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Orcid Publication

Detalle de: Quantifying long-term predictability in microbial plankton dynamics

Title Quantifying long-term predictability in microbial plankton dynamics
Abstract

Determining predictability in community turnover is a key ecological question. In the microbial world, seasonality has been reported for communities inhabiting temperate zones, but not much is known on seasonality for individual species. Specifically, we have a vague understanding on the amount of species displaying predictability during temporal community turnover as well as on their dynamics. Here we developed a ‘ Recurrence Index ’ to quantify predictability in microbial species. Applying our index to 18S rDNA metabarcoding data from one of the longest temporal observatories of marine plankton we determined that 13% of the picoeukaryotic and 19% of the nanoeukaryotic species, accounting for about 40% of the community abundance in both fractions, feature predictable dynamics when sampled monthly during 10 years. Thus, most of the species analysed had unpredictable temporal abundance patterns. Altogether, we show that species with both predictable and unpredictable temporal dynamics can occur within the same seasonal microbial community.

Apa Reference Giner, C.R., Balagué, V., Krabberød, A.K., Ferrera, I., Reñé, A., Garcés, E., Gasol, J.M., Logares, R. & Massana, R. (2017). Quantifying long-term predictability in microbial plankton dynamics. 10.1101/237743
Doi 10.1101/237743
Publication Date 21 Dec 2017
Publication Type Preprint
Researcher Ramiro Ernesto Logares
Ontology Microbial communities, Amplicon Sequencing, Marine Systems
Research Groups
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