Quantitative comparison of taxa and taxon concepts in the diatom genus Fragilariopsis: a case study on using slide scanning, multi‐expert image annotation and image analysis in taxonomy

Beszteri, Bánk; Allen, Claire ORCID: https://orcid.org/0000-0002-0938-0551; Almandoz, Gastón O; Armand, Leanne; Ángeles Barcena, Maria; Cantzler, Hannelore; Crosta, Xavier; Esper, Oliver; Jordan, Richard W; Kauer, Gerhard; Klaas, Christine; Kloster, Michael; Leventer, Amy; Pike, Jennifer; Rigual Hernández, Andrés S. 2018 Quantitative comparison of taxa and taxon concepts in the diatom genus Fragilariopsis: a case study on using slide scanning, multi‐expert image annotation and image analysis in taxonomy. Journal of Phycology, 54 (5). 703-719. 10.1111/jpy.12767

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Abstract/Summary

Semi‐automated methods for microscopic image acquisition, image analysis and taxonomic identification have repeatedly received attention in diatom analysis. Less well studied is the question whether and how such methods might prove useful for clarifying the delimitation of species that are difficult to separate for human taxonomists. To try to answer this question, three very similar Fragilariopsis species endemic to the Southern Ocean were targeted in this study: F. obliquecostata, F. ritscheri, and F. sublinearis. A set of 501 extended focus depth specimen images were obtained using a standardized, semi‐automated microscopic procedure. Twelve diatomists independently identified these specimen images in order to reconcile taxonomic opinions and agree upon a taxonomic gold standard. Using image analyses, we then extracted morphometric features representing taxonomic characters of the target taxa. The discriminating ability of individual morphometric features was tested visually and statistically, and multivariate classification experiments were performed to test the agreement of the quantitatively‐defined taxa assignments with expert consensus opinion. Beyond an updated differential diagnosis of the studied taxa, our study also shows that automated imaging and image analysis procedures for diatoms are coming close to reaching a broad applicability for routine use.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1111/jpy.12767
ISSN:	00223646
Additional Keywords:	automatic diatom identification, Bacillariophyta, image analysis
Date made live:	02 Aug 2018 15:17 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/520656

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