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Ian W. Bishop

Publications and source records attributed to Ian W. Bishop.

4 recordsLinked to original sources

Diatoms.org: Supporting taxonomists, connecting communities

Consistent identification of diatoms is a prerequisite for studying their ecology, biogeography, and successful application as environmental indicators. However, taxonomic consistency among observers has been difficult to achieve because taxonomic information is scattered across numerous literature sources, presenting challenges to the diatomist. Firstly, literature is often inaccessible because of cost or its location in journals that are not widely circulated. Secondly, taxonomic revisions of diatoms are taking place faster than floras can be updated. Finally, taxonomic information is often contradictory across literature sources. These issues can be addressed by developing a content creation community dedicated to making taxonomic, ecological, and image-based data freely available for diatom researchers. Diatoms.org represents such a content curation community, providing open, online access to a vast amount of recent and historical information on North American diatom taxonomy and ecology. The content curation community aggregates existing taxonomic information, creates new content, and provides feedback in the form of corrections and notices of literature with nomenclatural changes. The website not only addresses the needs of experienced diatom scientists for consistent identification but is also designed to meet users at their level of expertise, including engaging the lay public in the importance of diatom science. The website now contains over 1000 species pages contributed by over 100 content contributors, from students to established scientists. The project began with the intent to provide accurate information on diatom identification, ecology, and distribution using an approach that incorporates engaging design, user feedback, and advanced data access technology. In retrospect, the project that began as an ‘extended electronic book’ has emerged not only as a means to support taxonomists, but for practitioners to communicate and collaborate, expanding the size of and benefits to the content curation community. In this paper, we outline the development of diatoms.org , document key elements of the project, examine ongoing challenges and consider the unexpected emergent properties, including the value of diatoms.org as a source of data. Ultimately, if the field of diatom taxonomy, ecology, and biodiversity is to be relevant, a new generation of taxonomists needs to be trained and employed using new tools. We propose that diatoms.org is in a key position to serve as a hub of training and continuity for the study of diatom biodiversity and aquatic conditions.

Diatom Research

Reduction of taxonomic bias in diatom species data

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 four elements of sample preparation, taxon identification and enumeration, and quality control (QC). We used six independent datasets to assess the effect of the adjustments on analytical outcomes. The first dataset was produced by three laboratories with a total of five analysts following established protocols (Charles et al. 2002), or their slight variations. The remaining datasets were produced by 1-3 laboratories with a total of 2-3 analysts following a revised protocol. The revised protocol included the following modifications: 1) development of coordinated pre-count voucher floras based on morphological operational taxonomic units (mOTUs), 2) random assignment of samples to analysts, 3) post-count identification and documentation of taxa (as opposed to an approach in which analysts assign names while they enumerate), and 4) increased use of 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.

Limnology and Oceanography: Methods

Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets

Diatom data have been collected in large-scale biological assessments in the United States, such as the U.S. Environmental Protection Agency’s National Rivers and Streams Assessment (NRSA). However, the effectiveness of diatoms as indicators may suffer if inconsistent taxon identifications across different analysts obscure the relationships between assemblage composition and environmental variables. To reduce these inconsistencies, we harmonized the 2008–2009 NRSA data from nine analysts by updating names to current synonyms and by statistically identifying taxa with high analyst signal (taxa with more variation in relative abundance explained by the analyst factor, relative to environmental variables). We then screened a subset of samples with QA/QC data and combined taxa with mismatching identifications by the primary and secondary analysts. When these combined “slash groups” did not reduce analyst signal, we elevated taxa to the genus level or omitted taxa in difficult species complexes. We examined the variation explained by analyst in the original and revised datasets. Further, we examined how revising the datasets to reduce analyst signal can reduce inconsistency, thereby uncovering the variation in assemblage composition explained by total phosphorus (TP), an environmental variable of high priority for water managers. To produce a revised dataset with the greatest taxonomic consistency, we ultimately made 124 slash groups, omitted 7 taxa in the small naviculoid (e.g., Sellaphora atomoides ) species complex, and elevated Nitzschia , Diploneis , and Tryblionella taxa to the genus level. Relative to the original dataset, the revised dataset had more overlap among samples grouped by analyst in ordination space, less variation explained by the analyst factor, and more than double the variation in assemblage composition explained by TP. Elevating all taxa to the genus level did not eliminate analyst signal completely, and analyst remained the most important predictor for the genera Sellaphora , Mayamaea , and Psammodictyon , indicating that these taxa present the greatest obstacle to consistent identification in this dataset. Although our process did not completely remove analyst signal, this work provides a method to minimize analyst signal and improve detection of diatom association with TP in large datasets involving multiple analysts. Examination of variation in assemblage data explained by analyst and taxonomic harmonization may be necessary steps for improving data quality and the utility of diatoms as indicators of environmental variables.

Ecological Indicators

A diatom voucher flora from selected southeast rivers (USA)

This flora is intended to serve as an image voucher for samples analyzed for the U.S. Geological Survey Southeast Stream Quality Assessment (SESQA). The SESQA study included measurement of watershed and water quality parameters to determine the factors that have the greatest potential to alter biotic condition. Algal samples were collected at 108 sites in 2014, from streams representing gradients in chemical and physical alteration across the southeast region. More than 375 taxa were identified during analysis for species composition and abundance. This manuscript documents the flora with light micrographs of specimens representative of their morphologic range. We define “voucher flora” as images of specimens and the names applied to those specimens for a given project. Taxonomic vouchers from federal programs have generally not been made public, yet they are a salient element of a well-documented species dataset, particularly for long-term studies. This study is part of a broader effort to improve and encourage taxonomic consistency in federal, state and local programs by accessible identification resources and inter-lab comparisons.

Phytotaxa