\a Aqudtir:Ecolog' 36: 395-110.2002. 395 7T @2002KluwerAcudenicPublishers.Printedh theNetlErlands. Monitoring changein aquatic invertebratebiodiversity: samplesizet faunal elementsand analvtical methods S.A. Halsel,D.J. Calel, E.J.JasinskalandR.J.Shiel2 I Deparlment oJ Conservatiotland land Managemen4Scienc-e Division, PO Bor Sl WannerooWA 6916,Austrclia (Fax +61 89306 I64I: E-mail: [email protected]);t Departmentof EnvironmentalBiobgy, Unbersity of Adelqide,Adelaide SA 5005, Australin Accepted 24 October 2001 microinvertebrates,ordination,salinity, speciesaccumulationcurves Ke1 word,r.macroinvertebrates, Abstract Replicationis usually legardedas an integral pal1 of biological sampling,yet the cost of extensivewithin-wet!and replication prohibits its use in broad-scalemonitoring of trends in aquatic invertebratebiodiversity.In this paper, we report resultsof testing an alternativeprotocol, whereby only two samplesare collected from a wetland per monitodng event and then analysedusing ordination to detect any changesin inveftebratebiodiversity over time. Sinulated data suggestedordinationofcombined datafrom the two sampleswould detect20% speciestumover and be a cost effectivemethodof monitoring changesin biodiversity,whereaspower analysesshowedabout 10 samples were required to detect20% changein speciesrichnessusing ANOVA. Errors will be higher if yearswith extreme climatic events (e.g. drought), which often have dramatic short-term effects on invedebratecommunities, are included in analyses.We also suggestthatprotocolsfor monitodng aquaticinvedebratebiodiversity shouldinclude microinvertebrates.Almost half the speciescollectedfrom the wetlandsin this study were microinvertebratesand their biodiversity was poorly predictedby macroinvertebratedata. Introduction Biodiversity in wetlandsis being reducedby agricul tural, urban and industrial developmentthrough most of the world (Barbault & Sastrapradja,1995t Ricciardi & Rasmussen, 1999) and the situation is often perceived as a crisis (Savage, 1995). In response, many progmms have been initiated to conservewetland communitiesand processesat a regional or local scale(e.g. Hails, 1996; Froend et a1., 1997). Such programs usually include monitoring of biodiversity. Ideally, any species loss or significant changes in community stlucture will be detectedand appropriate managementinteF,'entionwill occur to recoverthe speciesor community. Developing monitoring protocols that are ljkely both to be adoptedand to provide adequateinforma tion about changes in aquatic invertebratebiodiver sity is difficult (Fairweather,1991; Humphrey et al., 1995). As managementagenciesale faced with an evergreateraray ofsituations that requiremonitodng, protocols that minimize costs will be preferred. This is achieved most easily by reducing the number of samplescollected and processed,although low numbers of samplesoften preventimpo ant changesbeing detected(Fairweather,1991; Streever,I 998). Most aquatic studiessamplerelatively small areas or volumesand, therefore,collect only a small proportion of speciespresentat the sampling site (seeRouch & Danielopol,I997; Tumer & Trexler,1997:Butcher, 1999).There is scopeto increasethe areaof substrate, or volume of water, sampled and collect a grcater proportion of the speciespresent.Thus, large-volume samplesmay be one way of maintaining the ability to detect changewhile reducing number of samplesand associatedcosts (Andrew & Mapstone, 1987; Kneib, r). 199 Another challenge in monitoring aquatic invertebrate biodiversity is selecting the appropriateorganisms to sample. Results will be useful only if the 396 groups chosen are representativeof trends in overall aquatic invertebrate pattems (see Green, 1979, p. 34). Few studies have examined the relationship betweenoverall aquatic invefiebratebiodiversity and its componentsbut, working on trees,Azarbayjani & Richardson(1999) showed little correlation between richness within most arthropod orders and overall aboreal arthropod diversity. Results from large-scale wetland suryeys also suggestpredictions of overall speciesrichness based on the chness of particular orders will frequendy be unreliable becausevarious orders exhibit different patternsof occurrence(Halse et al., 2000b: seealso Usseglio-Polateraet al., 2000). Many monitoring studieshave used speciesrichnessas a