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Boreal environment research 12: 561569 issn 1239-6095

hk 24 ob 2007 2007

ib w pypk y

K vu1), l lp2) d a-l hp3)

1)Section o Ecology, Department o Biology, FI-20014 University o Turku, Finland (e-mail: kristiina.

[email protected])2)Finnish Environment Institute, FI-00250Helsinki, Finland3)Karelian Research Institute, University o Joensuu, and North Karelian Environment Centre, FI-80100

Joensuu, Finland

Received 14 Sep. 2005, accepted 15 Mar. 2007 (Editor in charge o this article: Johanna Mattila)

vu, K., lp, l. & hp, a.-l. 2007: ib w pypk y-

. Boreal Env. Res. 12: 561569.

Phytoplankton is one of the biological quality elements of the Water Framework Directive

of European Union for ecological classication of surface waters included. The reliabil -ity and comparability of phytoplankton data is, therefore, essential in assessment of theclassication. The recently published standard for phytoplankton analysis based on theUtermhl technique supports stringent demands for comparability of data. We tested thecomparability of phytoplankton analyses (Utermhl method) between professional and

non-professional analysts. The coefcient of variation was highly variable, 10%42% forprofessionals and 8%57% for non-professionals. Elimination of the error caused by sub-sampling and the increase in the minimum number of enumerated units decreased the CVespecially within professionals. CV was smaller (4%19%) when samples were counted byone person. In order to minimize the variability caused by differences between subsamples,new methods for comparison testing both for technical enumeration and for species identi-cation should be developed.

IntroductionPhytoplankton communities are sensitive to

changes in their environment and, therefore,phytoplankton total biomass and many phyto-plankton species are used as indicators of waterquality (Jrnefelt 1952, Heinonen 1980, Olrik1994, Reynolds 1997, Heinonen et al. 2000,Reynolds et al. 2002, Brettum and Andersen2005). Phytoplankton communities give moreinformation on changes in water quality than

mere nutrient concentrations or chlorophyll aconcentrations. Standards for chemical labora-tory analyses (e.g. National Board of Waters inFinland 1981 and 1984, SNV Rapport 3075),

which are relatively simple to follow, have beenused since the 1980s. In contrast, quantitativeanalyses of natural phytoplankton multispecies

communities are more complicated to perform.Furthermore, only recently a commonly acceptedstandard for phytoplankton enumeration waspublished (EN 15402 2006).

Currently phytoplankton counting methodsvary from country to country. Several alternativecounting chambers, e.g. Sedgwick-Rafter, Lundand Palmer-Maloney, are used for phytoplankton

analyses if inverted microscopes are not available(Welch 1948, Palmer and Maloney 1954, Lund etal. 1959, Guillard 1978). The Sedgwick-Rafterchamber is best suited for counting large algae

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562 Vuorio et al. Boreal env. res. v. 12

at low concentrations, and the Palmer-Maloneychamber is of use for nanoplankton counting

(Guillard 1978, EN 15402 2006). The Utermhltechnique (Utermhl 1958), however, is better

suited in quantitative analyses of multispeciesphytoplankton communities, especially in nutri-ent-poor waters. This method requires an invertedmicroscope equipped with high quality optics inorder to obtain reliable results (Olrik et al. 1998,Lepist 1999). Although a uniform methodologyfor phytoplankton counting based on Utermhlmethod was suggested by Olrik et al. (1998) forfreshwater, the recommended method is not fullyfollowed or evaluated. The new European stand-ard for phytoplankton counting and statistical

analyses based on Utermhl technique has beenpublished (EN 15402 2006) and should replaceconicting national standards in 29 Europeancountries at the latest by February 2007.

The implementation of the Water FrameworkDirective (European Union 2000) requires fre-quent phytoplankton monitoring and compara-ble phytoplankton results, e.g. the use of equalcounting methods and harmonization of spe-cies identication, at least among members of

the same Geographical Intercalibration Group(GIG). Ecological classication of surface watersincluded in the Water Framework Directive isbased not only on quantities of phytoplankton(biomass) but also on taxonomic compositionand size structures of phytoplankton communi-ties. At the present, phytoplankton analysis is theonly method to produce these taxonomic qualityelements, including e.g. indicator species. Har-monization of enumeration procedures and spe-cies identication should, therefore, be includedin the quality control of phytoplankton analyses.

