MICROZOOPLANKTON COMPOSITION AND DYNAMICS IN LAKE ERIE

A Thesis

Presented to

The Graduate Faculty of the University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Kenneth M. Moats

May 2006

MICROZOOPLANKTON COMPOSITION AND DYNAMICS IN LAKE ERIE

Kenneth M. Moats

Thesis

Approved: Accepted:

______Advisor Department Chair Peter J. Lavrentyev Richard L. Londraville

______Committee Member Dean of the College R. Joel Duff Ronald F. Levant

______Committee Member Dean of the Graduate School David M. Klarer George R. Newkome

______Date

ii ACKNOWLEDGEMENTS

I would like to thank my graduate advisor Dr. Peter Lavrentyev for introducing me to the study of aquatic microbial ecology and for the opportunity to conduct this study. The importance of his guidance and expertise in every aspect of this research cannot be understated. I would also like to thank him for the patience, support, and encouragement he provided throughout my tenure.

I would also like to thank the other members of my advisory committee, Dr. Joel Duff and Dr. David Klarer, for the helpful advice and comments offered during the preparation of this manuscript. I would like to extend my thanks to Dr. Klarer and the staff of Old Woman Creek

NERR for logistical support and the sharing of unpublished data on Old Woman Creek.

I thank Dr. Frank Jochem of Florida International University, Dr. Henry Vanderploeg and

Dr. Stuart Ludsin of Great Lakes Environmental Research Laboratory, and the Captain and crew of the US EPA R/V Lake Guardian for logistical support during the Lake Erie experiments.

Special thanks to Dr. Francisco Moore for logistical support throughout this study and the

National Science Foundation and National Oceanic and Atmospheric Administration for financial support.

Finally, I would like to thank my wife and family for the encouragement and support they provided throughout this endeavor.

iii TABLE OF CONTENTS

Page

LIST OF TABLES….…………………………………………………………………….vi

LIST OF FIGURES……………………………………………………………………...vii

CHAPTER

I. INTRODUCTION...... 1

II. MATERIALS AND METHODS...... 9

The Study Sites ...... 9

Estuarine Sites………………………………………………………………….9

Offshore Lake Erie Sites……………………………………………………...11

Herbivory Experiments...... 12

Sample Analysis...... 14

Chlorophyll a Analysis………………………………………………………14

Microscopic Analysis...... 15

Phytoplankton Enumeration via Flow-Cytometry...... 16

Phytoplankton Growth and Grazing Mortality ...... 17

III. RESULTS ...... 21

Water Temperature...... 21

Chlorophyll a ...... 21

Microzooplankton...... 22

iv Phytoplankton Growth and Grazing Mortality ...... 25

Microzooplankton Growth and Production ...... 26

IV. DISCUSSION...... 55

Conclusions...... 61

REFERENCES ...... 62

v LIST OF TABLES

Table Page

1 Experimental sites ...... 30

2 Site data…………………………………………………...... 31

3 Distribution of ciliate taxa across estuarine sites……...... 32

4 Distribution of ciliate taxa across offshore sites...... 33

5 Distribution of dinoflagellate and rotifer taxa across estuarine sites….....34

6 Distribution of dinoflagellate and rotifer taxa across offshore sites...... 35

7 Microzooplankton biomass...... 36

8 Biomass to chlorophyll a ratios……………………...... 40

9 Phytoplankton community growth and mortalilty rates...... 44

10 Phytoplankton growth and mortality rates in size fractions……………...45

11 Phytoplankton mortality rates in dark incubations………………………46

12 Phytoplankton growth and mortality rats based on flow-cytometry…..…47

13 Microzooplankton growth and secondary production……………...……48

14 Average production contribution by microzooplankton groups……...….52

15 Taxon-specific contribution to microzooplankton secondary production………………………………………………………………..53

16 Microzooplankton grazing impact……………………………………….54

vi LIST OF FIGURES

Figure Page

1 Sampling locations in Old Woman Creek National Estuarine Research Reserve...... 19

2 Sampling locations in Lake Erie……………………………………...... 20

3 Microzooplankton community biomass...... 37

4 Relative microzooplankton biomass contribution……………………….38

5 Average total microzooplankton biomass contribution………………….39

6 Total microzooplankton biomass vs. Chl regression for all experimental sites…………………………………………………….…..41

7 Total microzooplankton biomass vs. Chl regression for estuarine experimental sites………………………………………………………...42

8 Total microzooplankton biomass vs. Chl regression for offshore experimental sites………………………………………………………...43

9 Microzooplankton growth vs. phytoplankton mortality dynamic……...... 49

10 Phytoplankton growth vs. microzooplankton growth dynamics……...….50

11 Phytoplankton growth vs. phytoplankton mortality dynamics….……….51

vii CHAPTER I

INTRODUCTION

The pelagic microbial food web

The Microbial Food Web (MFW) is a complex and dynamic assemblage of planktonic microorganisms including viruses, heterotrophic and photosynthetic bacteria and protists, and micrometazoa (Pomeroy 1974; Azam et al. 1983; Sherr and Sherr 2001). The MFW has been recognized as the dominant creator and processor of primary production in both marine (Sherr and Sherr 2001) and freshwater systems (Fahnenstiel et al. 1998).

Constituents of the MFW range in size from 0.02 µm to 200 µm. This range is further divided into size fractions in an effort to describe trophic interactions, although this is not always accurate due to the ability of certain microbial grazers (e.g. dinoflagellates) to ingest prey of similar or greater size (Hansen and Calado 1999). In general terms, the picoplankton (0.2-2µm) size fraction consist mainly of heterotrophic bacteria and autotrophic cyanobacteria (i.e. Synechococcus), although some eukaryotes also fall into this category. The nanoplankton (2-20µm) includes auto- and heterotrophic flagellated protists, smaller diatoms, and some ciliates, whereas diatoms, dinoflagellates, ciliates, and colonial cyanobacteria are major components of the microplankton (20-200µm) size fraction.

1 Plankton are typically assigned the following trophic roles: phytoplankton (algae and cyanobacteria) are primary producers, utilizing photosynthetically active radiation

(PAR) to drive CO2 fixation. Heterotrophic bacteria, and grazers are secondary producers due to their dependence on organic material as an energy source. Portions of primary and secondary production are utilized by primary consumers mainly of which are nano-sized flagellates and small ciliates. These grazers are then consumed by microzooplankton- sized ciliates, dinoflagellates, and sarcodines (e.g. heliozoans). Microplankton form a direct trophic link to crustacean mesozooplankton, other planktonic invertebrates, and fish larvae (Stoecker and Capuzzo 1990) as well as benthic invertebrates (e.g. the zebra mussel, Lavrentyev et al. 1995).

However, this generalized concept is often difficult to apply within the MFW due to wide spread mixotrophy (i.e. the ability to combine or switch between heterotrophic and autotrophic modes of nutrition, Turner and Roff 1993). In many situations, the MFW includes complex trophic cascades, which have significant effects on the energy transfer through pelagic ecosystems and nutrient cycling rates (Legendre and Rassoulzadegan

1995, Lavrentyev et al. 1997). In freshwater systems, rotifers can act as an additional trophic level within the MFW by feeding on algae, ciliates and other protists (McCormick and Cairns 1991; Weisse and Frahm 2002). These invertebrates (Phylum Rotifera) range in size from 60 µm to 2500 µm and are capable of herbivory, bacterivory, as well as predation on autotrophic and heterotrophic protists (Gilbert 1988; Arndt 1993).

The pelagic zones of the Laurentian Great Lakes possess an abundant assemblage of ciliates and flagellates (Taylor and Haynen 1987; Carrick and Fahnenstiel 1990) that exert substantial top-down control of bacteria (Gardner et al. 1986; Pernie et al. 1990;

2 Hwang and Heath 1997; Lavrentyev et al. 1997) and picophytoplankton (Fahnenstiel et al. 1991). Although Lake Erie has the highest microbial plankton biomass of the five

Great Lakes (Fahnenstiel et al. 1998), with the exception of a coastal site (Lavrentyev et al. 2004), no data on microzooplankton herbivory is available in the literature. Over 275 rotifer species have been identified in the Great Lakes, yet their function in MFW dynamics and the trophic cascading effects they produce have not been well studied in these lakes.

Because the MFW constituents possess short (hours to days) generation times, both MFW structure and productivity are highly variable and respond almost instantaneously to both biotic and abiotic factors (i.e. nutrient level, temperature, competition, and predation). Abiotic gradients in natural waters provide a powerful tool for examining relationships between MFW composition and trophodynamics in microbial communities (Turner and Roff 1993). The energy flux through the microbial food web differs across a trophic gradient, that is, from coastal eutrophic conditions to offshore oligotrophic conditions to (Cole 1999). The foundation of these models relies on the amount nutrients (N, P, Si, Fe, trace elements) available to primary (phytoplankton) and secondary producers (bacteria). Elevated nutrient concentrations (eutrophic conditions) are typically found in coastal areas due to allochthonous inputs of nutrients and organic material from the watershed. This system may experience nutrient pulses throughout the open water period due to storm runoff, groundwater input, and resuspension of organic- rich sediments.

Due to shallow depth and turbulent conditions, these nutrients will remain suspended in the water column and thus available to producers. Autotrophic biomass

3 typically exceeds the biomass of heterotrophs in these systems (Gasol et al. 1997) leading

to accumulation of primary production (Uye et al. 1999). On the other hand, the

resuspended sediments often create less than favorable conditions for photosynthesis

following episodic storm events. This combination of eutrophic conditions and the

unstable physical environment results in highly dynamic and diverse algal assemblages including large, small, and colonial taxa and intense benthic-pelagic coupling.

Offshore plankton mainly rely on autochthonous nutrient inputs during times of

water column mixing and upwelling of nutrient-rich bottom water (spring and fall

turnover) and on nutrient recycling within the water column during stratification (Lehrter et al. 1999). In monomictic systems, such as Lake Erie, little or no further nutrient input into the pelagic MFW is expected during stratification. This oligotrophic condition exacerbates competition for limiting nutrients and favor organisms with a high surface area:volume ratio (mostly small cells) or other adaptations, such as mixotrophy (Probyn et al. 1990, Stoecker 1987). The shift in phytoplankton size structure toward smaller cells can make a higher proportion of primary production available to microbial grazers

(e.g. ciliates), thus transferring a higher percentage of primary production through the

MFW (Uye et al. 1999). Of course, the opposite scenario may occur if phytoplankton production is driven by large and colonial species that exceed the size range of the

grazing population, resulting in less efficient energy transfer and trophic decoupling.

The structure of the MFW may contain information on food web function unobtainable via measurements of community rates. To obtain a more detailed and informative model of MFW structure it is necessary to survey (measure, enumerate, and identify) the predominant component species throughout the trophic hierarchy. The

4 functional aspect can be determined utilizing the growth rates of primary and secondary producers and the growth and grazing rates of their predators, heterotrophic nano- flagellates (HNAN) and, especially, the microzooplankton (MZP).

Phagotrophy by microzooplankton is an important mechanism controlling phytoplankton primary production and bacteria biomass in both pelagic (Landry et al.

1995; Putland 2000; Levinsen and Nielsen 2002) and coastal systems (Murrel et al.

2002). These grazers are ubiquitous in both marine and limnetic environments and can exhibit growth rates that exceed those of their prey (Sherr et al. 1988; Hansen and

Christoffersen 1995). In addition to phagotrophy, many ciliates and dinoflagellates are capable of mixotrophy, reverting to autotrophy via algal endosymbionts or the harboring of functional chloroplasts from previously ingested prey (Stoecker 1990; Hansen and

Calado 1999). Microzooplankton exhibit multiple feeding strategies including raptorial and suspension feeding. Several dinoflagellate genera utilize tube feeding or a feeding veil, which allows them to consume prey cytoplasm without having to engulf an entire cell. These mechanisms enable dinoflagellates to feed on cells of similar or greater size than themselves (Hansen and Calado 1999).

