Journal of Plankton Research Vol.23 no.2 pp.117-141, 2001
© Oxford University Press 2001
Universal multifractals and ocean patchiness: phytoplankton, physical fields and coastal heterogeneity
1 Physics Department And Giroq (groupe Interuniversitaire De Recherches Océanographiques Du Québec), Mcgill University, 3600 University Street, Montréal, Québec, H3a 2t8, 2 Département De Biologie Et Ciroq, Pavillon Vachon, Université Laval, Québec, Québec, G1k 7p4, 3 Department Of Zoology, College Of Biological Science, University Of Guelph, Guelph, Ontario, N1g 2w1, Canada, 4 Laboratoire De Modélisation En Mécanique, Bp 162, U. Pierre Et Marie-Curie, 4 PL. Jussieu, Paris, 75005, France, 5 Sultan Qaboos University, Faculty Of Agriculture, Department Of Fisheries, Po Box 34, Al-Khod 123, Sultanate Of Oman And 6 Research And Development, Lockheed Martin Electronic Systems Canada, 6111 Royalmount Avenue, Montreal, Quebec, H4p 1k6, Canada
We argue that a wide-range scaling approach is demanded by standard Stommel diagrams and that it can unify the treatment of phytoplankton variability over wide ranges of scales. By investigating the effects of coastal heterogeneity on the variability of in situ salinity (S), oxygen (
O), temperature (T), optical transmissivity (t) and phytoplankton proxy data (fluorescence; p) over the range ~0.4–1600 m, we statistically characterize the heterogeneity of these variables, determining both the range and types of scaling, as well as their scale-by-scale interrelationships. By comparing bays with systematically varying large-scale heterogeneity, we were able to investigate the influence of the latter on the variability, systematically determining the three universal multifractal parameters as well as the exponent characterizing extreme self-organized critical behaviour. We found that, consistent with turbulent dominated dynamics, T, O, S and t were scaling over essentially the entire observed range of scales, with T and O being statistically very close to passive scalars. However, p was quite different, displaying two regimes separated by a characteristic ‘planktoscale’ typically ~100 m, but highly variable. The large-scale regime was neither passive scalar nor growth dominated (Denman–Platt), but was rather in between the two (the corresponding exponent was Hp 
1/8 rather than 0 or 1/3, respectively). In addition, we found a new small-scale regime with Hp –1/3, which is much ‘rougher’ than passive scalar (which has Hp = +1/3). We propose a simple model involving both growth and turbulence to account for the large scale, and grazing and turbulence (predator–prey zooplankton/phytoplankton interactions) to account for the small scale. Depending on the value of a dimensionless grazing constant Gr = D/(
g2
) (where D is the zooplankton diffusion constant, g is the phytoplankton growth constant and is the turbulent energy flux), the small scale is dominated either by the turbulent grazing (Gr > 1) or by passive scalar turbulence (Gr < 1). In the grazing regime, we also theoretically predict that the density fluctuation exponent = –1/3, which is quite close to the data and quantifies the tendency of the zooplankton to uniformize the phytoplankton distribution by preferentially grazing high-concentration patches.
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