velocity and sediment disturbance of periphyton in headwater streams: biomass and metabolism

Velocity and Sediment Disturbance of Periphyton in Headwater Streams: Biomass andMetabolismAuthor(s): Barry J. F. Biggs, Robert A. Smith and Maurice J. DuncanSource: Journal of the North American Benthological Society, Vol. 18, No. 2 (Jun., 1999), pp.222-241Published by: Society for Freshwater ScienceStable URL: http://www.jstor.org/stable/1468462 .

Accessed: 09/12/2014 05:31

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact [email protected].

.

Society for Freshwater Science is collaborating with JSTOR to digitize, preserve and extend access to Journalof the North American Benthological Society.

http://www.jstor.org

This content downloaded from 128.239.99.140 on Tue, 9 Dec 2014 05:31:05 AMAll use subject to JSTOR Terms and Conditions

http://www.jstor.org/action/showPublisher?publisherCode=nabs

http://www.jstor.org/stable/1468462?origin=JSTOR-pdf

http://www.jstor.org/page/info/about/policies/terms.jsp


J. N. Am. Benthol. Soc., 1999, 18(2):222-241 ? 1999 by The North American Benthological Society

Velocity and sediment disturbance of periphyton in headwater streams: biomass and metabolism

BARRY J. E BIGGS1, ROBERT A. SMITH, AND MAURICE J. DUNCAN

National Institute of Water and Atmospheric Research Ltd, P O. Box 8602, Christchurch, New Zealand

Abstract. Disturbance by floods is believed to be 1 of the fundamental controllers of temporal and

spatial patterns in stream periphyton. However, the exact causes of biomass losses are still poorly understood and discharge measures of disturbance often only explain limited variance in periphyton development. We investigated the effects of 2 of the main mechanisms of flood disturbance to periphyton-frequency of high-velocity events and frequency of bed sediment movement-in an effort to better understand disturbance processes and improve the quantification of flood disturbance re-

gimes for studies of stream periphyton. Three sites were selected in headwater streams in each of 4

groups according to a 2-way factorial design of frequency of high-velocity events and sediment

stability, giving a total of 12 sites. Periphyton were sampled monthly for 15 mo and analyzed for

chlorophyll a. Maximum photosynthetic rates (Pma), chlorophyll-specific P,,,, community respiration (CR), and Pmax:CR ratios were determined seasonally. Nutrient concentrations were generally low and did not vary as a function of disturbance regime.

Peaks in chlorophyll a were usually low reflecting the low nutrients. Chlorophyll was 2-10x higher where bed sediments moved <15x/y and with seasonal maxima most often in autumn. Frequency of bed movement, soluble reactive P, and the frequency of velocity perturbations were significant predictors of mean monthly chlorophyll a (r2 = 0.88).

Chlorophyll a and water temperature were major correlates of P,,,, specific Pm,,, and CR, and thus the metabolic variables partly reflected changes in biomass among the disturbance regimes. With

chlorophyll and temperature removed as covariates, the main factor influencing all metabolic parameters was season. Pmax was 7X higher in summer than in spring when minima occurred, chlorophyll- specific Pmax was 10x higher in summer than in spring, and CR was 4x higher in autumn than in

spring. Pm,x:CR ratios indicated that the communities were generally autotrophic at times of maximum

photosynthesis with the highest ratios in summer (3x higher than winter). The frequency of velocity perturbations also had a significant effect on Pmax:CR ratios with highest ratios at sites where there was a low frequency of high-velocity events. Our results suggest that sediment instability greatly increases disturbance intensity for periphyton. It is therefore essential to assess not just the frequency of floods, but also the degree of bed movement when quantifying disturbance regimes for periphyton in headwater streams.

Key words: disturbance ecology, stream ecology, stream metabolism, autotrophic biomass, habitat

templet, bed sediments, sediment stability, habitat hydraulics, disturbance resilience.

Disturbance is any perturbation from sources external to a community that results in sudden

mortality of organisms and occurs over time scales much shorter than the accumulation of biomass (Grime 1979, Sousa 1984, Pickett and White 1985, Huston 1994). Disturbance by flood events is an important cause of spatial and tem-

poral variability in benthic communities of streams (Resh et al. 1988, Hildrew and Giller 1994, Allan 1995). The effects are usually measured in terms of changes in biomass, commu-

nity metabolism, and taxonomic composition (e.g., Fisher et al. 1982, Biggs and Close 1989, Grimm and Fisher 1989, Peterson and Stevenson 1992, Boulton et al. 1992, Scarsbrook and Town-

1 E-mail address: [email protected]

send 1993, Biggs 1995, Death and Winterbourn 1995, Uehlinger and Naegeli 1998).

It is important that descriptors of disturbance are independent of their biotic effects (Grimm and Fisher 1989). Elevations in discharge have

traditionally been used as a measure of disturbance to stream benthic communities (e.g., Biggs 1988, Grimm and Fisher 1989, Biggs and Close 1989, Poff and Ward 1989, Quinn and

Hickey 1990, Uehlinger 1991, Lohman et al. 1992, Power 1992, Scarsbrook and Townsend 1993, Poff and Allan 1995, Clausen and Biggs 1997). Discharge has the attraction that data are often easily obtained from federal or state water resources monitoring agencies (e.g., Poff and Ward 1989), it has a rich history of analysis and definition of many statistics (Poff and Ward

222



VELOCITY AND SEDIMENT DISTURBANCE OF STREAM PERIPHYTON

1989, Gordon et al. 1992, Poff 1996, Clausen and

Biggs 1997), and it integrates the forces exerted on benthic environments (Dingman 1984, Gor- don et al. 1992). However, the use of discharge to characterize disturbance regimes has not been totally satisfactory (Townsend et al. 1997). For example, from field observations and a large amount of residual variance in analyses of com-

munity responses to high-discharge events, it is clear that any given increase in discharge can have quite different biological effects in different streams (e.g., fig. 7 in Biggs and Close 1989) or different effects in the same stream at different times of the year (Boulton et al. 1992). Some of the variability in effects may be a result of vary- ing resistance among populations (e.g., Grimm and Fisher 1989, Boulton et al. 1992, Peterson and Stevenson 1992, Scarsbrook and Townsend 1993, Biggs and Thomsen 1995), but it is likely that differences in hydraulic forces among events and among sites are also important. In- deed, spatial variations in flow forces are un-

doubtedly responsible for a major proportion of

patchiness within streams (Hildrew and Giller 1994).

The primary hydraulic properties of a flood that could vary, and could separately cause different effects on benthic communities, are elevations in velocity/shear stress and bed sediment movement. Elevated velocities are usually a precursor to sediment movement, but there are many streams and habitats within streams where these processes are only weakly coupled (Duncan and Biggs 1998). For example, streams with high sediment supply tend to have very unstable beds (Dietrich et al. 1989) and some sediments can be mobile at discharges as low as the mean. Even minor increases in discharge can then cause major bed instability. Conversely, low sediment supply can result in highly armored beds that are usually stable. Therefore, floods in such streams may only increase velocities. For stream periphyton, elevated velocities alone can be very destructive (Homer et al. 1990, Boulton et al. 1992, Peterson and Steven- son 1992, Biggs and Thomsen 1995) because periphyton mainly grow on the upper surfaces of streambed sediments, the communities are generally immobile (unlike many invertebrates), and forces on sediments increase exponentially with increases in velocity (Dingman 1984). However, depending on the age and growth form of the mat, not all periphyton will usually

be sloughed by elevated velocities alone (Ueh- linger 1991, Biggs and Thomsen 1995, Fran- coeur et al. 1998). Relict communities of tightly adhering and low-profile taxa often remain after sloughing events, resulting in rapid gap replacement and re-growth during flow recessions (Francoeur et al. 1998). Conversely, sediment de- stabilization can result in more catastrophic losses of periphyton by abrasion, including removal of small and tightly adhering taxa, and slow re-growth during flow recessions (Biggs and Close 1989, Peterson 1996, Francoeur et al. 1998). Differences in these processes within streams often result in higher average biomass on larger, more stable sediments such as boul- ders (Douglas 1958, Tett et al. 1978, Uehlinger 1991, Peterson et al. 1994, Peterson 1996, Fran- coeur et al. 1998). Clausen and Biggs (1998) also found that armoring of gravel and cobble beds significantly reduced flood disturbance effects on biomass with the magnitude of this reduction increasing as flood frequency increased. However, contrary to these results, several studies have been unable to find differences in periphyton biomass between stable and unstable sediments within streams after floods (Power and Stewart 1987, Grimm and Fisher 1989). Grimm and Fisher (1989) reasoned that this was a result of mobile particles abrading the surfaces of stable particles.

