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.
Wu N, Faber C, Sun X, Qu Y, Wang C, et al. (2016) Importance of sampling frequency when collecting diatoms. Scientific Reports 6: 36950. Available: http://dx.doi.org/10.1038/srep36950.
This study was supported financially by a DFG grant (FO 301/15-1, FO 301/15-2, WU 749/1-1, WU 749/1-2) (N. Wu, C. Faber), AIAS CO-FUND funding (N. Wu) and China Scholarship Council (CSC) (X. Sun, Y. Qu). We would like to thank Dr. Jessica Barker for the English polishing, Mrs. Monika Westphal, Mrs. Bettina Hollmann and student assistances for their support during the field campaigns. B. Messyasz, M. Kokociński and C. Wetzel helped greatly with the diatom identification. The constructive comments of two anonymous reviewers greatly improved our manuscript.
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