Identificación de factores de la anadromía en trucha (Salmo trutta) y ...

Departamento de Bioquímica, Genética e Inmunología

Área de Genética

Identificación de factores de la anadromía en trucha

(Salmo trutta) y su aplicación a programas de conservación

Memoria presentada por Francisco Marco Rius para optar al Grado de Doctor por la Universidade de Vigo

Vigo, Mayo de 2013

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Identificación+de+factores+de+la+anadromía+en+trucha+(Salmo&trutta)+y+su+aplicación+a+programas+de+conservación Francisco+Marco+Rius+

FINANCIACIÓN Y BECAS

Esta tesis doctoral ha sido parcialmente financiada por los siguientes

proyectos de investigación:

• Título: “Bases ecológicas y genéticas para la recuperación de

poblaciones de reo (Salmo trutta)” financiado por el Ministerio de

Educación y Ciencia con referencia CGL2007-60572/BOS. Octubre

2007 - Septiembre 2010.

• Título: “Estudios durante la etapa marina para la recuperación de

poblaciones de reo (Salmo trutta): Bases ecológicas e identificación

de secuencias reguladoras asociadas al comportamiento migrador”

financiado por el Ministerio de Educación y Ciencia con referencia

CGL2010-14964. Enero 2011 – Diciembre 2013.

Durante el desarrollo de la presente tesis doctoral, Francisco Marco Rius

ha disfrutado de las siguientes ayudas:

• Ayuda Predoctoral de Formación de Personal Investigador con

referencia BES-2008-001973.

• Contrato como investigador Predoctoral en el Departamento de

Genética de la Universidad de Vigo.

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La presente tesis doctoral ha dado lugar a las siguientes publicaciones:

• Marco-Rius, F., Caballero, P., Morán, P., & García de Leániz, C.

(2012). And the last shall be first: heterochrony and compensatory

marine growth in sea trout (Salmo trutta). PLoS ONE, 7(10),

e45528.


(2013). Mixed-effects modelling of scale growth profiles predicts the

occurrence of early and late fish migrants. PLoS ONE, 8(4),

e61744.

• Morán, P., Marco-Rius, F., Megías, M., Covelo-Soto, L., & Pérez-

Figueroa, A. (2013). Environmental induced methylation changes

associated with seawater adaptation in brown trout. Aquaculture,

392-395, 77–83.

• Marco-Rius, F., Sotelo, G., Caballero, P., Morán, P. (2013). Insights

for planning an effective stocking program in anadromous brown

trout (Salmo trutta). Aceptado en Canadian Journal of Fisheries and

Aquatic Sciences.


Can migrants escape from density-dependence?. Aceptado en

Ecology and Evolution

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ÍNDICE DE CONTENIDO

RESUMEN .......................................................................................................... 4!

INTRODUCCIÓN ................................................................................................ 8!

La trucha común .............................................................................................. 9!

Regulación de la pesca de trucha .................................................................. 10!

La anadromía en la trucha ............................................................................. 11!

El problema .................................................................................................... 12!

Trabajos incluidos en la presente tesis doctoral: unidad de coherencia temática y objetivos. ....................................................................................... 14!

I. RELACIÓN ENTRE LA FASE DE AGUA DULCE Y AGUA MARINA ..... 15!

II. METODOLOGIA BASADA EN EL ANÁLISIS DE ESCAMAS ................ 15!

III. RELACIONES ENTRE LA ABUNDANCIA DE REOS Y LA COMPETENCIA. ANÁLISIS TEMPORAL DE LAS POBLACIONES. ......... 16!

IV. DIRECTRICES PARA LA PLANIFICACIÓN DE UN PROGRAMA DE REPOBLACIÓN DE REO ........................................................................... 17!

V. METILACIÓN Y ADAPTACIÓN AL AGUA DE MAR .............................. 19!

Referencias .................................................................................................... 20!

DISCUSIÓN ...................................................................................................... 31!

Introducción y antecedentes .......................................................................... 32!

Técnicas desarrolladas y utilizadas en la presente tesis doctoral ................. 35!

TÉCNICAS GENÉTICAS EMPLEADAS ..................................................... 36!

TÉCNICAS ECOLÓGICAS Y ESTADÍSTICAS EMPLEADAS ................... 38!

APORTACIONES DE LA PRESENTE TESIS DOCTORAL ....................... 39!

Perspectivas futuras ....................................................................................... 44!

Referencias .................................................................................................... 48!

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CONCLUSIONES .............................................................................................. 57!

REPRINTS DE LAS PUBLICACIONES ............................................................ 60!

And the last shall be first: heterochrony and compensatory marine growth in sea trout (Salmo trutta) .................................................................................. 61!

Mixed-effects modelling of scale growth profiles predicts the occurrence of early and late fish migrants ............................................................................ 72!

Can migrants escape from density-dependence? ......................................... 80!

Insights for planning an effective stocking program in anadromous brown trout (Salmo trutta) ................................................................................................. 92!

Environmental induced methylation changes associated with seawater adaptation in brown trout ............................................................................. 110!

FACTOR DE IMPACTO Y CALIDAD DE LAS PUBLICACIONES .................. 118!

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RESUMEN

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RESUMEN

La trucha común, Salmo trutta, es una especie de salmonido que exhibe

diferentes comportamientos de migración dependiendo del ambiente. Algunas

poblaciones contienen juveniles que migran frecuente al mar mientras en otras,

los movimientos son muy restringidos y los individuos tienden a quedarse toda

la vida en agua dulce. El término migración parcial se usa para describir el

fenómeno por el cual la población se divide entre individuos migradores y

residentes. Normalmente, en ríos localizados en áreas costeras con acceso al

mar, la trucha anádroma o reo y la trucha residente viven en simpatría. Cuando

los adultos migradores vuelven al río de origen para el desove, las truchas y los

reos pueden reproducirse entre ellos y los juveniles crecen sin distinción alguna

en el mismo río. Cuando llega la época del esguinado, la decisión entre migrar

o permanecer en el río se toma cuando se excede cierto umbral de condiciones

ecológicas y genéticas, lo que representa un claro ejemplo de plasticidad

fenotípica.

Las poblaciones de trucha se someten continuamente a programas de

repoblación por el gran interés socio-económico de la especie. Lo que ocurre

es que estos programas de repoblación están destinados principalmente a las

poblaciones residentes. A pesar del gran interés del reo desde el punto de vista

recreativo, las repoblaciones no aumentan el numero de estos individuos

debido a que la domesticación ocurrida en la piscifactoría hasta la suelta

produce efectos sobre la capacidad de anadromía. Por ello, en los últimos años

la cantidad de reos se ha visto disminuida respecto a la cantidad de trucha.

Los objetivos principales de este trabajo han sido tratar de cuantificar las

condiciones genéticas y ecológicas que van a determinar la migración de la

trucha e intentar aplicar los resultados para llevar a cabo un programa de

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repoblación que aumente la fracción anádroma de los individuos soltados en

poblaciones naturales.

En primer lugar se realizó un control de los individuos migradores de seis

poblaciones naturales distintas con el objeto de observar diferencias entre ellas

y determinar la necesidad de condiciones particulares en la conservación de la

especie dependiendo de la cuenca. Además también se cuantificó la relación

en el crecimiento entre la fase de río y la de mar para conocer los efectos de la

migración sobre el crecimiento.

En segundo lugar, se observaron las diferencias en el crecimiento y las

relaciones denso-dependientes en una serie temporal de 13 años en dos

poblaciones. Esto permitió observar y cuantificar la relación del crecimiento con

la abundancia de individuos en la cuenca y su tendencia en los años

estudiados. La relación que existe entre el número de individuos y el

crecimiento resulta importante en la gestión de las repoblaciones, ya que

deben adaptarse los individuos repoblados a la capacidad de carga de la

cuenca donde son soltados. Además, a lo largo de este estudio se desarrolló

una técnica de análisis mediante el uso de escamas y métodos estadísticos

que permitió diferenciar los individuos migradores de los tardíos en función del

crecimiento juvenil.

Paralelamente, se realizó una repoblación mediante huevos plantados y

juveniles de un año de edad teniendo en cuenta ciertos parámetros genéticos,

como el tipo de reproductor usado en el cruce (migrador o residente) o el grado

de similitud entre el MHC (de las siglas en inglés Major Histocompatibility

Complpex) de los progenitores. Tras completar su ciclo vital, cierto número de

individuos fueron capturados antes de desovar en una estación de captura. Se

observó que los parámetros genéticos de los progenitores son clave para el

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aumento de la fase anádroma, aunque también se registraron individuos

residentes provenientes de todos los cruces.

Finalmente, como consecuencia de la necesidad de nuevas técnicas genéticas

para el estudio de la anadromía y su adaptación a técnicas de repoblación, se

desarrolló un estudio de metilación de los tejidos. Se comprobó como una dieta

rica en sal está relacionada con cambios en la metilación de las branquias, y a

su vez, como los individuos alimentados con esta dieta durante un tiempo

específico son capaces de sobrevivir mejor en agua salada. Por tanto, la

metilación es un proceso reversible que puede coordinarse con los programas

de repoblación para resultar en un diseño óptimo de estrategias para el

aumento de la fase anádroma.

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INTRODUCCIÓN

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INTRODUCCIÓN

La trucha común

La trucha común (Salmo trutta L.) es el pez más abundante en aguas

continentales de la región paleártica (Elliot 1994). La distribución geográfica de

esta especie se extiende de forma natural desde el océano Ártico (norte de

Noruega) y el mar Blanco (Rusia) hasta las montañas del Atlas en el norte de

África, y desde Islandia hasta el mar Aral en Afganistán y Pakistán.

La trucha muestra una considerable variación y plasticidad en muchos

aspectos de su morfología, ecología y comportamiento (Klemetsen y col. 2003;

Jensen y col. 2008; Fraser y col. 2011). La gran diversidad de adaptaciones

ecológicas y de comportamiento explica que durante mucho tiempo se haya

clasificado en más de 50 especies diferentes (Behnke 1972) atendiendo a su

forma, color, tamaño, etc. Todas las truchas tienen capacidad migradora,

aunque en función del lugar donde realizan su ciclo de vida (hábitat de agua

dulce o salada) se distinguen dos tipos: trucha residente y trucha migradora o

anádroma (reo; Jonsson y Jonsson 1993; Caballero y col. 2012).

Aunque todas las truchas que habitan en Europa pertenecen a una sola

especie, ésta presenta diferentes subespecies o variedades locales (García-

Marín y col. 1999; Bernatchez 2001; Ayllon y col. 2006). Parece claro que gran

parte de las poblaciones de trucha actualmente existentes en Europa se

originaron a partir de trucha migradora al mar, en una recolonización que tuvo

lugar hace unos 14.000 años, y que en los lugares en donde existen varios

tipos de trucha el estado ancestral reciente es la anadromía. Posteriormente

las poblaciones de los diferentes ríos y lagos evolucionaron de forma

independiente (Ferguson 2006).

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Las dos variedades de trucha que habitan en España, tradicionalmente

clasificadas erróneamente como subespecies y denominadas trucha común y

reo, son en realidad morfotipos (o fenotipos) que se han adaptado a unas

determinadas condiciones de vida y a unos ciclos biológicos concretos

(Caballero y col. 2012). La trucha marina o reo (tradicionalmente S.trutta trutta)

es un migrador anádromo que realiza la mayor parte de su ciclo vital en agua

dulce y en un momento dado de su ciclo de vida (en general a partir del

segundo año de vida en el río) esguina (se vuelve de color plateado) y se

desplaza a los estuarios para completar su crecimiento en un tiempo que oscila

entre unos pocos meses y años (Elliott 1994; Caballero y col. 2012). El reo se

puede encontrar en los ríos que drenan al Cantábrico y los que lo hacen al

Atlántico por encima de la latitud 42º N (río Limia en el norte de Portugal;

Bouza y col. 1999; Caballero 2006). La trucha común (tradicionalmente S. trutta

fario) es la variedad residente que desarrolla toda su vida en aguas dulces.

Esta variedad sólo migra aguas arriba durante la época de reproducción en

busca de lugares idóneos para la freza, pero siempre en aguas dulces. La

trucha permanece presente en muchos ríos de la península aunque se ha

extinguido en varios de ellos (Toledo y col. 1993; Hervella y Caballero 1999).

Regulación de la pesca de trucha

En Galicia, la trucha está sujeta a explotación regulada legalmente.

Únicamente está permitida la pesca con caña en el río, mientras que la pesca

en el mar bien con caña o con redes está totalmente prohibida y

económicamente penalizada. La ley que rige la pesca fluvial en Galicia es la

Ley 7/1992 de 24 de julio y el reglamento que la desarrolla, se rige por el

Decreto 130/1997 de 14 de mayo, por el que se aprueba el Reglamento de

Ordenación de la Pesca Fluvial y de los ecosistemas Acuáticos. El periodo

hábil de pesca oscila entre mediados de marzo y finales de agosto, existiendo

en los ríos zonas de veda (prohibición de pesca), zonas libres y cotos

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regulados. Para pescar es necesario estar en posesión de la correspondiente

licencia emitida por las diferentes comunidades autónomas. La diferencia entre

la trucha residente y la trucha anádroma es de tal magnitud que la mayoría de

los pescadores deportivos creen que se trata de dos especies diferentes, a lo

que contribuye sin duda la regulación de la pesca (a efectos de número de

capturas y tamaños mínimos) donde claramente se diferencia entre trucha y

reo a nivel administrativo.

