的协同与权衡. 科学通报, 67, 986-996.] | |
[33] |
Conradi T, Van Meerbeek K, Ordonez A, Svenning JC (2020). Biogeographic historical legacies in the net primary productivity of Northern Hemisphere forests. Ecology Letters, 23, 800-810.
DOI PMID |
[34] |
Cornwell WK, Pearse WD, Dalrymple RL, Zanne AE (2019). What we (don’t) know about global plant diversity. Ecography, 42, 1819-1831.
DOI |
[35] | Craven D, Eisenhauer N, Pearse WD, Hautier Y, Isbell F, Roscher C, Bahn M, Beierkuhnlein C, Bönisch G, Buchmann N, Byun C, Catford JA, Cerabolini BEL, Cornelissen JHC, Craine JM, et al. (2018). Multiple facets of biodiversity drive the diversity-stability relationship. Nature Ecology & Evolution, 2, 1579-1587. |
[36] |
DeMalach N, Ron R, Kadmon R (2019). Mechanisms of seed mass variation along resource gradients. Ecology Letters, 22, 181-189.
DOI PMID |
[37] |
Deng MF, Liu WX, Li P, Jiang L, Li SP, Jia Z, Yang S, Guo LL, Wang ZH, Liu LL (2021). Intraspecific trait variation drives grassland species richness and productivity under changing precipitation. Ecosphere, 12, e03707. DOI: 10.1002/ecs2.3707.
DOI |
[38] |
Devictor V, Mouillot D, Meynard C, Jiguet F, Thuiller W, Mouquet N (2010). Spatial mismatch and congruence between taxonomic, phylogenetic and functional diversity: the need for integrative conservation strategies in a changing world. Ecology Letters, 13, 1030-1040.
DOI PMID |
[39] |
Díaz S, Kattge J, Cornelissen JHC, Wright IJ, Lavorel S, Dray S, Reu B, Kleyer M, Wirth C, Prentice IC, Garnier E, Böenisch G, Westoby M, Poorter H, Reich PB, et al. (2016). The global spectrum of plant form and function. Nature, 529, 167-173.
DOI |
[40] |
Díaz S, Lavorel S, de Bello F, Quétier F, Grigulis K, Robson TM (2007). Incorporating plant functional diversity effects in ecosystem service assessments. Proceedings of the National Academy of Sciences of the United States of America, 104, 20684-20689.
DOI PMID |
[41] |
Dong N, Prentice IC, Wright IJ, Evans BJ, Togashi HF, Caddy-Retalic S, McInerney FA, Sparrow B, Leitch E, Lowe AJ (2020). Components of leaf-trait variation along environmental gradients. New Phytologist, 228, 82-94.
DOI URL |
[42] |
Donovan LA, Maherali H, Caruso CM, Huber H, de Kroon H (2011). The evolution of the worldwide leaf economics spectrum. Trends in Ecology & Evolution, 26, 88-95.
DOI URL |
[43] |
Dray S, Legendre P (2008). Testing the species traits-environment relationships: the fourth-corner problem revisited. Ecology, 89, 3400-3412.
PMID |
[44] |
Du YJ, Mao LF, Queenborough SA, Primack R, Comita LS, Hampe A, Ma KP (2020). Macro-scale variation and environmental predictors of flowering and fruiting phenology in the Chinese angiosperm flora. Journal of Biogeography, 47, 2303-2314.
DOI URL |
[45] |
Durán SM, Martin RE, Díaz S, Maitner BS, Malhi Y, Salinas E, Shenkin A, Silman MR, Wieczynski DJ, Asner GP, Bentley LP, Savage VM, Enquist BJ (2019). Informing trait-based ecology by assessing remotely sensed functional diversity across a broad tropical temperature gradient. Science Advances, 5, eaaw8114. DOI: 8110.1126/sciadv.aaw8114.
DOI |
[46] |
Echeverría-Londoño S, Enquist BJ, Neves DM, Violle C, Boyle B, Kraft NJB, Maitner BS, McGill B, Peet RK, Sandel B, Smith SA, Svenning JC, Wiser SK, Kerkhoff AJ (2018). Plant functional diversity and the biogeography of biomes in north and south America. Frontiers in Ecology and Evolution, 6, 219. DOI: 10.3389/fevo.2018.00219.
DOI |
[47] |
Enquist BJ, Condit R, Peet RK, Schildhauer M, Thiers BM (2016). Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. PeerJ Preprints, 4, e2615v2612. DOI: 10.7287/peerj.preprints.2615v2.
DOI |
[48] |
Enquist BJ, Kerkhoff AJ, Stark SC, Swenson NG, McCarthy MC, Price CA (2007). A general integrative model for scaling plant growth, carbon flux, and functional trait spectra. Nature, 449, 218-222.
DOI |
[49] | Enquist BJ, West GB, Brown JH (2009). Extensions and evaluations of a general quantitative theory of forest structure and dynamics. Proceedings of the National Academy of Sciences of the United States of America, 106, 7046-7051. |
[50] | Enquist BJ, West GB, Charnov EL, Brown JH (1999). Allometric scaling of production and life-history variation in vascular plants. Nature, 401, 907-911. |
[51] |
Eriksson O, Friis EM, Löfgren P (2000). Seed size, fruit size, and dispersal systems in angiosperms from the Early Cretaceous to the late tertiary. American Naturalist, 156, 47-58.
DOI URL |
[52] |
Faith DP (1992). Conservation evaluation and phylogenetic diversity. Biological Conservation, 61, 1-10.
DOI URL |
[53] |
Falster DS, Westoby M (2003). Plant height and evolutionary games. Trends in Ecology & Evolution, 18, 337-343.
DOI URL |
[54] |
Feng X, Liang Y, Gallardo B, Papeş M (2020). Physiology in ecological niche modeling: using zebra mussel’s upper thermal tolerance to refine model predictions through Bayesian analysis. Ecography, 43, 270-282.
DOI URL |
[55] |
Feng X, Papeş M (2017). Physiological limits in an ecological niche modeling framework: a case study of water temperature and salinity constraints of freshwater bivalves invasive in USA. Ecological Modelling, 346, 48-57.
DOI URL |
[56] |
Finegan B, Peña-Claros M, de Oliveira A, Ascarrunz N, Bret-Harte MS, Carreño-Rocabado G, Casanoves F, Díaz S, Eguiguren Velepucha P, Fernandez F, Licona JC, Lorenzo L, Salgado Negret B, Vaz M, Poorter L (2015). Does functional trait diversity predict above-ground biomass and productivity of tropical forests? Testing three alternative hypotheses. Journal of Ecology, 103, 191-201.
DOI URL |
[57] |
Flynn DFB, Mirotchnick N, Jain M, Palmer MI, Naeem S (2011). Functional and phylogenetic diversity as predictors of biodiversity—Ecosystem-function relationships. Ecology, 92, 1573-1581.
DOI PMID |
[58] |
Folk RA, Siniscalchi CM (2021). Biodiversity at the global scale: the synthesis continues. American Journal of Botany, 108, 912-924.
