Journal of Fish Biology (2002) 60, 000–000doi:10.1006/jfbi.2002.2147, available online at http://www.idealibrary.com on

Ontogenetic shift in nocturnal microhabitat selection bygiant kokopu in a New Zealand stream

A. L. W†, B. O. D G. P. C*Department of Zoology, University of Otago, P.O. Box 56, Dunedin, New Zealand

(Received 18 February 2002, Accepted 4 October 2002)

Nocturnal microhabitat selection in relation to size was examined for a New Zealanddrift-feeding freshwater fish, the giant kokopu Galaxias argenteus in three coastal Otagostreams. Evidence for ontogenetic shifts in microhabitat selection were observed, particularlywith respect to water velocity and depth. Small (<80 mm) giant kokopu tended to occur inshallow backwaters adjacent to fast flowing water. In contrast, larger individuals (�80 mm)were most commonly observed in deeper, slower flowing pools. These patterns of habitatselection are most likely associated with the trade-offs involved with the selection of optimalhabitats for drift feeding combined with avoidance of intra-specific competition and the threatof predation from larger conspecifics.

� 2002 Published by Elsevier Science Ltd on behalf of The Fisheries Society of the British Isles.

Key words: habitat selection; Galaxias argenteus; fish behaviour; habitat use.

INTRODUCTION

Microhabitat selection by drift-feeding fishes in streams is determined by anumber of interacting biotic (e.g. competition and predation) and abiotic (e.g.stream size, flow velocity and substratum) factors (Matthews, 1998; Jacksonet al., 2001). The ecological requirements of fishes may change in relation to sizeresulting in ontogenetic niche shifts represented by predictable changes in habitatselected over the life cycle of a fish (Moyle & Vondracek, 1985; Matthews, 1998).The disproportionate use of a particular microhabitat type in relation to itsavailability within a habitat suggests non-random selective use of availablehabitat (Pert & Erman, 1994; Moore et al., 1999).

Consideration of a single physical variable, such as water velocity, illustratesthe various competing demands that can influence habitat choice. Water velocitydirectly influences the energetic cost associated with maintaining position in thewater column (Facey & Grossman, 1992; Hill & Grossman, 1993) and these costsoften vary between size-classes (Baltz & Moyle, 1984). Fishes have to balancethe energetic costs of maintaining their position in the water column and thegains associated with the supply of food (Fausch, 1984). Preferred positions arelikely to be in areas of low water velocity adjacent to faster currents, thusminimizing energy expenditure but still allowing access to invertebrate drift(Smith & Li, 1983). Adjacent velocities, however, should not be so high so as to

*Author to whom correspondence should be addressed. Tel.: +64 3 479 7972; fax: +64 3 479 7584;email: gerry.closs@stonebow.otago.ac.nz

†Present address: Warnell School of Forest Resources, University of Georgia, Athens, GA 30602,U.S.A.

10022–1112/02/000000+00 $35.00/0 � 2002 Published by Elsevier Science Ltd on behalf of The Fisheries Society of the British Isles.

reduce the ability of the individual to catch prey (Hughes & Dill, 1990;Vondracek & Longanecker, 1993). Suboptimal use of habitat may occur whenan individual is exposed to a high risk of predation or competition inits preferred habitat (Baltz & Moyle, 1984; Schlosser, 1987; Heggenes, 1988).Inter- or intra-specific competition or the threat of predation may drivevulnerable fishes into shallow water or areas of high velocity often reducing theirnet energetic returns and overall growth rates (Fausch, 1984).

