Grazing rates of crustacean zooplankton communities ... - Celia Symons

Hydrobiologia (2012) 694:131–141 DOI 10.1007/s10750-012-1137-6

PRIMARY RESEARCH PAPER

Grazing rates of crustacean zooplankton communities on intact phytoplankton communities in Canadian Subarctic lakes and ponds Celia C. Symons • Shelley E. Arnott Jon N. Sweetman

•

Received: 28 September 2011 / Revised: 17 February 2012 / Accepted: 24 April 2012 / Published online: 19 May 2012 Ó Springer Science+Business Media B.V. 2012

Abstract Zooplankton grazing can potentially affect the biomass and composition of phytoplankton communities directly and indirectly. Low chlorophyll a concentration for a given TP concentration and simplified fishless food webs lead to the expectation that zooplankton community grazing rates are high in Subarctic regions; however, zooplankton community grazing rates have not been determined for Subarctic lakes/ponds. We estimated zooplankton community grazing rates on phytoplankton in 12 lakes and ponds in Wapusk National Park, Canada using a microcosm grazing experiment. Lakes and ponds differed in zooplankton taxonomic composition, Chl-a concentration, and zooplankton biomass. We found that the grazing rates on the total chlorophyll a (GRTotal) ranged 0–13.7% grazed per day and the grazing rates on the edible (\30 lm, GR\30) chlorophyll a was 0 to 16.7% per day. GRTotal increased with lake Daphnia and cladoceran biomass, as did GR\30, which also had

Handling editor: Mariana Meerhoff C. C. Symons (&) S. E. Arnott Department of Biology, Queen’s University, Kingston, ON K7L 3N6, Canada e-mail: [email protected] S. E. Arnott e-mail: [email protected] J. N. Sweetman Parks Canada, 145 McDermot Ave, Winnipeg, MB R3B 0R9, Canada

a negative relationship with the total in-lake Chla. The calculated zooplankton grazing rates were within the range found for larger, temperate lakes. Keywords Grazing Subarctic ponds Zooplankton Phytoplankton Cladoceran biomass

Introduction Zooplankton grazing affects the biomass and composition of phytoplankton communities directly through consumptive effects of grazing and indirectly through nutrient regeneration (Carpenter & Kitchell, 1984; Sterner, 1989; Vanni & Findlay, 1990). Although nutrient inputs determine the potential biomass of phytoplankton, zooplankton grazing can cause a significant deviation from this maximum (Carpenter & Kitchell, 1988). Many studies have used controlled laboratory settings to determine species-specific grazing rates (e.g., Peters & Downing, 1984; Bertilsson et al., 2003), and some studies have calculated grazing rates for intact zooplankton communities on intact phytoplankton communities (e.g., Cyr & Pace, 1992; Cyr, 1998); however, little is known about the zooplankton community grazing rates in Subarctic lakes/ponds. Subarctic/Arctic lakes were shown to have a lower phytoplankton biomass for a given TP than temperate lakes in a study by Flanagan et al. (2003) that used published data from 433 lake-years (269 different lakes) from latitudes ranging from 41 to 79°N. One

