, Volume 33, Issue 2, pp 491–505 | Cite as

A whole-plant functional scheme predicting the early growth of tropical tree species: evidence from 15 tree species in Central Africa

  • Ariane MirabelEmail author
  • Dakis-Yaoba Ouédraogo
  • Hans Beeckman
  • Claire Delvaux
  • Jean-Louis Doucet
  • Bruno Hérault
  • Adeline Fayolle
Original Article


Key message

This study highlighted the consistency of a functional scheme integrating leaf, stem and root traits, biomass allocation and stem anatomy for 15 tropical tree species at the seedling stage. This functional scheme was shaped by the trade-offs for resource use and the hydraulics of the plants and was found to determine seedling growth.


Functional traits determine plant functioning, performance and response to the environment and define species functional strategy. The functional strategy of 15 African tree species was assessed by (1) highlighting the structure of traits covariance and the underlying functional trade-offs, (2) inferring a whole-plant functional scheme and (3) testing the correlation of the functional scheme with plant performance for two early developmental stages (seedlings and saplings). We selected 10 seedlings for each of the 15 species studied from a nursery in south-eastern Cameroon and measured 18 functional traits, including leaf, stem and root traits, biomass allocation and stem anatomy. We assessed the height and diameter growth of the seedlings and the DBH growth and survival for the saplings of nearby plantations. Multivariate analyses highlighted the covariations among the functional traits of the leaf/stem/root, biomass allocation ratios and stem anatomy. The major trait covariation axes were driven by two trade-offs, first between resource acquisition and conservation and second between hydraulic safety and efficiency. The axes were integrated into a Bayesian network inferring a functional scheme at the whole-plant scale, which was found to predict the growth of the seedlings but not the performance of the saplings. The functional strategies of the seedlings were determined by an integrated whole-plant scheme reflecting the trade-offs for resource use and plant hydraulics. The scheme predicted the growth of the seedlings through mechanistic pathways from the wood stem to all the plant traits, but it appeared to shift at the stage of the saplings.


‘Fast–slow’ plant economics spectrum Integrated functional type Wood anatomy Ontogeny Performance Seedlings Functional trade-offs 



The authors are grateful to the Pallisco Logging Company for access to the site, to the NGO Nature Plus for logistic support, and to Françoise Toussaint and Gilles Collinet from the Soil-System Unit of Gembloux Agro-Bio Tech, University of Liège, Belgium, for the chemical analyses of leaf samples. We also thank Eric Marcon and Stéphane Traissac from the EcoFoG Unit, French Guiana, for valuable comments on the manuscript. A. M. benefitted from a grant of the Agence Universitaire de la Francophonie (AUF). Part of this study was funded by the HERBAXYLAREDD project (BR/143/A3/HERBAXYLAREDD).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

468_2018_1795_MOESM1_ESM.docx (35 kb)
Supplementary material 1 (DOCX 34 KB)


