PRIMARY RESEARCH PAPER

Fast microzooplankton grazing on fast-growing,low-biomass phytoplankton: a case study in spring inChesapeake Bay, Delaware Inland Bays and Delaware Bay

Jun Sun Æ Yuanyuan Feng Æ Yaohong Zhang ÆDavid A. Hutchins

Received: 9 May 2006 / Revised: 28 March 2007 / Accepted: 30 March 2007 / Published online: 21 June 2007

� Springer Science+Business Media B.V. 2007

Abstract Dilution experiments were performed to

examine the growth and grazing mortality rates of

picophytoplankton (<2 mm), nanophytoplankton

(2–20 mm), and microphytoplankton (>20 mm) at

stations in the Chesapeake Bay (CB), the Delaware

Inland Bays (DIB) and the Delaware Bay (DB), in

early spring 2005. At station CB microphytoplankton,

including chain-forming diatoms were dominant, and

the microzooplankton assemblage was mainly com-

posed of the tintinnid Tintinnopsis beroidea. At

station DIB, the dominant species were microphyto-

planktonic dinoflagellates, while the microzooplank-

ton community was mainly composed of copepod

nauplii and the oligotrich ciliate Strombidium sp. At

station DB, nanophytoplankton were dominant com-

ponents, and Strombidium and Tintinnopsis beroidea

were the co-dominant microzooplankton. The growth

rate and grazing mortality rate were 0.13–3.43 and

0.09–1.92 d�1 for the different size fractionated

phytoplankton. The microzooplankton ingested 73,

171, and 49% of standing stocks, and 95, 70, and 48%

of potential primary productivity for total phyto-

plankton at station CB, DIB, and DB respectively.

The carbon flux for total phytoplankton consumed by

microzooplankton was 1224.11, 100.76, and

85.85 mg C l�1 d�1 at station CB, DIB, and DB,

respectively. According to the grazing mortality rate,

carbon consumption rate and carbon flux turn over

rates, microzooplankton in study area mostly pre-

ferred to graze on picophytoplankton, which was

faster growing but was lowest biomass component of

the phytoplankton. The faster grazing on Fast-Grow-

ing-Low-Biomass (FGLB) phenomenon in coastal

regions is explained as a resource partitioning

strategy. This quite likely argues that although

microzooplankton grazes strongly on phytoplankton

in these regions, these microzooplankton grazers are

passive.

Keywords Microzooplankton � Size fractionated

phytoplankton � Selective grazing � Biomass �Chesapeake Bay � Delaware Inland Bays � Delaware

Bay

Introduction

Phytoplankton growth is always affected by two

kinds of forces. One of these is intrinsic growth, and

the other is extrinsic removal processes such as

Handling editor: K. Martens

J. Sun (&)

Key Laboratory of Marine Ecology & Environmental

Science, Institute of Oceanology, Chinese Academy of

Sciences, Nanhai Road 7th, Qingdao 266071, P.R. China

e-mail: phytoplankton@163.com

Y. Feng � Y. Zhang � D. A. Hutchins

Graduate College of Marine Studies, University of

Delaware, Lewes, DE 19958, USA

123

Hydrobiologia (2007) 589:127–139

DOI 10.1007/s10750-007-0730-6

grazing mortality, viral lysis, sinking, and advection

(Reynolds, 1998), parasitism (Kagami et al., 2007),

etc. Because each phytoplankton species has a

different intrinsic growth rate, and each predator

has a different grazing capability, it is not an easy

task to explain the apparent growth rate of a species-

rich phytoplankton assemblage. Phytoplankton net

growth rate variability can be caused by resource

availability, sometimes called ‘‘bottom-up’’ control,

and by loss rate variations caused by grazing, called

‘‘top-down’’ control (Lehman, 1991). Bottom-up

controls of phytoplankton growth, as key controls,

have a long history of study in marine systems, while

top–down control has received increasing attention

recently (Banse, 1994; Cushing, 1990).