La anadromía en la trucha

La anadromía es señal de cambios fisiológicos, ya que los requisitos para vivir

en agua dulce y agua salada son diferentes, así como los patrones de

alimentación y comportamiento (Caballero y col. 2006). Existen diferentes

evidencias de que existe una base genética para muchos de los cambios

mencionados, aunque la mejor explicación para la anadromía es considerarla

como un carácter cuantitativo controlado por múltiples genes y con influencia

del ambiente. Cuando la combinación de estos factores excede un valor

umbral, la consecuencia será la migración al mar (Jonsson y Jonsson 1993;

Ferguson 2006). Numerosos trabajos examinan y comparan la variabilidad

genética en muestras de trucha anádroma y residente del mismo río utilizando

alozimas, DNA mitocondrial y marcadores nucleares como mini y microsatélites

(Petersson y col. 2001; Hansen y col. 2002; Hovgaard y col. 2006). A pesar de

su gran interés, estos estudios presentan dos grandes problemas. El primero

de ellos es la posibilidad de que las truchas analizadas no sean siempre parte

de la misma población, ya que dentro de un río pueden coexistir varias

poblaciones, sobre todo en ríos con numerosos afluentes. El segundo de los

problemas recae en la dificultad para distinguir durante la fase juvenil a los

individuos residentes de los migradores (véanse criterios en Bagliniere 2000),

ya que al producirse el esguinado en diferentes épocas del año, una trucha

clasificada como residente en primavera podría ser migradora en otoño.

Aunque la mayoría de estos estudios concluyen que no existen diferencias

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genéticas entre las dos variedades de trucha, esto no se traduce de manera

directa en ausencia de base genética de la anadromía, ya que al tratarse de un

carácter cuantitativo umbral, los resultados obtenidos con marcadores

moleculares neutros no son contradictorios (Ferguson 2006). Además, existen

patrones de expresión génica diferenciados entre ambos tipos de trucha (Giger

y col. 2006) y también existen evidencias del control genético de

comportamiento anádromo en trucha y otras especies afines. Algunas de estas

evidencias son:

• Pérdida de anadromía en poblaciones con la construcción de barreras

físicas (Jonson 1982; Morita y col. 2009)

• Poblaciones de reo diferentes muestran diferentes patrones de

migración (Jonsson y L'Abee-Lund 1993; Jonsson y col. 2001)

• En estudios experimentales la progenie de reo produce más reo que la

progenie de trucha residente (Skrochowska 1969)

• Comportamiento migrador diferente entre machos y hembras de una

misma población (Fleming 1993; Caballero y col. 2012)

• Control genético de la dirección de migración (Nielsen y col. 2001)

• El patrón temporal de migración aguas arriba y abajo está determinado

genéticamente en el salmón Atlántico (Nielsen y col. 2001; Stewart y col.

2002)

El problema

En los últimos años las poblaciones de trucha en España han disminuido, tanto

en número como en tamaño e independientemente de la pertenencia a

poblaciones anádromas o residentes. La principales causas están envueltas en

esta diminución son la contaminación, las obras públicas (principalmente

construcción de presas y canalización de ríos), y la sobreexplotación. Esta

situación es general en los países industrializados, si bien hay que señalar que

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la situación de la trucha en la mayoría de los ríos españoles no es

preocupante. Con el objeto de restaurar o incrementar algunas de las

poblaciones, es habitual que en determinados ríos se realicen actuaciones

concretas como repoblaciones con individuos procedentes de piscifactoría,

transferencia de individuos de unas poblaciones a otras o cría en cautividad y

posterior suelta de alevines y juveniles del propio río. Estas actuaciones han

tenido un éxito desigual dependiente de los ríos y métodos utilizados (Morán y

col. 1991; Izquierdo y col. 2006; Almodóvar y col. 2006).

En las poblaciones de trucha que habitan en las partes bajas de los ríos

conviven y se reproducen individuos que completan todo su ciclo de vida en

agua dulce con aquellos que realizan migraciones al mar. En las repoblaciones

realizadas en estas zonas parece claro que las truchas que sobreviven

carecen, en su mayor parte, de componente migrador al mar, por lo que es

muy difícil con las metodologías utilizadas hasta la fecha, recuperar

poblaciones de reo. En muchos casos este fracaso es atribuible al stock

utilizado. Así por ejemplo en España durante muchos años se utilizó en la

repoblación un stock centroeuropeo de piscifactoría que, debido a su cría

continua en agua dulce, es posible que hubiera perdido su capacidad de

migración (Morán y col. 1991; Serrano y col. 2009). Lo sorprendente es que

cuando se reproducen en cautividad reos salvajes y sus alevines son criados

en piscifactoría durante un periodo inferior a un año, al utilizarlos para

suplementar los ríos, su capacidad de migración se ve enormemente

disminuida (Serrano y col. 2009). Está contrastado por experiencias en otros

países, que la repoblación, sobre todo si se utilizan stocks domesticados,

disminuye drásticamente el potencial de anadromía de las poblaciones salvajes

(Østergaard y col. 2003; Ruzzante y col. 2004) y que el simple hecho de

mantener las truchas en piscifactoría durante la etapa juvenil disminuye este

potencial, posiblemente debido a la alimentación (Glover y col. 2004). Por

tanto, parece claro que la trucha de repoblación no contribuye a aumentar la

fracción anádroma de las poblaciones de trucha con acceso al mar.

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Trabajos incluidos en la presente tesis doctoral: unidad de coherencia temática y objetivos.

La presente tesis doctoral es un compendio de cinco publicaciones científicas,

de las cuales todas ellas han sido aceptadas. La tesis se realizó siguiendo la

normativa de la Universidad de Vigo y se centra en el estudio de las bases

ecológicas y genéticas de la anadromía en las poblaciones de trucha común.

Como se mencionó anteriormente, la relación entre ambas disciplinas (ecología

y genética) es clave para la obtención de nuevos conocimientos sobre el

fenotipo migrador de esta especie. Además, los estudios llevados a cabo en la

presente tesis doctoral sirven para sentar las bases de un programa de

repoblación enfocado a aumentar el fenotipo migrador de las poblaciones de

trucha. La tesis se puede dividir en dos bloques ligeramente diferenciados,

aunque totalmente dependientes entre ellos.

El primer bloque se centra en aspectos puramente ecológicos que ocurren

durante las primeras etapas de desarrollo de los individuos, tanto en el río

como en el mar. También se evalúan otros factores importantes como la

competencia denso-dependiente y su relación con la cantidad de individuos

presentes en el río o dispuestos a migrar. Ambos aspectos se estudiaron

utilizando técnicas de análisis de escamas. Paralelamente a los estudios

citados anteriormente, se desarrolló una nueva técnica para el análisis de las

escamas basado en el crecimiento reflejado en cada anillo depositado (Elliott y

Chambers 1996) y el análisis mediante modelos lineales de efectos mixtos

(Zuur y col. 2009). Con esta técnica analítica es posible diferenciar individuos

potencialmente migradores en las primeras etapas de agua dulce. Este método

se utilizó también para observar la variación en el crecimiento individual de los

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juveniles dependiendo de la cantidad de individuos adultos capturados antes

de la reproducción.

I. RELACIÓN ENTRE LA FASE DE AGUA DULCE Y AGUA MARINA

El crecimiento en etapas tempranas es, en muchas especies, un buen

indicador del crecimiento en etapas posteriores, ya que los juveniles con

tamaño superior a la media pueden tener ventajas competitivas (Mangel y

Stamps 2001). No obstante, en especies migradoras la relación entre el

crecimiento juvenil y adulto está poco claro. Varios estudios de campo revelan

diferentes presiones de selección para la talla en salmónidos anádromos en

diferentes ambientes (i.e. agua dulce y marina: Jonsson y col. 1991;

Scarnecchia y col. 1989). Estos datos sugieren la existencia de mecanismos de

compensación de crecimiento entre el río y el mar. Además, la relación entre la

talla de migración y la talla en la primera etapa marina (post-esguín) tampoco

está clara. Debido a que la selección actúa intensamente sobre la talla de los

salmónidos (Garcia de Leaniz y col. 2007) en el Reprint I: “And the last shall

be first: heterochrony and compensatory marine growth in sea trout

(Salmo trutta)” se explora el coeficiente de variación del tamaño corporal con

objeto de cuantificar la variación fenotípica (Agrawal 2001) a través del estudio

en diferentes fases vitales de individuos anádromos de seis poblaciones

diferentes (Einum y col. 2002; Jonsson y Jonsson 2007). Específicamente, la

hipótesis de partida es que el coeficiente de variación en el tamaño corporal

difiere entre el río y el mar, reflejando compensaciones en el tamaño a lo largo

de la ontogenia.

II. METODOLOGIA BASADA EN EL ANÁLISIS DE ESCAMAS

El crecimiento es usado comúnmente como un indicador de la fitness, pero es

sólo valido si la variación de este crecimiento se representa en relación con sus

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congéneres. Desafortunadamente, en condiciones naturales, evaluar la

variación de las tasas de crecimiento resulta problemático debido a que los

individuos tienen que ser marcados y a que la obtención de varias medidas de

un mismo individuo a lo largo del tiempo es difícil, ya que las recapturas de

individuos suelen ser muy limitadas. Por ello, en el Reprint II: “Mixed-effects

modelling of scale growth profiles predicts the occurrence of early and

late fish migrants” se utiliza un método basado en el análisis del espacio

entre anillos de crecimiento consecutivos de la escama (circuli) para reconstruir

perfiles individuales de crecimiento. Además, se utiliza un análisis estadístico

basado en las diferencias en la intersección y las pendientes con el objetivo de

aumentar la potencia, la exactitud y precisión de los resultados (van de Pol

2012). El método descrito se utilizó para predecir la migración temprana o

tardía de los individuos de dos poblaciones distintas en función del crecimiento

registrado durante la primera fase del crecimiento de agua dulce. Además,

también se comparó el modelo lineal de efectos mixtos utilizado para el análisis

de escamas con un modelado clásico como el de Von Bertalanffy (1938).

III. RELACIONES ENTRE LA ABUNDANCIA DE REOS Y LA COMPETENCIA. ANÁLISIS TEMPORAL DE LAS POBLACIONES.

Entender las fluctuaciones temporales en el crecimiento, así como el número

de individuos que forman parte de una población es desde hace mucho tiempo

un desafío clave en ecología de poblaciones (Krebs 2009). La denso-

dependencia es quizás uno de los reguladores endógenos clave en muchas

especies (Brook y Bradshaw 2006) y por el cual el crecimiento es controlado en

función de los recursos existentes y la cantidad de individuos que se

aprovechan de ellos. La consideración de la regulación denso-dependiente es

importante para la gestión de poblaciones explotadas como las poblaciones de

truchas, ya que la mortalidad asociada a la pesca puede tener importantes

efectos en la densidad (Minto y col. 2008). Los sistemas de agua dulce son

típicamente más limitados en recursos que los marinos (Ross 1986) y por tanto,

se considera que el crecimiento denso-dependiente en ríos está causado por la

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competencia en la obtención de alimento más que por la competencia por

interferencia del espacio (Grant e Imre 2005). A pesar de ello, ambos

mecanismos de competencia pueden operar y resultar en idénticas relaciones

denso-dependientes (Ward y col. 2007). Por el contrario, en el mar el efecto de

la densidad en salmónidos se considera que está mediada exclusivamente por

la competencia de alimento (Peterman 1984) ya que se asume que es muy

difícil para los individuos monopolizar el espacio o defender los recursos en el

mar (Snover y col. 2005). En el Reprint III: “Can migrants escape from

density-dependence?” (en revisión en Ecology and Evolution) se comprobó

que la variación del crecimiento en agua dulce de los reos muestra cambios

dependiendo de la abundancia anual de truchas debido al aumento de la

competencia. Contrariamente a lo esperado, la variación del crecimiento en el

mar también registró cambios dependientes de la abundancia de juveniles que

migran al mar, sugiriendo que las truchas migradoras no pueden ‘escapar’

completamente al efecto de la competencia.

El segundo bloque de esta tesis doctoral se centra en los aspectos genéticos

del fenotipo anádromo de la trucha.

IV. DIRECTRICES PARA LA PLANIFICACIÓN DE UN PROGRAMA DE REPOBLACIÓN DE REO

La trucha común está a menudo sujeta a programas de repoblación debido a la

pesca recreativa a la que se ven sometidas ciertas poblaciones (Juanes y col.

2011). Por esta razón, es común utilizar truchas criadas en cautividad para

aumentar las poblaciones en los ríos o lagos (Jonsson y Jonsson 2011).

Numerosos autores han establecido pros y contras de esta práctica (Fleming y

col. 1997; Jonsson y col. 2003) y los resultados parecen estar íntimamente

ligados con el stock parental utilizado en los programas de repoblación, ya que

el éxito de la progenie se reduce cuando se utilizan truchas domesticadas

(Morán y col. 1991; Martínez y col. 1993; Dahl y col. 2006). Por otra parte, el

18!!


ambiente de la piscifactoría normalmente favorece rasgos completamente

diferentes de los que la selección natural favorece en la vida salvaje (Rogell y

col. 2012). Uno de los rasgos más afectados por la piscifactoría es el

componente de la anadromía (Serrano y col. 2009).

En el Reprint IV: “Insights for planning an effective stocking program in

anadromous brown trout (Salmo trutta)” se proponen las bases para el

desarrollo de un programa enfocado a la repoblación de poblaciones

anádromas basado en la selección de los reproductores, el uso de diferentes

edades de repoblación y su relación con la tasa de retorno tras la migración

marina y el coste económico.

Las herramientas usadas para el estudio genético de estos stocks han variado

desde técnicas de paternidad mediante el uso de microsatélites hasta el

estudio del MHC clase II gen-β (de las siglas en inglés, Major Histocompatibility

Complex) o la metilación de tejidos. Además se relacionaron los resultados con

efectos maternos como el tamaño o número de huevos y con efectos paternos

como el fenotipo paterno.

Este experimento en el medio natural ha servido de base para la comparación

de las tasas de retorno de individuos repoblados pertenecientes a los mismos

cruces y criados en cautividad. Con estas comparaciones se han podido

vislumbrar ciertos patrones necesarios para la realización de protocolos que

sirvan para aumentar la abundancia de este fenotipo migrador. A su vez, sirvió

para comprobar que la de mayoría de los cruces se obtuvieron individuos

anádromos y a su vez individuos residentes, lo que sirvió como comienzo de la

búsqueda de nuevos aspectos genéticos en el estudio de la anadromía.

19!!


