Advancing dendrochronology with R: an overview of packages and future perspectives

Jan Altman¹Nela Altmanova¹Pavel Fibich¹Kirill Korznikov¹Patrick Fonti^2*

• ¹Institute of Botany (ASCR), Průhonice, Czechia
• ²Landscape Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland

Modern analytical tools are essential for advancing research and facilitating interdisciplinary collaboration. The R software serves as a comprehensive solution for statistical computing and graphics in all scientific disciplines, including dendrochronology.Beyond managing traditional tasks like data processing, analysis, and results visualization, R is pivotal in integrating innovative techniques, such as multi-proxy datasets, artificial intelligence or machine learning, to address emerging challenges in tree-ring research.However, a comprehensive overview of R's functionalities in dendrochronology is lacking, despite its growing importance and increasing role in interdisciplinary research. Here we present an overview of 38 R packages relevant to tree-ring research, categorized by functionality. For each R package, concise descriptions and examples of usage are provided to facilitate the identification and selection of suitable tools for researchers, academicians, and students within and outside the field. We further discuss the transformative potential of R in building a centralized, open-access ecosystem, emphasizing its role in standardizing workflows, enhancing reproducibility, and expanding dendrochronology's integration with other scientific disciplines in a digital era. We propose that these advancements not only streamline dendrochronological workflows but also provide valuable insights for addressing global environmental and ecological challenges.