Urban influences on Cladophora blooms in Lake Ontario

Journal of Great Lakes Research 38 (2012) 116–123

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Urban influences on Cladophora blooms in Lake Ontario Scott N. Higgins a,⁎, Christopher M. Pennuto b, E. Todd Howell c, Theodore W. Lewis d, Joseph C. Makarewicz d a

Freshwater Institute, Fisheries and Oceans Canada, 501 University Crescent, Winnipeg, MB, Canada R3T 2N6 Biology Department & Great Lakes Center, Buffalo State College, 1300 Elmwood Avenue, Buffalo, NY 14222, USA c Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment, 125 Resources Road, Etobicoke, Ontario, Canada M9P 3V6 d Department of Environmental Science and Biology, The College at Brockport, State University of New York, Brockport, NY 14420, USA b

a r t i c l e

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Article history: Received 27 April 2011 Accepted 8 September 2011 Available online 5 January 2012 Communicated by Vi Richardson Keywords: Cladophora Eutrophication Dreissenid Nearshore Filamentous algae

a b s t r a c t Cladophora biomass and bloom occurrences were highly variable across Lake Ontario during 2008. Cladophora growth rates were strongly phosphorus (P) limited, and P loading from local watersheds appeared to be the underlying driver for the spatial variability in Cladophora biomass. Cladophora growth rates are likely more sensitive to P loading than prior to dreissenid invasion, since these mussels can transform particulate P into soluble forms with increased bioavailability. While increased P bioavailability due to dreissenid mussel excretion was likely important in many areas, there was little evidence that P from metabolic waste products of dreissenid mussels was sufficient to produce severe blooms in absence of localized P enrichment. Our results indicated that the effective management of Cladophora blooms in Lake Ontario should occur through managing P loading at local scales while ensuring lake-wide P concentrations do not increase. When monitoring and managing these blooms in Lake Ontario it will be important to consider that ambient concentrations of soluble reactive phosphorus (SRP) are likely under biological control in areas with extensive Cladophora blooms, that Cladophora may obtain SRP from underlying dreissenid beds, and that SRP concentrations in overlaying waters may not reflect the sum of P available for growth. As dreissenids can transform particulate P into bio-available P, management of P from localized sources should focus on reducing both total P and soluble P loading to nearshore waters. Crown Copyright © 2011 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. All rights reserved.

Introduction The green alga Cladophora glomerata is among the most ubiquitous and problematic macroalgal species in fresh and brackish water habitats across the globe (Higgins et al., 2008a, 2008b). C. glomerata is found on every continent except Antarctica and on most major island chains (Guiry and Guiry, 2007; Sheath and Cole, 1992). While the alga is widely distributed, bloom formations have historically been restricted to areas of moderate to high nutrient concentrations (Dodds, 1991; Herbst, 1969; Parker and Maberly, 2000; Whitton, 1970). However, following the invasion of the mollusks Dreissena polymorpha (zebra mussel) and Dreissena rostriformis bugensis (quagga mussel) into fresh and brackish water habitats across Europe and North America, increased growth rates and biomass accrual of Cladophora and other macroalgal species have been reported (Auer et al., 2010; Bootsma et al., 2004; Lowe and Pillsbury, 1995; Malkin et al., 2010; Orlova et al., 2004). In some cases extensive blooms of these macroalgae now occur in lakes otherwise considered oligotrophic to slightly mesototrophic. For example, following the establishment of dreissenids across the Laurentian Great Lakes in the late 1980s and early 1990s, spatially ⁎ Corresponding author. E-mail address: [email protected] (S.N. Higgins).

extensive blooms of C. glomerata now frequently occur across shorelines in Lake Michigan (Bootsma et al., 2004; Tomlinson et al., 2010), Lake Erie (Higgins et al., 2005b), and Lake Ontario (Depew et al., 2009; Higgins et al., 2008b; Malkin et al., 2010). Cladophora blooms are a costly nuisance; fouling recreational beaches, fishing nets, and industrial water intakes. Both living and decomposing Cladophora filaments can also provide a suitable environment for the growth and survival of bacterial species (Escherichia coli) used as indicators of fecal contamination. In a study on Lake Michigan, E. coli was found on 97% of Cladophora samples collected from ten beaches across four states (Whitman et al., 2003). In proximity to point sources, pathogenic bacteria were found associated with living Cladophora filaments (Byappanahalli et al., 2003; Byappanahalli et al., 2007; Byappanahalli et al., 2009; Byappanahalli and Whitman, 2009; Englebert et al., 2008; Ishii et al., 2006; Olapade et al., 2006; Whitman et al., 2003; Whitman and Nevers, 2008). In the Laurentian Great Lakes region the growth of C. glomerata is mediated by water temperature, solar irradiance, availability of hard substrata for attachment, and availability of soluble phosphorus (Auer et al., 2010; Higgins et al., 2006; Higgins et al., 2008b). With the exception of temperature, dreissenid mussels have altered each of these drivers in ways that facilitate increased growth rates. When environmental conditions for growth are suitable, the distribution of