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hypothesized cause of this relationship is higher topdown control of phytoplankton biomass in Subarctic/ Arctic ponds than temperate lakes (Flanagan et al., 2003); however, zooplankton community grazing rates have not been compared between the two regions. The main reason to believe high top-down control may be driving the low chlorophyll a (Chl-a)– TP relationship is that many shallow tundra ponds are characterized by low phytoplankton biomass, yet zooplankton biomass and abundance are higher than in deeper lakes with similarly low Chl-a levels (O’Brien et al., 1979; Rautio & Vincent, 2006). High zooplankton biomass may be maintained despite the low phytoplankton biomass as zooplankton can supplement their diets using a diversity of carbon sources in tundra lakes/ponds, such as bacteria and benthic microbial mats (Tranvik, 1988; Hessen, 1992; Rautio & Vincent, 2007). This may allow zooplankton to maintain high grazing pressure on phytoplankton even when phytoplankton biomass is too low to sustain the zooplankton community biomass. In addition, Subarctic ponds are often characterized as simple fishless systems without vertebrate predators of zooplankton, as many of the ponds freeze solid and are devoid of fish (Dodson, 1975). Simple fishless systems generally have strong control on productivity, as there is low predation on herbivore grazers (Hansson, 1992). Overall, high zooplankton biomass relative to Chla concentration and simple fishless systems characteristic of Subarctic tundra ponds suggests that zooplankton community grazing rates in this region will be relatively higher than in temperate lakes. Within temperate lakes, grazing rates increase with zooplankton biomass (Cyr & Pace, 1992; Cyr, 1998), and vary with the taxonomic composition of the zooplankton community (Pace, 1984). In lab and field studies, cladocerans have higher mass-specific grazing rates than copepods (Pace, 1984; Peters & Downing, 1984), so for a given biomass, the grazing rate of cladoceran-dominated communities should be higher than copepod-dominated communities; however, some field studies have found that cladoceran- and copepod-dominated community grazing rates are similar (e.g., Cyr, 1998). Within cladocerans, large taxa ([1 mm) such as Daphnia spp. have the highest grazing rates, and communities dominated by these large zooplankton have higher grazing rates (Hrba´cˇek et al., 1961; Shapiro 1980; Carpenter et al., 1987). Herbaceous zooplankton can alter phytoplankton

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Hydrobiologia (2012) 694:131–141

species composition and size structure through selective grazing (Carpenter & Kitchell, 1984). Cladocerans primarily consume ‘edible’ phytoplankton \30 lm in diameter (James & Forsyth, 1990), and many copepods select for larger phytoplankton particles, although some species are omnivorous (ChowFraser & Wong, 1985). This results in a shift to inedible phytoplankton in cladoceran-dominated communities (e.g., Carpenter et al., 1987) and edible phytoplankton in copepod-dominated communities (e.g., Stibor et al., 2004). In this study we aimed to quantify the grazing rates of zooplankton communities in 12 tundra lakes/ponds located in Wapusk National Park (WNP), Manitoba. In temperate regions community grazing rates on whole phytoplankton communities range from 3 to 30% of the phytoplankton biomass being grazed per day (Cyr, 1998). We expected that the calculated grazing rates would be higher in these shallow tundra lakes/ponds due to the lack of vertebrate predation on zooplankton, and the presence of large Daphnia spp. (S. Arnott & J. Sweetman, unpublished data). In addition, we expected that grazing rates would be correlated with zooplankton taxonomic composition, with higher grazing rates being associated with higher cladoceran biomass. We measured the grazing rate on both the total and edible (\ 30 lm) fraction of phytoplankton, and we expected that cladoceran-dominated zooplankton communities would have higher grazing rates on edible phytoplankton, whereas copepod-dominated communities would have higher grazing rates on larger phytoplankton.

Methods Study sites and sampling methods The ponds chosen for this study are located in Wapusk National Park (WNP), Canada (Fig. 1). The park is located on the Hudson Bay lowlands, and represents a transition zone between taiga and Subarctic tundra. The park is 11,475 km2 in size and contains [10,000 meltwater lakes and ponds distributed throughout spruce forest, peatland and coastal fen habitats. The ponds vary in habitat type, size and water chemistry, but all are shallow (0.5–2 m). Most of the ponds/lakes did not have macrophytes, and the sediments were flocculant with no obvious algal mats. The 12 ponds chosen for this study were selected from lakes/ponds


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Fig. 1 Map of the location of the 12 study lakes/ponds in Wapusk National Park

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included in a 21-pond nutrient enrichment bioassay study to have a wide range of Chl-a and TP concentrations (Symons et al., 2011). At each of our 12 study lakes/ponds we used a YSI handheld meter (YSI 600XL water quality probe) to measure temperature. We collected 40 l of water *10 cm below the water surface in 4-l cubitainers. We recorded the surface area of the lake, and took GPS coordinates. We sampled the zooplankton community semi-quantitatively using a 25-cm diameter, 80-lm mesh net pulled horizontally through *10 m of water, a method that should be adequate for these shallow lakes/ponds. Zooplankton samples were preserved in 70% ethanol. Upon returning to the lab at the end of each day we used the collected water to set up the grazing experiment and, collect water chemistry samples. Water chemistry analysis was performed at the National Water Research Institute in Burlington, Ontario (Environment Canada), and included analyses for nutrients (TP, NO3–NO2, NH4, TN), and dissolved organic carbon (DOC) according to the protocols described in Environment Canada (1994). Zooplankton for the grazing experiment were collected 10–40 cm below the water surface of each lake/pond using a 1-l container. Water was gently filtered through a container with 80-lm mesh side windows to condense the zooplankton. This process was repeated until 2, 4, 8, 12, 14 and 16 l had been filtered, and live zooplankton condensed from each of these volumes were stored separately in 250 ml containers until the start of the grazing experiment within 4 h of collection. All sampling was completed by helicopter between July 25 and 31, 2010.


