Australian Joumal of Ecology (1995) 20, 324-334

The dietary overlap between red kangaroos (Macropus rufus)and sheep {Ovis aries) in the arid rangelands of Australia

G. P. EDWARDS,* T. J. DAWSON AND D. B. CROFTSchool of Biological Science, The University of New South Wales, PO Box 1,Kensington, NSW 2033, Australia

Abstract The interaction between red kangaroos and sheep in the more arid areas of Australiawas examined by means of a large-scale manipulative experiment. The diets of red kangaroosand sheep grazing together and separately in large paddocks were studied to assess whethercompetition for food might influence diet selection in these species. Diets and the amount ofintra- and interspecific dietary overlap varied in accordance with pasture conditions. At pasturebiomasses ranging from 50 to 200 g m"̂ (dry weight [wt]), the diets of red kangaroos and sheepoverlapped by 58-73%, with forbs and grasses being the major items in the diets of bothspecies. The diets of both sheep and red kangaroos under different experimental regimes weresimilar. In dry times (pasture biomass 40-50 g m ^ (dry wt) more shrubs were eaten by bothspecies and the amount of dietary overlap tended to be lower (52-66%). The diets of kangarooswere similar between paddocks. However, in paddocks containing both species sheep consumedproportionately more chenopodaceous shrubs and fewer grasses than those in 'kangaroo-free'paddocks.

Key words: dietary interaction, herbivore ecology, kangaroos, sheep.

INTRODUCTION

About 20 million sheep (Ovis aries; adult bodyweight60—80 kg) are grazed throughout the arid and semi-aridareas of southern Australia (Caughley 1987). In theseareas, which are collectively known as the sheep range-lands, four species of large kangaroo also occur. The redkangaroo (Macropus rufus; 30-90 kg) and the hill kangarooor euro (Macropus robustus; 17-60 kg) are ubiquitouswhereas the eastern grey kangaroo (Macropus giganteus;30-80 kg) and the westem grey kangaroo (Macropusfuliginosus; 30—80 kg) are most abundant in the less aridareas (see Caughley 1987 for distributions).

Sheep and the large kangaroos are all generalist herbi-vores of similar body size and their diets often overlapconsiderably (see reviews: Barker 1987; Dawson 1989;Edwards 1989). Like sheep, which are true ruminants,kangaroos utilize foregut fermentation to digest plantfibre (Hume 1982). Sheep and red kangaroos have similarfood intakes (60-65 gkg""" d a y ' (dry wt); Short 1985),similar bite rates (50-60 bites min"'; Short 1986) and arealike in their 'grazing efficiencies'; in 'graze-down' trialsboth are able to graze pasture plants down to similar

•Present address: Arid Zone Research Institute (CCNT), Wild-life Division, PO Box 1046, Alice Springs, NT 0871, Australia.

Accepted for publication August 1994.

heights (Short 1985). However, while there are manysimilarities, some niche parameters are different. Notably,sheep are able to crop food faster than kangaroos becausethey take larger bites (Short 1986).

Given that the ecological niches of sheep and the largekangaroos have several parameters in common, particu-larly in relation to diet, it is not surprising that there hasbeen concem from sheep pastoralists that 'competing'kangaroos affect their livelihood. The competition issueis also of interest to conservation groups worried aboutthe long-term survival of kangaroos, especially in aridareas with unpredictable rainfall. Only recently has thistopic been addressed through the use of manipulativefield experiments. In a study conducted in the semi-aridwoodlands of central-westem New South Wales, Wilson(1991) found that competition between westem greykangaroos and sheep lowered sheep productivity.

We have examined the competitive interaction betweenred kangaroos and sheep in the more arid areas ofAustralia by means of a large-scale manipulative experi-ment. During this investigation the diets of red kangaroosand sheep grazing together and separately in large pad-docks were studied to assess whether competition forfood might influence diet selection in these species.Previous studies have not been rigorous enough to answerthis question.

