Undergraduate Review

Volume 1 Article 10

2004

Investigating Fluctuating Asymmetry of the LarvalDamselfly, Calopteryx maculata (Odonata:Calopterigidae)Edward Kelliher

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This item is available as part of Virtual Commons, the open-access institutional repository of Bridgewater State University, Bridgewater, Massachusetts.Copyright © 2004 Edward Kelliher

Recommended CitationKelliher, Edward (2004). Investigating Fluctuating Asymmetry of the Larval Damselfly, Calopteryx maculata (Odonata:Calopterigidae). Undergraduate Review, 1, 29-40.Available at: http://vc.bridgew.edu/undergrad_rev/vol1/iss1/10

Investigating Fluctuating Asymmetry of the Larval Damselfly, Calopteryxmaculata (Odonata: Calopterigidae)

Cover Page FootnoteThis research was made possible by a grant from the Adrian Tinsley Program (ATP).

This contents is available in Undergraduate Review: http://vc.bridgew.edu/undergrad_rev/vol1/iss1/10

Investigating FluctuatingAsymmetry of the LarvalDamselfly, Calopteryxmaculata (Odonata: Calop­terigidae)

by Edward Kelliher

Edward Kelliher is a senior ma­joring in Environmental Biologyand minoring in Chemistry. He isoriginally from Bridgewater, MA.He presented this paper at the2004 BSC Environmental Sympo­sium, NCUR, and NEC Confer­ences. He is currently studying atAcadia University under a KillamFellowship and hopes to pursuegraduate study in Marine Biolo­gy/Oceanography. Edward wouldlike to make it known that he wasalways pickedfirst for kickball.

ABSTRACT: Fluctuating asymmetry (FA), or subtlerandom deviations from perfect bilateral symmetry,

has recently become a useful tool in allowing researchers tounderstand more about an organism's health, fitness, devel­opmental stability and environmental stressors. Ultimately,FA studies can be used as an indirect measurement of thequality of an aquatic system over time. We measured andexamined the femur segments of the larval damselfly, Calo­pteryx maculata from sites on the Town, Hockomock, andSalisbury Plain Rivers, of Plymouth County, Massachusettsto determine FA levels. After accounting for measurementerror, preliminary results show that variations in symmetryare not correlated to individual trait size. Also, the Hocko­mock River site showed FA levels thee times higher thanthe Salisbury Plain river, and twice that of the Town River.Finally, severe femur deformation of some individuals atall sites suggests that other, more serious developmental orenvironmental factors may be inhibiting normal develop­ment. Results from a simple two-way ANOVA of differ­ences in right and left femur segments and a Kolmogorov­Smirnov test for normality strongly suggest that the firstfemur of C. maculata is a useful trait for FA measurement.

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This research was made possible by a grantfrom the Adrian Tinsley Program (ATP).

Introduction

Fluctuating asymmetry (FA), orsubtle, random deviations from perfect bilat­eral symmetry (Van Valen, 1962) has be­come a useful tool in allowing researchers tounderstand more about an organism's health,.developmental stability (Palmer 1996) andgenetic or environmental stressors (Learyand Allendorf, 1989; Graham et.a!. 1993)as well as the effects of hybridization andadaptation through inheritance (Hochwenderand Fritz 1999). The idea of this measure­ment comes from the expected developmentof perfect symmetry of a bilateral character(Palmer and Strobeck 1986). Thus, measure­ment of deviations from perfect bilateralsymmetry can be done to infer whetherthere are factors that affect the morphologyof bilateral traits throughout the develop­ment of the organism. Ultimately, if onecould develop methods that could rule outheritable components and genetic stressors,then fluctuating asymmetry can be used as ameasure of how precisely development hasoccurred in terms of an organism's environ­ment (Palmer 1996).

