Estudio comportamental y herramientas de
identificación de doradas y lubinas escapadas:
implicaciones para la gestión sostenible de la
acuicultura.
Pablo Arechavala López
Behavioural assessment and identification tools for sea bream and sea bass
escapees: implications for sustainable aquaculture management.
Estudio comportamental y herramientas de identificación de doradas y lubinas
escapadas: implicaciones para la gestión sostenible de la acuicultura.
Memoria presentada para el grado de Doctor Internacional
en la Universidad de Alicante por
PABLO ARECHAVALA LÓPEZ
ALICANTE, Octubre 2012
Dirigida por: Dr. Pablo J. Sánchez Jerez y Dr. Just T. Bayle Sempere
En primer lugar he de agradecer a los trabajadores y responsables de las empresas de
acuicultura; de manera especial a Agustín, Jesús y sus chicos de CULMAR (Cultivos
Marinos de Guardamar; Grupo Marjal), por abrirnos las puertas de sus instalaciones y de su
amistad, mostrando un total apoyo durante la realización de esta tesis y facilitándonos
mucho el trabajo. Gracias por los buenos momentos, las risas y los cafés mañaneros en el
puerto. También agradecer a los trabajadores de las lonjas y a los pescadores locales, tanto
profesionales como deportivos, su voluntaria colaboración en la recolección de doradas y
lubinas durante estos años.
Esta tesis doctoral ha sido financiada por el 7º Programa Marco de la Comisión Europea, y
forma parte del proyecto “PREVENT ESCAPES: assessing the causes and developing
measures to prevent the escape of fish from sea-cage aquaculture (num. 226885)”. Muchas
gracias al Departamento de Ciencias del Mar y Biología Aplicada y al IMEM Ramón
Margalef de la Universidad de Alicante por respaldarme y facilitarme en todo momento la
parte logística de este proyecto. Por supuesto, gracias también al CIMAR por haberme
permitido trabajar y disfrutar en sus instalaciones (lo siento por el olor a pescado!).
A modo más personal, gracias de todo corazón a mis directores de tesis Pablo Sánchez y Just
Bayle. Vosotros pusisteis vuestra confianza en mi hace ya unos cuantos años y me
enseñasteis a desenvolverme en este mundo. Nada de esto hubiese comenzado si no me
hubierais dado la oportunidad de formar parte de vuestro equipo. Just, tu encendiste la llama
de mi curiosidad por la ciencia de los peces, gracias por esta oportunidad y por tu apoyo.
Pablo, eres el alma de esta tesis. Me has guiado y aconsejado en cada paso que he dado desde
el primer día, mostrándome el camino para llegar aquí. Gracias a los dos por vuestra
amistad y por hacerlo posible!
There are also two important persons that I really like to thank, the other pillars of this
project. Ingebrigt Uglem, you taught me everything I know about fish telemetry and offered
me the possibility to do what I really love. And Tim Dempster, thanks for your supports and
good advices these last years, you helped me to walk in the right direction. Sincerely, thank
you mates for your close friendship despite of the distance. Half of this thesis is thanks to
you guys!
Agradecer a todos y cada uno de los investigadores (y buenos amigos) que he conocido
gracias a este proyecto. Of course, thanks a lot to all the people involved in this European
project (Norwegians, Greeks, Irish, Canadians, English, Scottish, Maltese, Basks and the
rest of Spanish guys). It was a pleasure to meet all of you and thanks for supporting me
(next time I´ll pay the beers). You really made me feel part of this “Escape family” (the little
one, of course).Thanks for your kindness and friendship!
Como no, a mi familia “biológica” alicantina y sanvicentera, con la que he compartido
muchos y buenos momentos en los últimos años. Todos vosotros me acogisteis con los brazos
abiertos desde el primer día, y he de agradeceros vuestra más sincera amistad. Como sois un
porrón de gente y no quiero dejar a nadie en el tintero me temo que no pondré la ristra de
nombres tan esperada. Eso sí, desde el más viejo al más joven, del más cuerdo al más “tarao”,
pasando por todas las casas, despachos y laboratorios…daros todos por aludidos!
No obstante, muchos me habéis sufrido desde el primer día en todo este proceso que llaman
tesis doctoral, pero tengo que agradecer especialmente a aquellos que han aportado su granito
(o granazo) de arena, ayudándome y soportándome en los muestreos, en los despachos y/o
en los bares: Dami, Tocho, Fran, Javi, Carlos, Ana`s, Gema, Juanfran, Ester, Kilian, Aitor,
Alfonso, José Luis, Vicky, Loya, Elena, Tito, Cande, Marko, Juanma, Lydia, Juani, Martin,
Joan, David, Ana… Gracias!
Por último, y precisamente los más importantes, mi familia. Tengo que darles las gracias a
mis padres José y Toñi, y a mi hermana Mónica (con sus dos soles María y Ana), por su
calor y su ternura, por su ayuda y su apoyo incondicional en todo momento (pese a que no
les voy a visitar muy a menudo últimamente!). Ellos me criaron en un entorno que olía y
sabía a mar (y a sidra), que se oía el mar…a cientos de kilómetros de distancia de la costa
más cercana! Gracias por enseñarme a respetarlo y amarlo. Pero sobre todo, gracias por
enseñarme a luchar para conseguir alcanzar mis metas, por muy lejanas o imposibles que
parezcan. Nunca sabré como agradeceros todo esto! Y termino con la persona que armoniza
mi vida, que no ha dejado de apoyarme y animarme en todo este tiempo…Maite, gracias por
estar siempre a mi lado!
A todos, GRACIAS!
CONTENTS
CONTENTS
General Abstract / Resumen General ........................................................................................ 5
1. Introduction............................................................................................................................ 11
1.1. Gilthead sea bream ................................................................................................ 13
1.1.1. Systematic, biology and ecology
1.1.2. Sea bream farming industry
1.2. European sea bass ................................................................................................. 15
1.2.1. Systematic, biology and ecology
1.2.2. Sea bass farming industry
1.3. Escapes of farmed fish from net-pens ..................................................................... 17
1.3.1. What are escapes?
1.3.2. Causes of escapes in the Mediterranean farms
1.4. Problematic of escapees ........................................................................................ 18
1.4.1. Genetic interactions with wild conspecifics
1.4.2. Ecological interactions with wild stocks
1.4.3. Risk of non-indigenous stock establishment
1.4.4. Potential diseases and pathogens transmission
1.4.5. Influence on local fisheries and consumers
1.5. Objectives ................................................................................................................ 28
1.5.1. General objectives
1.5.2. Specific objectives
2. Post-escape behaviour of farmed sea bream ..................................................................... 29
2.1. Abstract.................................................................................................................... 31
2.2. Introduction .............................................................................................................. 31
2.3. Material and methods .............................................................................................. 32
2.3.1. Study area
2.3.2. Tracking and tagging procedure
2.3.3. External tagging and recapture programme
2.3.4. Habitat use and feeding habits
2.3.5. Data analysis
2.4. Results ..................................................................................................................... 36
2.4.1. Swimming behaviour at farms facilities
2.4.2. Dispersion and interaction with fisheries
2.4.3. Habitat use and feeding habits
2.5. Discussion .............................................................................................................. 42
3. Post-escape behaviour of farmed sea bass ...................................................................... 47
3.1. Abstract.................................................................................................................... 49
3.2. Introduction .............................................................................................................. 49
3.3. Material and methods .............................................................................................. 49
3.3.1. Study area
3.3.2. Tracking and tagging procedure
3.3.3. External tagging and recapture programme
3.3.4. Habitat use and feeding habits
3.3.5. Data analysis
3.4. Results ..................................................................................................................... 52
3.4.1. Swimming behaviour at farms facilities
3.4.2. Dispersion, habitat use and feeding habits
3.5. Discussion .............................................................................................................. 54
3
SEA BREAM AND SEA BASS ESCAPEES
4. Differentiating the wild or farmed origin of sea bream and sea bass .............................. 59
4.1. Abstract.................................................................................................................... 61
4.2. Introduction .............................................................................................................. 61
4.3. Material and Methods .............................................................................................. 62
4.3.1. Fish sampling
4.3.2. Morphometry
4.3.3. Scales sampling
4.3.4. Otoliths sampling
4.3.5. Fins condition
4.4. Results ..................................................................................................................... 67
4.4.1. Morphological differences
4.4.2. Scales characteristics
4.4.3. Otoliths shape
4.4.4. Fins condition
4.5. Discussion ............................................................................................................... 80
4.5.1. Morphology
4.5.2. Scales
4.5.3. Otoliths
4.5.4. Fins
4.5.5. Conclusions
5. Evaluation of tools for identifying escapees: a review ..................................................... 87
5.1. Abstract.................................................................................................................... 89
5.2. Introduction .............................................................................................................. 89
5.3. Literature analysis ................................................................................................... 90
5.4. Analytical tools used to discriminate wild and farmed fish ...................................... 90
5.4.1. External Appearance and Morphology
5.4.2. Organoleptic Characteristics
5.4.3. Proximate Composition and Fatty Acid Profile
5.4.4. Stable Isotopes
5.4.5. Trace Elements
5.4.6. Accumulative Pollutants
5.4.7. Genetic Differences
5.5. Implications and guidelines .................................................................................. 103
6. General Discussion ............................................................................................................. 107
6.1. Relevance of sea bream and sea bass escapees ................................................ 109
6.2. Guidelines for management strategies .................................................................. 109
6.2.1. Prevention, mitigation and impact reduction strategies
6.2.2. Strategies for genetic consequences
6.3. Risk analysis of sea bream and sea bass escapees ............................................ 112
6.4. Gaps of knowledge and future research ............................................................... 114
Conclusions / Conclusiones .................................................................................................. 119
References ............................................................................................................................... 125
Annex: Published Material ..................................................................................................... 149
4
ABSTRACT / RESÚMEN
GENERAL ABSTRACT / RESUMEN GENERAL
Gilthead sea bream (Sparus aurata L.) and
European sea bass (Dicentrarchus labrax L.)
are marine species of great economic
importance, particularly in Mediterranean
aquaculture. Mediterranean fish farming
industry has risen during the last decade,
and is already widely established in the
Mediterranean basin, particularly in
Greece, Turkey, Spain and Italy; and can be
growing in other European countries such
as Croatia, Malta and Cyprus. However,
derived problems also began to arise
concerning escape events in sea bream and
sea bass aquaculture.
La dorada (Sparus aurata L.) y la lubina
(Dicentrarchus labrax L.) son dos especies
marinas de gran valor económico,
particularmente
en
la
acuicultura
Mediterránea. La industria acuícola del
Mediterráneo ha aumentado durante la
última década, y se ha establecido
ampliamente
por
toda
la
cuenca
Mediterránea, particularmente en Grecia,
Turquía, España e Italia y continuará
creciendo en otros países como Croacia,
Malta y Chipre. No obstante, también
surgen ciertos problemas en los cultivos de
doradas y lubinas, como son los escapes.
Escapes are caused mainly by technical and
operational failures at farm facilities, and
represent a considerable economical loss for
the farmers. Escapes of sea bream and sea
bass from sea cages have been sporadically
recorded throughout the Mediterranean,
and their potential to interact with the
natural populations is considered one of the
main
environmental
problems
in
aquaculture. Genetic and ecological effects
through
interbreeding,
predation,
competition (food, habitat, mating) and the
transfer of diseases to wild fish as well as to
other farmed stocks are the most important
threats. However, knowledge on the fate
and effects of the escaped aquacultured sea
bream and sea bass in the Mediterranean
was still sparse.
Los escapes son causados principalmente
por fallos técnicos y operacionales en las
instalaciones, y representan considerables
pérdidas económicas para los piscicultores.
Se han registrado esporádicamente escapes
de doradas y lubinas a lo largo de todo el
Mediterráneo, y su potencial para
interactuar con las poblaciones naturales se
considera uno de los principales problemas
medioambientales en la acuicultura. Los
escapes pueden crear serios efectos
genéticos y ecológicos en las poblaciones
salvajes, ya sea por reproducción,
depredación, competición (por alimento,
hábitat o apareamiento) y/o transmisión de
enfermedades a peces salvajes o a otros
cultivos cercanos. No obstante, se
desconocen realmente los efectos de los
escapes de dorada y lubina cultivada en el
Mediterráneo.
Therefore, this thesis aims to improve the
knowledge about the potential effects of
escaped sea bream and sea bass in the
Mediterranean coast through tagging
experiments, as well as developing
practical techniques for reliable and
effective identification of escaped fish,
through the evaluation of different types of
methodologies. Furthermore, it was
discussed the need and potential for
developing and implementing various
preventive and mitigate measures in order
to improve the forthcoming sustainable
aquaculture management. In chapters 2 and
3, the post-escape behaviour of farmed sea
bream and sea bass was assessed
respectively, demonstrating the complex
negative ecological consequences that
Por ello, esta tesis trata de mejorar el
conocimiento sobre los posibles efectos de
los escapes de dorada y lubina en la costa
Mediterránea mediante experimentos de
marcaje, así como desarrollar técnicas
prácticas para la identificación fiable y
eficaz de los escapados, evaluando
diferentes metodologías. Además, se
discute el potencial y la necesidad de
desarrollar e implementar diferentes
medidas de prevención y mitigación con el
fin de mejorar la futura gestión sostenible
de la actividad acuícola. En los capítulos 2 y
3 de la presente tesis se estudia el
comportamiento de las doradas y las
lubinas cultivadas cuando se escapan
7
SEA BREAM AND SEA BASS ESCAPEES
escapees might entail to nearby cultured
and wild stocks. Escape incidents of sea
bream tagged with acoustic transmitters
and/or external tags were simulated.
Within the first week, both escaped sea
bream and sea bass showed repeated
movements
among
different
farms,
probably related with feeding activity at
farms or looking for shelter among cages.
Moreover, escaped sea bream and sea bass
are biologically able to survive for long
periods once in the wild, feeding on natural
preys and swimming to nearby farm
facilities and coastal habitats (feeding and
spawning areas). Furthermore, local
fisheries contributed largely recapturing
tagged individuals that disperse from farm
facilities, being professional trammelnetters the major contributors for sea bream
and recreational fishermen for sea bass.
Thus, it is also illustrated not only the
importance of local fisheries to reduce the
potential effects of escape incidents on
natural stocks, but also that other related
sectors such as fish markets and consumers
can be affected.
The knowledge acquired in these chapters 2
and 3 highlights the need to develop
practical methodologies for reliable and
effective identification of escaped fish, easy
to apply in the field and with quick results.
Therefore, different types of identification
techniques and methodologies were
evaluated in chapter 4, based on the fact
that farmed fish experience different
environments, stocking densities and
feeding regimes compared to wild fish. The
analyses of fish growth showed that farmed
fish presented higher weight-length
relationship values than wild fish on both
species.
In
addition,
significant
differences
provided through morphometry evidence
that the cranial and body regions of sea
bream and sea bass are different regarding
their farm or wild origin. Moreover, scales
characteristics and otoliths shape analysis
discriminated wild and farmed individuals
with high accuracy. In fact, scales
characteristic are suggested to be the easiest
and quickest way to identify escapees
within wild stocks, since neither specific
8
de las jaulas, demostrando los complejos
efectos ecológicos negativos que los escapes
podrían implicar en los cultivos cercanos y
en las poblaciones salvajes. Para ello se
simularon incidentes de escapes en las
jaulas, usando técnicas de marcaje externo y
acústico. Durante la primera semana,
algunos individuos de ambas especies
mostraron repetidos movimientos entre las
diferentes instalaciones, probablemente en
busca de alimento o refugio entre las jaulas.
Además, se ha demostrado que las doradas
y las lubinas escapadas son biológicamente
capaces de sobrevivir en libertad,
alimentándose de presas naturales y
nadando en los alrededores de las
instalaciones acuícolas y hábitats costeros
(zonas de alimentación y reproducción).
Asimismo,
los
pescadores
locales
contribuyeron en gran medida en la
recaptura de los individuos marcados que
se dispersaron de las jaulas, siendo los
trasmalleros profesionales y los pescadores
deportivos los que mas doradas y lubinas
recapturaron respectivamente. Por tanto, se
ha demostrado no sólo la importancia de
los pescadores locales a la hora de reducir
el potencial efecto de los escapes en los
stocks nativos, sino también que otros
sectores pueden verse afectados por dichos
incidentes, como los pescaderos y los
consumidores de pescado local.
Mediante el conocimiento adquirido en los
capítulos 2 y 3, se destaca la necesidad de
desarrollar prácticas metodologías que
identifiquen los escapes de manera fiable y
eficaz, fácil de aplicar en el campo y con
rápidos resultados. Por tanto, en el
siguiente capítulo 4 se desarrollaron
diferentes tipos de metodologías, basadas
en el hecho de que los peces cultivados
experimentan
diferentes
ambientes,
densidades y regímenes alimenticios, en
comparación con los peces salvajes.
Analizando el crecimiento se mostró que
los peces de las jaulas presentan valores
más elevados del índice talla-peso que los
peces salvajes para ambas especies.
Además, mediante técnicas morfométricas
se observaron diferencias en ciertas
regiones del cráneo y del cuerpo que
permiten discernir entre individuos salvajes
ABSTRACT / RESÚMEN
tools nor experience is required. In
addition, the resulting differences in fin
damaging found on sea bream might
suggest the use of fin erosion as a potential
indicator to identify recent escaped sea
bream in the field after an escape event,
although fin recovery time in this species is
unknown. Conversely, the lack of
significant differences on fin damaging
found on sea bass according to the origin
suggests that fin condition indices are not
suitable to be used as fish origin indicator,
but could be useful as fish welfare indicator
within farmed stocks, improving the
knowledge of handling, stock densities and
open-sea cage environment conditions.
On the basis of the results obtained in
chapter 5, a total of 60 studies were
reviewed, evauating the validity and
applicability of different techniques applied
to discriminate farmed from wild fish for
sea bream and sea bass. Among these
techniques it can be found: genetic
differences, chemical characteristics (i.e.
fatty acid compositions, trace elements,
pollutants, stable isotopes), morphology
and organoleptic characteristics among
others, including those seen in previous
chapter 4. Many of these studies dealt with
food science and product quality, rather
than tracing escapees. A wide range of
identification
tools
are
useful
in
determining the correct origin of captures
and proper labelling of marketed fish.
The most common technique used
differences in the lipid and fatty acid
composition of fish. External appearance
and morphometry are useful for rapid
assessments and can be achieved with high
accuracy and little cost, especially for sea
bream. This makes these methods suitable
for detecting large and recent escape events
and for ensuring wild and farmed fish is
separated in the marketplace. Techniques
using differences in chemical or genetic
composition
are
more
useful
for
environmental monitoring, as they have
higher accuracy and can detect escapees
long after the escape incident. For instance,
they might be used to identify escaped
individuals within fisheries captures, which
would help to assess their contribution on
wild populations. Regulatory bodies should
legislate
protocols
which
describe
y cultivados en las dos especies.
Conjuntamente, el análisis de las escamas y
del perfil de los otolitos también permite
discriminar entre salvajes y cultivados con
alta precisión. De hecho, el análisis de las
características de las escamas es el método
más sencillo y rápido para identificar
escapados, ya que no se requiere
instrumentación específica ni elevado
conocimiento. Por último, las diferencias
encontradas en la condición de las aletas en
dorada sugieren el uso del índice de
erosión como un potencial indicador sólo
para identificar escapados recientes en el
campo tras un escape, ya que se desconoce
el tiempo de regeneración de las aletas para
esta especie. Por el contrario, no se
encontraron diferencias en la condición de
las aletas de lubina, por lo que parece no ser
adecuado como indicador del origen salvaje
o cultivado en esta especie. En cambio,
podría ser útil como indicador de bienestar
de los peces en las piscifactorías, para
mejorar el conocimiento sobre el manejo de
los peces, densidad en las jaulas y las
condiciones de las instalaciones en mar
abierto.
En base a los resultados obtenidos en el
capítulo 5, se revisaron un total de 60
trabajos evaluándose la aplicabilidad y
validez de diferentes técnicas para
distinguir, específicamente en dorada y
lubina, entre individuos cultivados y
salvajes. Entre estas técnicas se encuentran:
diferencias
genéticas,
características
químicas (p.ej. composición de ácidos
grasos, elementos traza, contaminantes,
isótopos
estables),
morfología
y
características organolépticas entre otras,
incluidas las vistas en el capítulo 4. La
mayoría de esos estudios se centran en
cuestiones gastronómicas y calidad del
producto, más que en el monitoreo de los
escapes. No obstante, se hallaron un amplio
rango de herramientas de identificación
útiles para determinar el origen de las
capturas y para ser aplicados en el correcto
etiquetaje del pescado en los mercados.
Las técnicas más comunes se basan en
diferencias en los lípidos y en la
composición de ácidos grasos del pez. La
apariencia externa y la morfometría son
útiles
para una evaluación rápida,
pudiendo alcanzar una alta fiabilidad
9
SEA BREAM AND SEA BASS ESCAPEES
the technique(s) that must be applied in
specific circumstances.
Finally, it was evidenced through this thesis
that there are significant interactions
between local coastal ecosystems and
escapes from aquaculture, though there is
still a high uncertainty about their
consequences.
However,
management
measures should be taken to eliminate or
minimize those risks, which ensures that
economic, social, and ecological benefits
from aquaculture are jointly achieved. It is
clear that with the expected growth of
marine aquaculture in the future, any
rational policy for addressing escapes must
focus first on prevention, but follow up
with strong management measures to
eliminate, or at least minimize, ecological
damage once escapes occur. These
measures must be cost effective, but the
benefits of protecting ecosystem integrity
should be accounted for as well.
10
y bajo costo, sobre todo en dorada. Esto
hace que estos métodos sean adecuados
para la detección de grandes escapes y
recientes, así como para asegurar la correcta
clasificación del pescado en el mercado
acorde con su origen. Las técnicas que usan
las diferencias químicas o genéticas son
más útiles en materia de gestión ambiental,
ya que poseen mayor precisión y pueden
detectar individuos escapados tiempo
después de escaparse. Por ejemplo, pueden
usarse para identificar los escapes en las
capturas de los pescadores, y así poder
evaluar su contribución en los stocks
salvajes. Los organismos reguladores
deberían legislar ciertos protocolos donde
describan la(s) técnica(s) que debe aplicarse
en circunstancias específicas.
Finalmente, mediante esta tesis se ha
comprobado que existe cierta interacción
entre los escapes y los ecosistemas costeros
locales,
aunque
existe
una
gran
incertidumbre sobre sus consecuencias. No
obstante, se deberían tomar medidas de
gestión para evitarlos o minimizarlos, lo
que asegurarían que se alcanzasen
beneficios económicos, sociales y ecológicos
de manera conjunta. Está claro que con el
esperado futuro crecimiento de la
acuicultura marina, cualquier política
racional para hacer frente a los escapes
debe centrarse en primer lugar en la
prevención, pero seguido de unas medidas
de gestión fuertes para eliminar, o al menos
minimizar, los daños ecológicos una vez
ocurra el escape. Estas medidas deben ser
rentables, pero los beneficios de proteger la
integridad del ecosistema deben tenerse
también en cuenta.
CHAPTER 1
1. INTRODUCTION
1.1. Gilthead sea bream
1.1.1. Systematic, biology and ecology
Class: Osteichthia
Order: Perciforms
Family: Sparidae
Genera: Sparus
Sp: Sparus aurata L.
The gilthead sea bream, Sparus aurata (L.), is
a subtropical Sparidae that inhabits
seagrass beds and sandy bottoms as well as
the surf zone, commonly to depths of about
30 m, but adults may occur at 150 m depth.
It occurs naturally in the Mediterranean
and the Black Sea (rare), and in the Eastern
Atlantic, from the British Isles, Strait of
Gibraltar to Cape Verde and around the
Canary Islands. It is reported as a sedentary
fish, though migrations are likely to occur
on the Eastern Atlantic coast, from Spain to
British Isles. It occurs either solitary or in
small aggregations. It is an euryaline
species and moves in early spring towards
protected coastal waters in search for
abundant food and milder temperatures
(trophic migration). In late autumn it
returns to the open sea for breeding
purposes, being very sensitive to low
temperatures (lower lethal limit is 2°C). It is
mainly carnivorous (shellfish, including
mussels
and
oysters),
accessorily
herbivorous (Froese and Pauly 2006). The
sea bream is a protandrous hermaphrodite:
it is a functional male in the first two years
and at over 30 cm in length becomes
female.
During the male phase, the
bisexual gonad has functional testicular,
with asynchronous spermatogenesis, and
non-functional ovarian areas.
Figure 1.1. Gilthead sea bream Sparus aurata
Ovarian development is also asynchronous,
and females are batch spawners that can lay
20000-80000 eggs per day for a period of up
to 3 months. In the Mediterranean, they
reproduce between October and December
(Froese and Pauly 2006).
Gilthead sea bream is a highly appreciate
target species in the Mediterranean
countries, regularly present on the fish
markets, which is captured with traditional
and sporting equipment, and sometimes
with semi-professional systems (Spain,
Sicily, Egypt and Cyprus); trawl nets,
bottom set long-line and hand-line are
commonly used. The world capture
production of gilthead sea bream is quite
constant throughout the years, fluctuating
from 5000 to 8000 t y-1 (total world capture
was 7.889 t in 2009). However, the cultured
sea bream increases, being around the 95%
of total production (Figure 1.2a). Similar
situation occurs in Spain, where fishery
captures of sea bream keep constant and
reached 1151 t in 2009, less than 5% of
Spanish aquaculture production (Figure
1.2b)(APROMAR 2011).
Figure 1.2. Aquaculture and fisheries evolution of sea bream from 1981 to 2009. A: world production; B:
Spanish production (Data from FAO and FEAP, in APROMAR 2011).
13
SEA BREAM AND SEA BASS ESCAPEES
1.1.2. Sea bream farming industry
The gilthead sea bream has traditionally
been cultured in Mediterranean coastal
lagoons and brackish/salt water ponds,
especially in Italy and Egypt. These
extensive fish rearing systems acted as like
natural fish traps, taking advantage of the
natural trophic migration of juveniles from
the sea (Sola et al. 2007). Restocking was
usually performed with wild fry and
juveniles,
collected
by
specialised
fishermen. By the late 1970s, the reduced
availability of wild fry and the increasing
demand from intensive farms enhanced the
development
of
induced
spawning
techniques, establishing by the end of the
1980s a production scheme based on a
reliable and programmed quantity of fry
(Sola et al. 2007).
At present, gilthead sea bream is cultured
in 19 different countries, and most
production of gilthead sea bream is from
intensive farming in open-sea cages or
inland tanks. However, extensive farming
still remains a traditional activity in some
regions, but with a very low impact on the
market. In the Mediterranean the main sea
bream producers are Greece, with
approximately 72000 t (51.5% of the total
production), Turkey with 21000 t (15%) and
Spain with 20360 t (14.6%) (Figure 1.3).
However, there are main other European
and Mediterranean countries that grow sea
bream, such as Italy, France, Cyprus,
Portugal, Croatia, Malta, Tunisia and
Morocco (Figure 1.3). Despite of the great
and fast growth of sea bream farming in the
world during the last decades, it has
suffered a bit decrease the last 2-3 years.
According to FEAP statistics, the total
production of gilthead sea bream in 2010
was 139925 t for European and
Mediterranean
countries
(APROMAR
2011). This number is a 16.6% lesser than
previous year (2009: 167000 t), which it was
also reduced a 6.5% respect to 2008 (Figure
3.2). Aquaculture sea bream production in
Spain presents a similar pattern. In 2010,
the production reached 20360 t, a 14.1%
lesser than in 2009 (23690 t), and also lesser
than in 2008. Analysing specifically the
Spanish areas, the Valencian Community is
ahead in the Spanish sea bream production
(37% of the total), followed by Murcia
(29%), Canary Islands (15%), Andalusia
(12%) and Catalonia (8%) (Figure 1.4).
Andalusia
11.6%
Valencian
37.2%
Canary I.
14.8%
Catalonia
7.7%
Murcia
28.7%
Figure 1.4. Percentage distribution of sea bream
production in Spanish areas (APROMAR 2011).
Figure 1.3. Evolution of sea bream farming production in European and Mediterranean countries from
1985 to 2010 (Data from FAO and FEAP, in APROMAR 2011).
14
CHAPTER 1
1.2. European sea bass
1.2.1. Systematic, biology and ecology
Class: Osteichthia
Order: Perciforms
Family: Moronidae
Genera: Dicentrarchus
Sp: Dicentrarchus labrax L.
The European (or common) sea bass,
Dicentrarchus labrax L., is a demersal
Moronidae that inhabit coastal waters
down to about 100 meters depth, but more
common in shallow waters (Lloris 2002).
They occur in coastal waters of the Atlantic
Ocean from South of Norway (60°N) to
Western Sahara (30°N) and throughout the
Mediterranean Sea and the Black Sea. They
are found on various kinds of bottoms on
marine coastal waters, estuaries, lagoons
and occasionally rivers. Young fish form
school, but adults appear to be less
gregarious. Juveniles feed chiefly on
invertebrate (shrimps and molluscs), taking
increasingly more fish with age since adults
are piscivorous. European sea bass is a
gonochoristic species. Spawning takes place
in winter in the Mediterranean Sea
(December to March) and in spring in the
Atlantic Ocean (up to June). Eggs and
larvae have a great dispersal during the 3
first months of life and adults migrate over
several hundreds of kilometres (Froese and
Pauly 2006).
Figure 1.5. European sea bass Dicentrarchus
labrax
It is a fish with high commercial interest for
both professional and recreational fisheries.
Indeed, there is a specific sea bass fishery in
the North Eastern Atlantic, considered a
well-managed and sustainable activity.
Captures fisheries production in the
Mediterranean Sea and Atlantic Ocean
remain constant throughout the years, with
a production between 8000 and 12000 t y-1
(total world capture was 11933 t in 2009)
(APROMAR 2011).
However, aquaculture production has
increased in the last decades and cultured
sea bass production at present reaches the
90% of total sea bass production (Figure
1.6a). Similar situation is found in Spain,
where fishery captures of sea bream keep
constant and reached 638 t in 2009, less than
5% of Spanish aquaculture production
(Figure 1.6b)(APROMAR 2011).
Figure 1.6. Aquaculture and fisheries evolution of sea bass from 1981 to 2009. A: world production; B:
Spanish production (Data from FAO and FEAP, in APROMAR 2011).
15
SEA BREAM AND SEA BASS ESCAPEES
1.2.2. Sea bass farming industry
European sea bass is currently achieved
intensively mostly in open-sea cages (10 to
20 kg/m3) and in concrete raceways (30 to
80 kg/m3 in France, Italy and Spain), but it
is also cultured extensively in ponds (< 2
kg/m3 in Portugal, Greece, Egypt) or in
closed systems. Sea bass farming has been
in progress since the mid-1980s when the
mastering of early survival until weaning
(from 0 - 10% to 35 - 65%) was achieved
with better management practices. The fry
quality variability remains one of the main
issues. Other important issues are related to
the species slow growth, its susceptibility to
viral diseases in warm waters and to its
poor conversion efficiency (>1.6 in large
size fish). Some of these critical aspects can
be linked to the fact that in farming
conditions there is an excess of males (70 to
95%) that present a precocious sexual
maturation (<100 g) and a slower growth.
Nowadays, sea bass farming production in
the world reached 118931 t in 2010
(APROMAR 2011), similar values to those
reached in 2009, but a 6.6% less than sea
bass production in 2008. Similarly to sea
bream production, the main sea bass
producer countries are Greece (47000 t y-1;
39,6% of total production), Turkey (35.000 t
y-1; 29,5%) and Spain (12.495 t y-1; 10,5%).
But also it is cultured in other European
and Mediterranean countries such as Italy,
France, Croatia, Portugal, Cyprus, Tunisia,
Egypt, United Arab Emirates, Libya, Malta,
Bosnian, Morocco, Slovenia, Germany and
Algeria (Figure 1.7). In case of Spain, total
sea bass production was 12495 t in 2010, a
9.7% less than in 2009. Regarding the
different Spanish areas, the Canary Islands
are the main sea bass producer (30%),
followed by Andalusia (29%), Murcia
(19%), Valencian Community (19%) and
Catalonia (2%) (Figure 1.8) (APROMAR
2011).
Murcia
19.2%
Valencian
19.1%
Catalonia
2%
Canary I
30.4%
Andalusia
29.3%
Figure 1.8. Percentage distribution of sea bass
production in Spanish areas (APROMAR 2011).
Figure 1.7. Evolution of sea bass farming production in European and Mediterranean countries from 1985
to 2010 (Data from FAO and FEAP, in APROMAR 2011).
16
CHAPTER 1
1.3. Escapes of farmed fish from netpens
1.11), or spills through handling of fish is
difficult to determine (Dempster et al. 2007).
1.3.1. What are escapes?
Escapes of fish from sea-cage aquaculture
have typically been thought of as referring
to juvenile and adult fish. “Fish escape” is
defined as the ability of a single or a group
of fish to get out of the net-pen facilities.
Such escapes have been reported for almost
all species presently cultured around the
world, including Atlantic salmon, Atlantic
cod, rainbow trout, Arctic charr, halibut,
sea bream, sea bass, meagre and kingfish
(e.g. Soto et al. 2001; Gillanders and Joyce
2005; Moe et al. 2007; Thorstad et al. 2008;
Toledo-Guedes et al. 2009).
Figure 1.9. Gilthead sea bream inside the cage
looking outside through the net.
Recently, a second form of escape has come
into focus, involving the escape of viable,
fertilized eggs spawned by farmed
individuals from sea-cage facilities, or so
called “escape through spawning” (Jørstad
et al. 2008). This phenomenon has forced a
redefinition of the term ‘escapes from
aquaculture’ to include the escapement of
fertilized eggs into the wider marine
environment.
Figure 1.10. Broken cage due to a storm. (Photo:
Ø. Jensen).
A recent study within the European project
“Prevent-Escape”
(7th
European
Framework, num. 226885) reported the
escape causes from questionnaires in 6
European countries (Ireland, Scotland,
Norway, Spain, Greece, and Malta).
Regarding Mediterranean countries, they
reported that the main causes of escape
incidents for sea bream and sea bass were
due to either biological (51.5%; e.g. net
bitting, predator attack) or structural
failures (39.4%; e.g. cage break, mooring
failure, mechanical net damage), rather
than operational failures (6%; e.g.
harvesting, grading, transport), being
higher the number of incidents in sea
bream than in sea bass (Jensen et al. in
preparation).
1.3.2. Causes of escapes in the
Mediterranean farms
It is well known that reared individuals
escape from farm facilities, due to technical
and operational failures, but the proportion
of escapes that are due to storms (Fig. 1.10),
holes in the netting caused by predators or
farmed individuals within the cage (Fig.
Figure 1.11. A hole in a sea bream net-pen.
(Photo: Oceanographica)
Within the causes that provoke structural
failures, storms are the most important
cause, but also inappropriate moorings and
cages could lead to escape incidents (Figure
17
SEA BREAM AND SEA BASS ESCAPEES
1.12). In addition, within the causes that
could damage the net, net bitting by farmed
fish are the most common, followed by
holes made by predators or chafes/snags
(Figure 1.13).
the coast of Italy (Díaz-López and BernalShirai 2007), with some deaths as a
consequence
of
accidental
net
entanglements. Monk seals (Monachus
monachus) have attacked fish at several
marine fish farms in the Turkish Aegean
Sea resulting in damage to both the net
cages and fish, which escaped as a result of
the attacks (Güçlüsoy and Savas 2003).
Figure 1.12. Percentage of the main causes that
provoke structural failures.
Figure 1.14. Bluefish Pomatomus saltatrix stuck in
a net hole. (Photo: P. Sanchez-Jerez)
1.4. Problematic of escapees
Figure 1.13. Percentages of the main causes for
net damaging.
Indeed, cultured sea bream have shown a
propensity to bite their surrounding nets,
focusing on visual imperfections, whether it
is fouling on the net, attachment areas,
repairs, or worn and loose threads. Sea
bass, although not so prone to net biting,
seems much more opportunistic about
escaping through openings in the net.
However, both pre-escape nibbling and
opportunistic behaviours increase the
probability of losses from cages.
In the Mediterranean Sea, predatory
interactions with aquaculture by birds,
finfish and marine mammals occur with
frequency (Sanchez-Jerez et al. 2008).
Predators such as bluefish (Pomatomus
saltatrix ) aggregates around sea-cage farms
in high abundances and enters into cages
(Fig. 1.14) to predate on the cultured fish
causing serious problems (Sanchez-Jerez et
al. 2008). Interactions with marine
mammals also occurs, but in a lesser extent.
For instance, bottlenose dolphins (Tursiops
truncatus) aggregate around farms along
18
Fish farming industry has risen during the
last decade, as it was seen, and derived
problems also began to arise concerning
escape events. Escape incidents in open-sea
cages produce important losses in farmed
fish biomass production within cages, and
therefore, losses in economical incomes. A
recent study within the European project
“Prevent-Escape” reported the extent and
costs of escape incidents in 6 European
countries (Ireland, Scotland, Norway,
Spain,
Greece,
and
Malta)
from
questionnaires
to
fish-farm
experts.
Regarding the Mediterranean fin-fish
industry, they reported that significant
numbers of farmed sea bream and sea bass
escape from the Mediterranean farms in
both small and large-scale incidents (>7
million fish in 67 incidents over the period
of the study). The cost of escapes at point of
first sale was very significant in terms of
lost income (€42.8 million p.a.), and such
implications of escapes have been shown to
have negative effects on the viability of
individual commercial concerns (Jackson et
al. in preparation).
