Evaluación de interacciones ambientales de peces escapados de jaulas de cultivo

UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA Evaluación de interacciones ambientales de peces escapados de jaulas de cultivo. M. Besay Ramírez Bordón Doctorado en Acuicultura: Producción controlada de animales acuáticos. Ca-directores: Dr. Ricardo Haroun Tabraue (Grupo de Investigación en Biodiversidad y Conservación - BIOCON) -I.U. ECOAQUA y Dr. Daniel Montero Vítores (Grupo de Investigación en Acuicultura - GIA) -I.U. ECOAQUA 3 4 ÍNDICE GENERAL ÍNDICE DE FIGURAS LISTA DE ACRÓNIMOS AGRADECIMIENTOS ÍNDICE GENERAL 1 INTRODUCCIÓN GENERAL 1.1.Situación actual de la acuicultura 1.2 Características biológicas generales 1.2.1 Lubina 1.2.2 Corvina 1.3 Aspectos generales del cultivo en Europa 1.4 Implicaciones medioambientales de la acuicultura 1.4.1 Implicaciones medioambientales generales 1.4.2 Escapes 1.4.3 Impacto de los escapes 1.5 Bioindicadores 1.5.1 Perfil lipídico 1.5.2 Cambios morfológicos 1.6 Establecimiento de poblaciones de peces escapados 1. 6.1 Censos visuales 1.6.2 Telemetría 1.6.3 Contenidos estomacales 1. 6.4 Desarrollo gonadal. 2 HIPÓTESIS Y OBJETIVOS 3 MATERIAL Y MÉTODOS 3.1 Organigramade la tesis 3.2 Región de estudio 3.3 Captura y transporte de las muestras 3.4 Disección de los peces 3.5 Análisis bioquímico 5 8 13 15 19 21 22 22 26 28 31 31 34 37 38 40 43 45 46 46 48 48 51 55 57 57 58 61 64 5 3.6 Establecimiento de poblaciones 65 4 "AQUAFEED IMPRINT ON BOGUE (Boops boops) POPULATIONS AND THE VALUE OF FATTY ACIDS AS INDICATORS OF AQUACULTURE-ECOSYSTEM INTERACTION: ARE WE USING THEM PROPERL Y? 67 4.1 Abstract 69 4.2 Introduction 70 4.3 Materials and Methods 73 4.3.1 Sampling points 73 4.3.2 Fish samples 74 4.3.3 Biochemical and fatty acid analysis 74 4.3.4 Statistical analysis 75 4.4 Results 75 4.5 Discussion 85 4.6 Acknowledgements 91 5 "MONITORING A MASSIVE ESCAPE OF EUROPEAN SEA BASS (Dicentrarchus labrax) AT AN OCEANIC ISLAND: POTENTIAL SPECIES FERALIZATION 93 5.1 Abstract 5.2 Introduction 5.2 Materials and methods 5.2.1 Sampling design and study locations 5.2.2 Fish surveys 5.2.3 Stomach contents 5.2.4 Gonadal development 5.2.5 Lipid and FA projiles 5.2.6 Data analysis 5.3 Results 5.3.1 Spatial-temporal distribution 5.3.2 Stomach contents of escaped European sea bass 5.3.3 Ganada/ development of escaped European sea bass 5. 3.4 FA pro files of escaped European sea bass 5.4 Discussion 5.5 Acknowledgements 95 96 100 100 101 102 102 102 103 104 104 109 112 112 125 132 6 "MORPHOLOGICAL DIFFERENCES BETWEEN FARMED AND ESCAPED SEA BASS (Dicentrarchus labrax)" 6.1 Abstract 6.2 Introduction 6.3 Material and Methods 133 135 135 137 6 6.4 Results 6.5 Discussion 6.6 Acknowledgements 140 145 147 7 "POST-ESCAPE BEHA VIOR OF CULTURED EUROPEAN SEA BASS, Dicentrarchus /abrax, AND MEAGRE, Argyrosomus regius" 149 7 .1 Abstract 151 7.2 Introduction 152 7.3 Materials and methods 155 7.4 Results 158 7 .5 Discussion 162 7.6 Acknowledgements 165 8. DISCUSIÓN GENERAL 167 9. CONCLUSIONES 177 10. BIBLIOGRAFÍA 181 7 INDICE DE FIGURAS Fig. l. l. Lubina (Dicentrarchus labrax) adulta .............................................. 23 Fig. 1.2. Mapa de la distribución de la lubina (D. labrax) ................................. 24 Fig. 1.3. Grupo de lubinas escapadas ......................................................... 25 Fig. 1.4. Corvina (Argyrosomus regius) adulta ............................................. 26 Fig. 1.5. Mapa de la distribución de la corvina (Argyrosomus regius) ................. .27 Fig. 1.6. Jaulas flotantes off-shore en Tufia (Gran Canaria, España) ................... 29 Fig. 1.7. Buzo reparando pequeñas roturas en la red de una jaula de engorde ......... 35 Fig. 1.8. Anilla de amarre ...................................................................... .35 Fig. 1.9. Ranking de las principales causas de escapes (I) ............................... .36 Fig. 1.10. Ranking de las principales causas de escapes (II) .............................. 37 Fig. 1.11. Ilustración comparativa entre lubina cultivada y lubina salvaje ............ .45 Fig. 1.12. Transmisor (TAG) de telemetría acústica ...................................... .47 Fig. 1.13. Receptor de telemetría acústica .................................................. .47 Fig. 3. l. Mapa de la zona de estudio (Islas Canarias, España) ........................... 58 Fig. 3.2. Captura de lubina escapada en el litoral de Gran Canaria ..................... 59 Fig. 3.4. Representación de arte de cerco y maniobra de pesca ......................... 60 Fig. 3.5. Lubina sobre superficie diseñada para análisis morfométrico ............... 63 Fig. 3.6. Examen gonadal de un ejemplar de corvina ..................................... 63 Fig. 3.7. Corte histológico de gónada de hembra de lubina escapada .................. 64 Fig. 3.8. Análisis bioquímico en el laboratorio ........................................... 65 Fig. 4.1. Location of stations for sampling points at Canary Islands .................. 73 Fig. 4.2. Effect of sea cages farm and sewage outfall on selected fatty acids in bogue at different sampling points .................................................... 79 Fig. 4.3. Principal Component analysis (PCA) of all fatty acids within the 8 different sampling points ................................................................ 84 Fig. 5.1. Map ofthe study area detailing sampling locations ..................... 100 Fig. 5.2. Size-class and frequency of occurrence of escaped sea bass ........... 106 Fig. 5 .3. Mean abundan ces of escaped sea bass at La Palma Island ............. 107 Fig. 5.4. Mean abundances of escaped sea bass at different substratum ........ 108 Fig. 5 .5. Size-frequency distributions of escaped sea bass ....................... 108 Fig. 5.6. Percentage Index ofRelative Importance (% IRI) of different prey in the diet of escaped sea bass ........................................................ 111 Fig. 5.7. Non-metric multi-dimensional scaling ordination of muscle and liver fatty acids profiles of sea bass ................................................ 113 Fig. 5.8. Percentage oflipid content and fatty acids in muscle and liver of escaped sea bass .................................................................... 116 Fig. 6.1. Map of study area detailing sampling farms .......................... 139 Fig. 6.2. The 13 landmarks and the distance, which were used for body shape study of sea bass ............................................................... 139 Fig. 6.3. Non-metric multi-dimensional scaling plots ofbody ................. 141 Fig. 7. l. Map of the study area in the eastern coast of Gran Canaria ......... 155 Fig. 7.2. Detection of meagre and sea bass after release ....................... 160 Fig. 7.3. Detections of meagre and sea bass for the entire period ............ 160 Fig. 7.4. Box plot of swimming depth of released individuals ............... 162 9 ÍNDICE DE TABLAS Tabla 1.1 Talla por clase de edad en Dicentrarchus labrax en distintas áreas geográficas ....................................................................... 26 Taba 1.2. Clasificación y ejemplos de la actividad acuícola costera, off-coast y off-shore según condiciones fisicas e hidrodinámicas ............. 30 Tabla 1.3. Resumen del uso de indicadores para identificar lubinas escapadas ............................................................................................ 39 Tabla 1.4. Ácidos grasos estudiados que mostraron un aumento al comparar peces cultivados/'asociados a las instalaciones (fuera de las jaulas)' y peces cultivados/salvajes ........................................................ .41 Tabla 3.1. Estadíos de desarrollo gonadal para examen macroscópico ...... 62 Table 4.1. Crude lipid, moisture and ash content of muscle, liver and whole fish, and condition index and HSI ofbogue ...................................... 76 Table 4.2. Muscle Fatty Acids pro file of bogue from the different sampling Points .................................................................................. 80 Table 4.3. Liver fatty acid profile ofbogue ..................................... 81 Table 4.4 Whole fish fatty acid profile ofbogue ................................ 82 Table 4.5. SIMPER analysis. Contribution ofthe main fatty acids to overall dissimilarities between human input and the rest of sampling points away fr om cages ............................................................................. 85 Table 4.6. SIMPER analysis. Contribution ofthe main fatty acids in different tissues to overall dissimilarities between fish inside sea cages and fish around sewage outfall ......................................................... 87 Table 5.1. ANOVA results ofthe effect of 'Time' and 'Locality' on the abundance of sea bass .............................................................. 105 10 Table 5.2 Length and weight of each capture fish ............................ 109 Table 5.3. Result of multivariate analysis ofvariance (MANO VA) testing for differences in the fatty acids profiles ..................................... 113 Table 5.4 Percentage value of different fatty acids identified in muscle of sea bass with varying distance from sea cage fish farms ............... 121 Table 5.5 Percentage valueof different fatty acids identified in liver of sea bass with varying distance from sea cage fish farms .................. 123 Table 6.1. Codes of morphological measurements with corresponding landmarks ......................................................................... 140 Table 6.2. Weight and length of cultivated and escaped fish from both studied island ..................................................................... 141 Table 6.3. Results of PERMANOVA analysis ofbody shape ............ 142 Table 6.4. SIMPER analysis. Contribution ofthe body measurements to overall dissimilarities between cultured and escaped body shape ... 143 Table 6.5. Significant differences ofvariables showed by ANOVA analysis, among studied factors ............................................. 144 Table 7. l. P values of two-tail Fisher exact test contrasting the presence oftagged sea bass and meagre between zones ............... 159 11 ABSTRACT The production of marine organisms is an increasing industry, which implies certain impacts in the environment. Throughout this thesis we have focused on the study of fish escapees from off-shore fish-farms. Four experiments were designed in order: 1) to study the aquafeeds effects in the associated ichthyofauna; 2) the potential use of lipid profile and morphology as biomarkers for escapees; and 3) to evaluate the fish behaviour after an escape event. The first experiment showed that cages associated fish (bogue -Boops boops) changed their lipid profile respect to those non-associated wild conspecifics, however that difference disappeared in a short distance away from the aquaculture cages and can be contaminated by other coastal lipid sources. The second experiment showed that the lipid profile of escaped sea bass was changing as they were adapting to environment, differing from those cultured; also, we observed sorne degree of environmental adaptation in the Canarian coast. In third experiment we found few morphometric differences between cultivated and escaped sea bass. The fourth experiment indicated that sea bass and meagre remain approximately one week around cages after an escape event, with an exponential decrease of individuals throughout that week. We concluded that the aquafeeds affect the lipid profile of associated fish, increasing fatty acids typically associated to terrestrial oils, nevertheless, others input sources of these terrestrial oils were identified on the coast. Escaped sea bass do not change lipid profile with the distance to aquaculture cages, it changes with time after escape. The lipid profile is not a bioindicator of escaped fish, however the morphometry could be used so. A low percentage of escape sea bass survived survive capacity in the Canarian coast, but populations tends to disappear along time. Keywords: Aquaculture, Escapees, Biomarkers, Fatty Acids, Morphometry, Telemetry, Establishment, Behaviour, Sea Bass, Meagre. 18 1Evaluación de interacciones ambientales de peces escapados de jaulas de cultivos. INTRODUCCIÓN GENERAL 1.1. Situación actual de la acuicultura La acuicultura puede definirse como el cultivo de orgamsmos acuáticos mediante técnicas encaminadas a hacer más eficiente su producción. Aunque tiene una historia de 4.000 años, ha sido a partir de los últimos 50 años cuando se ha convertido en una actividad socioeconómica relevante, dando empleo a más de 12 millones de personas en el mundo (APROMAR 2012). Abarca diversos sistemas de cultivo en aguas continentales, costeras y marítimas, utilizando y produciendo una amplia variedad de especies. Los sistemas de cultivo varían desde algunos muy sencillos, como los estanques familiares en varios países asiáticos, hasta otros de alta tecnología como los sistemas de circuito cerrados de producción intensiva (FAO 2014a). En general, el cultivo de especies animales conllevan una serie de fases: mantenimiento de reproductores, hatchery (huevos y larvas), nursery (post-larvas) y engorde de juveniles. En el caso de la fase de engorde, la tendencia mayoritaria es que por razones económicas, ésta tenga lugar en jaulas marinas, circulares o rectangulares, fondeadas a una cierta distancia de la costa Cada una de estas fases se ha ido desarrollando y especializando, e implica diferentes sistemas y tecnologías de cultivo. En este sentido y por lo que respecta a la presente tesis doctoral, cuando hablemos del cultivo, nos referiremos a la fase de engorde de juveniles de lubina y corvina en jaulas de cultivo marinas, por ser la fase del cultivo que entraña un riesgo real de escapes. Ante la complicada realidad que estamos viviendo en este comienzo de siglo (problemas financieros, cambios climáticos y escasez de recursos), propiciada por la superpoblación del planeta, la humanidad debe afrontar el reto que se nos presenta pensando como especie y no como las distintas naciones que nos separan. La F AO apunta que uno de los principales problemas del siglo XXI será la producción de alimentos para abastecer este incremento de población. Esta producción deberá aumentar en un 70% entre 201 O y 2050 21 (cuando llegaremos a 9,6 billones de personas). Según la FAO, de la superficie total de la Tierra tan solo es aprovechable para la agricultura y ganadería el 38% (52.129.685 km2). Teniendo en cuenta que la mayor parte de la superficie del planeta la conforman los océanos y el agotamiento de los recursos terrestres, parece obvio que este aumento de la producción primaria tendrá lugar en los mares y océanos. Además, una de las principales ventajas que presenta la producción marina es que no se necesita emplear agua dulce, cuyo agotamiento es otro de los principales problemas de este siglo. Dentro del sector de producción de alimentos, la acuicultura es la actividad que más rápidamente ha crecido en los últimos años, alcanzando las 97,201,872 t (146,229,575,654 €) y convirtiéndose en el principal productor de alimentos de origen acuático (50.87 %), de un total de 191,063,087 ten 2013 (FAO 2015b). Dentro de esta producción acuícola se incluye el cultivo de especies de peces de origen marino (1,788,164 t), que también ha experimentando un importante crecimiento durante los últimos años (FAO 2015b). 