DOI URL |
[59] |
Fontana S, Rasmann S, de Bello F, Pomati F, Moretti M (2021). Reconciling trait based perspectives along a trait-integration continuum. Ecology, 102, e03472. DOI: 10.1002/ecy.3472.
DOI |
[60] |
Freckleton RP, Harvey PH, Pagel M (2002). Phylogenetic analysis and comparative data: a test and review of evidence. The American Naturalist, 160, 712-726.
DOI PMID |
[61] |
Freschet GT, Cornelissen JHC, Aerts R (2010). Evidence of the “plant economics spectrum” in a subarctic flora. Journal of Ecology, 98, 362-373.
DOI URL |
[62] |
Freschet GT, Valverde-Barrantes OJ, Tucker CM, Craine JM, McCormack ML, Violle C, Fort F, Blackwood CB, Urban-Mead KR, Iversen CM, Bonis A, Comas LH, Cornelissen JHC, Dong M, Guo DL, et al. (2017). Climate, soil and plant functional types as drivers of global fine-root trait variation. Journal of Ecology, 105, 1182-1196.
DOI URL |
[63] |
Funk JL, Larson JE, Ames GM, Butterfield BJ, Cavender-Bares J, Firn J, Laughlin DC, Sutton-Grier AE, Williams L, Wright J (2017). Revisiting the Holy Grail: using plant functional traits to understand ecological processes. Biological Reviews, 92, 1156-1173.
DOI URL |
[64] | Gallagher RV, Falster DS, Maitner BS, Salguero-Gómez R, Vandvik V, Pearse WD, Schneider FD, Kattge J, Poelen JH, Madin JS, Ankenbrand MJ, Penone C, Feng X, Adams VM, Alroy J, et al. (2020). Open Science principles for accelerating trait-based science across the Tree of Life. Nature Ecology & Evolution, 4, 294-303. |
[65] |
Gao DX, Wang S, Wei FL, Wu XT, Zhou S, Wang LX, Li ZD, Chen P, Fu BJ (2022). The vulnerability of ecosystem structure in the semi-arid area revealed by the functional trait networks. Ecological Indicators, 139, 108894. DOI: 10.1016/j.ecolind.2022.108894.
DOI |
[66] |
Garnier E, Cortez J, Billès G, Navas ML, Roumet C, Debussche M, Laurent G, Blanchard A, Aubry D, Bellmann A, Neill C, Toussaint JP (2004). Plant functional markers capture ecosystem properties during secondary succession. Ecology, 85, 2630-2637.
DOI URL |
[67] |
Geng Y, Ma WH, Wang L, Baumann F, Kühn P, Scholten T, He JS (2017). Linking above- and belowground traits to soil and climate variables: an integrated database on China’s grassland species. Ecology, 98, 1471. DOI: 10.1002/ecy.1780.
DOI |
[68] | Givnish TJ (1978). Ecological aspects of plant morphology: leaf form in relation to environment. Acta Biotheoretica, 27, 83-142. |
[69] | Gleason SM, Barnard DM, Green TR, MacKay S, Wang DR, Ainsworth EA, Altenhofen J, Brodribb TJ, Cochard H, Comas LH, Cooper M, Creek D, DeJonge KC, Delzon S, Fritschi FB, et al. (2022). Physiological trait networks enhance understanding of crop growth and water use in contrasting environments. Plant, Cell & Environment, 45, 2554-2572. |
[70] |
Green SJ, Brookson CB, Hardy NA, Crowder LB (2022). Trait-based approaches to global change ecology: moving from description to prediction. Proceedings of the Royal Society B: Biological Sciences, 289, 20220071. DOI: 10.1098/rspb.2022.0071.
DOI |
[71] |
Greenwood S, Ruiz-Benito P, Martínez-Vilalta J, Lloret F, Kitzberger T, Allen CD, Fensham R, Laughlin DC, Kattge J, Bönisch G, Kraft NJB, Jump AS (2017). Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area. Ecology Letters, 20, 539-553.
DOI PMID |
[72] |
Griffin-Nolan RJ, Blumenthal DM, Collins SL, Farkas TE, Hoffman AM, Mueller KE, Ocheltree TW, Smith MD, Whitney KD, Knapp AK (2019). Shifts in plant functional composition following long-term drought in grasslands. Journal of Ecology, 107, 2133-2148.
DOI |
[73] |
Griffith DM, Osborne CP, Edwards EJ, Bachle S, Beerling DJ, Bond WJ, Gallaher TJ, Helliker BR, Lehmann CER, Leatherman L, Nippert JB, Pau S, Qiu F, Riley WJ, Smith MD, et al. (2020). Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models. New Phytologist, 228, 15-23.
DOI PMID |
[74] |
Grime JP, Hunt R (1975). Relative growth-rate: its range and adaptive significance in a local flora. Journal of Ecology, 63, 393-422.
DOI URL |
[75] | Guerrero-Ramírez NR, Mommer L, Freschet GT, Iversen CM, McCormack ML, Kattge J, Poorter H, van der Plas F, Bergmann J, Kuyper TW, York LM, Bruelheide H, Laughlin DC, Meier IC, Roumet C, et al. (2021). Global root traits (GRooT) database. Global Ecology and Biogeography, 30, 25-37. |
[76] |
Han WX, Fang JY, Guo DL, Zhang Y (2005). Leaf nitrogen and phosphorus stoichiometry across 753 terrestrial plant species in China. New Phytologist, 168, 377-385.
DOI PMID |
[77] |
He LL, Liu Y, He H, Liu Y, Qi JF, Zhang XJ, Li YH, Mao YW, Zhou SL, Zheng XL, Bai QZ, Zhao BL, Wang DF, Wen JQ, Mysore KS, et al. (2020). A molecular framework underlying the compound leaf pattern of Medicago truncatula. Nature Plants, 6, 511-521.
DOI PMID |
[78] |
He NP, Li Y, Liu CC, Xu L, Li MX, Zhang JH, He JS, Tang ZY, Han XG, Ye Q, Xiao CW, Yu Q, Liu SR, Sun W, Niu SL, Li SG, Sack L, Yu GR (2020). Plant trait networks: improved resolution of the dimensionality of adaptation. Trends in Ecology & Evolution, 35, 908-918.
DOI URL |
[79] |
He NP, Liu CC, Piao SL, Sack L, Xu L, Luo YQ, He JS, Han XG, Zhou GS, Zhou XH, Lin Y, Yu Q, Liu SR, Sun W, Niu SL, et al. (2019). Ecosystem traits linking functional traits to macroecology. Trends in Ecology & Evolution, 34, 200-210.
DOI URL |
[80] |
He NP, Liu CC, Tian M, Li ML, Yang H, Yu GR, Guo DL, Smith MD, Yu Q, Hou JH (2018). Variation in leaf anatomical traits from tropical to cold-temperate forests and linkage to ecosystem functions. Functional Ecology, 32, 10-19.
DOI URL |
[81] |
Henn JJ, Buzzard V, Enquist BJ, Halbritter AH, Klanderud K, Maitner BS, Michaletz ST, Pötsch C, Seltzer L, Telford RJ, Yang Y, Zhang L, Vandvik V (2018). Intraspecific trait variation and phenotypic plasticity mediate alpine plant species response to climate change. Frontiers in Plant Science, 9, 1548. DOI: 10.3389/fpls.2018.01548.
