WE WANT

Memoirs ofthe Museum ofVictoria 56(2):483-490 (1997)

PREDICTING SPECIES RICHNESS FORAUSTRALASIAN FRESHWATER MACROINVERTEBRATES: DOWE WANT TO KNOW?

J.E. Growns¹ and I.O. Growns

AustralianWaterTechnologies, PO Box 73, WestRyde, NSW 2114, Australia

lPresentaddress: Murray-Darling Freshwater ResearchCentre, POBox 921, Albury, NSW2640, Australia

Abstract

Growns,J.E. and Growns, I.O., 1997. Predicting species richness forAustralasian fresh- watermacroinvertebrates:dowewanttoknow?MemoirsoftheMuseumol Victoria56(2):

483-490.

Theidentificationof freshwatermacroinvertebratesto familylevelisbecomingincreas- inglypopularfor surveys, predictivemodels andpollution indicesinAustraliabecauseit is

quickerandcheaper than genusor specieslevelidentification,anditrequireslessspecialised knowledge.Familyrichnesshas beenusedasa predictorofspeciesrichness for other taxo- nomicgroups suchas vertebrates, antsandplantsandwewereinterestedinseeingwhether this might be a useful method for freshwater macroinvertebrates. Taxon lists from one PapuaNewGuinean and34Australian datasetsfrom lenticandloticwaterswere usedto regressthe numberoffamilies againstthetotal number oftaxa (specieswhere possible).

Also, theabilityofthenumberofspeciesand morphospecieswithin someorders(Coleop- tera, Diptera, Ephemeroptera and Trichoptera) to predict overall species richness was investigated.The numberofallfamiliesexplained 91%ofthe variationinspeciesrichness.

The numberofspecies within each ofthe orders explained between 60 and 85% of the variationinoverallspecies richness.We^{concludethatitwouldbe}possible to predict species richnessin thisway,particularlyifsampling techniquesandsamplingeffortwerestandard- ised.Theterms'species richness'and'biodiversity'are oftenusedsynonymouslyalthough theformerisonly a subsetofthelatter. Someofthe limitationsand dangers ofassessing species richness insteadofbiodiversity are discussed.

Introduction

Mostfreshwaterstudiesaddressingbiodiversity haveassumedthat biodiversityandspeciesrich- nessaresynonymous^(e.g.,Langand Raymond, 1993; Allanand Flecker, 1993; but seeCollier, 1993). Species richness is very expensive to determine using traditional methods and tax-

onomy. Rapid^{BiologicalAssessment}(RBA)has been developed ^{inordertoover}comethesedif- ficulties. RBA ^{isbasedoneithertheuse ofmor-}

phospecies ratherthan formally named species (basic RBA) oron identifying either subsets of communities or only identifying to taxonomic

levelshigher than species (ordinalRBA: Beattie et al., 1993). Wepresent an evaluation ofhow

effective ordinal RBA ^{is likely to be for fresh-}

water invertebrate communities.

Ordinal RBAassumesthathigher-taxonrich- ness or thenumber^{ofspeciesintaxonomicsub-}

setsare closely related to overall species richness but this has rarely been tested. Williams and Gaston (1994) used family richness to predict species richnessofBritish ferns, British butter-

flies, Australian passerine birdsand North and CentralAmericanbats.Theyfoundthat foreach of these groups of organisms, family ^richness explainedat least 79%of the^variationinspecies

richnessandconcludedthat 'with carefulchoice of higher-taxon rank, it may be possible to re- deploy effort from taxonomically intensive to taxonomically extensive surveys'. Andersen (1995) used a similar approach to estimate speciesrichnessof Australian antsusinggeneric diversity.

We obtained taxon lists from 34 datasets throughoutAustraliaand one from PapuaNew

Guinea and used familyrichness for the whole community andthe numbersofmorphospecies within four orders (Coleoptera, Diptera, Ephemeroptera and Trichoptera) as predictors ofcommunity species richness.

Methods

The number offamilies, total number of taxa and the numbers of coleopteran, ephemerop- teran, trichopteran and dipteran taxa were determined for 34 taxon lists from surveys throughout Australia and 1 from Papua New Guinea (Table 1). The Australian studies were fromall states and one^territory: Western Aus-

tralia, 10; New ^{South Wales,} 9; Victoria, 5;

Queensland, 3; Northern Territory, 3, South Australia, 2, Tasmania, 2. The types offresh- water systemwerealsovery varied andeightof

483

https://doi.org/10.24199/j.mmv.1997.56.42 28 February 1997

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486 J.E.GROWNS AND ^I.O.CROWNS

the studies had at least some sites that were polluted (Table 1).

The total number oftaxa for each studywas taken as the number of recognised taxonomic units(RTUs)forthat study, e.g., wherechiron-

omid larvae were not identified beyond family, this was counted as one RTU. Immature and unidentified taxa werenot included unlessthey were the only RTU in that family or genus.

Coleopteran adultsand larvaewere considered to be different RTU's unless they were both identified to the same published species name.

Whereidentificationwasnottaken eventofam-

ilylevel,eachgroup wastakenasoneRTU,^e.g.,

Hydracarina.

