SPECTRAL FINGERPRINTING OF ALGAL COMMUNITIES: A NOVEL APPROACH TOBIOFILM ANALYSIS AND BIOMONITORING1

Chad Larson and Sophia I. Passy2

Department of Biology, University of Texas at Arlington, Box 19498, Arlington, Texas 76019-0498, USA

A new technique for spectral fingerprinting ofmajor algal groups in the freshwater periphyton(i.e. cyanobacteria, green algae, and diatoms) wasdeveloped using confocal laser scanning micro-scopy. This technique used the differential spectralemission signatures of photosynthetic algae andallowed their spatially explicit quantification andcommunity three-dimensional reconstruction. Algalbiovolume measurements, carried out with thistechnique, are superior to existing protocols involv-ing chl and ash-free dry mass assessments becausethey are nondestructive, localized, and specific at agroup level. This technique can be used to generatedepth profiles of the periphytic mat with variousapplications in aquatic ecology and biofilm ana-lysis.

Key index words: benthos; biovolume; confocal laserscanning microscopy; phytoplankton; periphyton;three-dimensional reconstruction

Abbreviations: 3-D, three-dimensional; ANOVA,analysis of variance; CLSM, confocal laser scanningmicroscopy; LM, light microscopy

Recently there has been a growing interest in mi-crobial biofilm structure and function because of theirpractical importance and implications for biotechnolo-gy and bioengineering. The structure of microbial bio-film communities has been shown to be related to theirfunctional responses to the environment, to the nutri-ent uptake and efflux of wastes, to intrabiofilm masstransport dynamics, and to the interactions that occurin the communities (Tolker-Nielsen and Molin 2000).For that reason, much research has been devoted torevealing microbial biofilm structure, using LM, imageanalysis, and molecular approaches (Davies et al. 1998,Yang et al. 2000, Zhang and Bishop 2001). Confocalmicroscopy has become an indispensable tool in mi-crobial biofilm studies because it permits the nonde-structive examination of live biofilms and the detectionof structural and compositional patterns at preciselydefined distances from the biofilm surface. Thus, withthe aid of a confocal microscope, the following at-tributes have been sequentially quantified within the

biofilm thickness: algal, bacterial, and exopolymer bio-film components (Lawrence et al. 1998a, Zhang andFang 2001); live and dead biovolume distribution (Neuand Lawrence 1997); and the relationship betweenbiofilm fractal structure and direction of water flow(Hermanowicz et al. 1995).

Periphytic biofilms represent a unique system,where photosynthetic algae coexist within a multilay-ered structure composed of multiple species of variousprofiles, growth habits, and successional appearance.Periphyton is a major source of organic carbon in loticecosystems and a powerful indicator for ecosystemhealth. Yet, largely due to the lack of relevant technol-ogy, there is disproportionate scarcity of informationon the three-dimensional (3-D) structure of live peri-phytic biofilms and how the environment affects it.

Streamwater quality deterioration as a consequenceof anthropogenic influence is a major concern of oursociety, and biomonitoring this process has been ofparamount importance to a number of state and fed-eral agencies. Biomonitoring protocols using periphy-ton have been developed and constantly improved butso far have been restricted to measuring algal biodi-versity (species composition) and biovolume (cell den-sity, chl a, and ash-free dry mass) (Barbour et al. 1999).These techniques frequently involve destruction of thebiofilm and multiple steps preceding the final waterquality assessment, including substrate scraping, labo-ratory processing, microscopy analyses (identificationand counting), entering data into spreadsheets, andvarious metric calculations. Hence, there may be pro-gressive error accumulation associated with theseprotocols, stemming from a number of reasons. First,not all cells are removed from the substrate becausethe number of missed cells depends on the amount ofhuman effort and the roughness of the substrate(Becker et al. 1997), which can vary tremendouslyacross sites even within the same survey. Second, notall cells are recovered after chemical processing, whichsometimes requires multiple washing of the material.And finally, simple miscalculations of the metrics canresult in erroneous conclusions. On the other hand,total biovolume measurements, which are less prone tosome of the aforementioned errors, are destructive,nonspecific, depend on the efficiency of chl extraction,and are sensitive to the ratio of chl a to the other typesof chl, often resulting in chl under- or overestimations.

Our objective was to develop a technique based onconfocal laser scanning microscopy (CLSM) that would

1Received 8 September 2004. Accepted 21 December 2004.2Author for correspondence: e-mail sophia.passy@uta.edu.

