tax_QA

This is data and code that contributed to the following dissertation chapter, which is in preparation for publication:

A robust template for increasing taxonomic quality assurance in an era of declining taxonomic capacity

Erica T. Jarvis Mason¹, Andrew R. Thompson², Brice X. Semmens¹

¹Scripps Institution of Oceanography, University of California San Diego, California, USA
²NOAA Southwest Fisheries Science Center, California, USA

R-script files:

1. JarvisMasonetal_AccPrec.R (Model probabilities of accurate and precise species classifications, and add an effect of taxonomist)

   • Compare and contrast taxonomist skill (Bayesian binomial model, with options for adding a fixed effect or random effect of taxonomist)

2. JarvisMasonetal_TaxMorph.R (Explore the utility of a suite of characters for species discrimination, and identify the most important characters)

   • Identify potential areas of taxonomist bias, subjectivity in interpreting characters (Bayesian multinomial logistic regression)
   • Identify which characters are most important (random forest)