SHEEP-RED KANGAROO DIETARY INTERACTION 325

METHODS

Experimental design

The experiment was conducted at the University of NewSouth Wales Arid Zone Research Station at Fowlers Gapin northwestern New South Wales, Australia (31°05'S,141°43'E). Fowlers Gap covers 39 200 ha and is locatedin the sheep rangelands in an area of high red kangaroodensity (Caughley 1987). General details conceming theclimate, soils, geology, vegetation and fauna of the areaare given in Mabbutt (1973).

In selecting a site for this study two main objectiveshad to be met: the site had to be uniform in terms ofvegetation characteristics and large enough to accom-modate replicated experimental units of sufficient size toreflect the natural grazing conditions for red kangaroosand sheep in the arid rangelands. A site containing goodred kangaroo habitat located on the open plains in theeast of Fowlers Gap was chosen. The site was within oneland system, known as the Conservation land system,which lies between the main creek systems. The Con-servation land system is composed of a mosaic of landclass units with characteristic soil and vegetation. Thetopography is typically flat with some minor flood-outs(Milthorpe 1973). The vegetation includes drought-resistant perennial shrubs (bluebushes: Maireana spp.;saltbushes: Atriplex spp.; cottonbush: Maireana aphylla),peretmial grasses (e.g. Eragrostis, Enneapogon and Astreblaspp.), copperburrs (Sclerolaena spp.), ephemeral grassesand forbs (ephemeral dicots). Large trees are rare andthe common small tree ( < 3 m) is prickly wattle (Acaciavictoriae), which occurs mainly along the drainagechannels.

The study site covered 3718 ha and incorporated sixcontiguous paddocks of similar size (620 ha approxi-mately), which were used as experimental units (Fig. 1).Three experimental regimes were imposed from Decem-ber 1985 to April 1988: control (kangaroos plus sheep).

Fig. 1. Map of the study area showitig the experimental design andlocation of rain gauges (•). Sheep = sheep-only; roo = kangaroo-otily; sheep/roo = sheep plus kangaroos.

kangaroo-only (removal of sheep), sheep-only (removalof kangaroos). In the context of this design, the 'treat-ment' is whether a species was or was not with the otherspecies. Treatments were replicated twice in space butwere not allotted randomly. Adjacent paddocks werechosen for the sheep-only treatment to save on the costof electric fencing (see following) and the other treatmentswere arranged to give a blocked design (see Fig. 1).

A 1.2 m high electric fence was used to deter kangaroosfrom entering the sheep-only treatment paddocks. Theelectric fence was a leaky barrier and regular cullinghelped to maintain very low densities of kangaroos in thesheep-only treatment paddocks (see Edwards 1990).Kangaroos were allowed to free-range in the remainingpaddocks; the existing sheep-control fences providedlittle barrier to kangaroos.

Stocking rates for sheep were determined followingassessments of carrying capacity (after Condon et al,1969) made for each paddock by officers of the SoilConservation Service of New South Wales. Such esti-mates are conservative (Condon et al, 1969) and so allpaddocks containing sheep were stocked at a level 10%above the 'recommended' rate (0.12-0.14 ha"') to give astocking rate which more closely matched the long-termdistrict average, which is approximately 0.20 ha"' (esti-mate based on Condon's 1968 equation and mean rainfalldata for Fowlers Gap, see Results).

In summary, the experimental design was similar to a'mechanical diallel' (Underwood 1986) with two repli-cates. The control paddocks (sheep plus kangaroos) hadthe same density of sheep as the sheep-only treatmentpaddocks but also contained free-ranging kangaroos.Such a design is appropriate for examining interspecificcompetition because it provides unconfounded results(Underwood 1986).

Rainfall and vegetation

Weekly rainfall data were collected from two gauges atthe study site (Fig. 1).

The total lateral cover of herbaceous vegetation andsub-shrubs was monitored using the wheel-point tech-nique (Tidmarsh & Havenga 1955). Ten surveys ofvegetation were conducted between September 1985 andApril 1988 at about 3 month intervals. About 2500 pointswere recorded for each paddock at each survey alongfixed transects totalling about 8 km in length. Respectiveland class units were sampled in proportion to their area.One point was recorded for each revolution of the wheeland a 'hit' was recorded when the needle touched anypart of a plant. Plants were identified to species wherepossible and if the needle simultaneously touched morethan one species then hits were recorded for each species.