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S.N. Higgins et al. / Journal of Great Lakes Research 38 (2012) 116–123

Cladophora is primarily limited by a hard substratum for attachment of zoospores and akinetes that develop into algal filaments. In addition to rocky lake bottoms and man-made structures, dreissenid shells provide substratum; increasing the initial standing stock of algal cells during the spring, particularly in habitats that would otherwise be considered marginal. Dreissenids also have improved water clarity in nearshore regions by increasing light saturated growth rates to deeper depths, extending the maximum depth of colonization, and increasing the carrying capacity (i.e. maximum biomass) of Cladophora beds (Auer et al., 2010; Higgins et al., 2008b; Malkin et al., 2008). When in dense stands, Cladophora filaments would, presumably, reduce advective mixing of soluble nutrients excreted by the mussels to the overlying water column; providing Cladophora with a competitive advantage for phosphorus (P) uptake. Recent modeling efforts have indicated that the changes in these drivers (light, P availability, physical habitat) over the dreissenid establishment period, rather than any potential changes in P loading, were the most plausible explanation for the resurgence of Cladophora blooms in the lower Laurentian Great Lakes (Auer et al., 2010; Higgins et al., 2008b). From a management perspective, that dreissenids may facilitate Cladophora blooms in lakes with relatively low concentrations of soluble reactive phosphorus (SRP) is troublesome. Nonetheless, agencies around the Great Lakes region are being asked to develop strategies in order to reduce bloom occurrences. Historically, Pabatement strategies in the Great Lakes have dealt primarily with reducing P concentrations at the lake or lake-basin scale (IJC, 1980; Vallentyne and Thomas, 1978). Such efforts, instituted under the Great Lakes Water Quality Agreement (IJC, 1980), were largely successful in reducing or eliminating Cladophora blooms in the lower Laurentian Great Lakes from the mid-1980s until dreissenid establishment (Auer et al., 2010; Higgins et al., 2008b; Painter and Kamaitis, 1987). Modeling studies have indicated that given improvements in light and available substratum, growth rates of Cladophora are now more sensitive to P availability than prior to dreissenid invasion (Auer et al., 2010; Malkin et al., 2008). It has also been postulated that dense populations of dreissenids in coastal regions may act as efficient ‘nearshore traps’ of P arriving from catchments (Hecky et al., 2004), suggesting that phosphorus in either particulate or soluble form could become available for Cladophora growth and that increased growth rates and higher biomass accrual could occur in proximity to point sources. Here, we address the questions: 1) Are Cladophora growth rates and bloom occurrences in Lake Ontario phosphorus (P) limited; 2) Are Cladophora ‘bloom’ occurrences limited to areas of localized nutrient enrichment; and 3) In the absence of localized

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nutrient enrichment are dreissenids capable of supplying sufficient P in to meet Cladophora growth requirements and produce ‘bloom’ occurrences? Methods Site descriptions The seven sites in this study (Fig. 1), four within Canadian waters (sites 1–4) and three (sites 5–7) within waters of the United States, were chosen to reflect a potential gradient of impact from adjacent watersheds. The sites included locations adjacent to highly urbanized areas (e.g., Site 3, Greater Toronto Area population > 5 million; and Rochester, New York, with a population (metro) >1 million) to locations where adjacent land use was minimal (e.g., Site 7). As land use factors not associated with human population could be important (e.g., agriculture), human population density itself was not used to describe potential variations in Cladophora biomass or indicators of P deficiency. Instead, we utilized conservative chemical tracers of human activities (i.e. chloride, conductivity) and local nutrient concentrations (Total P [TP], SRP, Nitrate [NO3]). Each site was considered as a rectangular box with approximate dimensions: 10 km (horizontal to the shoreline) by ≥1 km (perpendicular to the shoreline). The depth range at each site ranged from 0 to >70 m. However, since >90% of depth integrated Cladophora biomass occurred at depths b20 m (Appendix Fig. 2), water quality data from stations with >20 m were excluded from assessments of nearshore water quality conditions. All sites were colonized by dreissenid mussels with mean densities at each site varying from 462 to 1385 ind. m − 2 at Canadian sites (sites1–4, Fig. 1) and 278–1515 ind. m − 2 at U.S. sites (sites 5–7, Fig. 1) (Pennuto et al., 2012). Field sampling and analytical methods The Canadian and U.S. sites were sampled independently by two research groups using similar methods. A suite of limnological variables (see below) was collected within each site, three to five times from late April–October of 2008. We primarily utilized data from two sampling events that occurred between May and early August, the period of maximum Cladophora growth. Research vessels of each group were outfitted with shipboard flow-through systems, where water was collected from 1 m below the surface at the ship's bow and pumped through a series of instruments. Each data point was time-stamped and geo-referenced. Periodically, water was collected from an intake valve of the flow through system for water

