Environmental stress can be either anthropogenic ornatural and several studies have examined the effects ofone or the other kind (Strong and James, 1992; Clarke,1993a; Polak, 1993; Hurtado et al., 1997; Rabitsch,1997). But few have examined both kinds of stress con-currently. This study investigated the relationship be-tween an anthropogenic and a natural stressor and thelevel of FA in two traits (forewings and hindfemora) ofa gomphocerine grasshopper species, Chorthippus par-allelus (Zetterstedt). Gomphocerinae belong to a groupof species that has its origin and central area of distribu-tion in the mesophilic grasslands of Siberia with a conti-nental climate. Here it can reach considerable densities(up to 300 individuals per m2) and tends to produceswarms in good years. During the period of warmingafter the last Ice Age, they spread quickly over all ofNorth and Central Europe. The maritime climate inSouthern Europe prevents higher densities from occur-

Environmental stress and fluctuating asymmetry in the grasshopper Chorthippus parallelus (Acrididae: Gomphocerinae)

Anja Jentzsch*, Günther Köhler and Jens Schumacher

Institut für Ökologie, Friedrich-Schiller-Universität Jena, Germany

Received May 28, 2002 · Revised version received December 19, 2002 · Accepted Dec. 30, 2002

Summary

We examined the effect of agrochemical pollution/fertilisation of the soil and climatic conditions at high altitudes on fluctuating asym-metry (FA) level in hindfemur and forewing lengths of the grasshopper Chorthippus parallelus (Zetterstedt). All traits and samples ex-hibited ideal FA. Forewings, which are less functionally significant in this species, generally exhibited greater FA than the more func-tionally significant femora. Forewing FA was also more affected by stress induced by climatic conditions at high altitudes than femurFA. The high altitude sample was the most asymmetric sample for both traits, followed by the two control samples. The two samplesfrom agrochemically contaminated habitats showed the lowest asymmetry in femora and forewings of C. parallelus. These results sug-gest that high altitude imposes more stress on this grasshopper species than does agrochemical contamination although the stress re-sponse was more dramatic in the less functional trait.

Key words: agrochemical pollution, fertilisation, extreme climatic conditions, marginal population, trait functionality and FA

0944-2006/03/106/02-117 $ 15.00/0

Introduction

The relationship between stress and developmental sta-bility has been widely investigated. Fluctuating asym-metry (FA), which arises from small random differencesbetween the left and the right side in a given characterduring development of an individual, is a common man-ifestation of random developmental variability and itselevation above a certain threshold has been attributedto increased developmental instability. Fluctuatingasymmetry is affected by environmental deterioration aswell as by genomic deterioration (inbreeding or reducedcoadaptation). Both types of stress (environmental orgenetic) are recognised to influence developmental sta-bility (Lens et al., 2002). Fluctuating asymmetry hasproved its usefulness for the detection of effects of dif-ferent types of environmental stresses (for reviews seeZakharov, 1992; Clarke, 1993a; Parsons, 1994).

Zoology 106 (2003): 117–125© by Urban & Fischer Verlaghttp://www.urbanfischer.de/journals/zoology

*Corresponding author: Anja Jentzsch, Institut für Ökologie, Dornburger Str. 159, 07749 Jena, Germany; phone: ++49-3641-949400;fax: ++49-3641-949402; e-mail: anja.jentzsch@web.de

ring. Generally, 1–4 individuals per m2 are high densi-ties in Central Europe (Ingrisch and Köhler, 1998).Chorthippus parallelus occurs in Central Europe in nat-ural populations in its brachypterous morph, i.e. bothwingpairs are short and flight muscles are weakly devel-oped. Individuals mainly use legs for locomotion andare excellent climbers and jumpers but they use theirwings only rarely (wing using rate 20%; Ingrisch andKöhler, 1998). The proportion of macropterous individ-uals with long wings and functional flight musclesvaries between 0 and 65% in a population. Those den-sity-dependent changes in behaviour and ecology aremainly observed in populations living in the central areaof distribution and in laboratory populations. During ourcollection of specimens we found three macropterousindividuals and did not include them in this study. Be-cause the level of FA sometimes depends on the func-tional importance of traits (Møller, 1993; Clarke, 1998)and the characters chosen for this study are used to dif-ferent extents for locomotion, we expected that the loco-motory important legs would have lower levels of FAthan the locomotory unimportant forewings.As an anthropogenic stressor, agrochemical pollutionof the soil was examined because prior studies showedthe absence of gomphocerine grasshoppers in highlycontaminated habitats near a fertiliser plant in Jena andthe gradual increase in grasshopper densities after theclosure of the plant (Köhler et al., 1987). Unfavourableosmotic conditions appeared to cause high egg mortal-ity (Köhler, 1984). Beyond that primary effect of os-motic stress, specific effects of certain chemical com-pounds accumulated in the foodplants may impede de-velopment in larvae. We also investigated a habitat reg-ularly fertilised with NPK-fertiliser that was likely to

