THE ABC'S OF DIATOM IDENTIFICATION USING LASER HOLOGRAPHY

John CAIRNS, Jr .*, K . L. DICKSON*, John SLOCOMB*

Biology Department and Center for Environmental Studies ; Virginia Polytechnic Institute and State University,Blacksburg, Virginia 24061 U .S.A .

Received July 23, 1976

Keywords: Laser holography, diatom identification, rapid biological information systems, pollution monitoring

* Co-authors

Abstract

Biomonitoring systems designed to protect the integrity of aqua-tic ecosystems must satisfy complementary requirements if theyare to be used in a successful management program. First, theymust generate reliable information with respect to the currentbiological status of the ecosystem ; and second, they must be ca-pable of reducing the lag time in the feedback of this information .This paper describes a biomonitoring system, currently being de-veloped, that employs coherent optical spatial filtering techni-ques to rapidly identify diatoms and process species-abundanceinformation. Preliminary results indicate that the optical pro-blems associated with such a system can be overcome satisfac-torily, although investigations are continuing into the problem ofinterfacing a microscope directly to the optical system . We envi-sion that this system can eventually be employed in a manage-ment program along with chemical and physical data to obtainfull beneficial use of the ecosystem without damage .

Introduction

At the 1975 Phycological Society Meetings with theAmerican Institute of Biological Sciences at Corvallis,Oregon, it became evident while one of us (Cairns, inpress a) was presenting a related paper that there was con-siderable interest as well as misunderstanding about alaser system being developed at Virginia Polytechnic In-stitute and State University . The purpose of this paper is :(i) to describe the apparatus; (ii) indicate the stage ofdevelopment; (iii) suggest uses and limitations of theapparatus ; (iv) provide sources of further information .

Dr. W. Junk b . v. Publishers - The Hague, The Netherlands

Hydrobiologia vol . 54, 1, pag . 7-16, 1977

We wish to emphasize that this system is not :(a) a fully operational unit ready for commercial produc-

tion ;(b) a replacement for the professional judgments of

skilled taxonomists ;(c) a means of describing new species or phylogenetic re-

lationships ;(d) a unit designed to provide new insights into diatom

structure .Rather, this system is :

(a) a unit that will provide rapid identification of the spe-cies in a diatom community using type specimensfurnished by a diatom taxonomist (e .g ., it will serveas a `taxonomic extender' which can use the judg-ments of professional taxonomists and speed up theirapplication) ;

(b) an operational experimental unit capable of identi-fying all individuals structurally similar to the indivi-dual specimen from which the filter was made - butwith a number of problems as yet unresolved whichmust be resolved for full operation ;

(c) a system which promises to streamline the presentlaborious and often arduous effort of qualified diato-mists by speeding up routine identifications and there-by freeing them so that more time can be devoted tointerpretation and judgments .

The need for rapid biological information systems forpollution monitoring and environmental quality controlhas been described by Cairns et al . (1970, 1973a). Therationale for ecosystem management versus protectionof individual species has been discussed by Cairns (1972,1975, in press b) . Related information is in Cairns et al .

7

(1972 a) and Cairns (1974) . The laser unit can be used toprovide information on (1) the number of species, (2) thekinds of species, and (3) the number of individuals perspecies in a diatom community, thus making it compati-ble with any assessment system based on information ofthis type. It would be equally suitable for indicator speciesanalyses or diversity indices .

The following papers are referenced for readers who

wish more detail or are interested in the development ofthe apparatus : Cairns et al ., 1972 b, 1973 b, 1974, in pressa, b, c ; Almeida et al ., 1971, 1975, in press a, b; Dicksonet al ., in press .

Management of aquatic ecosystems requires a clearunderstanding of the goals to be achieved, current infor-mation on the status of the ecosystem, and the motiva-tion and technology to take action . Control measuresapplied to aquatic ecosystems, in the absence of infor-mation on the condition of the system, are apt to be in-appropriate . They may overprotect the receiving systemat times and underprotect it at others since the ability of

ecosystems to receive wastes is not constant through timeor from one ecosystem to another. A major determinantof the effectiveness and efficiency of ecological qualitycontrol is the lag time in the feedback of biological infor-mation . If the lag time is too great, the control measuresmay repeatedly overshoot or undershoot the desired goal .