Fig. 1. Map of Lake Ontario with study site locations. Circles represent transects where Cladophora samples were collected.

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standard methods and are described in detail within companion studies (Howell et al., 2012; Makarewicz et al., 2012a, 2012b). Onshore–offshore transects were established within each study area (n = 2 transects at all Canadian sites; n = 3 at all U.S. sites) (Fig. 1) for sampling the benthic algal community using SCUBA. Transects were sampled at least twice during the main Cladophora growth period (Jun–Aug). Transects at U.S. sites were sampled at 2 m, 5 m, 10 m, and 20 m depths. Transects at Canadian sites were sampled at 3 m, 6 m, 10 m, and 18 m depths. At each site/depth Cladophora filaments were harvested from 3 to 5 quadrats (0.15 m 2 Canada; 0.25 m 2, U.S.) over rocky habitats, cleaned of debris and macroinvertebrates, frozen, and returned to the laboratory. Areal biomass was estimated by weighing the total ‘wet mass’ in each quadrat, weighing a sub-sample, drying the sub-sample at 60 °C to constant weight, and calculating total dry mass in each quadrat from the wet weight/dry weight ratio of the sub-sample. For U.S. sites, phosphorus contained within Cladophora tissues (QP) was determined as follows: one Cladophora sample from each site/depth was thawed, rinsed with deionized water, and dried to constant weight at 60 °C. Dried Cladophora tissues (0.80 to 59 mg dry weight) were then digested using the sulfuric acid–nitric acid digestion procedure (APHA 4500-P) prior to analysis by the automated (Technicon Autoanalyser) colorimetric ascorbic acid method (APHA, 2005). The remaining Cladophora samples were thawed and pressed between layers of paper towels at a standard pressure to obtain wet mass. Samples were then freeze–dried (− 40 o C) in a Labconco freeze drier (Model 77535) for up to 24 h and reweighed to obtain dry mass. Samples were combusted at 500 °C for 2 h in a muffle furnace (Lindberg/Blue Model BF51766A-1) and the ash-free dry mass (AFDM) was calculated as the difference in mass between dried and combusted samples. Cladophora tissues from Canadian sites were harvested from each quadrat for biomass estimates and an additional sample was collected for tissue nutrient analysis. All tissue samples were immediately drained of water and frozen on dry ice. Each sample was freeze–dried and acid digested, and nutrient content was determined using colorimetry (OMOE, 2010; OMOE, 2011). Data manipulation and statistics

Fig. 2. The depth distribution of a) Cladophora biomass, b) tissue P concentration (QP), and c) the cumulative biomass at seven sites in Lake Ontario. Symbols represent the study sites as follows: Cobourg (closed circle), Ajax (closed triangle), Toronto (closed diamond), Grimsby (closed square), Oak Orchard (open circle), Rochester (open square), and Mexico Bay (open triangle). The dashed horizontal line in panel b represents the value (0.16% DM) below which Cladophora growth becomes increasingly Plimited. For panel c, biomass at depths other than those directly measured were estimated using site-specific empirical relationships between biomass and depth (see Methods) and normalized to the total depth-integrated biomass at each site.

