Phytoplankton traits from long-term oceanographic time-series

Mutshinda, CM, Finkel, ZV, Widdicombe, CE and Irwin, AJ 2017 Phytoplankton traits from long-term oceanographic time-series. Marine Ecology Progress Series. https://doi.org/10.3354/meps12220

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Official URL: http://www.int-res.com/abstracts/meps/v576/p11-25/

Abstract/Summary

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.

Item Type: Publication - Article
Additional Keywords: Phytoplankton, Time-series, Traits, Growth rate, Grazing rate, English Channel
Subjects: Botany
Computer Science
Data and Information
Ecology and Environment
Marine Sciences
Divisions: Plymouth Marine Laboratory > National Capability categories > Added Value
Plymouth Marine Laboratory > National Capability categories > Western Channel Observatory
Plymouth Marine Laboratory > Science Areas > Marine Ecology and Biodiversity
Plymouth Marine Laboratory > Science Areas > Marine System Modelling
Depositing User: Claire Widdicombe
Date made live: 02 May 2018 14:58
Last Modified: 13 Dec 2023 12:21
URI: https://plymsea.ac.uk/id/eprint/7887

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