During the last decades, phytoplanktonresearch quality controls in brackish water

have been introduced among Baltic countries(HELCOM 1997). For freshwaters, however,quality controls of phytoplankton analyses are

still rare, despite the fact that phytoplanktoncommunities have been studied in Nordic coun-tries since the beginning of the 20th century(in Finland e.g. Levander 1900, Blomqvist etal. 1915, Jrnefelt 1937, and in Sweden e.g.Cleve-Euler and Huss 1912). Furthermore, thenation-wide routine phytoplankton monitoringprogrammes have been operated by Finnish and

Swedish authorities since the 1960s (e.g. Hei-nonen 1980, Willn 2001, Lepist 2004). Sincethe 1980s Finnish phytoplankton analysts aswell as the Nordic phytoplankton and periphyton

group (NPPG) have harmonized species identi-cation. Recently, intercalibrations of phytoplank-ton enumerations have also been introduced e.g. in 1989 the Danish National EnvironmentalMonitoring Programme for lakes was launchedincluding routine intercalibrations among activeDanish phytoplankton analysts (Jensen and Sn-dergaard 1994, Lauridsen et al. 2005).

Performed intercalibrations have shown thatthere are differences in phytoplankton resultsbetween laboratories as well as between indi-

vidual phytoplankton counts carried out by dif-ferent persons (Barinova et al. 1980, Rott 1981,Huttunen 1985, Niemi et al. 1985, Jensen andSndergaard 1994, HELCOM 1997). This mustbe taken into account when comparing phyto-

plankton results. Though in Nordic countriesthe Utermhl technique is widely used (Olriket al. 1998), every individual analyst modiesthis technique according to the properties of themicroscope used.

There is thus an urgent need to reconsiderphytoplankton analysis methodology, to trainanalysts, and to perform intercalibrations amongworking analysts to increase the accuracy of

phytoplankton data. Furthermore, for ecologicalclassication there is a need to determine theacceptable level of variation caused by differ-ences in subsamples. In this paper we provideresults from two intercalibrations among Finn-

ish universities and research laboratories, andone joint FinnishSwedishNorwegian inter-calibration. The aim of these intercalibrationswas to evaluate the identication of species,and, more importantly, variability of quantitativeresults. Here we discuss the variability of count-ing results between analysts, and methodologicalproblems related to intercalibrations.

Methods

Three intercalibration sessions were performed in2002, 2003 and 2005. Participants were dividedinto two groups, and the results of phytoplank-ton analyses performed by professional analysts

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Boreal env. res. v. 12 Intercalibrations o reshwater phytoplankton analyses 563

were, on daily basis, compared with those ofanalysts occasionally counting phytoplankton

samples or students in training to be professionalphytoplankton analysts. A nonparametric Mann-

Whitney U-test was used to compare differencesbetween professional and non-professional phy-toplankton analysts.

First intercalibration session 2002

The rst intercalibration session was also a train-ing session in the methodology, and was thusdeliberately kept simple. The phytoplanktonsample for this session represented a 2-meter-

deep water column of a lake in SW Finland.Samples of 200 ml were preserved with acidLugols solution and combined into one sampleof two litres. This combined sample was mixedand divided into subsamples of 100 ml for eachparticipant. The two taxa to be counted werethe cryptophyte Rhodomonas lacustris and thecolony forming diatom Fragilaria crotonensis.In addition, only the volume to be sedimented(25 ml) was provided. Otherwise, every par-

ticipant used their own modication of the Uter-mhl counting method (Utermhl 1958, Olrik etal. 1998). Participants were instructed to give thecell numbers as units per litre. Altogether 13 ana-lysts participated in the rst intercalibration.