have imposed similar but weaker stress than agrochem-ical soil pollution. Control samples were available fromphysically similar but unpolluted/fertilised habitats. Atthe same time, the effect of natural climatic stress athigh altitudes was investigated by comparing one sam-ple from the Alps (2000 m) with the samples from Cen-tral Europe. At altitudes higher than 2500 m speciesdensity for different Ensifera and Caelifera species de-clines to extinction (Ingrisch and Köhler 1998). Indi-viduals of Chorthippus parallelus were already scarceat 2000 m and the population can be considered to liveat the margins of the species range. Because this type ofstress acts more generally, it may disrupt developmen-tal processes and elevate asymmetry levels more easilythan specific stressors such as chemical compounds. In this study we were therefore able to compare the ef-fect of natural and anthropogenic stress on two traits ofa widespread grasshopper species. We also expectedthat the level of FA would differ between traits becauseof their different functionality.

Materials and methods

Populations studied

Chorthippus parallelus were collected from five differ-ent habitats (Table 1). Three habitats were sampledaround Jena (Thuringia, Germany). Two were south-ward slopes of the main valley of the Saale River, but, inrelation to the main wind direction, one lay directly be-hind a fertiliser plant (the polluted area, hereafter re-ferred to as POLL) while the other was situated severalkilometres in front of the plant in a nature reserve (con-trol nature reserve; CONR). POLL was influenced overseveral years (at least 1957–1985) by emissions of

118

A. Jentzsch et al.

Zoology 106 (2003) 2

Table 1. Habitat characteristics for Chorthippus parallelus

sample situation inclination altitude density habitat character maintenance suspected stress

CONR 50° 52′ N 12–15° 220 m high (fresh) semiarid from 1995 annual nonemowing

Nature Reserve 11° 34′ E grassland

POLL 51° 00′ N 7–24 ° 170 m low dense lawn of none, occasionally sheep agrochemical

Pollution 11° 46′ E Agropyron repens fertiliser plant pollution1990/91: pH, Mg, P, Ca, Cd, F notably above limit

COFC ~51° 57′ N 0 ° ~80 m high poor grassland annual mowing in Aug–Sep none

Forest Clearing ~5° 41′ E

FERT ~51° 57′ N 0 ° ~80 m low pasture 50 kg N/ha/year fertilisation

Fertilisation ~5° 41′ E half-yearly grazing with1,81 cattle/ha /year

HIAL ~47° 12′ N 5 ° 2000 m high subalpine pasture? climate

High Altitude ~10° 54′ E pasture

population density values are estimations for 1996, low = 0–3 individuals/m2; high = 4–10 individuals/m2

waste and raw material dust (including P-, Mg-, K-, Na-,F-compounds) and HF, SO2, SO3 and HCl raised duringproduction and transport of fertiliser. In 1990 and 1991,pH, Mg, Ca, Cd, and F were still notably enhanced inthe soil (Metzner et al., 1997). Near the plant only Puc-cinellia distans was able to grow whereas higher up theslope (much higher than the emittent) also Agropyronrepens, Bromus erectus and Festuca rubra had estab-lished and were still the main floral components whenthe populations were sampled. Grasshoppers werefound there only rarely in the 1970’s. A gradual increasein grasshopper density was detectable after the declineof emissions in the 1980’s and the closing down of theplant in 1990 (Köhler, 1988). Two additional habitatswere sampled in Wageningen (The Netherlands) be-cause in this area, general maintenance and fertilisationprotocols have been documented for several years. Onewas a cattle pasture with yearly fertilisation (fertilisedpasture; FERT) and the other an annually mowed forestclearing (control forest clearing; COFC). One popula-tion was sampled in the Austrian Alps (high altitude;HIAL) in the region of the Kühtai-pass. All populations of Chorthippus parallelus were sam-pled in July or August 1996, except the HIAL popula-tion, which was sampled in 1993. Sample sizes werebetween 65 and 43 for femora and between 49 and 35for forewings (Appendix 1).

Measurement procedures

Initially, four metric (hindfemur length, hindtibialength, forewing and hindwing length) and two meristictraits (number of cells formed by crossveins betweenmedia and cubitus 1 in the forewing, and number oftibia spines of hind leg) were measured. Only hindfe-mur and forewing length proved to be measureablewith adequate repeatability and fulfilled the statisticalrequirements of FA estimation. Furthermore, wings andlegs required different measurement approaches.