Six major categories of plant types were recognized forthe study area (Table 1): flat-leaved chenopods (salt-

326 G, P, E D W A R D S ET AL.

Table 1. Regression equations for estimating dry vegetation biomass in g m^plants

per cent cover data (x) for each sub-category of

Major category

Flat-leaved chenopod

Round-leaved chenopod

Maireana aphyllaGrass

ForbMalvaceous spp.

Sub-category

PerennialAnnualCopperburrPoverty bushBluebush—TaUMediumShortForbMalvaceous

Representative species

Atriplex vesicariaA triplex holocarpaSclerolaena diacanthaSclerolaena dtvaricataMaireana georgeiMaireana aphyllaEragrostis setifoliaEnneapogon avenaceusTripogon loliiformusHelichrysum and Plantago spp.—

Regression equation

log>'= l,355(logx) +0,544\ogy= l,070(logx) +0,595\ogy = 0,986(log x) +0,634\ogy= L488(logx) +0,557\ogy= l,130(logx) + 0,728\ogy^ l,388(logx)+0,610\ogy= l,026(logx)+0,571log>'= l,248(logx)+0,473\ogy = 0,846(log x)+0,299log >' = 0,941(logx)+ 0,541

0,900,970,950,960,960,970,980,930,890,76

n

810778

1012108

24

Major category groupings are also shown. Logarithms to base 10, The Sclerolaena diacantha regression equation was used toestimate the biomass of malvaceous spp, because tbe growth form of tbese plants is similar.

bushes), rotmd-leaved chenopods (copperburrs and blue-bushes), cottonbush, grasses, forbs and malvaceous sub-shrubs (non-chenopod shrubs ofthe families Malvaceae,Solanaceae and Amaranthaceae). Within these, severalsub-categories based on growth form were also recognized(Table 1). Cover data from the wheel-point method werepooled initially to sub-category level.

Ideally, in point sampling of vegetation, the needleshould be of infinitely small diameter, otherwise cover isoverestimated (Goodall 1952), In a one-off subsidiaryexperiment biases involved with the wheel-point methodwere estimated, A species representing each of the sub-categories used to classify vegetation was selected (Table1) and cover measurements were made for each using the10 mm diameter needle of the device and a cross wiresighting tube (Witikworth & Goodall 1962), Cover datafrom the wheel-point method previously pooled to sub-category level were corrected for estimated biases.

A ftirther one-off subsidiary experiment was conductedto establish the relationship between plant cover andbiomass. A 1 m^ quadrat was used to assess cover foreach species representing each of the sub-categories usedto classify vegetation (Table 1). The quadrat was sub-divided into a grid of 25 units each measuring 20 X 20cm. Cover in each grid imit was estimated by eye andestimates were then summed to give the total cover forthe quadrat. Quadrats were then harvested. Seven to 241 m^ quadrats of increasing cover were harvested for eachspecies. Samples were dried for 48 h at 80°C andweighed to determine dry biomass. Least-squares regres-sions of dry standing biomass versus percentage coverwere then constructed for each vegetation sub-category.Cover data were then used to estimate the total standingdry biomass for each sub-category. These data were thensummed to give biomasses for each major vegetationcategory in each paddock.

The Proportional Similarity Index (PS; Feinsinger etal. 1981) was used to measure the similarity of vegetationresources (overlap) between paddocks based upon thebiomass composition of the pasture on offer (majorcategory data) for each sample period:

where P; is the proportion of resource items in state i inpaddock P, and Q; is the proportion of resource items instate i in paddock Q,

Diet

Diet analysis involved the microscopic identification ofplant epidermal fragments in faecal samples. This methodhas been used widely to determine herbivore diets (Sparks& Malechek 1968; Storr 1968) and its accuracy andbiases have been well documented (Vavra & Holechek1980; Kessler et al. 1981; Holechek et al. 1982; Norbury& Sanson 1992).

On eight occasions between March 1986 and February1988, four to eight samples of fresh faeces, each from adifferent animal, were collected for red kangaroos andsheep from their respective paddocks from arotmd per-manent plots. Four to five pellets from the same de-fecation ( < 5 cm apart) were collected for kangaroos and20-30 pellets for sheep.