Microzooplankton generally feed on smaller-sized

cells which are not utilized efficiently by larger

consumers. Thus microzooplankton, as trophic inter-

mediates, make considerable production accessible to

the higher trophic level consumers in the food web

(Berk et al., 1977; Landry & Hassett, 1982). Over the

past two decades, many dilution experiments (Landry

& Hassett, 1982) have been performed to examine the

grazing impact of microzooplankton in various

waters all around the world (e.g. Collos et al.,

2005; Strom, 2002). Based on these dilution exper-

iment results, the microzooplankton have been

recently suggested to be the primary grazers of

marine phytoplankton, and 60–70% of primary

production is consumed by microzooplankton (Calbet

& Landry, 2004). While elegant, there is also recent

debate over the accuracy of the dilution method, it

will ‘‘prone to providing over-estimates of grazing

rates and unlikely to furnish evidence of low grazing

rates’’ (Dolan & McKeon, 2004). Although dilution

method has these fatal faults and uninterpretable

results occurred frequently, it can be used as a

comparable method for measuring microzooplankton

grazing rates in a regional or a time series ecological

processes studies.

The grazing behavior of microzooplankton on

phytoplankton is complex (Strom et al., 2001). Strom

(2002) presented the concept of ‘‘higher grazing rates

on faster-growing cells’’, and explained that this

coupling of growth and grazing rates acts to promote

planktonic ecosystem stability. Soon thereafter came

the ‘loophole’ blooming mechanism (Irigoien et al.,

2004), which can be explained as ‘‘an ecosystem at

maturity, with strong trophic links, where a

perturbation loosens some of the trophic links

allowing an opportunistic species to colonize (dom-

inate) the ecosystem’’. Together, these two papers

make a compelling case that the predator-prey link, in

particular the phenomenon of microzooplankton

grazing on faster growing phytoplankton, is critical

for the control of primary production. But there have

been still few studies on selectivity of microzoo-

plankton feeding based on dilution experiments

(Strom, 2002), and therefore the hypothesis of ‘‘faster

grazing on faster-growing cells’’ still lacks adequate

supporting field data.

To test this hypothesis, we designed dilution

experiments to measure microzooplankton grazing

on size fractionated phytoplankton at three typical

stations in the Chesapeake Bay, the Delaware Inland

Bays, and Delaware Bay, U.S.A. All of these areas

are characterized by various degrees of eutrophica-

tion and relatively high phytoplankton biomass

(Malone et al., 1996), and frequent harmful algal

blooms have been reported in the Delaware Bay and

Delaware Inland Bays (Bourdelais et al., 2002;

Burkholder & Glasgow, 2001). Despite this, no

published microzooplankton grazing studies have

been carried out in these two bays.

Methods

Study stations and experiment setup

Water samples were collected from three stations in

the Chesapeake Bay (CB), the Delaware Inland Bays

(DIB) and the pier water of College of Marine

Studies of the University of Delaware in the Dela-

ware Bay estuary (DB) (Fig. 1). The water used in the

experiments was collected from 0.5 m depth using a

Niskin water sampler, transferred gently into two 40-l

carboys, and then transported immediately to the

laboratory where the dilution experiments were

conducted. The Particle-free water (PFW) was

prepared by filtering seawater through Millipore

capsule (0.2 mm) filters under slight air pressure.

The remaining seawater (initial seawater, ISW) was

size-fractionated to remove mesozooplankton by

gently pouring it through a 200-mm mesh.

The ISW was diluted by PFW to five target

dilutions of 20, 40, 60, 80, and 100% (ISW: ISW plus

PFW) in 2.8-l transparent polycarbonate bottles. The

128 Hydrobiologia (2007) 589:127–139

123

incubation volume was 2.8 l and treatments were

carried out in triplicate. To simulate in situ condi-

tions, all bottles were incubated 0.2 m under the

water using flow-through surface DB water on a dock

near the laboratory for about 24 h. All filtration

apparatus, mesh, carboy containers and incubation

polycarbonate bottles were cleaned with 10% HCl

and thoroughly rinsed with filtered seawater prior to

each experiment.

Two water samples were collected at the begin-

ning of each incubation (time zero) to determine the

initial chlorophyll a concentrations. These samples

were filtered through 0.2 mm Millipore polycarbon-

ate filters at <200 mm Hg vacuum and stored in the

dark at � 208C until they were analyzed. The

double ISW samples were size-fractionated collected

to examine the growth rate and grazing mortality

rates of phytoplankton. ISW samples were filtered

through 20, 2, and 0.2 mm Millipore polycarbonate

filters in turn to measure the concentration of

picophytoplankton (0.2–2 mm), nanophytoplankton

(2–20 mm) and microphytoplankton (20–200 mm)

chlorophyll a.