In the past two decades, most microzooplankton herbivory studies have relied on the serial dilution technique developed by Landry and Hassett (1982). Dilution experiments have proven their utility by measuring phytoplankton growth and grazing mortality rates simultaneously in a single experiment. Furthermore, the net growth rates of entire assemblages and/or of individual populations can be measured through enumeration of specific taxa before and after incubation (e.g. Fahnenstiel et al. 1995).

5 Finally, this method is relatively simple to set up and exposes the community to minimal

amounts of manipulation and disruption.

The premise of this technique is that diluting sea (or lake) water with pre-filtered

water will decrease the encounter rate of predator (flagellates, ciliates, and rotifers) and

prey (phytoplankton and bacteria) populations. As grazing pressure is reduced across the dilution gradient the prey species will respond with increased growth rates. Linear regression of the apparent growth rates vs. the nominal dilution (i.e. fraction of unfiltered water) allows extrapolation of the specific growth rate at the 100% dilution (absence of grazers), denoted as the y-intercept. Furthermore, the grazing rate of microzooplankton is determined by calculating the absolute negative of the regression line slope. These calculations rely on two assumptions: (1) individual phytoplankton growth is density independent, which usually means that nutrient conditions must be equal across the dilution gradient, (2) microzooplankton grazing impact is inversely proportional to dilution.

The serial dilution technique was originally developed for use in oligotrophic areas of the Pacific Ocean where phytoplankton biomass is almost entirely composed of picoplankton (<2µm). The diverse assemblage of phytoplankton in eutrophic coastal waters can elicit differential responses to dilution and lead to less consistent results

(Fahnenstiel et al. 1995; Lewitus 1998). These results (e.g. non-linear, non-significant) are commonly attributed to ‘saturated feeding’ and contamination (Gallegos 1989;

Landry 1994; Redden et al. 2002) and in many cases are not reported in the literature.

Therefore, utility of this technique in productive waters is currently in question.

6 Although MZP are considered important grazers of phytoplankton, their

composition and dynamics are regularly ignored in grazing experiments. Considering

only phytoplankton mortality rates when investigating MZP impact on primary production does not utilize the full potential of the dilution technique, nor does it give us

insight into the trophic interactions responsible for the rates observed. Examination of

MZP composition and dynamics will help to describe the role of specific taxa, or groups of related taxa, in the transfer of energy through the MFW as well as how this process is influenced by abiotic parameters. Currently, there is no information on MZP herbivory in the Great Lakes, except for one study in Lake Michigan involving Synechococcus

(Fahnenstiel et al. 1991). Also, no information is available regarding MZP secondary

production and their role in carbon transfer in coastal and offshore waters of Lake Erie.

Recently, considerable attention has been given to the occurrences of hypoxic

zones in the central Lake Erie basin. Known as ‘dead zones’, these pockets of low-

oxygen (<2 mg/L) or anoxic water form in the hypolimnion near the end of the summer.

In marine and freshwater systems, planktonic protists have been associated with these

hypoxic/anoxic zones, forming aggregations at their boundaries (Finlay 1990; Fenchel et

al.1995; Park and Cho 2002). Investigation of MFW trophodynamics in these areas is

vital in order to understand the biotic processes involved in the formation and duration of

these zones. Currently, no data pertaining to MZP composition and dynamics in the

hypoxic zone of Lake Erie is available.

The lack of information regarding MFW composition and dynamics in Lake Erie

led to this study with the following objectives:

1) To examine MFW structure and dynamics across a trophic gradient

7 2) To relate microzooplankton composition and dynamics to herbivory rates in

coastal and offshore waters of Lake Erie

3) Test the applicability of the dilution technique in productive inland waters

To address these questions 28 dilution experiments were conducted in estuarine and offshore sites in Lake Erie from May, 2003 to September, 2005.

8 CHAPTER II

MATERIALS AND METHODS

The Study Sites

Estuarine Sites

The estuarine portion of the study was conducted as part of the NSF-funded Microbial

Observatory. Here experiments were conducted at the Old Woman Creek National

Estuarine Research Reserve (OWC). In addition, three coastal sites in the western basin of Lake Erie were also examoined.

OWC lies on the southern shore of Lake Erie, approximately 5km east of the city of Huron, Ohio (Figure 1). At 230 hectares, OWCNERR and Nature State Preserve is the smallest member of the Natural Estuarine Research Reserve system and is unique in that it is the only national reserve on the Great lakes as well as the only freshwater member of the system. Within the boundaries of the Reserve are several terrestrial and aquatic habitats including woodlands, wetlands, prairie lands, swamp forests, mud flats, open water, a lagoon, and a barrier beach. Within each habitat reside highly diverse floral and faunal assemblages.

The estuary proper has been described as the ‘drowned mouth’ (Klarer and Millie

1994) of Old Woman Creek, a small tributary of Lake Erie that drains a 69km² area of

9 primarily agricultural land. Although the term ‘estuary’ generally describes the area at which freshwater, typically from a river, is discharged and mixes with the saltwater of an ocean or sea, the term has been proven applicable through studies involving nutrient up- take (Klarer & Millie 1989), and biomass and diversity of microbial communities(Lavrentyev et al. 2004). Overall, this freshwater estuary performs many of the biotic and abiotic functions of a typical marine estuary including sediment and pollution control, flood conveyance and storage, wildlife habitat, groundwater recharge, and amelioration of storm-water runoff (Klarer 1988; Herdendorf et al. 2006).

A recent examination of the microbial communities at four sites along a stream- lake transect in OWC and adjacent coastal Lake Erie revealed increased microbial biomass and species richness, as well as ammonium uptake and regeneration, along the stream-estuary-lake transect with maximum levels at the confluence (Lavrentyev et al.

2004).

In addition to sites associated with OWC, experiments were conducted at coastal sites near the confluences of the Huron and Maumee rivers and within Sandusky Bay.

These near-river sites, like those of OWC, receive high amounts of allochthonous nutrient input from the surrounding drainage basin but, because they are open to the lake throughout the year, do not experience the extreme physical changes that regularly occur within OWC. The Sandusky Bay site acts as a semi-enclosed estuary site. Its broad area increases residence time allowing for the development of nuisance algal blooms and extended ecological activity.

10

Offshore Lake Erie Sites

The offshore part of the study was conducted within the NOAA-funded International

Field Year on Lake Erie. The study sites include the eastern and western basins but most were located in the central basin (Figure 2). These sites were selected in order to measure grazing across multiple abiotic conditions. The western basin is relatively shallow (mean depth = 7 m) and the most turbid of the three basins due to wind-driven turbulence. Water quality is significantly influenced by the Maumee and Detroit rivers which expel sand, silt, and nutrient laden water collected from their largely agricultural drainage basins. Although thermal stratification occurs here, episodic storm events can destroy such conditions resulting in multiple fully-mixed conditions throughout the summer. Sites within the central basin represented the oligotrophic component of the trophic gradient and allowed for the study of MFW dynamics at various water column stratifications. Maximum depth of this area is 24 m with an average ca. 18 m. This basin experienced stable thermal stratification throughout summer exhibited hypoxia in the hypolimnion in September 2005. Finally, a site in the eastern basin was included in order to obtain lake-wide MZP composition and dynamics. Due to the depth of this portion of the lake, averaging 24 m with a maximum of 63 m, the eastern basin does not exhibit hypoxic zones despite thermal stratification throughout the summer. Water here is of relatively low turbidity as there are no significant river inputs in this region.

11 Herbivory Experiments

At the estuarine sites, water for serial dilution experiments was collected in 20L

polyethylene carboys (40L total) that were pre-washed with 10% hydrochloric acid followed by thorough rinsing with deionized water and finally nano-pure deionized

water. Prior to filling, each container was rinsed with ambient estuarine water. Samples

were taken from the sub-surface by submerging (approx. 30 cm) the container mouth and

allowing the water to slowly fill the carboy to ensure organisms were not damaged. The

carboys were then placed in coolers and transported (approximately 1.5 hours) to the

laboratory at the University of Akron.

Once in the lab, all experimental water was gently passed though a 153µm Nitex

screen to remove mesozooplankton and will represent ‘whole’ water for the dilution

experiment. A portion of the sample was filtered through in-line 3.0µm and 0.2µm Pall

Science capsule filters. The first 0.5-1.0L of filtered water was considered rinse water for

the capsules and disposed. All filtration of experimental water was performed via gravity

filtration in order to minimize physical damage to the plankton (Ferguson et al. 1984).

This 0.2µm filtered water was then mixed with proportions of whole water to produce

concentrations of 100%, 80%, 60%, 30%, and 10% of whole lake water (WLW). Each

-1 concentration was amended with 50µg L (final concentration, KH2PO4) to ensure

nutrient availability would not limit phytoplankton growth across the dilution gradient.

This concentration was within the range of phosphate concentrations measured as part of the on-going monitoring program in OWC (D. Klarer, OWCNERR, pers. communication). Each dilution was then placed in triplicate Nalgene 1-L clear glass bottles. As with all equipment that comes into contact with experimental water

12 (excluding filter capsules), the incubation bottles were soaked in 10% hydrochloric acid

and rinsed a minimum of three times with deionized and nano-pure deionized water. The

samples were capped and placed in an incubator set at ambient temperature and PAR

levels (12:12 light:dark cycle) for a 24-hour incubation period. In addition, a set of

undiluted samples was incubated without nutrient additions (control) to estimate in-situ growth rates (Caron 2001) as well as a triplicate dilution series (including control) that was incubated at ambient temperature but without light (‘dark’ incubations) for the duration of the incubation period.

Initial and final (after 24 hour incubation period) sub-samples from each dilution were taken for enumeration microplankton and Chl a analysis. Aliquots of 100ml were preserved with Lugol’s iodine (1% final concentration) and immediately refrigerated

(4ºC) until analyzed. Finally, triplicate initial and final subsamples were collected on 0.2-

μm 47 mm polycarbonate (Millipore P/N GTTP 04700) or nylon (Nylaflo®, Pall Life

Sciences P/N 66602) filters, placed in 15 mL polyethylene culture tubes, and immediately frozen for chlorophyll a (Chl) analysis (see below).

Offshore serial dilution experiments were conducted aboard the EPA’s research vessel Lake Guardian. In these experiments water was collected from the conductivity, temperature, and depth (CTD) sampling device mounted with a rosette of twelve 8-L

Niskin bottles. Dilution experiment preparation followed the protocol above except for the following modifications:

(1) the dilution series was reduced to 100%, 65%, 30%, and 10% whole water as well as a control line, (2) the dark incubations were not included with these experiments, and (3) there was a nutrient addition of P, N, and Si at the Redfield ratio (16:1:1,

13 respectively) (final P concentration 50 µg L-1). The samples were incubated at ambient temperature in Percival diurnal incubators. The light levels were adjusted as close as possible to ambient (within 20%) and 12:12 h. (4) In experiments involving hypoxic/anoxic hypolimnetic conditions, special precautions were taken in order to prevent exposure of the experimental water to atmospheric oxygen. Prior to sample collection, 2L polypropylene (Nalgene®) carboys and the incubation bottles were purged of atmosphere with low pressure nitrogen vapor and sealed. During water collection, the

Niskin bottles were drained via Tygon® tubing into the carboys while displacing the water with nitrogen vapor. Appropriate capsule filters were placed in-line between the

Niskin bottle and carboy until the desired amount of filtered water was obtained. The capsule filters were then removed and replaced with a 153 µm in-line filter in order to

obtain WLW. The same approach was employed when filling individual incubation

bottles. Just prior to the collection of final samples, incubation bottles were checked for

leaks to ensure a proper seal was maintained throughout the incubation.

