ArticleScientific reports2016
Importance of sampling frequency when collecting diatoms.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Diatoms recovery from wastewater: Overview from an ecological and economic perspective.Journal of water process engineering · 2021Article
- Strong and recurring seasonality revealed within stream diatom assemblages.Scientific reports · 2019Article
- Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.Ecology and evolution · 2018Article
- Diatoms as an indicator for tile drainage flow in a German lowland catchment.Environmental sciences Europe · 2018Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms' temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected and analyzed daily riverine diatom samples over a 1-year period (25 April 2013-30 April 2014) at the outlet of a German lowland river. The samples were classified into five clusters (1-5) by a Kohonen Self-Organizing Map (SOM) method based on similarity between species compositions over time. ASFs were determined to be 25 days at Cluster 2 (June-July 2013) and 13 days at Cluster 5 (February-April 2014), whereas no specific ASFs were found at Cluster 1 (April-May 2013), 3 (August-November 2013) (>30 days) and Cluster 4 (December 2013 - January 2014) (<1 day). ASFs showed dramatic seasonality and were negatively related to hydrological wetness conditions, suggesting that sampling interval should be reduced with increasing catchment wetness. A key implication of our findings for freshwater management is that long-term bio-monitoring protocols should be developed with the knowledge of tracking algal temporal dynamics with an appropriate sampling frequency.
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