Femora

Femora were unsuitable for common optical measuringtechniques. Their landmarks could not be projected si-multaneously because they were not in an optical plane.Consequently, they were measured with an electronicVernier caliper (Helios-digit-Präzisions-Taschenmeß-schieber, to 0.01 mm accuracy) under a binocular micro-scope. As landmarks the most distant points of the outerrim of the upper, larger lobe of the notched base and theouter rim of the upper one of the two genicular lobes atthe apex were chosen (Fig. 1). Legs were removed frombodies and glued onto white cardboard with multipur-pose glue. All legs were measured twice and the repeatswere examined for pairs with differences larger than

0.05 mm. Such legs were remeasured again until a pairof repeats was completed within the 0.05 mm limit. In allcases, multiple measurements never gave higher differ-ences than the first repeat pair. The limit of 0.05 mm wasset because it provided a reasonably small amount ofmaximum measurement error (around δ/2 where δ is thestandard deviation of the R–L frequency distribution)and it appeared to be only a matter of observer attentionto measure within this limit. Furthermore, because ofshrinkage, it would not be possible to measure the origi-nal length later again if statistical analysis revealed ex-treme measurement error in single legs. A defined mea-surement scheme allowed all measurements of a popula-tion, as well as all necessary remeasurements, to be com-pleted within two hours of removal from ethanol.Shrinkage effects should therefore be small and becauseshrinkage occurred between both repeats of the measure-ment of one side, it is added to normal measurementerror and its effects can be partitioned out from FA esti-mates by calculating FA10 (Palmer, 1994).

Forewings

Forewings do not withstand the clamping betweenmeasuring jaws of a Vernier caliper or other mechanicalmeasurement devices due to their delicacy. Therefore,forewings were removed from bodies and placed onto aglass slide. As they were wet with ethanol, they stuckoptimally to the glass surface and were thoroughly flat-tened before being covered with a second glass slide.Mounting was not used because the wings were heldfirmly by the slides even when dried and optical distor-tion should have been minimised. Images were pro-jected onto a digitising board (Wacom UD 1824, 18′′ by24′′) by the aid of a special, vertically installed projec-tor (Fraunhofer Institute for Applied Optics and Preci-sion Mechanics, Jena, Thuringia, Germany, accuracy0.001 mm) that allowed precise adjustment of magnifi-cation and illumination. Wings were magnified 25times and the landmarks marked on the digitising board(Figure 1). For measurements of the tegmina, land-marks were the start point of the marginal membrane atthe base of the forewing and the rounded apex of theforewing. In the alae, the length of the third vanal veinwas measured. Data were directly transferred to a com-puter running Alias-software (Silicon Graphics Indigo2

Extreme workstation, Silicon Graphics, MountainView, CA; Alias Studio software, Alias Wavefront,Toronto; Ontario, Canada, version 6.0) and convertedto mm. A whole set of measurements (about 60 pairs ofwings, i.e., one sample) was completed before measur-ing it the second time. In the end, the two sets werematched and examined for differences between repeats.Again, all wings with a difference larger than 0.05 mmwere re-measured as described above.

119

Stress and FA in Chorthippus parallelus

Zoology 106 (2003) 2

Much care was taken to ensure an exact set-up of in-struments (for instance, projector-board distance) orpositioning of objects in relation to the lens centre. Ad-ditionally, a conversion factor was determined for eachsession to make measurements comparable betweensessions. As forewings had to be prepared in advance, they haddried out at the time of measurement. In a test,forewings shrank generally about 0.097 mm (i.e.,0.86% of the initial mean length). Shrinkage magnitudewas therefore comparable to the expected asymmetry,and could have influenced FA-estimation considerablyif it had not been acting similarly on both forewings ofthe individual. Examining the data revealed that in twothird of the cases shrinkage difference between the twoforewings was smaller or equal to δ/2 (δ is again thestandard deviation of the R–L frequency distribution)but in the other one third it was rather large (between0.056 and 0.139 mm, i.e., between δ/2 and δ of R–Lfrequency distribution). Nevertheless, the correlationbetween (R–L) of both conditions is very high (r = 0.953, P < 0.001, N = 16). To test the influence ofshrinkage on the FA index itself, results of the two-way,mixed-model ANOVA of both conditions were com-pared. The F-test showed that the difference between

FA 10 values of both conditions was not significant(F15,15 = 1.31, P = 0.31). Influence of shrinkage on FA-level was therefore negligible in this case. Gener-ally, though, the large number of individuals with ashrinkage level similar to | R–L | requires great care toavoid the potentially confounding effects of shrinkageif characters are measured after drying or start dryingbetween measurements.