Sample Analysis

Chlorophyll a Analysis

For Chl analysis triplicate initial and final subsamples were taken from each

dilution (one subsample from each incubation bottle for finals) and were vacuum-filtered

under low pressure (<5mm Hg) to minimize cell damage and potential loss of

photopigments into the filtrate. Aliquots ranged from 50-250 mL in OWC and 400-750

mL in offshore Lake Erie sites depending on trophic status, turbidity level, concentration

14 of whole water, and filter pore-size. For total Chl, 0.2 µm pore-size polycarbonate filters were used. In experiments where size-fractionated chlorophyll was implemented, 25 µm pore-size nylon screen (Nitex) was used. Chl concentration in the <25 µm size-fraction was calculated by subtracting the Chl concentration on the 25 µm filter from the total concentration (0.2 µm filter). Concentration analysis of Chl was performed utilizing the non-acidic method (Welschmeyer 1994). Filters with collected plankton were placed into

15 mL polyethylene culture tubes and kept frozen (~-20 ºC) until Chl extraction. For extraction, 10 mL of 90% acetone was added to each culture tube ensuring the filter was entirely submerged, covered with aluminum foil, and placed back into the freezer for a

24-hour extraction period. Concentrations were then measured using a Turner Designs

TD-700 fluorometer.

Microscopic Analysis

Microscopic analysis involved identification, enumeration, and measurement of microzooplankton (MZP) to quantify biomass, growth rates, and composition. For all serial dilution experiments, initial and final WLW samples were preserved with acid

Lugol’s iodine (1% final concentration). To determine MZP composition 20-100 mL samples (depending on cell and detritus concentration) were settled in Utermohl chambers and the entire slide examined under an Olympus IX-70 microscope equipped with a SPOT-2 digital camera. For biomass estimates, at least 20 cells (more for abundant taxa) were measured for length and width using an eyepiece micrometer and volumes calculated by approximate geometric shape (Wetzel and Likens 1991). Ciliate,

15 dinoflagellates, and rotifer volumes were then converted to biomass according to Putt and

Stoecker (1989), Mender-Duer and Lessard (2000), and Fahnenstiel et al. (1998),

respectively. MZP identification was based on their morphological characteristics. The following taxonomic keys were used: Foissner et al. 1999; Wehr and Sheath (2003);

Stemberger (1979).

Phytoplankton Enumeration via Flow Cytometry

In addition to Chl analysis, phytoplankton cell counts were obtained via an imaging-in-flow system (FlowCAM; Sieracki et al. 1998). This system represents a combination flow cytometer/progressive scan digital video camera. Cells were analyzed

within continuous flows of 0.2 to 1 ml min-1, depending on phytoplankton abundance.

Every cell passing through the flow chamber was measured by the FlowCAM and data were obtained on cell linear dimensions and chlorophyll content. This redesigned

FlowCAM, which in addition to the features described above, was equipped with an

Argon gas blue laser (Melles Griot 20mW 488 nm) and apochromatic optics (0.85 numerical aperture). This combination improved fluorescence detection and resolution up to 0.5 μm per pixel. In test runs, the instrument was able to detect most phytoplankton cells >3 μm. The flow-cytometry data were verified using conventional microscopic techniques described above.

16 Phytoplankton Growth and Grazing Mortality

Phytoplankton growth and grazing mortality rates were calculated via linear

regression of the apparent growth rates vs. nominal dilution (i.e. fraction of WLW) The

growth rates were determined in each bottle using the initial and final concentrations of

Chl, its size-fractions, and flow-cytometry-based cell using the following equation:

(1) r = ln (Pt/Po) / t

-1 -1 where, r = exponential growth rate (d ), t = time of incubation (d ), and Pt and Po are final and initial population concentrations, respectively. These r-values are then plotted against the dilution gradient in a linear regression to obtain specific growth rates in the absence of grazing (μ, y-intercept) and grazing mortality rates (m, the slope x -1).

Microzooplankton taxon specific growth rate was calculated using the following equation:

(2) r = ln (Bt/Bo) / t

-1 -1 where, r = exponential growth rate (d ), t = time of incubation (d ), and Bt and Bo are

final and initial biomass (µg C L-1 d-1) concentrations, respectively. For biomass

calculations see above.

Secondary production estimates were calculated using the following equation:

(3) MSP = r (Bo)

where, MSP = microzooplankton secondary production (µg C L-1 d-1), r = taxon-specific

-1 -1 exponential growth rate (d ), and Bo = initial biomass (µg C L , see above) of that taxa.

Taxa were deemed predominant if their contribution to total MZP production exceeded

5%.

17 Carbon ingestion rates of MZP communities was calculated using the following

equation (Rivkin et al. 1999):

(4) Ic = (Co*expµ - Co*exp(µ-m)) X 50

-1 -1 where, Ic = the amount of carbon ingested (µg C L d ), Co = total Chl concentration

(µg L-1), µ = phytoplankton growth (d-1), and m = phytoplankton grazing mortality (d-1),

50 = carbon to chlorophyll ratio calculation from Lavrentyev et al. (2004).

The MZP grazing impact on phytoplankton was estimated by calculating the percentage of primary production (%PP) ingested (d-1) using the following equation

(Rivkin 1999):

µ (µ-m) µ (5) %PP = (((Coexp - Co) – (Coexp – Co))/(Coexp -Co)) X 100

-1 where, Co = initial phytoplankton biomass (µg C L ), µ = phytoplankton community

growth rate (d-1), and m = grazing mortality rate (d-1).

Because grazer taxon specific growth rates may vary across the dilution gradient,

time averaged biomass (BTA) was calculated to account for any disparity using the

following equation:

(6) BTA = (B1 – B0)/ ln(B1/B0)

where, B1 and B0 are the final and initial biomass measured for each taxa in undiluted

treatment water (see above).

All data recording and calculations was performed in MS Excel spreadsheets.

Linear regression and ANOVA were used to test the results of grazing experiments and

differences between estuarine and offshore sites, and data sets.

18

Figure 1. Sampling locations in Old Woman Creek National Estuarine Research

Reserve. Location of sample sites associated with OWC. (▲) indicates location of the stream site (Site 1), the estuary mouth site (Site 3), and the nearshore lake site

(Site 4).

19

N 932 Dunkirk Port Colborne Erie Port Dover sampling sites. See Table 1 for site Ashtabula DW M13 Port Stanley E78 Cleveland BE BW 958 . Approximate location of Lake Erie AE Vermillion 5 HE OW C HR SB Leamington Sandusky Windsor 6L Detroit 973 3M Figure 2. Sampling locations in Lake Erie coordinates. Monroe -83.5 -83 -82.5 -82 -81.5 -81 -80.5 -80 -79.5 -79

43 42 Toledo 42.5 41.5

20 CHAPTER III

RESULTS

Water temperature

Water temperature varied due to season and sample depth with estuarine and

offshore sites, respectively (Table 2). Average temperatures for estuarine and offshore

sites were similar at 18.2±1.6°C (SE) and 18.6°C (±1.2). Estuarine sample temperatures

ranged from 7.6°C at site 3 in November (Exp. 15) to 26.5°C at site 3M in July (Exp. 9).

Offshore water temperatures varied less despite multiple sampling depths during periods of water column stratification. These temperatures ranged from 10.9°C in the

hypolimnion of site HE (Exp. 23) to 25.4°C in the epilimnion of site BE (Exp. 22)

recorded only two days prior.

Chlorophyll a

Water column Chl concentrations across all sites ranged from 0.33 to 31.0 µg L-1

at offshore Site M13 (Exp. 19) and estuarine Site 4 (Exp.8), respectively (Table 2).

Within estuarine sites, Chl concentrations averaged 8.2 µg L-1 (± 2.1) with the highest

value observed at Site 4 (Exp. 8) mentioned above and lowest at Site 1 in October (1.36

µg L-1, Exp. 13). It should be noted that the high Chl concentration at Site 4 was observed

following a storm event. This elevated Chl concentration may have been due to the

21 accumulation of cyanobacteria along the coastline, a result of physical forcing by wind

and wave action. Of the 10 sites where measured (Table 10), Chl in the <25µm size

fraction comprise on average 65% (±7.8) of total Chl. The highest proportion of this

fraction was 92.7% recorded from Site 3 in November (Exp. 15). This site also recorded

the lowest proportion of 8.7% in June (Exp. 6). Offshore sites exhibited Chl

concentrations ranging from 0.33 to 7.80 µg L-1, with an average value of 2.7 µg L-1

(±0.62). The lowest offshore value was observed at Site 5 (Exp. 12) in August and the

highest value at the aforementioned Site M13 in June. The two offshore sites where size

fractionated Chl measurements were performed, Sites 6L (Exp. 7) and 5 (Exp.12), the

<25µm fraction comprised 81.4% and 65.2% of total Chl, respectively.

Microzooplankton

MZP taxa identified in this study are listed in Tables 3,4 and included ciliates

(Ciliophora), rotifers (Rotifera), and dinoflagellates (Sarcomastigophora). Choreotrichs

and oligotrichs (referred to as oligotrichs hereon) were the most commonly encountered

ciliates and represented predominant taxa at all but Site 13. The oligotrich

Rimostrombidium brachykinetum or R. velox was a predominant taxa in 90% of all sites.

Other common taxa of this group included R. humile, Limnostrombidium spp.,

Pelagostrombidium sp., and in estuarine sites the loricated oligotrichs Codonella sp. and

Tintinnidium sp. The prostomatids Urotricha farcta and U. pelagica were common in

both estuarine and offshore sites, while Balanion sp. was present in over 50% offshore

sites. Less common ciliates with periodic predominance included the pleurostomatid

Histiobalantium sp., the peritrich Vorticella sp., and the haptorid Mesodinium sp.

22 Rotifers were the next most common and predominant group in estuarine and

offshore sites. All common rotifers collected belonged to the order Ploima and included

Keratella sp, Polyarthra sp., and Testudinium sp. Although rotifer biomass declined offshore, their contribution to total MZP production rivaled that of many ciliate taxa.

Dinoflagellates were common and contributed considerably to total production in

offshore waters but were represented by only three taxa. Gymnodinium sp. and Ceratium

sp. were considered predominant in 65% and 57% of offshore sites, respectively.

MZP biomass over all sites sampled ranged from 1.75 to 135.0 µg C L-1 while averaging 25.1 µg C L-1 (±6.0) (Table 7, Figure 3). This range was observed within the

boundary of the OWC estuary in August 2004 at Sites 1 (Exp. 13) and Site 3 (Exp. 11),

respectively. Estuarine sites exhibited a higher average MZP biomass (34.8 µg C L-1, ±

11.1) compared to offshore sites (16.8 µg C L-1 ±3.9). Offshore biomass ranged from 2.1

to 45.6 µg C L-1 in a hypolimion sample (Site DW, Exp. 21) and an epilimnion sample

(Site BE, Exp. 22) collected in August 2005, respectively. Removing dinoflagellates from total MZP biomass significantly changes only offshore sites, reducing average MZP biomass to 10.8 µg C L-1 (±6.1).

Average ciliate biomass in estuarine sites ranged from 0.7 µg C L-1 (Site 1, Exp.

13) to 82.0 µg C L-1 (Site 3, Exp. 6) while averaging 21.2 µg C L-1 (±7.1). Observed

offshore ciliate biomass was lower than estuarine, averaging 7.5 µg C L-1 (±2.2) and

ranging from 1.0 to 26.9 µg C L-1 in a hypolimnion sample (Site DW, Exp. 21) and

epilimnion sample (Site 5, Exp. 12), respectively. In estuarine sites ciliates averaged 60.2

% of total MZP biomass. In offshore sites this value decreased to 45.9% but was not

significantly different (P>0.05, ANOVA). Average ciliate biomass to Chl ratios were

23 slightly higher in offshore sites compared to estuarine sites with values of 4.75 (±1.6) and

3.14 (±0.9), respectively. Average ratio of all sites combined was 3.94 (±0.9).

Estuarine rotifer biomass ranged from 1.1 to 37.9 µg C L-1 with an average of

10.1 (± 2.9). The lowest observed biomass was observed in Site 1 (Exp. 10), while the

highest biomass occurred at Site 3 in August 2004 (Exp. 11). In offshore sites, rotifer

biomass ranged from 0 to 10.5 µg C L-1 in a hypoxic-hypolimnion sample from Site AE

(Exp. 27) and Site 5 (Exp. 12), respectively. Average offshore rotifer biomass was 3.24

µg C L-1 (± 0.84). This trend was also observed in rotifer contribution to total biomass

where the average contribution to total biomass significantly declined (P< 0.05,

ANOVA) from 43.9% in estuarine sites to 14% in offshore sites.

