Diagnostic Properties of Phytoplankton Time Series from Remote Sensing
Remote sensing provides our only window into the phytoplankton community on synoptic scales, permitting the construction of spatially distributed time series of biomass indexed as chlorophyll concentration. Data from the SeaWiFS mission have accumulated to the point where they meet the criterion of a 10-year series. The seasonal phytoplankton cycle is the dominant mode of temporal variability. The time series can be used to construct a variety of ecological indicators of the pelagic system useful in ecosystem-based management. These are reviewed and examples of their implementation are presented. Phenology of phytoplankton blooms is given particular attention. Interannual variation in some of the indicators is strong, presumably a response to variation in large-scale forcing. Examination of the results in the context of a simple phytoplankton-nutrient model enhances the interpretation. Remote sensing imagery also lends itself to the retrieval of information on community structure, in addition to biomass. More information will be recovered from satellite imagery if the remote-sensing program is coupled closely to a ship program on which appropriate bio-optical observations are made. The data series can be distilled to yield concise descriptions of the unfolding of ecosystem characteristics through time.
KeywordsEcological indicators Phytoplankton Ocean colour Remote sensing Phenology
- Cushing, D.H. 1959. The seasonal variation in oceanic production as a problem in population dynamics. Journal du Conseil 24(3): 455–464.Google Scholar
- Feldman, G.C., and C.R. McClain. 2007. Ocean color web, SeaWiFS reprocessing 5.2. Greenbelt: NASA Goddard Space Flight Center.Google Scholar
- Friedland, K., J.A. Hare, G. Wood, L. Col, L. Buckley, D. Mountain, J. Kane, J. Brodziak, R.G. Lough, and C.H. Pilskaln. 2008. Does the fall phytoplankton bloom control recruitment of Georges Bank haddock, Melanogrammus aeglefinus, through parental condition? Canadian Journal of Fisheries and Aquatic Sciences 65(6): 1076–1086.CrossRefGoogle Scholar
- Hjort, J. 1914. Fluctuations in the great fisheries of Northern Europe, viewed in the light of biological research. Const. Int. Explor. Mer. 20: 1–228.Google Scholar
- LeQuéré, C., S.P. Harrison, I.C. Prentice, E.T. Buitenhuis, O. Aumont, L. Bopp, H. Claustre, L. C. da Cunha, R. Geider, X. Giraud, C. Klaas, K.E. Kohfeld, L. Legendre, M. Manizza, T. Platt, R.B. Rivkin, S. Sathyendranath, J. Uitz, A.J. Watson, and D. Wolf-Gladrow. 2005. Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models. Global Change Biology 11: 2016–2040.Google Scholar
- Longhurst, A. 1998. Ecological geography of the sea. San Diego: Academic.Google Scholar
- Longhurst, A. 2007. Ecological Geography of the Sea (2nd edn.). Amsterdam: Elsevier.Google Scholar
- Platt, T., P. Jauhari, and S. Sathyendranath. 1992. The importance and measurement of new production. In Primary productivity and biogeochemical cycles in the sea, eds. P.G. Falkowski, and A.D. Woodhead, 273–284. New York: Plenum.Google Scholar
- Platt, T., and S. Sathyendranath. 1996. Biological oceanography and fisheries management. Int. Counc. Explor. Sea CM 0: 3.Google Scholar
- Platt, T., G. N. White III, L. Zhai, S. Sathyendranath, and S. Roy. 2009. The phenology of phytoplankton blooms: Ecosystem indicators from remote sensing. Ecological Modelling. doi: 10.1016/j.ecolmodel.2008.11.022.
- Sathyendranath, S., V. Stuart, A. Nair, K. Oka, T. Nakane, H. Bouman, M.-H. Forget, H. Maass, and T. Platt. 2009. Carbon-to-chlorophyll ratio and growth rate of phytoplankton in the sea. Marine Ecology-Progress Series. doi: 10.3354/meps07998.
- Sverdrup, H.U. 1953. On conditions for the vernal blooming of phytoplankton. Journal du Conseil 18(3): 287–295.Google Scholar
- Tang, C. 2007. High-resolution monthly temperature and salinity climatologies for the northwestern North Atlantic Ocean. Canadian Data Report of Hydrography and Ocean Sciences 169: iv + 55.Google Scholar
- Walker, N.D., and N.N. Rabalais. 2006. Relationships among satellite chlorophyll a, river inputs, and hypoxia on the Louisiana Continental shelf, Gulf of Mexico. Estuaries and Coasts 29(6B): 1081–1093.Google Scholar