DOI |
[82] |
Hobbie SE (2015). Plant species effects on nutrient cycling: revisiting litter feedbacks. Trends in Ecology & Evolution, 30, 357-363.
DOI URL |
[83] |
Houlton BZ, Morford SL, Dahlgren RA (2018). Convergent evidence for widespread rock nitrogen sources in Earth’s surface environment. Science, 360, 58-62.
DOI PMID |
[84] |
Hu YK, Pan X, Liu GF, Li WB, Dai WH, Tang SL, Zhang YL, Xiao T, Chen LY, Xiong W, Zhou MY, Song YB, Dong M (2015). Novel evidence for within-species leaf economics spectrum at multiple spatial scales. Frontiers in Plant Science, 6, 901. DOI: 10.3389/fpls.2015.00901.
DOI |
[85] |
Huang JH, Chen B, Liu CR, Lai JS, Zhang JL, Ma KP (2012). Identifying hotspots of endemic woody seed plant diversity in China. Diversity and Distributions, 18, 673-688.
DOI URL |
[86] | Iversen CM, McCormack ML, Powell AS, Blackwood CB, Freschet GT, Kattge J, Roumet C, Stover DB, Soudzilovskaia NA, Valverde-Barrantes OJ, van Bodegom PM, Violle C (2017). A global Fine-Root Ecology Database to address below-ground challenges in plant ecology. New Phytologist, 215, 15-26. |
[87] |
Iversen LL, Girón JG, Pan YJ (2022). Towards linking freshwater plants and ecosystems via functional biogeography. Aquatic Botany, 176, 103454. DOI: 10.1016/j.aquabot.2021.103454.
DOI |
[88] |
Jacquet C, Mouillot D, Kulbicki M, Gravel D (2017). Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation. Ecology Letters, 20, 135-146.
DOI PMID |
[89] |
Jetz W, Cavender-Bares J, Pavlick R, Schimel D, Davis FW, Asner GP, Guralnick R, Kattge J, Latimer AM, Moorcroft P, Schaepman ME, Schildhauer MP, Schneider FD, Schrodt F, Stahl U, Ustin SL (2016). Monitoring plant functional diversity from space. Nature Plants, 2, 16024. DOI: 10.1038/nplants.2016.24.
DOI |
[90] | Jiang XL, Zhang WG (2010). Functional diversity and its research method. Acta Ecologica Sinica, 30, 2766-2773. |
[江小雷, 张卫国 (2010). 功能多样性及其研究方法. 生态学报, 30, 2766-2773.] | |
[91] |
Kamilar JM, Cooper N (2013). Phylogenetic signal in primate behaviour, ecology and life history. Philosophical Transactions of the Royal Society B: Biological Sciences, 368, 20120341. DOI: 10.1098/rstb.2012.0341.
DOI |
[92] |
Kattge J, Bönisch G, Díaz S, Lavorel S, Prentice IC, Leadley P, Tautenhahn S, Werner GDA, Aakala T, Abedi M, Acosta ATR, Adamidis GC, Adamson K, Aiba M, Albert CH, et al. (2020). TRY plant trait database—Enhanced coverage and open access. Global Change Biology, 26, 119-188.
DOI PMID |
[93] | Kattge J, Díaz S, Lavorel S, Prentice IC, Leadley P, Böenisch G, Garnier E, Westoby M, Reich PB, Wright IJ, Cornelissen JHC, Violle C, Harrison SP, van Bodegom PM, Reichstein M, et al. (2011). TRY—A global database of plant traits. Global Change Biology, 17, 2905-2935. |
[94] |
Kimball S, Funk JL, Spasojevic MJ, Suding KN, Parker S, Goulden ML (2016). Can functional traits predict plant community response to global change? Ecosphere, 7, e01602. DOI: 10.1002/ecs2.1602.
DOI |
[95] |
Klein T, Randin C, Körner C (2015). Water availability predicts forest canopy height at the global scale. Ecology Letters, 18, 1311-1320.
DOI URL |
[96] |
Kommineni VK, Tautenhahn S, Baddam P, Gaikwad J, Wieczorek B, Triki A, Kattge J (2021). Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries. Biodiversity Data Journal, 9, e69806. DOI: 10.3897/BDJ.9.e69806.
DOI |
[97] |
Kong DL, Ma CG, Zhang Q, Li L, Chen XY, Zeng H, Guo DL (2014). Leading dimensions in absorptive root trait variation across 96 subtropical forest species. New Phytologist, 203, 863-872.
DOI PMID |
[98] |
Kong DL, Wang JJ, Wu HF, Valverde-Barrantes OJ, Wang RL, Zeng H, Kardol P, Zhang HY, Feng YL (2019). Nonlinearity of root trait relationships and the root economics spectrum. Nature Communications, 10, 2203. DOI: 10.1038/s41467-019-10245-6.
DOI |
[99] |
Kozlov MV, Lanta V, Zverev V, Zvereva EL (2015). Background losses of woody plant foliage to insects show variable relationships with plant functional traits across the globe. Journal of Ecology, 103, 1519-1528.
DOI URL |
[100] |
Kraft NJB, Metz MR, Condit RS, Chave J (2010). The relationship between wood density and mortality in a global tropical forest data set. New Phytologist, 188, 1124-1136.
DOI PMID |
[101] |
Kunstler G, Falster D, Coomes DA, Hui F, Kooyman RM, Laughlin DC, Poorter L, Vanderwel M, Vieilledent G, Wright SJ, Aiba M, Baraloto C, Caspersen J, Cornelissen JHC, Gourlet-Fleury S, et al. (2016). Plant functional traits have globally consistent effects on competition. Nature, 529, 204-207.
DOI |
[102] |
Laine AM, Lindholm T, Nilsson M, Kutznetsov O, Jassey VEJ, Tuittila ES (2021). Functional diversity and trait composition of vascular plant and Sphagnum moss communities during peatland succession across land uplift regions. Journal of Ecology, 109, 1774-1789.
DOI URL |
[103] |
Larjavaara M, Muller-Landau HC (2010). Rethinking the value of high wood density. Functional Ecology, 24, 701-705.
DOI URL |
[104] | Laureto LMO, Cianciaruso MV, Samia DSM (2015). Functional diversity: an overview of its history and applicability. Natureza & Conservação, 13, 112-116. |
[105] |
Lavorel S, Garnier E (2002). Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Functional Ecology, 16, 545-556.
DOI URL |
[106] | Legendre P, Galzin R, Harmelin-Vivien ML (1997). Relating behavior to habitat: solutions to the fourth-corner problem. Ecology, 78, 547-562. |
[107] |
Li Y, Liu CC, Xu L, Li MX, Zhang JH, He NP (2021). Leaf trait networks based on global data: representing variation and adaptation in plants. Frontiers in Plant Science, 12, 710530. DOI: 10.3389/fpls.2021.710530.
DOI |
[108] |
Li Y, Liu CC, Zhang JH, Yang H, Xu L, Wang QF, Sack L, Wu XQ, Hou JH, He NP (2018). Variation in leaf chlorophyll concentration from tropical to cold-temperate forests: association with gross primary productivity. Ecological Indicators, 85, 383-389.
