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Abstract
Inconsistency in taxonomic identification and analyst bias impede the effective use of diatom data in regional and national stream and lake surveys. In this study, we evaluated the effect of existing protocols and a revised protocol on the precision of diatom species counts. The revised protocol adjusts five elements of sample preparation, taxon identification and enumeration, and quality control (QC) samples. We used six independent datasets to assess the effect of the adjustments on analytical outcomes. The first dataset was produced by five analysts from three laboratories following a standard protocol (Charles et al. 2002). The remaining datasets were produced by 2-3 analysts in 1-3 laboratories following a revised protocol. The revised protocol included the following modifications: 1) use of Battarbee settling chambers to prepare coverslips, 2) development of coordinated pre-count voucher floras based on morphological operational taxonomic units (mOTUs), 3) random assignment of samples to analysts, 4) post-count identification and documentation of taxa, and 5) increased QC samples. The revised protocol reduced taxonomic bias, as measured by reduction in analyst signal, and improved similarity among QC samples. Reduced taxonomic bias improves the performance of biological assessments, facilitates transparency across studies, and refines estimates of diatom species distributions.
Highlights
Lack of consistency in taxonomic identification of diatoms stems, in part, from a reliance on European floras and the resulting misapplication of names to North American species (Kociolek and Spaulding 2000)
One survey was collected as a joint effort between the U.S Geological Survey (USGS) and the U.S Environmental Protection Agency (USEPA): the 2013 Midwest Stream Quality Assessment (MSQA) (Van Metre et al 2012; Garrett et al 2017)
Taxonomic bias has been problematic for diatom data sets combined across analysts and laboratories (Cao et al 2007; Kelly et al 2009; Kahlert et al 2016; Lee et al 2019)
Summary
Recommended Citation Tyree, M.A., Bishop, I.W., Hawkins, C.P., Mitchell, R. and Spaulding, S.A. (2020), Reduction of taxonomic bias in diatom species data. Recommended Citation Tyree, M.A., Bishop, I.W., Hawkins, C.P., Mitchell, R. and Spaulding, S.A. (2020), Reduction of taxonomic bias in diatom species data. Wiley Periodicals, Inc. on behalf of Association for the Sciences of Limnology and Oceanography.
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