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J. Phycol. 41, 439–446 (2005)r 2005 Phycological Society of AmericaDOI: 10.1111/j.1529-8817.2005.04162.x

allow 1) the spectral separation of algal groups for thestudy of the 3-D structure of intact biofilms in real-timeand 2) a quick, reliable, spatially explicit, and nonin-vasive method for algal quantification for the purposesof stream ecology and biomonitoring.

MATERIALS AND METHODS

Algal communities. An experiment involving natural bio-film communities was initiated in which 20 L of water wereplaced into each of three aquaria. The water was collectedfrom a small stream flowing through the university campus.On the bottom of each aquarium, 49 � 49-mm porcelain tileswere placed equidistant from one another. A 400-W metalhalide lamp, placed above the aquaria, provided light on a14:10-h light:dark daily ratio. We allowed an initial period ofcolonization of 5 days, after which one tile was randomly re-trieved from each aquarium and placed into an accompany-ing Petri dish with enough distilled water to cover the tile.The tiles were collected on days 5, 7, 10, 12, 14, and 17 ofcolonization and examined with the confocal microscope. Forthe depth profile study of algal colonization, the tiles werekept in aquaria for 26 days. Natural communities composedof a mixture of different algae were sampled from varioussources, including drains and puddles. Artificial communitiesassembled from cultured algae, including Anabaena flos-aquae(Lyngb.) De Brebisson and Navicula pelliculosa (Breb.) Hilse(from UTEX algal cultures, Austin, Texas, USA), and Oocystissp. were used as controls in spectral analyses.

Confocal microscopy. We used an Axioplan 2 LSM 510META (Zeiss, Jena, Germany) with two single-channel detec-tors and a polychromatic 32-channel detector (META) forfast acquisition of lambda stacks (see below) and multiple ad-justable pinholes for high-resolution multifluorescence im-aging. The microscope was equipped with Ar laser (458, 477,488, 514 nm) 30mW, He/Ne laser (543 nm) 1mW, andHe/Ne laser (633 nm) 5mW. Viewing was carried out witha 40 � 0.80 NA water-immersion objective.

In the biofilm experiment, six random fields were exam-ined on each tile. In vivo fluorescence of the algal communitieswas excited with 458- and 488-nm lasers, whereas their emis-sion peaks were captured in the range of 580–740nm. Spectralseparation was achieved by means of a unique combination ofspectral detection and analysis, performed by an emission fin-gerprinting device, the META detector, and Linear Unmixingsoftware (Zeiss Advanced Imaging Microscopy Group, Jena,Germany) with the capability to separate up to eight emissionchannels. For each xy focal plane, the LSM 510 META meas-ures the incremental emission every 10nm and produces astack of images, called lambda stack. Focusing through a spec-imen at desired increments on the z axis generates a Z-stack.An image stack with emission information in x, y, and z dimen-sions allows the determination of spectral signatures at anylocation of a specimen. Reference emission spectra for the algalclasses were generated and stored in the Zeiss LSM SpectraDatabase using representative species from each class. TheLinear Unmixing function uses reference spectra to separatethe mixed signals in the image stack. It uses the entire emissionspectrum of each fluorescing substance, which permits theseparation of widely overlapping fluorescence emission signalsand reduces the crosstalk between the different emission spec-tra. It should be noted that species within the same class werespectrally indistinguishable.

Once a confocal image had been captured and the mixedsignals separated with Linear Unmixing into separate chan-nels, the biovolume (mm3 �field�1) of each algal class in theimage, which occupies a separate channel, was quantified usingthe 3-D for LSM software. A mean of the six random fields was

then multiplied by the number of fields in a square centimeterto obtain the biovolume of algae per square centimeter. Thephysiological state of an algal cell (particularly senescence)can affect its fluorescence, and in this study this was most evidentin diatoms. Because of this, a small amount of the fluore-scent signal emitted by senescing diatoms was at times detectedin the green algae channel. However, this problem waslargely alleviated by subtracting the signal emitted by one classof algae from the signal emitted by the other using the softwarefunctions.

For the observations of artificial communities of culturedalgae, twomixtures (A and B) were prepared by placing severaldrops from each culture into a depression slide. The threespecies were allowed to settle for 5min after which a field wasrandomly chosen and the contents captured in a confocal im-age. After separating the different algal classes by applying theLinear Unmixing function, the biovolume for each algal classwas quantified in 3-D for LSM as described above.

