pcrecon: An R Package for Nested Principal Component Regression Climate Reconstructions

Authors: Laura Smith*, University of Tennessee, Nicholas Nagle, University of Tennessee, Stockton Maxwell, Radford University , Daniel Hocking, NOAA Fisheries
Topics: Paleoenvironmental Change, Physical Geography, Biogeography
Keywords: Dendrochronology, R, Climate, Proxy Reconstruction
Session Type: Virtual Paper
Day: 4/9/2021
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual 30
Presentation File: No File Uploaded

The process of tree-ring analysis frequently relies on the use of multiple, stand-alone software programs for cross-dating, ring-width file editing, standardization, chronology development, and more. Moving between these programs, each with a very specific application and user interface, presents workflow issues for the user as well as general barriers to transparency and reproducibility. In the last 10-15 years, major efforts have been made to port many of these applications to the R statistical programming environment, most notably with the package dplR (Bunn et. al, 2007). Legacy fixed-width file formats common to dendrochronology can be read into R using functions within the dplR package, and all manner of analysis (tree-ring specific or not) performed within that single environment. A record of the data analysis process is kept via scripts, text files containing R code, thus improving reproducibility and transparency in the process. We present pcrecon, a new software package for the development of nested principal component regression (PCR) climate reconstructions from tree ring data in R. This package duplicates and extends the well-known Fortran program PcReg. The use of a standard, versatile, common, and cross-disciplinary platform for analysis is important for clear communication and reproducibility of results, as well as collaborations with subject matter experts in other fields.

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