measureofbiodiversity and analysedthe data with ANOVA. Two drawbacksare that comparatively large numbersof samplesare requiredto detecttrends and that the method works best when speciesloss, ratherthan tumover,is occurring.The earliestchanges in biodiversity, however,are usually the replacement of sensitivespeciesby more tolerant ones without a reduction in overall speciesrichness (Growns et al., 1992).Multivariate dissimilarity measures,which take accountof tumover, are better indicators of biodiversity and may be analysedusing ANOVA (Faith et a1., 1995; Edward et a1.,2001) or ordination (Gray et a1., 1990;Streever,1998). This paper repofis a protocol for monitoring aquaticinvertebratebiodiversity in wetlands,basedon large sweepsamples,minimal within-wedand replication, identification of micro- and macroinvertebrates, and ordination analysis. It is an extension of the ordination method proposedfor wetland monitoring by Froend et al. (199'7) and its intended use is examination of long-term temporal changesat individual wetlands. We tested the protocol at five ecologically different wetlands, representingsulTogatesfor some of the changesthat might occur at a single wetland over many yea$ as a result of anthropogenicchanges in its catchment,to examinewhether the protocol was likely to detect changes in the aquatic invertebmte community. It is not our intention to challenge the needfor replicated,contolled studieswhen the causal effects of particular environmentalimpacts are being examined. Materials and methods Five relatively shallow, basin wetlands in the wheatgrowing zone of south westem Australia (Figure 1) Towdiming e Bn-de Mearfield Figure L Locati,ot of the five wetlands in south-west Western Australia. The 300 mm and 600 lnm rainfall isohyets corr€spond approximately to boundaries of the area with most secondary salinisation. 8 6 0 z 3 4 5 Cotrducaivity 0og10) F,g&r"2. Nunberof invertebrate species in eachwetlandcompared wilh log{ransformed conductivily values asa measure of salinity (rz:0.831,p<0.0s). were sampled in spdng (October) 1997. The region has a Mediterraneanclimate with winter rainfall and hot, dry summers. Annual average rainfall varies from 600 mm at Lakes Towerinning and Wheatfleld to 400 mm at Lake Bryde (Figure 1), with 80-907o of rain falling betweenMay and September.Average maximum temperaturesin Januaryand Februaryrange from 32 'C at Lake Logue to 26 "C at Lake Wheatfield (Bureauof Statistics,1995). Prior to agdcultural clearing, vegetationconsisted mostly of open woodland dominatedby eucalyptsor heathland dominated by Proteaceaeand Myrtaceae. Wetlandswere usually fringed by the trees Casuarina 39'1 Bryde Wheatfield Coyrecup Towerinning Logre Fry&,"cJ. Mear numbef (+ SE) of invetebfate speciescollected irom cach wetlaDdby single samples,two (adjacent)samplesfrom the same sector,two (paired) samplesfrom diflerent sectors.Number collecled by four samplesis also shown (seelexl fbr details ofsample collecting). obesa and Melaleuca spp., with occasionaleucalypts (Halseet a1.,1993a).Sedgesoccurredaroundthe water's edge of most wetlandsand acrossthe lakebedof shallow seasonalwaterbodies.Casuarina obesa a\d Melaleuca spp.sometimesoccured acrossIarge parts of the lakebed of wetlandsthat intermittently flooded to greaterdepths(ca. 2 m). Land clearing, and the replacementof deep-rooted perennial vegetationwith annual crops, has reduced transpirationrates and resulted in fising saline water tablesin n.ruchof the agriculturalzone, especiallybe tween the 600 and 300 mm isohyets (George et al., 1995). The processis often referred to as secondary salinisation and has profoundly affected the ecology of many ecosystemsin south-westemAustralia (see Williams, 1999),including causingthe deathof much wetland vegetationand its replacementby salt-tolerant samphirc.Remnantsofdead treesaroundwetlandsare now a commonsight(Halseet al., 1993a). Attributes such as size, depth, type and extent of riparian vegetation, and frequency of flooding var ied among the five wetlands but probably the most ecologically important differencesrelated to salinity status and associatedchangesin riparian vegetation (Table l). As wellas simplifying vegetationcomnuni ties, secondarysalinity reducesthe diversity of aquatic invertebrates(Timms, 1981)and alterswaterbirdcommunities(Halseet al., 1993b). In terms of