RingdateR: A statistical and graphical tool for crossdating

Crossdating is the defining technique of dendrochronology, ensuring that all measurements in a dataset are annually resolved and absolutely dated. This level of accuracy allows for the development of high-resolution environmental reconstructions of climate, disturbance, and productivity not only in trees, but also in other ring-forming organisms including fish, corals, and bivalves. However, crossdating is a laborious process and can be a significant bottleneck in the development of new chronologies, especially when attempting to find matches among undated, dead-collected material. Several software packages have been developed to aid in crossdating, yet efficiently identifying matches among large numbers of dead-collected samples of unknown antiquity remains a gap in functionality. To address this issue we present RingdateR, a new stand-alone and web-based application for statistical and graphical crossdating that shares many key features with established crossdating applications, but has been optimised for crossdating large collections of dead-collected material. The workflow allows users to load undated measurement time series in common file types (e.g. pos, lps, csv, and xlsx) to be matched against one another (i.e. pairwise analyses) or against an existing chronology. RingdateR provides graphical tools to help identify false or missed rings remaining in the matched measurement time series and to evaluate the impact of the newly crossdated measurement time series on chronology statistics. Whilst the decision as to whether a sample is correctly crossdated ultimately lies with careful visual inspection and discretion of the investigator, guidance from RingdateR can greatly expedite the process, especially when building chronologies that involve dead-collected samples.