J. N. Am. BentJd. !3cc, 1998,17(4j518-5246 1998 by 7h North American ihh0bgkd sodety

Temporal variability of stream macroinvertebrate abundance andbiomass following pesticide disturbance

JOHN J. HIJTCHENS, JR.*

Institute of Ecolqy., Unimsity of Georgia, Athens, Georgia 30602 USA

Deartment of Entomology, Unizzrsity of Georgia, Athens, Georgia 30602 USA

J. BRUCE WALLACE

hstitute of Ecology and Department of Entomobgy, Unimity qf Georgia, Athens, Georgia jO602 USA

AbSfrad. bk d&ell&d the eXkllt Of macrOinvertebrate ~covery in a former pesticide-treatedstream (FIS) relative to a reference stxeam (R5) by examhkg macroinvertebrate colonking redmaple (Acer r&rum L.) litter bags between 5 to 10 y following pe&ide.treatment. Mean abundamxand biomass, vari+ility in abundance and biomass (using the coefficient of variation [cvj), andassemblagestrudutewerecomparedbothwithinandamongyearstoassessrecavery.Theyofstuayinchtded3dtoughtyearsfollowedby2wetyeaft.Meantotal alhdame and biomass ofmacroi&xtebra~es, and that of most functional feeding groups (FFG) did not &niCcantly differbetween streams during this study nor did within-year variability of these means, indicating mac-roinvertebrates in FE had recovered relative to RS. Some exceptions to the above patterns (shredderabundance and mean annual gw biomass) resulted from the dynamics of a single taxon in eachgroup (Lewfru and Pa~ufqtoph&~ia, respectively). Macroinvertebrate assemblage structure in litter bag8was Similar between streams throughout the study as shown by their similar ordination scores; hence,assemblage structure had also recovered. In each stream, mean annual abwdawe and biomass oftotal 1 and of each FFG, aside from shredder abundance, differed signikmtlyamong years. However, assemblage structure, was generally similar among years. Among-year CVswere usually lower than within-year CVs because macroinvertebrate abundance and biomass fluc-tuated more during a year than it did from year to year, and difkent proces8es apparently contriiuted to the variation observed at these 2 time scales. For exampk juvenile development t&ne influ-enced within-year CV8, indicating that life-histciy &aracteristics affec&d temporal yariability of mat-roinvertebrate abundance and biomass. Ekamination of both the means and their variaxes was usefulfor determining thk extent of recovery and how macroinvertebrates responded to natural environ-mental variability. The detailed analysis of temporal dynamic8 at different time scales afforded bythe CV supported our contention that F’T’S had recovered from the pesticide application relative toR!3.

Key umd& lone-term rec&ery, within-year variability, ‘among-y&r variability, coefficient of vari-atio< life history, iohort produckm inter&l.

The ability of stream macroinvertebrate as-semblages to recover from disturbance dependson many fakrs, including 1) life-history char-acteristics of organisms, 2) timing of the distur-bance, 3) presence of survivors within disturbedsites, 4) distance of source populations for re-colonization, and 5) nature of the disturbance(Gore and Milner 1990, Wallace 1990, Yaunt and

l E-mail address: hutchens@sparc.ecology.uga.edu2 Present address: Department of Agricultural Biol-

ogy, Kangweon National University, Chuncheon, 200-701,' South Korea

Niemi 1990, Mackay 1992, Milner 1994). For ex-ample, species that have high vagility or thatsurvive disturbances can recolonize disturbedareas rapidly, often in a stodwtic mannerlarge-Iy dependent on the ‘timing of the disturbancerelatk .to their life-cycle stage (e.g., Gray andFisher 1981, Fisher et al. 1982, Wallace et aL1986, Whiles and Wallace 1992, 1995). Subse-quent &mges in a recovering macroinverte-brate assemblage may result from further recol-onization and biotic interactions, but also de-pend on the natural diskrbance regime of theare? (Fisher 1983).

518

19981 LONG-TERM RECOVERY OF MA~ROINVERTEBRATES 519

Disturbances can generally be categorized aseither pulse or press type (sensu Bender et al.1984). Pulse disturbances are short term andcause relatively instantaneous alterations topopulation densities or community structure,whereas press disturbances are long term andcause a sustained alteration of these parameters.Distinguishing between disturbance type canpromote understanding of recovery mecha-nisms of lotic macroinvertebrate assemblagesbecause recovery is affected both by direct ef-fects of the disturbance on organisms and long-term physical changes to habitats (Resh et al.1988, Yaunt and Niemi 1990). For example log-ging activities can alter both habitat quality andthe energy base of streams. Recovery of streammacroinvertebrates following catchment log-ging, then, is linked to recovery of the riparianvegetation and substrate characteristics of thestream bed (Webster et al. 1983, Stone and Wal-lace 1998). In such cases, it is hard to separatethe response of macroinvertebrates to the actualdisturbance from their ability to recover fromresidual physical alterations to the stream. Incontrast, pulse disturbances caused by somepollutants, such as pesticides, affect stream biotawithout inducing any significant changes in thephysical environment (Wallace 1990, Milner1994).

Here, we report results of a study comparingmacroinvertebrate colonization of’ litter bags ina stream that had been treated with pesticide 5y prior with that in an untreated referencestream. Seasonal applications of a pesticide (me-thoxychlor) to this headwater strkm removedanimals from the stream without signi6cantlychanging the’.physical habitat or energy sources,such as leaflitter and associated microbes (Cuff:ney et aL 1984,199O). This arrangement allowedus to assess the recovery from disturbance with-in the context of natural fluctuations in popu-lations. Natural variability in macroinwxtebrateassemblage Structure ablmdancq and biomassis a product of both within-year, and among-year changes associated with factors such as lifecycles, availability of resources, and climate(Resh and Rosenberg 1989). Detecting changesin the magnitude of natural fluctuations in ani-mal populations following disturbance is essen-tial, yet often neglected (Underwood ,1994). Inour analyses, we examine these fluctuations us-ing measures of both mean values and variancebecause analyses of means alone may hide im-

pO*i ecological information about recoveryand long-term population dynamics (Under-wood 1991,1994, Palmer et al. 1997).