column nutrients. We refer to these locations within each site as stations, and they were held constant between each sampling cruise. Conductivity, dissolved organic carbon (DOC) fluorescence, hydrocarbon fluorescence, and turbidity data were collected from instruments associated with the shipboard flow-through system, and nutrient data (SRP, TP, and chloride) from water samples. Hydrocarbon fluorescence, DOC fluorescence, and chloride were measured only at Canadian sites (sites 1–4, Fig. 1), and were used to evaluate the utility of conductivity (which was measured at all sites) as a tracer of human activities in adjacent watersheds. Chemical analyses were conducted using

Frequency distributions (data not shown) of chemistry data indicated that, in almost all cases, values were non-normally distributed, instead being strongly right skewed. Since skewed distributions can affect estimates of population centroids (i.e. population means), we reported median values in addition to means and standard deviations. Common transformations were unsuccessful in normalizing these distributions for comparison tests. Therefore we used a nonparametric method, an ANOVA on rank data test in combination with Dunn's post hoc tests, to estimate the significance of differences in median values for physical and chemical variables between sites. For each site, mean Cladophora biomass for a specific depth (e.g. 2 m) was calculated by averaging values collected from the two transects. We used an exponential decay function to estimate values at depths where data were not collected. In all cases these non-linear regression relationships were significant (p b 0.01) with R 2 values > 0.83 except the Cobourg site (R 2 = 0.60). Estimates of depthintegrated biomass summed values from each depth, assuming a slope of one (i.e. 1 m − 2 of lake-bottom per 1 m increase in depth) and 100% substratum availability. Differences in depth-integrated biomass between sites using this approach reflected differences in growth, removing slope and substratum availability as complicating factors. However, extrapolating from our estimates of depthintegrated biomass to estimates of total biomass at each site, or at other sites in Lake Ontario, would require more detailed information on the slope of the lake-bottom and substratum availability than is currently available.

S.N. Higgins et al. / Journal of Great Lakes Research 38 (2012) 116–123

Modeling A Cladophora growth model (CGM), previously calibrated and field tested in Lake Erie (Higgins et al., 2005a; Higgins et al., 2006) and Lake Ontario (Malkin et al., 2008), was used to assist in the interpretation of field collected data. The model was used to assess how variations in SRP, water clarity (kPAR), and temperature would affect depth-integrated Cladophora biomass and its depth distribution. The model is fully described in Higgins et al. (2005a, 2005b, 2006). Model simulations were conducted for a period of 184 days (May 01–Oct 31). Solar irradiance was held constant between model runs at values found in 2002 over Lake Erie (Higgins et al., 2006). Daily water temperature data were available from temperature loggers deployed at the Cobourg site for the duration of the study. Extinction coefficients for PAR (kPAR) were calculated from an empirical relationship between kPAR and turbidity and allowed to vary with station depth (Higgins et al., 2005a). Results Chemical characteristics We primarily used conductivity as a tracer of human activities as it was routinely collected by both groups of investigators. Conductivity was linearly correlated with other chemical tracers of human activity such as chloride (n = 546, r = 0.99, p b 0.001), hydrocarbon fluorescence (n = 501, r = 0.77, p b 0.001), and DOC fluorescence (n = 473, r = 0.82, p b 0.001) at sites 1–4 (Fig. 1). Chloride, hydrocarbon fluorescence and DOC fluorescence were not collected at sites 5–7. Conductivity values across all sites and depths during the May–August period were highly variable, ranging from 271 to 635 μS cm − 1 (n = 486). Spatial and temporal variations in conductivity were highest at stations with shallow depths (b1 m) and declined with subsequent increases in station depth (Fig. 3), suggesting inputs of terrigenous

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origin. Offshore stations (> 20 m station depth) had relatively low and uniform conductivity values during the May–June (n = 75, median = 308) and July–Aug (n = 71, median = 303) sampling periods (Tables 1, 2; Fig. 3). Median conductivity values were significantly different among the seven nearshore (≤ 20 m) sites (ANOVA on rank data, p b 0.05), with highest values found at sites (Ajax, Toronto, Grimsby) adjacent to highly urbanized areas in western Lake Ontario (Fig. 4). Lowest values were found at two sites in central Lake Ontario (Oak Orchard, Cobourg), with intermediate values found at other central and eastern sites (Rochester, Mexico Bay). As with conductivity and concentrations of nutrients (see below), turbidity values were non-normally distributed (right skewed, data not shown). Across all sites and depth turbidity values ranged from 0.1 to 46.3 NTU (n = 479, median = 1.3), and variability declined with increases in station depth (Fig. 3). Median turbidity values were significantly different among sites (ANOVA on ranks, p b 0.01), with highest values found at sites (sites 5–7) along the southern and eastern areas of the lake (Tables 1, 2). Lowest turbidity values were associated with sites (sites 1–4) along the northern and western portions of the lake (Table 1, 2). These turbidity data were used to estimate Secchi depths using an empirically derived power function from data collected at sites 1–4, as Secchi data were not routinely collected at sites 5–7. The derived function was as follows: Y = 3.21 · X − 0.77 (n = 108, R 2 = 0.64), where Y represents Secchi depth (m) and X represents turbidity (NTU). Estimated Secchi depths, calculated from median turbidity values at each site, ranged from 1.5 to 5.4 m. Turbidity values were not significantly correlated with conductivity (p > 0.05) across the seven sites. Distributions of SRP and total P concentrations were similar to those described for conductivity and turbidity; values were non-normally distributed (right skewed) and variability declined with increases in station depth (Fig. 3). At most sites median SRP concentrations were ≤1 mg m− 3 during the May–June and July–August sampling periods