V. METILACIÓN Y ADAPTACIÓN AL AGUA DE MAR

En condiciones naturales, los dos fenotipos de trucha se diferencian

claramente durante el segundo año de sus vidas debido a la habilidad de

algunos juveniles para llevar a cabo el esguinado (Økland y col. 1993). Este

proceso implica importantes adaptaciones fisiológicas y morfológicas al agua

marina, preparando así al individuo a la vida en mar abierto antes de haber

migrado. Los cambios en la morfología externa incluyen cambios en la forma

del cuerpo y en los patrones de coloración (Björnsson y col. 2011). Los

cambios fisiológicos están principalmente relacionados con el incremento de la

tolerancia al agua salada y cambios en sus tasas de crecimiento metabólico.

Además, el incremento de la tolerancia al agua marina requiere la

diferenciación y la activación del transporte epitelial, así como de la síntesis de

nuevas proteínas de transporte (McCormick 2001).

Como consecuencia de la necesidad de nuevas técnicas genéticas para el

estudio de la anadromía, la epigenética (i.e. metilación de los tejidos) puede

ayudar a entender el proceso de esguinado en la trucha. El esguinado es un

proceso reversible que puede ser estimulado por factores externos, ya que

individuos genotípicamente iguales pueden mostrar diferentes fenotipos. En el

Reprint IV: “Environmental induced methylation changes associated with

seawater adaptation in brown trout” se investigó si los cambios en la

metilación global del ADN pueden estar relacionados con la anadromía y si el

nivel de metilación puede cambiar en respuesta al estrés osmótico inducido por

estímulos externos como dietas ricas en sal. Entender los efectos de los

estímulos externos va a permitir un mejor manejo de los peces, y a su vez se

podrían incrementar las tasas de esguinado según la necesidad.

20!!


Cada uno de los reprints en los que se divide esta tesis doctoral sirve para

avanzar en el conocimiento de la biología de la trucha migradora. El reo,

supone en Galicia un gran recurso natural y económico. Esta tesis aborda su

estudio desde un punto de vista multidisciplinar, donde aspectos metodológicos

variados y novedosos sirven para conocer aspectos genéticos y ecológicos de

esta especie.

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DISCUSIÓN

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DISCUSIÓN

Introducción y antecedentes

A continuación se discuten, de manera conjunta, los resultados obtenidos en la

presente tesis doctoral para dotar de coherencia y unidad el conjunto de los

trabajos presentados.

La migración de la trucha común se atribuye a la ventaja adquirida por los

individuos migradores sobre los congéneres que han permanecido en el río,

como por ejemplo una mayor fecundidad (Jonsson y Jonsson 1993), selección

de pareja (Revisado en Esteve 2005) o un aumento de la fitness de la progenie

debida a efectos maternos (Crespi y Teo 2002). No obstante, estos

mecanismos son poco conocidos. Numerosos estudios sugieren que la

migración en la trucha es el resultado de la interacción entre genética y

ambiente de modo que cuando se alcanza un determinado umbral el individuo

va a migrar (Ferguson 2006). Sin embargo, la cuantificación de ese umbral es

complicada y la gran mayoría de los trabajos se han centrado en aspectos

diferentes e independientes entre sí y que pueden ser agrupados y clasificados

según la propuesta de Rounsefell (1958) que descompone la anadromía en

seis partes:

(1) La distancia recorrida durante la migración marina, analizada comúnmente

mediante métodos de marcado-recaptura (Caballero y col. 2006).

(2) La duración de la estancia en el mar, que es muy variada en los reos,

pudiendo ir desde unos pocos meses hasta cuatro años antes de volver al río a

desovar por primera vez (Elliott 1994).

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(3) El estado de maduración y desarrollo alcanzado en el mar, que varía

dependiendo del tiempo que el individuo pasa en el agua marina. En hembras

reproductoras se traduce en una gran variabilidad en el tamaño y cantidad de

huevos (Jonsson y Jonsson 1999; Mousseau y Fox 1998).

(4) Los hábitos de desove y hábitats de los reos, que están íntimamente

ligados a la estrategia elegida por los individuos. Así, los reos que vuelven a

desovar al río tienen ventajas a la hora de elegir los sitios de desove debido a

su mayor tamaño. Por el contrario, pierden fitness, a medida que se desplacen

aguas arriba, cuando se comparan con los individuos residentes, ya que el

gasto energético es muy superior (Bohlin y col. 2001).

(5) La mortalidad tras el desove, es decir el porcentaje de iteroparidad (Crespi y

Teo 2002; Caballero y col. 2006).

(6) La aparición de formas residentes de la especie, donde la trucha puede

completar su ciclo sin tener que migar al mar. Esta forma residente se

desarrolló a partir de un ancestro anádromo que se refugió de la última

glaciación (Ferguson 2006) y evolucionó en los casos donde las poblaciones

perdieron su salida al mar. De la misma manera, las poblaciones actuales

residentes a las que, por mejoras de hábitat, se les proporciona una salida al

mar pueden tener la capacidad de desarrollar formas anádromas (Kallio-

Nyberg 2010).

Todos estos componentes de la anadromía deben unirse a otro rasgo propio

del género Salmo que está íntimamente ligado con su ciclo de vida, el homing

(i.e. retorno a desovar al río de origen; Stabell 1984; Jonsson y Jonsson 2012).

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Finalmente, hay que añadir el papel que tienen en la migración las diferencias

genéticas entre individuos. Una gran parte de los trabajos enfocados a la

búsqueda de diferencias genéticas entre individuos migradores y residentes de

una misma población concluyen que no hay diferenciación genética ente

individuos de ambos fenotipos (Cross y col. 1992; Pettersson y col. 2001), y

que la reproducción entre ambos fenotipos es habitual (Skaala y Naevdal

1989). Por otra parte, también se analizaron poblaciones separadas por

obstáculos naturales (Pettersson y col. 2001) y no se encontraron diferencias

genéticas entre truchas residentes y anádromas que conviven simpátricamente

por debajo del obstáculo. Además, los análisis de asignación, no demostraron

que truchas residentes fueran inmigrantes de la población establecida aguas

arriba del obstáculo, con lo que se descartó que los individuos hubieran

emigrado aguas abajo.

Un aspecto ecológico no relacionado directamente con el proceso de

anadromía y tratado en la presente tesis doctoral es el crecimiento y la

supervivencia denso-dependiente (Lobón-Cerviá 2007). Este sistema

endógeno de regulación adquiere una notable importancia en las poblaciones

parcialmente migradoras por diversas razones.

(1) El estado energético del individuo esta relacionado con la migración

(Forseth y col. 1999) e íntimamente ligado con el reparto de recursos en la

población.

(2) La variabilidad anual en el crecimiento de los juveniles es grande e influye

en la decisión de la táctica vital (Cucherousset y col. 2005).

(3) Los ambientes donde crecen los juveniles están relacionados con la táctica

vital (Morinville y Rasmussen 2006).

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El estado energético de los individuos supone que la asignación proporcional

de energía entre individuos migradores es menor que la asignación entre los

que permanecen en el río más tiempo. Esa reducción en la proporción de

energía entre el primer y el segundo año es mayor en los individuos anádromos

(Forseth y col. 1999) y es una explicación de por qué la mayoría de los

individuos migran con dos años. Por tanto, los individuos que crezcan más

rápido tenderán a cambiar su nicho antes que aquellos que lo hacen más

despacio. La tasa de crecimiento, dependiente entre otras cosas de las

relaciones de densidad que existe en la población, marca la tendencia en la

dispersión y migración de los juveniles (Kaspersson y Hojesjo 2009). Por otra

parte, es de gran importancia determinar cómo cambian esas relaciones en el

tiempo para poder gestionar mejor las poblaciones. Por ejemplo, la

competencia entre cohortes y el tipo de ambiente donde se desarrollan los

individuos influye en el cambio de las relaciones entre los individuos de una

población (Cucherousset y col. 2005), lo que sugiere que las variaciones en el

ambiente a pequeño nivel pueden determinar, a causa de la relación que existe

entre costes metabólicos y estrategia, la táctica del individuo (Morinville y

Rasmussen 2006).

Técnicas desarrolladas y utilizadas en la presente tesis doctoral

Durante el transcurso de esta tesis doctoral se han desarrollado y aplicado

nuevas técnicas para el estudio de la anadromía en las poblaciones de trucha.

La metodología utilizada tiene el objetivo de mejorar la gestión de las

poblaciones para favorecer el fenotipo migrador de la trucha. A continuación se

detallan estas técnicas y se señalan las mejoras respecto a trabajos anteriores

o bien su aplicación novedosa al campo del estudio de la trucha común.

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TÉCNICAS GENÉTICAS EMPLEADAS

Análisis de paternidad. Esta herramienta se emplea de forma habitual en

numerosos estudios de genética poblacional de trucha con diferentes objetivos.

Por ejemplo, para documentar el sistema de apareamiento en el medio natural

mediante el estudio de los potenciales reproductores de una población y la

descendencia con el objetivo de determinar cómo la proximidad y el tamaño

corporal influyen a la hora del apareamiento (Servezob y col. 2010) o para la

asignación de la progenie a cruces híbridos (Castillo y col. 2010).

El objetivo perseguido con el análisis de la paternidad en esta tesis doctoral ha

estado destinado a la asignación de los individuos capturados a un cruce

determinado, realizado en la piscifactoría. La asignación fue empleada

paralelamente como herramienta para el estudio del crecimiento, supervivencia

y dispersión en condiciones naturales de huevos plantados a lo largo de dos

años, aunque sirvió especialmente para el reconocimiento de adultos de

retorno tras completar su ciclo vital (Reprint IV: “Insights for planning an effective stocking program in anadromous brown trout (Salmo trutta)”).

MHC. Los análisis del MHC (tanto clase I como II) son frecuentes en

salmónidos y en particular en trucha común (Campos y col. 2006; Coughlan y

col. 2006). El MHC clase I está implicado en la elección de la pareja y los

posibles efectos beneficiosos que tiene esta elección sobre la fitness de la

descendencia. Aunque algunos autores sostienen una relación positiva entre la

selección de la pareja y la fitness de la descendencia (Consuegra y Garcia de

Leaniz 2008), distinguir entre los efectos de la elección de pareja y otros

factores de la selección sexual es complicado (Kokko 2001). En salmón

Atlántico, los estudios sugieren que cuanto mayor es la variabilidad en el MHC

clase I de los padres, mayor es la resistencia a parásitos marinos de su

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descendencia (Consuegra y Garcia de Leaniz 2008). Por otra parte, en el

estudio del MHC clase II en poblaciones aisladas de trucha se observaron

variabilidades muy distintas dependiendo de la localidad (Campos y col. 2006),

lo que sugiere que en la gestión de las poblaciones debería incluirse esta

variable.

En consonancia con estos estudios, en el estudio de la tasa de retorno en

función de las familias empleadas y el tipo de repoblación llevado a cabo en el

Reprint IV: “Insights for planning an effective stocking program in

anadromous brown trout (Salmo trutta)”, se cuantificó la variabilidad en el

MHC de los cruces empleados con el objetivo de observar si esta variable está

relacionada con la supervivencia y migración de los descendientes.

Metilación global. La metilación es uno de los principales mecanismos

epigenéticos de regulación génica que existen junto con la modificación de

histonas y el ARN no codificante. La metilación consiste en la adición de un

grupo metilo a la citosina, situadas en las islas CpG. Esto está relacionado con

el silenciamiento de genes (De Smet y col. 1999; Jones y Takai 2001). Existen

evidencias que demuestran la importancia de factores epigenéticos en la

modulación de la plasticidad fenotípica (Johnson y Tricker 2010). Por tanto, el

estudio del grado de metilación global durante el proceso del esguinado

supone una novedosa técnica aplicada al estudio de la anadromía en especies

parcialmente migradoras como la trucha. Con el objetivo de cuantificar las

diferencias en metilación global, y si éstas pueden ser modificadas por

estímulos ambientales, en el Reprint V: “Environmental induced

methylation changes associated with seawater adaptation in brown trout”,

se utilizó la técnica de MSAP (de las siglas en inglés methylation-sensitive

amplified polymorphism; Reyna-Lopez y col. 1997) para cuantificar los cambios

de metilación global en branquias de trucha alimentadas con dietas

enriquecidas en sal (Perry y Rivero-López 2012). Estas dietas, fáciles de

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preparar, podrían tener gran efecto en las políticas de gestión de poblaciones

migradoras.

TÉCNICAS ECOLÓGICAS Y ESTADÍSTICAS EMPLEADAS

Técnicas de análisis de escama. Las escamas son pequeñas placas rígidas

que crecen en la piel de muchos animales. En concreto, las escamas de las

truchas son cicloideas y contienen una serie de anillos que se van acumulando

a medida que el individuo crece. Con ello, es posible estudiar el crecimiento de

un individuo desde la fecha de nacimiento hasta su captura sin que el animal

sufra daños (i.e. como en el estudio de los otolitos). Otra de las características

que hacen a las escamas muy útiles para el estudio del crecimiento en

salmónidos es que se puede establecer su edad, ya que los crecimientos de la

escama en invierno son fácilmente diferenciables (Elliott and Chambers 1996).

Por tanto es posible identificar la edad total del individuo. Finalmente, también

es posible identificar de manera sencilla la fase de agua dulce de la marina y

cuándo se produce la transición entre ambos medios.

El estudio de escamas es común en muchas especies, incluso existen

protocolos descritos por la FAO para su análisis (Bilton 1975; Gayanilo y col.

2005). La mayoría de los métodos de estudio se basan en (1) el cálculo de la

edad (o punto especifico, i.e. esguinado) a partir de la escama y (2) el

retrocálculo del tamaño de la escama (revisado en Francis 1990) para obtener

una medida de longitud del individuo durante cada año de su vida en función

de lo que mide la escama en dicho punto (Morita y Fukuwaka 2006; Gagne y

Rodriguez 2008; Kuparinen y col. 2009). Esta técnica es ampliamente utilizada

en pesquerías para la obtención de curvas de crecimiento como la de Von

Bertalanffy (1938).