Diet samples were prepared, motmted on slides andscored as described in Ellis et al. (1977, 1992). The sixmajor plant categories that were used to classify vegetationwere readily identifiable microscopically and so were alsoused to score dietary samples. A ftirther category couldalso be distinguished for dietary particles: 'browse' (woodyparts of trees).

The PS Index was used to measure dietary overlaps.

S H E E P - R E D KANGAROO DIETARY INTERACTION 327

Here P,' is the proportion of item i in the diet of animal P,and Q, is the proportion of item / in the diet of animal Q.

Measures of dietary overlap were compared using theMantel test (Mantel 1967) to ascertain whether dietswere significantly different between species. The Manteltest is a non-parametric statistical procedure for com-paring two distance matrices (Patterson 1986; Schnell etal, 1985). In an investigation of n individuals, eachmatrix (A and B) has dimensions oinXn, Matrix A is the

data matrix which in this analysis was composed ofdistances between all pairs of individuals (= dietaryoverlap based on PS measures). Matrix B represents thenull hypothesis being tested. Here each element was zerowhere the corresponding element in matrix A was abetween species comparison or one for a within speciescomparison.

Because the diets of animals from different areas mayreflect differences in resource availability (Hurlbert 1978;

Table 2. Results of the Mantel tests for interspecific differences in diets based on PS tneasures of dietary overlap

Date

March 1986

June 1986

August 1986

Novetnber 1986

March 1987

July 1987

October 1987

Febmary 1988

Location

PooledSheep/roolSheep/roo2PooledSheep/roolSheep/roo2PooledSheep/roolSheep/roo2PooledSheep/roolSheep/roo2PooledSheep/roolSheep/roo2PooledSheep/roolPooledSheep/roolSheep/roo2PooledSheep/roolSheep/roo2

n

2561616

3602520

4684224

3042028

2881616

19620

3571520

3802030

Mean overlap

0.7340.6950.7710.6620.7060.6190.5220.5660.4350.6030.6160.6350.7320.8530.8170.6250.5470.5800.5210.5240.6690.8680.436

SD

0.1000.0310.1090.1480.1260.1300.1610.1700.1220.2540.2840.2930.1870.1300.1480.1300.1410.1940.1140.1640.2540.0540.264

Mantel r

15.5484.1412.379

- 0.0480.3210.619

11.3625.1295.6409.2162.1040.5758.9010.3221.703

11.8964.213

13.4204.3283.9185.5011.2232.229

F

< 0.001< 0.001< 0.005

NSNSNS

< 0.001<0.001<0.001<0.001<0.05

NS<0.001

NSNS

< 0.001<0.001< 0.001< 0.001<0.001<0.001

NS<0.05

n = No. of cotnparisons; SD = standard deviation; NS = not significant; pooled — data pooled for each species between treatments;sheep/roo2 treatment diets for July 1987 were based on results for only one animal of either species due to sample loss and have beenomitted.

Table 3. Results of the Mantel tests for intraspecific differences in diets between treatments based oti PS measures of dietary overlap

Date

March 1986June 1986August 1986November 1986March 1987July 1987October 1987Febmary 1988

n

6410080646436

110100

Meanoverlap

0.8910.6440.6650.8700.9340.7800.7760.812

Red kangaroosSD

0.0540.1510.1410.1260.0310.1410.1480.122

Mantel r

1.6210.3781.0790.353

-0.229-0.581-0.667-0.891

F

NSNSNSNSNSNSNSNS

n

6481

1698480407090

Meanoverlap

0.8090.6450.5880.6620.7350.7770.7650.630

SheepSD

0.0630.1540.1510.1940.1640.0940.1440.296

Mantel t

1.3544.1137.947

- 0.4351.2821.7870.2180.451

F

NS<0.001<0.001

NSNSNSNSNS

n — No. of comparisons; SD = standard deviation; NS = not significant.

