New Zealand Freshwater Fish Database (NZFFD). (McDowall ... preservation of New Zealand fish fauna. ..... were for longfinned eels and torrentfish, the worst.
New Zealand Journal of Marine and Freshwater Research, 1996: Vol. 30: 239—255 0028-8330/96/3002-0239 $2.50/0 © The Royal Society of New Zealand 1996
239
Distribution and abundance of freshwater fish in New Zealand rivers
I. G. JOWETT J. RICHARDSON National Institute of Water & Atmospheric Research Ltd P.O. Box 11-115 Hamilton, New Zealand Abstract The distribution and abundance of fish at sites in 38 medium to large New Zealand rivers were examined. Fish density varied from 5 to 200 fish per 100 m2, with an average of 53 fish. Our study sites contained a greater species richness and abundance than records stored on the New Zealand Freshwater Fish Database, where the average density was 28 fish per 100 m2. The average number of species at the study sites was 5, compared to 3 in the national database. Comparison of first-pass catches with multiple-pass population estimates showed that there was no difference in capture probability between species and that on average 51% of the population was captured on the first pass. The diadromous habit of many native species, and their ability to penetrate inland, was an overwhelming influence on their distribution. There was little regional variation in species composition, apart from the presence or absence of three nondiadromous species. Two distinct fish communities were evident: lowland and upland. Lowland communities typically contained the highest density and diversity offish, whereas upland communities were dominated by one or two species. Many river sites were intermediate between lowland and upland, both in species composition and fish density, and showed a gradual reduction in abundance and change in community structure with elevation, as those fish less able to penetrate inland disappeared and non-diadromous species began to appear. Elevation was the most important discriminating factor, with physical habitat and
M95042 Received 3 July 1995; accepted 6 December 1995
catchment variables less important. Fish densities were highest in gravel substrate of 50 mm or finer, and the amount of run and pool habitat may have influenced species composition. The relationships between catchment variables and species distribution and abundance were probably a reflection of geographical location. Keywords native fish; abundance; community; distribution; land use; habitat INTRODUCTION Most detailed studies of New Zealand freshwater fish communities have occurred in confined geographical areas and in small headwater streams, and have associated local variations in fish community composition and abundance with land use. For example, Hanchet (1990) and Swales & West (1991) found that removal of native forest negatively affected the distribution and abundance of most species of large galaxiid in tributaries of the Waikato River. Graynoth (1979) reported that logging of exotic forests in Nelson reduced the abundance of dwarf galaxias, and Taylor (1988) suggested that at least five other species were potentially sensitive to logging operations because of their association with sediment-free, clear-water habitats in south Westland. Other studies have suggested that two introduced species, brown and rainbow trout, may limit the abundance of native fish through competition for food in Canterbury rivers (Cadwallader 1975; Sagar & Eldon 1983), by predation in tributaries of the Taieri River (Townsend & Crowl 1991), or by a combination of both in Lake Taupo spawning streams (Kusabs & Swales 1991). Glova et al. (1985) suggested that the frequency and severity of floods might account for differences in abundance in a study of braided Canterbury rivers. Hayes et al. (1989) and McDowall (1993) proposed that the diadromous habit of most New Zealand species—most undertake two obligatory journeys between the sea and fresh water (McDowall
240
New Zealand Journal of Marine and Freshwater Research, 1996, Vol. 30
1990)—was the most important factor influencing fish communities in rivers and streams. The only large-scale study was by Minns (1990), who performed a cluster analysis and discriminant analysis on presence/absence data from the NIWA New Zealand Freshwater Fish Database (NZFFD) (McDowall & Richardson 1983). He expected variables such as indigenous forest and scrub to emerge as positive factors, giving evidence of the impact of land-use changes on native species, but concluded that the patterns of linkages that he found between species and variables were coincidences of geography. Nevertheless, he reported that both land-use changes and introductions of exotic species have caused changes in the distribution of native fish species, and that measures of habitat suitability might help resolve further questions of cause and effect critical to the preservation of New Zealand fish fauna. Our purpose was to compare fish communities in medium to large rivers on a national scale and to identify the physical, geographical, and biological factors associated with these communities. An important component of this study was the assessment offish abundance at sampling sites. In order to compare fish densities between sampling sites on a broad scale and to minimise small-scale differences in habitat between sites, we developed a habitat stratified sampling procedure. We evaluate the utility of this procedure by comparing habitataveraged fish densities with estimates offish density determined by the average density in the sampling area and the removal method using multiple-pass electrofishing.
