Mar Biol
DOI 10.1007/s00227-011-1744-1
ORIGINAL PAPER
Global patterns of epipelagic gelatinous zooplankton biomass
M. K. S. Lilley • S. E. Beggs • T. K. Doyle
V. J. Hobson • K. H. P. Stromberg •
G. C. Hays
•
Received: 18 April 2011 / Accepted: 21 June 2011
Ó Springer-Verlag 2011
Abstract There is concern that overfishing may lead to a
proliferation of jellyfish through a process known as fishing
down the food web. However, there has been no global
synthesis of patterns of gelatinous zooplankton biomass
(GZB), an important first step in determining any future
trends. A meta-analysis of epipelagic-GZB patterns was
undertaken, encompassing 58 locations on a global scale,
and spanning the years 1967–2009. Epipelagic-GZB
decreased strongly with increasing total water column
depth (r2 = 0.543, p \ 0.001, n = 58): in shallow
(\50 m) coastal waters, epipelagic-GZB was typically
7429 the levels in deep ocean ([2,000 m) sites. However,
the ratio of GZB to primary productivity showed high
values across a range of depths, i.e. this measure of the
Communicated by U. Sommer.
Electronic supplementary material The online version of this
article (doi:10.1007/s00227-011-1744-1) contains supplementary
material, which is available to authorized users.
M. K. S. Lilley V. J. Hobson G. C. Hays (&)
Department of Biosciences, Swansea University,
Singleton Park, Swansea SA2 8PP, UK
e-mail: [email protected]
S. E. Beggs
Fisheries and Aquatic Ecosystems Branch,
Agri-Food and Biosciences Institute,
Newforge Lane, Belfast BT9 5PX, UK
T. K. Doyle
Coastal and Marine Research Centre, ERI, University College
Cork, Glucksman Marine Facility, Naval Base, Haulbowline,
Cobh, Cork, Ireland
K. H. P. Stromberg
Swedish Meteorological and Hydrological Institute,
Folkborgsvägen 1, 60176 Norrköping, Sweden
relative abundance of gelatinous zooplankton did not covary with depth.
Introduction
There is intense interest in how the biological structure of
the oceans may be changing as a result of climate change,
eutrophication and overfishing (Halpern et al. 2008). It has
been suggested that targeted removal of the larger fish
remaining in ecosystems may cause a progressive pattern
of fishing down the food chain until systems are dominated
by invertebrates, such as jellyfish (Hay 2006; Daskalov
et al. 2007). Whilst there is now good evidence that fishing
has changed the trophic level targeted by fisheries in some
areas (Essington et al. 2006), i.e. fishing down the food
chain (Pauly et al. 1998) is underway, evidence for the
switch to gelatinous zooplankton-dominated systems is
currently limited (Pauly et al. 2009). This switch may
already have occurred in some regions (Boero et al. 2008;
Lynam et al. 2006) and elsewhere the concern is that
continued overfishing may be causing the rapid approach
of this tipping point. In addition, climatic changes and the
increase in the number of anthropogenic structures in the
sea may result in greater jellyfish abundances (for a review,
see Purcell et al. 2007).
Concern of gelatinous zooplankton taking over perturbed systems has led to an increase in research into this
group with, for example, several international conferences
and recent reviews on the importance of gelatinous zooplankton (Pauly et al. 2009; Pitt and Purcell 2009; Richardson et al. 2009). However, despite this increasing
interest in gelatinous zooplankton, little is currently known
about the ecology of this group and the processes that lead
to high gelatinous zooplankton abundance (Hamner and
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Mar Biol
Dawson 2009; Mills 2001). This view has partially arisen
because gelatinous zooplankton are notoriously difficult to
sample from research ships using conventional plankton
sampling gear (nets and water bottles) because of their
extremely patchy distribution and fragile nature (see Purcell 2009 for a review). Put simply, the lack of information
stems from gelatinous zooplankton being overlooked by
researchers (Mills 1995) and consequentially, the best data
sets often result from the bycatch of annual fisheries surveys (Hay et al. 1990; Brodeur et al. 1999) or localised
studies (Moller 1980; Cargo and King 1990). These data
sets generally yield numerical abundances of individual
species which are then related to climatic variables (e.g.
Lynam et al. 2004), but the cross-comparison of the
gelatinous zooplankton biomass at different sites has not
been attempted.