Initial water samples for phytoplankton (250 ml)

and microzooplankton (2 l) were preserved in

paraformaldehyde (final concentration 0.2%) and

1% Lugol solution separately. These samples were

stored at room temperature in the dark until they

were counted by the Utermohl method (Utermohl,

1958). After 24 h incubation, these bottles were

gently shaken, and 50 ml of phytoplankton and

500 ml microzooplankton water samples from each

treatment were stored in the same manner as the

initial samples.

Sample analyses

Chlorophyll a was extracted in dark with 90%

acetone for 24 h at 48C and measured by a Turner-

Designs fluorometer (Welschmeyer, 1994). Phyto-

plankton and microzooplankton were enumerated

and identified to species level (Marshall, 1969;

Tomas, 1997) using an inverted microscope at

400 · magnification after sedimentation for 24 h

in 25 ml chambers. The biovolumes of phytoplank-

ton present in samples were calculated by standard

36

37

38

39

40 30N

77 76 75 W

Baltimore

Dover

AnnapolisWashington D. C.

Lewes

Richmond

Philadelphia

Wilmington

Scale: 1:2717328

DIB

DB

CB

Chesapeake B

ay

Delaw

are Bay

o

o

o

o

o

o o o

NEW JERSEY

DE

LAW

AR

E

PENNSYLVANIA

MARYLAND

Fig. 1 Study sites in the Chesapeake Bay, Delaware Inland Bays and Delaware Bay

Hydrobiologia (2007) 589:127–139 129

123

geometric models (Sun & Liu, 2003), then the

carbon biomass was calculated using Eppley’s

formula (Eppley et al., 1970). Based on these data,

a carbon:chlorophyll a ratio was calculated for each

experiment, in order to examine the distribution of

the carbon biomass and carbon flux consumed by

microzooplankton.

Microzooplankton biomass was determined from

biovolume or body length conversion biomass.

Appropriate body dimensions (longest dimension)

were measured to determine lorica volume of tintin-

nids and cell volume of naked ciliates. An ellipsoid

volume was assign to these latter microzooplankton,

the volume (in mm3) was calculated as V = (1/6) · p· length · breadth · depth (Knap et al., 1996).

The lorica volume was converted to carbon weight of

a tintinnid (Ct, pg) using a factor of 0.19 pg mm�3,

and the cell volume was converted to that of a naked

ciliate using a factor of 0.14 pg mm�3 (Putt &

Stoecker, 1989). The carbon weight of copepod

nauplii (Cc, ng) was calculated from body length

(BL, mm) with the regression equation Cc = 1.51

· 10�5 · BL2.94 (Uye et al., 1996).

Dilution experiment data analysis

Data analysis procedures for the dilution method were

according to the literature (Landry & Hassett, 1982).

According to the dilution method, ISW is diluted with

PFW to various target dilution levels; after incubation,

each incubation bottle yields an independent estimate

of the prey apparent growth rate (AGR).

AGRðday�1Þ ¼ lnðPt=PoÞt

where t is the duration of the incubation in days and

Pt and P0 are the initial and final phytoplankton crops

respectively. The rates of prey growth and grazing

mortality were calculated by the linear regression of

AGR versus actual dilution factor (ADF) (ISW: ISW

plus PFW). The absolute value of the slope of the

regression is the mortality rate of phytoplankton due

to grazing (g, d�1) and the ordinal intercept (y-

intercept) of the regression is the growth rate of

phytoplankton in the absence of grazing (l, d�1). The

grazing impact on prey by microzooplankton is often

expressed by net growth rate (NGR = l � g, d�1)

and other indices as follows.

The percentage of potential primary production

ingested by microzooplankton per day (%Pp, d�1) for

each of the three experiments was calculated using

equation:

%Pp ¼ðCoel � CoÞ � ðCoel�g � CoÞ

Coel � Co� 100

where C0 is phytoplankton carbon (mg C l�1) at time

zero in the undiluted treatment. The percentage of

phytoplankton standing crop ingested per day (%Ps,

d�1) was calculated using equation:

%Ps ¼ðCoel � CoÞ � ðCoel�g � CoÞ

Co� 100

The rate of ingestion of phytoplankton carbon

(Ic, mg C l�1 d�1) was calculated as the difference in

carbon production by the phytoplankton in the

absence (C0el) and presence (C0el�g) of microzoo-

plankton (Landry et al., 2000):

Ic ¼ Coel � Coel�g

The turn over rate of carbon flux (Tz, d�1) between

microzooplankton and phytoplankton, which repre-

sent the amount of phytoplankton carbon transferred

into microzooplankton in a day, was calculated as

follows:

Tz ¼Ic

Cz

where Cz is microzooplankton carbon (mg C l�1) at

time zero in the undiluted treatment.

