Literature DB >> 34025297

Reduction of taxonomic bias in diatom species data.

Meredith A Tyree1, Ian W Bishop2, Charles P Hawkins3, Richard Mitchell4, Sarah A Spaulding1,5.   

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.

Keywords:  Bacillariophyceae; analyst bias; national survey; regional survey; taxonomic consistency

Year:  2020        PMID: 34025297      PMCID: PMC8139252          DOI: 10.1002/lom3.10350

Source DB:  PubMed          Journal:  Limnol Oceanogr Methods        ISSN: 1541-5856            Impact factor:   2.634


  5 in total

1.  Genus-level, trait-based multimetric diatom indices for assessing the ecological condition of rivers and streams across the conterminous United States.

Authors:  Luisa Riato; Ryan A Hill; Alan T Herlihy; David V Peck; Philip R Kaufmann; John L Stoddard; Steven G Paulsen
Journal:  Ecol Indic       Date:  2022-08       Impact factor: 6.263

2.  Diatoms.org: supporting taxonomists, connecting communities.

Authors:  Sarah A Spaulding; Marina G Potapova; Ian W Bishop; Sylvia S Lee; Tim S Gasperak; Elena Jovanoska; Paula C Furey; Mark B Edlund
Journal:  Diatom Res       Date:  2022-01-11       Impact factor: 1.386

3.  A web-based tool for assessing the condition of benthic diatom assemblages in streams and rivers of the conterminous United States.

Authors:  Daren M Carlisle; Sarah A Spaulding; Meredith A Tyree; Nicholas O Schulte; Sylvia S Lee; Richard M Mitchell; Amina A Pollard
Journal:  Ecol Indic       Date:  2022-02       Impact factor: 6.263

4.  Resources and Practices to Improve Diatom Data Quality.

Authors:  Janice Alers-García; Sylvia S Lee; Sarah A Spaulding
Journal:  Limnol Oceanogr Bull       Date:  2021-03-26

5.  A harmonized dataset of sediment diatoms from hundreds of lakes in the northeastern United States.

Authors:  Marina G Potapova; Sylvia S Lee; Sarah A Spaulding; Nicholas O Schulte
Journal:  Sci Data       Date:  2022-09-03       Impact factor: 8.501

  5 in total

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