METHODS Study sites Mosley (1992) classified river gauging sites based on their morphology and found that most rivers meandered within a wide shingle bed while following a relatively steep, straight course to the sea. Small, steep tributaries with coarse substrate and bankside vegetation accounted for less than 20% of New Zealand river gauging sites. Our sampling sites were typical of New Zealand rivers, as defined by Mosley (1992), and were located in 17 South Island and 21 North Island rivers selected from the "100 rivers" database (Biggs et al. 1990), to provide a range of rivers on the east and west coasts of both main islands (Fig. 1). The catchment area of the study sites varied from 38 km2 to 1760
km2, considerably larger than the small streams often studied—e.g., in Graynoth (1979), Hanchet (1990), Swales & West (1991), and Townsend & Crowl (1991)—so that results from this study do not necessarily apply to first- and second-order streams. Most rivers were located in one of seven localised regions (Fig. 1); east or west coast South Island, Nelson/Marlborough, Wellington, Wairarapa, Hawkes Bay, or Taranaki. General characteristics of the rivers are shown in Table 1. Sites were down stream of any major dams or waterfalls, so that the abundance of diadromous species was not influenced by lack of free access to the sea. All sites had good hydrological records from which flow statistics were calculated. In-stream habitat survey data were available for all study rivers. These described the morphology of the river at the fish sampling site, and included at least one pool/run/riffle sequence. Procedures for the collection and analysis of in-stream habitat data are given in Jowett (1990). Catchment data on rock type, topography, land use, soil type, and erosion status were taken from the national land resources inventory (NWASCO 1975-79). These variables were expressed as percentages of the total catchment area and are described more fully in Biggs et al. (1990). Site locations were described by map coordinates (NZMS 260 1:50 000) and island: either North or South Island. Fish abundance In each river, two runs and two riffles within about 3 km of each other were fished. Pools were not sampled because trial expeditions (NIWA unpubl. data) and other studies (Richardson & Jowett 1995) showed that comparatively few of the smaller native fish were present in pools because the combination of fine substrate with deep water provided unsuitable habitat (Jowett & Richardson 1995). Distribution data were therefore most efficiently obtained by sampling runs and riffles. Stratified sampling reduces the effort required to establish estimates offish abundance, minimises sampling bias caused by habitat differences between sites, and allows comparison of abundance data between rivers without the confounding influence of habitat differences due to river size. In this study, our sampling locations were stratified by depth within runs and riffles because most native fish species have well-defined depth and velocity preferences (Jowett & Richardson 1995) and variation in habitat would cause large variations in
Jowett & Richardson—Distribution and abundance of NZ freshwater fish Fig. 1 Location of sampling sites in New Zealand. The size of the circle represents the total number offish captured at the site.
241
N
North Island Waikato
Hawkes Bay 40° S
Wairarapa
- 45° S
fish abundance. Depth, rather than velocity, was selected as the primary stratification variable because fish movements during a flood suggested that the distribution offish was more closely related to depth than velocity (Jowett & Richardson 1994). Lanes with relatively uniform hydraulic characteristics were marked by placing weighted ropes at depths of 0.125, 0.25, and 0.5 m. Rivers were initially sampled to a maximum depth of 0.75 m, but subsequent analysis (Jowett & Richardson 1995) showed that fish abundance was low at depths greater than 0.5 m. Sampling was subsequently carried out to a maximum depth of 0.5 m, or to the centre of the river if the river was shallower than 0.5 m. A lane length of 15 m was selected to maximise the area sampled and yet limit the
South Island
variation in depth and velocity within the lane. Fish disturbed while marking lanes usually darted into the substrate without any significant shift in location. When electrofishing, a fish would occasionally dart into another lane. These fish were captured and recorded as originating from the lane in which they were first seen. Each lane was sampled by downstream singlepass electrofishing using a team of three people with either a back-pack or bank-based 350 W generator-powered electric fishing machine operated at 150 to 300 V (depending on the conductivity). Fish were caught either in scoop nets or a downstream stopnet. The number, total weight, and species of fish caught were recorded. The width of each lane was measured at three points
Table 1 Site characteristics and habitat-averaged fish densities (no. per 100 m2) from depth stratified single-pass electrofishing of runs and riffles. Diadromous fish species are marked with a hatch (#). The key to fish species abbreviations is shown in Table 4.
River Akatarawa Baton Esk Grey Hakataramea Hutt Inangahua Kakanui Kapuni Kauaeranga Kaupokonui Maerewhenua Mangahao Mangatainoka Mangles Motueka Ohau Opihi Orari Oroua Otaki Pauatahanui Pelorus Pohangina Rai Riwaka Ruamahanga Selwyn Stony Taipo Takaka Tutaekuri Waimana Waingawa Waiongona Waiohine Wairoa Wanganui
Elevation (ma.s.l.)
Distance (km)
120 85 10 130 210 80 200 2 60 15 145 220 90 90 230 85 90 20 280 90 70 5 25 90 25 60 85 290 70 130 95 20 130 115 105 110 25 240
31 41 6 62 66 27 91 4 5 8 15 55 132 130 115 40 24 9 43 94 15 1 22 116 24 8 106 80 5 43 34 16 68 109 15 100 14 278
Median Mean discharge substrate (m3 s-r) size (mm) 7.7 7.2 5.9 55.9 6.1 22.1 15.7 5.5 1.7 6.6 3.1 2.9 14.9 17.5 9.8 61.3 6.0 19.0 8.9 11.1 29.8 0.7 21.3 17.3 12.2 2.4 9.7 3.4 6.2 43.6 15.0 17.5 8.1 11.2 26.2 2.6 15.8 22.8
81.3 96.1 20.7 110.5 51.0 111.1 100.1 47.0 48.2 88.1 129.1 78.5 52.5 37.0 71.0 105.3 57.1 48.6 71.5 39.4 58.5 28.1 86.4 43.6 52.9 109.5 44.5 51.3 148.0 64.3 108.4 21.2 91.9 55.7 147.4 73.8 62.0 70.7
LF#
SF#
TF#
BG#
RF#
CB«
UPL
CR
VUL
BT
Other
Total
1.3 1.9 2.3 4.6 0.0 2.7 2.7 10.9 40.2 3.6 5.0 0.0 5.3 4.9 2.5 6.1 0.3 0.2 0.0 2.7 20.5 20.9 0.9 0.5 0.9 8.4 45.9 0.5 7.5 0.2 3.2 3.7 25.4 16.0 15.0 9.3 22.1 3.3
