Trees

, Volume 27, Issue 4, pp 913–925 | Cite as

Effect of ring width, cambial age, and climatic variables on the within-ring wood density profile of Norway spruce Picea abies (L.) Karst.

  • Tony Franceschini
  • Fleur Longuetaud
  • Jean-Daniel Bontemps
  • Olivier Bouriaud
  • Benoît-Damien Caritey
  • Jean-Michel Leban
Original Paper

Abstract

Studying the effects of dendrometric and climatic variables on within-ring density variations needs flexible and interpretable models. We described the within-ring density profile using a piecewise linear regression and studied its dependence on (1) dendrometric variables such as cambial age (CA) and ring width (RW), and (2) climatic variables. Based on X-ray analysis of 5,191 Norway spruce rings, a six-parameter three-segmented model was fitted on each within-ring density profile. Each model parameter was related to dendrometric and climatic variables using multiple linear regressions. Then, these models were assembled in two models relating the within-ring density profile to (1) RW and CA (model M1), and (2) climatic variables (model M2). M1 showed an R2 of 83.4 % and a residual standard error of 68.5 kg m−3. Larger rings were associated with a decrease of latewood proportion and mean ring density. Rings with high CA were characterised by high maximum ring density. M2 showed an R2 of 60.9 % and a residual standard error of 94.9 kg m−3. Warm summers increased the maximum ring density. Years with favourable water status decreased mean ring density. The piecewise linear models allowed the classification of within-ring density profiles in three types. Considering CA and RW led to the most explicative model since RW described many processes such as silviculture or climate. Earlywood density was impacted by water status while latewood density was conditioned by both temperatures and water status. Our approach may be used for the identification of within-ring density fluctuations or to assess the effects of silviculture or global change on the within-ring density profile.

Keywords

Wood density Piecewise linear regression Climate Dendrometric variables Conifers 

Abbreviations

D

Within-ring density

EW

Earlywood

TW

Transitionwood

LW

Latewood

CA

Cambial age

RW

Ring width

x

Relative position in the ring

Dmin

Parameter defining the minimum within-ring density

a0

Parameter defining the slope of EW

a1

Parameter defining the slope of TW

a2

Parameter defining the slope of LW

Dmax

Parameter defining the maximum within-ring density

x1

Parameter defining the relative position of the limit between EW and TW

x2

Parameter defining the relative position of the limit between TW and LW

Dmin0, Dmin1, Dmin2

Parameters of the model M1.1

a00, a01

Parameters of the model M1.2

a10, a11, a12

Parameters of the model M1.3

Dmax0, Dmax1, Dmax2, Dmax3

Parameters of the model M1.4

x10, x11

Parameters of the model M1.5

x20, x21

Parameters of the model M1.6

ε

Residuals of models

RMSE

Root mean square error

TN

Monthly minimum temperature

TX

Monthly maximum temperature

SWc

Soil water content

SWd

Soil water deficit

Supplementary material

468_2013_844_MOESM1_ESM.docx (325 kb)
Supplementary material 1 (DOCX 331 kb)