It is clear that there is still much to learn about mechanisms of disturbance during floods and, in particular, how variations in the frequency of velocity perturbations and sediment movement jointly and separately operate as mechanisms to disturb stream periphyton. In this paper, we de- scribe a detailed study of the effects of water velocity fluctuations vs bed sediment stability on periphyton biomass and metabolism in 12 headwater streams in New Zealand. We hypoth- esized that the different interactions between velocity and sediment stability could result in streams with different seasonal patterns of periphyton biomass and metabolism, and affect the overall mean level of these variables during the year. As stated by Hildrew and Giller (1994): "Even though flow is the distinguishing vari- able of running water habitats, ecologists have struggled to characterize it adequately". They also stated: "Evidently, there is still much to do to understand the relationship between disturbances, habitat heterogeneity and refugia. We need to enter a new phase of carefully con-

1999] 223



B. J. F. BIGGS ET AL.

FIG. 1. Location of study sites in the South Island of New Zealand (IHV, infrequent high velocities; FHV, frequent high velocities; US, unstable sediments; SS, stable sediments).

ceived, and probably larger scale, field experi- mentation, to answer some of these questions and test hypotheses".

Study Sites

The streams were situated in hill country of the South Island, New Zealand (Fig. 1). Sites were selected according to a factorial design covering low and high frequencies of high-velocity events (caused by floods) and low and

high levels of sediment stability (caused by variations in sediment supply regimes and floods). No records of historical discharge or bed sediment stability were available from the streams, so a priori selection was based on gaging stations in nearby catchments and field assessment of the relative degree of armoring of the stream beds. A bed was considered to be armored when the surface layer of sediments was well sorted with a dominance of cobble-size particles that were embedded in finer particles, and the subsurface layer consisted of a much higher proportion of fines. Once sites had been selected, gaging stations were installed and hydraulic surveys carried out (see below) to determine the

frequency of high-velocity events and bed sediment movement. These data were used to clas-

sify the streams for data analysis into 4 cate-

gories: 1) infrequent high velocities, unstable sediments (IHV, US); 2) infrequent high velocities, stable sediments (IHV, SS); 3) frequent high velocities, unstable sediments (FHV, US); and 4) frequent high velocities, stable sediments (FHV, SS). This classification formed the basis for AN- OVA data analysis (see later).

The study sites were runs 10-20 m long in each stream, and at median flows had mean

depths of <0.3 m, mean cross-section velocities of 0.3-0.65 m/s, and widths of 1.6-12.7 m (Table 1). There was little direct shading of sites during the day, although all sites received some shad-

ing in the morning and late afternoon from banks and riparian vegetation, particularly dur-

ing winter. Bed sediments were dominated by gravels and cobbles. Sediment particle-size anal-

ysis was done in the field using the Wolman (1954) method, which showed no significant difference in the diameter of the 84th percentile (DM) sediment size fraction between the sites with low vs high frequency of high-velocity events (i.e., p > 0.05; 2-way ANOVA). Also, the D84 sediment size did not vary significantly between the sites with low vs high frequency of bed sediment movement (mean median diameter of D84 fraction at SS sites = 164 mm vs 130 mm for US; p = 0.189; 2-way ANOVA).

None of the catchments were intensively farmed, and vegetation cover varied from native beech and podocarp-broadleaf forest (Sams, Rough, Slaty, Camp, Victoria, Bowyers) to pre- dominantly native snow tussock grassland with low intensity sheep or cattle grazing (the re-

maining streams). These differences in vegetation cover/land use did not vary systematically with the disturbance-regime classification.

Methods

Velocity and sediment stability assessments

Pressure transducer water-level recorders were installed near each study reach to quantify flood regimes over a 3-y period beginning Jan- uary 1994. Sites were visited approximately monthly to download data and carry out gagings for discharge-water-level rating curves. Additional high-flow gagings were carried out at all sites to ensure that the flows during flood

peaks were well defined. Problems occurred with recording water levels at the North Kowai

224 [Volume 18




TABLE 1. Summary of hydrological data for the study sites calculated from 3 y of flow monitoring and

hydraulic parameters for each sampling reach. Mean velocity, mean depth, and mean width were determined at median flows by hydraulic modeling. Note that this classification of sites according to disturbance regime varies somewhat from that in a companion study on bed sediment clusters (Biggs et al. 1997) because of the

longer hydrological record now available and analysis of disturbance in terms of frequency of high-velocity events and movement of the diameter of the 84th percentile (D8) sediment size fraction. FRE3 = frequency of

high-discharge events with a magnitude >3x the median flow (Clausen and Biggs 1997, 1998).

Median Reach Mean Mean Mean Catchment flow FRE3 slope D8 velocity depth width

Site area (km2) (m2/s) (/y) (%) (mm) (m/s) (m) (m)

Infrequent high velocities, unstable substrates

North Kowai 34.9 1.04 7.4 2.9 139 0.44 0.18 4.76

Rough 4.9 0.34 24.0 4.0 158 0.41 0.16 4.79 Timber 13.9 0.26 20.5 1.4 57 0.39 0.14 4.85

Infrequent high velocities, stable substrates

Bowyers 23.2 0.60 22.6 1.2 190 0.39 0.17 9.38 West Kowai 19.6 0.46 8.8 2.2 200 0.65 0.32 4.87 Kyebur 9.4 0.08 30.0 0.9 152 0.30 0.09 3.10

Frequent high velocities, unstable substrates

Sams 7.0 0.23 34.6 2.5 151 0.30 0.15 6.05

Slaty 15.1 1.10 37.4 0.9 160 0.43 0.19 12.72

Camp 6.9 0.63 31.3 0.6 113 0.40 0.17 9.39

Frequent high velocities, stable substrates

Granity 7.6 0.20 34.6 0.8 134 0.36 0.29 1.58 Victoria 8.5 0.50 19.0 2.6 206 0.47 0.20 4.95 Woolshed 29.3 0.34 25.4 0.5 103 0.29 0.14 7.35

and Camp Stream sites because of moving sediments and changing bed configuration. Record- er sites had to be changed several times in those streams and any gaps or poor-quality records were filled using regression estimates based on data from a neighboring catchment.

Hydraulic surveys were carried out at approximately median flows over the periphyton sampling reaches. These surveys involved mul-

tiple transects across the streams at downstream intervals of 5-8 m. Channel elevations, water depths, and velocities (at 0.4 of the depth from the bottom) were measured at up to 15 points across each transect. Average water surface

slope of the sampling reach was calculated from 3 water-surface elevation measurements at each transect. These data were used to convert discharge to mean reach velocity using Jarrett's (1984, 1990) formula:

Q = 3.17 AR?083 S?.12

where Q is discharge (m3/s), A is the cross-sec- tional area of the flow (m2), R is the hydraulic radius (m), and S is the slope. This formula was

developed specifically for estimating discharge, or velocity if discharge is known, in streams with high relative roughness such as in this study.

The frequency of high-velocity events associated with floods was calculated using the velocity-time records for the 15-mo periphyton sampling period. A high-velocity event was defined as any increase in velocity >1.5x the median velocity for the study period, which was equivalent to an increase in discharge of 2.6-3.8x the median discharge at the sites. Only peaks >5 d apart were counted as individual events. The frequency of high-discharge events was also determined for each site as FRE3 (Clausen and Biggs 1997) using the 3 y of flow record and with a 5-d lag before a subsequent event was counted. We used an arbitrary frequency crite- rion for high-velocity events of 15/y to classify streams as having relatively low or high frequency velocity perturbations.

Sediment stability was assessed using the method described by Duncan and Biggs (1998), which was developed for steep streams with

1999] 225




high relative roughness (i.e., bed sediments dominated by cobbles interspersed among boul- ders and shallow water depth). Briefly, this method uses Komar's (1989) approach, which is based on the assumption that particles <D50 (the median particle size) may be hidden by larger particles and are consequently harder to move than expected, whereas larger particles are more exposed to the flow, may roll more easily over smaller particles, and consequently are easier to move than expected. As slopes increase, particles are also more easily moved un- til at angles above their angle of repose they may move without the assistance of fluvial forces. Also, once the depth-to-sediment height ratio becomes small (e.g., <2.5), then the critical di- mensionless shear stress changes and correc- tions are applied. The resultant equations were used to estimate the maximum sediment particle size that could be mobilized for a given set of hydraulic conditions. We used discharge ex- ceeding that necessary to mobilize up to the D8 sediment size as a threshold for determining the frequency of large-scale bed sediment movement at a site. The D84 was chosen as the threshold sediment size for movement because particles around this size play a strong role in maintaining the structural integrity of the bed. Once this size fraction is entrained then mass movement of the bed can be expected. A study using in situ bed sediment tagging was carried out at all sites to validate the modeling of sediment mobilization. The study demonstrated good agreement between measured and predicted threshold flows for bed movement (M. J. Dun- can and B. J. F Biggs, unpublished data).

Water quality

Each site was visited approximately monthly between 1 August 1994 and 30 October 1995, giving a total of 14 or 15 monthly samplings per site. One sampling was missed at 8 sites because of floods. Temperature and conductivity were measured on each visit using a thermometer and conductivity meter, respectively. Duplicate water samples were collected from mid-stream of each site in acid-washed polyethylene bottles, chilled to 1-4?C, and were sent to the laboratory on ice where they were received within 24 h of collection. Samples were immediately filtered through 0.45 ,xm cellulose acetate filters, and the filtrate was frozen for later analysis of N03-N,

NH4-N, and soluble reactive P (SRP) using methods described in Biggs and Close (1989). Nutrient analyses were carried out on a Tech- nicon II autoanalyzer (Dublin, Ireland).

