Freshwater Biology (1987) 17, 14.V15()

Unsuitability of introduced tiles for sampling blackfly larvae(Diptera: Simuliidae)*

ANTOrNE MORIN Department of Biology. McGill University. Montreal

SUMMARY. 1. Blackfly larvae were collected from twenty-one stationsin five lake outlets in Southern Quebec. Tiles (total area=500cm") wereintroduced in early March, and collected 4 weeks later: randomlyselected rocks (30-500cm") from the surrounding area were collected atthe same time.

2. Larval densities on tiles were significantly less variable than onrocks. The variance of density estimates on tiles averaged 369f of theobserved variance on natural rocks, or 67% when variance on rocks wascorrected for average rock size.

3. Tiles significantly overestimated densities on rocks in somestreams, and significantly underestimated them in others. These differ-ences could not be explained by microhabitat differences (distance fromthe lake, depth, current velocity) between rock and tile samples. Thebias that tiles introduce in density estimates precludes their use incomparisons among sites.

Introduction

Efficient blackfly control relies on adequatesurveys of their populations. Quantitative esti-mates of blackfly larvae are costly because ofboth Ihe time necessary to process samples andthe high number of replicates required toachieve even moderate precision (Downing.1979; Resh, 1979: Morin, 1985). Measurementof densities on introduced tiles has been prop-osed as a partial solution to reduce samplingcosts since standardization of the substrateshould reduce sampling variability and there-fore sampling effort {Lewis & Bennett, 1974:Gersabeck & Merritt. 1979; Lamberti & Resh,1985).

•This is a contribution to the Lake Memphrema-gog project.

Correspondence: Mr Antoine Morin, Departmentof Biology. McGill University, 1205 Avenue Doc-teur Penfield. Montreal. Canada H3A lBl.

Sampling from introduced substrates iseffective if the density estimates on the sub-strates are less variable than those in natureand unbiased in their estimations. Rosenberg& Resh (1982) concluded from a literaturereview that estimates of density from artificialsubstrates are, on average, less variable thandensity estimates on natural substrata. Howev-er, their comparison ignored the relationshipbetween mean density and the variance of thedensity estimates (Taylor. 1961). This couldhave affected the conclusion of their studysince Morin (1985). after correction for therelationship between the variance and themean, concluded that artificial substrates donot reduce sampling variablility on average.Both studies (Rosenberg & Resh, 1982;Morin. 1985) are poor tests of the hypothesisthat artificial substrates reduce samplingvariability because the artificial and naturalsubstrate data that were compared generally

143

144 Atitoitie Morin

came from different sites and considered diffe-rent species. A more rigourous test could beperformed on estimates of density obtained onbiith artificial and natural substrates for thesame sites and taxa. Even if artificial sub-strates produce less variable estimates of densi-ty, biased estimates, caused by the selectivityof introduced substrates, could offset thebenefits of reduced variability. Selectivity ofartificial substrates is a controversial area, andthe biases differ among species and substratesinvolved (Rosenberg & Resh. 1982). If theselectivity of a given substrate for a taxa wasknown and constant, one could correct for thebias of the artifical substrate. Unfortunately,most studies of selectivity deal with a singlesite and little is known about the performanceof artificial substrates in different streams.

This study compares the precision and theestimates of density of blackfly larvae obtainedfrom introduced tiles and natural rocks in fivelake outlets. The comparison permits an eva-luation of the suitability of sampting intro-duced tiles to estimate the density of blackflieson natural substrate.

Material and Methods

Siudv area and sampting design

The five lake outlets are in the EasternTownships, in Southern Quebec (Table 1).Each outlet was divided in sections corres-ponding to riffle areas. On 3 March 1984 fiveto seven clay tiles (dimensions 15x15x0.8cm;total area 5(H)cm )̂ were distributed randomlyon the stream bottom at each station. A monthlater, between 2 April and 5 April 1984. thetiles were collected with three to fifteen ran-domly selected rocks (total area 3O-5OOcm )̂from the same riffle. Natural substrate in theoutlets varied from sand to large cobbles, andaquatic vegetation was absent from all streamsduring the sampling period. Water tempera-tures during the colonization period and on theday of collection ranged between 0 and 1.5°C.