Statistical Analysis

The pattern of asymmetry for all samples was analysedby visually examining frequency distributions of(R–L), testing for significance of directional asymme-try by t-test and normality of frequency distribution byKolmogorov-Smirnov test. Initially, four of the fivesamples exhibited skew and/or leptokurtosis. The im-plications of skew and leptokurtosis for FA-estimationare controversial (Palmer and Strobeck, 1992, Grahamet al., 1993). Some researchers suggest excluding allsamples showing non-normality from analysis becauseit may indicate a mixed sample of individuals prone toantisymmetry and others exhibiting FA (Palmer andStrobeck, 1992). Others argue that leptokurtic distribu-tions arise when the sample contains a certain number

120

A. Jentzsch et al.

Zoology 106 (2003) 2

Fig. 1. Hindleg and forewing ofChorthippus parallelus, arrows in-dicate landmarks that defined thelinear measurements used in theanalyses. c, costa; sc, subcosta; r, ra-dius; m, media; cu, cubitus; cu 1–2,cubitus 1–2; v, vannal vein.

of individuals with large asymmetries and are thereforea general feature of populations with low developmen-tal stability (Gangestad and Thornhill, 1999). Extremeindividuals may bear part of the information of the sam-ple that should not be neglected. As outliers occur for avariety of different reasons, data should be examinedcarefully. Enhanced susceptibility of certain individualsto developmental noise may play a role in generatingoutliers as well as measurement error or injury andtrauma during development, which are naturally notconsidered developmental noise. After examination ofdata and individuals, we excluded the most extremeoutliers (i.e., eight individuals with | R–L | > 5δ) fromthe five femur samples because we suspected reasonsother than developmental noise for their extreme asym-metry. Another 12 individuals with δ > |R–L | < 5δ wereconsidered as ‘normal’ outliers and included in analy-sis. Excluding the extreme outliers removed all signs ofnon-normality from the data.The relationship between (R–L) and trait size wastested by visual examination of scatterplots and by cor-relation of | R–L | vs. (R+L)/2. Mean character lengthwas preferred against any other measure of body sizebecause femur length as well as forewing length variedmuch more than the corresponding (R–L). Therefore,the direct correlation of (R–L) and the correspondingtrait size was appropriate (Palmer, 1994). Additionally,femur length is generally used as a measure of bodysize in Gomphocerinae. Differences in mean characterlength among samples was tested by one-way ANOVAof individual mean length. The influence of measurement error (ME) was deter-mined by two-way, mixed model analysis of variance(ANOVA) with two factors (side as fixed factor and in-dividual as random factor, Palmer and Strobeck, 1986)for all samples. The variance component due to mea-surement error was then compared between samples,traits and techniques by Bartlett-test. For each sample,three FA-indices were calculated, following the con-vention of (Palmer, 1994). FA1 is the mean of | R–L |,FA4 is the variance of (R–L), and FA10 is a variancecomponent from two-way, mixed model ANOVA. Itrepresents the asymmetry variance without the influ-ence of measurement error.Because each sample consisted of about the same num-ber of males and females, FA was calculated separatelyand compared by F-test to ensure that pooling did notcombine subsamples of different asymmetry. Differ-ences in FA between samples and traits were tested byF-tests of FA10 for each character separately and by amodified Levene’s test for pooled characters (actually atwo-way ANOVA of |R–L |, where trait and populationare fixed effects; Palmer, 1994). The correlation be-tween | R–L | of forewings and femora within individu-als of one sample was analysed to ensure that both traits

were unrelated. Significance level for all tests was 5%.For multiple tests (Appendix 1), a sequential Bonfer-roni adjustment was carried out for each ‘family oftests’ (Rice, 1989). We considered samples of the sametrait as belonging to one ‘family of tests’. Statisticalanalysis was done by SAS statistical package, Release6.12 (SAS Institute Inc., Cary, NC, USA; box plot andfrequency distribution of (R–L), Kolmogorov-Smirnovtest, student’s t-test, scatter plots and correlation of(R–L) and trait size, two-way, mixed model ANOVAwith two factors, FA 4), by SPSS statistical package(SPSS Incorporation, version 10.0; one-way ANOVA,independent t-tests, modified Levene’s test, correlationof |R–L | of forewings and femora), by Microsoft Excelsoftware (Microsoft Corporation, version 5.0a and 97SR-1; F-test, sequential Bonferroni Pi’s, and FA 1, and FA 10, Bartlett’s-test).

