Structural and Functional Responsesof Plankton to a Mixture of FourTetracyclines in AquaticMicrocosmsC H R I S T I A N J . W I L S O N , *R I C H A R D A . B R A I N , H A N S S A N D E R S O N ,D A V I D J . J O H N S O N , K E T U T T . B E S T A R I ,P A U L K . S I B L E Y , A N DK E I T H R . S O L O M O N

Centre for Toxicology and Department of EnvironmentalBiology, University of Guelph, Guelph,Ontario, N1G 2W1 Canada

Pharmaceuticals are routinely detected at low concen-trations in surface waters, but effects on non-target organismsare not well understood. Microcosms were used toassess ecological responses in freshwater ecosystems toa mixture of four tetracyclines commonly used in veterinaryand human medicine. Triplicate microcosms were treatedwith tetracycline, oxytetracycline, doxycycline, andchlortetracycline, resulting in measured time-weightedaverage total mixture concentrations of 0, 0.080, 0.218, 0.662,and 2.29 µM, respectively. Responses were assessed interms of structure and function based on measurements ofzooplankton and phytoplankton communities, ecosystemproductivity, and water quality. Effects were observed forsome endpoints g the 0.218 µM treatment. The largestresponses were concentration-dependent reductions intotal phytoplankton abundance and species richness.Phytoplankton abundance recovered to control levels inall microcosms after treatment was terminated, and resilience(time to return to normal operating range during stress)was observed with respect to phytoplankton species richness.Zooplankton were generally unaffected by the tetracyclines.Responses also included decreased water clarity, loweroxygen concentration, and water temperature. Functionalendpoints showed varying sensitivity. On the basis ofdissolved oxygen concentrations, community respiration(R) increased while primary productivity (P) was unchangedwith increased treatment concentration. The effectsobserved occurred at considerably greater concentrationsthan are currently measured in the environment, indicatingminimal risk to aquatic organisms.

IntroductionIn the past few years, pharmaceuticals have attracted muchattention due to their widespread use, occurrence in theenvironment, and concerns of bacterial resistance. Increasingevidence indicates that pharmaceuticals may be as ubiquitousin the environment as other organic contaminants (1), yetlittle is known about their potential ecological effects.Pharmaceutical loading can occur year round, via effluentfrom sewage treatment plants (STPs) as well as periodically,

via runoff from manure, agricultural waste, and biosolidsapplication, or pharmaceutical manufacturing processes. Ineffect, this creates a situation of pseudo-persistence (2, 3),where dissipation is balanced by continual input (1); however,some pharmaceuticals display considerable persistence (4)and may bioconcentrate in organisms (5). Concentrations ofpharmaceuticals have been found to exhibit wide spatial andtemporal variability (3), with reported concentrations insurface waters of North America and Europe occurring inthe nanograms to micrograms per liter range (6-8).

There is loading of pharmaceuticals from agriculturalpractices including, in particular, antibiotics. Agricultural usesof antibiotics accounted for 35% (ca. 4700 t) of all antibioticsdispensed in the European Union in 2002 (9). In the UnitedStates, farm animals are estimated to consume 70% (ca. 11 200t) of all antibiotics administered (10). Antibiotics have beenfound thus far in the low micrograms per liter range in sewageeffluent and surface waters (3, 7). Tetracyclines, used forboth human and veterinary applications, are the largesttherapeutic class of antibiotics used in the United States,accounting for approximately 29% of total usage (3231 t)(10). In the EU, approximately 30% of the total usage oftetracycline antibiotics was as growth promoters in animalfeed prior to the phase-out of antimicrobial growth promotersin 2000 (11). Tetracyclines are relatively persistent in manure(12) and have been observed to accumulate in soils afterapplication of manure (13) and in sediments in aquacultureoperations (14). Chlortetracycline (CTC), oxytetracycline(OTC), and tetracycline (TC) have been measured in surfacewater of the United States at maximum concentrations of0.69, 0.34, and 0.11 µg/L, respectively (7).

Until now, assessments on the effects of pharmaceuticalsin the environment have been derived largely from single-species toxicity tests (6). These tests have evolved from theregulatory requirements of chemical registration whereresponses are related to survival and growth of organisms.The tests have limitations in that they utilize a restrictedrange of test species, cannot detect indirect effects resultingfrom interactions between organisms and their environment,and do not directly evaluate ecosystem-level functional effects(15).

Many substances assessed by standard single-speciesbioassays typically have acute to chronic effects measureratios (ACR) less than 100-1000 (16). Pharmaceuticals oftenhave effects mediated via specific receptor mechanisms,which act at sub-lethal levels, and are thus predicted to havemuch larger ACRs (16). In addition, some receptors, such asthose of the steroid hormones are highly conserved in natureand are found in many organisms (17, 18). For these reasons,extrapolating from acute laboratory toxicity data may provideinadequate predictions of environmental effects of phar-maceuticals. Therefore, chronic testing as well as testing ofmultiple organisms and levels of organization is appropriate(2).

Studies conducted in multispecies experimental systems(microcosms) under realistic field conditions offer severaladvantages over laboratory-based single-species tests in thestudy of substances such as pharmaceuticals. Microcosmsencompass several levels of biological organization and offerthe ability to evaluate sensitivity of multiple endpoints to astressor, thus they are important tools for ecotoxicologicaleffect characterizations (19). Microcosms enable detectionof non-lethal subtle changes in structural parameters suchas species richness, and in functional measures, such asprimary production and nutrient uptake. Control microcosmsare used as references to model the normal operating range

* Corresponding author phone: (519)824-4120, ext. 58918; fax:(519)837-3861; e-mail: christia@uoguelph.ca.