1.2 Características biológicas generales 1.2.1 Lubina La lubina (Dicentrarchus labrax Linnaeus 1758) es un pez teleósteo que pertenece a la clase Actinopterigia, orden Perciformes, familia Moronidae, género Dicentrarchus y especie D. labrax (Fig. 1.1). Este pez se distribuye desde Noruega a Cabo Blanco, incluyendo el Mediterráneo y el Mar Negro (Moretti et al., 1999) (Fig. 1.2). Su rango natural de distribución incluye las Islas Canarias orientales: Fuerteventura y Lanzarote (Brito 1991 ), aunque en la actualidad la podemos encontrar en otras islas del archipiélago Canario (Gran Canaria, Tenerife y La Palma) (Fig. 3.1) como consecuencia de escapes de acuicultura (Carrillo and Castillo, 2001; Toledo et al., 2009; Toledo et al., 2012) (Fig. 1.3). En su hábitat natural se encuentra en las aguas costeras, aunque también están presentes a mayor profundidad, llegando a los 100 m. Posee un amplio rango de distribución observándose en estuarios, 22 canales, lagunas e incluso ríos. En Canarias, Toledo et al. (2009) observaron, en lubinas escapadas, una preferencia de costas con sustratos formados por pequeñas rocas o cantos. Figura 1.1. Lubina (Dicentrarchus labrax) adulta. La lubina es una especie gonocórica (Arias A., 1980; González A., 2003) de elevada fecundidad (150.000 -200.000 huevos por kg/hembra). La proporción de sexos es prácticamente 1: 1 entre machos y hembras durante los tres primeros años de vida, llegando a 4:1 a favor de las hembras en el 4° y 5° año (Arias A., 1980). En cautividad suele ser 3:1, siempre favorable a machos (Carrillo et al., 1995; Colombo et al., 1997). La reproducción tiene lugar entre los meses de diciembre a marzo (Do Chi and Hoai Thong, 1971; Bamabé G., 1976; Arias A., 1980; González A., 2003). La talla de primera madurez de esta especie es de 32,3 cm ( con un rango 23 -46 cm) (Froese and Pauly 2006). Laffaille et al., (2001) sitúan la época de reproducción entre febrero y abril en la costa Británica. Algunos estudios demuestran un pico reproductivo a finales de julio en el Atlántico. Para que comience la gametogénesis esta especie requiere salinidades inferiores al agua de mar (< 35 %o) y los últimos pasos del desarrollo gonadal una salinidad de 35 %o. (FAO, 1999). La temperatura 23 mínima y máxima para que se produzca la gametogénesis es 9-18 º C respectivamente (FAO, 1999) y el rango óptimo para la puesta está e°:tre 13-15 º C (Moretti et al., 1999). La supervivencia de las larvas aumenta considerablemente al disminuir la salinidad. Numerosos autores han encontrado un reclutamiento de la especie en medios estuarinos (Arias A., 1980; Serrano L., 1989; Laffaille et al., 2001 ). El rango de temperatura óptima de incubación de la puesta va desde 13ºC a 17° (Devauchelle and Coves, 1988; Saka et al., 2001), considerándose este el límite superior de temperatura óptima de incubación. ,..a Relalive pooatJlllee o1 ocet.rrenee -o.so -1.00 -0.60 -0.79 0A0 · 0.59 0,20-0.39 0.01 -0.19 Figura 1.2. Mapa de la distribución de la lubina (D. labrax) en el Atlántico Oriental (Froese and Pauly 2006) El periodo de larva tiene una duración de 46 días a 16,5ºC (Houde and Zastrow, 1993). La dispersión puede durar 3 meses (huevos y larva pelágica. Además existen otros factores ambientales que afectan a la reproducción de la especie, tales como fotoperiodo, hidrodinámica, predadores, disponibilidad de alimentos, etc. 24 Es un predador que se alimenta principalmente de crustáceos, moluscos y peces (Tortonese 1986; Laffaille et al., 2001; Leitao et al., 2008; Toledo et al., 2009). Su dieta cambia a lo largo de su ciclo vital, dependiendo del tamaño del individuo (Arias, 1980; Kennedy and Fitzmaurice, 1972). En estadios juveniles se alimentan de crustáceos y pequeños peces (Tortonese, 1986; Laffaille et al., 2001; Leitao et al., 2008; FAO 1999). Los animales de más de 20 cm consumen camarones y cangrejos principalmente (F AO, 1999). Esta especie en el medio natural tiene un crecimiento lento ( aproximadamente 4 años para alcanzar 1 kg de peso medio). Puede alcanzar los 100 cm de longitud y los 12 Kg de peso (FAO, 1999). Los machos crecen menos y más lentamente que las hembras (Arias, 1980; Carrillo et al., 1995), además viven menos. Arias (1980) no encontró ningún macho con más de cinco años de edad entre 1013 lubinas muestreadas. Figura 1.3. Grupo de lubinas escapadas en la escollera de Santa Cruz de la Palma (Santa Cruz de Tenerife, España) El crecimiento de estos peces es mayor en poblaciones que penetran en lagunas litorales (Arias, 1980). Chervinski (1975) registró un mayor crecimiento en agua dulce frente agua de mar. En la tabla 1.1 se muestran los resultados obtenidos por algunos autores en distintas regiones geográficas. 25 Tabla 1.1 Talla (mm) por clase de edad (años) en Dicentrarchus labrax para diferentes autores en distintas áreas geográficas. 1 Arias, 1980. 2 Gravier, 1961. 3 Labourg and Stequert, 1973. 4 Bemabé 1973; 5 Serrano, 1989. Tabla de Arias (1980), añadiéndose datos de Serrano (1989). Edad (años) Zona 1 2 3 4 5 6 7 1. Cádiz (España, Atlántico)* 180,9 288,5 378,5 458,8 528,6 598,3 645,0 2. Marruecos 150 220 290 340 400 450 500 (Mediterráneo) 3. Arcachon 110 210 260 300 320 350 390 (Francia, Atlántico)* 4. Thau 174 283 382 486 539 576 621 (Francia, Mediterráneo)* 5. Aveiro 166 213 (Portugal, Atlántico)* *Estudios realizados en estuarios o lagunas. 1.2.2 Corvina La corvina es un pez teleósteo que pertenece a la clase Actinopterigia, orden Perciformes, familia Sciaenidae, género Argyrosomus y especie A. regius (Fig. 1.4). Figura 1.4. Corvina (Argyrosomus regius) adulta. Este pez se distribuye por el Atlántico Oriental desde Francia hasta Senegal, incluyendo el Mediterráneo Occidental (Quéméner 2002). El rango de distribución incluye las Islas Canarias (Dooley et al., 1985; Lloris et al., 1991) (Fig. 1.5). Esta especie está presente en 26 aguas costeras, asociadas a plataforma continental, son peces bentónicos, aunque se le puede encontrar en toda la columna de agua (Froese and Pauly 2006). Estos animales pueden alcanzar los 2 metros de envergadura y 50 kg de peso. La temperatura del agua es el factor más importante que determina la migración trófica y la reproducción de la corvina. Tanto los adultos como los juveniles realizan migraciones inducidas por los cambios de temperaturas. (Froese and Pauly 2006; Stipa and Angelini 2005). 0.80 -1.00 0.60-0.79 0A0 • 0.59 0.20 • 0.39 0.01 · 0.19 Figura 1.5. Mapa de la distribución de la corvina (Argyrosomus regius) en el Atlántico Oriental (Froese and Pauly 2006) La talla de primera madurez se ha establecido en 61.6 cm para los machos y entre 7011 O cm para las hembras. Entre marzo y agosto las corvinas adultas se aproximan a la costa, penetrando en los estuarios para desovar. Las larvas y juveniles se desarrollan en ese medio estuarino hasta que al final del verano migran a aguas costeras. Estos juveniles se incorporan al stock reproductor a los 6 años de edad (González-Quirós et al., 2011). Las condiciones más favorables para el crecimiento y desarrollo se dan entre 17 y 21 ºC, aunque se pueden adaptar 27 nasas. Dentro de las modalidades de acuicultura, el engorde de peces en instalaciones off shore tiene una de las mayores huellas de carbono, ya que se aumenta el consumo energético para transportar alimentos, materiales y los propios peces, hasta las instalaciones En cambio, la acuicultura extensiva (Mytilus galloprovincialis) fue la actividad con menor huella de carbono con un valor de 0.08 kg CO2/kg producido. 1.4.2 Escapes Tradicionalmente la definición de 'escapes' de acuicultura solo englobaba a peces, tanto juveniles como adultos. Más recientemente, J0rstad et al. (2008) descubrieron que se estaban liberando huevos fecundados desde las jaulas, con lo que se ha redefinido el término "escapes" para incluir esta, introducción de huevos fecundados en el medio, por parte de los peces cultivados. En el tipo de instalaciones off-shore encontramos dos tipos de escapes: crónicos, aquellos que ocurren con relativa periodicidad y bajo número de individuos, cuya principal causa son los agujeros en la red ocasionados por mordidas por predadores y los propios peces cultivados (Fig. 1. 7); y los escapes masivos (> 10,000 individuos) ocasionados principalmente por roturas de las anillas de amarre (Fig. 1.8) (Jackson et al., 2015). Según Jensen et al. (2010), estos escapes masivos en la actualidad son poco frecuentes en la acuicultura off-shore Noruega. Representan el 19 % de los incidentes de escapes en cultivo de salmón y bacalao, pero suponen el 91 % en el número total de individuos escapados. 34 Figura 1. 7. Buzo reparando pequeñas roturas en la red de una jaula de engorde. Figura 1.8. Anilla de amarre. Jackson et al. (2015), además de coincidir con lo expuesto por Jensen et al. (2010), describen las principales causas de los escapes en la acuicultura europea (Figs. 1.9 y 1.10): 35 1. Fallos en los puntos de amarre y sujeción de las jaulas. Esto normalmente se debe, a su vez, a una combinación de 3 factores: desgaste del material, falta de revisión reemplazamiento y aparición de condiciones marítimas adversas (temporales, mar de fondo, tormentas, etc.). 2. Predadores. Animales que tienen capacidad de realizar roturas en la red, con la intención de alimentarse de los peces que se cultivan en el interior de las jaulas. 3. Uso de materiales inapropiados en las jaulas. 4. Eventos tormentosos y de mal estado de la mar. Temporales de tal intensidad, que aunque el material de la instalación (cabos, muertos, redes, anillos, etc .. ) es el adecuado, estos sufren roturas por sobrecarga. N.tbiting Predator Unknown (hole in net) Chafelsnag Stormewnt Handing Human error Pumping Unknown Other Workboats lnappropríatlt mooríngs Equipment failure 5abotilge Fractured pip11 Towing Poor quailily nets Flotsilm Poorrepair Thetl lnappropríam cages Wlllboat - - - - - - - - - 11 o 5 Undertying causes of escapes vs number of incidents 10 15 20 25 30 Number of incida,ts 1 ■Numberofincilents 1 35 40 45 Figura 1.9. Ranking de las principales causas de escapes, según el número de escapes reportados (Jackson et al., 2015). 36 4% 11 Mooring failure Predator D lnappropriate cages □Unknown (hole in net) D Other Storm event Figura 1.1 O. Ranking de las principales causas de escapes, según el número de peces escapados (Jackson et al., 2015). 1.4.3 Impacto de los escapes Solo en Noruega, las jaulas existentes pueden contener unos 325 millones de salmones en cada ciclo de engorde; mientras que los salmones salvajes que entran a desovar en estos ríos cada año, apenas llegan a 1 millón de individuos. Según Naylor et al. (2005), los escapes se presentan como un problema para la sostenibilidad de la acuicultura. Los escapes representan problemas por mezcla genética de poblaciones separadas geográficamente, alteración de la cadena trófica, introducción de patógenos y enfermedades, competencia intra e interespecífica o introducción de especies exóticas (CBD, 2004; Molina and Vergara 2005; Naylor et al., 2005; Vergara et al., 2005; Jensen et al., 2010; Grigorakis and Rigo 2011). Además, en términos económicos los escapes representan un total de pérdidas de 47.5 millones de euros al año (Jackson et al., 2015). Se han descrito escapes de jaulas marinas para especies como el salmón Atlántico, el bacalao Atlántico (Gadus morhua), trucha arcoíris (Oncorhynchus mykiss), trucha Alpina (Salvelinus alpinus), halibut (Hippoglossus 37 hippoglossus), dorada (Sparus aurata), lubina, corvina o serviola (Serio/a lalandi) (Soto et al., 2001, Naylor et al., 2005, Gillanders and Joyce 2005, Moe et al., 2009). Dentro de esta línea de investigación, la especie más ampliamente estudiada es el salmón Atlántico, mientras que el conocimiento acerca del impacto de especies como la lubina, la dorada o corvina es muy limitado o inexistente. Cuando se producen escapes en determinadas zonas, estos pueden entrañar una problemática particular por encontrarse en ecosistemas donde las poblaciones naturales de las especies cultivadas sean pequeñas o inexistentes, por presentar un impacto menos predecible y unas pérdidas económicas mayores (Soto et al., 2001; ICES 2004). Este podría ser el caso de Canarias donde en el 2012 se ha alcanzado una producción de 3600 t de lubina (JACUMAR 2014) y solo han sido descritas pequeñas poblaciones autóctonas en las islas orientales (Fuerteventura y Lanzarote) (Brito, 1991 ), ( donde único sería posible la mezcla de poblaciones). Además varios trabajos han concluido que no existen evidencias de la reproducción de esta especie (poblaciones de peces escapados) en las demás islas (Carrillo and Castillo 2001; Toledo et al., 2009). Estos mismos trabajos señalan que la dieta de las lubinas escapadas es similar a la de otras especies locales, llegando competir por el recurso (Carrillo and Castillo 2001; Toledo et al., 2009). 