CHAPTER 1
In addition, escapees can have detrimental
genetic
and
ecological
effects
on
populations of wild conspecifics and native
populations, and the present level of
escapees is regarded as a problem for the
future
sustainability
of
sea-cage
aquaculture (Naylor et al. 2005). A single
sea-cage may hold 100s of thousands of
cultured fish, meaning that sites with
multiple cages may contain more than 1
million fish. Due to the large numerical
imbalances of caged compared to wild
populations, escapement raises important
concerns about ecological and genetic
impacts. Evidence of environmental effects
on wild populations is largely limited to
Atlantic salmon, as these interactions have
been intensively studied, with more limited
information for Atlantic cod. Concerns
about these potential environmental risks in
the Mediterranean fish farming are
nowadays
arising,
but
knowledge
regarding how escapes might affect
ecosystems is limited.
1.4.1. Genetic interactions with wild
populations
The intensification of fish culture practices
has increased the need to study genetic
structure in cultured and wild fish stocks,
and to face related problems. Farmed
gilthead sea bream and European sea bass
species
are
genetically
manipulated
through breeding regimes and owning to
domestication
attain
commercially
desirable attributes such as high growth
rates, disease resistance, altered aggression,
adaptation to high stocking densities
(Thorland et al. 2006; Dupont-Nivet et al.
2008; Antonello et al. 2009; Navarro et al.
2009; Grigorakis and Rigos 2011). However,
the main purpose was to produce fish and
little attention was given to eventual
impacts on the genetic integrity of the
exploited stocks (Miggiano et al. 2005).
The possible genetic interactions between
escaped fish and native (initially) fish
populations are summarized in Figure 1.15
(modified from Youngson et al. 2001). Time
(box 1) has an effect, direct or indirect, on
the variables described in all the other
boxes and modulates progression through
the flow chart. On the left, the aquaculture
environment and the genetic condition of
aquaculture fish (boxes 2 and 3) combine to
determine their character at escape (box 4).
On the right of the chart, the character of
indigenous fish (box 8) is determined in a
similar way. After introduction takes place,
the character and the abundance of the
introduced and indigenous fish (boxes 5
and 9) interact to determine the resultant
abundance of both groups in the mixed
population (boxes 10-12). The same factors
determine relative abundance (box 13).
Both relative and absolute abundance are
determinants of genetic diversity which
may be measured in a number of ways (box
14). After interaction has occurred, the
qualities of the natural environment (box 6),
and the qualities of the indigenous fish (box
7) are reset by feedback effects. In the first
case, feedback is direct. In the latter case,
potential feedback effects are modulated by
reproductive fitness - the relative abilities of
competing escaped and indigenous fish to
contribute to the next generation of
progeny. Finally, time (box 1) resets the
value of boxes 7 and 8 on generational
intervals, according to the outcome of prior
interactions
and
according
to the
subsequent inputs (continuous or sporadic)
from boxes 4 and 5.
Thus, the potential dangers from breeding
of Mediterranean escaped farmed fish with
native wild populations can be summarized
in: a) alteration of natural genetic
architecture resulting from the transfer of
native genotypes among differentiated wild
populations because of the use of non-local
aquaculture stock; b) introduction to wild
populations of novel or previously
uncommon
genotypes
produced by
deliberate or inadvertent selection for
performance traits related to aquaculture; c)
weakening of native populations of wild
fish through the exclusion of native fish by
competing
aquaculture
fish
that
subsequently
demonstrate
low
reproductive fitness (Youngson et al. 2001).
This is particularly true when the wild
population is already at dangerously low
abundance
in
a
certain
region.
19
Native Fish
Escaped Fish
SEA BREAM AND SEA BASS ESCAPEES
Figure 1.15. Generalized flow chart for genetic interactions between escapees and wild populations
(modified from Youngson et al. 2001).
Ferguson et al. (2007) reported that
hybridization of farmed salmon with wild
conspecifics has the potential to genetically
alter the native populations, reduce local
adaptation and negatively affect population
viability and character. In fact, successful
spawning of escaped farmed salmon in
rivers both within and outside their native
range has been widely documented (see
review by Weir and Grant 2005). Several
studies have shown that escaped farmed
salmon breeding in the wild have changed
the
genetic
composition
of
wild
populations (e.g. Clifford et al. 1998a,b;
Skaala et al. 2004).
Figure 1.16. Pair of Atlantic salmon paired off
during spawning season (Photo: Paul Nicklen).
20
However, large-scale field experiments
undertaken in Norway and Ireland showed
highly reduced survival and lifetime
success of farm and hybrid salmon
compared to wild salmon (McGinnity et al.
1997, 2003; Fleming et al. 2000).
In the case of Atlantic cod, little direct
evidence exists for negative interactions of
escaped and wild Atlantic cod juveniles or
adults, despite predictions that negative
consequences will result (Bekkevold et al.
2006). At present, cod farming is a
relatively new industry, thus if negative
consequences exist they may not have had
sufficient time to manifest and/or be
detected (Jensen et al. 2010). Telemetry
studies of simulated cod escapes have
indicated that escapees, mix with wild
populations in fjord environments and can
move to spawning grounds in the
spawning season (Uglem et al. 2008, 2010).
Behavioral studies have further indicated
that escaped farmed cod are likely to
hybridise with wild cod (Meager et al.
2009).
However, farmed cod may have limited
reproductive success in sperm competition
with wild cod, which lowers the risk of
genetic
introgression
from escapees
CHAPTER 2
(Skjæraasen et al. 2009). In addition, it is
believed that farmed cod has the potential
to spawn in sea-cages before they are
slaughtered, and there is considerable
potential for cod eggs to entrained in the
vicinity native spawning areas, and
resultant “escaped” larvae could experience
favorable conditions for survival and lead
to serious ecological and genetic effects in
wild populations (for a review see Jensen et
al. 2010).
In the case of sea bream, there is a high
genetic
variability
within
the
Mediterranean Sea. Some studies on wild
gilthead sea bream evidenced a slight
degree of genetic differentiation on
Mediterranean populations. De Innocentis
et al. (2002) identified a genetic
differentiation between Atlantic and
Mediterranean wild populations, and
within the Mediterranean itself. However,
other studies suggested that if some genetic
differences exist, they were not apparently
associated
with
geographic
or
oceanographic factors (Youngson et al. 2001;
Palma et al. 2001; Alarcón et al. 2004; BenSlimen et al. 2004; De Innocentiis et al. 2004;
Rossi et al. 2006).
Thus, the migration of individuals and
consequent crossing between neighboring
populations seems to be the main reason
for the slight genetic differentiation found
(Palma et al. 2001).
Figure 1.17. Gilthead sea bream in natural
coastal habitats (Photo: M. Vazquez-Luis).
On the other hand, there is evidence that
production of both male and female
gametes of sea bream occurs within cages
under the present industrial pattern, and
spawning within sea-cages is suspected to
have led to greater recruitment to wild sea
bream stocks (Dimitriou et al. 2007).
Therefore, it is likely that farmed sea bream
and escapees could have influenced in such
genetic variability in the Mediterranean
Sea, since the use of non-locality
broodstocks is widely extent in the
Mediterranean countries (De Innocentiis et
al. 2005).
In the case of European sea bass, wild
population genetic differentiation is well
studied, and three genetically distinct zones
were identified: the Atlantic Ocean (the
Alboran Sea included), the western
Mediterranean
and
the
eastern
Mediterranean (i.e. Patarnello et al. 1993,
Allegrucci et al. 1997; García de León et al.
1997; Castilho and McAndrew 1998; Sola et
al. 1998; Bahri-Sfar et al. 2000, 2005; Castilho
and Ciftci 2005; Ergüden and Turan 2005;
Katsares et al. 2005; Lemaire et al. 2005).
Some studies detected cases (mostly
Eastern Mediterranean) where population
samples did not cluster according to their
geographic origin, but with western
Mediterranean samples (Patarnello et al.
1993, Allegrucci et al. 1997). This is not
surprising, since many hatcheries around
the Mediterranean used broodstock, eggs or
fingerlings originating from the western
basin, when sea bass aquaculture began
(Youngson et al. 2001; Haffray et al. 2007).
Therefore, it is evident that some wild
Mediterranean stocks may have already
been affected by escapees (Bahri-Sfar et al.,
2005). In fact, the large differences between
natural spawning and hatchery conditions,
i.e., the practice of artificial selection, the
hybridisation of different stocks and
strains, the transfer of broodstocks, eggs,
larvae and fry over large distances, involve
the risk of inbreeding, or causing artificial
gene flow, which could induce a
biodiversity
decline
or
outbreeding
depression (Sola et al. 1998). However, there
is a lack of studies about interbreeding
evidences through both fish and eggs
escapes on Mediterranean species, so
further research are still necessary to
improve the knowledge of genetic
interactions of escapes on Mediterranean
wild populations.
21
SEA BREAM AND SEA BASS ESCAPEES
1.4.2. Ecological interactions with wild
stocks
Other negative environmental impacts of
Mediterranean escapees arise from much
more serious and direct biotic interactions,
such an increased competition and
predation on wild populations, resulting in
serious alterations on native ecosystems.
Cultured fish are used to eat food pellets in
sea-cages, but once they escape to the wild
they must switch on natural prey in natural
habitats to survive, where could compete
with native wild fish populations.
Moreover, escaped fish could predate
locally on some species, and such
population could be at serious risk if
predation pressure occurs in high densities
on specific life-stage (larvae, juveniles or
adults) or important seasons (e.g. spawning
or recruitment). In addition, the presence of
escapees in spawning areas might lead to
competition for mate with their wild
conspecifics,
either
interbreeding
is
successful or not.
Some studies on Atlantic salmon reported
that escapees caught on marine feeding
grounds had similar condition factors than
wild conspecifics, suggesting that escaped
salmon are able to adapt effectively to the
wild environment, since they seem to
consume similar food resources as wild
salmon (Hislop and Webb 1992; Jacobsen
and Hansen 2001). Some indications of the
latter were given in a Chilean study where
escaped coho salmon Oncorhynchus kisutch
and rainbow trout O. mykiss appeared to
switch readily to natural prey diets;
however, escaped Atlantic salmon had the
highest level of stomach emptiness and the
highest occurrence of pellets from fish
farms in their stomachs (Soto et al. 2001). In
accordance with this, high recaptures of
tagged adult salmon have been reported in
the vicinity of release sites for the first
months after release (Hansen 2006, Olsen
and Skilbrei 2010; Skilbrei and Jørgensen
2010, Skilbrei et al. 2010). Hansen (2006)
suggested that escaped fish may also have a
problem switching to live prey, possibly
depending on their age, life stage, time
spent in cages and species. Jonsson and
Jonsson
(2006)
investigated
feeding
competition between wild and farmed
salmon in coastal areas and in the ocean,
22
suggesting that it is not likely that
availability of food in the ocean is a
limitation for wild Atlantic salmon
production, and that feeding competition
with escaped farmed salmon limits food
availability for wild salmon. However, food
competition is not only limited to wild
conspecifics but also to other wild fish
species which consume the same food
resources. Jonsson and Jonsson (2006)
suggest that competitive interactions (food
or habitat) may mostly occur in areas with
high densities of cultured fish. Similar
interaction has been suggested for Atlantic
cod since escapees are able to move among
farms and to coastal areas following escape,
surviving for long periods in the wild
(Uglem et al. 2008, 2010), although direct
evidence for competition effects is at
present lacking.
Figure 1.18. Atlantic cod inside the rearing netpen.
Similarly, limited information exists on sea
bream and sea bass farming. Intentional
releases of cultured sea bream for stock
enhancement have been reported from the
southern Atlantic coast of Spain, and in the
Bay of Cadiz (Sánchez-Lamadrid 2002,
2004). Released fish moved less than 10 km
from the release point. Good growth rates
and condition indices indicate that the
released fish adapted to life in the wild,
suggesting that populations of wild fish
could also be altered by released fish. For
example, there is correlative evidence of a
substantial increase in wild populations of
sea bream after fish farming began in the
Messolonghi lagoon, Greece (Dimitriou et
al. 2007). Dempster et al. (2002) found very
few sea bream near sea-cages in which they
were being reared, which suggests either
CHAPTER 2
low levels of escape or that escapees move
rapidly away from the farms to other
habitats. Based on the ecology of sea bream
and the location of most fish farms in areas
close to wild sea bream habitats, it is
probable that escapees would mix with
their wild conspecifics. The only published
long-term data available on escapes of sea
bass indicate that when sea bass cultured
from western Mediterranean populations
escaped in the eastern Mediterranean, they
established
and
maintained
distinct
populations with the local population
(Bahri-Sfar et al. 2005).
Figure 1.19. European sea bass in Mediterranean
shallow coastal waters.
1.4.3. Risk of non-indigenous stock
establishment
Even more risk exists if escapes of farmed
fish occur in small locations or in areas
outside their natural distribution may be
particularly problematic, constituting an
introduction of a non-native species or
“exotic” species. Similarly to previous
sections, risks associated with non-native
species introductions include degradation
of the host environment, disruption of the
host community, genetic degradation of the
host stock, introduction of diseases, and
socioeconomic effects (Welcome 1988). The
introduction of non-native species is a
global concern with frequently more severe
ecological impacts than native species,
though often unpredictable. In fact,
numerous studies into the impact of alien
fish species on aquatic natural assemblages
have been carried out, although mainly for
fresh-water fish or salmonids (e.g.
Cadwallader 1996; Fleming et al. 2000;
Buschmann 2001; McGinnity et al. 2003;
Dextrase and Mandrak 2006; Townsend
and Simon 2006; CIESM 2007). They
reported that alien invasive species were a
primary factor of extinction or drastic
reduction of certain populations due to
competition, loss of genetic diversity,
predation or pathogen transfer processes.
The success of an invasive species is largely
determined by fluctuating biotic and abiotic
conditions that determine the window of
opportunity for establishment (Naylor et al.
2005). The probability of invasion success
increases with repeated introduction and is
frequently preceded by numerous failures
(Naylor et al. 2005). Of 3141 introductions of
aquatic species recorded by the Food and
Agriculture Organization of the United
Nations in 1998, 39% were a result of
aquaculture (FAO 1999). Thus, the near
inevitability of escapes from aquaculture
facilities has led to the recommendation
that
introductions
of
species
for
aquaculture should be considered an
introduction to the wild, even if the facility
is considered a closed system (FAO 1995).
However, some authors (Carlton 1996;
Casal 2006) point out the lack of
information and the need for experimental
studies that will be essential to keep up
with the present-day flow of establishments
and invasions of introduced marine species,
and their impact on marine ecosystems.
In the case of sea bream and sea bass
farming industry, although the most
important proportion of open-sea farm
facilities are sited within the Mediterranean
Basin and some areas of European Atlantic
coast, where corresponding wild species
are geographically well distributed, this
industry has been developed in other
regions where this wild species are not
found in the marine environment. Punctual
escape events and introductions of nonnative sea bream and sea bass escapees in
the marine environment have been
recorded in different areas, such as Madeira
island (Alves and Alves 2002), Red Sea
(Krupp and Schneider 1989; FAO 1997;
Khalaf 2005; Bartley 2006), Persian, Arabian
and Omán Gulfs (FAO 1997; Bartley 2006),
and Gulf of California (Balart et al. 2009).
Indeed, the best reported example of nonnative fish escapes can be found in the
Canary Islands, where many an unknown
23
SEA BREAM AND SEA BASS ESCAPEES
number of fish are escaping from cages
which could be affecting natural fish
assemblages. (González-Lorenzo et al. 2005;
Toledo-Guedes et al. 2009). Some evidence
points to the fact that both sea bass and sea
bream have been introduced to the central
and western islands of the Canary
archipelago through aquaculture. However,
small native populations are established on
eastern
islands
(Lanzarote
and
Fuerteventura) (Brito et al. 2002) which
possibly depend on larval dispersion
through upwelling filaments from African
coastal populations (Rodríguez et al. 1999;
Becognée et al. 2006). This spatial
distribution could mean that escaped
individuals either show little mobility and
site fidelity or present high mortality rates,
which in this case the population may
strongly depend on escaped individuals for
establishment (Toledo-Guedes et al. 2009).
increase the potential ecological effects
previously cited, affecting the whole fish
population dynamic and the ecosystem
heath.
On the other hand, it is noticeable the
raising development of new aquacultured
finfish species during last years. For
instance, the meagre (Argyrosomus regius),
that
are
recently
expanding
their
production
mainly
throughout
the
Mediterranean Basin and Canary Islands.
Although it is suggested that escapees of
this species could be considered as
“native”, the geographic distribution and
genetic fragmentation of this species
suggests that could be also considered
nowadays as “non-native” fish in some
regions (Haffray et al. 2012). Natural
meagre populations are specifically found
in
some
regions
of
the
eastern
Mediterranean and some areas of the
European and African Atlantic coast,
however, some punctual individual
captures were reported in western
Mediterranean
some
decades
ago.
Unpublished studies carried out in western
Mediterranean Sea on feral meagre
populations reported that they seemed to
be able not only to establish for long
periods in coastal natural habitats, but also
to feed on natural preys such as crustaceans
and finfish (Valero-Rodríguez 2012).
Figure 1.20. A shoal of escaped sea bass
swimming in coastal areas in Canary Islands.
(Photo: www.canariasactual.com)
González-Lorenzo et al. (2005) and ToledoGuedes et al. (2009) demonstrated a
persistence of sea bream and sea bass
escapees in coastal natural habitats, being
able
to
exploit
natural
resources,
overlapping with native fish diets. For
escaped sea bass, the negative ecological
interaction with native populations seemed
to be even higher than for sea bream, since
they could compete with local top
predators in shallow coastal areas (ToledoGuedes et al. 2009). Moreover, some sea
bass escaped individuals were found with
mature gonads, but also they suggested
that escaped sea bass could act as vectors of
new pathogens introduction in native
assemblages (Toledo-Guedes et al. 2009,
2012). Therefore, non-native escapees
24
Figure 1.21. Juvenile of feral meagre captured in
the Western Mediterranean Sea.
Moreover, some feral individuals were
found with mature female gonads.
However, re-stocking studies of this species
in Majorca Island suggested that they are
not able to reproduce in the wild (Grau,
pers. com.). Therefore, further studies are
highly needed also on new cultured
CHAPTER 2
species, which could be considered both
native and non-native fish in specific
regions, which will improve our knowledge
about their potential environmental effects
and the sustainable development of
forthcoming aquaculture.
1.4.4. Potential diseases and pathogens
transmission
Losses due to various pathogens are one of
the main factors that affect the
sustainability of any fish farming industry.
Some of them have either devastating
effects on fish production in terms of high
mortalities, or reduction in growth of the
fish as in the case of many parasitic
infections. The rapid expansion of farm
facilities in to new areas might help local
pathogens affect new cultured stocks, and
the new environmental conditions could
favour the growth and expansion of some
pathogens. Moreover, the intensification of
cultured fish might also increase the
pathogen concentration within cages and
enlarge their spreading (Murray 2009), and
escapees can act as vector of these
pathogens among farms (Uglem et al. 2008),
amplifying the disease spreading range.
Thus, the transmission of such pathogens in
aquaculture cages are suspected to be: a)
directly from previous infected fish from
hatcheries, b) through water current
dispersion from cages, c) through crosscontamination between farmed and wild
fish, and d) due to escapees, which could
act as vectors among other farming stocks
and wild populations when escape from net
pens.
The potential transmission of pathogens
through escapees has been widely studied
on salmonids (e.g. Ford and Myers 2008;
Jensen et al. 2010; Johansen et al. 2011). For
instance, Atlantic salmon escapees from
aquaculture in Norway have been
identified as reservoirs of sea lice in coastal
waters (Heuch and Mo 2001; Revie et al.
2009). Moreover, a case of accidental
introduction from Scotland to Norway of
furunculosus (a bacterial disease) was
reported in the 1990s due to a transfer of
stocks, as then believed to have been spread
from farmed to wild populations by
escapees (Naylor et al. 2005). In addition,
60000 salmon infected with infectious
salmon anaemia and 115000 salmon
infected with pancreas disease escaped
from farms in southern Norway in 2007, yet
whether these precipitated infections in
wild populations is unknown (Thorstad et
al. 2008). Regarding Atlantic cod, the
potential transmission of pathogens and
parasites from escapees to wild populations
has been suggested (Øines et al. 2006;
Uglem et al. 2008; Hansen et al. 2009), since
a high connectivity among farms and
nearby wild fish stocks through movements
of escapees exists, although direct evidence
for these effects is at present lacking.
Although aquaculture in the Mediterranean
countries is relatively young, some signs of
spreading of diseases and parasites have
been recorded, occasionally causing
considerable problems and mortalities to
the farmed stocks (for reviews see AlvarezPellitero 2004; Barja 2004; Toranzo 2004).
However, there is a lack of studies
regarding this potential risk of escapees.
Among the most important pathogens on
cultured sea bream and sea bass, it can be
found a large number of virus, bacteria and
different pathogens such as several
Myxozoa, monogeneans ectoparasites and
some isopoda parasites (for a review see
Raynard et al. 2007). Moreover, sea bream
and sea bass share many of these
pathogens, which improve the potential
cross-contamination between both species,
either farmed and wild stocks. The
horizontal and vertical transmissions of
some pathogens, as well as their speciespecificity, might increase such potential
risk of escapees to propagate diseases to
their conspecifics.
Furthermore, the existence of a wide
number of wild fish around farms (Figure
1.22) sharing the same pathogens than
farmed/escaped sea bream and sea bass,
increase the importance of escapees as
potential vectors of disease and pathogens
to wild stocks. It was demonstrated that
farm facilities and coastal habitats are
connected through farm-aggregated grey
mullets (Figure 1.23), suggesting the
possibility to act as vectors of disease
transmission among cages and wild
populations (Arechavala-Lopez et al. 2010).
However, direct diseases or pathogens
transmission has not been demonstrated
25
SEA BREAM AND SEA BASS ESCAPEES
between farmed and wild fish in the
Mediterranean,
and
only
suspected
transmission and sporadic isolations and
identifications of pathogens from farmed
and wild fish that live in the vicinity of the
Mediterranean fish facilities have been
made (Raynard et al. 2007).
Figure 1.23. Mugilids swimming
Mediterranean farming cages.
around
1.4.5. Influence on local fisheries and
consumers
Figure 1.22. Farm-aggregated wild
assemblage beneath Mediterranean cages.
fish
Therefore, the movement patterns of
escaped sea bream and sea bass in
Mediterranean sea-cages farming might
predispose them to act as vectors of disease
not only among farms but also among
adjacent wild fish populations in a larger
area, amplifying the range of infections and
their potential biological and economic
consequences on nearby farmed stocks and
target species for local fisheries. Moreover,
not only some pathogens might affect
human health, but also farmers use
antibiotics to combat some diseases. If
infected or antibiotic-treated escapees are
caught by local fishermen, it could lead to
serious problems for consumer’s health.
Therefore, there is a necessity to assess the
behaviour
and
movements
of
Mediterranean escapees around farm
facilities and nearby coastal waters, which
could help to improve the knowledge about
the spread of pathogens and diseases
through escapees and the range of their
potential risks.
26
Indirectly, escape-driven declines in wild
fish populations are more likely to affect
commercial
fishing
interests
and,
occasionally, the effects of escapes are only
evident through fisheries landings, which
could
be
reflected
into
economic
consequences in fisheries activity. Although
wild sea bream and sea bass captures in the
Mediterranean seem not to have been
increased at a global scale by increased
farming activity during last decades
(APROMAR 2011), escapes may have other
consequences at a regional scale: either a
detrimental impact on vulnerable target
fish populations, substituting for wild
catch; or supplementing wild captures with
the presence of both escapees and target
species within landings.
Although the economic consequences of
escapees on local fisheries can be regarded
as
quite
similar
among
different
Mediterranean regions in general terms, the
occurrence of both cited cases will highly
depend on several factors, which vary
among localities and seasons, such as: a) the
farm size and distance from fishing
grounds; b) the magnitude and periodicity
of escape incidents; c) the characteristics of
local fisheries (both professional and
recreational);
d)
the
environmental
characteristics of the locality, which will
depend on the survival and establishment
of escapees; and e) the health of wild fish
stocks and target populations in this region.
CHAPTER 2
Regarding this interaction from the
magnitude and periodicity of escapes
incidents, different scenarios could happen.
In the case of short-scale incidents (that
means a “leak” of escapees through holes
or operational failures independently of the
fish-size), the Mediterranean target stocks
might not be affected in a short-term and
some punctual escaped individuals might
appear within fisheries landings. If that
occurs, the captured escapee can be
mislabelled in some of the steps through
the market chain (from fishermen to final
fish market). Since they sell a farmed fish as
a native one, whose prizes usually are 4
times higher than same farmed species,
they
will
have
higher
incomes.
Consequently, the main affected of this
fraud are the consumers, who are paying a
higher prize for a lower fish quality.
Figure 1.24. One-day “miraculous” capture of
sea bream by local fishermen.
On the other hand, if massive or large-scale
escape incidents occur, the contribution of
escapees on fisheries captures will be high,
collapsing the fishing gears and decreasing
the captures of target species. In this case,
the total incomes for fishermen will be low,
due to both the low prizes for escaped
species and the low quantity of target
species for sale. However, the negative
economic consequences for fisheries will be
more or less severe depending on the
densities of the wild stock in this region,
apart from the capabilities of escapees to
move to local fishing grounds, compete for
natural resources and predate on target
species. However, if escaped farmed fish
are considered “non-native” in this region,
the negative ecological and economic
consequences could be more severe. From
the consumer’s point of view, escaped
farmed species could be cheaper; however,
interesting wild species for consumption
could be even more expensive due to its
scarcity. In addition, if more escape
incidents do not occur following a massive
escape, the latter situation might become
similar to the former, since the presence of
escaped fish within fisheries captures will
be decreased over time.
There are many studies about the influence
of escaped farmed salmon on professional
fisheries accounting for a substantial part of
the commercial salmon catches in Atlantic
and Pacific oceanic and fresh waters (e.g.
Hansen et al. 1987, 1993, 1999; Lund et al.
1991; Youngson et al. 1997; Crozier et al.
1998; Morton and Volpe 2002; Skilbrei and
Wennevik 2006). However, despite of the
evident potential environmental and
economic impacts of escapees, there is a
lack of studies about the contribution of
Mediterranean
escapees
in
fisheries
landings.
Dimitriou et al. (2007) recorded a mean
increase of about 80% of total gilthead sea
bream landings in recent years from the
fish trap fisheries of the MessolonghiEtoliko lagoon (Greece), suggesting an
influence of the rearing activities in the
area, through both reproduction in cages
and escape incidents. They reported a huge
increase in the number of young sea bream
and sea bass in the area, and therefore, a
decrease in the mean size of the specimens
from fisheries. This can be attributed to the
negative influence of stock density on
individual growth rates, suggesting the
existence
of
a
density-dependent
mechanism (Carver and Mallet 1990).
Furthermore,
these
changes
in
demographic features and the landings of
gilthead sea bream in the lagoons were
accompanied by a decrease in the total
income from the species sales (9.1%), and
the prices of the most remaining species
decreased substantially, resulting in
financial difficulties for the fishing
cooperatives (Dimitriou et al. 2007).
In agreement with this, a recent study
carried out in western Mediterranean
coastal waters suggested that sea bream
escapees contribute in great measure on
artisanal fisheries landings (Izquierdo-
27
SEA BREAM AND SEA BASS ESCAPEES
Gomez et al. unpublished data). However,
this increased catches of sea bream
represented an increase of total income for
this specie (about 5%), and total captures
and incomes from the rest of target species
were not affected. This could be explained
by either the high selectivity of the artisanal
fishing gears, or the low densities that overexploited wild sea bream populations
presented in this area. However, it must be
taken into account the long-term effects of
the potential fitness reduction of wild sea
bream
populations
and
ecological
interactions on fisheries stocks by escapees.
In addition, massive escape incidents were
not recorded during this study period,
which could have affected in great measure
on total captures and incomes in a shortterm. According to that, an increment from
1% up to 40% of total captures of sea bream
and sea bass were recorded following a
massive escape incident in Canary Islands
(Toledo-Guedes unpublished data). Since
they are considered non-native species in
this area, captures of escapees were an
income increase for local fisheries during
some months after the incident, but also the
abundant presence of escapees in shallow
waters increased the fishing effort of
recreational fishing along the coast.
Therefore, escapes could also increase
revenues for the recreational fishing
industry by providing new types of sport
fish, although these gains must be balanced
with the reduction in native fish catch
resulting from aforementioned ecological
impacts of escapes, since specific native fish
are also extremely important to the
recreational fishing industry in many
regions. Thus, further research are highly
necessary to improved our knowledge
about the long-term socio-economic
consequences of Mediterranean escapees on
farming related sectors, such as local
fisheries, retailers and consumers, which
are indirectly affected by the environmental
problems of escapees on wild populations.
28
1.5. Objetives
1.5.1. General objectives
The first goal of this study is to provide
valuable data regarding immediate and
long-term post-escape behaviour, dispersal
patterns and distribution of simulated
escapes of cultured sea bream and sea bass
from full-scale commercial farms. Secondly,
to develop simple, reliable and effective
methods of identifying farmed sea bream
and sea bass after escape. Finally, to
evaluate the knowledge adquired to
provide further implications for sustainable
aquaculture management, and therefore,
for minimisation of potential negative
ecosystem effects.
1.5.2. Specific objectives
Specifically, this is study is aimed at:
- providing behavioural information of
farmed escaped sea bream and sea bass,
through simulating small-scale escape
incidents of acoustically-tagged fish, tag
and recapture studies of larger numbers of
fish with external visible tags, and assessing
the feeding behaviour and habitat use of
recaptured tagged fish.
- developing practical methodologies for
reliable and effective identification of
escaped fish, through the evaluation of
different types of methodologies: analyses
of fish growth, pattern in scales, otoliths
shape,
external
appearance
and
morphological analyses;
- evaluating the existent techniques to
distinguish between wild and farmed sea
bream and sea bass in order to analyis their
applicability and suitability as tools for
management;
- discussing the need and potential for
developing and implementing various
mitigative measures for recapturing
escaped fish and to assess the potential
risks of fish escape in the marine
environment.
CHAPTER 2
2. POST-ESCAPE BEHAVIOUR OF FARMED SEA BREAM
2.1. Abstract
Escapes of cultured gilthead sea bream (Sparus aurata L.) have been recorded throughout the
Mediterranean Sea. In the current study we simulated escape incidents of sea bream tagged
with acoustic transmitters (N=38) or external tags (N=2191). Tagged individuals showed both a
high dispersion within the first 5 days after release and a high mortality rate (>60%) where the
fish appeared to be predated at the release farm. However, some individuals remained not only
at the release farm but also at the nearby farm facilities for long periods, surviving up to 4
weeks with a clear diurnal swimming depth behaviour related to farm activity. Local fisheries
contributed largely recapturing tagged individuals that disperse from farm facilities (7.25%),
being professional trammel-netters the major contributors (71.5%). Those recaptured
individuals were caught on usual fishing grounds and habitats where they wild conspecific live
(seagrass, sand or rocky bottoms), feeding on natural preys such as crustaceans and molluscs
after one week in the wildness. Therefore, our findings emphasize the potential consequences
that escapees might entail interacting with nearby cultured and wild stocks, and the importance
of local fisheries to reduce the potential effects of escape incidents on natural stocks.
.
2.2. Introduction
Escape of farmed fish from sea-cages is
considered
as
one
of
the
main
environmental
problems
caused
by
aquaculture and it is perceived as a threat
to natural biodiversity in marine waters.
Escaped fish may cause undesirable
ecological effects in native populations
through interbreeding, competition for food
or habitats, as well as transfer of pathogens
to wild fish or other farmed stocks (Fiske et
al. 2005; Dempster et al. 2007; Thorstad et al.
2008). Gilthead sea bream Sparus aurata L.
(Sparidae) is a marine species of great
economic importance for Mediterranean
aquaculture and fisheries (FAO 2011).
Sea bream escapees from sea cages have
been sporadically recorded (Dempster et al.
2002, 2005; Boyra et al. 2004; Tuya et al.
2005, 2006; Valle et al. 2007; FernandezJover et al. 2008), mainly as a result of
technical and operational failures in terms
of cage breakdown due to extreme weather,
holes caused by wear and tear of the
netting
and
operational
accidents
(Dempster et al. 2007). In general, largescale escapes due to cage breakdown are
more likely to be reported, as such damages
are easy to detect and the numbers of
escaped fish are high. However, escapes
through smaller holes in the netting are less
likely to be noticed and farmers may have
difficulties to estimate how many fish have
escaped before holes are discovered
(Dempster et al. 2007). Holes may also be
created by farmed fish actively biting in the
net or by continuous close interactions with
the net wall (Ås 2005; Moe et al. 2007), as it
has been also observed on sea bream cages
(pers. obs.). Predators (i.e. bluefish
Pomatomus saltatrix) are also known to bite
through cage netting to get at the fish inside
(Sanchez-Jerez et al. 2008).
Figure 2.1. Shoal of escaped sea bream beneath
farming cages in Canary Islands. (Photo:
Oceanographica)
Farmed fish experience non-natural high
densities within the cages, with an
abundance of food and typically an absence
of predators. This may affect the
development of behaviour and possibly
also entail artificial selection on traits that
adapt the farmed fish to a life in captivity
(Huntingford et al. 2006; Salvanes and
Braithwaite 2006). In turn this may also
31
SEA BREAM AND SEA BASS ESCAPEES
influence the fitness of escaped fish
compared to their wild conspecifics
(Huntingford et al. 2006; Salvanes and
Braithwaite
2006).
The
post-escape
behaviour of several other aquaculture fish
species, such as salmon (Salmo salar) and
cod (Gadus morhua), has been extensively
studied (Naylor et al. 2005; Jonsson and
Jonsson 2006; Moe et al. 2007; Thorstad et al.
2008; Uglem et al. 2008, 2010; Hansen et al.
2009; Skilbrei et al. 2009, 2010). However,
few corresponding studies have been
carried out for escaped fish from fish farms
in the Mediterranean.
In addition, farm-aggregated wild fish are
actively exploited by artisanal fisheries in
the Mediterranean (Akyol and Ertosluk
2010; Arechavala-Lopez et al. 2011a) and
escape incidents are often followed by
increased catches in the local fisheries. In
the current study we simulated escape
incidents with fish equipped with acoustic
transmitters or tagged with external tags
aiming: (i) to assess the dispersion and
survival of farmed sea bream after an
escape incident; (ii) to demonstrate
connectivity among farms and local fishing
areas through escaped sea bream
movements; (iii) to map the habitat use and
feeding habits of escapees; and (iv) to
evaluate to what extent escapees are
recaptured by local fisheries.
2.3. Material and Methods
2.3.1. Study Area
The study was carried out in a coastal bay
in the southeast of Spain (UTM: 30S
0710736 4219249) (Figure 2.2). In this bay,
there are four floating-cage fish farms
(Figure 2.2a) located 3 to 4 km offshore on
soft muddy bottoms at depths ranging from
23 to 30 m. Distances among farms vary
from 1 to 5 km. Farms F1, F4 and the farm
where all experimental releases were
carried out (F3-R) grow ca. 1200 t y-1 of
European sea bass (Dicentrarchus labrax)
and gilthead sea bream (Sparus aurata).
Farm F2 is an inactive farm whose floating
structures remain without fish and nets.
Artisanal fisheries usually work at a local
scale, i.e. near the coast and around farm
facilities, only moving some kms away
from their local harbours. Eleven artisanal
vessels operate in the study area from the
port of Guardamar del Segura, around 30
artisanal vessels from Santa Pola, 4 artisanal
vessels from Tabarca and 9 vessels from
Torrevieja; most of them trammel-netters
and some long-liners boats. Furthermore, a
marine protected area with special fishing
restrictions is located around Tabarca
Island (Forcada et al. 2009)(Figure 2.2).
Figure 2.2. Map of Guardamar Bay, south-eastern Spain, and the locations of the farms facilities
(rectangles). Pushpin: receiver location. Externally tagged fish were released at farm F3-R (black pushpin)
32
CHAPTER 2
2.3.2. Tracking and tagging procedure
Immediate post-escape dispersion and
survival of sea bream from cages were
studied
by
tagging
with
acoustic
transmitters 38 gilthead sea bream (Sparus
aurata) from the cage where they were
released
(F3-R,
Figure
2.2).
Their
spatiotemporal distribution was monitoring
using an array of 10 automatic receivers
(Vemco Ltd., model VR2; Figure 2.3)
positioned at different farms and adjacent
areas throughout the Guardamar Bay (Fig.
2.2b). One receiver was positioned at the
farm where the experimental release was
carried out (F3-R), two more at the
operational farms (F1, F4) and one receiver
was deployed at the inactive farm (F2).
Finally, the other 6 receivers (A, B, C, D, E,
G) were deployed forming a circle with the
other 2 receivers (F2, F4) around the farm
where the tagged fish were released (F3-R;
Fig. 2.2b).
Figure 2.3. Deployment of a receiver VR2
anchored to a bordering buoy at farms.
The depth at the receiver sites varied
between 25 and 35 m. The receivers were
attached
to
anchored
ropes
at
approximately 4 meters distance to the
bottom, except for the receivers deployed at
the fish farms, which were suspended 12 m
below the water surface. The average
distance between receivers positioned in
the circle was 800 m. All receivers recorded
the fish-identification code, date, depth and
time of detection from transmitters when a
tagged fish was within the receiver range.
The detection range of the transmitters was
determined by carrying out a series of
range tests, where both the depth of the
receiver and the transmitter were varied
(Uglem et al. 2008). These tests showed that
maximum detection range of receivers
varied between 300 and 400 m in radius.
Acoustic tagging was carried out at two
dates: 24 individuals were tagged on 19th
November 2009 and 14 individuals on 10th
December 2009 (Table 2.1). The former were
tagged with pressure sensor transmitter
while the latter did not transmit swimming
depth. The standard lengths (SL±sd) of
acoustically tagged fish in each release was
among 27.6±1.6 cm and 28.2±1.1 cm; and
average total weights (TW±sd) was among
461.2 ±101.6 g and 564.3 ±81.7 g,
respectively (Table 2.1).
Immediately before tagging with acoustic
transmitters, the fish were collected from
the storage pen (F3-R) using a hand net.
