Oyster-Sea Nettle Interdependence and Altered Control Within
the Chesapeake Bay Ecosystem
DENISE L. BREITBURG1,* and RICHARD S. FULFORD1,{
1 Smithsonian Environmental Research Center, P. O. Box 28, Edgewater, Maryland 20678
ABSTRACT: Research on the effects of declining abundances of the Eastern oyster (Crassostrea virginica) in Chesapeake
Bay and other estuaries has primarily focused on the role of oysters in filtration and nutrient dynamics, and as habitat for fish
or fish prey. Oysters also play a key role in providing substrate for the overwintering polyp stage of the scyphomedusa sea
nettle, Chrysaora quinquecirrha, which is an important consumer of zooplankton, ctenophores, and icthyoplankton. Temporal
trends in sea nettle abundances in visual counts from the dock at Chesapeake Biological Laboratory, trawls conducted in the
mesohaline portion of the Patuxent River, and published data from the mainstem Chesapeake Bay indicate that sea nettles
declined in the mid 1980s when overfishing and increased disease mortality led to sharp decreases in oyster landings and
abundance. Climate trends, previously associated with interannual variation in sea nettle abundances, do not explain the
sharp decline. A potentially important consequence of declining sea nettle abundances may be an increase in their ctenophore
prey (Mnemiopsis leidyi), and a resultant increase in predation on icthyoplankton and oyster larvae. Increased predation on
oyster larvae by ctenophores may inhibit recovery of oyster populations and reinforce the current low abundance of oysters in
Chesapeake Bay.
Introduction
The effects of overfishing of higher trophic levels
on marine food webs and fisheries yields have
received considerable, well-deserved attention in
recent years (Jackson et al. 2001; Myers and Worm
2003). Marine food webs subjected to heavy fishing
removals often have reduced piscivore populations,
increased abundances of planktivores relative to
piscivores, and fisheries characterized by progres-
sively decreasing mean trophic levels (Pauly et al.
1998). Instead, commercial fisheries in many
estuarine systems now target mid trophic level
species. In Chesapeake Bay during 1990?2000,
63% of the commercial landings by weight were
comprised of planktivores, another 31% by species
whose diets are dominated by benthic invertebrates,
and only 6% by fish species that are wholly or
partially piscivorous (NMFS unpublished data).
These percentages reflect the predominance of
the Atlantic menhaden (Brevoortia tyrannus) and
blue crab (Callinectes sapidus) fisheries. Eastern
oyster (Crassostrea virginica), which now makes up
about 1% of the landings, once yielded landings
approximately 100-fold higher. Shellfish and Gulf
menhaden (Brevoortia patronus) comprised 92% of
the commercial landings in state and federal waters
of Louisiana during the same time period (NMFS
unpublished data). In the North Carolina Pamlico-
Albemarle sound and mesohaline tributaries, 82%
of 1990?2000 commercial landings were shellfish
and Atlantic menhaden (Hesselman unpublished
data). Planktivorous fishes and shellfish support
important fisheries in a number of European and
Asian estuaries as well (DeJong and Van Raaphorst
1995; Pinnegar et al. 2003; Sugiyama et al. 2004).
Reduced abundances of mid trophic level species
can be particularly important because the structure
of the food web at that point can strongly influence
the transmission of both nutrient enrichment and
fishing effects through the food web (Hart 2002).
Anthropogenic influence on the abundance of mid
trophic level species can also strongly effect estua-
rine food webs where these species create habitat
and influence the physical environment as well as
playing an important direct role in food web
interactions. Ecosystem engineers, such as oysters
and corals, have a disproportionate effect on the
ecosystems they inhabit, and their decline can
dramatically alter system structure and function
(Coen et al. 1999; Coleman and Williams 2002;
Newell 2004).
In this paper we examine temporal patterns of
abundances of several key species in the Chesapeake
ecosystem and suggest that one of the most
important effects of the decline in oysters on the
estuarine food web is mediated through the effect
of oysters on the scyphomedusa Chrysaora quinquecir-
rha (sea nettle; Fig. 1). Sea nettles are dominant
consumers in Chesapeake Bay (Cowan and Houde
1993; Purcell and Cowan 1995), are seasonally
*Corresponding author; tele: 443/482-2308; fax: 443/482-
2380; e-mail: breitburgd@si.edu
{Current address: Gulf Coast Research Laboratory, The
University of Southern Mississippi, P. O. Box 7000, Ocean
Springs, Mississippi 39566-7000.
Estuaries and Coasts Vol. 29, No. 5, p. 776?784 October 2006
776 2006 Estuarine Research Federation
abundant in other Atlantic and Gulf of Mexico
estuaries, and have congeners in the Eastern and
Western Pacific and the Eastern Atlantic oceans.
Oysters historically created the most extensive hard
substrate habitat in Chesapeake Bay. Oyster shell
serves as the primary substrate for the sessile,
overwintering polyp stage of the sea nettle. Polyp
abundance on substrates, such as twigs, sticks, piers
and human debris, is low (Cones 1968; Cones and
Haven 1969), and polyps on submerged vegetation
are unlikely to survive the winter senescence of
these plants in Chesapeake Bay (Cones and Haven
1969). The indirect effects of declining sea nettle
abundances may include decreased probability of
oyster population recovery and increased shunting
of energy within the food web to gelatinous
predators rather than fish.
