Advertisement

Trees

, Volume 22, Issue 1, pp 87–104 | Cite as

Modelling foliage characteristics in 3D tree crowns: influence on light interception and leaf irradiance

  • Claude-Eric Parveaud
  • Jérôme Chopard
  • Jean Dauzat
  • Benoît Courbaud
  • Daniel AuclairEmail author
Original Paper

Abstract

Because of the difficulty and time involved in making exhaustive measurements of the geometric parameters of large tree crowns, simplifying hypotheses are often used in 3D virtual plant modelling, but the effects on the radiation balance of each approximation are rarely assessed. Three hybrid walnut trees aged 7–9 years were digitized to analyse the effect of the crown geometric variables on light capture. The six studied variables were: (1) leaf area, (2) number of leaves per annual shoot, (3) position of leaves, (4) orientation of leaves, (5) leaflet inclination, and (6) lamina shape. For each variable, a sensitivity analysis compared a reference, based on observed values, with scenarios consisting of simplifying hypotheses. The total incident light intercepted during a bright day and the distributions of leaf irradiance were calculated using the Archimed radiative transfer model. Since some of the crown parameters were generated stochastically, the radiation simulations were repeated until results stabilised. Simplified models can be used to calculate with satisfactory results individual leaf area and number of leaves per shoot. Conversely, differentiating statistical distributions of individual leaf area between short and long shoots is more difficult and may generate errors up to 30%. Leaf clumping is a determining factor and requires correct grouping of leaves around the annual shoots bearing them. The effect of position of leaves along the shoot is less than 2%. Simple statistical distributions are adequate for representing leaf angle. Finally, the effect of specific leaf geometry is very important, but it can be approached using a limited number of representative leaf shapes.

Keywords

Sensitivity analysis Leaf irradiance Crown reconstruction Leaf clumping Juglans regia × nigra 

Abbreviations

C1

Crown number 1 (614 leaves)

C2

Crown number 2 (2 397 leaves)

C3

Crown number 3 (4 943 leaves)

xi, yi, zi

Spatial coordinates of leaf i

Aij

Leaf surface area of the leaf i on annual shoot j (cm2)

Lj

Length of the annual shoot j (cm)

Rij

Relative rank of node i on shoot j

Nj

Number of leaves on the annual shoot j

Dj

Basal diameter of the annual shoot j (cm)

Pni,j

Relative position of the ith node on the annual shoot j

Nleaflet

Number of leaflets on a leaf

LAD

Leaf area density (m2 m−3)

Ei

Leaf irradiance (μmols m−2 s−1) for leaf number i

IPAR

Total photosynthetic active radiation intercepted by a crown (mols s−1)

rPPFD

Relative photosynthetic photon flux density distribution (%)

\( \overline{{{\text{STAR}}}} \)

Silhouette to total area ratio integrated on the sky vault

Greek letters

ψ

Azimuth angle of average leaf plane (degrees)

θ

Elevation angle of average leaf plane (degrees)

ϕ

Roll angle of average leaf plane (degrees)

α

Leaf normal inclination (degrees)

εi

Light interception efficiency of a crown

λleaflet

Angle between two leaflets with the same point of attachment (degrees)

Notes

Acknowledgments

The authors are very grateful to Michaël Guéroult, Lydie Dufour and Sylvie Sabatier who helped for topological and geometric plant observations and measurements. Sylvie Sabatier made her data on internode length available. Christian Dupraz coordinated the SAFE project and the Restinclières agroforestry experimental site and contributed to discussions. We also thank Hervé Sinoquet and Évelyne Costes and two anonymous reviewers for their helpful comments and advice on the first version of the manuscript. This study was partly supported by the SAFE project (Silvoarable Agroforestry For Europe, E.U. contract QLK5-CT-2001-00560) and by a joint Ph.D. grant from the Région Languedoc-Roussillon and INRA. AMAP (Botany and Computational Plant Architecture) is a joint research unit which associates CIRAD (UMR51), CNRS (UMR5120), INRA (UMR931), IRD (R123), and Montpellier 2 University (UM27); http://www.amap.cirad.fr/