1.5 Bioindicadores Para poder comenzar a estudiar los escapes de acuicultura, con el fin de entender cómo estos pueden interactuar y/o afectar al entorno, es imprescindible poder diferenciar, tanto en el medio marino como una vez capturados, individuos escapados de aquellos salvajes. Los investigadores han propuesto varios métodos como la diferenciación genética (Gwak et al., 2003; Glover et al., 2009), cambios en el perfil lipídico (Grigorakis et al., 2002; Femández Jover et al., 2007;), elementos traza-morfología en escamas y otolitos (Lund and Hansen 1991; Katayama and Isshiki 2007; Adey et al., 2009; Person-Le Ruyet and Le Bayon 2009), 38 trazas biomoleculares (Megdal et al., 2009), isótopos estables (Weber et al., 2002), diferencias morfológicas (Loy et al., 1999; Murta, 2000; Cramon-Taubadel et al., 2005; ; Ellis et al., 2009; Uglem et al., 2011; Arechavala-López et al., 2013b). Cada uno conlleva una serie de ventajas e inconvenientes, como queda reflejado en la tabla 1.3, donde Jackson et al. (2015) han recopilado gran número de ellos. En el presente trabajo se han testado de forma más exhaustiva los bioindicadores relacionados con los cambios de perfil lipídico y diferencias morfológicas, al considerar que nos pueden suministrar información científica de interés relacionada con las interacciones de los peces escapados con el medio ambiente. Tabla 1.3. Resumen del uso de indicadores para identificar lubinas (Dicentrarchus labrax) escapadas. La escala de idoneidad va desde el negro (máxima) al blanco (menos recomendable) (Jackson et al., 2015). Costoenefi, Ouick rt�ponsc lc'T'poral oe�istcnce F ,hrnes managemcnt Sdk� Et Consumers Farmers E•-1ironmentat Management ld•nt 'rcation smgc ndvidua Ong nal farrr �toe� SEABASS Otolrth &eatu,es Scale features Fin Trace Genetrc methods 39 1.5.1 Perfil lipídico Muchos autores proclaman el perfil lipídico como un indicador de la salud medioambiental (Dunn et al., 2008; Hu et al., 2008; Maazouzi et al., 2008) y en estos últimos años se le ha prestado especial atención debido a los continuos cambios que sufren los piensos para acuicultura. Tradicionalmente los peces cultivados se alimentaban con piensos hechos a base de harina y aceite de pescado, pero el encarecimiento de esta la materia prima ha obligado a sustituirlos en parte, sobre todo el aceite de pescado por aceite de origen vegetal (Tacon and Metían 2008). Su uso está limitado por la falta de n-3 HUF A, a pesar de la alta concentración de ácidos grasos como linoleico (LA) (18: 2n-6) y linolénico (ALA) (18: 3n-3) (Turchini et al., 2009). Estos ácidos grasos son incorporados a los tejidos de los peces cultivados, aunque también pueden transferirse a los peces salvajes que se encuentran alrededor de las jaulas de cultivo, debido al exceso de alimento que sale fuera; llegando a cambiar las condiciones biométricas y la composición de ácidos grasos del perfil lipídico, así como la de los animales de los siguientes niveles tróficos (Dalsgaard and St. John 2004; Femández-Jover et al., 2007; Skog et al., 2003). Por esta rezón se han propuesto ciertos ácidos grasos (LA, OA, ALA) como indicador de la influencia de la acuicultura en el medio marino y de peces escapados (Rueda et al., 2001, Femández-Jover et al., 2007; Megdal et al., 2009). En la tabla 1.4 se muestran los resultados obtenidos por algunos autores utilizando los ácidos grasos como indicadores 40 Tabla 1 .4. Resumen de los resultados en estudios previos. Se muestran los ácidos grasos estudiados que mostraron un aumento al comparar peces cultivados/'asociados a las instalaciones (fuera de las jaulas)' y peces cultivados/salvajes. Autor Species Rueda et al., Diplodus 2001 puntazw Grigorakis et al., Sparus aurata 2002 Tissue Wild Músculo ¡ 22:Sn-3 Hígado i 20:Sn-3 22:6n-3 Músculo Into Cage Around Cage ¡ 18:2n-6 18:ln-9 20:Sn-3 i 18:2n-6 18:ln-9 i 18:ln-9 18:2n-6 18:3n-3 41 Skog et al., 2003 Pollachius virens Músculo ¡ n-3/n-6 L. Mnari et al., Sparus aurata Músculo ¡ 18:ln-9 2007 Hígado ¡ 18:ln-9 Femandez-Jover Trachurus Músculo ¡ 22:6n-3 et al., 2007 mediterraneus n-3/n-6 Martinez-Rubio Boops boops Músculo ¡ 22:6n-3 i 18:ln-9 18:3n-3 18:2n-6 i 22:6n-3 n-3/n-6 18:2n-6 18:3n-3 i 18:3n-3 n-3/n-6 22:6n-3 20:Sn-3 i 18:2n-6 18:ln-9 i 18:2n-6 42 et al., 2009 Megdal et al., Salmo salar 2009 Hígado ¡ 22:6n-3 Músculo 1.5.2 Cambios morfológicos 18:ln-9 i 18:2n-6 18:ln-9 ¡ 18:2n-6 La descripción cuantitativa, análisis e interpretación de la morfología son herramientas fundamentales en el campo de la biología en general. Las técnicas morfológicas se basan, a rasgos generales, en el análisis de las distancias entre una serie de puntos situados estratégicamente a lo largo del cuerpo de la especie a estudiar. Los grupos de individuos de una misma especie pueden mostrar diferencias morfológicas (Fig. 1.11) como consecuencia de las diferencias genéticas y medioambientales (Barlow, 1961; Kinnison and Hendry 2004; Solem et al., 2006), llegando a poderse utilizar estas diferencias para identificar el stock de origen (Hurlbut and Clay 1998; Murta, 2000; Solem et al., 2006) o servir para diferenciar peces que fueron cultivados de otros salvajes (Loy et al., 1999; Murta, 2000; Cramon Taubadel et al., 2005; Arechavala-López et al., 2011; Uglem et al., 2011). Los cambios morfológicos de especies cultivadas está relacionada con los primeros estadíos de desarrollo 43 50 2Evaluación de interacciones ambientales de peces escapados de jaulas de cultivos. HIPÓTESIS Y OBJETIVOS La hipótesis general de la presente tesis es que (1) el perfil lipídico de los peces (fauna asociada y peces cultivados) bajo influencia acuícola cambia con respecto a la distancia a la que se encuentren de las instalaciones de cultivo; aunque, por otro lado, (2) este perfil puede estar influenciado por otras fuentes de ácidos grasos de origen terrestre, con lo que (3) el perfil lipídico no es una herramienta efectiva para determinar con rotundidad el origen del animal. (4) Existen otras herramientas como la morfometría que si lo son. (5) Estos peces escapados (lubina y corvina) tienen capacidad de sobrevivir en el medio, aprovechando los recursos existentes, aunque sin llegar a reproducirse. Con el fin de validar estas hipótesis se definieron los siguientes objetivos: ■Conocer el efecto del ,excedente de piensos usados en las jaulas de engorde, sobre el perfil lipídico de la comunidad ictiológica asociada ■ Estudiar la viabilidad del uso de determinados ácidos grasos como biomarcadores de acuicultura, usando como modelo una especie cosmopolita que se encuentra generalmente asociada a sistemas de cultivo y otra especie cultivada con poblaciones de peces escapados a lo largo de la costa de una isla oceánica. ■Estudiar la viabilidad de otros parámetros como indicadores de peces de ongen acuícola: Morfometría ■Analizar la variación espacio-temporal de peces cultivados, escapados tras un escape masivo alrededor de una isla oceánica o modelizando el escape mediante una suelta controlada; así como conocer el grado de asentamiento de estas poblaciones (alimentación y potencial reproductor). 53 54 3Evaluación de interacciones ambientales de peces escapados de jaulas de cultivos. MATERIAL Y MÉTODOS 3.1 Organigrama de la tesis La fase experimental de esta tesis doctoral comenzó en agosto del 2009 y se prolongó con diferentes experimentos hasta febrero del 2012. 3.2 Zona de estudio La totalidad de los experimentos llevados a cabo durante la presente tesis doctoral, fueron realizados en el archipiélago Canario (España). Esta región se encuentra entre los 27º 37' hasta los 29° 15' N; y 13º 24' hasta los 18º 11' W (Fig. 3.1). Se trata de un archipiélago oceánico, situado en el Atlántico Centro-Oriental. Su situación cercana al continente Africano ( a 100 km de Tarfaya, Marruecos), un régimen prácticamente constante de vientos alisios (generador de micro afloramientos) junto a la existencia de una corriente fría ("Corriente Fría de Canarias"), una alta biodiversidad marina, existencia de 7 islas donde se encuentran gran variedad de ecosistemas marinos ( con 3 reservas marinas integrales), islas muy pobladas frente a otras de escasa población, gradientes naturales entre islas, etc ... hacen que nos encontremos ante lo que podemos considerar como uno de los mejores laboratorios marinos naturales del planeta. 57 Figura 3 .1. Mapa de la zona de estudio (Islas Canarias, España). Las áreas en negro indican zonas con presencia de instalaciones de engorde 'offshore'. Las áreas en rojo, en cambio, indican zonas donde existían instalaciones pero en la actualidad su actividad ha cesado. 3.3 Captura y transporte de las muestras Los peces salvajes que se precisaron durante los experimentos, se capturaron mediante pesca recreativa (a caña y pesca submarina) y pesca profesional (cerco y nasas). La técnica a utilizar dependió de la especie objeto, zona de pesca, características del experimento y, sobre todo, las posibilidades logísticas (mirar Material y Métodos de cada experimento). La pesca a caña consiste en una línea de nailon o hilo sintético, de gran resistencia y enrollada en un carrete manual, que pasa por unas anillas fijas a la caña. Una vez liberada dicha línea, es recogida a través del carrete; el bajo de línea (parte del arte que realmente ejerce la pesca) se 58 utilizó un palangre vertical consistente en un plomo (para que la línea llegue al fondo), y tres anzuelos en vertical separados 20 cm del plomo y entre sí. Como camada para los anzuelos se usó langostino (Penaeus notialis). La pesca submarina consiste en la inmersión en apnea (sin equipo de respiración autónomo), equipado como mínimo de gafas, tubo, aletas y fusil submarino, que libera un arpón metálico con el que se captura el pez (Fig. 3.2). Los peces capturados mediante esta técnica no fueron seleccionados bajo ningún criterio (tamaño, coloración, comportamiento, zona, etc), para evitar un sesgo en el muestreo. Figura 3.2. El autor capturando lubina escapada en el litoral de Gran Canaria. La nasa para peces es un armazón, generalmente de forma circular, revestido de una red o forro, cuya malla tiene forma hexagonal regular, con una o dos entradas y una puerta. Las entradas tienen forma de embudo, quedando hacia el interior la parte más estrecha, de tal forma que permite la entrada de los peces pero no su salida. La malla es degradable y tiene una luz de malla mínima de 50,8 mm en las nasas grandes y de 31,6 mm en las pequeñas (no 59 66 4Evaluación de interacciones ambientales de peces escapados de jaulas de cultivos. ,t\CIDOS GRASOS COMO BIOINDICADORES 4 "AQUAFEED IMPRINT ON BOGUE (Boops hoops) POPULATIONS AND THE VALUE OF FATTY ACIDS AS INDICATORS OF AQUACULTURE ECOSYSTEM INTERACTION: ARE WE USING THEM PROPERLY? Besay Ramírezª·\ Daniel Montero\ Marisol Izquierdo\ Ricardo Harounb ªGrupo de Investigación en Acuicultura. Universidad de Las Palmas de Gran Canaria and Instituto Canario de Ciencias Marinas. P.O. Box 56. 35200. Telde, Las Palmas, Canary Islands, Spain. bBIOGES, Marine Sciences Faculty, Campus Tafira, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas de G.C., Canary Islands, Spain. 4.1 Abstract The increasing aquaculture production in coastal areas has resulted in different interactions with the environment. Thus, studies on the escape of farmed fish into the ecosystem have been recently increased for different reasons such as competition with wild populations, genetic pollution, among others. Morphological and physiological indicators have been proposed as biomarkers for escapees, including biometrical parameters, morphology of scales and otholits, microchemistry of scales, RNA/DNA ratios or fatty acid content of muscle. Fatty acid profile have been received increasing attention due to the changes of ingredients and feeding strategies occurring within aquafeeds in the last years, with an increased use of terrestrial ingredients to substitute marine ingredients. This study evaluates 1) the effect of wasted food on fatty acid of a farm-associated and 2) the suitability of fatty acid profile as a bioindicator of aquaculture-ecosystem interactions, using the bogue (Boops boops) as a model. This species is an opportunistic fish usually associated to -or even withinsea farms, and with a high natural occurrence in Mediterranean and Atlantic coasts, 69 which integrates in its body composition the feeding strategies arising from the different habitats in which this species is located. Keywords: aquaculture-ecosystem interaction, wasted aquafeeds, fatty acid indicator 4.2 Introduction Aquaculture constitutes the fastest growmg food production sector and the mam contributor of marine food to satisfy the demand of the unceasingly increasing human population (Tacon and Metian 2009). Nevertheless, this fast growth can only be maintained if it is sustainable under a social, economic and, particularly, environmental point of view. Thus, the fast development of aquaculture production in coastal areas, particularly when i t is sea based, has promoted the r-esearch on its interactions with the environment, (Naylor et al., 2000; Black, 2001; Hargrave, 2005; Holmes et al., 2008). Aquaculture activity may affect marine biodiversity in relation to genetic variability, species-species interaction or ecosystem alteration (CBD, 2004). The most direct effect of aquaculture on the environment, and the most studied, is that coming from wasted food and, secondly, faecal discharges, that may modify the characteristics of the sediment under the fish cages (Molina-Dominguez et al., 2001; Mente et al., 2006). Besides, the sea cages presence may alter the icthyological community around them (Carss, 1990; Machías et al., 2004; Tuya et al., 2006; Dempster et al., 2005). Nevertheless, other types of impacts could relate to the addition of anti-fouling treatments, transfer of parasites or exotic species, discharge of toxic therapeutic products or fish escapes (Hewitt et al., 2003; IUCN, 2007; Femández-Jover et al., 2010). Escapes of fish from sea-cage aquaculture have been reported for many aquaculture species including Atlantic salmon (Salmo salar), Atlantic cod (Gadus morhua), rainbow trout (Oncorhynchus mykiss) Arctic char (Salvelinus alpinus), halibut (Hippoglossus hippoglossus), gilthead sea bream (Sparus aurata), European sea bass (Dicentrachus labrax), meagre (Argyrosomus regius) or kingfish (Serio/a lalandi) (Soto et al., 2001, Naylor et al. 2005, 70 Gillanders and J oyce, 2005, Moe et al., 2007). The nature of the escapes is multi-factorial but is mainly related to farming equipments and its operations. Massive fish escapes (more than 10.000 fish) are very rare and represent only 19% of the escape incidents reported in salmon or cod, but they account for 91 % of the total number of escaped fish (Jensen et al., 2010). When escaped fish belong to an exotic species, the environmental impact is less predictable and is consider as one of the major threats of aquaculture activities to ecosystems from both a biological or an economic perspective (Soto et al., 2001). If the escapes belong to a native species, the interactions escaped-wild fish are difficult to precise and may include the mutual transfer of diseases and pathogens, competition for food or interbreeding (Jensen et al., 2010), despite both types of fish differ on behavioral ecology and life history depending on the two niches: wild and aquaculture (Gross, 1998). To identify those animals coming from aquaculture in order to better understand these interactions, it is necessary to develop an appropriate methodological approach. Several morphological and physiological indicators have been proposed to be useful to identify escapees, including biometrical parameters (U glem et al., 2011; Ellis et al., 2009), scales and otholits morphology (Person-Le Ruyet and Le Bayon 2009; Katayama and Isshiki 2007), scales mineral contents (Adey et al., 2009) RNA/DNA ratios (Gwak et al., 2003) or muscle fatty acid composition (Grigorakis et al., 2002; Femández-Jover et al., 2007). Regarding the latest, the fatty acid profile has been claimed to be a good bio-indicator of ecosystem health (Dunn et al., 2008; Hu et al., 2008; Maazouzi et al., 2008). The fatty acid profile has received an increasing attention due to the changes in aquafeeds ingredients during the last years. Traditionally, fish were fed diets based on fishmeal and fish oíl as mean ingredients for its adequate price and content in sorne essential fatty acids for fish, such as docosahexaenoic acid (DHA) (22:6n-3), eicosapentaenoic acid (EPA) (20:5n-3) and arachidonic acid (ARA) (20:4n6). These fatty acids, which have a wide plethora of very important functions, are consider 71 essential for marine fish since these species have not the ability to bio convert shorter fatty acids into these fatty acids due to the very low activity of delta 6 and delta 5 desaturase in these fish (Izquierdo and Koven 2011). However, within the last decade, the world production of fish oil has become stagnant, global fish oil costs increased and fish oil inclusion in compound aquafeeds has been substituted by more sustainable vegetable oils (Tacon and Metian 2008). The use of vegetable oils in marine fish is constrained by their lack of n-3 HUFA, despite the high abundance of the 18:C fatty acid precursors linoleic acid (LA) (18: 2n-6) and alpha-linolenic acid (ALA) (18: 3n-3) (Turchini et al., 2009). These precursor fatty acids are incorporated into the tissues of aquaculture fish, but can be also transferred to wild fish. Fish around the cages may feed on waste pellets from farms, what leads to changes in body condition and fatty acid profiles making their body composition and that of other organisms in different trophic levels more similar to that of cultivated fish (Skog et al. 2003; Dalsgaard et al., 2003; Femández-Jover et al., 2007). For this reason, the presence of certain fatty acids, such as LA and oleic acid (OA) (18: ln-9), in wild organisms has been proposed as an indicator of the influence of aquaculture on marine ecosystems (Rueda et al., 2001; Femández-Jover et al., 2007; Megdal et al., 2009). Nevertheless, the presence of each of these fatty acids in fish tissues may be aff ected by diff erent factors that should be considered such as the metabolic utilization of dietary fatty acids, their selective retention or the period required to deplete them from the different tissues (Izquierdo et al., 2005). Moreover, the presence of those fatty acids in wild fish could be also related to a different origin than aquaculture feeds, such as other human activities (Quemeneur and Marty 1992; Sargent et al., 2002; Wong et al., 2008). Thus, the objective of the present study was 1) to evaluate the effect of wasted food on the fatty acid composition of a farm-associated and 2) the suitability of fatty acid profile as a bioindicator of aquaculture-ecosystem interactions, i.e., the potential value of sorne fatty acids as aquafeed tracers on escaped fish. The bogue was used as a model, 72 since this species is an opportunistic fish frequently associated to sea farms (Dempster et al., 2005), but also with a high natural occurrence in Mediterranean and Atlantic coasts. The location of the study in an oceanic Archipelago (Canary Islands) composed of several islands with a very different degree of development of coastal aquaculture or human activity, has allow to compare isolated sites with very different characteristics to better define the relative importance of aquaculture activities to the fatty acid profile of sea-cage associated fish communities. 