DATA SOURCES AND ANALYSES
Data on temporal patterns of sea nettle abun-
dance come from three sources. Visual counts of sea
nettle medusae were made along the length of the
pier at Chesapeake Biological Laboratory (CBL) in
Solomons, Maryland, up to 5 d wk21 during the
months medusa were present from 1960?1988,
1989?1998, 2001?2002, and August?September
2005. Data through 1986 were published in Cargo
and King (1990). Counts were continued past that
date but were not published. Counts were con-
ducted by Cargo with help from M. Wiley and H.
Millsaps through 1991, by M. Wiley during 1992?
1993, by H. Millsaps during 1994?1998, by E.
Setzler-Hamilton (trained by H. Millsaps) during
2001?2002, and by R. Burrell from our laboratory
(also trained by H. Millsaps) beginning in August
2005. In three comparison counts, Burrell?s counts
averaged 20% higher than simultaneous counts by
Millsaps.
Except as noted below, analyses of interannual
variation here use the mean counts for the 4-wk
period each year with the highest sea nettle
abundances. The timing of peak sea nettle abun-
dances can vary, and sometimes occurs in Septem-
ber. Limiting analyses to July and August as in Cargo
and King (1990) can confound the timing and
magnitude of peak sea nettle abundance. We
excluded 1972 (the year of Hurricane Agnes) from
analyses because no samples were taken in July and
there are no independent data indicating the
timing of peak sea nettle abundances that year.
We included 2005 counts even though they did not
begin until August because peak densities in 2005
Patuxent River trawls (described below) occurred
on August 10. We also compared analyses with and
without 1969 included. Mean peak and mean July-
August sea nettle counts in 1969 were more than
twice that in any other year in the data record. Our
analyses of the Cargo and Millsaps data set also
differ from that of Purcell and Decker (2005), who
used total annual counts. We chose to use the 4-wk
peak because the number and timing of samples
varied somewhat among years. Purcell and Decker?s
analyses also only included data through 1995.
The second data set consists of sea nettle and
ctenophore samples taken during 1992?1993, 1998?
2001, and 2003?2005 with 226?244 mm mesh 1-m2
Tucker trawls at two sites in the mesohaline
Patuxent River (Keister et al. 2000; Breitburg et al.
2003, unpublished data). All unqualified references
to ctenophores in this paper refer to the lobate
ctenophore, Mnemiopsis leidyi. Samples were drained
on 2-mm mesh sieves or in colanders, and total
volume and numbers of each species were de-
termined on board. Each density estimate used in
analyses here consists of an average of duplicate
surface, pycnocline, and bottom-layer trawls during
1992?2001 or more than 2 upper and lower water
column trawls during 2003?2005. Multiple samples
taken at the same site, date, and diel period (day or
night) were averaged. Sea nettle densities (number
m23) and ctenophore biovolume (ml m23) are
reported. We also reanalyze data reported in Purcell
and Decker (2005) for the mainstem Chesapeake
Bay. As with the Patuxent samples, gelatinous
zooplankton for that study were collected with a 1-
m2 Tucker trawl.
Data on oyster landings in Maryland waters were
used to estimate changes over time in the abun-
dance of oyster shell substrate available to sea nettle
polyps. We used landings data provided by C. Judy,
the Shellfish Program Director of Maryland De-
Fig. 1. Simplified Chesapeake Bay food web. Solid arrows
indicate trophic connections; dashed arrows indicate habitat
provision. A reduction in oyster abundance reduces habitat for
sea nettle polyps, which may result in reduced predation mortality
of ctenophores and a greater shunting of energy to ctenophores
relative to planktivorous and piscivorous fishes. Bolder arrows
represent trophic pathways that are predicted to increase in
importance as sea nettle abundances increase.
Sea Nettle and Oyster Declines 777
partment of Natural Resources (unpublished data)
because several different sets of annual estimates
were found online and in reports. Summer sea
nettle abundances were compared to the previous
winter?s oyster landings. We used Maryland-wide
data instead of Patuxent River oyster landings in
analyses because the low number of watermen
fishing oysters in the Patuxent results in high
interannual variation in river landings that is likely
independent of stock levels.
Cargo and King (1990) suggested that the
January-June Chesapeake streamflow strongly influ-
enced interannual variation in sea nettle abun-
dances reflected in their CBL pier count data
because of the negative effect of low salinity on
ephyra production. Their analysis included July-
August data for 1960?1986. We reexamined this
relationship to determine whether trends in river
discharge might explain the decline in sea nettle
counts at the CBL pier and densities in Patuxent
River trawls. Stream discharge data for the portion
of Chesapeake Bay above the mouth of the Potomac
River were provided by J. Manning (unpublished
data) of the U.S. Geological Survey (USGS) who
updated provisional data found on the USGS
website (http://md.water.usgs.gov/monthly/bay1.
html).
A more recent analysis of the Cargo and King
(with added years by Wiley and Millsaps) 1960?1995
data set suggested a significant relationship between
the North Atlantic Oscillation (NAO), which influ-
ences a suite of environmental variables and sea
nettle abundance (Purcell and Decker 2005). We
repeated this analysis with the complete 1960?2005
pier count data set. We used the site-based
December-March NAO index to examine climate
effects on sea nettle abundances so that our analyses
would be directly comparable to those of Purcell
and Decker (2005; http://www.cgd.ucar.edu/cas/
jhurrell/Data/naodjfmindex.1864-2005.xls).