Sampte collection and measurement

Each rock or tile was carefully lifted fromthe stream and immediately preserved with95% ethanol, in a plastic bag. Freezing

TABLE 1. Description of the sampling stations and number of tiles and rocks sampled.Geographical coordinates of the lakes, discharge of ihc outlets. [Q. measured on 2 April1985). distance downstream from the lake al each station (O). mean current velocity2cm above the subsirate (V). mean water depth (Z). and number of rocks (R) and tiles(T) collected at each station.

Lake Latitude LongitudeQ D

(m)z(m) R

Argent

Stukely

?2''19'W

?2°22'W

72°09'W

72''17'W

72''I4'W

4.1

0.3

2.8

0.8

2.9

2030

2040

140

5152545

115170190

5152565

10520405565

0.4A0.64

0.470.100.33

0.480.420.650.430.550.450.29

0.220.590.120.140.31

0.590.220.400.31

0.430.41

0.190.160.14

0.190.250.190.290.280.340.36

0.140.150.20O.IO0.14

0.170.27(t.I90.28

1015397

11U134

It98

8678585ft.S

65565

6646666

76666

6655

Bias of introduced tiles 145

temperatures prevented the use of a down-stream net. but visual counts of larvae on thesurface of the substrates prior to collectionwere almost identical to the numbers collected(maximum loss 3%, n = 17). Current velocity2 cm above each substrate was measured with aPigmy current meter; depth and distance fromthe lake were also noted for each samplebefore retrieval.

In the laboratory, samples were gentlywashed and the larvae collected on a 75/misieve. Larvae were sorted under a dissectingmicroscope. Prosimutiutti mixtumlfuscumSyme and Davies, Simutium vittatum Zetter-stedt and Stegopterna mutata (Malloch) wereidentified according to the criteria of Wood etat. (1963). Cleaned rocks were wrapped inaluminium foil and their surface areas wereestimated from the weight of the foil. Becauseof the wrinkles in the foil, the surface area ofthe rocks could not be estimated directly fromthe weight of the foil per cm .̂ Instead, aregression was estimated between the surfacearea of objects of known surface area and theweight of the foil used to wrap them. Adifferent regression equation was required foreach roll of foil because the weight per cm"differed among rolls. The 95% confidencelimits of estimates of rock surface lay within5-15% of the mean.

Statistical anatyses

Since rock size varied among samples andwas on average smaller than tile size, I fearedthat all comparisons might be confounded by asize effect. However, rock size had no effecton the density of Prosimulium mixtum/ftiscum.Stegopterna mutata or Simutium vittatum(Spearman rank correlations, 0.03, —0.02, 0.01respectively, «=169. PS>0.05). Consequently,no correction for rock size was necessary.

Variability of density estimates on rocks andtiles was compared by fitting a least-squaresregression between sample variance {s~) andmean density (X. individuals per square metre)at each station with an indicator variable (5)for substrate type (S=0 for rocks, 5=1 fortiles:

where a, b and c are fitted constants. Data forthe three species of blackfly larvae were

pooled for this analysis, which is equivalent toan analysis of covariance for differences inelevation (Draper & Smith, 1966).

Densities of each species on tiles and onrocks in each stream were compared by aKruskal-Wallis non-parametric test. For eachstream, species composition on tiles and rockswas compared by Chi-square.

Results

Variability of density estimates

Tiles yielded significantly more precise esti-mates of density than rocks. The variance onrocks and on tiles follows the equation:

log 5^=0.790+1.839 log Jf-0.440 5 (2)

which explains 95.3% of the variability in logs~ (n = 126). All three coefficients are highlysignificant (Mest, P<0.0001). Variance ofdensity on tiles was, on average, only 36%(U)-"'")of that on rocks (Fig. la).

Variability of benthic density tends to de-crease with increasing sampler size (Downing,1979; Morin. 1985). Rocks were smaller thantiles on average, and the smaller samplingvariability of tiles may be a size effect. Toaccount for this, variance was predicted fromthe equation estimated by Morin (1985):

log ^^=0.468+1.386 log A'+0.047 (log Xp-0.384 log/I (3)

where A (sampler size, m") was replaced byaverage rock area (m') at each station or bytile area. A second regression analysis wasperformed relating the observed variance tothe predicted variance Hog s'. Eq. (3)) and theindicator variable for substrate type {S).