relationships between the wetlands, Lakes Bryde, Towerinning and Coyrecup can be viewed as being positionedalong a temporal gradient of secondarysalinisation with Lake Bryde still relatively fresh, Lake Towednning mildly salinised and Coyrecup showing effects of long-term (40 f years) salinisation.Lakes Logue and Wheatfield have similar salinity to Towerinning but more complex submerged and ripadan vegetation,respectively,and are displaced from the gmdient. Their salinity levels mostly reflect naturalprocesse.:an historicalmarineconnectionat Wheatlield and evapo-concentration at Logue. Sampling in each wetland was stratified,with two widely separatedarcasbeing sampled(called sectors) and two random samplesbeing collected within each sector. The aim was to obtain measurcsof withinsectorand between-sectorvariation.Each samplecon'benthic' sistedof and 'planktonic' sub-samples.The benthic sub-samplewas collected by 50 m of vigorous, discontinuoussweepingover a distancaof about 200 m with a 250 pm mesh pond net on a D-shaped frame (350 mm wide and 250 mm high). All identiflable wetland habitats 51 m deep between the shore and centueof the wetland were sampled, including water column, submergedvegetation, bottom sediments, along submergedlogs and around tree trunks. Contentsof the pond net were emptied into a bucket severaltimes dudlg sampling to reduceresistanceof the net in the water. After elutriation and removal of large debris, the sub-samplewas preserved in 707o ethanol. The planktonic sub-samplewas collected by 50 m of more gentle sweeping with a 50 g.m mesh 398 l) in October 1997. long term saliniry pauern. Zrble /. Flooding ffequenc),,waier deprb (m) and co.dnctivily (tS crn domirlnr vegclationand \\,etlandsize (hr) at the five well.rndssampled Flooding October October Srlinity Vegetation salinitv Finging lrces (,44?l.r/cr./.?r 1,100 Brydc spp/eucalypts) Towefinning PermaneDl 3.2 Vegetationmostly cleared.a few r80 dcad ol livc lrccs ca. 2 Whe.rtiiekl Permancnl Loguc Scasonal Coyrccup S c m i p e r m a n e n t 0.9 Brackish 6700 Densefringing M?ldlPr.rr Frcsh-brackish 7300 F tirEine Cdsudina obesd, 150 caDegmsson lakebed pond oet on the same-sized tiame in the sarnchabitats, other than benthos, and was prescrvedin I 2ol' fomaldehyde. In the laboratory, benthic samples were sieved through a stackof 2 mm, 500 7rm,250 pm and 90 pm meshsievesandthe pofiionretainedin eachsicvewas sofiedundera dissectingmicroscope. Planktonicsamples were sievedthrough250 prm,90 pm and 53 irm mesh sieves.All animalswere sortedand identified to the lowestlevelpossible.This was usuallyspeciesor morphospecies and, lbr convenicnce, we usethe term specieswhen rcferring to the numberof taxa identiiied in a wetland.We also usethe terms microinvertebrates and macroinvertebrates to brcak iDvertebrates into two groupsbasedlooselyon size.Wc dcfinenicroinvertebratesas speciesbelonging to the Protista,Rotifera, Cladocera,Ostracodaand Copepodaand we refer to all other invertebratesas macroinvertebfates, although nany of them are quite small (e.g. sone speciesof Nematoda,AcarinaandChilonomidae). Analysis Numbers ol invcrtebratespeciescollectcd in samples flom difTerentwetlandswere comparedby 1-way ANOVA using PROC ANOVA in the SAS analysis package(SAS lnstitute1990),aftcrchcckingthatdata werc normally distributedand homoscedastic. Number of samplesrequiredto be 907osureof detecting 20Voor 30Vodeclinein speciesrichnessin a wetland was estimatedby the method of Snedecor& Cochran ( 1 9 8 0 p, p . 1 0 2 1 0 6 ) u , s i n gc v: 0 . 0 5a n dF - 0 . 1 0 . The averagepropol'tionol'species recovcredby singlcsamples,two samplesfrom the samesecto.of a wetland and two san]plesfron different sectol'swas Fringnrg dead trees (salt-affected) comparedwith the tolal number of speciesprescnt in the wetland,asestimatedby the formula of Karakassis (r995) S t, 1 - a l5r rnJ 5q -.