To explore whether declining sea nettle abun-
dances might result in an increase in their
ctenophore prey, we examined temporal patterns
in ctenophore abundance in mesohaline stations in
the Maryland portion of Chesapeake Bay (stations
CB2.2, CB3.3C, CB4.3C, and CB5.2) and its tributar-
ies (the Patuxent, Choptank, and Potomac Rivers)
sampled by the Chesapeake Bay Zooplankton
Monitoring Program from 1985 to 2002 (http://
www.chesapeakebay.net/data/index.htm). These
samples were taken with a 20-cm diameter, 202-mm
mesh net and drained on a 2-mm mesh sieve prior
to onboard determination of total volume and
numerical abundance of each species. Data used
in correlations are the mean June or July-August ml
ctenophores m23 through the entire water column
for all tributary or mainstem bay sites listed above.
In the first 3 yr of the monitoring program, Beroe
ovata (a ctenophore predator of M. leidyi) and M.
leidyi were lumped into a single ctenophore catego-
ry. In order to include 1985?1987 in our data set, we
lumped both species for our analysis. In years the
two species were counted separately, Beroe was either
not present or averaged only a small percent of the
June?August biovolume of M. leidyi. It is not known
whether sea nettles consume Beroe spp.
Curve-fitting was done with SigmaPlot (Version
8.0, Jandel Scientific, San Rafael, California). Both
linear and nonlinear fits were tested, and the best fit
is reported. Where R2 values were similar for several
linear and nonlinear relationships, and where no
significant fits were found, only linear regression
results are reported. Statistical analyses used SAS
(Version 9.1, SAS Institute Inc., Cary, North
Carolina).
Results
TEMPORAL PATTERNS IN SEA NETTLE AND
OYSTER ABUNDANCES
Three data sets that overlap in time provide
evidence that sea nettle abundances have declined
since the mid 1980s and have remained far below
historical levels since about 1990. The first data set
consists of visual counts of sea nettles made from
the CBL pier from 1960 to 2005 (Fig. 2). Although
there is considerable interannual variation in mean
4-wk peak sea nettle abundances in this data set,
there is a strong pattern of high interannual
variation and peak counts exceeding 100 in 19 of
26 years during 1960?1986 as compared to consis-
tently low counts during 1990?2005. The second
data set from the mesohaline mainstem Chesapeake
Bay published by Purcell and Decker (2005)
indicates that sea nettle densities were approximate-
ly 4-fold higher in 1987?1990 than in 1995?2000.
The third data set, of trawl data from the mesoha-
line Patuxent River, indicates that mean July?August
densities during 1992?2005 were low, averaging
0.07 ind m23. Mean sea nettle densities were
0.15 ind m23 in 1992?1993 (based on annual
means; n 5 12 sets of duplicate trawls per year),
as compared to a mean of 0.03 ind m23 during
1999?2005 (n 5 6, 12, 1, and 12 sets of duplicate
trawls for 1998, 2001, 2003, and 2004, respectively,
and 12 sets of unreplicated trawls in 2005; Fig. 3).
Oyster landings in Maryland peaked in the late
19th century, declined until the 1960s primarily as
a result of overfishing and associated habitat
destruction, and then declined again beginning in
the mid 1980s as a consequence of the combined
stresses of overfishing, disease, and habitat degra-
dation (NRC 2004; Fig. 2). Major die-offs of market-
sized oysters related to both Perkinsus marinus and
778 D. L. Breitburg and R. S. Fulford
Haplosporidium nelsoni infections were reported in
Maryland during summer 1987. Current oyster
landings are only 2% of historical 1870?1900 land-
ings. The decline in landings may underestimate
the decline in hard substrate available to sea nettle
polyps because of heavy siltation in oyster bars with
few living oysters (Smith et al. 2005).
A comparison of temporal patterns of oyster
landings and sea nettle pier counts since 1960
indicates that abundances of both species declined
during the same period and have remained low
since that time. Current oyster landings are only
11% of that prior to the mid 1980s decline. Annual
landings during 1959?1960 through the 1985?1986
oyster seasons averaged 2,096,383 6 22,834 (stan-
dard error) bushels yr21, as compared to 227,553 6
8,842 bushels yr21 during the 1989?1990 through
2004?2005 seasons. Recent sea nettle pier counts
are only 10% of that prior to the mid 1980s oyster
decline. Peak annual counts during 1960?1986
averaged 257 6 12, as compared to 26 6 1 during
1990?2005.
River discharge patterns did not explain the mid
1980s decline in sea nettle abundances, and once
the unusually high 1969 value was removed,
explained little of the interannual variation in the
data set originally analyzed by Cargo and King
Fig. 3. Density (6 SE) of gelatinous zooplankton in mesoha-
line Patuxent River trawl collections during 1992?2005, plotted
against river discharge for the portion of the Chesapeake Bay
north of the mouth of the Potomac River, and compared to M.
leidyi biovolume. The relationship between sea nettle and cteno-
phore abundances is better described using sea nettle number
than volume.
Fig. 2. Temporal pattern of sea nettle counts and Maryland
oyster landings during 1965?2005. The dashed vertical line
indicates 1987, when high levels of disease-related mortality
began reducing oyster abundances below 1960?1986 levels. The
timing of other data sets discussed in manuscript are indicated as
mainstem trawls (Purcell and Decker 2005) and Patuxent trawls
(Keister et al. 2000; Breitburg et al. 2003; Breitburg et al.
unpublished data).
Sea Nettle and Oyster Declines 779
(1990; Table 1). There was no long-term trend in
January?June river discharge above the Potomac
River during the 1960?2005 period (correlation
between year and streamflow: R 5 0.02, p 5 0.90)
and no significant difference in streamflow between
the 1960?1986 period prior to the oyster and sea
nettle decline and the 1990?2005 period following
the decline of both species (F 5 0.00, p 5 0.999).