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Friedland y Haas (1996) sustituyeron el uso de tamaños de la escama a una

edad específica por el uso de los anillos de la escama, en concreto eso del

espacio existente entre dos anillos consecutivos. Estos anillos de crecimiento,

que se sitúan entre los puntos para determinar la edad, habían sido

desechados anteriormente para el estudio del crecimiento. Aún así, estos

autores, al igual que se ha hecho en el análisis de crecimiento basado en el

tamaño a diferentes edades, usaron un método de análisis enfocado en el

análisis de las medias de varios individuos.

La técnica desarrollada en la presente tesis doctoral para el análisis de las

escamas se basa en el espacio de crecimiento entre anillos consecutivos junto

con un modelado de efectos lineales mixtos (Zuur y col. 2009) en sustitución al

análisis de medias. Además se corrigieron aspectos técnicos como la

correlación de los errores. Este tipo de análisis, explicado en el Reprint II:

“Mixed-effects modelling of scale growth profiles predicts the occurrence

of early and late fish migrants”, se utilizó en el estudio de una serie temporal

de 13 años en la cual se analizaron escamas de truchas de dos ríos con el

objetivo de evaluar cómo la abundancia de juveniles en el agua dulce y de

esguines en el mar afecta al crecimiento (Reprint III: “Can migrants escape

from density-dependence?”). Las técnicas de modelado con efectos mixtos

proporcionan al estudio una potencia, precisión y exactitud mayor que los

análisis de medias (van de Pol 2012), ya que está basado en mediciones

múltiples de un mismo individuo y su variación en las intersecciones y

pendientes de crecimiento.

APORTACIONES DE LA PRESENTE TESIS DOCTORAL

Las aportaciones de la presente tesis doctoral se pueden dividir en cuatro

bloques diferentes, y todas ellas enfocadas a la gestión de las poblaciones.

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(1) Estudio del crecimiento en agua dulce y agua salada mediante el uso

de escamas. La gestión adecuada de un recurso como el reo pasa por

conocer con exactitud cómo es el desarrollo de los individuos en los dos

ambientes donde crecen y cuál es la relación entre ellos. Además, la gestión

óptima de las poblaciones puede ser diferente debido a las adaptaciones

locales de los salmónidos (revisado en Fraser y col. 2011) y sus diferencias a lo

largo de la ontogenia (Parra y col. 2011). En la presente tesis doctoral se

aportan las diferencias registradas en varias poblaciones de reo en relación

con el desarrollo en las distintas fases del ciclo vital y en relación al crecimiento

agua dulce-agua salada. La importancia del ambiente marino aparece como un

factor determinante en el desarrollo de los adultos, ya que va a permitir a

aquellos individuos mas desfavorecidos en el río (i.e. menores tallas), alcanzar

e incluso sobrepasar a los más favorecidos. Además, también se proporcionan

las diferencias existentes en la talla y edad de esguinado y las edades de

retorno al río con el objeto de complementar la información recogida mediante

pesca eléctrica en el río.

El conocimiento de las relaciones entre agua dulce y marina en distintas

poblaciones es necesario para su gestión. Estas diferencias se pueden

registrar anualmente, entre distintas cuencas. A su vez, si existe un registro de

años anteriores, se pueden observar tendencias y desequilibrios en las

poblaciones con objeto de poder actuar sobre el ambiente o sobre cierta parte

del ciclo vital donde se registra el problema (i.e. disminución de la talla de

esguinado, bajo crecimiento marino, reducción de la edad de maduración,

desequilibrio en la compensación de talla en el mar). En conjunto, la mejora de

la gestión puede ser notable mediante una observación constante de todos los

parámetros descritos.

(2) El desarrollo de una nueva metodología como herramienta para el

análisis de escamas. El estudio de las escamas supone en la gestión de las

poblaciones una importante fuente de información fácilmente aprovechable

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(Bilton 1975). En los ríos existen estaciones de captura que proporcionan,

información de los reproductores que remontan el río para el desove (Saura y

col. 2006; Caballero 2002). Es ahí donde se pueden recoger y almacenar las

escamas sin que los individuos sufran daño alguno. Con la recogida de datos

tales como peso, longitud y sexo, más la información presente en las escamas,

es posible obtener gran cantidad de datos que pueden aplicarse en la gestión

de poblaciones, tanto en el río como en el mar. Con el desarrollo de esta

técnica basada en un método estadístico de efectos mixtos y en la información

individual repetida a lo largo de la escama se mejoran los siguientes aspectos

en la gestión:

• La variación individual y la estacionalidad del crecimiento que registra

este nuevo método puede suplir carencias de otros métodos populares

como el de Von Bertalanffy (1938). La variación en los rasgos que

afectan a la fitness (i.e. crecimiento o talla) necesitan ser interpretados

en relación con lo registrado por los congéneres. El gran número de

puntos comparados en cada individuo permite que dichas

comparaciones entre individuos tengan mayor robustez que aquellos

resultados donde sólo se registran dos puntos de cada individuo (como

normalmente ocurre en el marcado-recaptura; van de Pol 2012). Por

tanto, la fiabilidad de los resultados obtenidos aumenta

considerablemente cuando se utilizan las escamas en lugar de

mediciones sobre el tamaño corporal.

• Se implementa la relación entre la competencia y el crecimiento entre

individuos de una misma población. La influencia sobre el crecimiento

del número de juveniles presentes en una cuenca o el número de

esguines que emigran hacia el mar se puede registrar mediante el uso

de las escamas y el método descrito. Es de gran importancia en los

programas de repoblación saber cuál va a ser el impacto del número de

individuos liberados en el río, ya que un número elevado de individuos

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soltados va a provocar, a parte de la interferencia con las poblaciones

salvajes, que el reparto de los recursos se vea perjudicado por el

aumento de la competencia (Lobón-Cerviá 2007). La aportación de esta

tesis doctoral mediante la técnica de escamas señala la importancia de

considerar en conjunto el número de juveniles que existen en el río y su

crecimiento. Típicamente, la denso-dependencia se asocia al

crecimiento en agua dulce (Jenkins y col. 1999; Bohlin y col. 2002;

Lobón-Cerviá 2007). En cambio, mediante el análisis de dos poblaciones

a lo largo de un periodo de 13 años, se observó cómo la densidad de

esguines afecta también al crecimiento marino. Esto aflora la

importancia de tener en cuenta no sólo la diferencia entre ríos en la

conservación de las poblaciones, sino que además hay que empezar a

tener en cuenta la perspectiva costera en su gestión.

(3) Comparación de métodos de repoblación y resultados positivos en el

aumento del fenotipo migrador. Los métodos de repoblación pueden variar

según la estación, meteorología y objetivos de la repoblación. La principal

aportación de esta tesis doctoral ha sido desarrollar un programa de

repoblación óptimo basado en protocolos clásicos de repoblación para

aumentar los individuos migradores de una población.

Este protocolo se basa en factores fácilmente manejables por los órganos de

gestión y con la consideración de aspectos económicos con el fin de reducir al

máximo los costes de la repoblación.

El método está basado en el estudio de dos rasgos observables en la

piscifactoría: el tamaño de los huevos de la hembra (Einum y Fleming 2002) y

el fenotipo del padre usado en el cruce (Skrochowska 1969). Además, en el

laboratorio se realizó un análisis genético de los reproductores para observar el

grado de similitud entre los alelos del MHC clase II (Campos y col. 2007).

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Por otro lado se compararon distintos métodos de repoblación: la plantación de

huevos y la repoblación de individuos de un año para maximizar la producción

de esguines (Jokikokko y Jutila 2004). Tras realizar las medidas

correspondientes en la piscifactoría del tamaño de los huevos, se identificó el

fenotipo paterno y se midió la variabilidad genética de los padres en el MHC.

Tras ello, se esperó a que los individuos completaran su ciclo vital en ambos

tipos de repoblación (i.e. plantado de huevos y suelta tras un año en la

piscifactoría).

La tasa de retorno entre los años 2010 y 2011 supuso casi un 10% del total de

la población de reos que retornaron a desovar. Además, esta tasa de retorno

se consiguió usando sólo una pequeña sección de un afluente del río principal.

Es importante indicar que los volúmenes tanto de huevos como de individuos

repoblados fueron sensiblemente inferiores a los que normalmente se utilizan

en programas de repoblación de salmón Atlántico. Con estos resultados se

abre un proceso para adoptar nuevos protocolos de repoblación

(4) Implementación de nuevas técnicas genéticas para la mejora frente al

estrés osmótico en individuos de repoblación. Uno de los problemas de las

repoblaciones, a parte de las interacciones con las poblaciones salvajes

(revisado en Naish y col. 2008), es la pérdida de los rasgos propios de las

poblaciones salvajes para completar el ciclo vital (Rogell y col. 2012). La

pérdida de la anadromía es una de las características que más afectan en la

conservación de las poblaciones parcialmente migradoras, ya que el uso de

individuos domesticados puede reducir el número de individuos migradores

(Serrano y col. 2009).

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En la presente tesis doctoral se aportan soluciones para la cría de truchas en

cautividad basadas en estudios de la interacción ente metilación y factores

ambientales. Concretamente, se han identificado y cuantificado los cambios de

metilación global en branquias provocados por una dieta rica en sal. Con los

resultados obtenidos es posible establecer un protocolo de alimentación

óptimo, para minimizar el estrés osmótico que se produce al inicio de la

migración.

Perspectivas futuras

La investigación relacionada con salmónidos anádromos necesita continuas

mejoras para la conservación de las especies. Debido a la explotación tanto del

recurso como del ambiente en el que se desarrollan, las dificultades de las

poblaciones salvajes se mantienen o incluso empeoran con el paso del tiempo.

Una de las principales herramientas que se deberían desarrollar en el campo

de la conservación está relacionada con la combinación entre las mejoras de

hábitat (Griffiths y col. 2011), la explotación sostenible del recurso (EIFAC

2008) y los programas de repoblación. Para tener una visión de la situación de

los últimos años en esta materia se puede tomar como ejemplo la región de la

provincia de Pontevedra:

• Cada año en función de la situación del recurso, hay regulaciones en

materia de pesca donde se limita el número de individuos que se

pueden capturar independientemente de las licencias expedidas (Xunta

de Galicia 2013).

• Los programas de repoblación realizados en ambas especies

contribuyen a la recuperación de numerosos ríos tras su práctica

extinción (Saura y col. 2006).

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No obstante, en los los últimos diez años se han registrado numerosas

catástrofes indirectamente relacionadas con la destrucción del hábitat:

• Vertidos devastadores que afectaron tramos enteros de río (Umia en

2006, Lagares en 2007).

• Obras públicas que colmataron el lecho impidiendo la supervivencia de

peces (Barxa en 2009, Cabanelas en 2009).

En estos casos, los programas de repoblación junto con políticas de mejora de

hábitat pueden mitigar los efectos negativos. Por ello, es trascendente para la

conservación de las especies anádromas desarrollar un programa de

conservación que sea efectivo, fácil de realizar (a nivel de piscifactoría y en

medio natural) y económicamente viable.

El programa de repoblación mostrado en la presente tesis doctoral cumple,

inicialmente, los tres requisitos, aunque existe un gran margen de mejora en la

efectividad. Por ello:

(1) Se hace necesario la continua mejora de las estrategias de repoblación, en

especial las poblaciones de reo, ya que, al formar parte de una especie

parcialmente migradora, es necesario maximizar la proporción de individuos

anádromos. Debido a la existencia de numerosas estaciones de captura, sería

posible analizar si los métodos propuestos pueden ser utilizados

independientemente de la cuenca donde se llevan a cabo.

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(2) Es necesario comparar el método descrito en el Reprint IV con el método

de repoblación basado en individuos criados en la piscifactoría mediante

métodos de mejora frente al estrés osmótico Reprint V. Este último puede ser

más costoso pero a su vez puede proporcionar resultados más rápidos debido

al uso de individuos criados en piscifactoría en vez de plantados en el medio

natural como huevos. Su uso para zonas de urgente recuperación podría ser

más adecuado.

(3) El estudio del estrés osmótico demostró una supervivencia superior de los

individuos alimentados con dietas enriquecidas en sal al ser trasvasados a

agua salada. Esta mejora en la adaptación debe ser explorada en un futuro con

el objetivo de investigar qué genes en particular se activan o desactivan por

agentes externos, lo que permitiría criar truchas en condiciones óptimas que

faciliten la supervivencia durante los cambios de salinidad. Esto puede influir en

las estrategias de repoblación, ya que se podrían sustituir las repoblaciones en

río por las repoblaciones en aguas salobres o incluso en agua oceánica.

(4) Adaptar las repoblaciones, tanto en forma de huevo, como juvenil a las

densidades que existen de juveniles en el río como a la densidad de esguines

que emigran al mar. Las poblaciones de reo parecen ser sensibles a la denso-

dependencia tanto en el río como en el estuario y por tanto, ese factor debe ser

considerado en los planes de repoblación. Un excesivo número de individuos

en las sueltas pueden llegar a producir una reducción en el crecimiento de los

individuos, tanto en poblaciones salvajes, repobladas como en ambos

ambientes. Por tanto, los mecanismos de adaptación relacionados con el

tamaño (esguinado, estado de maduración, etc.) pueden estar negativamente

afectados por el exceso de individuos sobre la capacidad de carga. El número

óptimo de individuos debe ponderarse mediante estudios específicos en cada

río y es necesario tener estimas tanto del número de individuos presentes en el

río (juveniles de un año específicamente) como del número de esguines.

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Considerar los mecanismos de adaptación a la osmorregulación y los

mecanismos de denso-dependencia pueden mejorar los planes de repoblación.

Junto con los análisis de los reproductores en la piscifactoría y una mejora de

la gestión del hábitat sería posible que la conservación de la especie estuviera

más cerca de un diseño óptimo.

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57!!


CONCLUSIONES

58!!


CONCLUSIONES

1. La compensación marina en el crecimiento de los esguines de menor

tamaño permite recuperar una talla óptima y por tanto eliminar la desventaja

inicial adquirida en agua dulce.