In this study, patterns of ontogenetic variation were examined in the nocturnalmicrohabitat selection of a New Zealand freshwater fish, the giant kokopuGalaxias argenteus Gmelin. In contrast to most galaxiid species, giant kokopugrow to a relatively large size (maximum total length, LT, 58 cm). Although theyare predominantly invertebrate drift feeders (Jellyman, 1979; Rasmussen, 1990;David, 2002), large adults are known to be piscivorous (Rasmussen, 1990;Bonnett, 2000). Despite the potentially piscivorous behaviour of large fish,adults and juveniles will frequently coexist along a stream reach (David, 2002).Based on the relative size difference between juvenile and adult fish, inter-cohortpredation would appear to represent a significant threat to juvenile fish. If so,ontogenetic shifts in microhabitat use similar to those observed in various speciesof potentially piscivorous drift feeding fishes, particularly salmonids (Baltz et al.,1991; Greenberg et al., 1996) may occur. Based on observations of drift feedingsalmonids in small streams (Baltz et al., 1991; Greenberg et al., 1996), it waspredicted that large giant kokopu should be disproportionately represented inpositions located in deep, slow-flowing pools downstream of a run or riffle whichprovide a supply of drifting invertebrates. In contrast, juvenile fish will be lesslikely to occur in habitats occupied by adult fish, most likely occupying shallowerhabitats located along stream margins or riffle sections. Prediction of likelypatterns of habitat selection in giant kokopu, however, is complicated by theirlargely nocturnal behaviour (David, 2002). Studies of habitat selection of driftfeeding fishes have generally focused on diurnal behaviour (Baltz et al., 1991;Greenberg et al., 1996). Where nocturnal behaviour has been studied, it hastypically concentrated on seasonal changes in activity and habitat selectionassociated with declining temperature rather than ontogenetic variation inhabitat selection (Fraser et al., 1993, 1995; Heggenes et al., 1993).

METHODS

STUDY SITESThis study was carried out between January and April 2001 in Alex’s Creek (170�03� E;

46�02� S), Boundary Creek (170�04� E; 46�58� S) and Cullen’s Creek (170�03� E; 46�03� S)(Fig. 1), a second order and two third-order streams respectively, in the Lake Waihola–Lake Waipori catchment. The three streams are typically <2 m wide and <0·3 m deepand are characterized by a fine gravel and bed rock substratum.

HABITAT USE AND AVAILABILITYGiant kokopu were located at night using an unfiltered spotlight powered by a 12 V

lead-acid battery. Each stream reach was systematically sampled once in an upstreamdirection to ensure that all observations were independent. Sampling was done from thestream bank where possible to minimize disturbance to the fish (McCullough, 1998) andcare was taken to avoid lighting unsurveyed sections upstream of the immediate survey

2 . . .

section. Only those fish that were clearly undisturbed when first caught in the beam ofthe spotlight were included in the study. When illuminated by a light, giant kokopu willusually remain in position for a short period. If holding a mid-water position, they willthen slowly sink to a resting position on the bed of the stream. Sudden fast movementsaway from their initial position when first illuminated are rarely observed. Wheredisturbance by a spotlight does induce a movement away from their initial position, fishgenerally move under nearby cover and can no longer be detected by observers. Oncesighted, the focal position of each fish was marked with a weighted, numbered float. TheLT of each fish was estimated by measuring the distance between adjacent substratumfeatures on the stream bed where possible or by visual estimation. All observers wereexperienced in visual estimation of LT and repeated measurements of fish over the courseof the study maintained an accuracy of �10%.

The following day, microhabitat variables associated with the position of each fish asindicated by the position of the numbered floats were recorded. Water velocity wasmeasured using a Marsh–McBirney Flomate� electronic flow meter at the recordedvertical position of the fish (resolution �0·01 m s�1). In addition, the fastest velocitywithin 30 cm of the focal point of each fish was recorded. The dominant substratum typeat the marked position was estimated using a modified Wentworth scale (<2 mm silt;2–4 mm sand; 4–64 mm gravel; 64–256 mm cobble; >256 mm boulder; Sagar, 1993). Thedepth at the focal point was also recorded. The stream morphology at each point wasvisually classified as either a backwater, pool, run or riffle. Pools were classified as areasof still or slow flowing water, while backwaters were recorded as areas of water flowingin the opposite direction to the main current and adjacent to the bank. Many of theobserved backwaters were relatively small in area and all were adjacent to either a pool,run or riffle. Riffles were defined as areas of fast flowing water with a broken surface, andruns as fast flowing water with an unbroken surface (Hayes et al., 1989; Moore et al.,1999; Chadderton & Alibone, 2000).

The available habitat within the stream was estimated by measuring the samemicrohabitat variables (except the fastest velocity within 30 cm) at 10 positions upstream

F. 1. Sampling localities at three streams in Otago for giant kokopu. Solid bars across streams indicatethe upstream and downstream boundaries of the sampled reaches.

