Advertisement

Trees

, Volume 33, Issue 6, pp 1615–1625 | Cite as

Sugar maple (Acer saccharum Marsh.) shoot architecture reveals coordinated ontogenetic changes between shoot specialization and branching pattern

  • Olivier Taugourdeau
  • Sylvain DelagrangeEmail author
  • Bastien Lecigne
  • Rita Sousa-Silva
  • Christian Messier
Original Article
  • 104 Downloads

Abstract

Key message

Trees display contrasting specialized annual shoots during their life-span and along with ontogeny-driven modifications in their branching pattern, they can fulfill different combinations of light exploitation and space exploration functions

Abstract

Tree ontogeny is related to major changes in tree structure and function at different scales, from individual organs to the whole tree. Yet, little is known about the direct effects of tree ontogeny on shoot specialization and branching patterns. Such specific architectural changes occurring with tree growth and aging are of critical importance for understanding the response of trees to their environment. The uppermost branching system of 0.1- to 23-m-tall sugar maple trees was sampled at the end of the growing season. Measurements were made at both the branching system (n = 40) and annual shoot scales (n = 803). An algorithm for automated shoot typology was developed to characterize branching pattern variations. Sugar maple shoots were divided into four types with contrasting sizes and levels of foliage (i.e., relative biomass allocation into leaves, LMF). These morphological differences were interpreted as functional specializations for light exploitation (high LMF) or space exploration and support (low LMF). Only annual trunk shoots exhibited trait value changes during ontogeny such as a minimum allocation to foliage in the current-year shoots for the 5-m-tall trees, which is related to lower light interception capabilities but higher space exploration abilities. However, this relative loss of light interception function is compensated by ontogenetic changes at the branching system scale, which are associated with higher rates of ramification to produce lateral shoots. This study reveals how branching system and annual shoot traits change simultaneously during tree ontogeny to fulfill different functions, particularly light exploitation and space exploration.

Keywords

Biomass allocation Current-year shoot Leaf mass area (LMA) Ontogeny Plant architecture Shoot allometry 

Notes

Acknowledgements

The authors gratefully thank R. Pouliot for site selection, M. Follett for (climbing the trees for) data collection in mature trees, J. Poirier for scanning leaf samples, S. Martinez Ruiz for biomass measurements, W.F.J. Parsons for manuscript revision, and C. Nock and P. de Reffye for providing valuable advice throughout the project. A postdoctoral fellowship to OT was funded by the Chaire de recherche CNRSG/Hydro-Quebec.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

468_2019_1884_MOESM1_ESM.docx (373 kb)
Supplementary material 1 (DOCX 372 kb)