1.8 0.4 28.3 0.0 0.0 0.3 0.0 1.8 2.4 21.1 3.2 0.0 7.8 2.9 0.0 1.1 0.0 9.3 0.0 3.7 0.3 32.1 0.1 5.5 0.8 0.2 10.7 0.0 0.0 0.0 0.1 72.9 1.5 2.2 2.5 1.3 0.0 1.9
0.0 1.2 25.8 0.5 0.0 0.0 0.1 3.3 10.2 3.0 0.0 0.0 6.9 0.2 0.0 1.6 0.6 17.6 0.0 4.3 16.8 0.0 0.0 2.1 0.3 0.5 19.5 0.0 1.0 0.6 0.0 5.6 0.6 7.1 0.0 15.3 4.5 0.0
35.0 1.7 2.3 4.6 0.0 6.8 0.0 204.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 180.8 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 0.0
30.3 0.1 0.0 1.6 0.0 21.7 0.0 0.3 3.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 8.6 0.0 0.0 0.0 8.3 29.7 0.0 0.0 0.0 0.1 0.3 0.0 6.3 0.0 0.0 0.0 1.7 0.1 2.3 21.7 0.5 0.0
0.0 0.0 79.4 0.0 1.3 0.7 0.0 19.6 0.0 0.0 0.0 0.0 15.6 0.0 0.0 0.0 0.0 35.7 0.0 0.0 0.2 3.3 0.0 2.1 0.0 0.0 0.3 0.0 0.0 0.0 0.0 42.8 0.0 0.0 0.0 0.8 0.0 0.0
0.0 5.0 0.0 0.0 15.8 0.0 5.2 0.0 0.0 0.0 0.0 45.7 20.7 68.9 8.1 4.4 3.6 8.2 25.6 20.1 0.0 0.0 10.2 2.5 74.6 0.0 0.6 44.8 0.0 0.0 3.7 0.0 0.0 2.5 0.0 0.0 3.6 0.0
0.5 0.0 0.0 0.0 0.0 0.8 0.0 0.0 0.0 6.6 0.0 0.0 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.2
0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 23.6 0.0 0.0 0.0 0.0 0.0 0.4 38.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 28.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4.1 3.0 0.0 0.7 1.3 2.6 1.1 0.0 0.0 0.0 0.2 1.1 0.4 0.0 1.8 0.7 0.5 0.0 0.4 0.0 0.0 0.0 0.6 4.2 0.2 1.3 0.6 2.0 0.0 3.6 2.6 0.0 0.0 0.5 0.0 0.0 0.5 0.2
0.0 0.1 0.0 0.3 5.7 0.0 0.0 0.1 1.0 3.5 0.0 1.7 0.0 0.0 0.0 0.3 1.6 0.0 0.0 0.4 0.0 31.2 0.0 0.0 0.9 0.0 0.0 0.0 2.3 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.1 0.0
73.0 13.4 138.1 12.3 24.3 35.6 9.1 240.1 56.9 37.8 8.4 72.1 57.5 76.9 12.4 14.2 16.0 252.2 64.2 31.2 46.1 117.2 11.8 16.9 77.9 10.5 77.9 75.7 17.1 4.5 9.6 125.6 29.2 28.4 19.8 48.4 31.3 7.6
2; a
N 5
g. g 3
2
CD
3
Jowett & Richardson—Distribution and abundance of NZ freshwater fish along its length and the area fished was calculated as the average width times the lane length. The elevation of each site and its distance from the sea were measured from 1 : 50 000 topographical maps. The average gradient between the site and sea was calculated. Substrate size in each run and riffle was measured by the Wolman walk method (Wolman 1954). The median substrate size (dso) and substrate grading ratio (the ratio of the d)5 to d85 sizes) were calculated. Fish densities in the study rivers were compared to fish densities extracted from the NZFFD (McDowall & Richardson 1983) to determine whether fish densities in the study rivers were representative of New Zealand rivers. The NZFFD was searched for all records where fish numbers had been determined by single-pass electric fishing areas similar in size to the areas fished at the study sites. Records were excluded if the area fished was less than 50 m2 or more than 2000 m2. Sites upstream of downstream obstacles were excluded and multiple records at the same location were combined. Analysis The relationship between fish numbers collected in a single electrofishing pass and population estimates was determined for each species present by multiple-pass electrofishing in seven of the study rivers. The probability of capture,/?, is the fraction of the fish population caught by unit effort: p=l- U2IU\ where U\ is the number offish captured on the first pass and U2 the number captured on the second pass. Population estimates were calculated after three replicate passes using maximum likelihood formulas given by Otis et al. (1978). Capture probabilities were compared between species to determine whether single-pass fishing data would contain any species bias. Population estimates were compared to fish numbers captured on the first pass using Spearman rank correlation, to assess the ability of single-pass electrofishing to rank sites in order of abundance correctly. The numerical relationship between single-pass and multiple-pass estimates and confidence limits on the predictions were calculated by Pearson correlation. Fish densities were calculated by two methods: the average density in the total area electrofished per site, and the average of the fish densities in each habitat stratified sampling lane. Because the lanes were stratified by depth and velocity, the
243
average fish density in each lane and river was independent of the amount of each habitat type in the river. Thus, habitat-averaged estimates of fish density are not necessarily measures of total population density because they have not been adjusted for the proportions of each habitat type. Water deeper than 0.5 m and pools were not sampled so fish densities, especially for larger fish such as eels and brown trout, are not necessarily true averages for a river. However, these data are comparable with those from the NZFFD because total river populations are rarely sampled or estimated, except in small streams where depths are less than 0.5 m. Spearman rank correlation was used to identify relationships between the density of different species to test whether interspecific interactions were influencing fish abundance. Similarly, Spearman rank correlation was used to identify relationships between fish density and environmental variables. The relationship between fish communities (composition and abundance) and river characteristics and land use was examined by first identifying groups of rivers that contained similar fish assemblages using cluster analysis, and then identifying the variables that differed between groups by univariate analysis of variance and discriminant analysis. We used the TWINSPAN programme (Hill 1979) for cluster analysis (to three levels of subdivision with five pseudospecies at cut levels of 0, 10, 20, 30, and 40 fish per 100 m2; univariate non-parametric analysis of variance to identify variables that differed significantly between the TWINSPAN groups; and discriminant analysis to investigate multivariate relationships (Klecka 1980). Where necessary, square root transforms were used so that frequency distributions were approximately normal. Stepwise discriminant analysis (SAS 1985) identified an initial set of variables. Separate models were developed using six or fewer variables describing site (physical and hydrological) and land use (catchment), so that the influence of land use and physical factors on distribution could be compared.