There were also multi-year droughts, conditions
thought conducive to high sea nettle abundances,
in both the 1960s, when sea nettle abundances were
at their maxima, and during 1999?2002, when sea
nettle abundances were at extremely low levels.
A re-examination of the 1960?1986 Solomons
pier count data indicates a strong negative relation-
ship between January?June river discharge (from
Table 1 in Cargo and King 1990) and both July?
August mean counts (from Table 1 in Cargo and
King 1990) and 4-wk peak mean sea nettle counts.
Statistical results are summarized in Table 1 of this
manuscript. Somewhat less of the interannual
variation is explained by river discharge for the
peak mean than July?August mean because peak
densities sometimes occur in September in low
salinity years. A second analysis with 1969 removed
to examine the pattern in the absence of the single
year of unusually high sea nettle counts suggests
that river discharge typically explained little of the
interannual variation in sea nettle counts even in
the original data set (Table 1). No relationship was
found between peak sea nettle counts and river
discharge during 1990?2005.
Trawl data also do not support a strong role of
river discharge influencing interannual variation in
sea nettle densities following the decline of oysters
(Fig. 3). Both the early 1990s and the 1998?2005
periods include one or more years with above
average rainfall and one or more years with below
average rainfall. River discharge in the Maryland
portion of Chesapeake Bay did not explain a signif-
icant portion of the interannual variation in sea
nettle densities in trawls (linear regression: R2 5
0.04, p 5 0.61).
Our analysis suggests that the relationship be-
tween the NAO and sea nettle abundances may have
changed as sea nettle densities declined (Fig. 4). An
analysis of 1960?1986 mean 4-wk peak sea nettle
counts regressed against mean December?March
NAO (http://www.cgd.ucar.edu/cas/jhurrell/Data/
naodjfmindex.1864-2005.xls) yielded a negative re-
lationship between CBL pier counts and NAO,
similar to findings of Purcell and Decker (2005; R2
5 0.33, p 5 0.002 for this analysis versus R2 5 0.36
reported in Purcell and Decker). In contrast, there
was a trend towards a positive relationship between
sea nettle pier counts and NAO for the 1990?2005
portion of the data set (R2 5 0.32, p , 0.07),
a positive relationship between the NAO and sea
nettle densities in our Patuxent River trawl data set
encompassing 1992?2005 (R2 5 0.52, p 5 0.04), and
no significant relationship between the NAO index
and data reported in Purcell and Decker (2005) for
TABLE 1. Relationship between January?June discharge above
the mouth of the Potomac River and visual counts of sea nettles at
the Chesapeake Biological Laboratory Pier. The original analysis
by Cargo and King (1990) included July?August counts for 1960?
1986. Results of the best-fit model (exponential decline or linear)
are shown. na 5 not applicable. Data were analyzed with and
without 1969 included because sea nettle counts in that year were
more than twice as high as in any other year in the data record.
Years Sea Nettle Data Model 1969 Data R2 p
1960?1986 July?August
mean
exponential included 0.35 0.001
1960?1986 4-wk peak
mean
exponential included 0.29 0.005
1960?1986 July?August
mean
linear removed 0.15 0.06
1960?1986 4-wk peak
mean
linear removed 0.18 0.03
1990?2005 4-wk peak
mean
linear na 0.05 0.47
1960?2005 4-wk peak
mean
linear removed 0.07 0.10
Fig. 4. Relationship between sea nettle abundance and NAO
index. Inclusion of 1969 data had little effect on the analysis.
780 D. L. Breitburg and R. S. Fulford
the mainstem Chesapeake Bay 1987?1999 (R25 0.16,
p 5 0.29). Sea nettle densities in recent years have
been low regardless of NAO index values.
FOOD WEB RESPONSES TO DECLINING SEA
NETTLE ABUNDANCE
Sea nettles are the dominant predators of the
ctenophore, M. leidyi, in Chesapeake Bay (Feigen-
baum and Kelly 1984; Purcell and Cowan 1995;
Purcell and Decker 2005; Fig. 1). When abundant,
sea nettles can eliminate or reduce ctenophore
biomass and abundance. During the period of
1985?2002, when sea nettles densities declined, the
biovolume (ml m23) of ctenophores (mostlyM. leidyi)
collected in the Chesapeake Bay Zooplankton Mon-
itoring Program increased in both the tributaries and
mainstem of the mesohaline Maryland portion of the
Chesapeake Bay (Fig. 5). Peak densities occurred in
the late 1990s. A similar increase was found by Purcell
and Decker (2005) for the mainstem Chesapeake
Bay. High ctenophore biovolume also tended to be
associated with low sea nettle density in the Patuxent
River (Fig. 3) but the relationship was not statistically
significant (p 5 0.20).
A number of climatic factors can influence the
abundance of M. leidyi (Sullivan et al. 2001; Oviatt
2004; Purcell and Decker 2005) and have been
suggested to have led to increasing ctenophore
abundances in Chesapeake and Narragansett Bays.
If declining sea nettle abundances have contributed
to the increasing ctenophore abundances in Chesa-
peake Bay, the increase should be greatest when
and where sea nettles historically were most
abundant and potentially exerted the greatest
control on their ctenophore prey. We predicted
that the rate of increase in ctenophore abundance
should be greater in the mesohaline reaches of
tributaries, where sea nettles reach their greatest
abundances (Purcell et al. 2001), than in the
mesohaline mainstem Chesapeake Bay, and that
the increase should be greater in July and August,
when sea nettle biomass typically peaks, than in
June.