phytoplankton a known volume of water was first filtered through 30-lm mesh to remove large phytoplankton and then filtered through a glass fiber filter (Whatman GF/C). Total phytoplankton biomass was determined by filtering a known amount of water though a glass fiber filter (Whatman GF/C). Filters were frozen until extraction. Chl-a concentration was determined within a month after the experiment using a Turner Designs TD700 fluorometer following a 24 h methanol extraction (Welschmeyer, 1994). Nutrients were added to each cubitainer, 89 lM l-1 N was added as a sodium nitrate (NaNO3) solution and 0.81 lM l-1 of P was added as a potassium phosphate (KH2PO4) solution. Nutrients were added to saturate phytoplankton growth rates (i.e., to promote exponential growth throughout incubation) to allow for the calculation of zooplankton grazing rates without the confounding factor of zooplankton nutrient regeneration, which would be higher in treatments with more zooplankton. For each lake the zooplankton were added at target densities of 90.5 ambient lake zooplankton density, ambient density (A), 2, 3, 3.5 and 4 A. There was also a no-zooplankton control to account for phytoplankton growth during incubation. The cubitainers were then incubated outdoors for 3–4 days in a polar bear-proof compound. The cubitainers were incubated in sunlight, and were gently agitated multiple times a day to reduce the effect of phytoplankton sedimentation. After incubation both total and edible Chl-a samples were taken from each cubitainer according to the protocol above, and zooplankton in each cubitainer were collected on 80-lm mesh and preserved in 70% ethanol for later enumeration.

Grazing rate set-up Zooplankton samples Community grazing rates for total and edible (\30 lm) phytoplankton were measured using a protocol originated by Lehman & Sandgren (1985), and modified by Cyr (1998). For each of the 12 ponds/lakes we used 7 microcosms to establish a zooplankton concentration gradient and measured change in concentration of phytoplankton during incubation to calculate the grazing rates. At each lake we filled 7 4-l cubitainers with pond water filtered through 80-lm mesh to allow phytoplankton to pass through, and exclude zooplankton. 500 ml of water was then removed from each cubitainer to obtain measurements of initial total and edible phytoplankton biomass. For the edible fraction of

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Zooplankton were enumerated on a Leica MZ16 dissecting microscope. Zooplankton samples from the grazing experiment were counted in entirety. Copepods were identified to the orders Calanoida and Cyclopodia, and cladocerans were identified to genus or family (i.e., Bosmina, Daphnia, Chydorid, Holopedium). Zooplankton samples from the lakes were enumerated to higher taxonomic resolution (usually species) and using a sub-sampling procedure designed to detect rare species. Successive subsamples were taken from a standardized 100-ml sample and counted until a minimum of 200 individuals was reached. To


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target rare species no more than 30 nauplii, no more than 50 copepodids and no more than 50 individuals for dominant taxa were counted. After the target 200 individuals were reached the remainder of the sample was scanned to detect rare species. Taxonomic keys used include Ward & Whipple (1959), Wilson & Yeatman (1959), Hebert & Hann (1986), and De Melo & Hebert (1994). For each zooplankton sample the first 20 animals of each taxonomic group were measured to calculate biomass using length–weight regression equations from McCauley (1984), Dumont et al., (1975), and Girard & Reid (1990) to be used to assess mass-specific grazing rates. Heterocope septentrionalis were excluded from the biomass calculations, as they are predatory (Kling et al., 1992) and would not contribute to phytoplankton grazing. Grazing rate calculations Following Cyr (1998), realized algal growth rate (r, day-1) was calculated for each cubitainer as: r ¼ lnðCo =C1 Þ=T