The sea bream were then anaesthetised by
immersion in an aqueous solution of
metacaine (0.75 g MS222 L-1, anaesthetic
volume 40 L, immersion period 3 ± 1 min,
temperature in solution: 15-17 ºC). Once
anaesthetized, the fish were weighed and
measured and placed with the ventral side
up onto a V-shaped surgical table. An
incision (~1 cm) was made on the ventral
surface posterior to the pelvic girdle using a
scalpel (Figure 2.4a). The transmitter
(Thelma Biotel Ltd., Trondheim, Norway;
14 units of model LP-9, 69KHz, 9 x 23 mm,
depth range 50m; and 24 units of model
ADT-9, 69KHz, 9 x 34, depth range 130m
and pressure sensor; both: pulse coded
transmission “Id”, 5-15 sec delay) was
gently inserted through the incision and
pushed into the body cavity above the
pelvic girdle (Figure 2.4b). The incision was
closed with two or three independent silk
sutures (2/0 Ethicon) (Figure 2.4c,d). The
fish were regularly sprayed with water
during the surgery (mean ± SD handling
time 3 ± 1 min, mean recovery time 2 ± 1
min). Before each incision, the surgical
equipment was rinsed in 70% ethanol and
allowed to dry. In addition, sea bream were
tagged on one side near the dorsal fin base
with external T-bar anchor tags (Hallprint
Ltd, Victor Harbor, South Australia) to
enable individual identification in case of
recapture (Figure 2.5). After tagging, the
fish were released from the boat next to a
sea cage once it showed a normal
swimming behaviour. The tagged fish were
released together with 50 un-tagged fish.
33
SEA BREAM AND SEA BASS ESCAPEES
Thus, the release simulated commonly
occurring small-scale escape incidents due
to operational failure during sorting and
handling of fish. The release was monitored
by divers following the release and all
tagged fish showed normal swimming
behaviour compared to untagged fish. All
handling and tagging was conducted
according to the Spanish regulations for the
treatment and welfare of animals (Real
Decreto 1201/2005, published in BOE num.
252, 21st October 2005).
Table 2.1. Characteristics of tagged fish. Type of tagging, date of releases, number of samples, standard
length (SL ± standard deviation), average total weight (TW ± standard deviation) and percentage of
recaptured fish.
Released
Acoustic
Acoustic
T-bar
T-bar
Recaptured
Date (m/d/y)
N
SL (cm)
TW (g)
N
SL (cm)
TW (g)
%
11/19/2009
12/10/2009
03/26/2010
07/27/2010
24
14
697
1494
27.6 ± 1.6
28.2 ± 1.1
20.6 ± 1.8
20.8 ± 1.5
461.2 ± 101.6
564.3 ± 81.7
272.7 ± 69.1
260.7 ± 48.3
0
0
25
134
21.4 ± 1.5
20.8 ± 1.4
304.7 ± 82.8
262.2 ± 44.1
3.5
8.9
Figure 2.4. Acoustic tagging procedure on farmed sea bream.
2.3.3. External tagging and recapture
programme
A total of 697 and 1494 farmed sea bream
from F3-R were externally tagged on the
26th of March (cold season) and on the 27 th
of July of 2010 (warm season) respectively.
Standard lengths (±sd) of tagged sea bream
in the cold and warm seasons were 20.6
±1.8 cm and 20.8 ±1.5 cm respectively,
while total weights (±sd) were 272.7 ±69.1 g
and 260.7 ±48.3 g (Table 2.1). The external
34
tags were t-bar anchor tags (Hallprint Ltd,
Victor Harbor, South Australia), which
have an exposed filament length of 15 mm
and a yellow external marker of 45 mm that
bear the individual code number, the name
of the institution and a telephone number
printed along with the code. The tagging
pistols used were the Avery Denissom
model TagFast III (Hallprint Ltd, Victor
Harbor, South Australia). This tagging
method has also been successfully applied
in previous studies on gilthead sea bream
CHAPTER 2
(Sánchez-Lamadrid 2001, 2004). Tags were
inserted into the flesh about 1 cm behind
the base of the dorsal fin according to
Astorga et al. (2005) (Figure 2.5). The tagged
fish were held in oxygenated tanks for 2
hours before being released to monitor their
health and recovery.
Information about the tagging programme
was sent to most recreational and
professional fishermen's associations, ports,
fishing stores and fishery research centres
along the coast of the study area. This
included a poster and pamphlets describing
the programme with instructions about
what to do in the event of recapturing a
tagged sea bream (Figure 2.6). Moreover,
these posters and pamphlets were
distributed in specific locations of greater
influx of coastal fishermen along the shore
of Alicante, such as sandy beaches and port
breakwaters and piers. When a tagged fish
was recaptured, the fishermen provided
information about the recapture date and
point (GPS position), approximate depth of
fishing and type of gear.
Figure 2.6. Poster describing the taggingrecapture programme and instructions for
rewards.
2.3.4. Habitat use and feeding habits
Habitat use of escapees was examined by
evaluating the bottom type at each
recapture position. For each recaptured
individual, the standard length (SL, cm)
and total wet weight (TW, g) were
measured in the laboratory. Moreover, food
items from the recaptured sea bream were
examined. Stomachs (from oesophagus to
pyloric sphincter) were dissected and
preserved in 70% ethanol. Gut contents
were observed under a microscope. Dietary
items, identified to the lowest possible
taxonomic level, were counted and
weighed after removal of surface water by
blotting paper.
Figure 2.5. External tagging procedure on
farmed sea bream.
The importance of different prey types was
evaluated by calculating the Frequency of
Occurrence (%O = 100 x number of
stomachs containing prey i/total number of
stomachs containing prey) and Percentage
Weight (%W = 100 x weight of prey i/ total
weight of all prey) (Hyslop 1980). Vacuity
Index (VI = 100 x number of empty
stomachs/total number of stomachs
analysed) was also calculated. Diet breadth
(C) and niche dominance (D) were
determined according to the Simpson
35
SEA BREAM AND SEA BASS ESCAPEES
indexes (C=1/Σpi2; D=Σpi2), where pi is
the frequency of appearance of prey i
(Simpson 1949).
2.3.5. Data analysis
The
receivers
occasionally
recorded
acoustic noise that was interpreted as a
single reception of a transmitter ID code. To
exclude such false signals, single detections
within a 30-min period were considered
erroneous (Arechavala-Lopez et al. 2010).
Presence within the detection range of a
receiver was thus defined as when a fish
was detected twice or more within a 30-min
period. Presence at any receiver was
examined by comparing the time a fish was
detected at any receiver with the total time
recorded during the study period for each
fish. Undetermined data (Ud) was defined
as those individuals with pressure sensor
tags that remained stationary for a long
time and did not show any vertical
movements apart from what could be
explained by tidal variation. Movements
among farms were defined as one-way
movements, i.e. if a fish moved from one
farm to another and then returned this was
recorded as two separate movements.
Variation in vertical distribution of sea
bream at farms in relation to time of day
and farm feeding schedule was examined
by comparing the mean swimming depths
and daily detections of each remaining fish
at any of the 4 farms among different times
of the day. Only days where a fish had been
detected more than twice at a farm were
included in the analyses.
To analyse diurnal variation in swimming
depth, each day was divided into two
periods, the first one from 06:00 to 18:59 h
being defined as day (from dawn to dusk)
and the remaining period as night (from
dusk to dawn). Furthermore, to analyse
swimming depth in relation to feeding at
farms, each day time was divided into a
feeding period (06:00 to 14:59 h) and a nonfeeding period (15:00 to 18:59 h).
Generalized linear model (GLM) repeated
measurements analyses were used to test
for differences in swimming depth and
daily detections (both dependent variables)
between individuals (random factor)
among different periods of a day (24 h, day
vs. night periods, and feeding vs. non-
36
feeding periods; covariates). The GLM
repeated measures procedure provides
analysis of variance when the same
measurement (detections) is made several
times on each subject or case (individuals).
Chi-square (X2) statistic was used to
investigate whether distributions of
recaptures within habitats differ between
seasons. All data were analysed using SPSS
15.0.
2.4. Results
2.4.1. Swimming behaviour at farm
facilities
All the acoustically tagged fish were
recorded at the release farm (F3-R) during
the first day after release and a high
proportion of tagged fish (N=15; 44.1%)
remained at the release farm during the
first 5 days (Figure 2.7). Moreover, 9 of the
tagged sea bream (26.5%) were recorded at
other fish farms, and 1 individual was
detected up to 4 weeks within the receiver
array after release time (Figure 2.7).
However, some of the tagged sea bream
(N=13; 38.2%) were not detected after the
first week (Nd; Figure 2.7), possibly
because they had left the study area, were
outside the detection ranges of the
receivers, or had been fished without being
reported; but none of them were recaptured
by fishermen during the study period
(Table 2.1).
In addition, a high proportion of the tagged
fish (N=21; 61.7%) were defined as
stationary or undetermined (Ud; Figure
2.7). They were likely to be dead since they
were continuously recorded at the same
receiver until the end of the study. Nonstationary fish (N=9) tagged with
transmitters with a pressure sensor which
remained nearby farm facilities showed a
clear diurnal variation in vertical
movements when they were detected at a
farm, with a greater swimming depth
during day time especially during the
morning hours, compared with night time
(Figure 2.8). Significant differences were
found between swimming depth and daynight periods (F=19.216; p<0.001), but there
were no differences in swimming depth
CHAPTER 2
among individuals (F=2.184; p=0.155),
among the 24 h of a day (F=0.876; p=0.360)
or between feeding-no feeding periods
(F=2.488; p=0.130). Number of daily
detections at farms throughout a day
showed a peak during the first hours in the
morning, but there were no overall
significant differences among the 24 h of a
day (F=2.529; p=0.127), day-night periods
(F=0.517; p=0.481) or feeding-no feeding
periods (F=2.680; p=0.117).
Connectivity among farms was evidenced
through the movements of non-stationary
sea bream, but the movement patterns
differed among individuals (Table 2.2,
Figure 2.9). Some individuals remained
beneath the same facility, but some others
visited different facilities during recorded
time (Table 2.2, Figure 2.9). For instance,
fish 8 (Id-08) was recorded up to 31 days in
the study area, repeatedly visiting 3 out of 4
farms before it disappeared from the
receiver array (Table 2.2, Figures 2.9, 2.10a).
Fish 6 (Id-43) was detected at all the farms
during a 12 day period before disappearing
(Table 2.2, Figures 2.9, 2.10b). Fish 5 (Id-46)
remained at the release farm for the first 3
days and then moved out of the receiver
array without being detected at any other
farm (Table 2.2, Figures 2.9, 2.10c). Fish 9
(Id-51) was detected for 18 days, moving
several times in and out of the detection
ranges of the receivers and visiting only the
inactive farm the first day (Table 2.2,
Figures 2.9, 2.10d).
Figure 2.7. Proportion of acoustically tagged S. aurata represented by bubble size (the smallest bubble
represent one fish, while the largest represent 100%) recorded by the receivers in detection zones after
release; mostly organised from North to South (see Figure 1 for exact location). Ud: undetermined data;
Nd: no data at any receiver. Tagged fish were released at farm FR.
Figure 2.8. Vertical distribution and daily detections of tagged sea bream (N=9) around fish farms during
the period of a day. Bars show mean depth values with standard error lines. Plotted line shows mean
number of daily detections. Dark area: night time; white area: day time; striped area: feeding time at
farms.
37
SEA BREAM AND SEA BASS ESCAPEES
Table 2.2. Recorded time (days) and number of movements (mov.) of the 9 non-stationary tagged sea
bream that moved from the release farm F3 (R) to other fish farms (F1, F2, F4) during the study period.
Num. F visited: number of farms where the fish were detected.
Fish ID code Max Days Recorded Presence at F (%) F visited F-F mov. Mov./day F Sequence
1
25
3
90
1
1
0.333
R-F4
2
21
5
98.6
0
0
R
3
33
7
95
0
0
R
4
17
4
98.6
0
0
R
5
46
3
100
0
0
R
6
43
12
43
4
4
0.333
R- F2-F1-R- F4
7
12
7
79.6
2
2
0.285
R- F4-R
8
08
31
9
3
4
0.129
R- F2-F1- F2-R
9
51
18
1
2
2
0.111
R- F2-R
Days after release
0
1
2
3
4
5
6
7
8
9
10
11
12
13
18
29
30
31
Fish (Id)
1 (25)
6 (43)
7 (12)
8 (8)
9 (51)
F3 (R):
F4 (S):
F1 (Far):
F2 (N):
Figure 2.9. Detailed movements of tagged sea bream among farm facilities during recorded time. Black
spot: end of signal detection. Dotted line: fish movements out of the detection range at farms.
Figure 2.10. Sequences of movements of tagged S. aurata within the receivers array. Arrows represent a
simulated direction of the tagged fish following the detections. Tagged fish were released at farm F 3R. ?
means no data of tagged fish from any receiver.
38
CHAPTER 2
2.4.2. Dispersion and interaction with
fisheries
A total of 25 and 134 individuals from the
first and second releases of externally
tagged fish (i.e. cold and warm season),
were recaptured by local fishermen during
the study period. This corresponds to 3.5%
and 8.9% of the tagged fish (Table 2.1).
Standard length (SL±sd) of recaptured sea
bream in the cold and warm seasons was
21.4 ±1.5 cm and 20.8 ±1.4 cm, respectively
(Table 2.1). Average total weights (TW±sd)
was 304.7 ±82.8 g for recaptures from the
cold season release, and 262.2 ±44.1 g for
fish tagged during the warm season (Table
2.1). The cumulative recaptures during the
cold season exhibited a steady increase
during the first month up to close to the 3%,
and after that the recapture rate decrease
with the last report 60 days after release
(Figure 2.11). In contrast, the cumulative
recapture rates plot increased rapidly
during the first week in the warm season,
reaching almost 8%. Later the increase in
recapture rate was less in the warm season
compared with the cold season. The last
recapture in the warm season was reported
45 days after release (Figure 2.11). During
the cold season, artisanal fishing was
responsible for 76% of the recaptures, with
sepia trammel-net being the most effective
commercial fishing gear for recapture of
escapees (60%) followed by gillnet (16%).
Recreational fishing stood for 24% of the
recaptures
(Figure
2.12).
Moreover,
artisanal fishing contributed with the 67%
of the total recaptures during the warm
season with shrimp trammel-net being the
largest contributor (47%), followed by sepia
trammel-net (19%) and gillnet (1%).
Recreational fishing stood for 33% of the
recaptures for the warm season escape with
spear-fishing being (23%) more important
than
anglers
(10%;
Figure
2.12).
Figure 2.11. Cumulative recaptures throughout the days after release following the cold season (black
dashed line) and warm season releases (grey solid line).
Figure 2.12. Contributions of the different types of fishing gears on recaptures of tagged and released sea
bream for both tagging seasons.
39
SEA BREAM AND SEA BASS ESCAPEES
2.4.3. Habitat use and feeding habits
A large part of the recaptures was reported
from areas close to the shoreline and fish
farms (Figure 2.13). Most of the recaptures
occurred next to Guardamar del Segura
harbour by recreational fishermen or
between the farm area and the coast by
artisanal fishermen. However, some tagged
sea bream were recaptured in the northern
and southern part of the study area by
recreational fishing (Figure 2.13). Most
tagged fish were caught on seagrass
bottoms, during both cold and warm
season (48% and 40% respectively; Table
2.3, Figure 2.13), followed by captures on
fine sandy bottoms (12% and 17%
respectively) and close to harbours (8% and
10% respectively; Table 2.3). Overall,
recaptures among both seasons were
significant differences according to habitats
(X2: p<0.001). Recaptures on detritus and
gravel bottoms only occurred in the warm
season (17%; Table 2.3), while recaptures in
mixture habitats were higher in the cold
season than in warm season (32% and 16%
respectively; Table 2.3).
Table
2.3.
Distribution
of
recaptures
(percentages) among the different habitats of the
bay for both seasons of release. * Mixture:
seaweed, seagrass, sandy and rocky bottom.
Habitat
Harbour
Seagrass
Detritus and gravel
Fine sand
Mixture*
Cold
season
8
48
0
12
32
Warm
season
10
40
17
17
16
Figure 2.13. Spatiotemporal distribution of recaptured sea bream according to the habitats distribution in
the study area. Numbers indicate the day of recapture after release by different local fisheries. White
numbers: day of recaptures by artisanal fisheries; black numbers: day of recaptures by recreational
fisheries.
A total of 31 items, clustered in 10 main
groups, were identified from the stomach
contents of recaptured sea bream (Table
2.4). For individuals captured during the
first day after release, macrophytes, such as
algae and seagrass, was the most important
item found in the stomachs (50%O,
40
46.2%W), followed by food pellets (40%O,
15.1%W), and human litter such as cigarette
butts or strings (33.7 %W; Table 2.4, Figure
2.14). Sea bream captured within the second
day also fed mainly on macrophytes
(seagrass: 80%O, algae: 55.2%W), but also
on echinoderms (20%O, 4.1 %W), food
CHAPTER 2
pellets (20.4%W) and decapods (12.7%W)
probably also from farm structures (Table
2.4, Figure 2.14). Fish captured within the
third day fed not only on macrophytes
(70%O, 79.2%W), but also on crustaceans
(50%O, 5.4%W), mainly amphipods from
farm facilities such as Caprella dilatata and
Jassa marmorata (30%O, 3.2%W), and
molluscs (0.3%O, 11.4%W) with bivalves
being the most important group (20%O,
10.8%W; Table 2.4, Figure 2.14). The
stomach content from fish captured
between days 4 and 9 after release consisted
of high proportions of macrophytes and
crustaceans (60%O in both cases), but in
terms of weight, the most important items
were the molluscs gastropods (47.4%W;
Table 2.4, Figure 2.14). In this group of fish
the high presence of detritus must be taken
into account (40%O), as well as food pellets
(20%O) and human litter (20%O) in the
stomachs, probably due to a close contact
with farm facilities (Table 2.4, Figure 2.14).
Fish captured beyond 9 days after release
had relatively large proportions of molluscs
in the stomach (90%O, 44.6%W), with
gastropods and bivalves constituting 60%O,
25.1%W and 60%O, 19.4%W, respectively;
Table 2.4, Figure 2.14), followed by
crustacean decapods (40%O, 10.2%W) and
inorganic sediments such as sand and grit
(40%O, 9.2%W). Food pellets represented
18%W of the stomach content after 9 days,
while macrophytes were almost absent
(10%O, 0.1%W; Table 2.4).
Table 2.4. Frequency of occurrence (%O) and percentage of wet weight (%W) of food items,
number of prey items, vacuity index, diet breadth and diet dominance indexes for tagged sea
bream regarding the different time of recapture after release (days).
Gut contents
Inorg Sediment
Detritus
1 day
%O
%W
-
2 days
%O
%W
10
5.1
3 days
%O
%W
10
0.6
4-9 days
%O
%W
-
>9 days
%O
%W
40
9.2
-
-
10
0.5
10
1.6
40
6.3
10
10.2
50
40
10
46.2
16.6
29.6
80
40
40
55.2
17.9
37.3
70
40
30
79.2
26.3
52.9
60
40
20
18.9
8.4
10.5
10
10
-
0.1
0.1
-
-
-
-
-
-
-
-
-
10
1.2
Mollusca
Bivalvia
Cardiidae
Kelliidae
Mactridae2
Mytilidae3
Ostreidae
Pectinidae
Gasteropoda
Naticidae
Rissoidae4
Turritelidae
Unidentified
10
10
10
-
4.1
4.1
4.1
-
10
10
10
10
10
-
2.0
1.0
1.0
1.0
1.0
-
30
20
10
10
10
10
-
11.4
10.8
5.4
5.4
0.6
0.6
-
20
20
20
20
-
47.4
47.4
5.3
42.1
-
90
60
10
40
10
10
10
60
30
40
30
44.6
19.4
12.9
13.1
0.4
12.4
0.4
25.1
7.2
17.5
0.3
Crustacea
Amphipoda
Caprellidea5
Gammaridea6
Decapoda
Unidentified
-
-
10
10
-
12.7
12.7
-
50
30
20
10
10
10
5.4
3.2
2.2
0.9
1.6
0.6
60
20
40
19.0
15.8
3.2
40
40
-
10.2
10.2
-
Echinoidea
Regularia7
Irregularia8
-
-
20
10
10
4.1
1.0
3.1
10
10
1.3
1.3
-
-
10
10
5.1
5.1
Macrophyta
Algae
Seagrass1
Briozoa
Fish Remains
20
1.0
10
0.3
10
1.0
Food Pellets
40
15.1
10
20.4
20
5.3
10
18.4
Human Litter9
10
33.7
20
3.2
30
23
41
20
11
Fish sampling (N)
66.6
47.8
60.9
75
36.4
Vacuity Index
2.08
1.98
1.96
1.47
0.86
Diet Breath
0.48
0.50
0.51
0.68
1.16
Diet Dominance
1: Cymodocea nodosa; 2: Spisula subtroncata; 3: Musculus custulatus and Mytilus sp.; 4: Gen. Rissoa; 5: Caprella dilatata; 6: Jassa
marmorata; 7: Paracentrotus lividus; 8: Brissus unicolor; 9: cigarette butts and strings.
41
SEA BREAM AND SEA BASS ESCAPEES
Figure 2.14. Proportion of the main food items of recaptured sea bream according to the different time of
recapture after release (days). A: per cent occurrence; B: percent weight.
2.5. Discussion
Tagged sea bream showed both a high
dispersion within the first 5 days after
release and a high mortality rate (>60%)
where the fish appeared to be predated at
the
release
farm.
However,
some
individuals remained not only at the release
farm but also at the nearby farm facilities
for long periods, surviving up to 4 weeks
with a clear diurnal swimming depth
behaviour related to farm activity. Local
fisheries contributed recapturing tagged
individuals that disperse from farm
facilities, being professional trammelnetters the major contributors. Those
recaptured individuals were mostly caught
on seagrass, sand or rocky bottoms where
they wild conspecific live, feeding on
natural preys such as crustaceans and
molluscs after one week in the wildness.
It has been suggested that escapees show a
high degree of site fidelity or, in contrast,
low site fidelity but high mortality rates
(Toledo–Guedes et al. 2009). Past studies on
salmon (S. salar) and cod (G. morhua)
suggested that such escapees may either
remain near the farm site or disperse
rapidly following release, with low survival
rates through predation or local fishing
(Hansen 2006; Uglem et al. 2008, 2010; Olsen
42
and Skilbrei 2010; Skilbrei et al. 2010). A
high mortality rate on farmed sea bream
after an escape incident was found in this
tracking
study.
High
densities
of
piscivorous predators has been reported
around farms in this specific area (e.g.
Fernandez-Jover et al. 2008; ArechavalaLopez et al. 2010), such as bluefish
(Pomatomus saltatrix), which are attracted to
the farms due to an abundance of smaller
prey fish. Moreover, it has been observed
that bluefish manage to get into the cages
where they feed especially on the cultured
sea bream fish (Sanchez-Jerez et al. 2008).
Tracked sea bream were determined to be
dead on basis of lack of other vertical and
horizontal movements to those fish
equipped with pressure sensing tags, and
based on absence of horizontal movements
to the rest of tagged individuals. It could be
expected that signals recorded from a
transmitter of a predated fish which is
within the stomach of the predator showed
sudden changes in swimming depths, as it
has been observed in smolts eaten by cod, a
marine predator (Thorstad et al. 2011;
Hedger et al. 2011). In contrast, bluefish
bites its prey breaking them up in two
pieces rather than swallow them whole, so
the transmitter is likely to fall down to the
bottom.
CHAPTER 2
It is documented that both the swimming
capacity and the behavioural repertoire of
farmed
fish,
including
antipredator
behaviour, is impaired compared to wild
fish, probably as a result of artificial
selection and lack of experience (Salvanes
and Breithwaite 2006). However, it is also
likely that the physical condition of some of
the fish was reduced due to the tagging
procedure. Hence, it is reasonable to believe
that the released fish experienced a high
predation pressure during the first few
days after simulated escape. Nevertheless,
it cannot be ruled out that tagging in some
way affected sea bream behaviour and
survival. In addition, lack of detections for
some fish after release might be caused by
intensive fishing efforts around farms as
commercial fishermen exploit the large
amount of wild fish being attracted to
farms
(Akyol
and
Ertosluk
2010;
Arechavala-Lopez et al. 2011a). It is
probable that some of the tagged fish were
caught and not reported. It is nevertheless
not possible to rule out the fact that
stationary fish without pressure sensing
tags were still alive at the end of the study
and that they showed a pronounced fidelity
to the farm they originated from. However,
no escapees were observed on punctual
visual surveys carried out at farm facilities
during this study.
Tracked fish that evidently neither died
after release nor dispersed away from
detection range showed a varied movement
pattern among individuals. However, all of
them visited another farm besides the
release one, indicating the existence of
connectivity among farm facilities through
their movements. When these individuals
remained next to a facility, they tended to
stay close to the surface during night time,
while they descended to greater depth in
the morning. This might be a result of the
natural diurnal variation in behaviour and
vertical movements of sea bream. For
instance, Velázquez et al. (2004) describe sea
bream as a dual species, since it is able to
adapt its feeding activity spontaneously to
the dark or the light phase. However,
Abecasis and Erzini (2008) did not find any
daily pattern when comparing night and
day detections of tagged sea bream released
in the wild. The diurnal variation in vertical
movements found in the current study
seemed to be influenced by feeding time at
farms (which typically starts around 06:00
a.m.) since waste feed from farms becomes
available at depths below 10 m for escapees
and wild farm-aggregated fish that reside
outside the cage. It has been shown that
farmed sea bream synchronize their
locomotor activity to both the light and
feeding phases (Bégout and Lagardère
1995; López-Olmeda et al. 2009; Sánchez et
al. 2009; Montoya et al. 2010). The finding
that escaped sea bream stay in the upper 34 m during night time might be related not
only to absence of fish feed but also to the
lack of vessel traffic at farms. The acoustic
energy produced by vessel traffic is
detected by many fish species (Ross 2005;
Popper and Hastings 2009), and could
influence
their
swimming
activity,
migration motivation or stimulating food
acquisition (Buscaino et al. 2010).
Once the escapees disperse from farming
area they are likely to be captured by local
fisheries, and the average recapture rate of
sea bream tagged with external tags
obtained (7.2%) was comparable with those
from other studies carried out in the
southern part of the Iberian Peninsula
(from 6.3% to 11.2%) (Sánchez-Lamadrid et
al. 2002, 2004; Santos et al. 2006), and in the
Balearic Islands (5.9%; Valencia et al. 2007).
This indicates a high intensity of fishing on
the released fish, mainly during the first
days after release, i.e. presumably before
the escapees had adapted to their new
environment (Sánchez-Lamadrid et al.
2004). The recapture rates could be
regarded as minimum estimates due to loss
of tags (Sanchez-Lamadrid 2001). In fact,
scars were detected on some untagged
bigger fish caught by fishermen, exactly in
the position where the tags were inserted.
Differences on recapture rates in terms of
cumulative percentage and time of last
recapture could be related to several
factors, including the place and date of
release (Sánchez-Lamadrid et al. 2002). The
local fishing fleet presents a welldifferentiated distribution among seasons
with captures of wild fish being more
common during the warm season because
of the increasing fishing effort. Moreover,
recreational fishing had lower success
catching escaped sea bream in both seasons
43
SEA BREAM AND SEA BASS ESCAPEES
than commercial fisheries, with the gillnetting being the most efficient. Similar
results were obtained in recent studies
about escaped salmon in Norwegian fjords
where recaptures by gill-nets were the most
efficient method (Olsen and Skilbrei 2010),
followed by coastal bag nets when the
former is not permitted (Chittenden et al.
2011). In contrast, Valencia et al. (2007)
reported about the 85.7% of recaptured sea
bream were caught by recreational
fishermen in Balearic Islands. Nonetheless,
recapture fisheries are a realistic option for
reducing the impact of escape events
(Uglem et al. 2010).
It has been suggested that escaped farmed
fish, including sea bream, have inferior
competitive abilities and that they are less
able to perceive environmental stimuli
useful for their settlement compared to
wild fish and that this in turn may
negatively affect their survival in the wild
(Olla et al. 1994; D’Anna et al. 2004; Santos et
al. 2006; Basaran et al. 2007). In the current
study escaped sea bream were frequently
recaptured in the most common natural
habitat of this species (Abecasis and Erzini
2008) and stomach analyses of a subsample
of fish indicated that escapees may feed on
natural prey from the first day after escape.
Gilthead sea bream is an opportunistic
feeder, adapting its diet to the food items
available in the habitat (Pita et al. 2002;
Tancioni et al. 2003). The primary prey
items in the diet of wild sea bream are
mollusc bivalves, followed by gastropods
and crustaceans decapods, but they also
feed
on
polychaetes,
crustacean
amphipods,
seagrass,
algae
and
occasionally fish (Arias 1980; Rosecchi 1985;
Pita et al. 2002; Tancioni et al. 2003; Chaoui
et al. 2005). Initially, escaped sea bream fed
on macrophytes and food pellets from
farms. Later, they began to prey on
echinoderms and crustaceans mostly
associated to farm facilities. Finally, they
fed on more common natural prey from the
fifth day after release, mainly molluscs and
crustaceans. It is remarkably that food
pellets were present in the stomach of both
the first and the last recaptured individuals.
This could be supported by Abecasis and
Erzini (2008) who found that two out of the
three tagged fish released about 4 km from
44
the capture location returned to this site
after release. The findings in this study
illustrate not only the trophic flexibility of
escaped sea bream, but also the ability to
feed on their most common natural prey
after a short period of time, as the feeding
habits of escapees approached that of wild
congeners one week after escape.
Moreover, a significant number of wild fish
were caught together with escapees, even
up to 20 km from the release farm. This
agrees with previous studies on dispersal of
released sea bream, where recaptures have
been recorded from 18 to more than 40 km
away from the release spot (SánchezLamadrid et al. 2002; Santos et al. 2006). The
fact that feeding grounds and habitat use of
escapees overlapped with wild fish ones,
since escapees occur together with their
wild conspecific and are able to switch to
natural prey within short time periods,
reflects their potential for survival in the
wild and their high risk for native
populations.
In conclusion, escaped sea bream moves to
other farms and natural habitats where
concurred with other cultured and wild
conspecifics, and they are also able to
utilize natural food resources within a short
time frame. The initial mortality of farmed
fish following small-scale escape incidents
may be high, possibly as a result of
predation. However, the predation risk will
likely vary according to season and the
occurrence of predators around the farms.
The recapture of escapees from small-scale
escape incidents that survive the first days
may also be substantial, even without
specific recapture fisheries. Our data do not
allow long-term evaluation of the survival
and ecological effects of escapees, but as
known from other farmed species, even a
modest survival rate after escape might
entail negative ecological consequences for
wild populations (Thorstad et al. 2008).
Apart from the necessity of regulatory tools
and technological measures to prevent
escape incidents, methodologies to reduce
the potential effects following an escape
event are also desirable. Such methods
could be the use of sterile fish or the
location of farms away from areas of
particular importance to wild fish stocks,
especially in the case of restocking
CHAPTER 2
programmes
or
massive
escapes.
Furthermore,
development
of
methodologies and strategies to recapture
escapees through collaborations with local
fisheries, especially in the case of large-scale
escape incidents, are highly necessary.
45
SEA BREAM AND SEA BASS ESCAPEES
46
CHAPTER 3
3. POST-ESCAPE BEHAVIOUR OF FARMED SEA BASS
3.1. Abstract
European sea bass is an important species for both Mediterranean aquaculture and fisheries.
Similarly to gilthead sea bream, several escape incidents from open-sea cages have been
reported. However, knowledge about their potential interactions with nearby farms and wild
populations are scarce. In this study it was shown that escaped sea bass are able to survive for
prolonged periods in the environment, although a high mortality rate was also recorded.
Through telemetry it was evidenced that some of them are capable to move relatively quickly
and repeatedly among several Mediterranean fish farms within the first week after release. In
addition, through recaptures of local fishermen of externally tagged sea bass, it was
demonstrated that they also disperse from farm facilities, mainly visiting estuarine coastal
habitats where they feed on natural preys, although it is likely that they need more time to
adapt to the new environment than sea bream. However, the results might indicate that longterm ecological impacts of such escape incidents might be relatively insignificant due to high
mortalities of escapees. However, it was evidenced the potential risk of escaped sea bass on
wild assemblages through competition for natural resources and predation on other species,
which could lead locally to serious ecological problems if both massive escape and/or large-size
fish escape incidents occurs, especially in coastal and estuarine populations.
3.2. Introduction
European sea bass (Dicentrarchus labrax L.)
is a marine species of great economic
importance, particularly in Mediterranean
fisheries and aquaculture (APROMAR
2011). Similar to gilthead sea bream,
escapes of sea bass from sea cages have
been also sporadically recorded in the
Mediterranean (Dempster et al. 2002; Vita et
al. 2004; Valle et al. 2007; Fernandez-Jover et
al. 2008) and quite extensively in the
Canary Islands (Toledo-Guedes et al. 2009),
where it is considered to be a non-native
species. As it was shown in the introduction
section of this thesis, escapes are caused
mainly by technical and operational
failures, and represent a considerable
economical loss for the farmers and a
potential environmental threat to native
populations.
In the previous chapter 2, it was evidence
that farmed escaped gilthead sea bream not
only remained for long periods swimming
among farm facilities, but also dispersed to
nearby fishing grounds and coastal areas
competing for food and habitat with wild
conspecifics and other species (ArechavalaLopez et al. 2012c). Therefore it was
highlighted the negative potential effects of
escapees through transmitting pathogens
among cages and to coastal areas,
competition for food, habitat and mate with
wild populations, and interbreeding with
wild conspecifics dwelling coastal natural
habitats in the Mediterranean.
However, knowledge on the fate and effects
of the escaped aquaculture sea bass in the
Mediterranean is sparse. Therefore, for a
better understanding of these potentially
negative effects it is important to know the
immediate post-escape behaviour of
escaped sea bass. Thus, the objective of this
study was: (i) to describe the swimming
behaviour of escaped sea bass and their
movements at farm facilities through
telemetry, (ii) to estimate the residence time
and survival of escaped individuals around
a source farm, and (iii) to evaluate the
potentially of negative effects of escapees
on wild populations by assessing the
habitat use and feeding behaviour of
recaptured sea bass through external
tagging at coastal Mediterranean farms.
3.3. Material and Methods
3.3.1. Study Area
The study was carried out in the same
Mediterranean coastal farming area as in
previous sea bream study (see description
in chapter 2), where there is a farming area
among local fishing grounds (Figure 3.1).
49
SEA BREAM AND SEA BASS ESCAPEES
Figure 3.1. Map of Guardamar Bay, south-eastern Spain, and the locations of the farms facilities (rectangles
or F). Pushpin: receiver location. Externally tagged fish were released at R (black pushpin), within farm F3.
3.3.2. Tracking and tagging procedure
Similarly to sea bream study, immediate
post-escape swimming and dispersal
behaviour of escaped sea bass were studied
by acoustically tagging and releasing 10
individuals from cages. Average lengths
and weights of the fish were 27.85 (±1.29)
cm and 377 (±45) g (±SE), respectively. The
telemetry protocols and tagging procedure
were exactly the same as applied for sea
bream in previous chapter 2. Their
spatiotemporal distribution was monitoring
using the same array of 10 automatic
receivers (Vemco Ltd., model VR2; Fig. 2.3),
positioned at different farms and adjacent
areas throughout the Guardamar Bay (Fig.
3.1b). The individuals were anaesthetised
(MS222) and the transmitter (Thelma Biotel
Ltd, Trondheim, Norway, model LP-9,
69KHz, 9x23 mm, weight in air ⁄ water of
4.0 per 2.5 g, depth range 50 m) inserted
into the body cavity through a small ventral
incision closed with 2-3 stitches (Figure 3.2).
Farmed sea bass were also tagged with
external streamer tags (Hallprint Ltd, Victor
Harbour, South Australia). After tagging,
the fish were allowed to recover (for at least
2 h) in a large container onboard the fishing
vessel before being simultaneously released
on the 11th November 2009 from the boat
close to a sea cage (F3-R), together with 16
non-tagged individuals (Figure 3.3). The
release was monitored by divers and all
tagged fish showed normal swimming
50
behaviour compared to the non-tagged fish.
All handling and tagging was conducted
according to Spanish regulations for the
treatment and welfare of animals (Real
Decreto 1201 ⁄ 2005, BOE #252, 21 October
2005).
Figure 3.2. Tagging farmed sea bass with
acoustic transmitters. (Photo: P. Sanchez-Jerez)
3.3.3. External tagging and recapture
programme
A total of 1186 sea bass individuals from
farm F3, were externally tagged and
released in the same farm facility where
they were growing (F3-R; Fig. 3.1),
simulating escape incidents in two different
times. Specifically, 688 and 498 individuals
were tagged and released on the 27th and
29th of July 2011 respectively. Total average
length (standard length ± sd) and average
weight (total weight ± sd) at release time
CHAPTER 3
were 26.4 ± 1.8 cm and 302.9 ± 81.6 g,
respectively. As in sea bream study
(previous chapter 2), T-bar anchor tags
(Hallprint Ltd, Victor Harbor, South
Australia) were used, which have an
exposed filament length of 15 mm and a
yellow or red external marker of 45 mm
that bear the individual code number, the
name of the institution and a telephone
number printed along with the individual
code. Tags were inserted into the flesh,
about 1 cm behind the base of the dorsal
fin, by tagging pistols (Avery Denissom
model TagFast III; Hallprint Ltd, Victor
Harbor, South Australia). This kind of tags
allows the fish freedom of movement, are
relatively quick and easy to apply, and
have good retentive properties (Pawson et
al. 1987). Similar tagging method has also
been successfully applied in previous
studies on reared sea bass juveniles for
restocking programs (Grati et al. 2011), on
wild sea bass (Pickett et al. 2004; Pawson et
al. 2007). The tagged fish were held in
oxygenated tanks for 2 hours before being
released to monitor their health and
recovery.
poster and pamphlets describing the
programme with instructions about what to
do in the event of recapturing a tagged fish
and reward conditions (Figure 3.4).
