Roy, Shovonlal ; Bhattacharya, Sabyasachi ; Das, Partha ; Chattopadhyay, Joydev (2007) Interaction among Non-toxic Phytoplankton, Toxic Phytoplankton and Zooplankton: Inferences from Field Observations Journal of Biological Physics, 33 (1). pp. 1-17. ISSN 0092-0606
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Official URL: http://doi.org/10.1007/s10867-007-9038-z
Related URL: http://dx.doi.org/10.1007/s10867-007-9038-z
Abstract
We explore the mutual dependencies and interactions among different groups of species of the plankton population, based on an analysis of the long-term field observations carried out by our group in the North–West coast of the Bay of Bengal. The plankton community is structured into three groups of species, namely, non-toxic phytoplankton (NTP), toxic phytoplankton (TPP) and zooplankton. To find the pair-wise dependencies among the three groups of plankton, Pearson and partial correlation coefficients are calculated. To explore the simultaneous interaction among all the three groups, a time series analysis is performed. Following an Expectation Maximization (E-M) algorithm, those data points which are missing due to irregularities in sampling are estimated, and with the completed data set a Vector Auto-Regressive (VAR) model is analyzed. The overall analysis demonstrates that toxin-producing phytoplankton play two distinct roles: the inhibition on consumption of toxic substances reduces the abundance of zooplankton, and the toxic materials released by TPP significantly compensate for the competitive disadvantages among phytoplankton species. Our study suggests that the presence of TPP might be a possible cause for the generation of a complex interaction among the large number of phytoplankton and zooplankton species that might be responsible for the prolonged coexistence of the plankton species in a fluctuating biomass.
Item Type: | Article |
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Source: | Copyright of this article belongs to Springer Nature Switzerland AG |
Keywords: | Coexistence;Paradox of plankton;Toxin-producing plankton;Partial correlation;Time series;E-M algorithm;VAR model |
ID Code: | 132408 |
Deposited On: | 16 Dec 2022 05:27 |
Last Modified: | 16 Dec 2022 05:27 |
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