2. El estudio retrospectivo sobre el crecimiento de la trucha migradora en el

río y en el mar indica que los individuos de una misma edad alcanzan tallas

parecidas en el momento del desove pese a haber experimentado diferentes

trayectorias de crecimiento.

3. El nuevo método utilizado para examinar la variación en las trayectorias de

crecimiento de las escamas basado en un modelo lineal de efectos mixtos

permite establecer que las relaciones entre la abundancia de individuos y su

crecimiento son claves en la gestión de los hábitats tanto de agua dulce como

de agua salada.

4. Los experimentos de repoblación realizados indican que la repoblación

durante la fase de huevo es más eficaz para el aumento de la parte anádroma

de la población que la repoblación con individuos de mayor edad. Este método

reduce además sensiblemente el coste de las repoblaciones.

5. En la selección de reproductores para la reproducción artificial los aspectos

más importantes que deben considerarse son el fenotipo paterno y la

diversidad del MHC. La elección de hembras anádromas y machos anádromos

(siempre que sea posible) aumentan las posibilidades de migración de la

descendencia.

59!!


6. Los experimentos realizados en piscifactoría indican que la dieta puede

regular, mediante mecanismos epigenéticos, la expresión de genes. La

alimentación con dietas ricas en sal mejora significativamente la supervivencia

de las truchas en agua de mar.

60!!


REPRINTS DE LAS PUBLICACIONES

61!!


And the last shall be first: heterochrony and compensatory

marine growth in sea trout (Salmo trutta)

And the Last Shall Be First: Heterochrony andCompensatory Marine Growth in Sea Trout (Salmo trutta)Francisco Marco-Rius1, Pablo Caballero2, Paloma Moran1, Carlos Garcia de Leaniz3*

1 Departamento de Bioquımica, Genetica e Inmunologıa, Universidad de Vigo, Vigo, Spain, 2 Consellerıa de Medio Rural, Servizo de Conservacion da Natureza, Xunta de

Galicia, Pontevedra, Spain, 3 Department of BioSciences, Swansea University, Swansea, United Kingdom

Abstract

Early juvenile growth is a good indicator of growth later in life in many species because larger than average juveniles tendto have a competitive advantage. However, for migratory species the relationship between juvenile and adult growthremains obscure. We used scale analysis to reconstruct growth trajectories of migratory sea trout (Salmo trutta) from sixneighbouring populations, and compared the size individuals attained in freshwater (before migration) with theirsubsequent growth at sea (after migration). We also calculated the coefficient of variation (CV) to examine how much bodysize varied across populations and life stages. Specifically, we tested the hypothesis that the CV on body size would differbetween freshwater and marine environment, perhaps reflecting different trade-offs during ontogeny. Neighbouring seatrout populations differed significantly in time spent at sea and in age-adjusted size of returning adults, but not on size ofseaward migration, which was surprisingly uniform and may be indicative of strong selection pressures. The CV on body sizedecreased significantly over time and was highest during the first 8 months of life (when juvenile mortality is highest) andlowest during the marine phase. Size attained in freshwater was negatively related to growth during the first marinegrowing season, suggesting the existence of compensatory growth, whereby individuals that grow poorly in freshwater areable to catch up later at sea. Analysis of 61 datasets indicates that negative or no associations between pre- and post-migratory growth are common amongst migratory salmonids. We suggest that despite a widespread selective advantage oflarge body size in freshwater, freshwater growth is a poor predictor of final body size amongst migratory fish becauseselection may favour growth heterochrony during transitions to a novel environment, and marine compensatory growthmay negate any initial size advantage acquired in freshwater.

Citation: Marco-Rius F, Caballero P, Moran P, Garcia de Leaniz C (2012) And the Last Shall Be First: Heterochrony and Compensatory Marine Growth in Sea Trout(Salmo trutta). PLoS ONE 7(10): e45528. doi:10.1371/journal.pone.0045528

Editor: Casper Breuker, Oxford Brookes University, United Kingdom

Received April 20, 2012; Accepted August 20, 2012; Published October 1, 2012

Copyright: ! 2012 Marco-Rius et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was funded by grants from Ministerio de Ciencia y Tecnologıa (CGL2007-60572 and CGL2010-14964), and Fondos FEDER(PGIDIT03PXIC30102PN; Grupos de Referencia Competitiva, 2010/80). Francisco Marco-Rius was supported by a pre-doctoral fellowship from the SpanishGovernment (BES-2008-001973). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Many animals pass through some migratory stage during theirlives [1–2], typically in relation to feeding or reproduction.Migrations are thought to maximise age-specific fecundity and theprobability of surviving from one breeding season to the next [3–4], and have been interpreted as a response to adversity [5].

Migrations are energetically costly and a trade off may beexpected to exist between the costs of migrations and the fitnessbenefits accrued by a larger body sizes [1], as well as betweenpredator avoidance and feeding gains [6]. Migrants typicallyachieve a larger body size than non-migrants, but may also sustainhigher mortality rates than resident individuals [7–8]. Such trade-offs between growth and mortality are common in many speciesand can reflect a balance between foraging and predation risk,growth and maturation, and growth and resistance to diseases,amongst others [9]. These may result in individuals achievingsimilar fitness, despite having grown at widely different rates [10].

Amongst anadromous salmonids, which must migrate betweenvery different freshwater and marine environments, the risk ofpredation increases at sea [11] and a relatively narrow optimumsize at migration appears to exist [12]. Yet, size at migration (smolt

size) and growth during the first marine season (post smolt growth)are perhaps the traits that differ the most amongst populations[7,13–14], probably because homing behaviour tends to result ingeographical isolation and locally adapted populations [15].Maturation schedules also tend to differ greatly amongstpopulations [16], even among fish inhabiting neighbouring rivers[13,17] suggesting the existence of different and spatially localisedtrade-offs.

Field studies have revealed contrasting selection pressures forbody size of anadromous salmonids in freshwater and marineenvironments [18–21] suggesting the existence of different trade-offs in rivers and sea. Yet, the relationship between pre-migratorygrowth in freshwater (i.e. smolt size) and post-migratory growth inthe sea (i.e. post-smolt growth) is not clear. There appear to be asmany studies reporting a negative relationship between smoltlength and marine growth [16,22–24] as there are studiesreporting a positive or no relationship [25–27]. This suggests thatthere can be considerable variation in the way individuals adapt toenvironmental change during their transition from freshwater tomarine environments.

Here we used scale image analysis to reconstruct individualgrowth trajectories of migratory brown (sea trout, Salmo trutta) in

PLOS ONE | www.plosone.org 1 October 2012 | Volume 7 | Issue 10 | e45528

order to examine the relationship between smolt size and postsmolt growth in six neighbouring populations. As selection can actstrongly on body size and size-related traits in juvenile salmonids[15], we used the coefficient of variation on body size (CV) inorder to quantify the extent of phenotypic variation [28] acrossdifferent life stages. Specifically, we tested the hypothesis that thecoefficient of variation on body size of migratory trout would differbetween the freshwater and marine environment, perhapsreflecting different trade-offs during ontogeny [22–23]. Further-more, because selection in fishes tends to be strongest during theearly juvenile stages - when mortality is highest but when body sizeis also smallest [29–30] - we also expected to find a negativerelationship between developmental stage and the extent ofindividual variation in body size.

Methods

Study PopulationsMigratory sea trout were caught between August and October

2002 on their returning migration by government officials inupstream traps or by angling by licensed sport fishermen in sixneighbouring rivers in NW Spain (Fig. 1). Study populationsdiffered in physical as well as in key demographic parameters,including population abundance (as inferred from rod and linecaches), age and body size, and expected survival (as inferred fromincidence of multiple spawners and maximum longevity; Table 1).Upstream migrants were assumed to have been caught on theirriver of origin as these populations had shown isolation by distanceand restricted gene flow, which are suggestive of strong homingbehaviour [31].

Ethics StatementCollection of scale samples was carried out by fisheries staff of

the Regional Government of Galicia (Wildlife Service) using a non-intrusive procedure and according to current Spanish Regulations.No specific permits were required for the described field studies,and these did not involve endangered or protected species.

Scale Analysis and Growth ProfilesScales of 30 individuals per river were stored dry in paper

envelopes, along with information on their body size (fork length,mm). Between three and five scales with a clear (non–regenerated)nucleus were selected per individual to prevent bias due to loss ofgrowth rings [32]. Acetate impressions were made with the aid ofa pressure roller and the resulting impressions were then scannedwith a Minolta MS 6000 microfilm scanner at 23–506magnifica-tions and saved as high resolution TIFF images as in [33].

The software Image-J v. 1.4.1 [34] was employed to digitize theposition of each growth ring (circuli), to identify the annual growthrings (annuli), and to measure the inter-circuli spacing along the360u scale axis with reference to a calibrated scale bar in order toderive measures of scale growth [35]. The freshwater and marineages were determined based on the number of annuli [36], and thepoints of entry of smolts into the sea (beginning of marine phase)and end of the first marine growing season (post-smolt growth,PSG) were noted [16]. Twenty three finnocks (individuals whichhad returned to freshwater before completing one full winter at sea[37]) were excluded from analysis as these provided no compa-rable data on post-smolt growth.

Individual growth profiles were obtained by plotting circulinumber against scale size at four key life stages: (a) first freshwaterwinter, (b) moment of entry into the sea, (c) end of first marinegrowing season, and (d) return of adults into freshwater from thesea. Ordinary Least Squares (OLS) regression was then used to

determine scale growth slopes, measured between the scale focusand the scale edge [38].

Reliability of Scale AnalysisA paired t-test was used to assess non-random deviations in scale

radii between the original scales and their acetate impressions(n = 30) in order to quantify potential bias in scale measurementsarising from pressure from the hand roller. To ascertain theprecision of the scale analysis, we estimated the repeatability of thepoint of entry into the sea and of the end of the first marinegrowing season by measuring the scales of 30 individuals twice ina double blind fashion and calculating the intra-class correlationcoefficient (a-Cronbach) as per [33]. The Pearson correlationcoefficient was used to evaluate the strength of the associationbetween scale radius and body size of fish in each river. Thecoefficients of variation (CV = SD/mean) were then examined tocompare the precision of body size and scale measurements.Precision in scale measurements (0.01 mm; CV = 13.9%) wasbetter than that of body size measurements (cm; CV = 15.3%), andthe former was therefore preferred to examine growth variationamong migratory trout.

In order to evaluate if the relationship between somatic growthand scale radius changed with age or body size, we tested forhomogeneity of slopes in an ANCOVA model [39] using eitherage (five age classes) or body size (four size quartiles) as covariates.We also checked that the relationship between age and body size(Log10) was linear within the limits of this study (F1,126 = 17.392,P,0,001), and not different among rivers (River F5,126 = 0.323,P = 0.898; River6Age interaction F5,126 = 0.060, P = 0.998).

Statistical AnalysisAnalyses were carried out using SYSTAT 10.0 and the R

software [40]. The R MASS package [41] was used to modelvariation in post smolt growth (PSG) in relation to smolt size, smoltage and river identity, and the Akaike information criteria (AIC)was used for model selection.

We employed the CV to quantify phenotypic variation in bodysize [28] among populations and across four different key lifestages (first freshwater winter, moment of entry into the sea, firstmarine growing season, and return as adult to the river). Onlyindividuals that had spent 2 years in freshwater (S2 smolts) wereused, as this was the dominant smolt age in the study populationsand the number of fish of other smolt ages was low. Approximate95% confidence limits were constructed by bootstrapping 1,000replicates, and the Fligner-Killen test (a non-parametric version ofLevene’s test which is robust to departures of normality [42]) wasused to compare differences in CV among stages of developmentand among rivers.

We visualized growth reaction norms during the freshwater tomarine transition by plotting individual growth trajectoriesbetween the moment of entry into the sea (smolt size) and thegrowth of the first marine growing season (PSG). These trajectoriesdescribed how individuals responded to environmental changeaccording to population of origin and smolt age. Variation inindividual growth trajectories was analysed by repeated measuresANCOVA using river of origin as a fixed factor and smolt age andsea age as covariates. We then calculated the partial correlationcoefficient to test the strength of association between freshwaterand marine growth once the effects of freshwater and sea age hadbeen statistically partialled out. This was achieved by calculatingthe correlation between the residuals of freshwater and marinegrowth after each had been regressed on freshwater and sea age.

Finally, in order to estimate the extent and magnitude ofcompensatory marine growth we computed the size rank of

Compensatory Marine Growth in Sea Trout


individual fish before and after migrating into the sea, andcalculated Spearman rank correlation coefficients (rs) betweenfreshwater and marine growth for each river. In the absence ofcompensatory marine growth, we would expect to find a positivecorrelation between smolt size and postsmolt growth, as largerthan average smolts would continue to be larger than average atsea. On the other hand, if fish exhibited compensatory marinegrowth, we would expect to find no association between smolt sizeand postsmolt growth, as smaller than average fish would be ableto catch-up (and move up the size rank) at sea.

Results

Reliability of Scale MeasurementsThere was no significant distortion of scale radius due to the

impression process (t29 = 0.547, P = 0.465), indicating that acetateimpressions gave an accurate, unbiased representation of scalesize. Repeatabilities of scale size were high, both for smolt scalelength (a-Cronbach = 0.879) and for scale size attained at the endof the first marine growing season (a-Cronbach = 0.918). Scaleradius and fork length were positively correlated (r = +0.654,P = 0.001), and the relationship was not different among rivers

(F5,136 = 1.002, P = 0.419) allowing us to use scale measurements toreconstruct changes in body size regardless of river identity.

Testing of interactions terms in ANCOVA indicated that therelationship between somatic growth and scale radius was notaffected by age or body size (age6scale radius F7,102 = 0.983,P = 0.447; body size6scale radius F14,91 = 1.344, P = 0.197), i.e.slopes were homogeneous across age and size classes.