Periphyton

In each study reach, 2 transects (1 m apart) were placed across the stream and the width was divided equally into 5 points. Periphyton was sampled by collecting a stone located be- neath every point across each of the 2 transects, resulting in 10 replicate samples per site. Al-

though no conscious bias was used in retrieving stones, this procedure effectively excluded particles > ca 400 mm median diameter because

they were too large to lift. On the stream bank, the x, y, and z dimen-

sions of each stone were recorded. The entire stone was then thoroughly scrubbed with a stiff

nylon brush into 1.5 L of stream water in a bucket. All 10 stones were scrubbed in the same water giving a single composite sample of periphyton. The periphyton slurry was then trans- ferred to 2-L plastic bottles, chilled, and sent to the laboratory for processing within 36 h.

Seasonal measurements of metabolism (maximum primary production, Pmax, and communi-

ty respiration, CR) were made within the stream

using a rapid benthic-respirometer method based on changes in oxygen over time (Hickey 1988). Prior to periphyton removal, the 5 rocks collected across the 1st transect were placed in the submerged respirometer (a plexiglass chamber with internal dimensions = 0.16 x 0.38 m). The respirometer was sealed and water was re- circulated through the chamber with a sub- mersible pump. Dissolved oxygen (DO) within the chamber was monitored using a DO probe and a scaling amplifier to increase the working range (usually 1 mg/L) to full scale. The data were collected on a chart recorder. Temperature was also monitored to ensure that it stayed constant during each incubation. A 1500-W quartz halogen lamp placed 60 cm above the chamber in the stream flow and powered from a bank- side generator was used to achieve standard

light conditions for all incubations. This lamp gave a light intensity of 550 ixmol m-2s- in the chamber, which was sufficient to achieve light- saturated photosynthesis of the intact mats

(Boston and Hill 1991, Hill and Boston 1991, Young and Huryn 1996, Dodds et al. 1999). Mea-

226 [Volume 18




surements of DO change were made over periods of 3-5-min with linear sections of the re- cordings used to calculate maximum net primary production (NPP). An opaque rubber sheet was used to prevent all light penetration to the chamber for determining CR. At the com- pletion of each set of measurements, the volume of water in the chamber was measured and the community was scrubbed from the stones as described earlier. Metabolism on the 5 rocks collected across the 2nd transect was then determined in the same way. Measurements from the 2 sets of 5 rocks were averaged for the final metabolism results. Pmax was calculated as the sum of NPP and CR.

Each periphyton sample was homogenized in the laboratory using a blender. Subsamples of 10-150 mL were removed from the suspension (after shaking) and filtered onto glass-fiber filters to concentrate the periphyton for analysis of chlorophyll a. Chlorophyll was extracted from periphyton on the filters using boiling 90% eth- anol and was measured on a spectrophotometer (Sartory and Grobbelaar 1984). A correction was made for phaeopigments using acidification.

Data analysis

Month-to-month variability of chlorophyll a was assessed in 2 ways. First we used autocorrelation analysis with a time lag of 1 mo. We interpreted high autocorrelation coefficients to indicate little month-to-month change in biomass and, thus, high temporal stability. Second, we calculated the coefficient of variation (CV) of the arithmetic mean monthly chlorophyll a. High coefficients occur in time-series data where there are occasional very high (or low) values, with little variability for considerable intervals between. We interpreted high CV to indicate sites prone to sporadic high biomass/ bloom conditions with extended periods of similar biomass between these events.

Mean monthly chlorophyll a concentrations were also calculated for each site as a function of season (austral summer = 1 Dec.-28 Feb.; autumn = 1 Mar.-31 May; winter = 1 June-30 Aug.; spring = 1 Sep.-30 Nov.). Differences in chlorophyll and the metabolic variables were assessed using ANOVA (2 levels for frequency of high-velocity events, 2 levels for sediment stability, and 4 levels for season). Treatment differences with a probability of p < 0.05 were ac-

30-

C 0 0 20- c ._

E 10

d z ,

u

.1 3 2

9 7

8

'1

5 I ., I

10 12

la II

0 10 20 30 0 10 20 30

40 40

No. high-velocity events/y

FIG. 2. Location of the study sites on a habitat matrix defined by interactions between frequency of high-velocity events (>1.5x median velocity) and bed sediment stability (frequency that sediment up to 84th percentile size fraction [D84] moves). Numbers denote sites as follows: 1 = North Kowai, 2 = Rough, 3 =

Timber, 4 = Bowyers, 5 = West Kowai, 6 = Kyeburn, 7 = Sams, 8 = Slaty, 9 = Camp, 10 = Granity, 11 Victoria, and 12 = Woolshed.

cepted as being significant. Periphyton biomass and temperature are factors known to affect periphyton metabolism (e.g., Boston and Hill 1991, Hill and Boston 1991, DeNicola 1996, Dodds et al. 1999). These variables were therefore includ- ed as covariates in ANOVAs of Pmax, chlorophyll- specific P,,,, and CR. Stepwise multiple regression using backward elimination (p < 0.15 for

inclusion) was used to further explore factors

controlling chlorophyll a biomass and metabolism. Loge transformations were applied where

necessary.

Results

All sites had moderate to steep water surface

slopes and median flows of 0.08-1.10 m3/s (Ta- ble 1). Frequency of high-velocity events during the study period varied from 0.83 to 37.5/y, and

frequency of D84 bed sediment movement varied from 0 to 28/y (Fig. 2). Although there was variation in the levels of these 2 variables within each disturbance regime, the average frequency of high-velocity events varied significantly between the 2 velocity regimes (average of 6.2 vs

26.8/y; 2-way ANOVA, p = 0.001), but did not

vary significantly between the 2 sediment sta-

bility regimes (average of 15.2 vs 17.8; 2-way

227 1999]

I I I I




ANOVA, p = 0.548). Similarly, the frequency of sediment movement varied significantly between the 2 sediment stability regimes (average of 3.6 vs 23.3/y; 2-way ANOVA, p = 0.0001), but did not vary significantly between the 2 ve-

locity regimes (average of 12.0 vs 15.0/y; 2-way ANOVA, p = 0.162). A weak seasonal pattern of fewer high-velocity events occurred in late summer and early autumn (January-March) at sites with infrequent high-velocity events (data not shown for brevity but see a 15-mo sample of the

3-y time series of velocity in Fig. 3). Monthly water quality data (Table 2) indicated

moderate to low concentrations of nutrients in all streams. Two-way ANOVA of the mean

monthly conductivity and soluble nutrient concentrations yielded no significant differences

among disturbance regimes for any variables. Soluble inorganic N:P ratios indicated both N and P could potentially limit growth at the sites, and this finding was confirmed in a companion study (Francoeur et al. 1999). However, stream- water N:P ratios were not a good indicator of the type or degree of nutrient limitation in any specific stream or over all seasons (Francoeur et al. 1999).

Chlorophyll a

Chlorophyll a concentrations were relatively low at all sites (cf. Biggs and Close 1989, Grimm and Fisher 1989, Lohman et al. 1992, Biggs 1995), regardless of disturbance regime (Fig. 3). Chlorophyll peaks at sites with unstable sediments generally coincided with periods of more stable velocity. Larger, longer-term, fluctuations in chlorophyll a occurred at sites with stable sediments regardless of the frequency of high- velocity events (e.g., Granity; FHV, SS).

Autocorrelation coefficients for month-to- month variation in chlorophyll a did not differ

significantly as a function of frequency of velocity perturbations or sediment stability (2-way ANOVA, p = 0.486 for velocity perturbations, p = 0.308 for sediment stability, and p= 0.951 for their interaction). Similarly, CV of chlorophyll a did not differ significantly as a function of disturbance regimes. However, there was a tenden-

cy for CV to be higher at the sites with low- frequency velocity perturbations (2-way ANO- VA, p = 0.062 for velocity perturbations, p = 0.929 for sediment stability, and p = 0.547 for velocity perturbations x sediment stability in-

teraction). This result suggested that month-to- month variability in chlorophyll a differed between the velocity perturbation regimes, typically having infrequent but relatively high peaks in biomass at the IHV sites (Fig. 3).

Average chlorophyll a varied strongly as a function of sediment stability (being highest where sediments were stable) and moderately as a function of season (Fig. 4, Table 3). How- ever, there was no velocity regime effect nor any interaction term effects. At the SS sites and the FHV, US sites, average seasonal chlorophyll a peaked in autumn, and generally declined through winter, spring, and summer. Chloro- phyll a was highest in winter at the IHV, US sites.

Replotting the chlorophyll a time-series data as a function of days since the last bed-moving event (Fig. 5) illustrated that, although initial re- colonization can be quite rapid, accrual of chlorophyll a biomass to >10 mg/m2 generally re-

quired periods of stability of 20-50 d. This accrual rarely occurred at the sites with unstable bed sediments. Longer-term accrual dynamics at the sites with stable sediments tended to reach an asymptote after 50 d, but did not dis- play clear patterns of accrual and sloughing that have been identified in many other studies (Biggs 1996).