  1. Aubry-Kientz M, Hérault B, Ayotte-Trépanier C, Baraloto C, Rossi V (2013) Toward trait-based mortality models for tropical forests. PLoS One 8(5):e63678CrossRefPubMedPubMedCentralGoogle Scholar
  2. Baraloto C, Paine TCE, Poorter L, Beauchene J, Bonal D, Domenech AM et al (2010) Decoupled leaf and stem economics in rain forest trees. Ecol Lett 13:1338–1347CrossRefPubMedGoogle Scholar
  3. Bardgett RD, Mommer L, De Vries FT (2014) Going underground: root traits as drivers of ecosystem processes. Trends Ecol Evol 29:692–699CrossRefPubMedGoogle Scholar
  4. Beeckman H (2016) Wood anatomy and trait-based ecology. IAWA J 37:127–151CrossRefGoogle Scholar
  5. Bénédet F, Vincke D, Fayolle A, Doucet JL, Gourlet-Fleury S (2014) Cofortraits, African plant traits information database. Version 1.0Google Scholar
  6. Borchert R (1994) Soil and stem water storage determine phenology and distribution of tropical dry forest trees. Ecology 75:1437–1449CrossRefGoogle Scholar
  7. Bucci SJ, Scholz FG, Campanello PI, Montti L, Jimenez-Castillo M, Rockwell FA et al (2012) Hydraulic differences along the water transport system of South American Nothofagus species: do leaves protect the stem functionality? Tree Physiol 32:880–893CrossRefPubMedGoogle Scholar
  8. Caldwell E, Read J, Sanson GD (2015) Which leaf mechanical traits correlate with insect herbivory among feeding guilds? Ann Bot 117-2:349–361Google Scholar
  9. Cavaleri MA, Oberbauer SF, Clark DB, Clark DA, Ryan MG (2010) Height is more important than light in determining leaf morphology in a tropical forest. Ecology 91(6):1730–1739CrossRefPubMedGoogle Scholar
  10. Chapin FS (1980) The mineral nutrition of wild plants. Annu Rev Ecol Syst 11:233–260CrossRefGoogle Scholar
  11. Chave J, Coomes D, Jansen S, Lewis SL, Swenson NG, Zanne AE (2009) Towards a worldwide wood economics spectrum. Ecol Lett 12:351–366CrossRefPubMedGoogle Scholar
  12. Cornelissen JHC et al (2003) A handbook of protocols for standardized and easy measurement of plant functional traits worldwide. Aust J Bot 51:335–380CrossRefGoogle Scholar
  13. Delagrange S, Potvin C, Messier C, Coll L (2008) Linking multiple-level tree traits with biomass accumulation in native tree species used for reforestation in Panama. Trees 22(3):337–349CrossRefGoogle Scholar
  14. Development Team Quantum GIS (2015) QGIS geographic information system. Accessed May 2015
  15. Doucet JL, Kouadio YL, Monticelli D, Lejeune P (2009) Enrichment of logging gaps with moabi (Baillonella toxisperma Pierre) in a Central African rain forest. For Ecol Manage 258(11):2407–2415CrossRefGoogle Scholar
  16. Doucet JL, Daïnou K, Ligot G, Ouédraogo DY, Bourland N, Ward SE et al (2016) Enrichment of Central African logged forests with high-value tree species: testing a new approach to regenerating degraded forests. Int J Biodivers Sci Ecosyst Serv Manag 12.1(2):83–95Google Scholar
  17. Dray S, Dufour AB (2007) The ade4 package: implementing the duality diagram for ecologists. J Stat Softw 22(44):1–20Google Scholar
  18. Falster DS, Brännström Å, Dieckmann U, Westoby M (2011) Influence of four major plant traits on average height, leaf-area cover, net primary productivity, and biomass density in single-species forests: a theoretical investigation. J Ecol 99(1):148–164CrossRefGoogle Scholar
  19. Fan ZX, Zhang SB, Hao GY, Slik JWF, Cao KF (2012) Hydraulic conductivity traits predict growth rates and adult stature of 40 Asian tropical tree species better than wood density. J Ecol 100:732–741CrossRefGoogle Scholar
  20. Fortunel C, Fine PVA, Baraloto C (2012) Leaf, stem and root tissue strategies across 758 Neotropical tree species. Funct Ecol 26:1153–1161CrossRefGoogle Scholar
  21. Fortunel C, Ruelle J, Beauchêne J, Fine PVA, Baraloto C (2013) Wood specific gravity and anatomy of branches and roots in 113 Amazonian rainforest tree species across environmental gradients. New Phytol 202:79–94CrossRefPubMedGoogle Scholar
  22. Freschet GT, Cornelissen JHC, van Logtestijn RSP, Aerts R (2010) Evidence of the “plant economics spectrum” in a subarctic flora. J Ecol 98:362–373CrossRefGoogle Scholar
  23. Garnier E, Shipley B (2001) A standardized protocol for the determination of specific leaf area and leaf dry matter content. Funct Ecol 15:688–695CrossRefGoogle Scholar
  24. Garnier E, Laurent G, Bellmann A, Debain S, Berthelier P, Ducout B et al (2001) Consistency of species ranking based on functional leaf traits. New Phytol 152:69–83CrossRefGoogle Scholar
  25. Gibert A, Gray EF, Westoby M, Wright IJ, Falster DS (2016) Plant species traits and growth rates: meta-analysis shows correlations change with plant size, as predicted. J Ecol 104:1488–1503CrossRefGoogle Scholar