Wallace et al. (1986) previously examined therecovery of the pesticide-treated and referencestreams for 2 y and found that trophic recovery(i.e, functional feeding group FG] abundanceand biomass) had occurred, but not taxonomicrecovery. We examined these same streams for5ytoexamine whether trophic recovery per-sisted and whether taxonomic recovery oc-curred. Many studies of recovery are limited to<l y so our study provided a valuable oppor-tunity to examine a relatively long-term recov-ery sequence. Furthermore because the streamswere sampled throughout the year, we wereable to compare recovery patterns within andamong years. Little is known about the relativeamount of variation between these 2 temporalwalks because simultaneous comparisons ofvariability are rare

Our specik objectives were 1) to compare themeans of total macroinvertebrates and FFGabundance and biomass colonizing litter bags ina pesticidedisturbed stream and a nearby ref-erence stream to determine the extent of recov-ery relative to a previous short-term study (wal-lace et al. 1986), 2) to compare the variability ofthese means at within- and among-year tem-poral scales to help determine recovery and de-scribe patterns of variability, and 3) to compareassemblage structure within and between thesestreams.

Study Site ’

The study.was conducted at the Coweeta Hy-drologic Laboratory (CHL), a 1626ha drainagebasin in the Blue Ridge Province of the southernAppalachian Mountains (lat 35”03’N, long83‘25’W). The 2 first-order streams used in thisstudy drain Catchments 53 and 55. Thesestreams have predominately mixed-substratebeds (a heterogeneous mixture of cobbles, peb-bles, gravel, satu$ and silt), and are similar inelevatim size, slope aspect, and thermalregime(Table 1). The dominant riparian vegetation ofthese systems is also similar, and includes thedeciduous red maple (Acer rubrum L.), tulippoplar (Liriodendron fuZipij%ra L.), red oak (QuT-cus rubru L.), white oak (Q. a&a L.), and the w-ergreen rhododendron (Khoclodendron maximumL!). The rhododendron understory provides

520 J. J. HTJTCHENS ET AL. [volume 17.

TABLE 1. Physical characteristics of the formertreatment stream (FE) and reference stream (RS).

Rs

catchmenthea &4Blevatim (m as1 at &me)&pea

Length (mlBankfull area (m’)Gradient (cm/m)

Mean annual disdwge (L/s)198519861987198819891990

Annual degree days (6-yavg.)

5 .2 7 . 58 2 0 8 1 0

S S

‘145 1 7 03 2 7 3 7 3

2 7 2 0

0.59 0.950.33 0,500.74 1.430.42 0.691.451.56 248

4 5 1 1

heavyshadingofthestreamsevenafterthema-jor leaf fall period (October to December).

Catchment53servedastheformertreatmentstream (FTS), whereas catchment 55 was thereference stream (RS). FTS received 4 seasonalpesticide treatments from its upstream springSeeps to a gauging flume during 1980 (Wallaceet al. 1982). The pesticide methoqxhlor (l,l,l-tl-lcbmu-bis @ethqphenyl]ethane;Chem-ical Abstracts Service (CAS) No. 72X3-5), wasapplied to the entire stream channel on eachdatefor5~husing2handsprayersatarateof10 mg’/L based on discharge at the flume Al-thoUghVeryloWleveIsofmethoxychlor~per-sistforyiearsinstreamsediments(wallaceetaL1989), this residual pesticide appears to be tight-ly bound to sediments and inactive (see Murty1986). Survivors and aerial adults were the pri-

- _ ., mary mechanisms for macroinvertebrate recol-onization of FTS (W’ce et aL 1991b) becausethe gauging flume prevented ,recobnizaiionfrom downstream sources (!SGderstr&n 1987).Drift from upstream sources (Townsend andHildrew 1976) was minimal because the streamwas treated up to its source Further details areavailable in Wallace et 5;1. (1982,1986) and Cuff-ney et al. (1984,199O).

We initiated our study in 1985,5 y after ces-sation of pesticide treatment. Annual precipita-

tion over our 5-y study was 90.4% of the kmg-term average, yet the study period encompassedextremes in >60 y of record at Coweeta (US De-partment of Agriculture WSDA] Forest Service,Coweeta Hydrologic Laboratory, unpublisheddata). Drought conditions occurred from 1985 to1988 (precipitaticm = 74.2% -of average), in&d-.ing the kwest (1986 = 124.0 cm, 68.7% of av-erage), and the 3rd-lowest (1988 = 126.7 cm,70.2% of average) annual precipitations on re;cord. In contrast, 1989-1990 were wet years(precipitation = 1229% of average), with thehighest annual precipitation on record in 1989(234.1 cm, 129.8% of average), followed by anabove-average year (1990 = 209.5 cm, 116.1% ofaverage). As a result of this variation in precip-itation stream discharge varied considerablybong years Fable 1, Fig. 1). In addition, thewetted area of stream channeh ranged from 95to171m2inFTSandfrom206t0266m2inRS(Wallace et al. 1991a).