A more detailed analysis of the effect of sediment stability on chlorophyll a revealed a strong hump-shaped relationship between mean monthly chlorophyll and frequency of bed sediment movement (Fig. 6). A stepwise multiple regression of mean chlorophyll as a function of the environmental variables identified the frequency of bed movement, mean monthly SRP, and the frequency of velocity perturbations as the only significant predictors of biomass (Table 4). These variables explained 88% of the variance in mean monthly chlorophyll.

Metabolism

Pmax.-A stepwise multiple regression analysis determined that chlorophyll a and water temperature were significant correlates of Pmax (Fig. 7: 2-tailed Students t value for a stepwise regression of chlorophyll a = 3.477, p = 0.001 and temperature = 3.091, p = 0.003; df = 2, 45; r2 = 0.32).

Season had a significant effect on Pmax (Table 5), even with the effects of the covariates chlo-

228 [Volume 18




Infrequent high velocities 1

: . . J <

I I I I I I I I I I I I I I I -

2

..A . I I * ! i I , ! * . . . I

I I I I I i I I I I . I I I i A SOND JF MAMJASOi

3

ASONDJFMAMJJASO

Frequent high velocities

AS ON J F M AMJ A SO AS ONDJ FM AMJ JA SO

ASONDJFMAMJ J ASO ASOND JF MAMJ J AS O

Month Month

FIG. 3. Temporal variations in chlorophyll a biomass and velocities for each study stream. Dashed lines

represent 1.5X median velocity criteria for high-velocity events. Numbers denote sites as in Fig. 2.

rophyll a and temperature removed. Highest values for Pmax were in summer (overall mean = 381 mg 02 m-2 h-1, SE = 107), followed by autumn (overall mean = 148 mg 02 m-2 h-l, SE

= 20), with lowest in spring (overall mean = 51

mg 02 m-2 h-1, SE = 11) (see also Table 6). There was a significant interaction between season and velocity'regime indicating that Pmax varied

19991 229

40-

30-

20-

10-

.V E o- ? _ 40.

41) E E30

-220

3 30-

20-

10-

0- 0-

Co

4-.

E

0

(0

>1

0 E

*a

0

0

0 E

0

.0 (I) 70 u, -W~ cn

N

CM

>l

0 L o

S

.0




TABLE 2. Summary of mean water quality data (+1 SE) for the study sites, sampled monthly, for the period 1 August 1994 to 30 October 1995. N:P ratio calculated by weight of N and P. SRP = soluble reactive P.

Temper- Conduc- ature tivity Turbidity TSS NH4-N NO3-N SRP

Site ?C pH (pLS/cm) (NTU) (mg/L) (mg/m3) (mg/m3) (mg/m3) N:P

Infrequent high velocities, unstable substrates North Kowai 8.2 7.4 40

(1.09) (0.01) (1.52) Rough 6.8 7.4 45

(0.71) (0.01) (3.40) Timber 8.2 7.4 55

(0.94) (0.02) (5.15)

Infrequent high velocities, stable substrates

Bowyers 7.5 7.4 42

(0.88) (0.08) (2.25) West Kowai 9.5 7.6 69

(1.05) (0.04) (2.65) Kyeburn 7.6 7.4 53

(1.06) (0.07) (16.80)

Frequent high velocities, unstable substrates Sams 9.8 6.8 28

(0.85) (0.06) (3.35) Slaty 9.4 7.1 37

(0.78) (0.60) (1.77) Camp 9.8 7.5 58

(0.81) (0.06) (3.65)

Frequent high velocities, stable substrates

Granity 11.9 6.3 27

(1.24) (0.11) (2.06) Victoria 8.7 7.2 33

(1.11) (0.07) (7.26) Woolshed 9.2 7.3 49

(1.17) (0.13) (6.43)

3.0

(2.41) 0.2

(0.05) 17.2

(16.76)

0.6

(0.24) 0.8

(0.41) 0.2

(0.10)

0.3

(0.05) 0.4

(0.13) 0.3

(0.09)

1.0

(0.19) 0.3

(0.05) 0.5

(0.15)

9.5

(8.00) 1.0

(0.40) 100

(96.67)

2.6

(1.04) 3.0

(1.91) 0.77

(0.45)

0.8

(0.28) 1.2

(0.63) 3.3

(0.79)

4.8

(2.18) 1.08

(0.32) 1.1

(0.28)

2.0

(0.29) 1.9

(0.21) 2.7

(0.67)

2.7

(0.33) 3.4

(0.44) 2.2

(0.23)

5.1

(0.46) 2.7

(0.29) 1.7

(0.25)

6.8

(0.57) 2.4

(0.19) 3.8

(0.70)

18.4

(6.04) 19.2

(1.84) 21.0

(5.24)

14.2

(1.87) 34.4

(9.85) 4.0

(0.70)

7.3

(1.00) 17.7

(2.07) 37.4

(2.77)

130

(31.21) 5.8

(1.00) 218

(43.33)

1.8

(0.24) 1.6

(0.14) 1.7

(0.28)

2.7

(0.23) 1.8

(0.23) 1.8

(0.24)

1.6

(0.14) 1.7

(0.16) 2.0

(0.19)

31.6

(29.4) 1.3

(0.11) 4.1

(0.51)

10.2

(1.63) 15.3

(2.56) 12.9

(2.74)

7.3

(1.78) 21.7

(3.97) 4.2

(0.72)

8.5

(0.84) 14.0

(2.00) 22.6

(2.87)

97.6

(22.64) 8.5

(1.68) 55.4

(7.63)

unequally among seasons for sites with low vs

high frequencies of velocity perturbations (Fig. 8). Pmax at sites with a low frequency of high velocities peaked in summer and decreased in autumn, whereas P,ax peaked in autumn at sites with a low frequency of velocity perturbations. This result reflected weak seasonal differences in the frequency of floods among the regimes (see previous section and Fig. 3).

Chlorophyll-specific Pax.--Stepwise multiple regression determined that biomass and tem-

perature accounted for significant variability in

chlorophyll-specific Pmax (Fig. 7: 2-tailed Stu- dents t value for Ln chlorophyll a = -6.685, p < 0.001; temperature t value = 2.507, p = 0.016; df = 2, 42; r2 = 0.57). Chlorophyll-specific Pmax was negatively correlated with chlorophyll a and positively correlated with temperature.

Season had a highly significant effect on chlo-

rophyll-specific Pmx, even with the effects of

chlorophyll a and temperature removed (Table 5). Highest values occurred in summer (overall mean = 108 mg 02 mg chlorophyll a-' m-2 h-1, SE = 1.4), followed by autumn (38 mg 0, mg chlorophyll a-' m-2 h-1, SE = 1.5), and lowest values in spring (overall mean = 10 mg 02 mg chlorophyll a-' m-2 h-1, SE = 1.5) (Table 6). How- ever, a significant interaction between velocity and season indicated that the seasonal effect was not uniform among disturbance regimes. Overall, because the sites with stable sediments had highest biomass (Fig. 4), these sites also had the lowest chlorophyll-specific Pmax (overall means of 46.5 for sites with SS vs 129.5 mg 02

mg chlorophyll a-' h-~ for US). CR.-Season had a highly significant effect on

230 [Volume 18




3(

2C

E 10

E

0 .c 30

2a

.0

0

IHV, US

.- mt t

IHV, SS

I-

s_-

i^?^ i ii

FHV, US

- FIHVl h

FHV, SS

I I I 1 1

\.\ ?0,ke \,

uniform way among the treatments and seasons.

Pmax:CR.-As could be expected, the periphyton communities were dominated by autotrophic processes at times of maximum photosynthesis (i.e., Pmax:CR > 1; Table 6). Season had a

highly significant effect on Pmax:CR ratios (Table 5) with the highest ratio in summer (overall mean = 5.0, SE = 1.24) and the lowest in winter (overall mean = 1.5, SE = 1.18). Velocity also had a significant effect with ratios being highest at the IHV sites (overall IHV mean = 3.3, SE = 1.23 vs FHV mean = 1.9, SE = 1.23). Three of the 4 interaction terms were significant indicating that the effects of the velocity regime varied seasonally. The effects of sediment stability also varied seasonally.

FIG. 4. Mean seasonal chlorophyll a biomass in each of the disturbance regimes (+1 SE) (see Fig. 1 for abbreviations of disturbance regimes).

community respiration, even with the effects of the chlorophyll a and temperature covariates removed (Table 5). Highest values occurred in autumn (overall mean = 67 mg 02 m-2 h-l, SE =

1.15), followed by summer (40 mg 02 m-2 h-1, SE = 1.7), with lowest values occurring in spring (14 mg 02 m-2 h-1, SE = 1.5) (see also Table 6). However, significant interaction terms between the velocity and sediment stability regimes, and between sediment stability and season indicated that CR varied in a complex, non-

TABLE 3. Three-way ANOVA for chlorophyll a as a function of frequency of high-velocity events, sediment stability, season, and their interactions. *p <

0.05, ***p < 0.001.