Bilateral organisms undergoingdevelopment are highly homeostatic andcapable of buffering for variation due to de­velopmental noise. This is defined as smallcompletely random accidents or errors in 'development of a trait that are exclusivelyenvironmental in origin and that inhibit anorganism's pre-determined genetic path fordevelopment (Palmer 1996). Consequently,subtle differences between the left and rightmeasures of a trait in a bilaterally symmetri­cal organism are the product of opposingforces: one that acts to disrupt development(developmental noise), and one that seeksto counteract the disruptive effects (devel-

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opmental stability) (Fig. 1) (Palmer 1996).When indices are calculated that expressfluctuating asymmetry as a variance or anaverage absolute value of the differencebetween right and left measures of bilat­eral traits (Palmer and Strobeck 1986), thelarger the (FA), the lower the developmentalstability. Similarly, if (FA) measurementis low, it can be noted that the organismof interest has a high buffering capacity tominimize developmental variations or thatthere is little developmental noise at play(Fig. l)(Fuller and Houle 2002; Rowe, et.al1997).

o

R-LFig. 1.FA reflects the opposing processes of developmentalnoise Vs. developmental stability (Palmer 1993). 'Stability' is the force that decreases FA, thus allow­ing development to proceed more perfectly (forcesthe graph inward towards zero). 'Noise' is the forcethat increases FA, which tends to push the graphoutwards away from zero.

There is evidence that FA has a heritablebasis (Fuller and Houle 2002; Hochwenderand Fritz 1998; Palmer and Strobeck 1986'Palmer 1996). Studies have shown that 'developmental stability was reduced (orFA increased) through increased homozy­gosity in hybrids between nominal speciesand others. Even so, environmental factorssuch as extreme physical conditions (wa­ter temperature), pollutants (heavy metals,nitrates, phosphates, metal salts) or declinesin habitat quality will contribute directly todevelopmental noise (Palmer and Strobeck1992)

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and also playa crucial role in the overallcondition of individuals and populations.

Therefore, is measurement of (FA)a tool for correlating environmental stress­ors, genetic stressors or a combination?The question has yet to be answered. Theanswer most likely is a combination of thetwo (Clarke, 1995; Fuller and Houle 2002),but to what degree? If fluctuating asymme­try is to be used accurately and effectively,one must somehow be able to measureorganisms whose bilateral traits are "wellbehaved" enough so that underlying fac-tors causing asymmetry are environmentalby nature (developmental noise). Then, onemust be able to distinguish these traits from"poorly behaved" characters that have asym­metry due to either direct genomic inter­vention (directional asymmetry, DA) or byfactors that create other forms of asymmetry(antisymmetry, non-covariant asymmetry)(Palmer 1996).

Other controversies that surroundthis measurement for imperfection are mea­surement error and data interpretation. Forbilateral variation in traits to be used as atool for quantifying a real measure of devel­opmental precision (defined as the accuracyby which genetic programs in the same in­dividual produce the exact same structures)(Palmer 2001), three criteria must be met: 1)between sides variation must be significantlygreater than measurement error, 2) variationdue to measurement error must be factoredout to insure credible measures of asym­metry; this being because FA measures areexceedingly small, close to 1% of the actualtrait size 3) the measures taken must meetthe statistical criteria for 'ideal' FA hav-ing a mean R-L of zero and being normallydistributed (Fig. 2) (Palmer 1994). Withoutthese steps, quantitative data for fluctuatingasymmetry cannot be interpreted with muchconfidence (Palmer and Strobeck 1997).Care must also be taken when analyzing

graphical interpretations of bilateral varia-

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tion. With a frequency distribution, twoother measures of asymmetry that cannotmeasure developmental precision or devel­opmental noise can be revealed. Directionalasymmetry (DA) defined as repeatableasymmetry with respect to side (Fig 3), andantisymmetry, or repeatable asymmetrythat is random with respect to side (Fig.4) (Palmer and Strobeck 1997) will havedistinct qualitative patterns when plottedusing a frequency distribution. Directionallyasymmetrical graphs will exhibit normal dis­tribution around a mean that is non-zero, asopposed to graphs with a normal distributionthat is zero (Fig. 2). Directional asymmetryis often found in nature (the classic exampleis the larger claw found on fiddler crabs) andcan be attributed to that organism's geneticresponse to its environment. Antisym­metrical graphs will appear as platykurtic orbimodal distributions around a mean of zero.Even though there are arguments that DAand antisymmetry can arise due to someform of developmental noise, not all formsof DA and antisymmetry are signs of re­duced fitness (Palmer and Strobeck 1992).By factoring out directional asymmetry andantisymmetry, (that is, by determining nor­mal distribution around mean zero) one candeduce whether FA is present in a populationsample.

oa)

R-L

Fig. 2 Example of fluctuating asymmetry (FA) dis­tribution for bilateral organism (Palmer 1994). Themajority of organisms measured for FA will appear tobe close to zero; in other words, have nearly perfectsymmetry.