Moreover, these posters and pamphlets
were distributed in specific locations of
greater influx of coastal fishermen along the
coast, such as sandy beaches and port
breakwaters.
Figure 3.4. Poster describing the taggingrecapture programme of sea bass and
instructions for rewards.
3.3.4. Habitat use and feeding habits
Figure 3.3. Releasing tagged sea bass at fish farm
facilities (simulating an escape). (Photo: I. Uglem).
Information about the tagging programme
was sent to recreational and professional
fishermen's associations, ports, fishing
stores and fishery research centres along
the coast of the study area. This included a
When a tagged fish was recaptured, the
fishermen
provided
the
fish
and
information about the recapture point, time,
and fishing method (gear and bait).
Moreover, standard length (cm) and total
weight (g) were recorded from recaptured
specimens, as well as and the sex and
gonad maturity (Sex M.). Recaptured
tagged sea bass individuals were
immediately frozen (-80ºC) after being
caught. Stomach contents of recaptures
were analysed in order to assess the feeding
habits of sea bass escapes. Stomachs (from
the oesophagus to the pyloric sphincter)
were dissected and preserved in 70%
ethanol. Gut contents were observed under
a microscope. Dietary items, identified to
the lowest possible taxonomic level, were
counted and weighed after the removal of
surface water by a blotting paper.
51
SEA BREAM AND SEA BASS ESCAPEES
3.3.5. Data analysis
The
receivers
occasionally
recorded
acoustic noise that was interpreted as a
single reception of a transmitter ID code. To
exclude such false signals, single detections
within a 30-min period were considered
erroneous (Arechavala-Lopez et al. 2010).
Presence within the detection range of a
receiver was thus defined as when a fish
was detected twice or more within a 30-min
period. Presence and residence time at
farms were examined by comparing the
time a fish was detected at any farm with
the total time recorded along the study
period for each fish. Movements among
farms
were
defined
as
one-way
movements, i.e. if a fish moved from one
farm to another and then returned, this was
recorded as two separate movements.
Movement speed was calculated based on
two movement times from the inactive farm
(F2) to the further farm (F1) for each
individual (distance: 3 km ±350 m assumed
variation receiver range).
Thus, the release simulated the commonly
occurring escape incidents due to
operational failures during sorting and
handling of fish.
3.4. Results
3.4.1. Swimming at farm facilities
All tagged fish were recorded at the release
farm (FR) during the first day after release
(Figure 3.5). Four of the tagged fish were
recorded at other fish farms (Table 3.1;
Figures 3.6 and 3.7). Three of these were
detected at the F1 farm located 3.5 km from
F3-R during days 3 and 4 (Table 3.1; Figures
3.6 and 3.7). The movement speeds (±SE)
from F3-R to F1 for these three fish were:
Id#1: 0.08 (±0.02) m s-1; Id#2: 0.16 (±0.03) m
s-1; and Id#3: 0.26 (±0.07) m s-1. The fish
recorded at other farms than at F3-R were
present at any of the four fish farms
between 30.7 and 77.7% of the study period,
while the number of inter-farm movements
for these fish ranged from 2 to 7 (Table 3.1;
Figure 3.6). The number of one-way
movements per day during the first 3
weeks after release for these four fish
varied between 0.13 and 1.0.
Figure 3.5. Daily numbers of tagged D. labrax detected by different receivers. Tagged fish were released at
farm FR.
Figure 3.6. Detailed movements of tagged sea bass among farm facilities during recorded time. Black spot:
end of signal detection. Dotted line: fish movements out of the detection range at farms.
52
CHAPTER 3
Table 3.1. Recorded time (days) and number of movements (movs.) of the 5 non-stationary tagged sea
bream that moved from the release farm F3 (R) to other fish farms (F1, F2, F4) during the study period.
Num. F visited: number of farms where the fish were detected.
Sea bass
1
Max Days
Recorded
7
Presence
at F (%)
77.7
num F
visited
3
F-F
movs
4
2
7
30.7
4
7
1
3
21
54.6
3
5
0.238
4
2
100
0
0
-
5
18
58.6
2
2
0.111
ID
Mov/day
0.571
Sequence
F3R – F4- F3R - F1- F3R
F3R - F2- F1- F2- F3R - F2- F3R – F4
F3R - F2- F1- F3R – F2- F3R
F3R
F3R – F4- F3R
Figure 3.7. Movement sequences of tagged sea bass within receivers, from the release day (11 November
2009) until either end of tagged fish life (X) or no signal detections from any receiver. Arrows = simulated
direction of tagged fish. Tagged fish were released at farm F3-R.
One of the fish that moved among farms
was detected at all farms in the study area,
while two were recorded at three farms and
one at two farms. The four fish that showed
inter-farm movements were active form 7
to 21 days (Figure 3.7). Two of them
seemed to become stationary at one single
receiver (at F3-R and F4 respectively)
through the remaining study period after
day 7 (Figure 3.7). The two other fish
disappeared from F3-R after 17 and 21 days
(Figure 3.7). One of the tagged fish
disappeared from F3-R the second day after
release. It is possible that the fish
53
SEA BREAM AND SEA BASS ESCAPEES
disappeared from F3-R, never to be
detected by any of the receivers, were
captured by local fishermen fishing close to
the sea cages. The remaining five fish were
continuously recorded at the release farm
throughout the 60-day study period. When
a fish was detected by only one receiver
over long periods (1–2 months), this meant
that it was stationary within a relatively
small area (approximately 600–800 m in
diameter). In comparison, the four fish
detected at other farms other than the
release farm were relatively active for
periods of up to 21 days before they
disappeared or “settled” at different farms.
Hence, it is likely that the long-term
stationary fish were dead, even though the
possibility that the tagged fish were still
alive cannot be ruled out.
3.4.2. Dispersion, habitat use and
feeding habits
A total of 15 sea bass individuals (1.26%)
were recaptured following the escape
incidents (Table 3.2). Standard length (±sd)
and total weight (±sd) of recaptures were
28.1 ±1.9 cm and 372.5 ±79.1 g respectively.
All of them were caught gradually over 3
months (Table 3.2, Fig. 3.8) by local
recreational fishermen with fishing rods in
the mouth of Segura River, at the entrance
of Guardamar harbour (Fig. 3.1). Any fish
were recaptured either by professional
fishermen or out of the river mouth
First recapture was on the 7th day after
release, and the last recapture occurred up
to 94 days after release (Table 3.2, Fig. 3.8).
Identification tags from all recaptures were
given by local fishermen; however, only 9
specimens
were
recovered
integers.
Therefore, further feeding habits analysis
was only possible to be carried out in these
latter 9 specimens (Table 3.2). Regarding
sexual maturity, all of them were immature
male (6 individuals on stage I and 4
individuals in stage II) (Table 3.2).
According to prey items found in the
stomachs, 4 of these 9 recaptured fish
(44.4%)
presented
empty
stomachs.
Individual num. 4, which was recaptured
13 days after release, presented 5 decapod
larvae in its stomach (Table 3.2). Particulate
organic matter, similar to that found in the
bottom of the river, was found in the
54
stomach of sea bass num. 6, which was
recaptured 24 days after release. Moreover,
food pellets were found in the stomach of
individual num.11, which was in the wild
up to 37 days. Sea bass num. 13 and 14
were recaptured 44 and 69 days after
release, and presented fish remains and
polychaeta remains respectively in their
stomachs (Table 3.2).
3.5. Discussion
It was shown that escaped sea bass are able
to survive for prolonged periods in the
environment, moving relatively quickly
and repeatedly among several fish farms,
but also visiting estuarine coastal habitats
where they feed on natural preys. The fast
movements of escapees among different
farms separated some kilometres distance is
supported by other studies that have also
shown that tagged and released sea bass
may move over relatively large areas
during short periods (Bégout-Anras et al.
1997; Quayle et al. 2009). Fast and repeated
movements among fish farms might
represent a vector for disease transmission
among cages if they were infected (Uglem
et al. 2008). Furthermore, our results
indicate that the immediate mortality of
escaped sea bass may be high in the wild.
High mortalities were also estimated to
occur in escaped sea bream (chapter 2Arechavala-Lopez et al. 2012c), since postrelease three-dimensional movements were
followed by long periods with no variations
in location or depth.
Toledo-Guedes et al. (2009) suggested that
the apparent close association of tagged
and released cultured sea bass with farms
could be due to two different processes:
either sea bass show a relative high degree
of site fidelity and are thus more abundant
near fish farms, or they show low site
fidelity but suffer high mortalities in
surrounding habitats, as proposed in other
geographical areas. Other study showed
that released farmed steelhead trout
(Oncorhynchus mykiss) may stay around the
release cages and other adjacent farms,
especially during the feeding periods, for
weeks before they disappear (Bridger et al.
2001). In contrast, other studies have
demonstrated high and rapid dispersal
CHAPTER 3
rates for Atlantic cod (G. morhua) (Uglem et
al. 2008, 2010) and Atlantic salmon (S. salar)
(Skilbrei et al. 2010) after escape events. Our
results might indicate that escaped sea bass
show high fidelity to farm areas during few
days after release, but also that the postescape mortality is likely to be high. The
mortality might be a result of fishing,
predation or tagging effects. High fishing
efforts have been reported around
Mediterranean fish farms (Akyol and
Ertosluk 2010). We also noted a higher
fishing pressure around the studied fish
farms than in areas with no farming
activities, principally by artisanal fishermen
deploying gillnets and trammel nets or
trolling close to the sea cages, and also large
captures of escaped sea bass have
frequently been sold at local fish markets.
Nevertheless, no tagged fish was returned
by professional fishermen.
Table 3.2. Time of recapture (days after release), standard length (SL ± standard deviation), total weight
(W ± standard deviation), sex and maturity stage (Sex M.), and stomach contents of total recaptured
tagged sea bass during the study period.
Fish
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Id-tag
0214
4885
0445
4115
4417
4866
0326
4257
4162
4019
4820
4108
4556
0194
4484
days a. r.
7
11
11
13
14
24
28
28
28
36
37
39
44
69
94
SL (cm)
26.2
31.1
28.5
28.5
25.5
27
29
30.4
27
-
W (g)
372
432
430
338
270
305
450
480
276
-
Sex M.
Male (I)
Male (II)
Male (II)
Male (I)
Male (I)
Male (I)
Male (II)
Male (II)
Male (I)
Male (I)
Stomach contents
Empty
Empty
Decapod juveniles (n=5; 0.3 g)
Empty
Particulate organic matter (0.6 g)
Food pellets (3 g)
Empty
Fish remains (0.9 g)
Polychaeta (0.1 g)
-
Figure 3.8. Number of tagged sea bass recaptures, and percentages, during the study period
Furthermore, coastal marine fish farms
attract a large range of predator species
(Beveridge 2001). High numbers of bluefish
(P. saltatrix) have been observed in the
vicinity of the study farms (FernandezJover et al. 2008; Arechavala-Lopez et al.
2010), either actively feeding on wild fish
aggregating around the cages or on farmed
fish within the cages (Sanchez-Jerez et al.
2008). In addition, it is also known the high
presence of fish-eating birds at farms and
their impacts (Melotti et al. 2004, 2008).
Thus, it is likely that the farms attract both
prey and predators, increasing the
predation pressure around farms. Even
though the swimming pattern of tagged
55
SEA BREAM AND SEA BASS ESCAPEES
and untagged fish did not differ markedly
immediately after release it is not unlikely
that some of the tagged fish could have a
reduced swimming capacity after release
and therefore be easier prey for predator
fish. Thus, the estimated mortality for
tagged fish could be higher than for
untagged fish. Studies in sea bass juveniles
showed similar patterns of antipredator
behaviour in both farmed and wild juvenile
individuals (Malavasi et al. 2004, 2008).
However, wild sea bass presented higher
reactivity to eel Anguilla anguilla predator
(Malavasi et al. 2004) and the mean freezing
duration in response towards visual and
mechanical
overhead
stimulus
was
significantly lower in hatchery-reared
juveniles (Malavasi et al. 2008). In addition,
Handelsman et al. (2010) reported a
relatively poorer sprint performance and
lower survival rates of cultured sea bass
compare with wild conspecifics against
avian predation in mesocosms, suggesting
that cultured sea bass would not fare well
in natural environments. Therefore, natural
predation immediately post-escape incident
seems to be important reducing the number
of escaped sea bass survivals.
Reliable knowledge about survival, and
particularly dispersion, habitat use, feeding
habits of farmed sea bass following an
escape incident in a coastal Mediterranean
farming area has been revealed in this
study. Indeed, it was shown that some
escaped sea bass are able to survive up to 3
months in the wild, moving to estuarine
areas and switching on natural preys.
Although the low average recapture rate
obtained in this study (1.26%) could
indicate a high predation pressure or lack
of capabilities to survive of escaped sea
bass similar recapture percentages were
found on hatchery-reared sea bass released
in the Adriatic Sea (0.45% in Grati et al.
2011), and in mark-recapture studies
carried out in European Atlantic coast on
wild sea bass (1.1% in Fritsch et al. 2007;
3.7% in Pickett et al. 2004; 4.5% in Pawson et
al. 2007; rarely more than 10% in other
studies, e.g. Kelley 1979). The recapture
rates could be regarded as minimum
estimates due either to loss of tags
(Sánchez-Lamadrid 2001) and to the fact
that fishermen preferred to keep the fish,
56
despite of being aware about the markrecapture program.
European sea bass is an important target
species for
both professional and
recreational fisheries. In other studies, the
tagged sea bass were occasionally caught
mainly using gillnets, trammel nets and
fishing rods in both in-shore and off-shore
waters (Pickett et al. 2004; Frisch et al. 2007;
Pawson et al. 2007; Grati et al. 2011).
However, the low number of recaptures by
local fisheries reported in this study
suggests either a low catch-ability of
escaped sea bass or high natural mortality
rates after release. However, despite of the
lack of captures from off-shore waters, it
cannot be ruled out the possibility that
tagged escaped sea bass dispersed from
Mediterranean farm facilities to deeper
waters where they are more difficult to be
captured by fisheries.
It is remarkable the fact that all recaptured
individuals in the present study were
caught by recreational fisheries with fishing
rods in the mouth of the Segura River
which flows into sea water through a small
harbour with estuarine conditions. That
means that escaped sea bass left the farm
facilities to move towards the inshore
shallower waters, especially river estuaries
or harbours. The same behaviour was
observed in Canary Islands, where escaped
sea bass were commonly found in shallow
coastal habitats, mainly in harbours,
marinas and artificial beaches, being more
abundant at zones near fish farms (ToledoGuedes et al. 2009). Grati et al. (2011)
reported that the majority of the hatcheryreared sea bass tagged and released in
artificial reefs were concentrated in the
estuaries and harbours. Similar results were
also found in tagged gilthead sea bream,
released both on farm facilities (see chapter
2-Arechavala-Lopez et al. 2012c) and on
artificial reefs (Sánchez-Lamadrid 1998,
2002; D'Anna et al. 2004).
Therefore, brackish waters and estuaries
seem to be particularly suitable habitat for
escaped sea bass, dwelling with their wild
conspecifics. European sea bass inhabits
coastal waters down to about 100 m depth,
although it is more common in shallow
waters like estuaries, lagoons, and tidal
CHAPTER 3
flats (Lloris 2002). Sea bass individuals less
than 36 cm length appear to remain in
inshore nursery areas to which they recruit
as post-larvae (Pawson et al. 1987; Jennings
and Pawson 1992), whereas sea bass greater
than 36 cm tend to emigrate and disperse
widely around the coast (Pickett et al. 2004).
Therefore, the presence of sea bass escapes
in shallow waters highlights the negative
interaction of habitat competition of
escaped sea bass with native fish
assemblages, especially if long-scale escape
incidents
occur.
Furthermore,
the
movement of sea bass escapees to
spawning grounds increases the risk of
mate competition and interbreeding with
wild conspecifics. Despite of the fact that all
recaptures were immature in the present
study, Toledo-Guedes et al. (2009) reported
a sea bass escapee of 51 cm having
developed female gonads (stage IV) at the
time of capture. Therefore, not only
escapees might mature in the wild if the
survive for long periods, but also matured
individuals can escape directly from farms.
Figure 3.9. Escaped sea bass and sea bream
captured by recreational fishermen with fishing
rods at a local harbour.
In addition, this inshore migration of
escaped sea bass could be due to the higher
availability of more suitable prey items in
shallow waters, mainly in estuarine areas.
European sea bass is an opportunistic
species, exhibits demersal behaviour, that
predate mainly on fish and benthic
crustaceans of both soft and hard-bottoms,
such as crabs and shrimps, but it can be
also found a variety of prey items
(Tortonese 1986). An extensive amount of
literature exists concerning wild sea bass
feeding, covering from the young to adult
stages of the species, mainly in the
estuarine systems of European Atlantic
(Kennedy and Fitzmaurice 1972; Fahy 1980;
Aprahamian and Barr 1985; Kelley 1987;
Pickett and Pawson 1994; Cabral and Costa
2001; Laffaille et al. 2001; Maes et al. 2003;
Hampel et al. 2005; Sá et al. 2006; Leitão et al.
2008; Martinho et al. 2008; Riley et al. 2011)
as well as in estuarine and lagoonal
Mediterranean regions (Ktari et al. 1978;
Barnabe 1980; Ferrari and Chieregato 1981;
Roblin and Brusle 1984; Kara and Derbal
1996; Rogdakis et al. 2010). However, there
is a lack of studies about the feeding habits
of escaped sea bass in the Mediterranean.
There is only one study reporting the diet
composition of hatchery-reared sea bass
released for re-stocking wild populations in
a Mediterranean coastal lagoon (Grati et al.
2011). In addition, González-Lorenzo et al.
(2005) and Toledo-Guedes et al. (2009)
reported the diet composition of farmed sea
bass escaped from fish farm in the Canary
Islands, where they are non-native species
In the present study, it was demonstrated
that farmed sea bass is able to switch on
natural preys once they escaped from a
Mediterranean farm, at least from the 13th
day after release. Although these data are
from a limited number of specimens the
results are in concordance with previous
cited studies on wild and escaped sea bass.
Decapod juveniles, fish remains and
polychaeta found in the stomachs of
recaptured sea bass were also found within
the natural diet of wild and released
hatchery-reared
sea
bass
in
a
Mediterranean coastal lagoon (Rogdakis et
al. 2010; Grati et al. 2011). Moreover, a wide
variety of finfish were reported as main
preferred prey for escaped sea bass in the
Canary Islands, but also crustaceans as
secondary common prey (GonzálezLorenzo et al. 2005; Toledo-Guedes et al.
2009). The presence of POM (oddments) in
the stomachs could be an indicative of the
aggressiveness on feeding behaviour of
escaped sea bass, switching for preys in
soft-bottoms. Moreover, food pellets in the
stomach could reveal a high affinity of
escapees for farm areas, but it is likely to be
from fish-baiting by recreational fishermen.
In
addition,
although
recaptured
individuals presented a high proportion of
57
SEA BREAM AND SEA BASS ESCAPEES
empty stomachs (44.4%), this percentage is
in concordance with other studies on
escaped sea bass in Canary Islands (66% in
González-Lorenzo et al. 2008; 50% in
Toledo-Guedes et al. 2009), but also on wild
sea bass from Atlantic and Mediterranean
populations (45% in Kelley 1987; 34.5% in
Rogdakis et al. 2010; 33% in Grati et al.
2011). Moreover, the diet composition of
wild sea bass presents strong differences
between fish size classes, mainly feeding on
benthic crustaceans (amphipods, shrimps
and crabs) when smaller sizes and being
more piscivorous (mostly fry and juveniles
finfish) in higher sizes, increasing their
trophic level (Rogdakis et al. 2010). In
agreement with Toledo-Guedes et al. (2009),
we can consider escaped sea bass in the
Mediterranean as an opportunistic species,
clearly able to exploit natural resources,
which could need some time for adaption
to new environmental conditions, but also
could become more piscivorous in larger
sizes.
58
In the current study, the deliberate releases
of tagged fish resemble small-scale
handling losses of fish from sea bass farms.
Our results thus might indicate that longterm ecological impacts of such escape
incidents might be relatively insignificant
due to the probable high mortalities of
escapees. However, it was evidenced the
potential risk of escaped sea bass on wild
assemblages through competition for
natural resources and predation on other
species, which could lead locally to serious
ecological problems if both massive escape
and/or large-size fish escape incidents
occurs, especially in coastal and estuarine
populations.
Nevertheless,
more
knowledge
regarding
survival
and
movements of escapees following largescale escape incidents is required to
evaluate the potentiality of such negative
ecological impacts due to escaped farmed
sea bass, as well as to improve the
management for recapture of escapees and
thereby reduce the risk potential of
intermingling with natural populations.
CHAPTER 4
4. DIFFERENTIATING THE WILD/FARMED ORIGIN OF SEA BREAM AND SEA BASS
4.1. Abstract
It is known that farmed individuals escape from farm facilities, but the extent of escape events
is not easy to report and estimate because of the difficulty to distinguish between wild and
farmed individuals. The environment in which farmed fish are raised differs vastly from that
experienced by their wild counterparts, since under farming conditions fish grow faster and
exist in stable environmental settings. This provides a prospect in utilizing these differences to
distinguish between farmed and wild Mediterranean species (i.e. sea bream and sea bass). The
study of weight-length relationships presented farmed individuals with higher values than
wild fish on both species, and significant differences provided through morphometry evidence
that the cranial and body regions of sea bream and sea bass are different regarding their farm or
wild origin at different scales. Additionally, differences in external characteristics of scales were
detected between origins. A high proportion of farmed sea bream presented regenerated
nucleus and scale malformations, and a complete lack of annual rings was found in the farmed
sea bass. Moreover, variation in otolith morphology was examined through shape descriptors
and elliptic Fourier descriptors (EFDs). Important differences were found within geographical
origins according to each shape descriptor separately and discriminant analysis with either all
shape descriptors together or EFDs were able to classify with high accuracy both sea bream and
sea bass according to their origin. Furthermore, farmed sea bream fins resulted more eroded
and splitted than wild sea bream fins, due to farming conditions within open-sea cages. Fin
condition values on sea bream escapees resulted to be between farmed and wild sea bream
values, which could indicate that farmed fish fins are recovered from farming abrasion along
the time once they are in the wildness. Any differences were found on sea bass fin erosion index
according to their farmed or wild origin. However, wild sea bass presented significantly more
splitted caudal fin than sea bass from farms and escapees. Therefore, the use of scale
characteristics is suggested to be the easiest and quickest way to distinguish farmed or escaped
fish within wild stocks. In addition, a multidisciplinary approach, with scales, morphological
variations on body and otoliths shapes or fins condition, seemed to be a valuable tool for
studying the biomass contribution of escapees to local habitats. This contribution could be
determined by identifying escaped individuals from fisheries landings as a first step to assess
the potential negative effects of fish farm escapees on the environment, and their contribution
on wild stocks and fisheries captures.
4.2. Introduction
It is well known that reared individuals
escape from farm facilities due to technical
and operational failures, and as it was
shown in previous chapters, the potential
for negative consequences to occur through
interbreeding, predation, competition or
transmitting pathogens to closely reared
and wild populations is significant. Because
of the difficulty in surveying directly the
escapes events and for a better
understanding of these potential negative
effects, it is imperative to distinguish and
quantify the number of individuals that
escape from sea-cages, aside from their
mobility, spatial distribution and survival
assessment. In hatcheries, fish grow faster
and frequently with different patterns and
environment than in the wild and this
phenomenon has been mainly utilized to
distinguish between wild and reared fish,
mainly in salmonids, with a relatively high
degree of certainty (see Fiske et al. 2005).
Such different developmental modifications
of body parts may exist also between wild
and farmed sea bream and sea bass in the
Mediterranean, given that they experience
large differences in feeding regimen and
environment (Grigorakis 2007). Moreover,
the presence of malformations or
morphoanatomical anomalies in reared sea
bream and sea bass has been widely
documented (Paperna 1978; Francescon et
al. 1988; Balebona et al. 1993; Boglione et al.
1993, 2001; Marino et al. 1993; Chatain 1994;
Koumoundourous et al. 1997; Loy et al.
1999, 2000; Afonso et al. 2000; Sfakianakis et
al. 2006).
61
SEA BREAM AND SEA BASS ESCAPEES
Besides morphological differences between
wild and farmed fish, several techniques
using scale and otolith patterns have been
developed with a relatively high degree of
certainty in several fish species (i.e. Antere
and Ikonen 1983; Ross and Pickard 1990;
Borzecka et al. 1990; Barlow and Gregg
1991; Lund and Hansen 1991; Hindar and
L´Abée-Lund 1992; Friedland et al. 1994;
Eaton 1996; Youngson et al. 1997, Hiilivirta
et al. 1998; Uglem et al. 2011). Furthermore,
the occurrence of fin erosion is substantially
greater in farming conditions than in the
natural environment, possibly due to the
unnatural densities, feeds provided, and
rearing environments (Mork et al. 1989;
Latremouille 2003; Ellis et al. 2008). The
presence of fin erosion has been used also
to determine whether the fish have farmed
or wild origins in several fish species (e.g.
Moring 1982; Bosakowski and Wagner
1994; Turnbull et al. 1996; Jobling et al. 1998;
Clayton et al. 1998; Smith 2003; Person-Le
Ruyet and Le Bayon 2009).
However, there is a lack of studies in the
Mediterranean Sea discriminating farmed
fish from wild stocks, neither through
morphometry,
scales
characteristics,
otoliths shape nor fin condition. Therefore,
the aims of this study were: (i) to assess the
body measures through somatometry and
morphometry which can discriminate
between farmed or wild origin for sea
bream and sea bass; (ii) to compare the
scales patterns and otolith shape from
farmed and wild sea bream and sea bass
through image-processing techniques, so as
to be able to discriminate between origins;
(iii) to evidence first differences in
erodibility of fins on sea bream and sea bass
according to their wild or farm origin; (iv)
to propose specific parameters which help
to develop new methods for the
identification of escapees, and could
therefore be used for studying their
contribution on local stocks and fisheries
landings.
4.3. Material and Methods
4.3.1. Fish Sampling
A total of 100 farmed sea bream and 100
farmed sea bass from 2 different Spanish
farms, and 100 wild sea bream and 100 sea
bream from 2 different fish markets, were
obtained during the period of July 2009–
June 2010 (Figure 4.1; Table 4.1). Moreover,
200 wild and farmed sea bream and 200
wild and farmed sea bass were obtained in
October 2009, from a single locality and a
single farm in Greece (Figure 4.1; Table 4.1).
In addition, 100 individuals from each
studied species were presumed to be
farmed escapees captured from local
fisheries in Spain, which were only used for
fin condition analysis since scales
methodology were applied to confirm their
farmed origin (Figure 4.1; Table 4.1).
Figure 4.1. Maps of the study areas in Spain and Greece, showing the wild and farmed fish sampling
localities.
62
CHAPTER 4
Table 4.1. Characteristics of sea bream and sea bass specimens used in this study.
Species
Locality
Origin
Sea bream
Spain
Wild
Farmed
Escaped
Wild
Farmed
Escaped
25.3-47.9
28.6-39.4
16.8-31.8
13.1-17.5
13.0-17.5
-
100
100
100
100
-
60
60
60
60
-
60
60
60
60
-
100
100
100
-
Wild
Farmed
Escaped
Wild
Farmed
Escaped
17.3-54.7
32.7-38.6
8.2-60.7
18.1-27.8
19.0-25.0
-
100
100
100
100
-
60
60
60
60
-
60
60
60
60
-
100
100
100
-
Greece
Sea bass
Spain
Greece
Ls range (cm)
4.3.2. Morphometry
The fish standard length (Ls) and total
weight (Wt) were measured to the nearest
millimetre and gram, respectively. The
relationship between Wt and Ls of farmed
and wild fish for each species were
estimated separately using the formula: Wt
= aLsb. Moreover, morphometric indices
such as Fulton’s Condition Index [K = 100 ×
total weight/(total length)3], Cephalic Index
[CI = (head length/total length)] and
Relative Profile Index [RP = (maximum
body height/total length)] were computed
from linear and weight measurements.
Each sea bream and sea bass was
photographed with a digital camera
(Canon® Powershot-G10) mounted on
tripod with a light source. A ruler was used
on each photograph to ensure correct
calibration in the following image
processing. Morphological landmarks were
selected to give a precise definition of the
fish morphology (Humphries et al. 1981;
Strauss and Bookstein 1982). Altogether 16
morphological landmarks on sea bream
(Figure 4.2; Table 4.2) and 17 morphological
landmarks on sea bass were used (Figure
4.3; Table 4.2), and they were placed using
the image processing programme ImageJ
(Abramoff et al. 2004), in which the
morphological landmarks are given as x
and y co-ordinates. This tool is called Truss
Network System (TNS) and covers the
entire fish in a uniform network which
should theoretically increase the likelihood
of extracting morphometric differences
within and between species. A regionally
unbiased
network
of
morphometric
measurements over the two-dimensional
Morphom.
Scales
Otoliths
Fins C.
outline of a fish should give more
information about local body differences
than a conventional set of measurements
(Strauss and Bookstein 1982; Bookstein
1982). A total of 31 morphological vectors
were selected among the landmarks on sea
bream and 30 morphological vectors on sea
bass (Table 4.2). The distances between the
landmarks were determined from their coordinates. The repeatability of all
measurements
was
determined
by
measuring 20 sea bream and 20 sea bass
from each group three different times. The
coefficient of variation (CV) ranged from
0.5 to2%, which indicates a high accuracy
and repeatability of this method.
Figure 4.2. The 16 landmarks and the distances
measured
which
were
used
for
the
morphological analysis on sea bream. The
morphometric traits described from the
landmarks are shown in Table 4.2. Solid lines:
Truss Network System; dotted line: additional
measurements. 1: tip of the premaxillary; 2:
point of maximum curvature in the head profile
curve; 3: anterior insertion of dorsal fin; 4:
posterior insertion of dorsal fin; 5: dorsal point
at least depth of caudal peduncle; 6: posterior
extremity of the lateral line; 7: ventral point at
least depth of caudal peduncle; 8: posterior
63
SEA BREAM AND SEA BASS ESCAPEES
insertion of anal fin; 9: anterior insertion of anal
fin; 10: anterior insertion of pelvic fin; 11:
insertion of the operculum on the profile; 12:
dorsal insertion of pectoral fin; 13: most anterior
point of the eye; 14: most dorsal point of the eye;
15: most posterior point of the eye; 16: most
ventral point of the eye.
Table 4.2. Morphological traits of sea bream and
sea bass measured from the landmarks in Fig.4.2
and Fig 4.3.
S.aurata
Code
D. labrax
Landmark
Code
Landmark
A1
1-2
A1
1-2
A2
2 - 10
A2
2 - 12
A3
10 - 11
A3
1 - 12
A4
1 - 11
B1
2-3
A5
1 - 10
B2
3 - 11
A6
2 - 11
B3
11 - 12
B1
2-3
B4
2 - 11
B2
3-9
B5
3 - 12
B3
9 - 10
C1
3-4
B4
2-9
C2
4 - 10
B5
3 - 10
C3
10 - 11
B6
3 - 11
C4
3 - 10
C1
3-4
C5
4 - 11
C2
4-8
D1
4-5
C3
8-9
D2
5-9
C4
3-8
D3
9 - 10
C5
4-9
D4
4-9
C6
4 - 10
D5
5 - 10
D1
4-5
E1
5-6
D2
5-7
E2
6-8
D3
7-8
E3
8-9
D4
4-7
E4
5-8
D5
5-8
E5
6-9
E1
5-6
F1
6-7
E2
6-7
F2
7-8
F1
1 - 12
F3
1 - 13
F2
11 - 12
F4
7 - 13
F3
6 - 12
Eye L
14 - 16
Eye L
13 - 15
Eye H
15 - 17
Eye H
14 - 16
SL
1-7
SL
1-6
An analysis of variance (ANOVA) of a
univariate General Lineal Model (uGLM,
95% C.I.) was used to test for differences
within each species on fish standard length
and total weight using origin (Or: wild and
farm) and countries (Co: Spain and Greece)
as independent variables. When significant
differences were detected for a given factor,
64
the source of differences was identified
using SNK test. An analysis of covariance
(uGLM, 95% C.I.; covariable: Ls) was also
used to test for differences on W-L
relationships according to fish origin. In
order to avoid the effect of the different
specimen’s lengths in the study, all
morphological traits were size adjusted
using the method described by Reist (1985),
because heterogeneity in size among
samples
produces
heterogeneity
in
measurements. These transformations were
done separately for the different group
analysis (Spain, Greece and both together
Spain-Greece) to avoid interference from
the other groups. All the size-correlated
traits were standardized to a mean of zero
and a standard deviation of 1.
Figure 4.3. The 17 landmarks and the distance
measured which were used for morphological
measurement on sea bass. The morphological
traits described from the landmarks are shown
in Table 4.2. Solid lines: Truss Network System;
dotted line: additional length measures. 1: tip of
the premaxillary; 2: point of maximum
curvature in the head profile curve; 3: anterior
insertion of the first dorsal fin; 4: anterior
insertion of the second dorsal fin; 5: posterior
insertion of the second dorsal fin; 6: dorsal point
at least depth of caudal peduncle; 7: posterior
extremity of the lateral line; 8: ventral point at
least depth of caudal peduncle; 9: posterior
insertion of anal fin; 10: anterior insertion of anal
fin; 11: anterior insertion of pelvic fin; 12:
insertion of the operculum on the profile; 13:
dorsal insertion of pectoral fin; 14: most anterior
point of the eye; 15: most dorsal point of the eye;
16: most posterior point of the eye; 17: most
ventral point of the eye.
Multivariate statistics (SPSS, version 15.0
for Windows) were used to test for intraand inter-groups variation. Statistical
differences
for
size
and
all
the
morphometric indices among groups was
tested by ANOVA at P<0.05. A principal
component analysis (PCA), with varimax
CHAPTER 4
rotation was selected because the rotation
minimizes the number of variables that
have high loadings on a factor. All PCAs
with eigenvalue >1.00 were considered as
important (Chatfield and Collins, 1983) and
variables were tested by ANOVA at P<0.05.
Discriminant analyses were then used to
test for group membership. The different
discriminant functions are hereafter
described as DC1, DC2, etc. ANOVA was
used to test if there were differences in
morphological traits between the wild and
the farmed sea bream and sea bass
respectively. All statistical analysis were
carried out with SPSS (15.0) software.
4.3.3. Scales sampling and patterns
Scale samples were removed from under
the anterior dorsal fin. At least 5 scales from
individual were selected, cleaned and
mounted dry between two glasses slides
and examined and photographed under
binocular stereoscope (Leica® MZ-9.5; 16x)
for further image-processing analysis
(Figure 4.4). Scale pictures were captured
with a Canon (Powershot-S70®, 7.1
Megapixels) digital camera, and scale
radius (distance from the nucleus to the
edge) was measured using the ImageJ 1.42
software. Number of sclerites was
measured from each sample following the
methodology described by Lancelotti et al.
(2003) based on density differences between
scale circuli or esclerites within each scale,
with the number of annuli also measured
when possible. Regenerated nuclei and
deformed scales were also quantified from
each individual (Figure 4.4).
Two readers examined scales and identical
counts were obtained in 97% and 98% of
the sampled sea bream and sea bass
respectively. An analysis of covariance
(uGLM, 95% C.I.; covariable: Ls) was also
used to test for differences on scale
measurements according to fish origin.
Linear regression relationships were
determined between each of the different
measured scale parameters (as dependent
variables) and fish Ls (as the independent
variable). An analysis of the residual sum of
squares (ARSS) was used to compare the
wild and farmed resulting equations from
linear regression relationships (Chow 1960).
Figure 4.4. Wild and farmed sea bream and sea
bass scales. A: wild sea bream scale of fish
Ls=18.3 cm; B: farmed sea bream scale of fish
Ls=18.1 cm with regenerated nucleus; C: wild
sea bass scale of fish L=22 cm; D: farmed sea
bass scale of fish Ls=20.1 cm without clear
annual rings.
4.3.4. Otoliths sampling and
measurements
Both sagitta otoliths were removed from
individuals and used to estimate the
number of annual increments on both
transverse sections and whole nonsectioned otoliths. Left sagitta otoliths from
specimens were collected, immersed in 1:1
solution of glycerine-alcohol, positioned
with the sulcus acusticus facing up and the
rostrum to the upper side, and
photographed under a binocular steroscope
(Leica® MZ-9.5; 16x) using reflected light
and a dark background with a millimetric
scale (Figure 4.5). Otolith digital images
were captured using a Canon (PowershotS70®, 7.1 Megapixels) digital camera for
further image processing analysis with
ImageJ software.
Otolith shape descriptors were measured
from each otolith: Area (mm2), Perimeter
(mm), Circularity (4πArea/Perimeter2),
Roundness (4Area/πMajor axis), Aspect
Ratio (OH/OL=Major axis/minor axis) and
Otolith weight (OW, mg). Moreover, a
closed-form Fourier analysis (Younker and
Ehrlich 1977; Kuhl and Giardina 1982;
Lestrel 1997) was applied to the twodimensional projection of the distal side of
65
SEA BREAM AND SEA BASS ESCAPEES
the otolith. This method decomposes the
irregular shape of the contour into a series
of orthogonal terms called the elliptic
Fourier descriptors (EFDs) or harmonics.