328 G. P. EDWARDS ET AL.

Petraitis 1979), two sets of Mantel analyses were per-formed (Table 2). First the diets of all kangaroos werepooled between treatments as were sheep diets (= pooled)to give the mean overlap in diet between species acrossall treatments; then the diets of sheep and kangaroos inthe same paddocks (i.e. those from the sheep/kangarootreatments) were compared. Where comparisons werebased on a sample of less than 14 animals (i.e. fewer than196 comparisons), a Monte-carlo simulation with 500randomizations was used to test the Mantel statistic(Schnell et al. 1985).

To examine whether interspecific competition influ-ences diet selection, we used the Mantel test to comparethe diets of sheep grazing allopatrically to those of sheepgrazing in the presence of red kangaroos (Table 3). Hereeach element of Matrix B was zero where the correspond-ing element in matrix A was a between treatment compari-son or one for a within treatment comparison. We simi-larly compared the diets of red kangaroos. Accordingly,individual diets were pooled between paddocks for eachexperimental treatment. While pooling here represents'sacrificial pseudoreplication' (Hurlbert 1984), it is re-quired by the Mantel test. If an interaction betweentreatment and diet were evident then paddock-baseddiets (i.e. no pooling) were compared using nested ANOVA

(paddock nested within treatment) to properly test fortreatment effects on diet composition. Paddock was con-sidered a random factor and the paddocks within treat-ments term appropriately used as the error term to testfor treatment effects (Winer 1971). Proportions werearcsine transformed prior to ANOVA (Zar 1984).

Dietary selectivity was measured crudely by dividingthe proportion of each component in the diet by itsrelative availability (Owen-Smith & Cooper 1987). Thisparameter, known as the forage ratio (F), has a valueapproximating 1.0 when the resource item is being usedin proportion to its availability. Biomass estimates forvegetation surveys were used as measures of resourceavailability for diet samples where appropriate to calcu-late F. Browse availability was not measured in thisstudy and so browse could not be used in calculations ofdietary selectivity. However, it was not important in thediet of either species (see Results).

Statistical analysis

Mantel tests and calculations involving the PS Index andthe forage ratio were carried out using either programswritten for an Apple He or Macintosh computer.

Regressions were performed using the SPSS'' softwarepackage (SPSS Inc. 1986) mounted on a Vax 11/780 orIBM 3090 mainframe computer. The ANOVA were per-formed using SYSTAT for Windows, version 1.0 on aPC.

RESULTS

Rainfall and vegetation

The annual mean rainfall at Fowlers Gap based on datafor 1966-92 was 241.8 mm. Rainfall at the study site for1984-87 was: 331.3 mm in 1984, 152.5 mm in 1985,

80

60

e

cro•:

20

n

1.. .Ill1. 1 III

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D1985 1986 1987

Month

Fig. 2. Average monthly rainfall at the study site.

Sample

Fig. 3. Estimated dry biomasses for each vegetation component ineach paddock. (—A— rool; -O— sheep/rool; —•— sheepl; —A—roo2; —•— sheep/roo2; —O— sheep2)

S H E E P - R E D KANGAROO DIETARY INTERACTION 329

149,2 mm in 1986 and 302.4 mm in 1987, Monthlyrainfall at the study site for 1985-87 is shown in Fig, 2,

Equations for estimating biomass from point-coverdata are presented in Table 1. Estimated biomasses foreach vegetation category and their dynamics were broadlysimilar for all paddocks (Figs 3, 4), However somedifferences were evident, Rool paddock consistentlyyielded lower biomasses than other paddocks because itcontained a larger proportion of bare scalded areas,Sheep/rool paddock contained more flat-leaved cheno-pods, and sheep2 paddock more M. aphylla than any ofthe other paddocks. Nevertheless, all paddocks weregenerally alike in vegetation composition: mean similarityvalues generated by the PS Index (+SE) ranged from0,76+ 0,12 (June 1986) to 0,86±0,05 (September 1985),Note that a value of one indicates total similarity (com-plete overlap) whereas zero indicates complete dissimi-larity (no overlap).