RESULTS Comparison of single- and multiple-pass electrofishing In the seven rivers sampled by multiple-pass electrofishing, only nine species were present and
New Zealand Journal of Marine and Freshwater Research, 1996, Vol. 30
244
250
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100
1 150
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100
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10
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10
100
1000
50
0
50
100
150
200
250
Habitat averaged fish density
First pass Fig. 2 Comparison of fish density per species (per 100 m2) from the first electrofishing pass and the population estimated from three electrofishing passes. The 95% confidence intervals on the regression line are shown as solid lines and the 95% prediction intervals are shown as dashed lines.
Fig. 3 Comparison of habitat-averaged fish density per species (per 100 m2) with the average fish density over the entire area sampled per site, plotted with the linear regression line.
there were sufficient numbers of only six species for comparison of population estimates with fish numbers captured on the first pass. Multiple-pass electrofishing showed that the average probability of capture was greater than 0.5 for all nine species (Table 2), indicating that reliable population estimates could usually be obtained (Armour et al. 1983). However, for all species except torrentfish, common bully, and brown trout, there were occasions when it was not possible to obtain a
population estimate after three passes, because more fish were caught in a later pass than in an earlier pass. This only occurred when less than five fish were captured in total. Analysis of variance showed that there were no significant differences between average capture probabilities for any of the species (F = 0.77; P = 0.67); thus single-pass electric fishing was not biased towards any of the six species. Rank correlation coefficients between fish numbers of the first pass and the total population estimate were high, with significant relationships (P < 0.05) in all instances. The best correlations were for longfinned eels and torrentfish, the worst for upland bully. To establish the confidence limits of population estimates from single-pass data, the number of each species of fish captured on the first pass was regressed against the population estimate (Fig. 2). Three data points were excluded because the probability of capture was less than 0.2 and the population estimate was therefore very unreliable (Armour et al. 1983). The equation relating population estimate to first pass density was: Population density = 1.96 x (first-pass density)1 °28. Thus, on average, 51% of the estimated fish population was captured on the first pass. The upper prediction interval with 95% confidence was about 2.4 times the first pass catch (Fig. 2).
Table 2 Multiple-pass electric fishing results; average probability of capture for different species and Spearman rank correlation of population estimates and fish numbers caught on the first pass. *, P < 0.05; **,P 75 mm. There were significant differences in total fish
Table 3 Variation in average fish density with median substrate size (mm) and probability that there is no significant difference (Mann-Whitney U-test) between substrate categories. Median substrate size Species Longfinned eel Shortfmned eel Torrentfish Bluegilled bully Redfmned bully Common bully Upland bully Cran's bully G. vulgaris Brown trout All species
< 45 mm (N=l)
45—75 mm (N=\6)
> 75 mm (,V=15)
P
11.6 22.3 8.2 0.4 4.3 18.3 0.0 13.2 0.0 0.7 83.5
8.3 1.7 5.2 24.1 2.7 4.6 0.2 13.0 4.2 0.7 65.1
5.9 2.2 0.6 3.2 4.3 0.1 0.5 5.0 1.6 1.2 24.9
0.739 0.001 0.041 0.988 0.649 0.005 0.458 0.420 0.177 0.208 0.007
Table 4 Spearman rank correlation coefficients offish densities for 10 common fish species at 38 sites in the lower half of the matrix and only for sites where species co-existed in the upper half. —, fewer than 5 sites with cooccurrence. *, significant (P < 0.05) correlation. Species code Common name LF SF TF BG RF CB UPL CR VUL BT Total
Longfinned eel Shortfmned eel Torrentfish Bluegilled bully Redfinned bully Common bully Upland bully Cran's bully G. vulgaris Brown trout All species
LF
SF 0.09
0.36* 0.40* -0.26 0.51* 0.05 -0.51' -0.04 -0.56* -0.49* 0.07
TF
BG
0.32 0.20 0.45 0.05 0.45* ^ . 0.40 \ 0.14 0.11 -0.04 0.12 0.23 0.51* 0.44* 0.34* -0.27 -0.19 -0.17 0.23 -0.13 0.12 -0.25 -0.30 -0.03 -0.52* -0.43* 0.03 0.47* 0.37 0.36
RF
CB
-0.24 0.13 0.14 0.20
-0.52 0.62* 0.03 -O.60 0.31
0.05 -0.57* 0.03 -0.33* -0.15 0.12
UPL
CR
0.70 -0.33 _ -0.16 — -0.44 0.10 0.50 -0.18 ^ \ 0.04 -0.20 ^ \ 0.06 0.51* -0.15 -0.25 0.26 0.08 0.57* 0.12 0.01
VUL _ _ — 0.50 0.14 0.30
BT -0.45* -0.24 -0.21 0.83 0.35 -0.10 -0.17 _ -0.44*
247
Jowett & Richardson—Distribution and abundance of NZ freshwater fish Fig. 6 Dendrogram of TWINSPAN classification of fish species.
1 I
1
1
Blueg lied bully Redfinned bully
Longfinned eel Shortfinned ee Cran's bully Common bully Torrentfish
Fig. 7 Dendrogram of TWINSPAN classification of study sites and indicator species.
