Freshwater Biology (2005) 50, 1081–1093
doi:10.1111/j.1365-2427.2005.01374.x
APPLIED ISSUES
The long-term effect of artificial destratification on phytoplankton species composition in a subtropical reservoir J A S O N P . A N T E N U C C I , * A N A S G H A D O U A N I , * M I C H E L E A . B U R F O R D † A N D J O S E´ R . R O M E R O * *Centre for Water Research, University of Western Australia, Crawley, Australia † Centre for Riverine Landscapes, Faculty of Environmental Science, Griffith University, Nathan, Australia
SUMMARY 1. The response of phytoplankton to the installation of an artificial destratification system in North Pine Dam, Brisbane (Australia) was investigated over an 18 year period (1984– 2002); 11 years before and 7 years after installation. 2. An overall increase in phytoplankton abundance was revealed for some groups (in particular, diatoms, cyanobacteria and chlorophytes), but not for others (chlorophytes). Changes in the abundance of chlorophyte functional groups was attributed to eutrophication. 3. A strong spatial gradient in phytoplankton abundance and chlorophyll a was observed, with low abundance in the downstream regions affected by the destratification system which was likely because of light limitation induced by vertical mixing. The upstream region acted as a surrogate for the unaltered state of the reservoir, particularly as an indicator of eutrophication without direct influence from the destratification system. Despite the continuous trend in eutrophication of the reservoir, there has been a definite decrease in the rate of eutrophication (approximately 30%) since the installation of the destratification system at the downstream locations. 4. Correlations of the dominant cyanobacteria Cylindrospermopsis raciborskii with other genera changed after destratification, indicating that prior to destratification the dominance of Cylindrospermopsis was because of its ability to compete for phosphorus, whereas after destratification its dominance was because of its ability to compete for light. Keywords: artificial destratification, cyanobacteria, Cylindrospermopsis raciborskii, phytoplankton succession
Introduction Drinking water reservoirs worldwide are coming under increasing pressure because of catchment development. The summer stratification period is often associated with poor water quality because of Correspondence: Jason Antenucci, Centre for Water Research, University of Western Australia, M015, 35 Stirling Hwy, Crawley, Australia 6009. E-mail:
[email protected] 2005 Blackwell Publishing Ltd
low dissolved oxygen (DO) levels caused by the decomposition of organic matter resulting in higher sediment release rates of metals and nutrients. This internal loading can often exceed external loads (e.g. Steinberg, 1983; Prepas et al., 1997), and so is a potential target for remediation. Two approaches are typically used to reduce internal nutrient loading: hypolimnetic oxygenation and artificial destratification. Hypolimnetic oxygenation involves injecting oxygen into the hypolimnion to increase oxygen to levels where internal loading is 1081
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minimised (e.g. Prepas et al., 1997). This technique maintains stratification with less disruption of the previous ecological balance in the epilimnion (Prepas & Burke, 1997). Artificial destratification, on the contrary, involves the installation of a mechanical system to breakdown the summer stratification. By increasing the rate of vertical mixing, oxygen introduced through atmospheric exchange is transported to depth, thereby reducing internal loading (e.g. Schladow & Fisher, 1995; Sherman, Whittington & Oliver, 2000). Artificial destratification can also affect phytoplankton community assemblages, as the typical summer conditions are altered because of enhanced vertical mixing. This increased mixing can result in the selection of low light-adapted species (e.g. Steinberg & Tille-Backhaus, 1990; Burgi & Stadelmann, 2002) or species susceptible to high sedimentation losses (e.g. Jungo et al., 2001), and implies that phytoplankton dynamics in a reservoir can be altered through artificial destratification (Lund, 1971). Moreover, several studies have used artificial destratification to reduce populations of potentially toxic species (e.g. Visser et al., 1996; Lindenschmidt, 1999). In this study we analyse a long-term data set (1984– 2003) of phytoplankton abundance measurements in a subtropical reservoir both before and after the installation of an artificial destratification system in 1995. The reservoir experiences elevated concentrations of cyanobacteria, in particular Cylindrospermopsis raciborskii Woloszyn´ska (Harris & Baxter, 1996). This species is becoming increasing prevalent worldwide (Padisak, 1997), and is a strong phosphorus competitor (Istvanovics et al., 2000), can fix nitrogen, regulate buoyancy and has a low light tolerance (Padisak, 1997). It is generally found in warmer waters, as the optimum temperature for growth is between 25 and 30 C and the temperature for maximum toxin production is 20 C (Saker & Griffiths, 2000). Given the long-term data set available in North Pine Dam, there is a unique opportunity to investigate the behaviour of this increasingly important cyanobacteria under a range of different environmental conditions. The main objectives of the present study were: (i) to describe long-term trends in phytoplankton abundance, and to determine if trends were altered by the installation of the artificial destratification system; (ii) to investigate whether any spatial gradients existed in the reservoir and what impacts these might have on phytoplankton abundance and (iii) to assess the
factors resulting in the dominance of C. raciborskii both before and after the installation of the artificial destratification system.