F- Source of variation MS df statistic

Velocity events 13 1 0.45 Sediment stability 464 1 16.10*** Season 91 3 3.16*

Velocity events x Sediment

stability 0.02 1 0.00

Velocity events x Season 5.4 3 0.19 Sediment stability x Season 50 3 1.73

Velocity events x Sediment

stability x Season 4.7 3 0.16 Error 29 32 Total 47

Discussion

Our study has demonstrated for these headwater streams that bed sediment stability is a far more important determinant of periphyton biomass than the occurrence of high-velocity events. Sediment stability also modified the effects of season. Sites with stable bed sediments had a mean monthly biomass 2-10X higher than sites with unstable bed sediments.

Through the effect on biomass, sediment stabil-

ity also influenced Pmax, chlorophyll-specific Pmax, and CR, although these last 3 variables also varied strongly by season. Seasonal patterns in

chlorophyll a were most pronounced at sites where bed sediments were stable. These results

provided some support for our hypothesis that different interactions between velocity and sediment stability could influence seasonal patterns of periphyton biomass and metabolism, and

suggested that interstream variations in sediment stability could explain some of the major differences in periphyton biomass and metabolism among temperate headwater streams. This result supports previous studies by Cobb et al. (1992) and Townsend et al. (1997) on invertebrates, which found that differences in benthic invertebrate communities among streams were better explained by bed movement than dis-

charge parameters.

Chlorophyll a

The lack of any velocity regime effect on chlo-

rophyll a did not support 1 of our principal hy-

1999] 231

1 -



B. J. F. BIGGS ET AL. [Volume 18

Infrequent high velocities Frequent high velocities 100.00

.1 10.00 < 7

*. * -6

1.00

0~*S~~~~~ * 0.10

*~~~~~~~~~0.1 100.00 ! ! I i i

10.00 f

1.00,

0.10

100.00 i I I I

o10.00 '

y 3

1.00 .

0.10

0.01 , i i i i I 0 100 200 300 400 500

100.00

4 10.00

1.00

0.10

100.00 1 I

10.00 5

1.00

0.10

10000 . . .

100.00 I, i I I I

10.00- 0 8

1.00

0.10

100.00 I I i

10.00 9l

1.001 *.

0.10

nni

0 100 200 300 400 500

10 I "

niolJ . I

100.00 j , 1 , I I

11

* 12 * - * * *

I "-'-- - 6 10.00? * *

1.001

0.10i

v.V, I ! i I I I . . . . I I I I

0 100 200 300 400 500 0 100 200 300 400 500

Days since flood

FIG. 5. Chlorophyll a biomass as a function of days since the last bed-moving flood. Lines fitted using

distance-weighted least squares. Numbers denote sites as in Fig. 2.

232

00.00-

10.00-

1.00-

0.10- C"

E E

0-5 -

.0

(U 0 m -

s0 C _ v

4 -. 0

ECU (n IC

E c E E Q

0? c 0 -_

S O 0

- Iuv.vv I

10.001

1.001

0.10-

0.01 I . . nn t . . I

e ? ?

.*-*




E 12- x I Chlorophyll -3200 ' 10- X Invertebrates - .

E . - 2400 '

.- X ^ 6-1^ x -1600 H

5. 4 2- - 02

-

0 I , . i.

0

0 10 20 30 No. D84 moving eventsly

FIG. 6. Mean monthly chlorophyll a (+1 SE) as a function of frequency of bed sediment movement

among the sites as defined in Fig. 2. Best-fit line gen- erated from distance-weighted least squares analysis. Also shown are mean monthly densities of invertebrates from the stones on which the periphyton resid- ed (see Discussion).

potheses and may have been a result of a number of factors. Foremost is likely to be the resistance properties of the taxa dominating the communities. Previous experimental studies

(e.g., Peterson and Stevenson 1992, Biggs and Thomsen 1995) have shown that low-growing and tightly adhering diatom taxa are much more resistant to sloughing caused by increases in water velocity than taller-growing filamentous green algae. In general, communities at our sites were dominated by diatoms or tightly ad-

hering cyanobacteria (authors' unpublished data). Nutrient supply concentrations may have been too low at all sites to allow extensive de-

velopment of larger filamentous green algae (Biggs et al. 1998) that could have been sloughed by velocity perturbations alone.

Our biomass results agree well with the recent study of Clausen and Biggs (1998). They assessed mean monthly chlorophyll a in 25 other New Zealand streams in relation to frequency of floods (determined as the frequency of dis-

charge events >3x median discharge) and de-

gree of bed sediment armoring (armored vs not armored). Clausen and Biggs (1998) found that mean chlorophyll a concentrations were 2-4x higher in streams with armored sediments when the frequency of floods was 5-10/y. How- ever, this difference increased to 10X higher when the frequency of floods was >20/y. Thus, as could be expected, in many gravel-cobble bed streams the degree of armoring becomes in-

creasingly important in determining periphyton community resistance to flood disturbance as

TABLE 4. Multiple regression of loge mean month-

ly chlorophyll a biomass as a function of frequency of

high-velocity events, frequency of bed sediment movement, and soluble reactive P (SRP) concentrations. In-

dependent variables are ordered according to their de-

creasing contribution to the model (r2 = 0.88). ** p < 0.01, **

p < 0.001.

Coeffi- t- Source of variation cient SE statistic

Constant 2.738 0.372 7.37***

Frequency of bed sediment movement -0.073 0.012 -6.10***

SRP 0.281 0.055 5.08*** Ln SRP -3.005 0.587 -5.12***

Frequency of high- velocity events 0.036 0.011 3.39**

1000

c

0-

I CV I 4---s 21

zz,",

FIG. 7. Maximum primary production (Pmax) (A) and chlorophyll-specific Pmax (B) as functions of chlo-

rophyll a and temperature. Surface fitted with dis-

tance-weighted least squares smoothing.

1999] 233




TABLE 5. Three-way ANOVA for metabolic parameters (Pmax = maximum primary production, CR = com-

munity respiration) as a function of frequency of high-velocity events, sediment stability, season, and their interactions. * p < 0.05, ** p < 0.01, *** p < 0.001.

Source of variation df MS F-statistic

Velocity events Sediment stability Season

Velocity events x Sediment stability Velocity events x Season Sediment stability x Season

Velocity events x Sediment stability x Season Covariates - Ln chlorophyll a

Temperature Error

Ln specific Pmax



Velocity events x Sediment stability x Season Covariates - Ln chlorophyll a

Temperature Error

Ln CR



Velocity events X Sediment stability X Season Covariates - Ln chlorophyll a

Temperature Error

LnP,m,:CR



Velocity events x Sediment stability x Season Error

1 1 3 1 3 3 3 1 1

30

1 1 3 1 3 3 3 1 1

27

1 1 3 1 3 3 3 1 1

30

1 1 3 1 3 3 3

28

29402 6914

214444 65715

106088 10497 6355

264038 32045 23131

1.026 0.007 4.154 0.974 1.463 0.523 0.674

24.676 0.138 0.480

0.022 0.003 5.712 7.876 3.440 3.020 1.766 9.790 0.948 1.032

2.715 0.100 3.282 3.130 1.740 1.946 0.807 0.591

1.271 0.299 9.271*** 2.841 4.586** 0.454 0.275

11.415** 0.248

2.137 0.015 8.649*** 2.027 3.045* 1.088 1.404

51.376*** 0.287

0.022 0.003 5.537** 7.634** 3.335* 2.928* 1.711 9.490** 0.919

4.593* 0.170 5.551** 5.294* 2.943 3.291* 1.365

the frequency of floods increases. Knowledge of when a community is reset to a pioneer stage will be essential for understanding and model-

ing temporal dynamics of periphyton in stream ecosystems. If relict communities (sensu Town- send 1989) can remain following a disturbance

event, then postdisturbance resilience could be dominated by different processes such as gap replacement, rather than full succession, and overall levels of community development may be quite different (e.g., Francoeur et al. 1998, Biggs et al. 1999).

234 [Volume 18




TABLE 6. Summary of mean seasonal metabolic rate data ( 1 maximum primary production, CR = community respiration.

