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Microcosm pollution monitoring
Cairns, Jr., J.; Dickson, K.L.; Slocomb, J.P.; Almeida, S.P.; Eu, J.K.T.; Liu, C.Y.C.; Smith, H.F. (1974). Microcosm pollution monitoring, in: Hemphill, D.D. (Ed.) Trace substances in environmental health - 8. pp. 223-228
In: Hemphill, D.D. (Ed.) (1974). Trace substances in environmental health - 8. University of Missouri: Missouri. , more

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  • Cairns, Jr., J.
  • Dickson, K.L.
  • Slocomb, J.P.
  • Almeida, S.P.
  • Eu, J.K.T.
  • Liu, C.Y.C.
  • Smith, H.F.

    Management of aquatic ecosystems requires a clear understanding of the goals to be achieved, current information on the status of the ecosystem and the motivation and technology to take action. Control measures applied to aquatic ecosystems, in the absence of information on the condition of the system, are apt to be inappropriate and thus may overprotect the receiving system at times and underprotect it at others since the ability of ecosystems to receive wastes is not constant through time or from one ecosystem to another. A major determinant of the effectiveness and efficiency of ecological quality control is the lag time in the feedback of biological information. If the lag time is too great, the control measures may repeatedly overshoot or undershoot the desired goal. This microcosm monitoring system is based on the use of a coherent optical spatial filtering system to identify diatoms rapidly. Ideally a system of this type could function within a computer based network of in-stream monitoring stations measuring deviations from the normal or reference community of diatoms. The system is based on the utilization of laser generated Fourier transform holograms as spatial frequency filters designed to select diatoms of one particular structure from a mixture of diatoms of varying structure (i.e. to identify the type of diatom which matches that particular filter). A mechanical system fitted to a reference library of spatial filters of many different species of diatoms could then rapidly scan a sample consisting of a diatom community and greatly reduce the time required for sample analysis. This information could then be used in the management program along with chemical and physical data to obtain full beneficial use of the ecosystem without damage

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