The harmonics are a series of sine and
cosine curves that are generated by taking a
Fourier expansion of radius vectors drawn
from the centroid of the object as a function
of the phase angle, resulting in a series of
sine and cosine curves (Younker and
Ehrlich 1977; Bird et al. 1986). The SHAPE
program developed by Iwata and Ukai
(2002) was used to extract the contour
shape of the otoliths and to evaluate
biological contour shapes based on the
EFDs. The programs included in SHAPE
can be used on image processing (namely
contour recording and derivation of EFDs),
on principal component analysis (PCA) of
EFDs, and on the visualisation of shape
variations estimated by the principal
components (Iwata and Ukai 2002). All
otolith shape descriptors were normalized
to a standard one, to carry out
morphometrical analyses and avoid
allometric effects, taking into account the
allometric relationship as was suggested by
Lleonart et al. (2000). For each morphologic
measurement the allometric relationship
with Ls was calculated. The equation used
was the standard Y=aXb, fitted using a
logarithmic transformation to homogenize
the residuals. Each measurement Y was
transformed into Z using the formula
Z=Y(X0/X)b, where X is the fish length Ls,
X0 is the mean Ls of all individuals within
each studied group and species (Lleonart et
al. 2000). An ANOVA (uGLM, 95% C.I.) and
SNK post-hoc test were also applied to test
for differences among origins and countries
on normalized otoliths shape descriptors.
Canonical discriminant function analysis
was used to determine the efficacy of the
measured
otoliths
variables
(shape
descriptors and EFDs) to discriminate
between wild and farmed individuals. All
statistical analysis were carried out with
SPSS (15.0) software.
Figure 4.5. Example of otoliths and shape contours of wild sea bream (A, Ls=36.4cm), farmed sea bream
(B, Ls=32.1cm), wild sea bass (C, Ls=24.9cm) and farmed sea bass (D, Ls=35.7cm).
4.3.5. Fin condition
Fin condition can be measured by different
ways according to the type of erosion the
fin presents (Figure 4.6). In this study, fin
erosion was determined for all fins
according to the Person-Le Ruyet and Le
Bayon (2009) fin erosion scale, which
quantify the progressive loss in fin area for
sea bass juveniles and adults. This index is
a numerical system based on a visual
66
assessment of fin condition of all fins on a
scale from 0 (perfect fin) to 4 (short and
dysfunctional fin). The anterior area of
dorsal fin on sea bream and the anterior
dorsal fin on sea bass were excluded from
erosion assessment because they are
usually damaged by handling and therefore
difficult to assess (Person-Le Ruyet and Le
Bayon 2009). The erosion parameters were
calculated from erosion levels of all fins as
follows: Fin Erosion Index (FEI), mean
CHAPTER 4
erosion level of the 5 fins and each fin
separately of all fish sampled per fish
origin; Fin Splitting Index (FSI), mean
number of splits per fish calculated for all
fins and specific fins separately of all fish
sampled per fish origin. Moreover, the
relative frequency of the erosion and
splitting levels recorded in all fins and each
fin separately of all fish examined per fish
origin was calculated. The reproducibility
and objectivity of these methods were
assessed by conducting inter- and intraoperator tests on all the same individuals.
Two independent assessments were made
by the same two trained operators.
Univariate General Linear Model (uGLM;
covariable: fish standard length; pvalue<0.05) was used to test if there were
differences
in
erosion
parameters
(dependant variable) among fish origins
(fixed factors). The Student-Newman-Keuls
(SNK)
test
for
post-hoc
multiple
comparisons were applied when necessary.
Discriminant analyses were then used to
test for group membership according to fin
erosion parameters.
Figure 4.6. Example of different caudal fin erosions (low, frayed and splitted) in sea bream (A,B,C) and sea
bass (D,E,F).
4.4. Results
4.4.1. Morphological differences
Sea bream and sea bass individuals used in
this study showed significant differences in
Ls and Wt, where fish from Spain presented
higher values than fish from Greece for
both origins and species (uGLM, p<0.001).
Moreover, sea bream Ls and Wt values
from wild individuals were significantly
higher than those from farmed fish in Spain
(SNK test, p<0.001), but there were no
differences in Greece (SNK test, p>0.05). In
sea bass, Ls values were higher for wild fish
than for farmed fish in both countries (SNK
test, p<0.05), but there were no differences
on Wt values (SNK test, p>0.05). The
relationship between Ls and Wt was
calculated for both species according to
different origin (Figure 4.7). The resultant
equation for wild sea bream was
W=0.0198L2.988 (r2=0.997) and for farmed sea
bream was W=0.0037L3.623 (r2=0.989). The
analysis of covariance revealed significant
differences not only in the covariable
67
SEA BREAM AND SEA BASS ESCAPEES
(uGLM, Ls: p<0.001), but also in the
interaction of both main factors (uGLM, Or
x Co: p<0.001) where differences between
origins were significant in Spain. Thus,
such differences between wild and farmed
fish increased with fish size (Figure 4.7a).
The equation for wild sea bass was
W=0.0035L3.413 (r2=0.955), and for farmed
sea bass was W=0.0009L3.866 (r2=0.992).
Analysis of covariance in sea bass also
showed an interaction of both main factors
(uGLM, Or x Co: p<0.001), where variation
between wild and farmed fish were
significant in Spain (Figure 4.7b).
Fulton’s Condition Index (K) revealed
significant differences between wild and
farmed individuals of both studied species
(ANOVA; P≤0.01) with the farmed fish
exhibiting the highest values (Figure 4.8).
Cephalic
Index
(CI)
values
were
significantly different in sea bass (ANOVA;
P≤0.05), where wild fish showed the
highest values in both countries; but there
were no significant differences between
wild and farmed sea bream specimens
(ANOVA; P>0.05; Figure 4.8). However,
values of Relative Profile Index (RP) were
significantly different among sea bream
from different origins (ANOVA; P≤0.05),
where farmed fish showed higher values
than wild fish, while there were no
differences for sea bass in both countries
(ANOVA; P>0.05; Figure 4.8).
Figure 4.7. Weight-Length relationship of farmed and wild sea bream (A) and sea bass (B). Grey circles:
farmed fish; black squares: wild fish; straight line: linear regression of farmed fish; dotted line: linear
regression of wild fish.
Figure 4.8. Morphometric indices of wild (W) and farmed (F) sea bream and sea bass from Spain and
Greece. Bars show mean values ± standard deviation.
68
CHAPTER 4
Results evidenced clear differences between
wild and farmed fish, mainly on the cranial
and body regions, for both sea bass and sea
bream. A combination of 5 principal
components explained as much as 87.03%
of the variation of size-adjusted bodymorphology variables for Spanish sea
bream (ANOVA, P≤0.01; Table 4.3). In case
of Greece, 8 principal components
explained as much as 85.69% of this
variation in sea bream, but only 4 with
significant differences (ANOVA, P≤0.01;
Table 4.3).
Since there were only two groups from
Greece, the discriminant analysis gave only
one function and it was therefore not
possible to plot the relationship between
components. However, classification score
for the discriminant analysis resulted in
98% of wild fish and 99% of farmed fish
from Greece being correctly classified.
Comparisons between wild and farmed sea
bream according to their Spanish or Greek
origin showed clear differences for almost
all of the taken measurements (Figure 4.9b).
Nonetheless,
discriminant
analysis
exhibited that around 3% of wild
individuals, both from Greece and Spain,
could be of cultivated origin (Table 4.4). It is
remarkable
that
these
individuals
presented high indices values. The
differences in morphological traits were
significant (ANOVA, P≤0.05) for all
discriminant functions for all groups, and
could be explained by the group origin
(Wilks`s λ, ANOVA, P≤0.01; Table 4.5).
In both countries, the most important
differences were located in the anterior
body portion, principally in head
measurements
and
body
height.
Discriminant analysis presented four
differentiated groups in Spain, belonging to
the two fish farms and two control localities
(Figure 4.9a). Two percent of wild fish were
not adequately assigned, which may
indicate a cultivated origin, while 100% of
the farmed fish were correctly classified.
Table 4.3. Component loadings, per cent of variance (%V) and eigenvalues (Eigen.) for the principal
components (with varimax rotation) in the Spain and Greece groups analyses for sea bream. Components
with significant differences (ANOVA; P ≤ 0.05) in morphological traits between farmed and wild sea
bream are marked in bold (see Table 2 for definition of characters)
Eye H
B2
B5
A6
C4
A5
A4
B6
B4
C6
B3
B1
A2
C5
F1
C2
D4
E2
D2
D5
C3
D3
D1
F2
C1
A1
F3
A3
E1
Eye L
%V
Eigenv.
Anova
PC1
0.954
0.920
0.920
0.907
0.879
0.869
0.866
0.866
0.855
0.850
0.827
0.818
0.808
0.802
0.795
0.767
0.756
0.754
0.752
0.750
0.729
0.725
SPAIN
PC2
PC3
PC4
PC5
-0.661
0.477
0.628
0.430
0.484
0.463
0.517
0.594
30.03
9.01
<0.01
20.52
6.15
<0.01
16.51
4.95
<0.01
14.81
4.44
<0.01
5.17
1.55
<0.01
A5
A3
A2
B5
B6
D2
F1
F2
B4
A6
B3
C1
C4
B2
B1
C3
C5
F3
C6
D3
D5
C2
E2
E1
Eye L
Eye H
A4
D4
D1
A1
PC1
0.859
0.849
0.848
0.823
0.708
0.661
0.660
0.652
0.639
0.524
0.516
PC2
PC3
GREECE
PC4
PC5
PC6
PC7
PC8
0.878
0.853
0.739
-0.557
0.897
0.830
0.614
0.574
0.868
0.844
0.525
0.831
0.813
0.850
0.723
0.596
0.746
0.832
0.861
24.18
7.25
<0.01
11.12
3.34
<0.01
10.93
3.28
<0.01
10.07
3.02
0.61
8.93
2.68
0.16
8.56
2.57
0.92
6.67
2.01
<0.01
5.22
1.59
0.82
69
SEA BREAM AND SEA BASS ESCAPEES
Figure 4.9. Scatterplots of functions 1 and 2 for: A) the discriminant analysis at Spain group including the
two locations of farmed sea bream and the two localities of wild sea bream; and B) the discriminant
analysis including the groups of farmed and wild sea bream from Spain and Greece.
Table 4.4. Inter-group classification score result (in per cent) for the discriminant analysis of the four
groups of sea bream
Sparus aurata
Origin group
(%)
SPAIN
Group
Spain Farmed
Spain Wild
Greece Farmed
Greece Wild
Farmed
100
3
0
0
GREECE
Wild
0
97
0
0
Farmed
0
0
98
3
Wild
0
0
2
97
Total
100
100
100
100
Table 4.5. Data from the intra- and inter-groups discrimination analyses. The groups of sea bream were
classified from these functions (F) in the discriminant analysis.
Spain
Spain
Spain
Greece
F
1
2
3
1
Eigenvalue
10.849
5.132
0.555
4.975
Per cent
variance
65.6
31.0
3.4
100.0
Cumulative
variance
65.6
96.6
100.0
100.0
Canonical
correlation
0.957
0.915
0.598
0.912
Wilk`s λ
0.009
0.105
0.643
0.167
X2
884.059
421.750
82.608
327.129
d.f.
60
38
18
30
P
<0.001
<0.001
<0.001
<0.001
Spain-Greece
Spain-Greece
Spain-Greece
1
2
3
1695.914
5.206
3.057
99.5
0.3
0.2
99.5
99.8
100.0
1.000
0.916
0.868
0.000
0.040
0.247
4073.060
1232.292
534.946
90
58
28
<0.001
<0.001
<0.001
Significant differences in morphological
traits between wild and farmed sea bass in
Spain were described by 2 components in
the PCA analysis which explained 86.47%
of the variation (ANOVA, P≤0.01; Table
4.6). First component principally correlated
with longitudinal and transversal body
measurements, while head and eye
measurements were most representative for
the second component. Variation in
morphological traits between farmed and
wild sea bass from Greece was explained
by 5 principal components (80.12%) but
only 3 of them presented significant
70
differences (ANOVA, P≤0.05; Table 4.6).
These differences were mainly due to eye
and head measurements (PC1) and some
transversal body measurements (PC2).
Discriminant analysis plot for Spanish sea
bass groups illustrated a pronounced
variation in the morphological traits
between wild and farmed fish, where the
two locations of farmed fish were more
similar between them, and the two wild
groups
were
considerably
more
heterogeneous (Figure 4.10a). However, the
2% of wild fish from Spain were not
correctly classified, whereas 100% of the
CHAPTER 4
farmed fish were correctly assigned. Since
there were only two groups of sea bass
from Greece, the discriminant analysis gave
only one function and it was therefore not
possible to plot the relationship between
components.
However,
discriminant
analysis correctly grouped the 100% of
individuals within their respective group.
When comparing morphological traits for
sea bass from Spain and Greece together,
significant differences were explained by 2
principal components (93.52%; ANOVA,
P≤0.01). Body measurements were mainly
located on the first component (PC1:
56.2%), while head and eyes measurements
were more important in the second one
(PC2: 37.2%). The first two resulting
functions from discriminant analysis
explained 70.4% and 23.1% of the variation,
respectively (Table 4.7); and the differences
in morphological traits were significant
(Wilks`s λ, ANOVA, P≤0.01; Table 4.7).
Plotting these two functions, the first one
grouped the sea bass according to their
geographical origin, while the second
function grouped the samples according to
their wild or farm origin (Figure 4.10b).
Moreover, 98% and 99% of reared sea bass
from Spain and Greece were respectively
correctly grouped (Table 4.8). Furthermore,
88% of wild sea bass from Spain were
correctly assigned, but 5% and 7% were
assigned to Greek and Spanish farm origin.
Only 1% of wild sea bass from Greece were
not correctly grouped (Table 4.8).
Table 4.6. Component loadings, per cent of variance (%V) and eigenvalues for the principal components
(with varimax rotation) in the Spain and Greece groups analyses for sea bass. Components with significant
differences (ANOVA; P ≤ 0.05) in morphological traits between farmed and wild sea bass are marked in
bold (see Table 4.2 for definition of characters).
F4
E4
D2
C2
C5
E3
C4
D4
E5
D5
C3
B2
E1
E2
C1
B5
D1
B1
B3
D3
B4
F3
A3
A1
Eye L
A2
F2
Eye H
F1
%V
Eigenv.
ANOVA
SPAIN
PC1
0.945
0.905
0.890
0.887
0.885
0.884
0.875
0.872
0.867
0.859
0.855
0.851
0.847
0.839
0.835
0.815
0.812
0.787
0.771
0.756
0.697
PC2
0.919
0.914
0.853
0.830
0.800
0.695
0.685
0.632
57.72
16.74
<0.01
33.75
9.79
<0.01
F3
Eye L
A3
A2
Eye H
B4
D5
B3
F2
F4
F1
C1
A1
D3
C5
E2
D1
C2
D4
C4
B2
C3
E4
E1
E3
D2
E5
B1
B5
PC1
0.904
0.805
0.801
0.729
0.725
0.692
0.543
0.419
GREECE
PC2
PC3
PC4
PC5
0.724
0.675
0.671
0.664
-0.655
0.583
0.554
0.491
0.780
0.748
0.712
0.627
0.597
0.581
0.907
0.885
0.659
0.626
0.516
0.758
0.687
22.64
6.56
<0.01
18.01
5.22
<0.01
16.01
4.64
0.24
14.98
4.34
0.11
8.48
2.46
0.03
71
SEA BREAM AND SEA BASS ESCAPEES
Figure 4.10. Scatterplot of functions 1 and 2 for: A) the discriminant analysis at Spain-group including the
two locations of farmed sea bass and the two localities of wild sea bass; and B) the discriminant analysis
including the groups of farmed and wild sea bass from Spain and Greece: Spain Farmed: white circle;
Spain Wild: white triangle; Greece Farmed: black star; Greece Wild: grey pentagon.
Table 4.7. Data from the intra- and inter-groups discrimination analyses. The groups of sea bass were
classified from these functions (F) in the discriminant analysis.
Group
Spain
Spain
Spain
Greece
F
1
2
3
1
Eigenvalue
4.405
.930
.348
7.596
Per cent
variance
77.5
16.4
6.1
100.0
Cumulative
variance
77.5
93.9
100.0
100.0
Canonical
correlation
0.903
0.694
0.508
0.940
Wilk`s
λ
0.071
0.384
0.742
0.116
X2
485.064
175.457
54.848
394.768
d.f.
81
52
25
29
P
<0.001
<0.001
<0.001
<0.001
Spain-Greece
Spain-Greece
Spain-Greece
1
2
3
9.818
3.227
0.908
70.4
23.1
6.5
70.4
93.5
100.0
0.953
0.874
0.690
0.011
0.124
0.524
1709.278
798.482
247.106
87
56
27
<0.001
<0.001
<0.001
Table 4.8. Inter-group classification score result (in per cent) for the discriminant analysis of the four
groups of sea bass.
Dicentrarchus labrax
SPAIN
Group
Farmed
Wild
Farmed
Wild
Origin group
Spain Farmed
98
2
0
0
100
(%)
Spain Wild
7
88
5
0
100
Greece Farmed
0
0
99
1
100
Greece Wild
0
1
0
99
100
4.4.2. Scales characteristics
Despite the easy readability of scale
parameters in almost all the wild sea bream
(99%), the high presence of regenerated
nuclei (98% of individuals) and malformed
scales (73% of studied scales) in farmed
individuals prevented the measurements of
scale radius and number of sclerites and
annulis in farmed fish scales (Figure 4.4a,
b). Therefore, scale parameters were not
possible to be compared between wild and
farmed sea bream. Regarding scale
72
GREECE
Total
parameters in sea bass, a number of annuli
were clearly observed in 100% of wild
individuals (Figure 4.4c) but could not be
measured in farmed individuals due to the
absolute lack of such annual deposition in
their
scales
(100%;
Figure
4.4d).
Nonetheless, mean scale radius (±sd) in
wild and farmed sea bass were 3.17±1.07
mm and 3.13±0.81 mm respectively. Mean
number of sclerites (±sd) in sea bass were
132.53 ±35.92 in wild fish and 147.63 ±25.67
in farmed fish. Despite not being corrected
for fish length, as significant interactions
CHAPTER 4
between both dependent variables and Ls
were found (uGLM, Ls: p<0.001), both scale
radius and number of esclerites were
positively associated with each other and
with fish length in wild and farmed sea
bass, whilst being well described by the
linear regression model (Figure 4.11). Scale
radius-Ls
presented
similar
linear
regression between wild and farmed fish
(Figure 4.11a; wild: r2=0.719; farmed:
r2=0.796) but statistical differences were not
found through ARSS (F=0.082<F2,239,0.01). In
contrast, esclerites number in farmed fish
presented higher values than wild fish
according to both Ls (Figure 4.11b; wild:
r2=0.335;
farmed:
r2=0.649;
F=9.179
>F2,239,0.01) and scale radius (Figure 4.11c,
wild: r2=0.368; farmed: r2=0.818; F=13.106
>F2,239,0.01).
Figure 4.11. Linear regression of sea bass scale
radius-fish length (A), sclerite numbers-fish
length (B), and scale radius-esclerite number (C).
Grey circles: farmed sea bass; black triangles:
wild sea bass; straight line: linear regression of
farmed sea bass; dotted line: linear regression of
wild sea bass.
4.4.3. Otoliths shape
Otoliths from wild fish of both sea bream
and sea bass species showed a clear
seasonal pattern, with alternating opaque
and translucent zones, which allowed the
age classification of wild specimens. In
contrast, otoliths from farmed fish were
completely opaque or having one or more
translucent zones closed to the edge, and
therefore age groups for farmed fish were
impossible to determine.
Following length standardization of shape
descriptors, differences were found for each
parameter for both species. For sea bream,
the otolith area, perimeter, roundness,
OH/OL ratio, and weight showed a
significant interaction between countries
and origins (uGLM, Co x Or: p<0.01; Figure
4.12). However, otolith circularity from
Greek samples presented significantly
higher values than Spanish individuals
(uGLM, Co: p<0.01; Figure 4.12). For sea
bass, analyses showed an interaction
between otolith parameters, such as area,
perimeter and circularity, and both country
and origin factors (uGLM, Co x Or: p<0.01);
while otolith roundness, OH/OL ratio and
weight presented differences only between
studied countries (uGLM, Co: p<0.01;
Figure 4.13).
Despite the fact that dissimilarities were
found mainly according to geographical or
size differences, otolith parameters were
included together in further discriminant
analysis because of the interesting variation
observed. Therefore, two main groups of
sea bream were distinguished by the
discriminant analysis with all shape
descriptors, where the first function
separated the fish from Spain from those
from Greece (Figure 4.14a). The first
canonical discriminant function explained
98.7% of total variance (Eigenvalue =
49.057; Wilk`s lambda = 0.012; p<0.001)
while the second accounted for 1.2%
(Eigenvalue = 0.613; Wilk`s lambda = 0.595;
p<0.001). The cross-validation procedure
correctly classified the 89.5% with shape
descriptors (Table 4.9), where fish from
Spain were better classified into different
origin (farmed: 100%; wild: 90.3%) than fish
from Greece (farmed: 80.6%; wild: 87.1%).
In contrast, three main groups were
distinguished
with
EFDs
by
the
discriminant analysis: wild and farmed fish
from Greece closely grouped, and both
wild and farmed fish from Spain separately
(Figure 4.14b). The first canonical
73
SEA BREAM AND SEA BASS ESCAPEES
discriminant function explained 55.3% of
total variance (Eigenvalue = 6.090; Wilk`s
lambda = 0.013; p<0.001), the second
accounted for 31.4% (Eigenvalue = 3.457;
Wilk`s lambda = 0.091; p<0.001) and the
third for 13.3% (Eigenvalue = 1.471; Wilk`s
lambda = 0.405; p<0.001). The crossvalidation procedure correctly classified the
95.7% with EFDs, with similar percentages
among the four groups (Table 4.9).
Discriminant analysis of all shape
descriptors on sea bass distinguished three
main groups of individuals, which were
wild and farmed fish from Spain
separately, and wild and farmed fish from
Greece together (Figure 4.15a). The first
canonical discriminant function explained
62.3% of total variance (Eigenvalue = 4.160;
Wilk`s lambda = 0.042; p<0.001), the second
function 29.8% (Eigenvalue = 1.989; Wilk`s
lambda = 0.218; p<0.001), and the third
accounted for 8% (Eigenvalue = 0.533;
Wilk`s lambda = 0.652; p<0.001). The crossvalidation procedure correctly classified the
93.2% of sea bass with shape descriptors
(Table 4.10), where farmed individuals
from Greece presented the lowest
classification percentages (85%), and
farmed fish from Spain the highest values
(100%). Regarding discriminant analysis
with EFDs, four main groups were
distinguished (Figure 4.15b) and the 95.2%
of individuals were correctly classified
through cross-validation procedure, with
similar percentages among groups (Table
4.10). The first canonical discriminant
function explained 41.6% of total variance
(Eigenvalue = 3.439; Wilk`s lambda = 0.021;
p<0.001), the second accounted for 40.3%
(Eigenvalue = 3.326; Wilk`s lambda = 0.093;
p<0.001) and the third for 18.1%
(Eigenvalue = 1.494; Wilk`s lambda = 0.401;
p<0.001).
Figure 4.12. Box plots (― : median, □ : 25-75% percentiles; ┬,┴ : highest and lowest values) of standard
leght (Ls) standardized otoliths variables (Z-values) for wild and farmed Sparus aurata according to farm
and wild origin within each country. OH: otolith height; OL: otolith length; OW: otolith weight. SNK
values following significant differences in the interaction of both factors through ANOVA are shown with
different lower case letters within each box plot (p < 0.05).
74
CHAPTER 4
Figure 4.13. Box plots (― : median, □ : 25-75% percentiles; ┬,┴ : highest and lowest values) of standard
leght (Ls) standardized otoliths variables (Z-values) for wild and farmed Dicentrarchus labrax according to
farm and wild origin within each country. OH: otolith height; OL: otolith length; OW: otolith weight. SNK
values following significant differences in the interaction of both factors through ANOVA are shown with
different lower case letters within each box plot (p < 0.05).
Figure 4.14. Plot of first and second discriminate functions of the discriminate analysis for wild and
farmed sea bream from both studied countries. A: otolith shape descriptors; B: elliptical Fourier
descriptors (EFDs).
75
SEA BREAM AND SEA BASS ESCAPEES
Table 4.9. Discriminate analysis classification with the cross-validation testing procedure, expressed in
percentages for wild and farmed sea bream from both studied countries. A: otolith shape descriptors
(correctly classified: 89.5%); B: elliptical Fourier descriptors (EFDs; correctly classified: 95.7%).
A)
Farm
Wild
Spain
Greece
Spain
Greece
Predicted Group Membership (%)
Farm
Wild
Spain
Greece
Spain
Greece
100
0
0
0
0
80.6
0
19.4
9.7
0
90.3
0
0
12.9
0
87.1
N
60
45
60
45
B)
Farm
Wild
Spain
Greece
Spain
Greece
96.9
0
3.1
1.8
0
95.6
0
3.6
3.1
0
95.4
0
0
4.4
1.5
94.6
60
45
60
45
Figure 4.15. Plot of first and second discriminate functions of the discriminate analysis for wild and
farmed sea bass from both studied countries. A: otolith shape descriptors; B: elliptical Fourier descriptors
(EFDs).
Table 4.10. Plot of first and second discriminate functions of the discriminate analysis for wild and farmed
sea bass from both studied countries. A: otolith shape descriptors (correctly classified: 93.2%); B: elliptical
Fourier descriptors (EFDs; correctly classified: 95.2%).
Spain
Greece
Spain
Greece
Predicted Group Membership (%)
Farm
Wild
Spain
Greece
Spain
100
0
0
0
85
0
0
2.6
92.3
0
5
5
Greece
0
15
5.1
90
N
60
40
60
40
Spain
Greece
Spain
Greece
95.1
0
2.5
0
0
0
2.5
96.1
60
40
60
40
A)
Farm
Wild
B)
Farm
Wild
76
0
94.4
0
0
4.9
5.6
95
3.9
CHAPTER 4
6.4.4. Fins condition
Identical counts were obtained in 96% and
97% of the sampled sea bream and sea bass
respectively between two trained operators.
Analysis of variance (uGLM) showed no
significant differences among the 3
different fish origins according to the fish
size (Ls). For sea bream, no differences
were found on Fin Erosion Index (FEI) and
Fin Splitting Index (FSI) on sea bream
according to fish standard length (uGLM,
p-value>0.05). However, FEI revealed
significant differences on sea bream
according to fish origin not only for all fins
but also within each specific fin (uGLM, pvalue<0.01; Figure 4.16a). Farmed sea
bream showed the highest values of fin
erosion, followed by escapees, both further
than wild fish. Similar results were found
on dorsal, caudal and pectoral fins, being
the latter two the most eroded on farmed
fish. Anal and pelvic fins on farmed and
escaped fish presented similar erosion, both
significantly different from wild fin fish
(Figure 4.16a). FSI on sea bream presented
significant differences for all fins and
specific fins separately (uGLM, pvalue<0.01; Figure 4.16b). Mean erosion
values for all fins showed the highest
splitting values on escaped sea bream and
the lowest on wild fish. Splitting on dorsal
and anal fins were similar on farmed and
wild sea bream but significant different
from wild fish. Caudal and pelvic fins were
the most splitted on escapees while pectoral
fin was on farmed fish (Figure 4.16b). In
terms of occurrence, the lowest values of fin
erosion and fin splitting were more
frequent on wild sea bream (Figure 4.17a).
Farmed fish presented the highest values
on fin erosion (Figure 4.17a), while the
highest values of fin splitting were more
frequent on both farmed and escaped sea
bream (Figure 4.17b). Discriminant analysis
showed an 87.6% correctly classified with
FEI, being the 3 different groups well
defined in the scatterplot (Table 4.11, Fig.
4.18a). Conversely, only the 69.9% were
correctly classified with FSI, being the 75%
of wild fish correctly grouped, the 72% of
farmed fish and 63% of escapees (Table
4.11, Fig. 4.18b).
Figure 4.16. Mean fin erosion index (A) and fin splitting index (B) values on sea bream fins according to
fish origin. Black columns: wild fish; white columns: farmed fish; grey columns: escaped fish. Bars show
mean standard errors (±SE). Values with different letters at the same group of columns are significantly
different (p < 0.05)
Figure 4.17. Occurrence (%) of fin erosion index (A) and fin splitting index (B) values according to
different sea bream origins. Black line: wild fish; dotted line: farmed fish; grey line: escaped fish.
77
SEA BREAM AND SEA BASS ESCAPEES
Fig. 4.18. Scatterplot of discriminant analysis functions for both fin erosion (A) and fin splitting (B) indices
on sea bream according to fish origin. Black circles: wild fish; white squares: farmed fish; grey triangles:
escaped fish.
Table 4.11. Percentage classification score results for the discrimination analysis among different origins
according to calculated fin erosion indices. %CC: total percentage of correctly classified; FEI: fin erosion
index; FSI: fin splitting index.
Species
S. aurata
D. labrax
Index
FEI
%CC
87.6
FSI
69.9
FEI
48.7
FSI
60.2
Wild
Farm
Escape
Wild
Farm
Escape
Wild
88
0
9
75
18
17
Farm
2
97
9
15
72
20
Escape
10
3
82
10
10
63
N
100
100
100
100
100
100
Wild
Farm
Escape
Wild
Farm
Escape
33
30
22
50
8
15
30
50
15
24
66
20
37
20
63
26
26
65
100
100
100
100
100
100
For sea bass, resulting FEI showed no
significant differences not only for all sea
bass fins but also for specific fins separately
(uGLM, p-value>0.05; Figure 4.19a).
However,
FSI
revealed
significant
differences for all fins together, being wild
fish fins the most splitted meanwhile
farmed fish fins were the less splitted
(uGLM, p-value<0.01; Figure 4.19b). No
differences were found on FEI and FSI
according to fish standard length (uGLM,
p-value>0.05).
Caudal
fin
showed
significant differences among the 3
different origin groups according to FSI
values, where wild fish presented the most
splitted caudal fin, followed by escaped fish
and finally the farmed fish (Figure 4.19b).
Dorsal, anal, pelvic and pectoral fins
presented in all cases the highest FSI values
on wild sea bass, being significantly
78
different from farmed and escaped sea bass
together (Figure 4.19b). Fin erosion
occurrence on sea bass showed similar
profiles among the 3 origin groups, whose
highest percentages were observed from 1
to 1.5 erosion values (Figure 4.20a).
However, fin splitting occurrence on
farmed and escaped sea bass presented the
highest values from 0 to 1 splitting values,
showing a completely different profile from
wild sea bass whose percentages were
lower but spread among the different
splitting values (Figure 4.20b). Only the
48.7% and the 60.2% of all sea bass
individuals were correctly classified
through discriminant analysis according to
resulted FEI and FSI values respectively,
being all percentages among groups lower
than 66% (Table 4.11, Figure 4.21a,b).
CHAPTER 4
Figure 4.19. Mean fin erosion index (A) and fin splitting index (B) values on sea bass fins according to fish
origin. Black columns: wild fish; white columns: farmed fish; grey columns: escaped fish. Bars show mean
standard errors (±SE). Values with different letters at the same group of columns are significantly different
(p < 0.05).
Figure 4.20. Fin erosion (A) and fin splitting (B) occurrences (%) on sea bass according to different fish
origins.
Figure 4.21. Scatterplot of discriminant analysis functions for both fin erosion and fin splitting indices on
sea bass according to fish origin.
79
SEA BREAM AND SEA BASS ESCAPEES
4.5. Discussion
4.5.1. Morphology
Body morphology was clearly different
between wild and farmed fish for both
species. The fast growth of farmed fish into
the cages compared to wild fish is easily
observable as in this study farmed
individuals presented higher weight values
than wild individuals for a fixed size. Such
differences are more pronounced in larger
individuals than in small ones, and are also
more distinguishable in sea bream than in
sea bass specimens. The resulting bcoefficient
from
the
weight-length
relationship on wild sea bream (2.98)
indicated isometric growth, which aligns
with
previous
findings
on
wild
Mediterranean sea bream that reported a
range from 2.62 to 3.22 (Lasserre and
Labourg 1974; Arnal et al. 1976; Suau and
López 1976; Arias 1980; Wassef 1990;
Kraljević and Dulčić 1997; Chaoui et al.
2006; Dimitriou et al. 2007; Mehanna 2007;
Akyol and Gamsiz 2010). However, the bcoefficient on farmed sea bream was
remarkably
higher
than
for
wild
individuals, and more noticeable in larger
sizes. For sea bass, the b-coefficient value
found for wild individuals was also lower
than for farmed specimens (3.41 and 3.86
respectively), but both are higher than
those found in previous studies which
ranged from 3.01 to 3.14 (Arias 1980;
Serrano-Gordo 1989).
The spatial consistency of these results
indicate the usefulness of these indices in
discriminating the origin of the studied
species, such as the Cephalic Index for sea
bass, the Relative Profile Index for sea
bream or Fulton’s Condition Index for both
species. In addition, morphometric analyses
suggest that most differences are located
primarily in the head and anterior region of
the body of the fish. Specifically, these
differences on sea bream were focused
either on the head height (B5) or the
distances from the base of the pectoral fin
to the edges of the mouth (A5) and to
forehead (A2); while for sea bass they were
on head and body length (F3 and F4
respectively), proportions of the eye and
the distances from the base of the
operculum to the edge of the mouth (A2)
80
and to the forehead (A3)(Table 4.2, Figure
4.3).
These morphological differentiations could
be due to either the selective breeding
programmes applied in aquaculture,
genetic
drift
following
founding
generations, or the different origin of fish
used as broodstocks (Karaiskou et al. 2009).
Although the accidental escapes of fish
from farms have certainly contributed to a
mix of all gilthead sea bream genetic stocks
(Sola et al. 2007), a high genetic
differentiation between cultivated and wild
populations from the same area has been
reported, which might indicate no evidence
for significant genetic flow between them
(Alarcón et al. 2004). The first genetics
studies carried out on gilthead sea bream
populations reported conflicting data
concerning the existence of panmictic
(Cervelli et al. 1985) or subdivided
populations (Funkenstein et al. 1990). More
recent studies have depicted a picture of
species subdivision that still needs to be
clarified. The results of Arabaci et al. (2010)
suggest a slight but significant population
structure for the Mediterranean Sea and
Atlantic Ocean, but not apparently
associated
with
geographic
or
oceanographic factors (Alarcón et al. 2004;
Ben-Slimen et al. 2004; De Innocentiis et al.
2004; Karaiskou et al. 2005; Rossi et al. 2006).
Additionally to fish origin, it should be
noted that the mean sizes among Spanish
and Greek sea bream in this study were
significantly different. Mean size (both
length and weight) of Spanish sea bream
proved to be higher than the group from
Greece.
Thus,
some
morphological
variations between regions may be the
result of differences in individual’s age, and
hence body size. Gilthead sea bream are
characterized by remarkable anatomical
changes throughout their life history
(Cataldi et al. 1987), and this species is
known to undergo ontogenetic shifts in
feeding habits (Mariani et al. 2002; Tancioni
et al. 2003). Furthermore, a pattern of
allometric growth on different body regions
was characterized for each age-stage (Russo
et al. 2007). Further studies will be
necessary to compare different sizes of
farmed and wild sea bream from different
geographical regions.
CHAPTER 4
In the case of European sea bass, numerous
genetic population differentiation studies at
different geographic scales have led to the
identification of three genetically distinct
zones: the northeastern Atlantic Ocean, the
western Mediterranean and the eastern
Mediterranean (Patarnello et al. 1993;
Allegrucci et al. 1997; García de León et al.
1997; Castilho and McAndrew 1998; Sola et
al. 1998; Bahri-Sfar et al. 2000; Castilho and
Ciftci 2005; Ergüden et al. 2005; Katsares et
al. 2005; Lemaire et al. 2005). In this study,
some wild sea bass from Spain (7%) were
grouped along with farmed fish from Spain
through discriminate analysis, which
probably belong to an escapee group; but
some others (5%) were grouped with sea
bass from Greek farms. Cases in which
individuals do not cluster with other
samples
belonging
to
the
same
geographical origin are not surprising,
since eggs or fingerlings originating from
the western basin were most likely used to
seed many hatcheries around the
Mediterranean when sea bass aquaculture,
and therefore escapes into the wild, began
in the early 1980s (Haffray et al. 2007).
On the other hand, phenotypic differences
are not necessarily indicative of genetic
differentiation between populations (Ihssen
et al. 1981; Allendorf 1988), and thus the
detection of morphological differences
among populations cannot usually be taken
as evidence of genetic differentiation
(Turan 1999). Phenotypic plasticity of fish
allows them to respond adaptively to
environmental change by modification to
their physiology and behaviour which
leads to changes in their morphology,
reproduction or survival that mitigate the
effects of environmental variation (Stearns
1983;
Meyer
1987).
Unlike
wild
populations, farmed fish live inside the
cages with a periodic feeding rate and
easily available food, suggesting that
foraging is different from wild fish (Arabaci
et al. 2010). Therefore, the morphological
differences found in this study between
wild and farmed sea bream agree with
those differences found by Grigorakis et al.
(2002) where wild sea bream presented
lower body height, sharper snout and more
spindle-shaped body than cultured sea
bream. Moreover, such differences could be
partly explained by dietary shifts, which
induce changes on the body shape (Keast
1978), influencing prey selection and catch
efficiency (Mérigoux and Ponton 1998).
Furthermore, as they have been widely
reported for farmed sea bream and sea
bass, all fish species may develop shape
abnormalities under farming conditions
(Divanach et al. 1996). Some of such
anomalies are observable not only in
different body regions (Paperna 1978;
Francescon et al. 1988; Balebona et al. 1993;
Marino et al. 1993; Boglione et al. 1993, 2001;
Chatain 1994; Koumoundourous et al. 1997;
Loy et al. 1999, 2000; Afonso et al. 2000;
Sfakianakis et al. 2006; Tulli et al. 2009), but
also in fins, otoliths and scales (Carrillo et
al. 2001; Arechavala-Lopez present chapter).