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(NOR). Microcosm responses are also used to characterizerecoverysa return to the NORsand resilience, the timerequired to return to the NOR during stress (20-22). Realisticecological models can be constructed to explain complexresponses to stressors, which can be interpreted in terms ofadverse effects on ecosystem structure and function. Theseexperimental systems provide the opportunity to test hy-potheses about structural effects in a controlled setting andexplore novel ways of quantifying function. Lastly, micro-cosms can be used to assess the fate of parent substances(19, 23) and the toxicity of metabolites and breakdownproducts that may be formed. Microcosms are beginning tobe used to assess pharmaceuticals and similar products inaquatic (4, 24, 25) and terrestrial (26) environments.

This research had two major objectives. The first was toassess the effects of a mixture of four tetracycline antibiotics(chlortetracycline, CTC; oxytetracycline, OTC; tetracycline,TC; and doxycycline, DC) on ecosystem structure andfunction and the interactions between these in freshwateraquatic microcosms. Because of the frequent co-occurrenceof pharmaceuticals in the environment, including tetracy-clines (7, 27), we tested the compounds as a mixture.Furthermore, the mixture was tested over a wide concentra-tion range to identify potential worst-case responses andthresholds of biological activity (24, 28, 29), providing uswith the capacity to extrapolate to different ecosystems anddifferent concentrations (20). The second objective was totest possible novel indicators of ecosystem change. Theseobjectives were addressed by measuring changes in phy-toplankton and zooplankton communities, physicochemicalparameters, and estimates of ecosystem functional efficiencyand recovery. This study was part of a larger investigation ontetracyclines in the aquatic environment, aspects of whichhave been reported elsewhere (26, 29, 30).

Materials and MethodsMicrocosm Experiments. The outdoor microcosms used inthis study are located at the University of Guelph and havebeen described in detail elsewhere (31). Briefly, the micro-cosms are in-ground, PVC-lined, and 1.2 m deep with a watervolume of approximately 12 000 L. The bottom was linedwith plastic trays containing natural sediment. Water wascirculated between the microcosms and a spring-fed supplypond at a rate of 12 000 L/d for 2 weeks prior to treatmentto ensure uniform assemblages of zooplankton, algae, andwater chemistry.

Tetracycline hydrochloride (TC; 444.43 g/mol, 98.0%),oxytetracycline hydrochloride (OTC; 460.43 g/mol, 85.1%),and doxycycline hydrochloride (DC; 444.43 g/mol, 91.2%)were supplied by Wiler PCCA Corp (London, ON, Canada),and chlortetracycline (CTC; 478.88 g/mol, 97.7%) was sup-plied by Medisca Inc. (Ville Saint-Laurent, PQ, Canada).Fifteen ponds were used in triplicate for five treatment groups.A mixture of the four tetracyclines was created using nominalconcentrations of 0, 10, 30, 100, and 300 µg/L for eachcompound. Concentrations were selected to encompassworst-case exposure values and thresholds of biologicaleffects (29).

Treatment began on June 2, 2003, and water samples weretaken regularly by depth integrating sampler (32) for analysisof the tetracyclines by HPLC-UV/VIS (29). All the tetracy-clines had a half-life of <3 d (29). On the basis of the residueinformation, the microcosms were treated with the ap-propriate amount of each compound every second day afterstudy initiation to maintain nominal concentrations (29).The measured time-weighted average concentrations of thefour tetracyclines in each treatment were (in µg/L): (9.10 ×8.32 × 11.2 × 10.6), (24.9 × 25.1 × 29.4 × 24.9), (72.0 × 79.9× 75.9 × 76.1), and (260 × 296 × 208 × 281) for TC × OTC× CTC × DC, respectively, corresponding to time-weighted

average total molar concentrations of 0.080, 0.218, 0.662,and 2.29 µM. Over the course of the study, measuredconcentrations were approximately 85% of nominal (29).Molar units are used for assessment and comparisonpurposes for the remainder of this paper. Application oftetracyclines was terminated 34 d after initial treatment.

Microcosms were sampled for physical, chemical, andbiological parameters on days -2, -1, 2, 7, 14, 21, 28, 35, 42and 49, relative to initial application of tetracycline mixture.Separate integrated water samples were obtained to measurelight transmission, pH, hardness, alkalinity, chlorophyll,phosphorus, and nitrogen. Light transmission was measuredon a Biochrom Ultraspec 3100 pro UV/visible spectropho-tometer (Cambridge, UK) at λ ) 400 nm wavelength.Transmission at 50 cm (half-microcosm) depth was calculatedusing the Bourger-Lambert law (29). Water hardness,alkalinity, and conductivity were quantified using standardmethods and kits from Hach (Hach Company, Loveland, CO).The pH was measured using a Fisher Accumet Research AR20(Fisher Scientific, USA). Chlorophyll-a was measured ac-cording to U.S. EPA Method 445.0 (33). For phytoplanktonsamples, a 250-mL aliquot from an integrated 4-L samplewas removed and preserved with Lugol’s solution (24).Zooplankton sampling was conducted using custom-builtactivity traps, which capture zooplankton during dailymigration cycles (24). Two traps were placed for 20 h in eachmicrocosm. The samples were filtered through a 30-µm meshto concentrate the organisms, which were then preservedwith sugar-formalin until counting and enumeration. Fol-lowing identification, entire zooplankton samples werewashed to remove sugar-formalin and then freeze-dried toobtain a dry weight for biomass measurements.

