title: Importance of sampling frequency when collecting diatoms.
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.
authors.affiliation: Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, 24118 Kiel, Germany.|Aarhus Institute of Advanced Studies, Aarhus University, Høegh-Guldbergs Gade 6B, 8000 Aarhus C, Denmark.|Department of Bioscience, Aarhus University, Ole Worms Allé 1, 8000 Aarhus C, Denmark.
authors.forename: Naicheng
authors.initials: N
authors.lastname: Wu
authors.affiliation: Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, 24118 Kiel, Germany.
authors.forename: Claas
authors.initials: C
authors.lastname: Faber
authors.affiliation: Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, 24118 Kiel, Germany.
authors.forename: Xiuming
authors.initials: X
authors.lastname: Sun
authors.affiliation: Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, 24118 Kiel, Germany.
authors.forename: Yueming
authors.initials: Y
authors.lastname: Qu
authors.affiliation: Pearl River Fisheries Research Institute, Chinese Academy of Fishery Science, 510380 Guangzhou, China.
authors.forename: Chao
authors.initials: C
authors.lastname: Wang
authors.affiliation: Marine Science and Engineering, Red Sea Research Centre, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
authors.forename: Snjezana
authors.initials: S
authors.lastname: Ivetic
authors.affiliation: Department of Bioscience, Aarhus University, Ole Worms Allé 1, 8000 Aarhus C, Denmark.
authors.forename: Tenna
authors.initials: T
authors.lastname: Riis
authors.affiliation: Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, 24118 Kiel, Germany.
authors.forename: Uta
authors.initials: U
authors.lastname: Ulrich
authors.affiliation: Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, 24118 Kiel, Germany.
authors.forename: Nicola
authors.initials: N
authors.lastname: Fohrer
mesh_terms: D000465:Algorithms; D017377:Diatoms / Q000145:classification*; D004784:Environmental Monitoring / Q000379:methods*; D005618:Fresh Water / Q000032:analysis; D045483:Rivers; D012621:Seasons