SE) for each disturbance regime. Pma

Chlorophyll-specific Pmax (mg 02 mg

Pmax chlorophyll a-' CR (mg 02 Season (mg 02 m-2 h-1) m-2 h-1) m-2 h-1) Pmax:CR

Infrequent high velocities, unstable sediments Summer 605

(261) Autumn 134

(21) Spring 39

(23) Winter 57

(39)

Infrequent high velocities, stable sediments

595

(261) 120

(46) 23

(16) 29 (7)

82 (13) 79

(28) 22 (4) 27

(13)

7.1

(2.7) 2.3

(0.9) 1.4

(0.8) 1.8

(0.5)

Summer

Autumn

Spring

580

(231) 152

(37) 73

(31) 68

(15)

Winter

Frequent high velocities, unstable sediments Summer 50

(25) Autumn 124

(11) Spring

Winter

37

(6) 37

(19)

Frequent high velocities, stable sediments Summer 288

(165) Autumn 182

(77) Spring 88

(61) Winter 43

(20)

We found that seasonal fluctuations in chlorophyll a were more conspicuous in streams with stable sediments. Without regular abrasion, the periphyton communities in these streams were able to accrue over a period of months before major losses occurred (Fig. 5). Strong seasonality in temperate stream biomass has typically been reported from more physically benign streams (Biggs 1996). However, Ro-

semond (1994) has also found that strong snail grazing activity can mute seasonal variations in biomass and primary productivity in some stable streams. Flood disturbances may set seasonal patterns where flooding is seasonal (e.g., Power 1992), and if the floods are absent then biomass may persist for long periods (Rounick and Gregory 1981). However, such strong seasonality in biomass dynamics, with a peak in

1999] 235

119 (60) 21

(10) 21

(9) 6

(4)

162

(55) 64

(20) 39

(14) 7

(5)

50

(8) 204

(192) 15 (6) 14

(9)

3

(2) 61

(14) 31

(12) 31

(21)

3.4

(0.2) 2.6

(0.6) 2.0

(0.7) 39

(24)

16

(9.1) 2.1

(0.4) 1.4

(0.3) 1.5

(0.6)

3.2

(0.8) 1.8

(0.5) 0.8

(0.1) 1.6

(0.7)

107

(58) 71

(54) 8

(6) 10 (6)

112

(76) 91

(16) 109

(78) 29 (3)




FHV, US

n i FHV, SS

I

^,e ,e< ̂ ,s'

FIG. 8. Mean seasonal maximum primary production (Pmax) in each of the disturbance regimes (+1 SE) (see Fig. 1 for abbreviations of disturbance regimes).

autumn despite frequent floods, as found in the

present, study is unusual. This temporal pattern in biomass may be a result of greater commu-

nity resistance to disturbance at certain times of the year associated with seasonal changes in

light regimes. Biggs et al. (1999) found that a reduction in maximum daily light levels to <400 iumol m-2 s-1 caused a significant increase in resistance of a diatom-dominated mat to scour disturbance. This resistance occurred through a

change in the physiology and physical structure of the mat (including a major increase in bulk

density under lower light) rather than changes in taxonomic composition. Similar to our results, Boulton et al. (1992) reported a consistent

cycle of seasonal change in benthic invertebrates of a Sonoran Desert stream, despite repeated flood disturbances.

The results of the multiple regression analysis of mean monthly chlorophyll a as a function of disturbance frequency and nutrients strongly supports several previous studies that have considered the interactive effects of nutrient resource supply and flood disturbance frequency (e.g., Biggs and Close 1989, Lohman et al. 1992, Biggs 1995) and the biomass components of the habitat matrix model proposed by Biggs et al. (1998). Indeed, the variance explained by disturbance and nutrient parameters in the present study (88%) is close to the 85% explained in a

previous study by Biggs (1995) for mean month-

ly chlorophyll a in 16 other New Zealand streams.

The role of grazing invertebrates has not been directly addressed in this study, but they have the potential to impart top-down control on biomass accrual (see reviews by Feminella and Hawkins 1995, Steinman 1996), and this control is likely to be strongest under physically benign conditions (Biggs et al. 1998). It is possible that invertebrate grazing could be contributing to the hump-shaped relationship observed between chlorophyll a and frequency of bed movement (Fig. 6). In Fig. 6, we have plotted the mean density of invertebrates at each site, to-

gether with chlorophyll, as a function of fre-

quency of bed movement. There was a significantly higher abundance of invertebrates where the frequency of bed movement was <10/y (geometric mean of 2233 vs 787 where event fre-

quency was >10/y; 1-way ANOVA, p <0.001) and it is possible that invertebrates could be

suppressing periphyton biomass accrual in this

range of the disturbance gradient. Where bed

moving events were more frequent (e.g., -monthly), there was a reduction in invertebrate densities and periphyton biomass increased. This shift in balance between the 2 tro-

phic levels may have been a result of more rapid recovery of the periphyton than invertebrates between events. Thus, there may have been win- dows of opportunity in the streams with moderate frequency disturbances that allowed the

periphyton to develop under lower grazing pressure. At high frequencies of bed movement

(e.g., -biweekly), periphyton and invertebrates were poorly developed. Both communities were

probably constrained by habitat instability at this end of the disturbance frequency gradient. These results are particularly intriguing because they appear to demonstrate a shift from top- down control of periphyton under physically benign, low-disturbance conditions to bottom-

up control under harsh, frequently disturbed conditions. This result supports the general ten- ant of the harsh-benign hypothesis of Menge (1976) and the disturbance-resource supply- grazer habitat matrix model for stream periphyton of Biggs et al. (1998). The threshold at which this apparent shift in control processes occurred was -10 bed-moving events/y.

Metabolism

We had expected a significant effect of disturbance regime on Pmax, and interpreted the

500

400

300

200.

N. 100l E & O

E 500

E 400. 300-

200-

100-

0-

us

IHV, SS

I I I i I

236 [Volume 18

e 11-




lack of this effect to be a result of removing the influence of chlorophyll a as a covariate in the ANOVA. We re-ran the ANOVA for Pmax without covariates to test whether the type of disturbance regime became a significant factor ex- plaining variance in Pmax. However, season was still the predominant effect on Pmax, with the velocity regime having a secondary effect (2-way ANOVA, p = 0.042 for velocity perturbations, p = 0.343 for sediment stability, and p = 0.0002 for season). A reanalysis of the chlorophyll-specific Pma ANOVA without covariates also identified season as the most significant effect, with sediment stability as a secondary effect (2-way ANOVA, p = 0.205 for velocity perturbations, p = 0.016 for sediment stability, and p = 0.0002 for season). It is clear that production processes in these streams are most strongly driven by season and that disturbance regimes are only of secondary significance. Indeed, growth-rate de- terminations in a parallel study (Francoeur et al. 1999) indicated that periphyton growth at these sites was almost twice as high in summer as in winter.

The mechanisms behind the strong seasonal effect on production cannot be explained by differences in light conditions at the time of analysis because artificial lighting was used to stan- dardize photon flux for the assays throughout the year. Temperature and biomass differences contributed to some of the seasonal effects, but there was still considerable unexplained variance. Seasonal changes in taxonomic composition may have also influenced this result. How- ever, Dodds et al. (1999) were unable to detect significant community effects in Pmax between diatoms, green algae, and cyanobacteria. Thus, shifts in community taxonomic composition may not explain the seasonal effect. Alternative- ly, the effect may have been a result of community acclimation to the natural light history during the days or weeks prior to each set of assays. Such light history effects have been not- ed previously for lotic periphyton (Jasper and Bothwell 1986).

Other studies have found a strong correlation between periphyton Pmax and mat biomass (e.g., Boston and Hill 1991, Hill and Boston 1991, Dodds et al. 1999). However, using a model of photosynthetic rates as a function of mat thickness (-biomass) and taking into account self- shading effects at high biomass, Dodds et al. (1999) predicted that maximum photosynthetic

rates should saturate as a function of biomass. This prediction is generally supported by our data. For example, at low temperatures there was an asymptote in Pmax where chlorophyll a exceeded -10 mg/m2 (Fig. 7). This effect may be temperature dependent because the biomass level at which Pmax saturated appeared to increase with higher temperatures. Dodds et al. (1999) also predicted that chlorophyll-specific photosynthetic rates should decrease as a function of increasing mat biomass as a function of self-shading. This prediction is supported by a number of previous investigations (e.g., Pfeifer and McDiffett 1975, Hudon et al. 1987, Boston and Hill 1991, Hill and Boston 1991), and our study (Fig. 7). However, as with P,mx, this rela-

tionship may be temperature dependent. Of particular interest was the potential effect

of the different disturbance mechanisms on the balance between autotrophy and heterotrophy. Biggs et al. (1999) experimentally found that a scour disturbance significantly increased the Pmax:CR ratio by removing poorly attached de- tritus, thus reducing CR. The overall result was an increase in the dominance of autotrophic processes in the post-disturbance period. How- ever, Young and Huryn (1996) and Uehlinger and Naegeli (1998), using whole-river metabolism analysis, reported that frequent floods (effects of velocity and sediment stability were not discriminated) favored the dominance of heterotrophy (i.e., low Pmax:CR), whereas infrequent floods led to autotrophy (i.e., high Pmax:CR). We

anticipated in our study that the sites with stable sediments would have higher CR and lower Pmax:CR ratios than sites with unstable sediments because of the higher biomass of relict communities (Francoeur et al. 1998). There was no significant effect of substrate stability, but there was an effect of velocity regime. Average Pm,x:CR ratios were significantly higher at the sites with infrequent velocity perturbations sug- gesting that streams with infrequent flooding will be more dominated by autotrophic processes regardless of bed sediment stability. This finding supports the results of Young and Hu- ryn (1996) and Uehlinger and Naegeli (1998).