DOI URL |
[109] |
Li YQ, Reich PB, Schmid B, Shrestha N, Feng X, Lyu T, Maitner BS, Xu XT, Li YC, Zou DT, Tan ZH, Su XY, Tang ZY, Guo QH, Feng XJ, et al. (2020). Leaf size of woody dicots predicts ecosystem primary productivity. Ecology Letters, 23, 1003-1013.
DOI PMID |
[110] |
Li YQ, Wang ZH, Xu XT, Han WX, Wang QG, Zou DT (2016). Leaf margin analysis of Chinese woody plants and the constraints on its application to palaeoclimatic reconstruction. Global Ecology and Biogeography, 25, 1401-1415.
DOI URL |
[111] |
Liu CC, Li Y, He NP (2022). Differential adaptation of lianas and trees in wet and dry forests revealed by trait correlation networks. Ecological Indicators, 135, 108564. DOI: 10.1016/j.ecolind.2022.108564.
DOI |
[112] |
Liu H, Gleason SM, Hao GY, Hua L, He PC, Goldstein G, Ye Q (2019). Hydraulic traits are coordinated with maximum plant height at the global scale. Science Advances, 5, eaav1332. DOI: 0.1126/sciadv.aav1332.
DOI |
[113] |
Lyu T, Wang Yy, Luo A, Li YQ, Peng SJ, Cai HY, Zeng H, Wang ZH (2021). Effects of climate, plant height, and evolutionary age on geographical patterns of fruit type. Frontiers in Plant Science, 12, 604272. DOI: 10.3389/fpls.2021.604272.
DOI |
[114] |
Ma SH, He F, Tian D, Zou DT, Yan ZB, Yang YL, Zhou TC, Huang KY, Shen HH, Fang JY (2018a). Variations and determinants of carbon content in plants: a global synthesis. Biogeosciences, 15, 693-702.
DOI URL |
[115] |
Ma XL, Mahecha MD, Migliavacca M, van der Plas F, Benavides R, Ratcliffe S, Kattge J, Richter R, Musavi T, Baeten L, Barnoaiea I, Bohn FJ, Bouriaud O, Bussotti F, Coppi A, et al. (2019). Inferring plant functional diversity from space: the potential of Sentinel-2. Remote Sensing of Environment, 233, 111368. DOI: 10.1016/j.rse.2019.111368.
DOI |
[116] |
Ma ZQ, Guo DL, Xu XL, Lu MZ, Bardgett RD, Eissenstat DM, McCormack ML, Hedin LO (2018b). Evolutionary history resolves global organization of root functional traits. Nature, 555, 94-97.
DOI URL |
[117] | Maitner BS, Boyle B, Casler N, Condit R, Donoghue II J, Durán SM, Guaderrama D, Hinchliff CE, Jørgensen PM, Kraft NJB, McGill B, Merow C, Morueta-Holme N, Peet RK, et al. (2018). The Bien R package: a tool to access the Botanical Information and Ecology Network (BIEN) database. Methods in Ecology and Evolution, 9, 373-379. |
[118] |
Marjakangas EL, Muñoz G, Turney S, Albrecht J, Neuschulz EL, Schleuning M, Lessard JP (2022). Trait-based inference of ecological network assembly: a conceptual framework and methodological toolbox. Ecological Monographs, 92, e1502. DOI: 10.1002/ecm.1502.
DOI |
[119] |
Markesteijn L, Poorter L, Bongers F, Paz H, Sack L (2011). Hydraulics and life history of tropical dry forest tree species: coordination of species’ drought and shade tolerance. New Phytologist, 191, 480-495.
DOI PMID |
[120] |
Mason CM, Goolsby EW, Humphreys DP, Donovan LA (2016). Phylogenetic structural equation modelling reveals no need for an “origin” of the leaf economics spectrum. Ecology Letters, 19, 54-61.
DOI URL |
[121] |
Mason NWH, Mouillot D, Lee WG, Wilson JB (2005). Functional richness, functional evenness and functional divergence: the primary components of functional diversity. Oikos, 111, 112-118.
DOI URL |
[122] |
Maynard DS, Bialic-Murphy L, Zohner CM, Averill C, van den Hoogen J, Ma HZ, Mo LD, Smith GR, Acosta ATR, Aubin I, Berenguer E, Boonman CCF, Catford JA, Cerabolini BEL, Dias AS, et al. (2022). Global relationships in tree functional traits. Nature Communications, 13, 3185. DOI: 10.1038/s41467-022-30888-2.
DOI |
[123] |
Mazel F, Pennell MW, Cadotte MW, Díaz S, Dalla Riva GV, Grenyer R, Leprieur F, Mooers AO, Mouillot D, Tucker CM, Pearse WD (2018). Prioritizing phylogenetic diversity captures functional diversity unreliably. Nature Communications, 9, 2888. DOI: 10.1038/s41467-018-05126-3.
DOI |
[124] |
Messier J, Lechowicz MJ, McGill BJ, Violle C, Enquist BJ (2017a). Interspecific integration of trait dimensions at local scales: the plant phenotype as an integrated network. Journal of Ecology, 105, 1775-1790.
DOI URL |
[125] |
Messier J, McGill BJ, Enquist BJ, Lechowicz MJ (2017b). Trait variation and integration across scales: Is the leaf economic spectrum present at local scales? Ecography, 40, 685-697.
DOI URL |
[126] |
Messier J, McGill BJ, Lechowicz MJ (2010). How do traits vary across ecological scales? A case for trait-based ecology. Ecology Letters, 13, 838-848.
DOI PMID |
[127] |
Michaletz ST, Cheng DL, Kerkhoff AJ, Enquist BJ (2014). Convergence of terrestrial plant production across global climate gradients. Nature, 512, 39-43.
DOI |
[128] |
Michaletz ST, Kerkhoff AJ, Enquist BJ (2018). Drivers of terrestrial plant production across broad geographical gradients. Global Ecology and Biogeography, 27, 166-174.
DOI URL |
[129] |
Michaletz ST, Weiser MD, McDowell NG, Zhou JZ, Kaspari M, Helliker BR, Enquist BJ (2016). The energetic and carbon economic origins of leaf thermoregulation. Nature Plants, 2, 16129. DOI: 10.1038/nplants.2016.129.
DOI |
[130] |
Moles AT, Ackerly DD, Tweddle JC, Dickie JB, Smith R, Leishman MR, Mayfield MM, Pitman A, Wood JT, Westoby M (2007). Global patterns in seed size. Global Ecology and Biogeography, 16, 109-116.
DOI URL |
[131] |
Moles AT, Ackerly DD, Webb CO, Tweddle JC, Dickie JB, Pitman AJ, Westoby M (2005). Factors that shape seed mass evolution. Proceedings of the National Academy of Sciences of the United States of America, 102, 10540-10544.
PMID |
[132] |
Moles AT, Wallis IR, Foley WJ, Warton DI, Stegen JC, Bisigato AJ, Cella-Pizarro L, Clark CJ, Cohen PS, Cornwell WK, Edwards W, Ejrnaes R, Gonzales-Ojeda T, Graae BJ, Hay G, et al. (2011). Putting plant resistance traits on the map: a test of the idea that plants are better defended at lower latitudes. New Phytologist, 191, 777-788.