References

  1. Adam B (1999) POL95: software to drive a Polhemus Fastrak 3 SPACE 3D digitiser. Version 1.0. UMR PIAF INRA-UBP, Clermont-Ferrand, FRGoogle Scholar
  2. Ashton PMS, Olander LP, Berlyn GP, Thadani R, Cameron IR (1997) Changes in leaf structure in relation to crown position and tree size of Betula papyrifera within fire-origin stands of interior cedar-hemlock. Can J Bot 76:1180–1187CrossRefGoogle Scholar
  3. Balandier P, Lacointe A, Le Roux X, Sinoquet H, Cruiziat P, Le Dizès S (2000) SIMWAL: a structural–functional model simulating single walnut tree growth in response to climate and pruning. Ann For Sci 57:571–585CrossRefGoogle Scholar
  4. Barczi JF, de Reffye P, Caraglio Y (1997) Essai sur l’identification et la mise en ouvre des paramètres nécessaires à la simulation d’une architecture végétale. In: Bouchon J, de Reffye P, Barthélémy D (eds) Modélisation et simulation de l’architecture des végétaux. Science Update. INRA, Versailles, FR, pp 205–254Google Scholar
  5. Barthélémy D, Caraglio Y (2007) Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny. Ann Bot 99:375–407PubMedCrossRefGoogle Scholar
  6. Boudon F, Nouguier C, Godin C (2001) GEOM module manual. I. User guide. CIRAD, Montpellier, FRGoogle Scholar
  7. Brown PL, Doley D, Keenan RJ (2000) Estimating tree crown dimensions using digital analysis of vertical photographs. Agric For Meteorol 100:199–212CrossRefGoogle Scholar
  8. Casella E, Sinoquet H (2003) A method for describing the canopy architecture of coppice poplar with allometric relationships. Tree Physiol 23:1153–1169PubMedGoogle Scholar
  9. Chelle M (2005) Phylloclimate or the climate perceived by individual plant organs: What is it? How to model it? What for? New Phytol 166:781–790PubMedCrossRefGoogle Scholar
  10. Chenu K, Franck N, Dauzat J, Barczi JF, Rey H, Lecoeur J (2005) Integrated responses of rosette organogenesis, morphogenesis and architecture to reduced incident light in Arabidopsis thaliana results in higher efficiency of light interception. Funct Plant Biol 32:1123–1134CrossRefGoogle Scholar
  11. Dauzat J, Eroy MN (1997) Simulating light regime and intercrop yields in a coconut based farming system. Eur J Agron 7:63–74CrossRefGoogle Scholar
  12. Dauzat J, Rapidel B, Berger A (2001) Simulation of leaf transpiration and sap flow in virtual plants: model description and application to a coffee plantation in Costa Rica. Agric Forest Meteorol 109:143–160CrossRefGoogle Scholar
  13. de Castro F, Fetcher N (1998) Three dimensional model of the interception of light by a canopy. Agric Forest Meteorol 90:215–233CrossRefGoogle Scholar
  14. de Castro F, Fetcher N (1999) The effect of leaf clustering in the interception of light in vegetal canopies : theoretical considerations. Ecol Model 116:125–134CrossRefGoogle Scholar
  15. de Wit CT (1965) Photosynthesis of leaf canopies. Agric Res Rep 663, Wageningen, NLGoogle Scholar
  16. den Dulk JA (1989) The interpretation of remote sensing, a feasibility study. WAU dissertation 1265, Wageningen, NLGoogle Scholar
  17. Eschenbach C (2005) Emergent properties modelled with the functional structural tree growth model ALMIS: Computer experiments on resource gain and use. Ecol Model 186:470–488CrossRefGoogle Scholar
  18. Falster DS, Westoby M (2003) Leaf size and angle vary widely across species: what consequences for light interception? New Phytol 158:509–525CrossRefGoogle Scholar