Brc
n trout
G. vuIgaris Upland bully
1 1
1
Group 1
I
Brown trout 1
I
Esk Kakanui Tutaekuri Opihi
i Group 2
1 Longfinned eel
1
1 Baton Ohau Taipo Akatarawa Grey Hutt Riwaka Wanganui Pohangina Takaka Inangahua Motueka Kaupokonui
1 Group 3
G OUp4
G. 1 vulgaris
1 bully Common 1 Kapuni Kauaeranga Pauatahanui Otaki Stony Waimana Waiohine Ruamahanga Waingawa Wairoa Waiongona
i Grot p 5
Mangles Pelorus Mangahao Mangatainoka Oroua Rai
1 Hakataramea Maerewhenua Orari Selwyn
density between each of these substrate categories as well as densities of shortfinned eels, common bully, and torrentfish (Table 3). The relationship between fish densities and substrate size was not a function of distance from the sea because substrate size did not vary significantly with elevation (Spearman r = 0.300, P > 0.05).
Upland bully and G. vulgaris were positively related. When fish densities were compared for those sites that contained coexisting species, there was a positive relationship (P < 0.05) between the densities of shortfinned eels and common bully and a negative relationship between brown trout and longfinned eels (Table 4).
Inter-specific relationships Spearman rank correlations between species densities showed the relationships between the groups of diadromous and non-diadromous fish (Table 4). The density of common bully was positively related to total fish density as well as to the density of shortfinned eels, torrentfish, and bluegilled bully. The density of longfinned eels was positively related to that of shortfinned eels, torrentfish, and redfinned bully, but negatively related to the density of upland bully, G. vulgaris, and brown trout. The density of brown trout was negatively related to total fish density as well as to the density of shortfinned eels and torrentfish.
TWINSPAN classification of fish assemblages Four fish species associations were identified (Fig. 6). These association groups were formed of nondiadromous inland species (upland bully and G. vulgaris), an exotic species (brown trout), and two mainly diadromous groups—one consisting of two bully species that are usually found close to the coast (redfinned bully, bluegilled bully) and the other of species that are more widespread (longfinned and shortfinned eels, torrentfish, common and Cran's bully) (McDowall 1990). Initial classification of the sampling sites separated upland sites from lowland sites (Fig. 7). Examination of the TWINSPAN indicator species
New Zealand Journal of Marine and Freshwater Research, 1996, Vol. 30
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upland bully, whereas Group 5 were South Island rivers that contained few species other than upland bully and G. vulgaris. The separation into Group 1 and Groups 2 and 3 used common bully as the primary indicator species. Group 1 sites contained high numbers of most species, especially common and bluegilled bully. The indicator species for Groups 2 and 3 were longfinned eels and brown trout, with Group 2 containing longfinned eels in abundance and Group 3 sites containing brown trout.
and average fish densities in each group characterised differences between the groups. The primary division was based on upland bully as the indicator species and defined the separation between upland and lowland sites. The lowland sites (Groups 1, 2, and 3) contained a wide range of species, whereas the upland sites (Groups 4 and 5) contained upland bully and few other species except G. vulgaris (Table 5). The separation into Groups 4 and 5 was based on the presence of G. vulgaris. Group 4 contained both species of eel and high numbers of
Table 5 Average fish densities (no. per 100 m2) in each of the TWINSPAN fish assemblages. Densities of indicator species are shown bold. Twinspan group and indicator species Species Longfinned eel Shortfinned eel Torrentfish Bluegilled bully Redfinned bully Common bully Upland bully Cran's bully G. vulgaris Brown trout Total fish density
1 (N=4)
2 (7V=11)
3 (N=13)
4 (N=6)
5 (N=4)
4.3 28.1 13.1 96.9 0.1 44.4 2.1 0.0 0.1 0.0 189
20.6 6.7 7.1 0.0 6.7 0.4 0.6 0.6 0.0 0.1 46
3.1 1.1 0.6 3.7 4.8 0.2 1.9 0.2 0.0 1.9 18
2.9 2.6 2.0 0.0 0.0 2.6 33.7 0.1 0.0 0.5 44
0.1 0.0 0.0 0.0 0.0 0.3 33.0 0.0 22.6 1.2 59
Table 6 Mean site and catchment characteristics with significant differences between TWINSPAN fish assemblages. Island = 1 for North Island, 2 for South Island, latitude and longitude are in NZMS 260 map coordinates (100 km). Kruskal-Wallis, *,P< 0.05; **, P < 0.01; ***, P < 0.001.
Variable Elevation*** Distance* Island* Longitude* Latitude* Local stream gradient** Percentage boulder** Percentage gravel** Substrate size* Substrate d50** Percentage pool* Percentage run** Rolling land* Tussock** Forest** Variability of mean annual flood*** Runoff (my- 1 )***
1 (N=4)
Study site grouping 2 3 4 (7V=11) (/V=13) (N=6)
13 8.8 1.5 26.0 59.0 2 1 54 41.3 34.4 41 45 40 39 7
72 40.5 1.1 26.8 61.4 6 21 27 138.7 76.9 54 32 11 17 53
0.60 0.52
0.38 2.67
119 62.3 1.5 25.6 60.2 5 21 26 146.4 91.3 38 48 10 18 50 0.36 2.15
92 86.1 1.5 26.3 60.3 3 6 37 92.0 56.5 53 35 7 15 46 0.39 1.40
5 0V=4) 250 61 2 23.5 56.6 5 9 48 85.1 63.1 29 50 17 86 3 0.80 0.48
Jowett & Richardson—Distribution and abundance of NZ freshwater fish
249
Site characteristics of rivers in each group were examined to identify variables that discriminated between the different fish assemblages. Seventeen variables showed significant (P < 0.05) differences between groups (Table 6). The most significant differences (P < 0.001) were between site elevation, run-off, and variability of mean annual floods—all reflecting the geographical location of the site.
proportion of tussock and undeveloped grassland, little forest, and channels with gravel/cobble substrate. Group 4 sites were geographically more diverse than Group 5 and contained significantly less tussock grassland and less variation in mean annual flood than Group 5 sites. The elevations of the Group 4 sites were in the same range as those of the lowland Group 3 sites.