References

  1. Baret S, Nicolini E, Le Bourgeois T, Strasberg D (2003) Developmental patterns of the invasive bramble (Rubus alceifolius Poiret, Rosaceae) in Réunion island: an architectural and morphometric analysis. Ann Bot 91:39–48.  https://doi.org/10.1093/aob/mcg006 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Barthélémy D, Caraglio Y (2007) Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny. Ann Bot 99:375–407CrossRefGoogle Scholar
  3. Barthélémy D, Caraglio Y, Costes E (1997) Architecture, gradients morphogénétiques et âge physiologique chez les végétaux. In: Bouchon J, de Reffye P, Barthélémy D (eds) Modélisation et simulation de l’architecture des végétaux. Science u. INRA, CIRAD-GERDAT-AMAP, Paris, pp 89–136Google Scholar
  4. Bishop DA, Beier CM, Pederson N et al (2015) Regional growth decline of sugar maple (Acer saccharum) and its potential causes. Ecosphere 6:art179.  https://doi.org/10.1890/es15-00260.1 CrossRefGoogle Scholar
  5. Borianne P, Brunel G (2012) Automated valuation of leaves area for large-scale analysis needing data coupling or petioles deletion. In: Proceedings—2012 IEEE 4th international symposium on plant growth modeling, simulation, visualization and applications, PMA 2012. IEEE, pp 50–57Google Scholar
  6. Buissart F, Vennetier M, Delagrange S et al (2018) The relative weight of ontogeny, topology and climate in the architectural development of three North American conifers. AoB Plants.  https://doi.org/10.1093/aobpla/ply045 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Coble AP, Cavaleri MA, Niinemets Ü (2014) Light drives vertical gradients of leaf morphology in a sugar maple (Acer saccharum) forest. Tree Physiol 34:146–158.  https://doi.org/10.1093/treephys/tpt126 CrossRefPubMedGoogle Scholar
  8. Cochard H, Coste S, Chanson B et al (2005) Hydraulic architecture correlates with bud organogenesis and primary shoot growth in beech (Fagus sylvatica). Tree Physiol 25:1545–1552.  https://doi.org/10.1093/treephys/25.12.1545 CrossRefPubMedGoogle Scholar
  9. Delagrange S, Messier C, Lechowicz MJ, Dizengremel P (2004) Physiological, morphological and allocational plasticity in understory deciduous trees: importance of plant size and light availability. Tree Physiol 24:775–784.  https://doi.org/10.1093/treephys/24.7.775 CrossRefPubMedGoogle Scholar
  10. Delagrange S, Montpied P, Dreyer E et al (2006) Does shade improve light interception efficiency? A comparison among seedlings from shade-tolerant and -intolerant temperate deciduous tree species. New Phytol 172:293–304.  https://doi.org/10.1111/j.1469-8137.2006.01814.x CrossRefPubMedGoogle Scholar
  11. Farnsworth KD, Niklas KJ (1995) Theories of optimization, form and function in branching architecture in plants. Funct Ecol 9:355–363.  https://doi.org/10.2307/2389997 CrossRefGoogle Scholar
  12. Freschet GT, Swart EM, Cornelissen JHC (2015) Integrated plant phenotypic responses to contrasting above- and below-ground resources: key roles of specific leaf area and root mass fraction. New Phytol 206:1247–1260.  https://doi.org/10.1111/nph.13352 CrossRefPubMedGoogle Scholar
  13. Godman R, Yawney H, Tubbs C (1990) Sugar maple (Acer saccharum Marsh.). In: Silvics of North America, vol 2. Hardwoods, United States Department of Agriculture (USDA), Forest Service, Agriculture Handbook 654. https://www.fs.usda.gov/treesearch/pubs/1548
  14. Griffon S, de Coligny F (2014) AMAPstudio: an editing and simulation software suite for plants architecture modelling. Ecol Modell 290:3–10.  https://doi.org/10.1016/j.ecolmodel.2013.10.037 CrossRefGoogle Scholar
  15. Henry HAL, Aarssen LW (2001) Inter- and intraspecific relationships between shade tolerance and shade avoidance in temperate trees. Oikos 93:477–487.  https://doi.org/10.1034/j.1600-0706.2001.930313.x CrossRefGoogle Scholar
  16. Heuret P, Meredieu C, Coudurier T et al (2006) Ontogenetic trends in the morphological features of main stem annual shoots of Pinus pinaster (Pinaceae). Am J Bot 93:1577–1587.  https://doi.org/10.3732/ajb.93.11.1577 CrossRefPubMedGoogle Scholar
  17. Horsley SB, Long RP, Bailey SW et al (2002) Health of eastern North American sugar maple forests and factors affecting decline. North J Appl For 19:34–44CrossRefGoogle Scholar
  18. Ishii H (2011) How do changes in leaf/shoot morphology and crown architecture affect growth and physiological function of tall trees? In: Meinzer F, Lachenbruch B, Dawson T (eds) Size- and age-related changes in tree structure and function SE—tree physiology, vol 4. Springer, Dordrecht, pp 215–232Google Scholar
  19. Ishii H, Ford ED (2001) The role of epicormic shoot production in maintaining foliage in old Pseudotsuga menziesii (Douglas-fir) trees. Can J Bot 79:251–264.  https://doi.org/10.1139/cjb-79-3-251 CrossRefGoogle Scholar
