distributions in two gravel-bed New Zealand rivers ... NIWA, National Institute of Water and Atmospheric Research, P.O. Box 11 115, Hamilton, New Zealand.
Freshwater Biology (1994) 32, 489-500
Hydraulic parameters and benthic invertebrate distributions in two gravel-bed New Zealand rivers JOHN M. QUINN AND CHRISTOPHER W. HICKEY NIWA, National Institute of Water and Atmospheric Research, P.O. Box 11 115, Hamilton, New Zealand
SUMMARY 1. Benthic invertebrates were sampled over a matrix of about eighty combinations of mean velodty (10-150cms~^) and depth (10-150cm) in two rivers that differed in substrate size variability. Vertical velodty profiles were measured at each sample site and substratum roughness was measured and estimated from percentage cover by stone size classes. The influence of depth on periphyton biomass was also measured. 2. The hydraulic and substrate data were used to investigate the correlations between conventional (mean velodty, depth, subsfrate size) and complex hydraulic variables (Froude number, shear velodty, and water column and boundary Reynolds number) that were either calculated from direct measurements or inferred from mean velodty, depth, kinematic viscosity and substrate roughness. The ecological relevance of these hydraulic variables was investigated by comparing their degree of correlation with invertebrate densities and community metrics. 3. The invertebrate variables had similar correlations with mean velodty and the complex near-bed hydraulic variables in the river with uniform cobble subsfrates. In the river with diverse subsfrates, however, average correlations with Froude number, and inferred shear velodty and boundary Reynolds number were 25-45% higher than with velodty. Of all the individual hydraulic parameters, the boundary Reynolds number, calculated from simple measures, was most sfrongly correlated with benthic invertebrate distributions and taxa richness. However, invertebrate distributions were more sfrongly correlated with predictions of multiple regression models, incorporating substrate size, depth and mean velodty, than with any single hydraulic variable. 4. Hydraulic influences on food availability and oxygen concentration in the benthos are likely mechanisms affecting the hydraulic preferences of several taxa. Lower periphyton biomass with depth, partly attributable to light attenuation, appeared to have a nonhydraulic influence on a collector-browser spedes. Introduction The action of flowing water is a dominant feature of stream and river ecosystems. The interactions of flow and sediment create a mosaic of habitat conditions (e.g. food/nutrient supply, gas exchange, erosive shear stress) that creates a templet for biotic interactions (e.g. Statzner, Gore & Resh, 1988; Peckarsky, Horn & Statzner, 1990; Poff & Ward, 1992). Recognition of the importance of flow for benthic invertebrates in lotic environments has led to the development of habitat suitability models for a variety of spedes (e.g. Gore & Judy, 1981; Jowett et al., 1991; Gore, Layzer & Russell, 489
1992; Collier, 1993) to aid dedsions on flow management. Methods and techniques have also been proposed for objectively assessing habitat types (Jowett, 1993) and for characterizing and classifying hydraulic conditions (Statzner et al, 1988; Davis & Barmuta, 1989; Statzner & Muller, 1989; Carling, 1992; Young, 1992). These developments have the potential to improve greatly sampling programmes and experimental designs in lotic ecology by allowing variation due to hydraulic factors to be incorporated better, and by improving hydraulic matching between systems of contrasting water depth (e.g. natural streams v mesocosms).
490 J.M. Quinn and C.W. Hickey Despite these developments, few studies have investigated the relationships between conventional and complex hydraulic variables relating to near-bed conditions, or compared inferred near-bed hydraulic parameters with directly measured values (based on vertical velodty profiles) and their relationships with biotic variables. One exception, Statzner et al (1988), reviews a variety of conventional and complex hydraulic measures (excluding directly measured near-bed parameters) and the distribution of benthic invertebrates. They concluded that measures of near-bed hydraulic conditions (calculated from a combination of kinematic viscosity, mean velodty, depth and visually assessed substrate roughness) provide the best predictors of benthic invertebrate distribution, but state that 'further testing is absolutely necessary'. In this study, we compared a range of conventional and complex hydraulic parameters proposed for use in lotic studies by Statzner et al (1988), Davis and Barmuta (1989) and Carling (1992), and compared directly measured near-bed hydraulic parameters with corresponding inferred values. To do this we compared reladonships amongst hydraulic parameters measured over a wide range of habitats in two gravel bed rivers, and their relationships with distributions of several benthic invertebrate spedes and with community parameters.