Variability in Life Histories Among PopulationsSea trout populations differed significantly in sea age

(F5,132 = 5.39, P,0.001), but not on smolt age (F5,132 = 0.55,P = 0.736). Populations did not vary in the size of smolts(F5,126 = 1.87, P = 0.104), once the overriding effect of smolt age(F1,126 = 110.53, P,0.001) had been statistically controlled for, butthere was an interaction between smolt age and river of origin onsmolt size (F1,126 = 110.53, P = 0.029) suggesting that differentpopulations experienced different freshwater growth patternsbefore migrating to sea. Sea trout populations also differed insize of returning adults (F5,126 = 3.20, P = 0.009) once theimportant effect of sea age had been statistically accounted for(F1,126 = 25.51, P,0.001).

Figure 1. Study sea trout (Salmo trutta) populations in Galicia, NW Spain.doi:10.1371/journal.pone.0045528.g001



Individual Variation in Reconstructed Growth ProfilesIndividual variation in reconstructed growth profiles was high

among individuals (Fig. 2; CV = 71.2%) and increased significantlyover time (Fligner-Killen Test, x2 = 59.91 df = 3, P,0.001) as fishfollowed diverging growth trajectories. The CV on body size, asinferred from variation in scale size and calculated for thosereturning adults that had spent two winters in freshwater and onewinter at sea (the dominant age class), varied significantly amonglife stages (Fig. 3;Fligner-Killen test x2 = 55.51, df = 3, P,0.001),being highest during the first 8 months of life (when juvenilemortality is highest) and lowest when adults returned from the sea.Populations differed significantly in CV for body size only duringthe first winter in freshwater (Fligner-Killen test x2 = 14.50, df = 5,P = 0.013), but not at later stages (smolt x2 = 5.33, df = 5,P = 0.376; PSG x2 = 9.036, df = 5, P = 0.107; returning adultsx2 = 1.678, df = 5, P = 0.891).

Compensatory Marine GrowthWe concentrated on modelling post-smolt growth (PSG) during

the first marine growing season, as this was the stage where therewas greatest variation among individuals, and we could obtaindata from all fish regardless of time spent at sea. We used aspredictors the age and size of smolts, as well as the river of origin,to test the prediction that early growth performance duringfreshwater life was a good predictor of growth performance later inlife at sea. Analysis of individual growth reaction norms (Fig. 4)indicated that smolt size at the moment of entry into the sea wasnegatively correlated with subsequent growth during the firstmarine growing season, once the effects of sea age and freshwaterage had been statistically partialled out (partial correlationr = 20.233, df = 134, P = 0.006).

Following stepwise multiple regression, variation in post-smoltgrowth (PSG) was accounted for by river of origin (F5,106 = 11.079,P,0.001), smolt scale length (F1,106 = 7.838, P,0.001) and smoltage (F2,106 = 3.975, P = 0.048), in addition to a significant 3-wayinteraction among river, smolt age and smolt scale length(F7,106 = 2.967, P = 0.007). The minimal adequate model ex-plained about 53% of the variance in PSG (F31,106 = 3.68,P,0.001, AIC = 2474.72) and provided evidence of a negativerelationship between size attained in freshwater and subsequentgrowth at sea.

Compensatory marine growth (revealed by the frequency of fishmoving up the size rank following entry into the sea) wassubstantial and widespread. Thus, all populations exhibitedcompensatory growth, as suggested by non-significant rankcorrelation coefficients between smolt size and post-smolt growth(these ranged from rs = 20.442, P = 0.051 in the R Tambre tors = 0.043, P = 0.846 for the R. Eume). The results also indicatethat between 45% (R. Tambre) and 54% (R. Ulla) of fish displayeda gain in size rank at sea, depending on population of origin.Average change in post-migratory size rank of those fish displayingcompensatory growth ranged from 7.6 positions in the R. Ulla to10.4 positions in the R. Lerez, suggesting that size rank changesare likely to be biologically meaningful.

Discussion

Our study on migratory trout indicates that there is a negativerelationship between the size of juveniles in freshwater prior tomigration and their subsequent growth at sea, once the effects ofage on growth are controlled for. In general, a positive relationshipbetween freshwater and marine growth is expected if marine foodresources are patchily distributed, and dominant individuals canmonopolize resources, as they tend to do in freshwater [43]. In

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01



contrast, when marine resources are evenly distributed, resourcemonopolization is not possible, or the costs of resource defencesimply outweigh its benefits, a negative or no correlation betweenfreshwater and marine growth can be expected [44].

Negative correlations between pre and post-migratory growthhave been reported in many studies of anadromous salmonids andsuggest the existence of trade-offs, whereby traits that promote fastgrowth in one environment do not translate into rapid growth inother environments. Indeed, analysis of 61 datasets representingfour salmonid species (Table 2) indicates that there is no significantassociation between smolt size and marine growth in the majorityof studies (55.7%), and that negative relationships (29.5% of cases)tend to be more likely to occur than positive ones (14.8% of

comparisons), though not statistically so (x2 = 3.0 df = 1,P = 0.083). Our study, like most other studies, suggests thatjuvenile size is a poor predictor of subsequent growth at seabecause individuals that grow slowly in freshwater are able tocompensate with enhanced post-migratory growth later in life.There are various possible reasons for this.

Firstly, it is possible that gender differences (which were notmeasured in our study) may introduce a source of variation in therelationship between pre- and post-migratory body size, forexample if males and females achieve different sizes [45] or areunder different selection pressures [46–47]. However, studieswhere gender has been controlled for [22] failed to find a positiverelationship between freshwater size and marine growth, or found

Figure 2. Individual scale growth profiles of migratory sea trout. Shown are estimated scale sizes (a proxy for body size) at each circulinumber. Dark line represents mean values (95 CI) adjusted for a common smolt age and sea age at four key life stages (first winter in freshwater, entryinto the sea – dotted line, end of first marine growing season, and adult returning to freshwater).doi:10.1371/journal.pone.0045528.g002



an inverse relationship, suggesting that the lack of association isa common phenomenon. Lack of association between pre- andpost-migratory growth may also be due to low statistical power.For example, with our sample size (n = 138) we were able to detecta correlation greater than 0.21 or lower than 20.21 with 80%power, but power to detect weaker associations (and to reject thenull hypothesis of no correlation) may have been too low inprevious studies [48].

Thirdly, random measurement error would tend to blur anyrelationship between freshwater and marine growth. This may beparticularly true if back-calculation of body size (instead of scalegrowth) is used because in situ measurements of fish size may lackprecision in the field [49]. On the other hand, scale size measuredin the laboratory has been shown to be a reliable indicator of smoltsize in salmonids [50], and our study shows that repeatability inscale size was high and that no bias due to the scale impressionprocess could be detected. Therefore, we are confident that ourestimates of scale growth are reliable, and that these allow us toreconstruct changes in growth of migratory trout and to comparegrowth trajectories of individuals.

Using size comparisons to infer rate of growth implicitlyassumes that individuals have grown over the same period of time.This would be true only if all fish had emerged and smolted at thesame time, and grown over the same length of time in the marineenvironment. Otherwise, variation in growth rates may beconfounded by variation in the length of the growing season,and this may mask the detection of size trade-offs. All adults usedin our study were caught in freshwater over a relatively shortperiod of time (August–October), and we excluded from analysisthose fish that had spent less than one full winter at sea to reduceadditional sources of variation. Information on timing of alevinemergence was not available in our study, but development insouthern brown trout populations is rapid and emergence is likelyto be short and less protracted than in more northern latitudes[51–52]. Data from a downstream smolt trap in one of the studyrivers (R. Ulla) indicates that the timing of smolt migration is

highly clumped, with 50% of smolts moving downstream overa relatively narrow time window (average during 1998–2001 was16 days, range = 6–28 days). This suggests that the observedvariation in the size of individuals cannot solely be explained bydifferences in the timing of emergence, timing of smolting, or inlength of the growing season, which are thought to have beensimilar among individuals in our study. Other studies have alsoshown that such differences are small in relation to variation insmolt size and post-smolt growth [22].

Compensatory growth, where individuals that grow poorlyduring periods of nutritional deficit are then able to acceleratetheir growth and ‘‘catch-up’’ when conditions improve [10,53], isthe most plausible explanation for the observed inverse relation-ship between freshwater and marine growth shown in our study.Migration has been viewed as a strategy to ‘‘escape’’ from harshconditions, typically caused by predation and competition fromincreasingly larger conspecifics [54]. Among facultative anadro-mous salmonids, migration is thought to represent a trade-offbetween better growth opportunities at sea, but also greater riskfrom predation [7,55]. Although there is some evidence fordensity-dependence in salmonid marine survival [56], the evidenceis not compelling. In contrast, evidence of density-dependentmarine growth is much more common [57–59], though this ismost readily apparent during the late marine phase, presumablybecause the costs of reduced growth are less likely to have animpact on survival later in life [60]. Often the mean scale radius ofsalmonid migrants is significantly smaller than that of returningadults from the same cohort, suggesting that small migrants sustainhigh mortality at sea [49]. More generally, large individuals oftenhave a survival advantage over small conspecifics, both infreshwater and in the sea [50,61–64] adding some support tothe ‘bigger is better’ hypothesis. However, there are also manycases when no such size advantage is apparent [65], or when size-selective mortality favours a large body size in some years anda small size in others [66–67], perhaps because phenotypicadjustment is the norm in salmonid populations [15,68].

Figure 3. Temporal trends in the coefficient of variation (CV) for scale size (a proxy for body size) of three year old sea trout (2.1.age class) at four key life stages, stratified by population of origin. Shown are mean values and approximate 95% confidence intervalsderived from 1,000 bootstrap replicates.doi:10.1371/journal.pone.0045528.g003



Whatever the precise direction of selection, a recent meta-analysis [69] has shown that fish are subjected to extreme selectionon body size during early life, the strength of which typicallydecreases over time. This is consistent with our results onmigratory trout, which indicate that the CV for body size (asinferred from variation in scale size) varies markedly over the lifetime of individuals, decreasing with time as fish migrated fromfreshwater into the sea. With the exception of the first freshwaterwinter, no differences were found among six neighbouringpopulations, suggesting that once the critical time for survivalhas passed [70–71], selection probably operates in a similar way inneighbouring rivers.

The coefficient of variation (CV) is useful for quantifyingphenotypic variation [28] and for examining ontogenetic sizechanges in longitudinal studies [51]. CV is expected to decreasewhen stabilizing selection acts upon a continuous trait, and can beuseful as a preliminary step towards more detailed selectionanalysis [72]. Individual variation in growth rates decreases withincreasing competition in brown trout [29,46], suggesting thatchanges in the CV could track changes in selection intensity.

During the first stages of their lives, brown trout juveniles tend tobe subjected to strong selection mediated by both density-dependent and density-independent processes [73], the relativestrengths of which may differ markedly from site to site, and alsofrom year to year [70,74–75]. Early density dependent processesare thought to decrease at smolting, when territoriality inmigratory salmonids disappears and the strength of intra-specificcompetition weakens in preparation for the marine migration [55].Osmoregulation amongs smolts is accompanied by tissue differ-entiation of gut, gill and kidney [55,76], and juveniles must reacha minimum threshold smolt size or will not smolt [55]. Smolt size,not age, is the primary determinant of marine survival inanadromous salmonids [76], and strong selection for smolt sizemay therefore be expected to exist. Indeed, our study indicatesthat there was relatively little variation for smolt size in migratorybrown trout, and a significant decrease in CV from the firstfreshwater winter onwards. Individual variation in salmonids bodysize has been shown to decrease after periods of intense selection,for example following size-selective predation [77–78] or poorfeeding conditions at sea [61].

Figure 4. Individual growth reaction norms during the freshwater to marine transition in six sea trout populations, stratified bysmolt age (# 1 yr, n 2 yr. +3 yr). Shown are matched comparisons between scale size at the moment of entry into the sea and subsequent scalegrowth increment during the first marine growing season (PSG) for each individual fish.doi:10.1371/journal.pone.0045528.g004



Some authors have found that variation in smolt size and agedecrease with increasing stream size (e.g. [79]), apparently becausethe success of large juveniles is more variable and less predictablein small than in large streams [46]. However, no such relationshipwas apparent in our study populations, which displayed the samenarrow variation in smolt size in spite of relatively large differencesin stream size and in demographic parameters (Table 1), againsuggesting that smolt size is probably under strong selection.

In summary, our study indicates that there is an inverserelationship between pre- and post-migratory size in migratorytrout, which we interpret as indicative of marine compensatorygrowth. The CV on body size was highest during the firstfreshwater winter and decreased during the marine phase, and thisappears to track changes in juvenile mortality. In addition toheritable variation, phenotypic plasticity and genotype6environ-ment interactions, ontogenetic variation due to changes in thetiming or rate of developmental events (growth heterochrony [80])can be an important source of body size variation [81–82]. This isparticularly true in fishes, which have indeterminate growth, andwhere even small changes in heterochrony can result in largemorphological differences among individuals [83–84]). Geneduplication may have also allowed large phenotypic diversificationamongst the teleosts [85], as it provides ‘‘extra genetic materialfreed from the need to function in only one way, and thereforeavailable for experimental [evolutionary] change’’ [81].

We suggest that despite a widespread selective advantage oflarge body size in freshwater, freshwater growth is a poor predictor

of final body size amongst migratory fish because selection mayfavour growth heterochrony leading to marine compensatorygrowth. Marine compensatory growth allows size-depressedindividuals to catch-up later in life and may, therefore, negateany initial size advantage acquired in freshwater. Such a mecha-nism could be responsible for the heterogeneity in growthtrajectories observed in our study, a pattern not readily detectedin captivity [86], where food is generally plentiful and naturalselection relaxed. Ultimately, growth heterochrony could helpmaintain phenotypic variation in sea trout because anadromousindividuals could attain similar sizes at spawning (and hence havesimilar fecundities) despite having experienced very differentgrowth trajectories early in life.

Acknowledgments

We wish to thank Pilar Alvarino and Diego Figueroa for technicalassistance and Sonia Consuegra and four anonymous referees for usefulcomments on previous versions of this manuscript.