Results

Differences in asymmetry

Asymmetry in both traits did not differ between sexes,so the sexes of each sample were pooled for furtheranalysis. Differences in asymmetry among sampleswere analysed for pooled traits of each sample by amodified Levene’s test. The HIAL sample was signifi-cantly more asymmetric than POLL and FERT but didnot differ from CONR and COFC (Table 2, samplestatistics). Differences in asymmetry between pol-luted/fertilised habitats and natural habitats of the sameregion were not significant but the more natural habitatconsistently housed the more asymmetric population(CONR vs. POLL in Jena and COFC vs. FERT in Wa-geningen, Fig. 2). If asymmetry differences among samples for separatetraits were analysed, the F-test of FA10 was used. Aftersequential Bonferroni adjustment, differences inforewing asymmetry were significant between theHIAL and POLL sample (F47,32 = 2.97, P < 0.001),HIAL and FERT sample (F47,44 = 2.80, P < 0.001), andHIAL and COFC sample (F47,43 = 2.20, P < 0.01). Infemora, differences were significant between the HIALand FERT sample (F42,53 = 2.46, P = 0.001), the CONRand FERT sample (F59,53 = 2.17, P < 0.01) and theCOFC and FERT sample (F59,53 = 1.99, P < 0.01). Figure 2 shows the asymmetry variation of femora andforewings separately. Different letters above columnsindicate differences in asymmetry among samples. The data suggest an overall tendency for forewings toexhibit larger FA-values than femora. The above de-scribed Levene’s test revealed that FA differences be-tween traits were consistently significant in all compar-isons (Table 2, trait statistics) and that those differences

121

Stress and FA in Chorthippus parallelus

Zoology 106 (2003) 2

were in the same direction (Table 2, interaction statis-tics and Fig. 2). Therefore, no differences were de-tectable in the FA response of femora and wings to thestressors, although Figure 2 suggests that forewings ofthe HIAL sample respond more strongly than femoraand three of the four trait × site interaction terms werenearly significant statistically when HIAL was com-pared to the other sites (Table 2).

Pattern of asymmetry

The five femur samples were all normally distributedaround a mean of zero (Appendix 1, but see Materialsand methods). The forewing data of the five sampleswere also normally distributed around a mean of zero(Appendix 1). A significant correlation between | R–L |and character length occurred in female forewings of

the HIAL sample (t = 3.839, P < 0.01, N = 24, indepen-dent sample t-test). The lack of correlation between| R–L | and trait size in other samples can not be ex-plained by size range differences between those sam-ples and the HIAL females (CV’s of female forewingdata files had a range of 4.24 and 17.02 whereby theHIAL sample had a medium CV of 8.47). Since femaleforewings of the HIAL sample were the only signifi-cant case and the opposite sex as well as the whole sam-ple were not correlated, we did not correct for size dependence by individual. However, mean charac-ter length differed between samples in both traits (forewing: F4,221 = 11.718, P < 0.001, femur: F4,275 = 8.763, P < 0.001, one-way ANOVA). Examina-tion of data revealed that the FERT sample had a verysmall mean character length in both traits (Appendix 1).If the FERT sample is excluded from analysis, differ-ences between mean character length are not detectableamong samples (forewing: F3,174 = 2.642, P = 0.051,femur: F3,212 = 1.869, P = 0.136, one-way ANOVA).Consequently, the correlation of log [var (R–L)] vs.mean [(R+L)/2] was calculated to clarify whether(R–L) differed between samples due to differences inmean forewing length. This yielded no correlation be-tween both measures for all individuals pooled and forfemales and males separately. Therefore, it was not nec-essary to correct for body size by sample. Measurement error was small in both measurementtechniques. For femur measurements, the error compo-nent from the two-way, mixed model ANOVA was atleast ten times smaller than the between-sides variancecomponent. It did not differ between samples (χ2 = 3.33, df = 5, P = 0.65, Bartlett-test). In forewingmeasurements, ME was at least 30 times smaller thanthe between-sides variance component and again didnot differ between samples (forewings: χ2 = 2.41, df = 8, P = 0.966, Bartlett-test). The comparison of errorcomponents between measurement techniques also re-vealed no differences between femur and forewing mea-surements (χ2 = 8.23, df = 10, P = 0.606, Bartlett-test).

122

A. Jentzsch et al.

Zoology 106 (2003) 2

Fig. 2. Fluctuating asymmetry (FA10) values for femora andforewings of Chorthippus parallelus. POLL, fertiliser plant;FERT, fertilised pasture; COFC, CONR, control habitats (forestclearing, nature reserve, respectively); HIAL, high altitude habi-tat. Same letters indicate samples among which differences werenot significant statistically (F–test).