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R-L

R-L

Materials and Methods

fall and May 1996) and may be a "sink" forheavy metals acquired though consumption.In this case, the term "sink" (bioaccumula­tion) refers to an organism that will acquire,over time, contaminants based on what itingests for food and habitat location.

Sample collections. Three sites werechosen with various degrees of anthropogen­ic influence to compare levels of FA. Theywere also chosen because the habitat thatsupports C. maculata growth and develop­ment (muddy root-filled banks, overhangingvegetation, moderate current) can be foundon these three rivers.

Thirty-three male and female C.maculata were collected on the south bankof the Town River (TWN029, N 41 degrees02.321; W 070 degrees 58.676. PlymouthCounty, Bridgewater MA.) on June 8, and 9,2003. Twenty-two C. maculata were collect­ed on the banks of the Hockomock River (N41 degrees, 00.560; W 070 degrees, 34.199 ,Plymouth County, Bridgewater MA.). Thir­ty-five C. maculata were collected on thebanks of the Salisbury Plain River (SLP027:42 degrees 03'.218N; 71 degrees 00.588W,Plymouth County, Brockton MA.) (fig. 5).

Nymph maturity was assessed inthe field using size and wing pads. If wingvenation was apparent through the wingpads, the last instar of maturity was inferred.Nymph maturity is important in that devel­opmental processes have allowed for legsegment lengths to reach peak growth. Allspecimens were captured using aquatic kicknets and placed in sample jars of no morethan 6 per jar. Within three hours of acquisi­tion, samples were stored in 70% ETOH atodegrees C for 24 hours and then placed atroom temperature until measured.

Fig. 3 Example of directional asymmetry (DA) dis­tribution for bilateral organism (Palmer 1994)

c)

b)

Fig. 4. Example of Antisymmetry (platykurtic or bi­modal) Distribution for Bilateral Organism (Palmer1994)

o

o

There are four reasons why C.maculata is a good candidate for fluctuatingasymmetry analysis: 1) it is abundant in thestreams of S.E. Massachusetts (Westfall andMay 1996),2) it is the most easily identifi­able damselfly larvae when collecting fieldsamples a 3) it is a fairly large aquatic insectwith many large bilateral characteristics(femur, tibia, antennae, wing pads) (Westfalland May 1996) and 4) C. maculata is a pre­dacious animal that is close to the top of thefood chain in its particular ecosystem (West-

The focus of this research is to deter­mine whether the bilateral traits of the larvaldamselfly, C. maculata, (specifically the fe­mur segments of three bilateral appendages)exhibit fluctuating asymmetry.

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Fig. 5. Map of three sample sites for C. maculata col­lection, June 2003

Measurement Preparation. Two­dimensional imaging of C. maculata wasstandardized using transparency film andclear microscope slides (fig. 6). Sampleswere laid ventrally and wholly intact, 8individuals per transparency sheet (6 femursegments per individual, 48 femur seg­ments per transparency set). Legs of eachspecimen were pinned flat underneath clearmicroscope slides that were taped ontothe transparency. Seventy percent ethanolwas applied to each specimen twice duringpreparation to ensure that body parts do notshorten due to dessication. 'Wet' specimenswere used because resolution of leg suturesbecame more visible when scanned. Achiev­ing two-dimensional imagery is important

in accounting for measurement error whenmeasurement software is used. Each set ofspecimens was scanned twice at a resolutionof 600 dpi using a Hewlett Packard ScanJet8200e flatbed scanner. At this resolution,all images produced have pixel dimensionsof 0.05 x 0.05 mm. All measurements arepresented in millimeters. After scanning,samples were catalogued and placed in indi­vidual vials of 70% EtOH and kept at roomtemperature.

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Fig. 6. Scanned image of finalinstar nymph, C. maculata

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Measurements.