The ratio of tributary to mainstem bay mean July?
August ctenophore biovolumes increased during
the 1985?2002 sampling period (Fig. 5; R2 5 0.39, p
5 0.006). Mean biovolume tended to be lower in
the tributaries than in the mainstem in the early
part of the time series and higher than in the
mainstem in later years. Log-transformed cteno-
phore biovolume significantly increased in July and
August in both the tributaries and mainstem (R2 5
0.41, p 5 0.004 for both comparisons) and also
showed a trend towards increasing in June (tribu-
tary sites: R2 5 0.20, p 5 0.06; mainstem sites: R2 5
0.19, p 5 0.07). Analysis of variance (ANOVA) on
log-transformed data indicated that the rate of
increase was greater in July?August than in June
(two-way ANOVA with year as continuous variable;
year: F 5 27.38, p , 0.0001; June versus July?
August: F 5 6.95, p 5 0.01; year 3 month
interaction: F 5 6.90, p 5 0.01; Fig. 5).
Discussion
Our analysis indicates that the decline in oyster
abundances, caused by overfishing, disease, and
habitat degradation, has important effects on estua-
Fig. 5. Ratio of ctenophore biovolumes in tributaries versus
mainstem samples during June?August and intramural changes in
seasonal patterns of ctenophores abundance in mesohaline
tributaries and mainstem Chesapeake Bay stations. In the bottom
two panels, open circles are June biovolumes; closed circles are
July?August biovolumes.
Sea Nettle and Oyster Declines 781
rine food webs beyond those previously highlighted.
The importance of oysters to water filtration, nutrient
cycling, and habitat provision for fish and benthic
invertebrates is well established (Newell 1988, 2004;
Coen et al. 1999). Our results indicate oysters also
exert a strong influence on food web structure, as well
as the potential success of oyster restoration, because
of their pivotal role in providing habitat for the sessile
overwintering stage of a dominant pelagic consumer,
the scyphomedusan sea nettle.
Prior to the mid 1980s oyster decline, sea nettle
abundances in the Maryland portion of Chesapeake
Bay were higher and exhibited considerable in-
terannual variation, which was influenced by climate
variability (Cargo and King 1990; Purcell and
Decker 2005). We suggest that by the late 1980s
the abundance of shell substrate available to settling
sea nettle planula and growing polyps declined
below a critical threshold. Once that threshold was
reached, interannual variation in sea nettle abun-
dance no longer responded to interannual variabil-
ity in climate, but instead remained low.
The coincidence of temporal patterns of sea
nettle and oyster abundance in Narragansett Bay
may be even more striking than that in the
Chesapeake system. Sea nettles occurred in Narra-
gansett Bay during the 19th and early 20th centuries
(Fewkes 1881; Fish 1925) and presumably earlier,
while oysters were virtually eliminated from Narra-
gansett Bay following the 1938 hurricane. Today,
both sea nettles and oysters are restricted to a few
coastal Rhode Island salt ponds (Fofonoff personal
communication; Oviatt personal communication;
Sullivan-Watts personal communication; Gifford
personal communication). Along the Gulf of
Mexico coast of the U.S., which retains large oyster
populations, sea nettle densities have remained
stable or increased (Graham 2001).
This threshold in hard substrate available to sea
nettle polyps in Chesapeake Bay appears to have
triggered a more systemic threshold response that is
reinforced by the relaxation of sea nettle control
over ctenophores, which are predators of oyster
larvae (see also Purcell and Decker 2005). This low
sea nettle, high ctenophore regime is characterized
by increased predation on zooplankton and ichthyo-
plankton, increased predation on oyster larvae
(Purcell and Decker 2005), and a likely increased
shunting of energy to gelatinous zooplankton
relative to fish (Fig. 1). Oysters ultimately mediate
the flow of energy to planktivorous and piscivorous
fishes by influencing the balance between sea
nettles and ctenophores.
M. leidyi has both a higher feeding rate per unit
biomass and volume than do sea nettles (Purcell
and Decker 2005) and a greater capacity for a rapid
numerical increase than either sea nettles or the
dominant trophically similar zooplanktivorous fish,
the bay anchovy, Anchoa mitchilli. M. leidyi has
a generation time of about 2 wk, approximately
the same as the calanoid copepod Acartia tonsa,
which comprises over 90% of mesozooplankton
biomass during summer in the mesohaline Chesa-
peake Bay. Both sea nettles and bay anchovy
typically have annual generation times. All three
species have high reproduction rates, but daily egg
production of medium sized (e.g., 5 cm) individual
hermaphroditic ctenophores can exceed the num-
ber of eggs spawned per bay anchovy female during
spawning events (Zastrow et al. 1991; Purcell et al.
2001). The potential rate of population increase
resulting from strobilization by sea nettle polyps and
egg production by bay anchovy is considerably lower
than that of ctenophores, which combine high egg
production (up to 14,000 eggs ind21 d21; Kremer
1976) with short generation time. Because of the
combination of higher feeding rates and greater
potential for numerical response, as well as greater
utilization of copepod nauplii and microzooplank-
ton, ctenophores are more likely than sea nettles to
deplete the zooplankton prey they share with
planktivorous fishes, and inflict heavier predation
mortality on fish eggs and larvae. Thus, a decline in
oyster abundance that favors increased abundance
of ctenophores should ultimately reduce energy
flow to top piscivores through summer breeding
planktivorous fishes such as bay anchovy (Fig. 1).