Second intercalibration session 2003

For the second intercalibration, the preparationof the sample was equal to the rst session, butinstructions were given in more detail. The set-tled volume was also 25 ml, and four taxa were tobe counted: the diatoms Aulacoseira subarcticavar. subborealis and Asterionella formosa; thechlorophyte Desmodesmus bicellularis; and thecyanobacterium Radiocystis geminata. A. sub-arctica var. subborealis were counted as singlecells and D. bicellularis as cell pairs, using atotal magnication of 6001000. Asterionellawas also counted as single cells but Radiocystis

as subcolonies containing approximately 150cells using a total magnication of 200250. Atleast 50 units (i.e. cells, cell pairs or subcolonies)of each taxon were counted. Special attention

was paid to the counting of colony forming taxa,therefore no attempt was made to split up the

Radiocystis into single cells. Results were givenas units per one litre. A total of 12 analysts took

part in the second intercalibration.In order to study the reproducibility of phy-toplankton counts, Toini Tikkanen sedimentedthree subsamples and counted each of themusing two different counting methods. The cryp-tophyte Rhodomonas lacustris was counted incrossing diagonals and in 20 elds with a totalmagnication of 500. The diatom Fragilariacrotonensis was counted using the same methodsbut with a magnication of 200. A nonparamet-ric Mann-Whitney U-test was performed to test

the differences between subsamples and betweenthe two different counting methods (SPSS 11.5.1for Windows, SPSS Inc. 19892002).

Third intercalibration session 2005

The joint FinnishSwedishNorwegian intercali-bration in 2005 was conducted during a Nordicphytoplankton workshop. The setup was simpler

than that of a natural sample because only threelaboratory strains were used, a unicellular greenalga and two lamentous cyanobacteria. Twoseparate samples were settled, one containing thechlorophyte Selenastrum sp. and the other con-taining the two strains of lamentous cyanobac-teria Planktothrix sp. and Anabaena sp. Partici-pants were instructed to count 10 elds from onediagonal; Selenastrum sp. was counted as singlecells and the two cyanobacteria as laments.Analysts were also advised to assess the numberof cells ofAnabaena laments and the numberof 25 m long sublaments of Planktothrix.Magnications were 650 for Selenastrum sp.and 400 for the cyanobacterial trichomes. All22 participants counted the sample containingSelenastrum sp., but because of limited timeonly 14 participants counted both samples.

Results

Intercalibrations

During the rst intercalibration, the range of

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cell numbers counted was large: 23253 cellsofRhodomonas lacustris and 4502255 cells ofFragilaria crotonensis. The average cell num-bers per litre are shown in Table 1. Among all

participants, the coefcient of variation (CV) forboth taxa was 21%. Among professionals (N= 8)who count phytoplankton samples daily, the CVwas 19% for both Rhodomonas and Fragilaria.Among other analysts the corresponding valuewas 24%. The differences in phytoplanktoncounts between professionals and non-profes-sionals were not statistically signicant (Mann-Whitney U-test).

During the second intercalibration, the rangeof the cell number counted ofAulacoseira was

129623, and of Desmodesmus 74443. Therange of colonies ofRadiocystis was 55166and ofAsterionella 801109. Table 2 gives the

results converted into number of cells or colo-nies l1. When the cell and colony counts wereconverted into numbers of units l1, the coef-cients of variation were 15% for Aulacoseira,

34% forDesmodesmus, 29% forRadiocystis and35% for Asterionella (Table 2). The variationbetween participants was smaller than in the rstintercalibration attempt: coefcients of variationamong the professionals (N = 78) were 14%for Aulacoseira, 19% for Desmodesmus, 33%for Radiocystis, and 42% for Asterionella; and20, 57%, 23% and 20% for non-professionals,respectively. The phytoplankton counts betweenprofessionals and non-professionals were notstatistically signicant (Mann-Whitney U-test).