Iogs^=-0.263+1.128iog?-0.177S (4)

This regression also explained 95.3% of thevariability in sampling variance, and tiles stillyielded significantly (/-test. P=0.007) moreprecise density estimates than rocks (Fig. lb).When corrected for both mean density andsampler size, variance on tiles was 67%

oi77 observed on rocks.

Comparability of mean density estimates

There was a relatively poor agreement be-tween estimates of density on tiles and on

146 Antoine Morin

9 - |

UC01

to>

oT3<D

O

8 -

7 -

6 -

5 -

4 -

3 -

2 -

A

£ 5

CD 4 .

0)

« 3 -o

2-

B

A r o c k sA t i l e s

1 2 3

l o g m e a n d e n s i t y ( i n d .

A r o c k sA t i l e s

1 4 5 6 7

p r e d i c t e d l o g v a r i a n c e

FIG. 1. Variability of density estimates on rocks and on tiles: (A) log variance as a function of mean density;(B) observed log variance as a function of the variance predicted from the equation of Morin (1985). The fulland broken lines represent the regressions for rock and tile data respectively.

rocks (Fig. 2). Density estimates on tilesdiffered significantly from estimates on rocksin some streams and the tile bias differedbetween streams (Table 2). Densities of Pro-simulium mixtumlftiscum on tiles were similarto those on rocks, except in the outlet of LakeOrford where tiles significantly overestimateddensity on rocks. Simulium vittatum was signi-

ficantly less abundant on tiles than on rocks inthe outlet of Lake Lovering, but significantlymore abundant on tiles in Orford. Stegopternamutata was always more abundant on tiles thanon rocks, but the bias was significant only inthe outlets of Lake Lovering, Orford andStukely.

The biases of the tiles could not be attri-

Bias of introdticed tiles 147

100 -

50

10

5 H

5 10 50 100

S l O Ho

5 -

O S . V I t t a t u m

10

100-

50

10

5

« A r g e n t

o L i b b y

• L o v e r i n g

• 0 r ( 0 r d

* S t u k e l y

•

•

S. m u t a t a

1 5 1 0d e n s i t y o n r o c k s C i n d . p e r 1 0 0 c m * )

FIG. 2. Comparison of densities of blackfly larvae observed on tiles and rocks. Geometric mean density ofProsimutium mixtumlfuscum. Simutium vittatum and Stegopterna mutata on tiles and rocks at each station.

148 Antoine Morin

TABLE 2. Comparison of the observed densities on rocks and tiles. Sign of thebias of the density estimates on tiles when the raw densities {B,) or the residualsof the regressions models of Table 3 (8 .̂) are compared to densities observed onrocks. Probability that the median density observed on rocks and tiles is thesame (Kruskall-Wallis test).

P. mixtumlfuscumB,B,

S. vittatumfirfi.

S. mutataBrBe

Argent

+ ns+ ns

+ *- n s

+ ns

Libby

+ ns- ns

+ ns+ ns

+ tts+ ns

Lovering

-ns- ns

_ •_••

+•

Orford

+ ***+ " *

+ " •+ •*•

+ " •

Stukely

+ ns+ ns

+ ns+ I1S

+*

OS P>0.05; •P<0.05; •• 'P<0.001.

buted to differetices in the microenvirontnentbetween rock and tile samples. To ascertainthat the differences between rocks and tileswere not due to differences in the microcondi-tions above the substrates, a multiple regres-sion between the density and the physicalvariables was estimated for each species ineach stream for the pooled rock and tilesamples:

(5)

where V is the current velocity 2 cm above thesubstrate (m s"'). D is the distance from thelake (m). and Z is the water depth (m).