Fig. 3. Water quality variables as a function of station depth in Lake Ontario during May–August 2008. All sites, dates, and depths are included.

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Table 1 Water quality conditions at nearshore (b20 m depth) and offshore sites in Lake Ontario during May–June 2008. N values represent the number of stations where samples were collected. Site

Cobourg Ajax Toronto Grimsby Oak Orchard Rochester Mexico Bay Offshore (> 20 m)

N

18 10 36 21 22 28 27 75

Conductivity (μS cm− 1)

Turbidity (NTU)

Mean

Median

Mean

Median

Mean

Median

Mean

Median

309 ± 5 326 ± 12 336 ± 44 318 ± 9 313 ± 39 324 ± 48 311 ± 13 310 ± 15

310 322 319 316 301 306 309 308

0.5 ± 0.4 1.1 ± 0.4 1.1 ± 1.5 1.3 ± 2.7 1.8 ± 0.8 3.4 ± 3.0 2.1 ± 1.6 1.0 ± 0.8

0.4 1.1 0.7 0.7 1.6 2.1 1.7 0.8

0.1 ± 0.0 2.9 ± 6.8 2.0 ± 8.4 0.1 ± 0.2 1.6 ± 0.9 1.1 ± 1.3 0.9 ± 0.6 0.9 ± 1.9

0.5 0.7 0.5 0.5 1.4 0.9 0.8 0.1

5.7 ± 1.6 11.9 ± 11.4 10.5 ± 16.4 7.2 ± 9.8 10.7 ± 4.1 11.0 ± 8.8 12.8 ± 7.9 7.5 ± 9.6

5.0 8.5 7.0 5.0 9.7 9.1 10.5 7.8

(Table 1,2). Higher median values, which were ≤2.3 mg m− 3, were found at the Oak Orchard and Rochester sites (Table 1,2). Median Total P concentrations were generally b10 mg m − 3 during the May– June and July–August sampling periods, except at the Mexico Bay site during the May–June period and Toronto and Rochester sites during the July–August period (Tables 1,2). Total P and SRP were not significantly correlated with conductivity (p> 0.05). Cladophora biomass and nutrient status Depth-integrated Cladophora biomass varied by 6 × between sites (Fig. 5). Greater than 90% of the site-to-site variability in depthintegrated biomass occurred at depths ≤5 m, and at deeper depths biomass values were similar (Fig. 2a). At shallow depths tissue P concentrations were generally below the threshold [0.16% dry mass (DM), (Auer and Canale, 1982)] of P-sufficiency (Fig. 2b). At all sites except Toronto and Ajax, tissue P values at shallow depths (≤3 m) were ≤0.06% DM, the threshold required for positive growth (Auer and Canale, 1982; Vallentyne and Thomas, 1978; Wong and Clark, 1976), during the July–August sampling period (Fig. 2b). Both depth-integrated Cladophora biomass and estimates of areal biomass at shallow depths (≤3 m) were linearly correlated with conductivity (Fig. 5). Tissue P values at these shallow depths (≤3 m) were moderately correlated (p = 0.06) with conductivity (Fig. 5). Increases in depth at most sites were associated with increases in QP (Fig. 2b). Such increases in QP with depth reflect the inability of Cladophora to fully utilize internal stores as light limitation becomes an important factor controlling growth rates (Malkin et al., 2008). Model sensitivity analysis Increases in water clarity (Δ Kd = 0.15) at sites with SRP concentrations typical of ‘low impact’ sites (e.g. Cobourg) were capable of increasing depth-integrated biomass by ~ 2×, with increases from background occurring primarily at intermediate (4–15 m) depths (Fig. 6a). However, such increases in water clarity did not increase model outputs in shallow depths (b5 m) to values found at ‘high impact’ sites (Fig. 6a). Variations in water temperature (from −2.5 °C to