DOI PMID |
[133] |
Moles AT, Warton DI, Warman L, Swenson NG, Laffan SW, Zanne AE, Pitman A, Hemmings FA, Leishman MR (2009). Global patterns in plant height. Journal of Ecology, 97, 923-932.
DOI URL |
[134] |
Molina-Venegas R, Moreno-Saiz JC, Castro Parga I, Davies TJ, Peres-Neto PR, Rodríguez MÁ (2018). Assessing among-lineage variability in phylogenetic imputation of functional trait datasets. Ecography, 41, 1740-1749.
DOI URL |
[135] |
Molina-Venegas R, Rodríguez MÁ (2017). Revisiting phylogenetic signal; strong or negligible impacts of polytomies and branch length information? BMC Evolutionary Biology, 17, 53. DOI: 10.1186/s12862-017-0898-y.
DOI |
[136] |
Moreno-Martínez Á, Camps-Valls G, Kattge J, Robinson N, Reichstein M, van Bodegom P, Kramer K, Cornelissen JHC, Reich P, Bahn M, Niinemets Ü, Peñuelas J, Craine JM, Cerabolini BEL, Minden V, et al. (2018). A methodology to derive global maps of leaf traits using remote sensing and climate data. Remote Sensing of Environment, 218, 69-88.
DOI URL |
[137] |
Mouchet MA, Villéger S, Mason NWH, Mouillot D (2010). Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules. Functional Ecology, 24, 867-876.
DOI URL |
[138] |
Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000). Biodiversity hotspots for conservation priorities. Nature, 403, 853-858.
DOI |
[139] |
Nathan J, Osem Y, Shachak M, Meron E (2016). Linking functional diversity to resource availability and disturbance: a mechanistic approach for water-limited plant communities. Journal of Ecology, 104, 419-429.
DOI URL |
[140] |
O’Brien MJ, Engelbrecht BMJ, Joswig J, Pereyra G, Schuldt B, Jansen S, Kattge J, Landhäusser SM, Levick SR, Preisler Y, Väänänen P, Macinnis-Ng C (2017). A synthesis of tree functional traits related to drought-induced mortality in forests across climatic zones. Journal of Applied Ecology, 54, 1669-1686.
DOI URL |
[141] |
Olson ME, Soriano D, Rosell JA, Anfodillo T, Donoghue MJ, Edwards EJ, León-Gómez C, Dawson T, Camarero Martínez JJ, Castorena M, Echeverría A, Espinosa CI, Fajardo A, Gazol A, Isnard S, et al. (2018). Plant height and hydraulic vulnerability to drought and cold. Proceedings of the National Academy of Sciences of the United States of America, 115, 7551-7556.
DOI PMID |
[142] |
Ottaviani G, Keppel G, Götzenberger L, Harrison S, Opedal ØH, Conti L, Liancourt P, Klimešová J, Silveira FAO, Jiménez-Alfaro B, Negoita L, Doležal J, Hájek M, Ibanez T, Méndez-Castro FE, Chytrý M (2020). Linking plant functional ecology to island biogeography. Trends in Plant Science, 25, 329-339.
DOI PMID |
[143] |
Padulles Cubino J, Biurrun I, Bonari G, Braslavskaya T, Font X, Jandt U, Jansen F, Rašomavičius V, Škvorc Z, Willner W, Chytrý M (2021). The leaf economic and plant size spectra of European forest understory vegetation. Ecography, 44, 1311-1324.
DOI URL |
[144] |
Pavlick R, Drewry DT, Bohn K, Reu B, Kleidon A (2013). The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs. Biogeosciences, 10, 4137-4177.
DOI URL |
[145] |
Penone C, Davidson AD, Shoemaker KT, di Marco M, Rondinini C, Brooks TM, Young BE, Graham CH, Costa GC (2014). Imputation of missing data in life-history trait datasets: Which approach performs the best? Methods in Ecology and Evolution, 5, 961-970.
DOI URL |
[146] |
Peppe DJ, Lemons CR, Royer DL, Wing SL, Wright IJ, Lusk CH, Rhoden CH (2014). Biomechanical and leaf-climate relationships: a comparison of ferns and seed plants. American Journal of Botany, 101, 338-347.
DOI PMID |
[147] |
Peppe DJ, Royer DL, Cariglino B, Oliver SY, Newman S, Leight E, Enikolopov G, Fernandez-Burgos M, Herrera F, Adams JM, Correa E, Currano ED, Erickson JM, Hinojosa LF, Hoganson JW, et al. (2011). Sensitivity of leaf size and shape to climate: global patterns and paleoclimatic applications. New Phytologist, 190, 724-739.
DOI PMID |
[148] |
Peres-Neto PR, Dray S, ter Braak CJF (2017). Linking trait variation to the environment: critical issues with community-weighted mean correlation resolved by the fourth-corner approach. Ecography, 40, 806-816.
DOI URL |
[149] |
Petchey OL, Gaston KJ (2006). Functional diversity: back to basics and looking forward. Ecology Letters, 9, 741-758.
DOI PMID |
[150] |
Peterson ML, Doak DF, Morris WF (2019). Incorporating local adaptation into forecasts of species’ distribution and abundance under climate change. Global Change Biology, 25, 775-793.
DOI PMID |
[151] | Poorter H (1989). Interspecific variation in relative growth rate: on ecological causes and physiological consequences// Lambers H, Cambridge ML, Konings H, Pons TL. Causes and Consequences of Variation in Growth Rate and Productivity of Higher Plants. SPB Academic Publishing, the Hague, the Netherlands. 45-68. |
[152] |
Poorter L, van der Sande MT, Arets EJMM, Ascarrunz N, Enquist BJ, Finegan B, Licona JC, Martínez-Ramos M, Mazzei L, Meave JA, Muñoz R, Nytch CJ, de Oliveira AA, Pérez-García EA, Prado-Junior J, et al. (2017). Biodiversity and climate determine the functioning of Neotropical forests. Global Ecology and Biogeography, 26, 1423-1434.
DOI URL |
[153] | Poyatos R, Sus O, Badiella L, Mencuccini M, Martínez-Vilalta J (2018). Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information. Biogeosciences, 15, 2601-2617. |
[154] | Rapacciuolo G, Graham CH, Marin J, Behm JE, Costa GC, Hedges SB, Helmus MR, Radeloff VC, Young BE, Brooks TM (2019). Species diversity as a surrogate for conservation of phylogenetic and functional diversity in terrestrial vertebrates across the Americas. Nature Ecology & Evolution, 3, 53-61. |
[155] |
Regos A, Gagne L, Alcaraz-Segura D, Honrado JP, Domínguez J (2019). Effects of species traits and environmental predictors on performance and transferability of ecological niche models. Scientific Reports, 9, 4221. DOI: 10.1038/s41598-019-40766-5.
DOI |
[156] |
Reich PB (2012). Key canopy traits drive forest productivity. Proceedings of the Royal Society B: Biological Sciences, 279, 2128-2134.
