Issue № 4 |
Original research |
pdf-version |
Syarki Maria | Northern water problems Institute KRC RAN, Petrozavodsk, st.A.Nevskogo, 50, msyarki@yandex.ru |
Keywords: least squares method orthogonal distance minimization method seasonal dynamics trajectory time shifts intra-annual and inter-annual variability phenological phases zooplankton |
Summary: The first response of natural systems to climate change is temporary shifts in seasonal phenomena. The paper considers approaches and methods for studying the zooplankton seasonal dynamics with special attention to temporal variability. The analysis and formalization of the average long-term trajectories of the abundance seasonal dynamics were carried out, and the phases of the seasonal process or phenophases were identified based on a series of data on zooplankton of the Kondopoga Bay of Lake Onega (1988–2021). The determination of the trajectories of the dynamics was carried out using the moving average methods and approximation by a given function. The parameters of the function were determined by the least squares regression (LSR) and orthogonal distance regression (ODR) methods. It is shown that a more accurate method is to use ODR. The scale of their intra-annual and interannual variability was estimated based on a series of models of the average long-term seasonal dynamics of quantities. The scale of possible time shifts was estimated and criteria for the extremity of rebound points were proposed. It was shown that within the vegetation period there are reliably 4 phenophases with characteristic features of the zooplankton structure using the method of discriminant analysis. Their terms differ from calendar seasons. Information obtained by different methods (continuous and discrete approaches) complement each other. Methods for formalizing seasonal plankton dynamics are the basis for assessing the response of plankton to fluctuations in climatic and anthropogenic factors. © Petrozavodsk State University |
Received on: 30 August 2024 Published on: 10 December 2024 |