Measurements of dissolved oxygen concentration andpoint temperature were obtained with a YSI Model 55 m(YSI, Yellow Springs, OH) at three marked horizontal positionsat each of three depths (25 and 55 cm from the surface and10 cm above the bottom sediment). Additionally, measure-ments were taken at two different times on each sample day:2-4 pm and 4-6 am.

Oxygen concentrations and biomass were also used toassess functional responses to the tetracycline mixture.Several function-related rates and ratios were used asmeasures of function. These were originally used to describeecological succession by Odum (34) and were later modifiedto characterize ecosystem changes following stress (15, 35).

The above measures were used to derive a rate per dayat each exposure concentration using a nonlinear regressionmodel for oxygen (exponential decay) and average rate forbiomass. The rates derived directly from the measuresincluded community respiration (R), the rate of oxygen useby heterotrophs; energy flow between primary productionand respiration (E, where E ) P + R); and biomass productionrate (B). Gross primary productivity (P), the rate of oxygenproduction by autotrophic primary producers, was calculatedfrom the difference of E - R. Community metabolism, theratio of gross primary production to community respiration(P/R) at each concentration was estimated using the oxygenrates (34). Other functional descriptors, including P/B, R/B,B/E, and net daily metabolism (P - R), were calculated usingthe above rates (15). Using zooplankton biomass rate changeover time, the biomass:energy flow ratio (B/E) was calculated,resulting in a measure of total amount of zooplanktonbiomass supported by a given flow of energy between primaryproduction and respiration. This rate has units grams ofzooplankton per milligrams/liter of O2. Also measured wasgross production:biomass ratio (P/B). This is a measure ofoxygen available per unit mass of heterotroph (zoo-plankton) expressed as milligrams/liter of O2 per gram ofzooplankton. The oxygen requirement per mass of het-erotroph (R/B) also was estimated (same units). Net daily

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metabolism (NDM) was calculated as the difference betweenthe rate of primary productivity and community respiration.Rate over time for each concentration was integrated into asingle data point on the plots of the above parameters (seeFigure 6).

Plankton Identification. All individuals in 3 × 1 mLsubsamples were identified by light microscope down to thelowest taxonomic unit (usually species) to determine speciesrichness (number of unique taxa) (36-39).

For the purposes of interpretation, plankton were clas-sified into groups or classes based on evolutionary historyand ecology as “trophospecies”, aggregations of biologicalspecies on the basis of trophic similarity (20, 40, 41).Phytoplankton were classified into four groups: (i) cyano-bacteria (blue-green algae, Cyanophyta); (ii) green algae andeuglenoids (Chlorophyta); (iii) Heterokont algal species, suchas diatoms; and (iv) cryptomonads and dinoflagellates(Cryptophyta/Dinophyta) (39).

Zooplankton were classified into five groups based onevolutionary relationships, food size, and ecological role asabove (41). These groups were (i) Rotifera (order Rotatoria);(ii) Cladocera; (iii) Copepoda; (iv) small macroinvertebrates(less than 1 mm; all noncrustacean arthropods, vermiformes);and (v) large macroinvertebrates (greater than 1 mm; laterarthropod instars and adults, gastropods) (36-38).

Statistical Evaluation. Analysis of variance (ANOVA) andDunnett’s test were used to determine if there were treat-ment-dependent responses for each endpoint and/or sta-tistically significant differences between treated and controlmicrocosms at each sampling day (42). Effect measures (EC10,EC50) and functional rates were estimated using linear andnonlinear regression models in SigmaPlot (43). All tests wereconducted with type I error rate R ) 0.10 (44). This was chosenbecause of the natural variability of the system and to beprotective to the environment (45). Power calculations wereperformed with the UCLA power calculator (46).

ResultsPhysicochemical Parameters. Analysis of light transmissionof the water at λ ) 400 nm showed a concentration- andtime-dependent decrease in light transmission in both the0.662 and 2.29 µM treatments, beginning 2 d after treatmentand was significant from day 7 onward (p < 0.1). At the highestconcentration, this resulted in a 98% reduction in the amountof light penetrating to a depth of 50 cm as compared to controlby day 35 (Figure 1a) (29). This coloration (i.e., darkening)of the microcosms persisted until at least day 63 (data notshown).

Temperature showed a significant treatment-dependentreduction beginning day 7 post-initiation (p < 0.1; Figure1b). The two highest treatments had significantly andconsistently lower temperature than control at almost alllocations for both morning and midday measurements.Largest differences relative to control were found at thegreatest depth (10 cm from sediment) at midday and, fromday 14 to 42, the highest treatment was 2-3 °C lower thancontrol (p < 0.1).

