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Carybdea marsupialis (Cubozoa) at a shallow
beach in West Mediterranean: are they
where they want to be?
Cesar Bordehore1, Elia Durá1, Antonio Ortiz1, Isidro Rico1,
Melissa J. Acevedo 1,2, Antonio Canepa and Verónica L. Fuentes2
Fourth International Jellyfish Bloom Symposium, 5-7 June 2013 – Hiroshima, Japan
1, Department of Ecology and IMEM Ramon Margalef, University of Alicante, Spain.
2, Institute of Marine Sciences, Spanish Research Council, Barcelona, Spain.
.
INTRODUCTIONION
Scyphozoan and cubozoan jellyfish are unevenly distributed. Differences in spatial distribution of adult jellyfish have been correlated with
water temperature (1) or salinity and river run-off (2). Densities of cubozoans are generally low, with values of <3 medusae per
100m3 (Great Barrier Reef, Australia , 3).
In the studied area (W Mediterranean, SE Spain) we detected high densities of C. marsupialis in shallow waters (0 to 1,5 m depth) during
Summer and Autumn 2008 (4). This high density of individuals in shallow waters resulted in a high number of stung bathers (3.330
people between 16th July to 15th September 2008). The next year (2009), we quantified densities and sizes of box jellyfish in order to
compare them with the previous data collected in 2008, and we also measured other environmental variables to elucidate how this
species interact with the environment. We analyze the correlation of C. marsupialis presence and densities with different
parameters such as temperature, salinity, sea bottom, visibility, sea and sky condition.
ISTUDY AREA
Denia is a coastal city where sun-and-beach tourism is the main item on its economy. Each summer
about 30.000-50.000 tourists are added to the permanent population of 45.000 inhabitants. There is
intensive watered agriculture in the surroundings, which uses a high quantity of fertilizers rich in
nitrate and phosphate. Rainfall range from 600 and 800mm per year, being mid-late autumn when rain
is more abundant. Low salinity close to the shore was originated to by sub-surface aquifer discharge
(~6· 106m3·y-1, 120-170mg NO3=·l-1).
The study area comprises 17km along the coastline with a low underwater slope and a variety of sea
bottoms: sand, Posidonia oceanica, boulders, and mud. We sampled at 8 beaches (organized into 5
groups) as in Bordehore et al (4) (Fig. 1). At each sampling point we took different number of samples,
depending mainly on swell and accumulations of Posidonia oceanica death leaves in the sampling areas –
net towing is impossible in such conditions-.
IMATERIALS & METHODS
Sampling
We sampled from 1th October to 15th November 2009 performing net trawlings parallel to the
coastline, by walking at 2-3 km·h-1.We towed plankton nets of 4mm mesh, squared shape, 0.1256 m2
of mouth area. We used a set of 4 nets in a row, approximately 1m apart each other. At each
sampling site we sampled from 2 to 5 transects of 30 meters, leaving 30m of separation between
each transect.
At each transect we recorded environmental variables such as: substrate type (sand, mud, boulder,
rocky), visibility (Sechhi disk in horizontal), sky conditions (sunny/cloudy), sea state (categorical
scale:1-6, where 1 is calm and 6 is rough sea), and water temperature and salinity using a
compact Infinity-CT attached to one of the nets (sensor depth at 0.4m – 0.6m).
Data treatment
We used Simple Generalized Linear Model (GLM) and Mixed (GLMM) to elucidate how Carybdea
marsupialis distribution was correlated to the measured environmental factors.
RESULTSION
Different densities among sampling sites (fig 4) and before vs after a storm
occurred at the middle of the period. Transects from 15th October only captured
16 individuals in 2165,31 m3, being this amount of individuals not enough to
perform any correlation analysis. We only used for analysis data from 2th
September to 14th October to correlate densities of C. marsupialis with
independent environmental values. C. marsupialis maximum density was
recorded at Raset beach on 8th October (249,43 indv/100m3). Comparing
densities and individuals size (fig 5) structure between 2008 and 2009 data
were similar at each beach.
Environmental variables (fig 6):
The variable that better explained the spatial distribution of C. marsupialis was
low salinity (GLM, p-valor<0.001), with some values under 222 psu.
We also obtained a significative correlation with low visibility (GLM, p-
valor<0.001) and sunny days (GLM, p_valor<0.001).
The other variables (water temperatura, depth, and sea bottom) didn’t show
positive correlation.