Although many aspects of sea nettle and cteno-
phore diets are similar, one key difference is that
ctenophores readily prey on oyster larvae while sea
nettles do not (Purcell et al. 1991). A decline in
oyster abundance that ultimately results in an
increase in ctenophores, results in an increase in
ctenophore predation on oyster larvae, reinforcing
the regime shift from a moderate-to-high oyster
state to a low oyster state. This is a potentially
important example of hysteresis in which the
trajectory describing the decline of oysters may be
unavailable as a restoration trajectory without active
intervention.
Pilot experiments indicate that clearance rates of
ctenophores feeding on oyster veliger larvae are
similar to those of ctenophores feeding on the
calanoid copepod A. tonsa (Fulford and Breitburg
unpublished data). We applied the average Acartia
clearance rate estimates listed in Purcell et al.
(2001) to Chesapeake Bay Zooplankton Monitoring
Program tributary data shown in Fig. 5 and results
of individual trawls from the Patuxent River, and
assumed an average ctenophore length of 5 cm.
These calculations indicate that ctenophores cur-
rently consume 10?25% of oyster larvae on average
throughout the summer, and locally can consume
40% to nearly 100% of oyster larvae at peak
782 D. L. Breitburg and R. S. Fulford
densities. Predicted clearance rates are about 35%
higher if Chesapeake-specific clearance rates mea-
sured in 1-m3 mesocosms are used (Purcell et al.
2001; Purcell and Decker 2005) or if ctenophore
biomass is dominated by smaller individuals. Oyster
spawning in Chesapeake Bay occurs from late May
or June through September or early October, with
peak spawning in July (Thompson et al. 1996).
Highest abundance of oyster larvae potentially
coincides with the time period at which ctenophore
densities and predation potential are low if sea
nettles are abundant, but high if sea nettle densities
are low. Under the current low sea nettle regime,
locally high densities of ctenophores can likely limit
oyster recruitment, reinforcing the low oyster, low
sea nettle, high ctenophore state. This trophic
consequence of the habitat role of oyster likely
contributes to the list of factors, including disease,
habitat destruction, overfishing, and siltation, that
impede recovery of oysters in Chesapeake Bay.
Our analysis does not address the presumed low
abundance of sea nettles at high oyster densities
prior to increased fishing pressure following Euro-
pean colonization and eutrophication in the mid
20th century. The scant discussion of sea nettles in
historic writings has been interpreted to suggest
that sea nettles, which have a quite painful sting,
were generally low in abundance (Kennedy and
Mountford 2001). The longer term historical
trajectory may have been one of increasing sea
nettles with increasing eutrophication until a low-
oyster threshold was crossed, at which point
abundances declined. Under current nutrient load-
ing and fishing pressure, the magnitude of increase
in oyster biomass targeted in restoration strategies
(i.e., a 10-fold increase, CBP 2000) would likely
return Chesapeake Bay to a mid 20th century high
sea nettle regime, not to an earlier low sea nettle,
high oyster regime.
Oyster population recovery has been cited as an
important ecological tool for improving water clarity
and secondary production in Chesapeake Bay and
elsewhere. If ecosystem structure has crossed
a threshold into a new state, as we suggest here,
ecosystem responses to such recovery efforts be-
come more difficult to predict. The food web
consequences of low oyster abundance represent
a change in ecosystem structure that may be difficult
to reverse by small scale, incremental improvements
in oyster habitat or adult mortality. Complex
feedback between the benthic and pelagic compo-
nents of estuarine systems, and within food webs,
may be extremely important to our understanding
of how estuarine ecosystems respond to overfishing
and other stressors, and how to manage and restore
these ecosystems once they have been fundamen-
tally changed by human activity.
ACKNOWLEDGMENTS
Many people shared unpublished data or helped locate data
sources for this paper. We would like to thank Harold Millsaps for
providing unpublished data on pier counts, insight into methods
used by David Cargo, and training that allowed us to resume these
counts. Kent Mountford provided an electronic file of the CBL
pier count data through 1995. We are grateful to the family of
Eileen Setzler-Hamilton (deceased) for allowing the continued
use of her unpublished data. Paul Fofonoff provided references
and alerted us to changing sea nettle abundances in Narragansett
Bay and Rhode Island salt ponds; Dian Gifford, Barbara Sullivan,
and Candace Oviatt shared their observations and insight about
Rhode Island systems. Jennifer Purcell and Mary Beth Decker
provided raw data from their 2005 paper. James Manning
provided corrected water discharge data, Don Hesselman pro-
vided North Carolina Fisheries data, and Chris Judy provided
Maryland oyster landings data. Chesapeake Bay ctenophore data
were originally collected by the monitoring program led by
Richard Lacouture and William Burton. Previously unpublished
field data were collected with the help of many collaborators,
students, technicians, and boat captains including Jennifer
Purcell, Mary Beth Decker, Rebecca Burrell, Sarah Kolesar,
Carolyn Reid, Eileen Graham, Jesse Phillips-Kress, Danielle
Tuzzolino, Amelia Fort, Amanda Glazier, Genevieve Smith, Daniel
Brown, William Yates, and J Hixson. Funding for analysis and
previously unpublished Patuxent River trawl data was provided by
Maryland Sea Grant Program, the EPA STAR Program, NOAA-
COP funding to the Chesapeake Synthesis project, the EPA
Chesapeake Bay Program, and the Smithsonian Institution
Marine Science Network.