Quantification of disturbance regimes

Quantification of disturbance regimes at the appropriate spatial and temporal scales is not a trivial task (Townsend et al. 1997). It is clear

1999] 237




from our results that disturbance regimes in headwater streams need to be characterized in an ecologically meaningful way, but the large number of potential measures makes the choice of variables difficult (Biggs 1995, Clausen and

Biggs 1997, 1998). In moderate to enriched streams, interflood regeneration and low-flow biomass are usually high (Grimm and Fisher 1989, Lohman et al. 1992, Biggs 1995) and communities are often dominated by green filamentous algae (Grimm and Fisher 1989, Biggs 1995, 1996). In such environments, perturbations in

velocity can cause major disturbance of communities, and thus velocity can be a useful var- iable for quantifying disturbance regimes (e.g., Biggs 1995, Biggs and Thomsen 1995). Boulton et al. (1992) also observed that significant disturbance of invertebrates could occur with freshets that do not result in major bed movement where invertebrates inhabit thick periphyton mats vulnerable to small increases in ve-

locity. However, in unenriched streams where communities are dominated by strongly attached diatoms/cyanobacteria and interflood

growth rates and biomass are low, the velocity forces associated with most floods do not appear to cause severe disturbance of periphyton. Consequently, discharge or measures based on

velocity may be inadequate as indicators of disturbance, and an accurate measure of substrate movement needs to be used as a basis for quantifying disturbance regimes for periphyton.

The question then arises as to what is the best

way to determine frequency of bed sediment movement? Previous methods used by sediment

transport engineers are generally based on the Sheilds formula (e.g., Dingman 1984). However, many of the assumptions behind these methods are transgressed in streams with heterogeneous sediment sizes, steep slopes, and low ratios of water depth to grain size (Duncan and Biggs 1998). Indeed, such formulae are definitely not

applicable where sediments are imbricated, embedded, or armored. A number of recent studies

investigating disturbance of invertebrate communities have used the frequency of movement of painted rocks placed on the stream bed as an index of bed stability (e.g., Death and Winter- bourn 1995, Townsend et al. 1997). This method

may be effective for stream beds dominated by gravel-sized particles and smaller, and those that are naturally very unstable (e.g., from a

high sediment supply regime), but the painted

rock method will greatly overestimate the instability of armored or imbricated beds where

strong particle interlocking develops over time.

Although there is still room for further refine- ment, our method gives a reasonable estimate of the frequency of bed destabilizing floods in both armored and unarmored streams. Also, it is an absolute measure (rather than a relative

instability index) that can be used as a basis for

developing empirical and predictive relation-

ships for benthic communities in streams where

hydrological disturbance is an important con- troller of community dynamics. Parameters re-

quired for this method are a discharge hydrograph, water surface slope at mean flows or

greater, hydraulic radius, and the size distribu- tion of the top layer of bed sediments. The critical velocity (and equivalent discharge) for movement of any given particle size is then calculated using equation 4 of Duncan and Biggs (1998). The hydrograph is then reviewed to determine how often the critical flow for the given particle size is exceeded.

In conclusion, it is now generally understood that disturbance is a primary factor influencing temporal and spatial variability, and pattern in natural ecosystems (Huston 1994). Streams world wide are subjected to regular flood disturbance events (Minshall 1988, Resh et al. 1988), and these disturbances vary greatly in

magnitude and associated intensity of physical forces. Different mechanisms of disturbance can occur in streams during floods, and we have demonstrated that depending on the dominant mechanism a given series of floods may have

quite different effects on periphyton communities in different streams. Of particular importance is the way substrate instability greatly en- hances the intensity of disturbance by floods. Indeed, differences in disturbance intensity (and not simply frequency) should be given much greater consideration as a factor generat- ing large-scale pattern in the autotrophic biomass and metabolism of temperate stream eco-

systems.

Acknowledgements

We are grateful to the NIWA hydrological field parties for maintaining the gaging and

sampling program with such diligence, Steve Francoeur for field assistance, and Faye Richards for water quality analyses. We also thank Liz

238 [Volume 18




Bergey for review comments on an earlier draft of the manuscript. The paper has greatly bene- fited from suggestions made by Chris Peterson and Walter Hill. This research was carried out under Contracts C01519 and C01813 (Environ- mental Hydrology and Habitat Hydraulics) funded by the New Zealand Foundation for Re- search, Science and Technology.

Literature Cited

ALLAN, J. D. 1995. Stream ecology: structure and function of running waters. Chapman and Hall, Lon- don, UK.

BIGGS, B. J. F 1988. Algal proliferations in New Zea- land's shallow stony foothills-fed rivers: toward a

predictive model. Verhandlungen der Internation- alen Vereinigung fur theoretische und angewand- te Limnologie 23:1405-1411.

BIGGS, B. J. F 1995. The contribution of disturbance, catchment geology and landuse to the habitat

template of periphyton in stream ecosystems. Freshwater Biology 33:419-438.

BIGGS, B. J. F 1996. Patterns in benthic algae of streams. Pages 31-56 in R. J. Stevenson, M. L. Bothwell, and R. L. Lowe (editors). Algal ecology: freshwater benthic ecosystems. Academic Press, San Diego.

BIGGS, B. J. E, AND M. E. CLOSE. 1989. Periphyton biomass dynamics in gravel bed rivers: the relative effects of flows and nutrients. Freshwater Biology 22:209-231.

BIGGS, B. J. F, M. J. DUNCAN, S. N. FRANCOEUR, AND W. D. MEYER. 1997. Physical characterisation of micro-form bed cluster refugia in 12 headwater streams, New Zealand. New Zealand Journal of Marine and Freshwater Research 31:413-422.

BIGGS, B. J. F, R. J. STEVENSON, AND R. L. LOWE. 1998. A habitat matrix conceptual model for stream periphyton. Archiv fur Hydrobiologie 143:21-56.

BIGGS, B. J. F, AND H. A. THOMSEN. 1995. Disturbance in stream periphyton by perturbations in shear stress: time to structural failure and differences in

community resistance. Journal of Phycology 31: 233-241.

BIGGS, B. J. F, N. C. TUCHMAN, R. L. LOWE, AND R. J. STEVENSON. 1999. Resource stress alters hydrological disturbance effects in a stream periphyton community. Oikos 85:95-108.

BOSTON, H. L., AND W. R. HILL. 1991. Photosynthesis- light relations of stream periphyton communities.

Limnology and Oceanography 36:644-656. BOULTON, A. J., C. G. PETERSON, N. B. GRIMM, AND S.

G. FISHER. 1992. Stability of an aquatic macroinvertebrate community in a multiyear hydrologic disturbance regime. Ecology 73:2192-2207.

CLAUSEN, B., AND B. J. F BIGGS. 1997. Relationships

between benthic biota and hydrological indices in New Zealand streams. Freshwater Biology 38: 327-342.

CLAUSEN, B., AND B. J. F BIGGS. 1998. Streamflow var-

iability indices for riverine environmental studies.

Pages 357-364 in H. Wheater and C. Kirby (editors). Hydrology in a changing environment. Vol- ume 1. John Wiley and Sons, Chichester, UK.

COBB, G. G., T. D. GALLOWAY, AND J. F FLANNAGAN.

1992. Effects of discharge and substrate stability on density and species composition of stream in- sects. Canadian Journal of Fisheries and Aquatic Sciences 49:1788-1795.

DEATH, R. G., AND M. J. WINTERBOURN. 1995. Diver-

sity patterns in stream benthic invertebrate communities: the influence of habitat stability. Ecolo-

gy 76:1446-1460. DENICOLA, D. M. 1996. Periphyton responses to tem-

perature at different ecological levels. Pages 149- 181 in R. J. Stevenson, M. L. Bothwell, and R. L. Lowe (editors). Algal ecology: benthic freshwater

ecosystems. Academic Press, San Diego. DIETRICH, W. E., J. W. KIRCHNER, H. IKEDA, AND F IS-

EYA. 1989. Sediment supply and the development of the coarse surface layer in gravel-bed rivers. Nature 340:215-217.

DINGMAN, S. L. 1984. Fluvial hydrology. H. Freeman and Co., New York.

DODDS, W. K., B. J. F BIGGS, AND R. L. LOWE. 1999.

Photosynthesis-irradiance patterns in benthic mi-

croalgae: variations as a function of assemblage thickness and community structure. Journal of

Phycology 35:42-53. DOUGLAS, B. 1958. The ecology of the attached dia-

toms and other algae in a stony stream. Journal of Ecology 46:295-322.

DUNCAN, M. J., AND B. J. F BIGGS 1998. Substrate sta-

bility vs flood frequency and its ecological implications for headwater streams. Pages 347-355 in H. Wheater and C. Kirby (editors). Hydrology in a changing environment. Volume 1. John Wiley and Sons, Chichester, UK.

FEMINELLA, J. W, AND C. P. HAWKINS. 1995. Interac- tions between stream herbivores and periphyton: a quantitative analysis of past experiments. Jour- nal of the North American Benthological Society 14:465-509.

