Applying climwin to dendrochronology: A breakthrough in the analyses of tree responses to environmental variability

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.