Two types of biological monitoring systems are neededto adequately manage and protect aquatic resources .First, one needs biological monitors which can serve as`early warning systems.' These are designed to detect in-dustrial spills of hazardous materials and thus preventecological damage . An array of different biomonitoringsystems of this type have been developed (Cairns, Dick-son, and Westlake, in press). Secondly, we need bio-monitoring systems which can evaluate the `health' ofbiological communities found in the aquatic ecosystemsreceiving waste discharges . These 'in-stream' monitoringsystems are in early stages of development .

This paper describes a biomonitoring system underdevelopment at Virginia Polytechnic Institute and StateUniversity which should ultimately become a means ofrapidly determining diatom community structure . Thediatoms constitute a group of unicellular algae whichhave been found to reflect complex shifts in water quality(Patrick et al ., 1954, 1968; Patrick, 1971 ; Archibald, 1 972) .Both changes in the kinds of diatom species present andchanges in the species-abundance relationships in a com-munity can provide valuable information in the assess-ment of the effects of pollutants .

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The discussions which follow describe the current stageof development and operation of a rapid automated sys-tem which employs laser holographic techniques for theidentification of diatom species. The prototype modelis being used to address the optical problems associatedwith diatom recognition . In addition, we are developingthe electro-optical and computer hardware/software sys-tems that are essential for the automation of the proto-

type .

The prototype system

Pattern RecognitionThe taxonomy of the diatoms is based primarily on therecognition of certain patterns of physical form which areapparent in the cleared frustule of the cell . These patterns,or character sets, are visually matched against somereference descriptor (usually a taxonomic key) by thetaxonomist in order to identify the diatom . This kind ofpattern recognition process is not unique to taxonomicwork. Vander Lugt (1965) introduced the use of speciallyconstructed holograms as optical spatial filters whichcould be employed in character recognition studies . Be-cause the diatoms possess the desirable properties ofrigidity of form and complex character sets, they are

quite suitable for pattern recognition using coherent op-tical spatial filtering techniques .

The optical spatial filter used for character recognitionis essentially a holographic record of the two-dimensionalperiodic or aperiodic structure of an object . Once the filter

has been formed, it can then be used to sift data in theform of complex wavefronts from unknown objects . Ifone of these unknown objects generates the same type op-tical information that has been stored on the filter, the in-teraction of object and filter will provide a bright spot ofthe illuminating light at a specific point beyond the filter,indicating that a match or character recognition has oc-curred. By constructing different optical filters for dif-ferent objects, a virtually unlimited number of identifi-cations can be made . More specifically, one should beable to construct optical filters for any species of diatomwhich has a unique set of structural characteristics, andsubsequently, use these filters to identify species in sam-ples .

Formation of the Optical FilterIn the present optical system, 35 mm transparencies ofdiatoms were used as input specimens rather than actual

images from a microscopic field of view . There has beenno attempt to couple a microscope directly to the system .Instead, fields of view on a microscope slide are photo-graphed to obtain high quality black and white transpar-encies . The magnifications required depend on the dia-tom size. The photographic step is a definite bottleneck .However, we anticipate that this step can be eventuallyeliminated through the use of real-time recording materi-als (as opposed to photographic emulsions presently usedwhich require not only exposure but development as well)such as the new photochromic films being developed .These real-time film materials can be used to record aprojected field of view from a microscope without theusual processing .

Any diatom specimen, whether periodic or aperiodicin its configuration, forms a diffraction pattern in the rearfocal plane of an imaging lens when properly illuminated(Slaytor, 1970). It can be shown (Collier et al ., 1971) thatthe amplitude distributions of the object are related tothis diffraction pattern by Fourier transform functions .Thus, the transformed wavefront eminating from thespecimen contains all the structural information of thefrustule, and this information can be translated (or coded)in the form of an interference pattern . In order to preserveall this information, it is necessary to employ holographictechniques .