During the third intercalibration, the rangeof the counts ofSelenastrum cells was 340495(CV = 9%,N= 22). ForAnabaena the number of

Table 1. ru f b: ddu

u u d u (u 1), f

(cv% = dd d pg

u) g p d g

pp. tx w ud Rhodomonas

lacustris (rd ) d Fragilaria crotonensis (Fg

). Pp ub 13 ud Rhodomonas

lacustris w (= 13a d 13B).

cu . rd Fg

01 31200 163626

02 23664 140461

03 27988 139700

04 33600 132700

05 29600 186400

06 30400 68815

07 44020 219360

08 29268 177210

09 21726 14017810 33300 250000

11 30666 180761

12 38500 158000

13 43314 157635

P

m 31180 165637

cv% 19 19

N 8 8

n-p

m 33501 177381

cv% 24 24

N 5 5

am 32073 170530

cv% 21 21

N 13 13

Table 2. ru d b: dd-

u u u d u (u 1), f

(cv% = dd d pg

u) g p d g

pp. tx w ud Aulacoseira

subarctica. subborealis(au u;u), Desmodesmus

bicellularis (D b), Radiocystis geminata (rd

g) d Asterionella ormosa(a ).

cu au u;u D b rd g a

.

01 3540000 6020000 99670 90110

02 3409000 5382000 51360 54640

03 3712000 5184000 79880 25990

04 3470000 4400000 48000 49500

05 3540000 4980000 43200 38100

06 4346100 3951000 55800 52200

07 3588145 6960138 79128 47100

08 2585024 46107 2707209 4072000 3357000 44600 73700

10 3700000 3500000 64125 46170

11 2788378 7068214 80384 54636

12 2710400 1760000 60995 59886

P

m 3523784 5268163 62893 48089

cv% 14 19 33 42

N 8 7 8 8

n-p

m 3317695 3921304 62526 58598

cv% 20 57 23 20

N 4 4 4 4

am 3455087 4778396 62771 51592

cv% 15 34 29 35

N 12 11 12 12

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cells counted varied from 297 to 542 (CV = 18%,N= 14) and that of trichomes from 43 to 99 (CV= 25%,N= 13). The range in Planktothrix count-ing units of 25 m was 81175 (CV 25%, N=

14) and that of whole trichomes from 35 to 67(CV = 17%, N= 13). Among professional phy-toplankton analysts, the deviations of CV were10% for Selenastrum cells, 18% for Anabaenacells and 23% forAnabaena trichomes, 20% forPlanktothrix counting units and 13% for Plank-tothrix trichomes (Table 3). For other analyststhe corresponding deviations of CV were 8%,18%, 16%, 35% and 20%, respectively. Again,

the differences in phytoplankton counts betweenprofessionals and non-professionals were notstatistically signicant (Mann-Whitney U-test).

Repeatability of phytoplanktoncountings

In order to test the reproducibility of the phyto-plankton countings, two different subsamples ofthe same material were sedimented and countedthree times by the same person, using two dif-ferent methods (20 elds versus crossing diago-

Table 3. ru d b: ddu bu u u d u, f -

(cv% = dd d pg u) g p d g pp.

tx w ud w by wg g: Selenastrum, Anabaenad Planktothrix;

s = Selenastrum, ab1 = Anabaena, ab2 = Anabaena, P1 = Planktothrixu 25 ,

d P2 = Planktothrix.

cu . s ab1 ab2 P1 P2

01 64603027 42989047 8997708 12496816 5898497

02 70461235 37890346 7498090 9697529 5398625

03 70135779 35291008 5898497 8097937 5198675

04 80387645 35790881 6898242 12796740 5698548

05 65253939 47687850 7798013 10297376 3998981

06 55327529 54186195 9897478 16395823 539862507 69973051 32091824 4298905 11497071 5698548