Table 2. Results of modified Levene’s test (two-way ANOVA, sample and trait as fixed effects) of FA variation in Chorthippus parallelus

site trait interaction––––––––––––––––––––––––––––––––––––––––––––– –––––––––––––––––––––––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––––––––––––

Sites compared F df1 df2 P F df1 df2 P F df1 df2 P

HIAL vs. CONR 4.541 1 201 0.034 21.508 1 201 0.000 3.320 1 201 0.070HIAL vs. POLL 9.543 1 170 0.002 19.868 1 170 0.000 3.568 1 170 0.061HIAL vs. FERT 16.831 1 204 0.000 28.215 1 204 0.000 4.190 1 204 0.042HIAL vs. COFC 5.221 1 203 0.023 24.186 1 203 0.000 2.504 1 203 0.115

CONR vs. POLL 1.289 1 183 0.258 9.662 1 183 0.002 0.011 1 183 0.917COFC vs. FERT 3.150 1 219 0.077 17.012 1 219 0.000 0.09 1 217 0.765

CONR – Nature Reserve, COFC – Forest Clearing, FERT – fertilised pasture, HIAL – high altitude, POLL – polluted areabold type indicates significance after sequential Bonferroni adjustment for six samples

Discussion

The characters chosen for analysis showed consistentlydifferent asymmetry values. In Chorthippus parallelus,both wing pairs are reduced and nearly non-functionaland seldom participate in locomotory activities. Ourstudy revealed that they were developmentally less sta-ble than femora, which serve a locomotory function. Aninverse relationship between functional importance andFA has been shown before (Møller, 1993, Clarke, 1998). Our results further suggest that climatic stress at highaltitude has a greater effect on forewing asymmetrythan on femoral asymmetry in Chorthippus parallelus.They therefore support the suggestion that functionallyimportant characters are more rigidly canalised andhence remain symmetrical when the population is dis-turbed because symmetry is required for functionwhereas traits not related to individual fitness may dis-play relatively poor buffering ability (Clarke, 1995;Markow, 1995). However, this lack of concordance among charactersmay also result from different susceptibility patterns ofthe traits during the time of development. If charactersdiffer in time of susceptibility to environmental distur-bance and stress intensity changes during development,which is conceivable for climatic stress, then differenttraits might react differently to enhanced general stresslevels.If the five populations of Chorthippus parallelus areranked for asymmetry, the sample from the Alps(HIAL) is most asymmetric in both traits and this wassignificant for 2 of 4 comparisons. Extreme climaticconditions therefore appear to have an effect on FA, ashas been observed at the margins of other speciesranges (Soulé and Baker, 1968; Zakharov, 1992). Gen-erally, limits to species distribution in the absence ofgeographical borders correlate with extreme climaticfeatures such as temperature extremes or desiccationstress. The border itself appears to be determined by aninteraction between climatic stresses and the metaboliccosts caused by increasing energy metabolism to coun-teract these stresses (Parsons, 1994). For the species in-vestigated here, that point is reached at altitudes above2500 m where the density for different Ensifera andCaelifera species, including Chorthippus parallelus,declines to zero (Illich and Windig, 1998). Next to the naturally stressed population, the highest FAwas found in the two control populations followed bythe two populations from agrochemically influencedhabitats. The data therefore refute the hypothesis of de-teriorating effects of chemical compounds (like Cad-mium or Fluor, that were still concentrated in the groundin POLL or Mg-, N-, P-, K-compounds frompollution/fertilisation in POLL and FERT) on the devel-

opment of grasshopper adult phenotypes. Thus, the ob-served negative influence of highly contaminated soilon grasshopper survival in POLL in the 1970’s and 80’smay be attributed completely to adverse osmotic condi-tions on eggs. Lower contamination levels that allowgrasshopper egg development (POLL during samplingtime) or moderate, regular fertilisation (FERT) may in-fluence grasshoppers through changes in habitat struc-ture and foodplant frequency and this is obviously bene-ficial. Prior studies have yielded inconsistent results,where FA is not always increased by habitat contamina-tion (Clarke, 1993a, 1993b; Rahmel and Ruf, 1994; Ra-bitsch, 1997). At chronically contaminated sites, organ-isms may be able to buffer effects of specific stressorssuch as heavy metals or special chemical compounds.Experimental work suggests that stress levels must bevery high (near lethality) to induce higher FA (Parsons,1990a, 1990b). In natural populations, it is even moredifficult to show the association between FA and stressbecause one does not know the severity of the stress interms of fitness reduction under field conditions.

Acknowledgements

We thank Klaus Reinhardt and Jörg Samietz for stimu-lating discussion of the subject, Jana Eccard for valu-able comments on the manuscript and Frank Nebel forsupport of A. J.

References

Clarke, G.M. 1993a. Fluctuating asymmetry of invertebrate pop-ulations as a biological indicator of environmental quality. En-viron. Pollution 82: 207–11.

