On the roles of cell size and trophic strategy in North Atlantic diatom and dinoflagellate communities

• Published in: Limnology and Oceanography
• Main Authors: Barton, Andrew D., Finkel, Zoe V., Ward, Ben A., Johns, David G., Follows, Michael J.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2012
• Subjects: North Atlantic
• Online Access: http://dx.doi.org/10.4319/lo.2013.58.1.0254; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.4319%2Flo.2013.58.1.0254; https://aslopubs.onlinelibrary.wiley.com/doi/pdf/10.4319/lo.2013.58.1.0254

We have examined the inter‐ and intra‐group seasonal succession of 113 diatom and dinoflagellate taxa, as surveyed by the Continuous Plankton Recorder (CPR) in the North Atlantic, by grouping taxa according to two key functional traits: cell size (µg C cell −1 ) and trophic strategy (photoautotrophy, mixotrophy, or heterotrophy). Mixotrophic dinoflagellates follow photoautotrophic diatoms but precede their obligate heterotrophic counterparts in the succession because of the relative advantages afforded by photosynthesizing when light and nutrients are available in spring. The mean cell size of the sampled diatoms is smallest in the summer, likely because of the higher specific nutrient affinity of smaller relative to larger cells. Contrastingly, we hypothesize that mixotrophy diminishes the size selection based on nutrient limitation and accounts for the lack of a seasonal size shift among surveyed dinoflagellates. Relatively small, heterotrophic dinoflagellates (µg C cell −1 < 10 −3 ) peak after other, larger dinoflagellates, in part because of the increased abundance of their small prey during nutrient‐deplete summer months. The largest surveyed diatoms (µg C cell −1 > 10 −2 ) bloom later than others, and we hypothesize that this may be because of their relatively slow maximum potential growth rates and high internal nutrient storage, as well as to the slower predation of these larger cells. The new trait database and analysis presented here helps translate the taxonomic information of the CPR survey into metrics that can be directly compared with trait‐based models.