4.3 Materials and Methods 4.3.1 Sampling points To determine the potential area of influence of aquaculture activities on wild fish fatty acid profiles and compare it with those of fish from areas free of aquaculture production but having or not other human activities, seven sampling points were selected. 29°00' '.� __ _)· f.um(Ol.-:naitd0.051:m) 0501.::n. >lOOb 1?'00' Figure 4.1. Location of stations for sampling points at Canary Islands, in Central East Atlantic Ocean. The first sampling point was located inside a cage of a fish farm at Tufia (O km), east coast of Gran Canaria Island, were wild bogue have entered and fed almost exclusively on aquafeeds. The second one was located near the cages (0.05 km). The third was 3 km away from the fish 73 farm at Gando, east coast of Gran Canaria (3 km). A fourth sampling point was located at 6 km from the fish cages (6 km). The fifth was in Arguineguín, south west coast of Gran Canaria Island (50 km), where there is no aquaculture, but animals coming from aquaculture could be also present. The sixth sampling point was located in an aquaculture free island, El Hierro Island, were a marine reserve is located (> 100km) (Fig. 4.1 ). Finally, the seventh sampling point was at the vicinity of sewage outfall from Las Palmas de Gran Canaria city that fulfills all the legal requirements of Spanish and European Union legislations for this type of outfalls. 4.3.2 Fish samples Fish samples were · obtained from the different sampling points defined. At least 20 individuals from each sampling point were obtained within same week by fishing or netting, both during summer (August) and winter (February). All individuals were sacrificed after sampling and kept in ice until dissection in the lab, where whole fish and their livers were weighed and measured. From each sampling point, 9 fish were used for whole fish analysis, whereas liver and muscle were dissected from another 9 individuals, all the samples being packed under vacuum and kept at -80ºC until analysis. Fulton's K condition index (CI) was calculated as an indicator of general well-being of individuals. This morphometric index is based on the assumption that heavier fishes for a given length are in better condition: K = IO0*(WglL/), where Wg is the gutted body weight (g) and L1 is the total length (cm), and was calculated for all the animals captured. Hepatosomatic index (HSI) was calculated as HSI=(liver weight x bodyweighC1) *100. 4.3.3 Biochemical and fatty acid analysis Biochemical compositions of fish were analyzed following standard procedures (AOAC, 2000). Ash content was determined by combustion in a muffle fumace at 600 ºC for 12 h; moisture content was determined by drying the sample at 105 ºC until it achieved a 74 constant weight; finally, crude lipid content was extracted following the method of Folch et al. (1957). Fatty acids from total lipids (stored under nitrogen atmosphere at-80 ºC) were prepared by transmethylation as described by Christie (1982) and fatty acid methyl esters separated by gas chromatography under the conditions described by Izquierdo et al. (1990). All analyses were conducted in triplicate. 4.3.4 Statistical analysis To test whether condition index, HSI, fat content and the main F As varied among the proximity and season, an analysis of variance (ANOVA) was used, which incorporated the factors -season (fixed) with two levels (summer and winter) and proximity (fixed) with 6 levels (localities): 0km, 0.05km, 3km, 6km, 50km and >l00km. Fish weight and liver weight (in liver analysis) were covariates. Variance was not homogeneous and data transformations did not get homogeneity, then significance level at 0.01 (P<0.01) was defined, and increased confidence level (99%). (Underwood, 1997). Principal components analysis (PCA) was used as the ordination method. Variables that had more influence on similarities within groups and dissimilarities among groups of locations were calculated using the SIMPER (similarity percentages) procedure (Clarke, 1993). Inside sea cages (0km) were compared with sewage outfall. A permutation test (PERMANOV A) was used to assess the significance of the overall fatty acid composition among the considered sources ofvariation (Anderson, 2004). 4.4 Results Those fish inside sea cages showed aquaculture-related increases of CI and HSI. CI was significantly (P<0.01) higher for bogues inside the fish cage (0km). Besides, HSI was significantly (P<0.01) higher inside sea cages when compared to values obtained at 6 and 50 km stations (Table 4.1 ). Proximate composition analysis showed that there were also influences of aquaculture on biochemical composition of fish inside sea cages. Lipid content 75 20:3n-3 0.1±0.0 0.1±0.0 0.6±0.l 0.1±0.0 0.2±0.0 0.4±0.1 0.0±0.0 20:4n-3 0.6±0.2 0.6±0.l 0.6±0.1 0.4±0.2 0.4±0.l 0.4±0.l 0.1±0.0 20:5n-3 5.6±1.7 6.4±2.0 5.9±0.7 5.2±1.4 4.8±2.3 5.6±1.1 1.3±0.4 22:5n-6 0.2±0.0 0.4±0.1 1.5±0.3 0.9±0.3 1.2±0.4 2.0±0.5 0.3±0.0 22:5n-3 2.2±0.4 2.8±0.6 1.4±0.2 2.2±1.2 l.2±0.3 1.9±0.6 0.4±0.2 22:6n-3 6.l±l.9 12.0±5.9 26.6±4.7 19.2±4.3 23.0±9.4 28.1±5.9 4.4±1.0 Table 4.4 Whole fish fatty acid profile of bogue (Boops boops) from the different sampling points (mean± SD). N=l8. Whole fish 0km 0.05 km 3km 6km 50km >100 kmSewage outfall 14:0 4.2±0.4 4.3±0.2 2.8±0.4 4.3±1.5 2.5±1.5 2.3±0.2 2.4±0.0 16:ln-7 6.5±0.5 6.0±0.2 3.4±0.5 6.1±1.3 2.9±1.3 2.8±0.1 3.3±0.3 16:2n-4 0.7±0.3 0.7±0.1 l.0±0.4 0.9±0.0 1.1±0.5 1.4±0.2 0.3±0.1 17:0 0.8±0.2 0.8±0.1 0.4±0.1 0.8±0.2 0.5±0.1 0.3±0.1 0.3±0.0 16:4n-3 0.6±0.3 0.6±0.1 0.7±0.4 0.6±0.3 0.7±0.7 0.2±0.0 0.7±0.1 18:0 4.9±0.3 5.6±0.4 8.6±1.1 6.7±1.0 8.7±1.0 8.4±1.1 7.1±0.8 18:ln-9 19.9±2.9 19.4±0.8 11.8±1.1 18.1±1.2 1 l.2±1.3 9.6±2.0 26.6±1.6 18:ln-7 3.3±0.6 3.0±0.7 2.8±0.2 3.6±0.5 2.5±0.3 2.2±0.5 2.2±0.2 18:2n-6 17.1±2.1 14.1±0.7 2.8±0.8 7.2±0.9 3.4±0.9 1.4±0.3 16.4±1.7 18:3n-3 1.7±0.3 1.6±0.1 0.6±0.2 0.7±0.1 0.8±0.2 0.4±0.1 0.6±0.0 18:4n-3 1.1±0.5 0.9±0.1 0.5±0.2 0.8±0.2 0.5±0.3 0.3±0.1 0.3±0.0 18:4n-1 0.2±0.l 0.1±0.0 0.0±0.0 0.1±0.0 0.0±0.0 0.0±0.0 0.0±0.0 20:ln-9+n-7 1.1±0.l 1.7±0.3 3.5±1.2 1.7±0.3 1.3±0.6 3.0±1.2 1.1±0.2 20:ln-5 0.2±0.0 0.3±0.0 0.3±0.1 0.3±0.1 0.2±0.1 0.3±0.2 0.1±0.0 82 Whole fish 20:4n-6 0.6±0.1 0.8±0.1 4.0±0.9 2.0±1.1 4.1±2.4 2.6±0.4 1.4±0.2 20:3n3 0.1±0.0 0.1±0.0 0.3±0.1 0.1±0.0 0.2±0.1 0.3±0.0 0.1±0.0 20:4n-3 0.5±0.1 0.5±0.1 0.4±0.1 0.4±0.1 0.3±0.1 0.3±0.0 0.2±0.0 20:Sn-3 6.5±1.8 5.9±1.0 4.2±0.5 5.8±1.2 4.1±0.4 4.0±0.5 1.9±0.3 22:Sn-6 0.2±0.0 0.4±0.1 1.5±0.3 0.6±0.2 1.9±0.5 2.5±0.4 0.9±0.3 22:Sn-3 1.8±0.3 2.3±0.5 1.1±0.2 2.1±0.4 1.1±0.3 1.1±0. l 0.5±0.1 22:6n-3 6.6±2.1 8.3±0.9 19.6±3.4 10.4±2.6 23.6±6.6 27.0±5.6 10.4±2.2 Muscle, liver and whole fish LA content were significantly (P<0.01) higher in fish inside sea cages, but not different from those coming from the sewage outfall (Fig. 4.2b ). Alpha linolenic acid was significantly (P<0.01) highest in fish inside the cage or at 0.05km (Fig. 4.2c). Interestingly, EPA values obtained for muscle 0km was significantly (P<0.01) higher than the values obtained for the rest of the sampling points except from those coming from 0.05km and 6 km point. Sewage outfall fish had the lowest (P<0.0 1) content in EPA in muscle (Fig 4.2d). Arachidonic acid values varied markedly among the different samples, without a clear pattem, denoting the essentiality of this fatty acid and suggesting a potential relation with the different dietary regimes. Nevertheless, values were significantly (P<0.01) lower for fish at 0km, 0.05km and sewage outfall, without significant differences with 100 km samples (Fig. 4.2e). Similarly, DHA also varied among samples and were significantly (P<0.01) lowest at 0km, 0.05km and at the sewage outfall (Fig. 4.2f). Since n-6 fatty acids were higher in fish inside the sea cages, at 0.05 km and the sewage outfall and long chain n-3 fatty acids were lower, the ratio n-3/n-6 was significantly lowest for those fish (Fig. 4.2g). The PCA analysis of fatty acids contents showed two different groups of samples: those from fish obtained inside the sea cages (0km), at 0.05km together or in the sewage 83 outfall in one hand and those located at 3km, 50km and >l00km in the other hand (Fig. 4.3). The data obtained in the 6km group remained between both groups. PERMANOV A analysis showed that these differences in fatty acid composition were significant (P<0.01). A whole SIMPER analysis of pooled data from the three tissues showed dissimilarity between samples of fish inside the cage, at 0,05km or the sewage outfall and samples at 3km, 6km, 50km and 100km, was high 34.07. This analysis showed that the main differentiating FAs were DHA, OA and LA (Table 4.5), followed by palmitic acid (16:0). PCA 8 ::K o ¿o ::K )o AOkm X o oxo■o.os km � oo X3km ºx ◊6km -8 •-2q 8 +i xx<i :t:so km + �X 0>100 km + Sewage outfall -6 -8 Figure 4.3. Principal Component analysis (PCA) of all fatty acids within the different sampling points. Besides, dissimilarity given by SIMPER analysis between samples from animals inside sea cage (0km) and the sewage outfalls was low: 19.35. This analysis showed that the main differentiating FAs were OA, EPA and DHA ( 24.43, 12.30 and 10.32 % of contribution respectively). Other fatty acids such as LA contributed with 6.79, whereas ARA contributed with 1.64% (Table 4.6). 84 Table 4.5. SIMPER analysis. Contribution of the main fatty acids in different tissues (muscle liver and whole fish) to overall dissimilarities between human input (aquaculture-related sampling points plus sewage outfall) and the rest of sampling points away from cages (3km, 6km, 50km, >l00km), and percentage to the cumulative dissimilarity. Groups Human input and Sampling points away from cages. Average dissimilarity = 34.07 Human Sampling points away from input cages Fatty Average Average Dissimilarity / Contributio Cumulativ abundanc Average abundance acids Dissimilarity SD n¾ e% e 22:6n-3 9.43 26.17 8.68 1.78 25.47 25.47 18:ln-9 22.09 9.71 6.4 1.75 18.8 44.27 18:2n-6 14.7 3.21 5.76 2.48 16.92 61.19 16:0 20.0 23.01 1.85 1.41 5.42 66.6 20:4n-6 1.03 4.52 1.77 1.31 5.18 71.78 16:ln-7 4.79 2.71 1.27 1.64 3.74 75.52 20:5n-3 4.5 4.56 1.15 1.56 3.39 78.91 18:0 6.57 8.35 1.14 1.43 3.35 82.26 14:0 3.09 1.92 0.83 1.54 2.43 84.69 22:5n-6 0.51 1.93 0.74 1.61 2.17 86.86 20:ln1.17 1.82 9+n-7 0.48 1.04 1.41 88.27 22:5n-3 1.61 1.46 0.47 1.47 1.39 89.66 18:ln-7 2.91 2.29 0.44 1.33 1.28 90.94 4.5 Discussion It has been widely described that sea cages farros aggregate wild fish around the floating structures, altering their natural occurrence, schooling behaviour and feeding behaviour even when the cages are empty (Machias et al., 2004; Tuya et al., 2006; Dempster et al., 2005; Arechavala-López et al., 2011). Sea cages may mimic the role of Marine 85 Protected Areas (Dempster et al., 2004; 2005) as consequence of both natural prey concentration or the existence of wasted food in the water column from aquaculture activity (Tuya et al., 2006; Mente et al., 2008). About 80% of the particulate organic matter may be consumed before it settles on the sediment (Vita et al., 2004). In this sense, farm-associated fish help to remove wastes produced and may enhance local fishing (Vita et al., 2004; Dempster et al., 2005; Dimitriou et al., 2007). However, fish associated to these structures may be influenced by the composition of the aquafeeds wastes as a consequence of the abundance of a highly energetic food. In the present study, tissue lipid contents of bogue found far from the sea cages were close to those previously described for this species in the Mediterranean (Ozogul and Ozogul 2007). In comparison, bogues found inside the fish farm showed an increased lipid content in muscle and whole fish, whereas in fish surrounding the cages the values showed intermediate values. This fact, together with the higher CI, may be related to the continuous availability of the highly energetic aquafeeds (up to 27% lipid content, Sargent et al., 2002) and the reduction in the bogue energy expenditure for predatory effort. Aquaculture-associated fish have been found to have higher lipid content in muscle (Skog et al., 2003; Femandez-Jover et al., 2007). Indeed, the lipid content in fish muscle changes in relation to the species, geographical origin, season and, especially diet (Rasoarahona et al., 2005). Other studies have shown that liver lipids are higher in farmed than in wild sea bream (Grigorakis et al., 2002; Mnari et al., 2007) and sharpsnout sea bream Diplodus puntazzo (Rueda et al., 2001). In the present study, despite lipid contents were also higher in liver of bogues associated to the farms, their values were similar to those found close to the sewage outfall and could not be considered as a good indicator of aquaculture influence. Although the balance between energy intake and expenditure markedly affects tissue lipid contents and CI, the diet may also markedly affect also the tissue fatty acid profile as a 86 consequence of the type of dietary lipids ingested. Thus, the fatty acid profile in the different fish tissues is characteristic of the different dietary oils (reviewed by Turchini et al., 2009). At present aquafeeds include vegetable oils and meals that increase the fish content