Lowland sites (Groups 1, 2, and 3) The average elevation of the lowland sites was 85 m above sea level, and ranged from 2 to 240 m a.s.l.; the average elevation of each group increased from Group 1 to Group 3. Fish abundance and diversity were highest at the Group 1 sites which were close to the east coast of both islands at low elevations. The elevation of Group 1 sites ranged from 2 to 20 m a.s.l. and a high percentage of their catchment was rolling land. The substrate size at Group 1 sites was markedly smaller than in other groups (Table 6). The average number of species per Group 1 site was 6. Group 2 sites also contained a diverse range of fish species, with an average of 5 species per site, and a lower level of abundance than Group 1 sites. Group 3 sites had a similar number of species to Group 2, but lower levels of abundance than either Group 1 or Group 2. The characteristics of Group 2 and 3 sites were similar. Sites of both groups had coarse substrate and a high percentage of the catchment in forest. Group 2 sites tended to be in the North Island and at lower elevations (KruskalWallis, P < 0.05) than Group 3 sites. Group 2 sites had more pool habitat, whereas Group 3 sites had more run habitat. In this instance, habitat refers to a river characteristic derived from habitat surveys of selected reaches and is not related to the habitat stratified sampling sites. Sites in Groups 2 and 3 could be described as mid-elevation sites with lowland fish assemblages, characterised by coarse substrate, and with over 50% of the catchment forested.
Discriminant analysis
Upland sites (Groups 4 and 5) Fish diversity was slightly lower at Group 4 and 5 upland sites than at lowland sites, with an average of 5 species per site at Group 4 sites and 4 species per site at Group 5 sites. The average elevation of the upland sites was 155 m a.s.l. and ranged from 25 to 290 m a.s.l. Group 5 sites were at an elevation of 210 to 290 m a.s.l. in inland South Canterbury/ North Otago; their catchments contained a high
Univariate analysis of variance (Table 7) showed that elevation was one of the most important discriminating factors. A discriminant model with this single variable correctly predicted 47% of the groups (Table 8). The discriminant equations can be used to determine elevation boundaries between groups, and thus suggest elevation ranges for the different groups. The elevation boundary between Group 1 and Group 2 sites was at 41 m a.s.l., the boundary between Group 2 and 3 at 100 m a.s.l., whereas the boundaries between Groups 3 and 4 and Group 5 overlapped at 185 and 171 m a.s.l., respectively. The other variables included by the stepwise analysis were North or South Island, distance from the sea, median substrate size, variability of mean annual floods, and percentage of run habitat at median flow. Although this analysis produced good separation between Groups 1 and 5, it did not discriminate well between Groups 2, 3, and 4. Stepwise analysis using these three groups alone suggested that run habitat, longitude, gradient, and distance from the sea were the best discriminators between these groups. Variables were eliminated by trial and error to form a model with six variables that had 84% classification success with all four roots significant (P < 0.05) (Table 9). Correlations between the discriminant factors and variables showed that the first factor was related to elevation and longitude, and the second factor was related to elevation and substrate size. This gave good separation between Groups 1,2, 3, and 5, but Group 4 overlapped Groups 2 and 3 (Fig. 8). Factors 3 and 4 separated Group 4 from the other groups, on the basis of gradient and substrate size (Table 9). Land-use variables also formed a good discriminant model. Percentage of tussock and undeveloped grassland was the most important discriminating variable, followed by elevation, distance from sea, variability of mean annual floods, and percentage rolling land. Percentage of tussock and undeveloped grassland discriminated well
New Zealand Journal of Marine and Freshwater Research, 1996, Vol. 30
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between Groups 1 and 5, contributing to the high correlation coefficient, but poorly between Groups 2, 3, and 4, so that its classification success was not as good as elevation (Table 8). Overall the result was similar to that of the previous model; stepwise selection of variables separated Groups 1 and 5 from the rest, but provided little separation of Groups 2, 3, and 4. A model of six variables, giving 84% classification success, was found by trial and error from the stepwise discriminators for all five Groups and Groups 2,3, and 4 alone (Table 9). Correlations between the discriminant factors and variables showed that the first discriminant factor was most closely related to the percentage of tussock and undeveloped grassland and elevation. The second factor was positively related to elevation and negatively related to percentage tussock. This discriminated well between Groups 1 and 5, but less so between Groups 2, 3, and 4 (Fig. 8).
DISCUSSION Survey techniques Comparison of single-pass electrofishing fish densities with multiple-pass population estimates showed that about half the estimated population is caught on the first pass. Prediction confidence limits (95%) for the population are between 1 and 2.4 times the first pass catch. Hayes & Baird (1994) compared electric fishing density estimates of juvenile brown trout and also found that approximately half the fish were caught on the first pass. Jones & Stockwell (1995) discuss the relative merits of multiple- and single-pass electric fishing and point out that that single-pass electric fishing can provide trout population estimates with measurable precision and that the variation in fish density between sites is often greater than the at-site sampling error. Using arguments similar to those of Hankin & Reeves (1988), they suggest that better assessments of populations will be achieved by increasing the coverage of the survey rather than the precision of the method. In this study, we used single-pass electric fishing to maximise the area surveyed and to obtain estimates of relative abundance at different sites rather than more precise population estimates. We also used a habitatstratified approach to ensure that we surveyed the same area of habitat at each site. Subsequent comparison of habitat-averaged densities with fish density over the whole sampling area showed that there was little difference between the two methods.