//l b. where S"" is the theoreticallimit of the asymptote o l t h e s p e ri e . J ( c u m u l i r l i , ' ,n.u r r e . i . i r t h e m e a n numberof speciesin all possiblecombinationsof k ' i r m p l e su. n dp . r n db d e h n et h er e p r e . r i o lni n eo l j , r on 51. The formulaof Kay et al. (1999),in slightlymodified form, was usedto derivespeciesaccumulation curves ai - ai | \,44/17-3)) where zr; is the mean number of additional taxa col lected in the lth replicate,and 4l and 44 are the mean numberof additionaltaxa collectedin the third and fourth replicates,rcspectively.For samplesof all in vertebratesliom Coyrecup. d2 and1,4 were used to provide an estimateof the rate of changeot'the species accumulationculve because,owing to chanccd3 : a4,which prevented 4i reltchingan asymptote(generai caseis thata; > a;11). Similarity of invertebratesamplesfrom within and betweenwetlandswas examinedby ordination.This was done to test whether changeslikely to occur within one wetland over time, as a result of human activity, could be detectedreliably by single samples. ln a formal monitoring program,the ordination would 'marker' wetcontain invertebratedata fiom several lands,typical of the rangeof wetlandsin the region, and a tempoml se es ofsamples from the wetland be ing monitored.The markcr wctlands,sampledprior 399 to the commencementof monitoring, provide a stan dardisedframeworkforintelpreting the magnitudeand direction of changesin invertebratebiodiversity at the monitored wetland. Ordination was based on semi-strong-hybrid multi dimensionalscaling in the PATN analysispackage (Belbin, 1993)with presence/absence invertebrate data and the Czekanowskidissimiladty measure.Dissimilarity values >0.95 were re-calculatedusjng the shortestpath option (Belbin, 1993).F-ratios,calculatedby ANOSIM (Clark & Green,1988),were used as a measureof within-wetland vadation relative to separationbetween wetlands. lnfomation about the overall invertebratecommunity of each wetland available from micro- or macroinvertebratesalone was examinedby comparing ordinationsbased on microor macroinvertebmteswith thosebasedon all invertebmtes. Ability of two samples from diff'erent sectorsto charactedsethe overall invertebratecommunity of a wetland was examined using four 'paired' samples, which wele derived by combining all possible pairs of samplesfrom the two different wetland sectors.In addition, all four samplesfrom a wetland were combined to provide a 'composite' species list for the wetland. Paired and composite samples were used, together with simulated samples,in two ordinations. The first examined effect of speciestumover on position of samplesin ordinationspaceand included 20 modified samples, derived by replacing approxi mately f 0%, 20Eo, 30Eoand 40dloof the speciesin compositesamplesof eachwetland with speciesfrom the other four wetlands. Replacementswere random, within the constmint that only biologically realistic changeswere allowed. Ubiquitous speciesknown to have wide ecological toleranceswere rarely replaced and speciesthat occuffed in only one or two samples from a wetland were more likely than those in four all samples(although some four-samplespecieswere replaced,especially in the 307oand 4070 steps). Replacementsmadeat the l07o stepwere carriedinto the 204/ostep, unless they were randomly selectedto be rcplaced,etc. The secondordination examinedeffect of species Ioss on position of samplesin ordination space and included 15 modified samples, derived by removing 10Ea,20Eoand 307c of speciesfrom composite samples, using the samemethodologyasfor replacements. (")roo --r- Bryde 80 960 9ao I 20 (b) 70 -'r- Bryde 60 .E t0 220 t0 0 l 3 5 7 9 l l l l 1 5 No. of sMples G) 60 50 d20 z IO 0 1 3 5 7 9 1 1 1 31 5 No.olsanples Frgrre 4. Species accumulation al cach welland with increasing number of samples. (a) all aquatic inveflebrates.(b) macfoinveF tebrates,(c) microinvef ebrates. Results At least 150 aquatic invertebrate species were collected from the live wetlands,with Lake Bryde yielding most species(87) and Coyrecup fewest (20) (Table 2, Appendix). The proportionof microinverte bratesvariedfron 487oinBryde to 31Voin Wheatfield. At order level, differencesin proportion of Cladocera among wetlandswere especiallypronounced(237aof speciesir Bryde, < 27oin Wheatfield). Mean numbersofspeciescollectedper invertebmte sample differed significantly between wetlands (Ta ble 3), and therewas a significantnegativerelationship betweenspeciesrichnessand salinity(Figure2), confirming that speciesrichnesswill changeif the salinity of a wetland changessubstantiallyover time (seealso 400 Table 2. Nnmber of inveftebrate species of various taxonomic gmups in the live wetlands Bryde 0 t t l 6 0 3 0 2 0 11 5 l 0 2 ' 7 Hydrozoa Turbellaria Nematoda Tardigrada Rotiiem Mollusca