Scanned images of C. maculatafrom each site were enlarged to 18 timesthe normal size on the computer screen andmeasured using a streaming data point-tracetool in Sigma Pro Scan 5.0 image analy-sis software. A 10mm x 10mm grid wasscanned next to each specimen for calibra­tion purposes. Calibration was done at the2x dimension of Sigma Pro Scan and wasset at 25.01996667 pixels/mm based on theaverage of three calibration measures. Threemeasurements of each femur segment (6femur segments, 18 measurements per speci­men) were made from the suture connectingthe femur to the trochanter joint, to the tipof a hook or bump-like feature located justbefore the suture that connects femur to thetibia segment (Westfall and May, 1996).

Two measurements were traced fol­lowing the bottom portion of the scannedimage and one taken using the middle ofthe femur image (care was taken to ensurethat the top and bottom of the two-dimen­sional femur image was kept equidistantwhile measuring). Sutures were marked witha yellow trace overlay at 27 times normaltrait size to ensure accurate location withinthe image and kept as a permanent overlay.Measurements were taken in red overlay inrandom order and were erased after eachmeasurement. All measurements were takenon the same image by the same person andexported to an Excel spreadsheet with 5significant digits.

Two assessments were made to de­termine if the femur segments of C. macu­lata are suitable to undergo (FA) analysis: 1)determination of whether trait size correlatesto deviation from ideal symmetry (meanzero) and 2) if the frequency of deviationaround ideal symmetry is normally distrib­uted. Each leg pair was given its own mea-

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surement category (RI-Ll, R2-L2, R3-L3respectively) and each pair was treated as anindependent trait.

A two-way analysis of variance onfemur length data at all sites was done usingSPSS 11.5 general linear model; univari-ate. Femur length was considered the inde­pendent variable with sides being the fixedfactor and the specimen (individual) treatedas the random factor (Palmer 1993). Thiswas done to test the significance of FA inrelation to measurement error. Ultimately, ifthe interaction variance in the ANOVA is notsignificant, these tests indicate whether ornot a trait can be used for FA studies (Palmer1996). Outliers were removed followingPalmer (2001) in order to use C. maculata asan organism whose traits are 'well behaved.'

A Kolmogorov-Srnirnov test wasalso conducted to determine if the R-L datawas normally distributed around a mean ofzero and not DA or antisymmetry.

Results

Using the SPSS Explore utility toolfor outlier analysis and the Kolmogorov­Smimov test on R-L data, only the firstfemur pair can be used for FA analysesbecause it passes the Kolmogorov-Srnirnovnormality test and the Simple two-wayANOVA test to determine if DA, antisym­metry or non-covariant asymmetry is present(other forms of subtle asymmetry that needto be partitioned out) (Table 1).

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Variancedf Var87 ***0.01392 0.01393 0.01783 ***0.02371 0.03173 0.01661 ***0.03350 0.025

two-way 0

specimens' femur lengthsdf Spec Side Side x Spec.0.2 28 0 0.98 00.104 30 0 0.174 **0.913*0.021 29 0 0.705 00.2 27 0 0.365 00.2 25 0.005 **.034 0*0.006 26 0 0.58 00.2 20 0 0.288 00.2 16 0 0.174 **0.907

orma tyTest of R-L pairs

Site stat df Signif.WNFI R-L 0.067 87WNF2 R-L 0.085 92WNF3 R-L 0.101 93

SLPFI R-L 0.063 83SLPF2 R-L 0.065 71SLPF3 R-L 0.126 73

MKFI R-L 0.09 61HMKF2 R-L 0.103 50

Table 1. Kolmogorov-Smirnov test for nor­mality, two-way ANOVA and variance datasets for three traits of C. maculata on threerivers in Plymouth County, MA.

KeyTWN - Town RiverSLP - Salisbury Plain RiverHMK - Hockomock RiverFl, F2, F3 refer to femur pairsdf - Degrees of freedomVar - VarianceR-L - right minus left* Does not pass normality test (p<0.05)** Failed interaction in two-way ANaVA*** Indicates that this data can be used in FA studies

14_-------------------,The second femur pair passed

tests for normality at all three sites(Table 1) but failed to exhibit FA be­cause it failed the 'sides*specimen'interaction from the ANaVA test. Thirdfemur length data sets for all threesites pass the ANaVA test to eliminateDA, antisymmetry or skew, but fail theKolmogorov-Smirnov test for normal­ity since they are significantly differentfrom a normal distribution (Table 1).