Figure i shows the arrangement of apparatus necessary

LASER

BEAMSEPARATION

MA

'146100

to form the Vander Lugt type hologram which was usedas the optical spatial filter. The beam from a helium-neonlaser is split into two pathways, one pathway serves as asource of reference waves, and the other passes through aphotomicrographic transparency of the diatom speci-men for which the optical filter is to be made . As thebeam passes through the image of the diatom, it isuniquely altered in a manner corresponding to the struc-tural information of the frustule . A lens is then used totransform and focus the object waves on a photographicplate which is located in the rear focal plane of the lens .The reference waves are also imaged on the photographicplate at some specific angle to the object waves and the re-sulting interference pattern recorded . The developed plateis the optical spatial filter (Vander Lugt hologram) con-taining a complete record of the structural pattern of theoriginal diatom specimen . Since the structural pattern ofthe frustule is taxonomically unique, the optical filter isanalogous to a fingerprint . By changing the angle betweenthe reference and object waves at the point of incidence onthe photographic plate, different aspects of the structuralcharacter of the diatom can be emphasized in the filter(e .g., either overall shape of the frustule to the exclusionof detailed structure or vice versa) .

Approximately 100 optical spatial filters can be placedon a single 50 mm by 50 mm photographic plate. Forexample, Figure 2 shows 16 optical filters for 16 different

MIRROR

1

COHERENTLIGHT WAVES

POSITIVEIMAGE OF ADIATOMOBJECTALTERED

LIGHT WAVES CONTAININGOPTICAL INFORMATION

OF DIATOM

PHOTOGRAPHICGLASS PLATE

TRANSFORMEDOBJECT WAVES

INTERACTION OFREFERENCE AND OBJECTWAVES TO FORM THE

INTERFERENCE PATTERN

Fig . i . The construction of the optical spatial filter is accomplished through the use of the basic arrangement of appara-tus shown . See text for explanation .

9

diatom species. Notice how each differs in the location oflight and dark areas . Also, notice the bands that are pre-sent in some and absent in others . Basically, to use thelaser biomonitoring system it is necessary to build up areference library of optical spatial filters of diatoms im-portant in the aquatic system under study . Of course,there are thousands of diatom species, and it may not befeasible to make optical filters of all these species . How-ever, it is highly likely that a few hundred species may beall that are necessary to effectively monitor a particularriver or estuary .

Io

Fig . 2 . Twelve optical spatial filters were positioned on a glass photographic plate (2" x 2") . Since the size of each filteris generally inversely related to the size of the input image, approximately coo such filters can be placed on a plate .

At present, the quality of the optical filter is limited bythe quality of the input transparency (i .e ., contrast andresolution of the specimen in question) . For this reason,it is important that care be taken in photographing eachdiatom used to make an optical filter so as to obtain atransparency that is adequate for traditional taxonomicpurposes .

Pattern Recognition Using the Optical Spatial FilterThe optical spatial filter is a unique record of the structur-al pattern of a particular diatom specimen . It is peculiar

to this type hologram that in an optical system of suitablegeometry, it can be used to `scan' an array of unknowndiatoms and `recognize' those specimens in the arraywhich possess the same structural characteristics . Figure3 illustrates a simple configuration that will performpattern recognition on an unknown array of diatoms in asample using an optical spatial filter for a known diatomspecies .

As previously discussed, the Fourier transform of theentire unknown array will be focused in the rear focalplane of lens i where the spatial filter of the known specieshas been placed . In this case, however, the transformedlight waves from the input interact and pass through thefilter forming a complex product of light waves . It is theinteraction of object waves and filter which is the essentialaspect of the pattern recognition process . After passingthrough the filter, the complex wavefront is again Fouriertransformed by lens 2 . If a correlation between the spatialfilter (known species) and one of the unknown specimenspresent on the input transparency occurs, then a brightdot will appear in the rear focal plane of lens 2 (i .e ., theoutput plane) . Should the input array contain two ormore specimens of the known species stored on the filter,then two or more dots would appear in the output plane .The number of dots corresponds exactly to the numberof `matches' or identifications that the filter makes on theunknown array . It is important to note also, that the rela-tive position(s) of the matched specimen(s) in the inputarray are retained on the output screen .

Figure 4 illustrates an actual identification of a diatomspecies from an array of diatoms. We constructed anoptical spatial filter for the centric diatom Heliopeltametii and matched this filter against the array of diatomsshown in the figure. As is apparent from the output, the

I LASER

COHERENT LIGHT

OPTICALWAVES

LENS I

FILTER

LENS 2

system successfully identified the eight H. metii speci-mens in the array . Similar results have also been achievedin identifying the other specimens in the input array .(The other specimens include four Surirella cardinalis,four Stauroneis phoenicenteron and one Stictodiscuscalifornicus) .