StreamdischargewasmeasuredbytheUSDAForest Service during frost-free months (Aprilthrough November) fmn 1985 to 1990 by usingstage recorders attached to H flumes, whichwereinstalledatthebaseofFTSandRS.Forwintermonthswhentheftumescouldnotbe.used, discharge was calculated using regres-sionsofdkhargeinFTSandRSversusdis-charge in a nearby gauged catchment (C 2) witha V-not& weir (t” = 0.903 and 0.931 for C 2versus FTS ind RS, respectively).

Methods

Lifter bag preparatiunRed maple leaves from CHL were collected

in mid-October of 1984, 1985, 1987, 1988, and1989, and ca 15 g (air-dried weight) were placedinto 20 x 35 cm plastic mesh bags (mesh size:ca 5 mm). In mid-December of each year, 60 lit-ter bags were placed into mixed-substrate hab-itats of each stream,. During baseflow currentvelocity in these habitats is ca 10 cm/s (J. B.Wallace, unpublished data) snd depth is ~10cm. Bags were secured to the stream bed withgutter nails in multiple reaches over the entirestream length.

Macroi&brate co&xtion and processingEach month from January to June of each year,

and at 6-wk intervals during the last l/2 of each

19981 LONG-TERMRECOVERYOFMACROINVERTEBRATES 5 2 1

RS’ .

Nov 84 Nov8S NW& Nw87 Nw88 Nw89 Nw90

(FTS)duiingourstudy. - - .

year, 5 litter bags were’collected randomly fromeach stream. Sediment, .detritus, and macroin-vertebrates were washed from litter bags onto a125-v-mesh sieve, and preserved in a 6-8%formalin solution containing a small amount ofPhloxine B dye to facilitate sorting macroinver-tebrates from debris. Samples were processedthrough nested lOOO- and 1.25-)Lm-mesh sieves.All macroinvertebrates retained on the lOOO-Frnsieve were removed and identified. The sampleretained on the 12!5qm sieve was subsampled(l/4 to l/64 of the original sample) using asample splitter (Waters 1969) before removinganimals. Macroikertebrates in subsampleswere removed, identified, and measured to thenearest mm for conversion to ash-free dry mass(AFDM) using taxon-specifk length-weight re-gressions (Huryn 1986, Huryn and Wallace1987).

Taxonomic and FFG assignments followedthat of Merritt and Cummins (1984) or otherstudies of the benthic fauna in CHL (Huron andWallace 1987, Lugthart 1991)+ We use the termsgatherers and filterers for collector-gatherersand collector-filterers, respectively throughoutthe paper Scrapers were not included in sepa-rate FFG analyses because they composed Cl%

oftotalabundanceandbiomassinlitterbagas-SemblageS.

Criteriaj7r rewmy and shztistical anahps

We assessed macroinvertebrate recovery inFT!3relativetoRSusingavarietyofmetricsorindicators, which included total abundance andbiomasstoexamine theoverallresponsetothepesticide treatment, and abundance and bio-mass of each FFG to evaluate recovery of trophicstructure Because estimates of absolute abun-dance can be extremely variable, we also includ-ed metrics based on the variability in means.These variation-based metrics improved our.ability to evaluate recovery over time. Finallywe evaluated diffexnces in taxonomic structureof macroinvertebrate assemblages in FTS andR!3 using ordination.

Total and FFG-specific abundance and bio-mass of macroinvertebrates were compared be-tween streams, among years, and within yearsusing a repeated measures analysis of varianceAbundance and biomass data were In (x + 1)transformed to correct problems with heteros-cedasticity. Analyses were conducted using theGqzral Linear Model (GLM) of SAS (Release

522 J. J. HUTCXIENS ET AL:.

6.03, SAS Institute Inc., Ca& North Carolina).This study like most ecosystem-level manipu-lations, involved pseudoreplication,. Therefore,differences between RS and FTS cannot bestrictly attributed to treatment effects (Hurlbert1984).

Variability in macroinvertebrate abundanceand biomass between streams was comparedusing the coefficient of variation (CV) for totalmacroinvertebrates, for each FFG, and for the

dominant shredder taxa. We chose CV as ourmetric because it is scaled to the mean inde-pendent of sample size, and easily interpreted(Wi&mson 1984, Grossman’et al. 1990, Mc-Arde et al. 1990, Palmer et aL 1997). Within-year CVs were calculated using the means oflitterbags collected on each sampling date with-in a given year, yielding 5 within-year CVs (1for each year) for each group in each streambased on abundance or biomass. The means ofreplicate litterbags for each sampling date wereused to calculate within-year CVs to remove thevariability associated with sampling from tem-poral variability. Among-year CVs, in contrast,were calculated using the 5 annual means,yielding a single among-year CV for each groupin each stream based on abundance or biomass.

We compared the within-year CVs for theabundance and biomass of total macroinvert~brates, of each FFG, and of the dominant shred-der taxa between streams by comparing their95% confidence intervals (CL) (Zar 1984). These

: within-year CVs were normally distributed andhad equal variances. We could not statisticallycompare among-year CVs between streams be-cause ther? was orily 1 value per stream.

Life-history characteristics can affect temporalvariability of macroinvertebrate abundance and

, biomass. Thus, we’investigated whether therewas a relationship between juvenile develop-ment time of individual taxa and their.within-year CVs of abundance and biomass. Linear re-

*. ., gress+ms were done between within-year CVs(n = 5) for each of 22 taxa and their respectivecohort production intervals (CPI). CPI providesan estimate of development time measured asthe mean length in days of the aquatic stage(Eknke 1984). Separate regressions were donefor FTS and RS. Within-year CVs of taxa werelog,,,-transformed to correct problems with non-normality and heteroscedasticity. CPIs for mosttaxa in CHL streams have been reported byLug&art and Wallace (1992), although some

volume 17

multivoltine taxa with unclear CPIs, i.e, Chiron-omidae and Copepoda, were conservatively es-timated at 90 and 100 d, respectively@‘Doherty 1985, Huryn 1990). The 22 taxa usedin this analysis represented 92-96% of totalabundance and N-94% of total biomass in bothstreams. These taxa included representativesfrom each FFG, except for scrapers. Diplecfronatnetaqui was excluded from the analyses for RSbecause it was not collected in 2 of 5 y.

