Skip to main content
Download PDF
  • Original Article
  • Published:

Mortality of silver fir and Norway Spruce in the Western Alps — a semi-parametric approach combining size-dependent and growth-dependent mortality

Mortalité du sapin pectiné et de l’épicea commmun dans les alpes occidentales — une approche semi-paramétrique combinant la mortalité dépendant de la taille et de la croissance

Annals of Forest Science volume 67, page 305 (2010)Cite this article

Abstract

Question

Tree mortality can be modeled using two complementary covariates, tree size and tree growth. Tree growth is an integrative measure of tree vitality while tree diameter is a good index of sensitivity to disturbances and can be considered as a proxy for tree age which may indicate senescence. Few mortality models integrate both covariates because classical model calibration requires large permanent plot data-sets which are rare. How then can we calibrate a multivariate mortality model including size and growth when permanent plots data are not available?

Location

To answer this question, we studied Abies alba and Picea abies mortality in the French Swiss and Italian Alps.

Method

Our study proposes an alternative semi-parametric method which includes a random sample of living and dead trees with diameter and growth measurements.

Results

We were able to calibrate a mortality model combining both size-dependent and growth-dependent mortality. We demonstrated that A. alba had a lower annual mortality rate (10%) than P. abies (18%) for low growth (< 0.2 mmyear−1). We also demonstrated that for higher diameters (DBH ≥ 70 cm), P. abies had a higher mortality rate (0.45%) than A. alba (0.32%).

Conclusion

Our results are consistent with the mechanisms of colonization-competition trade-off and of successional niche theory which may explain the coexistence of these two species in the Alps. The method we developed should be useful for forecasting tree mortality and can improve the efficiency of forest dynamics models.

Résumé

Question

Il est possible de modéliser la mortalité des arbres en utilisant deux covariables complémentaires : la taille et la croissance de l’arbre. La croissance est une mesure synthétique de la vitalité alors que le diamètre est un bon indicateur de la sensibilité aux perturbations et est très fortement corrélé à l’âge de l’arbre, qui détermine la sénescence. Peu de modèles de mortalité intègrent les deux covariables, car cela nécessite, pour les approches classiques, une calibration à partir de données de placettes permanentes qui sont rares. Comment obtenir un modèle de mortalité multivarié, incluant la taille et la croissance, lorsque des données de placettes permanentes ne sont pas disponibles?

Localisation géographique

Pour répondre à cette question, nous avons étudié la mortalité du sapin pectiné (Abies alba) et de l’epicéa commmun (Picea abies) dans les Alpes suisses françaises et italiennes.

Méthode

Notre étude propose une méthode semi-parametrique alternative s’appuyant sur un échantillon d’arbres morts et vivants avec des mesures de diamètre et de croissance.

Résultats

Nous avons obtenu un modèle combinant la mortalité dépendant à la fois de la taille et de la croissance. Nous avons démontré qu’A. alba avait un taux de mortalité inférieur (10 %) à celui de P. abies (18 %) pour une faible croissance (< 0.2 mman−1). De plus, pour de larges diamètres (DBH >- 70 cm), P. abies a un taux de mortalité supérieur (0.45 %) à A. alba (0.32 %).

Conclusion

Nos résultats sont en accord avec les mécanismes de niche de succession et de compromis entre colonisation et compétition qui sont invoqués pour expliquer la coexistence des deux espéces dans les Alpes. Notre méthode devrait contribuer à améliorer la prédiction du taux de mortalité et la précision des modèles de dynamique forestière.

Abbreviations

DBH:

Diameter at Breast Height (DBH = 1.30 m)

P. abies:

Picea abies (L.) Karst. (Norway Spruce)

A. alba:

Abies alba Mill. (Silver Fir)

NFI:

National Forest Inventory

References

  • Ayer M., Brunk H.D., Ewing G.M., Reid W.T., and Silverman E., 1955. An empirical distribution function for sampling with incomplete information. Ann. Math. Stat. 26: 641–647.

    Article  Google Scholar 

  • Bigler C. and Bugmann H., 2003. Growth-dependent tree mortality models based on tree-rings. Can. J. For. Res. 33: 210–221.

    Article  Google Scholar 

  • Bugmann H., 1994. On the ecology of mountainous forests in a changing climate: a simulation study. Ph.D. thesis, Swiss federal institute of technology, Zürich.

    Google Scholar 

  • Canham C.D., Papaik M.J., and Latty E.F., 2001. Interspecific variation in susceptibility to windthrow as a function of tree size and storm severity for northern temperate tree species. Can. J. For. Res. 31: 1–10.

