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Diatoms from the genus Achnanthidium in flowing waters of the Appalachian Mountains (North America): Ecology, distribution and taxonomic notes
Journal article   Open access   Peer reviewed

Diatoms from the genus Achnanthidium in flowing waters of the Appalachian Mountains (North America): Ecology, distribution and taxonomic notes

Karin C. Ponader and Marina G. Potapova
Limnologica, v 37(3), pp 227-241
2007
url
https://doi.org/10.1016/j.limno.2007.01.004View
Published, Version of Record (VoR)Open Access (Publisher-Specific) Open

Abstract

Achnanthidium Appalachian Mountains Diatoms Distribution Ecology Generalized additive models Non-parametric multiplicative regression models Rivers Taxonomy Water-quality assessment
Diatoms from the genus Achnanthidium are abundant in rivers, streams, and springs of the Appalachian Mountains. They inhabit clean and polluted waters, including those affected by acid mine drainage. The identification of Achnanthidium taxa is difficult due to their small cell size and insufficient information in the diatom floras. We studied the taxonomy and ecology of Achnanthidium in Appalachian rivers by analyzing a data set of benthic diatom samples and corresponding water chemistry data collected during several water-quality surveys from 181 sampling sites. Ten species were identified using scanning electron and light microscopy: A. alpestre (Lowe & Kociolek) Lowe & Kociolek, A. atomus (Hustedt) Monnier, Lange-Bertalot, & Ector, A. deflexum (Reimer) Kingston, A. duthii (Sreenivasa) Edlund, A. eutrophilum (Lange-Bertalot) Lange-Bertalot, A. cf. gracillimum (Meister) Lange-Bertalot, A. cf. latecephalum Kobayasi, A. minutissimum (Kützing) Czarnecki (sensu lato), A. reimeri (Camburn) comb. nov., and A. rivulare Potapova & Ponader. The distribution of common taxa in relation to water chemistry was studied by fitting non-parametric regression models (generalized additive models, GAM, and non-parametric multiplicative regression models, NPMR) to species relative abundances. Studied Achnanthidium species differed considerably in their responses to water chemistry. These results suggest that species-level identifications will lead to more accurate bioassessments.

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Domestic collaboration
Web of Science research areas
Limnology
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