Additionally, in order to estimate the selective

grazing impacts on phytoplankton, the rates of

growth and grazing mortality were indirectly calcu-

lated from the difference of chlorophyll a concentra-

tion among pico-, nano-, and micro-phytoplankton,

respectively.

Results

Phytoplankton species and biomass

The abundance and biomass of phytoplankton at

the studied stations are presented in Table 1.

130 Hydrobiologia (2007) 589:127–139

123

Phytoplankton community structure was significantly

different at the three stations in spring. At station CB

there were 36 phytoplankton species found, mainly

diatoms. The dominant species were Skeletonema

tropicum, S. costatum and Asterionellopsis glacialis.

Station DB had a similar phytoplankton assemblage

with Cylindrotheca closterium, A. glacialis and

Thalassiosira rotula as the dominant species. Species

richness at DB was 31, but total cell abundance was

only one twelfth of that at station CB. In contrast,

only 17 phytoplankton species were found at Station

DIB. Species composition at this station was obvi-

ously different from the other two stations with

mainly dinoflagellates including Gymnodinium sp.,

Prorocentrum minimium, and Scrippsiella trochoidea

as the dominant species. The total phytoplankton

biomasses at stations CB, DIB, and DB were 1,682,

59, and 174 mg C l�1 respectively, and most of the

phytoplankton biomass was contributed by these

dominant species.

The initial chlorophyll a concentrations were 33.5,

1.9, and 5.4 mg l�1 at stations CB, DIB and DB,

Table 1 Phytoplankton species and biomass at station CB, DIB, and DB

Time Stations Species Abundance (cells l�1) Biomass (mg C l�1)

3/13/05 CB Skeletonema tropicumCleve 5108,892 112.40

Skeletonema costatum (Greville) Cleve 3649,209 71.17

Asterionellopsis glacialis (Castracane) Round 1476,657 175.29

Thalassiosira rotula Meunier 1120,222 546.39

Thalassiosira nordenskioldii Cleve 848,653 93.21

Thalassionema nitzschioides (Grunow) Mereschkowsky 831,680 34.99

Chaetoceros subtilis Cleve 763,788 17.11

Thalassiosira decipiens (Grunow) Jørgensen 594,057 101.03

Scrippsiella trochoidea (Stein) Balech ex Loeblich III 390,380 169.36

Alexandriumsp. 186,704 206.04

Ditylum brightwellii (West) Grunow 24,242 22.25

Other phytoplankton 31,668 132.58

4/17/05 DIB Gymnodinium sp. 354,645 4.34

Prorocentrum minimium (Pavillard) Schiller 135,732 19.55

Scrippsiella trochoidea 65,793 11.14

Skeletonema costatum 42,835 0.94

Asterionellopsis glacialis 45,489 7.97

Thalassiosira nordenskioldii 35,784 3.34

Thalassionema nitzschioides 41,142 1.44

Heterosigma akashiwo (Hada) Hada ex Hara & Chihara 26,242 5.14

Other phytoplankton 1,073 4.94

3/5/05 DB Cylindrotheca closterium (Ehrenberg) Reimann & Lewin 458,666 7.55

Asterionellopsis glacialis 281,991 33.48

Thalassiosira rotula 113,904 55.56

Skeletonema costatum 80,261 1.57

Thalassiosira nordenskioldii 45,834 5.03

Thalassionema nitzschioides 53,509 2.25

Scrippsiella trochoidea 68,787 29.84

Chaetoceros subtilis 39,761 0.89

Thalassiosira decipiens 39,369 6.70

Alexandrium sp. 17,520 19.33

Other phytoplankton 4,735 12.23

Hydrobiologia (2007) 589:127–139 131

123

respectively. The proportion of each size fraction as a

fraction of total chlorophyll a concentration is shown

in Fig. 2. At station CB, microphytoplankton were the

major component of the phytoplankton community,

comprising 74.1% of the total size spectrum. At

station DIB, although microphytoplankton were still

dominant (51.5% of the total), nanophytoplankton

also were a substantial component at 36.5% of total

chlorophyll a. At station DB, nanophytoplankton

were the predominant component, reaching 80.2% of

the total biomass. These were mainly composed of

Cylindrotheca closterium and other chain-forming

nanophytoplankton.