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and downstream of each recorded fish. These points were determined by placingtransects at 2 m intervals along the reach and sampling at one of five random points(selected using a random number table) across the channel. Positions one or five were10 cm from the water’s edge on each bank. Position three was the centre of the channel,and positions two and four were midway between the channel centre and positions oneand five respectively. Where fish were located within 20 m of each other, habitatvariables from 10 positions were recorded upstream and downstream from each fish andat 2 m intervals between each fish.

STATISTICAL ANALYSISTo determine whether the habitat available within each stream was similar, a

multivariate comparison of four habitat variables (velocity, depth, substratum type andstream width) available within the three streams was performed using a correlation-basedprincipal component analysis (PCA; Clarke & Warwick, 1994; Sokal & Rohlf, 1995).Analysis of similarities (ANOSIM) was performed using normalized Euclidean distancesto determine if the three streams contained significantly different habitat types.ANOSIM uses Monte-Carlo randomization techniques to calculate a test statistic (R)based on the difference between the average of all rank dissimilarities between objectsbetween groups and the average of all rank dissimilarities between objects within groups(Quinn & Keough, 2002). ANOSIM tests the null hypothesis that the average of the rankdissimilarities between all possible pairs of objects in different groups is the same as theaverage of the rank dissimilarities between objects in the same groups (Quinn & Keough,2002). It does not require the assumptions of normality and homoscedascity to be metand can be used with multivariate data (Clarke & Green, 1988; Clarke, 1993; Quinn &Keough, 2002). R was calculated using 999 random permutations and a test wasconsidered significant if P<0·05.

Giant kokopu were a priori divided into three size-classes; small (<80 mm), medium(80–159 mm) and large (�160 mm LT). The division between small and medium giantkokopu was based on the likely maximum length for 1 year giant kokopu (Jellyman,1979). The division between the medium and large giant kokopu represented theapproximate mid-point in the size distribution of fish from 80 mm up to the maximumsize of c. 300 mm LT fish which were known to inhabit the study streams.

Microhabitat selection was examined by pooling data across the three streams andcomparing habitat utilized by giant kokopu to that available. Data were pooled tosimplify the presentation of results and maintain an adequate sample size acrosscatagories for a meaningful analysis. Data for each microhabitat variable were dividedinto categories and the proportion of individuals occurring within a particular categorywas calculated for each of the three size classes (McDowall, 1998). Microhabitatselection, or the non-random use of each habitat parameter, was determined separatelyfor each of the size classes by comparing the habitat used to that available in the streamswith a �2 goodness of fit test. The available habitat data were used as the expected habitatuse and criteria were set using the methods of Roscoe & Byars (1971) reducing the effectof inflated values due to empty cells. Overall habitat use of the three size classes of giantkokopu were compared using a correlation-based PCA (Clarke & Warwick, 1994; Sokal& Rohlf, 1995). ANOSIM using normalized Euclidean distances was used to determineif observed differences in overall habitat use between the size classes were statisticallysignificant (Clarke & Warwick, 1994; Quinn & Keough 2002).

RESULTS

AVAILABLE HABITATA total of 644 random habitat points were sampled from c. 5 km of stream

over a 4 month period. The majority of samples were taken from Alex’s Creek(n=359, 2·5 km) followed by Boundary Creek (n=143, 1·5 km) and Cullen’sCreek (n=142, 1 km). The numbers of points recorded from each stream

4 . . .

reflected the number of fish and distance between individual fish observed in eachstream. High fish densities, particularly in Alex’s and Cullen’s Creeks, resultedin overlap of the habitat points measured for each fish, hence fewer point habitatmeasurements relative to the number of fish observed.

The correlation-based PCA ordination revealed primary habitat gradientsrelated to water velocity and depth on PC 1 and channel width and substratumparticle size on PC 2 (Fig. 2). Collectively, the two axes account for 65% of thetotal sample variation (Table I). There was a significant difference in the habitatavailable within the three streams (ANOSIM, R=0·024, P=0·049). Multiplepairwise comparisons of the three streams using ANOSIM determined that these

(c)

PC2

PC1

(b)

PC2

PC1

(a)

PC2

PC1

shallowfast

deepslow

Wide channelCoarse substratum

Narrow channelFine substratum

F. 2. Two-dimensional PCA ordinations of the available microhabitat variables for three Otagostreams: (a) Alex’s Creek (n=359), (b) Cullen’s Creek (n=142) and (c) Boundary Creek (n=143).PC1 and PC2 account for 65% of the total sample variability. Environmental gradients indicatedon PC1 and PC2 in (a) apply to (b) and (c).