However, wild-caught sea bream and sea
bass
present
a
low
number
of
malformations and are scarcely affected by
any severe anomalies (Boglione et al. 2001;
Loy et al. 2000). In the present study,
farmed fish were carefully selected from the
captures looking for streamlined wild-like
profiles, associated with absence or light
anomalies cadres (Loy et al. 2000), to avoid
these morphoanatomical differences cited
above. Despite this, significant differences
have been detected mainly in the anterior
region for both species, resulting neither
from malformations nor abnormalities.
4.5.2. Scales
High fish densities within cages (5-10
kg/m3) lead to greater numbers of physical
collisions and thus high friction among
individuals,
and
consequently
the
pronounced levels of scale loss. This can
also occur due through abrasion (Eaton
1996), aggressiveness, lymphocystis or
handling (Fiske et al. 2005). Logically, the
greater difficulty of scale detachment in
farmed fish is a result of the process of scale
replacement, which occurs more frequently
in these fish. In this study, farmed sea
bream showed higher average levels of
replacement scales than wild fish, which
helps to classify sea bream specimens
according to their origin. Grigorakis et al.
(2002)
also
suggested
identification
indicators apart from other external and
compositional differences, such as the
detachment and abundance of scales
between wild and cultured sea bream. The
81
SEA BREAM AND SEA BASS ESCAPEES
authors highlighted the ease at which scales
would detach from wild sea bream, in
contrast to farmed sea bream scales which
were less abundant and very difficult to
detach (Grigorakis et al. 2002). Although
fish are able to completely replace a scale
within a year of its loss, wild fish scales are
still distinguishable from those of the
farmed ones, which will never regenerate
the nucleus. In salmonids, the need to
replace
scales
has
declined
since
aquaculture practices have changed in
recent years, which have led to less fish
handling (Fiske et al. 2005). Furthermore,
scale abnormalities are frequent in sea
bream and sea bass reared in cages, often
associated with vertebral deformities
(Divanach et al. 1996). This was seen, for
instance, in the slightly disoriented patterns
on cultured sea bream scales of the lateral
line (Carrillo et al. 2001), while the
abnormal reorganization of scales after
regeneration has been suggested (BereitherHahn and Zylberberg 1993).
In addition, growth patterns are also
reflected in scale patterns as wild fish have
a slower growth rate and show more annuli
and less esclerites on their scales than
farmed fish. This is a result of the more
constant environmental conditions under
which the fish are reared, combined with a
regular food supply, serving to remove or
at least ameliorate the effects of seasonality
on the growth pattern of the fish. Our
findings agree with Eaton (1996), who
demonstrated that annuli on the scales of
farmed sea bass, as well as being fewer in
number, are also less well defined or even
absent. Moreover, differences between wild
and farmed fish according to the esclerites
number found in this study are only
applicable on sea bass, and could be helpful
in examining the origin of individuals.
Several studies have used detailed scale
patterns, such as circuli spacing, shape and
texture of scale, in order to discriminate the
wild or farm origin of other fish species
with high accuracy (Antere and Ikonen
1983; Borzecka et al. 1990; Ross and Pickard
1990; Barlow and Gregg 1991; Lund and
Hansen 1991; Friedland et al. 1994; Hiilivirta
et al. 1998, Uglem et al. 2011). The precision
of our findings suggests the reading scale
as a conservative method for identifying
82
the number of farmed escapees in samples
from fisheries.
4.5.3. Otoliths
Environmental conditions, food supply and
also genetic dissimilarities can influence the
shape of the sagittal otoliths (Pannella 1971;
Cardinale et al. 2004; Galley et al. 2006),
which is a factor that has been used as a
method for identifying species (ParisiBaradada et al. 2010). Moreover, specific
characteristics
emerge
within
an
individual’s
growth
(Lombarte
and
Castellón 1991) which could help to
distinguish its farm or wild origin. Similar
to our findings, a comparison of otoliths
from wild and farmed salmon parr detected
that naturally produced fish showed a
seasonal pattern, alternating opaque and
translucent zones, while hatchery-reared
parr otoliths were completely opaque or
had their translucent zones close to the
edge (Hindar and L´Abée-Lund 1992).
Transparent otoliths with rough distal
surface and irregular increments were
found in farmed Ayu, Plecoglosssus altivelis
(Izuka 2001). Furthermore, some hatcheryproduced red drum, Sciaenops ocellatus, and
stocked lake trout, Salvelinus namaycush,
were found to have aberrant sagittae
(David et al. 1994; Bowen et al. 1999).
Katayama and Isshiki (2007) found
variations not only in opaque-translucent
zones in otoliths of farmed and wild
Japanese flounder, Paralichthys olivaceus, but
also in otolith ellipticity. Fowler et al. (2003)
found that otoliths from farmed yellow-tail
kingfish,
Seriola
lalandi,
were
morphometrically more variable than wild
fish.
In agreement with Tuset et al. (2008), sea
bream otoliths had a pentagonal to elliptic
shape with serrate margins, while the sea
bass otolith shape was fusiform to oblong.
In both species, shape descriptors
separately were not useful to discriminate
between wild and farmed fish origin,
however, discriminant analysis using all
descriptors together showed clear origin
differences. In sea bream, important
differences were found within geographical
origins, which could be explained by either
genetic, morphological or size distribution
differences of Mediterranean stocks.
CHAPTER 4
However, the EFDs analysis, which is fishlength
independent,
distinguished
individuals according to their wild-farm
origin with high accuracy, but similarities
were also present in otolith shape within
smaller individuals. Conversely, variations
between wild and farmed sea bass were
found through all shape descriptors and
EFDs
discriminant
analysis,
which
classified sea bass specimens with high
accuracy. Therefore, combining image
analysis techniques with elliptical Fourier
analysis provided an efficient method for
describing
otolith
shape
and
for
distinguishing origins. To date, these
methodologies are considered to be an
objective method that are more reliable
than the ones that use external
morphometric traits, as they are not
affected by short-term variations in fish
physiological condition, standard tissue
preservation techniques, or by geographical
differences in morphology (Campana and
Casselman 1993; Ponton 2006).
4.5.4. Fins condition
Gilthead sea bream and European sea bass
presented some differences on fin
damaging according to their wild or farmed
origin. In the case of sea bream, wild
individuals were shown to have a better fin
condition - less eroded, less frayed and less
splitted - than farmed and escaped fish.
This fact agrees with the assumption that
the occurrence of fin damaging and erosion
is substantially greater in rearing conditions
than in the natural environment, possibly
due to the high densities, feeds provided
and aquaculture operations (Mork et al.
1989). Sará et al. (2007) demonstrated that
the most frequent movements of farmed sea
bream inside the cage were, apart from
horizontal
and
vertical
movements,
collisions between fishes. According to this,
it was evidenced that the most exposed fins
-pectoral, caudal and dorsal fins- from
farmed sea bream resulted the highest
eroded. In fact, caudal fin presented the
worst fin condition of all fins on both fish
from farms and escaped. Moreover, the
high presence of splits on escaped sea
bream fins, mainly on caudal and pelvic
fins, points to these fins to be more fragile
and weaker after farming conditions than
wild fish fins, and therefore, they might be
more susceptible to suffer other type of fin
damaging such as splitting or nipping.
On the other hand, the degree of fin erosion
on sea bass was not significantly different
among fish individuals from different
origins. Sará et al. (2007) reported that
farmed sea bass were most of the time
horizontally and close to the bottom under
farming conditions, but do not present
almost collisions with nets or surrounding
conspecifics, although Person-Le Ruyet and
Le Bayon (2009) found that dorsal fin on
farmed sea bass appears to be the most
eroded by abrasion, probably due to high
densities inside the cage. However, our
results suggest that such erosion could be
either intrinsic of the natural behaviour of
this species, or due to lower rearing
densities, since such erosion levels in both
farmed and escaped sea bass were similar
to wild individuals. However, a high
degree of fin splitting was found in these
wild
specimens,
which
presented
significantly high splitted caudal fins,
probably due to aggressive confrontations
with other conspecifics (Abbott et al. 1985),
or predators such as bluefish Pomatomus
saltatrix which is commonly abundant in
our study area (Sanchez-Jerez et al. 2008). It
is remarkable the fact that escaped sea bass
in the present study presented a high
splitting degree on caudal fin, being more
similar to wild individuals than to farmed
sea bass. This could highlight the idea that
such splits in caudal fins on escaped sea
bass are the result of having to survive in
the wild, although it might not lead to
ecological implications for escapees.
Some authors suggested that the existence
of a high degree of erosion in any of the fins
could be a major impediment for migratory
movements, escape from predators or
capture preys, and therefore, for the
survival of escaped fish (Saunders and
Allen 1967; Weber and Wahle 1969; Nicola
and Cordone 1973; Mears and Hatch 1976).
Comparing the swimming performance of
farmed and wild sea bream, Basaran et al.
(2007) found that wild sea bream had a
significantly higher critical swimming
speed than the farmed fish. They suggested
that farmed sea bream may not have the
ability to compete with wild sea bream in
native seawaters, and therefore, if cultured
83
SEA BREAM AND SEA BASS ESCAPEES
84
fish escape from cages, they would be less
likely to survive, grow and reproduce
because swimming performance is crucial
for survival (Plaut 2001). However, in
chapter 2 it was evidenced that escaped sea
bream are able to survive for long periods,
swimming some kilometers away from
farms facilities and benefiting from natural
resources such as natural preys and refuge
(Arechavala-Lopez
et
al.
2012c).
Furthermore, the fin condition on escaped
sea bream reported in this study suggests
potential fin regeneration from erosion,
mainly in dorsal, caudal and pectoral fins,
which could help to their short-term
survival once in the wild. However, further
studies are necessary to improve the
knowledge about regeneration time of
damaged/eroded fins from farming
abrasion in this species.
4.5.5. Conclusions
Teleost fish have a remarkable capacity to
regenerate damaged fins and several
studies on fin regeneration have been
conducted in diverse fish species (for a
review see Akimenko et al. 2003). The fin
regeneration process is essentially the same
in all the species, which can be summarized
in three steps: (1) wound healing and
formation of the wound epidermis; (2)
formation of a regeneration blastema, a
population of mesenchymal progenitor
cells that are necessary for proliferation and
patterning of the regenerating limb/fin;
and (3) regenerative outgrowth and pattern
reformation (Akimenko et al. 2003; Poss et
al. 2003). However, there is a noticeable
species-dependent variability in the
rapidity of the process. A complete
regeneration takes a few weeks to months,
although time required depends upon the
amount of tissue initially removed, the
size/age of the fish and environmental
conditions such as water temperature (e.g.
Akimenko et al. 2003; Ellis et al. 2008; Shao
et al. 2009). Although there is no studies on
Mediterranean species, regeneration of
eroded fins on escaped sea bream should
not take longer than days or few weeks,
since only lateral dermal fin rays appeared
to be damaged and no signs of infection or
amputation were found. Therefore, the
diminishing of fin erosion signals due to fin
regeneration could make more difficult to
distinguish between escaped and wild fish
in nature.
Consequently, scale analysis is the most
useful tool to discriminate farmed
specimens within fishery stocks in both the
short and long term. Great scientific
expertise is not required to interpret the
origins from scale samples, and is the
easiest and quickest way to analyse sea
bream and sea bass specimens. Scales taken
from the indicated area will not only be
amongst the oldest on the fish (and so
contain the most complete history of its
growth), but are also the largest and have
the most standardized shape, and will
therefore be the easiest to analyse.
Furthermore, they are also less likely to
have been lost and replaced by the fish at
some time during its life, and are
unaffected by freezing or storage in ice.
Thus, this method is recommended for
fishery studies to evaluate the influence of
escaped fish on wild stocks in the field.
Observed differences between wild and
farmed fish in growth rates due to regular
feeding and environmental conditions at
farms affect biological parameters which
are reflected in fish morphology, scales and
otoliths parameters, and fins conditions.
Nevertheless, it is remarkable that the
larger farmed individuals are more
dissimilar to their wild conspecifics, most
likely due to the stable environmental
conditions experienced throughout their
life within the cage. However, feeding
habits and thus growth rates will change if
escaped farmed fish survive for relatively
long periods in the wild, therefore affecting
the weight-length relationship, otoliths
characteristics, fin regeneration
and
external morphology.
The analysis of otoliths through image
processing is more objective in classifying
farmed or wild specimens, although it is
more difficult and laborious to obtain from
routine surveys, while requiring more time
and advanced equipment. Therefore, this
methodology has been suggested as useful
for specific identification to assure the
origin of some specimens or improving
identification through scales, but not for
screening large samples from fisheries. In
addition, the use of morphoanatomical
indices (K, CI, RP) and some morphological
CHAPTER 4
differences or shape features through image
processing (TNS) seems to have also a wide
applicability in the identification of wild
and farmed fish. Therefore, direct
observations
and
image-processing
techniques can be applied in fisheries
science as they have a potential for stock
identification.
The resulting differences in fin damaging
found on sea bream might suggest the use
of fin damaging as potential indicators to
identify recent escaped sea bream in the
field after an escape event, probably during
the first one or two weeks after the farming
incident. Conversely, the lack of significant
differences on fin damaging found on sea
bass according to the origin suggests that
fin condition indices are not suitable to be
used as fish origin indicator, but could be
useful as fish welfare indicator within
farmed stocks. Therefore, the use of such
fin damaging indicators could be helpful
for
aquaculture
management
in
Mediterranean species, to assess fish
welfare at fish farms stocks, improving the
knowledge of handling, stock densities and
open-sea cage environment conditions.
In general, it must be taken into account
that an escapee that survives over time may
resemble a wild individual due to the
changes on habitat and food. Therefore, the
use of a combined approach of fin
damaging
indicators,
scales
and
morphology could improve the efficiency
of escapes identification in the field.
However, the application of other
techniques, such as genetic and other
biological indicators (e.g. fatty acids, trace
elements), should be considered for the
more precise quantification of escapes
within natural populations, fisheries
landing or for evaluation of re-stocking
programs. Specifically, a multidisciplinary
approach will help to evaluate the
contribution of escapees on local stocks and
fisheries landings with higher accuracy.
Ultimately, it will improve not only our
knowledge on the potential negative effects
of escape events but also on the sustainable
management of both fisheries and
aquaculture.
85
SEA BREAM AND SEA BASS ESCAPEES
86
CHAPTER 5
5. EVALUATION OF TOOLS FOR IDENTIFYING ESCAPEES: A REVIEW
5.1. Abstract
Based on the fact that farmed fish experience different environments, stocking densities and
feeding regimes compared to wild fish, several techniques have been developed to discriminate
the wild or farmed origin of fish. Additionaly to the tools seen in previous chapter 4, there are
other techniques that quantify such differences through genetics, chemical characteristics, fatty
acid compositions, trace elements, pollutants, stable isotopes, external appearance and
organoleptic characteristics. A total of 60 studies that used techniques to discriminate farmed
from wild fish for Gilthead sea bream and European sea bass form the basis of this review. The
most common technique used differences in the lipid and fatty acid composition of fish. Many
of these studies dealt with food science and product quality, rather than tracing escapees. A
wide range of identification tools are useful in determining the correct origin of captures and
proper labelling of marketed fish. External appearance and morphometry are useful for rapid
assessments and can be achieved with high accuracy and little cost, especially for sea bream.
This makes these methods suitable for detecting large and recent escape events and for ensuring
wild and farmed fish is separated in the marketplace. Techniques using differences in chemical
or genetic composition are more useful for environmental monitoring, as they have higher
accuracy and can detect escapees long after the escape incident. Regulatory bodies should
legislate protocols which describe the technique(s) that must be applied in specific
circumstances.
.
5.2. Introduction
The complexity and importance of the
potential environmental consequences that
escapees could cause on native populations
highlight the necessity of developing costeffective tools to detect farmed individuals
within wild stocks. As it was seen in the
previous chapter 4, effective tools will
improve knowledge of the frequency and
extent of escape events, help to assess
potential genetic and ecological risks of
escapees to wild populations, and assess
the contribution of escapees to fisheries
landings. A number of stock identification
methods have been developed for fisheriesrelated applications. Adapting these
techniques to distinguish between wild and
escaped farmed fish began in the mid-80s
when, for simple and quick identification, a
combination of several techniques were
used routinely to survey the amount of
farmed escapees in catches of salmon (Fiske
et al. 2005). More recently, several studies
on the discrimination of farmed and wild
sea bream and sea bass have been
published which have compared genetics,
chemical
characteristics,
fatty
acid
composition, levels of certain trace
elements,
concentrations
of
certain
pollutants, stable isotope concentrations,
morphology
and
organoleptic
characteristics (Table 5.1). In this review,
we summarize the existing methods
applied to sea bream and sea bass to
determine differences among farmed and
wild individuals, from the easiest and
cheapest, to the most labour-intensive or
expensive. Further, we evaluate the
applicability and suitability of such
techniques as tools to differentiate escapees
within wild stocks for future sustainable
aquaculture and fisheries management.
Figure 5.1. Captured gilthead sea bream by
trammel-netters in the Western Mediterranean
Sea. Which one is an escapee or a wild
individual? (Photo: D. Izquierdo-Gomez)
89
SEA BREAM AND SEA BASS ESCAPEES
5.3. Literature analysis
lipids and FAs composition) from the
standpoint of both the producer and the
consumer, to better inform farmers,
retailers and consumers of the effects of the
different food production methods on the
final
product
quality.
Within
the
production chain, similar fish products can
arise from different points of origin;
consequently, there is potential for fraud
due
to
product
mislabelling.
The
temptation to label farmed fish as wild fish
by some fish merchants, retailers and
restauranteurs may arise because of the
price premium commanded by wild fish.
However, little effort has been made to
develop verifiable and robust methods to
distinguish farmed from wild fish to
combat mislabelling and conform to
legislation (Bell et al. 2007; Morrison et al.
2007).
We reviewed 60 publications (58 peerreviewed articles and 2 reports) on
differences between wild and farmed fish,
specifically for sea bream and sea bass
(Table 5.1). A wide variety of approaches
and techniques exist in the literature and
the specific purpose of studies varies
widely among publications. Fatty acids
and/or lipid analyses have been used most
frequently (63% of total reviewed works;
Figure
5.2a).
Studies
based
on
morphological differences between wild
and farmed sea bream and sea bass are also
numerous (37%), as well as those that have
used proximate composition of tissues to
differentiate wild and farmed fish (27%).
Techniques using stable isotopes and
pollutants have been used less frequently
(12% each).
5.4. Analytical tools used to
discriminate wild and farmed fish
The reviewed studies were classified
according to the aims and scope of each
journal (Figure 5.2b). Studies relating to
food
science
(i.e.
food
chemistry,
organoleptic studies and culinary interest)
were most common, followed by those
dealing with aquaculture (aquatic food
resources) and pollutants (environmental
pollution and monitoring assessment).
Studies with a focus on marine biology,
ecology, ichthyology and veterinary aspects
were less abundant. The main research
driver appears to be determining
nutritional flesh quality differences (mainly
5.4.1. External appearance and
morphology
External appearance and morphological
characteristics to some degree reflect the
life history of fish (Grigorakis 2007).
External characteristics in farmed fish are
affected by culture conditions, such as
stocking density and feeding strategy
(Grigorakis 2007).
B)
A)
Genetics
9
Prox. Comp.
Mar. Biol. Ecol.
Ichthyology
16
FAs / Lipids
37
7
Food Science
Pollutants
7
Veterinary
Others
24
52
6
Chemical. Molec.
9
E.A./Morphol.
Organoleptic
13
Aquaculture
Stable Isotopes
Trace Elements
4
23
9
18
14
Environ. Pollution
19
Grey Lit./Reports
2
General Res.
1
Figure 5.2. Number of classified works within the literature reviewed: (A) according to each subject within
the present review; and (B) according to the aims and scope of the journal.
90
CHAPTER 5
Table 5.1. Reviewed works about differentiating farmed and wild fish origin on Sparus aurata (A) and
Dicentrarchus labrax (B). G: genetic; PC: proximate composition; FA/L: fatty acids/lipids; SI: stable
isotopes; POL: pollutants; TE: trace elements; EAM: external appearance and morphology; OC:
organoleptic characteristics; Others: i.e. muscle cellularity and activity, pH, free aminoacids, collagen, etc.
Authors
Dissemination
GEN
PC
FA/L
SI
POL
TE
EAM
OC
Others
Alarcón et al. 2004
A
-
-
-
-
-
-
-
-
Alasalvar et al. 2002a
-
B
B
-
-
B
-
-
B
Food Chem.
Alasalvar et al. 2002b
-
A
A
-
-
-
-
A
-
J. Agric. Food Chem.
Alasalvar et al. 2005
-
-
-
-
-
-
-
A
-
J. Agric. Food Chem.
Allegruzzi et al. 1997
B
-
-
-
-
-
-
-
-
Marine Biology
Antunes and Gil 2004
-
-
-
-
B
-
-
-
-
Chemosphere
Arechavala-Lopez et al. 2012a
-
-
-
-
-
-
A,B
-
-
Hydrobiol.
Arechavala-Lopez et al. 2012b
-
-
-
-
-
-
A,B
-
-
J. Fish Biology
Arechavala-Lopez et al. 2012d
-
-
-
-
-
-
A,B
-
-
J. Appl. Ichthyol.
Attouchi and Sadok 2010
-
A
A
-
-
-
-
-
A
Food Chem.
Attouchi and Sadok 2011
-
A
A
-
-
-
-
-
A
Food Bioprocess Techol.
Bell et al. 2007
-
-
B
B
-
-
-
-
-
J. Agric. Food Chem.
Blanes et al. 2009
-
-
A
-
A
-
-
-
-
Arch. Environ. Contam. Toxicol.
Boglione et al. 2001
-
-
-
-
-
-
A
-
-
Aquaculture
Carpene et al. 1998
-
-
A
-
-
A
-
-
A
Fish Physiol. Biochem.
Carubelli et al. 2007
-
-
B
-
B
-
-
-
-
Chemosphere
Çoban et al. 2008
-
-
-
-
-
-
A
-
-
Turkish Journal of Zoology
De Innocentiis et al. 2005
A
-
-
-
-
-
-
-
-
Aquaculture
Del Coco et al. 2009
-
-
A
-
-
-
-
-
A
Eaton 1996
-
-
-
-
-
-
B
Erdem et al. 2009
-
-
B
-
-
-
-
-
B
J. Anim. Vet. Adv.
Fasolato et al. 2010
-
B
B
B
-
-
B
-
-
J. Agric. Food Chem.
Fernandes et al. 2007
-
-
-
-
B
B
B
-
-
Environ. Res.
Ferreira et al. 2010
-
-
B
-
B
B
B
-
-
Ecotoxicol. Environ. Safety
Flos et al. 2002
-
A
A
-
-
-
A
A
A
Aquacult. Int.
Fuentes et al. 2010
-
B
B
-
-
B
B
B
B
Food Chem.
Grigorakis 2007
-
A,B
A,B
-
-
-
A,B
A,B
Grigorakis et al. 2002
-
A
A
-
-
-
A
A
-
Int. J. Food Sci. Techol.
Grigorakis et al. 2003
-
A
A
-
-
-
-
A
-
Aquaculture
Karaiskou et al. 2009
A
-
-
-
-
-
-
-
-
J. Fish Biology
Krajnović-Ozretić et al. 1994
-
-
B
-
-
-
B
-
-
Comp. Biochem. Physiol.
Lenas et al. 2010
-
-
A,B
-
-
-
-
-
A,B
Int. Aquat. Res.
Lo Turco et al. 2007
-
-
B
-
B
-
-
-
-
Environ. Monit. Assess.
Loukavitis et al. 2012
A
-
-
-
-
-
-
-
-
Aquacult. Res.
Mannina et al. 2008
-
-
B
-
-
-
-
-
B
Talanta
Miggiano et al. 2005
A
-
-
-
-
-
-
-
-
Aquacult. Int.
Minganti et al. 2010
-
-
-
-
-
A
-
-
-
Mar. Pollut. Bull.
Mnari et al. 2007
-
-
A
-
-
-
-
-
-
Food Chem.
Mnari et al. 2010a
-
-
B
-
-
B
-
-
-
African J. Food Sci.
Mnari et al. 2010b
-
-
A
-
-
-
-
-
A
Int. J. Food Sci. Techol.
Mnari et al. 2010c
-
-
A
-
-
-
-
-
A
J. Agric. Food Chem.
Monti et al. 2005
-
-
B
-
-
B
-
-
B
Anal. Chem.
Moreno-Rojas et al. 2007
-
-
-
A
-
-
-
-
-
Rapid Commun. Mass Spectrom.
Morrison et al. 2007
-
-
A
A
-
-
-
-
A
Lipids
Nasopoulou et al. 2007
-
-
A,B
-
-
-
-
-
-
Food Chem.
Orban et al. 2002
-
B
B
-
-
B
-
-
-
J. Food. Sci.
Orban et al. 2003
-
A,B
A,B
-
-
-
-
-
A,B
J. Food. Sci.
Ottavian et al. 2012
-
B
B
B
-
-
B
-
-
J. Agric. Food Chem.
Palma et al. 2001
A
-
-
-
-
-
A
-
-
J. Mar. Biol. Ass. UK
Patarnello et al. 1993
B
-
-
-
-
-
B
-
-
Mol. Mar. Biol. Biotechnol.
Periago et al. 2005
-
B
B
-
-
-
B
B
B
Aquaculture
Rezzi et al. 2007
-
-
A
-
-
-
-
-
A
J. Agric. Food Chem.
Rogdakis et al. 2011
-
-
-
-
-
-
A
-
-
Int. J. Fish. Aquacult.
Sağlik et al. 2003
-
-
A,B
-
-
-
-
-
-
Eur. J. Lipid Sci. Technol.
Santaella et al. 2007
-
B
B
-
-
B
-
-
B
An. Vet. (Murcia)
Serrano et al. 2007
-
-
A
A
-
-
-
-
-
Chemosphere
Serrano et al. 2008
-
-
-
A
A
-
-
-
-
Sci. Tot. Environment
Šimat et al. 2012
-
A
-
-
-
-
A
A
A
J. Appl. Ichthyol.
Sola et al. 1998
B
-
-
-
-
-
B
-
-
CIHEAM Opt. Medit.
Yildiz et al. 2008
-
-
A,B
-
-
-
-
-
-
Int. J. Food Sci. Techol.
(Journal)
Aquaculture
Nutrients
Fish. Res. Tech. Report
Aquaculture
91
SEA BREAM AND SEA BASS ESCAPEES
Several studies document that the
morphology of wild sea bream differs
significantly from farmed individuals. Wild
sea bream have a lower body height,
sharper snout and a more squat and
compact shape; they are shorter, wider and
higher (Flos et al. 2002; Grigorakis et al.
2002; Rogdakis et al. 2011). Farmed sea
bream have small, rounded and less
developed
teeth
than
their
wild
counterparts which have bigger, sharper
teeth (Grigorakis et al. 2002). Skin
characteristics can also differ, but
differences have not been universally
detected. Farmed sea bream have been
determined to have thicker skin, which is
darker in the dorsal and head areas, and the
characteristic iridescent colours are much
duller (Grigorakis et al. 2002; Rogdakis et al.
2011; Šimat et al. 2012). In contrast, colour
similarities between wild and semiintensively produced sea bream were found
by Flos et al. (2002), suggesting that skin
pigmentation is related to access to natural
rather than commercial food.
continuous growth pattern compared with
their wild counterparts, which have clear
annual rings which indicate large seasonal
differences in growth rates (Chapter 4Arechavala-Lopez et al. 2012b).
Farmed sea bream have fewer scales than
wild fish and these are more difficult to
detach (Grigorakis et al. 2002), with slightly
disoriented patterns on scales of the lateral
line (Carrillo et al. 2001) and regenerated
nuclei due to the loss of scales in farming
conditions (Katselis et al. 2003; Chapter 4Arechavala-Lopez et al. 2012b). Differences
in the condition of farmed and wild sea
bream fins are typically strong. Farmed fish
have smaller anal and sharper dorsal fins
(Grigorakis et al. 2002), and a higher degree
of erosion in the caudal and pectoral fins
(Chapter 4-Arechavala-Lopez et al. 2012d).
However, fin regeneration must be
considered when determining fish origin
(Chapter 4-Arechavala-Lopez et al. 2012d).
The condition index is an important tool to
measure body shape and acts as a good
indicator of dietary condition and history
(Grigorakis 2007). Higher condition indices
for farmed fish compared to wild fish are
typically observed for both sea bream (Flos
et al. 2002; Rogdakis et al. 2011; Chapter 4Arechavala-Lopez et al. 2012a) and sea bass
(Krajnović-Ozretić et al. 1994; Fernandes et
al. 2007; Fasolato et al. 2010; Chapter 4Arechavala-Lopez et al. 2012a). Relative
profile index and cephalic index have also
been suggested as indicators of fish origin
for sea bream and sea bass, respectively
(Flos et al. 2002; Chapter 4-ArechavalaLopez et al. 2012a). Other morphometric
techniques applied to otoliths have
revealed significant differences in otolith
shape between wild and farmed fish for sea
bream and sea bass (Chapter 4-ArechavalaLopez et al. 2012b). Thus, wild and cultured
sea bream and sea bass show a range of
distinct morphometric differences, which
not only indicate dietary condition and
history (Grigorakis 2007), but might also be
easy, cheap and reliable tools to
discriminate fish origin, being suitable for
detecting large and recent escapees (see
Table 5.2 for a summary).
For sea bass, Eaton (1996) suggested that
external differences among wild and
cultured fish are not pronounced, and
identification cannot rely on shape, colour
or general appearance. Fin condition is also
difficult to use as an indicator of fish origin
in sea bass (Chapter 4-Arechavala-Lopez et
al. 2012d). However, genetic deformities in
a number of fin rays and vertebrae on
farmed sea bass have been shown (Sola et
al. 1998). Moreover, farmed sea bass scales,
which are fed continuously, have a
92
Significant morphometric differences in
cranial and body features, and skeletal
abnormalities, exist among fish of farmed
or wild origin for sea bream (from larvae to
adult) and sea bass (juvenile and adult)
(Boglione et al. 2001; Rogdakis et al. 2011;
Chapter 4-Arechavala-Lopez et al. 2012a).
These differences diminished in released
sea bream after 6-7 months in the wild,
however, mean values and variances of key
morphological
features
remained
sufficiently different to distinguish the two
groups (Rogdakis et al. 2011). However, no
differences were found in geometrical
morphometry between lagoon caught and
cultured fish by Çoban et al. (2008), which
was though to be related to similarities in
conditions (feeding and stocking) between
culture and lagoon environments.
CHAPTER 5
Table 5.2. Summary of sea bream and sea bass characteristics according to the wild or farm origin, based
on the external appearance, morphology and organoleptic characteristics found in the literature reviewed.
Sparus aurata
Characteristics
BODY/SHAPE
Farmed
Dicentrarchus labrax
Wild
Farmed
Wild
- Higher body height
- Lower body
height
- Higher K
- Lower K
- Higher condition
index (K)
- Lower K and RPI
- Lower cephalic
index
- Higher cephalic
index
- Higher relative profile
index (RPI)
- Squat and
compact shape
- Skeletal
abnormalities
- Slight sharp head
- Shiny silver
- High contrast grey
colours
- Regenerated nucleus - Clear nucleus
- Lack of annual
- Clear annual rings
- Fewer density
- Higher density
deposition
- Low erosion signs
- Deformities in fin
rays
- Low probability of
abnormalities
- Whiter appearance
- Darker
appearance
- Higher smell
- Fresher smell
- Heavier smell
- Softer smell
- Higher juiciness
- Higher springiness,
- Higher juiciness
- More pleasant
taste
- Higher tenderness
hardness,
cohesiveness,
- Higher tenderness
- Firmer texture
chewiness, gummies,
- Dry/fibrous
sensation
firmness and
deformability
- Sharper snout
TEETH
SKIN
- Small and less
developed
- More developed
- Rounded and
squared shape
- Sharper and
conical
- Duller colours, darker - Brighter
in head and dorsal
iridescent colours
areas
- Harder skin with
thicker walls
SCALES
- Thinner skin
- Slight disoriented
FINS
- High erosion degree
in caudal and pectoral
fins
- Smaller belly and
sharper dorsal fin
ORGANOLEPTIC
5.4.2. Organoleptic characteristics
Organoleptic properties and nutritional
value are two sets of characteristics that,
together with freshness (quality of
appearance, taste and texture), consumers
use to determine the quality of fish
(Grigorakis 2007). These characteristics
strongly
depend
on
the
chemical
composition of the fish, which in turn
depends on the intrinsic characteristics of
the fish (e.g. species, age, sex),
environmental variables (e.g. temperature,
salinity) and feeding history (e.g. diet
composition, feeding rate; Grigorakis 1999).
The nutritional value and organoleptic
characteristics of fish are especially affected
by rearing conditions, so that composition
and sensory parameters between wild and
farmed fish differ (Børrensen 1992).
Artificial diets in farmed fish provide a
wide range of nutrients, which not only
determine fish growth rate but also flesh
composition, in particular the lipid content,
which may be quantitatively and
qualitatively modified. Studies revealing
the existence of differences in the
organoleptic
characteristics
between
farmed and wild sea bream (Alasalvar et al.
2002b, 2005; Flos et al. 2002; Grigorakis et al.
2002, 2003; Šimat et al. 2012) and sea bass
(Periago et al. 2005; Fuentes et al. 2010) are
common (Table 5.2).
Grigorakis et al. (2003) found that wild sea
bream muscle has a darker appearance
compared to the whiter appearance of
farmed sea bream. Wild fish have to move
continuously, and have higher proportions
of dark muscle used for continuous
swimming. In contrast, white muscles are
used for rapid burst swimming and the
93
SEA BREAM AND SEA BASS ESCAPEES
higher fat content in cultured fish muscle
may contribute to its whiter appearance
(Grigorakis et al. 2003). The most common
sensory descriptors assigned to wild sea
bream were a more pleasant taste and a
firmer texture than farmed fish (Grigorakis
et al. 2003). Fat content strongly affects the
impression of taste in the mouth, and
differences in texture of fish muscle have
been related to lipid, protein and moisture
contents (Venugopal and Shahidi 1996).
Fat-rich tissues usually taste very smooth
and succulent (‘‘juicy’’), while the sensation
of ‘‘dryness’’ or ‘‘fibrousness’’ (‘‘rough’’ or
‘‘coarse’’) describes the tissue better when
fat levels are low (Grigorakis et al. 2003).
The volatile aroma compounds profile of
wild fish differ to those of cultured fish, as
they contain a higher number of tastecontributing compounds (Grigorakis et al.
2003; Alasalvar et al. 2005). Grigorakis et al.
(2002) defined the external smell of wild sea
bream as much softer than farmed sea
bream, which sometimes smelt like fish oil.
However, sensorial indicators do not
consistently provide a clear basis to
separate farmed and wild sea bream. A
sensorial evaluation by Flos et al. (2002)
found differences among sea bream from
three different inland culture systems but
no differences between them and wild
conspecifics. In addition, Alasalvar et al.
(2002b) found that the texture of cultured
and wild sea bream stored in ice decreased
throughout the storage period, and they
were not significantly different until after
day 16 when the wild sea bream was
significantly softer than the cultured fish.
Šimat et al. (2012) applied the Quality Index
Method, which is a sensory evaluation
method using a scoring system, to find
differences between wild and farmed sea
bream.
For sea bass, significant differences
between cultured and farmed fish have
been detected for all textural parameters
measured.
Springiness,
hardness,
cohesiveness,
chewiness,
gummies,
firmness and deformability are all higher in
wild compared to farmed specimens
(Periago et al. 2005; Fuentes et al. 2010). The
flesh of wild fish is firmer, which could be
attributed to its lower fat content and the
higher level of swimming activity. High fat
content in farmed fish could lead to a
94
poorer texture, but texture is also related to
other factors, such as collagen content of
the flesh, pH, and the muscle fibre size
(Johnston et al. 2000; Periago et al. 2005).
Moreover, farmed sea bass were darker
than wild fish, which could be attributed to
the differences found in moisture content
(Fuentes et al. 2010). Farmed and wild fish
differ in proximate composition, colour,
texture, fatty acids and free amino acids
profiles. Therefore, organoleptic differences
can, to a large extent, be related to
compositional differences. Thus, the
application of a multi-indicator based
approach
using
physico-chemical
parameters and organoleptic characteristics
could be highly useful to distinguish
farmed and wild fish.
5.4.3. Proximate composition and fatty
acid profile
In intensive marine aquaculture, the high
lipid content of the diet and the intensive
feeding regime affect the chemical
composition of the fish, resulting in a
higher fat content (Lopparrelli et al. 2004).
The vast majority of studies dealing with
muscle proximate composition of sea bream
have found that wild individuals have
lower lipid and higher water contents than
farmed sea bream, both from inland and
offshore culture (Carpene et al. 1998;
Alasalvar et al. 2002b; Flos et al. 2002;
Grigorakis et al. 2002, 2003; Orban et al.
2003; Nasopoulou et al. 2007; Attouchi and
Sadok 2010, 2011; Šimat et al. 2012) (Table
5.3). These two parameters are usually
inversely correlated and such proportions
are attributed to the high dietary fat level in
the feed and the reduced activity of
cultured fish (Alasalvar et al. 2002a).
Whether protein levels differ among
farmed and wild fish is more uncertain;
some studies have documented higher
protein concentrations in wild sea bream
muscle compared to farmed fish muscle
(Carpene et al. 1998; Grigorakis et al. 2002;
Orban et al. 2003), while others have found
no significant differences (Alasalvar et al.
2002b; Flos et al. 2002; Grigorakis et al. 2003;
Nasopoulou et al. 2007; Attouchi and Sadok
2010, 2011). Protein content may not only
be determined by diet, but also by species,
genetic characteristics and fish size
CHAPTER 5
(Grigorakis 2007; Attouchi and Sadok 2010).
Furthermore, all previous authors reported
no significant differences in ash analysis
between sea bream of different origin.
al. 2002a; Orban et al. 2003; Periago et al.