08 64928483 44288716 9297631 12296867 6698293

09 79411277 35690907 7298141 13096663 5098701

10 65742123

11 73715796

12 72576700 35191034 5798523 17495543 5698548

13 72576700 29692435 5098701 9697529 4198930

14 80550373

15 70135779

16 63952114

17 74203980

18 7794672519 69973051

20 77295813 45388436 9597555

21 64277571 39090041 6798268 8997708 3499109

22 63789386 29992359 4798777 8197911 4598828

P

m 69085444 40656308 7542523 11852536 5454166

cv% 10 18 23 20 13

N 11 9 9 9 9

n-p

m 71570745 35870861 5618835 10797249 4498854

cv% 8 18 16 35 20

N 11 5 4 5 4

am 70328094 38947220 6952075 11475648 5160224

cv% 9 18 25 25 17

N 22 14 13 14 13

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nals). For Rhodomonas cells the count from 20elds gave a CV of 13% for both subsamples,and that from crossing diagonals was 12% forthe rst subsample and 10% for the second sub-sample. For Fragilaria cells corresponding CVswere 19% and 14% when enumerated from 20elds and 23% and 5% when enumerated fromcrossing diagonals, respectively. The highest CVwas probably due to uneven sedimentation in

one of the three subsamples sedimented. Thenumbers ofRhodomonas ranged from 165 000to 235 000 units l1 when counted from 20 eldsand from 133 380 to 226 200 when counted fromcrossing diagonals. The corresponding valuesfor Fragilaria cells were 690 0001 100 000and 808 0801 993 400 units l1 (Fig. 1). Thisvariability was thus considerably smaller thanvariability between different analysts count-ing subsamples of the same material. However,we also observed a statistically signicant dif-ference (Mann-Whitney U-test: U = 3.5, P =0.02) between the two sedimented chambers in

Rhodomonas counts. The CV was lower whenmore Fragilaria cells were counted from twodiagonals, however, there were no signicantdifferences (Mann-Whitney U-test) between thetwo methods.

Discussion

During all three intercalibrations, thoroughinstructions were given for sample preparation,enumeration technique, and taxa to be counted.

During the rst intercalibration, participantswere allowed to use their own modication ofthe Utermhl method. To decrease the minimumvariation, participants were given more detailedinstructions, e.g. a minimum number of units tobe counted during the second intercalibration.The maximum variation, however, increasedwithin non-professional analysts but especially

within professional analysts. When differences

arising from subsampling and sedimentationwere excluded in the third intercalibration, thevariation within professional analysts decreasedfurther but the variation also decreased withinnon-professional analysts. Despite this decrease,however, the inexperience of some participantscaused unavoidable remaining variation in theresults. Due to high overall variation within bothprofessional and non-professional analysts, thedifferences between professional and non-pro-fessional analysts were not signicant.

Most previous intercalibrations have har-monized marine phytoplankton analyses (e.g.Hobro and Willn 1977, Barinova et al. 1980,Hllfors and Niemi 1990, HELCOM 1997) andfewer intercalibrations have been concerned withfreshwater phytoplankton (e.g. Rott 1981, Jensenand Sndergaard 1994, Veen et al. 2005). Ourintercalibrations applied the Utermhl technique,considered to be the most precise of existingmethods and a common standard for phytoplank-

ton analyses within EU (EN 15204 2006). Thepresent study is limited in scope as comparedwith previous intercalibrations of freshwater

phytoplankton (Rott 1981, Jensen and Snder-

Rhodomonas lacustris

Subsample

1 2 1 2

No

ofcounted

units(x103

l1)

12

14

16

18

20

22

24

20 fields2 diagonals

Fragilaria crotonensis

Subsample

1 2 1 260

70

80

90

100

110

120

130

Fig. 1. t ub (u 1 sD) Rhodomonas lacustrisd Fragilaria crotonensis w d

ubp dug d b pg pby u by t tkk.

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gaard 1994) deviating the following ways: First,entire samples from nature were not analysed;instead, only a few easily recognised specieswere considered. Second, calculations of the

species biovolume were not performed; insteadwe enumerated only cell/colony numbers. Last,ultrasonically treated samples of colony formingcyanobacteria were not used, because ultrasoni-cation complicates species identication, andbecause ultrasonication is not included in thenew EU standard (EN 15204 2006). Despitethese deviations our results are congruent withthe earlier studies showing high variability (CVs)between laboratories and individual analysts,especially when natural samples are used (e.g.