Zooplankton and microplankton biomass are known to
vary on a latitudinal basis in the Atlantic ocean, with
lowest biomass around the tropics and highest at the
equator (San Martin et al. 2006). However, corresponding
patterns for gelatinous zooplankton have not been examined. Here, we explore gelatinous zooplankton biomass
patterns by undertaking a spatial meta-analysis from sites
across the globe that range between shallow coastal sites
and deep oceanic sites, in both tropical and temperate
regions. We explore the relationships between gelatinous
zooplankton and depth and the productivity of a region.
Hence, we point the way forward to how a global synthesis of the impact of gelatinous zooplankton might be
revealed.
Materials and methods
Compiling the database
Data on epipelagic gelatinous zooplankton biomass (GZB)
was sourced from the published literature (see Supplementary Information). We targeted papers that detailed the
biomass of planktonic gelatinous organisms (or gelata, see
Haddock et al. (2004) for a definition) of the groups:
scyphomedusae, ctenophores, hydromedusae and tunicates.
Where possible all data were converted into the same units
of grams of wet weight per 100 cubic metres (gWW
100 m-3), however in many cases, the volume sampled at
sites identified with GZB went unreported. In these cases,
conversion was not possible and these samples were not
included within the database. Often the units reported were
carbon, dry weight or number of individuals per unit volume along with the size range of species or taxonomic
groups collected; here we were able to convert the units to
wet weight. We used species or taxa-specific conversions
to derive wet weight (WW) from carbon weight (CW),
123
dry weight (DW), bell diameter (BD) or jellyfish length,
with preference given to equations from other studies in the
same area by the same authors. Equations were compared
between studies and were shown to produce similar results.
For example, A. aurita biomass of 291 milligrams of carbon per cubic metre (mg C m-3) (Han and Uye 2009) was
converted to 21,847 gWW 100 m-3, using Uye and Shumauchi (2005)’s CW = 3.7%DW and DW = 3.6%WW
ratios, although a direct conversion would have estimated
31,052 gWW 100 m-3 (CW (mg) = 20.85 ? (WW 9
0.87) Schneider and Behrends 1994). Conversions generated from juveniles or a restricted range of sizes of jellyfish
were excluded.
Standing stock (weight per area) estimates were converted to biomass per unit volume estimates using the
depths of sampling. This was the epipelagic zone (150 m)
for deep-water sites. For areas shallower than 150 m,
sampling depths were obtained from source material,
except Site 5 where 2 m surface visibility was assumed
(pers. obs.), Site 6 where mean depth was used, and Sites
45 & 48 where the average net height (listed as 31–41 m)
was used. Published abundance data lacking weight or bell
diameters was excluded in the absence of methods for
conversion. Where publications detailed the gelatinous
zooplankton biomass across several years, we calculated
the mean gelatinous zooplankton biomass for the entire
series. For five studies where there was regular monthly or
quarterly sampling, we excluded data from the winter in
the calculation of the mean biomass for that site. For three
sites, visual observations were deemed acceptable without
net validation. Site 1 was surveyed by divers traversing the
entire water column with a defined field of view to
calculate volumetric measurements. By contrast, Sites 4
and 5 were very shallow locations; boat transects
ensuring visibility throughout the water column, with
only 3–13% of medusae occurring below 1 m depth at
Site 4 (Pitt and Kingsford 2003). Biomass data was also
excluded where the original data could not be traced and
from locations with only one survey date and fewer than
three samples.
Primary productivity
Global estimates of primary productivity (averaged over
1998–2005) were obtained directly (Smyth et al. 2005;
Strömberg et al. 2009) and subsequently smoothed to a 0.5°
by 0.5° resolution using ArcGIS v 9.3. Ocean colour data
used in this study were produced by the SeaWiFS Project at
Goddard Space Flight Center. The data were obtained from
the Goddard Earth Sciences Distributed Active Archive
Center under the auspices of the National Aeronautics and
Space Administration. Use of this data is in accordance
with the SeaWiFS Research Data Use Terms and
Mar Biol
Conditions Agreement. We examined how primary productivity and secondary biomass within the epipelagic zone
varied globally with total water column depth, sourced
from the General Bathymetric Chart of the Oceans
(GEBCO—http://www.gebco.net) 30 s data set. Data were
obtained for 144,796 pixels. After removing pixels that
straddled land (which led to unreliable water depth values),
the data were arranged by total water column depth and
then mean values for groups of 1,000 pixels were calculated. This procedure was implemented so that each mean
value was based on the same sample size of pixels.