Figure 5 is a schematic of the present prototype system .Basically, the system integrates computer. control withthe basic optical components to produce a partially auto-mated system. Unknowns in the form of 35 mm transpar-encies of diatom arrays are positioned into the opticalsystem under computer control. An optical filter of aknown diatom species is also positioned in the opticalsystem. Alignment and focus of the beam, lenses, andoptical filters are optimized through computer control ofsensitive step motors . This is critical since componentscannot be out of alignment more than 2 microns . Theoutput plane is automatically scanned by a televisioncamera and the location and intensity of the correlationdots determined and digitized for recording in the PdPI I-4o mini-computer controlling the total system . Undereither manual or automatic control, a signal can be sentto position an optical filter of another diatom species inthe optical system . This can then be used to determine thepresence and number of this species on the unknown in-put transparency . This process is repeated for the entirereference library of diatoms . The species abundance datagenerated are stored in the computer for analysis . Thisprocess can be automated so that it should take only a fewminutes to analyze a sample .

n

UNKNOWN ARRAY

TRANSFORMED

OUTPUT OFOF DIATOMS

LIGHT WAVES

CORRELATION DOTS

INTERACTION OFINFORMATION -CONTAINING

LIGHT WAVESAND THE OPTICAL FILTER

Fig . 3 . The arrangement of apparatus shown, is the simplist configuration that will perform pattern recognition . Notethat the unknown array of diatoms is actually a two-dimensional 35 mm transparency .

II

Fig . 4. This figure shows both input and output planes during a correlation test for the diatom Heliopelta metii. Theintensity of the correlation dots indicate an excellent match . Note the positions of the dots relative to the input array .(Slide of arrayed diatoms courtesy of Drs . Ruth Patrick and Charles Reimer, Philadelphia Academy of Science) .

Problem resolution and preliminary results

Signal to Noise RatiosWhen a correlation is made between filter and specimenthe output dot (or dots in a multiple match) is surroundedby some degree of flare light or noise resulting from thecross-correlations of the filter with the unmatchedspecimens in the array . This combination of output dot(s)(i .e ., the signal) and the accompanying noise is phtoelec-trically scanned and recorded as the ratio of signal tobackground noise . It is the magnitude of this ratio whichis important in determining whether or not a match hasoccurred. Ideally, the strongest signal (i .e ., the highestpossible degree of correlation) occurs when one diatom iscorrelated with itself. In this case, the S/N ratio is veryhigh (i .e ., ten or twelve to one) . As the strength of thecorrelation weakens, the S/N ratio falls off rapidly . Oneimportant aspect in the development of the optical sys-tem will be to establish ratio levels that the operator or the

12

computer can interpret as being a match or not-a-match .This type of investigation can only be made with the assis-tance of a trained diatom specialist to provide the finalmeasure of discrimination .

Table i shows the results of a study conducted with thesystem to discriminate three species of Cyclotella . Dr .Rex Lowe, Bowling Green State University, provided uswith 35 mm slides of Cyclotella michiganiana, CyclotellaOperculata and Cyclotella stelligera . We constructedoptical filters of C. michiganiana, C. operculata, andthree filters of C. stelligera for specimens with orna-mented centers, unornamented centers, and a compositeof both types .

As can be seen from Table i the signal to noise ratiosfor discrimination are quite good . All of the auto-corre-lation signals (i .e ., the output signals obtained for aparticular species matched against itself) have been nor-malized to io. These auto-correlations are represented inthe table as io* . Two special cases in the table are repre-

TELETYPEFOR

SYSTEM CONTROL

DIGITALTO

ANALOGCONVERSION

OFCONTROL SIGNAL

I LASER -10

MAINCOMPUTER

I DATA ANALYSIS2 SYSTEM CONTROL

SENDS INSTRUCTIONS• FOR CHANGE OF OPTICAL

FILTERS AND INPUT

INPUTOF UNKNOWN

ARRAY LENS I

Fig . 5 . This figure shows the fundamental arrangement of the prototype system . As illustrated, it reflects the correlationset-up, (refer to Figure i for filter construction) .

sented where the two forms of C . stelligera were matchedagainst the composite filter . As can be seen, the outputsignals of 9 .5 and to are more than sufficient for discrimi-nation indicating that the composite filter would be ade-quate in routine analysis . All other numbers in the tablerepresent the cross-correlation signals (i .e., one speciesmatched against a different species) . In each case, thesignal to noise ratios are low, indicating that no match hasoccurred .