Based on chlorophyll a size fraction and biovo-

lume conversion to carbon biomass for the total

phytoplankton assemblage, the carbon biomass of

each phytoplankton size fraction was calculated. The

total carbon biomass was 1,682, 58.81, and

174 mg C l�1 at station CB, DIB, and DB respectively

(Table 2). Biomass was quite high at station CB,

because the major component of the phytoplankton

community was microphytoplankton at this station

and these big-celled diatoms comprised most of

biomass for the whole assemblage (Table 1). The

most biomass contributed by any single species at this

station was Thalassiosira rotula, which reached

546 mg C l�1, nearly 1/3 of the whole biomass

(Table 1).

Microzooplankton community species

composition and biomass

Microzooplankton abundance and biovolume conver-

sion to carbon biomass is shown in Table 3. The

tintinnid Tintinnopsis beroidea was the most domi-

nant species at station CB, at 1,347 ind. l�1, and

copepod nauplii and oligotrichida were also found.

The most dominant microzooplankton at station DIB

were copepod nauplii, at 232 ind. l�1, and abundance

of the aloricate ciliate Strombidium was also quite

high (153 ind. l�1). At station DB, the oligotrich

Strombidium strobilum and the tintinnid Tintinnopsis

beroidea were co-dominant species, at 388 and

231 ind. l�1 respectively. The microzooplankton

carbon biomass values at stations CB, DIB, and DB

were 102, 44, and 75 mg C l�1, respectively.

Growth rates of size fractionated phytoplankton

The growth rates of size fractionated and whole size

spectrum phytoplankton are shown in Table 2. These

ranged from 0.13 to 2.10 d�1. The growth rates of the

total phytoplankton community at stations CB, DIB,

and DB were 0.56, 1.23, and 0.83 d�1 respectively. It

is obvious that the growth rates increase successively

with a decrease in size from micro- to nano- to

picophytoplankton.

Grazing rate and pressure of microzooplankton on

size fractionated phytoplankton

The grazing rates of microzooplankton on different

size fractionated phytoplankton at the studied stations

are summarized in Table 2. The values ranged from

0.12 to 1.92 d�1.

At station CB, the major microzooplankton species

was the tintinnid Tintinnopsis beroidea, and high

microzooplankton grazing rates were found on pic-

ophytoplankton. At station DB, where the major

microzooplankton species were the oligotrichStrom-

bidium strobilum and the tintinnid Tintinenopsis

beroidea, high microzooplankton grazing rates were

found on nanophytoplankton and picophytoplankton.

At station DIB, the major microzooplankton were

copepod nauplii and oligotrichida, which prefer to

prey on nanophytoplankton and picophytoplankton.

The microzooplankton grazing pressure on the phy-

toplankton community expressed by the percentage

0

80

100

40

20

60

CB DIB DB

%

Station

< 2 µm Picophytoplankton2 - 20 µm Nanophytoplankton> 20 µm Microphytoplankton

Fig. 2 Percentage composition of size fractionated phyto-

plankton at stations CB, DIB, and DB

132 Hydrobiologia (2007) 589:127–139

123

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Hydrobiologia (2007) 589:127–139 133

123

of phytoplankton standing crop (%Ps) and percentage

of ingested phytoplankton potential production

(%Pp), are shown in Table 2. The microzooplankton

ingested 73, 171, and 85% of standing stocks for total

phytoplankton at stations CB, DIB, and DB respec-

tively, while they ingested 95, 70, and 66% of

potential primary productivity by the total phyto-

plankton community respectively. The highest %Ps

was found on picophytoplankton at all three stations

notwithstanding different biomass in the various size

fractions, growth rates, and grazing rates. Meanwhile

different maximum %Pp values were found on

microphytoplankton, picophytoplankton and pic-

ophytoplankton at stations CB, DIB, and DB (98,

97, and 99%, respectively).

The carbon flux consumed by microzooplankton

was 1,224, 101, and 149 mg C l�1 d�1 at stations CB,

DIB and DB respectively (Table 2). The phytoplank-

ton carbon consumption rate by microzooplankton

was high at station CB because phytoplankton carbon

biomass was highest at this station (Tables 1 and 2).