DOI URL |
[157] |
Reich PB (2014). The world-wide “fast-slow” plant economics spectrum: a traits manifesto. Journal of Ecology, 102, 275-301.
DOI URL |
[158] |
Reich PB, Oleksyn J (2004). Global patterns of plant leaf N and P in relation to temperature and latitude. Proceedings of the National Academy of Sciences of the United States of America, 101, 11001-11006.
DOI PMID |
[159] |
Reich PB, Walters MB, Ellsworth DS (1997). From tropics to tundra: global convergence in plant functioning. Proceedings of the National Academy of Sciences of the United States of America, 94, 13730-13734.
PMID |
[160] |
Reichstein M, Bahn M, Mahecha MD, Kattge J, Baldocchi DD (2014). Linking plant and ecosystem functional biogeography. Proceedings of the National Academy of Sciences of the United States of America, 111, 13697-13702.
DOI PMID |
[161] |
Roddy AB, Martínez-Perez C, Teixido AL, Cornelissen TG, Olson ME, Oliveira RS, Silveira FAO (2021). Towards the flower economics spectrum. New Phytologist, 229, 665-672.
DOI URL |
[162] |
Roscher C, Schumacher J, Gubsch M, Lipowsky A, Weigelt A, Buchmann N, Schmid B, Schulze ED (2012). Using plant functional traits to explain diversity-productivity relationships. PLoS ONE, 7, e36760. DOI: 10.1371/journal.pone.0036760.
DOI |
[163] |
Roumet C, Birouste M, Picon-Cochard C, Ghestem M, Osman N, Vrignon-Brenas S, Cao KF, Stokes A (2016). Root structure-function relationships in 74 species: evidence of a root economics spectrum related to carbon economy. New Phytologist, 210, 815-826.
DOI PMID |
[164] |
Royer DL, Peppe DJ, Wheeler EA, Niinemets Ü (2012). Roles of climate and functional traits in controlling toothed vs. untoothed leaf margins. American Journal of Botany, 99, 915-922.
DOI PMID |
[165] |
Sack L, Scoffoni C, John GP, Poorter H, Mason CM, Mendez-Alonzo R, Donovan LA (2013). How do leaf veins influence the worldwide leaf economic spectrum? Review and synthesis. Journal of Experimental Botany, 64, 4053-4080.
DOI PMID |
[166] |
Sakschewski B, von Bloh W, Boit A, Rammig A, Kattge J, Poorter L, Peñuelas J, Thonicke K (2015). Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model. Global Change Biology, 21, 2711-2725.
DOI PMID |
[167] |
Sarker SK, Reeve R, Matthiopoulos J (2021). Solving the fourth-corner problem: forecasting ecosystem primary production from spatial multispecies trait-based models. Ecological Monographs, 91, e01454. DOI: 10.1002/ecm.1454.
DOI |
[168] |
Scheiter S, Langan L, Higgins SI (2013). Next-generation dynamic global vegetation models: learning from community ecology. New Phytologist, 198, 957-969.
DOI PMID |
[169] |
Schiller C, Schmidtlein S, Boonman C, Moreno-Martínez A, Kattenborn T (2021). Deep learning and citizen science enable automated plant trait predictions from photographs. Scientific Reports, 11, 16395. DOI: 10.1038/s41598-021-95616-0.
DOI |
[170] |
Schmitt S, Maréchaux I, Chave J, Fischer FJ, Piponiot C, Traissac S, Hérault B (2020). Functional diversity improves tropical forest resilience: insights from a long-term virtual experiment. Journal of Ecology, 108, 831-843.
DOI URL |
[171] |
Schneider FD, Morsdorf F, Schmid B, Petchey OL, Hueni A, Schimel DS, Schaepman ME (2017). Mapping functional diversity from remotely sensed morphological and physiological forest traits. Nature Communications, 8, 1441. DOI: 10.1038/s41467-017-01530-3.
DOI |
[172] |
Schrodt F, Kattge J, Shan HH, Fazayeli F, Joswig J, Banerjee A, Reichstein M, Bönisch G, Díaz S, Dickie J, Gillison A, Karpatne A, Lavorel S, Leadley P, Wirth CB, et al. (2015). BHPMF—A hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Global Ecology and Biogeography, 24, 1510-1521.
DOI URL |
[173] |
Shipley B, Lechowicz MJ, Wright I, Reich PB (2006). Fundamental trade-offs generating the worldwide leaf economics spectrum. Ecology, 87, 535-541.
PMID |
[174] |
Siefert A, Violle C, Chalmandrier L, Albert CH, Taudiere A, Fajardo A, Aarssen LW, Baraloto C, Carlucci MB, Cianciaruso MV, de Dantas VL, de Bello F, Duarte LDS, Fonseca CR, Freschet GT, et al. (2015). A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. Ecology Letters, 18, 1406-1419.
DOI PMID |
[175] |
Simard M, Pinto N, Fisher JB, Baccini A (2011). Mapping forest canopy height globally with spaceborne lidar. Journal of Geophysical Research: Biogeosciences, 116, G04021. DOI: 10.1029/2011JG001708.
DOI |
[176] |
Šímová I, Rueda M, Hawkins BA (2017). Stress from cold and drought as drivers of functional trait spectra in North American angiosperm tree assemblages. Ecology and Evolution, 7, 7548-7559.
DOI PMID |
[177] |
Šímová I, Sandel B, Enquist BJ, Michaletz ST, Kattge J, Violle C, McGill BJ, Blonder B, Engemann K, Peet RK, Wiser SK, Morueta-Holme N, Boyle B, Kraft NJB, Svenning JC (2019). The relationship of woody plant size and leaf nutrient content to large-scale productivity for forests across the Americas. Journal of Ecology, 107, 2278-2290.
DOI URL |
[178] |
Šímová I, Violle C, Kraft NJB, Storch D, Svenning JC, Boyle B, Donoghue II JC, Jørgensen P, McGill BJ, Morueta-Holme N, Piel WH, Peet RK, Regetz J, Schildhauer M, Spencer N, et al. (2015). Shifts in trait means and variances in North American tree assemblages: species richness patterns are loosely related to the functional space. Ecography, 38, 649-658.
DOI URL |
[179] |
Šímová I, Violle C, Svenning JC, Kattge J, Engemann K, Sandel B, Peet RK, Wiser SK, Blonder B, McGill BJ, Boyle B, Morueta-Holme N, Kraft NJB, van Bodegom PM, Gutiérrez AG, et al. (2018). Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species. Journal of Biogeography, 45, 895-916.
DOI URL |
[180] |
Sinnott-Armstrong MA, Downie AE, Federman S, Valido A, Jordano P, Donoghue MJ (2018). Global geographic patterns in the colours and sizes of animal-dispersed fruits. Global Ecology and Biogeography, 27, 1339-1351.
DOI URL |
[181] |
Smart SM, Glanville HC, Blanes MDC, Mercado LM, Emmett BA, Jones DL, Cosby BJ, Marrs RH, Butler A, Marshall MR, Reinsch S, Herrero-Jáuregui C, Hodgson JG (2017). Leaf dry matter content is better at predicting above-ground net primary production than specific leaf area. Functional Ecology, 31, 1336-1344.