Macroinvertebrate assemblage structure in lit-ter bags was analyzed by ordinating the logI,, (x+ I)-transformed mean abundance and biomassof 11 common taxa in both streams on each col-lection date. Each of these 11 taxa composed atleast 5% of total biomass in either stream in 2or more years. Fewer taxa were used than the22 above to reduce noise associated with raretaxa (Gauch 1982). We ‘used detrended corre-spondence analysis @CA, Hill and Gauch 1980)nm with MVSP (Version 3.0, Kovach Computing!Services, Anglesey, Wales, UK) to ordinate thedata. DCA produces a similarity matrix basedon chi-square distances.

ReSults

Discharge

Discharge was consistently higher in RS thanin FTS (‘Table 1, Fig. l), presumably because of .the larger catchment of RS. HiJwewr,thetimingof discharge lTlZ&XWwaSSimilarbetween

streams (Fig. 1). Although drought conditionsexisted from 1985 through 1988, both streamsremained perenrkl and experienced occasionalsmall rainfall-induced increases in discharge(usually cl0 L/s) during this period.

Within- and among-year analy@s ofrnacroitiehate aZnm&nce and biomass

Mean annual abundance of total macroinver-tebrates and of each FFG, aside from filterersand shredders, did not differ significantly be-tween streams (Table 2). Filterers were moreabundant in RS than in IT!3 each year (Fig. 2),but only composed 0.1-0.4% of total abundancein any year Although shredders were consis-tently more abundant in RS than in F’PS (Fig. 2),this difkrence was heavily influenced by onestcmefly, Larctra, In fact, the other abundantshredders (i.e., Lepidostoma, Tallape&, and Pyc-

1998J LONG-TERM RECOVERY OF MACROINVERTEBRATES 523

TABLE 2. Results ot e&h repeated measures analysis of variance comparing the In (x + I)-transformedabundance of total macroinvertebrates and functid &ding groups in the reti (RS) and former treatment(FTS) streams in each year and on each date Strew = Rs vs FI’S, Year = among years (1985,1986,198&1990), Date = collection dates within years, df = degrees of freedom, MS = mean square, p < 0.05 are in bold. ’

Variable

Stream Date XX Date X Date X Stream X Error

s t r e a m Y e a r Year Error Date Stream Y e a r Year IDate

Total dfMSFP

Filtems d fIa!3F

'Gatherers LMSF

PldiltOrSLlb23F

Shmdders fhMSFP

10.1120290.5961

4;.46542.87co.oo1

10.3000.690.413

. .

Lo40.450.5071

14.98614.84

<o.oln

4 313.916 1.89835.7l 4.87

<O.OOl 0.0074 34.677 0.7284.22 0.660.007 0.5844 3

16.358 2.19037.50 5.02-=o.ool 0.0064. 3

10.593 122615.72 1.82<o.ool 0.164

4 31.748 4.3191.73 4.280.167 0.0-U

3 20.390

3 21.107

3 20.436

3 2'0.674

3 21.010

8 8 3 2 2 43.197 1.469 0.993 0.4218.60 3.95 2.67 1.13

co.001 ~0.001 <o.olll 0.3108 8 3 2 2 45.276 1.7l8 1.623 2.0762.87 0.93 0.88 1 . 1 30.005 0.489 0.653 0.3128 8 3 2 2 43.796 1 . 4 2 1 1.122 0.4498.98 3.36 265 1.06

CO.OOl 0.001 <o.ool 0.3908 8 3 2 2 45.902 1.6!54 1.477 0.834

11.74 329 2.94 1.66<O.OOl 0.001 <o.ool 0.0308 8 3 2 2 43.044 5.577 1.351 1.6783.19 5.84 1 . 4 1 1.760.002 <O.OOl 0.076 0.018

2560.372

2561.839

2560.423

2560.503

2560.955

rqmyche) were usually more abundant in FT!3than in RS. Macroinvertebrate assehblages inboth streams were dominated by gathers (86-92%oftotalabundanceinFTSand83-91%inFS), of which Copepoda and Chironomidaecomposed 90-95%. Thus, results for total an-nual mean abunwce in both streams reflectedthe dynamics of these 2 groups.

MeanamnQlbiomassoftotalmacroinverte-brates and each FFG did not signikantly differbetween streams, except for filterers and gath-erers (Table 3). Filterer biomass was higher’inRSthaninFTS,butagainonlycomposedasmall proportion of total biomass (2-6%). High-

. er gatherer biomass in RS was attributed to a._ single mayfly Purfz&ptuph&bia. Conversely other

major gatherer taxa (i.e., Amphinemura, C&iron-omidae, Copepoda, and Oligochaeta) tended tobe higher iq F’IS. The contribution of shredders,predators, and gatherers to total biomass wasmore evenly distrikted than that observed fortotal zibudance.

In most years and in both streams, meanabundance and biomass varied similarly amongcollection dates (Figs 3,4). Within-year variation

of mean abundance for shredders and filtererstended to differ more between streams than for.other FFGs (Fig. 3), but this was not necessarilytrue of variation in mean biomass (Fig. A).