Hobro & Willn 1977, Barinova et al. 1980, Rott1981, Niemi et al. 1985, Veen et al. 2005).

The exact quantitative composition of phy-toplankton in a sample is difcult, if not impos-sible, to assess. Estimates of relative uncertaintytherefore must be derived from phytoplanktoncounts by multiple persons. Quantitative uncer-tainty depends partly on the abundance of a spe-cic taxon in a sample and partly on the amountof units counted (Lund 1958, Olrik et al. 1998).

Because the volume of sedimented water is basedon phytoplankton densities in water, changes inabundances affect the number of units enumer-ated (Eloranta 1978). This uncertainty of countsmust be expressed for each taxon separately.

In our comparisons, counts of colonial spe-cies showed highest CVs between analysts.During the second intercalibration, the CV washigh for Desmodesmus suggesting that some of

the participants may have counted this bicellularspecies as single cells although instructions were

given to count two-celled colonies. Moreover,high CV forRadiocystis suggests that the size ofsubcolonies was difcult to determine. Specialattention was thus paid to the colony formingtaxa that were counted, either as subcoloniesestimated by the cell number (such as the cyano-bacteria Radiocystis) or as single cells (the dia-tomsAsterionella and Fragilaria). Colonies con-sisting of several tens or hundreds of cells maygive a distorted picture of the number of colonies

if only the number of cells is enumerated. There-fore, a sufcient number of colonies (e.g.Radio-cystis geminata), not cells, must thus be countedto reduce the CV. Some researchers have tried

to solve the problem by counting ultrasonically

treated samples, where the CV would have beenmuch reduced (Jensen and Sndergaard 1994,Olrik et al. 1998). Even in this method, how-

ever, sufcient numbers of colonies may not becounted as the cells may originate from only afew large colonies, e.g. during HELCOM inter-calibrations systematic errors arouse from low

counts (HELCOM 1997). In the present studythe extent of uncertainty (CV) decreased withincreasing number of units counted. Our resultsconrm that the number of units counted has tobe high enough to minimize the CV.

Even though special attention was paid to theless trained participants, our results reveal that

the primary determinants of variation betweenanalyses are the experience and carefulness ofthe participants as earlier noticed by Barinovaet al. (1980) and Rott (1981). This variation,specically, may originate from the failure toprecisely follow instructions, individual modi-cations of the Utermhl method, or differencesin the optical quality of microscopes. Beforephytoplankton results can be accepted as validin an international context, analysts must thus

undergo thorough training at a professional labo-ratory and intercalibrate their results with thoseof professional analysts.

Variability between natural phytoplanktonsamples can be high and further increase thevariability between analysts (Hakala et al. 2002).In this study, the variability between naturalsubsamples counted by one analyst was as highas 20%, and even higher, up to 57%, betweendifferent analysts. This variability, thus, has tobe considered when comparing data with thevalid ecological class boundaries. The reliabilityand comparability of quantitative and qualita-tive phytoplankton data in assessment of theecological classication of lakes and coastalwaters depends as well on the quality of thework on phytoplankton and also very much onthe person that works up the material. In future,this variability challenges the implementation of

ecological classication of waters because datafrom human impacted waters analyzed by vari-

ous laboratories is compared with reference dataanalyzed by environmental authorities.

The results of these intercalibration testsshowed that it is necessary to elaborate a test

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which excludes the variation between subsam-ples of natural phytoplankton to reliably compare

true variability between analysts. Furthermore, agood knowledge of phytoplankton taxonomy is

essential in order to correctly identify species forecological classication. Therefore, in additionto the technical performance of phytoplankton

enumeration, comparison tests for species identi-cation are also needed.

Acknowledgements: We acknowledge especially Lic. Phil.Toini Tikkanen, the grand old lady of phytoplankton work inFinland, who made the extra tests, and all the phytoplanktonanalysts who took part the intercalibrations. We also thankProfessor Jouko Sarvala for his valuable comments on themanuscript. Mark Higgins proofread the manuscript.

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