Oligochaeta Cladocela Ostracoda Copepoda Amphipoda Isopoda Other Crustacea Coleoptem Ceratopogonidae Chironomidae Other Diptera Hemiptera Odonata Trichoptera Microinve(ebrates Macroinvertebrates Total no. of species 2 1 4 3 3 2 42 45 87 Towerinning 0 t t 0 0 0 3 1 3 8 6 1 0 0 5 Wheatfleld CoFecup I 0 0 I I I I I I 0 4 0 0 0 0 I 0 2 6 3 I l 2 3 I 7 2 I 0 0 3 3 4 3 4 I 0 lt 22 33 I I 8 4 5 6 4 3 1 3 t'7 33 50 Logue I 9 4 3 3 4 20 I I I 4 3 I t 0 2 I 2 0 0 0 9 11 20 Table 3. Mean + SE numbem of micro-, macrc- and all invertebrate species collected in four samples and esfimated number of samples (N*) needed to delect a 2070 decline in species dchness with 90% confidence. Numbers of micro-, maclo- and all invertebratesdiffercd significantly betweenwetlands(F: ? 1.1,F:38.3, F:51.1, respectively, p < 0.0001). Means with differcnt letters were significantly diferent (r < 0.05) Wetland Bryde Towerinning Wheatfield Logue Coyrecup Microinvertebrates Macroinvertebrates Allspecies Mean V.rn V.an ll' 56.2+1.1 A 3t.2t3.4C 42.2+2.9 B 23.0+2.0 D 15.5+0.6 E 2 21 9 15 4 N' 26.8+0.5 A 2 12.2+1.4 B 23 14.0+1.3 B 16 8.2+0.6 C 11 7.2*0.2 C 3 lv+ 29.5+0.9 A 3 1 9 . 0 + 2 . 1 B2 3 28.2+1.7 A 7 14.8t1.5 B t9 8.2+0.6 C 11 401 lirblr f. Estinated number of samples (N.) before an ad ditional sanple collected < I extfa species. the estimated numbers of speciespresent in each wetland using formulae o f K a y e t a l . ( 1 9 9 9 )a n d K a r a k a s s i (s1 9 9 5 ) ,a n d t h e n u m b e r o[ speciescol]ecledin lbur samples N+ Speciesestimated K")*r Bryde Towcinning Whealiield Logue Coyrecup 8 9 l0 6 5 9 9 6 3 78 3 8 2 3 "!{-"k"r*' 91 58 75 36 23 Speciescollected in four samples 87 50 20 Timms I98l , 1998). Using ANOVA, the estimated number of samplesneededto be 907i, sure of detecthg a 20c/adecreasein speciesrichness at individual wetlandsvaried from 2 at Bryde to 21 at Towerinning (Table 3). Variation in these estimates reflects stochasticelror in estimatesof variancebecauseof small samplesizesin our studyand about10 sampleswould probablyproducethe statisticalpower requiredat most wetlands. Estimated number of samples needed to detecta 30% reduction varied from 2 10. Diflerences betweeDwetlands were less clear cut when micro or macroinvertebratesalone were examined; for example Wheatfield was similar to Bryde in terms of macroinvertebraterichness but more like Towerinning in number of microinvertebrates(Table 3). There was a tendencyfor fewer samplesto be neededto detect a 20olodecline in microinvertebrate than macroinvertebraterichness,althoughthe opposite applied at Wheatfield (Table3). Estimatesol speciesrichnessin each wetland suggesteda single sampleusually collects about 60% of speciespresent at the time of sampling (range 4381c/o),two samplesfrom different sectors15Vo, and four samples897o(Table4, Figule 3). Between-sector variation in speciescomposition was usually greater than within-sector variation so that, except at Coyrecup where there was no difference, about 77, more taxa werr collected by two samples from different sectors than by two fiom the same sector Depending on wetland, 6-10 sampleswere requircdto collect all speciespresent(Figure 4a). Rate of accumulation of microinveftebrateswas greater than nacroinveflebmtes and fewer samples were neededto collect all micronve(ebratespecies(Figures4b and 4c). All samplescontainedsufficientinformation about the inyertebratecommunity of their source wetland to separatethem in oldination space frorn samples collectedin the other wetlands(Figures5a and 5b). Furthemore, all samplesfrom a wetland were close in ordination spaceto the composite sample for that wetland and, thus, probably containedmost of the information signal of the full invertebratecommunity. While theseresults are, at least partly, a consequence of the ordination containing wetlands with very different comnLrnity composition(the spreadof samples from the samewetland would be greaterand betweenwetland separationless clear if all wetlandshad similar communities), it strongly implies that ordinating a temporal series of single samples from a wetland within a framework ofmarker wetlandswill detectany substantialecologicalchangesthat have occulTed. Relative positions of samplesfrom different wetIands changedsomewhatin ordinationsbasedon microiDvertebrates or macroinvertebrates alone, with