Borne out of my research presented in Chapter 2, this work is intended as a research methods contribution to the field of taxonomy and highlights a suite of tools for increasing taxonomic quality assurance of taxonomic classifications.
This research was supported by a grant awarded by the California Ocean Protection Council (Proposition 84 Competitive Grant Program, Project R/OPCSFAQ-09) and administered by the California Sea Grant College Program. The following synopsis is taken from our manuscript, which is currently in preparation for publication submission.
A robust template for increasing taxonomic quality assurance during an era of decreasing taxonomic capacity
Erica T. Jarvis Mason1,2, William W. Watson2, Andrew R. Thompson2, Noelle M. Bowlin2, Brice X. Semmens1
1Scripps Institution of Oceanography, University of California San Diego, California, USA
22Fisheries Resources Division, Southwest Fisheries Science Center, NOAA Fisheries, California, USA
Abstract
Sound conservation efforts heavily rely on accurate taxonomic identification and classification of organisms. Yet, in an era of limited taxonomic capacity, confidence in taxonomic expertise has waned. Here, we present a robust template for identifying taxonomic calibration needs and increasing taxonomic quality assurance. Our method includes six steps for use in a variety of applications, including constructing taxonomic keys or field guides, taxonomic training, and conducting standardized periodic quality control and quality assurance measures. These processes include a novel combination of classical taxonomy and modern statistical methods (i.e., Bayesian inference, machine learning) that are useful in identifying important taxonomic characters and taxonomic bias, where and when taxonomic calibration is required, and measuring performance in classifications over time. The template is easy to implement, has wide application, and will be useful for maintaining high taxonomic standards in long-term monitoring efforts and taxonomic key development, even in cases where taxonomic capacity is limited.