MEPS 294:295-309 (2005)  -  doi:10.3354/meps294295

Plankton patchiness, turbulent transport and spatial spectra

Peter J. S. Franks*

Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California 92093-0218, USA

ABSTRACT: Spatial variability of plankton is a well-known, though poorly characterized and understood, phenomenon. Several studies suggest that patches of plankton are essential to the growth and survival of some planktonic species; thus, any ability to predict the spatial patterns of plankton would significantly enhance our understanding of ocean ecosystems. Furthermore, models that accurately describe planktonic patchiness could permit a mechanistic understanding of the dynamics structuring the plankton. One such model is based on plankton being mixed in 3D isotropic turbulence, giving a k–5/3 slope to the spatial spectrum of plankton variability. Many papers have been published that (often favorably) compare their data to this k–5/3 model. Using a selection of papers published since 1993, I show, however, that the data in many of these studies have not been gathered on scales that allow comparison to the k–5/3 model. I then discuss whether planktonic data can even be used to test such a model: the model is continuum-based, while plankton are quanta at scales relevant to the turbulent scales. Still, many data sets resolving planktonic patchiness show a k–5/3 slope of the spectrum, or at least show a biological spectrum with a different slope than the temperature, salinity, or velocity spectra. I discuss several aspects of biological data that might consistently bias the spectral slopes of planktonic spectra, and conclude that the spectral slope does not contain enough information to distinguish among alternate models of plankton patchiness. While this paper is not a critique of the k–5/3 model or of the spectral method, it is a critique of the use of spectra of biological properties to test the k–5/3 model. I hope that by pointing out some of the pitfalls of spectral analysis of biological data we might gain better insights into the physical-biological interactions creating microscale patchiness in the ocean.


KEY WORDS: Turbulence · Patchiness · Spectrum · Inertial subrange · Plankton · Variability


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