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Published on: November 12, 2021
Biogeography of dinoflagellate cysts in northwest Atlantic estuaries
Andrea M Price1, Vera Pospelova2, Michael R S Coffin3
1Department of Geography McGill University 805 Sherbrooke Street West Montréal QC H3A 0B9 Canada.
Abstract:
Few biogeographic studies of dinoflagellate cysts include the near-shore estuarine environment. We determine the effect of estuary type, biogeography, and water quality on the spatial distribution of organic-walled dinoflagellate cysts from the Northeast USA (Maine to Delaware) and Canada (Prince Edward Island). A total of 69 surface sediment samples were collected from 27 estuaries, from sites with surface salinities >20. Dinoflagellate cysts were examined microscopically and compared to environmental parameters using multivariate ordination techniques. The spatial distribution of cyst taxa reflects biogeographic provinces established by other marine organisms, with Cape Cod separating the northern Acadian Province from the southern Virginian Province. Species such as Lingulodinium machaerophorum and Polysphaeridinium zoharyi were found almost exclusively in the Virginian Province, while others such as Dubridinium spp. and Islandinium? cezare were more abundant in the Acadian Province. Tidal range, sea surface temperature (SST), and sea surface salinity (SSS) are statistically significant parameters influencing cyst assemblages. Samples from the same type of estuary cluster together in canonical correspondence analysis when the estuaries are within the same biogeographic province. The large geographic extent of this study, encompassing four main estuary types (riverine, lagoon, coastal embayment, and fjord), allowed us to determine that the type of estuary has an important influence on cyst assemblages. Due to greater seasonal variations in SSTs and SSSs in estuaries compared to the open ocean, cyst assemblages show distinct latitudinal trends. The estuarine context is important for understanding present-day species distribution, the factors controlling them, and to better predict how they may change in the future.
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