Like daily temperature, differences in dissolved oxygenconcentration between the highest tetracycline treatmentand control were largest at the greatest depth at midday.Significantly lower oxygen concentrations relative to controlwere fairly consistent (p < 0.1) over the study period at alldepths for the 2.29 µM treatment (except day 21). For oxygenconcentrations at midday and mid-depth (55 cm), the 0.662µM treatment was significantly lower than control on days7 and 14 (p ) 0.005 and 0.009), while the 2.29 µM treatmenthad lower oxygen concentration for days 2, 7, 14, 28, 35, and42 (p < 0.10; Figure 1c).

Recovery of both temperature and dissolved oxygenconcentration to control values was not observed aftercessation of treatment (temperature: for 0.662 and 2.29 µMtreatments; oxygen: for 2.29 µM; Figure 1b,c).

The majority of other water chemistry parameters showedonly slight or periodic treatment effects. Alkalinity, pH, totalphosphorus and nitrogen showed no significant treatmentrelated responses during the study period (p > 0.10). Waterhardness was significantly increased between day 21 anddays 35 in the highest treatment (days 21, 28, and 35; p )0.011, 0.007, and 0.095). Conductivity showed a consistentsignificant treatment-dependent increase on days 7, 21, 28,and 35 in the 2.29 µM treatment (p ) 0.003, 0.062, 0.074, and0.012, respectively; days 7 and 28 LOEC ) 0.662 µM). Inter-replicate variability for chlorophyll-a measurements waslarge, possibly due to interference from filamentous algae.Thus, chlorophyll effects were not included as part of theevaluation.

Phytoplankton. Total phytoplankton abundance (sumof counts of all four groups) showed a significant treatment-dependent reduction, evident at all intervals beginning day2 post-initiation, in the 0.662 and 2.29 µM treatments (p <0.1). At days 21 and 35, abundance was significantly reduced

FIGURE 1. Physicochemical parameter responses to a four-tetracycline mixture over time in aquatic microcosms. (a) Lighttransmission at λ ) 400 nm, depth ) 50 cm. (b) Temperature (°C),PM (depth average). (c) Dissolved oxygen concentration (mg/L ofO2), PM at 55 cm. The asterisk (*) represents a statistically significantdifference of treatment relative to control (r ) 0.10).

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with LOECs of 0.218 µM (p ) 0.076 and 0.0004). Followingcessation of treatment, abundance in the affected treatmentsdid not significantly differ from controls by day 49 (p > 0.1).The decrease in abundance observed at 0.662 and 2.29 µMconcentrations was reflected in all four phytoplankton groups(Figure 2a-d). The most rapid and large decreases inabundance were seen in the cyanobacteria and cryptophyta/dinophyta groups (Figure 2d).

Total phytoplankton species richness (Figure 3a) declinedin a treatment-related manner following the initial applicationbut had significantly lower species richness than controlsonly on day 7 at 0.662 and 2.29 µM (p ) 0.015 and 0.004) andon day 21 at 2.29 µM (p ) 0.017). For days 35 and 49, therewere no significant differences in species richness betweenany treatment and the controls for total phytoplankton orindividual groups (Figure 3; p > 0.10). Cyanobacteria andChlorophyta species richness showed periodic significanteffects during the study (p < 0.1). A more consistent effecton species richness was observed among Heterokonts, whichshowed responses on all post-treatment days up to 21 d afterinitial application (Figure 3b; day 7 LOEC ) 0.218 µM; p <0.1), and within the Cryptophyta/Dinophyta with a LOEC of0.662 µM on both days 7 and 21 (p ) 0.004 and 0.083; Figure3c).

Zooplankton. During the study period, no statisticallysignificant effect on zooplankton biomass was observed(Figure 4a; p > 0.1). Similarly, the relative proportions ofeach zooplankton group in the community did not show anytrends relative to treatment, although cladocerans andcopepods tended to become dominant over time, indepen-dent of tetracycline treatment, comprising >90% of thespecies by day 49. The tetracycline mixture had no effect onzooplankton species richness (Figure 4b; p > 0.1). Sporadicsignificant responses were observed among the zooplanktongroups, but these were inconsistent and not treatment-related.

Total zooplankton abundance counts revealed a treat-ment-related response to the tetracycline mixture over thecourse of the experiment (day 21, 2.29 µM; p ) 0.002).Individually, some of the groups also showed treatmentresponses. Rotifers showed a significant increase in abun-dance relative to controls in the 0.662 and 2.29 µM at day 7(p ) 0.004 and 0.001), the 0.662 µM at day 21 (p ) 0.018), andin 2.29 µM at day 35 (p ) 0.073) (Figure 5a). Cladoceranabundance was significantly increased relative to control inthe highest treatment on day 21 (2.29 µM; Figure 5b; p )0.004). This increase was not reflected in biomass (Figure4a). Abundance of the other three groups increased signifi-cantly relative to control in the highest treatment on day 2(p < 0.1) but only periodically thereafter (Figure 5c-e).

Ecosystem Function. The rate of biomass productionincreased with increasing concentration, and was signifi-cantly greater than control at 2.29 µM (Figure 6a; p ) 0.079).Community respiration also increased with higher concen-trations (Figure 6b). Primary productivity was less affectedby treatment, although a slight increase occurred (Figure6b). Using control as a reference (normalized to 1), com-munity metabolism (P/R) decreased with increasing con-centration (Figure 6c).