Effect of formaldehyde additions on algal fluorescence. Ap-proximately 25mL of the A. flos-aquae, Oocystis sp., andN. pelliculosa cultures were placed into each of three scintil-lation vials. In one vial there was no addition of formalde-hyde, whereas formaldehyde to a final concentration of 5%was added to the other two vials. Immediately after the ad-dition of formaldehyde, the fluorescence of 10 individualcells was measured with the confocal microscope. The vialcontaining no formalin and one of the vials containing for-malin were placed under constant illumination. The thirdvial containing formalin was placed in a drawer receiving nolight. The fluorescence of algae was measured again after 1,2, 3, 4, 7, and 14 days.

LM. After observation with the confocal microscope, thebiofilm on the surface of each tile was scraped off with a razorblade and a toothbrush, diluted, and preserved in 5% for-maldehyde to a final volume of 40 mL. Biofilm ‘‘clumps’’were separated with a pulse sonification device for 5 s. Thiswas long enough to separate large clumps but short enoughto avoid cell damage. After each 40-mL sample was uniformlymixed, a subsample was placed into a Palmer-Maloney count-ing cell (Wildlife Supply Company, Buffalo, NY, USA) andobserved under a light microscope at 40 � 0.65 NA. Theabundance of each algal class (cyanobacteria, green algae,and diatoms) was estimated by counting 20–30 fields andconverting the number of counted cells to density per squarecentimeter of tile. Average cell volume for each species wasdetermined in every sample by measuring the dimensions ofall individuals when less than 20 were encountered and 20when there were many individuals. The biovolume was cal-culated by incorporating the cellular dimensions in formulaefor solid geometric shapes most closely matching the shape ofthe cells (Wetzel and Likens 1991). In each sample, cellularbiovolume was determined by multiplying the number ofcells of each species by its mean cell volume. Finally, totalbiovolume per class was derived by summing the respectivecellular biovolumes of all encountered class constituents.

For the examinations involving artificial communities ofcultured algae, a digital transmitted light image of six fields wastaken and immediately followed by the capture of a confocalimage in each depression slide (mixtures A and B). The LSMviewing software allows the dimensions of objects within theimage to be measured by outlining the object. Biovolumes ofeach class of algae in a field were obtained by measuring thedimensions of all objects and applying the aforementionedformulae.

Statistical analyses. A three-way analysis of variance (ANOVA)with biovolume measurement method (confocal vs. transmit-ted light), algal class (cyanobacteria, green algae, and diatoms),and mixture (A and B) as factors and log10-transformed bio-volume as the dependent variable was carried out on artificial

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communities using SYSTAT 8.0 (SPSS Inc., Chicago, IL,USA). A repeated-measures ANOVA for two grouping factors(i.e. biovolume measurement method and algal class) and onewithin factor (i.e. day of colonization) was conducted on nat-ural communities with SYSTAT.

RESULTS

Emission signatures of algal groups. Algal fluores-cence was best induced after excitation with the Arlaser at 458 and 488 nm. The emission spectra ofcyanobacteria were considerably different fromgreen algae and diatoms. Emission of cyanobacteriapeaked at 650 nm, whereas the emission of diatomsand green algae peaked at 675 and 690nm, respec-tively (Fig. 1). This was also evident in the lambdastack showing algal emission in an incremental fash-ion (Fig. 2). The capability of the META detector forincremental emission reading made possible thespectral separation and subsequent quantification ofdiatoms and green algae despite the large overlapbetween their emissions (Figs. 3 and 4, a and b).Three-dimensional reconstructions of each algalcomponent as well as the entire community were cre-ated for natural communities (Fig. 3) and biofilms,which were too thick, opaque, and packed with de-tritus to allow any coherent information to be gath-ered by LM (Fig. 4, c and d).

Biovolume assessments. Biovolume assessments werecarried out on natural and artificial communities.Natural communities on porcelain tiles were exam-ined, and biovolume of each algal class was estimatedby confocal microscopy directly from the tile and byPalmer-Maloney cell counting after scraping of the

FIG. 2. Lambda stack of the emis-sion spectra of mixed algal communityobtained by CLSM.

FIG. 1. Emission spectra of three different algal classes ob-tained by CLSM. Each spectrum is an average of five measure-ments.

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biofilm. Repeated-measures ANOVA demonstratedfor each algal class that the biovolume across the sixcolonization days was not dependent on enumerationmethod (P5 0.166, n5 108). Analyses of artificialcommunities assembled from cultured algae support-ed these results. The confocal estimates of the bio-volume of individual algal groups were again notsignificantly different from the Palmer-Maloney cellestimates across the two algal mixtures (three-wayANOVA, P5 0.680, n5 72).