Diatom OrientationIn order to obtain the greatest possible S / N ratio in a par-ticular correlation, the orientation of the diatoms in the

Table 1 . Discrimination results with three species of CycZoteZZa

(I) form possessing stellate pattern(2) form not possessing stellate pattern

-•

auto-correlation signalsoutput correlation signal to noise ratio in 10 - e watts

ANALOGTO DIGITALCONVERSIONOF SIGNAL

OPTICALFILTER

LENS2

INS

-0I

V

TELEVISIONCAMERA

ELECTRONICSCANNING

OFOUTPUTIMAGE

OUTPUT 1

--0

unknown array with respect to the filter is critical. Recallthat in constructing the spatial filter a reference specimenis used as the input . Suppose, for example, that this speci-men has an angular translation of zero degrees on thetransparency (assuming it is a naviculoid shaped frustule) .The filter constructed from this specimen not only re-flects the structural characteristics of the frustule but alsoits particular angular translation . A filter constructedfrom this same specimen, but with a 30% translation,would have a different appearance and, of course, possessdifferent optical properties with respect to correlations ofunknown specimens . The greatest signal strength is ob-tained when the specimens in the unknown array are inperfect alignment with their corresponding filter . Aseither the filter or the specimens are translated away fromthis alignment, the strength of the signal begins to fall off .

Figures 6 and 7 represent typical signal responses to therotation of the specimen being correlated. In Figure 6, thespecimen was rotated about its geometrical axis whileFigure 7 represents signal response during rotation of thefield of view (actually a 35 mm frame) about its center .Notice that rotation of the specimen about its axis resultsin less dramatic changes in signal strength althoughcenter-of-field rotation is the more practical method es-pecially when faced with a large number of specimens perfield of view .

t3

Optical filters

CycZoteZZamiehiganiana

CycZoteZZaopercuZata

CycZoteZZasteZZigera

(1)

CycZoteZZasteZZigera

(2)

CyelotollosteZZigeracomposite

CycZoteZZamiehiganiana 10* D .91** 1 .4 1 .62

CycZoteZZaopercuZata 1 .38 10* 1 .4 1 .30

CycZoteZlasteZZigera (I) 0 .69 1 .44 10' 10

CycZostolOosteZZigera (2) 0 .92 0 .94 10* 9 .5

-10°

1 4

12 -

.I.I..II.1J-4°

-2'

0'

2°

4'

6°

CENTER OF DIATOM ROTATION

Fig . 6 . Correlation peak when the input slide is rotated ± to°about the diatom center for which the filter was made .

Diatom Size VariationsDiatoms of the same species do vary in size from speci-men to specimen and like angular translation, these sizevariations are critical in correlation studies . In addition tostructural characteristics and orientation, the filter alsoreflects the size of the specimen used to make the filter . Ifspecimens in an unknown array are larger or smaller thantheir corresponding specimen stored on the filter, the S/ Nratio will be less than optimum . Figure 8 illustrates theeffects of varying the size of an arrayed specimen with res-pect to its filter . The ratio falls off fairly rapidly frommatching size (0 .8 on the graph) and then begins a moregradual decrease above 4% variation .

Problems of FocusThose who have worked with microscopes know that it isextremely difficult to get everything in a field of viewequally in focus due to the problem of depth of field, espe-cially at higher magnifications . Thus, we find some dia-

II_,II10°

2'

4°

6°

CENTER OF FIELD ROTATION

Fig. 7 . Correlation peak as a function on the input slide beingrotated ± io° about the 35 mm slide's geometric axis .

O

QZ

DIATOM SURIRELLA

III3.4

I I

17

25

33

SIZE VARIATION,

Fig. 8 . The signal to noise (S/N) ratio of the correlation peakvaries as the input diaom changes size but is still being matchedagainst a fixed-size filter for that diatom .

tom specimens are clear and others fuzzy . In the presentsystem where we use transparencies as input this is a realproblem. However, we feel that this problem can be re-solved either through the use of the real-time recordingmaterials previously mentioned, which would permitchanging the focal plane of the field of view, or by over-laying the optical filters . In the later approach a series ofoptical filters can be made for each diatom species invarious degrees of focus. These can then be superimposedand used as the optical spatial filter . Thus, the opticalfilter would contain optical information about a parti-cular species in various stages of focus .