in fatty acids characteristics from terrestrial sources (Turchini et al., 2009). Thus, sorne fatty acids such as 18:C n-6 or 18:C (mainly LA and OA) are present in aquafeeds in a higher proportion than in the natural marine environment, due to the inclusion of soybean, sunflower or canola oils (Brown and Hart 2010; Turchini and Mailer 2010). The type of dietary fatty acids affects different metabolic pathways and the expression of genes encoding many different proteins including those involved in lipid metabolism (Izquierdo and Koven 2011). For instance, vegetable oils increase lipids storage as triacylglicerols, especially in the liver, as well as the type of fatty acids used to obtain energy by modulating the beta-oxidation capacity (Torstensen and Tocher 2010). Table 4.6. SIMPER analysis. Contribution of the main fatty acids in different tissues (muscle liver and whole fish), to overall dissimilarities between fish inside sea cages (O km) and fish around sewage outfall, and percentage to the cumulative dissimilarity. Groups: Inside sea cages and Sewage outfall Average dissimilarity= 19.35 Inside sea Sewage cages outfall Fatty Average Average Average acids abundan ce abundance Dissimilarity 18:ln-9 19.88 28.54 4.73 20:5n-3 6.18 1.41 2.38 22:6n-3 7.08 8.65 2 16:ln-7 6.01 3.26 1.38 Dissimilarit Contributi Cumulati y/SD on¾ ve% 1.67 24.43 24.43 3.31 12.3 36.73 1.1 10.32 47.05 2.34 7.14 54.2 87 18:2n-6 16.21 18.03 1.31 1.54 6.79 60.98 16:0 19.12 20.22 1.15 1.13 5.92 66.9 14:0 3.81 2.11 0.87 2.04 4.5 71.4 18:0 5.64 6.67 0.85 1.38 4.38 75.78 22:5n-3 1.93 0.46 0.73 3.74 3.8 79.58 18:3n-3 1.71 0.71 0.5 3.62 2.59 82.17 18:ln-7 3.13 2.44 0.38 1.45 1.99 84.15 18:4n-3 0.88 0.24 0.32 1.84 1.67 85.83 20:4n-6 0.62 1.25 0.32 2.07 1.64 87.46 22:5n-6 0.2 0.74 0.27 1.06 1.39 88.85 17:0 0.75 0.25 0.25 3.41 1.29 90.14 Fernandez-Jover et al. (2007) related higher values of LA and OA to farm-associated fish, together with a reduction in Highly Unsaturated Fatty Acids (HUFAs) in comparison to non associated fish. Similarly, Martinez-Rubio et al. (2009) found higher OA and LA contents together with lower DHA, ARA, ARA/EPA and n-3/n-6 in muscle of bogue sampled around a fish farm. In Norwegian fiords, LA and ALA were higher in saithe (Pollachius virens L.) found near to a fish farm and decreased with the increasing distance from the farm, suggesting a dilution gradient effect of aquaculture activities (Skog et al., 2003). The results of the present study, agree well with those observations studies, being LA, OA, ALA percentage higher in bogues influenced by aquaculture, and ARA and DHA lower. This aquaculture influenced fatty acid profile was diluted by the distance to the sea cages farm and disappeared at 3 km from the farm. Mente et al. (2006) proposed that sorne fish species from Scotland, including saithe, effectively move from distances larger than 2 km far away from sea cages to feed aquafeeds pellets. In our study, the dominant currents in the farm zone, east of Gran 88 Canaria Island, run north to south, but no aquaculture wasted-feed effect could be detected at 3km. Interestingly, EPA values are increased in muscle for aquaculture-influenced fish in agreement with those results obtained by Rueda et al., (2001) for sharpsnout sea bream. On the other hand no differences on EPA have been reported among wild and cultured Atlantic salmon (Megdal et al., 2009). Based on those described changes of fatty acids due to aquaculture influence, sorne authors have proposed certain fatty acids ( and even general FA changes) as biomarkers or indicators in studies of the structure and dynamics of fish food webs around Mediterranean marine fish farms (Femández-Jover et al., 2010). However Megdal et al. (2009) proposed that not all the fatty acids can be used as indicators, LA being a reliable indicator for Atlantic salmon. For sea bream, HUFAs have been proposed as indicators being EPA more abundant in cultured fish, but ARA more abundant in wild (Rueda et al., 2001). Both LA and ALA have been described to be presented at higher concentrations in cultured fish than wild fish (Mnari et al., 2007). However, few of this studies took into account other parameters and events that can be affecting fatty acid composition of wild and aquaculture fish other than aquafeeds. Firstly, fatty acids of the different tissues reflect in a general way the fatty acid profile of the diet, due to the accumulation of fatty acids as triacylglicerols (Torstensen and Tocher 2010) and, although 18:C fatty acids are increased in aquafeeds-fed fish, these fatty acids tend to be eliminated or washed-out progressively from the fillet and other tissues as soon as those animals stop to feed aquafeeds (Izquierdo et al., 2005; Torstensen et al., 2004). Secondly, 18:C fatty acids, and specially LA, is also abundant in the marine trophic chain, being algae and other organisms rich on this fatty acid (Meziane and Tsuchiya 2000, 2002; Ortiz et al., 2006), all of these organisms being candidates to be predated by escaped fish and of natural occurrence both around farm structures and on the wild. Thirdly, aquafeeds 89 formulae are continuously changing depending on the ingredients availability and prices, and consequently fatty acid profile of aquafeeds is in a continuous evolution (Gunstone, 2010), and thus, farm associated animals and aquaculture fish are not receiving always the same fatty acid composition. Fourthly, although aquaculture wastes are important inputs of these "terrestrial" fatty acids, other human activities increase the presence of these fatty acids in the marine environment, through sewages and agriculture activities (Quemeneur and Marty 1992; Seguel et al., 2001). Indeed, sewage outfall is a variable source of different fatty acids that directly change fatty acid profiles of organisms living around them (Y ep, 2006), being this effect disseminated within large distances (Seguel et al., 2001). For instance, urban waste waters have been shown to alter fatty acid profile of sediments and marine organisms (Yip, 2006; Dunn et al., 2008). Wong et al. (2008) found a relationship of trophic linkage between mussel fatty acids (Perna viridis) and fatty acid profile from suspended particulate matter, affected by domestic sewage. These authors, as well as others (Yip, 2006), defined an increase of LA and OA in animals around sewage outfalls. In agreement, in the present study bogue sampled around a sewage outfall showed the accumulation of LA and OA, denoting that statistically the fatty acid profile of fish living in the vicinity of a sewage outfall is similar to those associated to a fish farm. Nevertheless, they only slightly differed on the levels of LA and EPA. Moreover, samples obtained at 6km point, in the vicinity of Las Palmas de Gran Canaria city, showed higher values of those "terrestrial" fatty acids than samples with no human effects the 100km sampling point. Besides, not only urban waste water can be inducing an important input of LA or OA in the marine environment, but also other human activities such as agriculture wastewater. For instance, agriculture wastewater modifies the fatty acid profiles of the marine crab (Uca vocans) or the mollusc (Terebralia sulcata) (Meziane and Tsuchiya 2002). Mangrove detritus input (Meziane and Tsuchiya 2002), and 90 uncontrolled input of different chemicals and contaminants, such as diesel oil, have been also seen to alter the fatty acid composition of the gastropod Littorina littorea (Grahl-Nielsen and Bamung 1985). Therefore, the presence of those so-called "terrestrial" fatty acids in the marine trophic webs is due to multiple sources and not only due to aquafeeds. In conclusion fish farros have a direct effect on the CI, muscle and whole lipid content of bogue inside or around the sea cage, as a consequence of continuous availability of food that completely disappeared at 3 km from the cages. Despite aquafeeds also affected the bogue fatty acid profiles by increasing linoleic and oleic acids and reducing DHA, these profiles were very similar to those of bogue sampled close to a sewage outfall. Therefore, the fatty acid profile <loes not seem to be a completely reliable biomarker of aquaculture activities, since other human activities including urban waters may induce similar changes in the linoleic acid, oleic acid and DHA contents. 4.6 Acknowledgements Authors would like to thanks Rafael Guirao, Rector Ramírez, Jonás Ramírez, Juan Luis Sánchez, and Cristobal Ruano for assistance during sampling, and the staff of the Canexmar fish farros for their help. We are grateful for the assistance of Femando Tuya in statistical analysis 91 have existed, are related to aquaculture escapes (Carrillo and Castillo, 2001; Toledo et al., 2009; Toledo et al., 2012). In these islands, for example, escaped European sea bass diet overlaps with other top predators and may become a new competitor for local species (Carrillo et al., 1995; Toledo et al., 2009; Toledo et al., 2014a), though significant correlations between the number of escapees and abundances of other fish species were not found in the Canary Islands (Toledo et al., 2014a). Yet, there is no reported evidence of reproduction of escaped European sea bass from this archipelago (Carrillo et al., 1995; Toledo et al., 2009), although developed gonads have been found (Toledo et al., 2012). Inbreeding would be exclusively possible at the eastem islands, where small wild populations exist (Brito 1991). Several morphological and physiological indicators have been proposed as useful tools for the identification of escapees, based on biometrical parameters (Ellis et al., 2009; Uglem et al., 2011), scales and otholits morphology (Katayama and Isshiki, 2007; Person-Le Ruyet and Le Bayon, 2009), scale mineral contents (Adey et al., 2009), RNA/DNA ratios (Gwak et al., 2003) or muscle fatty acid (FA) composition (Grigorakis et al., 2002; Femández-Jover et al., 2007, 2011; Arechavala-López et al., 2013b). Regarding the latter, the FA profile has been claimed to be a good bio-indicator of species interactions (Dunn et al., 2008; Hu et al., 2008; Maazouzi et al., 2008). The FA profile has received increasing attention due to changes in aquafeed ingredients over recent years. Traditionally, fish were fed with diets based on fishmeal and fish oíl as the main ingredients to ensure a competitive price and adequate content in sorne essential FAs for fish, such as docosahexaenoic acid (DHA) (22:6n-3), eicosapentaenoic acid (EPA) (20:5n-3) and arachidonic acid (ARA) (20:4n-6). These FAs, which have a plethora of very important functions, are considered essential for marine fish, since these species do not have the ability to bio-convert shorter F As into these F As, due to the very low activity of delta 6 and delta 5 desaturase in these fish (Izquierdo and Koven, 2011 ). Given that the world production of fish oíl is stagnated with the consequent increase in 98 cost, there is a strong trend for the use of vegetable oils as fish oils substitutes (Tacon and Metían, 2008). The use of vegetable oils in the feeds of marine fish is problematic, because of their lack of long chain n-3 PUFA, and the abundance of the 18:C FAs precursors, e.g. linoleic acid (LA) (18: 2n-6) and alpha-linolenic acid (ALA) (18: 3n-3) (Turchini et al., 2009). These F As precursors are incorporated into the tissues of farmed fish, and can also be transferred to wild fish (Femández-Jover et al., 2011 ). Wild fishes around offshore aquaculture cages may feed on pellets released from farms, resulting in changes in body condition and FA profiles, bringing their body composition and that of other organisms in different trophic levels closer to that of cultivated fish (Skog et al., 2003; Femández-Jover et al., 2007, 2011 ). For this reason, the presence of certain F As, such as LA, ARA and oleic acid (OA) (18: ln-9), in wild organisms has been proposed as an indicator of the influence of aquaculture on marine ecosystems (Rueda et al., 2001, Femández-Jover et al., 2007; Femández-Jover et al., 2011; Arechavala-López et al., 2013b). Toe goal of this paper was, firstly, to analyze the spatio-temporal variability in the population structure of escaped European sea bass after a massive escape (approximately 1,500,000 fish, 400,000 kg, 30-45 cm of total length at the moment of escape) that occurred on February 2010 at La Palma Island (Canary Islands, eastem Atlantic). We secondly determined whether escaped European sea bass diet, reproductive potential and FA pro file changed with distance from aquaculture cages. We hypothesize that: (1) escaped fish can re distribute around the entire island perimeter after a massive escape, (2) being able to adapt to the wild by consuming local prey, (3) lacking reproduction and ( 4) altering their FA profiles depending on distance from the source of escapees. 99 5.2 Materials and methods 5.2.1 Sampling design and study locations To monitor the massive escape of European sea bass that occurred between the 20 and 26th February 2010 at La Palma Island, we selected six locations throughout the entire island perimeter (Fig. 5.1). One location was immediately adjacent to the escape point (a sea-cage fish farm off Tazacorte) and the rest were selected at different distances away from this point, northward and southward around the entire island perimeter. One location (El Remo) was set within a marine reserve (Reserva Marina Isla de La Palma). No location was selected in the north face of the island due to prevailing swells from the NW that impedes regular sampling. This protocol was repeated six times (i.e. sampling campaigns): August 2010, September 2010, October 2010, November 2010, August 2011 and October 2011. Locations encompassed a range ofhabitats at shallow water (ca. 5-10 m depth). 18" 17" 16" 15º 14º • ATLANTIC OCENl 1---ba--P-alma------if-------+-------+-----�- Gran Canaria � 0 �--,------------1 2ac 7 O km 50 Figure 5. l. Map of the study area detailing sampling locations at La Palma Island: 1 Tazacorte (Acuipalma S.L. farm); 2 El Remo (marine reserve); 3 La Salemera; 4 Santa Cruz de la Palma; 5 Puerto Talavera; 6 Puntagorda; and Gran Canaria Island: 7 Melenara (ADSA S.L. and Canexmar S.L. farms); 8 Arinaga; 9 Castillo del Romeral (ADSA S.L. and Playa Vargas S.L. farms); 10 (San Cristobal). 100 To study stomach contents, gonad development and F As profile, escaped European sea bass were captured by spear-fishing throughout the entire study, i.e. from August 2010 to October 2011, at both La Palma and Gran Canaria. Although sorne of them presented unusable tissues due to shaft impacts, this was the most appropriate and effective capture method because local fishermen do not fish close to the surf, where European sea bass are often grouped (Toledo et al. 2009). Catches were kept in ice until processed in the laboratory, where individuals were weighed (accuracy to 0.1 g) and measured (accuracy to 0.1 cm). The gonads, stomachs, muscle tissue and livers were removed from each individual; the gonads were preserved in formaldehyde and the stomachs preserved in 70% ethanol; muscle tissue and livers were frozen for subsequent lipid analysis. Samples for lipid analyses were categorized according to 3 distances from aquaculture facilities: 'Cages': O km (inside cages), 'Near cages': <10 km and 'Far away from cages':> 10 km. In addition to samples collected at La Palma Island (i.e. where the escape event took place), samples were simultaneously taken at Gran Canaria Island (Fig. 5 .1) to assess whether pattems with distance from aquaculture cages for a range of descriptors (see below) were consistent between the two islands. By increasing the spatial replication, the robustness of the study is enhanced if results were consistent between both islands. In La Palma Island, there is only one off-shore farm, while at Gran Canaria there are four off-shore fish farms located at two locations (Fig. 5.1). 