Meananmlal abundance of total macroinver-tebrates and of each FFG, except for shreddkrs,difked si*cantly among years (Table 2), pri-marily because meananrmlabundancewaslower in 1985 and 1986 than in 1988,1989, and1990 (Fig. 2). Significant Stream X Year inter-actions were also noted for most of these groups(Table 2) because abumhceinFTStendedtobe higher than in RS during 1985 and 1986, butlower than in RS during 1988 and 1990 (Fig. 2).Significant diff&nces in mean annual bio-mass among years were also noted for totalmaaoinvextebrates and for each FFG (Table 3);Asforabundance,bivwasusuallylowerinthefirst2yofthestudycomparedtothelast3Y m3 2).

The effect of the date of litter bag collectionwas always highly significant (p I 0.005) for theabundance and biomass of all macroinverte-brates and each FFG except for filterer biomass(Tables 2,3). This result demonstrates that with-

524 J. J. HUT~-ENS ET AL.

8000

8000

4000

2000

40+----1300

;I g.&&

1

P

0- 8000B$ 8000-

88 4000

5 20009

I I I Ii I1

P - t -

:: “Q

.,

‘cl’

4:-13020

id

.' P.** - -10 ‘0.’

0

800 -1500

400300 ;* 'fJ.

:. 200100.;

!-f!f? ..d:”

85 88 8788 89 90

Total

Shredders

GathererS

Fimn

Predators

9 080708050

w. -. .I I I I I I I

.

[VolUme 17

0h-rrn-n50.140 -I

‘“,1m85 88 87'88 89 90

FIG. 2. Annual means (21 SE) for abundance andbiomass,ofea& functid feeding group and totalmawbrates in the former treatment stream (FE) and in the reference stream (R!3) vs yeaz In some casestheerrorbzirsarehiddenbysymbols.

.. in-year changes in abundance and biomass werelarge sources of variation during the.study.

Within- and among-year miance inmacroinxertebrate abundance and biomass

Within- ahd among-year variability of mac-roinvertebrate abundance and biomass weres&ilar between streams (Fig. 5), despite theirdifferent disturbance histories. There were no

significant differences between streams inwithin-year CVs based on the abundance orbiomass of total macroinvertebrates, tif anyFFG (95% CIs, Fig. 5), or shredder taxa exceptfor the sericostomatid caddisfly, Ezttigia (bio-mass only, Fig. 6).

Within-year CVs of abundance and biomasswere usdy hi* than among-year CVs fortotal macroinvertebrates, each FFG, and individ-ual shredder taxa (Figs 5,6). These results dem-

19981 LONG-TERM RECOVERY OF MACROINVERTEBRATES 525

TABLE 3. Results of eadi repeated measures analysis of mce comparing the In (x + l)-kansformedbiomass of total macroinvertebrates and functional feeding groups in the reference (RS) and former treatment(FE) skeams in ea& year and on each date. Stream = Rs vs FIS, Year = among years (1985,1986, 1988-1990), Date = collection dates within years, df = degrees of freedom, MS = mean square, p C 0.05 tie in bold.

Variable

Date xStream Stream

X Date X Date X X ErrorSkeam Year Year Error Date Strealll Y e a r Y e a r @ate)

Total d f 1 4 3Ia!3 0.251 1.028 0.697F 0.83 3.42 2.32P 0.368 0.020 0.094

Filterers df 1 4 3MS 9.215 2.478 0,570F 13.25 3.56 0.82P 0.001 0.016 0.493

Gatherers df 1 4 3MS 1.021 7.569 1325F 4.30 31.89 5.58P 0.046 co.ool 0.003

PledatoP df 1 4 3Ia!3 1.883 3.215 1.424F 3.09 5.27 234P 0.088 0.002 0.092

Shredders df 1 4 3M S 0.207 2.466 0.942F 0.40 4.72 1.80P 0.533 0.004 0.167

320301

320.6%

320.237

320.610

320.523

8. 81324 0.5175.08 1.98

<O.OOl 0.0498 81.197 0.7811.56 1.020.137 0.4238 80.846 0.9683.85 4.40

CO.OOl <o.ool8 82.841 0.3415.81 0.70

co.otn 0.6938 84.413 1.8147.76 3.19

co.001 O.OOi

32 240.597 03492.29 134

<om1 0.13932 24

0.790 on31.03 0.930.428 0.563

32 240.553 0.449251 204

<0.001 0.00432 24

1.262 0.5462.58 1.12

<0.001 032532 24

1.074 0.5771.89 1.020.004 0.446

~-256

0.261

2560.767

2560.220

2560.489

2560.568

on&rate that changes in macroinvertebrateabundance and biomass were greater withinyears than among years.

Regression analyses of within-year CVs ofabundanceandbiomassandCFGforthe22taxa(Fig. 7) indicated that with&year vahbiliity inboth abundance (FTS: p = 0.006, P = 0.068, n= 110; Rs: p = 0.015 P = 0.059, n = 105) andbiomks (F’& p < 0.001, +J = 0.143, n = 110;RS: p < .O.OOl, 9 = 0.146, n =, 105) &easedwith longer juvenile development times. Al-though these regressions explained relativelylit-tle of the variation seen in within-year CVs, theysuggested that difkrences in life history influ-enced temporal variability, especially of bio-mass