Dinoflagellates occurred in <1% of estuarine samples, but were common in

offshore sites occurring in 86% of these samples (Table 5). Offshore, dinoflagellate

biomass averaged 6.0 (±2.1) and ranged from 0 to 28.5. No measurable biomass was

observed at two sites, Site 6L (Exp. 7) and Site 5 (Exp. 12). The highest biomass

occurred at Site HE (Exp. 28) in September, 2005. Dinoflagellate’s average contribution

to total biomass increased significantly (P< 0.05, ANOVA) from 0.7% in estuarine sites

to 26.2% at the offshore sites (Figures 4,5).

Average MZP biomass to Chl ratios revealed considerable differences between

estuarine and offshore sites with values of 4.8 (±1.7) and 10.1 (±3.1), respectively (Table

8). Combining all sites produced an average value of 7.4 (±1.7). When dinoflagellates

are removed from MZP biomass calculations the offshore ratio is reduced to 5.6 (± 1.2)

and becomes comparable with the unchanged estuarine average, 4.8 (±1.6). Linear

regression analysis produced a significant positive relationship (P< 0.05) between MZP

24 biomass and Chl concentration in both estuarine (Figure 7) and offshore (Figure 8) sites, as well as all sites combined (Figure 6). In order to observe a significant relationship in the regressions involving estuarine sites and all sites combined, two outlying values were removed. In both regressions the values from Site 4 (Exp. 8) and Site SB (Exp. 16) were excluded from the analysis. As mentioned above, the Site 4 value exhibited an elevated

Chl concentration possibly due to the accumulation of cyanobacteria (mostly Anabaena sp.) at this coastal site following a storm event. Physical forcing via wind and wave action may have driven excessive amounts of this alga towards the shore where it remained until currents dispersed the accumulation offshore. The second value removed from these analyses was obtained from an experimental site in Sandusky Bay. This sample not only revealed a relatively high Chl concentration, but was composed primarily of the filamentous cyanobacteria Planktothrix sp. that is beyond the edible size range of most microzooplankton.

Phytoplankton growth and grazing mortality

Dilution evoked a linear response in phytoplankton growth in 12 of the 28 dilution experiments conducted in this study (Table 9). Phytoplankton grew at >0.1 d-1 in

14 experiments, declined in 10, and did not change appreciably in 4. The maximum growth rate of 1.4 d-1 occurred at Site 4 in June, 2003 (Exp. 2). Site 973 (Exp. 17)

produced the maximum decline (-1.04 d-1) in June, 2005. The average growth rate of

phytoplankton was 0.43 d-1 (±0.14) and 0.37 d-1 (±0.1) in estuarine and offshore waters,

respectively. In two experiments, 12 and 18, phytoplankton growth in the 10% treatment

significantly exceeded that of 100%, but this response was non-linear. In seven

25 experiments, dilution inhibited phytoplankton growth. This type of response was observed when phytoplankton growth in 100% exceeds that of the 10% treatment. The

result is a positive regression slope, of which six were linear (P< 0.05). When

phytoplankton did not respond or was inhibited by dilution growth rates were taken from

the 100% treatment.

Grazing mortality >0.1 d-1 was observed in 14 experiments. MZP grazing rates in

estuarine and offshore waters was 0.51 d-1 (±0.15) and 0.47 d-1 (±0.10), respectively. In

those experiments, where both grazing mortality and phytoplankton growth rates were

measured, their ratio was 1.2 and 1.3 in estuarine and offshore waters, respectively.

Size fractionated Chl showed that large and small-sized phytoplankton responded

to dilution differently. Typically, the large fraction either did not respond to dilution or

declined in diluted samples, whereas the smaller fractions increased across the dilution

gradient (Table 10). Flow cytometric direct cells counts further illustrate this trend

(Table 12). Dark incubations stimulated grazing in several experiments (Table 11). The

effect of phytoplankton size on herbivory was similar in the light and dark experiments.

Microzooplankton Growth and Production

MZP community growth >0.1 d-1 was observed in 16 experiments. Community growth rates averaged 0.51 d-1 (±0.07) across all sites studied (Table 13). In estuarine

sites, MZP growth rates ranged from 0.12 d-1 to 1.02 d-1 (Exps. 11 and 2, respectively)

while averaging 0.41 d-1 (±0.09). Offshore, MZP growth average was 0.51 d-1 (±0.11)

with a range of 0.1 d-1 (Exp. 22) and 0.95 (Exp. 7), respectively. MZP growth was

observed in 64% of estuarine experiments and 50% of offshore experiments. Ciliate

26 growth in offshore experiments ranged from 0.0.1 d-1 (Exp. 23) to 0.61d-1 (Exp. 7) with

an average growth rate of 0.46 d-1 (±0.09). In estuarine experiments, ciliate growth

ranged from 0.18 d-1 (Exp. 3) to 1.31 d-1 (Exp. 2) while averaging 0.67 d-1 (±16). Ciliate

growth occurred in 57% and 64% of offshore and estuarine experiments, respectively.

Rotifer growth in offshore experiments ranged from 0.12 d-1 (Exp. 7) to 0.74 d-1 (Exps.

22, 26), and averaged 0.53 (±0.17). In estuarine experiments, average rotifer growth was similar at 0.67 d-1 (±0.06) and ranged from 0.44 d-1 (Exp. 11) to 0.82 d-1 (Exp. 8).

Dinoflagellates were observed at 86% of offshore sites ranging in growth from

0.1 d-1 (Exp. 26) to 0.88 d-1 (Exp. 21). Average dinoflagellate growth in offshore

experiments was 0.50 d-1 (±0.13). Growth occurred in one estuarine experiment with a

growth value of 0.13 d-1 (Exp. 4).

Microzooplankton community secondary production was measured in 16 of 28

experiments ranging from 0.74 ug C L-1 d-1 (Exp. 21) to 62.1 ug C L-1 d-2 (Exp. 6).

Average community production was 6.6 ug C L-1 d-1 (±2.5) and 18.3 ug C L-1 d-1 (±6.7) in offshore and estuarine experiments, respectively. Figure 9 displays the significant (P=

0.02) effect of MZP community growth on MZP grazing rate.

The contribution of oligotrich ciliates and nano-sized ciliates (Group 2) to total production remained consistent between offshore and estuarine waters (Table 14). Other ciliates, many of which did not contribute more than 5% of total production individually

(Table 15), doubled their average contribution to total production in estuarine sites compared to offshore sites. The rotifers showed a slight increase in average production contribution in estuarine waters (Table 14) although their average biomass at these sites was triple that of offshore sites (Figure 5). As with average biomass contribution,

27 dinoflagellates average contribution to production increased considerably in offshore

sites (23.3%) compared to estuarine sites (0.3%). Taxa responsible for the bulk of MZP secondary production included the choreotrichs Rimostrombidium brachykinetum, in both offshore and estuarine waters, and R. velox at the estuarine sites along with the oligotrich,

Pelegostrombidium sp. (Table 15). Rotifer biomass and production contribution was dominated by Keratella sp. in estuarine sites and Polyarthra sp. contribution was substantial at both estuarine and offshore sites. Although relatively absent from estuarine sites, the dinoflagellates Ceratium sp. and Gymnodinium sp. contributed substantially to

both average production and time-averaged biomass in offshore sites (Table 15).

Predominant taxa of both estuarine and offshore sites contributed similarly to both total

daily production (63.2% and 63.8%, respectively), and time-averaged biomass (27.2%

and 39.1%, respectively).

In the dilution experiments that produced measurable grazing rates, MZP

production in linear experiments was dominated by oligotrichs (Table 14) while ‘other

ciliates’ and dinoflagellates each contributed less than 10%. In the experiments, where

grazing could not be detected at the community level, oligotrichs contributed far less to

MZP secondary production, while ‘other ciliates’ and dinoflagellate contribution doubled, becoming comparable to that of rotifers and nano-ciliates.

Primary production and carbon flux estimates revealed higher variability in estuarine waters than in offshore waters. The estuarine sites displayed higher primary production rates, MZP grazing pressure and carbon ingestion rates by the MZP community (Table 16). MZP carbon ingested was near or exceeded phytoplankton carbon

production in most estuarine sites. In offshore sites where both primary production and

28 carbon ingestion rates were measured, MZP assimilated nearly 50% of the phytoplankton production.

29 Table 1. Experimental sites. Experiment number (Exp. #), date sampled, season sampled, site identification, and location in decimal degrees (DD). Season: S = summer, F = fall.

Region: E = estuarine, O = offshore.

Exp. # Date Season Site ID Latitude (DD) Longitude (DD)

01 16-Jun-03 S HR 41.4042 -82.5431

02 30-Jun-03 S 4 41.3843 -82.5141

03 28-Jul-03 S HR 41.4042 -82.5431

04 9-Sep-03 F 3 41.3822 -82.5141

05 20-Oct-03 F 3 42.3822 -82.5141

06 10-Jun-04 S 3 43.3822 -82.5141

07 21-Jun-04 S 6L 41.8205 -83.2983

08 28-Jun-04 S 4 41.3843 -82.5141

09 13-Jul-04 S 3M 41.7302 -83.4149

10 26-Jul-04 S 1 41.3728 -82.5128

11 3-Aug-04 S 3 43.3822 -82.5141

12 17-Aug-04 S 5 41.5350 -82.2597

13 24-Aug-04 S 1 41.3728 -82.5128

14 18-Oct-04 F 4 41.3843 -82.5141

15 8-Nov-04 F 3 43.3822 -82.5141

16 8-Nov-04 F SB 41.4613 -82.6723

17 7-Jun-05 S 973 41.7922 -83.3319

18 9-Jun-05 S E78 42.1167 -81.2500

19 10-Jun-05 S M13 42.2500 -80.8000

20 11-Jun-05 S 932 42.7919 -79.2101

21 15-Aug-05 S DW 42.1200 -80.5256

22 16-Aug-05 S BE 41.5795 -80.3912

23 18-Aug-05 S HE 42.5112 -81.1971

24 18-Aug-05 S HE 42.5112 -81.1971

25 15-Sep-05 F 958 41.3166 -82.1535

26 17-Sep-05 F BW 41.5795 -81.4310

27 18-Sep-05 F AE 41.4943 -82.0347

28 10-Sep-05 F HE 42.5112 -81.1971

30 Table 2. Site data. Region designation of sample, layer of water column stratification sampled, water temperature and chlorophyll a concentration for all experiments. See

Table 1 for site identification.

Exp. # Region Stratification Temperature (°C) Chl a (µg L-1) 01 E Mixed 18.7 6.1 02 E Mixed 22.2 1.5 03 E Mixed 23.6 6.9 04 E Mixed 21.7 7.8 05 E Mixed 10.5 4.3 06 E Mixed 18.1 7.6 07 O Mixed 23.5 2.0 08 E Mixed 21.4 31.0 09 E Mixed 26.5 4.5 10 E Mixed 20.3 2.7 11 E Mixed 21.6 14.9 12 O Mixed 22.0 7.8 13 E Mixed 22.3 1.4 14 E Mixed 12.3 4.8 15 E Mixed 7.6 4.1 16 E Mixed 8.5 16.7 17 O Epilimnion 22.1 6.8 18 O Epilimnion 21.0 0.7 19 O Epilimnion 18.5 0.3 20 O Epilimnion 17.4 0.5 21 O Hypolimnion 12.7 1.0 22 O Epilimnion 25.4 3.7 23 O Hypolimnion 10.9 1.3 24 O Metalimnion 15.4 1.6 25 O Epilimnion 22.0 3.7 26 O Hypolimnion 14.0 0.9 27 O Hypolimnion 14.0 1.0 28 O Epilimnion 22.1 5.3

31 Table 3. Distribution of ciliate taxa across estuarine sites. The symbol(•) indicates occurrence and (+) indicates predominant taxa as described in methods. Ciliate taxonomy is based on Foissner (1999). Sites are identified in Table 1.