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differences occurred between Boundary and Alex’s Creeks (R=0·054, P=0·008),and Boundary and Cullen’s Creeks (R=0·019, P=0·002). There was no signifi-cant difference between the habitat available in Alex’s and Cullen’s Creeks(P=0·364).

All broad habitat types were available within each of the three streams,although relative proportions varied. Alex’s Creek was dominated by pool-rifflehabitat [Fig. 2(a)], which can be seen by the proportion of the total number ofrandom samples that fell within the top right (areas of deep, slow water in anarrow channel; 34%) and bottom left (wide channels with fast, shallow flows;35%) quadrants of Fig. 2(a). Shallow, narrow sections of stream with highvelocities were also relatively common (25%). In comparison, there were veryfew areas characterized by deep, wide pools with low velocities (6%). These fewpools tended to be towards the upstream end of the study reach in Alex’s Creekand were typically dominated by a bedrock substratum. Cullen’s Creek wassimilar in structure to Alex’s Creek [Fig. 2(b)], with slow, deep pools character-ized by wide channels and bedrock substrata occurring towards the upperreaches of the surveyed area (37%). The lower reaches were characterized bydeep, silty pools (23%). Faster areas of water were also common, with both fineand coarse substrata representing 20% each of the total habitat types. BoundaryCreek was also characterized by a wide range of habitat types [Fig. 2(c)],although slow deep channels with a coarse substratum dominated (42%). Aconsiderable proportion of the Boundary Creek was also characterized by areasof fast, shallow flows in wide channels (30%). Narrow channels with finesubstrata were less common, occurring in conjunction with deep, slow velocities(18%) and shallow, fast flows (10%).

SIZE CLASS DISTRIBUTIONA total of 199 undisturbed giant kokopu were observed over a 4 month period,

ranging from 45 to 300 mm LT. Fish in the medium size class (80–159 mm)comprised 46% of the total, with 34% of fish being >160 mm. The small sizeclass (<80 mm) contained the remaining 20% of individuals, although this wasdominated by fish <60 mm. One hundred and twenty-two giant kokopu weresighted in Alex’s Creek, ranging in length from 45 to 300 mm. The dominant sizeclass in Alex’s Creek contained individuals <60 mm (21%), with a secondarypeak at 160–180 mm (14%). A wide size range was also observed across the58 giant kokopu counted in Cullen’s Creek (55–300 mm). The most abundant

T I. Coefficients of the first two principal componentsobtained from the available habitat data within three Otago

streams

Variable PC1 PC2

Velocity �0·544 �0·232Depth 0·498 �0·368Substratum �0·463 �0·710Stream width 0·491 �0·554Variation explained (%) 43 22

6 . . .

category was 80–99 mm (32%), followed by peaks at 120–129 mm (18%) and220–229 mm (9%). The abundance and size distribution of giant kokopu inBoundary Creek was noticeably different to that found in Alex’s and Cullen’sCreeks. Only 18 individuals were observed along a 1·5 km reach, ranging inlength from 100 mm to 250 mm LT. There was no dominant size class althoughthe majority of individuals were >160 mm, suggesting only limited recruitment.

MICROHABITAT SELECTIONAll size classes of giant kokopu exhibited clear microhabitat selection with