The first femur segment is there­fore the best-suited or best "behaved"trait to proceed onto a comparison ofvariances of the R-L data, since it passesthe Kolmogorov-Smirnov test for nor­mality and the ANaVA test (Table 1).Individual graphs depicting normaldistribution are given for the right-leftdifferences in first femur lengths (Figs.7,8,9).

12

10

a

6

2

o

Std.Dw= .11

Me~n = .04<:1N = B7.DD

':.Jr ~ 7 ':.0 ':.[}.. -0, .~ -~ '''), ..p-, ~.>- ,~~ ~6' ~e ~6' ~ IS" TjJ'" IS" ~ fj" ~

Fig.? Town River Femur 1 R-L,June 2003

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std. De-I = .15

Me;an =-.02

N =83.00

0......------------------------, The FA index used is the variance ofR-L(Palmer 1993, FA #4) because it is easilycomputed and is the most powerful testfor the differences between two samplesand is also better for estimating betweensides variation. It is also a useful index inthat it is not biased by directional asym­metry (Palmer 1993). The variances ob­tained with the simple two-way ANaVAusing the first femur pair showed thatthe Town River sample to be the lowest(.013), the Salisbury Plain River to behigher (.023) and the Hockomock Riversample showing the highest (.033) FA(Table 3).

o

o-.38 -.25 -.13 0.00 .13

Fig. 8 . Salisbury Plain River Femur1 R-L, June 2003

.25 Discussion

There appears to be a directcorrelation to the particular femur mea-

20~----------------------,

10

o

Std. Dl3v =.18

Mean = -.03N = 131.00

-.38 -.25 -.13 0.00 .13 .25 .38 .50

Fig. 9. Hockomock River Femur 1R-L June 2003

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sured and the type of phenomenon that istaking place. All three R-L analyses on thefirst femur segment had normal distribu­tions and passed the ANaYA tests (Side,Side*Specimen and Specimen) and thus theresulting variances can be useful to FA tests(Palmer 1993). The other two traits mea­sured are not useful to FA investigations,but each femur length R-L failed for similarreasons, (either in the K-S test for Normalityor the two-way ANOYA).

The 'Side*Specimen' interactionconducted in the ANOYA test includes allforms of non-directional asymmetry, includ­ing FA, antisymmetry and normal-covari­ant asymmetry (Palmer 1993). If tests aresignificant for this part of the ANOYA, itindicates that asymmetry is present, butit cannot be deduced that it is fluctuatingasymmetry and therefore cannot be used inthis investigation. Both the Hockomock andTown river femur length 2 R-L data failedthis test (indicated by significant P-values)(Table 2). The Salisbury Plain second femurlengths R-L indicate that the 'Side' interac­tion is significant, which correlates to direc­tional asymmetry, DA (Palmer 1993).

The amount of fluctuating asymme­try displayed at each sample site is a mea­sure of the variance of the R-L data (Palmer1993). The results are interesting in theamount of variance displayed at each par­ticular site. In this investigation, the Hocko­mock River sample site is our theoreticalclean site. Since it is located in a state-des­ignated environment critical area wetland,in was thought that the least amount of FAwould be found. In contrast, the SalisburyPlain River is used in this investigation asthe contaminated site due to its locationdownstream of the City of Brockton, knownin the past for its large tanning factoriesfor shoe manufacturing. However, the dataindicates that the Hockomock River sitecontained C.maculata that displayed R-Lvariances that were higher than that of the

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Salisbury Plain River, contrary to initialthinking.

The search for traits that exhibit FAis the search for traits that respond inef­ficiently to developmental noise (and thushave poor developmental stability). Thequestion that this investigation ultimatelyasks is whether femur length measurementsof the C.maculata can generate meaningfulrepresentations of what is happening in theenvironment during development. More spe­cifically, are the variances obtained at eachsample site giving an accurate representationto the amount of environmental stress? Twoquestions arise: is the Salisbury Plain Rivercleaner than expected, or is the HockomockRiver more stressed environmentally? What­ever the case may be, more research needs tobe done to more accurately determine whatis happening. Since aquatic environmentsare dynamic, so may be the levels of FA thatcan be measured over time.