    Article  Google Scholar 

  • Clark J.S., 1996. Testing disturbance theory with long-term data: Alternative life-history solutions to the distribution of events. Am. Nat. 148: 976–996.

    Article  Google Scholar 

  • Coomes D.A., Duncan R.P., Allen R.B., and Truscott J., 2003. Disturbances prevent stem size-density distributions in natural forests from following scaling relationships. Ecol. Lett. 6: 980–989.

    Article  Google Scholar 

  • Courbaud B., de Coligny F., and Cordonnier T., 2003. Simulating radiation distribution in a heterogeneous Norway spruce forest on a slope. Agric. For. Meteorol. 116: 1–18.

    Article  Google Scholar 

  • Das A., Battles J., van Mantgem P.J., and Stephenson N.L., 2008. Spatial elements of mortality risk in old-growth forests. Ecology 89: 1744–1756.

    Article  PubMed  Google Scholar 

  • Dobbertin M., 2005. Tree growth as indicator of tree vitality and of tree reaction to environmental stress: a review. Eur. J. For. Res. 124: 319–333.

    Google Scholar 

  • Dovčiak M., Hrivnák R., Ujházy K., and Gömöry D., 2008. Seed rain and environmental controls on invasion of Picea abies into grassland. Plant Ecol. 194: 135–148.

    Article  Google Scholar 

  • Eid T. and Tuhus E., 2001. Models for individual tree mortality in Norway. For. Ecol. Manag. 154: 69–84.

    Article  Google Scholar 

  • Fortin M., Bedard S., DeBlois J., and Meunier S., 2008. Predicting individual tree mortality in northern hardwood stands under uneven-aged management in southern Quebec, canada. Ann. For. Sci. 65: 205.

    Article  Google Scholar 

  • Franklin J.F., Shugart H.H., and Harmon M.E., 1987. Tree death as an ecological process. BioScience 550–556.

  • Fridman J. and Valinger E., 1998. Modelling probability of snow and wind damage using tree, stand, and site characteristics from Pinus sylvestris sample plots. Scan. J. For. Res. 13: 348–356.

    Article  Google Scholar 

  • Gower S.T., McMurtrie R.E., and Murty D., 1996. Aboveground net primary production decline with stand age: Potential causes. Trends Ecol. Evol. 11: 378–382.

    Article  PubMed  CAS  Google Scholar 

  • Grassi G. and Bagnaresi U., 2001. Foliar morphological and physiological plasticity in Picea abies and Abies alba saplings along a natural light gradient. Tree Physiol. 21: 959–967.

    PubMed  CAS  Google Scholar 

  • Hansen E.M., Bentz B.J., Munson A.S., Vandygriff J.C., and Turner D.L., 2006. Evaluation of funnel traps for estimating tree mortality and associated population phase of spruce beetle in Utah. Can. J. For. Res. 36: 2574–2584.

    Article  Google Scholar 

  • Harcombe P.A., 1987. Tree life table. Bioscience 37: 557–568.

    Article  Google Scholar 

  • Hawkes C., 2000. Woody plant mortality algorithms: description, problems and progress. Ecol. Model. 126: 225–248.

    Article  Google Scholar 

  • Hubbard R.M., Bond B.J., and Ryan M.G., 1999. Evidence that hydraulic conductance limits photosynthesis in old Pinus ponderosa trees. Tree Physiol. 19: 165–172.

    PubMed  Google Scholar 

  • Ihaka R. and Gentleman R., 1996. R: A Language for Data Analysis and Graphics. J. Comp. Graph. Stat. 5: 299–314.

    Article  Google Scholar 

  • Kobe R.K. and Coates K.D., 1997. Models of sapling mortality as a function of growth to characterize interspecific variation in shade tolerance of eight tree species of northwestern British Columbia. Can. J. For. Res. 27: 227–236.

    Article  Google Scholar 

  • Kobe R.K., Pacala S.W., and Silander J.A., 1995. Juvenile tree survivorship as a component of shade tolerance. Ecol. Appl. 5: 517–532.

    Article  Google Scholar 

  • Korzukhin M.D. and Ter-Mikaelian M.T., 1995. An individual tree-based model of competition for light. Ecol. Model. 79: 221–229.

    Article  Google Scholar 

  • Kunstler G., Curt T., Bouchaud M., and Lepart J., 2005. Growth, mortality, and morphological response of European beech and downy oak along a light gradient in sub-Mediterranean forest. Can. J. For. Res. 35: 1657–1668.

    Article  Google Scholar 

  • Lavine M., 1991. Problems in Extrapolation Illustrated with Space-Shuttle O-Ring Data. J. Am. Stat. Assoc. 86: 919–921.