Effect of formaldehyde additions on algal fluores-cence. The addition of formaldehyde did not imme-

diately alter the algal fluorescence (Fig. 5). As timeprogressed, the fluorescence of the fixed algae keptin the dark persisted but their emission spectrachanged, which was most evident in cyanobacteriaand green algae. All fixed algae continued to fluo-resce with diminished intensity even after 14 days ofexposure (data not shown). Fixed algae exposed tolight from all three groups exhibited more or lessstrongly diminished fluorescence 1 day after fixationand negligible fluorescence by the end of the exper-iment (Fig. 5). Despite the continuous fluorescence ofalgae even after 14 days of fixation, their successful

FIG. 3. CLSM image illustrating the spectral separation into different channels and 3-D reconstructions of three algal groups in amixed community. Each panel is also available as a movie clip for 3-D viewing at http://www.blackwellpublishing.com/products/journals/suppmat/JPY/JPY04162/jpy04162sm.htm.

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spectral separation was achieved only within the first2 days of exposure to formalin. After 1 day of expo-sure, the spectral separation of the three species wasas clear as with the live controls, that is, each algalgroup emitted only in one channel (as in Fig. 3). After2 days, the green algae started to fluoresce in thediatom channel, but this noise was eliminated bythe software subtraction function. At longer expo-sure durations, fluorescence of all three groups

was detected in all channels, which prevented theirdistinction.

Depth profile. After confirming the accuracy of con-focal microscopy in spectral separation and biovol-ume assessment of different algal groups, the 3-Dstructure of natural biofilms was examined duringthe course of their succession. Tiles with growingbiofilm were retrieved from the tanks on days 3, 21,and 26 of the experiment, analyzed with CLSM, and

FIG. 4. Transmitted light image (a) and CLSM image (b) of an artificial community, consisting of Anabaena flos-aquae, Oocystis sp., andNavicula pelliculosa (pseudo-colored in blue, green, and orange in b, respectively). Transmitted light image (c) and CLSM image (d) of anatural biofilm, consisting of cyanobacteria and green algae (pseudo-colored in blue and green in d, respectively). Images c and d arealso available as movie clips at http://www.blackwellpublishing.com/products/journals/suppmat/JPY/JPY04162/jpy04162sm.htm, showinga focusing through the depth of the biofilm and biofilm 3-D reconstruction, respectively.

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redeployed. Distinct community shifts were observedduring biofilm development. In the early stages, thebiofilm was homogeneous with diatom dominantsand chlorophyte subdominants evenly distributedthroughout the biofilm thickness (Fig. 6). In the in-termediate and final stages, the biofilm became pro-gressively stratified into chlorophyte-dominated anddiatom-dominated layers (Figs. 6 and 7).

Potential shortcomings of the CLSM fingerprinting tech-nique. Capturing lambda and Z-stacks of thick bio-films is time consuming and may take up to 20min.This may result in imprecise biovolume estimates ofmotile cells or colonies, which quickly traverse thefield of view. If the biofilm is rich in motile species butnot designed for redeployment, it should be fixedbefore confocal analysis; however, the examinationshould be carried out within 48 h of fixation.

There are possible limitations imposed by the bio-film thickness and compactness. In less compactbiofilms, composed of a mixture of algal groups withdifferent profiles, the maximal encountered depth

was 360mm, which was seen as an opaque mass inLM but was successfully spectrally dissected by CLSM.In highly compacted biofilms produced by the tightpacking of filamentous algae such as nostocaleancyanobacteria, the CLSM lasers were able to penetrateonly the top 200mm. Preliminary analyses suggest thatthe technique may be ineffective in distinguishing algalgroups having very similar pigment composition suchas the chl b-bearing chlorophytes and euglenophytesor the phycobiliprotein-bearing cyanobacteria andrhodophytes.

DISCUSSION

Periphytic biofilms have a complex structure andmany of their properties are best understood in threedimensions. Important ecological matters such as col-onization, population dynamics, interspecific competi-tion, and herbivory exist only in the context of thespatial organization of the biofilm and species patchdynamics. Still, very few spatial aspects of its structure

FIG. 5. Temporal au-tofluorescence patternsof Anabaena flos-aquae,Navicula pelliculosa, andOocystis sp. after preser-vation in 5% formalde-hyde as measured withCLSM.

