Abstract
Accurate taxonomic resolution in light microscopy analyses of microalgae is essential to achieve high quality, comparable results in both floristic analyses and biomonitoring studies. A number of closely related diatom taxa have been detected to date co-occurring within benthic diatom assemblages, sharing many morphological, morphometrical and ecological characteristics. In this contribution, we analysed the hypothesis that, where a large sample size (number of individuals) is available, common morphometrical parameters (valve length, width and stria density) are sufficient to achieve a correct identification to the species level. We focused on some common diatom taxa belonging to the genus Gomphonema. More than 400 valves and frustules were photographed in valve view and measured using Fiji software. Several statistical tools (mixture and discriminant analysis, k-means clustering, classification trees, etc.) were explored to test whether mere morphometry, independently of other valve features, leads to correct identifications, when compared to identifications made by experts. In view of the results obtained, morphometry-based determination in diatom taxonomy is discouraged.
Highlights
Diatoms are unicellular algae inhabiting many different aquatic and terrestrial environments worldwide
We explore the possibility of disentangling one of these groups (species related to Gomphonema gracile Ehr. (Reichardt, 2015) and G. parvulum (Kütz.) Kütz.) by unsupervised classification of individuals based only on their morphometric parameters
Five species attained large (N ≥ 45) populations, which were considered in subsequent analyses (N = 410)
Summary
Diatoms are unicellular algae inhabiting many different aquatic and terrestrial environments worldwide. To date, ∼105 different species have been described (Mann & Droop, 1996), with particular ecological preferences, so that there is a clear relationship between diatom communities and the environmental characteristics of their habitats. The main obstacle limiting their use lies in the difficulty of their taxonomic identification, since diagnoses at specific or subspecific levels are often required. This implies important investments in optical equipment and expert training. The identification and routine counting of diatoms is performed under light/phase contrast optical microscopy, but several tools are being proposed to automate the identification process by means of image analyses (Buf & Bayer, 2002; Kloster, Kauer & Beszteri, 2014) or DNA metabacoding (e.g., Vasselon et al, 2017)
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