Clarke, G.M. 1993b. Patterns of developmental stability ofChrysopa perla L. (Neuroptera: Chrysopidae) in response toenvironmental pollution. Environ. Entomol. 22: 1362–6.

Clarke, G.M. 1995. The genetic basis of developmental stability.II. Asymmetry of extreme phenotypes revisited. Amer. Nat.146: 708–25.

Clarke, G.M. 1998. The genetic basis of developmental stability.IV. Individual and populational asymmetry parameters. Hered-ity 80: 553–61.

Gangestad, S.W. and R. Thornhill. 1999. Individual differences indevelopmental precision and fluctuating asymmetry: A modeland its implications. J. Evolut. Biol. 12: 402–16.

Graham, J.H., D.C. Freeman and J.M. Emlen. 1993. Antisymme-try, directional asymmetry, and dynamic morphogenesis. Genetica (Dordrecht) 89: 121–37.

Hurtado, L., S. Castrezana, M. Mateos, D. McLaurin, M.K. Tello,J. Campoy and T.A. Markow. 1997. Developmental stabilityand environmental stress in natural populations of Drosophilapachea. Ecotoxicology 6: 233–8.

Illich, J.P. and N. Windig. 1998. Die Heuschrecken (Orthoptera:Saltatoria) der Hohen Tauern: Verbreitung, Ökologie,Gemeinschaftstrukturen und Gefährdung. WissenschaftlicheMitteilungen des Nationalparks Hohe Tauern 4: 57–158.

123

Stress and FA in Chorthippus parallelus

Zoology 106 (2003) 2

Ingrisch, S. and G. Köhler. 1998. Die Heuschrecken Mittel-europas. Westarp Wissenschaften Verlagsgesellschaft mbH,Magdeburg.

Köhler, G. 1984. Über den Einfluss von Luftverunreinigung aufÖkosysteme. VI. Untersuchungen zur Einwirkung von Indus-triestaub auf Feldheuschrecken (Orthoptera: Acrididae). Wissenschaftliche Zeitschrift der Universität Jena, Natur-wissenschaftliche Reihe 33: 321–7.

Köhler, G. 1988. Persistenz und Genese von Heuschrecken-Assoziationen (Orthoptera: Acrididae) in zentraleuropäischenRasenökosystemen. Zool. Jb. Syst. Jena 115: 303–27.

Köhler, G., H.P. Brodhun and G. Schäller. 1987. (Orthoptera:Acrididae). Oecologia 74: 112–21.

Lens, L., S. Van Dongen, S. Kark and E. Matthysen. 2002. Fluc-tuating asymmetry as an indicator of fitness: Can we bridge thegap between studies? Biol. Rev. 77: 27–38.

Markow, T.A. 1995. Evolutionary ecology and developmental in-stability. Ann. Rev. Entomol. 40: 105–20.

Metzner, K., Y. Friedrich and G. Schäller. 1997. Bodenparametereines Immissionsgebietes vor und nach der Schließung einesDüngemittelwerkes (1979–1997). Beitr. Ökologie 3: 51–75.

Møller, A.P. 1993. Developmental stability, sexual selection andspeciation. J. Evolut. Biol. 6: 493–509.

Palmer, A.R. and C. Strobeck. 1986. Fluctuating asymmetry:Measurement, analysis, patterns. Ann. Rev. Ecol. Syst. 17:391–421.

Palmer, A.R. and C. Strobeck. 1992. Fluctuating asymmetry as ameasure of developmental stability: implications of non-nor-mal distributions and power of statistical tests. Acta Zool.Fenn. 191: 57–70.

Palmer, A.R. 1994. Fluctuating asymmetry analysis: A primer.In: Developmental Instability: Its Origins and Evolutionary

Implications. (T.A. Markow, ed.) Kluwer Academic Publish-ers, Dordrecht, Netherlands, pp. 335–64.

Parsons, P.A. 1990a. Fluctuating asymmetry: An epigenetic mea-sure of stress. Biol. Rev. Cambridge Phil. Soc. 65: 131–45.

Parsons, P.A. 1990b. Fluctuating asymmetry and stress intensity.Trends Ecol. Evol. 5: 97–8.

Parsons, P.A. 1994. Developmental variability and the limits ofadaptation: interactions with stress. In: Developmental Insta-bility: Its Origins and Evolutionary Implications. (T.A.Markow, ed.) Kluwer Academic Publishers, Netherlands, pp.247–55.

Polak, M. 1993. Parasites increase fluctuating asymmetry of maleDrosophila nigrospiracula: Implications for sexual selection.Genetica 89: 255–65.