Materials and methods Study sites The Mohaka and Mangles Rivers were selected for study from eighty-eight rivers in a previous national survey (Quinn & Hickey, 1990) because they provided the optimal combination of a range of hydraulic habitat conditions, and high densities and diversity of benthic invertebrates. The Mohaka drains the Kaimanawa Ranges, east of Lake Taupo in the central North Island of New Zealand, and the Mangles has headwaters in Nelson Lakes National Park in the north of the South Island. Site and catchment characteristics are summarized in Table 1. Mean annual temperature was 4.5°C higher in the Mohaka then the Mangles, and daily average temperature was 5°C higher (i7°C) during the surveys. Both rivers have predominantly undeveloped catchments, but run through areas of improved pasture at the study
Table 1 General information about the sites and their catchments. Flow, temperature and catchment data are from the Water Resources Database (NIWA, Christchurch), and mean autumn baseflow water quality data are from Qose and Davies-CoUey (1990) Attributes Site attributes Latitude Longitude Flow at sampling (m^s~') Median flow (m'' s"') Flow variability (cv) Mean annual temp. (°C) Elevation (m) Catchment land use % improved pasture % scrub % grassland % native forest Baseflow water quality Dissolved reactive P (mg m"'') NO3-N (mgm"^) Chlorophyll a (mgm"^) Black disc visibility (m) Filtered absorbance 270 nm
Mangles
Mohaka
41''49' 172''26'
39°10' 176°38'
4.3 5.8
24 30 0.9
1.27 11.7
15.2
244
320
7 11 6 75
8 30 13 48
4 58 1.1 3.0
0.046
6 122 0.5 4.2
0.016
reaches. The Mohaka reach was open, whereas a forest-covered cliff on the north side of the Mangles reach prevented direct sunlight. The substrata were relatively uniform and dominated by small and large cobbles in the Mangles, but ranged from small gravel to boulders in the Mohaka. General information on the densities of common invertebrate taxa in the rivers is given elsewhere (Jowett et al, 1991). SampUng
The rivers were sampled in the austral summer during February (Mohaka) and March (Mangles) of 1988 under baseflow conditions (i.e. atflowsexceeded 63% and 65% of the time, respectively). Flows were stable (none greater 3 times the median) in the Mohaka for 7 months prior to the survey but were more variable in the Mangles, with six events during the previous six months with flows of 5-18 times the median. A matrix of combinations of mean current velodty (of approximately 10, 20, 30, 40, 50, 60, 80, 100 and 150 cm s"^) and depth (20, 30, 40, 50, 75, 100 and 150 cm) were sampled. We focused on sites which had at least 2 m of comparable upstream substratum and flow conditions (this was possible for about
Hydraulic parameters and benthic invertebrates 491
80% of the sites). We were unable to locate sitematrix combinations for three of the deep and fast conditions in the Mohaka, and four in the Mangles. Sites covering a full range of velodties were also sampled at 10 cm depth in the Mangles and six additional samples were collected at 30 cm depth where the mean velodties were 20, 50 and 80cms~\ giving a total of seventy-four invertebrate samples. In the Mohaka, four replicate sites were also sampled in areas of relatively uniform substrate dominated by small gravel, large gravel, small cobble, large cobble and boulders, giving a total of seventy-nine samples. Sampling locations that fitted the required combinations of mean velodty and depth were identified before invertebrate sampling and marked with painted, colour-coded stones, placed immediately upstream. Hydraulic habitat conditions were characterized more fully at each sampling site after invertebrate sampling. The depth and mean velodty (mean over 20 s at six-tenths of the depth) were measured at the upstream edge of the sampling site using an electromagnetic current meter (Montedoro-Whitney Model PVM-2A) attached to a gauging rod. The vertical velodty profile was established by measuring the velodty at depths 2, 5, 8, 10, 15, 25, 50, 100 and 150 cm above the substrate, as appropriate for the depth (these measurements were not made at the six replicate sites in the Mangles or the eighteen replicate sites in the Mohaka). Each profile's plot of velodty v log depth was examined. Where a good log-normal relationship was evident (88% of cases), the data from the six depths within 25 cm from the bed were used to calculate the friction or shear velodty [(L/f=l/(slopex5.75) (Smith, 1975)] and the bed roughness [zo = the intercept of the plot of velodty v log depth (Carling, 1992)]. Velocity at 2 cm above the bed was usually (in 60% of cases) below the velodty/log depth regression line. In these cases, the velodty at 2 cm depth was excluded when calculating Uf and ZQ. This was because these velodties were more likely to be influenced by small-scale variations in bed form (e.g. position of sensor in relation to the nearest cobble) than velodties further above the bed, which better reflect the average conditions at the 0.1 m^ sampling scale. Velodty was strongly correlated with log depth for the edited data (mean 1^ = 0.92).