LITERATURE CITED
BREITBURG, D. L., A. ADAMACK, S. E. KOLESAR, M. B. DECKER, K. A.
ROSE, J. E. PURCELL, J. E. KEISTER, AND J. H. COWAN JR. 2003.
The pattern and influence of low dissolved oxygen in the
Patuxent River, a seasonally hypoxic estuary. Estuaries 26:280?
297.
CARGO, D. G. 1979. Observations on the settling behavior of
planular larvae of Chrysaora quinquecirrha. International Journal of
Invertebrate Reproduction 1:279?287.
CARGO, D. G. AND D. R. KING. 1990. Forecasting the abundance of
the sea nettle, Chrysaora quinquecirrha, in the Chesapeake Bay.
Estuaries 13:486?491.
CARGO, D. G. 1979. Observations on the settling behavior of
planular larvae of Chrysaora quinquecirrha. International Journal of
Invertebrate Reproduction 1:279?287.
CARGO, D. G. AND D. R. KING. 1990. Forecasting the abundance of
the sea nettle, Chrysaora quinquecirrha, in the Chesapeake Bay.
Estuaries 13:486?491.
CBP (CHESAPEAKE BAY PROGRAM). 2000. Chesapeake 2000. http://
www.chesapeakebay.net/agreement.htm
CHESAPEAKE BAY PROGRAM (CBP). 2000. Chesapeake 2000. http://
www.chesapeakebay.net/agreement.htm
COEN, L. D., M. W. LUCKENBACH, AND D. L. BREITBURG. 1999. The
role of oyster reefs as essential fish habitat: A review of current
knowledge and some new perspectives, p. 438?454. In L. R.
Benaka (ed.), Fish Habitat: Essential Fish Habitat and Re-
habilitation. American Fisheries Society, Symposium 22.
Bethesda, Maryland.
COLEMAN, F. C. AND S. L. WILLIAMS. 2002. Overexploiting marine
ecosystem engineers: potential consequences for biodiversity.
Trends in Ecology and Evolution 17:40?44.
CONES, H. N. 1968. Distribution of Chrysaora quinquecirrha in the
York river. M.A. Thesis. College of William and Mary Virginia
Institute of Marine Science, Williamsburg, Virginia.
CONES, H. N. AND D. S. HAVEN. 1969. Distribution of Chrysaora
quinquecirrha in the York river. Chesapeake Science 10:75?84.
Sea Nettle and Oyster Declines 783
COWAN, JR., J. H. AND E. D. HOUDE. 1993. Relative predation
potentials of scyphomedusae, ctenophores and planktivorous
fish on ichthyoplankton in Chesapeake Bay. Marine Ecology
Progress Series 95:55?65.
DE JONGE, V. N. AND W. VAN RAAPHORST. 1995. Eutrophication of
the Dutch Wadden Sea (western Europe), an estuarine area
controlled by the River Rhine, p. 129?149. In, A. J. McComb
(ed.), Eutrophic Shallow Estuaries and Lagoons. CRC Press,
Boca Raton, Florida.
FEIGENBAUM, D. AND M. KELLY. 1984. Changes in the lower
Chesapeake Bay food chain in presence of the sea nettle
Chrysaora quinquecirrha (Scyphomedusa). Marine Ecology Progress
Series 19:39?47.
FEWKES, J. W. 1881. Studies of the jelly-fishes of Narragansett Bay.
Harvard University Museum of Comparative Zoology Bulletin 8:141?
182.
FISH, C. J. 1925. Seasonal distribution of the plankton of the
Woods Hole region. Fishery Bulletin 41:91?179.
GRAHAM, W. M. 2001. Numerical increases and distributional shifts
of Chrysaora quinquecirrha (Desor) and Aurelia aurelia (Linne?)
(Cnidaria: Scyphozoa) in the northern Gulf of Mexico.
Hydrobiologia 451:97?111.
HART, D. R. 2002. Intraguild predation, invertebrate predators,
and trophic cascades in lake food webs. Journal of Theoretical
Biology 218:111?128.
JACKSON, J. B. C., M. X. KIRBY, W. H. BERGER, K. A. BJORNDAL, L. W.
BOTSFORD, B. J. BOURQUE, R. H. BRADBURY, R. COOKE, J.
ERLANDSON, J. A. ESTES, T. P. HUGHES, S. KIDWELL, C. B. LANGE,
H. S. LENIHAN, J. M. PANDOLFI, C. H. PETERSON, R. S. STENECK,
M. J. TEGNER, AND R. R. WARNER. 2001. Historical overfishing
and the recent collapse of coastal ecosystems. Science 293:629?
638.
KEISTER, J. E., E. D. HOUDE, AND D. L. BREITBURG. 2000. Effects of
bottom-layer hypoxia on abundances and depth distributions of
organisms in Patuxent River, Chesapeake Bay. Marine Ecology
Progress Series 205:43?59.
KENNEDY, V. S. AND K. MOUNTFORD. 2001. Human influences on
aquatic resources in the Chesapeake Bay watershed, p. 191?219.
In, P. D. Curtin, G. S. Brush, and G. W. Fisher (eds.),
Discovering the Chesapeake?The History of an Ecosystem.
Johns Hopkins Press, Baltimore, Maryland.
KREMER, P. 1976. Population dynamics and ecological energetics
of a pulsed zooplankton predator, the ctenophore Mnemiopsis
leidyi, p. 197?215. In, J. L. Wiley (ed.), Estuarine Processes.
Academic Press, New York.
