Phytoplankton traits from long-term oceanographic time-series

Abstract

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 576:11-25 (2017) - DOI: https://doi.org/10.3354/meps12220 Phytoplankton traits from long-term oceanographic time-series Crispin M. Mutshinda1, Zoe V. Finkel2, Claire E. Widdicombe3, Andrew J. Irwin1,* 1Mathematics & Computer Science, Mount Allison University, Sackville, NB E4L 1E6, Canada 2Environmental Science, Mount Allison University, Sackville, NB E4L 1A7, Canada 3Plymouth Marine Laboratory, Prospect Place, Plymouth PL1 3DH, UK *Corresponding author: airwin@mta.ca ABSTRACT: Trait values are usually extracted from laboratory studies of single phytoplankton species, which presents challenges for understanding the immense diversity of phytoplankton species and the wide range of dynamic ocean environments. Here we use a Bayesian approach and a trait-based model to extract trait values for 4 functional types and 10 diatom species from field data collected at Station L4 in the Western Channel Observatory, English Channel. We find differences in maximum net growth rate, temperature optimum and sensitivity, half-saturation constants for light and nitrogen, and density-dependent loss terms across the functional types. We find evidence of very high linear loss rates, suggesting that grazing may be even more important than commonly assumed and differences in density-dependent loss rates across functional types, indicating the presence of strong niche differentiation among functional types. Low half-saturation constants for nitrogen at the functional type level may indicate widespread mixotrophy. At the species level, we find a wide range of density-dependent effects, which may be a signal of diversity in grazing susceptibility or biotic interactions. This approach may be a way to obtain more realistic and better-constrained trait values for functional types to be used in ecosystem modeling. KEY WORDS: Phytoplankton · Time series · Traits · Growth rate · Grazing rate · English Channel Full text in pdf format Supplementary material PreviousNextCite this article as: Mutshinda CM, Finkel ZV, Widdicombe CE, Irwin AJ (2017) Phytoplankton traits from long-term oceanographic time-series. Mar Ecol Prog Ser 576:11-25. https://doi.org/10.3354/meps12220 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 576. Online publication date: August 03, 2017 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2017 Inter-Research.