Density was expressed in individuals perUK)cm" in this analysis to reduce artifactualscatter in the log transformed data at lowdensity. The lowest density that can be mea-sured on a rock of 100cm' is lOOind m^' (onelarva on the rock); when the numbers m~^ arelog transformed, the difference between 0 or 1larva on a rock of lOOcm" is 2 log units(log{I00+l)-log(0-(-l)=2.004). But whennumbers per 100cm* are log transformed, thegap between absence and presence of onelarvae is reduced to 0.3 log units{tog(l-i-l)-log(0+l)=0.301). Only the termscontributing significantly to the regression (f-test of the partial regression coefficient) were

TABLE 3. Microdistribution of Prosimutium mixtumlfuscum, Simutium vittatum and Stegopterna mutata inthe five outlets. Regression coefficients of the model log {Demhy+l) = a+bV+cV'+dD-i-eZ, where densityis the number of individuals per 100cm'. V is the current velocity 2cm above the substrate (m s ' ) . D is thedistance from the lake (m) and Z is the water depth (m). Number of observations {N). coefficient ofmultiple determination (R'). and mean squared error (MSE).

P. mixtum/fuscumArgentLibbyLoveringOrfordStukely

S. vittatumArgentLibbyLoveringOrfordStukely

S. mutataLibbyLoveringOrford

a

-0.0840.056

-0.3380.1970.082

-0.0761.242

-0.0800.480

-0.035

0.5450.0330.846

V

0.303"5.237***5.240***3.972"*1.820***

1.238"ns1.997*1.577***0.384*

nsns3.192"*

ns-3 .259"-3 .787"- 1 . 7 2 1 " *-0.844"

asns-1.469*-0 .990"ns

nsns-1,868*'

D

nsns0.002*nsns

ns-0.003'ns-0.003'ns

ns0.001**ns

Z

nsnsnsnsns

IB- 3 . 6 0 "nsnsns

-1.95"nsns

N

3635

1076546

3635

1076546

3510765

R'

0.180.520.150.560.40

0.180.250,060.240.15

0.110.060.22

MSE

0.0200.3590.5370.2900.117

0.3250.1860.2210.1420.070

0.1180.0610.527

ns P>0.05; •P<0.05; **P<0.01; **'P<0.001.

Bias of introduced tiles 149

TABLE 4. Proptirtion of each hlackfly species on rocks and tiles in ihc five outlets.Percentage of each species on rocks and liles, loial number of larvae collected (l^.Chi-square value (df=2) and probability that the species composition on rocks and tilesis identical.

Outlet

Argent

Libby

Lovering

Orford

Stukely

Substrate

RocksTilesRocksTilesRocksTilesRocksTilesRocksTiles

P. mixtumiftdscum(%)

34

92759494

4429

7972

S. vittatum(%)

9793

522

65

74

202?

S. mutata{%)

13220.31

5(167

1fl

N

974255

41193115

96826530

273129044

286795

2 4 —

456*"

43"**

332"*

12'*

P<0.001.

kept in the final models for each species ineach outlet (Table 3). If the observed tilebiases were due to differences in the micro-conditions sampled rather than to a substrateeffect, the residuals of rock and tile samplesaround the regressions should be similar. TheKruskall-Wallis tests were recalculated on theresiduals, and the results compared to thoseobtained on the raw data (Table 2). Theconclusions of these tests were unchanged intwelve of the thirteen cases, indicating that thetile biases cannot be explained by a samplingartifact.

The species composition differed significant-ly between rock and tile samples in the fivestreams (Table 4). Stegopterna mutata wasrelatively more abundant on tiles than on rocksin all streams, whereas Prosimutium mixtumifuscum tended to be relatively more abundanton rocks than on tiles. Simutium vittatumapparently preferred tiles in the outlet of lakesLibby and Stukely. but preferred rocks in thethree other outlets.

Discussion

Tiles provide estimates of density that are lessvariable than those obtained on rocks. Thehigher variability observed on rocks may resultfrom differences in texture or shape of therocks, error in surface determination, or to thepresence of predators or competitors (Hemp-hill & Cooper, 1983) that were absent from

tiles. Rock shape might be the most importantof these factors, since the proportion of thetotal surface that is actually available to thelarvae will depend on the shape of the rock.

Despite their reduced variability, tilesshould not be used to sample blackfly larvaewhen density estimates are required becausetiles are selective: density on tiles significantlydiffered from that observed on rocks for atleast one species in four of the five streams,and species composition on tiles significantlydiffered from that observed in rocks in allstreams. Tile bias varied among streams andmay be related to relative availability ofappropriate substrata (Disney.. 1972), to thepresence of competitors on natural substrata,or to differences in the dynamics of coloniza-tion among streams.