ð1Þ

where C0 is the initial Chl-a concentration (lg l-1), C1 is the Chl-a concentration after incubation (lg l-1) and T is the incubation length (days). This was calculated for total (rTotal) and edible (r\30) fractions of phytoplankton. The zooplankton community grazing rate was then calculated from the relationship between realized algal growth rate and zooplankton concentration. Grazing rate (day-1) was calculated as the slope (b) of: r ¼ bðZCÞ þ a

ð2Þ

where r is the realized algal growth per day, and a is the realized algal growth rate in the absence of zooplankton. ZC (relative zooplankton concentration) was calculated as the ratio of zooplankton biomass l-1 in the treatment to ambient lake zooplankton biomass l-1 as the measure of ZC must be relative to ambient pond zooplankton concentration to determine community grazing rates. This calculation of ZC was used instead of the target treatment concentrations (i.e., 0, 0.5, 1, 2, 3, 3.5, and 4 A) as the biomass in these treatments deviated from the target concentrations, probably due to patchiness in lake zooplankton distribution. Both a and b were estimated from linear regression. Grazing rate calculated in this manner is an estimate of zooplankton community grazing rate on

the phytoplankton community as it measures the decrease in the intrinsic rate of phytoplankton growth (day-1) per unit of ambient in situ zooplankton density. This method allows the calculation of grazing rates for intact crustacean zooplankton communities on intact phytoplankton communities, which may be more ecologically relevant than calculated grazing rates for zooplankton grazing on single species of phytoplankton as is often calculated in lab studies (Cyr, 1998). Non-significant relationships between r and ZC were interpreted as evidence that grazing was not significantly controlling phytoplankton biomass, and a grazing rate of 0 was used for all further analysis. The grazing rate on the total phytoplankton community (referred to as GRTotal) with units of day-1 was calculated using rTotal, and the grazing rate on the edible phytoplankton (referred to as GR\30) with units of day-1 was calculated using r\30. To facilitate comparison of the estimated grazing rates with other studies we converted GRTotal and GR\30 to other units. Grazing rates in l lg-1 dry weight of zooplankton day-1 were calculated as the quotient of rates (day-1) and zooplankton biomass (lg dry weight l-1). In addition, percent algae grazed per day was calculated as 100(1-eb), where b is the slope from Eq. 2. Grazing rate correlates Multiple regression was used to determine the lake variables that explained the most variation in estimated grazing rates between lakes. A maximum of 2 explanatory variables were included in each model considered due to low sample size (Quinn & Keough, 2002). The variables used in the models included lake zooplankton biomass, cladoceran biomass, Daphnia biomass, average size of zooplankton, lake area, total Chl-a, edible Chl-a, TP, DOC and lake temperature in all possible combinations of 2 variables. Collinearity of environmental predictor variables was detected if the variance inflation factor of any predictors was [10, and correlated variables were not included in models (Quinn & Keough, 2002). The best models were chosen by using corrected Akaike’s information criterion (AICc), where models within 2 AICc units were included in the best models subset (Quinn & Keough, 2002). From the best models subset, model simplification using ANOVA comparisons was used to determine the model that had the fewest variables that did not lose significant explanatory power (Zuur et al., 2007).

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abundant species (an average of [4% relative abundance for the 12 sites) were Leptodiaptomus minutus and Daphnia tenebrosa and most zooplankton species were rare. Chl-a ranged 0.87–6.48 lg l-1 (range standard error 0.02–0.56), and 72 to 100% of the phytoplankton was in the edible (\30 lm) fraction (Table 1). The Chl-a concentration in these 12 ponds was representative of the range of Chl-a concentration in the 21 ponds from Symons et al. (2011), which ranged 1.2–10.8 lg l-1 and averaged 3.4 lg l-1. TP ranged 3.6–14.4 lg l-1 and averaged 4.6 (Table 1). The Chl-a–TP relationship was not significant (F1,10 = 1.6, P = 0.23). The lake temperatures were high, ranging 17.7–23.2 C and averaging 20.5 C. Grazing rates were calculated for the total phytoplankton community (GRTotal) and the edible portion of the phytoplankton community (GR\30) for 12 ponds in WNP (Table 2). The percent phytoplankton grazed per day ranged 0–13.7% per day for the total phytoplankton community and 0–16.7% per day for the edible fraction of phytoplankton (Table 2). With the model selection both GRTotal and GR\30 had two models within 2 AICc units. The first model for GRTotal had a positive association of GRTotal with Daphnia biomass (r2 = 0.57, P = 0.003) and the second model had a positive association of GRTotal with cladoceran biomass (r2 = 0.55, P = 0.003) (Fig. 3; Table 3). The first parsimonious model for GR\30 had a positive association between GR\30 and Daphnia biomass (r2 = 0.77, P \ 0.001) and the second model had a positive association between GR\30 and cladoceran biomass, and a negative association between GR\30 and total Chl-a (r2 = 0.80, P \ 0.001; Table 3).