FISHER, S. G., L. J. GRAY, N. B. GRIMM, AND D. E. BUSCH. 1982. Temporal succession in a desert stream ecosystem following flash flooding. Eco-

logical Monographs 52:93-110. FRANCOEUR, S. N., B. J. F BIGGS, AND R. L. LOWE. 1998.

Microform bed clusters as refugia for periphyton in a flood-prone headwater stream. New Zealand Journal of Marine and Freshwater Research 32: 363-374.

FRANCOEUR, S. N., B. J. F BIGGS, R. SMITH, AND R. L. LOWE. 1999. Nutrient limitation of algal biomass

239 1999]




accrual in streams: seasonal patterns and com-

parison of methods. Journal of the North Ameri- can Benthological Society (in press).

GORDON, N. D., T. A. MCMAHON, AND B. L. FINLAY- SON 1992. Stream hydrology: an introduction for

ecologists. John Wiley and Sons, Brisbane, Austra- lia.

GRIME, J. P. 1979. Plant strategies and vegetation processes. John Wiley and Sons, Chichester, UK.

GRIMM, N. B., AND S. G. FISHER. 1989. Stability of periphyton and macroinvertebrates to disturbance

by flash floods in a desert stream. Journal of the North American Benthological Society 8:292-307.

HICKEY, C. W 1988. Benthic chamber for use in rivers:

testing against oxygen mass balances. Journal of Environmental Engineering 114:828-845.

HILDREW, A. G., AND P. S. GILLER. 1994. Patchiness,

species interactions and disturbance in the stream benthos. Pages 21-62 in P. S. Giller, A. G. Hildrew, and D. G. Raffaelli (editors). Aquatic ecology: scale, pattern and process. Blackwell Scientific Publications, Oxford, UK.

HILL, W R., AND H. L. BOSTON. 1991. Community de-

velopment alters photosynthesis-irradiance relations in stream periphyton. Limnology and

Oceanography 36:1375-1389. HORNER, R. R., E. B. WELCH, M. R. SEELEY, AND J. M.

JACOBY. 1990. Responses of periphyton to changes in current velocity, suspended sediment and

phosphorus concentration. Freshwater Biology 24: 215-232.

HUDON, C., H. G. DUTHIE, AND B. PAUL. 1987. Physi- ological modifications related to density increase in periphytic assemblages. Journal of Phycology 23:393-399.

HUSTON, M. A. 1994. Biological diversity: the coexis- tence of species on changing landscapes. Cam-

bridge University Press, Cambridge, UK.

JARRETT, R. D. 1984. Hydraulics of high gradient streams. Journal of Hydraulic Engineering 110: 1519-1539.

JARRETT, R. D. 1990. Hydrological and hydraulic research in mountain rivers. Water Resources Bul- letin 26:419-429.

JASPER, S., AND M. L. BOTHWELL. 1986. Photosynthetic characteristics of lotic periphyton. Canadian Jour- nal of Fisheries and Aquatic Sciences 43:1960- 1969.

KOMAR, P. D. 1989. Flow-competence evaluations of the hydraulic parameters of floods: an assessment of the technique. Pages 107-132 in K. Beven and P Carling (editors). Floods: hydrological, sedi-

mentological and geomorphological implications. John Wiley and Sons, Chichester, UK.

LOHMAN, K., J. R. JONES, AND B. D. PERKINS. 1992. Ef- fects of nutrient enrichment and flood frequency on periphyton biomass in northern Ozark

streams. Canadian Journal of Fisheries and

Aquatic Sciences 49:1198-1205. MENGE, B. A. 1976. Organization of the New England

rocky intertidal community: role of predation, competition, and environmental heterogeneity. Ecological Monographs 46:355-369.

MINSHALL, G. W. 1988. Stream ecosystem theory: a

global perspective. Journal of the North American

Benthological Society 7:263-288. PETERSON, C. G. 1996. Response of benthic algal com-

munities to natural physical disturbance. Pages 375402 in R. J. Stevenson, M. L. Bothwell, and R. L. Lowe (editors). Algal ecology: freshwater benthic ecosystems. Academic Press, San Diego.

PETERSON, C. G., AND R. J. STEVENSON. 1992. Resis- tance and resilience of lotic algal communities:

importance of disturbance timing and current.

Ecology 73:1445-1461. PETERSON, C. G., A. C. WEIBEL, N. B. GRIMM, AND S.

G. FISHER. 1994. Mechanisms of benthic algal re-

covery following spates: comparison of simulated and natural events. Oecologia 98:280-290.

PFEIFER, R. F, AND W. F MCDIFFETT. 1975. Some factors affecting primary productivity of stream rif- fle communities. Archiv fur Hydrobiologie 75: 306-317.

PICKETT, S. T. A., AND P. S. WHITE. 1985. Patch dynamics: a synthesis. Pages 371-384 in S. T. A. Pickett and P. S. White (editors). The ecology of natural disturbance and patch dynamics. Academic Press, San Diego.

POFF, N. L. 1996. A hydrogeography of unregulated streams in the United States and an examination of scale-dependence in some hydrological predictors. Freshwater Biology 36:71-91.

POFF, N. L., AND J. D. ALLAN. 1995. Functional organization of stream fish in relation to hydrological variability. Ecology 76:606-627.

POFF, N. L., AND J. V. WARD. 1989. Implications of streamflow variability and predictability for lotic

community structure: a regional analysis of streamflow patterns. Canadian Journal of Fisher- ies and Aquatic Sciences 46:1805-1818.

POWER, M. E. 1992. Hydrological and trophic controls of seasonal algal blooms in northern California rivers. Archiv fiir Hydrobiologie 125:375-410.

POWER, M. E., AND A. J. STEWART. 1987. Disturbance and recovery of an algal assemblage following flooding in an Oklahoma stream. American Mid- land Naturalist 117:333-345.

QUINN, J. M., AND C. W. HICKEY. 1990. Magnitude of effects of substrate particle size, recent flooding and catchment development on benthic invertebrate communities in 88 New Zealand rivers. New Zealand Journal of Marine and Freshwater Research 24:411-427.

RESH, V. H., A. V. BROWN, A. P. COVICH, M. E. GURTZ, W L. HIRAM, G. W. MINSHALL, S. R. REICE, A. L.

240 [Volume 18




SHELDON, J. B. WALLACE, AND R. C. WISSMAR. 1988. The role of disturbance in stream ecology. Journal of the North American Benthological So-

ciety 7:433-455. ROSEMOND, A. D. 1994. Multiple factors limit seasonal

variation in periphyton in a forest stream. Journal of the North American Benthological Society 13: 333-344.

ROUNICK, J. S., AND S. V. GREGORY. 1981. Temporal changes in periphyton standing crop during an

unusually dry winter in streams of the Western Cascades, Oregon. Hydrobiologia 83:197-205.

SARTORY, D. P., AND J. E. GROBBELAAR. 1984. Extraction of chlorophyll a from freshwater phytoplankton for spectrophotometric analysis. Hydrobiologia 114:177-187.

SCARSBROOK, M. R., AND C. R. TOWNSEND. 1993. Stream community structure in relation to spatial and temporal variation: a habitat templet study of two contrasting New Zealand streams. Freshwa- ter Biology 29:395-410.

SOUSA, W. P. 1984. The role of disturbance in natural communities. Annual Review of Ecology and

Systematics 15:353-391. STEINMAN, A. D. 1996. Effects of grazers on freshwater

benthic algae. Pages 341-373 in R. J. Stevenson, M. L. Bothwell, and R. L. Lowe (editors). Algal ecology: freshwater benthic ecosystems. Academ- ic Press, San Diego.

TETT, P., C. GALLEGOS, M. G. KELLY, G. M. HORNBER-

GER, AND B. J. COSBY. 1978. Relationships among substrate, flow, and benthic microalgal pigment density in the Mechums River, Virginia. Limnol-

ogy and Oceanography 23:785-797. TOWNSEND, C. R. 1989. The patch dynamics concept

of stream community ecology. Journal of the North American Benthological Society 8:36-50.

TOWNSEND, C. R., M. R. SCARSBROOK, AND S. DOL- EDEC. 1997. Quantifying disturbance in streams: alternative measures of disturbance in relation to macroinvertebrate species traits and species rich- ness. Journal of the North American Benthologi- cal Society 16:531-544.

UEHLINGER, U. 1991. Spatial and temporal variability of the periphyton biomass in a prealpine river (Necker, Switzerland). Archiv fur Hydrobiologie 123:219-237.

UEHLINGER, U., AND M. W. NAEGELI. 1998. Ecosystem metabolism, disturbance, and stability in a prealpine gravel bed river. Journal of the North Amer- ican Benthological Society 17:165-178.

WOLMAN, M. J. 1954. A method of sampling coarse river bed material. American Geophysical Union Transactions 35:951-956.

YOUNG, R. G., AND A. D. HURYN. 1996. Interannual variation in discharge controls ecosystem metabolism along a grassland river continuum. Cana- dian Journal of Fisheries and Aquatic Sciences 53: 2199-2211.

Received: 5 January 1998 Accepted: 23 April 1999

1999] 241



velocity and sediment disturbance of periphyton in headwater streams: biomass and metabolism

Documents