2005; Nasopoulou et al. 2007; Santaella et al.
2007; Fasolato et al. 2010; Fuentes et al. 2010;
Ottavian et al. 2012). Therefore, proximal
analysis is not a useful technique to
determine fish origin, but it provides a
basis for further analyses such as metabolic
profiling or determining fatty acid (FA)
signature.
Similar results have been found for sea bass
(Table 5.4); farmed individuals have higher
lipid levels than their wild conspecifics,
while no clear differences exist for proteins,
moisture and ash composition (Alasalvar et
Table 5.3. Resulting proximate composition and fatty acids profile on different tissues for sea bream
Sparus aurata from the literature reviewed. M: muscle; L: liver; G: gills; w: white; r: red; S: skin; B: brain; F:
farmed fish; W: wild fish; sv: seasonal variations; ns: no significant differences; †:inland culture; u.d.:
unpublished data.
Tissue
Proximate Composition (%)
Fatty Acids Profile (%)
Lipids
Prots.
Moist.
Ash
18:1
18:2
18:3
22:6
20:5
20:4
M
F>W
ns
W>F
ns
n-9
n-6
n-3
n-3
n-3
n-6
-
-
-
-
-
M
F>W
ns
W>F
ns
-
-
-
-
-
M, L, G
F>W
-
-
-
-
-
-
-
Mw
-
ns
-
-
W>F
F>W
-
Mr
-
W>F
-
-
W>F
F>W
M
F>W
-
-
-
-
M
F>W
-
-
-
L
F>W
-
-
M
F>W
ns
M
F>W
M
F>W
B
Author
n3/n6
MUFA
PUFA
-
-
-
-
Alasalvar et al. 2002b
-
-
-
-
Attouchi & Sadok 2010,2011
-
-
-
-
-
Blanes et al. 2009
F>W
-
-
-
-
-
Carpene et al. 1998
-
F>W
-
-
-
-
-
Carpene et al. 1998
-
-
-
-
-
-
-
-
Del Coco et al. 2009
F>W
F>W
ns
F>W
F>W
W>F
W>F
F>W
F>W
Fernandez-Jover et al. u.d.
-
F>W
F>W
F>W
F>W
F>W
W>F
W>F
F>W
F>W
Fernandez-Jover et al. u.d.
W>F
ns
-
-
-
-
-
-
-
-
-
Flos et al. 2002†
W>F
ns
ns
F>W
F>W
F>W
ns
ns
W>F
ns
-
-
Grigorakis et al. 2002
ns
W>F
ns
-
-
-
-
-
-
-
-
-
Grigorakis et al. 2003
F>W
-
-
-
F>W
F>W
W>F
F>W
F>W
ns
W>F
W>F
F>W
Lenas et al. 2010
M
F>W
-
-
-
W>F
F>W
F>W
F>W
W>F
W>F
F>W
ns
ns
Mnari et al. 2007
L
F>W
-
-
-
W>F
ns
F>W
F>W
F>W
W>F
F>W
W>F
F>W
Mnari et al. 2007
M
F>W
-
W>F
-
ns
F>W
F>W
F>W
F>W
W>F
F>W
W>F
F>W
Mnari et al. 2010b
M
F>W
-
-
-
W>F
F>W
-
F>W
F>W
W>F
-
-
-
Morrison et al. 2007
M
F>W
-
-
-
-
-
-
-
-
-
-
-
-
Nasopoulou et al. 2007
M
F>W
W>F
W>F
ns
W>F
F>W
F>W
W>F
W>F
W>F
ns
F>W
ns
Orban et al. 2003
M
F>W
-
-
-
-
-
-
-
-
-
-
-
-
Rezzi et al 2007
M
F>W
-
-
-
F>W
F>W
F>W
F>W
F>W
ns
ns
F>W
F>W
Saglik et al. 2003
S
F>W
-
-
-
F>W
F>W
F>W
ns
ns
ns
W>F
F>W
F>W
Saglik et al. 2003
M, L, G
F>W
-
-
-
-
-
-
-
-
-
-
-
-
Serrano et al. 2007
M
F>W
Ns
W>F
Ns
-
-
-
-
-
-
-
-
-
Šimat et al. 2012
M
F>W
-
-
-
sv
sv
sv
sv
sv
sv
-
sv
sv
Yildiz et al. 2008
Fish lipids are rich in long-chain n-3
polyunsaturated fatty acids (LC n-3 PUFA),
especially eicosapentaenoic acid (EPA:
20:5n-3) and docosahexaenoic acid (DHA:
22:6n-3), which play a vital role in human
nutrition, disease prevention and health
promotion (Horrocks and Yeo 1999).
Moreover, EPA, DHA and arachidonic acid
(ARA: 20:4n-6), are considered to be
essential dietary fatty acids. Since the
incorporation and storage of FAs in fish
tissues strongly depends on the FA profile
of the diet (see Sargent et al. 2002 for a
review), the current practice of substituting
fish oils with other vegetable lipid sources
in farmed marine fish diets leads to notable
changes in lipid composition and FA
profiles, due to the presence of FAs of
terrestrial origin such as oleic acid (OA:
18:1n-9), α-linolenic acid (LNA: 18:3n-3) or
linoleic acid (LA: 18:2n-6), which are
usually found in low levels in marine fish.
95
SEA BREAM AND SEA BASS ESCAPEES
Therefore, differences between wild and
farmed dietary FA profiles have been
widely used to discriminate farmed and
wild fish origin. Several authors have
studied the differences in FA composition
of different tissues, such as muscle, liver,
skin or brain, in both sea bream and sea
bass (see Tables 5.3 and 5.4). Generally, the
majority of these studies show pronounced
differences between wild and farmed fish
with respect to LA and ARA, which are
found in higher and lower levels for
cultured adult sea bass and sea bream,
respectively
(Figure
5.3).
However,
different patterns have been established for
other FAs and FA indexes between wild
and farmed fish because of the high
variability and high standard deviations
within the reviewed results. Such high
heterogeneity is strongly affected by the
dietary history and exhibits strong
seasonality (Grigorakis et al. 2007; Yildiz et
al. 2008). Hence, in addition to different
levels of LA and ARA, some authors have
suggested that the presence in different
tissues of specific FAs that come from diets
derived
from
different
marine
environments to that of the culture site may
serve as biomarkers for wild or farmed sea
bream and sea bass (e.g. cetoleic acid
22:1n11; Grigorakis et al. 2002).
Table 5.4. Resulting proximate composition and fatty acids profile on different tissues for sea bass
Dicentrarchus labrax from the literature reviewed. M: muscle; L: liver; d: dorsal; v: ventral; S: skin; B: brain;
F: farmed fish; W: wild fish; sv: seasonal variations; ns: no significant differences; u.d.: unpublished data.
Tissue
96
Proximate Composition (%)
Fatty Acids Profile (%)
Lipids
Prots.
Moist.
Ash
18:1
18:2
18:3
M
F>W
ns
W>F
ns
M
F>W
-
-
-
M
F>W
-
-
M
F>W
-
M
F>W
M
22:6
20:5
20:4
n-9
n-6
n-3
n-3
n-3
n-6
F>W
F>W
ns
W>F
W>F
ns
F>W
-
W>F
-
-
-
-
-
-
F>W
F>W
F>W
W>F
F>W
F>W
F>W
-
-
-
L
F>W
-
-
L
F>W
-
M
F>W
M
Author
n3/n6
MUFA
PUFA
W>F
W>F
F>W
W>F
W>F
W>F
-
-
-
Bell et al. 2007
-
-
-
-
-
-
Carubelli et al. 2007
ns
W>F
F>W
ns
W>F
F>W
W>F
F>W
F>W
W>F
W>F
W>F
W>F
F>W
ns
F>W
F>W
F>W
F>W
F>W
F>W
W>F
F>W
F>W
Fernandez-Jover et al. u.d.
-
F>W
W>F
F>W
F>W
F>W
ns
W>F
ns
ns
Fernandez-Jover et al. u.d.
-
-
-
-
-
-
-
-
-
-
-
Ferreira et al. 2010
-
-
-
-
-
-
W>F
W>F
-
W>F
F>W
W>F
Ferreira et al. 2010
F>W
W>F
W>F
ns
F>W
F>W
ns
W>F
W>F
W>F
W>F
ns
ns
Fuentes et al. 2010
M
F>W
-
-
-
F>W
F>W
W>F
W>F
W>F
-
-
-
W>F
Krajnović-Ozretić et al. 1994
L
F>W
-
-
-
F>W
F>W
W>F
W>F
W>F
-
-
-
W>F
Krajnović-Ozretić et al. 1994
B
F>W
-
-
-
F>W
F>W
F>W
F>W
ns
W>F
W>F
W>F
F>W
Lenas et al. 2010
M
ns
-
-
-
-
-
-
-
-
-
-
-
-
Lo Turco et al. 2007
L
F>W
-
-
-
-
-
-
-
-
-
-
-
-
Lo Turco et al. 2007
M
F>W
-
-
-
-
-
-
W>F
W>F
-
-
W>F
W>F
Mannina et al. 2008
S
F>W
-
-
-
-
-
-
W>F
W>F
-
-
W>F
W>F
Mannina et al. 2008
Md
F>W
-
-
-
ns
F>W
ns
ns
ns
W>F
ns
F>W
ns
Mnari et al. 2010a
Mv
F>W
-
-
-
ns
F>W
ns
ns
F>W
W>F
ns
ns
ns
Mnari et al. 2010a
L
F>W
-
-
-
ns
F>W
ns
ns
F>W
W>F
ns
ns
ns
Mnari et al. 2010a
M
F>W
-
-
-
W>F
W>F
W>F
W>F
W>F
F>W
-
-
W>F
Monti et al. 2005
M
F>W
-
-
-
-
-
-
-
-
-
-
-
-
M
F>W
ns
W>F
W>F
F>W
F>W
F>W
ns
ns
W>F
ns
W>F
ns
Orban et al. 2002
M
F>W
ns
W>F
ns
F>W
F>W
F>W
ns
ns
W>F
ns
W>F
F>W
Orban et al. 2003
M
F>W
F>W
W>F
F>W
F>W
F>W
ns
W>F
W>F
W>F
W>F
F>W
W>F
Ottavian et al. 2012
M
ns
ns
ns
-
ns
W>F
-
W>F
F>W
-
F>W
F>W
W>F
Periago et al. 2005
M
F>W
-
-
-
F>W
F>W
F>W
F>W
F>W
ns
W>F
F>W
F>W
Saglik et al. 2003
S
F>W
-
-
-
F>W
F>W
F>W
F>W
F>W
ns
W>F
F>W
F>W
Saglik et al. 2003
M
F>W
ns
ns
ns
W>F
F>W
-
W>F
F>W
-
F>W
-
-
M
F>W
-
-
-
sv
sv
sv
sv
F>W
ns
-
sv
sv
Alasalvar et al. 2002a
Erdem et al. 2007
Fasolato et al. 2010
Nasopoulou et al. 2007
Santaella et al. 2007
Yildiz et al. 2008
CHAPTER 5
Figure 5.3. Literature review of linoleic acid (LA) and arachidonic acid (ARA) on sea bream and sea bass
fish muscle with significant differences. Percentages of total FAs of wild fish (black bars) and farmed fish
(grey bars)
While the presence of characteristic
terrestrial fatty acids in farm diets provides
strong individual markers, the use of
multivariate analysis using FA profiles
further
strengthens
this
technique.
Multivariate analysis using FA profiles has
proved effective in assessing the influence
of coastal aquaculture on wild fish stocks
(Fernandez-Jover et al. 2007, 2009, 2011;
Arechavala-Lopez et al. 2011a). These
studies
have
usually
applied
gas
chromatography,
although
nuclear
magnetic resonance (NMR; Rezzi et al. 2007;
Mannina et al. 2008; Del Coco et al. 2009)
and near-infrared spectroscopy analysis
(NIRS; Ottavian et al. 2012) have detected
differences between wild and farmed sea
bream and sea bass, as well as their
geographic origin using lipids, FAs, and
different metabolites. However, these latter
techniques are not widely used for seafood
authentication due to problems in
procedure standardization (Forshed et al.
2003; Rezzi et al. 2007; Martinez et al. 2009).
Differences in lipid extraction, fatty acid
esterification and laboratory equipment
characteristics create variability among
results from different laboratories.
The most important source of concern
regarding all these techniques is the ‘washout’ of fatty acids and other metabolites,
due to feeding of escaped fish on natural
diets once in the wild (Chapters 2 and 3Arechavala-Lopez et al. 2012c). This process
will diminish the ‘signature’ farm-diet FAs
of terrestrial origin over time with the FA
profile of the escapee gradually becoming
more similar to those of wild fish. The FA
signature may clearly reveal the origin of
an individual if it has recently escaped from
a fish farm after being fed with commercial
pellets for a period of time (FernandezJover et al. unpublished data). However, postescape, the possibility exists that metabolic
and FA profiles will gradually modify if a
natural diet is sustained over time,
presumably weeks to months (Bell et al.
2003). How fast a change in fatty acid
pattern would occur is not possible to
97
SEA BREAM AND SEA BASS ESCAPEES
establish with certainty (Olsen and Skilbrei
2010). It is suggested that an escapee
captured after months feeding exclusively
on natural marine prey will have around
4% 18:2n-6 or less in muscle. However,
escaped fish can either consume feed
pellets around farms or be starving, and the
proportion of many fatty acids remains in
similar proportions throughout this period
(Johansson and Kiessling 1991; Olsen and
Skilbrei 2010). Thus, where detection of
long-term escapees is required, other
techniques are more appropriate.
of 13C than found for wild fish, for which
the scarcity of food induces a higher
metabolic turnover and results in less
accumulation of fat in the tissues. However,
different tissues provide variable results.
Serrano et al. (2007) found δ13C was only
depleted in farmed fish tissues with high
lipid contents, such as red muscle, the liver
and the gills. The variability in tissue lipid
content can alter bulk tissue δ13C values
(Focken and Becker 1998) and could be
falsely interpreted as dietary or habitat
shifts (Fasolato et al. 2010).
5.4.4. Stable isotopes
Stable isotope analysis is a powerful tool in
the analysis of trophic relationships in
aquatic environments. Carbon (13C),
nitrogen (15N) and oxygen (18O) are three
of the principal elements living organisms
are comprised of and ‘propagate’ from one
organism to another through food webs.
Assimilation and growth enriches the
isotopic signatures in marine vertebrates
(Serrano et al. 2007; Morrison et al. 2007).
The natural diet of wild fish depends on the
availability and accessibility of prey in a
particular habitat, which significantly
differs from a fish farm diet. Farmed fish
are cultured on manufactured diets
containing lower levels of marine-derived
raw materials which are often obtained
from non-local marine sources. Farmed fish
diets contain a significant terrestrial carbon
input from vegetable meals and oils, which
may reflect lighter isotopic content. Based
on these differences, stable isotope analysis
has been applied to discriminate wild and
farmed sea bream and sea bass.
Clear differences exist in the isotopic ratios
between wild and farmed fish in different
tissues of sea bream (Moreno-Rojas et al.
2007; Morrison et al. 2007; Serrano et al.
2007, 2008) and sea bass (Bell et al. 2007;
Fasolato et al. 2010; Ottavian et al. 2012).
δ13C was consistently lighter in farmed fish
than wild fish (Figure 5.4), which reflects
the different diets, and more specifically,
the use of terrestrial material (with lower
13C content) in the feed of farmed fish.
Farmed fish have higher lipid content in the
muscle, due to the high-fat diet that
produces tissues with higher lipid content.
This induces a larger isotopic fractionation
98
Figure 5.4. Literature review of δ13C isotopic
composition on sea bream and sea bass fish
muscle with significant differences. Percentages
of total FAs of wild fish (black bars) and farmed
fish (grey bars). All results are δ13 of the bulk oil
fraction of flesh total lipids; except (#) that is
from the glycerol/choline concentrated fraction
from flesh lipid extract.
With regard to δ15N, some authors
observed significant differences in the
nitrogen content and δ15N in muscle tissue
between farmed and wild sea bream
(Morrison et al. 2007) and sea bass (Bell et al.
2007; Fasolato et al. 2010), where wild fish
were isotopically enriched in 15N
compared with their farmed counterparts.
Such differences can be a consequence of
the higher trophic level of the fish feed in
the natural marine system, but it also may
vary according to the manufactured farmed
fish diet characteristics reflecting different
inputs from terrestrial N sources in farmed
sea bass (Fogel and Cifuentes 1993).
Moreno-Rojas et al. (2007) suggested that
differences in δ15N seemed to be more
informative of the geographical origin of
CHAPTER 5
fish, which could be related more to
differences in feed mixtures given to
farmed fish in each area or country than to
geological or environmental differences
among areas. Moreover, other factors may
influence δ15N, such as maturity or growth
rate, seasonal variations and analysis
techniques (Serrano et al. 2007, 2008). The
lipid extraction process should not affect
the 15N content of the defatted tissue,
unless the extraction process leaks proteins
linked to lipids (Soritopoulos et al. 2004).
Furthermore, analysis of δ18O from total oil
extracted from flesh lipid on sea bream
exhibited significant differences between
farmed and wild fish (Morrison et al. 2007).
In contrast, analysis of δ18O in sea bass
muscle did not show significant differences
(Bell et al. 2007). However, analysis of δ18O
may reflect latitudinal differences in mean
ocean δ18O, which is in isotopic
equilibrium with fish metabolic water and
therefore may discriminate between fish
caught in different geographical locations
(Bell et al. 2007; Morrison et al. 2007). The
utility of using δ18O as a discriminatory
factor between farmed and wild fish across
species must be carefully considered. While
the geographical location of farmed fish is
controlled, wild fish may migrate over
large geographical regions (Bell et al. 2007;
Morrison et al. 2007). The utility of
compound-specific isotope analysis has
been suggested as a powerful tool to
discriminate wild and farmed sea bream
and sea bass. Particularly, individual fatty
acid δ13C and bulk δ13C are good
indicators of farmed or wild fish origin.
Standardization of different methodologies
is required to provide a robust and method
able to be applied consistently over a range
of species from both the aquaculture and
fisheries sectors.
5.4.5. Trace elements
Marine fish incorporate different trace
elements from the environment into their
skeletal tissues and organs, either present in
seawater or the diet, forming a chemical
signature that will reflect the length of time
that a fish has inhabited a particular water
body (Lal 1989). Hence, trace element
profiles are likely to be unique to a given
population that inhabits one given location.
Wild populations of sea bass and sea bream
in the Mediterranean move among various
coastal habitats, thus it is difficult to detect
substantial differences in trace elemental
signatures among different populations of
wild fish (Gillanders et al. 2001). However,
aquaculture creates a special situation in
which fish are static in one location with
unique environmental conditions. Under
such circumstances, a distinct trace element
composition is likely to appear (Patterson
and Kingsford 2005). Where cage farming
exists, in addition to the natural presence of
metals in the aquatic environment from
geochemical and anthropogenic processes,
extra sources of trace metals may result
from
metal-based
antifoulants
used
periodically to protect the nets from
fouling, such as Cu. Fish diets are also
enriched with various essential metals,
including Cu, Fe, Zn, Mn, Co, Cr and Mg
among others (CIESM 2007).
Therefore, differences between farmed and
wild sea bream and sea bass have been
found through trace element analysis (See
Table 5.5). However, contrasting results
have been reported within the reviewed
literature. In sea bream, muscles of wild
fish were found to be more polluted than
farmed fish, presenting significantly higher
values of Hg and As (Minganti et al. 2010),
and either discrepancies or no significant
differences on other studied elements were
reported (Carpene et al. 1998; Minganti et al.
2010). Regarding trace elements in otoliths,
farmed sea bream presented higher values
of Ba, Mn and Fe, and lower of Sr, than
their wild conspecifics (Sanchez-Jerez et al.
unpublished data). The calcified tissues do
not incorporate trace elements in the same
way, since otoliths only incorporate trace
elements that are present in the
endolymphatic fluid that bathes them,
whereas scales incorporate trace elements
directly from the blood plasma (Wells et al.
2000). The trace metal microchemistry of
salmon scales has been successfully used to
discriminate between farmed and wild fish
(Adey et al. 2009) and differences were also
seen between farmed fish that shared the
same water body and diet – presumably
caused by subtle differences in local water
chemistry. Recent research within the
Prevent Escape project shows that a similar
analysis effectively discriminates wild and
99
SEA BREAM AND SEA BASS ESCAPEES
farmed sea bass and sea bream in the
Mediterranean (Black et al. unpublished
data). In sea bass, reviewed trace elements
analysis in muscle and liver showed
considerable divergence among the results.
However, it seems that wild sea bass
contain a higher proportion of heavy
metals, such as Hg and Pb, probably as a
consequence of pollution of the seawater by
industrial discharges (Monti et al. 2005). It is
remarkably that toxic elements, which have
been considered to be detrimental to
humans if ingested in concentrations above
certain levels, were present at levels below
their hazard level in all reviewed studies.
Interestingly Cu, which is below detection
limit in the studied wild fish, was present
in a measurable amount in farmed fish,
probably from anti-fouling components
(Monti et al. 2005, Ferreira et al. 2010).
Through scales and otoliths, farmed sea
bass showed higher values of Mn and Ba,
and lower of Sr, than wild sea bass. Despite
the fact that studies gave contrasting
results, most were able to distinguish wild
and farmed fish with great accuracy, but
only through a multivariate approach
which accounted for a wide range of
elements. No simple diagnostic elemental
concentration or ratio exists. This indicates
that the trace elemental profile might be
more appropriate than the presence or
absence of a specific quantity of an element.
5.4.6. Accumulative pollutants
Marine organisms can be contaminated by
potential exposure to various pollutants
such as organochlorine compounds (OCs)
and heavy metals, resulting in most of the
cases from the direct consumption of feed
or from the surrounding environment
(Grigorakis and Rigos 2011). These OCs are
represented mainly by polychlorinated
biphenyls (PCBs), polycyclic aromatic
hydrocarbons (PAHs), polychlorinated
dibenzodioxins (PCDDs), polychlorinated
dibenzofurans
(PCDFs),
polybrominateddiphenyl ethers (PBDEs),
hexachlorobenzenes
(HCBs),
dichlorodiphenyltrichloroethane (DDT) and
its degradation product (DDE) (Antunes
and Gil 2004; Ferreira et al. 2010; Grigorakis
and Rigos 2011). The organochlorines are
lipophilic or hydrophobic compounds that
accumulate preferentially in adipose
100
tissues, therefore, the higher fat content of
farmed fish indicates that they may have a
larger reservoir for absorption of such
persistent contaminants compared to their
wild counterparts (Grigorakis and Rigos
2011).
Several studies have documented the
occurrence of various organochlorines in
aquaculture products and feed by
providing useful comparisons between
wild and farmed fish in both sea bream and
sea bass species in the Mediterranean.
Concerns were initially raised with the
report of higher pollutant levels (e.g. PCBs,
toxaphene or dieldrin) for salmon
aquaculture (Hites et al. 2004). However,
farmed sea bream have lower levels of
pollutants in their tissues than wild sea
bream, with both groups always containing
levels below the guidelines recommended
for human consumption (Serrano et al. 2008;
Blanes et al. 2009). Total PCBs and DDTs in
the muscle, liver and gills are higher in wild
fish than in cultured sea bream, with the
highest concentration of pollutants found in
tissues of higher lipid content, despite the
higher biomagnification factors found in
farmed specimens (Serrano et al. 2008;
Blanes et al. 2009). The concentration of OCs
is uniform throughout the year in farmed
sea bream, while wild fish showed higher
seasonal
variability,
reflecting
environmental factors and seasonality in
growth rates. The low levels of
contaminants found in the feed supplied to
farmed
sea
bream
explain
the
organochlorine concentrations in their
tissues which remain below wild fish, in
spite of the intensive culture conditions and
higher trophic level of cultured specimens
(Serrano et al. 2008; Blanes et al. 2009).
In contrast, farmed sea bass are more
contaminated than wild sea bass, but their
levels were also below those recommended
for human consumption. Wild specimens
have lower levels of total PCBs and DDTs,
both in the liver and muscle, compared
with cultured bass (Antunes and Gil 2004;
Carubelli et al. 2007; Fernandes et al. 2007;
Lo Turco et al. 2007). Similarly, Ferreira et
al. (2010) found a higher accumulation of
OCs in cultured sea bass in the EasternAtlantic, but lower concentrations of metals
compared to wild bass. Higher exposure to
CHAPTER 5
PAHs was also observed in wild sea bass
(Fernandes et al. 2007). As for sea bream,
these differences have been attributed to
the level of contaminants present in the diet
and different feeding characteristics due to
the intensive culture in the farms (Antunes
and Gil 2004; Serrano et al. 2008).
Table 5.5. Resulting trace elements on different tissues for sea bream and sea bass from the literature
reviewed. M: muscle; O: otoliths; S: scales; L: liver; d: dorsal; v: ventral; F: farmed fish; W: wild fish; ns: no
significant differences.
Tissue
Na
K
Mg
Ca
Sr
Ba
Ti
V
Cr
Mo
Mn
Fe
Co
Black et al. u.d.
S.
-
-
Ns
-
W>F
W>F
Ns
W>F
F>W
F>W
Ns
F>W
ns
Carpene et al. 1998
M.
-
-
-
-
-
-
-
-
-
-
-
ns
-
Minganti et al. 2010
M.
-
-
-
-
-
-
-
ns
ns
ns
ns
ns
-
Sanchez-Jerez et al. u.d.
O.
-
-
ns
-
W>F
F>W
-
-
-
-
F>W
F>W
-
Alasalvar et al. 2002a
M.
-
-
-
-
-
-
W>F
F>W
ns
ns
ns
W>F
ns
Black et al. u.d.
S.
-
-
Ns
-
F>W
W>F
ns
F>W
ns
ns
F>W
ns
ns
M.,L.
-
-
-
-
-
-
-
-
-
-
-
-
-
Ferreira et al. 2010
M.
-
-
-
-
-
-
-
-
-
-
-
-
-
Ferreira et al. 2010
L.
-
-
-
-
-
-
-
-
-
-
-
-
-
Fuentes et al. 2010
M.
ns
ns
ns
ns
-
-
-
-
-
-
ns
ns
-
Mnari et al. 2010a
dM.
ns
F>W
ns
F>W
-
-
-
-
-
-
F>W
W>F
-
Mnari et al. 2010a
vM.
W>F
W>F
W>F
W>F
-
-
-
-
-
-
F>W
W>F
-
Mnari et al. 2010a
L.
W>F
W>F
W>F
F>W
-
-
-
-
-
-
ns
W>F
-
Monti et al. 2005
M.
-
-
-
-
-
-
-
ns
ns
-
F>W
ns
W>F
Orban et al. 2002
M.
ns
ns
ns
ns
-
-
-
-
ns
-
-
F>W
-
Sanchez-Jerez et al. u.d.
O.
-
-
ns
-
ns
F>W
-
-
-
-
F>W
Ns
-
Santaella et al. 2007
M.
W>F
W>F
ns
ns
-
-
-
-
-
-
-
W>F
-
Ni
Cu
Ag
Zn
Cd
Hg
Al
Pb
B
As
Sb
P
Se
Sparus aurata
Dicentrarchus labrax
Fernandes et al. 2007
Sparus aurata
Black et al. u.d.
S.
F>W
F>W
ns
ns
ns
-
F>W
W>F
-
W>F
-
-
ns
Carpene et al. 1998
M.
-
ns
-
ns
-
-
-
-
-
-
-
-
-
Minganti et al. 2010
M.
-
ns
-
ns
-
W>F
-
-
-
W>F
-
-
-
Sanchez-Jerez et al. u.d.
O.
-
-
-
-
-
-
-
-
-
-
-
-
-
Alasalvar et al. 2002a
M.
ns
ns
ns
ns
ns
-
W>F
ns
-
-
-
-
-
Black et al. u.d.
S.
ns
ns
ns
ns
ns
-
W>F
W>F
-
W>F
-
-
W>F
Dicentrarchus labrax
Fernandes et al. 2007
M.,L.
-
F>W
-
ns
F>W
-
-
-
-
-
-
-
-
Ferreira et al. 2010
M.
-
F>W
-
-
ns
-
-
ns
-
ns
-
-
-
Ferreira et al. 2010
L.
-
ns
-
-
W>F
-
-
W>F
-
W>F
-
-
-
Fuentes et al. 2010
M.
-
ns
-
ns
-
-
-
-
-
-
-
ns
-
Mnari et al. 2010a
dM.
-
W>F
-
F>W
-
-
-
-
-
-
-
-
-
Mnari et al. 2010a
vM.
-
ns
-
F>W
-
-
-
-
-
-
-
-
-
Mnari et al. 2010a
L.
-
F>W
-
W>F
-
-
-
-
-
-
-
-
-
Monti et al. 2005
M.
ns
F>W
-
W>F
W>F
W>F
W>F
F>W
F>W
ns
ns
ns
ns
Orban et al. 2002
M.
-
-
-
F>W
-
W>F
-
-
-
-
-
ns
W>F
Sanchez-Jerez et al. u.d.
O.
-
-
-
-
-
-
-
-
-
-
-
-
-
Santaella et al. 2007
M.
-
-
-
W>F
-
-
-
-
-
-
-
F>W
-
5.4.7. Genetic differences
The intensification of fish culture over
recent decades has increased the need for
mass production of good quality eggs
or/and fingerlings to supply aquaculture.
Often, the genetic structure of cultivated
populations differs from wild populations
and this can be used to identify the origin
of fish. Genetic differences between
cultured and wild fish can be apportioned
across three hierarchical levels, where the
upper level includes the differentiation
101
SEA BREAM AND SEA BASS ESCAPEES
from the previous levels. The first level of
differentiation is due to founder effects and
is common for most cultured organisms.
Broodstock are captured from the wild, but
represent a small sample of the whole
population. Thus, they only carry a small
proportion of the genetic diversity of the
whole population. This founder effect is
often accompanied by the loss of rare alleles
and changes in allele frequencies.
Furthermore, the effective population size
is lower in cultured populations than in the
wild (Youngson et al. 2001). A slight
decrease of variability of genetic structure
in cultivated populations compared to wild
stocks has occurred for sea bream (Palma et
al. 2001; Alarcón et al. 2004).
The second level of differentiation occurs
when the farmed stock comes from a
different location and is genetically
different from the local wild population.
Sea bream and sea bass hatcheries export
eggs or fingerlings to fish farms in several
countries around the Mediterranean
(Youngson et al. 2001; Haffray et al. 2007).
Therefore, the genetic differentiation
between the wild and farmed populations
depends on the differences between local
populations and the population from which
the farmed fish originated. Wild population
genetic structure is well studied in
European sea bass. Three genetically
distinct zones exist: the Atlantic Ocean (the
Alboran Sea included), the western
Mediterranean
and
the
eastern
Mediterranean (Patarnello et al. 1993,
Allegrucci et al. 1997; García de León et al.
1997; Castilho and McAndrew 1998; Sola et
al. 1998; Bahri-Sfar et al. 2000, 2005; Castilho
and Ciftci 2005; Ergüden and Turan 2005;
Katsares et al. 2005; Lemaire et al. 2005).
Microsatellite markers have been used to
detect cases where (mostly Eastern
Mediterranean) population samples did not
cluster according to their geographic origin,
but with western Mediterranean samples
(Patarnello et al. 1993, Allegrucci et al. 1997).
Therefore, it is evident that some wild
stocks may have already been affected by
escapees (Bahri-Sfar et al. 2005).
Sea bream display a different pattern of
genetic differentiation to sea bass. Some
studies on wild sea bream show a slight
genetic
differentiation
between
102
Mediterranean populations, but this was
not apparently associated with geographic
or oceanographic factors (Youngston et al.
2001; Palma et al. 2001; Alarcón et al. 2004;
Ben-Slimen et al. 2004; De Innocentiis et al.
2004; Rossi et al. 2006). However, De
Innocentiis et al. (2004) identified a genetic
differentiation between Atlantic and
Mediterranean wild populations, and
further fine-scale differentiation within the
Mediterranean
Sea.
Despite
such
discrepancies, the migration of individuals
and
consequent
crossing
between
neighbouring populations seems to be the
main reason for the slight genetic
differentiation found (Palma et al. 2001), but
justifies the difference between local wild
sea bream populations and adjacent farmed
populations.
The third level of differentiation is the effect
of artificial selection through selective
breeding of cultured fish. When specific
characteristics are artificially selected, the
genetic structure of the genome may
change due to the hitchhiking effect.
However, dramatic changes in phenotype
do not occur rapidly. Sea bass and sea
bream are selectively bred (García de Leon
et al. 1998; Brown 2003) for commercially
desirable traits such as high growth rates,
disease resistance, absence of skeletal
malformations, altered aggression, and
adaptation to high stocking densities
(Boglione et al. 2001; Thorland et al. 2006;
Dupont-Nivet et al. 2008; Antonello et al.
2009; Navarro et al. 2009; Grigorakis and
Rigos 2011). In this process, little attention
is given to possible impacts on the genetic
integrity of wild stocks when farmed fish
escape (Miggiano et al. 2005). Therefore,
new alleles or allelelic combinations from
farmed fish (adults or eggs escapes) could
invade the local population and change its
genetic structure through introgression.
Although the impact of mixing of farmed
and natural populations has not been
assessed, theory suggests that captive-bred
organisms could reduce the fitness of wild
populations (Lynch and O’Hely 2001, Ford
2002, Araki et al. 2009). The genetic
structure of a local population is the result
of long-term interactions between the
population and the environment. Different
environments might favor different alleles
or allelic combinations which maximize
CHAPTER 5
fitness
populations
in
specific
environments. Genetic drift might also have
fixed different alleles
in different
populations. Furthermore, populations that
have undergone artificial selection could be
less fit in natural environments. Thus,
introducing farmed genotypes into local
wild populations could reduce the fitness of
wild individuals. In addition, the large
differences between natural spawning and
hatchery conditions involve the risk of
inbreeding, or causing artificial gene flow,
which could induce a biodiversity decline
or outbreeding depression (Sola et al. 1998).
wild stocks due to farmed escapees and
determine the contribution of escapees to
fisheries landings, robust fish-origin
indicators are required. Sanchez-Jerez et al.
(2012) used a Delphi-method, which is
based on questionnaires sent to experts, to
score different indicators according to their
effectiveness, ability to be used quickly,
accuracy, applicability and usefulness for
different sectors. This Delphi study and the
knowledge summarized in the present
review enable us to recommend indicators
to detect escaped sea bream and sea bass in
wild populations (see Table 5.6).
Differences in the genomic structure of
farmed and wild populations can be used
to develop genetic tags for the identification
of escapees. Moreover, genetic tagging of
sea bream and sea bass broodstocks in
commercial hatcheries might be a suitable
tool to monitor the genetic impact of fish
farm escapes and/or restocking releases
(Castro et al. 2007; Sola et al. 2007). The
advantage of genetic methods is that they
can be performed at all life stages; from egg
to adult. The accuracy of the “DNA standby method” (Glover et al. 2008, 2009a,b) for
the identification of escapees depends on
the degree of divergence of farmed from
wild populations. This method has been
successfully used to identify escapees in a
number of species such as cod, salmon and
trout (Glover et al. 2008, 2010), but has not
been applied for sea bream or sea bass.
Recent studies show that sea bream and sea
bass farmed populations are significantly
different from wild populations in the
Mediterranean (Karaiskou et al. 2009,
Loukovitis et al. 2012, Ladoukakis et al.
unpublished data). Thus, the “DNA stand-by
method” could be applied to identify fish
farm escapees for a wide range of
aquaculture species in all regions of the
world (Glover 2010).
Morphology and external appearance are
highly useful to distinguish farmed from
wild fish for both sea bream and sea bass.
Further, the use of external characteristics
(e.g. colour patterns, fin erosion, scale
features), combined with morphometry
(e.g. body and otolith shape, condition
index) or/and organoleptic descriptors (e.g.
textural parameters), are the easiest,
quickest and cheapest ways to discriminate
the wild or farmed origin of fish where the
purpose is to detect escapees in the shortterm in the weeks to months after an escape
event has occurred (Tables 5.2 and 5.6).
These techniques can be used directly in the
field with high accuracy (e.g. scales),
without laborious or expensive equipment,
and they do not require expert knowledge
or
specialization.
Organoleptic
characteristics are likely to be less useful in
this regard as an expert panel is required to
accurately
assess
such
descriptors.
Therefore,
we
recommend
external
characteristics and morphology as a means
to detect escapees immediately post-escape
for farmers, fishermen, sellers, consumers,
scientists and managers.
5.5. Implications and guidelines
Few studies have sought to develop
techniques with the purpose of identifying
escaped farmed sea bream and sea bass
within wild populations to assist in
determining their genetic and ecological
effects. To evaluate the potential risk to
How long these parameters persists postescape, which will influence their accuracy,
remains unknown. Hence, we recommend
the application of a holistic and
multidisciplinary approach using other
physico-chemical parameters for research
and management applications that require
tracing escapes for time scales greater than
several months. Chemometric tools can
discriminate wild and farmed origin for sea
bream and sea bass (Table 5.6).
103
104
-Environmental
Management
-Single
Individual Id.
-Original Farm
Stock
-Quick
Response
-Temporal
Persistence
-Fisheries
Management
-Sellers &
Consumers
-Farmers
-Effectiveness
D. labrax
-Environmental
Management
-Single
Individual Id.
-Original Farm
Stock
-Quick
Response
-Temporal
Persistence
-Fisheries
Management
-Sellers &
Consumers
-Farmers
-Effectiveness
S. aurata
Colour,
Shape
Colour,
Shape
Fin
Erosion
Scale
Features
External
Appearance
Fin
Scale
Erosion
Features
Body
Morphology
Condition
Index (K)
Otolith
Shape
Morphometry
and Somatometry
Body
Condition
Otolith
Morphology
Index (K)
Shape
Texture
Organol..
Characts.