As grazing rates often correlate with zooplankton biomass in other grazing studies, the relationship between GR and lake zooplankton biomass (lg l-1) was investigated using linear regression. To determine if cladocerans and copepods differentially grazed on the edible and total phytoplankton assemblages the difference in grazing rates (GRdiff = GRTotal GR\30) was calculated. Relationships between GRdiff and both cladoceran biomass and copepod biomass were investigated using linear regression. Multivariate ordination techniques were used to determine if the grazing rates were related to taxonomic composition of the zooplankton community. Zooplankton biomass was Hellinger-transformed to decrease the influence of rare taxa and samples were centered and standardized (Legendre & Gallagher, 2001). A detrended correspondence analysis (DCA) was first used to indirectly determine gradient length. As the gradient was \3 (1.52) a linear model (principal components analysis, PCA) was used (Quinn & Keough, 2002). The relationship between GRTotal, GR\30 and community composition were tested using linear regression between GRTotal, GR\30 and axis 1, axis 2 scores. Statistical analyses were completed in R (R Development Core Team, 2010).

Results

Fig. 2 Zooplankton community composition for the 12 study lakes/ponds

Zooplankton composition: % biomass (µg L 1)

Zooplankton biomass in our 12 study ponds ranged 11–784 lg l-1, and taxonomic composition varied from 30 to 100% copepod biomass, with most lakes being copepod-dominated (Fig. 2). The most 100

80 Calanoid Nauplii Cyclopoid Daphnia Bosmina Chydorid Holopedium

60

40

20

0 C

CC

DD

G

I

J

Lake

123

K

L

M

N

P

Q


137

Table 1 Characteristics for the 12 study sites including: Latitude, longitude, total Chl-a (lg l-1), % edible (\ 30 lm) phytoplankton, TP (lg l-1), zooplankton biomass (lg l-1; ZB), lake surface area (ha; Area) and temperature (C) Lake

Lat

Long

Chl-a

% Edible

TP

ZB

Area

Temperature

WAP10-C

58.40602

-93.26443

0.87

96

4.6

774.6

0.3

WAP10-CC

58.67040

-93.18800

2.22

85.9

3.6

53.2

16.3

21.26

WAP10-DD

58.66940

-93.19890

2.21

91.6

4.1

57.2

1.0

20.15

WAP10-G

58.34246

-93.26108

2.13

82.2

6.1

416.6

0.1

19.47

WAP10-I

58.34165

-93.29168

0.88

89.2

14.4

784.6

0.8

17.67

WAP10-J

58.38516

-93.34488

3.46

77.0

6.8

169.4

2.3

21.41

WAP10-K

58.35090

-93.23186

2.8

72.1

10.1

11.0

3.1

18.35

WAP10-L

58.66088

-93.21593

6.48

75.5

4.6

229.5

120.7

18.23

WAP10-M

58.65680

-93.18700

4.98

84.3

4.1

392.1

44.8

17.78

WAP10-N

58.04564

-93.65352

5.99

100

5.2

309.2

0.1

23.15

WAP10-P

58.03104

-93.65635

4.19

100

5.7

326.1

0.5

22.67

WAP10-Q

58.39369

-93.38201

22.35

3.13

90.5

4.7

42.5

241.4

22.62

Mean

3.29

87.0

4.6

297.2

36.0

20.46

Standard deviation

1.83

9.3

3.6

265.3

73.6

1.99

We did not find evidence that cladocerans and copepods grazed differentially on edible and total phytoplankton biomass as there was no significant relationship between GRdiff and either cladoceran biomass (F1,10 = 2.64, P = 0.14), Daphnia biomass (F1,10 = 3.80, P = 0.08), or copepod biomass