Phylum CILIOPHORA 1 2 3 4 5 6 8 9 10 11 13 14 15 16 Order Prostomatida Balanion sp. • + • • Holophrya sp. + Prorodon sp. + • • • Urotricha farcta • • • • • • + • + • • • Urotricha pelagica • • + • • • • Order Haptorida Askenasia sp. • • • Cyclotrichium sp. + • Didinium nasutum • • + Heliozoa sp. + • + Mesodinium sp. + • Monodinium sp. + • Order Pleurostomatida Cyclidium sp. • Histiobalantium sp. • • • Pelagodileptus sp. • + • Order Peritrichida Vorticella sp. • + + • + • Order Choreotrichida Codonella cratera • • • + • • • • • Rimostrombidium brachykinetum + + • • + • • + + + + + Rimostrombidium humile • + + + • • • • Rimostrombidium velox + • + + + + + • + • + Rimostrombidium sp. Tintinnidium sp. + • • • • + + • • • • Order Oligotrichida Halteria sp. • • • • • Limnostrombidium viride • • + Limnostrombidium sp. • • • • • • • • • Pelagostrombidium sp. • + • • + • + Other Ciliophora Cyclotrichium sp. • Difflugia sp. • Heliozoa + • • Litonotus sp. • Paramecium sp. • Stentor sp. + + Uronema sp. • Vaginicola sp. • Unidentified Hypotrich • •

32 Table 4. Distribution of ciliate taxa across offshore sites. The symbol(•) indicates occurrence and (+) indicates predominant taxa as described in methods. Ciliate taxonomy is based on Foissner (1999). Sites are identified in Table 1.

Phylum CILIOPHORA 7 12 17 18 19 20 21 22 23 24 25 26 27 28 Order Prostomatida Balanion sp. • • • • • + • • Holophrya sp. • Prorodon sp. • • • Urotricha farcta + • • • + • • + • • • • Urotricha pelagica • • • • • • • • Order Haptorida Askenasia sp. • • • • • • Cyclotrichium sp. • • Didinium nasutum Heliozoa sp. • • • Mesodinium sp. • • Monodinium sp. Order Pleurostomatida Cyclidium sp. • • + Histiobalantium sp. + + • • + + Pelagodileptus sp. + Order Peritrichida Vorticella sp. • + • • • • • • Order Choreotrichida Codonella cratera • • • + • Rimostrombidium brachykinetum + • + • + + + • + • • • Rimostrombidium humile + • • • + • • + • • • Rimostrombidium velox + + + + • • + + + + • Rimostrombidium sp. • • • Tintinnidium sp. • + • • Order Oligotrichida Halteria sp. • • • • Limnostrombidium viride • • + • • Limnostrombidium sp. • + + + • + + + • Pelagostrombidium sp. + • • • • • + • + • • Other Ciliophora Amphileptus sp. • • Cyclotrichium sp. • Enchelydon sp. • • • Heliozoa + Stentor sp. • Uronema sp. •

33 Table 5. Distribution of dinoflagellate and rotifer taxa across estuarine sites. The symbol(•) indicates occurrence and (+) indicates predominant taxa as described in methods. Dinoflagellate and rotifer taxonomy is based on Wehr and Sheath (2003) and

Stemberger (1979), respectively. Sites are identified in Table 1.

Phylum DINOPHYTA 1 2 3 4 5 6 8 9 10 11 13 14 15 16

Order Gymnodiniales

Gymnodinium sp.

Peridinium sp. • • •

Order Gonyaulacales

Ceratium sp. • • + • •

Phylum ROTIFERA

Order Ploima

Asplanchna sp. +

Ascomorpha sp. •

Keratella sp. • + + + + + • + + +

Polyarthra sp. +++• ++++• • + • •

Testudinium sp. + + + + + + + + +

34 Table 6. Distribution of dinoflagellate and rotifer taxa across offshore sites. The symbol

(•) indicates occurrence and (+) indicates predominant taxa as described in methods.

Dinoflagellate and rotifer taxonomy is based on Wehr and Sheath (2003) and Stemberger

(1979),, respectively. Sites are identified in Table 1.

Phylum DINOPHYTA 7 12 17 18 19 20 21 22 23 24 25 26 27 28

Order Gymnodiniales

Gymnodinium sp. + + + + + + + + +

Peridinium sp. • • •

Order Gonyaulacales

Ceratium sp. + • + + + + + • + +

Phylum ROTIFERA

Order Ploima

Asplanchna sp. • + • +

Ascomorpha sp. •

Keratella sp. + + • • • +

Polyarthra sp. + + + + + + + + + +

Testudinium sp. + • + + + • + + •

35 Table 7. Microzooplankton biomass. Biomass (μg C l-1) for ciliates, rotifers, heliozoans

(Helio), and dinoflagellates (Dino) as well as total microzooplankton (MZP) and microzzoplankton excluding dinoflagellates (MZP w/o Dinos)

MZP Exp. # Ciliate Rotifer Helio Dino MZP (w/o Dinos) 1 14.6 8.43 0 0 23.0 23.0 2 2.61 3.49 0.24 0 6.34 6.34 3 6.37 10.4 0 0 16.8 16.8 4 57.8 2.55 0.61 2.13 63.0 60.9 5 8.26 2.48 0 0 10.7 10.7 6 82.0 27 0 0 109.0 109.0 8 7.92 8.45 0 0 16.37 16.3 9 38.8 18.6 0 0 57.4 57.4 10 8.72 1.13 0 0 9.80 9.80 11 59.2 37.9 37.9 0 135.0 135.0 13 0.71 1.05 0 0 1.75 1.75 14 3.24 3.86 0 0 7.0 7.0 15 3.26 4.6 0 0 7.80 7.80 16 11.4 11.3 0 0 22.7 22.7 7 2.33 2.03 0 0 4.30 4.30 12 26.9 10.4 0.48 0 37.8 37.8 17 4.48 4.7 0 0.54 9.72 9.18 18 2.78 0.27 0 2.25 5.2 2.97 19 4.26 1.14 0 2.36 7.8 5.40 20 9.81 3.44 0 6.26 19.5 13.2 21 1.02 0.51 0 0.57 2.10 1.53 22 24.4 8.91 0 12.3 45.6 33.3 23 1.67 4.19 0 15.6 21.4 5.86 24 1.92 2.43 0 7.31 11.6 4.35 25 9.72 3.64 0 6.26 19.5 13.3 26 6.71 0.64 0 1.94 9.29 7.35 27 1.68 0 0 0.48 2.16 1.68 28 7.74 3.03 0 28.5 39.3 10.7

36 160

140 Estuarine Offshore

-1 120

100

80

60

40 Total MZP Biomass ugC L MZP ugC Biomass Total

20

0 1 2 3 4 5 6 8 9 10 11 13 14 15 16 7 12 17 18 19 20 21 22 23 24 25 26 27 28 Experiment Figure 3. MZP community biomass. Total biomass (µg C L-1) of microzooplankton community at each experimental site. Sites have been arranged into estuarine and offshore as described in text. See Table 1 for site identification.

37 100%

80%

60%

40% Contribution

20%

0% 1 2 3 4 5 6 8 9 1011131415167 12171819202122232425262728 Experiment

Ciliates Rotifers Heliozoa Dinos

Figure 4. Relative microzooplankton biomass contribution. Contribution of ciliate, rotifer, heliozoa, and dinoflagellate (Dinos) biomass to total MZP biomass in each experiment. Experiments are grouped into estuarine (1-16) and offshore (7-28) sites. See table 1 for site description.

38 70.0

60.0

50.0

40.0

30.0 * 20.0 Average % Biomass * 10.0

0.0 Ciliates Rotifers Dinos

Estuarine Offshore

Figure 5. Average total biomass contribution. Average ciliate, rotifer, and dinoflagelate

(Dinos) contribution to total MZP biomass in estuarine and offshore sites. (*) indicates significance difference (P< 0.05, ANOVA.)

39 Table 8. Biomass to chlorophyll a ratios. Ratios of microzooplankton biomass (µg C L-1) including dinoflagellates (MZP), microzooplankton biomss excluding dinoflagellates

(w/o Dinos), and ciliate biomass (µg C L-1) to chlorophyll a (Chl) concentration (µg L-1).

Sites are identified in Table 1.

Exp. # MZP:Chl MZP:Chl (w/o Dinos) Ciliate:Chl 01 3.75 3.75 2.38 02 4.23 4.23 1.74 03 2.44 2.44 0.92 04 8.08 7.82 7.41 05 2.50 2.50 1.92 06 14.4 14.4 10.9 08 0.53 0.53 0.26 09 12.9 12.9 8.71 10 3.58 3.58 3.18 11 9.07 9.07 3.98 13 1.29 1.29 0.51 14 1.46 1.46 0.67 15 1.90 1.90 0.78 16 1.36 1.36 0.68 07 2.16 2.16 1.16 12 4.88 4.88 3.47 17 1.49 0.80 0.63 18 6.78 3.86 3.51 19 23.5 16.4 12.9 20 43.4 29.4 21.8 21 2.06 1.50 1.0 22 12.3 9.0 6.59 23 16.0 4.37 1.25 24 3.55 2.39 0.83 25 5.23 3.56 2.59 26 9.81 7.76 7.09 27 2.25 1.75 1.75 28 7.38 2.02 1.45

40 -1 120.00 y = 7.0125x + 0.3357 R2 = 0.4913 p< 0.0001

80.00

40.00 * MZP Biomass ugC L ugC Biomass MZP 0.00 * 0102030

Chl a ug L-1

Figure 6. Total MZP biomass vs. Chl regression for all experimental sites. The symbol

(*) indicates outliers removed from analysis (see text).

41 -1 y = 8.3256x - 3.9798 120 R2 = 0.5052 p=0.009 80

40 *

MZP Biomass ugC L ugC Biomass MZP 0 * 0102030

Chl a ug L-1

Figure 7. Total MZP biomass vs. Chl regression for estuarine experimental sites. The symbol (*) indicates outliers removed from analysis (see text). See Table 1 for list of estuarine sites.

42 y = 3.4796x + 8.8327 50 R2 = 0.3553 p= 0.02

-1 40

30

20

10 MZP Biomass ug C L MZP ug C Biomass

0 0123456

Chl a ug L-1

Figure 8. Total MZP biomass vs. Chl regression for offshore experimental sites. See

Table 1 for list of offshore sites.

43 Table 9. Phytoplankton growth and mortality rates. Phytoplankton community growth

(µ) and mortality (m) rates based on chlorophyll a dynamics; and response to dilution. L

= significant linear regression (P< 0.05), NL = non-linear response to dilution (P> 0.05),

NR = no response to dilution, and D = phytoplankton declined in diluted water, as

described in text. Response to Nutrient Addition (100% vs. Control): + = yes, 0 = no. (†) indicates growth rate reported from undiluted treatment (100%).

Response to Response to Exp. # µ (d-1) m (d-1) Dilution Nutrient Addition 01 0.11 0.4 L 0 02 1.4 1.2 L 0 03 0.45 0.24 L + 04 1.4 0.84 L 0 05 0.53 † 0 NR 0 06 0.31† 0 NR + 08 -0.01† 0 NR + 09 0.59 † 0 NR + 10 0.68† 0 D 0 11 0.64 0.59 L + 13 0.13† 0 NR 0 14 0.04† 0 NR + 15 -0.21 0.2 L 0 16 -0.14† 0 D 0 07 0.23 0.19 L 0 12 0.02 0.07 NL 0 17 -1.04 0.68 L + 18 -0.7 0.18 NL 0 19 -0.27 0.75 L 0 20 -0.41 0.79 L 0 21 -0.06† 0 D 0 22 0.5 0.35 L + 23 -0.29† 0 D 0 24 0.56† 0 D + 25 -0.21 0.32 L + 26 -0.21† 0 D 0 27 0.14† 0 NR 0 28 -0.12 † 0 D +

44 Table 10. Phytoplankton growth and mortality rates in size fractions. Experimental results of growth (µ) and mortality (m) rates based on size-fractionated chlorophyll a dynamics; and response to dilution. L = significant linear regression (P< 0.05), NL = non-linear response to dilution (P> 0.05), NR = no response to dilution, and D = phytoplankton declined in diluted water, as described in text. (†) indicates growth rate reported from undiluted treatment (100%).