Substrate roughness was determined in areas immediately upstream of those sampled for invert-
ebrates by measuring depth at 5 cm intervals over a i m length using a pressure transducer (NIWA Kainga, Christchurch, New Zealand) attached to a data logger. This technique is analogous to the use of a substrate profiler (Gore, 1978), except that the water surface is used as a datum and data collection and archiving is much more rapid. Substrate roughness was calculated as k^ (2 SD of depth; Statzner et al, 1988; Young, 1992). Care was taken to minimize the disturbance of the sampling area during these measurements. Substrate roughness in the Surber quadrat was also assessed by eye, prior to sampling, as percentage cover by the following size class categories [after Minshall (1984), Table 12.2]: sand (1 m. This apparent influence of depth on periphyton biomass was invesfigated by scraping, with a scalpel, representative 6 cm^ areas of the upper surfaces of four or eight stones collected at points 1 m apart in areas with velodty of about 60cms~^ and depths of 20,40,70,100 and 150 cm in the Mangles and 20, 50,100 and 150 cm in the Mohaka. The periphyton samples were stored in the dark on ice for 24-36h before analysis. Pigment was extracted in 90% acetone.
492 J.M. Quinn and C.W. Hickey and the chlorophyll a concentration (corrected for phaeophydn) measured (APHA, 1989). The influence of light on periphyton biomass, independent of depth effects, was investigated in the Mangles. Areas were sampled, using the methods described above, on the upper surfaces of twelve cobbles selected randomly at depths of 20—40 cm and mean velodty 50—100 cm s~^ in each of the shaded area of the main survey and an unshaded area immediately upstream. Differences in chlorophyll a (log-normalized) between the depth and shade classes were tested by analysis of variance [using the general linear models procedure of SAS (1985)] followed by Duncan's multiple range tests. The attenuation of photosynthetically active radiation (PAR) through the water column in the Mohaka was measured using a LiCor quantum sensor (192-SB).
I960)] but non-critical [i.e. Fr< 1 (Smith, 1975)], except for three sample sites in the Mangles. Relationships between hydrauUc variables
Correlations between the normalized hydraulic variables were similar in the two rivers (Table 3). [Correlations with shear stress (x) and thickness of the viscous sublayer (6') (not presented) were the same as with the friction velodties from which they were calculated.] As expected, mean velodty, Froude number and shear velodty were highly intercorrelated. These variables were also highly correlated with boundary Reynolds numbers in the Mangles, but less so in the Mohaka where substrate was more variable. Boundary Re values calculated from mean velodty, depth and measured or visually assessed bed roughness (Re*2 and Re*^, respectively) were highly correlated with each other and with Ref in both rivers. Similarly, the shear velocities calculated from the mean velodty, depth and measured or visually assessed bed roughness (i.e. U*2 arid li»3, respectively) were highly correlated with each other and with measured shear velodty (Uf). U*2 and U*^ did not differ significantly from each other in the individual rivers or for the combined data, but both
Results Similar ranges of physical and hydraulic characterisdcs were measured Ln the two rivers (Table 2), with the exception of particle size which was generally larger and less variable in the Mangles. Flow conditions were rough-turbulent in the water column [Re > 2000 (Smith, 1975)] and on the bed [Re*>70 (Schlichting,
Table 2 Summary of physical and hydraulic characteristics in study rivers Mangles Variable
n
D(cm) U (cms"') Zo (cm) K (cm)
74 74 62 68 74 74 74 74 62 68 74 62 68 74 62 68 74 62 68 74
ky (cm) SI Fr Re Uf ( c m s " ' ) U,2 ( c m s " ' ) U,3 ( c m s " ' ) 6'f (cm) 6'2 (cm) 6'3 (cm) Tf (dyncm"^) X2 (dyn cm~^) T3 (dyn cm"^)
Re, Re»2 Re»3
Mohaka
median 40.0 49.5 0.8 5.4 6.7 6.3
0.23 139840 5.8 4.1 4.6
0.025 0.036 0.031 33.9 16.7 21.3 2490 1714 2515
10%ile 12.0 10.5 0.04 3.4 5.2 5.9
0.06 34230 1.5 0.9 1.0
0.010 0.013 0.012 2.3 0.9 1.0 656 409 509
90%ile 102.5 111.5 2.3 8.2 8.0 6.6
0.69 580440 14.6 11.6 11.7 0.096 0.156 0.144 215 134 136
8644 6381 7050
n 79 79 53 73 79 79 79 79 54 73 79 54 73 79 54 73 79 51 73 79
median 50 47 0.5 4.5 4.1 5.6
0.21 212780 6.0 4.0 3.9
0.021 0.031 0.032 36.6 15.7 15.0 2465 1590 1424
10%Ue 20 16
0.04 2.6 1.5 4.4
0.06 58030 2.2 1.3 1.2
0.011 0.013 0.013 4.8 1.7 1.5 718 330 173
90%ile 118 106 1.9 9.0 8.2 6.6
0.53 693070 11.1 9.3 9.4
0.057 0.095 0.100 124 87 88
6793 5469 7007
HydrauUc parameters and benthic invertebrates
493
Table 3 Product-moment correlations (xlOO) between substrate and hydraulic variables (normalized by log transformation) for Mangles (upper data) and Mohaka (lower data) Rivers (see Appendix for abbreviations). Values >23 and 38 significant at P
