Integrating phytoplankton phenology, traits, and model-data fusion to advance bloom prediction
Date
2025
Authors
Hipsey, M.R.
Carey, C.C.
Brookes, J.D.
Burford, M.A.
Dang, H.V.
Ibelings, B.W.
Hamilton, D.P.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Limnology and Oceanography Letters, 2025; 10(6):1-20
Statement of Responsibility
Matthew R. Hipsey, Cayelan C. Carey, Justin D. Brookes, Michele A. Burford, Hoang V. Dang, Bas W. Ibelings, David P. Hamilton
Conference Name
Abstract
While there is a diversity of approaches for modeling phytoplankton blooms, their accuracy in predicting the onset and manifestation of a bloom is still lagging behind what is needed to support effective management. We outline a framework that integrates trait theory and ecosystem modeling to improve bloom prediction. This framework builds on the concept that the phenology of blooms is determined by the dynamic interaction between the environment and traits within the phytoplankton community. Phytoplankton groups exhibit a collection of traits that govern the interplay of processes that ultimately control the phases of bloom initiation, maintenance, and collapse. An example of process-trait mapping is used to demonstrate a more consistent approach to bloom model parameterization that allows better alignment with models and laboratory- and ecosystem-scale datasets. Further approaches linking statistical-mechanistic models to trait parameter databases are discussed as a way to help optimize models to better simulate bloom phenology and allow them to support a wider range of management needs.
School/Discipline
Dissertation Note
Provenance
Description
OnlinePubl.
Available online 13 August 2025
Access Status
Rights
© 2025 The Author(s). Limnology and Oceanography Letters published by Wiley Periodicals LLC on behalf of Association for the Sciences of Limnology and Oceanography. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.