Lamberti & Resh (1985) found that tilesaccurately represented natural populations ofmacroinvertebrates in Big Sulphur Creek,California. Tiles were also effective tools in theoutlet of Lake Libby in the present study, butthis was not always the case. One should becareful in extrapolating the results from BigSulphur Creek or Libby outlet to other sites orspecies, because what applied in these streamsdoes not necessarily apply in others. Peckarsky(1984) suggested that artificial substrates canbe effective in comparisons of productivityamong sites. The fact that tiles give biasedestimates of density in some sites implies thatproduction measurements from tile samplesmay not reflect the real production potential.

150 Antoine Morin

This study shows that selectivity of tiles varyamong streams; this makes tiles an unreliablesampling method. Density estimates in tilescould be corrected for bias but. because tilebias varies among streams, both tiles and rockshave to be sampled at each site. Moreover, thepossibility of seasonal bias has not yet beenstudied, thus the determination of a correctionfactor will represent a major undertaking foreach study site and sampling date. Tiles couldbe used to make crude estimates of speciescomposition but crude estimates can be madeas easily by collecting stones, especially sincethey do not involve a preliminary visit tointroduce the substrate. When both accuracyand cost are important, sampling the naturalsubstrate alone is probably the best strategy.

Acknowledgments

This research was supported by Natural Sci-ences and Engineering Research Council ofCanada through a grant awarded to Dr RobertH. Peters, McGill University, and a scholar-ship to A.M. I thank R. H. Peters and J.Rasmussen for comments on the manuscriptand Sara Griesbach for her extraordinary helpand support during field work.

References

Disney R.H.L, (1972) Observations on samplingpre-imaginal populations of black flies in WestCameroun. Buttetin of Entomotogical Research,61,483-503.

Downing J.A, (1979) Aggregation, transformation,and the design of benthos sampling programs.Journal of Fisheries Research Board of Canada,36. 1454-1463.

Draper N.R. & Smith H. (1966) Applied RegressionAnalysis. Wiley. New York.

Gersabeck E.F., Jr & Merritt R.W. (1979) Theeffect of physical factors on the colonization andrelocation behavior of immature black flies (Dip-tera: Simuliidae). Environmental Entomology, 8,34-39.

Hemphill N. & Cooper S.D. (1983) The effect ofphysical disturbance on the relative abundancesof two filter-feeding insects in a small stream.Oecologia (Berlin), 58. 378-382.

Lamberti G.A. & Resh V.H. (1985) Comparabilityof introduced tiles and natural substrates forsampling lotic bacteria, algae and macroinverte-brates. Freshwater Biologv, 15, 21-30.

Lewis D.J. & Bennett G.F. (1974) An artificialsubstrate for the quantitative comparison of thedensities of larval simuliid (Diptera) populations.Canadian Journal of Zoology, 52, 773-775.

Morin A. (1985) Variability of density estimates andthe optimization of sampling programs for streambenthos. Canadian Journal of Fisheries andAquatic Sciences, 42. 1530-1534.

Peckarsky B.L. (1984) Sampling the stream benthos.In: A Manuat on Methods for the Assessment ofSecondary Productivity in Fresh Waters (EdsJ. A. Downing and F. H. Rigier). BlackwellScientific Publications, Oxford.

Resh V.H. (1979) Sampling variability and lifehistory features: basic considerations in the de-sign of aquatic insect studies. Journat of FisheriesResearch Board of Canada, 36, 290-311.

Rosenberg D.M. & Resh V.H. (1982) The use ofartificial substrates in the study of freshwaterbenthic macroinvertebrates. In : Artificial Sub-strates (Ed. J. Cairns, Jr). Ann Arbor ScientificPublishers. Ann Arbor.

Taylor L.R. (1961) Aggregation, variance and themean, Nature, 189, 732-735.

Wood D.M.. Peterson B.V., Davies D.M. & Gyor-kos H. (1963) The black flies of Ontario. II.Larval identification with descriptions and illus-trations. Proceedings of the Entomotogical Socie-ty of Ontario. 93. 99-129.

(Manuscript accepted 24 April 1986)