Author Contributions

Conceived and designed the experiments: FMR PC PM CGL. Performedthe experiments: FMR PM CGL. Analyzed the data: FMR CGL.Contributed reagents/materials/analysis tools: PC PM CGL. Wrote thepaper: FMR CGL. Commented on the manuscript: PM PC.

Table 2. Studies on anadromous salmonids investigating the relationship between smolt size and post-smolt growth.

Relationship between smolt sizeand post-smolt growth

Type ofFish

Species Location 2 NS + Period Method Reference

S. salar Matre Aq St. 0 0 1 1981 MR H [27]

S. salar R. Narcea 5 1 0 1986–1990 BC W [16]

S. salar R. Esva 3 2 0 1986–1990 BC W [16]

S. salar R. Cares 1 1 0 1987–1988 BC W [16]

S. salar R. Penobscot 0 0 1 1973–1990 SG H [18]

S. salar Finland 0 0 1 1980–1991 MR H [26]

S. salar R. Imsa 1 0 0 1981–2003 MR H [23]

S. salar R. Alta 1 0 0 1993–1995 MR W [22]

S. salar Gulf St. Lawrence 0 1 0 1982–1984 SG W [25]

S. salar R. Ason 1 0 0 1948–2003 BC W [33]

S. salar R. Miramichi 0 1 0 1956–2003 BC W [87]

S. trutta Finland 1 0 0 1915–1989 Cline W [14]

O. kisutch Oregon 0 9 2 1991–2000 BC W [44]

O. kisutch Washington 0 8 2 1991–2000 BC W [44]

O. kisutch British Col. 2 9 0 1991–2000 BC W [44]

O. kisutch British Col. 1 0 0 1990 MR H [88]

O. mykiss British Col. 0 0 1 1990 MR H [88]

S. laucomaenis R. Nairo & Haraki 1 2 1 1990–1991 BC W [24]

S. trutta 6 rivers, NW Spain 1 0 0 2002 SG W This study

Total 18 34 9

Studies that found a negative relationship (2), no significant relationship (NS), and a positive relationship (+) are indicated. Method: MR mark and recapture, BC back-calculation of juvenile size, SG scale growth. Type of fish : H hatchery, W wild.doi:10.1371/journal.pone.0045528.t002



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72!!


Mixed-effects modelling of scale growth profiles predicts the

occurrence of early and late fish migrants

Mixed-Effects Modelling of Scale Growth Profiles Predictsthe Occurrence of Early and Late Fish MigrantsFrancisco Marco-Rius1, Pablo Caballero2, Paloma Moran1, Carlos Garcia de Leaniz3*

1 Departamento de Bioquımica, Genetica e Inmunologıa, Universidad de Vigo, Vigo, Spain, 2 Consellerıa de Medio Rural, Servizo de Conservacion da Natureza, Xunta de

Galicia, Pontevedra, Spain, 3 Department of BioSciences, Swansea University, Swansea, United Kingdom

Abstract

Fish growth is commonly used as a proxy for fitness but this is only valid if individual growth variation can be interpreted inrelation to conspecifics’ performance. Unfortunately, assessing individual variation in growth rates is problematic undernatural conditions because subjects typically need to be marked, repeated measurements of body size are difficult to obtainin the field, and recaptures may be limited to a few time events which will generally vary among individuals. The analysis ofconsecutive growth rings (circuli) found on scales and other hard structures offers an alternative to mark and recapture forexamining individual growth variation in fish and other aquatic vertebrates where growth rings can be visualized, butaccounting for autocorrelations and seasonal growth stanzas has proved challenging. Here we show how mixed-effectsmodelling of scale growth increments (inter-circuli spacing) can be used to reconstruct the growth trajectories of sea trout(Salmo trutta) and correctly classify 89% of individuals into early or late seaward migrants (smolts). Early migrants grewfaster than late migrants during their first year of life in freshwater in two natural populations, suggesting that migrationinto the sea was triggered by ontogenetic (intrinsic) drivers, rather than by competition with conspecifics. Our studyhighlights the profound effects that early growth can have on age at migration of a paradigmatic fish migrant and illustrateshow the analysis of inter-circuli spacing can be used to reconstruct the detailed growth of individuals when these cannot bemarked or are only caught once.

Citation: Marco-Rius F, Caballero P, Moran P, Garcia de Leaniz C (2013) Mixed-Effects Modelling of Scale Growth Profiles Predicts the Occurrence of Early and LateFish Migrants. PLoS ONE 8(4): e61744. doi:10.1371/journal.pone.0061744

Editor: Josep V. Planas, Universitat de Barcelona, Spain

Received September 30, 2012; Accepted March 13, 2013; Published April 16, 2013

Copyright: ! 2013 Marco-Rius et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was funded by grants from Ministerio de Ciencia y Tecnologıa (CGL2007-60572 and CGL2010-14964), and Fondos FEDER(PGIDIT03PXIC30102PN; Grupos de Referencia Competitiva, 2010/80). Francisco Marco-Rius was supported by a doctoral scholarship from the SpanishGovernment (BES-2008-001973). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: Carlos Garcia de Leaniz is a member of the Editorial Board of PLOS ONE. This does not alter the authors’ adherence to all the PLOS ONEpolicies on sharing data and materials.

* E-mail: [email protected]

Introduction

Body size is often the direct target of natural selection [1–3] andexamining how different individuals grow can reveal much abouthow they respond to competition and adapt to environmentalchange [4,5]. However, modelling animal growth has provedchallenging because there is considerable heterogeneity amongspecies and individuals, and because accounting for such diversityis inherently difficult at the analytical level [6]. For example,homoeothermic and poikilothermic organisms show markedlydifferent constraints on evolution of body size [7], and hence ongrowth. Growth can also vary markedly throughout the lives oforganisms, and regional-scale processes can affect individuals verydifferently depending on season [8,9]. Individuals may ceasefeeding or augment food intake depending on temporal cues butenvironmental thresholds may vary markedly among individualsgiving rise to divergent growth trajectories even among neigh-bouring conspecifics exposed to the same cues [10–12]. Inaddition, growth is intimately linked to many life history traits[13], and cannot be considered in isolation. For example, rate ofgrowth has a pervasive effect on age at maturity in fishes [14–16],and on longevity in mammals [17].

Anadromous salmonids are good models to examine the fitnessconsequences of individual variation in growth because resident

and migratory individuals commonly coexist and alternativereproductive tactics are often size-dependent [18,19] reflectingconsiderable phenotypic plasticity [20,21]. Thus, the choice toremain in freshwater or to migrate to sea is often determined bysize and/or growth thresholds [22] and these may in turn dependon metabolic efficiency [23]. However, movement can betriggered by two very different and seemingly opposing conditionsin relation to energy acquisition and individual performance. Poorgrowers may be forced to move in response to competition andlow food acquisition [24,25], while fast growers may move becausethey have increasingly high food demands, as high metabolic ratesare difficult to maintain in freshwater [26]. Thus, althoughmovement can be viewed as a generalized response to adversity[27], the underlying causes can be very different and will likelyhave different fitness consequences.

Individual growth is often estimated as the difference in bodysize between two or more arbitrarily chosen time events, but inmost field studies not all marked individuals can be recaptured, oreven sampled at the same times [28], making individualcomparisons difficult. More commonly, researchers are limitedto inferring growth from changes in the average size at successiveages or time events [29–31], often based on different individuals.Growth is then analyzed using models based in the VonBertalanffy [32] approximation [33–35], but this ignores individ-

PLOS ONE | www.plosone.org 1 April 2013 | Volume 8 | Issue 4 | e61744

ual variation in growth trajectories [36] and assumes that age isaccurately measured [37], something that is not always possible.

Here we used a method based on the analysis of the spacingbetween consecutive growth rings found in the scales (growthcirculi) to reconstruct individual growth trajectories of migratorybrown trout (sea trout, Salmo trutta) before they migrated to sea. Wespecifically compared the growth trajectories of individuals thatmigrated to sea after only one year in the river (early migrants)with those that delayed seaward migration for one or moreadditional years (late migrants). We hypothesized that earlymigrants would have grown faster than late migrants during theirfirst year of life if migration was triggered by high food demands(i.e. intrinsic drivers), but would have grown more slowly ifmigration was the result of extrinsic constraints, for examplecompetition resulting in low food acquisition.

Methods

Study populationsMigratory brown trout (sea trout) were caught in upstream traps

or by angling in the rivers Ulla and Lerez (Galicia, NW Spain)during 1999–2010. The two populations differ in key physical anddemographic parameters, including accessible length (Ler-ez = 25.1 Km, Ulla = 102.3 Km), watershed area (Ler-ez = 449.5 Km2, Ulla = 2803.6 Km2) and stream order (Lerez = 5,Ulla = 6). Mean angling catch of migratory trout during (used as aproxy for population size) was 101 individuals in the R. Lerez and1,934 individuals in the R. Ulla. Sea trout smolts in the R. Ullatend to be older (mean smolt age 2.260.45 yrs) and larger (meansmolt size 216644 mm) than those in the R. Lerez (mean smoltage 2.160.58 yrs; mean smolt size 191652 mm), while mean ageat return shows the opposite pattern (R. Ulla, 3.1560.84 yrs; R.Lerez, 3.5160.78

Scale analysis and reconstruction of growth profilesScales of 60 individuals per river and year were stored dry in

paper envelopes, along with information on their body size (forklength, mm). Between three and five scales with a clear nucleuswere selected per individual to minimize bias due to scaleregeneration [38]. Acetate impressions were made with the aidof a pressure roller and the resulting impressions scanned at 23–506 magnifications (Minolta MS 6000) as in [39]. The softwareImage-J v. 1.4.1 [40] was employed to digitize the position of eachgrowth ring (circulus) and to measure inter-circuli spacing withreference to a calibrated scale bar [41]. Freshwater and marineages were determined based on the number of annuli [42], and thepoint of entry of smolts into the sea identified by a change fromconcave to convex circuli (i.e. the point where circuli openoutwards on the posterior zone of the scale) and presence ofbroken growth rings [43].

Reliability of scale analysisA paired t-test was used to assess non-random deviations in scale

radii between the original scales and their acetate impressions(n = 30) in order to quantify potential bias in scale measurementsarising from pressure from the hand roller. To ascertain theprecision of the scale analysis, we estimated the repeatability of thepoint of entry into the sea and of the end of the first freshwatergrowing season by measuring the scales of 30 individuals twice in adouble blind fashion and calculating the intra-class correlationcoefficient (a-Cronbach) as per [21]. The Pearson correlationcoefficient was used to evaluate the strength of the associationbetween scale radius and body size of fish in each river. Thecoefficients of variation (CV) were then examined to compare the

precision of body size and scale measurements. Precision in scalemeasurements (0.01 mm; CV = 17.1%) was better than that ofbody size measurements (cm; CV = 19.2%), and the former wastherefore preferred to examine growth variation among migratorytrout. Thus, and in common with other recent studies [44–45], wedid not convert scale measurements into body size estimates, asthis would have merely introduced additional errors resulting from(1) low precision of body size measurements taken on live fish inthe field, and (2) uncertainty about the precise nature of thefunction linking scale growth to body growth.

Data analysisIn order to model individual variation in freshwater growth, we

examined the spacing between consecutive growth circuli (inter-circuli spacing), the number of growth circuli deposited in thescales, and the growth of the scales (scale length) attained at theend of the first year. We only modelled variation in freshwatergrowth as we are interested in explaining drivers of seawardmigration, and this allowed us to compare the common part of thescales of all migratory individuals, irrespective of the time they hadspent at sea. We employed binary logistic regression to model thelikelihood of early vs. late seaward migration as a function ofgrowth during the first year of life, and assessed model fit by thelog-likelihood ratio using SYSTAT 10.0. The first three circuli ofthe scale were not taken into account due to the possibility ofmissing growth rings during early life [44].

We used REML to model individual variation in inter-circulispacing with the ‘nlme 3.1–86’ package [46] on the R 2.14language [47]. A preliminary analysis of 20 randomly chosenindividuals per river suggested that the inclusion of random effectswas required to account for individual variation in slopes andintercepts (Figure S1, Supporting information). The inclusion ofhigher order polynomials allowed us to examine differences in theseasonal growth of one and two year old smolts, according to thefollowing expression (Equation 1):

Ri,j~b0zb1Pizb2Yi,jzb3Ai,jzb4Ci,jzb5C2i,jzb6(Ai{1)|

C3i,jzb7C4

i,jzb8Ri|Ci,jzb9LizaizbiCi,jzei,j

where R is the scale radius of individual i at circulus j, P is thepopulation (R. Lerez, 0, R. Ulla 1), Y represents the different smoltyears, A is the freshwater age, C is the scale circuli and L is the forklength of the fish returning from the sea. Random slopes (b) andintercepts (a) were assumed to be independent and normallydistributed with zero means and variances s2a and s2b,respectively; errors ei,j were also assumed to be independent andnormally distributed. We allowed for autocorrelation in inter-circuli spacing by considering an autoregressive (AR) model oforder one in the autocorrelation structure, as this provided a betterfit to the data than a model without correlated serial errors. TheBayesian Information Criteria (BIC) was used for model selectionof fixed effects, mixed effects and autocorrelation structure oferrors terms [48]. We employed the coefficient of variation (CV) toquantify individual variation in inter-circuli spacing at eachcirculus [21].

For the classical Von Bertalanffy growth model, a nonlinearleast-squares (nls) regression was used to estimate the growthparameters (L‘, k and t0) from the scales, using all the scale circuli(Equation 2):

L(t)~L? 1{e{k(t{t0)! "

Mixed-Effects Modelling of Fish Growth


Individual growth curves were fitted to each fish and comparisonswere made between fitted and observed values.

Ethics StatementWe made use of scales samples collected routinely for ageing

purposes by trained fisheries staff of the Regional Government ofGalicia (Wildlife Service). Scales were collected from anaesthetizedfish (clove oil) using a small fish knife and according to currentSpanish Regulations, as described in a previous study [21]. Afterthe fish had fully recovered from the anaesthesia (approx. 30 min),they were returned live to a point immediately upstream of thepoint of capture. No specific permits were required for scalecollection, as these did not involve endangered or protected speciesand the work was carried out by government fishery officers underthe supervision of one of the co-authors (PC), who is a governmentfish veterinarian.