SRP (mg m− 3)

Total P (mg m− 3)

+2.5 °C) at ‘low impact’ sites had relatively minor effects on depthintegrated biomass or the depth distribution of biomass (data not shown). Increases in depth-integrated biomass, and changes in the depth-distribution of biomass, consistent with that found between ‘low impact’ and ‘high impact’ sites were attainable through small (+0.5 mg P m − 3) increases in SRP (Fig. 6b). Model simulations for site 6 (Rochester), based on median SRP concentrations during the July–Aug period at that site (Table 2), suggested that depthintegrated biomass would be expected to be much higher (8×) than found in situ (Fig 6c). When simulations were conducted with cellular P (QP) values instead of SRP, biomass estimates were similar to measured values (Fig. 6c). Discussion Conductivity, chloride, hydrocarbon fluorescence, and DOC fluorescence (and other compounds) are all useful chemical tracers of human activities in adjacent watersheds, especially so in nearshore waters. Concentrations of chemical tracers and nutrients were generally highest within tributaries or other point sources, declining with distance as plumes mix with surrounding waters (Howell et al., 2012; Makarewicz et al., 2012a, 2012b). In some locations, particularly near urban centers and areas of restricted water circulation (e.g., harbors, embayments), larger areas of tracer and nutrient enrichment can occur through the cumulative effect of multiple tributaries and discharges. Not surprisingly, highest conductivity values were found at sites in western Lake Ontario adjacent to highly urbanized centers (i.e. Toronto, Ajax) and lowest at sites in central and eastern Lake Ontario (Mexico Bay, Oak Orchard, Cobourg) that were not strongly influenced by local tributaries. At these latter sites, conductivity values (≤ 310 μS cm − 1) were similar to offshore values that we refer to as ‘background’. Cladophora growth and biomass accrual were not uniform across Lake Ontario. Depth-integrated biomass varied by 6× between sites, with the majority (~ 90%) of these site-to-site differences occurring at shallow depths (≤5 m) where growth rates were P limited. These data provide compelling evidence that increases in biomass at ‘impacted sites’ were primarily driven by increased P-availability, rather

Table 2 Water quality conditions at nearshore (b20 m depth) and offshore sites in Lake Ontario during July–Aug 2008. N values represent the number of stations where samples were collected. Site

N

Cobourg Ajax Toronto Grimsby Oak Orchard Rochester Mexico Bay Offshore (> 20 m)

18 10 38 16 21 27 26 71

Conductivity (μS cm− 1)

SRP (mg m− 3)

Turbidity (NTU)

Total P (mg m− 3)

Mean

Median

Mean

Median

Mean

Median

Mean

Median

300 ± 3 306 ± 2 338 ± 65 324 ± 5 301 ± 2 317 ± 37 308 ± 6 305 ± 7

300 306 317 323 301 304 308 303

1.2 ± 0.9 1.8 ± 0.5 3.1 ± 7.1 1.3 ± 0.7 2.3 ± 0.7 4.6 ± 8.4 3.7 ± 1.5 1.7 ± 0.9

0.9 1.7 1.0 1.2 2.1 2.7 3.2 1.8

0.1 ± 0.0 0.1 ± 0.6 0.7 ± 7.0 0.8 ± 0.7 2.0 ± 0.7 1.5 ± 0.5 2.1 ± 0.4 1.0 ± 1.1

0.1 0.1 0.1 0.4 2.3 1.5 0.8 0.8

7.9 ± 5.0 8.8 ± 1.1 17.1 ± 19.6 8.5 ± 4.3 4.8 ± 1.3 10.3 ± 3.5 9.7 ± 1.9 7.0 ± 2.7

6.0 9.0 11.0 7.0 4.6 9.6 9.5 7.0

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Fig. 4. Median conductivity values at seven sites in Lake Ontario, May–June 2008. Numbers in brackets after site names refer to site numbers in Fig. 1. Letters above bars represent post hoc test results at p = 0.05 level (see Methods).