Total pasture biomasses were lowest for June-August1986 (Fig. 4: 45 g m"^ [dry wt]) as a result of low raitifallfrom January to August of that year (Fig. 2),

Diet

Diets are presented in Fig. 5 (raw data are available uponrequest from the authors). The percentage of unidenti-fiable particles in diet samples (primarily fragments ofvascular tissue) was usually higher for sheep (mean =63%) than for red kangaroos (mean = 48,4%),

Sheep and kangaroo diets changed according to pastureconditions. Dietary overlaps based on pooled data rangedfrom 52 to 73%, and were lowest during August 1986

250 r

200

50

Sample

Fig. 4. Total dry pasture biomasses for each paddock (symbols as inFig, 3),

(52%: Table 2), Surprisingly, June 1986 was the onlytime when pooled kangaroo and sheep diets were notsignificantly different. This was due to considerablevariability in kangaroo and sheep diets between paddocks,particularly in the proportion of chenopods eaten (Fig,5), For sheep and kangaroos grazing in the same pad-docks, interspecific dietary overlaps tended to be morevariable (44-87%: Table 2) and in nine ofthe 15 Mantelanalyses, sheep and kangaroo diets were significantlydifferent. Even so, a significant difference does not implythat the amount of dietary overlap was small.

The Mantel test did not indicate any interaction be-tween diet and treatment for kangaroos (i,e, diets did notappear to differ significantly between treatments: Table3), However, on two occasions (June 1986, August 1986)a possible interaction was indicated for sheep. Analysisof variance showed that a real treatment effect existedonly for August 1986, Sheep diets for sheep/roo paddockscontained proportionately more flat-leaved chenopod(nested ANOVA, Eia = 44,7; P < 0.025) and less grass(nested ANOVA, FI,2 = 65,5; P<0,025) than those foreither of the sheep-only paddocks.

Although both are generalist herbivores capable ofeating a wide variety of plants, sheep and red kangaroosare selective feeders as shown by their preferences forcertain vegetation components (Table 4), Note that pre-ferred foods may not be the principal components of thediet (e,g, malvaceous spp, for sheep). Generally redkangaroos showed positive selection for grass at all timesand for forb on occasions, and negative selection forother pasture components. However, in drier times (Jtme1986, August 1986) they increased their selectivity forflat-leaved chenopods, M. aphylla and malvaceous spp.Sheep generally always showed positive selection forgrass, forb and malvaceous spp, and negative selectionfor other pasture components. However, in drier timesthere was positive selection for flat-leaved chenopodsand M. aphylla (Table 4).

DISCUSSION

Although the method used to assess diets in this study isin common use for herbivores, it has two potentialdrawbacks. The first is that the more digestible types ofplants (e.g, forbs) are often underestimated in the diet(Norbury 1988), However, because kangaroos and sheephave similar digestive systems, biases due to differentialdigestibility are probably similar for both species and sothe dietary comparisons in this study are valid. Thesecond problem is that while diets may contain the sameplant category, the possibility remains that kangaroosand sheep eat different species of plants within thatgroup or even different parts of the same species. Theextent of this problem could not be ascertained in thisstudy.

330 G. P. EDWARDS

4R 4R 4R 4R 4S 4S 4S 4S

4R 4R 6R 4R 7S 6S 8S SS

4R 4R 4R 4R 4S 4S 5S 5S

100

80

60

40

20

0

Oct 87

5R 5R 5R 6R 3S 4S 5S 5S

o. a.

5R 5R 5R 5R 5S 4S 5S 4S

4R 4R 4R 4R SS 7S 4S 3S

Jul 87

4R SR 4R IR 5S IS 4S 4S

jgggg

CO t/l yl 1/1

Sample

SR SR SR 5R 4S 6S 5S 4S

Fig. 5. Percentage composition ofthe identifiable portion of samples of red kangaroo and sheep diets. Numbers on top of columns are samplesizes: R, red kangaroo; S, sheep. From bottom to top: (•) Oat-leaved chenopod; {^)Maireana aphylla; ( • ) round-leaved chenopod; (0) grass;(D) forb; (H) Malvaceous spp.; (LLII) browse.