Biomass supported by energy flow between primaryproduction and respiration (B/E) changed inconsistently withincreased concentration (Figure 6d). The P/B rate did notchange appreciably with increased concentration (Figure 6e).Similarly, no treatment-response was observed with R/B,although responses were inconsistent at lower concentrations(Figure 6e). Except for the lowest treatment, R/B (require-ment) was greater than P/B (available) at every concentration,indicating a naturally occurring oxygen debt. This was furtherconfirmed by the net daily metabolism (P - R), which

FIGURE 2. Phytoplankton responses to a four-tetracycline mixtureover time in aquatic microcosms. Changes in abundance representedas a percent of control of (a) Cyanophyta, (b) Chlorophyta, (c)Heterokonts, and (d) Cryptophyta/Dinophyta. The asterisk (*)represents a statistically significant difference of treatment relativeto control (r ) 0.10).

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indicated an oxygen deficit and which became increasinglynegative at higher concentrations (Figure 6b).

Effect Measures. Effect measures were derived for allassessed endpoints (Table 1). The most sensitive endpointswere those associated with phytoplankton. Zooplanktonshowed few significant responses. For some endpoints, effectmeasures were outside the data range. Where an effect wasnot detectable because of lack of significant regression andsignificant estimate, a statistical power test was performedon the data for the highest concentration to determine theprobability of avoiding a type II error (1 - â). Manyrelationships had low power (i.e., 1 - â < 0.8 (47); Table 1).

DiscussionWe conducted a comprehensive evaluation of a mixture oftetracyclines using aquatic microcosms to improve ourunderstanding of the ecotoxicology of these compounds.

Microcosms provide the ability to measure subtle effects ofstressors using both structural and functional endpoints.Structure endpoints are generally considered to be moresensitive to perturbation than function endpoints (48, 49),and protecting ecosystem structure is believed to be protec-tive of its function via maintenance of critical-functionkeystone species. Structural endpoints usually have lowervariability (22), are easy to measure and understand, andhence, are more widely used. However, at certain time-scalesand levels of organization, function can be more sensitive tostress (22). For example, if feeding is impaired in a givenspecies (a function at the species level), this could lead to achange in population abundance (structure) via mortality orreduced reproduction. However, feeding impairment maybe transitory because of compensatory mechanisms (22) anddifficult to measure, giving the impression of lack ofsensitivity.

Structural Responses. The four-tetracycline mixturecaused several physicochemical and biological responses inthe microcosms. Examination of the interactions betweencomponents of the system revealed both direct and indirecteffects. Among the physical endpoints, significant responseswere observed in light transmission, dissolved oxygenconcentration, and temperature. Other parameters, such aspH and conductivity, were less sensitive, showing significanteffects at only the highest treatment concentration periodi-cally. Overall, the relative sensitivity of physicochemicalparameters to treatment was light transmission > oxygen >temperature > conductivity, hardness, pH, and alkalinity.

Reduced light transmission in the microcosms was likelydue to the presence of breakdown products of the fourtetracyclines, which caused coloration of the water (30). Thelower temperatures in treated microcosms as compared tocontrols were probably an indirect effect resulting from theabsorption of solar radiation by the colored products; less

FIGURE 3. Phytoplankton responses to a four-tetracycline mixtureover time in aquatic microcosms. Changes in species richness(number of unique taxa) represented as a percent of control of (a)total phytoplankton species, (b) Heterokonts, and (c) Cryptophyta/Dinophyta. The asterisk (*) represents a statistically significantdifference of treatment relative to control (r ) 0.10).

FIGURE 4. Zooplankton responses to a four-tetracycline mixtureover time in aquatic microcosms: (a) zooplankton biomass and (b)zooplankton species richness, expressed as a percent of control.The asterisk (*) represents a statistically significant difference oftreatment relative to control (r ) 0.10).

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than 2% of incident light reached half-microcosm depth (∼50cm at λ ) 400 nm). This relationship is supported by the factthat the largest temperature differences among treatmentsoccurred during mid-afternoon at the greatest depth. Al-though photosynthetic activity was not measured directly,

FIGURE 6. Concentration responses of functional endpoints to afour-tetracycline mixture in aquatic microcosms. Functional ratesover the 35-d treatment period. (a) Biomass rate; (b) gross primaryproductivity, community respiration, and net daily metabolism; (c)community metabolism; (d) biomass supported by unit energy flow;and (e) oxygen requirement and availability. The asterisk (*) inpanel a represents a significant difference in rate as compared tocontrol. The dagger (†) in panel b denotes a significant fit to anexponential decay model. The biomass data points were calculatedfrom average rates over time for each concentration, and thecommunity respiration and energy flow rate (E) were estimatedfrom an exponential decay regression. The remaining functionalmeasures were derived from a difference or ratio of these threeterms, and standard errors are not shown.

FIGURE 5. Zooplankton responses to a four-tetracycline mixtureover time in aquatic microcosms. Changes in abundance representedas a percent of control: (a) Rotifera, (b) Cladocera, (c) Copepoda,(d) macroinvertebrates <1 mm, and (e) macroinvertebrates >1 mm.The asterisk (*) represents a statistically significant difference ofthe treatment relative to control (r ) 0.10).

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reduced light penetration may have reduced photosynthesisin resident macrophytes, periphyton, and phytoplankton,an effect that would explain the treatment-dependentdecrease in oxygen concentrations.