References

  1. Barbour RJ, Bergqvist G, Amundson C, Larsson B, Johnson JA (1997) New methods for evaluating intra-ring X-ray densitometry data: maximum derivative methods as compared to Mork’s index. In: Zhang SY et al (eds) CTIA/IUFRO international wood quality workshop proceedings, 18–22 August 1997, Québec City, Québec, pp II61–II67Google Scholar
  2. Bontemps JD (2006) Évolution de la productivité des peuplements réguliers et monospécifiques de hêtre (Fagus sylvatica L.) et de chêne sessile (Quercus petraea Liebl.) dans la moitié Nord de la France au cours du XX° siècle. Nancy, ENGREF. PhD DissertationGoogle Scholar
  3. Bouffier L, Rozenberg P, Raffin A, Kremer A (2008) Wood density variability in successive breeding populations of maritime pine. Can J For Res 38(8):2148–2158CrossRefGoogle Scholar
  4. Bouriaud O, Leban JM, Bert D, Deleuze C (2005) Intra-annual variations in climate influence growth and wood density of Norway spruce. Tree Physiol 25(6):651–660PubMedCrossRefGoogle Scholar
  5. Brandstrom J (2001) Micro- and ultrastructural aspects of Norway spruce tracheids: a review. IAWA J 22(4):333–353CrossRefGoogle Scholar
  6. Bruand A, Fernandez PN, Duval O (2003) Use of class pedotransfer functions based on texture and bulk density of clods to generate water retention curves. Soil Use Manag 19(3):232–242CrossRefGoogle Scholar
  7. Caussinus H, Mestre O (2004) Detection and correction of artificial shifts in climate series. J R Stat Soc Ser C Appl Stat 53(3):405–425CrossRefGoogle Scholar
  8. Crawley MJ (2007) The R book. Wiley, New YorkCrossRefGoogle Scholar
  9. Cuny EH, Rathgeber CBK, Lebourgeois F, Fortin M, Fournier M (2012) Life strategies in intra-annual dynamics of wood formation: example of three conifer species in a temperate forest in north-east France. Tree Physiol 32(5):612–625PubMedCrossRefGoogle Scholar
  10. de Luis M, Novak K, Raventós J, Gricar J, Prislan P, Cufar K (2011) Climate factors promoting intra-annual density fluctuations in Aleppo pine (Pinus halepensis) from semiarid sites. Dendrochronologia 29(3):163–169CrossRefGoogle Scholar
  11. Decoux V, Varcin E, Leban JM (2004) Relationships between the intra-ring wood density assessed by X-ray densitometry and optical anatomical measurements in conifers. Consequences for the cell wall apparent density determination. Ann For Sci 61(3):251–262CrossRefGoogle Scholar
  12. Deleuze C, Houllier F (1998) A simple process-based xylem growth model for describing wood microdensitometric profiles. J Theor Biol 193(1):99–113CrossRefGoogle Scholar
  13. Deslauriers A, Morin H, Begin Y (2003) Cellular phenology of annual ring formation of Abies balsamea in the Quebec boreal forest (Canada). Can J For Res 33(2):190–200CrossRefGoogle Scholar
  14. Deslauriers A, Rossi S, Anfodillo T, Saracino A (2008) Cambial phenology, wood formation and temperature thresholds in two contrasting years at high altitude in southern Italy. Tree Physiol 28(6):863–871PubMedCrossRefGoogle Scholar
  15. Duplat P, Tran-Ha M (1997) Modelling the dominant height growth of sessile oak (Quercus petraea Liebl) in France. Inter-regional variability and effect of the recent period (1959–1993). Ann Sci For 54(7):611–634CrossRefGoogle Scholar
  16. Franceschini T, Bontemps JD, Gelhaye P, Rittie D, Herve JC, Gegout JC, Leban JM (2010) Decreasing trend and fluctuations in the mean ring density of Norway spruce through the twentieth century. Ann For Sci 67(8):816 10pCrossRefGoogle Scholar
  17. Franceschini T, Bontemps J-D, Leban J-M (2012a) Transient historical decrease in earlywood and latewood density and unstable sensitivity to summer temperature for Norway spruce in northeastern France. Can J For Res 42(2):219–226CrossRefGoogle Scholar