    Article  Google Scholar 

  • Lee Y.J., 1971. Predicting mortality for even-aged stands of lodgepole pine. For. Chron. 47: 29–32.

    Google Scholar 

  • Lexer M.J. and Hönninger K., 2001. A modified 3D-patch model for spatially explicit simulation of vegetation composition in heteregeneous landscape. For. Ecol. Manage. 144: 43–65.

    Article  Google Scholar 

  • Lin J., Harcombe P.A., and Fulton M.R., 2001. Characterizing shade tolerance by the relationship between mortality and growth in tree saplings in a southeastern Texas forest. Can. J. For. Res. 31: 345–349.

    Google Scholar 

  • Lundstrom T., Jonas T., Stockli V., and Ammann W., 2007. Anchorage of mature conifers: Resistive turning moment, root-soil plate geometry and root growth orientation. Tree Physiol. 27: 1217–1227.

    PubMed  Google Scholar 

  • MacFarlane D.W., Green E.J., Brunner A., and Burkhart H.E., 2002. Predicting survival and growth rates for individual loblolly pine trees from light capture estimates. Can. J. For. Res. 32: 1970–1983.

    Article  Google Scholar 

  • Monserud R.A., 1976. Simulation of forest tree mortality. For. Sci. 22: 438–444.

    Google Scholar 

  • Monserud R.A. and Sterba H., 1999. Modeling individual tree mortality for Austrian forest species. For. Ecol. Manage. 113: 109–123.

    Article  Google Scholar 

  • Moore J.A., Hamilton D.A., Xiao Y., and Byrne J., 2004. Bedrock type significantly affects individual tree mortality for various conifers in the inland Northwest, USA. Can. J. For. Res. 34: 31–42.

    Article  Google Scholar 

  • Muller-Landau H.C., Condit R.S., Chave J., Thomas S.C., Bohlman S.A., Bunyavejchewin S., Davies S., Foster R., Gunatilleke S., Gunatilleke N., Harms K.E., Hart T., Hubbell S.P., Itoh A., Kassim A.R., LaFrankie J.V., Lee H.S., Losos E., Makana J.R., Ohkubo T., Sukumar R., Sun I.F., Supardi N.M.N., Tan S., Thompson J., Valencia R., Munoz G.V., Wills C., Yamakura T., Chuyong G., Dattaraja H.S., Esufali S., Hall P., Hernandez C., Kenfack D., Kiratiprayoon S., Suresh H.S., Thomas D., Vallejo M.I., and Ashton P., 2006. Testing metabolic ecology theory for allometric scaling of tree size, growth and mortality in tropical forests. Ecol. Lett. 9: 575–588.

    Article  PubMed  Google Scholar 

  • Nishimura T.B., 2006. Successional replacement mediated by frequency and severity of wind and snow disturbances in a Picea-Abies forest. J. Veg. Sci. 17: 57–64.

    Google Scholar 

  • Pacala S.W., Canham C., Saponara J., Silander J.A., Kobe R.K., and Ribbens E., 1996. Forest models defined by field measurements: estimation, error analysis and dynamics. Ecol. Monogr. 66: 1–43.

    Article  Google Scholar 

  • Pacala S.W. and Rees M., 1998. Models suggesting field experiments to test two hypotheses explaining successional diversity. Am. Nat. 152: 729–737.

    Article  PubMed  CAS  Google Scholar 

  • Papaik M.J. and Canham C.D., 2006. Species resistance and community response to wind disturbance regimes in northern temperate forests. J. Ecol. 94: 1011–1026.

    Article  Google Scholar 

  • Peet R.K. and Christensen N.L., 1987. Competition and tree death. BioScience 37: 586–595.

    Article  Google Scholar 

  • Peltola H., Kellomaki S., Vaisanen H., and Ikonen V.P., 1999. A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce, and birch. Can. J. For. Res. 29: 647–661.

    Article  Google Scholar 

  • Rees M., Condit R., Crawley M., Pacala S., and Tilman D., 2001. Long-term studies of vegetation dynamics. Science 293: 650–655.

    Article  PubMed  CAS  Google Scholar 

  • Sagnard F., Pichot C., Dreyfus P., Jordano P., and Fady B., 2007. Modelling seed dispersal to predict seedling recruitment: recolonization dynamics in a plantation forest. Ecol. Model. 203: 464–474.

    Article  Google Scholar 

  • Schütz J.-P., 1969. Etude des phénomènes de la croissance en hauteur et en diamètre du sapin (Abies alba Mill.) et de l’épicéa (Picea abies Karst.) dans deux peuplements jardinés et une forêt vierge. Ph.D. thesis, École Polytechnique Fédérale Zurich, Zurich.

