Symbolic Analysis of Plankton Swimming Trajectories: Case Study of Strobilidium sp. (Protista) Helical Walking under Various Food Conditions
| Type | Article | ||||||||
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| Date | 2010-08-20 | ||||||||
| Language | English | ||||||||
| Author(s) | Vandromme Pieter1, 2, 3, 4, Schmitt François G.1, 2, 3, Souissi Sami1, 2, 3, Buskey Edward J.5, Strickler J. Rudi6, Wu Cheng-Han7, Hwang Jiang-Shiou7 | ||||||||
| Affiliation(s) | 1 : Univ Lille Nord de France, France 2 : USTL, LOG, F-62930 Wimereux, France 3 : CNRS, UMR 8187, F-62930 Wimereux, France 4 : Univ Paris 6, UMR 7093 LOV, Observatoire Océanologique, BP 28, 06234 Villefranche-sur-mer, France 5 : University of Texas at Austin, Marine Science Institute, 750 Channel View Drive, Port Aransas, TX 78373-5015 USA 6 : Great Lakes WATER Institute, University of Wisconsin - Milwaukee, 600 E. Greenfield Ave., Milwaukee, WI 53204-2944 USA 7 : Institute of Marine Biology, National Taiwan Ocean University, Keelung 202, Taiwan |
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| Source | Zoological Studies (1021-5506) (Biodiversity Research Center, Academia Sinica), 2010-08-20 , Vol. 49 , N. 3 , P. 289-303 | ||||||||
| Keyword(s) | Protista, Plankton behavior, Swimming states, Symbolic dynamics, Simulation | ||||||||
| Abstract | The swimming behavior of the ciliate Strobilidium sp. was recorded using cinematographic techniques. A density of 20 ciliates/ml was used under 4 experimental food conditions: 121, 625, 3025, and 15,125 cells/ml of the dinoflagellate Gymnodinium sp. In total, 100 trajectories per experiment were recorded and analyzed. We classified this ciliate’s swimming trajectories into categories we called “helix”, “non-helix”, and “break”. These swimming states were identified using automated recognition of helices, based on values of swimming trajectory angles. We performed a symbolic analysis of the succession of swimming states which enabled discrimination between food concentration experiments, and provided a more-complete characterization of the swimming behavior. We found that helical swimming patterns first increased with food concentration then decreased with a corresponding increase in the numbers of breaks. Non-helical motions were related to high food concentrations. We further used these results to simulate a ciliate’s trajectories using a symbolic dynamic model to generate a sequence series. Helices were reconstructed using a model with 2 inputs: amplitude and period. This study shows that a methodology developed to describe copepod behavior can also be applied to characterize and simulate ciliate helical and non-helical swimming dynamics. | ||||||||
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