S H E E P - R E D KANGAROO DIETARY INTERACTION 331

Although the sample sizes used in tbis study to estimatediet were small (3—8), we believe tbat tbey provided anaccurate indication of diet selection for eacb species in

eacb paddock. Coefficients of variation (CV) of tbepercentage of grass and forb (tbe main dietary items) inred kangaroo diets ranged from 2 to 82% (mean = 20,3%,

Table 4. Dietary selectivity indices based on the forage ratio (F) for vegetation components

March 1986Flat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

June 1986Elat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

August 1986Flat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

November 1986Flat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

March 1987Flat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

July 1987Flat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

October 1987Flat-leaved chenopodRound-leaved chenopodMaireana aphyllaGrassForbMalvaceous

Rool

-—--1-00

——

+00—

——-1--1-—0

——

++——

———-1-——

—--

+——

———

——

RedRoo2

———-1-0-1-

———

+-1--1-

0——-1-0-1-

———

+——

———-1-——

—0—

+—-

———-1-0—

kangarooSheep/

rool

-—-

+-

0——-1--1--

0—000—

———

+——

———++-

———-1-—-

———-1-0—

Sheep/roo2

———-1-

+—

0——

——

———+00

———

—-

———

+—-

———+—-

———

+—

Sheep/rool

———0

+

——0-1--1-

—

—-1-—

———-1-

-1-

———-1--1--1-

———0-1-

+

———0-1--1-

SheepSheep/

roo2

———

+0

+——-f--0

+———00

———-1-0

+

———-1-00

———00-1-

————-1-

Sheepl

———0

++

-1-—0-1-0—

—

+—

—

———-1-4-

———

++

——-1-0+—

———0++

Sheep2

———-h

++

0——-1---

0——++0

———0-1-

———0-1--1-

——0-1-0-1-

—

—0+-1-

- = Negative selection (F<0,8); 0 = neutral selection (item eaten in proportion to availability: O,8<F<1,2); 4- - positiveselection ( F > 1,2),

332 G. P. EDWARDS

n = 31) and 10 to 91% (mean = 53.3%, n = 31), respec-tively. For sheep CV of grass and forb (also the maindietary items) ranged from 5 to 102% (mean = 34.8%,n = 31) and 4 to 77% (mean = 34.9%, n = 31), respec-tively. These CV values are similar to those found undersimilar environmental conditions by Dawson and Ellis(1994) who conducted their study in the same locality asthe present investigation from 1972 to 1978 and basedtheir dietary estimates on 7-10 stomach samples col-lected from each species per sample period. For redkangaroos, Dawson and Ellis's CV values were 3-66%(mean = 22.8%, « = 9) for grass and 33-100% (mean =62.5%, n = 8) for forb. For sheep, Dawson and FUis'sCV values were 6-60% (mean = 31.7%, « = 8) for grassand 25-100% (mean = 42.2%, « = 8) for forb.

The results of this study accord in broad detail withthose of others that have investigated sheep-red kangaroodiets. Although these studies have been conducted indifferent parts of Australia in different types of habitat,some consistent patterns are evident. Grass is the majordietary constituent of red kangaroos, irrespective of seasonand pasture condition (Chippendale 1962, 1968; Griffiths& Barker 1966; Storr 1968; Bailey et al. 1971; Griffiths etal. 191 A; Ellis et al. 1977; Barker 1987; Dawson & EUis1994). Forbs are eaten by red kangaroos but in smalleramounts than grasses (Chippendale 1962, 1968; Griffiths& Barker 1966; EUis et al. 1977; Barker 1987; Dawson &Ellis 1994) and when pasture availability declineschenopod shrubs are eaten also (Barker 1987; Dawson &Ellis 1994). Although sheep include proportionately moreforbs in their diet than red kangaroos, the same basicpattems are evident (Griffiths & Barker 1966; Storr1968; Griffiths et al. 1974; EUis et al. 1977; Barker 1987;Dawson & Ellis 1994) and so levels of dietary overlap areoften high. The preference of sheep for malvaceous sub-shrubs has also been demonstrated in another study(Dawson & Ellis 1994).

