Reduction of taxonomic bias in diatom species data.

Limnol Oceanogr Methods

Institute of Arctic and Alpine Research (INSTAAR), University of Colorado Boulder, Campus Box 450, Boulder, CO 80309-0450 USA.

Published: February 2020

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139252PMC
http://dx.doi.org/10.1002/lom3.10350DOI Listing

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