Mortality of silver fir and norway spruce in the Western Alps: a semi-parametric bayesian approach combining size-dependent and growth-dependent mortality
2010
Vieilledent, G. | Courbaud, B. | Kunstler, G. | Dhôte, J.F. | Ecosystèmes montagnards (UR EMGR) ; Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) | Laboratoire d'Etudes des Ressources Forêt-Bois (LERFoB) ; Institut National de la Recherche Agronomique (INRA)-AgroParisTech
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SEDYVIN
Mostrar más [+] Menos [-]Inglés. 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 consider as a proxy for tree age which determines senescence. Few mortality models integrate both covariates as classical model calibration need large permanent plots data-sets which are rare. How then to obtain a multivariate mortality model including size and growth when permanent plots data are not available? Location: To answer this question, we studied A. alba and P. abies mortality in the French and Swiss Alps. Method: Our study proposes an alternative semi-parametric Bayesian method which includes a random sample of living and dead trees with diameter and growth measurements. Results: We were able to obtain a mortality model combining both size-dependent and growth-dependent mortality. We demonstrated that A. alba had a lower mortality rate (10%) than P. abies (18%) for low growth (<20/100mm.an-1). We also demonstrated that for high diameter (DBH≥70cm), P. abies had a higher mortality rate (0.45%) than A. alba (0.32%). Conclusion: Our results fit to the mechanisms of colonization-competition trade-off and of successional niche which can explain, in part, the coexistence of the two species in the Alps. The method we developed should be of valuable help to forecast tree mortality and to improve the efficiency of forest dynamics model.
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