  19. Farque L, Sinoquet H, Colin F (2001) Canopy structure and light interception in Quercus petraea seedlings in relation to light regime and plant density. Tree Physiol 21:1257–1267PubMedGoogle Scholar
  20. Fleck S, Niinemets U, Cescatti A, Tenhunen JD (2003) Three-dimensional lamina architecture alters light-harvesting efficiency in Fagus: a leaf-scale analysis. Tree Physiol 23:577–589PubMedGoogle Scholar
  21. Fraser GW, Canham CD, Lertzman KP (1999) Gap Light Analyser (GLA), Version 2.0: imaging software to extract canopy structure and gap light indices from true-colour fisheye photographs, Users manual and program documentation. Simon Fraser University, Burnaby, BC, and Inst Ecosyst Stud, Millbrook, NY, USAGoogle Scholar
  22. Giuliani R, Magnanini E, Fracassa C, Nerozzi F (2000) Ground monitoring the light-shadow windows of a tree canopy to yield canopy light interception and morphological traits. Plant Cell Environ 23:783–796CrossRefGoogle Scholar
  23. Giuliani R, Magnanini E, Nerozzi F, Muzzi E, Sinoquet H (2005) Canopy probabilistic reconstruction inferred from Monte Carlo point-intercept leaf sampling. Agric Forest Meteorol 128:17–32CrossRefGoogle Scholar
  24. Godin C, Caraglio Y (1998) A multiscale model of plant topological structures. J Theor Biol 191:1–46PubMedCrossRefGoogle Scholar
  25. Godin C, Costes E, Caraglio Y (1997) Exploring plant topological structure with the AMAPmod software: an outline. Silva Fenn 31:355–366Google Scholar
  26. Godin C, Costes E, Sinoquet H (1999) A method for describing plant architecture which integrates topology and geometry. Ann Bot 84:343–357CrossRefGoogle Scholar
  27. Godin C, Sinoquet H (2005) Functional–structural plant modelling. New Phytol 166:705–708PubMedCrossRefGoogle Scholar
  28. Green S, McNaughton K, Wünsche JN, Clothier B (2003) Modeling light interception and transpiration of Apple tree canopies. Agron J 95:1380–1387CrossRefGoogle Scholar
  29. Hallé F, Oldeman RAA, Tomlinson PB (1978) Tropical trees and forests. An architectural analysis. Springer, BerlinGoogle Scholar
  30. Hanan J (1997) Virtual plants—integrating architectural and physiological models. Environ Model Softw 12:35–42CrossRefGoogle Scholar
  31. Hanan J, Wang YP (2004) Floradig: a configurable program for capturing plant architecture. In: Godin C, Hanah J, Kurth W, Lacointe A, Takenaka A, Prusinkiewicz P, de Jong T, Beveridge C, Andrieu B (eds) 4th International Workshop on Functional-Structural Plant Models, Montpellier, pp 407Google Scholar
  32. Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graph Stat 5:299–314CrossRefGoogle Scholar
  33. Kellomäki S, Strandman H (1995) A model for the structural growth of young Scots pine crowns based on light interception by shoots. Ecol Model 80:237–250CrossRefGoogle Scholar
  34. Massonnet C (2004) Variabilité architecturale et fonctionnelle du système aérien chez le pommier (Malus × domestica Borkh.): comparaison de quatre cultivars par une approche de modélisation structure-fonction. Thesis, Université Montpellier II, MontpellierGoogle Scholar
  35. Nicolini E, Chanson B (1999) La pousse courte, un indicateur du degré de maturation chez le hêtre (Fagus sylvatica L.). Can J Bot 77:1539–1550CrossRefGoogle Scholar
  36. Niinemets U (1998) Are compound-leaved woody species inherently shade-tolerant? An analysis of species ecological requirements and foliar support costs. Plant Ecol 134:1–11CrossRefGoogle Scholar
  37. Oker-Blom P, Kellomäki S (1983) Effect of grouping of foliage on the within stand and within-crown light regime: comparison of random and grouping canopy models. Agric For Meteorol 28:143–155CrossRefGoogle Scholar