Jowett & Richardson—Distribution and abundance of NZ freshwater fish
251
result in differences in fish abundance and species composition. Species diversity and abundance This study has emphasised the well-known paucity of New Zealand freshwater fish fauna (McDowall 1990). Only 19 of the 27 native species were found in the 38 rivers surveyed, and only 9 of them could be classed as common. However, average species richness and abundance at our study sites was higher than the average in the NZFFD. An average of 5 species per study site, or 3 species per site in the NZFFD, is exceptionally low compared to numbers found in continental rivers (Mahon 1984). For example, Taylor (1969) notes 82 or more species in one small tributary of the Mississippi River in the central United States. Fish densities, by single-pass electrofishing, varied from 200 fish per 100 m2 at low elevation sites to < 10 at many inland sites. Comparison with multiple-pass electrofishing indicated that total fish populations were approximately double the single-pass figures. Common bullies were usually abundant where a large number of other diadromous species occurred. In a study of habitat preferences, Jowett & Richardson (1995) noted that the habitat preferences of common bully were intermediate between those of a fastwater guild (e.g., torrentfish and bluegilled bully) and an edge-dwelling guild (e.g., upland bully and G. vulgaris), and suggested that flow management strategies based on common bully habitat could provide a satisfactory compromise between the opposing flow requirements of the two guilds. The positive relationship between total fish abundance and common bully density lends support to this argument.
B
CM
Factor 1 Fig. 8 Scatter-plot for the first two discriminant functions. Locations of each site are identified by their group number. Bivariate ellipses enclosing + I SD are shown for each group. The upper plot, A, is the model with physical and hydrological variables, and B is the model including land-use variables.
However, fish density and species composition can vary considerably with depth (Jowett & Richardson 1995), suggesting that differences in habitat availability between sampling sites could
Minns (1990) examined species distribution by catchment and map sheet (NZMS 1—1 : 63 360) and found positive associations between brown trout and longfinned eels and between the diadromous species that were common at our study sites. His analysis showed that the patterns of distribution for non-diadromous brown trout and G. vulgaris differed from those of the diadromous species. He found that upland bully co-occurred with brown trout, G. vulgaris, torrentfish, and bluegilled bully. We found upland bully rarely associated with the latter two species, especially not with bluegilled bully. Most rivers in this study were typical New Zealand third- to fourth-order rivers containing a limited but relatively consistent range of fish species. Other New Zealand native fish species
New Zealand Journal of Marine and Freshwater Research, 1996, Vol. 30
252
may occupy different riverine habitats that were not included in our sites. For instance, a number of galaxiid species, such as koaro, banded kokopu, etc. appear to be more common in small tributary streams, with others, such as giant kokopu and inanga, in slow flowing lowland zones (McDowall 1990). Factors influencing distribution and abundance Classification of species composition readily separated upland from lowland sites. In New Zealand, elevation is probably the most important riverine variable, relating to flow variability, water quality, periphyton, benthic invertebrates (Biggs et al. 1990), and brown trout (Jowett 1992). Elevation, rather than distance from the sea or average gradient between the site and sea, appeared to limit the distribution of diadromous species. The distance inland and the elevation gained by diadromous species depends on their climbing ability and the gradient and obstacles in particular river systems. Obviously it was not possible to measure, map, or locate all potential barriers or deterrents to fish passage. Some large low-gradient
river systems, such as the Manawatu and Ruamahanga, allow diadromous species such as torrentfish to penetrate a long distance inland and reach reasonable altitudes. Other river systems are shorter and steeper and diadromous species are less common further inland. Hayes et al. (1989) studied a single river catchment with a limited number of species. They identified koaro, with its legendary climbing ability and preferred habitat of tumbling rocky streams (McDowall 1990) as forming an "upland" group by itself, a mid-elevation group dominated by longfinned eels, and a lowland group of inanga, torrentfish, and bullies. They found that elevation and distance from the sea were the variables most closely related to fish distribution. Minns (1990) used presence/absence data from the NZFFD to identify species assemblages. He found close associations between torrentfish and bluegilled bully, shortfinned and longfinned eels, inanga and common bully; and recognised that these were often distinct from upland species (e.g., upland bully, brown trout, and G. vulgaris). Percentage of tussock and undeveloped grassland was also an important discriminator of
Table 8 Average squared canonical correlation and percentage sites correctly predicted by stepwise discriminant analysis using (A) physical and hydrological variables and (B) including catchment variables. B
A Correlation coefficient
% sites correct
Elevation Distance Island Substrate d50
0.15 0.26 0.32 0.39
47 52 61 71
Mean annual flood variability Run habitat %
0.43 0.48
Variable
Correlation coefficient
% sites correct
0.16 0.28 0.33 0.35
26 58 63 63
68
Tussock % Elevation Distance Mean annual flood variability Rolling land
0.41
71
79
Run habitat %
0.47
71
Variable
Table 9 Correlation between discriminant factors and variables using (A) physical and hydrological variables only (B) including catchment variables. A Variable Elevation Distance Longitude Substrate d50 Gradient Run habitat %
Factor 1 -0.64 -0.20 0.41 -0.09 -0.05 -0.29
2 0.55 0.35 0.26 0.46 0.33 -0.34
3 0.14 -0.31 -0.01 0.66 0.60 0.35
4 0.04 -0.33 -0.01 -0.20 0.58 -0.52
B Variable Elevation Distance Island Tussock % Gradient Run habitat %
Factor 1 -0.33 -0.07 -0.19 -0.45 -0.04 -0.16
2 0.75 0.51 0.03 -0.52 0.11 -0.11
3 -0.09 0.15 0.49 -0.1 -0.61 0.59
4 -0.39 0.17 0.13 0.52 -0.62 -0.46