In addition to depth-of-focus problem, there is also thematter of being able to recognize frustules in valve andgirdle views . For those species which frequently orient inboth views in the same sample, it is necessary to constructtwo optical filters for each respective view .

Utilization of the system

We envision that this system for identifying and countingdiatoms can be used in a river basin monitoring program .For example, such a system might be placed in a centrallocation in a river basin, and samples of diatom commu-nities could be collected on a routine basis from artificialsubstrates . On a daily, weekly, or monthly basis, the lasersystem could then be used to analyze the samples . Outputfrom the system could consist of a listing of the diatomspecies present in each sample, the number of specimensof each species present, a variety of diversity indices basedon species abundance relationships, cluster analyses, andmany other quantitative types of analyses . These types of

data could then be compared to historical data to detectshort-term or long-term changes in water quality . Theprimary value of this type of biomonitoring system isthat, upon complete development, it should be able toprovide a rapid, unbiased, and economical analysis of alarge number of diatom community samples .

Acknowledgments

The basic support for this research was provided by theNational Science Foundation, RANN Division (NSF/RANN/ IT/ GI-38357/ PR/ 7312) . We are deeply indebtedto Dr. Rex Lowe, Bowling Green University for fur-nishing diatom material which was used in the compa-risons in Table i . Dr. Charles W. Reimer and Dr . HeinzKoerner, Limnology Department, Academy of NaturalSciences of Philadelphia, have frequently furnished speci-mens throughout the course of these investigations . Dr .Cornelius I . Weber, Environmental Protection Agency,Cincinnati, Ohio, has been most generous with his timein discussing both operation and philosophy of these in-vestigations . This research would never have been startedhad it not been for the extensive use of diatoms in pollu-tion monitoring by Dr . Ruth Patrick whose advice, con-structive criticism, and encouragement throughout thecourse of these investigations have been enormouslyhelpful. We are indebted to Dr . Bruce Parker of VirginiaPolytechnic Institute and State University for his helpfulcomments on a rough draft of this paper .

References

Almeida, S . P ., Del Balzo, D ., Cairns, J . Jr ., Dickson, K . L. &Lanza, G . R. 1971. Holographic microscopy of diatoms .Trans. Kansas Acad . Sci . 74 (3-4) : 257-260 .

Almeida, S. P . & Eu, J . K . T . In press . Optical spatial filteringprocessor for water pollution monitoring . Proceedings Inter-national Electro-Optics Conference, Anaheim, Calif . Nov .,1975 .

Almeida, S. P . & Eu, J . K . T . In press. Water pollution moni-toring using matched spatial filters . Applied Optics .

Almeida, S . P .*, Eu*, J . K . T ., Liu*, C . Y . C ., Cairns, J . Jr .*,Dickson*, K . L . & Slocomb*, J . P . 1975 . Identification of dia-toms by an optical pattern recognition system for use in waterquality monitoring. Pages 156-16o in Proc. 2nd Annual NSF-RANN Trace Contaminants Conference, 1974 . LawrenceBerkeley Lab ., Univ . of Calif.

Archibald, R . E . M . 1972 . Diversity in some South African dia-tom associations and its relation to water quality . Water Re-sources 6 :1229-1238 .

Cairns, J ., Jr . 1972 . Rationalization of multiple use . Pages 421-430 in River Ecology and Man, Ray T . Oglesby, Clarence A.Carlson, and James A . McCann, eds. Academic Press, NewYork .

Cairns, J ., Jr . 1974. Indicator species vs . the concept of commu-nity structure as an index of pollution . Water Resources Bull .10 (2) : 338 - 347 .

Cairns, J ., Jr . 1975 . Quality control systems . Pages 588-611 inRiver Ecology, B . A . Whitten, ed . Blackwell's Sci . Publ . Ltd .,London .

Cairns, John, Jr . In press a . Zooperiphyton as Water Quality In-dicators . In Phycological Soc . of Am. Symp., Plankton andPeriphyton as Water Quality Indicators .