Sheep are reported to switch to chenopod shrubs morereadily than red kangaroos when pasture availabilitydeclines (EUis et al. 1977; Barker 1987; Dawson & EUis1994). Short (1985) showed that Maireana pyrimidatareached 20% of total intake for sheep at pasture biomasses(herbs only) of about 35 g m'^ (dry wt) and for redkangaroos at about 10 g m-^ (dry wt). Such a markeddichotomy was not observed in this study: chenopodsreached 20% of intake for sheep at herbaceous biomasses(grass, forb and malvaceous spp.) of 18-26 g m^̂ (^^^wt). For red kangaroos this occurred at 18-22 g m"^ (drywt). The discrepancy between these studies may be dueto site-related differences in the types of chenopodspresent and their palatabiUty characteristics.

This study indicates that interspecific competitionmay play a role in diet selection in red kangaroos andsheep. Red kangaroos appeared to deprive sympatricsheep of desirable fodder, notably grass, at low pasture

biomasses (about 45 g m ^ [dry wt]) forcing them toinclude proportionately more chenopodaceous shrubs intheir diet. However, while this suggests that a food-related competitive interaction exists, it does not demon-strate unequivocaUy that it occurs. A competitive inter-action results in either one or both species beingdisadvantaged in some way (Schoener 1983); we do notknow whether this change in diet affects sheep detri-mentally. This was explored in a concurrent investigationduring which indices of fitness were determined for redkangaroos and sheep.

That red kangaroos in both the sheep/roo treatmentpaddocks were able to maintain at least a 30% grassintake during August 1986 when sheep in these paddocksdid not, suggests that red kangaroos may be more efficientforagers than sheep. Three points bear mentioning inthis regard. Although both species are able to croppasture to similar heights (Short 1987), by virtue of theiranatomy, red kangaroos are better able to seek out rem-nant pasture under bushes and are able to dig forunderground shoots (Short 1987). Also, there is theoretic-ally a selective penalty involved with flocking behaviourat low pasture biomasses (Ekman & Rosander 1987)which affects sheep but not red kangaroos (mean groupsize 1.5-2.2 animals: Croft 1980; Johnson 1983). Sheepultimately form smaUer sub-flocks when pasture abund-ance is criticaUy low (Lynch 1974a,b), presumably tocombat this problem. Lastly, red kangaroos have amuch lower rate of water turnover than sheep (Dawsonet al. 1975). Consequently, in times of water stress, redkangaroos are able to forage further from water thansheep and therefore make better use of the availableresources.

The conclusions drawn from this study rest uponshowing that the change in sheep diet was not due tointrinsic differences between the paddocks. The treat-ments used in this study were replicated which is theappropriate way to overcome the problem of environ-mental heterogeneity when conducting field experiments(Hurlbert 1984). Furthermore, there is no evidence thatdifferences between the sheep paddocks in terms ofpreferred sheep forage (grasses, forbs and malvaceousspp.) were consistent between treatments. In fact sheep/rool paddock was more closely aUied with sheepl pad-dock, and sheep/roo2 paddock with sheep2 paddock interms of the dynamics and biomasses of these preferredforages (Fig. 3). Measurements made before the studycommenced (September 1985) also indicated that thebiomass of grasses was similar for each of the fourpaddocks containing sheep (Fig. 3). Thus the depletionof palatable grass resources in both of the sheep/rootreatment paddocks during 1986, to the extent that sheepwere obliged to consume relatively more flat-leaved cheno-pods and fewer grasses, can be attributable only to thefact that red kangaroos also eat grass.

SHEEP-RED KANGAROO DIETARY INTERACTION 333

ACKNOWLEDGEMENTS

We dedicate this paper to Alex Mazanov, We thankP. Adam, D. Anderson, G, Belovsky, B, Ellis, B. Fox,G, Grigg, A, Mazanov, M. Melville, S. McLeod,G. Moss, T, Pople, M. Westoby, the staff at FowlersGap, the Soil Conservation Service of New South Walesand the student, Earthwatch and other volunteers whoassisted with field work. This study was supported by theFowlers Gap Management Committee, an AustralianPostgraduate Award to G. Edwards, a grant from theAustralian National Parks Kangaroo Monitoring Unit toT. Dawson and D, Croft and an Austrahan ResearchCouncil Grant to T. Dawson,

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