Phytoplankton functional trait database from "Long-term monitoring data shed light on in situ feeding preferences in bivalves: a taxonomic and trait-based approach to phytoplankton"

DOI

We built a trait database of 385 phytoplankton taxa recorded in five Atlantic bays in France between 2009 and 2018. We focused on seven traits known or potentially expected to be determinant for bivalve molluscs nutrition, including morphological traits such as maximum cell size, shape and cover (i.e. cell wall structure), the ability to form colonies, presence of spicules, ecological (habitat) and physiological (harmfulness) traits. The database published by Ramond et al. (2019 - doi.org/10.17882/51662) served as the starting point for traits related to cell size, cell cover, colony building and spicules. Other traits and final missing information were completed with a systematic review of the literature, the references of which are given in the database. This literature research was carried out starting with sites located in France and then moving further afield in Europe and the rest of the world depending on the information available. With the exception of harmfulness, we used the following specific rules to define the traits of taxa identified at taxonomic ranks above the species: (i) the traits of the most abundant species in the dataset were assigned to the corresponding genus (in the rare cases where no species were identified, the assigned traits were those of the species/genus observed elsewhere in France or the most abundant species/genus in the same family), (ii) the traits of the most abundant genera were assigned to the corresponding family, (iii) the traits of a virtual taxon (i.e. a group of taxa with similar morphologies) were those of its most abundant member. The table (.xlsx format) comprises three spreadsheets: i) a main database with trait values for all phytoplankton taxa and associated references, and details of the references used for ii) cell shape, harmfulness and ecological habitat and iii) the other traits.

Identifier
DOI https://doi.org/10.17882/105375
Metadata Access http://www.seanoe.org/oai/OAIHandler?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:seanoe.org:105375
Provenance
Creator Gangnery, Aline; Hernandez Farinas, Tania; Pouvreau, Stephane
Publisher SEANOE
Publication Year 2025
Rights CC-BY
OpenAccess true
Contact SEANOE
Representation
Resource Type Dataset
Discipline Biospheric Sciences; Ecology; Geosciences; Natural Sciences