Cairns, J ., Jr. In press b . Biological Monitoring . In Harry B .Mark, Jr . and James S. Mattson, eds . Water Quality : TheChemical Point of View . Marcel Dekker, Inc ., New York .

Cairns, J ., Jr ., Dickson, K . L ., Sparks, R . E . & Waller, W . T .197o. A preliminary report on rapid biological informationsystems for water pollutional control . J . Water Pollut . ControlFed . 42 (5) : 685-703 .

Cairns, J ., Jr ., Dickson, K . L ., Lanza, G . R ., Almeida, S . P . &Del Balzo, D. 1972a. Coherent optical spatial filtering of dia-toms in water pollution monitoring . Archiv fur Mikrobiolo-gie . 83 : 141-146.

Cairns, J ., Jr ., Lanza, G . R . & Parker, B . C . 1972b . Pollution re-lated structural and functional changes in aquatic commu-nities with emphasis on freshwater algae and protozoans . Proc .Acad . Nat . Sci . Phila . 124 (5) : 79-127 .

Cairns, J ., Jr ., Lanza, G . R ., Sparks, R . E . & Waller, W . T . 1973a .Developing biological information systems for water qualitymanagement . Water Resour . Bull. 9 (1) : 81-99 .

Cairns, J ., Jr., Dickson, K . L . & Lanza, G . R . 1973b . Rapid biolo-gical monitoring systems for determining aquatic communitystructure in receiving systems . Pages 148-163 in BiologicalMethods for the Assessment of Water Quality . J . Cairns, Jr .,and K . L . Dickson, eds. Am. Soc . for Testing and MaterialsSTP No. 528 .

Cairns, J ., Jr ., Hall, J . W ., Morgan, E . L., Sparks, R . E ., Waller,W. T . & Westlake, G . F . 1974. The development of an auto-mated biological monitoring system for water quality mana-gement. Pages 43-55 in Proc . 7th Annual Conference on TraceSubstances in Environmental Health .

Cairns, John, Jr., Dickson, K . L., Slocomb, J . P ., Almeida, S . P .& Eu, J . K . T . In press . Automated pollution monitoring withmicrocosms . Proc . Ecol. Soc. of Amer . Symp., The Role ofMicrocosms in Ecological Research, Publ . by International.Environ . Studies .

Cairns, J ., Jr .*, Dickson*, K . L ., Slocomb*, J . P., Almeida*, S .P ., Eu*, J . K . T ., Liu*, C. Y . C . & Smith*, H . F. In press . Pollu-tion monitoring with microcosms . In Charles W . Finkel, Jr . .ed. Encyclopedia of Soil Science and Applied Geology, Vol .XIII-Applied Geology .

Cairns, J ., Jr ., Dickson, K . L . & Westlake, G . F . Co-editors . Inpress . Biological Monitoring of Water and Effluent Quality .Am. Soc . for Testing and Materials, Philadelphia .

Collier, R . J ., Burckhardt, C . B . & Lin, L . H . 1971 .Optical Holo-graphy . Academic Press, New York .

Dickson, K . L . . Slocomb, J . P ., Cairns, J . Jr ., Almeida, SilveroP. & Eu, J . K . T . In press . A laser based optical filtering systemto analyze samples of diatom communities . In Cairns, J ., Jr.,K . L . Dickson, G . F. Westlake, eds . Biological Monitoring ofWater and Effluent Quality, Am . Soc . for Testing and Materi-als, Philadelphia .

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Patrick, R ., Hohn, M. H . & Wallace, J . H . 1954 . A new methodfor determining the pattern of diatom flora . Not . Nat. No . 259 .

Patrick, R ., Roberts, N. A . & Davis, B . 1968 . The effect of changesin pH on the structure of diatom communities . Not . Nat. No .416 .

Patrick, R. 1971 . The effects of increasing light and temperatureon the structure of diatom communities . Limnology andOceanography. 16: 12 .

Slaytor, E . M . 1970 . Optical Methods in Biology . John Wiley andSons, Inc ., New York.

Vander Lugt, A ., Rotz, F . B . & Klooster, A . 1965 . Optical andelectro-optical information processing . Pages 125-141 in Sym-posium on Optical and Electro-optical Information Proceed-ings . J . T . Tippett et al ., eds. MIT Press, Cambridge, Massa-chusetts .

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