CONCLUSIONSON
Carybdea marsupialis at the sampling site shows patchy distribution (hundreds of meters) and high densities.
We find that low salinity is positively correlated to C. marsupialis distribution as showed by other authors (Gordon et al 2004;
Cutress and Studebaker, 1973).
Low salinity in the study area was not due to any river runoff but to sub-surface aquifer discharge (~6 106m3·y-1, and about
120-170mg NO3=·l-1), and seems that the response of the cubomedusae to low salinity is the same independently of the low
salinity origin.
We also detect a positive correlation with low visibility and sunny days.
Sea bottom had no any influence on C. marsupialis distribution, in contrast to other authors that stated that this species was
associated with sandy bottoms (Di Camilo et al 2006).
References:
[1] Bettoso, N., 2002. First record of Carybdea marsupialis (L., 1758) (Cnidaria:
Cubozoa) in the Gulf of Trieste. Periodicum Biologorum, 104, 233.
[2] Gordon, M. R., C. Hatcher & J. E. Seymour, 2004. Growth and age determination of
the tropical Australian cubozoan Chiropsalmus sp. Hydrobiologia 530: 339–345.
[3] Hartwick, R. F., 1991. Distributional ecology and behavior of the early life stages of
the box-jellyfish Chironex fleckeri. Hydrobiologia 216: 181–188.
[4] Bordehore, C., Fuentes, V. L., Atienza, D., Barberá, C., Fernandez-Jover, D., Roig,
M., Acevedo-Dudley, M. J., et al. (2011). Detection of an unusual presence of the
cubozoan Carybdea marsupialis at shallow beaches located near Denia, Spain (south-
western Mediterranean). Marine Biodiversity Records, 4(5), 1–6.
This research was carried out under contract LIFE 08 NAT ES 0064 (to VF and CB) co-
financed by the European Union, the Ministerio de Agricultura, Alimentación y Medio
Ambiente, Fundación Biodiversidad, and the Dirección General del Agua of the Regional
Government of Valencia. We also thank the collaboration of Balearia Foundation
(www.balearia.com), the Real Club Nautico Denia (www.cndenia.es) and el Portet
(www.elportetdedenia.es). .
5km
1 2 3 4 5
Fig.1 Sampling sites. SE Spain. Beach names: 1: Deveses+Almadrava
2: Molins 3: Bovetes 4: Raset 5: Marineta
Fig 2. Sampling
with a set of 4
nets in a row.
Fig 3. Measuring
an individual of
Carybdea
marsupialis
(distance
between
rhopalias).
0
10
20
30
40
50
before
after
before
after
before
after
before
after
before
after
Dev+Alm
Molins
Bov+Bris+Mar
Raset
Marineta
indvs /100m3 +SE
ND ND
Figure 4. Density (Indv/100m3) of Carybdea marsupialis
adults at each group of adjacent beaches, grouped in two sets
of data: before and after storm. Mean +SE. ND: No data.
Before: samples from 2nd to 14th October 2009. After: samples
from 20th October to 2nd November 2009. Storm began 15th
October, waves disappeared on 20th October.
Table 1. Number of transects done at each group of beaches, meters towed,
m3 of sea water filtered and densities (invds/100m3) of Carybdea
marsupialis and SE of the density.
Figure 6. Carybdea marsupialis response to environmental factors
Figure 5. Size histograms (in mm) at three periods. See how
sizes are increasing from August to the end of October.
www.cubomed.eu
Transects
number
M towed
M3 filtered
Indv. Captured
Dens/
100m3
SE
Deveses+Almadrava
before
4
240
35,28
15
42,52
7,13
after
216
6480
952,56
2
0,21
0,01
Molins
before
0
ND
ND
ND
ND
ND
after
138
4140
608,58
0
0,00
0,00
Bovetes+Brisas+M.Reig
before
56
3360
493,92
55
13,82
2,71
after
99
2970
436,59
0
0,00
0,00
Raset
before
134
6690
983,43
305
31,48
15,92
after
38
1140
167,58
14
8,35
2,48
Marineta
before
56
1680
246,96
0
0,00
0,00
after
0
ND
ND
ND
ND
ND
Before storm
250
11970
1759,59
375
20.05
8.58
After storm
491
14730
2165,31
16
0.73
0.22
Total
741
26700
3924,9
391
7.25
2.91