The carbon turn over rate between microzooplankton

and phytoplankton was 12.1, 2.3, and 2.0 d�1 at

stations CB, DIB, and DB respectively (Table 2),

demonstrating a high carbon flux between microzoo-

plankton and phytoplankton at all three stations. The

highest consumed carbon flux and turn over rate was

contributed by the fast growing picophytoplankton,

with lower values in turn for the nanophytoplankton

and microphytoplankton.

Discussion

Phytoplankton growth in these three bays

Similar to this study, high and variable phytoplankton

biomass was observed in these regions by previous

research (Malone et al., 1996). Their results showed

that when phytoplankton growth rates become nutri-

ent-saturated, the production and consumption of

phytoplankton biomass becomes uncoupled in time

and space. In the experiments, no additional nutrient

was added: the original evaluation procedure of

Landry & Hasset (1982) was performed. This is

because, that during the experimental season, the

Table 3 Microzooplankton composition and biomass at station CB, DIB, and DB

Time Stations Species Abundance

(individual l�1)

Carbon

(mg C l�1)

3/13/05 CB Copepod nauplii 83 1.93

Amphorellopsis acuta (Schmidt, 1901) Kofoid & Campbell,1929 91 5.98

Eutintinnis pectinis (Kofoid, 1905) Kofoid & Campbell,1939 329 6.05

Strombidium strobilum (Lochmann, 1908) Wulff, 1919 337 60.21

Tintinnopsis beroidea Stein, 1867 1347 13.62

Tintinnopsis dadyai Kofoid, 1929 78 0.53

Tintinnopsis nana Lohmann, 1908 95 0.51

Tintinnopsis radix (Imhof, 1886) Brandt, 1907 341 12.78

4/17/05 DIB Copepod nauplii 232 14.59

Strombidiumsp. 153 27.40

Tintinnopsis beroidea 99 1.00

Tintinnopsis dadyai 10 0.05

Tintinnopsis nana 37 0.21

Tintinnopsis radix 13 0.49

3/5/05 DB Copepod nauplii 16 0.35

Amphorellopsis acuta 38 2.39

Strombidium strobilum 388 69.33

Tintinnopsis beroidea 231 2.34

Tintinnopsis nana 8 0.05

Tintinnopsis radix 20 0.75

134 Hydrobiologia (2007) 589:127–139

123

Delaware Bay and the Chesapeake Bay have compa-

rable high rates of N and P loading (Pennock et al.,

1994; Malone et al., 1996), and the Delaware Inland

Bays are even more eutrophic (Price, 1998). How-

ever, there are three instances (CB 0.2–2 mm, DIB

Total, DIB 0.2–2 mm) (Fig. 3) where there is no

significant difference between the two highest dilu-

tion factors. Naturally, this could also come about

through saturated grazing in the least diluted frac-

tions, but without adding nutrients, we have no way

of separating the two factors. These faults should be

avoided by the following dilution experiments in

these regions.

Our results suggest that the phytoplankton com-

munity was growing faster in the Delaware Bay and

the Delaware Inland Bays than in the Chesapeake

Bay during the survey period. The net growth rates

for total phytoplankton were 0.04, 0.55, and 0.37 d�1

at stations CB, DIB, and DB respectively (Table 2).

Furthermore, based on the biovolume conversion

carbon biomass data, we can calculate the car-

bon:chlorophyll a ratio (C:Chl-a). This ratio was

50.3, 31.1, and 32.1 at stations CB, DIB, and DB

respectively. The ratio of C:Chl-a indirectly reflected

the growth of phytoplankton community at these

stations. A typical C:Chl-a ratio for fast-growing

coastal phytoplankton might be 30, but the C:Chl-a

ratio can be more than 300 (Banse, 1977). Usually

healthy, adapted phytoplankton tend to have low

C:Chl-a, and nutrient-starved or senescent phyto-

plankton have very high C:Chl-a ratios (Cloern,

1995; Marinho & Rodrigues, 2003). It is easily

concluded that phytoplankton community growth

status was better at stations DIB and DB at station

CB.

All the three stations showing that small sized

phytoplankton grow faster than big sized cells

(Table 2). These observations are supported by the

allometry theory of phytoplankton metabolic and

growth rates (Raven & Kubler, 2002). Larger phyto-

plankton have lower maximum specific growth rates

at resource (light, nutrient) saturation than do smaller

phytoplankton in the same phylogenetic group (Ga-

tham & Rhee, 1981), meanwhile, picophytoplankton

should have an advantage under nutrient-limiting

conditions due to their advantageous surface area to

volume ratio (Raven, 1998).

