This paper proposes a new approach to describing of Onego Lake plankton seasonal dynamics. The approach is based on the construction of the nonlinear regression measurement error models by virtue of the orthogonal distance method. The models describe average long-term plankton characteristics for every day of vegetative period, enable identify the main seasonal phenomena dates and evaluate annual and long-term plankton variability.
Russian Journal of Ecology – Springer Journals
Published: May 15, 2013
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