Plotsofthenumbersoftotal taxa against the

numbersoffamiliesand coleopteran, dipteran, ephemeropteran and trichopteran taxa were examinedfor outliers. The state in which each study occurredwas superimposed on the plotof numbers of families, in order to look for any regional variation.

Linear regression was used to examine the relationshipsbetweenthetotalnumbersoftaxa andthenumbersoffamiliesandthenumbersof coleopteran,ephemeropteran, trichopteranand dipteran taxa. All data were log| (x+l) trans-

formed and residuals were examined for nor- mality using NormalScores plots.

Totest the predictive valueofthe regression ofnumber offamilies versus total numbers of taxa,dataonnumbersoffamiliesandspeciesfor single sites were used from Marchant et al.

(1995). The data from thelowerLa Trobe and Thomson Riversandtheupper La TrobeRiver werenotusedfor thistestastheyhadbeen used

in the calculation of the regression equation.

Percentage error in prediction ofspecies rich- nesswascalculatedbysubtractingthenumberof predicted species from the actual number of species,so that anegativeerrormeansthatmore

species were predicted than were actually recorded. Percentage errorwas plotted against

number offamilies to identify any systematic errors.

Results

Allregressionswerehighlysignificant.Thenum- beroffamiliesexplained91%ofthe variationin thenumberoftotaltaxa(Table 2).The number of taxa from the taxonomic sub-groups were poorerpredictorsoftotalnumbersoftaxawith thenumbersof coleopterantaxa giving the best result(Table2).

For most states, not enough datasets were availabletoassess regional variation. However, the plot suggested that, for the datasets avail- able, lotic systems in south-west Western Aus- traliahadlowspecies richness,whereasthosein

NSWhadconsistently high species richness(Fig.

1). There was no evidence that the different states showed different relationships between species and family richness, i.e. the intercepts and slopes ofthe linesfor each state appeared very similar(Table 2).

The plot oftotal number oftaxa against the

number of coleopteran taxa (Fig. 2a) showed thatCarey Brook_{(study 21)}andthe Serpentine River(14)had lower proportions ofbeetletaxa than would have been expected and the Collie River₍₃₁₎ hada higher proportion thanwould

Table2. Regression resultsofpredictions oftotal numbersoftaxausing log(x- data.

1)transformed

Independent variable

Numberoffamilies:

All datasets

NSW

VIC

WA

Numberof coleopteran taxa

Numberofdipteran taxa

Numberoftrichopteran taxa

Numberofephemeropteran taxa

Intercept Slope r¹

35 -0.488 _{1.530 0.91}

9 -0.730 1.671 0.98

6 0.062 1.298 0.80

10 -0.046 _{1.260 0.83}

35 1.174 0.713 0.85

35 0.981 0.732 0.70

35 1.356 0.606 0.68

35 1.573 0.632 0.60

PREDICTINGSPECIESRICHNESS 487

Tasmania o Northern Territory

(J Victoria Queensland

* SouthAustralia NewSouthWales

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Numberof families

90 ¹OO 11O

Figure 1. Plotoftotalnumberoftaxa againstnumber offamiliesforthe 35studies. Thestate in whichthe studywasdoneisoverlaid.

have been expected. All these 3 areas are in south-westWesternAustralia.The same^plotfor dipteran taxa (Figure 2b) showed that Carey Brook hadahighproportion of Diptera whereas the Werribee (study 2) and Lerderderg rivers (study 3), which are both ephemeral rivers in Victoria, had low proportions of dipteran

larvae. This plot also showed a marked differ- enceinthe proportions of Dipterabetween ^the Williams River(study7)andthe RiverMurray andtributaries(study1),althoughtheybothhad similar total numbers of taxa. The plot for

Ephemeroptera (Figure 2c) indicated that the River Murray and tributaries, the Perth wet- lands (study 13) and theWerribee and Lerder- dergRivershadlownumberscomparedto their total numbers of taxa. The trichopteran plot (Figure 2d) indicated that theRiverMurray and

tributaries had low numbersof caddis whereas the Werribee and Lerderderg Rivers had high

numbers compared to their total numbers of taxa.

The^predictionofspecies richnessfromfamily richnessfor19singlesites(datafrom Marchant

et al., 1995) gave^amean errorof—7.7%(stan- darderror,2.5)withamaximumerrorof—_31%.

Theplotof percenterroragainstnumberof fam-

iliesshowed that roughly halfofthe siteswere predicted to within 10% ofthe actual species richness(Fig. 3). Also, 14out ofthe 19 predic- tions were for more species than actually occurred.

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488 J.E. GROWNSAND I.O. GROWNS

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Figure3. Plotof percentageerrorinprediction ofspecies richness againstnumberoffamilies forthe 19 single sitesfrom Marchant etal. (1995).

Discussion

The numberoffamilieswasa verygoodpredic- tor of community species richness (i.e., total

numberoftaxa) whereasthe taxon richness for the four orders were not such good predictors;

beetles werethe best ofthe four. This suggests that analysing whole communities to coarse taxonomic levels may be more reliable than specieslevel identification ofindicatorgroups,

ifestimates ofwhole community species rich- ness arewanted.