(F1,10 = 0.34, P = 0.57). There was no significant relationship between either GRTotal or GR\30 and zooplankton biomass (GRTotal: F1,10 = 3.2 P = 0.10; GR\30: F1,10 = 3.9 P = 0.07). PCA axis 1 explained 44% of the variation in zooplankton community composition, and axis 2

Table 2 Results from the grazing experiment including grazing rate on the total phytoplankton community (day-1; GRTotal), grazing rate on the total phytoplankton community per unit zooplankton biomass (l lg-1 dry weight of zooplankton day-1; GRT), % of the total phytoplankton community

grazed per day (% total), grazing rate on the edible portion of the phytoplankton community (day-1; GR\30), grazing rate on the edible phytoplankton community per unit zooplankton biomass (l lg-1 dry weight of zooplankton day-1; GRE), and % of edible phytoplankton grazed per day (% edible)

Lake

GRTotal

GRT

% Total

GR\30

GRE

WAP10-C

0.057 (0.014)

7.4 9 10-5

WAP10-CC

0

0

WAP10-DD WAP10-G

0 0.147 (0.048)

0 3.5 9 10-4

WAP10-I

0.077 (0.023)

9.8 9 10-5

WAP10-J

0.113 (0.023)

-4

6.7 9 10

WAP10-K

0.029 (0.008)

2.6 9 10-3

WAP10-L

0.087 (0.025)

WAP10-M

% Edible

5.5

0.066 (0.018)

8.5 9 10-5

0

0

0

0 13.7

0 0.182 (0.052)

0 4.4 9 10-4

0 16.7

7.4

0.116 (0.028)

1.5 9 10-4

11.0

10.7

0.112 (0.029)

-4

6.6 9 10

10.6

2.8

0.045 (0.007)

4.1 9 10-3

4.4

3.8 9 10-4

8.3

0.079 (0.016)

3.4 9 10-4

7.6

0.030 (0.012)

7.6 9 10-5

3.0

0.027 (0.007)

6.9 9 10-5

2.7

WAP10-N

0.040 (0.009)

1.3 9 10-4

3.9

0.030 (0.011)

9.7 9 10-5

3

WAP10-P

0.026 (0.009)

8.0 9 10-5

2.6

0.102 (0.011)

3.1 9 10-4

9.7

WAP10-Q

0.024 (0.007)

-4

5.6 9 10

2.4

0.025 (0.007)

-4

5.9 9 10

2.5

Mean

0.052

4.2 9 10-4

5.0

0.065

5.7 9 10-4

6.2

Standard deviation

0.045

7.2 9 10-4

4.23

0.055

1.1 9 10-3

5.1

6.4 0

Standard errors of grazing rates are in parentheses

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Fig. 3 Linear regression between log(x ? 1) transformed GRTotal and Daphnia biomass. Error bars represent the standard error of GRTotal, (standard error of b, Eq. 2)

explained 17% of the variation (Fig. 4). High axis 1 scores are associated with high biomass of cyclopoids and chydorids, and low axis 1 scores are associated with high calanoid biomass. High axis 2 scores are associated with high naupliar biomass, and low axis 2 scores are associated with high Holopedium biomass. The overall zooplankton community composition does not likely influence grazing rates in these lakes as GRTotal was not correlated to axis 1 or axis 2 scores (axis 1: F1,10 = 0.7, P = 0.43, axis 2: F1,10 = 0.003, P = 0.95), nor GR\30 (axis 1: F1,10 = 1.1, P = 0.32, axis 2: F1,10 = 0.62, P = 0.45).