Methods Study site North Pine Dam (Lake Samsonvale) is a large (volume 2·108 m3, surface area 19.7 km2) storage reservoir located at 27 15¢S, 152 55¢E, 30 km north of Brisbane, Australia. The reservoir was impounded in 1976, and supplies approximately 30% of the water for the city of Brisbane. The reservoir is characterised by large interannual variations in the hydraulic regime, with the retention time varying between 1 month and 3 years (Harris & Baxter, 1996). The catchment is typically unprotected, and consists of mixed land use such as agriculture, dairy farming, natural vegetation and semi-rural development. In 1995, persistent water quality problems, including elevated iron and manganese concentrations, as well as high levels of the potentially toxic cyanobacteria species Microcystis aeruginosa Ku¨tz. and C. raciborskii, lead to the installation of an artificial destratification system. The system is of the ‘bubble plume’ type, with a compressor pumping 200 L s)1 of compressed air through a pipe of diameter 90 mm with 33 clusters of holes spaced approximately 17 m apart. The system is typically switched on in mid-September and runs continuously until the end of April.
Sampling and analytical methods Phytoplankton data have been collected since 1983 from a site 100 m from the dam wall (Fig. 1; station S1), with sampling extending to upstream locations from 1997 onwards. The sampling interval was 7 days from 1983 to 1998, with the sampling interval extended to 14 days from July 1998 onwards. From 1983 to 1997, surface water samples were collected in 1 L polyethylene containers and stored overnight at 4 C. Each sample (250 mL) was concentrated to 5 mL by sand filtration (Harris & Baxter, 1996). Cell counts of the concentrate were performed under phase-contrast microscopy using a Sedgewick Rafter counting chamber (Graticules Ltd, Tonbridge, U.K.). After 1997, sample collection involved a 3 m long hosepipe sampler with a diameter of 5 cm. After mixing in a 2005 Blackwell Publishing Ltd, Freshwater Biology, 50, 1081–1093
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North Pine River
1 km S9 Diffuser S10
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Fig. 1 North Pine Dam, showing location of downstream (S1, S8) and upstream (S3, S9, S10) stations. S1 is the long-term station close to the dam wall. The location of the destratification system diffuser pipe is also shown.
bucket, a subsample of 250 mL was collected in a polyethylene bottle, 1 mL of 100% Lugols solution was added and samples were stored in the dark until counted. Samples were counted under phase-contrast microscopy using a Sedgewick Rafter counting chamber (American Public Health Association (APHA), 1995). Initially this involved sedimentation of cells before counting, but more recently direct enumeration has been used. A comparative study of the sand filtration, Lugol sedimentation and direct enumeration methods at low concentrations found no significant differences except for the small cyanobacterium Aphanocapsa, and so this genera has been excluded from the analysis. Phytoplankton were identified to the genus level and expressed as cells per millilitre. Subsamples of water were also collected 100 m from the dam wall for chlorophyll a and nutrient analyses. For chlorophyll a analyses from 1983 to 1997, samples were analysed by filtration, acetone 2005 Blackwell Publishing Ltd, Freshwater Biology, 50, 1081–1093
extraction and measurement using a spectrophotometer (American Public Health Association (APHA), 1995). A known volume was filtered, under vacuum, through membrane filters covered with a layer of diatomaceous earth (Kieselguhr). The diatomaceous earth and trapped particulate matter were scrapped off, and extracted in 90% acetone at 4 C for 2–24 h. Samples were then centrifuged and the absorbance of the extract measured spectrophotometrically. Since 1997, samples have been filtered onto glass fibre filters, extracted with acetone by grinding with a tissue grinder and absorbance of the extract measured with a spectrophotometer (APHA, 1995). Samples for total nitrogen (TN) and phosphorus (TP) were digested with persulphate, and analysed colorimetrically using a spectrophotometer (APHA, 1995). Chlorophyll a data (from 1983 to present) were also available from the offtake, situated on the dam wall and therefore 100 m from the surface site but at depth
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(usually 10–15 m). Water for this sample was taken beyond the pumps, and so there is the potential for cell lysis because of pressure and shearing effects. However, the advantage of this dataset is that the methodology for measuring chlorophyll a has been unchanged since 1983 (i.e. as described above for 1983–97). Profiles of temperature, DO and pH were collected at weekly or biweekly intervals in conjunction with the phytoplankton sampling. Nutrient data from in-lake stations were available only from 1997 to present, and showed average (±1 SD) TP concentration of 18 ± 8.2 lg P L)1 and TN of 570 ± 150 lg N L)1. Silica concentrations were highly variable, with an average concentration of 2.6 ± 2.2 mg Si L)1. pH in the surface layer varied between 7.3 and 8.7 about a geometric mean of 8.1. Monthly average temperature and DO concentrations were computed from profiler measurements made between 1978–94 (preintervention) and 1998– 2002 (postintervention). Sampling intervals during these periods varied between one and four times per month. All measurements made in each month over the entire period were averaged at each depth to produce monthly average profiles. Average annual chlorophyll a concentrations were computed from the period 1 July until 30 June, so as not to result in aliasing of the summer peak concentration around the December/January period.