5.2.2 Fish surveys At each location and time, fish were counted by means of visual census techniques through four replicated 50 m long transects, which were haphazardly laid out during daylight hours. The abundance and size of fish was recorded on waterproof paper by a SCUBA diver within 2 m of either side of transects, according to standard procedures implemented in the study region (Tuya et al. 2004). We also recorded the type of habitat under each transect (%), which was categorized according to 'big boulders' (> 2 m of diameter), 'small boulders' ( < 1 m 101 of diameter), 'sand', 'breakwaters' (i.e. artificial man-made constructions) and 'bare rock' (Tuya et al., 2004). 5.2.3 Stomach contents To analyze the diet composition of escapees, stomachs were weighed and the content removed. Total food items from each stomach were placed on filter paper to eliminate excess moisture and subsequently weighed. Prey items were identified to the lowest possible taxonomic level; the total number of prey items were counted and weighed for each stomach. The percentage composition by number and weight was then calculated for each prey category to calculate the indices of importance by number (IN), wet mass (IW) and global importance (IG). IN=[(% composition by number) X(% occurrence)}u2 (Windell, 1971; Vesin et al., 1981). IW = [(% wet mass) X(% occurrence)f12 (Castro, 1993). IG = (IN% +IW%) / 2 (Moreno and Castro 1995) 5.2.4 Gonadal development For each fish, gonads were macroscopically examined for sex differentiation to establish the stage of gonadal development, by using a visual scale of five stages of maturity based on color and the relative size of gonads: I undeveloped; II developing; III mature; IV spawn; V post-spawn (Holden and Raitt, 1974). 5.2.5 Lipid and FA pro.files A total of 60 livers and 60 muscles samples were analyzed. 1 O for each distance ('Cages', 'Near Cages', and 'Far away from Cages') from both La Palma and Gran Canaria 102 islands (n = 1 O). Biochemical assays followed standard procedures (AOAC, 2000). Moisture content was determined by drying the sample at 105 ºC, until achieving a constant weight. Crude lipid content was extracted following the method of Folch et al. (1957). F As from total lipids (stored under nitrogen atmosphere at -80 ºC) were prepared by transmethylation, as described by Christie ( 1982) and FA methyl esters separated by gas chromatography following Izquierdo et al. ( 1990). All analyses were conducted in triplicate. 5.2.6 Data analysis Fish survey data and FA profile composition were analyzed by means of ANOV A (Underwood, 1997). We tested for differences in escapees abundance between locations at varying distances from the escape point around La Palma Island and the sampling times through a 2-way ANOVA that incorporated the factors: (1) "Locality" (fixed factor with six levels, corresponding to the 6 locations) and (2) "Time" (fixed factor with six levels and orthogonal to the previous factor); "Time" was considered fixed, as sampling dates were equidistantly separated. A x2 tested for differences in diet composition (by considering the percentages of the different prey items) between islands, and a Wald-Wolfowitz test contrasted differences in fish length between islands. To test for differences in FA profile composition (total lipid, OA, LA, ALA, palmitic acid (PA) (16:0)), ARA, EPA, DHA, ¿satured, ¿monounsatured, ¿n-9, ¿n-6, ¿n-3 F and ¿n-3/¿n-6 ratio) with varying distance from cages, 2-way ANOVAs incorporated the factors: (1) "Island" (fixed factor with two levels: La Palma and Gran Canaria); (2) "Distance" (fixed factor with three levels corresponding to the three distances from the aquaculture sea farms: 'Cages', 'N ear cages' and 'Far away from cages'. Before the analyses, the Cochran's test was used to check for homogeneity of variances. If the test detected heterogeneous variances (Cochran's test, P < 0.01), data transformation was performed. In sorne cases, variances remained heterogeneous despite transformations; the significance level was then set at the more conservative O.O 1 103 value instead of the conventional 0.05 level to decrease a type I error (Underwood, 1997). If ANOV A detected significant differences, further analyses were performed by using the SNK a posteriori multiple comparison test (Underwood, 1997). When data did not achieve homogeneous variances, the Games-Howell post hoc test was used. The SIMPER analysis identified the main contributors to differences in FA pro files between islands at varying distance from cages. A Chi square (X2) tested for departures from a 1: 1 sex ratio. Non-metric multidimensional scaling (nm-MDS) ordination plots were implemented to visualize differences in the FA profiles (OA, LA, ALA, PA, ARA, EPA, DHA, ¿)atured, ¿monounsatured, In-9, In-6, In-3 FAs and In-3/In-6 ratio) from muscle and liver tissue between islands and the three distances from the aquaculture sea farms: 'Cages', 'Near cages' and 'Far away from cages'. The SPSS (v. 15.0), PRIMER (v. 5.2.4) and PERMANOVA (v.1.6) software were used in these statistical analyses. 5.3 Results 5.3.1 Spatial-temporal distribution of escaped European sea bass after the escape event The mean abundance of escaped European sea bass at La Palma Island was 4.9 ± 14.3 ind 100 m-2 (mean± SE, n = 144 transects) during the study period, which varied between O fish in severa} transects to a maximum of 100 ind 100 m-2• All locations had escaped European sea bass, at least one individual during the study period (Fig. 5.2). The ANOV A (Table 5 .1) demonstrated that escaped Euro pean sea bass densities decreased significantly (p<0.01) through the study period, particularly in October 2010; and that Tazacorte (i.e. the point of massive release) had significantly (p<0.01) higher densities (17.0 ± 29.1 ind 100 m-2) than the other locations (Fig. 5.3). 104 Table 5.1. ANOVA results of the effect of 'Time' and 'Locality' on the mean abundance of sea bass (Dicentrarchus labrax) at La Palma Island. Source of variation df MS F p Time 5 204.909 79.096 0.0002 Locality 5 150.132 57.951 0.0004 Time x Locality 25 29.859 11.526 0.2918 Residual 108 25.907 105 16 (a) 14 -10-15 C::J 16-20 -12 � -21-25 E C::J 26-30 o10 o � -31-35 -e, e 8 -36-40 ::::. C1) -41-45 e (U 6 C]46-50 -e, e ::::s - 51-55 Jl 4 < C:J 56-60 2 o 50 (b) 40 - � 30 C1) ::::s (,) C1) ... C1) (,) 20 e C1) ... ::::s (,) 10 o..,__ __ Sta. Cruz Talavera P. Gorda Tazacorte Salemera El Remo Figure 5.2. Size-class (a) abundances and (b) frequency of occurrence of escaped European sea bass, Dicentrarchus labrax, at each location around La Palma Island. Data were pooled for each location through the 6 sampling times. 106 The mean abundance of escaped European sea bass at La Palma Island was 4.9 ± 14.3 ind 100 m·2 (mean± SE, n = 144 transects) during the study period, which varied between O fish in severa! transects to a maximum of 100 ind 100 m ·2. All locations had escaped European sea bass, at least one individual during the study period (Fig. 5.2). 50 1 2 3 40 1 4 5 N • 6 E 30 o o - 'g 20 ·- 10 o oooo� � � � � � � � o o o o o o N N N N N N -lo. lo. lo. - <l,l Q,) <l,l "' -= -= -= � -= 1:)1) e o e a = -= Q,) < <l,l � Q,) < -o � - Q. o Q. <l,l z <l,l 00 00 Figure 5.3. Mean abundances (ind l00m-2) of escaped sea bass, Dicentrarchus labrax, at each time and location at La Palma Island. 1 Tazacorte (Acuipalma S.L. farm); 2 El Remo (marine reserve); 3 La Salemera; 4 Santa Cruz de la Palma; 5 Puerto Talavera; 6 Puntagorda The largest densities of escaped European sea bass from La Palma were observed in breakwaters (Game-Howell test, p<0.05, Fig. 5.4). The length range of observed European sea bass varied between 15 and 60 cm (Fig. 5.5); the majority of fish, however, were between 35 and 50 cm (Fig. 5.2). 107 B o o 00 � 0 o � � o $ � � $ $ o Stress: 0,07 Q:¡ [81 o o o 4. □Ca� □□ □ □• • • LP/Gages oLP/Near $ LP/Far ■GC/Cages oGC/Near [81 GC/Far Figure 5.7. Non-metric multi-dimensional scaling ordination of (A) muscle and (B) liver fatty acids profiles of sea bass, Dicentrarchus labrax, from 'Cages', 'Near' (<10 km away from the cages) and 'Far' (>10 km away from the cages) at La Palma (LP) and Gran Canaria (GC) islands. The majority of FAs showed a similar pattern with varying distance from cages at both islands (Tables 5.4 and 5.5). At La Palma Island, we typically detected significant differences in the percentage of FA with varying distance from the farm; this pattern, however, was minored at Gran Canaria Island, where we exclusively detected significant differences with varying distance from cages in the percentage of ¿n-3/¿n-6 ratio (Figs. 5.8_13 and 5.8_14), muscle total lipid (Fig. 5.8_1), OA from muscle (Fig. 5.8_3) and EPA from muscle (Fig. 5.8_9). A posteriori SNK tests demonstrated that crude lipid from individuals captured at La Palma Island, including both muscle (5.8_1) and liver (Fig. 5.8_2) tissues, had significantly larger values in samples coming from 'cages' than 'far away' from cages; 'Near' samples did not differ from 'far away' samples for muscle tissue (Fig. 5.8_1). At La Palma Island, the concentration of OA was significantly higher in samples from 'cages' than 'near' cages' or 'far away', for both muscle (Fig. 5.8_3) and liver (Fig. 5.8_ 4) samples. Cultured ('cages') European sea bass from La Palma had significantly higher LA (Figs. 5.8_5 and 5.8_6) and 114 ALA (Figs. 5.8_7 and 5.8_8) than 'near' and 'far away' samples, for both muscle and liver; fish from 'near' and 'far away' distances did not show significant differences. The percentage of EPA in muscle was larger at 'cages' relative to 'near' and 'far away' samples at Gran Canaria (Fig. 5.8_9); at La Palma, however, there was no difference between 'cages' and 'far away' samples (Fig. 5.8_9). The percentage of EPA in liver tissue (Fig. 5.8_10) differed between 'near cages' and 'far away' samples collected from La Palma. In-9 and ¿Monounsatured F As from La Palma followed the same pattem: significantly larger values for cultured fish than 'far away', for both muscle (Figs. 5.8_15 and 5.8_17, respectively) and liver (Figs. 5.8_16 and 5.8_18, respectively) tissue samples. 115 -25 1 E 100 2 25 b 3 Cl Cl ·¡¡¡ ·¡¡¡ 3: a 3: a a � 20 �80 "C 20 ��11) a "C 'tJ e: g 15 ;g. 60 11) 15 11) G) :-2 "C 'tJ <i. ::J 2 u: ... (.) (.) .... 40 Cl .... 10 o 10 o o 11) G) o Cl ... Cl (O e, (O e: e: 5 G) 20 5 11) (.) (.) � D.. D.. o o o Cages Near Far Cages Near Far Cages Near Far Muscle lipid content Liver fat content Oleic muscle 20 5 25 6 7 a a B a B o 'tJ 20 a 'tJ 2 11) 15 a, a a, E i.:: i.:: E -� -� e: e: 11) 11) 15 11) 2 :-2:-2 d. 10 <i. <i. .,,: u:u: Cl Cl 10 Cl ::, o o ::, o o ... ... ... a, 5 e, e, 5 o o o Cages Near Far Cages Near Far Cages Near Far Linoleic muscle Linoleic liver Linolenic muscle 12 9 10 10 25 11 B b AB B 10 8 20 'tJ !E 8 -� 6 a> 15 :2 :2 a 6 <i. <i. u: u: Cl 4 C) 10 e e 4 e e .... C) 2 2 5 o o o Cages Near Far Cages Near Far Cages Near Far EPAmuscle EPA liver DHAmuscle 5 13 6 14 25 b B B 4 5 20 '0 '0 B '0 a, a, G) !E !E � B e 4 e a, 3 a, G) 15 :'S! :'S! :'S! ci b ci 3ci u.: u.: u.: Cl 2 Cl b ba Cl 10 e e e e e 2 e .... .... C) C) C) 5 o o o Cages Near Far Cages Near Far Cages Near Far ¿n-3/¿n-6 muscle rn-3/¿n-6 liver r n-9 muscle 40 17 50 18 10 19 b b B '0 '0 40 '0 8 G) 30 CD G) !E !E !E e e: e: CD 30 G) 6 :'2 :'2 :'2 ,d. ,d. ,d. AB u.: 20 u.: u.: b Cl Cl 20 CI 4 e e e e e e .... ... e, 10 e, e, 10 2 o o o Cages Near Far Cages Near Far Cages Near Far L Monounsatured FA muscle L Monounsatured FA liver ARAmuscle 40 21 B 50 22 30 23 B B AB b 40 "C "C 30 Gl !E � i: 20 30 A :2 20 ,ci u: C) 20 oo o o 10 T" T" 10 e, e, 10 o o o Cages Near Far Cages Near Far Cages Near Far r n-3 FA muscle L n-3 FA liver Palmitic muscle 50 'ti 40 CD !E CD 30 < u: tll 20 e, e, 10 o 25 40 26 ■ Gran Canaria B B B □La Palma CD 30 :5! < 20 u: e, e, e, 10 o Cages Near Far Cages Near Far Saturad FA muscla Saturad FA livar Figure 5.8. Percentage of lipid content and fatty acids in muscle and liver of escaped sea bass, Dicentrarch away from the cages) and 'far' (> 10 km away from the cages). Alphabetic superscripts denote significant farms. 1) muscle lipid content; 2) liver fat content; 3) muscle oleic acid (18:2n-9); 4) liver oleic acid (18:2n liver linoleic acid (18:2n-6); 7) muscle linolenic acid (18:3n-3); 8) liver linolenic acid (18:3n-3); 9) muse liver eicosapentaenoic acid (20:5n-3); 11); muscle docosahexaenoic acid (22:6n-3); 12) liver docosahexa n-3/n-6; 14) liver ratio n-3/n-6; 15) muscle ¿ n-9 FA; 16) liver ¿ n-9 FA; 17) muscle ¿ monounsatured muscle arachidonic acid (20:4n-6); 20) liver arachidonic acid (20:4n-6); 21) muscle I n-3 FA; 22) liver I 1 24) liver palmitic acid (16:0); 25) muscle ¿ satured FA; 26) liver ¿ satured FA. In contrast, severa! F As showed an overall increase in their concentration with distance away from cages. For example, ARA showed higher values in 'far away' than 'cages' and 'near' samples, for both muscle (Fig. 5.8_19) and liver (Fig. 5.8_20) for La Palma, and exclusively for muscle tissue at Gran Canaria (Fig. 5.8_19). At La Palma, the percentage of DHA was significantly higher in 'far away' and 'near' samples than cultured fish ('cages') for muscle samples (Fig. 5.8_11). For liver samples (Fig. 5.8_12), however, there was no difference between 'near' and 'cages'. The concentration of¿n-3 FAs from La Palma, for both muscle (Fig. 5.8_21) and liver (Fig. 5.8_22), were larger in 'far away' than 'cages' samples. At Gran Canaria, we detected a larger concentration of ¿n-3 FAS for muscle samples at 'cages' (Fig. 5.8_21). No difference in the level of PA was registered between 'cages' and 'far away' samples from both islands, for both muscle (Fig. 5.8_23) and liver (Fig. 5.8_24). The ¿n-3/¿n-6 ratio and satured FAs from La Palma, for both muscle (Figs. 5.8_13 and 5.8_25, respectively) and liver (Figs. 5.8_14 and 5.8_26, respectively), were significant higher from 'near' and 'far away' than 'cages' samples. Finally, it is worth noting that the percentage of all FAs of cultured fish (i.e. 