Gmparisons of rnacroitiehate assemblagestruchcre

Assemblage structure based on abundanceand biomass was similar between streams kdamong years during the study because most ofthe ordination scores formed 1 large group in

similar species space (Fig. 8). Initial collectionsin both streams during 2 drought years (1985and 1986) clustered separately from the maiugroup with lower scores on both axes, althoughthiswasnotthecasefortheordinati~ofabun-danceinFTS.Mostoftheexplainedvariatkmineach o&nation (Axis 1) reflected d3ferentgroups of taxa that colonized either relativelywhole leaves soon after placement in the streamor more decomposed leaves later in the yeaxAxis 1 explained 34.2 and 33.4% of the variationin the zibundance and biomass ord.inahu, re-spectively. The initial collectim in January (cl&notedinFig.8byaSnexttoitsrespectivesym-bol) with most of the litter present had low Axis1 scores, whereas later collections had higherscores. January assemblages were dwacterhedby the shredders, Pycmpsyche, Lepidostoma, andTdZaperZa, and a predator, Beloneuria. Later sam-ples were dominated by small gatherers (Chi-r&da% Oligo&aeta, and Copepoda) andtheir prkdators (Ceratopogor@ae and lidtus),and 2 shredders, Leucfra and TipuZu. Axis 2 onlyexplained 15.7 and 16.1% of the variation in the

526 J. J. HUTCHENS ET AL. lvolume 17

bs 2.55 3.0

2 2.0. I>=G 4.5 1.0

8,jj 3.5m5 2.5%% 2.0

Shredders

- Filterers

1985 1986 1989FIG. 3. Log,, (x + i>transformed mean abuhnce of total macrohwkbrates.and each functid feeding

group if, fhe former treatment stream (FTS) and in the reference stream (RS) on each date of litter bag collection.

abundance and biomass ordinations, respective-ly. This axis was related to the dominance ofeither Pycnopsyche (high Axis 2 score) or Tipula(low Axis 2 yoke) in both abundance and bio-mass ordinaihs.

Discussion

Gmparisons behmn streams

-.”

Following the initial pesticide treatment toFTS in 1980, total macroinvertebrate abundancerecovered rapidly (117 d), but total biomass wasonly l/3 that of the reference streqm during the1st year of recovery (Cuffney et al. 1984). Theins& component of the macroinvertebrate as-semblage suffered losses in abundance and bio-mass of >90% (Cuffney et aL 1984). After 2 yof recovery in FT!S, m&n annual abundance andbiomass of total macroinvertebrates and FFGs

did not differ between treated an$ referencestreams (Wallace et al. ,1986). During recoveryyears 5-10, mean annual abundance and bio-mass of total macroinvertebrates and most FFGsinF’EalsodidnotdifferfromRS,andabun-dance &d biomass typically had simihr within-year dynamics. Recovery times of str+rns afterdirect application of pesticides are variable, butare often 51 y (Milner 1994). The somewhat lon-gertimeforrecoveryinFTSwasafunctionofmany factors, including 1) the lack of upstreamsources of recolonization, and 2) the repeatedseasonal applications of pesticidde, which elimi-nated colonists that either hatched from surviv-ing eggs or arrived from nearby streams be-tween treatments (Wallace et al. 1986, Chung etal. 1993). The continued similarities in FFGtdmndahce and biomass seen in our study in-dicated that there were no prolonged effects ofresidual pesticide in FE sediments. Overall, our

19981 LANG-TEXM RECOVERY OF MA~R~INVERTEBRATE~ 527

g 1.0g2 00 1:5

3 1.0

? 0.5

3 0.053. 2.5

-I Shredders . FTS q RS

I ’ I I I l

1985 1986 1988 1989 1 9 9 0FIG. 4. Log, (x + I)-transformed mean biom;iss of total macroinverie!xates and each functio~I feeding

group in the former treatment stream (FE) and in the reference stream (R!3) on ea& date of litter bag collections.

results agree with those expected from short-duration pulse disturbances because recoverywas long w.

Some exceptions to the above patterns (shred-der abundance and mean annual gatherer bio-mass) resulted from the dynamics of a singletaxon in each graup (Leucfru and ParaZe@p~&&respectively). Leuctra xmMimes functions as agatherer, especially in early instars (Hildrew etaL 1980, Dobson and Hildrew 1992), and the or-dination scores for Lfwztra were more similar togatherertaxathantoshreddertax+hus,clas-dying lieu&z as a shredder may be question-able and merits further atkntion (also see Stew-art and stark 1993).

We used CVs to examine trends for absoluteabundance and biomass, and to assess within-and among-year variability. We expected themean abundance and biomass of macroinverte-brates to fluctuate more. in FTS than in R!3 fol-

lo&ng the pesticide disturbance Streams recov-ering from disturbance may harbor more inver-tebrate populations with short life cycles, rapidgrowth, and high fecundity compared to near-.by undisturbed streams (W4lace 1990). In ad-ditim loss of a number of predatory taxa inFT$during the treatment year may have allowedvarious prey taxa to increase their survivorshipand growth rates (Cuffney et aL 1984); whichcould alsg increase va&bility in FTS macroin-vertebrates. However, the CVs showed no majordifferences in temporal variability betweenstreams. Therefore, the results for *abilityaround means agreed with those of meansalone, and demonstrated that macroinvertebrateabundance and biomass in ITS had recoveredfrom the pesticide disturbance Detailed analy-sis of -imacroinvertebrate temporal dynamicsprovided by the CVs supported our contentiontit abundance and biomass had recovered in

528

Total

Shredders

PredatorsGatherersFiiterers

Shredder8

Predators

GatherersFilterers

J. J. H~T~HEN~ ET AL. volume 17

Wthin-year variabilityAbundance Biomass

1 1

Among-year variability

0 40 80 120 0 40 80 120

WC4

F IG . 5. Mean within- (top) sind among-year (bottom) coefficients of variation (CV) for total macr~brateandeachfunhmalkdinggroup abudame (left) and biomass (right) in the former treatment streaq (ITS)and in the refereme stream (RS). Error bars for within-year CVs represent +95% confidence intervals.

