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JPR Advance Access originally published online on August 7, 2007
Journal of Plankton Research 2007 29(9):803-821; doi:10.1093/plankt/fbm061
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© The Author 2007. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

Asynchronous vertical migration and bimodal distribution of motile phytoplankton

David K. Ralston1,*, Dennis J. McGillicuddy, Jr.1 and David W. Townsend2

1 Applied Ocean Physics and Engineering, MS #12, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA 2 School of Marine Sciences, University of Maine, Orono, ME 04469, USA

* Corresponding Author: dralston{at}whoi.edu

Received on December 21, 2006; accepted on July 30, 2007


  Abstract

Some motile phytoplankton have the capability to exploit deep sources of nutrients in a vertical migration cycle: photosynthesis in the near-surface layer, transit to depth, uptake of the limiting nutrient and transit back to the surface layer. If all four steps can be completed within 24 h, then migrations can be synchronized to the day/night cycle to maximize photosynthetic efficiency. Alternatively, if physiological, behavioral or environmental factors make it impossible for the cycle to be completed in 24 h, then migration may be asynchronous. Many observations of phytoplankton reveal bimodal vertical distributions of organisms, with maxima near the surface and the nutricline. We demonstrate how bimodal vertical distributions of phytoplankton may be symptomatic of asynchronous vertical migration using a Lagrangian Ensemble numerical model. We simulate vertical migration of the dinoflagellate Alexandrium fundyense in conditions similar to those in the Gulf of Maine, where bimodal distributions of A. fundyense have been observed. Migration is regulated by internal nutritional state—organisms swim down toward the nitracline when depleted of nitrogen, and return to the surface after nutrient uptake. We test the sensitivity of the results to growth rate, nitrogen uptake rate and swimming speed, and find that organism distributions can be bimodal or unimodal depending on conditions. Finally, we develop an analytical estimate for population distribution based on organism characteristics and nutricline depth.

Communicating editor: K.J. Flynn


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