  18. Franceschini T, Lundqvist S-O, Bontemps J-D, Grahn T, Olsson L, Evans R, Leban J-M (2012b) Empirical models for radial and tangential fibre width in tree rings of Norway spruce in north-western Europe. Holzforschung 66(2):219–230CrossRefGoogle Scholar
  19. Fritts HC, Vaganov EA, Sviderskaya IV, Shashkin AV (1991) Climatic variation and tree-ring structure in conifers: empirical and mechanistic models of tree-ring width, number of cells, cell size, cell-wall thickness and wood density. Clim Res 1:97–116CrossRefGoogle Scholar
  20. Fujimoto T, Kita K, Kuromaru M (2008) Genetic control of intra-ring wood density variation in hybrid larch (Larix gmelinii var. japonica × L. kaempferi) F1. Wood Sci Technol 42(3):227–240CrossRefGoogle Scholar
  21. Gerendiain AZ, Peltola H, Pulkkinen P, Jaatinen R, Pappinen A, Kellomaki S (2007) Differences in growth and wood property traits in cloned Norway spruce (Picea abies). Can J For Res 37(12):2600–2611CrossRefGoogle Scholar
  22. Gindl W, Grabner M, Wimmer R (2000) The influence of temperature on latewood lignin content in treeline Norway spruce compared with maximum density and ring width. Trees Struct Funct 14(7):409–414CrossRefGoogle Scholar
  23. Gricar J, Cufar K (2008) Seasonal dynamics of phloem and xylem formation in silver fir and Norway spruce as affected by drought. Russ J Plant Physiol 55(4):538–543CrossRefGoogle Scholar
  24. Hughes MK (2002) Dendrochronology in climatology: the state of the art. Dendrochronologia 20(1–2):95–116CrossRefGoogle Scholar
  25. Hughes MK, Schweingruber FH, Cartwright D, Kelly PM (1984) July–August temperature at Edinburgh between 1721 and 1975 from tree-ring density and width data. Nature 308(5957):341–344CrossRefGoogle Scholar
  26. Ikonen VP, Peltola H, Wilhelmsson L, Kilpelainen A, Vaisanen H, Nuutinen T, Kellomaki S (2008) Modelling the distribution of wood properties along the stems of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) as affected by silvicultural management. For Ecol Manag 256(6):1356–1371CrossRefGoogle Scholar
  27. Ivkovich M, Rozenberg P (2004) A method for describing and modelling of within-ring wood density distribution in clones of three coniferous species. Ann For Sci 61(8):759–769CrossRefGoogle Scholar
  28. Jaakkola T, Makinen H, Saranpaa P (2005) Wood density in Norway spruce: changes with thinning intensity and tree age. Can J For Res 35(7):1767–1778CrossRefGoogle Scholar
  29. Jyske T, Makinen H, Saranpaa P (2008) Wood density within Norway spruce stems. Silva Fennica 42(3):439–455Google Scholar
  30. Jyske T, Holtta T, Makinen H, Nojd P, Lumme I, Spiecker H (2010) The effect of artificially induced drought on radial increment and wood properties of Norway spruce. Tree Physiol 30(1):103–115PubMedCrossRefGoogle Scholar
  31. Kantavichai R, Briggs D, Turnblom E (2010) Modeling effects of soil, climate, and silviculture on growth ring specific gravity of Douglas-fir on a drought-prone site in Western Washington. For Ecol Manag 259(6):1085–1092CrossRefGoogle Scholar
  32. Kirdyanov A, Hughes M, Vaganov E, Schweingruber F, Silkin P (2003) The importance of early summer temperature and date of snow melt for tree growth in the Siberian Subarctic. Trees Struct Funct 17(1):61–69CrossRefGoogle Scholar
  33. Kostiainen K, Kaakinen S, Saranpaa P, Sigurdsson BD, Lundqvist SO, Linder S, Vapaavuori E (2009) Stem wood properties of mature Norway spruce after 3 years of continuous exposure to elevated CO2 and temperature. Glob Chang Biol 15(2):368–379CrossRefGoogle Scholar
  34. Koubaa A, Zhang SYT, Makni S (2002) Defining the transition from earlywood to latewood in black spruce based on intra-ring wood density profiles from X-ray densitometry. Ann For Sci 59(5–6):511–518CrossRefGoogle Scholar