Enclosed locations lacked robust data at this scale resulting
from land masks. For 36 locations with robust primary
productivity, the productivity values were matched with the
corresponding gelatinous zooplankton biomass. A ratio
between epipelagic-GZB (gWW m-3) and primary
productivity (mg C m-3) was generated to establish the
trophic impact of the gelatinous zooplankton on the ecosystem and the data subsequently logged for clarity.
Results
Data on epipelagic gelatinous zooplankton abundance was
found for several thousand sites. For most sites, deriving
values of wet weight (g) per unit volume (m-3) was not
possible, mainly because abundance was simply reported
as number of individuals. In terms of number of samples,
the biggest data set is held in the COPEPOD database
(http://www.st.nmfs.noaa.gov/plankton/). This site reports
the numbers of cnidarians identified to various taxonomic
levels, however, there is currently no information on biomass. Furthermore, the samples are collected with small,
fine-mesh plankton nets which may not be suitable for
sampling large scyphozoan jellyfish. In total, we collated
data of biomass per unit volume within the epipelagic zone
from 58 studies worldwide (ranked by biomass—Fig. 1a;
S1) with mean biomass ranging from 0 to 5 9 104 gWW
100 m-3. To avoid confounding conclusions with heterogeneous sampling between sites, the number of observations, years sampled and samples per year were compared
with the biomass. In all cases, no correlation was found
(Pearson’s correlation p [ 0.29) and the data deemed
acceptably robust for further analyses.
The highest biomass (GZB) was recorded in Jellyfish
Lake, Palau (5 9 104 gWW 100 m-3, Fig. 1b). Offshore,
the northern Adriatic Sea (2.3 9 104 gWW 100 m-3,
Fig. 1b, c) recorded high GZB as a result of extensive blooms
of Pelagia noctiluca. High GZB was also reported for
Chesapeake Bay and other United States eastern seaboard
locations. The Black Sea, notable for Mnemiopsis outbreaks,
had levels of epipelagic-GZB two orders of magnitude lower
than Palau (4.9–5.2 9 102 vs. 5 9 104 gWW 100 m-3).
Fig. 1 a Location of epipelagic-GZB estimates; b Log plot of global
estimates of epipelagic-GZB biomass (n = 58 sites); and c Log plot
of epipelagic-GZB biomass in Europe (n = 21 sites). Scale comparable between b and c. Numbers also indicate biomass rank (1 being
highest and 58 lowest biomass), see Appendix S1
Similarly, estimates of epipelagic-GZB from the gelatinous
zooplankton-dominated Benguela upwelling system ranged
from 0.5 to 2.5 9 103 gWW 100 m-3, considerably below
the values for most shallow locations. Lowest biomass was
recorded in the central Atlantic and Norwegian Barents Sea.
Mean GZB decreased with the total water column depth
(mean water depth 672 m, range 2–5,100 m). Biomass was
greatest in shallow locations (many \10 m average depth),
such that log biomass = 4.36–1.09 9 log depth (F1,57 =
66.6, r2 = 0.543, p \ 0.001, Fig. 2). Although many sites
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Mar Biol
Fig. 2 Epipelagic-GZB as a function of total water depth (n = 58
sites, r2 = 0.543). Temperate regions are indicated by number,
tropical regions by letter where A site 1, B 6, C 16, D 28, E 36, F 37,
G 49 and H 54. Numbers also indicate biomass rank (1 being highest
and 58 lowest biomass), see Appendix S1
contained small sample sizes, there was no difference
between the trends with all samples included versus only the
32 sites with greater than 30 samples (F2,57 = 2.22,
p = 0.118). Equally, if the land-locked saltwater lake of
Palau (site 1) was excluded (F1,57 = 66.48, r2 = 0.547,
p \ 0.001), the same relationship was present. Finally, we
conducted a weighted least squares fit regression, where each
point was weighted by the log of the total number of samples
at that site. This analysis reiterated the conclusions of the unweighted regression analysis, with GZB again decreasing
markedly with total water depth (F1,53 = 54.06, r2 = 0.51,
p \ 0.001, excluding four sites with unknown sample
numbers). Hence, we are confident with the overall trends
and the conclusion that the epipelagic-GZB decreases with
total water depth. Tropical sites were found to have significantly higher GZB estimates than temperate regions
(ANCOVA F1,58 = 12.74, p = 0.001). Nevertheless, both
regions showed a declining trend with depth such that
log biomass in tropical regions = 5.57–1.18 9 log depth
(F1,7 = 19.54, p = 0.004) and temperate log biomass =
4.53–1.27 9 log depth (F1,49 = 72.36, p \ 0.001).