FTS relative to RS. The inclusion of end-points basin, which served as sources of~recolonists af-thatarebasedcinbothmeanresponsesandthe ‘ter pesticide treatment.vaxi&lity of responses @proved our ability tojudge the completeness of recovery1

Macroinvqtebrate assemblage structure inlit-Cornparis0ns among years

ter bags was &nilar between streams through-outthisstudyasshownbythesimilarordina-tion scores between streams. Thus, as with mac-ro&vertebrate density and biomass, assemblagestructure had also recovered in FTS relative to

.- . RS during this study. Two years after pesticide‘_ treatment ended, Wallace et al. (1986) found ma-

jor differences in taxonomic composition be-tweenthesestreams.Thesimilarities~inthepresent study (5-10 y after treatment) SW thatmore time was required for recovery of assem-blage structure compared to trophic structure(i.e., FFG abundance and biomass). The similar-ities in assemblage structure between RS andFTS partly resulted from their similar physicalcharacteristics and close proximity (300 to 1000m) to numerous headwater stre+ms in the CHL

We found more differences in mean annualabundance and biomass among years than be-tween streams. Studies that have examimd mul-ti-year trends (i.e., >2 y) in FFG or total ma&-invertebrate abundance have also reported largeamong-year changes (McElravy et aL 1989,Boulton et a.L 1992, Wmterboum 1997), but weareunawareofsimilarstidie!3thathaveexam-ined&angesinbiomassovermanyyears.

The year-to-year differences’ we observedwere primarily a result of lower macroinverte-brate abundance and biomass in the first 2 y ofthe study (especially in, 1986, the driest year on ’record at CHL) than in the last 3 y. Stream mac-roinvertebrates often concentrate in the reducedFtted area during periods of drought, causingdensities to increase (e.g., L&more et al. 1959,

19981 529:LONG-TERM RECOVERY OF MACROINVERTEEXATES

Within-year var iabi l i ty

Abundance Biomass

Fattigia

TalaperiaLeuciraTipulPvcnww~eLepidostoma -a

I I I I I I I I

A m o n g - y e a r variabiiii

FattigiaTalraperlaLeuctm77pula

~opsyche -ILepidostoma

I I I I I I 1

0 100 200 300 0 100 200 300

cv 0

FIG. 6. Mean within- (top) and among-year (bottom) coeff&nts of varialh (CT.‘) for the dominant shreddertaxabasedanabundance(left)andbiamass(right)inthefwmer~atmentstream~)and~the~~stream (RS). Error bars for within-year CVs zpresent +95% confidence Wervals. Asterisk iruhtes a significantdifkencebetweenFISandRS(p<O.O5). -

1991a). In contrast, streams in some of the stud-iescited~becameeitherintermittentoraseries of disc- pools.

Among-year cvs were usually lower thanwithin-year CVs, especially whenbased onbio-mass, because macroinvertebrate abundanceand biomass fluctuated more during a year thantheydidfromyeartoyear,whichisnotsur-prising when life-history patterns and coloni-zation time are considered. Most taxa in CHLstreamscompletetheirlifecyc!leswithin1y,meaning that sampling during ayear encom-passes the entire survivorship and growthcurves. Also, avail&Zty of co- particulateorganic matter in these systems is strongly sea-sonalbecauseofthelargeinfIuxofautumn-shedleaves that subsequently break down Thus,CHL stream macroinvertebrates naturally un-dergo changes in abundance and biomass dur-ing a year because of life-cycle events and var-iable resources. In contrast, much less is knownabout factors controlling natural inter-annualvariation in the taxonomic composition and bio-

Kamler and Fiedell960, Stanley et aL 1994).However, other studies have repmted both in-creases and decreases in annual abundance fol-lowing droughts, depending on taxonqecificlife-history ~acterisiics (Boulton and Lake1992, Boulton’et al. 1992). We observed no con-sistent drought-induced pattern in macromver-tebrate assemblages, perhaps because mixedsubstrate habitats are less sensitive to droughteffects than other habitats, such’as bedrock out-crops (Lug&art and Wallace 1992). Finally, re-gional climate may be an important factor; larg-er’andmoreconsistentdifferencesinabundancemay be expected in regions with more pro-nounced differences ill precipitati~ ag., theScmman Desert, USA (Boulton et al. 1992),runhern caMor&, USA (Mediterranean-typeclimate; McElravy et aL 1989, Power et aL 1996),and Australia (Boulton and Lake 1992) than thehumid, temperate CHL.‘Even in the severedrought years of 1986 and 1988, R!3 and F-P3continued to flcrw, although FTS decreased inwetted area by as much as 80% (Wallace et aL

!53Q

225

33 2.75

J. J. HUT~-ENS ET AL. [volume 17

Abundance

1.75

" &Ml88 ,5o.rn.~ *

275FTS

@0

2.50

I II I I I I Il.25 I I I , I I

0 200' 400 ,800 800 1000 1200 0 200 400 800 800 10001200

Biomass

RS

Cl

1 RS

CPI (d)

FIG. 7. Log,,-,-transformed within-year coeffi&nts of variation (CV) for 22 taxa based on abundame (top)and biomass (bottom) vs their respective cohort production interval (CF’I) in the former treatment stream (FE)and in the reference stream (FE). The lines are fitted regressions.

mass of invertebrate assemblages in suchstreams. Using long-term organic-matter bud-’gels for the&reams in this study, Wallace et al.(1997a) hypothesized that litter standing cropsundergo multi-year cycles of accumulation andloss as a result of variable discharge. Decreasedlitter in some years could have detrimental ef-fects on macroinvertebrates; experimentalwhole-stream reductions in litter reduced mac-

-’ . ._ roinvertebrate abundance biomass, and second-ary productiq~ (Wallace et al, 1997b). Difffmntprocesses contributed to the vkiation observedat within-year versus among-year time 8cales.