There was noevidencethat therewerediffer- ent relationships between numbers offamilies and community species richness in different regions ofAustralia. However, there was some evidence that lotic systems in NSW had very high species richness whereas lotic systems in south-west Western Australia had low species richness.Bunnand Davies(1990) suggestedthat the low species richnessof south-west Western Australianloticsystemsmaybedueto the area's isolation, historicalaridityand low primarypro- ductivity. Although low in numbers ofspecies formany groups, this area hasa very high pro- portion ofendemics among its flora and fauna, includingthe loticmacroinvertebrates(CSIRO, 1992; Christensen, 1992). In contrast, high levels ofspecies richness have previously been

observed for tabanid diptera and odonates, as well as forothercommunities,onthenorthcoast of NSW, which has been designated the Macpherson-Macleay overlap (CSIRO, 1991).

MacArthur (1972) observed that lotic invert- ebrates are the principal exception to the rule that the tropics have greater biodiversity then temperate areas. However, Lake et al. (1994) found that two Queensland creeks had signifi- cantly higher species richness than streams of similarstream ordersin Victoria. Ourdata did not show higher species richness for tropical areasbutthismaybeduetothesmallnumberof datasets fromthe tropics in this study.

Severalofthe species lists showedthatwhere communitiesarelow in speciesnumbersofone taxonomic group, they are high for another group. The intermittent Werribee and Lerder- derg Rivers in Victoria had low numbers of dipteran larvae and mayfly nymphs but high numbersof caddis flylarvae. Carey Brook,a in south-westWesternAustralia,had lownumbers ofbeetlesbut high numbersof dipteran larvae.

Thereare doubtlesshistorical and evolutionary reasonsforthese patternsbutitis interesting to notethat the overall relationshipbetweennum-

bersoffamiliesandcommunityspecies richness was the sameforthese areas as foralltheother studies.

PREDICTINGSPECIES RICHNESS ⁴⁸⁹

The predictions ofspecies richness forsingle siteswere not good. Onlyabout halfofthe pre- dictions for single sites fell within 10% ofthe actual species richnessand errors ofup to 31%

occurred. The majority of the predictions for single sites were forhigher numbersofspecies than actually occurred. This may in part be because Marchantet al. (1995) included ^oligo- chaetes, tricladsand mites assingle taxa. How-

ever, severalofthe 35 studiesused to calculate the regression equation alsodid this. Thecon- sistently high predicted ^species numbers are

more^likelytobe becausethe predictions are^for single siteswhereasthe regressionwasofstudies of multiple sites inanarea.Thelower sampling effort for the single sites would be expected to obtainalower proportion of^specieswithin each family compared to multiple site studies. For example,atmostsitesyou wouldbelikelytofind beetles from the family Dytiscidae. However, there are likely to be different species ofdytis- cidsatdifferentsites.Soasurvey ofseveralsites

wouldfind more^{speciesofdytiscidsthanasur-} vey of onlyonesite,whereasboth surveyswould record onlyonefamilyforthedifferentnumbers ofspecies. This highlights the care with which

this type of predictive technique must be used.

Ourresults should betreated withsome ^cau-

tion as thesamplingintensity,methods andtax-

onomyvariedamongstudiesandthegeographic distribution of the studies was uneven. How-

ever, we believe that we have shown that this

approach would ^behighly successful inpredict- ing the species richnessof freshwater macroin- vertebrates for an area. It might also show

interesting patterns, such as the apparent high levels ofspecies richness in northern NSW. In addition,ourobservation thatwhere one^group oforganisms in a community has low species richness, anothertaxonomic group^{in the} same communitymay^havehigh species richness, has interesting evolutionary implications.

However, we are concerned that the almost exclusivefocus on species richness ⁱⁿ biodiver- sityassessmentisunwarranted.Biodiversityisa difficult conceptto define as ^itcomprises many

different ideas,ofwhichspecies richness^isonly one. We ^{need to knowwhat} the species ^are: an assessment of^theirendemicity,^{rarity,suscepti-} bilityto extinctionanddistributioncan then be made,^{orat least attempted.It isalsoimportant} toknowwherethey^{fitinto their}community,i.e.

whetherthey ^areneededforthe continuingsur- vival of other organisms, and whetherthey are an example of a scientifically important

phenomenon, such as evolution (see Richard- son,thisvolume). It isobviously impossible ^for

all of this information to be obtained for all species,let aloneinthetime frames required by managersandlegislators.However,thisdoes not mean that species richnessalone should be used asa surrogateforbiodiversity. Scientistsneedto reach a consensuson what ^{aspectsofbiodiver-}

sityneedtobe consideredforconservation pur- poses and then communicate this to the wider community.

Acknowledgements

Thanks are due to LornaCharlton, Sam Lake, Richard PearsonandBelindaRobsonfortaking the time to provide species lists from unpub- lished data sets. Bruce Chessman made useful

comments on the manuscript. State Forests of

NSW, Hunter Water and^theHunter Catchment ManagementTrustaregratefully acknowledged

forallowing unpublished data ^tobe used.

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