Texture
Lipids
Total %,
LA, ARA
Proximate Comp.
and Fatty Acids.
Lipids
Total %,
LA, ARA
δ13C
δ13C
δ15C
δ18O
δ15C
δ18O
Stable Isotopes
Mn and Sr
in Scales
Mn and Sr
in Otoliths
Trace
Elements
Mn and Sr Mn and Sr
in Scales
in Otoliths
DNA
Stand-by
Genetic
Methods
DNA
Stand-by
Table 5.6. Colour table summarizing the recommendations for applicability of indicators of seabream and seabass escapes concerning to different aspects.
Range of colour corresponds from more accuracy or recommended (black) to less accuracy or recommended (white). (Modify from Sanchez-Jerez et al. 2012).
SEA BREAM AND SEA BASS ESCAPEES
CHAPTER 5
Specifically, the analysis of total lipids and
FA profiles (mainly the proportional
presence of LA and ARA), the proportion
of δ13C in fish flesh, and the presence of
specific trace elements (such as Cu and Hg
in fish flesh and Mn and Sr in otoliths and
scales), are likely to reflect the different
environmental and feeding characteristics
of fish. Moreover, several authors have
demonstrated the usefulness of a
multivariate approach, which draws upon
information
derived
from
diverse
techniques, as the best way to discriminate
fish origin and escapees with high
accuracy. However, such techniques are
usually expensive and require specific
knowledge, making them unavailable to
many sectors.
Fish physiology and biochemical process
are strongly influenced by geography and
seasonal variability, and limits to both the
detection and discrimination of chemical
characteristics should be established to
create analytical and management protocols
which can be widely applied.
In the future, new chemical or molecular
techniques may be developed that allow
discrimination of escapees with higher
accuracy (e.g. the use of unique chemical
otolith markers in juvenile fish from
hatcheries). Finally, the use of molecular
genetic markers is likely to be a suitable
tool for genetic discrimination of wild and
farmed fish, enabling monitoring of the
genetic impact of fish farm escapes and/or
restocking releases (Table 5.6). Broodstock
and their offspring should be genotyped in
hatcheries before going to open-sea cages,
and such information should be available to
the scientific community and managers, in
order to improve the accuracy and
suitability of genetic tools. Unfortunately,
genetic techniques, in spite of being nondestructive and being highly informative,
are among the most expensive and timeconsuming techniques currently available.
A wide range of fish origin descriptors are
available to detect escapees within wild
stocks. Some can be easily applied to
evaluate the contribution of escapees to
other sectors, such as fisheries, markets and
consumers, making them useful for rapid
assessments which do not require 100%
accuracy. As numerous tools can be used
to
achieve
specific
outcomes,
we
recommend that regulatory bodies must
establish protocols through legislation that
specify the most appropriate techniques to
each particular circumstance.
105
SEA BREAM AND SEA BASS ESCAPEES
106
CHAPTER 6
6. GENERAL DISCUSSION
6.1. Relevance of sea bream and sea
bass escapees
6.2. Guidelines for management
strategies
Sea bream and sea bass aquaculture is
already widely established in the
Mediterranean basin, mainly reared in
coastal net-pen facilities. In spite of the
reduction on sea bass and sea bream
production during the last three years, such
production is expected to increase in the
coming years, and may be carried out in
more exposed locations on open coasts
(Cardia and Lovatelli 2007). Therefore,
escape incidents in Mediterranean farms
and their related impacts are likely to
happen and even increase during next
years if measurements to prevent or reduce
them are not taken into account on
aquaculture management.
It is evident that there are significant risks
to ecosystems through escapes from
aquaculture
and
that
management
measures should be taken to eliminate or
minimize those risks, which ensures that
economic, social, and ecological benefits
from aquaculture are jointly achieved. It is
clear that with the expected growth of
marine aquaculture in the future, any
rational policy for addressing escapes must
focus first on prevention, but follow up
with strong management measures to
eliminate, or at least minimize, ecological
damage once escapes occur. These
measures must be cost effective, but the
benefits of protecting ecosystem integrity
should be accounted for as well.
In this thesis it was demonstrated that
escaped sea bream and sea bass are
biologically able to survive for long periods
once in the wild, feeding on natural preys
and swimming to nearby farm facilities and
coastal habitats (feeding and spawning
areas). Hence, it is reaffirmed the
interactions among escapees and nearby
farmed stocks, wild conspecifics and native
fish assemblages, which could lead to
environmental consequences (Figure 6.1).
Apart from economic losses to farmers,
escapes can also interact with local fisheries
through alterations of wild fish stocks.
However, escapees can remain around
farms during the first days following and
escape incident, but also disperse to coastal
fishing grounds, so the recapture of
escapees by local fishermen is an important
remark for future management strategies.
Therefore, other related sectors such as fish
markets and consumers can be also affected
(Figure 6.1).
Thus, the knowledge acquired in this thesis
helps us to better understand and evaluate
the potential effects of escapees in different
sectors, and highlights the necessity to
apply new management tools and measures
to prevent and reduce escapees and their
impacts, for a forthcoming sustainable
aquaculture activity.
6.2.1. Prevention, mitigation and
impact reduction strategies
First management steps must be taken to
prevent
introduction
of
infectious
pathogens in the ecosystem, as well as to
prevent escape incidents (both individuals
and gametes) which could damage the
health (ecological and genetic) of wild
populations of marine organisms. Control
of diseases in farmed fish can be achieved
by animal health, biosecurity programs and
other disease control measures (e.g.
including disease management areas or
surveillance zones around farms in site
selection programs) which are the most
effective, cost efficient, and long lasting,
usually designed to minimize the risk of
disease transmission in the different types
of facilities (Meyer 1991; Bondad-Reantaso
and Subansinghe 2008; Lyngstad et al.
2008). Disease control regulations for the
Mediterranean fin-fish aquaculture are well
established (Rodgers and Basurco 2009),
but the current legislation dealing with
health management issues are not
homogeneous
throughout
the
Mediterranean countries (Cardia and
Lovatelli 2007).
First of all, fish health and biosecurity
management must be improved at all levels
of the fish farming industry as the best tool
for the prevention, control and eradication
109
110
Consumers
Prof. Fisheries
Recreat. Fisheries
Aquaculture
Wild
Conspecifics
- increased government regulation/monitoring [Fa, Ma]
- develop containment plans [Fa, Ma]
Mitigation and impact reduction measures:
- genetic breeding selection [Fa, Sc]
- Ecosystem health/services
- Size frequency and densities
alterations of wild stocks
- Hybridization
- Genetic drift
B)
A)
Fisheries
Fisheries
~
~
Markets
Consumers
Consumers
B) MASSIVE ESCAPES
- Higher captures of escapees
- Lower captures of target sps.
- Lower incomes
- Lower prices in escaped sps.
- Higher prices in target sps.
Markets
long-term
A) SHORT-SCALE ESCAPES
- Low captures of escaped sps.
- Fraud in prices
- Higher incomes
- Affected consumers
- More fish to capture / more fun
- Lower recreational target species
- Losses on farmed stocks
- Lower production and lower incomes
- stricter guidelines for vessel operations [Fa, Ma, Fi]
- Populations dynamic changes
Interbreeding
Proper labelling of marketed fish (#) [Fa, Fi, Co, Se]
Improved human health and food safety legislation [Fi, Co, Se]
- socio-economic studies [Fa, Co, Se, Sc]
- fisheries studies [Fa, Fi, Sc]
Asses the contribution of escapees on fisheries landings: (#)
Escape prevention measures and mitigation plans [Fa, Fi]
Monitoring wild fish populations (#) [Sc, Fi]
Application of risk assesment [Fa, Sc, Ma]
Improved legislations about escapees [Fa, Ma, Fi]
-develop escapees recapture methods [Fa, Fi, Sc]
- compulsory reports of the escapes incidents [Fa, Ma]
- locating farms in appropriate areas [Fa, Ma]
- improved staff training [Fa]
- Feral stock establishment
- improved management/maintenance of structures [Fa]
- Local species introduction
Habitat competition
Mate competition
- improved farming techniques and technology [Fa]
Escape prevention strategies :
Minimum safe distance among farms [Fa, Ma]
Fish health and biosanitary regulations [Fa, Ma]
- Resources availability
- Food chain alterations
- New pathogens introduction
- Disease outbreaks
Food competition
Prey-predation
interactions
Disease / parasites
transmission
NOTE: K, condition factor; M, morphology; FA, fatty acids; SI, stable isotopes; TE, trace elements; G, genetic methods; * only for recent escapees.
-Sellers [Se]: K*, Scales
-Consumers [Co]: K*, Scales
-Scientist [Sc]: Scales, M*, K*, FA, SI, TE, G.
-Fisheries [Fi]: M*, K*, Scales
-Managers [Ma]: Scales, M*, K*, FA, SI, TE, G.
-Farmers [Fa]: Scales, K*, M*, FA, G.
(#) Escapees identification tools:
ESCAPES
Wild
Populations
Farmed
Stocks
Figure 6.1. Summary of interactions of Mediterranean escapees with wild populations, farming industry , local fisheries and consumers: consequences, guidelines and solutions.
SEA BREAM AND SEA BASS ESCAPEES
CHAPTER 6
of infectious disease and the preservation of
human, animal, and environmental health
(Lee 2003). In the case of sea bream and sea
bass grown in open-sea cages, pathogens
can be transported in association with
movement of equipment, staff and vessels
(Kennedy and Fitch 1990; Alderman 1996;
Ruiz et al. 2000; Murray 2005). Therefore,
biosecurity
measures
must
include
husbandry hygiene control of movements
of fish, materials used in the farm and staff,
using of cleaning and disinfection products,
as well as appropriate personal protective
equipment, among other fish health
management strategies (Bondad-Reantaso
and Subansinghe 2008).
Moreover, water is able to transmit freemoving
pathogenic
agents
between
hydrodynamically connected discrete fish
farms (Amundrud and Murray 2009, Frazer
2009), but also Mediterranean escapees and
farm-aggregated fish are considered
important vectors of diseases transmission
to either farmed stocks or nearby wild fish
populations. This implies that the existing
spacing system for fish farms requires
reconsidering based on knowledge of not
only hydrodynamics and human activities
but also of the fish movements around farm
facilities and nearby coastal waters, since
supra-local regions or important marine
areas (e.g. spawning or protected areas,
fishing grounds, etc.) could be negatively
affected. Thus, proper sitting of these types
of systems, however, may provide a means
of geographically limiting the ecological
and genetic interactions between farmed
and wild stocks.
Furthermore, it is important to take
significant steps to reduce the escapes
incidents by using advanced cage
technology and preventive management
practices.
Farming
techniques
and
technology should be improved to
effectively contain the organisms and
minimise the possibility of escape, such as
the use of adequate mooring systems,
floating structures and good quality and
suitable net cages. Thus, introducing
enforceable technical regulations for the
design, dimensioning, installation and
operation of sea-cage farms is required.
Moreover, certain operations within fish
farming are likely to pose a higher risk of
an escape event occurring if they are done
incorrectly. For instance, the anchoring and
mooring, connecting net-cages to floaters,
weighting of net-cages in currents, vessel
operations, the transfer organisms, grading
and harvesting, the inspections of net cages
and repairs, among others. Therefore, these
key processes should be identified, and
stricter
management
measures
and
mandatory training of staff who undertake
these processes would likely reduce human
errors that lead to escapes.
In addition, farmers should report the
escape incidents, as well as the presence of
infectious episodes, and share this
information among those relevant actors in
the area to develop shared management
plans. Management agreements by groups
of neighbouring farms are therefore an
essential tool in risk mitigation (Gustafson
et al. 2007), although generally lacking in
everyday practice. This becomes even more
important if escaped farmed stock were
under chemical treatment or vaccination
programs, which could negatively influence
consumer´s health if escapees are caught by
local fishermen and reach fish markets.
Containment management plans as a
preventive measure at farms should be
established in the Mediterranean countries
for a quick response in case of escape
incidents. The success of such a broadranging programme relies on the constant
open and interactive communication and
information exchange (Stipa and Angelini
2005).
Moreover, contingency plans should be set
up for recapturing escaped individuals in
the Mediterranean, where personnel must
be properly trained. Indeed, aquaculture
companies and local fisheries could
develop different recaptures methods
together according to temporal and spatial
characteristics, such as the environment,
behaviour of escaped species, and local
fisheries activity in this region. Recovering
escaped sea bream and sea bass around the
cages within some days/weeks of escape
seems to be difficult. However, increasing
the fishing activity by commercial or
recreational fishermen in the vicinity of the
farm after a major release could be efficient.
Fishing techniques could also be adapted,
including the use of specific devices, which
111
SEA BREAM AND SEA BASS ESCAPEES
perhaps would otherwise be illegal, under
specific authorisation for this purpose
(ICES 2006). This raises the problem of the
property rights provided that the fish
become “res nulla” when they are out of the
cage, even if the ground where the fish are
caught is rented to the fish farmer. Here
some clarification of the law could ease the
process. The degree to which a fish farm
should be monitored must be a function of
the degree of risk arising from the farming
system (ICES 2006).
6.2.2. Strategies for genetic
consequences
Careful planning and management to
prevent
introductions
of
escapees
(including non-native species and strains)
and release of gametes from marine
aquaculture facilities are more effective
than attempting to fix problems after those
species have become established or after
foreign genetic material has been
introduced. In some ways the introduction
of foreign genetic material may have more
insidious impacts on wild populations
because of the potential for these genes to
spread within the native population and
weaken its genetic structure. This is
especially true when the wild populations
are already depressed for a variety of other
reasons and when the level of farm escapes
is high relative to the wild population size.
Among the solutions that could be
proposed to the genetic problems posed by
Mediterranean escapees are: (i) the farming
of local strains, or (ii) the use of genetically
modified organisms (GMOs).
Farming of local stocks may be questioned
on two counts. First, within very few
generations farmed stock are likely to have
gone through a number of selection
bottlenecks, deliberate (e.g. selection for
growth, shape, colour, etc.) or accidental
(disease), thereby reducing heterogeneity.
In other words, farmed local stocks rapidly
begin to differ from their wild ancestors.
Secondly, few farmers would countenance
returning to the wild to seek broodstock,
thereby foregoing the benefits of selective
breeding on growth performance and
introducing the risk of importation of
disease to the farm (Beveridge 2001). In
addition, farming local strains do not solve
112
the risk of fertilized eggs escaping from net
pens, and potentially recruiting in the
environment; so further research are
necessary attempting to reduce the released
eggs.
Genetic selection for traits favourable for
fish aquaculture is widely used (Gjedrem
2000), mostly focused on enhancing the
growth and food conversion efficiency on
farmed fish species. In recent years,
experimental trials have demonstrated the
potential commercial advantage of GMOs
for some species (Maclean and Laight 2000).
Moreover, it appears quite likely that they
will eventually be used in European
aquaculture, but also suggested as a
solution
for
the
reported
genetic
consequences (Youngson et al. 2001). The
degradation of the wild strains of cultured
species due to genetic interactions could be
avoided by using sterile or triploid GM fish
(Naylor et al. 2005).
However,
many
difficulties
and
uncertainties remain to be solved for most
species. Although triploids are often sterile,
normal diploid individuals often remain
among the resulting stock. Moreover, they
tend to have a poorer grow-out
performance and survival than diploids,
and are prone to the development
deformities (reported in salmonids) that
affect growth and marketability (Benfey
2001, Sadler et al. 2001). In addition, there is
a observable consumer resistance to
consume GMOs, and a general concern
regarding their unknown environmental
effects on native populations, particularly
of the same species (e.g. Beringer 2000).
Therefore, there are many questions with
regard to performance and economics of
production of sterile fish as well as to their
marketing to solve, since triploid fish do
not generally perform well in culture and
producer organisations see little benefit of
developing the technology in terms of
marketability.
6.3. Risk analysis of sea bream and sea
bass escapees
Risk analysis is an important tool in
designing and justifying regulatory actions
in the international market place, for
CHAPTER 6
instance in the evaluation of the
environmental
effects
of
escaped
aquaculture
fish.
Regulators
and
developers need to make decisions on
investment and development opportunities
and proposals, taking account of the wide
range of issues concerned. In many cases,
full information on the probability of
undesirable environmental interactions
may not be available, so risk analysis helps
them to make important decisions with
higher certainty (ICES 2006). Risk analysis
consists, therefore, in a model of a clear and
transparent process that regulators can use
to come to justifiable decisions regarding
the management of their resource allocation
decisions. It provides an objective,
repeatable, and documented assessment of
risks posed by a particular course of action.
of uncertainty in our prediction of the
outcome?
Therefore, ecological risk assessment can be
considered a preventive measure for
sustainable
aquaculture
management,
which assesses the potential risk on the
biological interaction of farmed stocks,
escapes and wild fish populations.
Fairgrieve and Nash (2005) built a general
conceptual risk assessment model for
escapees according with their frequency
and intensity (see Figure 6.3), where it can
be observed how number and fitness of
wild fish populations might be affected
through different environmental process
after an escape incident.
Risk analysis can be broken down into four
components: 1) risk communication; 2)
hazard identification; 3) risk assessment;
and 4) risk management (see Figure 6.2
where the process and its components are
represented diagrammatically).
Figure 6.2. The four components of risk analysis
(ICES 2006).
Risk communication is the process by
which information and opinions regarding
risks are gathered from potentially affected
and other interested parties (stakeholders)
during a risk analysis, and by which the
results of the risk assessment and proposed
risk
management
measures
are
communicated to the decision makers and
stakeholders.
Hazard
identification
involves identification of those aspects of
the cultivation process (escape incidents in
our case) that could potentially produce
adverse consequences for the local
environment. Risk assessment tries to
answer the question: How likely is it to go
wrong and what would be the
consequences of it going wrong? Last, risk
management tries to answer: What can be
done to reduce the likelihood or
consequences of it going wrong, or the level
Figure 6.3. Conceptual model for biological
interactions of escapes with wild populations
(Fairgrieve and Nash 2005).
In this model, the two sources of biological
interactions from the escape of cultured fish
or their gametes from aquaculture facilities
are catastrophic releases (periodic natural
events such as storms) and chronic releases
(Figure 6.3). Their impact, however, is
modified by a number of things, amongst
which importantly are the numbers and the
genetic characteristics of both the escapees
and their resident indigenous wild
populations (for further details see
Fairgrieve and Nash 2005). Regardless of
the manner of escape, escapees may affect
the natural population in a number of
113
SEA BREAM AND SEA BASS ESCAPEES
ways. These authors reported that the most
important and direct consequence is
interbreeding, followed by the indirect
consequence of competition for mates and
nesting sites. In brief, the outcome can be a
reduction in the numerical or genetic
strength (fitness) of the wild population,
and possibly a reduction in fitness in other
fish populations. In agreement with the
management measures mentioned in
previous section, they suggested that
ecological risks from the biological
interactions of unplanned releases with
wild populations can be greatly reduced, as
they cannot be deleted altogether, by good
management practices.
However, other studies have been carried
out about environmental interactions of sea
bream and sea bass escapees, splitting
genetic and ecological interactions to obtain
a more detailed assessment of each risk
(ICES 2006; Sanchez-Jerez et al. 2012). It
must be noticed that the latter study was
done basing on the results obtained in the
present thesis. Therefore, the risks to wild
sea bream and sea bass populations posed
by escaped farmed fish was evaluated by
considering a list of biological questions of
relevance to genetic, and ecological issues,
suggesting
different
management
strategies in each specific interaction (see
table 6.1).
The final rating reported in both risks
evaluations were similar. For sea bream,
both genetic and ecological interactions
indicated a low intensity, low probability
and high uncertainty. For sea bass, both
genetic
and
ecological
interactions
indicated
also
low
intensity
and
probability. However, genetic interactions
indicated medium uncertainty while for
ecological
interactions
was
high.
Aquaculture of sea bass and sea bream is
relatively aged and many escapes have
been happening from the 90’s, without at
the moment evidence for deleterious effects
on wild populations. No complain from
professional fisher about the situation of
sea bass and sea bream catches could give
an idea low intensity risk. However the lack
of evidence could be purely an indication of
uncertainty and not absence of effects, but
because of the research effort carried out
during the last years, we can attribute a
114
medium uncertainty. However, there are
still many unsolved questions about
farmed, escaped and wild fish interaction,
and further research effort is indispensable.
6.4. Gaps of knowledge and future
research
Through this thesis, it was evidenced that
an improvement of current management
strategies is highly necessary as a starting
point to prevent and reduce the potential
environmental impacts of Mediterranean
escapees on coastal ecosystems, and
therefore, to ensure the sustainable
development of Mediterranean farming
activity. However, these strategies tools
must cover all levels of aquaculture
activity, from the production unit (pond,
tank, cage, etc.), farm, district/local or zone
levels,
to
the
national
and
regional/international level. In addition,
the suggested measures should be included
within governmental monitoring and
regulations,
improving
the
present
legislation concerning fisheries, human
health and food safety taken into account
the environmental and socio-economic risk
of escapees, to ensure that aquaculture
development is economically efficient and
causes minimal impact.
For that, further research is necessary to
cope with all this subjects due to the lack of
knowledge
that
still
exists
about
Mediterranean escapees, which will help to
improve effective risk assessment and
reduce uncertainty in predicted outcomes.
For instance, it is essential to monitor the
current local wild fish population where
the fish farming activity set up or will be
developed. Better information on the
structure and habitat use of wild
populations, as well as the health status of
an ecosystem could determine the further
successful or decline of introduced escapees
in the ecosystem. Evaluation of potential
effects on species or meta-population level
might disguise elevated probabilities of
effects for small local stocks.
Moreover, such studies should be had into
account for coastal planning management
or site selection programs for sea bream
and sea bass farm facilities. Another
options could be maximise the wild stocks
CHAPTER 6
in areas where farming activities are based,
particularly where wild stocks are scarce, to
decrease the impact of releases in a given
environment. In addition, it should be also
invested the development of practical offshore systems or economically competitive
land-based
technologies
to
reduce
interactions with inshore wild populations.
Table 6.1. Risk assessment and suggested mitigation measures of logical model steps regarding genetic
and ecological impacts of Mediterranean sea bream and sea bass escapees. I: intensity; P: probability; U:
uncertainty (modified from ICES 2006 and Sanchez-Jerez et al. 2012).
Logic Model Steps
Genetic
SEA BASS
Mitigation
I
P
U
I
P
U
Sea bream farms are established
in coastal waters
H
H
L
H
H
L
Where feasible move to land- based
production
There are phenotypic differences
between the wild and cultured
sea bream populations.
L
M
L
H
H
L
For each generation recruit all grow-out
stock from juveniles captured in the
wild.
Cultured sea bream escape from
cages
M
H
L
H
H
L
Improve escapees prevention measures
These phenotypic differences
arise primarily for genetic rather
than environmental reasons.
L
M
L
H
H
L
The primary route for genetic
interaction (interbreeding)
between cultured and wild sea
bream is through escapes of sea
bream from cages.
M
H
L
H
H
L
Cultured sea bream interbreed
with wild sea bream.
H
(biological questions)
General
SEA BREAM
(regulated/design/modified practices)
Recovery plan for escaped fish
Improve containment design and/or
build in fail-safe measures
Locating farms far from susceptible
areas (e.g. spawning grounds)
H
L
L
M
M
Use of sterile fish
Improve containment design and/or
build in fail-safe measures
Locating farms far from susceptible
areas (e.g. spawning grounds)
Ecological
The progeny of this interbreeding
(hybrids) show reduced fitness
L
L
M
L
L
H
For each generation recruit all grow-out
stock from juveniles captured in the wild
Sufficient gene flow to affect
survival rates of sea bream in
individual fisheries management
units.
M
L
L
L
L
M
Limit the distribution of sea bass
farming to either proximity to small
value stocks or very large stocks.
Genetic interaction caused
declines in endemic,
evolutionarily significant units
(populations).
L
L
L
L
L
L
Gene flow is pervasive and
persistent enough to affect fitness
at the level of species or metapopulation.
L
L
L
L
L
L
Limit the distribution of sea bass
farming in relation to the distribution of
the species or metapopulation
Cultured sea bass and sea bream
survive for a sufficient period to
entail ecosystem effects.
M
M
L
M
L
H
Improve escapees prevention measures
Escapees prey on conspecifics or
other species to such a degree that
potential prey species are
negatively affected
H
Escapees are able to successfully
compete with conspecifics or
other species over limited
resources like food, habitats and
mates
L
Escaped sea bass and sea bream
spread diseases and parasites that
may affect wild organisms
negatively.
L
Explanatory notes:
Recovery plan for escaped fish
L
H
M
L
H
Improve escapees prevention measures
Recovery plan for escaped fish.
Locating farms far from susceptible
areas (e.g. feeding or spawning grounds)
M
H
L
M
H
Improve escapees prevention measures
Recovery plan for escaped fish
Locating farms far from susceptible
areas (e.g. feeding or spawning grounds)
L
H
L
L
H
Improve containment design and/or
build in fail-safe measures
Recovery plan for escaped fish
Locating farms in appropiate areas (e.g.
safe distance among farms)
Severity = C – very intense, H – high, M – Moderate, L – Low, N – Negligible
Probability = H – High, M – moderate, L – Low, EL – Extremely Low, N – Negligible
Uncertainty = H- Highly uncertain, M – Moderately uncertain, L – Low uncertainty
115
SEA BREAM AND SEA BASS ESCAPEES
Furthermore, studies to determine the
survival of escapees, their migration
patterns in relation to their location (e.g.
inshore or offshore), their age (e.g. juveniles
or adults), the type of escape incident (e.g.
short-scale or massive), and the season they
are released (e.g. spawning period) are also
important.For instance, the impact of
releases in summer may be different from
winter, when sea bass and sea bream are
not
feeding
intensively
but
are
reproducing. Still, knowledge about the
nature of many infectious pathogens and
their pathways are at present scarce
(Raynard et al. 2007), so to invest in
epidemiological studies on farmed, escaped
and wild fish, as well as other potential
hosts, would help to better understand
their pathogenesis and future management.
Furthermore, the design of a database to
record all the pathogenic events at the
Mediterranean scale are also needed to
better understand and fight the risks of
pathogens mediated by aquaculture to the
marine ecosystems. It would be also
important to improve genetic approaches
or develop new techniques to produce fish
unable to survive in the wild, sterile or
immature during the whole period in the
cage (e.g. the efficacy of photoperiod
control on maturation).
In addition, further research is necessary to
improved or adapt the current fishing
techniques to recapture escaped fish
around farms, which should be a
mandatory
within
escape
incident
management at farms. However, to
improve the current legislation in the
Mediterranean farming activity is required
in this case, reaching to an agreement
among farmers, managers and fishermen.
Moreover, development new techniques to
recapture the fertilized eggs released in the
cages by farmed fish is needed, and it
should be a requisite for any coastal
farming activity, at least until the
maturation and spawning of farmed fish
within cages are solved.
Since escapees are captured in fishing
grounds contributing on local fisheries
landings, the identification tools suggested
in this thesis (e.g. morphology, chemical or
genetic tools; see chapters 4 and 5) are an
efficient tool to assess the contribution of
116
escapees within wild stocks in both shortand long-term studies. Moreover, they
would be useful to weight up the
catchability
of
escaped
fish,
their
economically contribution for local fisheries
over different seasons, which would help
also to better understand the dynamic of
escapees
and
wild
populations.
Furthermore, such identification tools could
be applied to assess the proportion of
mislabelled escaped fish that are sold in
local fish markets as wild fish, and
therefore, to assure the origin of fish for
consumers.
Figure 6.4. Mislabelled farmed sea bream as
wild individuals at a local fish market.
Thus, it is manifested the necessity to
improve the current legislation, adding a
compulsory proper labelling of every
marketed fish, to eliminate the potential
fraud that exist at present. However, it is
required to improve such identification
tools, but also a protocol indicating which
technique should be applied in a
determined circumstance should be
established by governmental legislation.
For instance, genetic methods could be
applied to determine the stock origin of an
escapee,
chemical
procedures
for
environmental
monitoring,
and
morphometric tools in fish markets.
Finally, it is clear that actual aquaculture
activity and its regulations must be
updated taken into account the recent
CHAPTER 6
knowledge acquired in this thesis about sea
bream and sea bass escapees and their
interacions with local ecosystems, since
they are highly diverse and heterogeneous
throughout the Mediterranean, starting
from
regional
governments
within
countries.
117
SEA BREAM AND SEA BASS ESCAPEES
118
CONCLUSIONS/CONCLUSIONES
CONCLUSIONS
1. Farmed sea bream and sea bass are able
to survive for prolonged periods following
escape incidents from Mediterranean
coastal open-sea cages. Some of them
remained around farm facilities within the
first 2-3 days after escape, and swam to
nearby farms during the first week and
through coastal shallow waters up to
several weeks.
2. Escaped sea bream and sea bass
presented a high dispersion throughout the
study area; however, it must be considered
the existence of a high mortality rates,
probably due to natural predation around
the cages and in coastal habitats.
3. Those sea bream escapees that remained
aggregated at farms presented a clear
diurnal behaviour, which could help to
develop new methodologies for recapturing
escapees immediately following an escape
event.
4. Escaped sea bream occupied natural
coastal habitats (mainly seagrass and sandy
areas) in a short term, where they quickly
learn to feed on natural preys (crustaceans
and molusks). In contrast, escaped sea bass
dwelled only estuaries and harbours but
seemed that they needs more time to get
used to the new environment and learning
to forage compare to escaped seabream.
5. Local fisheries, both artisanal (for
seabream) and recreational (for seabass),
can contribute in great measure to reduce
such potential risks of escapees through
recapturing them in coastal fishing
grounds.
6. Regarding identification tools, scale
characteristics analysis is the easiest and
quickest way to identify an escapee in the
field, and it is very useful for fishermen,
fishmonger and consumers.
7. External appearance and morphometry
(both body and otoliths shape) could be
useful in recent escape events, especially on
sea bream, and could complement the
identification by other techniques.
8. Chemical techniques (e.g. fatty acids,
stable isotopes or trace metals) could be
used for environmental monitoring, but
further studies are necessary to improve
their usefulness in long-term escapes.
9. Genetic methods could be applied to
determine the stock origin of an escapee in
long-term studies with the highest
accuracy, but is expensive and genetic
profiles of fish from hatcheries are needed.
10. The identification techniques of
escapees are important tools to be used on
fisheries and environmental assessments by
managers and scientifics to determine the
correct origin of captures and/or proper
labelling of marketed fish. However, it is
required to establish a protocol by
governmental legislation which indicates
the specific escapes identification technique
that must be applied in every determined
circumstance.
11. Although there is still a high uncertainty
about the potential consequences of
Mediterranean escapees, it is evident that
exist a complex environmental interaction
between escapees and wild populations
(through food, habitat and mating
competition, predation or disease and
pathogens transmission) which could alter
coastal ecosystems, essentially at a local
scale.
12. For a better assessment of potential
consequences of escapees, further studies
are needed to improve the current
knowledge about survival and interactions
of escapees with native fish stocks, to
properly monitor wild fish populations and
ecosystem status, as well as their
contribution of fisheries landings, and
therefore, the interaction of escapees with
fish consumers and their potential socioeconomic consequences.
13. Current escape prevention, mitigations
and
impact
reduction
measures
(contingency plans) must be improved
according to specific risks of escapees, and
should be a mandatory for farmers under
governmental regulations, supported by
local, regional or international legislations.
121
SEA BREAM AND SEA BASS ESCAPEES
CONCLUSIONES
1. Las doradas y lubinas de cultivo son
capaces de sobrevivir en el medio marino
del Mediterráneo tras escaparse de las
jaulas. Algunos individuos permanecen
alrededor de las jaulas los 2-3 primeros días
tras el incidente,
moviéndose entre
distintas instalaciones durante la primera
semana, y nadando en aguas costeras
someras durante varias semanas.
en dorada, pudiendo complementar la
identificación mediante otras técnicas.
2. Las doradas y las lubinas escapadas
presentan una alta dispersión por toda el
área de estudio, aunque también se debe
considerar la existencia de una alta
mortalidad, probablemente debido a
depredación natural alrededor de las
instalaciones y en hábitats costeros.
9. Los métodos genéticos se pueden aplicar
para determinar el stock de origen de un
escapado con alta precisión en estudios a
largo plazo, pero es caro y se necesitan los
perfiles genéticos de los peces procedentes
de los criaderos.
3. Aquellas doradas que permanecían
agregadas a las jaulas presentan un claro
comportamiento diurno, que podría ser de
ayuda para diseñar nuevas metodologías
para recapturar escapados inmediatamente
después de un escape.
4. Las doradas escapadas son capaces de
habitar en poco tiempo diferentes hábitats
costeros (principalmente praderas y
arenales) donde aprenden rápidamente a
alimentarse de presas naturales (crustáceos
y moluscos). Por el contrario, las lubinas
escapadas
ocupan
estuarios
zonas
portuarias pero parece que necesitan más
tiempo que las doradas para acostumbrarse
al nuevo medio y aprender a alimentarse.
5. Las pesquerías locales, tanto artesanales
(para doradas) como deportivos (para
lubina), pueden contribuir a reducir en
gran medida dicho riesgo mediante la
recaptura de escapados en caladeros
costeros.
6. En cuanto a las herramientas de
identificación, el análisis de las escamas es
el método más rápido y sencillo para
identificar un escapado en el campo, siendo
muy útil para pescadores, pescaderos y
consumidores.
7. La apariencia externa y la morfometría
(corporal y de los otolitos), podrían ser
útiles en escapes recientes, especialmente
122
8. Las técnicas químicas (p.ej. ácidos grasos,
isótopos estables o metales traza) se pueden
aplicar en estudios de seguimiento y
gestión ambiental, pero son necesarios más
estudios sobre su aplicabilidad en escapes a
largo plazo.
10. Las técnicas de identificación de
escapados son herramientas importantes
que deben ser usados por gestores, y
científicos, en estudios pesqueros y
medioambientales para determinar el
origen de las capturas y etiquetar
correctamente
los
pescados
comercializados. No obstante, es necesario
establecer un protocolo sobre la utilidad de
estas herramientas de identificación,
indicando la técnica que se debe aplicarse
en una determinada circunstancia, legislado
por los organismos gubernamentales.
11. Aunque aún existe una gran
incertidumbre
sobre
las
potenciales
consecuencias de los escapados en el
Mediterráneo, es evidente que existe una
compleja interacción entre los escapes y las
poblaciones
nativas
(mediante
competencia, depredación, transmisión de
enfermedades, etc.) que podrían alterar los
ecosistemas costeros, principalmente a
escala local.
12. Para evaluar mejor las consecuencias
potenciales de los escapados, son necesarios
más estudios sobre la supervivencia y las
interacciones de los escapados con los
stocks salvajes, y así poder gestionar
correctamente dichas poblaciones y el
estado del ecosistema, además de su
contribución en las capturas locales, y por
tanto, la interacción de los escapados con
los
consumidores
y
sus
posibles
consecuencias socio-económicas.
CONCLUSIONS/CONCLUSIONES
13. Se deben mejorar las medidas de
prevención, mitigación y reducción de
impacto (planes de contingencia) actuales
de las piscifactorías en función de los
riesgos específicos de los escapes, que
.
deberían ser obligatorias para los
acuicultores
bajo
normativas
gubernamentales, con el apoyo de las
legislaciones
locales,
regionales
o
internacionales.
123
SEA BREAM AND SEA BASS ESCAPEES
124
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ANNEX
ANNEX: PUBLISHED MATERIAL
Chapter 2:
Chapter 4:
Arechavala-Lopez P, Uglem I, FernandezJover D, Bayle-Sempere JT, Sanchez-Jerez P
(2012) Post-escape dispersion of farmed sea
bream (Sparus aurata L.) and recaptures by
local
fisheries
in
the
Western
Mediterranean Sea. Fisheries Research 121–
122, 126– 135.
Arechavala-Lopez P, Sanchez-Jerez P,
Bayle-Sempere
JT,
Sfakianakis
DG,
Somarakis S (2012) Discriminating farmed
gilthead sea bream Sparus aurata and
European sea bass Dicentrarchus labrax from
wild stocks through scales and otoliths.
Journal of Fish Biology 80 (6), 2159–2175.
Chapter 3:
Arechavala-Lopez P, Uglem I, FernandezJover D, Bayle-Sempere JT, Sanchez-Jerez P
(2011) Immediate post-escape behaviour of
farmed sea bass (Dicentrarchus labrax) in the
Mediterranean Sea. Journal of Applied
Ichthyology 27, 1375–1378.
Arechavala-Lopez P, Frutos J, IzquierdoGomez D, Bayle-Sempere JT, Sanchez-Jerez
P. Habitat use, feeding habits and metabolic
profile of European sea bass escaped from
Mediterranean open-sea cages. Aquatic
Living Resources, in preparation.
Chapter 2 and 3:
Arechavala-Lopez P, Sanchez-Jerez P,
Bayle-Sempere JT, Uglem I, Mladineo I
(2012) Could wild fish and farmed escapees
transfer pathogens among Mediterranean
fish farming areas? Aquaculture Environment
Interactions, submitted.
Arechavala-Lopez P, Sanchez-Jerez P,
Bayle-Sempere
JT,
Sfakianakis
DG,
Somarakis
S
(2012)
Morphological
differences between wild and farmed
Mediterranean fish. Hydrobiologia 679, 217–
231.
Arechavala-Lopez P, Sanchez-Jerez P,
Izquierdo-Gomez D, Toledo-Guedes K,
Bayle-Sempere JT (2012) Does fin damage
allow discrimination among wild, escaped
and farmed Sparus aurata (L.) and
Dicentrarchus labrax (L.)? Journal of Applied
Ichthyology, in press.
Chapter 5:
Arechavala-Lopez P, Fernandez-Jover D,
Black KD, Ladoukakis E, Bayle-Sempere JT,
Sanchez-Jerez P (2012) Differentiating the
wild or farmed origin of Mediterranean
fish: a review for sea bream and sea bass.
Reviews in Aquaculture, in press.
151