Primary productivity and secondary biomass within the
epipelagic zone showed a marked decline with total water
column depth from 10 to 10,000 m (Fig. 3a). However,
there was no correlation between the residual log-GZB: log
depth variation and the primary productivity of a region
(Pearson correlation = 0.136, n = 36, p = 0.343). At the
36 sites with robust productivity estimates, we compared
the balance between gelatinous material and production in
the epipelagic zone (Fig. 3b) and therefore, the probable
ecosystem role of gelatinous material. The ratio of GZB to
primary production showed a broad range of values, but
noticeably this ratio was consistently high across a range of
123
Fig. 3 a Epipelagic primary productivity (open circles) and Secondary biomass (closed circles) with a marked decline with total water
column depth, for depths from 10 to 10,000 m. Error bars are ±1SE
and are not displayed where the error was less than 1. b Relative
abundance of epipelagic gelatinous zooplankton biomass (GZB) to
primary productivity and hence an indication of the relative
ecosystem role of gelatinous zooplankton
depths. For example, high ratios were found in shallow or
enclosed sites—e.g. Gulf of Mexico and Sea of Azov
(\15 m), intermediate depth sites such as the Northern
Adriatic and Sea of Mamara (\70 m) and deep ocean sites
including the Benguela upwelling and Antarctic polar front
([400 m). In these sites, the gelatinous biomass is high
relative to the productivity of the region. However, it was
also noticeable that at many deeper sites the relative
abundance of gelatinous zooplankton was lower (e.g. North
Sea, Norwegian Barents Sea).
Taxonomically, the scyphozoan jellyfish Aurelia sp. (Se,
Fig. 4) or the often-invasive ctenophore Mnemiopsis leidyi
(Ct, Fig. 4) were the predominant species in 68% of the top
25 biomass regions identified (12 and 5 locations, respectively). Away from these predominately neritic locations,
hydromedusae such as Aequorea sp., the semaeostomes of
Chrysaora sp. and the coronate Periphylla periphylla
dominated the epipelagic layer of deeper oceanic locations
(Fig. 4; S1).
Mar Biol
Fig. 4 Relative dominance of gelatinous taxa within the epipelagic
zone as a function of the total water column depth, n = 11, 13, 14, 6,
8, 6 study sites, respectively. Species classified into Rhizostomeae
(Rh), Semaeostomeae (Se), Coronate (Co), Ctenophora (Ct), Tunicata
(Tu), Hydromedusae (Hy), Siphonophora (Si) and Unidentified
species (Un)
Discussion
Our work suggests that there are distinct patterns of
gelatinous zooplankton biomass in the global ocean. The
most parsimonious explanation for the decrease in epipelagic-GZB with total water column depth is that this pattern
is driven, at least in part, by patterns of primary production,
i.e. bottom-up control. Over global scales, the processes
that drive the abundance of many marine groups are fairly
well established with, for example, patterns of global primary productivity strongly linked to nutrient levels, trace
metal concentrations and light levels (Lalli and Parsons
1993). Shallow coastal sites tend to be more eutrophic and
have higher primary productivity than deep ocean sites
(Strömberg et al. 2009), a pattern broadly mimicked in our
results for gelatinous zooplankton (Fig. 1b, c). The pattern
of increasing GZB in shallow sites may explain why predators of gelatinous zooplankton, such as leatherback
turtles, often target coastal sites for foraging on large
scyphozoan species, such as Rhizostoma octopus (Houghton et al. 2006). Although intuitive, the change in epipelagic gelatinous biomass with depth has not previously
been highlighted on a broad, multi-species scale, despite
the widespread impact of gelatinous aggregations in many
estuarine and neritic habitats (Purcell et al. 2007).
Whilst we were able to assemble a data set that spanned
regions, water depths and habitats, one of our first important findings was that many of the studies where gelatinous
zooplankton have been sampled could not be included in
the meta-analysis for various reasons. A number of regions
exist, particularly in the Indian and southern Pacific oceans,
where cruises have recorded gelatinous zooplankton numbers, but not biomass or typical size classes. Oceanographic plankton tows are also known, in many cases, to
collect gelatinous biomass or biovolume (e.g. Angel and
Pugh 2000), but by towing from great depth to the surface
they may not characterise epipelagic abundance separately.