Reduced light intensity may have impacted phytoplanktonpopulations. There was a rapid decline in abundance of allfour phytoplankton groups and a corresponding reductionin species richness in two groups, the loss of which likelyreduced oxygen concentrations. The amount of available lightis closely correlated to survival and growth in phytoplankton(50), and similar responses were observed in the macrophyteM. sibiricum (29). However, many phytoplankton are motileorganisms and, unlike rooted macrophytes, are able to movethereby reducing the effect that light changes have on theirpopulations (50). Thus, a direct (toxic) effect of the tetra-cyclines on the phytoplankton community may be a moreplausible explanation for the population declines. Anti-algalproperties of tetracyclines and other antibiotics have beenwell-documented (51, 52). Toxicity studies of tetracyclinesin Microcystis aeruginosa (Cyanophyta) showed EC50 (7 d forgrowth) values for tetracycline, chlortetracycline, and ox-ytetracycline of 0.09, 0.05, and 0.207 mg/L (0.20, 0.10, and0.45 µM), respectively (53, 54). The green algae Selenastrumcapricornutum (Chlorophyta) responded at higher concen-trations, having EC50 values of 2.2, 3.1, and 4.5 mg/L (4.95,6.46, and 9.77 µM) for the same chemicals (53, 54), indicatingdifferential toxicity among types of algae. Mode of action ofthe tetracyclines is hypothesized to be disruption of ribosomefunction (i.e., protein synthesis inhibition) in both prokaryoticcyanobacteria and in chloroplasts of eukaryotic algae (e.g.,green algae), due to common evolutionary ancestry withbacteria (54). The higher sensitivity of the cyanobacteria maybe explained by their closer relationship with bacteria.

In our study, the most sensitive groups, based onabundance, were the Cyanophyta and Chlorophyta. Cryp-tophyta/Dinophyta had the largest effect sizes in abundanceand species richness, but they were less sensitive byconcentration. This implies that the sensitivity of the majorityof Cryptophyta/Dinophyta species was similar. The Cyano-phyta and Chlorophyta, despite being more sensitive in termsof abundance, were less responsive with respect to thenumber of taxa. This suggests that only a few common specieswere greatly affected by treatment. Unlike other groups,abundance of Heterokonts exhibited low sensitivity but a

much greater response with respect to species richness. Thisindicated a loss of rare, low abundance species. Thedifferential sensitivity between and within groups could beinfluenced by several factors, including inherent resistanceto the tetracyclines, specific grazing by zooplankton, ordifferential effect of light on some species due to their abilityto compensate for low light conditions (discussed above).

The response of phytoplankton may have been an indirecteffect due to increased grazing pressure by zooplankton,which is supported by several lines of evidence. Rotifera aretypically generalist filter feeders, processing both detritusand algae (36). Cladocera feed on similar food sets, processingalgae, bacteria, and sometimes protozoans (37). There wasa significant increase in abundance (500-800% of control)of both of these groups. Rotifera increased in abundance(relative to control) in the treated microcosms on days 7, 21,and 35, while Cladocera experienced a treatment-correlatedabundance peak on day 21. Both are assumed to have theability to exert a concentration-dependent grazing pressureon phytoplankton. However, Rotifera represented a decreas-ing fraction of the community in all microcosms with time(98-14% in control; 96-15% in 2.29 µM). In sympatry,Cladocera often out-compete or exclude rotifers, especiallywhen resources are limiting (36, 55). At the low abundancesobserved, rotifers are not expected to compete well withCladocera, thus any grazing that occurs is expected to bedue to Cladocera. Though food sizes overlap for theindividuals in these two groups, Rotifera predominantly grazesmaller sized particles (37), and there is evidence that smallgreen algae (Chlorophyta) are preferred (56). Cladocera havebeen shown to derive the greatest nutritional value fromcryptomonads (57). The treatment-dependent peak in Cla-docera on day 21 (Figure 5b) is consistent with a relativelylarge decrease in Cryptophyta/Dinophyta abundance (in-cludes cryptomonads; Figure 2d), at a time when the Rotiferawere in significant decline. Similar, less dramatic patterns ofdecline were observed in the other phytoplankton groups.There was no indication of effects due to rotifer grazing. Itis not certain why the cyanobacteria, the least desirable innutrition to zooplankton (57), declined in abundance withthe same pattern as other phytoplankton in this proposedindirect effect scenario. Furthermore, it is not certain whyzooplankton biomass did not show a treatment-related effect,while zooplankton biomass rate showed a significant increase

TABLE 1. Microcosm Effect Measures for Day 7 and Day 35 Post-Application of Four-Tetracycline Mixturea

day 7 day 35 day 7 day 35

microcosm endpoints EC10 (µM) EC50 (µM) EC10 (µM) EC50 (µM) EC10 (µM) EC50 (µM) EC10 (µM) EC50 (µM)

phytoplankton abundance species richnessCyanophyta nd 0.95 ( 0.49 nd 1.93 ( 0.72 0.53 ( 0.15 2.63 ( 0.74 1.00 1.00Chlorophyta 0.21 ( 0.06 nd nd 1.30 ( 0.52 0.84 ( 0.28 4.21 ( 1.44 0.60 0.60Heterokonts 0.26 ( 0.11 nd 0.75 ( 0.16 3.76 ( 0.80 0.51 ( 0.13 2.57 ( 0.66 0.68 ( 0.37 3.38 ( 1.81Crypto/Dinophyta nd 0.42 ( 0.15 0.47 ( 0.11 2.33 ( 0.54 0.44 ( 0.13 2.20 ( 0.66 0.10 0.10total phytoplankton 0.29 ( 0.10 nd 0.42 ( 0.07 2.08 ( 0.33 0.62 ( 0.14 3.09 ( 0.68 0.28 0.23