respect to focal water velocity and depth (Table II). Overall, giant kokopu of allsizes were most commonly encountered in areas of low focal water velocity with85, 73 and 64% of large, medium and small fish respectively being recorded infocal water velocities between 0 and 0·08 m s�1, a category representing 46% ofthe available habitat [Fig. 3(a)]. Other results, however, suggested that smallgiant kokopu tended to select quite different microhabitats compared withmicrohabitats selected by fish in the medium and large size classes. The majorityof small giant kokopu (56%) were located in areas adjacent to velocities >0·16 ms�1, with only 18% located in areas adjacent to water velocities of 0 to 0·08 ms�1 [Fig. 3(b)]. In contrast, medium and large individuals were generallypositioned adjacent to water velocities between 0 to 0·08 m s�1 (52% and 63%respectively). Giant kokopu were found in depths ranging from 0·05 to 0·92 m[Fig. 3(c)], with juveniles being most commonly found in water <0·1 m deep(72% used v. 25% available). Medium and large giant kokopu dominated inintermediate water depths. All size classes were most frequently recorded oversilty substrata [Fig. 3(d)] reflecting the slow focal water velocities in which theywere most commonly encountered. Differences in the microhabitat parametersused by the different size classes of fish were also reflected in the broader habitatcategories used by the fish. Small fish were disproportionately represented insmall backwaters (23% used v. 7% available) [Fig. 3(e)], many of which wereadjacent to fast-flowing riffles or runs. In contrast, medium and large fish weremost commonly encountered in pools [Fig. 3(e)].

Overall, PC 1 and 2 of the PCA for giant kokopu microhabitat use explained62·7% of the variation and were associated with gradients in depth and adjacentwater velocities, and substratum and focal water velocities respectively (Fig. 4and Table III). Microhabitat use of giant kokopu differed significantly betweenthe three size classes (ANOSIM; R=0·138, P<0·001). Pairwise ANOSIM tests

T II. Comparisons (�2 tests) between available stream habitat and habitat utilized bythree classes of giant kokopu

Variable (d.f.) Small Medium Large

Focal velocity (9) 29·4* 33·2* 44·3*Fastest velocity within 30 cm (9) 37·9* 6·5 11·7Depth (10) 46·1* 21·6* 34·8*Substratum (5) 9·0 16·5* 6·3Stream morphology (4) 51·0* 38·7* 40·3*

*Statistically significant (P<0·05).

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indicated this was due to differences between small individuals and the mediumand large size classes (R=0·266, P<0·001 and R=0·396, P<0·001 respectively).There was no significant difference in the microhabitat use of medium and largegiant kokopu (R= �0·034, P=0·1). On the PCA ordination, 66% of the smallfish were associated with slow, shallow water over fine substratum adjacent tofast flows [Fig. 4(a)]. Medium giant kokopu were spread evenly across the range

0Vegetation

0.8

Habitat

(e)

% F

requ

ency

Backwater

0.4

0Bedrock

0.5(d)

0.25

01000

0.8(c)

0.4

00.64

0.7(b)

0.35

0

0.9(a)

0.45

Pool Run Riffle

RockPebbleGravelSandSilt

8006004002000

0.480.320.160.00–0.16

0.640.480.320.160.00–0.16

Substratum

Depth (mm)

Velocity (m s–1)

Velocity (m s–1)

F. 3. Comparison between available habitat and microhabitats used by different size classes of giantkokopu (�, available habitat; �, small; , medium; , large) within three Otago streams. (a)Focal water velocity, (b) fastest water velocity within 30 cm, (c) depth, (d) substratum and (e)stream morphology.

8 . . .

of depths and adjacent current velocities [PC 1, Fig. 4(b)], and a greaterproportion of large individuals were associated with deeper water adjacent tolow velocities [39%; Fig. 4(c)].

DISCUSSION

Giant kokopu actively selected certain microhabitat types within streamenvironments and this selection varied with respect to the size of the individual.Ontogenetic shifts in habitat selection by giant kokopu were broadly comparablewith ontogenetic shifts in habitat use observed in a range of freshwater fishes,particularly stream-dwelling diurnal salmonids (Baltz & Moyle, 1984; Baltzet al., 1991; Heggenes, 2002). At night, small giant kokopu are typically foundin shallow, backwater habitats adjacent to high water velocities. In comparison,medium and large individuals tend to occur in slow-flowing, deep pools. Such

(c) PC2

PC1

(b) PC2

PC1

(a) PC2

PC1

Coarse substratumHigh focal velocity

DeepLow adjacentvelocity

ShallowHigh adjacentvelocity

Fine substratumLow focal velocity

F. 4. Two-dimensional PCA ordinations of the microhabitat variables used by the three size classes ofgiant kokopu. (a) Small (n=39), (b) medium (n=92) and (c) large (n=68). PC1 and PC2 accountfor 62·7% of the total sample variability. Environmental gradients indicated PC1 and PC2 on (a)also apply to (b) and (c).

