title: Towards a common methodology for developing logistic tree mortality models based on ring-width data.
abstract: Tree mortality is a key process shaping forest dynamics. Thus, there is a growing need for indicators of the likelihood of tree death. During the last decades, an increasing number of tree-ring based studies have aimed to derive growth-mortality functions, mostly using logistic models. The results of these studies, however, are difficult to compare and synthesize due to the diversity of approaches used for the sampling strategy (number and characteristics of alive and death observations), the type of explanatory growth variables included (level, trend, etc.), and the length of the time window (number of years preceding the alive/death observation) that maximized the discrimination ability of each growth variable. We assess the implications of key methodological decisions when developing tree-ring based growth-mortality relationships using logistic mixed-effects regression models. As examples, we use published tree-ring datasets from Abies alba (13 different sites), Nothofagus dombeyi (one site), and Quercus petraea (one site). Our approach is based on a constant sampling size and aims at (1) assessing the dependency of growth-mortality relationships on the statistical sampling scheme used, (2) determining the type of explanatory growth variables that should be considered, and (3) identifying the best length of the time window used to calculate them. The performance of tree-ring-based mortality models was reasonably high for all three species (area under the receiving operator characteristics curve, AUC > 0.7). Growth level variables were the most important predictors of mortality probability for two species (A. alba, N. dombeyi), while growth-trend variables need to be considered for Q. petraea. In addition, the length of the time window used to calculate each growth variable was highly uncertain and depended on the sampling scheme, as some growth-mortality relationships varied with tree age. The present study accounts for the main sampling-related biases to determine reliable species-specific growth-mortality relationships. Our results highlight the importance of using a sampling strategy that is consistent with the research question. Moving towards a common methodology for developing reliable growth-mortality relationships is an important step towards improving our understanding of tree mortality across species and its representation in dynamic vegetation models.
authors.affiliation: Forest Ecology, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, CH-8092 Zürich, Switzerland. maxime.cailleret@usys.ethz.ch.
authors.forename: Maxime
authors.initials: M
authors.lastname: Cailleret
authors.affiliation: Forest Ecology, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, CH-8092 Zürich, Switzerland.
authors.forename: Christof
authors.initials: C
authors.lastname: Bigler
authors.affiliation: Forest Ecology, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zürich, CH-8092 Zürich, Switzerland.
authors.forename: Harald
authors.initials: H
authors.lastname: Bugmann
authors.affiliation: Instituto Pirenaico de Ecología (IPE, CSIC), Avda. Montañana 1005, 50059, Zaragoza, Spain.
authors.forename: Jesús Julio
authors.initials: JJ
authors.lastname: Camarero
authors.affiliation: Department of Wood Science and Technology, Biotechnical Faculty, University of Ljubljana,SI-1000 Ljubljana, Slovenia.
authors.forename: Katarina
authors.initials: K
authors.lastname: Cˇufar
authors.affiliation: INRA, URFM, UR 629, Ecologie des Forêts Méditerranéennes, Domaine Saint Paul, Site Agroparc, F-84914, Avignon Cedex 9, France.
authors.forename: Hendrik
authors.initials: H
authors.lastname: Davi
authors.affiliation: Department of Botany, Faculty of Science and Technology, University of Debrecen, PO Box 14, H-4010, Debrecen, Hungary.
authors.forename: Ilona
authors.initials: I
authors.lastname: Mészáros
authors.affiliation: Department of Forest Science, University of Helsinki, PO Box 27, Helsinki, FI-00014, Finland.
authors.forename: Francesco
authors.initials: F
authors.lastname: Minunno
authors.affiliation: Natural Resources Institute Finland (Luke), Jokiniemenkuja 1, 01301, Vantaa, Finland.
authors.forename: Mikko
authors.initials: M
authors.lastname: Peltoniemi
authors.affiliation: Laboratory of Plant Biology and Nature Management (APNA), Vrije Universiteit Brussel, B-1050, Brussels, Belgium.|Laboratory of Wood Biology and Xylarium, Royal Museum for Central Africa (RMCA), B-3080, Tervuren, Belgium.
authors.forename: Elisabeth M R
authors.initials: EM
authors.lastname: Robert
authors.affiliation: INIBIOMA, CONICET-Universidad Nacional Comahue, Quintral 1250, Bariloche, Argentina.
authors.forename: María Laura
authors.initials: ML
authors.lastname: Suarez
authors.affiliation: Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, Contrada Fonte Lappone, Pesche, I-86090, Italy.
authors.forename: Roberto
authors.initials: R
authors.lastname: Tognetti
authors.affiliation: CREAF, Cerdanyola del Vallès E-08193, Barcelona, Spain.|University Autònoma Barcelona, Cerdanyola del Vallès E-08193, Barcelona, Spain.
authors.forename: Jordi
authors.initials: J
authors.lastname: Martínez-Vilalta
mesh_terms: D016015:Logistic Models; D008954:Models, Biological; D015999:Multivariate Analysis; D018401:Sample Size; D014197:Trees / Q000502:physiology*
keywords: 
  Abies alba
  ; 
  Nothofagus dombeyi
  ; 
  Quercus petraea
  ; growth-mortality relationship; logistic model; sampling; survival; tree mortality; tree ring