Life-history characteristics of ITS and R!3 taxaalso 2Bected within-year variability in abun-dance and biomass. Those tsxa @h longerju-yenile development times were more variablewithin years than those with shorter develop-ment times. This result was probably a functionof sampling frequency relative to voltinism.Muhivoliine taxa with overlapping cohorts, for

example, would vary considerably in abundanceand biomass between monthly sampling peri-ods. In contras$ monthly sampling ofunivoltinetaxawoulddetectchangesinthenumberandsize of individuals that are associated with nor-mal life-cycle events because of the slower d&velopment of these taxa-abm&nc e may rangefrom 0 just before egg hatching to several thou-sand soon after hatching. Fmthermore, for se-mivoltine and merovoltine taxa, 23 cohorts thatgreatly differ in abundmce and mean individ-ual size can co-occur, which would result in ahighly variable within-year CV for both abm-dance and biomass. Nevertheless, the regres-sions of within-year CVs of abundance and bio-ma8s against CPIs left much of the variabilityunexplained, so that other factors (e.g., resourc-es, biotic interactions, etc.) must also influencewithin-year changes in macroinvertebrate as-semblages in these streams.Macroinvertebrate assemblage structure was

19981 LONG-TERM RECOVERY OF MACROINVERTEJ3RATEs 531

1.0

0.8

0.2

cu 0.0en.-

2

0.0 0.2 0.4 0.6 0.8 1 1.0 0.0 0.2 0.4 0.6 0.8 1.0

Biomass

Abundance

RS

1.8.

1.5

1.2.

0.9

0.6

0.3

0.0IFTS RS

03 0.3 0.6 0.9 1.2 1.5 I.$\ 0.0 0.3 0.6 0.9 1.2 1.5 1.8

Axis1 .

.

FIG. 8. Ordinati plots of the first 2 axes from dekended corres~ence analyses for the abundance (top)and biomass (bottom) of 11 mamWte taxa in the former ‘keatment stream (FTS) and in the refemmstream (RS) on ea& co&ction date Open symbols represent drought years j1985, 1986, 1988) and closedsymbols represmt wet years (1989,199O). The 1st collectim date each year is denoted by S and subseq&tcollectlonsarecoMectedbythesameline

generally similar within either RS or FTS across lected in late summer were’similar amongyears as shown by the ordination results, Which years, although some differences, related to dis-agrees with some other multi-year studies of as- charge, were noted for late-spring samples..semblage structure (but see exceptions below). Richards and Minshall(l992) found similar rel-McElravy et al. (1989) found that varigus corn- ative abun+ance of common macroinvertebratesmu&y parameters for macroinvertebrates col- in 5 undisturbed streams in Idaho, USA, over 5

532 J. J. HUTCHENS ET AL.

y. However, they also found that communitystructure in 5 streams disturbed by wildfke 1 yprior to the study varied more among yearsthan the undisturbed streams because of de-creased’channel stability from large-scale loss ofcatbent and riparian vegetation in burnedcatchments. Other 4-5 y studies (Meffe andMiddey 1987, Weatherly and Ormerod 1990,Wmterbourn 1997) also found that assemblagestruchue changed little in response to naturalenvironmental fluctuations. These studies showthat biotic parameters based on assemblagestructure are robust to year-to-year changes as-sociated with natural vahbility. However, thisfinding should be limited to regions with near-by,undisturbedpopulationsavailableassourcesfor recohmization (Cushing and Gaines 1989).Interestingly assemblage structure in somestreamscanbesimilarfromyeartoyearforrea-sons other than consistent proportions of taxa.For example, Boulton et aL (1992) found a con-sistent cycle of seasonal change in assemblagestructure over 3 y in Sycamore creek, USA, butthis~gewaSaresultofvariationinpresenceorabsenceoftaxaratherthanintheirrelativeabumhceSimilarresultswereobtainedin2intermittent streams in Victoria, Australia (Bd-ton and Lake 1992). Still, includixig a pammeterthat measures assemblage structure in biomon-,itoringstudiesshouldbeusefuLInfact,aneval-uationofvariousmetricsusedintherapidbioassessment protocol of the US E&mnmen-talProtectionAgencyfoundlowCVsintheF%nkham and Pearson communitysimihityin-dex, a structure metric that hcorporates abun-dance and composihnal informati~ in unim-paired ee sites (Barbour et aL 1992).

PalmerandPoff(lq97)examhedhowtem-poral and spatial heterogeneity influences pat-terns and processes in streams. These authorshighlighted how variability within and acrossd&rent spatial scales affects streams, but pro-vided few examples illustrating effects of vari-

-’ ‘. ability within and aixoss different temporalscales. Our results demonstrate that examhingtemporal variability at different scales is u&Yfor studying macroinvertebrate responses to an-thropogenic disturbances and responses to anaturally dlanging environment. Future studiesshould examine what factors influence variationat different temporal scales, including macroin-vertebrate life histories, resource variability, andbiotic interactions.

volume 17

Acknowledgements

We thank S. Eggert and D. Johnson for dis-cussions about variability. S. Eggert, C. Peter-son, and 3 anonymous reviewers providedmany comments that lylped improve the man-uscript. We also thank W. Swank and otherUSFS personnel at CHL for logistical assistance,and precipitath and disdx4rge data. This re-mu& was supported by grants from the Na-tional Science Foundation.

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Receiz#d: 26 h4ay 1998Accepted: 9 December 1998