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ontogenetic shifts in habitat use by small fish are likely to be associated withavoidance of the threat of predation or intra-specific competition from largerconspecifics (Bresmet & Berg, 1999). Given that large adults are partlypiscivorous (Rasmussen, 1990; Bonnett, 2000), the avoidance of habitats occu-pied by juvenile fish is not surprising. Small and large fish can be observed inclose proximity to each other in pools by day in summer (David, 2002).Nocturnal segregation of adults and juveniles suggests that adults may present agreater risk to juveniles at night when the ability of juvenile fish to use visual cuesto avoid potentially piscivorous adults may be reduced.

Water velocity is generally a key determinant of habitat selection in streamfishes. Studies of drift-feeding species have typically found that individuals tendto move into areas of low flow as they increase in size (Heggenes, 1988; Baltzet al., 1991; Pert & Erman, 1994; Heggenes et al., 1999; Heggenes, 2002), apattern also observed in this study. Such ontogenetic shifts are generallyassociated with increasing dominance and lead to greater energetic gains(Jenkins, 1969; Fausch, 1984; Facey & Grossman, 1992). Giant kokopu havebeen shown to form localized dominance hierarchies based on size when feedingduring the day (David, 2002), and the current data suggests that nocturnalmicrohabitat selection for preferred positions is also influenced by size. Similarfeeding strategies have also been noted in rainbow trout Oncorhynchus mykiss(Walbaum), with water velocities lower at focal resting points than in feedingpositions (Smith & Li, 1983; Hill & Grossman, 1993; Vondracek & Longanecker,1993). It is notable that small giant kokopu tend to occupy positions adjacent toareas of relatively high water velocity. These areas may lead to lowered feedingefficiencies due to the relatively high velocity of invertebrates drifting past thusreducing the number of successful prey captures (Hill & Grossman, 1993). Therisk of predation from larger conspecifics, however, is likely to be considerablyreduced in such microhabitats (Schlosser, 1987; Metcalfe et al., 1999).

Giant kokopu exhibit ontogenetic shifts in microhabitat use comparable tothose observed in other species of drift feeding fishes in which adult fishes arealso potentially piscivorous, e.g. various species of salmonid (Baltz & Moyle,1984; Baltz et al., 1991). The results highlight the need to maintain a variety ofmicrohabitats in small streams likely to be occupied by relatively large driftfeeding fishes, such as giant kokopu. Given the potentially piscivorous nature oflarge adult fish, the presence of shallow, slow flowing microhabitats from whichjuvenile fish can feed whilst still avoiding adult fish is likely to be essential for

T III. Coefficients of the first two principal componentsobtained from the data on microhabitat selection by giant

kokopu

Variable PC1 PC2

Focal velocity 0·434 0·415Fastest velocity within 30 cm 0·691 �0·105Depth �0·579 0·183Substratum �0·001 0·885Variation explained (%) 37·0 25·7

10 . . .

their survival and longer-term recruitment. Overall, abundance of giant kokopuwas lower in Boundary Creek, the stream supporting the least habitat diversity ofthe three streams studied. Shallow backwater habitats preferentially selected byjuveniles in Alex and Cullen’s Creeks were poorly represented in BoundaryCreek, and giant kokopu <100 mm LT were not observed in this stream. Such apattern suggests that juveniles may be limited by a lack of suitable habitat inBoundary Creek. Giant kokopu are conspicuously absent from the low gradient,downstream reaches of the small streams that flow across the Taieri Riverfloodplain, including the lower reaches of the three study streams (David &Closs, 2001). Most of these streams have been channelized and retain little or nochannel complexity or cover, hence providing few of the microhabitats selectedby giant kokopu in this study. Elsewhere, giant kokopu remain abundant in lowgradient streams where instream cover and channel complexity remain(McDowall, 1990; Chadderton & Alibone, 2000). Such a pattern suggests thatrestoration of instream microhabitat heterogeneity may have the potential torestore giant kokopu populations to areas in which they were previouslyabundant.