Response to Response to µ (d-1) m (d-1) Dilution µ (d-1) m (d-1) Dilution Exp. # <25L <25 L <25L >25L >25 L >25L

06 0.54 0.22 NL 0.68† 0 D

08 0.14 0.13 NL 0.16† 0 D

09 0.83† 0 NR 0.66 0.25 NL

10 0.07† 0 NR 0.46† 0 D

11 0.65 0.61 L 0.62 0.50 L

13 0.32† 0 D 0.28 0.93 L

14 0.35† 0 NR -0.08 0.2 NL

15 -0.55† 0 NR 1.30 1.08 L

16 -0.27† 0 D 0.82 0.15 NL

07 0.29 0.31 L 0.08† 0 D

12 0.38 0.45 L -0.25† 0 D

45 Table 11. Phytoplankton mortality rates in dark incubations. Experimental results of

size-fractionated mortality (m) rates based on Chl dynamics in dark (Dk) incubations; and

response to dilution. L = significant linear regression (P< 0.05), NL = non-linear response to dilution (P> 0.05), NR = no response to dilution, and D = phytoplankton declined in diluted water, as described in text. Sites are identified in Table 1.

Respons e to Response Response m (d-1) Dilution m (d-1) to Dilution m (d-1) to Dilution Exp. # Total Dk Total Dk <25 µm Dk <25 µm Dk >25 µm D >25 µm Dk

06 0.90 L 1.48 L 0 D

08 0 NL 0 NL 0 D

09 0.11 NL 0.47 NL 0 D

10 0.30 L 0.32 L 0 NR

11 0.69 L 0.63 L 0.81 L

13 0 NR 0.09 NL 0.88 L

14 0 NR 0 NR 0 NR

07 0.32 L 0.41 L 0 D

12 0.15 L 0.52 L 0 D

46 Table 12. Phytoplankton growth and mortality rates based on flow-cytometry.

Experimental results of growth (µ) and mortality (m) rates based on size-fractioned Flow-

Cytometric cell counts of phytoplankton. Size ranges are based on equivalence spherical diameter (ESD). The symbol (-) indicates no data available. See Table 1 for site identification.

<4 5-10 11-20 >20 Total Exp # µ m µ m µ m µ m µ m

17 0.71 0 0.91 0 0.93 0 0.76 0 0.86 0

18 0.69 0 0.15 0 0.53 0 0.52 0 0.46 0

19 0.02 0.14 0.34 0.46 0.73 1.6 1.5 3.4 0.36 1.0

20 - - 0.09 0.55 1.3 0 -0.40 0.56 0.21 0.17

21 - - -0.13 0 -0.2 0.17 -0.83 0 -0.44 0

22 - - 1.5 1.4 1.3 1.4 1.9 1.7 1.6 1.6

23 - - 1.4 1.0 1.3 0.61 0.63 0 1.1 0.81

24 0.83 1.7 0.65 1.5 0.59 0.71 0.87 1.2 0.59 1.2

25 - - 2.2 3.1 2.9 4.2 1.7 3.9 1.7 2.1

47 Table 13. Microzooplankton growth and secondary production. Growth rates (d-1) for

ciliates, rotifers, dinoflagellates (Dinos), heliozoans and the microzooplankton

community (MZP). MZP w/o dinos = microzooplankton community growth rate (d-1) excluding dinoflagellate dynamics. MSP = microzooplankton community secondary production (µg C L-1 d-1). MSP w/o dinos = MSP excluding dinoflagellate production.

Experiments are arranged according to region: above dashed line = estuarine, below =

offshore. Sites are identified in Table 1.

Exp. MZP w/o MSP w/o # Ciliates Rotifers Dinos Heliozoans MZP dinos MSP dinos 01 -0.07 0.8 - - 0.34 0.34 7.83 7.83 02 1.31 0.7 - 1.4 1.02 1.02 6.47 6.47 03 0.18 0.52 - - 0.43 0.43 7.21 7.25 04 0.64 0.72 0.13 0.69 0.63 0.65 39.9 39.0 05 0.31 -0.72 - - 0.15 0.15 1.56 1.56 06 0.5 0.7 - - 0.6 0.6 62.10 62.10 08 0.51 0.82 - - 0.68 0.68 11.13 11.13 09 -0.29 -0.27 - - -0.28 -0.28 0 0 10 0.74 0 - - 0.62 0.62 6.09 6.09 11 0.33 0.44 -0.31 -0.29 0.12 0.22 22.22 30.40 13 -0.14 0 - - -0.05 -0.05 0 0 14 0.02 -0.69 - - -0.3 -0.3 0 0 15 -1.6 -0.4 - - -0.75 -0.75 0 0 16 -0.21 -0.34 - - -0.27 -0.27 0 0 07 1.34 0.12 - - 0.95 0.95 4.10 4.10 12 0.61 0.35 - 1.39 0.56 0.56 21.22 21.22 17 0.61 0.64 0 - 0.6 0.62 6.0 5.93 18 0.48 1.79 0.67 - 0.69 0.7 3.58 2.08 19 -0.002 0 -0.4 - -0.3 -0.24 0 0 20 0.05 0.63 0.45 - 0.31 0.31 6.1 3.15 21 0.06 0 0.88 - 0.34 0.04 0.74 0.07 22 -0.2 0.74 -0.02 - 0.1 0.15 4.74 4.91 23 0.09 -1.36 -1.17 - -1.02 -0.7 0 0 24 0.51 -2.2 0 - -0.08 -0.23 0 0 25 -1.17 0.01 -0.53 -0.41 -0.64 -0.7 0 0 26 -0.15 0.74 0.08 - -0.01 -0.03 0 0 27 -0.44 0 0.41 - -0.18 -0.18 0 0 28 -0.02 0.49 -0.1 - -0.03 0.15 0 1.62

48 0.50

0.40

0.30

m (d-1) 0.20

0.10

0.00 r >0 r <=0

Figure 9. Microzooplankton growth vs. phytoplankton mortality dynamics. Average phytoplankton mortality rate (m,d-1) when microzooplankton community biomass increased (r > 0) or did not change/declined (r <= 0) during incubation. Phytoplankton mortality based on linear regression analysis of Chl. Initial and final biomass measured from bottles with no nutrient amendment (control). P= 0.02 (ANOVA).

49

0.40

0.30

) -1 0.20 r (d

0.10

0.00

u >0 u <=0

Figure 10. Phytoplankton growth vs. microzooplankton growth dynamics. Average microzooplankton community growth rate (r, d-1) when the phytoplankton community grows (µ > 0, d-1) or does not change/declines (µ <= 0) during the incubation period.

Phytoplankton dynamics based on linear regression analysis of total Chl.

Microzooplankton dynamics as described in Figure 6a. P= 0.14 (ANOVA).

50

0.60

0.50

0.40

) -1 0.30 m (d 0.20

0.10

0.00

u >0 u <=0 Figure 11. Phytoplankton growth vs. phytoplankton mortality dynamics. Average phytoplankton mortality rate (grazing) (d-1) when phytoplankton grow (µ >0) or do not change/decline (µ <=0) during the incubation period. Growth and mortality rates base on linear regression analysis of Chl. P= 0.001 (ANOVA).

51 Table 14. Average production contribution by microzooplankton groups. Average contribution (%) of MZP groups to total secondary production. Grazing/No Grazing indicate experiments where grazing was and was not detected at the community level (i.e. total Chl).

Grazing No Grazing Offshore Estuarine Group 1: 38.8 6.3 29.0 30.3 Group 2: 18.7 19.9 18.3 19.7 Group 3: 9.7 20.6 8.5 16.4 Group 4: 9.3 19.5 23.3 0.3 Group 5: 24.9 19.5 20.9 26.3

Group 1: Choreotrichs & Oligotrichs Group 2: Nano-ciliates Rimostrombidium velox Rimostrombidium brachykinetum

Rimostrombidium humile Rimostrombidium sp. Pelagostrombidium sp. Urotricha farcta Limnostrombidium viride Balanion sp. Limnostrombidium sp. Halteria sp. Codonella cratera Tintinnidium sp.

Group 3: Other Ciliates Group 4: Dinos Mesodinium sp. Gymnodinium sp. Urotricha pelagica Peridinium sp. Vorticella sp. Ceratium sp. Histobalantium sp. Pelegodileptus sp. Monodinium sp. Group 5: Rotifers Prorodon sp. Polyarthra sp.

Heliozoa sp. Keratella sp. Didinium nasutum Testudinium sp. Vaginicola sp. Ascomorpha sp. Cyclidium sp. Askenasia sp. Enchelydon sp.

52 Table 15. Taxon-specific contribution to microzooplankton secondary production.

Average percent of total MZP daily production contributed by predominant taxa (>5%

Production Contribution) and their average percent contribution to time averaged (TA) biomass. Linear Response = Linear regression (P< 0.05); No Linear Response = Non-

linear regression (P> 0.05), no response, or phytoplankton decline; as described in text.

Linear Response Average % Prod Average % TA Biomass Rimostrombidium velox 18.8 9.5 Rimostrombidium brachykinetum 13.7 5.7 Polyarthra sp. 12.8 6.7 Keratella sp. 8.2 3.4 Pelagostrombidium sp. 6.3 2.1 Total 59.9 27.4

Non-linear Response Balanion sp. 15.2 1.3 Mesodinium sp. 14.3 0.9 Ceratium sp. 10.8 9.9 Keratella sp. 9.2 3.3 Gymnodinium sp. 8.6 1.5 Testudinium sp. 6.9 7.9 Total 65.1 24.8

Estuarine Rimostrombidium brachykinetum 16.4 4.3 Keratella sp. 15.0 4.3 Rimostrombidium velox 13.8 11.3 Mesodinium sp. 7.1 0.2 Polyarthra sp. 5.6 7.2 Pelagostrombidium sp. 5.2 1.2 Total 63.2 27.2

Offshore Rimostrombidium velox 16.6 0.6 Polyarthra sp. 15.3 6.4 Ceratium sp. 11.8 27.0 Gymnodinium sp. 11.5 1.5 Balanion sp. 8.6 3.5 Total 63.8 39.1

53 Table 16. Microzooplankton gazing impact. Phytoplankton primary production (PP, μg

C l-1 d-1), percent of phytoplankton standing stock removed by grazers per day (%Ps) , and MZP carbon ingestion rates (Ic µg C L-1 d-1 ) in estuarine and offshore experimental sites.

Estuarine

EXP # PP %Ps Ic 01 33.8 36.8 113.0 02 105.0 283 212.5 03 155.3 33.5 115.4 04 546.0 230 898.8 05 114.0 0 0.0 06 117.2 0 0.0 08 0 0 0.0 09 131.4 0 0.0 10 93.2 0 0.0 11 476.4 84.5 629.1 13 8.8 0 0.0 14 0 0 0.0 15 0 18.1 37.2 16 0 0 0.0

Offshore 07 22.8 21.8 21.6 12 0 6.9 26.8 17 0 49.3 167.5 18 0 16.5 6.3 19 0 52.8 8.7 20 0 54.6 12.3 21 0 0 0.0 22 92.5 48.7 90.1 23 0 0 0.0 24 43.4 0 0.0 25 0 27.4 51.2 26 0 0 0.0 27 6.7 0 0.0 28 0 0 0.0

54 CHAPTER IV

DISCUSSION

The results of this study indicate that microzooplankton herbivory is a major factor controlling phytoplankton in Lake Erie. Where measured, grazing impact averaged 81% of phytoplankton primary production, ranging from 53% to 350% based on the m:µ ratio. The impact of microzooplankton grazing on phytoplankton standing stock was also significant with ca. 30% of it being removed by grazers per day. The estimates of phytoplankton production and microzooplankton algal carbon ingestion obtained in offshore Lake Erie (6.7 to 92.8 μg C L-1 d-1 and 3.8 to 101 μg C L-1 d-1)

correspond very well to the primary production measured using 14C and 18O isotopes (8.4

to 168 μg C L-1 d-1 Ostrom et al. 2005). Traditionally, MZP grazing has been considered

important in picoplankton-dominated oligitrophic areas of the ocean, where MZP have

been estimated to consume ~60% of phytoplankton primary production (Calbet and

Landry 2004). The results of this study show that MZP can process similar amounts of

phytoplankton primary production in the Great Lakes, including the eutrophic coastal

waters of western Lake Erie.