'cages') differed between islands (Fig. 5.8, Tables 5.4 and 5.5), except the fat percentage, DHA, satured, ARA and PA in muscle tissue, and monounsatured, ¿n-9, satured, OA and PA in liver tissue. Table 5.4 Percentage value (mean± SD) of different fatty acids identified in muscle of sea bass with varying distance from sea cage fish farms. MUSCLE Cultured Near Far Gran Canaria La Palma Gran Canaria La Palma Gran Canaria La Palma Lipid 13.3 ± 4.7 11.2±4.0 14.8±8.2 5.0±1.4 9.2±3.8 4.2±1.6 n-9 19.4±1.7 23.0±1.2 22.2±3.1 17.7±3.5 20.1±2.2 11.9±3.2 n-615.6±1.6 19.0±0.8 17.0±4.2 8.2±2.6 17.3±4.9 12.0±2.4 n-3 28.9±3.8 21.9±2.0 19.5±5.7 25.9±5.3 21.9±3.7 30.7±8.7 121 Saturated 26.0±1.2 25.6±1.3 29.7±3.6 37.3±5.1 30.2±6.3 36.2±10.2 Monounsaturated 27.7±2.4 32.1±1.8 32.3±4.1 25.6±5.1 29.1±2.6 17.2±4.2 n-3/n-6 ratio 1.9±0.4 1.2±0.1 1.2±0.5 3.4±1.1 1.4±0.5 2.6±0.7 14:0 3.0±0.4 3.0±0.3 3.1±0.9 1.8±0.6 2.4±0.6 1.3±0.6 14:ln-7 0.0±0.0 0.1±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 14:ln-5 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 15:0 0.3±0.0 0.3±0.0 0.3±0.1 0.4±0.1 0.3±0.1 0.3±0.1 15:ln-5 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 16:01SO 0.0±0.0 0.0±0.0 0.1±0.0 0.6±0.8 0.1±0.0 1.0±0.9 16:0 17.3±0.9 17.8±1.4 20.3±2.3 26.1±3.8 20.9±4.5 23.3±6.1 16:ln-7 4.6±0.5 4.3±0.4 4.7±1.1 3.7±1.6 4.1±0.5 2.1±0.8 16:ln-5 0.1±0.0 0.1±0.0 0.1±0.0 0.2±0.1 0.2±0.0 0.1±0.1 16:2n-6 0.0±0.0 0.5±0.1 0.3±0.2 0.3±0.2 0.1±0.1 0.1±0.1 16:2n-4 0.4±0.1 0.2±0.0 0.3±0.1 0.6±0.2 0.3±0.1 0.4±0.2 17:0 0.4±0.l 0.3±0.l 0.2±0.0 0.2±0.2 0.2±0.0 0.2±0.1 16:3n-4 0.2±0.0 0.2±0.1 0.1±0.1 0.3±0.1 0.1±0.1 0.1±0.1 16:3n-3 0.1±0.0 0.1±0.0 0.1±0.1 0.2±0.0 0.1±0.0 0.2±0.1 16:3n-1 0.2±0.1 0.2±0.1 0.2±0.2 0.8±0.4 0.4±0.3 1.4±0.4 16:4n-3 0.4±0.1 0.4±0.1 0.4±0.2 0.6±0.3 0.3±0.l 0.8±0.3 16:4n-1 0.1±0.0 0.1±0.0 0.1±0.0 0.2±0.1 0.1±0.0 0.3±0.1 18:0 4.9±0.5 3.9±1.5 5.5±1.3 8.5±2.1 6.1±2.2 11.0±4.3 18:ln-9 17.4±1.5 22.4±1.1 21.5±3.0 17.2±3.4 19.5±2.3 11.2±2.8 18:ln-7 2.9±0.1 2.7±0.1 2.9±0.3 2.4±0.2 3.0±0.5 2.4±0.3 18:ln-5 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.1 18:2n-9 0.2±0.0 0.2±0.0 0.2±0.1 0.2±0.1 0.2±0.1 0.1±0.0 18:2n-6 12.5±1.8 16.1±0.7 14.3±4.3 2.9±2.0 12.8±7.2 4.0±1.7 18:2n-4 0.3±0.0 0.2±0.0 0.2±0.0 0.1±0.1 0.2±0.0 0.1±0.1 18:3n-6 0.2±0.0 0.2±0.0 0.2±0.1 0.1±0.1 0.2±0.1 0.2±0.1 18:3n-4 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.0±0.0 18:3n-3 1.5±0.2 2.1±0.2 1.5±0.5 0.4±0.3 1.7±0.6 0.4±0.1 18:3n-1 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 18:4n-3 0.9±0.1 0.6±0.1 0.6±0.2 0.7±0.8 0.5±0.2 0.2±0.1 18:4n-1 0.1±0.0 0.1±0.0 0.1±0.1 0.1±0.0 0.1±0.0 0.2±0.2 20:0 0.2±0.0 0.2±0.0 0.2±0.0 0.2±0.0 0.2±0.0 0.2±0.1 20:ln-9+n-7 1.4±0.2 1.5±0.1 1.8±0.6 1.4±0.5 1.4±0.2 0.8±0.4 20:ln-5 0.2±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.2±0.0 0.1±0.1 20:2n-9 0.1±0.0 0.1±0.0 0.1±0.0 0.0±0.0 0.1±0.0 0.0±0.0 20:2n-6 0.7±0.1 0.7±0.0 0.7±0.1 0.4±0.1 0.7±0.1 0.7±0.1 20:3n-9 0.1±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 20:3n-6 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.2±0.1 0.1±0.1 20:4n-6 1.3±0.3 1.0±0.2 1.0±0.4 3.4±2.2 2.7±2.2 5.9±3.0 20:3n-3 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.1 0.1±0.1 20:4n-3 0.5±0.0 0.4±0.0 0.3±0.1 0.3±0.2 0.3±0.1 0.2±0.1 20:Sn-3 9.8±0.9 7.4±0.7 6.1±2.0 4.8±1.4 5.7±1.6 7.3±2.6 22:ln-11 0.6±0.l 0.5±0.1 0.8±0.7 0.2±0.1 0.3±0.1 0.2±0.1 22:ln-9 0.2±0.0 0.2±0.0 0.2±0.1 0.2±0.1 0.2±0.0 0.1±0.1 22:4n-6 0.4±0.0 0.1±0.0 0.2±0.1 0.1±0.1 0.2±0.2 0.1±0.1 22:Sn-6 0.4±0.1 0.3±0.0 0.3±0.1 0.9±0.3 0.5±0.2 1.0±0.3 122 22:Sn-3 22:6n-3 1.9±0.2 13.7±3.1 1.4±0.1 9.5±1.6 1.2±0.3 9.3±4.4 0.8±0.3 18.1±4.3 1.6±0.6 11.5±2.6 1.5±0.9 20.1±6.4 Table 5.5 Percentage value (mean± SD) of different fatty acids identified in liver of sea bass with varying distance from sea cage fish farms. LIVER Cultured Near Far Gran Canaria La Palma Gran Canaria La Palma Gran Canaria La Palma Lipid 76.7±2.6 67.5±5.7 63.7±21.7 47.4±16.4 61.1±27.5 21.4±9.9 n-9 30.3±2.8 28.2±2.7 25.7±3.6 25.6±6.1 25.6±3.9 10.1±3.5 n-6 12.1±1.4 21.7±1.8 18.1±4.1 6.8±2.7 15.9±7.1 11.6±2.4 n-3 23.5±2.9 19.4±2.8 21.6±3.9 23.2±6.8 20.3±4.0 41.1±5.5 Saturated 22.8±1.4 21.4±1.8 23.3±2.8 32.1±3.8 27.2±7.6 29.9±6.5 Monounsaturated 39.7±3.0 36.1±2.8 35.5±4.5 35.7±6.8 35.1±4.7 16.1±4.7 n-3/n-6 ratio 2.0±0.2 0.9±0.1 1.2±0.4 4.0±2.1 1.5±0.7 3.7±0.9 14:0 1.9±0.2 1.8±0.6 2.4±0.7 1.9±0.4 2.2±0.6 1.7±0.7 14:ln-7 0.1±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 14:ln-5 0.1±0.0 0.1±0.0 0.0±0.0 0.1±0.0 0.1±0.0 0.1±0.0 15:0 0.3±0.0 0.2±0.0 0.3±0.1 0.4±0.1 0.3±0.1 0.5±0.1 15:ln-5 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 16:0ISO 0.1±0.0 0.0±0.0 0.1±0.0 0.1±0.0 0.1±0.0 0.1±0.1 16:0 16.6±1.1 15.7±1.7 16.4±1.8 23.7±2.6 19.8±5.9 20.0±4.2 16:ln-7 5.0±0.3 3.9±0.2 4.9±1.2 5.0±0.9 5.2±0.7 3.3±1.6 16:ln-5 0.1±0.0 0.1±0.0 0.2±0.0 0.3±0.1 0.2±0.l 0.2±0. l 16:2n-6 0.0±0.0 0.2±0.0 0.2±0.1 0.2±0.1 0.2±0.1 0.1±0.1 16:2n-4 0.2±0.0 0.2±0.0 0.3±0.2 0.5±0.3 0.3±0.1 0.4±0.2 17:0 0.2±0.0 0.2±0.1 0.3±0.1 0.3±0.4 0.3±0.1 0.1±0.1 16:3n-4 0.5±0.0 0.2±0.l 0.1±0.1 0.7±1.0 0.1±0.1 0.2±0.1 16:3n-3 0.1±0.0 0.1±0.0 0.1±0.0 0.9±2.4 0.1±0.0 0.1±0.1 16:3n-1 0.0±0.0 0.0±0.0 0.0±0.0 0.0±0.0 0.1±0.2 0.3±0.2 123 fish (Rueda et al., 2001; Bell et al., 2002; Blanchet et al., 2005; Femández-Jover et al., 2007, 2011; Mnari et al., 2007; Megdal et al., 2009). Normally, reared European sea bass present higher proportions of OA and LA and lower proportions of PA, ARA, EPA, and DHA than wild European sea bass (Alasalvar et al., 2002; Femández-Jover et al., 2011; Arechavala López et al., 2013b). Additionally, percentages oftotal saturated, as well as the n-3/n-6 ratio, are higher in wild than cultured European sea bass (Alasalvar et al., 2002; Femández-Jover et al., 2011); these results match the outcomes of this study. FA composition, however, may not be reliable biomarkers of aquaculture activities since other human activities, including discharges of urban waters, may induce similar changes (Ramírez et al., 2013), directly by feeding or due to the relatively high conservation of FA composition throughout the food web (Femández-Jover et al., 2011). This is particularly relevant for European sea bass, as a result of its quick dispersion behaviour. We also observed differences in the profile of F As between cultured fish from Gran Canaria and La Palma; this is a consequence of continuous changes in aquafeeds formulae that depends on the ingredients availability and fluctuating market prices (Gunstone, 2010). DHA, OA and LA seem to be selectively retained in European sea bass muscle (Montero et al., 2005). When fish that has been fed with vegetable oil containing diets is subjected to a period of fish oil re-feeding, the amount of 18:C FAs (particularly LA in those fish fed previously with soybean oil containing diet) remains higher and EPA lowers (Montero et al., 2005). To determine if a FA is a good aquaculture biomarker, it would be necessary to perform a study at the same region, where the FA composition should be in similar from both culture and escaped fish and distinct from wild fish. In the present study, however, there was no wild fish, so we were able to exclusively assess if FA composition changed with varying distance from farros. Contrary to Femández-Jover (2011), FA profile cannot be used as biomarkers, because there were significant differences between distance groups ('cages'- 130 'near'-'far') in this study. Moreover there is an inconsistency for F As highlighted among severa! studies (Grigorakis et al., 2002; Mnari et al., 2007; Arechavala-López et al., 201 la; Ramírez et al., 2013; Arechavala-López et al., 2013b), so the usefulness of FAs as biomarkers for escaped fish is doubtable. We found different F As than those proposed by Arechavala-López et al. (2013b) (i.e. LA and ARA) as possible biomarkers. The current study could suggests P A (liver) and EPA (both at liver and muscle) as the candidates as possible biomarkers, because these F As were not different with varying proximity from the farms; however further studies are necessary to confirm its reliability. This matches the result showed by Montero et al. (2005), where EPA values did not become to control diet (fish oil) after a re-feeding period in the laboratory. In the Canary Islands, Ramírez et al. (2013) concluded that ALA is a possible aquaculture biomarker for bogue, Boops boops, a zoo-planktivorous and opportunistic fish that aggregates around sea-cage fish farms in the Canary Island and the Mediterranean; this is because samples taken around sewage discharge points did not increase the ALA percentage. However, this study demonstrated that ALA cannot be used as a biomarker for escaped European sea bass. F As could be used to identify escaped fish when matching similar FA profiles from cultured fish. However, if FA profiles do not match those of cultured fish, it is impossible to work out whether a fish has been bom in the wild or, altematively, is an old escapee that has progressively suffer a wash-out. In summary, despite escaped fish were able to exploit natural resources, the density of escapees decreased through time. Those fish able to adapt and use natural resources altered their FA pro files in comparison to cultured fish, denoting the poor usefulness of FA profile as a good bio-indicator, limiting their potential to a very short period of time after escape events. 131 5.5 Acknowledgements Authors would like to thank María López Ruano for her help to produce this document. Our thanks also go to Tamia Brito, manager of La Palma Island Marine Protected Area. The staff at Acuipalma S.L. for their collaboration. David Jiménez Alvarado and Yamilet Cárdenes are acknowledged for their assistance during field sampling. This work was partially funded by Prevent Escape project (no. 226885). 132 6Evaluación de interacciones ambientales de peces escapados de jaulas de cultivos. QIFERENCIAS MORFOLÓGICAS 6 "MORPHOLOGICAL DIFFERENCES BETWEEN FARMED AND ESCAPED SEA BASS (Dicentrarchus labrax)" Besay Ramírezª'\ Daniel Montero\ Ricardo Harounb ªGrupo de Investigación en Acuicultura. Universidad de Las Palmas de Gran Canaria and Instituto Canario de Ciencias Marinas. P.O. Box 56. 35200. Telde, Las Palmas, Canary lslands, Spain. bBIOGES, Marine Sciences Faculty, Campus Tafira, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas de G.C., Canary lslands, Spain. 6.1 Abstract In order to evaluate the effectiveness of morphometry to distinguish farmed from escaped sea bass (Dicentrarchus labrax), twenty individuals of both farmed and escaped from Gran Canaria and La Palma Island (Canary Islands, Spain) were analyzed. We established thirteen landmarks which defined 28 morphological measurements that were processed by means of "Image-Pro Plus" software. ANOVA test showed differences only in two morphological measures from head region. Most of morphological measures matched between escaped and reared fish in Sea bass, pointing out that morphometry could be used as escape indicator because escaped fish practically did not differ from those cultured. 6.2 Introduction Global production of fish from aquaculture has grown substantially in the past decade, reaching 78.9 million tons in 2010. Aquaculture continues to be the fastest-growing animal food producing sector and currently accounts for nearly half ( 46.8 percent) of the world's food fish consumption (FAO 2012). FAO estimated sea bass (Dicentrarchus labrax) 135 European production about 55710 tons in 2010, contributing in 29.91 % of total European marine fish production and 44.24% of global sea bass production (125901 tons). Sea bass is an important commercial marine fish species along the Mediterranean and Eastern Atlantic coastline both for aquaculture and fisheries. Aquaculture has important implications for marine and coastal biodiversity at the level of genetic variability, species-species interaction and alteration within ecosystems (CBD 2004). The main impacts considered, and the most studied, are the effect of wasted food and faecal discharges, that alters and modify the sediment characteristics under fish cages (Molina-Dominguez et al. 2001; Mente et al. 2006), and the presence of sea cages that modifies the icthyological community around them (Carss 1990; Machías et al. 2004; Tuya et al. 2006; Dempster et al. 2005). Nevertheless, other sources of impacts have been studied such as addition of anti-fouling products, parasite transfers, exotic species, input of therapeutic products, visual impact or fish escapes (Hewitt et al. 2006; Femandez-Jover et al. 2010). Escapees could present environmental impact such as genetic interaction by interbreeding, transfer of pathogens, prey predation alteration, introduction of new alien species, habitat competition or/and alteration, etc. (CBD, 2004; Molina and Vergara 2005; Naylor et al. 2005; Vergara et al., 2005; Jensen et al., 2010; Grigorakis and Rigo 2011). Escapees can have detrimental genetic and ecological effects on populations of wild conspecifics, and the present level of escapees is regarded as a problem for the future sustainability of sea-cage aquaculture (Naylor et al., 2005). For sea bass, sea bream and meagre, knowledge regarding how escapes might affect ecosystems is limited or inexistent. To study this, is important to identify individuals that escape from sea-cages. Authors had suggested different ways to identify escaped fish as genetic (Glover et al. 2009), fatty acids (Femández-Jover et al. 2007), scales and otholits elementary profiles (Adey et al. 2009), 136 birnolecular trace (Megdal et al. 2009) or scales rnorphology (Lund and Hansen 1991 ). lntraspecific fish groups can show rnorphological differences due to environrnental differences coupled with adaptative genetic changes (Barlow G. 1961; Kinnison and Hendry 2004; Solern et al. 2006). Sorne authors had dernonstrated that body rnorphology can be used as stock identifier (Hurlbut and Clay 1998; Murta 2000; Solern et al. 2006; Swatripiyanka et al. 2011) or escape indicator (Loy et al. 1999; Murta 2000; Crarnon Taubadel et al. 2005; Arechavala-López et al. 2011; Uglern et al. 2011). The airn of this study was to evaluate the suitability of rnorphological variation as escapes indicator of Mediterranean aquacultured fish, identifying these body rneasures which match between escaped and reared fish in Sea bass. 6.3 Material and Methods Ten reared Sea bass were randornly sarnpled frorn each two fish farm placed in two different islands at Canarian Islands: Gran Canaria (Canexrnar S.L.) and La Palma (Acuipalrna S.L.) (Fig. 6.1). Escaped sea bass (n=20) were spearfished around Gran Canaria and La Palma. Sarnples were caught randornly between Septernber 2010 and Novernber 2011. A larger escape event was reported for Acuipalrna, in La Palma, seven rnonths before study sarnpling began. In Gran Canaria no large escape event during sarnpling were recorded. Logistics of sarnpling required the frozen of sarnples at -40 ºC. Fish were de frozen after dissection and then all sarnples were weighted (accuracy of 0.1 gr.) and rneasured (accuracy of 0.1 cm). Following, points were placed throughout fish body, to help to identify the landrnarks that we used in the posterior analysis. Morphological landrnarks were selected to give a precise definition of the fish rnorphology (Fig. 6.2). Properly calibrated coordinates of rnorphornetric locations, or 'landrnarks', are generally more efficient and precise than manual distance rneasurernents. We rneasured distances between selected landrnarks in the pattem of a graph called a truss (Strauss and Bookstein 1982), by 137 means of Image-Pro Plus (Media Cybemet, Silver Spring, MD, USA) software. 