Spatio-temporal population dynamics of six phytoplankton taxa

A1 Journal article (refereed)

Internal Authors/Editors

Publication Details

List of Authors: Louise Forsblom, Sirpa Lehtinen, Andreas Lindén
Publication year: 2019
Journal: Hydrobiologia
Volume number: 828
Issue number: 1
eISSN: 1573-5117


Studying aquatic population dynamics using spatio-temporal monitoring
data is associated with a number of challenges and choices. One can let
several samples represent the same population over larger areas, or
alternatively model the dynamics of each sampling location in continuous
space. We analysed the spatio-temporal population dynamics of six
phytoplankton taxa in the Baltic Sea applying multivariate state-space
models with first-order density dependence. We compared three spatial
scales and three models for spatial correlation between predefined
subpopulations using information theoretic model selection. We
hypothesised that populations close to each other display similar
dynamic properties and spatial synchrony decreasing with the distance.
We further hypothesize that intermediate-scale grouping of data into
subpopulations may parsimoniously represent such dynamics. All taxa
showed constant density dependence across space and strong spatial
synchrony, consistently requiring a parameter for spatial correlation
whenever models included several population states. The most
parsimonious spatial structure varied between taxa, most often being one
panmictic population or ten intercorrelated population states.
Evidently, longer time-series, containing more information, provide more
options for modelling detailed spatio-temporal patterns. With a few
decade-long plankton time-series data, we encourage determining the
appropriate spatial scale on biological grounds rather than model fit.

Last updated on 2020-04-08 at 06:21