Additionally other locations, such as Mar Menor in Spain
(Perez–Ruzafa et al. 2002), are known to have been colonised by gelatinous zooplankton, but biomass data has yet
to be published. Sometimes we could not generate biomass
values because the dimensions of animals were not reported, such as the 27 year time-series of Molinero et al.
(2008), or densities were not detailed in suitable units (e.g.
as numbers per square metre). Perhaps the biggest issue
with these studies was the volumes of water sampled in the
collection of gelatinous zooplankton were not reported.
Clearly, one important step towards an expanded data set
would be for future published studies of gelatinous zooplankton to include density values (whether wet weight,
dry weight or carbon content) per unit volume filtered.
Gelatinous zooplankton of various species can cover a
range of sizes: from a few grams to tens of kilograms. We
might expect that smaller fine-mesh nets are better for
sampling smaller or fragile gelatinous zooplankton that
occur in high densities, and may not be directly comparable
to the larger coarse-mesh nets that filter larger volumes of
water, sampling lower densities of larger and more robust
jellyfish. These are common issues with plankton sampling
(Harris et al. 2000). A similar problem arises when you
consider the scale of different studies with some studies
conducted over 100 m2 and others over 1,000 km2. Sampling over larger areas is likely to smooth out the consequences of patchy horizontal and vertical distribution and
produce better estimates of mean abundances over large
areas. Sampling over small areas, or a limited range of
depth layers, will tend to produce more variation in mean
abundance estimates depending on whether discrete high
density patches, inherent in zooplankton populations, are
sampled or missed. For instance, in the western Irish Sea,
an area of roughly 4,200 km2, Lynam et al. (2011) found
that 62 hauls were needed annually for a robust estimate of
mean gelatinous biomass.
There is also the potential for reporting bias in that high
gelatinous zooplankton abundance may be noteworthy and
hence more likely to lead to a publication. This might be
the case, for example, in the northern Adriatic, where the
wide-scale socioeconomic concerns caused by blooms of
the stinging jellyfish Pelagia noctiluca, attract considerable
focused research on this species and area (Purcell et al.
1999; Zavodnik 1991), although recent wavelet analysis
has confirmed the presence of five species in this region
over longer timescales (Kogovšek et al. 2010). Furthermore, downward vertical migration of zooplankton from
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Mar Biol
the epipelagic region by day (for example, Pugh 1990),
could result in sampling biases. However, shallow locations or integrated tows through the water column (e.g.
Pugh et al. 1997; Pages et al. 1996; Hay et al. 1990; Brodeur et al. 2008; Lynam et al. 2011) will mitigate these
biases. Finally, the inclusion of data documenting low
numerical and biomass samples within databases and
publications should be regarded with equal importance to
notable events. For instance, the continued recording of
regions currently affected by invasive species such as
Mnemiopsis, can document the extent of recovery over
time, with the Black Sea ecosystem reported to be returning to a healthier state following predation on Mnemiopsis
by the predatory ctenophore Beroe (Kideys 2002). We are
aware of these limitations of our data set and view this only
as a first step upon which to build a more comprehensive
global gelatinous zooplankton data set in future years.
Whilst strong links between depth and gelatinous zooplankton biomass were found, there was a considerable
level of unexplained variation (45.7%). What may be the
other factors that influence gelatinous zooplankton biomass? Latitudinally, distinguishing between tropical and
temperate regions accounted for an additional 8.6% of the
variation. Additional tropical samples and shallow polar
sites would further define this variability with the size and
biomass of other zooplankton groups known to increase
away from the tropics (San Martin et al. 2006). Even at
individual sites it is known that the biomass of gelatinous
zooplankton varies across years (Lynam et al. 2004). For
example, in the Irish Sea, mean annual GZB ranged from
9.95 to 2.8 9 102 gWW 100 m-3 over a 16-year timescale
(Lynam et al. 2011). In some cases, this inter-annual variability has been linked to climate indices (Lynam et al.
2004, 2011; Brodeur et al. 2008), with the implication that
certain environmental conditions may favour the development of gelatinous zooplankton, (Lynam et al. 2011).
Likewise, the climatic effect on the plankton composition
and subsequently the productivity of a region may vary
seasonally (Irigoien et al. 2000). Equally top–down control
may sometimes cause variation in the gelatinous zooplankton biomass, e.g. as seen with Mnemiopsis and Beroe
in the Black Sea (Kideys 2002).
