Applying climwin to dendrochronology: A breakthrough in the analyses of tree responses to environmental variability |
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Affiliation: | 1. Department of Forest Resource Planning and Informatics, Faculty of Forestry, Technical University in Zvolen, T.G. Masaryka 24, 96001 Zvolen, Slovakia;2. Departamento de Sistemas y Recursos Naturales, Escuela Técnica Superior de Ingeniería de Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040, Madrid, Spain;3. Instituto Pirenaico de Ecología (IPE-CSIC), Avda. Montañana 1005, 50080, Zaragoza, Spain;1. Nature Rings – Environmental Research and Education, Mainz, Germany;2. Department of Geography, Justus-Liebig-University, Gießen, Germany;3. Institute for Geosciences, Johannes Gutenberg University, Mainz, Germany;4. Department of Geography, Johannes Gutenberg University, Mainz, Germany;5. Deutscher Wetterdienst, Offenbach, Germany;6. Department of Geography, University of Cambridge, UK;7. Swiss Federal Research Institute WSL, Birmensdorf, Switzerland;8. Global Change Research Centre AS CR, Brno, Czech Republic;1. School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada;2. Mistik Askiwin Dendrochronology Lab, University of Saskatchewan, Saskatoon, SK, Canada;3. Department of Geography, University of Winnipeg, Winnipeg, MB, Canada;4. Global Institute for Water Security, Saskatoon, SK, Canada;5. Department of Soil Science, University of Saskatchewan, Saskatoon, SK, Canada;6. Centre d’étude de la forêt, Université du Québec à Montréal, Montréal, QC, Canada;7. Département Science et Technologie, Téluq, Université du Québec, Montréal, QC, Canada;8. Environment and Climate Change Canada, Watershed Hydrology and Ecology Research Division, Saskatoon, SK, Canada;9. Stantec Consulting Ltd., Saskatoon, SK, Canada;1. Siberian Federal University, 79 Svobodny pr., 660041 Krasnoyarsk, Russia;2. V.N. Sukachev Institute of Forest SB RAS, Federal Research Center ‘Krasnoyarsk Science Center SB RAS‘, Akademgorodok 50/28, Krasnoyarsk 660036, Russia;3. Department of Geography, University of Cambridge, CB2 3EN, UK;1. Chair of Forest Growth and Woody Biomass Production, TU Dresden, Germany;2. Institute of Botany and Landscape Ecology, University of Greifswald, Germany;3. Chair of Silviculture, University of Freiburg, Germany;4. Landesforst Mecklenburg-Vorpommern, Schwerin, Germany;1. Faculty of Science, Department of Botany, University of South Bohemia, Na Zlaté Stoce 1, 37005 České Budějovice, Czech Republic;2. Institute of Botany of the Academy of Sciences of the Czech Republic, Zámek 1, 25243 Průhonice, Czech Republic;3. Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014, Finland |
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Abstract: | Observational, correlative approaches are one of the backbones of dendrochronology. For instance, climate-growth relationships are usually quantified by calculating Pearson correlations. However, the ability to detect these relationships and the probability of declaring significant correlations by chance pose multiple challenges to such correlative framework. The R climwin package, developed a few years ago within the discipline of animal ecology, overcomes these limitations. In this paper we apply climwin to study relationships between climate and tree-ring widths and anatomy to show the advantages of using this package in the field of dendrochronology. This package allows calculating several models considering multiple windows relating a response variable to the climatic factors at different time resolutions. Then, the most parsimonious model is selected through an information-theoretic approach and randomization tests are computed to establish the significance of the selected model. We compare analyses based on Pearson correlations with climwin results using several environmental drivers (climate variables, drought indices, river flow), response variables (tree-ring width, tracheid lumen area and cell-wall thickness), and tree species from ecologically contrasting sites (cold- and water-limited conifers, Mediterranean riparian ash forests). Analyses of climate-growth/anatomy relationships based on the use of climwin showed several advantages over simple Pearson correlations: (i) they did not depend on the use of arbitrary time intervals of fixed duration, (ii) they allowed reducing probabilities associated with type I and II errors, (iii) they resulted in more consistent findings, (iv) they increased the capacity to detect differences between sites or periods in a time series, and (v) they provided more explanatory power. |
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Keywords: | Tree growth Dendroecology Model selection Wood anatomy R software Climate windows |
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