Spatio-temporal population dynamics of six phytoplankton taxa

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