  38. Oker-Blom P, Smolander H (1988) The ratio of shoot silhouette area to total needle area in Scots pine. For Sci 34:894–906Google Scholar
  39. Pearcy RW, Yang W (1996) A three-dimensional crown architecture model for assessment of light capture and carbon gain by understory plants. Oecologia 108:1–12CrossRefGoogle Scholar
  40. Pearcy RW, Muraoka H, Valladares F (2005) Crown architecture in sun and shade environments: assessing function and trade-offs with a three-dimensional simulation model. New Phytol 166:791PubMedCrossRefGoogle Scholar
  41. Phattaralerphong J, Sinoquet H (2005) A method for 3D reconstruction of tree crown volume from photographs: assessment with 3D-digitized plants. Tree Physiol 25:1229–1242PubMedGoogle Scholar
  42. Planchais I (1998) Modélisation de la croissance et de l’architecture du jeune Hêtre (Fagus sylvatica L.): effet de l’éclairement. Thesis, Université Paris XI, OrsayGoogle Scholar
  43. Planchais I, Sinoquet H (1998) Foliage determinants of light interception in sunny and shaded branches of Fagus sylvatica (L.). Agric For Meteorol 89:241–253CrossRefGoogle Scholar
  44. Polhemus Inc (1993) 3SPACE FASTRAK, User Manual, Revision F. Colchester, VT, USAGoogle Scholar
  45. Pradal C, Dones N, Godin C, Barbier de Reuille P, Boudon F, Adam B, Sinoquet H (2004) ALEA: a software for integrating analysis and simulation tools for 3D architecture and ecophysiology. In: Godin C, Hanah J, Kurth W, Lacointe A, Takenaka A, Prusinkiewicz P, de Jong T, Beveridge C, Andrieu B (eds) 4th International workshop on functional–structural plant models, Montpellier, pp 406Google Scholar
  46. Richardson AD, Berlyn GP, Ashton PMS, Thadani R, Cameron IR (1999) Foliar plasticity of hybrid spruce in relation to crown position and stand age. Can J Bot 78:305–317CrossRefGoogle Scholar
  47. Sabatier S (1999) Variabilité morphologique et architecturale de deux espèces de noyers : Juglans regia L., Juglans nigra L. et de deux espèces de noyers hybrides interspécifiques. Thesis, Université Montpellier II, MontpellierGoogle Scholar
  48. Sabatier S, Barthélémy D (2001) Annual shoot morphology and architecture in Persian Walnut, Juglans regia L. (Juglandaceae). Acta Hortic 544:255–264Google Scholar
  49. Sievänen R, Nikinmaa E, Nygren P, Ozier-Lafontaine H, Perttunen J, Hakula H (2000) Components of functional-structural tree models. Ann For Sci 57:399–412CrossRefGoogle Scholar
  50. Sekimura T (1995) The diversity in shoot morphology of herbaceous plants in relation to solar radiation captured by leaves. J Theor Biol 177:289–297CrossRefGoogle Scholar
  51. Shlyakhter I, Rozenoer M, Dorsey J, Teller S (2001) Reconstructing 3D tree models from instrumented photographs. IEEE Comput Graph 21:53–61CrossRefGoogle Scholar
  52. Sinoquet H, Rivet P (1997) Measurement and visualization of the architecture of an adult tree based on a three-dimensional digitising device. Trees 11:265–270CrossRefGoogle Scholar
  53. Sinoquet H, Adam B, Rivet P, Godin C (1997) Interactions between light and plant architecture in an agroforestry walnut tree. Agroforestry forum 8:37–40Google Scholar
  54. Sinoquet H, Thanisawanyangkura S, Mabrouk H, Kasemsap P (1998) Characterisation of light interception in canopies using 3D digitising and image processing. Ann Bot 82:203–212CrossRefGoogle Scholar