DOI URL |
[182] |
Soltis PS (2017). Digitization of herbaria enables novel research. American Journal of Botany, 104, 1281-1284.
DOI PMID |
[183] | Soudzilovskaia NA, Vaessen S, Barcelo M, He JH, Rahimlou S, Abarenkov K, Brundrett MC, Gomes SIF, Merckx V, Tedersoo L (2020). FungalRoot: global online database of plant mycorrhizal associations. New Phytologist, 227, 955-966. |
[184] |
Stahl U, Kattge J, Reu B, Voigt W, Ogle K, Dickie J, Wirth C (2013). Whole-plant trait spectra of North American woody plant species reflect fundamental ecological strategies. Ecosphere, 4, 128. DOI: 10.1890/ES13-00143.1.
DOI |
[185] | Stahl U, Reu B, Wirth C (2014). Predicting species’ range limits from functional traits for the tree flora of North America. Proceedings of the National Academy of Sciences of the United States of America, 111, 13739-13744. |
[186] |
Steudel B, Hallmann C, Lorenz M, Abrahamczyk S, Prinz K, Herrfurth C, Feussner I, Martini JWR, Kessler M (2016). Contrasting biodiversity-ecosystem functioning relationships in phylogenetic and functional diversity. New Phytologist, 212, 409-420.
DOI PMID |
[187] |
Swenson NG (2013). The assembly of tropical tree communities—The advances and shortcomings of phylogenetic and functional trait analyses. Ecography, 36, 264-276.
DOI URL |
[188] |
Swenson NG, Enquist BJ (2007). Ecological and evolutionary determinants of a key plant functional trait: wood density and its community-wide variation across latitude and elevation. American Journal of Botany, 94, 451-459.
DOI PMID |
[189] |
Swenson NG, Enquist BJ, Pither J, Kerkhoff AJ, Boyle B, Weiser MD, Elser JJ, Fagan WF, Forero-Montaña J, Fyllas N, Kraft NJB, Lake JK, Moles AT, Patiño S, Phillips OL, et al. (2012). The biogeography and filtering of woody plant functional diversity in North and South America. Global Ecology and Biogeography, 21, 798-808.
DOI URL |
[190] |
Swenson NG, Weiser MD, Mao LF, Araújo MB, Diniz-Filho JAF, Kollmann J, Nogués-Bravo D, Normand S, Rodríguez MA, García-Valdés R, Valladares F, Zavala MA, Svenning JC (2017). Phylogeny and the prediction of tree functional diversity across novel continental settings. Global Ecology and Biogeography, 26, 553-562.
DOI URL |
[191] | Tang ZY, Xu WT, Zhou GY, Bai YF, Li JX, Tang XL, Chen DM, Liu Q, Ma WH, Xiong GM, He HL, He NP, Guo YP, Guo Q, Zhu JL, et al. (2018). Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China’s terrestrial ecosystems. Proceedings of the National Academy of Sciences of the United States of America, 115, 4033-4038. |
[192] |
Tao SL, Guo QH, Li C, Wang ZH, Fang JY (2016). Global patterns and determinants of forest canopy height. Ecology, 97, 3265-3270.
DOI PMID |
[193] |
Tautenhahn S, Migliavacca M, Kattge J (2020). News on intra-specific trait variation, species sorting, and optimality theory for functional biogeography and beyond. New Phytologist, 228, 6-10.
DOI PMID |
[194] |
ter Braak CJF, Cormont A, Dray S (2012). Improved testing of species traits-environment relationships in the fourth-corner problem. Ecology, 93, 1525-1526.
PMID |
[195] |
Thom D, Taylor AR, Seidl R, Thuiller W, Wang JJ, Robideau M, Keeton WS (2021). Forest structure, not climate, is the primary driver of functional diversity in northeastern North America. Science of the Total Environment, 762, 143070. DOI: 10.1016/j.scitotenv.2020.143070.
DOI |
[196] |
Thomson FJ, Letten AD, Tamme R, Edwards W, Moles AT (2018). Can dispersal investment explain why tall plant species achieve longer dispersal distances than short plant species? New Phytologist, 217, 407-415.
DOI PMID |
[197] |
Tian D, Kattge J, Chen YH, Han WX, Luo YK, He JS, Hu HF, Tang ZY, Ma SH, Yan ZB, Lin QH, Schmid B, Fang JY (2019). A global database of paired leaf nitrogen and phosphorus concentrations of terrestrial plants. Ecology, 100, e02812. DOI: 10.1002/ecy.2812.
DOI |
[198] |
Tian D, Yan ZB, Niklas KJ, Han WX, Kattge J, Reich PB, Luo YK, Chen YH, Tang ZY, Hu HF, Wright IJ, Schmid B, Fang J (2017). Global leaf nitrogen and phosphorus stoichiometry and their scaling exponent. National Science Review, 5, 728-739.
DOI URL |
[199] |
Tiffney BH (1984). Seed size, dispersal syndromes, and the rise of the angiosperms: evidence and hypothesis. Annals of the Missouri Botanical Garden, 71, 551-576.
DOI URL |
[200] |
Tucker CM, Davies TJ, Cadotte MW, Pearse WD (2018). On the relationship between phylogenetic diversity and trait diversity. Ecology, 99, 1473-1479.
DOI PMID |
[201] |
Valverde-Barrantes OJ, Blackwood CB (2016). Root traits are multidimensional: specific root length is independent from root tissue density and the plant economic spectrum: commentary on Kramer-Walter et al. (2016). Journal of Ecology, 104, 1311-1313.
DOI URL |
[202] |
van Bodegom PM, Douma JC, Verheijen LM (2014). A fully traits-based approach to modeling global vegetation distribution. Proceedings of the National Academy of Sciences of the United States of America, 111, 13733-13738.
DOI PMID |
[203] |
Vasseur F, Violle C, Enquist BJ, Granier C, Vile D (2012). A common genetic basis to the origin of the leaf economics spectrum and metabolic scaling allometry. Ecology Letters, 15, 1149-1157.
DOI PMID |
[204] |
Veeken A, Santos MJ, McGowan S, Davies AL, Schrodt F (2022). Pollen-based reconstruction reveals the impact of the onset of agriculture on plant functional trait composition. Ecology Letters, 25, 1937-1951.
DOI PMID |
[205] |
Villéger S, Mason NWH, Mouillot D (2008). New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology, 89, 2290-2301.
DOI PMID |
[206] |
Violle C, Enquist BJ, McGill BJ, Jiang L, Albert CH, Hulshof C, Jung V, Messier J (2012). The return of the variance: intraspecific variability in community ecology. Trends in Ecology & Evolution, 27, 244-252.
DOI URL |
[207] |
Violle C, Navas ML, Vile D, Kazakou E, Fortunel C, Hummel I, Garnier E (2007). Let the concept of trait be functional! Oikos, 116, 882-892.
DOI URL |
[208] |
Violle C, Reich PB, Pacala SW, Enquist BJ, Kattge J (2014). The emergence and promise of functional biogeography. Proceedings of the National Academy of Sciences of the United States of America, 111, 13690-13696.