the microinvefiebmtepattem being more similar to that of l h ew h o l ei n r e r l e b r i i l e c o m m u nl iht a l nl o m t c r o i n ! e r tebrates(Figures 5c e). Samplesfrom the same wetland were usually closest to each other in ordination space,relatiyeto the distancebetweenwetlands,in the microinvertebrateordination, which was reflected by the highest F-ratjo from ANOSIM analysis(al1invertebrates,F : 3.301,macroinvertebrates, F:2.393, microinvertebmtes, F : 4.109, compositesamples excluded). Pairedsamplesfiom different secto$ of a wetland were closer in ordination space to both each other and compositesamplesthan were single samples(Figures 5a, 5b and 6). Paired samplesalso showedbetter discdminationbetweenwetlands(F : 5.586vs 3.301, compositesamplesexcluded).Thus, a pair of samples from different sectorsprovided more preciseinformation about the invertebratefauna of a wetland than a single sampleand enablefiner-scaledifferentiation of ecologicalcharacter. Ordination of modilled sample data, representing different levels of speciesturnover and loss at the five wetlands.showedspeciestumovercausedlargel shifts in ordination spacethan speciesloss (Figure 7). Shifis in sample position causedby turnover of - 207o in community composition were about twice the variation exhibited by paired samplesat all live wetlands (Figures 7a and 7b) and suggestedthat changes of 7 20Votn community con.rpositionwould be reliably detectedby ordination of a temporal seriesof paired samplesfrom a wetland(p < 0.2). 402 (b) (a) All tara 1.5 s* oo o trtr o t A^ o o oa c tla I o ao .F o .3# ls.. o o to 0 Ais 1 0 Aris I (d) (c) Mrcroinvertebrates 1.5 EF trtr 1.5 A A o 6 0 ^ . o otr F o o o o o o ; -1.5 o o o o . 0 Attu I (e, Microinv€debrates 1.5 t ' a t oa 0 Arb I (D 1.5 4A a a aa .o odAo t a a og o- - Etrs Etr- o o $ -1.5 ri"r o 1.5 -l.5 0 Aris I 1.5 Fr€rrs t Three-dimensionalordination of samplesfrom five wetlands. 0 Bryde, O Towerinning. a Wheatfield, tr Logue, A Coyrecup- (a, b) All invetebrate data, with composite samples(closedsymbol or arrowed). stress: 0.11; (c, d) macroinvertebratedata, stress: 0. i3; (e. 1) microinvertebratedata. stress: 0.06. 403 (a, Paired samples (b) 1.5 l.s aru t -1.5 s s 0 Arir I s , " & i a p 1.5 0 Atis I 1 f Fr,qr,"e6. Three dimensional odinalion of paired and composite (closed symbol or anowed) samples ftom each wetland. 0 Bryde, Towerinning, O Wheatlield, I Logue, A Coyrecup,stress: 0.09. Discussion Fofiy-five percent of species collected dudng this study were microinvertebrates,which is similar to proportions recorded in other studies and reinforces that microinvertebratesform a major component of wetland biodiversity (Dole-Olivier et al., 20001Halse et al., 2000b).The pattemsof micro- and macroinvertebratebiodiversity in the five wetlands differed (Table 3, Figure 5) and it was clear that monitodng based on one group alone would have been misleading in termsof overall invertebmtebiodiversity.Despitethis, most studies of wetland ecology and aquatic inyertebrate biodiversity sample only macroinvertebrates (Resh& McElravy, 1993). The estimateof 6 10 samplesto collect all species in the live wetlands (Table 4) was similar to the 4 6 samplesneededat Toolibin and Walbyring Lakes in south-westemAustralia using similar sampling methods (Halse et al.; 2000a). Four factors contributedto speciesaccumulating faster in these studies than in most others reported in the literature (e.g. Rouch & Danielopol, 1997; Butcher, 1999): (l) sweep sampling, which collects species more efnciendy than most techniques(Cheal et al., 1993; Tumer & Texler, 1997),(2) large effort per sample,(3) employing both small and intemediate mesh sizes to increaselikelihood of collecting micro- and macroinvertebrates, respectively,and (4) sampling a range of microhabitats.Sweepsamplesof micro- andmacroinvertebrates, collected over large areasand inporporatingas many microhabitatsas possible,yield more information on community composition than small samples at little extra cost. Our experiencehas shown that processing costsare more relatedto number and type of samples than volume of those samples. Despite recovedng speciesmore efficiently than most samplingprotocols (Rouch & Danielopol, 1997; Butcher, 1999), our single sweep samplescollected only about 60% of inveftebmte speciespresent in a wetland. Even when