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and development have been investigated in referenceto underlying physicochemical factors (Hoagland et al.1982, Steinman and Mcintire 1986, Hudon and Leg-endre 1987, Steinman et al. 1989). A major reason forthis has been our inability to study intact and growingbiofilms in their entirety. The approaches available sofar are almost exclusively based on SEM (Greenwoodet al. 1999), which destroys the living cells, discrimi-nates well only hard-shelled algae such as diatoms, andprovides only snapshots of single vertical or horizontalplanes. Light microscopy is inadequate for structuralbiofilm analysis because as they grow, biofilms quickly

become opaque and their algal constituents indistin-guishable. Confocal microscopy is becoming increas-ingly popular in microbial biofilm studies (Lawrenceet al. 1998b, Lawrence and Neu 1999). However, ex-isting confocal microscopy methods for periphytic bio-film analysis (Lawrence et al. 1998a, Sole et al. 2001,Neu et al. 2004) fail to distinguish between major algalgroups that are spectrally similar, such as green algaeand diatoms, and to produce direct and differentialvolumetric measurements of algal accumulation. Herewe described a new technique for spectral fingerprint-ing of periphytic biofilms using confocal microscopy,which permits in vivo examination of biofilms, discrim-ination of the major algal groups, and the differentialreconstruction of their 3-D structure. Moreover, per-iphytic biofilms that naturally occur on a wide variety ofopaque substrates, such as stones, sand, bark, andsnags, can be viewed just as easily as biofilms on glassslides. Finally, precise volumetric measurements ren-der this technique a useful tool for aquatic ecology andbiomonitoring. We outline several applications withgreat potential for future aquatic research.

First, emission fingerprinting using confocal micro-scopy can be used in analyses of biofilm colonizationpatterns under different environmental conditions.Detection and quantification of fluorescence shiftswithin biofilm depth would indicate major communi-ty shifts throughout bioaccumulation resulting fromabiotic and biotic interactions. The thickness of thebiofilm can be partitioned into slices (Z-stack), whereemission spectra of individual algal groups are cap-tured (lambda stack). From both stacks the character-istic depth profile of each algal group can bereconstructed in three dimensions, thus revealing in-formation about algal spatial arrangement within thebiofilm. Such analyses are impossible with convention-al LM or EM.

Second, this technique enables higher resolutionbiovolume measurements (at an algal group level)than standard procedures for chl assessment. The sep-arate biovolume quantification of each higher algaltaxon presents significantly more detail about themakeup of an algal community than total biovolumealone. This is achievable without having to destroy thesample by extracting the various photosynthetic pig-ments. By eliminating the need to remove the attachedbiofilm from the substrate, there is no loss of materialand analysis of the 3-D structure of the algal commu-nity can be performed.

Spectral fingerprinting can be applied equally suc-cessfully in phytoplankton biovolume assessments. Itmay aid in biomonitoring of nuisance cyanobacterialblooms, assessments of phytoplankton, or periphytonprimary productivity in any aquatic environment be-cause of its discriminating power at an algal class level.Another possible application is in the analysis andquantification of grazers’ gut contents in real time.Live protozoans, crustaceans, and midge larvae fed ondifferent diets can be viewed and their food vacuole orgut content spectrally analyzed, which is an essential

FIG. 6. Depth profiles of natural biofilms on tiles after 3, 21,and 26 days of colonization.

SPECTRAL FINGERPRINTING OF ALGAL COMMUNITIES 445

advantage over the existing invasive techniques (Glo-zier et al. 2000). Grazing has important implicationsfor algal accrual and succession, and as an intermedi-ary step in the organic matter flow through the foodwebs, it is pivotal in ecosystem functioning. Therefore,the ability to track the food preference and amount ingrazers’ diets is of great importance.

In conclusion, we present a spectral fingerprintingtechnique using confocal microscopy for the analysis ofbiofilms that is as precise at estimating algal biovolumeas conventional counting but more specific than exist-ing methods for total biovolume assessment, such aschl a and ash-free dry mass measurements. It allowsfor repeated real-time examinations of changing com-munity composition and 3-D structure of attached bio-films in response to a changing environment.

This work was supported by the University of Texas atArlington and the National Science Foundation under grantno. 0215852 to S. P. We are grateful to Jim Grover for in-sightful comments and discussions and to the two anonymousreviewers, whose constructive suggestions helped improve themanuscript.

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FIG. 7. Transmitted light image ofbiofilm accumulation after 26 days (a).Depth profile reconstruction of the im-age in a showing the differential spatialdistribution of algal taxa (b). Both im-ages are also available as video clips athttp://www.blackwellpublishing.com/products/journals/suppmat/JPY/JPY04162/jpy04162sm.htm.

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