Microzooplankton grazing mortality in these three

bays

Microzooplankton species composition and abun-

dance was studied in detail in Chesapeake Bay by

previous works (Dolan, 1991; Dolan & Coates,

1990). These works showed that in early spring

(April) Chesapeake Bay, the dominant microzoo-

plankton species were Strombidium sp. and copepod

nauplii, their abundance were ca. 10 and 70 ind. l�1

separately. But in our plankton sample, the dominant

species was tintinnid Tintinnopsis beroidea, also the

microzooplankton abundance was lower than these

previous works. This may explain, at least partially,

the uneven distribution of microzooplankton in

Chesapeake Bay, and often the unpredictable results

of biomanipulation experiments.

In Chesapeake Bay, microzooplankton grazing

plays an important role in regulating the populations

of two annual blooming dinoflagellates, Prorocen-

trum minimum and Karlodinium micrum (Johnson

et al., 2003). Meanwhile, microzooplankton can

heavily influence NH4+ regeneration by strongly

controlling the growth of <15 mm organisms (Miller

0.0 0.4

0.8 Total

0.0

0.4

0.8

1.2 > 20 µm

0.0

0.4

0.8

App

aren

t Gro

wth

Rat

e (d

-1)

2 – 20 µm

1.0

CB

0.0

1.0

2.0

3.0 0.2 – 2 µm

DIB

Actual Dilution Factor

DB

0.2 0.6

1.2

0.6 0.6 1.0 0.2 0.2 1.0

Fig. 3 Relationships between dilution level and apparent

growth rate of the total community and the three size fractions

of chlorophyll a at stations CB, DIB, and DB. Statistics are

presented in Table 2

Hydrobiologia (2007) 589:127–139 135

123

et al., 1995). Other studies show that microzooplank-

ton play a significant role on controlling phytoplank-

ton growth in Chesapeake Bay, especially in spring

(Gallegos & Jordan, 1997; McManus & Ederington-

Cantrell, 1992). Our preliminary study showed that in

spring, the microzooplankton exerts heavy grazing

pressure on phytoplankton in Chesapeake Bay, and

also has a significant effect on phytoplankton growth

in Delaware Bay and the Delaware Inland Bays.

The selectivity of microzooplankton grazing has

been verified by many investigations. It has been

shown that the mean grazing rate values are dramat-

ically affected by the composition of the microzoo-

plankton community (Burkill et al., 1987; Gifford,

1988; Smetacek, 1981). Many microzooplankton

select their prey based on the qualitative composition

of food particles (Burkill et al., 1987; Epstein &

Shiaris, 1992; Latasa et al., 1997; Landry et al.,

1998). Microzooplankton selective grazing is quite a

complex phenomenon: some protists can taste bio-

chemical properties of their food (e.g. Monger et al.,

1999), and reject disliked particles after capture

(Stoecker et al., 1995; Taniguchi & Takeda, 1988;

Wetherbee & Andersen, 1992). Some studies have

demonstrated that microzooplankton can selectively

graze on more nutritious phytoplankton species

(Stoecker et al., 1986; Buskey, 1997). The major

portion of many microzooplankton communities is

ciliates in many coastal regions (Paranjape, 1990;

Strom et al., 2001). Some ciliates are filter predators

and due to their body-size limitations, they can only

ingest food particles that fit their body-size or oral

cavity size (e.g. lorica diameter). Therefore the size

spectrum of food can be a criterion of microzoo-

plankton selective grazing (Zhang et al., 2005).

Dolan et al. (2002) shown that microzooplankton

diversity is heavily dependent on phytoplankton

diversity. In our study, the Shannon diversity index

value for these three size fractions was 1.07, 1.39,

and 0.81 at stations CB, DIB, and DB respectively.

These values are lower compared with data shown in

Dolan et al. (2002), thus the microzooplankton

community of our study stations was less complex.

This was good for simplifying microplankton food

cascading relationships in our study.