  26. Hérault B, Bachelot B, Poorter L, Rossi V, Bongers F, Chave J et al (2011) Functional traits shape ontogenetic growth trajectories of rain forest tree species. J Ecol 99:1431–1440CrossRefGoogle Scholar
  27. Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6:65–70Google Scholar
  28. Hummel I, Vile D, Violle C, Devaux J, Ricci B, Blanchard A, Garnier E, Roumet C (2007) Relating root structure and anatomy to whole-plant functioning in 14 herbaceous Mediterranean species. New Phytol 173:313–321CrossRefPubMedGoogle Scholar
  29. Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 282(53):457–481CrossRefGoogle Scholar
  30. Kitajima K, Poorter L (2008) Functional basis for resource niche partitioning by tropical trees. Trop For Commun Ecol 2008:160–181Google Scholar
  31. Kleyer M, Minden V (2015) Why functional ecology should consider all plant organs: an allocation-based perspective. Basic Appl Ecol 16:1–9CrossRefGoogle Scholar
  32. Lachenbruch B, Mcculloh KA (2014) Traits, properties, and performance: how woody plants combine hydraulic and mechanical functions in a cell, tissue, or whole plant. New Phytol 204:747–764CrossRefPubMedGoogle Scholar
  33. Lavorel S, Garnier E (2002) Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct Ecol 16:545–556CrossRefGoogle Scholar
  34. Lawes MJ, Midgley JJ, Clarke PJ (2013) Costs and benefits of relative bark thickness in relation to fire damage: a savanna/forest contrast. J Ecol 101:517–524CrossRefGoogle Scholar
  35. Lemon J (2006) Plotrix: a package in the red light district of R. R-News 6(4):8–12Google Scholar
  36. Lewis FI (2016) ABN: modelling multivariate data with additive bayesian networks. Accessed Dec 2016
  37. Li Y, Kröber W, Bruelheide H, Härdtle W, von Oheimb G (2017) Crown and leaf traits as predictors of subtropical tree sapling growth rates. J Plant Ecol 10(11):136–145CrossRefGoogle Scholar
  38. Lloyd J, Patiño S, Paiva RQ, Nardoto GB, Quesada CA, Santos AJB et al (2010) Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees. Biogeosciences 7:1833–1859CrossRefGoogle Scholar
  39. Markesteijn L, Poorter L (2009) Seedling root morphology and biomass allocation of 62 tropical tree species in relation to drought- and shade-tolerance. J Ecol 97:311–325CrossRefGoogle Scholar
  40. Markesteijn L, Poorter L, Paz H, Sack L, Bongers F (2011) Ecological differentiation in xylem cavitation resistance is associated with stem and leaf structural traits. Plant Cell Environ 34:137–148CrossRefPubMedGoogle Scholar
  41. Martínez-Garza C, Bongers F, Poorter L (2013) Are functional traits good predictors of species performance in restoration plantings in tropical abandoned pastures? For Ecol Manage 303:35–45CrossRefGoogle Scholar
  42. Meunier Q, Moumbogou C, Doucet JL (2015) Les Arbres Utiles du Gabon. Les presses Agronomiques de Gembloux, GemblouxGoogle Scholar
  43. Niinemets U et al (2004) Petiole length and biomass investment in support modify light interception efficiency in dense poplar plantations. Tree Physiol 24:141–154CrossRefPubMedGoogle Scholar
  44. Ostonen I, Püttsepp Ü, Biel C, Alberton O, Bakker MR, Lõhmus K et al (2014) Specific root length as an indicator of environmental change. Plant Biosyst 141:426–442CrossRefGoogle Scholar
  45. Paine TCE, Amissah L, Auge H, Baraloto C, Baruffol M, Bourland N et al (2015) Globally, functional traits are weak predictors of juvenile tree growth, and we do not know why. J Ecol 103:978–989CrossRefGoogle Scholar
  46. Pérez-Harguindeguy N, Díaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P et al (2013) New handbook of protocols for standardized measurement of plant functional traits worldwide. Aust J Bot 61:167–234CrossRefGoogle Scholar
  47. Philipson CD, Dent DH, O’Brien MJ, Chamagne J, Dzulkifli D, Nilus R, Philips S, Reynolds G, Saner P, Hector A (2014) A trait-based trade-off between growth and mortality: evidence from 15 tropical tree species using size-specific relative growth rates. Ecol Evol 4(18):3675–3688CrossRefPubMedPubMedCentralGoogle Scholar
  48. Poorter L, Bongers F (2006) Leaf traits are good predictors of plant performance across 53 rain forest species. Ecology 87(7):1733–1743CrossRefPubMedGoogle Scholar
  49. Poorter L, Rozendaal DMA (2008) Leaf size and leaf display of thirty-eight tropical tree species. Oecologia 158:35–46CrossRefPubMedGoogle Scholar
  50. Poorter L, Wright SJ, Paz H, Ackerly DD, Condit R, Harms E et al (2008) Are functional traits good predictors of demographic rates? Evidence from five neotropical forests. Ecology 89:1908–1920CrossRefGoogle Scholar
  51. Poorter L, McDonald I, Alarcon A, Fichtler E, Licona JC, Peña-Claros M et al (2010) The importance of wood traits and hydraulic conductance for the performance and life history strategies of 42 rainforest tree species. New Phytol 185:481–492CrossRefPubMedGoogle Scholar