Jowett & Richardson—Distribution and abundance of NZ freshwater fish fish distribution. The high elevation Group 5 sites that contained G. vulgaris were located in North Otago and South Canterbury where tussock and undeveloped pasture is common; it is not clear whether there is any cause-and-effect relationship. Low elevation Group 1 sites also contained a relatively high percentage of tussock or undeveloped grassland, whereas the other sites had a high percentage of forest catchment. Biggs et al. (1990) found that the percentage tussock and undeveloped grassland was related to water quality and trout distribution and abundance. In this study, the percentage of developed pasture in catchments did not appear to relate to fish distribution or abundance, even though it was related to water quality, periphyton, invertebrates (Biggs et al. 1990), and brown trout (Jowett 1992). Minns (1990) developed discriminant models that correctly predicted the presence/absence of individual species with between 58% and 85% success. He used a wide variety of land-use variables for these models and although he expected that the presence of native forest might be an important factor showing the impact of land-use changes, he concluded that the linkages between species and variables were coincidences of geography. Hayes et al. (1989) found an association between land use and species distribution in the Mokau catchment, but attributed this to the correlation between land use and distance from the sea. There was a negative relationship between the abundance of brown trout and a number of diadromous native species. Although it has been suggested that brown trout could be responsible for the disappearance of native species (Minns 1990; Townsend & Crowl 1991), the negative relationships could also be the result of different species' distributions rather than interspecific interaction. We found G. vulgaris and juvenile brown trout at the same sites and there was no indication that the presence of brown trout excluded G. vulgaris as found by Townsend & Crowl (1991) in the Taieri River. The variability of mean annual floods was a factor that discriminated between species assemblages. Flood variability was high for the lowland Group 1 and the upland Group 5 and lower for Groups 2 to 4. As the flow variation is largely controlled by climate (Jowett & Duncan 1990), this variable appears to be a descriptor of the geographic location of sites rather than an influence on fish abundance and species composition. Percentage of run habitat was the physical variable
253
that discriminated between Groups 2 and 3. Most study rivers fell into these groups and they contained similar fish species. Group 2 rivers were characterised by longfmned eels and Group 3 sites by brown trout. Group 2 sites had less run habitat than Group 3 sites—suggesting a linkage between run habitat and juvenile trout, and pool/riffle habitat and longfmned eels. The habitat differences may be linked to longitudinal distribution with longfinned eels dominating lower and middle reaches that tend to contain more pools and riffles, whereas brown trout dominate further up stream where run habitat is more common. Stream gradient v/as lower in Group 4 rivers, which were dominated by upland bullies. The low gradient and high percentage of pool habitat would make the habitat in this group of rivers particularly suitable for upland bullies which prefer shallow, slow-flowing water (Jowett & Richardson 1995). Substrate size appeared to have a significant influence on native fish abundance, with maximum fish density in gravel substrates, rather than cobble or boulder. Habitat preferences derived from a subset of data used in this study showed that torrentfish, shortfinned eels, and common bully preferred substrate finer than 50 mm, whereas 5 other native species all preferred substrate of 50 mm or greater (Jowett & Richardson 1995). We could find no variation in sampling efficiency with substrate size, nor any variation in substrate size with elevation, and conclude that the density of native fish is highest in gravel substrates that are so common in New Zealand rivers (Mosley 1992). Two factors, substrate and ease of access in rivers on alluvial plains, may explain the slightly higher abundance of native fish in east coast than in west coast rivers. In this study, land-use associations could be explained by diadromony and differences in elevation and geographical locations. Similarly, it was difficult to separate any habitat factors from the overwhelming influence of diadromy and geographical distribution of the fish species. Like Minns (1990), we expected more association of native fish species with native forest or scrub, but were unable to find any. In fact, in our study rivers native fish abundance was highest in catchments with the least forest, but this is probably because forest is least likely to occur at low elevations where the influence of diadromy is greatest, and species richness highest. This study encompassed a range of fish assemblages that were largely a result of diadromy. The number of sites within any
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New Zealand Journal of Marine and Freshwater Research, 1996, Vol. 30
one assemblage was not large enough to allow a more detailed examination of the influence of habitat and land use on fish diversity and abundance, but instead indicated the overall patterns of distribution and abundance that can be expected in medium to large New Zealand rivers.
ACKNOWLEDGMENTS We thank Greg Kelly and Dave West for their assistance with electrofishing and R. McDowall, T. Stephens, and the journal referees for their comments and improvements to this manuscript. This research was carried out with funding from the Foundation for Research, Science and Technology (New Zealand).
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Richardson, J.; Jowett, I. G. 1995: Minimum flow assessment for native fish in the Onekaka River, Golden Bay. National Institute of Water and Atmospheric Research, Science and technology series 21. 13 p. Sagar, P. M.; Eldon, G. A. 1983: Food and feeding of small fish in the Rakaia River, New Zealand. New Zealand journal of marine and freshwater research 17: 213—226. SAS 1985: SAS user's guide: Statistics version 5. Cary, North Carolina, SAS Institute Inc. 584 p. Swales, S.; West, D. W. 1991: Distribution, abundance and conservation status of native fish in some Waikato streams in the North Island of New Zealand. Journal of the Royal Society of New Zealand 21: 281-296. Taylor, M. J. 1988: Features of freshwater fish habitat in South Westland, and the effect of forestry practices. New Zealand Ministry of Agriculture and Fisheries, Freshwater fisheries report 97. 89 p. Taylor, W. R. 1969. A revision of the catfish genus Noturus Rafinesque with an analysis of higher groups in the Ictaluruidae. Bulletin of the U.S. National Museum 282. 315 p. Townsend, C. R.; Crowl, T. A. 1991: Fragmented population structure in a native New Zealand fish: an effect of introduced brown trout? Oikos 61: 347-354. Wolman, M. G. 1954: A method of sampling coarse river-bed material. American Geophysical Union 36: 951-956.