Epipelagic primary productivity and secondary biomass
both showed a decline with depth (Fig. 3a), although in
regions where both the productivity and GZB data was
available, the relative abundance of GZB to primary productivity did not change systematically with depth
(Fig. 3b). A high ratio of GZB to primary productivity may
indicate locations where the GZB may play a more
important ecosystem role, as was the case with Mnemiopsis
leidyi in the Black and Caspian Seas and the Sea of Azov
(Shiganova et al. 2001; Daskalov et al. 2007; Kideys and
Moghim 2003). Few locations might be expected to contain
123
gelatinous monocultures, but only one species was reported
from 37 of the 58 sites. This suggests that rarer species may
often be underreported. We would encourage the recording
of the whole gelatinous assemblage biomass during surveys, in addition to the key species, to provide a context for
the ecosystem impact of GZB.
In terms of the gelatinous zooplankton taxa, a scyphozoan jellyfish Aurelia sp. (reported as a species complex,
after Dawson et al. 2005) and a ctenophore Mnemiopsis
leidyi were often key members of the epipelagic gelatinous
fauna when high biomass was recorded (Fig. 4). Aurelia
sp. often seem to dominate in coastal sites and it is well
known to be very eurythermal and euryhaline which may
contribute to its success across a wide range of coastal
environments (Lucas 2001). Mnemiopsis is perhaps best
known as an invasive species which invaded into the Black
Sea, having wide socio-economic impacts (Kideys 2002),
but it also thrives in its natural habitat on the eastern seaboard of the United States, in locations such as Chesapeake
Bay (Purcell et al. 2001). In Chesapeake Bay, Mnemiopsis
leidyi biomass is negatively correlated with the predatory
scyphozoan jellyfish Chrysaora quinquecirrha. The balance between the species is driven by river discharge,
salinity and water temperatures, with potential eutrophication when M. leidyi is abundant (Purcell and Decker
2005). Interestingly, very high densities of gelatinous
zooplankton have been reported at many of the sites
where Mnemiopsis is present and eutrophication is likely
when high densities of this voracious predator occur
(Kideys 2002). Likewise, the invasive scyphozoan Phyllorhiza punctata contributes to the very high gelatinous
zooplankton densities found in the Gulf of Mexico
(Graham et al. 2003). It is thought that invasive gelatinous species are transported in ballast water (Ivanov et al.
2000), and their proliferation point to the need for better
treatment and/or management of ballast water to reduce
further introductions (Tsolaki and Diamadopoulos 2010).
One of the biggest concerns regarding gelatinous zooplankton is that overfishing, often of planktivorous fish
(Richardson et al. 2009), may result in increases in gelatinous zooplankton abundance. Sites where such increases
in gelatinous zooplankton have occurred include the
Benguela upwelling system, the Sea of Japan and the Black
Sea. Interestingly, all these sites show positive residuals on
the relationship between gelatinous zooplankton biomass
and total water column depth, i.e. show more gelatinous
zooplankton within the epipelagic zone than expected by
the relationship with depth (Fig. 2). This is the pattern that
is predicted if removal of planktivorous fish is an important
driver in high gelatinous zooplankton abundance (Daskalov
et al. 2007). By contrast, human activities have a considerable impact within the North Sea (Halpern et al. 2008),
but this region had lower than expected biomass (sites
Mar Biol
42–44, 46, 47; Figs. 2, 3b) and relatively low GZB compared to the productive nature of this region. The temporal
differences between the levels of abundance reported from
the North Sea (1971–1986 survey, Hay et al. 1990) versus
the sourced primary productivity data may have had an
effect, but similar results from 2004 to 2005 (Barz and
Hirche 2007) suggest that other climatic or anthropogenic
issues are restricting the potential North Sea GZB (Lynam
et al. 2010). Unfortunately, spatial gaps in our knowledge
of the biomass of gelatinous zooplankton prevent interpretation of the consistency of anthropogenic impacts, such
as overfishing, on global patterns of GZB.
Acknowledgments This work is part of EcoJel a project funded by
the Interreg 4a Ireland–Wales programme, which forms part of the
European Regional Development Fund (ERDF); Natural Environment
Research Council (NERC); and the Esmée Fairbairn Foundation.
Author contributions: GCH designed the study. MKSL compiled and
analysed the global gelatinous zooplankton data set. GCH and MKSL
wrote the paper with contributions from all authors. We wish to thank
F. Lombard for advice on the weighted regression. The authors
declare that they have no conflict of interest.
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