Rabitsch, W.B. 1997. Levels of asymmetry in Formica pratensisRetz. (Hymenoptera, Insecta) from a chronic metal-contami-nated site. Environ. Toxicol. Chem. 16: 1433–40.

Rahmel, U. and A. Ruf. 1994. Eine Feldmethode zum Nachweisvon anthropogenem Stress auf natürliche Tierpopulationen:„Fluctuating Asymmetry“. Natur und Landschaft 69: 104–8.

Rice, W.R. 1989. Analyzing tables of statistical tests. Evolution43: 223–5.

Soulé, M.E. and B. Baker. 1968. Phenetics of natural populationslV. The population asymmetry parameter in the butterflyCoenonympha tullia. Heredity 23: 611–4.

Strong, L. and S. James. 1992. Some effects of rearing the yellowdung fly Scatophaga stercoraria in cattle dung containingivermectin. Entomologica Experimentalis et Applicata 63:39–45.

Zakharov, V.M. 1992. Population phenogenetics: Analysis of de-velopmental stability in natural populations. Acta Zool. Fenn.191: 7–30.

124

A. Jentzsch et al.

Zoology 106 (2003) 2

125

Stress and FA in Chorthippus parallelus

Zoology 106 (2003) 2

App

endi

x 1.

Stat

istic

s of

freq

uenc

y di

stri

butio

n an

d FA

indi

ces

for f

emor

a an

d fo

rew

ing

of C

hort

hipp

us p

aral

lelu

s

N(R

+L

)/2

(R-L

)FA

1FA

4FA

10

mea

nSE

m

ean

SE

skew

SE

kurt

osis

SEt-

test

K-S

-tes

tm

ean

SEm

ean

SEδ2 i

MS e

rror

df

fem

urPO

LL

4310

.80.

2–0

.009

0.01

01.

560.

374.

030.

710.

440.

010.

0535

0.01

0.00

550.

000.

0025

0.00

0535

CO

NR

6110

.70.

10.

005

0.01

00.

300.

313.

680.

600.

640.

090.

0634

0.01

0.00

780.

000.

0036

0.00

0454

FER

T64

9.8

0.1

0.00

50.

010

–0.4

40.

300.

490.

590.

520.

020.

0472

0.01

0.00

380.

000.

0017

0.00

0353

CO

FC65

10.4

0.1

0.01

40.

010

–0.2

90.

304.

200.

590.

170.

150.

0594

0.01

0.00

710.

000.

0033

0.00

0359

HIA

L47

10.4

0.1

0.01

30.

010

0.37

0.35

2.29

0.68

0.36

0.05

0.06

670.

010.

0087

0.00

0.00

410.

0004

42

fore

win

gPO

LL

358.

890.

2–0

.017

0.03

00.

300.

40–0

.41

0.78

0.30

>0.

150.

0817

0.02

0.00

930.

000.

0045

0.00

0332

CO

NR

488.

960.

2–0

.005

0.02

00.

410.

340.

180.

670.

79>

0.15

0.09

350.

020.

0153

0.00

0.00

760.

0002

46FE

RT

487.

140.

10.

000

0.01

00.

260.

340.

370.

671.

00>

0.15

0.07

880.

010.

0098

0.00

0.00

480.

0003

44C

OFC

468.

160.

2–0

.004

0.02

0–0

.17

0.35

0.03

0.69

0.82

>0.

140.

0872

0.02

0.01

230.

000.

0061

0.00

0343

HIA

L49

8.55

0.2

–0.0

450.

020

1.06

0.34

1.31

0.67

0.06

0.01

70.

1711

0.02

0.02

700.

000.

0134

0.00

0347

HIA

L h

igh

altit

ude

habi

tat,

POL

L fe

rtili

ser p

lant

, FE

RT

fert

ilise

d pa

stur

e, C

OFC

con

trol

fore

st c

lear

ing,

CO

NR

con

trol

nat

ure

rese

rve

R =

leng

th o

f ri

ght s

ide,

L =

leng

th o

f le

ft s

ide,

t-te

st =

P-v

alue

of

stud

ent t

-tes

t, K

-S-t

est =

P-v

alue

of

Kol

mog

orov

-Sm

irno

v-te

st, F

A 1

= m

ean

IR-L

I, F

A 4

= v

ar (

R-L

), F

A 7

= v

ar (

R-

L)/

mea

n ((

R+L

)/2)

FA 1

0 ca

lcul

ated

aft

er tw

o-w

ay, m

ixed

mod

el A

NO

VA

, δ2 i

= va

rian

ce d

ue to

non

-dir

ectio

nal a

sym

met

ry, M

S err

or =

mea

n sq

uare

of m

easu

rem

ent e

rror

, df =

app

rox.

deg

rees

of f

reed

om