MYERS, R. A. AND B. WORM. 2003. Rapid worldwide depletion of
predatory fish communities. Nature 423:280?283.
NEWELL, R. I. E. 1988. Ecological changes in Chesapeake Bay: Are
they the result of overharvesting the American oyster, Crassos-
trea virginica?, p. 536?546. In, M. P. Lynch and E. C. Krome
(eds.), Understanding the Estuary: Advances in Chesapeake Bay
Research. Chesapeake Research Consortium, Gloucester Point,
Virginia.
NEWELL, R. I. E. 2004. Ecosystem influences of natural and
cultivated populations of suspension-feeding bivalve molluscs:
A review. Journal of Shellfish Research 23:51?61.
NATIONAL RESEARCH COUNCIL (NRC). 2004. Non-native Oysters in
Chesapeake Bay. The National Academies Press, Washington,
D.C.
OVIATT, C. 2004. The changing ecology of temperate coastal
waters during a warming trend. Estuaries 27:895?904.
PAULY, D., V. CHRISTENSEN, AND J. DALSGAARD. 1998. Fishing down
marine food webs. Science 279:860?863.
PINNEGAR, J. K., N. V. C. POLUNIN, AND F. BADALAMENTI. 2003.
Long-term changes in the trophic level of western Mediterra-
nean fishery and aquaculture landings. Canadian Journal of
Fisheries and Aquatic Sciences 60:222?235.
PURCELL, J. E. AND J. H. COWAN JR. 1995. Predation by the
scyphomedusan Chrysaora quinquecirrha on Mnemiopsis leidyi
ctenophores. Marine Ecology Progress Series 129:63?70.
PURCELL, J. E., F. P. CRESSWELL, D. G. CARGO, AND V. S. KENNEDY.
1991. Differential ingestion and digestion of bivalve larvae by
the scyphozoan Chrysaora quinquecirrha and the Ctenophore
Mnemiopsis leidyi. Biological Bulletin 180:103?111.
PURCELL, J. E. AND M. B. DECKER. 2005. Effects of climate on
relative predation by scyphomedusae and ctenophores on
copepods in Chesapeake Bay during 1987?2000. Limnology and
Oceanography 50:376?387.
PURCELL, J. E., T. A. SHIGANOVA, M. B. DECKER, AND E. D. HOUDE.
2001. Ctenophore Mnemiopsis in native and exotic habitats: U.S.
estuaries versus the Black Sea basin. Hydrobiologia 451:145?176.
SMITH, G. F., D. G. BRUCE, E. B. ROACH, A. HANSEN, R. I. E. NEWELL,
AND A. M. MCMANUS. 2005. Assessment of recent habitat
conditions of Eastern oyster Crassostrea virginica bars in mesoha-
line Chesapeake Bay. North American Journal of Fisheries
Management 25:1569?1590.
SUGIYAMA, S., D. STAPLES, AND S. J. FUNGE-SMITH. 2004. Status and
potential of fisheries and aquaculture in Asia and the Pacific.
Food and Agriculture Organization Regional Office for Asia
and the Pacific, Publication 2004/25. Bangkok, Thailand.
SULLIVAN, B. K., D. VAN KEUREN, AND M. CLAUCY. 2001. Timing and
size of blooms of the ctenophore Mnemiopsis leidyi in relation to
temperature in Narragansett Bay, RI. Hydrobiologia 451:113?120.
THOMPSON, R. J., R. I. E. NEWELL, V. S. KENNEDY, AND R. MANN.
1996. Reproductive processes and early development, p. 335?
370. In, V. S. Kennedy, R. I. E. Newell, and A. F. Eble (eds.), The
Eastern Oyster Crassostrea virginica. Maryland Sea Grant,
College Park, Maryland.
ZASTROW, C. E., E. D. HOUDE, AND L. G. MORIN. 1991. Spawning,
fecundity and hatch-date frequency of bay anchovy (Anchoa
mitchilli) in mid-Chesapeake Bay. Marine Ecology Progress Series
73:161?171.
SOURCES OF UNPUBLISHED MATERIALS
FOFONOFF, P. personal communication. Smithsonian Environmen-
tal Research Center, P. O. Box 28, Edgewater, Maryland 21037.
GIFFORD, D. personal communication. University of Rhode Island,
Graduate School of Oceanography, Narragansett, Rhode Island
02882.
HESSELMAN, D. unpublished data. North Carolina Division of
Marine Fisheries Trip Ticket Program, 3441 Arendell Street,
Morehead City, North Carolina 28557.
JUDY, C. unpublished data. Maryland Department of Natural
Resources, 580 Taylor Ave., Annapolis, Maryland 21401.
MANNING, J. J. unpublished data. U.S. Geological Survey Water
Resources Division, Water Resources for Maryland, Delaware,
and the District of Columbia, 8987 Yellow Brick Road,
Baltimore, Maryland 21237.
NATIONAL MARINE FISHERIES SERVICE (NMFS). 2005. unpublished
data. http://www.st.nmfs.gov/st1/commercial/landings/annual_
landings.html. NMFS, Fisheries Statistics Division, Silver Spring,
Maryland.
OVIATT, C. personal communication. University of Rhode Island,
Graduate School of Oceanography, Narragansett, Rhode Island
02882.
SULLIVAN-WATTS, B. personal communication. Biology Depart-
ment, Providence College, Providence, Rhode Island 02918.
Received, February 7, 2006
Accepted, May 2, 2006
784 D. L. Breitburg and R. S. Fulford