severalsampleswere taken,some patchily distdbuted or low-abundancespecies were missed. Yet, when documentingchangesin biodiver sity is the objective, these rare species may be of most intercst.We have no solution to this conundrum otherthan increasingsamplesize.We suggestthat taking paired samples,which on averagecollect 7570 of speciespresent,representsa reasonabletmde-off between cost and completenessof the species list but speciesaccumulationcurvescan be used to detemine the number of samplesrequiredfor a higher recovery rate (Moreno & Halffter, 2000). This study confirmed that large numbers of samples are usually required to demonstratechangesin speciesdchnessat a wetland, unlessexpectedchanges are large (about 10 samplesper wetland sampling occasion were neededto detect20Eodecline in species richnessand five to detect 30% decline). Examining change in speciescomposition using ordination is a more efficient way of detectingchangesin biodiversity (Gray et al., 1990; Warwick, 1993), particularly becausethe first changesin invertebratebiodivenity at wetlands subject to environmentalchangeusually in- 104 (a) Speciestumover 1 5 (b) 1.5 * &f.ts Y- f e t /t *E$ \r a \ q=.J I""t 0 Aris I 0 Ans I (dl (c) Speciesloss 15 1.5 a^ dg # 4 f $a a tr *f - 15 0 Aiis I $ r a -t 5 0 Ads 1 tlgrf" Z Three-dimensionalordination ofpaired samplcsliom cach wctland. 0 Bryde, (,iTowerinning, a Wheatfield. !Logue, A Coyfecup. (a. b) cffcct of 10 407. specieslumover oD position of composite sample (composite and sil11ulared sanples shown by closed symbots and connectedby lilre), stress= 0 I l , (c. d ) etrect of 10 30./. speciesloss on position of conposite saDple, stress= 0. 10. volve speciesreplacementratherthanreducedrichness (Grownset al., 1992). Streever(1998)showedsignificantpatternamong the invertebratecommunitiesol'difltrent sitesby ordinatingcombineddatafrom two smallcoresamplesper site, althoughpattems becamemore stableas number of samplesincrcased.Halse et al. (2000a)showedthat single large samplescould distinguishbetweendifferent types of wetland. This study conlirmed earlier results: ordination of data from large paired samples producedstablepatternsand characteisedthe wetland communityfrom which they were taken(Figure6). Ordination of modilied sample data, simulating t l p e ' o l ' i h r n g e l i k e l ) t o o c c u ro v e r l i m c a r a r e sult of anthropogenicchange, suggested> 207. speciesturnovercould be detectedreliabiy (Figures7a and 7b). The relativeinsensitivityof ordinationsto changesin speciesrichnessitself, which is characteristic of multivariate techniques(Clarke et al., 1996), i r b e n e f i c i ailn a l o n g t e r m m o n i r o r i n gf r o g r a m i n that small variations in sampling effofi over time (or amongoperators)have minimal effectson results. We have not tested the discdminatory power of paired-samplernonitoring in a lbrmal way because visual assessmentof effect size can be an ellective method of evalLration(see Anderson et al.. 2000). More figorous testing could be achieved by visual assessmentof simulated data from a larger number of wetlands or by ANOVA of dissimilarity measures (seeEdwardet al., 2001).However,the magnitudeof 405 changesthat are biologically significant is yet to be determinedand this should precedethe development of formal statisticaltests. The proposedmonitoring protocol is not intended to detectdisturbance-induced changesthat are smaller than the natural fluctuations between most years. These can only be detected using complex designs and, even then, are dilficult to demonstrate (Underwood, 1993). However, in stuongly seasonaland semi-aridclimates,suchas occur in much ofAustralia (Gentilli, 1972), drought and flood eventsmay cause much largerchargesin community composition,at interyals of a decadeor so, than are likely to be caused by anthropogenicfactors (Halse et al., 1998; Timms, 1998).Unusualnaturaleventscomplicatethe monitor ing of trends in wetland biodiversity and we suggest that the most appropdateaction is to exclude extreme years(asdefinedby water levelsor other crite a) from analysis,althoughin somesituationschangein the fre quencyof extleme events,and the occurrenceof their associatedinvertebratecommunities, will be important. Exclusion of years with extreme eventsreduces both the likelihood of Type I error (false evidenceof anthropogenicchange) and the cost of achieving an acceptablelevel of Type II error. Acknowledgements We thark WR. Kay and J.M. McRae for help in the field. A.W. Storey, PG. 