Quantitative comparison of taxa and taxon concepts in the diatom genus Fragilariopsis: a case study on using slide scanning, multiexpert image annotation, and image analysis in taxonomy¹

Abstract

Semiautomated 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, semiautomated 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.

Binary Masks of Concentric Rings as a Method to Approximate Identification of Diatoms Using Images

“…Since it is not only important to identify problem images of the same species as the reference image, but also to make an adequate discrimination from the other species, it is important to use metrics such as those shown in the eq. (18)(19)(20)(21), which will allow the adequate selection of binary masks with concentric rings for each species, and to obtain a better identification. D when Actinocyclus ingens is used as image reference and different values of  .…”

Deep learning-based diatom taxonomy on virtual slides

“…Scanning larger areas of microscopy slides instead of individual user-selected fields of view helps to avoid overlooking taxa at the object detection step and enables later re-analysis. Multi-user annotation, as implemented in BIIGLE, facilitates consensus-building and defining the gold standard in case of ambiguous labelling 11 .…”

“…being among the authors of this work. In some cases, multiple users annotated the same object, either agreeing or disagreeing on previously attached labels, where taxonomic disagreement is not uncommon 11 . This issue was resolved during data export (step 6).…”

“…Attempts to computerize parts or the whole of this workflow have been made repeatedly, starting with Cairns 7 , and in the most complete manner so far by the ADIAC project 8 , motivated by the desire to speed up the taxonomic enumeration process, to reduce its dependence on highly trained taxonomic experts, and to make identification results more reproducible and transparent. Recently, we described an updated re-implementation of most parts of this workflow, covering high throughput microscopic imaging, segmentation and outline shape feature extraction of diatom specimens 9 , 10 which we since mainly applied in morphometric investigations 11 – 14 . The missing component in this workflow has been automated or computer-assisted taxonomic identification.…”

Continents as Units for the Study of Floristic Assembly and Biodiversity: Focus on North America

“…While records of species remain at the core of biodiversity science, new discoveries are increasingly made possible using these records in combination with new technologies. New technologies emerging in florsitics research include remote sensing and drones, bioinformatics inferences that guide choices for field surveys, integrative and multidisciplinary studies such as in ecology and taxonomy, automated workflows, and utilizing genomic and environmental information for revealing morphologically cryptic diversity (Palmer et al, ; Raxworthy et al, ; Reginato, ; Wen et al, ; Beszteri et al, ; Zheng et al, ). These and other cutting‐edge methodologies are already in wide use in biodiversity studies in North America, and promise to continue to enhance efforts to document diversity of the continent (Loera et al, ; Kriebel, ).…”