  20. Koch GW, Stillet SC, Jennings GM, Davis SD (2004) The limits to tree height. Nature 428:851–854.  https://doi.org/10.1038/nature02417 CrossRefPubMedGoogle Scholar
  21. Kunstler G, Falster D, Coomes DA et al (2016) Plant functional traits have globally consistent effects on competition. Nature 529:204–207.  https://doi.org/10.1038/nature16476 CrossRefPubMedGoogle Scholar
  22. Lauri PE, Normand F (2017) Are leaves only involved in flowering? Bridging the gap between structural botany and functional morphology. Tree Physiol 37:1137–1139.  https://doi.org/10.1093/treephys/tpx068 CrossRefPubMedGoogle Scholar
  23. Letort V, Cournède PH, Mathieu A et al (2008) Parametric identification of a functional–structural tree growth model and application to beech trees (Fagus sylvatica). Funct Plant Biol 35:951–963.  https://doi.org/10.1071/fp08065 CrossRefGoogle Scholar
  24. Martre P, Dambreville A (2018) A model of leaf coordination to scale-up leaf expansion from the organ to the canopy. Plant Physiol 176:704–716.  https://doi.org/10.1104/pp.17.00986 CrossRefPubMedGoogle Scholar
  25. Massonnet C, Regnard JL, Lauri PÉ et al (2008) Contributions of foliage distribution and leaf functions to light interception, transpiration and photosynthetic capacities in two apple cultivars at branch and tree scales. Tree Physiol 28:665–678.  https://doi.org/10.1093/treephys/28.5.665 CrossRefPubMedGoogle Scholar
  26. Mathieu A, Cournede PH, Letort V et al (2009) A dynamic model of plant growth with interactions between development and functional mechanisms to study plant structural plasticity related to trophic competition. Ann Bot 103:1173–1186.  https://doi.org/10.1093/aob/mcp054 CrossRefPubMedPubMedCentralGoogle Scholar
  27. Matthews SN, Iverson LR (2017) Managing for delicious ecosystem service under climate change: can United States sugar maple (Acer saccharum) syrup production be maintained in a warming climate? Int J Biodivers Sci Ecosyst Serv Manag 13:40–52.  https://doi.org/10.1080/21513732.2017.1285815 CrossRefGoogle Scholar
  28. MFFP (2008) Norme de stratification écoforestière. Quatrième inventaire écoforestier du Québec méridional. Ministère des Forêts, de la Faune et des Parcs du Québec. Direction des inventaires forestiers. QuébecGoogle Scholar
  29. Millet J (2012) L’architecture des arbres des régions tempérées: son histoire, ses concepts, ses usages. Editions MultiMondes, MontrealGoogle Scholar
  30. Nicolini E, Chanson B (1999) La pousse courte, un indicateur du degré de maturation chez le hêtre (Fagus sylvatica L.). Can J Bot 77:1539–1550.  https://doi.org/10.1139/cjb-77-11-1539 CrossRefGoogle Scholar
  31. Niklas KJ, Cobb ED (2010) Ontogenetic changes in the numbers of short- vs. long-shoots account for decreasing specific leaf area in Acer rubrum (Aceraceae) as trees increase in size. Am J Bot 97:27–37.  https://doi.org/10.3732/ajb.0900249 CrossRefPubMedGoogle Scholar
  32. Nock CA, Caspersen JP, Thomas SC (2008) Large ontogenetic declines in intra-crown leaf area index in two temperate deciduous tree species. Ecology 89:744–753.  https://doi.org/10.1890/07-0531.1 CrossRefPubMedGoogle Scholar
  33. Onoda Y, Saluñga JB, Akutsu K et al (2014) Trade-off between light interception efficiency and light use efficiency: implications for species coexistence in one-sided light competition. J Ecol 102:167–175.  https://doi.org/10.1111/1365-2745.12184 CrossRefGoogle Scholar
  34. Osada N, Okabe Y, Hayashi D et al (2014) Differences between height- and light-dependent changes in shoot traits in five deciduous tree species. Oecologia 174:1–12.  https://doi.org/10.1007/s00442-013-2744-2 CrossRefPubMedGoogle Scholar
  35. Poorter H, Niinemets Ü, Poorter L et al (2009) Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis. New Phytol 182:565–588CrossRefGoogle Scholar
  36. Poorter H, Niklas KJ, Reich PB et al (2012) Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytol 193:30–50.  https://doi.org/10.1111/j.1469-8137.2011.03952.x CrossRefPubMedGoogle Scholar
  37. Posada JM, Sievänen R, Messier C et al (2012) Contributions of leaf photosynthetic capacity, leaf angle and self-shading to the maximization of net photosynthesis in Acer saccharum: a modelling assessment. Ann Bot 110:731–741.  https://doi.org/10.1093/aob/mcs106 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Puntieri J, Torres C, Magnin A et al (2018) Structural differentiation among annual shoots as related to growth dynamics in Luma apiculata trees (Myrtaceae). Flora Morphol Distrib Funct Ecol Plants 249:86–96.  https://doi.org/10.1016/j.flora.2018.10.005 CrossRefGoogle Scholar
  39. R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  40. Robitaille A (1988) Cartographie des districts écologiques: norme et techniques. Gouvernement du Québec, Bibliothèque et archives nationales du Québec 2013. http://www.mrn.gouv.qc.ca/forets/inventaire/inventaire-systeme.jsp