This research was funded by the Barry Jonassen Award from the Australian Society forFish Biology. Sincere thanks to S. Bennett, K. Blakemore, A. Dopheide, R. Goldsmith,S. Ledington, K. McKenzie, T. Murray, D. Shanahan and J. and J. Whitehead forassisting with the fieldwork. Comments from R. Stoffels greatly improved earlier draftsof this paper. This research was conducted under a University of Otago Animal EthicsPermit.

References

Baltz, D. M. & Moyle, P. B. (1984). Segregation by species and size class of rainbowtrout and Sacramento sucker in three Californian streams. Environmental Biologyof Fishes 10, 101–110.

Baltz, D. M., Vondracek, B., Brown, L. R. & Moyle, P. B. (1991). Seasonal changes inmicrohabitat selection by rainbow trout in a small stream. Transactions of theAmerican Fisheries Society 120, 166–176.

Bonnett, M. L. (2000). Critical Habitat Features of Giant Kokopu, Galaxias argenteus(Gmelin 1789). Christchurch: University of Canterbury.

Bresmet, G. & Berg, O. K. (1999). Three-dimensional microhabitat use by youngpool-dwelling Atlantic salmon and brown trout. Animal Behaviour 58, 1047–1059.

Chadderton, L. W. & Alibone, R. M. (2000). Habitat use and longitudinal distributionpatterns of native fish from a near pristine Stewart Island, New Zealand, stream.New Zealand Journal of Marine and Freshwater Research 34, 487–499.

Clarke, K. R. (1993). Non-parametric multivariate analyses of changes in communitystructure. Australian Journal of Ecology 18, 117–143.

Clarke, K. R. & Green, R. H. (1988). Statistical design and analysis for a ‘biologicaleffects’ study. Marine Ecology Progress Series 46, 213–226.

Clarke, K. R. & Warwick, R. M. (1994). Changes in Marine Communities: An Approachto Statistical Analysis and Interpretation. Plymouth: National EnvironmentResearch Council.

David, B. O. (2002). Ecology of Giant Kokopu. Dunedin: University of Otago.David, B. O. & Closs, G. P. (2001). Continuous remote monitoring of fish activity with

restricted home ranges using radiotelemetry. Journal of Fish Biology 59, 705–715doi:10.1006/jfbi.2001.1684.

Facey, D. E. & Grossman, G. D. (1992). The relationship between water velocity,energetic costs, and microhabitat use in four North American stream fishes.Hydrobiologia 239, 1–6.

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Fausch, K. D. (1984). Profitable stream positions for salmonids: relating specific growthrate to net energy gain. Canadian Journal of Fisheries and Aquatic Sciences 62,441–451.

Fraser, N. H. C., Metcalfe, N. B. & Thorpe, J. E. (1993). Temperature-dependant switchbetween diurnal and nocturnal foraging in salmon. Proceedings of the RoyalSociety of London B 252, 135–139.

Fraser, N. H. C., Heggenes, J., Metcalfe, N. B. & Thorpe, J. H. (1995). Low summertemperatures cause juvenile Atlantic salmon to become nocturnal. CanadianJournal of Zoology 73, 446–451.

Greenberg, L. A., Svendsen, P. & Harby, A. (1996). Availability of microhabitats andtheir use by brown trout (Salmo trutta) and grayling (Thymallus thymallus) in theRiver Vojman, Sweden. Regulated Rivers: Research and Management 12, 287–303.

Hayes, J. W., Leathwick, J. R. & Hanchet, S. M. (1989). Fish distribution patterns andtheir association with environmental factors in the Mokau River catchment, NewZealand. New Zealand Journal of Marine and Freshwater Research 23, 171–180.

Heggenes, J. (1988). Effect of experimentally increased intraspecific competition onsedentary adult brown trout (Salmo trutta) movement and stream habitat choice.Canadian Journal of Fisheries and Aquatic Sciences 45, 1163–1172.

Heggenes, J. (2002). Flexible summer habitat selection by wild, allopatric brown trout inlotic environments. Transactions of the American Fisheries Society 131, 287–298.

Heggenes, J., Krog, O. M. W., Lindas, O. R., Dokk, J. G. & Bremnes, T. (1993).Homeostatic behavioural responses in a changing environment: brown trout(Salmo trutta) become nocturnal in winter. Journal of Animal Ecology 62,295–308.