  35. Leban JM (1999) Un modèle de profil microdensitométrique pour le Cèdre de l’Atlas. In: Dreyfus PH (ed) Rapport final de la convention DERF-INRA n°01.40.27/98: Modélisation: croissance, branchaison, qualité des bois et intégration logicielle, p 23–30Google Scholar
  36. Leban JM, Houllier F (1992) Modelling the microdensitometric curves in Norway spruce taking into account intra and intertree variability. In: IUFRO All Division 5 Conference Forest Products, Nancy, 23–28 August 1992. ARBOLOR ed. Nancy, pp 309–310Google Scholar
  37. Lebourgeois F, Breda N, Ulrich E, Granier A (2005) Climate-tree-growth relationships of European beech (Fagus sylvatica L.) in the French Permanent Plot Network (RENECOFOR). Trees Struct Funct 19(4):385–401CrossRefGoogle Scholar
  38. Lenz P, Cloutier A, MacKay J, Beaulieu J (2010) Genetic control of wood properties in Picea glauca: an analysis of trends with cambial age. Can J For Res 40(4):703–715CrossRefGoogle Scholar
  39. Lundgren C (2004) Microfibril angle and density patterns of fertilized and irrigated Norway spruce. Silva Fennica 38(1):107–117Google Scholar
  40. Makinen H, Saranpaa P, Linder S (2002) Wood-density variation of Norway spruce in relation to nutrient optimization and fibre dimensions. Can J For Res 32(2):185–194CrossRefGoogle Scholar
  41. Makinen H, Jaakkola T, Piispanen R, Saranpaa P (2007) Predicting wood and tracheid properties of Norway spruce. For Ecol Manag 241(1–3):175–188CrossRefGoogle Scholar
  42. Meinzer FC, Lachenbruch B, Dawson TE (2011) Size- and age-related changes in tree structure and function. Springer, BerlinCrossRefGoogle Scholar
  43. Moisselin J-M, Schneider M, Canellas C, Mestre O (2002) Changements climatiques en France au XXe siècle. Étude de longues séries de données homogénéisées françaises de précipitations et températures. La Météorologie 38:45–56CrossRefGoogle Scholar
  44. Mothe F, Duchanois G, Zannier B, Leban J-M (1998) Analyse microdensitométrique appliquée au bois : méthode de traitement des données utilisée à l’Inra-ERQB (programme Cerd). Ann Sci For 55(3):301–313CrossRefGoogle Scholar
  45. Neuwirth B, Esper J, Schweingruber FH, Winiger M (2004) Site ecological differences to the climatic forcing of spruce pointer years from the Lötschental, Switzerland. Dendrochronologia 21(2):69–78CrossRefGoogle Scholar
  46. Nilsson U (1994) Development of growth and stand structure in Picea abies stands planted at different initial densities. Scand J For Res 9(2):135–142CrossRefGoogle Scholar
  47. Nocetti M, Rozenberg P, Chaix G, Macchioni N (2011) Provenance effect on the ring structure of teak (Tectona grandis L.f.) wood by X-ray microdensitometry. Ann For Sci 68(8):1375–1383CrossRefGoogle Scholar
  48. Olano JM, Eugenio M, Garcia-Cervigon AI, Folch M, Rozas V (2012) Quantitative tracheid anatomy reveals a complex environmental control of wood structure in continental Mediterranean climate. Int J Plant Sci 173(2):137–149CrossRefGoogle Scholar
  49. Olesen PO (1977) The variation of the basic density level and tracheid width within the juvenile and mature wood of Norway spruce. For Tree Improv 12:1–22Google Scholar
  50. Park Y-ID, Spiecker H (2005) Variations in the tree-ring structure of Norway spruce (Picea abies) under contrasting climates. Dendrochronologia 23(2):93–104CrossRefGoogle Scholar
  51. Park Y-ID, Dallaire G, Morin H (2006) A method for multiple intra-ring demarcation of coniferous trees. Ann For Sci 63(1):9–14CrossRefGoogle Scholar
  52. Pernestal K, Jonsson B, Larsson B (1995) A simple-model for density of annual rings. Wood Sci Technol 29(6):441–449CrossRefGoogle Scholar
  53. Piedallu C, Gegout JC (2007) Multiscale computation of solar radiation for predictive vegetation modelling. Ann For Sci 64(8):899–909CrossRefGoogle Scholar