Heterotrophic nanoflagellates (HNF) are ubiqui-

tous protozoan zooplankton in a size range of

2–20 mm, and the major picoautotroph grazers (Fen-

chel, 1986). From the list of our microzooplankton

species (Table 3), it is hardly possible to find the

picoautotrophs grazers; this is because HNF usually

checked under epifluorescence microscopy after

staining with 40,6-diamidino-2-phenylindole dihydro-

chloride (DAPI). Some study showing the Strombid-

ium spp. (Christaki et al., 1999) and mixotrophic

dinoflagellates, such as Ceratium fusus,Protoperidi-

nium conicum, Scrippsiella trochoide a (Jeong et al.,

2005), presented in our plankton samples, are also

possible picoautotrophs grazer.

Our study confirms that different grazers prefer to

prey upon different size groups of phytoplankton.

Microzooplankton at all three stations prefer to graze

on the fast growing picophytoplankton. However, as

in our experiments, in most coastal regions pic-

ophytoplankton are only a minor fraction of the

whole phytoplankton community. Therefore, the

major portion of the phytoplankton biomass could

not be effectively controlled by microzooplankton

grazing at these stations. As demonstrated by the

ingested phytoplankton carbon data (Ic data in

Table 2), picophytoplankton were heavily grazed by

microzooplankton. Although we cannot speculate

that without microzooplankton grazing picophyto-

plankton would be dominant, it is evident that

microzooplankton actually play a very important role

on carbon packaging and fluxes in coastal regions.

Faster grazing on fast-growing-low-biomass and

microzooplankton dilemma

Similar to our results, some research suggests that

bacterivorous flagellates tend to feed at higher rates

on faster-growing bacteria (del Giorgio et al., 1996;

Gonzalez et al., 1993), or that the fastest-growing

phytoplankton taxa often experience the highest

grazing pressures (Burkill et al., 1987; McManus &

Ederington-Cantrell, 1992; Strom & Welschmeyer,

1991; Verity et al., 1996). Strom (2002) summarized

this phenomenon, and explained that this coupling of

grazing rate and growth rate resulted in maintenance

of a stable ecosystem. She concluded that microzoo-

plankton grazing, especially selective grazing,

strongly controls the growth and succession pathway

of the phytoplankton community, resulting in a

balanced, diversified plankton system. Coupling

Strom’s ‘‘stability’’ theory with the ‘‘loophole’’

theory of Irigoien et al. (2004), can potentially

explain much of the entire process of phytoplankton

136 Hydrobiologia (2007) 589:127–139

123

community development in a marine ecosystem. Our

data are consistent with Strom’s phenomenon of

‘‘microzooplankton faster grazing on fast growing

phytoplankton’’ in coastal regions. Furthermore, in

our study, not only the highest Ic, Tz, and l was

presented in <2 mm phytoplankton size fraction, but

also the lowest biomass.

It is a dilemma for microzooplankton: whether to

graze on larger sized food as an efficient predator (as

described by the ‘‘optimal foraging theory’’ (Leh-

man, 1976), or to graze on smaller sized food to take

advantage of a reliable, long term food supply. For

the first situation, the microzooplankton is an active

predator, and for the second situation, it is a passive

grazer. The dominant mechanism explaining our data

set of faster grazing on Fast-Growing-Low-Biomass

(FGLB) phenomenon is resource partitioning. That is,

microzooplankton graze on faster growing and minor

biomass phytoplankton, which can provide plenty of

food over a long period of time. Although microzoo-

plankton grazes strongly on phytoplankton in these

regions, these microzooplankton grazers are passive.

In our experiments, picophytoplankton were

mostly controlled by microzooplankton grazing,

whereas the predominant bloom-forming phytoplank-

ton species are not picophytoplankton in these

regions (Bourdelais et al., 2002). That means, under

the circumstances, that the blooming ‘‘loophole’’

species is not mostly controlled by microzooplank-

ton. Nevertheless, microzooplankton selective graz-

ing still has a strong effect on controlling

phytoplankton biomass and the development path-

ways of the phytoplankton community in these

regions. This paper is just a preliminary case study,

as more field and theoretical research is needed to

further test and explore this FGLB phenomenon.

Acknowledgements The authors greatly acknowledge the

comments and suggestions of Dr. J, Padisak and Dr. F.X. Fu

which resulted in an improvement of the paper. This study was

supported by the NSFC 40306025, 40676089 and NBRPC

2006CB400605 to JS and NSF OCE 0423418 and EPA

ECOHAB R83-1041 to DAH. The remarks of two anonymous

reviewers greatly improved this manuscript.

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