Discussion The lakes/ponds in this study had similar high zooplankton biomass relative to phytoplankton biomass and no relationship between Chl-a and TP as other studies in Subarctic and Arctic regions (Flanagan et al. 2003), although overall zooplankton biomass was comparable to studies of zooplankton community grazing rates in temperate regions (e.g., Cyr & Pace, 1992). We expected community grazing rates to be

Fig. 4 Ordination biplot for the principal components analysis of zooplankton abundance of each lake. Percentages represent the variance explained by each PC axis. The letters represent the lakes (e.g., WAP10-C is denoted as C). Zooplankton taxa arrow labels correspond to calanoids (Cala), Bosmina (Bos), nauplii (Naup), Daphnia (Daph), cyclopoids (Cyclo), ostracods (Ost), chydorids (Chy), and Holopedium (Holo)

higher in this study than in temperate regions due to high zooplankton biomass relative to phytoplankton biomass, the simplified fishless food chains and the presence of large Daphnia spp. within the cladoceran community; however, the calculated grazing rates were within the range found in deeper, temperate lakes of similar surface temperatures (Cyr, 1998; Table 2). The calculated grazing rates were similar to grazing rates calculated in Subantarctic regions (2–11% grazed per day, Hansson & Tranvik, 1996), another area with low phytoplankton biomass for a given TP that was hypothesized to have high zooplankton grazing rates (Hansson, 1992). This might suggest that higher top-down grazing control of phytoplankton biomass in simple fishless systems is not the only cause of the low Chl-a for a given TP seen in Northern latitudes. Other causes of the lower Chl-a–TP

Table 3 Results of multiple linear regression of environmental variables to predict GRTotal and GR\30

GRTotal GR\30

Adjusted r2

F

P value

Variable

0.57

15.5

\0.01

log (Daphnia biomass ? 1)

0.017

3.94

0.55

14.3

\0.01

log(cladoceran biomass ? 1)

0.016

3.77

\0.01

0.77 0.80

37.6 23.4

\0.01 \0.01

log (Daphnia biomass ? 1) log(cladoceran biomass ? 1)

0.023 0.023

6.13 6.74

\0.01 \0.01

-0.010

-2.60

0.03

Total Chl-a P values are significant at P \ 0.05

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Coefficient

t value

P value \0.01


relationship, such as nitrogen or micronutrient limitation (e.g., Levine & Whalen 2001; Symons et al., 2011) and benthic algae competition (Flanagan et al., 2003) should be investigated. The grazing rates may have been lower than expected in these ponds because most communities were copepod-dominated. Copepods generally have lower grazing rates on phytoplankton in laboratory studies and are omnivorous, which may have contributed to low community grazing rates (Fig. 2). Low grazing rates on phytoplankton may also be due to zooplankton ingesting a diversity of particles. Bacteria and small detritus as well as phytoplankton would be present in the cubitainers and Arctic zooplankton have been shown to feed on a diversity of particles, particularly Daphnia spp. which feed on bacteria at high rates (Bertilsson et al., 2003); however, we did not quantify the abundance of bacteria. We chose to focus on the crustacean zooplankton grazing on phytoplankton to facilitate comparisons of our grazing rates to other studies using similar methods (e.g., Lehman & Sandgren, 1985; Cyr & Pace, 1992; Cyr, 1998). Low grazing on phytoplankton could also be influenced by a zooplankton preference for benthic algae. Although the species in our study are considered pelagic grazers (Rautio & Vincent, 2007), these species also supplement their diet with benthic algae (Rautio & Vincent, 2006). Because zooplankton are used to having this different energy source, they may have lower grazing rates on the pelagic algae present in the cubitainers. The variance in grazing rates between lakes was consistent with temperate grazing paradigms; grazing rates were positively related to Daphnia biomass and cladoceran biomass (Fig. 3; Table 3; e.g., Peters & Downing, 1984; Bertilsson et al., 2003; Rautio & Vincent, 2006), whereas total zooplankton biomass did not explain the variation in grazing rates, similar to Pace (1984). Some grazing studies have found that grazing rates are related to total zooplankton biomass (e.g. Lehman & Sandgren, 1985; Cyr & Pace, 1992; Cyr, 1998); however, in this study Daphnia biomass may be a better predictor of grazing rate as zooplankton biomass in these lakes was dominated by copepods (Fig. 2), which have low grazing rates on phytoplankton, and are often omnivorous (Chow-Fraser & Wong, 1985). Positive relationships between Daphnia/cladoceran biomass and grazing rates have been attributed to higher grazing rates in cladoceran species, which increase with body size in controlled lab