  54. Rathgeber CBK, Decoux V, Leban JM (2006) Linking intra-tree-ring wood density variations and tracheid anatomical characteristics in Douglas fir (Pseudotsuga menziesii (Mirb.) Franco). Ann For Sci 63(7):699–706CrossRefGoogle Scholar
  55. R Development Core Team (2011) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. URL:http://www.R-project.org
  56. Rossi S, Deslauriers A, Gricar J, Seo JW, Rathgeber CBK, Anfodillo T, Morin H, Levanic T, Oven P, Jalkanen R (2008) Critical temperatures for xylogenesis in conifers of cold climates. Glob Ecol Biogeogr 17(6):696–707CrossRefGoogle Scholar
  57. Rozas V, Garcia-Gonzalez I, Zas R (2011) Climatic control of intra-annual wood density fluctuations of Pinus pinaster in NW Spain. Trees Struct Funct 25(3):443–453CrossRefGoogle Scholar
  58. Rozenberg P, Franc A, Cahalan C (2001) Incorporating wood density in breeding programs for softwoods in Europe: a strategy and associated methods. Silvae Genet 50(1):1–7Google Scholar
  59. Rozenberg P, Schüte G, Ivkovich M, Bastien C, Bastien JC (2004) Clonal variation of indirect cambium reaction to within-growing season temperature changes in Douglas-fir. Forestry 77(4):257–268CrossRefGoogle Scholar
  60. Saint-Germain JL, Krause C (2008) Latitudinal variation in tree-ring and wood cell characteristics of Picea mariana across the continuous boreal forest in Quebec. Can J For Res 38(6):1397–1405CrossRefGoogle Scholar
  61. Sanchez-Vargas NM, Sanchez L, Rozenberg P (2007) Plastic and adaptive response to weather events: a pilot study in a maritime pine tree ring. Can J For Res 37(11):2090–2095CrossRefGoogle Scholar
  62. Schweingruber FH (1989) Tree rings. Basics and applications of dendrochronology. Kluwer, DordrechtGoogle Scholar
  63. Turc L (1955) Le bilan d’eau des sols: relations entre les précipitations, l’évaporation et l’écoulement. Ann Agron 6(1):3–133Google Scholar
  64. Vargas-Hernandez J, Adams WT (1991) Genetic variation of wood density components in young coastal Douglas-fir: implications for tree breeding. Can J For Res 21(12):1801–1807CrossRefGoogle Scholar
  65. Wang L, Payette S, Begin Y (2002) Relationships between anatomical and densitometric characteristics of black spruce and summer temperature at tree line in northern Quebec. Can J For Res 32(3):477–486CrossRefGoogle Scholar
  66. Wei C, Lintilhac PM (2007) Loss of stability: a new look at the physics of cell wall behavior during plant cell growth. Plant Physiol 145(3):763–772PubMedCrossRefGoogle Scholar
  67. Wimmer R, Grabner M (2000) A comparison of tree-ring features in Picea abies as correlated with climate. IAWA J 21(4):403–416CrossRefGoogle Scholar
  68. Yasue K, Funada R, Kobayashi O, Ohtani J (2000) The effects of tracheid dimensions on variations in maximum density of Picea glehnii and relationships to climatic factors. Trees Struct Funct 14(4):223–229CrossRefGoogle Scholar
  69. Zobel BJ, van Buijtenen JP (1989) Wood variation: its causes and control. Springer, Berlin GermanyCrossRefGoogle Scholar
  70. Zweifel R, Zimmermann L, Zeugin F, Newbery DM (2006) Intra-annual radial growth and water relations of trees: implications towards a growth mechanism. J Exp Bot 57(6):1445–1459PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tony Franceschini
    • 2
    • 3
  • Fleur Longuetaud
    • 2
  • Jean-Daniel Bontemps
    • 1
  • Olivier Bouriaud
    • 4
  • Benoît-Damien Caritey
    • 2
  • Jean-Michel Leban
    • 2
    • 3
  1. 1.AgroParisTech, ENGREFUMR 1092 Laboratoire d’Etude des Ressources Foret Bois (LERFob)NancyFrance
  2. 2.INRA, Centre de NancyUMR 1092 Laboratoire d’Etude des Ressources Foret Bois (LERFoB)ChampenouxFrance
  3. 3.ENSTIB, LERMaBUniversité de LorraineEpinalFrance
  4. 4.Forest Research and Management Institute-ICASCampulung MoldovenescRomania

Personalised recommendations