'Truss networks' of distances between landmark coordinates provide more comprehensive coverage of form for greater discriminating power. Strauss and Bookstein (1982) and Swatipriyanka et al. (2011) demonstrated the possibility of discrimination between populations by means of this technique. A total of 13 landmarks that defined 28 morphological measurements were defined (Table 6.1 ). Morphometric measurements were standardized to the overall mean total length, the standardized measure being given by: Mc=Mx (;�)b (Hurlbut and Clay 1998; Ihssen et al. 1981); where TL is the total length, Mis the original measurement, TL is the overall mean total length and b is the slope, within areas, of the geometric mean regression (Ricker 1973) on the logarithms of M and TL. Normalized measurements were statistically analyzed. Data were balanced, presented normal distribution (n > 30) and homogeneity of variances (Cochran's test; p>0.05). Non metric multidimensional scaling (nm-MDS) was used as the ordination method. A permutation test (PERMANOV A) was used to assess the significance of the overall body measurements among the considered sources of variation (factors) (Anderson 2004). Then, variables that had more influence on dissimilarities among origin factor were calculated using the SIMPER (similarity percentages) procedure (Clarke 1993). Finally an analysis of variance (ANOV A) was used to test differences of factors among each variable. If ANOV A detected significant differences, further analyses were performed by using the SNK a posteriori multiple comparison test (Underwood, 1997). Both for PERMANOVA and ANOVA the model incorporated the following experimental design: (1) Origin (fixed factor with 2 levels corresponding to cultivated and escaped origin); (2) Island (random and orthogonal factor with 2 levels corresponding to 2 different islands: Gran Canaria and La Palma). The SPSS (v. 15.0), PRIMER (v. 5.2.4) and PERMANOVA (v. 1.6) software were used for statistical analysis. 138 ,e· 17" 169 15º 14ºW ATLANTIC OCEAH L.<\.PAL'l\,iA 29" _,D Cane:miar fann O km 50 Figure 6.1. Map of study area detailing sampling farms in La Palma and Gran Canaria. Figure 6.2. The 13 landmarks and the distance measured between them, which were used for body shape study of sea bass. Black lines show significant differences between cultured and escaped fish. Landmarks were located as follows: 1 snout; 2 point of maximum curvature in the head profile curve; 3 origin of the first dorsal fin; 4 origin of the second dorsal fin; 5 posterior end 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; 1 O origin of anal fin; 11 origin of pelvic fin; 12 insertion of the operculum on the profile; 13 origin of pectoral fin. 139 survives over time could resemble a wild individual due to the changes on habitat and food. This phenotypic plasticity had been well documented by authors for different species (Currens et al. 1989; Beacham 1990; Robinson and Parsons 2002; Wintzer and Motta 2005); Released gilthead sea bream after a 6 to 7 month period in a wild habitat configured a wild like shape (Rogdakis et al. 2011 ), even juvenile brown trout and Atlantic salmon changed shape within a month in response to altered water velocities (Pakkasmaa and Piironen 2000). Fleming et al. (1994) demonstrated that sorne environmental induced differences due to juvenile hatchery rearing persisted but many disappeared. Differences between islands (Table 6.3) were due to these differences among cultivated fish and within those escaped fish, due to time elapsed after escape event. Cultivated fish differ between islands (b2, c2, c4, d4, f1 and :f2) due culture conditions (Sara et al. 1999): differences in stock density, aggressivity, stress, accumulation of perivisceral fat, hepatic hyperplasia and the type and quality of food (Favaloro et al. 2002; Fa valoro and Mazzola 2003; Sara et al. 1999), swimming performance (Basaran et al. 2007), fish mobility (Hanson et al. 2007), physical environmental condition and/or broodstock families resulting in genetic differences (as proposed by Solem et al. (2006) within Atlantic salmonjuveniles). On the other hand differences between cultured and escaped sea bass in Gran Canaria correspond to height measurement. It shows cultured higher bodies (b2, c2, c4 d4, f1 and :f2), i.e. more elongated bodies for escaped sea bass, matching with results showed by previous authors between wild and cultured fish (sea bream: Grigorakis et al. 2002; Eurasian perch: Mairesse et al. 2005; sea bass: Arechavala-López et al. 2011); and between cultured and escaped (hatchery-released) sea bream (Rogdakis et al. 2011 ). Wild individuals are characterized by a more elongated body shape when compared to those farmed (Mairesse et al. 2005). However results from La Palma were contrary, but only in 3 traits ( c2, c4 and :f2), so escaped bodies were higher. This could due to less escaped time, consequently has not 146 been time to morphological changes. Besides this, analyzed escaped sea bass from La Palma could coming from a cultured stock that might be phonotypical/genotypical different (higher bodies) than this current cultured analyzed. Summarizing previous authors is clear that body morphology is an interesting tool that permit to distingue between cultured and wild fish, including sea bass in Mediterranean (Arechavala-López et al. 2011), moreover seem possible to distingue even between cultured, hatchery-released and wild fish (Rogdakis et al. 2011 ). Our results supports that morphology can be used as escape indicator too, because escaped fish practically did not differ from those cultured in Gran Canaria and La Palma (were no autochthonous populations existed), however this conclusion should be considered cautiously due to its potential depend to the period of time after escape events since morphologic changes need time to occur. Further studies will be necessary taken into account the time elapsed since escape event. 6.6 Acknowledgements Authors would like to thank Acuipalma S.L. and Canexmar S.L. for their wide availability to get us the samples. Mónica Betancor for her assistance with the software and Víctor Tunset for provide us his knowledge in this issue. The study was partially financed by the EU-project Prevent Escape. 147 148 7Evaluación de interacciones ambientales de peces escapados de jaulas de cultivos. COMPORTAMIENTO POST-ESCAPE 7 "POST-ESCAPE BEHA VIOR OF CULTURED EUROPEAN SEA BASS, Dicentrarchus labrax, AND MEAGRE, Argyrosomus regius" Besay Ramírez\ Finn 0kland\ Femando Tuyaª, Ingebrigt Uglem\ Daniel Montero\ Ricardo Harounª ª Grupo de Investigación en Biodiversidad y Conservación, Centro de Biodiversidad y Gestión Ambiental, Universidad de Las Palmas de Gran Canaria, 35017 Las Palmas, Canary Islands, Spain. b Norwegian Institute ofNature Research, Tungasletta 2, 7485 Trondheim, Norway e Grupo de Investigación en Acuicultura. Universidad de Las Palmas de Gran Canaria, P.O. Box 56, 35200 Telde, Canary Islands, Spain. 7.1 Abstract Escapes from fish farms may involve considerable economic losses for aquaculture industry and cause negative interactions with the environment. The aim of this work was to study the movements of farmed sea bass, Dicentrarchus labrax, and meagre, Argyrosomus regius, following an induced escape, to understand the post-escape activity and behavior of escaped fish, as well as to suggest ways to mitigate escape events. Twenty five individuals of both sea bass and meagre were equipped with acoustic transmitters and released immediately adjacent to a fish farm in the eastem coast of Gran Canaria Island (Canary Islands, Spain). In addition, another 25 extemally tagged conspecifics of each species were also released. Fish movements around this farm were recorded by ten stationary receivers during three months. Recapture rates by fishermen were low, including only 1 sea bass and 2 meagre. Recaptured fishes showed signs of interaction with predators (biting attacks ). The 151 number of fish detected decreased exponentially during the first week after the release. Only nine fishes ( two meagre and seven sea bass) were detected at the study zone one month after the release. Apart from a tendency towards meagre being observed more often in the nearby coastal area, sea bass and meagre appeared to have similar post-escape movement patterns; most fish did not totally leave the farm through the first week, so we propose to focus recapture eff orts around cages during the first week after an escape event. 7.2 Introduction Global production of fish from aquaculture has grown substantially in the past decade, reaching more than 90 million tons in 2012 (F AO 2014 ). Aquaculture continues to be the fastest-growing animal food producing sector and currently accounts for nearly half (49.4%) of the world's food fish consumption (FAO, 2014). FAO estimated that European sea bass production reached 70,147 tons in 2012, contributing in 33.6 % of total European marine fish production, 3.1 % of European fish (included marine, freshwater and diadramous species) and 45.8% of global sea bass production (153,182 tons). The culture of other species, e.g. meagre, is expected to grow fast in the next few years. Indeed, meagre has the potential to become a mass market species (Monfort 2010) and it is a feasible candidate for the diversification of European aquaculture (Gil et al 2013). European meagre production was estimated in 1,865 tons in 2012, representing 0.9 % of the total European marine fish production, 0.08% of European fish (included marine, freshwater and diadramous species) and 11.7 % of the global meagre production (13,742 tons) (FAO 2014). Sea bass, Dicentrarchus labrax, is distributed from Norway to Cabo Blanco, including the Mediterranean and Black Sea (Moretti et al. 1999). Its natural range includes the easternmost islands of the Canarian Archipelago: Fuerteventura and Lanzarote (Brito 1991), but it has also been recently found at Gran Canaria, Tenerife and La Palma, as a 152 consequence of escape events from offshore aquaculture facilities (Carrillo and Castillo, 2001; Toledo et al., 2009). Sea bass typically has a wide range of distribution at local scales; it is frequent along inshore waters, inhabiting estuaries, canals, coastal lagoons and even the final part of rivers. This species can grow up to 1 m and reach 12 kg. The mean length at first maturity is 32.3 cm (range between 23-46 cm) (Froese and Pauly 2006). Sea bass feed mainly on crustaceans, molluscs and osteichthyes (Tortonese 1986; Laffaille et al. 2001; Leitao et al. 2008; Toledo et al. 2009). Meagre, Argyrosomus regius, is a fish distributed from France to Senegal, including the eastem Mediterranean (Quéméner 2002) and Canary Islands (Dooley et al., 1985; Lloris et al., 1991 ). Meagre is present at all depths along inshore and shelf waters (Froese and Pauly 2006). Both adults and juveniles are migratory in response to temperature changes (Froese and Pauly 2006; Stipa and Angelini 2005). Fish can grow up to 2 m and reach more than 50 kg. First maturity is estimated at 61.6 cm for males and within the 70-110 cm range for females; this species spawns in estuaries from March to August (González-Quirós et al 2011 ). Meagre feed mainly on crustaceans and osteichthyes (Moretti et al 1999; Gil et al 2014). Aquaculture has important implications for coastal biodiversity at the level of genetic variability, species interactions, and alterations within ecosystems (CBD 2004). The main impacts are the effect of wasted food and faecal discharges, which alters and modify the sediment characteristics under fish cages (Molina et al. 2001; Mente et al. 2006), and the aggregation of wild fishes around cages (Carss 1990; Machías et al. 2004; Dempster et al. 2005; Tuya et al. 2006). Other sources of impacts include the addition of anti-fouling products, parasite transfers, the input of therapeutic products, etc. (Hewitt et al. 2006; IUCN 2007; Femandez-Jover et al. 2010). 153 Offshore aquaculture of marine fish suffers from chronic and mass escapes, which may cause additional environmental impacts, such as genetic interaction by interbreeding with natural populations, transfer of pathogens, competition for food resources, introduction of exotic species, habitat competition or/and alteration, etc. (CBD 2004; Molina and Vergara 2005; Naylor et al. 2005; Vergara et al. 2005; Jensen et al. 2010; Grigorakis and Rigo 2011). Escapes could be particularly problematic in those zones where wild, native, populations are small, or zones outside from their natural distribution ranges. In the Canary Islands, for example, escaped sea bass and meagre diet may overlap with other top predators. Carrillo and Castillo (2001) and Toledo et al (2008) highlight that sea bass may become a new competitor for local species. No evidence of reproduction of escaped sea bass in the Canary Island has been reported however (Carrillo and Castillo 2001; Toledo et al. 2008; Ramírez et al. under review), and interbreeding (between wild and escaped fish) is exclusively possible in the easternmost islands: Fuerteventura and Lanzarote islands; because these are the only islands where wild, but reduced, populations exist (Brito 1991 ). While there is limited knowledge on how escaped sea bass interact with the environment, there is a total lack of insight regarding the potential interaction between escaped meagre and the environment The objective of this study was to describe the post escape behavior of both sea bass and meagre, by describing their spatial and temporal distribution around sea cages in coastal waters immediately after an escape. For this purpose, twenty five individuals of both sea bass and meagre acoustically tagged were released and movements recorded. In addition, to evaluate the feasibility of recapturing escaped fish by the local fishery, another twenty five extemally tagged conspecifics of each species were also released. Finally, we aimed to evaluate the degree of establishment (feralization) of escaped fish in the wild by studying the stomach contents of recaptured fish. 154 7.3 Materials and methods The study was carried out around a sea-cage fish farm located at Tufia (27º 57' N, 15º 22' W), on the east of Gran Canaria (Canary Islands, Spain); this is an area with a steep bathymetric slope (Fig. 7.1). The farm (Canexmar S.L.) cultures sea bream, Sparus aurata, as well as sea bass and meagre. Cages are located between 22 and 31 meters depth. During the study, both recreational (spear, hook and line) and commercial fisheries (mainly vía fish traps) occurred in the area surrounding the fish farm. Canary Islands 29°00' N Figure 7 .1. Map of the study area in the eastem coast of Gran Canaria, including receiver locations ( ) and farm perimeter O. The 'Near shore' zone included receivers: 1, 2 and 3; the 'Around farm' zone included receivers: 4, 5, 6, 7 and 8; the 'Off shore' zone included receivers: 9 and 1 O. Radial detection range of receivers was between 80 and 100 m. Fifty adult Sea bass (mean weigh ± SD = 829.73 ± 155.23 g) and fifty meagre (mean weigh ± SD = 966.75 ± 300.47 g) were obtained from the Canexmar S.L. reared stock, on the ih and 12th April 2010, respectively; this was 24 hours before tagging with acoustic transmitters. These individuals were transported, vía a transportation tank (500 l) with constant oxygen delivery, from the sea farm at Tufia to the Canary Institute of Marine 155