Heggenes, J., Bagliniere, J. L. & Cunjak, R. A. (1999). Spatial niche variability for youngAtlantic salmon (Salmo salar) and brown trout (S. trutta) in heterogeneousstreams. Ecology of Freshwater Fish 8, 1–21.

Hill, J. & Grossman, G. D. (1993). An energetic model of microhabitat use for rainbowtrout and rosyside dace. Ecology 74, 685–698.

Hughes, N. F. & Dill, L. M. (1990). Position choice by drift-feeding salmonids: modeland test for Arctic grayling Thymallus articus in subartic mountain streams,interior Alaska. Canadian Journal of Fisheries and Aquatic Sciences 49, 1994–1998.

Jackson, D. A., Peres-Neto, P. R. & Olden, J. D. (2001). What controls who is where inthe freshwater fish communities—the roles of biotic, abiotic, and spatial factors.Canadian Journal of Fisheries and Aquatic Sciences 58, 157–170.

Jellyman, D. J. (1979). Observations on the biology of the giant kokopu, Galaxiasargenteus (Gmelin 1789). Mauri Ora 7, 53–61.

Jenkins, T. M. (1969). Social structure, position choice and microdistribution of twotrout species (Salmo trutta and S. gairdneri) resident in mountain streams. AnimalBehaviour Monographs 2, 56–123.

Matthews, W. J. (1998). Patterns in Freshwater Fish Ecology. Amsterdam: KluwerAcademic Publishers.

McCullough, C. D. (1998). Abundance, Behaviour, and Habitat Requirements ofthe Nocturnal Banded Kokopu (Galaxias fasciatus) Gray (Pisces: Galaxiidae).Hamilton: University of Waikato.

McDowall, R. M. (1990). New Zealand Freshwater Fish: A Natural History & Guide.Auckland: Heinemann-Reed.

Metcalfe, N. B., Fraser, N. H. C. & Burns, M. D. (1999). Food availability andnocturnal vs. diurnal foraging trade-off in juvenile salmon. Journal of AnimalEcology 68, 371–381.

Moore, S., Alibone, R. M. & Townsend, C. R. (1999). Spawning site selection bytwo galaxiid fishes, Galaxias anomalus and G. depressiceps, in tributaries of theTaieri River, South Island, New Zealand. New Zealand Journal of Marine andFreshwater Research 33, 129–139.

Moyle, P. B. & Vondracek, B. (1985). Persistence and structure of the fish assemblage ina small California stream. Ecology 66, 1–13.

12 . . .

Pert, E. J. & Erman, D. C. (1994). Habitat use by adult rainbow trout under moderateartificial fluctuations in flow. Transactions of the American Fisheries Society 123,913–923.

Quinn, G. P. & Keough, M. J. (2002). Experimental Design and Data Analysis forBiologists. Cambridge: Cambridge University Press.

Rasmussen, A. G. (1990). Certain Aspects of the Biology of a Landlocked Population ofGiant Kokopu (Galaxias argenteus, Gmelin 1789). Dunedin: University of Otago.

Roscoe, J. T. & Byars, J. (1971). Sample size restraints commonly imposed on the use ofthe chi-square statistic. Journal of the American Statistical Association 66,755–759.

Sagar, P. (1993). Habitat use and models of abundance of maturing inanga in SouthIsland, New Zealand, streams. New Zealand Freshwater Miscellaneous Report104.

Schlosser, I. J. (1987). The role of predation in age- and size-related habitat use bystream fishes. Ecology 68, 651–659.

Smith, J. & Li, H. (1983). Energetic factors influencing foraging tactics of juvenilesteelhead trout, Salmo gairdneri. In Predators and Prey in Fishes (Noakes, D. L.,Lindquist, D., Helfman, G. & Ward, J., ed.), pp. 173–180. The Hague: Dr. WJunk.

Sokal, R. R. & Rohlf, F. J. (1995). Biometry. San Francisco: Freeman.Vondracek, B. & Longanecker, D. R. (1993). Habitat selection by rainbow trout

(Onchyrynchus mykiss) in a California stream: implications for the instream flowincremental methodology. Ecology of Freshwater Fish 2, 173–186.

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