Statistical methods Randomised intervention analysis (Carpenter et al., 1989) was used to determine if phytoplankton abundance had changed since the intervention. Time series of abundance observations were randomised to create 9999 permutations, from which the absolute difference between the average pre- and post-intervention concentrations were calculated. These absolute differences were then ranked along with the actual difference to produce a P-value. To adjust for changes in taxonomy during the sampling period, data for Anabaena and Aphanizomenon genera were combined, and data from Pseudanabaena, Limnothrix, Oscillatoria and Planktothrix genera were combined. Randomised intervention analysis was applied to genera that had a minimum of 40 occurrences both before and after the destratification. The selection of 40 occurrences was based on results
from Carpenter et al. (1989) who showed that using this cut-off difference of 1 SD or more was consistently detected with the randomised intervention analysis. Using this cut-off resulted in 21 genera that were analysed. To investigate for any spatial trends in phytoplankton abundance we used data from 89 samples collected between 1997 and 2002 when measurements were made at five locations across the lake (Fig. 1). Three locations are in the upstream part of the lake (approximately 1–1.5 km apart), whereas the remaining two are more typical of conditions in the deeper part of the lake (approximately 1.5 km apart and more than 3.2 km from the upstream stations). Phytoplankton abundance was averaged across each location to generate time series of upstream and downstream measurements. The randomised intervention analysis was used to determine if significant differences existed between the upstream and downstream regions.
Results Phytoplankton abundance was dominated by cyanobacteria, diatom and chlorophyte species from 1983 onwards (Fig. 2). Phytoplankton abundance increased over time (Fig. 2a), with periods of high phytoplankton abundance typically associated with dominance by cyanobacterial species. Temperature and DO profiles at the dam wall both before and after the intervention revealed reduced temperature gradients and increased hypolimnetic DO concentration because of artificial destratification (Figs 3 & 4). Destratification resulted in a decrease in thermocline gradient from 1 to 0.2 C m)1. DO has increased significantly; the period of low oxygen concentrations ( 0.05). Insufficient data were available for other genera. Based on these results we expected Cylindrospermopsis and Microcystis would be more abundant in the upstream location where the water column is more stable, but that Aulacoseira or Synedra would show no spatial patterns. This conjecture assumes that nutrient conditions are equal between both locations, which is true for total nutrients but is unknown for dissolved nutrients. This hypothesis was tested against the observations of spatial differences in the genera (Table 2). Randomised intervention analysis showed significant spatial gradients for groups S and L (including both Cylindrospermopsis and Microcystis), confirming the
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Fig. 7 Average annual chlorophyll a concentration for the wall location (circles) S1, the offtake location (triangles) S1 and the upstream location (squares) S3, S9, S10. The dashed line is the best fit to the wall data (gradient of 0.49 lg chl a L)1 year)1, r2 ¼ 0.63), the dotdash line is the best fit to the wall data prior to the intervention (gradient of 0.74 lg chl a L)1 year)1, r2 ¼ 0.49) and the dotted line is the best fit to the wall data prior to the intervention and the upstream data (a gradient of 0.71 lg chl a L)1 year)1, r2 ¼ 0.76). The vertical dashed bar indicates the installation of the destratification system.
importance of mixing (and hence light availability) on the presence of these genera. No spatial difference was observed for Aulacoseira lending support to the Lake Number analysis, and Synedra did not respond as expected indicating the importance of other factors. Our findings showed the importance of considering the effects of both nutrient and light/mixing conditions on phytoplankton genera. For example, differing responses of Microcystis to artificial mixing have been found. Visser et al. (1996) showed a dramatic reduction in Microcystis with increased mixing (as in this study), whereas, conversely, Lindenschmidt & Chorus (1998) found an increase in population abundance with increased mixing. In our study, we found no relationship between Aulacoseira abundance and water column stability, whereas others have found this genera to be more prevalent under increased
mixing (Visser et al., 1996; Lindenschmidt & Chorus, 1997).
Summary In summary, analysis of a long-term data set proved invaluable in assessing both the long-term impact of destratification on water quality (as chlorophyll a), as well as understanding the factors affecting the dominant cyanobacteria C. raciborskii. Although destratification was successful in reducing chlorophyll a in the downstream areas, the method was not successful in changing the dominance of Cylindrospermopsis. This indicates that the adaptive features of phytoplankton must be considered when implementing amelioration strategies in lakes and reservoirs, and that attempts to reduce internal loading should also be matched with efforts to reduce external nutrient loading. 2005 Blackwell Publishing Ltd, Freshwater Biology, 50, 1081–1093
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Table 1 Results of the randomised intervention analysis, showing abundance (cells mL)1) before and after destratification, the actual difference (AD), the P-value associated with the analysis (significant if