DOI PMID |
[209] |
Wang H, Harrison SP, Prentice IC, Yang YZ, Bai F, Togashi HF, Wang M, Zhou SX, Ni J (2018). The China Plant Trait Database: toward a comprehensive regional compilation of functional traits for land plants. Ecology, 99, 500. DOI: 10.1002/ecy.2091.
DOI |
[210] |
Wang H, Prentice IC, Keenan TF, Davis TW, Wright IJ, Cornwell WK, Evans BJ, Peng CH (2017). Towards a universal model for carbon dioxide uptake by plants. Nature Plants, 3, 734-741.
DOI PMID |
[211] |
Wang RL, Yu GR, He NP, Wang QF, Zhao N, Xu ZW, Ge JP (2015). Latitudinal variation of leaf stomatal traits from species to community level in forests: linkage with ecosystem productivity. Scientific Reports, 5, 14454. DOI: 10.1038/srep14454.
DOI |
[212] |
Wang YY, Luo A, Lyu T, Dimitrov D, Xu XT, Freckleton RP, Li YQ, Su XY, Li Y, Liu YC, Liu YP, Sandanov D, Li QJ, Hao ZQ, Liu SG, Wang ZH (2021). Global distribution and evolutionary transitions of angiosperm sexual systems. Ecology Letters, 24, 1835-1847.
DOI URL |
[213] |
Wang YY, Lyu T, Shrestha N, Lyu LS, Li YQ, Schmid B, Freckleton RP, Dimitrov D, Liu SG, Hao ZQ, Wang ZH (2020). Drivers of large-scale geographical variation in sexual systems of woody plants. Global Ecology and Biogeography, 29, 546-557.
DOI URL |
[214] |
Wang ZH, Li YQ, Su XY, Tao SL, Feng X, Wang QG, Xu XT, Liu YP, Michaletz ST, Shrestha N, Larjavaara M, Enquist BJ (2019a). Patterns and ecological determinants of woody plant height in eastern Eurasia and its relation to primary productivity. Journal of Plant Ecology, 12, 791-803.
DOI URL |
[215] |
Wang ZQ, Yu KL, Lv SQ, Niklas KJ, Mipam TD, Crowther TW, Umaña MN, Zhao Q, Huang H, Reich PB (2019b). The scaling of fine root nitrogen versus phosphorus in terrestrial plants: a global synthesis. Functional Ecology, 33, 2081-2094.
DOI URL |
[216] | Wang XY, Ma MG, Yao H (2009). Advance in Dynamic Global Vegetation Models. Remote Sensing Technology and Application, 24, 246-251. |
[王旭峰, 马明国, 姚辉(2009). 动态全球植被模型的研究进展. 遥感技术与应用, 24, 246-251.] | |
[217] |
Weigelt P, König C, Kreft H (2020). GIFT—A Global Inventory of Floras and Traits for macroecology and biogeography. Journal of Biogeography, 47, 16-43.
DOI URL |
[218] | West GB, Brown JH, Enquist BJ (1999). A general model for the structure and allometry of plant vascular systems. Nature, 400, 664-667. |
[219] |
Wieczynski DJ, Boyle B, Buzzard V, Duran SM, Henderson AN, Hulshof CM, Kerkhoff AJ, McCarthy MC, Michaletz ST, Swenson NG, Asner GP, Bentley LP, Enquist BJ, Savage VM (2019). Climate shapes and shifts functional biodiversity in forests worldwide. Proceedings of the National Academy of Sciences of the United States of America, 116, 587-592.
DOI PMID |
[220] |
Wilf P, Zhang SP, Chikkerur S, Little SA, Wing SL, Serre T (2016). Computer vision cracks the leaf code. Proceedings of the National Academy of Sciences of the United States of America, 113, 3305-3310.
DOI PMID |
[221] |
Winter M, Devictor V, Schweiger O (2013). Phylogenetic diversity and nature conservation: Where are we? Trends in Ecology & Evolution, 28, 199-204.
DOI URL |
[222] |
Wright IJ, Ackerly DD, Bongers F, Harms KE, Ibarra-Manriquez G, Martinez-Ramos M, Mazer SJ, Muller-Landau HC, Paz H, Pitman NCA, Poorter L, Silman MR, Vriesendorp CF, Webb CO, Westoby M, Wright SJ (2007). Relationships among ecologically important dimensions of plant trait variation in seven Neotropical forests. Annals of Botany, 99, 1003-1015.
DOI PMID |
[223] |
Wright IJ, Dong N, Maire V, Prentice IC, Westoby M, Díaz S, Gallagher RV, Jacobs BF, Kooyman R, Law EA, Leishman MR, Niinemets Ü, Reich PB, Sack L, Villar R, et al. (2017). Global climatic drivers of leaf size. Science, 357, 917-921.
DOI PMID |
[224] |
Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, et al. (2004). The worldwide leaf economics spectrum. Nature, 428, 821-827.
DOI |
[225] |
Wright IJ, Westoby M (2001). Understanding seedling growth relationships through specific leaf area and leaf nitrogen concentration: generalisations across growth forms and growth irradiance. Oecologia, 127, 21-29.
DOI PMID |
[226] |
Yang YZ, Zhao J, Zhao PX, Wang H, Wang BH, Su SF, Li MX, Wang LM, Zhu QA, Pang ZY, Peng HC (2019). Trait-based climate change predictions of vegetation sensitivity and distribution in China. Frontiers in Plant Science, 10, 908. DOI: 10.3389/fpls.2019.00908.
DOI |
[227] |
Yang YZ, Zhu QA, Peng CH, Wang H, Chen H (2015). From plant functional types to plant functional traits: a new paradigm in modelling global vegetation dynamics. Progress in Physical Geography: Earth and Environment, 39, 514-535.
DOI URL |
[228] |
Yang YZ, Zhu QA, Peng CH, Wang H, Xue W, Lin GH, Wen ZM, Chang J, Wang M, Liu GB, Li SQ (2016). A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. Scientific Reports, 6, 24110. DOI: 10.1038/srep24110.
DOI |
[229] | Yang YZ, Wang H, Zhu QA, Wen ZM, Peng CH, Lin GH (2018). Research progresses in improving dynamic global vegetation models (DGVMs) with plant functional traits. Chinese Science Bulletin, 63, 2599-2611. |
[杨延征, 王焓, 朱求安, 温仲明, 彭长辉, 林光辉 (2018). 植物功能性状对动态全球植被模型改进研究进展. 科学通报, 63, 2599-2611.] | |
[230] |
Zanne AE, Tank DC, Cornwell WK, Eastman JM, Smith SA, FitzJohn RG, McGlinn DJ, O’Meara BC, Moles AT, Reich PB, Royer DL, Soltis DE, Stevens PF, Westoby M, Wright IJ, et al. (2014). Three keys to the radiation of angiosperms into freezing environments. Nature, 506, 89-92.
DOI |
[231] |
Zhao Y, Cao HL, Xu WB, Chen GK, Lian JY, Du YJ, Ma KP (2018). Contributions of precipitation and temperature to the large scale geographic distribution of fleshy-fruited plant species: growth form matters. Scientific Reports, 8, 17017. DOI: 10.1038/s41598-018-35436-x.
DOI |
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