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feeding experiments (e.g., Peters & Downing, 1984; Bertilsson et al., 2003; Rautio & Vincent, 2006). The effect of cladoceran biomass on grazing rate may be exaggerated in this study as the main component of cladoceran biomass was predominantly large Daphnia spp. (average length 2.2 mm; Fig. 2), which are much larger than Daphnia spp. in studies that found similar grazing rates in cladoceran- and copepod-dominated communities (e.g. average length 1.2 mm Cyr & Pace, 1992; 0.9 mm Cyr, 1998). The overall zooplankton community composition did not explain the variation in grazing rates between lakes. This may be because Daphnia were present in most lakes and the first two principle components of variation were related to taxa that would not be expected to contribute greatly to grazing rates (e.g., chydorids, cyclopoids, Holopedium sp. and calanoids; Peters & Downing, 1984). GR\30 was positively associated with Daphnia and cladoceran biomass similar to GRTotal, but was negatively related to lake Chl-a. Negative relationships between grazing rates and food concentration have been found in temperate lakes (Cyr & Pace, 1992; Cyr, 1998). This relationship may suggest that grazing is controlling the biomass of edible phytoplankton in these lakes, i.e., as grazing rates increase there is a decreasing concentration of edible phytoplankton remaining in the ponds. This pattern could also reflect the negative relationship between zooplankton ingestion rates and phytoplankton biomass found in some lab experiments (e.g., Peters & Downing, 1984). Contrary to expectations we did not find that cladocerans/copepods selected for different size fractions of the phytoplankton community (e.g., total or ‘‘edible’’ phytoplankton). This may be due to the high abundance of Leptodiaptomus minutus in the copepod assemblages, which are small-bodied copepods that can feed effectively on small (1.5–14 lm) phytoplankton and picoplankton (Rautio & Vincent, 2006) which were included in our \30 lm ‘‘edible’’ portion of phytoplankton. In addition, the phytoplankton communities were dominated by smaller, ‘‘edible’’ phytoplankton (Table 1), reducing our ability to detect a difference in the grazing of total and ‘edible’ phytoplankton between copepods and cladocerans. These results provide insight into the grazing rate of Subarctic zooplankton communities, and show that the variation in grazing rates is explained by many of the same variables as in temperate regions. The limitations in extrapolating from these experimental results should

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be acknowledged. This experimental set-up relied on 3 assumptions: (i) That the probability of a phytoplankton cell being consumed is a direct function of encounter rates (ii) grazers are not food saturated (iii) phytoplankton growth is exponential. However, as in this study, adding nutrients and having low phytoplankton biomass minimizes error caused by these assumptions, and provides more accurate grazing rate estimates (Landry & Hassett, 1982). Differences in temperature during incubation between lakes could cause unexplained variation in grazing rates This is unlikely to be an important confounding variable in our studies as there was overlap in incubation times—all incubations were completed between July 25 and August 3 2011. In addition, the calculated grazing rates did not vary systematically with incubation start date. As nutrient loading is expected to increase in Arctic and Subarctic regions due to climate change, understanding the controls on phytoplankton biomass is important in predicting future changes. We expected high zooplankton biomass and the two-level food chain in tundra lakes/ponds would lead to high zooplankton grazing rates; however, this study has shown that the grazing rates were within the range of temperate oligotrophic lake zooplankton community grazing rates. The variation in grazing rates between ponds was similar to temperate grazing paradigms, with Daphnia and cladoceran biomass being the best predictor of zooplankton community grazing rates. Future studies are needed to understand the factors controlling the low Chl-a for a given TP in Subarctic ponds to make predictions about how phytoplankton biomass will be affected by climate change and resulting changes in nutrient loading (Wrona et al., 2006). Acknowledgments We thank Parks Canada and Manitoba Conservation for logistical support. Thanks to J. Larkin, D. Gray, K. Lemmen, A. Courchene and A. Cameron for help with fieldwork. This work was supported by a Natural Sciences and Engineering Research Council Discovery grant [RGPIN/ 229541-2009 to S.E.A.]; Natural Sciences and Engineering Research Council USRA [399782 to C.C.S.]; the Polar Continental Shelf Project [630-10 to S.E.A.]; and the Northern Scientific Training Program [to C.C.S].

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