There is some correlation to the timeat which adult damselflies are caught and theamount of FA that is present. Rowe and Lud­wig (1991) proposed that if fitness is cor­related positively to size, FA levels shouldincrease as emerging insects decrease in sizeas the emergence period progresses (Hard­ersen 2000). With this in mind, there mayalso be correlation to increased FA in levelsin larval damselflies due to smaller sizes oflate-maturing instars. Even so, there is onlyminimal evidence that suggests this phenom­enon. The Hockomock samples were collect­ed on June 15th and 19th, and the Town andSalisbury Plain Rivers were collected withinthree days of each other between June 3rdand the 6th. This being the case, the Salis­bury Plain River sample exhibited almosttwice the FA as in the Town River sample(Table 3). The importance of this stems fromemergence times and the nature of repro­ductive habits of C.maculata. Through fieldobservations and nymph collection tallies,most adults emerged between the first and

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fourth week of June. This suggests that thereis only a small window of time for growthvariation due to maturity and egg deposition.Adults that emerge first will copulate firstand thus will oviposit early in the summer.The eggs that are laid during the beginningof the summer will have a much longer timeto develop than those eggs oviposited duringlate summer and into the fall. This point mayhelp to explain the size differences observedin final instars of larvae among samples. The'significance of the three FA measurementswill remain unknown until a more intensivestudy is conducted in the summer of 2004,following measurement protocol and sampleparameters from Palmer (1993) to see ifthere are changes over time.

From the data gathered, a vast ma­jority of the deviation found in the samplepopulation falls at or below this one percenttrait size, but a few specimens from each siteexhibited large deviations from perfect sym­metry. Some portion of the outliers was ob­vious measurement error and was not usedin any of the tests. Upon closer inspection ofthe individuals in question, the femur seg­ments were severely underdeveloped or de­formed. These asymmetries are by no meanssubtle, nor do they imply small perturbationsthat occur accidentally throughout develop­ment. They were treated as deformities andwere not reported on the graph indicatingthe frequency distribution.

Whatever caused these deformi-ties to occur is unknown. Severe deformitysuggests severe stress and could possiblyhave both genetic and environmental factorsthat play into the severity. The question is,to what degree are the deformities geneticor environmental? Another hypothesis thatcould account for this limb deformation maybe that C. maculata, in larval development,may be able to regenerate certain segmentsof its body (say, if the larvae was preyedupon) so that its metamorphosis into adultlife as a predacious flying insect will not be

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compromised. A more thorough investiga­tion into this phenomenon needs to occur infuture studies.

There is some question as to whetherpopulations of C. maculata between differ­ent rivers will mix together to form a het­erogeneous population from various areas.This is very important in studies of FA indifferent populations. If there are differentpopulations mixing together, there will be noway to correlate an FA index with a distinctenvironmental condition of that area. In thissense, FA measurements cannot be usedwith much confidence even if there is strongevidence that suggests otherwise. Thus, FAanalysis of C.maculata will only be usefulif they are contained within a well-definedterritory (Hardersen 2000). We believe thatthe populations of C. maculata sampled inthis study do not mix. Although it was notan observed phenomenon, in C. maculatapopulations, the New Zealand damselfly X.zealandica adults do not migrate far fromthe emergence site (Hardersen 2000). Thisbrings up the question as to how far C. mac­

ulata travel from their natal origins and theimplications it has to biomonitoring studiesand FA analyses.

Conclusion

Measurement of the femur segments ofC.maculata may be good indicators ofdevelopmental noise, as the first femur pairheld up to a size dependency analysis, aKolmogorov-Smimov test for normalityand a simple two-way ANOVA. The firstfemur R-L data from all three rivers met allthe criteria for a proper FA measurementand exhibited different amounts of FA. Theother two femur pairs, although not nor­mally distributed or exhibiting DA or someother form of asymmetry, may still be strongcandidates for FA analysis if larger samplesizes per site are used. If more traits can berecognized as being "well behaved" traits

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for FA measurement, then the larval damsel­fly C. maculata may be useful as a tool forfuture biomonitoring studies and may leadto investigations of the rivers that nurturedthem.

Acknowledgements

I would like to thank Dr. Curry, ChrisHaslam, Erin Collupy, Kristen Backstromand the Biology Department at BridgewaterState College. Special thanks also goes outto the Adrian Tinsley Program, whose gen­erous contribution has made this researchcome to life.

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