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Application of functional data analysis to investigate seasonal progression with interannual variability in plankton abundance in the Bay of Fundy,Canada
Authors:Takayoshi Ikeda  Michael Dowd  Jennifer L Martin
Institution:1. Graduate School of Environmental Earth Science, Hokkaido University, N10W5 Sapporo 060-0810, Japan;2. Department of Mathematics and Statistics, Dalhousie University, Halifax, NS, Canada B3H 3J5;3. Fisheries and Oceans Canada, Biological Station, 531 Brandy Cove Road, St. Andrews, NB, Canada E5B 2L9
Abstract:The statistical technique of functional data analysis (FDA) is applied to a time series analysis of plankton monitoring data. The analysis is focused on revealing patterns in the seasonal cycle to assess interannual variability of several different taxonomic groups of plankton. Cell concentrations of diatom, dinoflagellate and zooplankton abundances from the Bay of Fundy, Canada provide the observations for analysis. FDA was performed on the log-transformed abundance data as a new approach for treating such types of sparse and noisy data. Differences in the seasonal progression were seen, with peak numbers, timings and abundance levels varying for the three groups as determined by curve registration and higher order derivatives using the objectively fit FDA curves. Nonmetric multidimensional scaling was used to capture seasonal variation among years. These results were further assessed in terms of dominant species and the relationships between groups for different seasons and years. It is anticipated that the easy to use, general and flexible technique of FDA could be applied to a wide variety of marine ecological data that are characterized by missing values and non-Gaussian distributions.
Keywords:statistical analysis  diatoms  algae blooms  temporal variations  interannual variability  abundance estimation
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