MZP possess fast turnover rates and contribute substantially to secondary

production in estuarine and offshore Lake Erie. The MZP community growth rate

average was consistent across the trophic gradient at 0.51 d-1, with similar ranges of 0.1 55 to 1.0 d-1. These rates are similar to the growth rates of microzooplankton measured in

June in southern Lake Michigan (Kovalcik 2001). The growth of ciliates in estuarine waters determined in this study (mean 0.67 d-1, range 0.18-1.31 d-1) agrees well with the

data obtained by Stoecker (1983) who measured ciliate growth in an estuary pond (mean

0.55, range 0-1.64 d-1). Specific growth rates of some ciliate taxa were higher in this

study compared to other studies conducted in limnetic waters. For example, the average

growth rate of Balanion sp. observed in this study was 1.31 d-1 (range 0.4 – 1.1 d-1),

doubled that of 0.6 d-1 and 0.65 d-1 reported by Carrias (2001) and Macek (1996),

respectively. Growth of oligitrich ciliates including Tintinnidium sp., Codonella sp.,

Halteria sp. Rimostrombidium sp. as well as the Peritrich Vorticella sp. and the

Prostomatid Urotricha sp. all agreed with those measured in offshore Lake Michigan

(Carrick et al. 1992) Saginaw Bay, Lake Huron (Lavrentyev et al. 1995), and Old Woman

Creek (Lavrentyev et al. 2004).

Community secondary production rates averaged 18.3 µg C L-1 d-1 in estuarine

and 5.8 µg C L-1 d-1 offshore. The offshore rate was similar to the rate of and within the

range of values reported by Kovalcik (2001) in southern Lake Michigan. Ciliates were the most productive group in both offshore and estuarine waters with average rates of 3.4 and 14.6 µg C L-1 d-1, respectively. This offshore value was considerably less than that of

7.8 µg C L-1 d-1 reported by Carrick et al. (1992) from offshore Lake Michigan. Even if

we included those experiments where MZP community did not grow or declined, the average secondary production rates in coastal and offshore Lake Erie in this study would be 11.7 and 3.3 µg C L-1 d-1, respectively. These values are comparable to the secondary

56 production of meso- and macrozooplankton in Lake Erie (0.6 – 10.2 μg C l-1 d-1,

including crustaceans, large rotifers, and zebra mussel larvae, Johannsson et al. 2000).

The shift in MZP composition between rotifers and dinoflagellates in estuarine

and offshore waters (Figure 5) showed minimal impact on the combined production rates

of these groups (estuarine = 6.7, offshore = 5.0 µg C L-1 d-1). The limited role of dinoflagellates in estuarine areas may be explained by turbulence. The feeding strategy of selective raptorial feeders, such as dinoflagellates, is dependent on their ability to locate and actively hunt prey cells. Turbulent estuarine water may interfere with their

locomotion and therefore the efficiency of this tactic. Also, many dinoflagellates are

mixotrophic (i.e. combine heterotrohic and photosynthetic nutrition) and adapted to

nutrient limited but optically clear offshore waters. When light conditions do not meet

their needs they can stop both photosynthesis and grazing (Stoecker et al. 1997). The

highly turbid estuarine water may affect dinoflagellate’s ability to carry out

photosynthesis at appreciable levels resulting in their relative absence from this area.

Ciliate biomass was similar between estuarine and offshore sites, despite the

reduction in rotifer biomass. Factors contributing to this trend may include decreased

resource availability and internal predation. The relatively low phytoplankton biomass in

offshore waters may not support the potential for increased ciliate biomass. Ciliates may

switch to bacterivory in order to maintain the observed concentrations. Alternatively, the

change in predominant ciliate taxa to larger oligitrichs (eg. Limnostrombidium spp. and

Pelagostronbidium sp.) in offshore waters may have led to internal predation of smaller

ciliates (eg. R. brachykinetum). Also, it is well documented that dinoflagellates, for

example Ceratium sp., can prey on ciliates (Smalley et al. 2002).

57 MZP dynamics and composition can determine their community grazing rates.

Most microzooplankton herbivory experiments ignore MZP themselves, focusing rather

on phytoplankton biomass or its proxies such as photopigment concentration. This study

suggests that MZP growth can be a prerequisite for observing appreciable grazing rates at the community level. This is not surprising given the fact that nutrition is required for growth. What must be considered is the cyclic pattern of predator/prey dynamics.

Microbial populations are characterized by short generation times (hours to days) and often oscillate close to their carrying capacity. Microcosm experiments (like the bottle incubations conducted in this study) are necessarily short-term (24 hours or less) to limit the containment artifacts. If these experiments happen to be conducted during the decline phase in MZP dynamics the outcome may suggest that grazing is not influencing phytoplankton biomass. Indeed this may be true for that distinct condition at the time of

sampling, but does not reflect the overall impact of grazing in a water body. There is of course the opposing condition where phytoplankton and MZP are in a state of high growth, resulting in grazing rates at the high end of the physiological range.

These considerations point out a need to conduct multiple grazing experiments, both temporally and spatially, in an effort to measure grazing at different periods of the growth and decline cycle. This will establish an “average” grazing impact in a body of water, as this study has done, that can be compared to areas of contrasting biotic and abiotic conditions. Also, one must keep in mind that community growth and mortality rates estimated in these experiments are the cumulative result of trophic and other interactions between multiple taxa comprising this community. Even within a certain size category there may be species at different states of activity. Examination of specific

58 MZP taxa allows for the finer resolution of MZP grazing impact and productivity

estimates. This is also a desirable but difficult task to accomplish in phytoplankton

communities, which are usually very complex.

Examination of the MZP community indicates that oligotrich ciliates are the key

herbivores in both offshore and estuarine waters. This may be due in part to their flexible trophic behavior (Fenchel and Finlay 1986). This group possesses multiple feeding strategies among and within taxa allowing for the ingestion of a variety of prey.

Suspension-feeding oligotrichs can ingest picoplankton including phytoplankton and bacteria when turbulent conditions prevail. The raptorial feeding strategy allows for the ingestion of nanoplankton as well as microplankton including diatoms and small ciliates in areas of low turbidity and low turbulence (i.e. offshore waters).

Although this and other studies indicate the coupling of MZP grazing with phytoplankton growth (Miller et al. 1995, Landry et al. 1997, Strom 2002), dark incubations suggest a short term decoupling of these dynamics as well. Heterotrophs

(most ciliates, rotifers) and mixotrophs (dinoflagellates, some ciliates) can have differential response to dark incubations. The latter group can suspend grazing activity in

the absence of light (Stoecker et al. 1997, Li et al. 2000). On the other hand, it has been

shown that heterotrophic ciliates intensify grazing on picophytoplankton at night (Simek

et al. 2000). Therefore, it is not impossible that dark incubations in this study affected

circadian rhythms of certain grazers.

The serial dilution technique initially developed for the measuring of MZP

grazing in low-Chl offshore marine environments have been known to yield differential

responses in systems with diverse algal assemblages (Fahnenstiel et al. 1995, Lewitus

59 1998). In many cases, when responses of this nature are observed in total Chl the investigators render these experiments failures, attributing contamination or ‘saturated feeding’ to these responses (Gallegos 1989, Landry 1994, Redden et al. 2002). In this study, total Chl alone could not fully explain the impact of MZP grazing in many experiments. This was due, in part, to the composition of the algal community of which a substantial proportion fell beyond the edible size range of the grazer community. Large filamentous (e.g. Planktothrix sp) and colonial blue-greens (e.g. Microcystis sp.) may exhibit a non-grazer-induced response to dilution, increased growth proportional to the dilution gradient cannot be assumed. The dynamics of this larger size fraction masked active MZP grazing of nano- and pico-phytoplankton in several the experiments. The results obtained in this study suggest that the serial dilution technique can produce reasonable growth and grazing mortality rate and secondary production estimates in productive waters. However, to be viable this approach may require a more detailed analysis of both phytoplankton and MZP communities, including taxon-specific determinations.

Conclusions

The results of this study lead to the following conclusions regarding microzooplankton dynamics and composition in coastal and offshore Lake Erie:

1. Microzooplankton herbivory is a major factor controlling phytoplankton

production and standing stock in both coastal and offshore Lake Erie.

60 2. Microzooplankton growth is a prerequisite for measurable herbivory rates at the

community level.

3. Within the microzooplankton community, oligotrich ciliates are the key

herbivores in both offshore and estuarine waters.

4. Microzooplankton contribution to the secondary production in Lake Erie is equal

that of meso and macrozooplankton.

61 REFERENCES

Arndt H. 1993. Rotifers as predators on components of the microbial food web (bacteria, heterotrophic flagellates, ciliates): a review. Hydrobiologia 255: 231- 246

Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA, Thingstad F. 1983. The ecological role of water-column microbes in the sea. Marine Ecology Progress Series 10:257-263

Calbet A, Landry MR. 2004. Phytoplankton growth, microzooplankton grazing, and carbon cycling in marine systems. Limnology and Oceanography 49 (1): 51-57

Carrias JF, Thouvenot A, Amblard C, Sime-Ngando T. 2001. Dynamics and growth estimates of planktonic protists during early spring in Lake Pavin, France Aquatic Microbial Ecology 24 (2): 163-174

Carrick HJ and Fahnenstiel GL. 1990. Planktonic protozoa in Lakes Huron and Michigan: Seasonal abundance and composition of ciliates and dinoflagellates. J.Great Lakes Res., 16: 319-329

Carrick HJ, Fahnenstiel GL and Taylor WD. 1992. Growth and production of planktonic protozoa in Lake Michigan: In situ versus in vitro comparisons and importance to food web dynamics. Limnol. Oceanogr. 37:1221-1255

Caron DA. 2001. Protistan herbivory and bacterivory. In: Paul JH (ed) Marine Microbiology. Methods Microbiol 30: 289-315

Cole JJ. 1999. Aquatic microbiology for ecosystem scientists: New and recycled paradigms in ecological microbiology. Ecosystems 2 (3): 215-225

Fahnenstiel GL, Carrick HJ, Iturriaga R. 1991. Physiological characteristics and food web-dynamics of Synechococcus in Lakes Huron and Michigan. Limnology and Oceanography 37:219-234

Fahnenstiel GL, McCormick MJ, Lang GA, Redalje DG, Lohrenz SE, Markowitz M, Wagoner B, Carrick HJ. 1995. Taxon-specific growth and loss rates for dominant phytoplankton populations from the northern Gulf of Mexico. Mar Ecol Progr Ser 117:229–39

62 Fahnenstiel GL, Krause AE, McCormick MJ, Carrick HJ, Schelske CL. 1998. Structure of the planktonic food web in the St. Lawrence Great Lakes. J Great Lakes Res 23: 531-554

Fenchel T and Finlay BJ. 1986. The structure and function of muller vesicles in loxodod ciliates. Journal of Protozoology 33 (1): 69-76

Fenchel T, Bernard C, Esteban G, Finlay BJ, Hansen PJ, Iversen N. 1995. Microbial diversity and activity in a danish fjord with anoxic deep-water. Ophelia 43 (1): 45- 100

Ferguson RL, Buckley EN, Palumbo AV. 1984. Response of marine bacterioplankton to differential filtration and confinement. Appl Environ Microbiol 47: 49-55

Finlay BJ. 1990. Physiological ecology of free-living protozoa. Advanced Microbial Ecology 11:1-35

Foissner W, Berger H, Schaumburg J. 1999. Identification and ecology of limnetic plankton ciliates. Bayerisches Landesamt fur Wasserwirtschaft, Munich, 793pp

Gallegos CL. 1989. Microzooplankton grazing on phytoplankton in the Rhode River, Maryland: nonlinear feeding kinetics. Mar Ecol Progr Ser 57:23-33

Gardner WS, Chandler JF, Laird GA, Scavia D. 1986. Microbial response to amino-acid additions in Lake Michigan-grazer control and substrate limitation of bacterial populations. Journal of Great Lakes Research 12 (3): 161-174

Gasol JM, del Giorgio PA, Duarte CM. 1997. Biomass distribution in marine planktonic communities. Limnology and Oceanography 42 (6): 1353-1363

Glibert PM. 1988. Primary productivity and pelagic nitrogen cycling. In: Blackburn TH, Sørensen J (eds) Nitrogen cycling in coastal marine environments, Wiley, Chichester, pp 3-31

Hansen B, Christoffersen K. 1995. Specific growth rates of heterotrophic plankton organisms in a eutrophic lake during a spring bloom. Journal of Plankton Research 17 (2): 413-430

Hansen PJ, Calado JA. 1999. Phagotrophic mechanisms of prey selection in free-living dinoflagellates. J. Eukaryot. Microbiol. 46: 382-389

Herdendorf CE, Klarer DM, Herdendorf RC. 2006. The Ecology of Old Woman Creek, Ohio: An Estuarine and Watershed Profile (2nd Ed.). Ohio Department of Natural Resources, Division of Wildlife,Columbus, Ohio. 452 pp.