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OLIGOCHAETA Ainudri Ius nharna Pinder&Bink\urst Tubificidae Derc dieitata (Mnller) Paranaislitoralis (Mnller\ Enchytraeidae ARTHROPDA ACARIFORMES Hydrachnidae Eylaissp. Halacaridae Oribatida Mesostigmata ANOSTRACA Branchinelh lyrtfera Lndet CONCHOSTRACA Caenesthzriasp.no\. A (nr lutraria) CLADOCERA Alona diaphanaKjng Alona rectangulanovaezealandiae Sars Alona didphlttutyermiculdtdSmiNov&Timms Alora sp.nov.A (Bryde) Alona cf. crassicauda Biape|tars rigid :audis s.l. S'J.ffn'o.' Biapertura cf. IonSiquaSfiirno'r' Leldigia cf. ciliata Garrllier Monospilusdiporus Smimov & Timms MonospiluselongatusSmirnov& Timms I t I I 5 2 4 408 Continued wetland t 3 5 Plurispina cf. chauLiodi.sFrey I Pleuroxuscf.foveatwFrcy I Rdt sp. nov. B (Venemores) I Ceriodaphnia laticaudata MJ€ller 2 4 I I Dophni.l cephalataKjrg I Daphnio carinata s.I. King 1 I I 1 Daphniopsis pusi a Serrenty I Daphniopsi.s quee sla densis Sergee.' I Simocephalus exspinosus De Grcer I SimocephalusvitoriensirSmimov&Timms 1 Macrcthri:c brerilet r Sfiirnov I Neothrix cf. drmata G\fiiey I I OSTRACODA Limnocytherc mowbmyeruis Chapnan Clpridei; australieuis I HatuIF' t IlJocypris australiensis Sars I I I lllocl,pr'i.r sp. nov. A I Alboa v,orooa De Deckker Australocypris insalaris (Chapman) I I I Bennelongia austmlis Br^dy) I Candonocypris notaezehndiae (Baid) I C)prctta bqlyi McKettzie I I I CJpinotus edwardiMcKenzie 1 Diacrpri.s spinosaDeDeckker I Eucyprb vircns JuJine I Heterccypris wtia De Deckker I M)tilpcypris ambiguosaDeDeckker I Mjtilocypris tastnanica chapmaniMcKenzle I Ilrodrcmus cf. canlonite.r De Deckker 1 Cwericercus sp.442 I I I 1 1 I 1 Retiq,pris clavaDeDecl.ker I I Cabonoctpris nunkeri De De.kket 1 Platycypris baueriHerbst Sarscypridopsis acaleata (Costa) I 1 1 1 laptocythere hcustris DeDeckker 1 Kennethia cristataDeDeckker I 1 COPEPODA Boecke a triarticulata (Thomson) Cala/noecia anpulla (Searle) I I I 1 1 Calamoeciaclite ataBayly I Gladioferens inparipe s Tt\onson Metacycbps sp.462 I I Metactclaps amaudi (sensn SaJs) Austrulocyclops australis (Sars\ I I Halicyclnps cf. anbiguus Kefet Mesocyclops brool<siDe Laurentiis et al. 1 I t I 409 Continued Wetland t 3 5 E ucyclops australiens is Mofion Ap ocycI op s den8 i.i us (Lepecbkine) Mesochru baylj,i Hamond Mesochm ?favaLang I Cletocamp tus deirersi (Rjchal.d) I OqJchocamptus benealensir (Sewell) I Schizopera cLlndestiw (Klie) I AMPHIPODA Austrochiltonia subtenuis (Sayce) ISOPODA Haloniscus sea ei (Chlhon) DECAPODA Palaemo etcs auitrali.s Dakln IIEMIPTERA Sallula nt brevicornis Rimes Saldidae A g rcp tocor ixa p arv ip unctata (I{nle) A grapto cori:ca hift ifaons (Ela1e) Mic mnecto robustlt HaIe Micronecta gruciis Hale Anisops gratus H^le Ani.sops occipitalis Brcddin Anisops sp. ODONATA Austrole stesannulos us (Sely s) I I Hemiandx pap ensis (Bulmeisrer\ I I Hemicordulia tau Selys I I TRICHOPTERA Notalina spira SLClair I Oecetis sp. I Synp h ito new ia wheeI eI i B ar,ks I Tr ip I ect i des aust ralis N avas I Leptoceridae sp. DIPIERA Tipulidae group C Anopheler annulipes Walker Culicoides sp. A. I I Nilobezzia sp. A I Nilobezzia sp.B Ceratopogonialae sp. A ,t Ceratopogonidae sp. B Psvchodidae I I Stratiomyidae I I I I Dolichopodidae i I ' 2 4 410 Continued Wedand r 3 5 Ephydridae ProcladiuspatuAcoh Skise Procladius ))illosimanusKi effer Ablabesmyianotabilis Sklse Pammerina leyiAensis (Skvse) CricotoplLsalbitarsusWalker Paralimnophyespullulus (Sk]dse\ ' Onhocladiinaesp.A %n],tdruarsp.A (nr Kto sensuCranston) Chiro o/nusoccidentalisSktse Chircnomlts tepperi Sk'rse Chironomuscf. alternansWalker D icrctendipespseltdoconjunctusEpler Dbrotendipessp.A PolJpedihonn bifer (Sk[se) Pollpedilum converum I ohannsen Cryptochi ronomusI risei dorsum Ki,eff er Ckldopelmacurtiwba Kieffer Parachironomussp.A COLEOPTERA A odessusbi.striIdtus(Cla*) AntiporusBilberti (Clark) Stemopriscusmuhimaculats (Claft) Necterosona penicillatus (Clark, Rftartr.r rutu,'alis wS Macleay I^cncetes Ianceolat6 (Clark\ Bens us discolor Blackbnm . Bemsusnunitipemis Blackb]'m Beross sp, Hydrophilidae Ochthebiussp. Heteroceridae Curculionidae 2 4
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