  52. Poorter Z, Niklas KJ, Reich PB, Oleksyn J, Poot P, Mommer L (2011) Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytol 193:30–50CrossRefPubMedGoogle Scholar
  53. Powell TL, Wheeler JK, de Oliveira AAR, Lola de Costa C, Saleska A, Meir P, Moorcroft PR (2017) Differences in xylem and leaf hydraulic traits explain differences in drought tolerance among mature Amazon rainforest trees. Glob Change Biol 23:4280–4293CrossRefGoogle Scholar
  54. Prado-Junior JA, Schiavini I, Vale VS, Raymundo D, Lopes SF, Poorter L (2016) Functional traits shape size-dependent growth and mortality rates of dry forest tree species. J Plant Ecol 10(16):895–906Google Scholar
  55. R Core Team (2014) R: a language and environment for statistical computing. Accessed Sept 2014
  56. Rasband WS (2015) ImageJ. Accessed Feb 2015
  57. Reich PB (2014) The world-wide “fast-slow” plant economics spectrum: a traits manifesto. J Ecol 102(2):275–301CrossRefGoogle Scholar
  58. Reich PB, Walters MB, Ellsworth DS (1997) From tropics to tundra: global convergence in plant functioning. Proc Natl Acad Sci 94(25):13730–13734CrossRefGoogle Scholar
  59. Reich PB, Wright IJ, Cavender-bares J, Craine JM, Oleksyn J, Westoby M et al (2003) The evolution of plant functional variation: traits, spectra, and strategies. Int J Plant Sci 1643:143–164CrossRefGoogle Scholar
  60. Revelle W (2015) psych: procedures for personality and psychological research. Accessed June 2015
  61. Royal Botanic Gardens Kew (2016) Seed information database. Version 7.1. Available from: Accessed July 2015
  62. Rüger N, Wirth C, Wright SJ, Condit R (2012) Functional traits explain light and size response of growth rates in tropical tree species. Ecology 93(12):2626–2636CrossRefGoogle Scholar
  63. Russo SE, Brown P, Tan S, Davies SJ (2008) Interspecific demographic trade-offs and soil-related habitat associations of tree species along resource gradients. J Ecol 96:192–203CrossRefGoogle Scholar
  64. Scheiter S, Langan L, Higgins SI (2013) Next-generation dynamic global vegetation models: learning from community ecology. New Phytol 198:957–969CrossRefPubMedGoogle Scholar
  65. Sendall KM, Reich PB, Lusk CH (2018) Size-related shifts in carbon gain and growth responses to light differ among rainforest evergreens of contrasting shade tolerance. Oecologia 2018:1–15Google Scholar
  66. Spicer R (2014) Symplasmic networks in secondary vascular tissues: parenchyma distribution and activity supporting long-distance transport. J Exp Bot 65:1829–1848CrossRefPubMedGoogle Scholar
  67. Valverde-Barrantes OJ, Freschet GT, Roumet C, Blackwood CB (2017) A worldview of root traits: the influence of ancestry, growth form, climate and mycorrhizal association on the functional trait variation of fine-root tissues in seed plants. New Phytol 215:1562–1573CrossRefGoogle Scholar
  68. Verbeeck H, Boeckx P, Steppe K (2011) Tropical forests: include Congo basin. Nature 479(7372):179Google Scholar
  69. Violle C, Navas ML, Vile D, Kazakou E, Fortunel C (2007) Let the concept of trait be functional! Oikos 116:882–892CrossRefGoogle Scholar
  70. Visser MD, Bruijning M, Wright SJ, Müller-Landau HC, Jongejans E et al (2016) Functional traits as predictors of vital rates across the life cycle of tropical trees. Funct Ecol 30:168–180CrossRefGoogle Scholar
  71. Westoby M, Wright IJ (2003) The leaf size-twig size spectrum and its relationship to other important spectra of variation among species. Oecologia 135:621–628CrossRefPubMedGoogle Scholar
  72. White F (1983) The vegetation of Africa. United Nations Sudano-Sahelien Office, ed. UNESCO, ParisGoogle Scholar
  73. Wright IJ, Westoby M (2001) Understanding seedling growth relationships through specific leaf area and leaf nitrogen concentration: generalizations across growth forms and growth irradiance. Oecologia 127:21–29CrossRefPubMedGoogle Scholar
  74. Wright IJ, Reich PB, Westoby M, Ackerly DD (2004) The worldwide leaf economics spectrum. Nature 428:821–827CrossRefPubMedGoogle Scholar
  75. Wright SJ, Kitajima K, Kraft NJB, Reich PB, Wright IJ, Bunker DE et al (2010) Functional traits and the growth—mortality trade-off in tropical trees. Ecology 91:3664–3674CrossRefPubMedGoogle Scholar
  76. Zanne AE, Lopez-Gonzalez G, Coomes DA, Ilic J, Jansen S et al (2009) Global wood density database. Dryad. Available from Accessed July 2015

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.TERRA Teaching and Research Center, Gembloux Agro-Bio TechGemblouxBelgium
  2. 2.Cirad, UR Forest and SocietiesMontpellierFrance
  3. 3.INPHB (Institut National Polytechnique Félix Houphouët Boigny)YamoussoukroIvory Coast
  4. 4.Service of Wood BiologyRoyal Museum of Central Africa (RMCA)TervurenBelgium

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