Community Structures of Phytoplankton with Emphasis on Toxic Cyanobacteria in an Ohio Inland Lake during Bloom Season

Abstract

The community structures of phytoplankton are important factors and indicators of lake water quality. Harmful algal blooms severely impact water supply, recreational activities and wildlife habitat. This study aimed to examine the phytoplankton composition and variations using microscopy, and identify harmful Cyanobacteria in weekly samples taken from four sites at Harsha Lake in southwest Ohio. Over the course of the summer in 2015, the phytoplankton of Harsha Lake consisted mainly of 13 taxa belonging to Bacillariophyta, Chlorophyta, Cryptophyta, Cyanobacteria, Dinophyta and Euglenophyta. Their significant successions started with Bacillariophyta and/or Chlorophyta, then bloomed with Cyanobacteria and ended with Chlorophyta and/or Dinophyta. Cyanobacteria members: Microcystis, Planktothrix, Dolichospermum, Aphanizomenon, Cylindrospermopsis, and Oscillatoria from the Cyanophyceae were identified to be dominant genera. These organisms varied spatially and temporally in similar patterns along with the variations of nutrients and formed the summer bloom with the total biomasses ranging from 0.01 to 114.89 mg L−1 with mean of 22.88 mg L−1. M. aeruginosa and P. rubescens were revealed as the microcystin producers, while A. circinalis and Aphanizomenon sp. were identified as a saxitoxin producer through cloning and sequencing PCR products of mcyA, mcyE and sxtA genes. The biomasses of phytoplankton, Cyanobacteria and Microcystis were positively correlated to nutrients, especially to total nitrogen. The total ELISA measurement for microcystin positively correlated with Cyanobacteria (R2 = 0.66, P < 0.0001), Microcystis (R2 = 0.64, P < 0.0001) and phytoplankton (R2 = 0.59, P < 0.0001). The basic information on the occurrence and biomasses of Cyanobacteria and total phytoplankton, and the analysis for toxic species, which were the first report for the inland water in Ohio, USA, will document the succession patterns of phytoplankton and toxin production over a season and provide data to predict risk occurrence to both human and ecological factors.

Spatial and temporal dynamics of a freshwater eukaryotic plankton community revealed via 18S rRNA gene metabarcoding

“…We also noted differences in taxonomic coverage between metabarcoding-and microscopybased approaches. While we detected several genera within the eukaryotic phytoplankton phyla reported by Chen et al (2017), specifically, Cyclotella (Bacillariophyta), Skeletonema (previously classified as Melosira, Bacillariophyta), Cryptomonas (Cryptophyta), Ceratium (Dinophyta/Dinoflagellata), and Peridinium (Dinophyta/Dinoflagellata), we did not detect genera such as Euglena (Euglenophyta) and Chlamydomonas (Chlorophyta). The lack of detection of Euglena can be explained by the poor sequence match of the sequencing primers used (particularly the forward primer).…”

“…For the zooplankton, the comparisons were made to data collected in May, June, and August of 2016 using plankton nets (6-m vertical draw, 150-μm mesh) for three different sites (LH1, LH2, LH4; US Army Corps of Engineers unpublished data). For the phytoplankton comparison, we used data reported by Chen et al (2017) for surface water samples collected from the same Lake Harsha sites during the same sampling period. Overall, the comparisons revealed similar population abundance trends among some taxa.…”

“…In comparison to phytoplankton data (Chen et al, 2017), dinoflagellates (Dinophyta/ Dinoflagellata) and diatoms (Bacillariophyta) were observed in similar relative abundance (cyanobacteria were excluded in the analysis as we used eukaryote-specific 18S rRNA gene primers). Specifically, dinoflagellates and diatoms comprised approximately 44 and 12%, respectively, of the total number of phytoplankton sequences while these groups were estimated to comprise approximately 59 and 9% of the total phytoplankton biomass based on morphological analysis.…”

Carbon and nitrogen recycling during cyanoHABs in dreissenid-invaded and non-invaded US midwestern lakes and reservoirs

“…The abundance of these eukaryotes also likely depends on seasonality and the influx of nutrients and increase in temperature that lead to the formation of harmful blooms. For instance, in Lake Harsha (a eutrophic reservoir in southwestern Ohio), algae were more abundant prior to and following the bloom of cyanobacteria (Chen et al, 2017). Thus, our observations of abundant Microcystis in the Ohio and Licking Rivers, Cylindrospermopsis in Brookeville Lake, Cyanobium in the Auglaize, lower Maumee, and Sandusky Rivers, and Planktothrix in most lakes and reservoirs, could reflect sampling time (e.g., September and August, respectively).…”

A Review and Perspective of eDNA Application to Eutrophication and HAB Control in Freshwater and Marine Ecosystems

“…The detection of species diversity, community structures and species change patterns are often of considerable significance in assessing the effectiveness of eutrophication and HAB control. For example, the biomass and species compositions of phytoplankton are important factors and indicators of lake water quality [87]. The analysis of species compositions can help discover ecological indicators to provide instructions to mitigate eutrophication and HABs in aquatic environments.…”