    Google Scholar 

  • Stokes A., Salin F., Kokutse A.D., Berthier S., Jeannin H., Mochan S., Dorren L., Kokutse N., Abd Ghani M., and Fourcaud T., 2005. Mechanical resistance of different tree species to rockfall in the French Alps. Plant Soil 278: 107–117.

    Article  CAS  Google Scholar 

  • Tilman D., 1994. Competition and biodiversity in spatially structured habitats. Ecology 75: 2–16.

    Article  Google Scholar 

  • Ulmer U., 2006. Schweizerisches Landesforstinventar LFI. Datenbankauszug der Erhebungen 1983–85 und 1993–95 vom 30. Mai 2006. Technical report, WSL, Eidg. Forschungsanstalt WSL, Birmensdorf.

    Google Scholar 

  • Uriarte M., Canham C.D., Thompson J., and Zimmerman J.K., 2004. A neighborhood analysis of tree growth and survival in a hurricane-driven tropical forest. Ecol. Monogr. 74: 591–614.

    Article  Google Scholar 

  • Valinger E. and Fridman J., 1997. Modelling probability of snow and wind damage in Scots pine stands using tree characteristics. For. Ecol. Manage. 97: 215–222.

    Article  Google Scholar 

  • Vieilledent G., Courbaud B., Kunstler G., Dhote J.F., and Clark J.S., 2009. Biases in the estimation of size-dependent mortality models: advantages of a semiparametric approach. Can. J. For. Res. 39: 1430–1443.

    Article  Google Scholar 

  • Wasser B. and Frehner M., 1996. Soins minimaux pour les forêts à fonction protectrice. Office Central Fédéral des Imprimés et du Matériel, Berne.

    Google Scholar 

  • Worrall J.J., Lee T.D., and Harrington T.C., 2005. Forest dynamics and agents that initiate and expand canopy gaps in Picea-Abies forests of Crawford Notch, New Hampshire, USA. J. Ecol. 93: 178–190.

    Article  Google Scholar 

  • Wunder J., Reineking B., Matter J.F., Bigler C., and Bugmann H., 2007. Predicting tree death for Fagus sylvatica and Abies alba using permanent plot data. J. Veg. Sci. 18: 525–534.

    Article  Google Scholar 

  • Wyckoff P.H. and Clark J.S., 2000. Predicting tree mortality from diameter growth: a comparison of maximum likelihood and Bayesian approaches. Can. J. For. Res. 30: 156–167.

    Article  Google Scholar 

  • Wyckoff P.H. and Clark J.S., 2002. The relationship between growth and mortality for seven co-occurring tree species in the southern Appalachian Mountains. J. Ecol. 90: 604–615.

    Article  Google Scholar 

  • Yao X.H., Titus S.J., and MacDonald S.E., 2001. A generalized logistic model of individual tree mortality for aspen, white spruce, and lodgepole pine in Alberta mixedwood forests. Can. J. For. Res. 31: 283–291.

    Google Scholar 

  • Zolubas P., 2003. Spruce Bark Beetle (Ips typographus L.) Risk based on individual tree parameters. In: IUFRO (Ed.), Forest insect population dynamics and host influences, Kanazawa, pp. 96–97.

Download references

Author information

Authors and Affiliations

  1. Cemagref-Mountain Ecosystems Research Unit, 2 rue de la Papeterie, BP 76, 38402, Saint-Martin-d’Hères Cedex, France

    Ghislain Vieilledent, Benoît Courbaud & Georges Kunstler

  2. Laboratoire d’Étude des Ressources Forêt Bois, AgroParisTech-UMR1092, 14 rue Girardet, 54000, Nancy, France

    Ghislain Vieilledent

  3. Cirad-UPR Dynamique Forestière, TA C-37/D, Campus International de Baillarguet, 34398, Montpellier Cedex 5, France

    Ghislain Vieilledent

  4. Laboratoire d’Étude des Ressources Forêt Bois, INRA-UMR1092, 14 rue Girardet, 54000, Nancy, France

    Jean-François Dhôte

  5. ONF-Département Recherche, Boulevard de Constance, 77300, Fontainebleau, France

    Jean-François Dhôte

Authors
  1. Ghislain Vieilledent
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Benoît Courbaud
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Georges Kunstler
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jean-François Dhôte
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ghislain Vieilledent.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Vieilledent, G., Courbaud, B., Kunstler, G. et al. Mortality of silver fir and Norway Spruce in the Western Alps — a semi-parametric approach combining size-dependent and growth-dependent mortality. Ann. For. Sci. 67, 305 (2010). https://doi.org/10.1051/forest/2009112

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1051/forest/2009112

Keywords

Mots-clés

Annals of Forest Science

ISSN: 1297-966X