than other potential factors (e.g. light availability, temperature). This interpretation was supported by the results of a sensitivity analysis using a Cladophora growth model (CGM) recently field tested and validated in Lake Erie and Lake Ontario (Higgins et al., 2005a; Higgins et al., 2006; Malkin et al., 2008). The sensitivity analysis indicated that variations in water clarity (Δ Kd = 0.15) or temperature (from −5 °C to + 5 °C) at SRP concentrations typical of our ‘low impact’ sites (0.1–0.5 mg P m − 3) could not account for increases in the depth-integrated biomass, or the changes to the depth distribution of biomass, found at higher impact sites. In contrast, modeled results for small increases in SRP (+0.4 mg m − 3) were entirely consistent with increases in depth integrated biomass, and changes in the depth distribution of biomass, between ‘low impact’ and ‘high impact’ sites. At some sites (5–7), model simulations using site-specific median SRP concentrations estimated depth-integrated biomass levels that were ~ 8 × higher than found in situ. Such large discrepancies between measured and modeled results at these sites suggested that either model input parameters were inappropriate or that some other factor restricted growth (e.g. low standing stock of akinetes) or increased sloughing (e.g. sand scour). Model performance improved considerably when cellular P (QP) values were used to estimate growth rather than SRP (Fig. 6c) indicating that the discrepancy was most likely associated with our estimates of SRP at these sites. It is certainly possible that our two sampling events during the spring–early summer period were unable to adequately capture the temporal dynamics of SRP at these sites at the resolution needed for modeling Cladophora growth. Cell quotas for P (and other macro-nutrients) are direct measures of nutrient status and are typically less variable on short time scales (hours to weeks) than water column nutrient concentrations in nearshore areas influenced by point sources (Higgins unpublished data). This result also indicates the utility of collecting and analyzing Cladophora tissues for nutrient status within monitoring programs. Thus, while changes in water clarity attributed to dreissenid mussel invasion have most likely altered the depth distribution of Cladophora and increased depth integrated biomass (Auer et al., 2010; Higgins et al., 2006; Malkin et al., 2008) between pre- and post-invasion periods, site-to-site variations in depth integrated biomass within Lake Ontario appear to be primarily controlled by P availability. At least one previous study has suggested that in order to control Cladophora blooms, target SRP concentrations should range between 0.2 and 1.0 mg P m − 3 (Tomlinson et al., 2010). These targets appear

Fig. 5. The relationship between chemical tracers of land use (conductivity) and a) tissue P concentration (y= −0.98+ 0.0034 · X, R2 = 0.45, p = 0.06) at shallow depth (≤3 m), b) Cladophora biomass at 2 m depth (y= −1189+ 3.9 · X, R2 = 0.78, p b 0.01), and c) depthintegrated Cladophora biomass (y= −7450 + 24.9 · X, R2 = 0.92, p b 0.01) at seven sites in Lake Ontario during 2008. Symbols refer to sites where samples were collected (see Fig. 3). Conductivity data represent median values during the May–June period as reported in Table 1. At Canadian sites biomass at 2 m depth was estimated from a site-specific empirical relationship between depth and biomass (see Methods).

useful as upper boundaries. However, as our results demonstrate, site-averaged water column SRP concentrations are frequently at or below these levels even in areas where Cladophora blooms are extensive. This apparent contradiction can occur through several means. First, when Cladophora beds are extensive they have a remarkable ability for P-uptake and storage and can reduce water column SRP concentrations to levels below analytical detection limits (Higgins et al., 2005b). Second, excretion of soluble P by dreissenids occurs near the sediment water interface and dreissenid beds overlain by Cladophora beds likely reduce advective mixing and increase boundary layer thickness. Ongoing studies have demonstrated that, under quiescent conditions, SRP concentrations can be elevated several cm above dreissenid beds (M. Auer, unpublished data). For these

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Fig. 6. Cladophora growth model (CGM) simulations vs. measured data in Lake Ontario during 2008. In panels a and b open circles and dashed lines refer to measured and simulated data respectively for a ‘low impact’ site (Cobourg), and solid circles represent measured data for a ‘high impact’ site (Toronto). Solid lines in panel a represent CGM simulations for increased water clarity (− 0.15 m− 1 kPAR), and in panel b represent increased SRP (+1.0 mg P m− 3), from baseline conditions at the ‘low impact’ site. Panel C indicates the effect of using SRP (dashed line) or QP (solid line) on modeled output compared with measured data (solid circles) at the Rochester site.