  55. Sinoquet H, Sonohat G, Phattaralerphong J, Godin C (2005) Foliage randomness and light interception in 3D digitised trees: an analysis from multiscale discretisation of the canopy. Plant Cell Environ 28:1158–1170CrossRefGoogle Scholar
  56. Sinoquet H, Le Roux X, Adam B, Ameglio T, Daudet FA (2001) RATP, a model for simulating the spatial distribution of radiation absorption, transpiration and photosynthesis within canopies: application to an isolated tree crown. Plant Cell Environ 24:395–406CrossRefGoogle Scholar
  57. Sonohat G, Sinoquet H, Kulandaivelu V, Combes D, Lescourret F (2006) Three-dimensional reconstruction of partially 3D-digitised peach tree canopies. Tree Physiol 26:337–351PubMedCrossRefGoogle Scholar
  58. Sonohat G, Sinoquet H, Varlet-Grancher C, Rakocevic M, Jacquet A, Simon JC, Adam B (2002) Leaf dispersion and light partitioning in three-dimensionally digitized tall fescue-white clover mixtures. Plant Cell Environ 25:529–538CrossRefGoogle Scholar
  59. Sterck FJ, Schieving F, Lemmens A, Pons TL (2005) Performance of trees in forest canopies: explorations with a bottom-up functional-structural plant growth model. New Phytol 166:827–843PubMedCrossRefGoogle Scholar
  60. Takafumi T, Yamaguchi J, Takeda Y (1998) Measurements of forest canopy structure with laser plane range-finding method—development of a measurement system and applications to real forests. Agric For Meteorol 91:149–160CrossRefGoogle Scholar
  61. Takenaka A (1994) Effects of leaf blade narrowness and petiole length on the light capture efficiency of a shoot. Ecol Res 9:109–114CrossRefGoogle Scholar
  62. Takenaka A, Inui Y, Osawa A (1998) Measurements of three-dimensional structure of plants with a simple device and estimation of light capture of individual leaves. Funct Ecol 12:159–165CrossRefGoogle Scholar
  63. Tappeiner U, Cernusca A (1998) Model simulation of spatial distribution of photosynthesis in structurally differing plant communities in the Central Caucasus. Ecol Model 113:201–223CrossRefGoogle Scholar
  64. Thanisawanyangkura S, Sinoquet H, Rivet P, Cretenet M, Jallas E (1997) Leaf orientation and sunlit leaf area distribution in cotton. Agric For Meteorol 86:1–15CrossRefGoogle Scholar
  65. Valladares F, Pearcy RW (1998) The functional ecology of shoot architecture in sun and shade plants of Heteromeles arbutifolia M. Roem., a Californian chaparral shrub. Oecologia 114:1–10CrossRefGoogle Scholar
  66. Vos J, Marcelis LFM, de Visser PHB, Struik PC, Evers JB (eds) (2007) Functional–structural plant modelling in crop production. Wageningen UR Frontis Series 22, Wageningen, NLGoogle Scholar
  67. Whitehead D, Grace J, Godfrey M (1990) Architectural distribution of foliage in individual Pinus radiata D. Don crowns and the effects of clumping on radiation interception. Tree Physiol 7:135–155PubMedGoogle Scholar
  68. Willaume M, Lauri PE, Sinoquet H (2004) Light interception in apple trees influenced by canopy architecture manipulation. Trees 18:705–713CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Claude-Eric Parveaud
    • 1
    • 2
  • Jérôme Chopard
    • 1
    • 3
  • Jean Dauzat
    • 4
  • Benoît Courbaud
    • 5
  • Daniel Auclair
    • 1
    • 6
    Email author
  1. 1.INRA, UMR AMAPMontpellierFrance
  2. 2.S.E.Nu.R.AChatteFrance
  3. 3.INRIA, UMR DAPMontpellierFrance
  4. 4.CIRAD, UMR AMAPMontpellierFrance
  5. 5.Cemagref, Unité de Recherche “Ecosystèmes Montagnards”Saint-Martin-d’HèresFrance
  6. 6.INRA, UMR AMAP (botAnique et bioinforMatique de l’Architecture des Plantes)Montpellier cedex 5France

Personalised recommendations