  41. Rueffler C, Hermisson J, Wagner GP (2012) Evolution of functional specialization and division of labor. Proc Natl Acad Sci 109:E326–E335.  https://doi.org/10.1073/pnas.1110521109 CrossRefPubMedGoogle Scholar
  42. Sabatier S, Barthélémy D (2001) Bud structure in relation to shoot morphology and position on the vegetative annual shoots of Juglans regia L. (Juglandaceae). Ann Bot 87:117–123.  https://doi.org/10.1006/anbo.2000.1312 CrossRefGoogle Scholar
  43. Suzuki AA, Suzuki M (2009) Why do lower order branches show greater shoot growth than higher order branches? Considering space availability as a factor affecting shoot growth. Trees Struct Funct 23:69–77.  https://doi.org/10.1007/s00468-008-0255-2 CrossRefGoogle Scholar
  44. Taugourdeau O, Barczi J, Caraglio Y (2012a) Simulation of morphogenetical gradients using a minimal functional–structural plant model (FSPM). In: 2012 IEEE 4th international symposium on plant growth modeling, simulation, visualization and applications. IEEE, pp 379–387Google Scholar
  45. Taugourdeau O, Dauzat J, Griffon S et al (2012b) Retrospective analysis of tree architecture in silver fir (Abies alba Mill.): ontogenetic trends and responses to environmental variability. Ann For Sci 69:713–721.  https://doi.org/10.1007/s13595-012-0188-1 CrossRefGoogle Scholar
  46. Taugourdeau O, Delagrange S, de Reffye P, Messier C (2013) Modelling sugar maple development along its whole ontogeny: modelling hypotheses and calibration methodology. In: Sievänen R, Nikinmaa E, Godin C et al. (eds) Proceedings of the 7th international conference on functional–structural plant models (FSPM2013). Finnish Society of Forest Science, Saariselkä, Finland, 9–14 June 2013, pp 234–236Google Scholar
  47. Thomas SC (2010) Photosynthetic capacity peaks at intermediate size in temperate deciduous trees. Tree Physiol 30:555–573.  https://doi.org/10.1093/treephys/tpq005 CrossRefPubMedGoogle Scholar
  48. Tondjo K, Brancheriau L, Sabatier S et al (2018) Stochastic modelling of tree architecture and biomass allocation: application to teak (Tectona grandis L. f.), a tree species with polycyclic growth and leaf neoformation. Ann Bot 121:1397–1410.  https://doi.org/10.1093/aob/mcy040 CrossRefPubMedPubMedCentralGoogle Scholar
  49. Van de Peer T, Verheyen K, Kint V et al (2017) Plasticity of tree architecture through interspecific and intraspecific competition in a young experimental plantation. For Ecol Manage 385:1–9.  https://doi.org/10.1016/j.foreco.2016.11.015 CrossRefGoogle Scholar
  50. Venables WN, Ripley BD (2002) Modern applied statistics with S. Fourth, SpringerCrossRefGoogle Scholar
  51. Vennetier M, Girard F, Taugourdeau O et al (2013) Climate change impact on tree architectural development and leaf area. In: Climate change—realities, impacts over ice cap, sea level and risks. InTechGoogle Scholar
  52. Vincent G, Harja D (2008) Exploring ecological significance of tree crown plasticity through three-dimensional modelling. Ann Bot 101:1221–1231.  https://doi.org/10.1093/aob/mcm189 CrossRefPubMedGoogle Scholar
  53. Weraduwage SM, Chen J, Anozie FC et al (2015) The relationship between leaf area growth and biomass accumulation in Arabidopsis thaliana. Front Plant Sci 6:167.  https://doi.org/10.3389/fpls.2015.00167 CrossRefPubMedPubMedCentralGoogle Scholar
  54. Xiang S, Liu Y, Fang F et al (2009) Stem architectural effect on leaf size, leaf number, and leaf mass fraction in plant twigs of woody species. Int J Plant Sci 170:999–1008.  https://doi.org/10.1086/605114 CrossRefGoogle Scholar
  55. Yagi T (2000) Morphology and biomass allocation of current-year shoots of ten tall tree species in cool temperate Japan. J Plant Res 113:171–183.  https://doi.org/10.1007/pl00013928 CrossRefGoogle Scholar
  56. Yagi T (2004) Within-tree variations in shoot differentiation patterns of ten tall tree species in a Japanese cool-temperate forest. Botany 82:228–243.  https://doi.org/10.1177/0890334414548459 CrossRefGoogle Scholar
  57. Yoshimura K (2011) Hydraulic function contributes to the variation in shoot morphology within the crown in Quercuscrispula. Tree Physiol 31:774–781.  https://doi.org/10.1093/treephys/tpr060 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Olivier Taugourdeau
    • 1
    • 2
    • 3
  • Sylvain Delagrange
    • 1
    • 2
    • 3
    Email author
  • Bastien Lecigne
    • 1
    • 3
  • Rita Sousa-Silva
    • 2
    • 3
  • Christian Messier
    • 1
    • 2
    • 3
  1. 1.Chaire CNRSG/Hydro-Québec, Département des Sciences BiologiquesUniversité du Québec à MontréalMontréalCanada
  2. 2.Institut des Sciences de la Forêt TempéréeUniversité du Québec en OutaouaisRiponCanada
  3. 3.Centre d’Étude de la ForêtMontréalCanada

Personalised recommendations