reasons, SRP concentrations in the water column overlaying Cladophora beds may underestimate P-availability. We recommend that in addition to monitoring SRP, surveys also collect Cladophora filaments to analyze for cellular nutrients (e.g. QP), which directly reflect the nutrient status of the alga. Following the establishment of dreissenid mussels widespread blooms of Cladophora began to re-appear in the nearshore regions of Lake Erie, Lake Michigan, Lake Ontario, and isolated locations in Lake Huron (Auer et al., 2010; Higgins et al., 2008b; Malkin et al., 2008). By enhancing water clarity and providing shell material that increased suitable physical habitat for the attachment of zoospores and akinetes, dreissenids have made Cladophora growth rates increasingly sensitive to concentrations of their limiting nutrient, phosphorus (Auer et al., 2010; Higgins et al., 2006; Malkin et al., 2008). Median conductivity values during the spring (May–June) period

were a useful predictor of the nutrient status (QP) and the maximum depth-integrated biomass of Cladophora between our sites. Since QP indicated that growth rates in the 0–5 m depth range were strongly P limited, we interpret our results to indicate that Cladophora growth was enhanced in locations associated with point sources of P enrichment. This interpretation was supported by a sensitivity analysis using a Cladophora growth model that has been field tested in both Lake Erie and Lake Ontario (Higgins et al., 2005a; Higgins et al., 2006; Malkin et al., 2008). Further, in locations where point-sources had little influence over water quality (conductivity values approximated ‘background’ levels) Cladophora biomass was below the 50 g DM m − 2 threshold proposed for ‘bloom’ or ‘nuisance’ conditions (Auer et al., 2010; Higgins et al., 2008a). These ‘low-impact’ sites had a range of dreissenid densities, but even at sites (e.g., Cobourg) where dreissenid densities were high (Pennuto et al., 2012) they were apparently incapable of supplying soluble P in sufficient quantities to produce Cladophora ‘blooms’. The metabolic waste products of dreissenids include soluble P in sufficient quantities to meet Cladophora growth requirements in some locations of Lake Ontario (Ozersky et al., 2009). However, the amount of P excreted in dreissenid waste products varies as a function of food quality and quantity (Arnott and Vanni, 1996). Our results demonstrated that in the absence of localized enrichment in Lake Ontario dreissenids were not generally capable of supplying P to Cladophora in sufficient quantities to overcome severely P-limited growth. Areal Cladophora biomass at sites not influenced by localized enrichment was b50 g DM m − 2, suggesting that such levels represented a baseline condition for sites influenced by whole-lake SRP concentrations in the absence of local sources. This finding is particularly important because it suggests that nuisance blooms are generally restricted to areas of localized nutrient enrichment in nearshore areas of Lake Ontario. Cladophora biomass routinely exceeded threshold levels (50 g DM m − 2) at sites affected by nutrient enrichment, sometimes exceeding 100 g DM m − 2. These values, while problematic, are below those found routinely in Lake Ontario during the 1970s (>200 g DM m − 2) before the full effect of nutrient abatement programs were realized and below values (>200 g DM m − 2) routinely found in eastern Lake Erie and western Lake Michigan postdreissenid invasion (Bootsma et al., 2004; Higgins et al., 2005b; Higgins et al., 2008b; Malkin et al., 2010). These data suggest that the current problems associated with Cladophora blooms in Lake Ontario would have been much worse and much more widely distributed had the strict nutrient abatement programs associated with the Great Lakes Water Quality agreement not been fully implemented, and will likely increase if P-loading rates to nearshore waters increases. In contrast, our data also indicate that Cladophora growth rates are strongly P limited in Lake Ontario, including at sites affected by point sources of enrichment. Thus, reductions in growth and ‘bloom’ occurrences are a highly probable response to localized reductions in P-loading to nearshore areas.

Acknowledgments Funding for this research was provided by the Ontario Ministry of the Environment and the New York State Department of Environmental Conservation. Publication costs were provided by Environment Canada and the USEPA. We would like to thank the Ontario Ministry of the Environment Great Lakes field group and the captains and crews of the Monitor VI (Ontario Ministry of the Environment), the Lake Guardian (USEPA) and the R/V Seneca (Buffalo State College). We thank Bruce Grey and Technical Support of Environment Canada for SCUBA support on the benthic surveys at the Canadian sites. Special thanks also to Gary Bowen of the Toronto Regional Conservation Authority for assistance with travel.

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