zooplankton abundance species richnessRotifera †0.54 ( 0.15 †2.69 ( 0.72 0.52 0.52 0.10 0.10 †0.22 ( 0.10 †1.11 ( 0.50Cladocera 0.28 0.28 0.18 0.18 0.63 0.63 0.15 0.15Copepoda 0.19 0.19 0.52 0.52 0.17 0.17 0.31 0.31macroinvertebrates 1 †0.67 ( 0.34 †3.36 ( 1.68 0.37 0.37 0.10 0.10 0.10 0.10macroinvertebrates 2 0.10 0.10 nd nd 0.29 0.29 0.39 ( 0.12 1.93 ( 0.61total zooplankton †0.88 ( 0.47 †4.40 ( 2.29 0.12 0.12 0.11 0.11 0.22 0.22zooplankton biomass 0.64 0.64 0.26 0.26

water variableslight transmission 0.29 ( 0.04 1.43 ( 0.19 0.50 ( 0.09 0.50 ( 0.10temperature 11.6 ( 2.1 58.3 ( 10.9 21.5 ( 1.50 21.4 ( 1.50dissolved oxygen 1.43 ( 0.38 7.13 ( 1.88 2.06 ( 0.33 2.06 ( 0.33

a Time-weighted average concentrations of the mixture were 0, 0.080, 0.218, 0.662, and 2.29 µΜ. Effective concentrations (EC10 and EC50) andstandard error were estimated from nonlinear regression models. Where no treatment-response was found, the power of the observations wascalculated. nd ) not determined because estimate not significant (p > 0.1). † ) increase/stimulation. Numbers in boldface type are the power,1- â.

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at the 2.29 µM treatment, but dominance of the communityby smaller cladocerans is suspected.

If an indirect treatment-mediated effect on phytoplanktonvia top-down pressure by zooplankton is correct, questionsremain regarding the cause of the zooplankton abundancepeaks. Larger zooplankton such as copepods and aquaticinsects showed only periodic changes in abundance and taxa,minimizing the likelihood of a top-down effect, such asreduced predation on Cladocera and Rotifera. Direct toxicityin the laboratory predicts acute and chronic effects at greaterconcentrations than used in the microcosms (58), suggestingthat these increases may have resulted from effects onphysiological processes, such as reproduction. Some chemi-cal stressors have been shown to increase abundance ofzooplankton in microcosm studies (59-62). This may changetrophic relationships and interactions and ultimately causeadverse effects on the structure and function of an ecosystem(63).

Effects on Function. Unlike structural effects, functionalmeasures do not always depend on specific interactionsbetween organisms and the environment but instead reflectthe integration of many biotic and abiotic components ofecosystems (22). As such, they can be used to characterizestressor effects at the community or ecosystem level oforganization with little knowledge of individual interactions(22). A number of functional responses were observed intreated microcosms.

Effects on community metabolism were evident in ourstudy. A trend expected in stressed ecosystems is a changeto a less mature state, which can be measured by manyfunctional parameters (35). Unbalancing of the communityproduction to community respiration (P/R) ratio is indicativeof this effect (35). A decline was observed in P/R withincreasing concentration relative to the control (assumed tobe the most mature and stable), indicating that exposedcommunities were stressed and inefficient as more oxygenwas consumed by heterotrophs than was being produced byautotrophs. This was attributed to a treatment-dependentincrease in R (Figure 6b). This premise is further supportedby a treatment-dependent effect on the NDM (Figure 6c). Ina stressed ecosystem, either P/B or R/B would be expectedto increase. This is an indication of stress, as energy is divertedfrom biomass to stress responses (35). Further, this meansthat the biomass supported (B/E) would be reduced. P/B,R/B, and B/E did not respond to the treatments (Figure 6d,e).From a community perspective, the lack of change in R/Bgiven P/R means that, even though respiration increasedwith increasing concentration, the oxygen consumed pergram of heterotroph remained the same because biomassincreased in proportion with respiration. Of significantinterest is that, in many of these measures, an oxygen deficitis noticeable at all concentrations (note the comparisonbetween P/B and R/B, Figure 6e). This suggests that themicrocosms themselves were not mature according to Odum(34). As the microcosms were 2 months old (14 d circulationperiod + 50 d of treatment), this is possible.

The treatment-dependent decrease in temperature in themicrocosms may have had functional significance. Decreasedoxygen consumption was expected in the cooler, 2.29 µMmicrocosms (reduced metabolism due to low temperature).However, this was not the case; over the study period, thecooler microcosms had approximately 3 times greater rateof oxygen consumption (0.018 mg L-1 d-1 vs 0.006 mg L-1

d-1; p < 0.1). Clearly, other factors such as bacterial activitycould affect oxygen consumption rate, but their precisecontribution to this treatment-related effect is not known.