63 Hwang SJ, Heath RT. 1997. Bacterial productivity and protistan bacterivory in coastal and offshore communities of Lake Erie. Can J Fish Aquat Sci. 54:788-799

Johannsson OE, Dermott R, Graham DM, Dahl JA, Millard ES, Myles DD, LeBlanc J. 2000. Benthic and pelagic secondary production in Lake Erie after the invasion of Dreissena spp. with implications for fish production Journal of Great Lakes Research 26 (1): 31-54

Klarer DM. 1988. The Role of a Freshwater Estuary in Mitigating Storm Water Inflow. OWC Tech. Report #5, ODNR, Div. of Natural Areas and Preserves. 54 pp. 1 app.

Klarer DM and Millie DF. 1989. Amelioration of storm-water quality by a freshwater estuary. Arch. Hydrobiol. 116: 375-389

Klarer DM and Millie DF. 1994. Regulation of phytoplankton dynamics in a Laurentian Great Lakes estuary. Hydrobiologia 286:97-108

Kovalcik PA. 2001. The winter-spring microzooplankton community in southern Lake Michigan : composition, trophic interactions, and response to large-scale episodic events. M.S. Thesis. University of Akron

Landry MR, Hassett RP. 1982. Estimating the grazing impact of marine micro- zooplankton. Marine Biology 67: 283-288.

Landry MR. 1994. Methods and controls for measuring the grazing impact of planktonic protists. Mar. Microb. Food Webs. 8:37-57.

Landry MR, Kirshtein J, Constantinou J. 1995. A refined dilution technique for measuring the community of grazing impact of microzooplankton, with experimental tests in the central equatorial Pacific. Mar. Ecol. Prog. Ser. 120: 53-63

Landry MR, Barber RT, Bidigare RR, Chai F, Coale KH, Dam HG, Lewis MR, Lindley ST, McCarthy JJ, Roman MR, Stoecker DK, Verity PG, White JR. 1997. Iron and grazing constraints on primary production in the central equatorial Pacific: An EqPac synthesis. Limnol Oceanogr 42 (3): 405-418

Lavrentyev PJ. 1994. Anthropogenic stress in ciliate communities: a short-term study at arctic tundra lakes. Arch . Hydrobiol. Beih. Ergeb. Limnol. 40:149-153.

Lavrentyev PJ, Gardner WS, Cavaletto JF, Beaver JR. 1995. Effects of the zebra mussel (Dreissena polymorpha Pallas) on protozoa and phytoplankton in Saginaw Bay, Lake Huron. J. Great Lakes Res. 21:545-557

64

Lavrentyev PJ, Gardner WS, Johnson JR. 1997. Cascading trophic effects on aquatic nitrification: experimental evidence and potential implications. Aquat Microb Ecol 13:161-175

Lavrentyev PJ, McCarthy MJ, Klarer DM, Jochem F, Gardner WS. 2004. Estuarine microbial food web patterns in a Lake Erie coastal wetland. Microbial Ecology 48 (4): 567-577

Legendre L and Rassoulzadegan F. 1995. Plankton and nutrient dynamics in marine waters. Ophelia. 41:153-172

Lehrter JC, Pennock JR, McManus GB. 1999. Microzooplankton grazing and nitrogen excretion across a surface estuarine-coastal interface. Estuaries 22: 113-125

Levinsen H, Nielsen TG. 2002. The trophic role of marine pelagic ciliates and heterotrophic dinoflagellates in arctic and temperate coastal ecosystems: A cross- latitude comparison. Limnol Oceanogr 47:427-439

Lewitus AJ, Koepfler ET, Morris JT. 1998. Seasonal variation in the regulation of phytoplankton by nitrogen and grazing in a salt-marsh estuary. Limnology and Oceanography 43: 636-646

Li AS, Stoecker DK, Coats DW. 2000. Mixotrophy in Gyrodinium galatheanum (Dinophyceae): Grazing responses to light intensity and inorganic nutrients. Journal of Phycology 36 (1): 33-45

Macek M, Simek K, Pernthaler J, Vyhnalek V, Psenner R. 1996. Growth rates of dominant planktonic ciliates in two freshwater bodies of different trophic degree. Journal of Plankton Research 18 (4): 463-481

McCormick PV, Cairns J. 1991. Effects of micrometazoa on the protistan assemblage of a littoral food web. Frashwater Biology 26 (1): 111-119

Menden-Deuer S, Lessard EJ. 2000. Carbon to volume relationships for dinoflagellates, diatoms, and other protist plankton. Limnol Oceangr 54(3):569-579

Miller CA, Penry DL, Glibert PM. 1995. The impact of trophic interactions on rates of nitrogen regeneration and grazing in Chesapeake Bay. Limnology and Oceanography 40 (5): 1005-1011

Miller CA, Glibert PM, Berg GM, Mulholland MR. 1997. Effects of grazer and substrate amendments on nutrient and plankton dynamics in estuarine enclosures. Aquatic Microbial Ecology 12 (3): 251-261

65 Murrell MC, Stanley RS, Lores EM, DiDonato GT, Flemer DA. 2002. Linkage between microzooplankton grazing and phytoplankton growth in a Gulf of Mexico estuary. Estuaries 25:19-29

Ostrom NE, Carrick HJ, Twiss MR, Piwinski L. 2005. Evaluation of primary production in Lake Erie by multiple proxies. Oecologia 145 (4): 669-669

Park JS and Cho BC. 2002. Active heterotrophic nanoflagellates in the hypoxic water- column of the eutrophic Masan Bay, Korea. Marine Ecology-Progress Series 230: 35-45

Pernie GL, Scavia D, Pace ML, Carrick HJ. 1990. Micrograzer impact and substrate limitation of bacterioplankton in Lake Michigan. Can J Fish Aquat Sci 47:1836-1841

Pomeroy LR. 1974. The ocean’s food web, a changing paradigm. Bioscience 24:499- 504

Probyn TA, Waldron HN, James AG. 1990. Size-fractionated measurements of nitrogen uptake in aged upwelled waters – Implications for pelagic food webs Limnology and Oceanography 35 (1): 202-210

Putland JN. 2000. Microzooplankton herbivory and bacterivory in Newfoundland coastal waters during spring, summer and winter. J Plankton Res 22: 253-277

Putt M and Stoecker DK. 1989. An experimentally determined carbon: volume ratio for marine oligotrichous ciliates from estuarine and coastal waters. Limnol Oceanogr 34:177-183

Redden AM, Sanderson BG, Rissik D. 2002. Extending the analysis of the dilution method to obtain the phytoplankton concentration at which microzooplankton grazing becomes saturated. Mar Ecol Progr Ser 226: 27-33

Rivkin RB, Putland JN, Anderson MR, Deibel D. 1999. Microzooplankton bacterivory and herbivory in the NE subarctic Pacific. Deep-Sea Research II 46: 2579-2618

Sherr BF, Sherr EB, Hopkinson CS. 1988. Trophic interactions wwith pelagic microbial communities – indications of feedback-regulation of carbon flow. Hydrobiologia 159 (1): 19-26

Sherr EB and Sherr BF. 1994. Bacterivory and Herbivory – Key roles of phagotrophic protists in pelagic food webs. Microbial Ecology 28 (2): 223-235

Sherr EB and Sherr BF. 2001. Marine microbes: An overview. In: Kirchman DL (ed) Microbial ecology of the oceans. Wiley-Liss p 13-46

66 Sieracki CK, Sieracki ME, Yentch CS. 1998. An imaging-in-flow system for automated analysis of marine microplankton. Mar Ecol Prog Ser 168:285-296

Simek K, Jurgens K, Nedoma J, Comerma M, Armengol J. 2000. Ecological role and bacterial grazing of Halteria spp.: small freshwater oligotrichs as dominant pelagic ciliate bacterivores. Aquatic Microbial Ecology 22 (1): 43-56

Smalley GW and Coats DW. 2002. Ecology of the red-tide dinoflagellate Ceratium furca: Distribution, mixotrophy, and grazing impact on ciliate populations of Chesapeake Bay Journal of Eukaryotic Microbiology 49 (1): 63-73

Stemberger RS. 1979. A guide to rotifers of the Laurentian Great Lakes. U.S. Environmental Protection Agency, Rept. No. EPA 600/4-79-021 185 pp.

Stoecker DK, Davis LH, Provan A. 1983. Growth of Favella sp. (Ciliata, Tintinnina) and other microzooplankters in cages incubated insitu and comparisons to growth-invitro. Marine Biology 75 (2-3): 293-302

Stoecker DK. 1987. Photosynthesis found in some single-celled marine animals. Oceanus 30 (3): 49-53

Stoecker DK and Capuzzo JM. 1990. Predation by Protozoa – Its importance to zooplankton. Journal of Plankton Research 12 (5): 891-908

Stoecker DK, Li AS, Coats DW, Gustafson DE, Nannen MK. 1997. Mixotrophy in the dinoflagellate Prorocentrum minimum. Marine Ecology-Progress Series 152 (1-3): 1- 12

Stoermer EF, Kreis RG, Andresen NA. 1999. Checklist of diatoms from the Laurentian Great Lakes, II. Journal of Great Lakes Research 25(3):515-566

Strom S. 2002. Novel interactions between phytoplankton and microzooplankton: their influence on the coupling between growth and grazing rates in the sea Hydrobiologia 480 (1-3): 41-54

Taylor WD and Heynen ML. 1987. Seasonal and vertical distribution of Ciliophora in Lake Ontario. Can. J. Fish. Aquat. Sci. 44: 2185-2191

Turner, JT and Roff JC. 1993. Trophic levels and trophospecies in marine plankton: Lessons from the microbial food web. Mar. Microb. Food Webs. 7:225-24

Uye S, Iwamoto N, Ueda T, Tamaki H, Nakahira K. 1999. Geographical variations in the trophic structure of the plankton community along a eutrophic-mesotrophic- oligotrophic transect Fisheries Oceanography 8 (3): 227-237

67

Wehr, JD, Sheath RG (eds.). 2003. Freshwater Algae of North America: Ecology and Classification (24 chapters), Academic Press, San Diego, CA. 950 pp.

Weisse T and Frahm A. 2002. Direct and indirect impact of two common rotifer species (Keratella spp.) on two abundant ciliate species (Urotricha furcata, Balanion planctonicum). Freshwater Biology 47 (1): 53-64

Welschmeyer NA. 1994. Fluorometric analysis of chlorophyll-a in the presence of chlorophyll-b and pheopigments. Limnology and Oceanography 39: 1985-1992

Wetzel RG and Likens RL. 1991. Composition and biomass of phytoplankton. In: Limnological Analyses. Second Edition. Springer Verlag. New York. Pp 139-165

68