The functional responses provided useful information oneffects of tetracyclines as several concentrations providedquality rate estimates, with small errors, for the study period.However, others produced larger errors because the rate

estimates were made at the extreme values of the regressionmodels. Confounding this, rate estimates at some concen-trations changed erratically over time. Thus, these functionalmeasures require additional information on effect sizes andregression models tailored to the parameter in questionbefore they can be used as common metrics in microcosmstudies. Nevertheless, they do provide an indication of effectson function complimenting structural evaluation; theyintegrate effects on several levels of organization and suggestwhere functional ecosystem-level effects may be observedin other studies. An excellent example is how the biomassrate integrated over time could be related to both energy andoxygen consumption in this system and the differencesbetween plants and animals (R/B vs P/B) and then comparedwith community structure observations.

Recovery and Resilience. Recovery, a return to a conditionsimilar to that in an untreated reference system after removalof stressor (20), is an important endpoint in ecotoxicology.In this study, recovery was assumed when the perturbedsystem was no longer statistically distinguishable from thecontrol. Resilience can be defined as the amount of timenecessary to return to the normal operating range (NOR) inthe continued presence of the stressor(s) (21). Resiliency isa functional parameter, facilitated by compensatory mech-anisms and functional redundancy (22).

There was evidence of resilience in phytoplankton speciesrichness in this study. All phytoplankton groups experienceda treatment-dependent decrease in taxa. Each returned tothe control condition (which would be expected to have theoriginal NOR) before cessation of treatment. Cyanophytaspecies richness returned to control levels by 21 days, whilethat of Chlorophyta, Heterokonts, and Cryptophyta/Dino-phyta took until day 35, suggesting less resiliency. Theseresponses most likely involved replacement of originalsusceptible species with more resistant species (22). Despitethis structural change, evidence of functional redundancywas seen in the stability of the gross primary productivitywith increased concentration (Figure 6b). Abundance of theindividual phytoplankton groups recovered but did not returnto control levels until day 49 and was less resilient than speciesrichness.

The isolated increases of abundance of some zooplanktontaxa also may be an indication of resiliency. The early peaksin abundance of Copepoda and macroinvertebrates (day 2)had disappeared by the next sampling day (day 7). Cladocerademonstrated similar responses, but peak abundance oc-curred later (day 21). Conversely, Rotifera peaked episodicallyduring the entire 49-d study. Overall, there was structuralstability in the zooplankton. This was demonstrated by theproportion of the groups in the community and communitybiomass, despite treatment. However, community respirationand biomass rate, functional measures of the zooplankton,all responded to treatment.

Relevance. The effect measures for tetracyclines observedin the microcosms for phytoplankton were similar to effectmeasures derived in laboratory assays. Laboratory toxicityvalues for algae ranged from 0.10 to 9.77 µM (a 7-d EC50) forindividual tetracyclines (53, 54), while the microcosm phy-toplankton effect measures ranged from 0.42 to 4.21 µM (day7 EC50) total mixture concentration. Responses to chronicexposures of phytoplankton in the microcosms were similarto those resulting from short-term microcosm exposures(Table 1). These suggest an acute-to-chronic ratio (ACR) of∼10. Microcosm zooplankton had effect concentrations thatwere comparable to phytoplankton but, compared to Daph-nia magna acute laboratory toxicity data (EC10 values > 220µM) (58), were lower than expected (day 7 abundanceEC10/50: 0.54-0.88/2.69-4.40 µM; Table 1). Contribution ofthe individual tetracyclines in the mixture to the responsein the microcosms is unknown. In short, the microcosm

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data suggest small extrapolation factors between levels oforganization and species, between acute and chronic effectsfor tetracyclines, and reduced uncertainty when consideringrisk.

Tetracyclines have been found in relatively low concen-trations in the environment. CTC, OTC, and TC have beenreported at maximum concentrations of 1.44 × 10-3, 0.74 ×10-3, and 0.24 × 10-3 µM (0.69, 0.34, and 0.11 µg/L) in surfacewaters (doxycycline not detected) (7). In addition, theydissipate rapidly from the water column (29). Environmentalconcentrations of individual tetracyclines likely exhibit highspatial and temporal variability (7). Effects observed in themicrocosm study predict effects only at much greaterconcentrations indicating low ecological risk.

Little is known about the breakdown products andmetabolites of tetracyclines and their direct effects other thanthe observed coloration. However, as the metabolites werepresent in our microcosms, the responses, or lack thereof,represent the aggregate result of exposures to both parentsubstance and degradation products, suggesting that theecological risks of these substances in aquatic environmentsare likely low.

Several factors may confound these estimates of risk. Thereis uncertainty of environmental concentrations. There isextrapolation uncertainty from single species to wholeassemblages. Additionally, interaction with keystone speciesmay amplify effects; whereas functional redundancy, suchas we observed in this study, may reduce these effects. Theadverse effects that occurred were dampened, and long-termimpairment to the microcosm community was not expected.The functional measures developed for this research proveduseful for quantifying subtle effects, and we believe that theiruse in the future for microcosm and other ecotoxicologystudies is warranted.

AcknowledgmentsWe thank Tamara Reitsma, Brian Laird, and Richard Frankfor technical assistance and Kim Rattan for phytoplanktonidentification. This research was funded by the CanadianNetwork of Toxicology Centres, Rx&D, Agriculture CanadaLEI, Canadian Pork Producers, Beef Cattle Research Council,and National Science and Engineering Research Council.

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Received for review February 15, 2004. Revised manuscriptreceived July 28, 2004. Accepted August 4, 2004.

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