Results

Reliability of scale analysisThe impression process produced no significant distortion of

scale radius (t29 = 0.547, P = 0.465), indicating that acetateimpressions gave an accurate, unbiased representation of scalesize. Repeatabilities of scale size were high, both for smolt scalelength (a-Cronbach = 0.879) and for scale size attained at the endof the first freshwater growing season (a-Cronbach = 0.898). Scaleradius and fork length were positively correlated (r = 0.747,P = 0.001), and the relationship was not different between rivers(F1,636 = 0.542, P = 0.589) allowing us to examine individualvariation in scale growth regardless of river identity.

Effect of first year growth on age of seaward migrationThe minimal adequate model that best explained age of

seaward migration included scale growth (estimate = 24.5,SE = 0.96, t = 24.66, P,0.001) and mean inter-circuli spacingduring the first year (estimate = 565.5, SE = 85.20, t = 6.64,P,0.001) as predictors. This provided a reasonably good fit tothe data (McFadden rho2 = 0.138, x2 = 60.263, df = 2, P,0.001)and correctly classified 89.4% of fish into early and late migrants.The inclusion of other terms and their interactions did notimprove model fit. In both rivers, early migrants (i.e. one year oldsmolts) were those that had attained higher rates of scale growthuntil their first winter (Fig. 1a; R. Lerez F3,448 = 13.123, P,0.001;R. Ulla F3,486 = 6.328, P,0.001). This was chiefly achieved bydepositing more growth rings for a given scale length (Fig. 1b; R.Lerez F3,448 = 14.279, P,0.001; R. Ulla F3,486 = 5.906, P = 0.001).Thus, scale length and number of growth rings were positivelycorrelated in both early and late migrants, but inter-circuli spacingand number of growth rings were not (Figure 2).

Individual variation in freshwater growthThe minimal adequate model for inter-circuli spacing in

freshwater included an autocorrelation term as well as randomslopes and intercepts (Table 1). Although random slopes andintercepts were relatively small, their inclusion significantlyimproved model fit, indicating that growth rates during earlydevelopment, as well as initial size differences, differed significantlyamong individuals and affected subsequent growth. The positiveand significant effect of fork length reflects the positive associationfound between body size and scale size, whereas the fourpolynomial terms of the model reflect the seasonality in inter-circuli spacing that was found to be necessary to include in orderto capture seasonal growth stanzas (Figure 3), and which differedsignificantly between rivers. Thus, inter-circuli spacing for the

Figure 1. Marginal means (± SE) of (a) scale growth and (b) no. of growth circuli deposited during the first year in sea trout ofdifferent smolt ages (age of seaward migration).doi:10.1371/journal.pone.0061744.g001



River Ulla was significantly higher than for the River Lerez. Incontrast, inter-circuli spacing did not vary significantly over the 11years of study. Trout which emigrated to sea after only one year ofgrowth in freshwater (early migrants) tended to have smaller thanaverage inter-circuli spacing during the first months of life thanthose that delayed migration for one or two additional years. Suchan effect was evident in both populations (Figure 1), and waslargely the consequence of having deposited more growth rings fora given scale length. Analysis of temporal trends in CV indicatesthat variability in scale length increments increased until the firstwinter in both rivers (Figure S2), suggesting that initial differencesin growth performance among individuals became amplified

during early life. Model checks indicate a moderately good fitbetween observed and predicted values (Supporting information,Figure S3) and well behaved residuals. On the other hand, modelfitting using individual Von Bertalanffy growth curves was very

Figure 2. Scatterplot matrix showing relationships betweenscale growth parameters (no. of growth circuli, mean inter-ciculi spacing, and scale length during the first year infreshwater) of returning sea trout migrating to sea as earlymigrants (1 year old smolts) or late migrants (2–4 year oldsmolts). Each variable is compared against the other two and therelationship between pairs of variables is shown by a solid red linerepresenting a locally weighted scatterplot smoothing (LOWESS) and bythe strength of the Pearson correlation coefficient (***P,0.001;**P,0.01). Frequency histograms for each variable are shown alongthe diagonal.doi:10.1371/journal.pone.0061744.g002

Figure 3. Fitted values of the mixed-effects model of inter-circuli spacing in the freshwater phase of migratory browntrout. Growth trajectories of one (N) and two-year old smolts ( ) areindicated. Correspondence between circuli number and calendarmonth is only approximate and is used to visualize the timing ofseasonal growth stanzas.doi:10.1371/journal.pone.0061744.g003



poor (R2 = 0.04), and gave exponential or even negative growth formany fish (data not shown).

Discussion

How does one examine individual variation in growth rateswhen subjects cannot be marked or few are ever recaptured? Webelieve that the analysis of growth rings may provide an answer.Fish scales are routinely collected in fisheries for ageing, but it haslong been recognised that the spacing between growth circuli(inter-circuli spacing) can also reveal much about the growth ofindividuals [49]. However, this information has traditionallyproven difficult to analyze [50]; often researchers simply back-calculate body size at a given age, work on average size incrementsat particular times, or apply corrections to the degrees of freedomin an attempt to account for autocorrelations in inter-circulispacing (e.g. [45]). We employed mixed effects modelling tocompare inter-circuli spacing in the scales of migratory browntrout, and used this information to reconstruct juvenile growthtrajectories in freshwater. To model seasonal changes in consec-utive length increments, we included first to fourth orderpolynomial terms as a smoothing function of time [51,52] andcompared the results to those obtained by applying individual VonBertalanffy equations.

Our results indicate that variation in early summer growthdiffered significantly among individuals (as evidence by theexistence of random intercepts and slopes), and that individualdifferences in early growth became amplified over the first monthsof life (as evidenced by an increase in the coefficient of variation).Large individual differences in early growth have been document-ed in salmonids soon after emergence from the redd [53] and theseappear to be closely related to dominance status [54], metabolicrate [55], and timing of hatching in relation to prior residencyeffects [56]. It is likely that the strength of density-dependent

regulation during early life may determine the extent of individualvariability in growth, so that fish which achieve high growth ratesduring their first year are able to maintain a size advantage later inlife [57]. Small individuals within a cohort are more influenced byintra-specific competition than large ones [58]. In this sense,incorporating random effects in the model, allows a better insightinto the nature of within-individual variation in growth patterns.

Egg size has been found to have a large effect on early growthand survival of salmonids [59,60] and it is possible that the largeindividual differences revealed by our analysis might be related tovariation in egg size (maternal effect; [61]) in addition todifferences in early rearing [62]. In addition, we found significantdifferences in the freshwater growth of sea trout inhabiting twoneighbouring rivers. This serves to highlight the large influencethat, in addition to maternal effects [62], local-scale rearingconditions may have on juvenile salmonids during early life[53,63]. The significant effect of body size in our model furthersuggests the growth experienced in freshwater has a positive effecton length at maturity. Marine survival of anadromous fish isthought to depend not just on growth attained at sea (e.g. [64]),but also on the size attained by juveniles before seaward migration(smolt size). Indeed, large smolts typically survive better thansmaller ones, particularly on bad years [65–67], and as ouranalysis illustrates, the retrospective analysis of inter-circuli spacingmay reveal periods when differences among individuals becomemost pronounced.

An additional advantage of modeling growth based on theseasonal deposition of growth circuli is to remove bias caused byan arbitrary choice of sampling events. For example, growth ofsoftwoods varies markedly between wood formed in spring andwood formed in summer and autumn [68], and an analysis of non-annual growth rings can provide valuable information onindividual growth variation that would be lost if only annualgrowth rings are examined (as it is often the case in fishery science).

Accounting for individual variation in fitness traits is becomingincreasingly important in ecological and evolutionary studies [69–72], because fitness is essentially a relative concept that needs to beinterpreted in relation to performance shown by conspecifics [73].Growth is commonly used as a proxy for fitness [74], yetcomparing large number of serially correlated points, typical ofgrowth studies, presents a considerable challenge [75]. Mixedeffects modelling [76,77] is useful in this respect, as it allows for theinclusion of random slopes and intercepts that can be used todescribe the growth of individuals, as well as for the incorporationof an auto-correlation structure. Recent studies have highlightedthe advantages of such an approach, and have stressed theimportance of avoiding sampling individuals only twice [78], acondition common to many growth studies.

In summary, we have illustrated how a new method based onmixed-effects modelling can be used to examine individualvariation in growth trajectories, reconstructed from multiplerepeated measurements of the spacing between consecutivegrowth rings, thereby affording greater statistical power thansimple growth estimates based on two or few arbitrarily chosenpoints in time. Fish scales can be collected non-destructively andstored dry for considerable time, providing unique archivalmaterial to address long-term population changes (e.g. [79–81]).Our approach makes it possible to quantify individual variationand seasonality in growth stanzas, something that popularmethods such as the Von Bertalanffy growth model cannot do.The method has shown good reproducibility, and can be readilyextended to the analysis of growth of other aquatic organismshaving hard structures where growth rings can be visualized, suchas otoliths, vertebrae, shells, or bones. We illustrate the application

Table 1. Parameter estimates in mixed-effects modelling ofinter-circuli spacing of sea trout in two study rivers.

Effects Estimate Std. Error t-value P-value

Fixed

Intercept 0.0389 0.00071 54.54 ,0.0001

FW age 22.667 1024 3.520 1024 20.75 0.449

River [Ulla] 0.0395 7.599 1024 52.07 ,0.0001

Circuli 22.722 1023 3.754 1025 272.52 ,0.0001

Circuli2 1.222 1024 1.815 1026 67.33 ,0.0001

Circuli3 20.453 1027 0.453 1028 249.72 ,0.0001

Circuli4 0.190 1027 0.024 1028 53.01 ,0.0001

FW age6Circuli3 1.001 1027 1.401 1028 7.22 ,0.0001

River [Ulla]6Circuli 6.200 1027 8.256 1026 0.07 0.946

Fork length 3.480 1026 1.234 1026 2.82 0.004

Random (SD)

Intercept 2.683 1023

Slope (Circuli) 8.706 1025

Residual 5.796 1023

Correlation structure

corr 0.742

Random effects are indicated by the standard deviation of slopes andintercepts.doi:10.1371/journal.pone.0061744.t001



of the method by examining growth of migratory brown troutfrom two populations, based on digitized impressions of fish scales.Analysis of inter-circuli spacing during the first year of lifeaccurately predicted whether trout migrated to sea as early (oneyear old) or late (2–4 year old) smolts, highlighting the profoundeffect that early growth can have on age at migration ofanadromous fish. The fact that early migrants grew faster thanolder ones suggests that seaward migration was primarily triggeredby ontogenetic (intrinsic) drivers, possibly in response to changes inenergetic state [26], rather than by extrinsic forces such ascompetition with conspecifics or low food availability [24,25].

Supporting Information

Figure S1 Variation in random slopes (time) andintercepts of the mixed-effects model of inter-circulispacing during the first year of freshwater growth for arandom sample of 20 sea trout from each of the twostudy rivers (R. Lerez, R Ulla).(TIFF)

Figure S2 Coefficient of variation (CV = SD/mean) ofinter-circuli spacing of freshwater growth in twopopulations of sea trout. Grey bands represent point-wise95 CI envelopes derived from bootstrapping.(TIFF)

Figure S3 Observed versus fitted values for the mixed-effects model of sea trout inter-circuli spacing in twopopulations of sea trout (R. Ulla, R. Lerez).(TIFF)

Acknowledgments

We thank Pilar Alvarino and Laura Cal for technical assistance, and SoniaConsuegra, Josep V Planas, and two anonymous reviewers for helpfulcomments on the manuscript.

Author Contributions

Conceived and designed the experiments: FMR CGL. Performed theexperiments: FMR PC PM CGL. Analyzed the data: FMR CGL.Contributed reagents/materials/analysis tools: PM CGL PC. Wrote thepaper: FMR CGL.

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Can migrants escape from density-dependence?

1

Contemporary ocean warming and freshwaterconditions are related to later sea age at maturityin Atlantic salmon spawning in Norwegian riversJaime Otero1, Arne J. Jensen2, Jan Henning L’Abee-Lund3, Nils Chr. Stenseth1,4, Geir O. Storvik,1,5 &Leif Asbjørn Vøllestad1

1Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biology, University of Oslo, P.O. Box 1066 Blindern, N-0316, Oslo,Norway

2Norwegian Institute for Nature Research, P.O. Box 5685 Sluppen, N-7485, Trondheim, Norway3Norwegian Water Resources and Energy Directorate, P.O. Box 5091 Majorstua, N-0301, Oslo, Norway4Institute of Marine Research, Flødevigen Marine Research Station, N-4817, His, Norway5Department of Mathematics, University of Oslo, P.O. Box 1066 Blindern, N-0316, Oslo, Norway

Keywords

discharge, maturation, Norway, Salmo salar,

sea surface temperature.

Correspondence

Jaime Otero, Centre for Ecological and

Evolutionary Synthesis (CEES), Department of

Biology, University of Oslo, P.O. Box 1066

Blindern, N-0316 Oslo, Norway. Tel: +47

22854400; Fax: +47 22854001;

E-mail: [email protected]

Funding Information

This study was funded by the Research

Council of Norway project nº 183989/S30.

Received: 6 February 2012; Revised: 20 June

2012; Accepted: 22 June 2012

Ecology and Evolution 2012; 2(9): 2192–2203

doi: 10.1002/ece3.337

Abstract

Atlantic salmon populations are reported to be declining throughout its range,raising major management concerns. Variation in adult fish abundance may bedue to variation in survival, growth, and timing of life history decisions. Giventhe complex life history, utilizing highly divergent habitats, the reasons fordeclines may be multiple and difficult to disentangle. Using recreational anglingdata of two sea age groups, one-sea-winter (1SW) and two-sea-winter (2SW)fish originated from the same smolt year class, we show that sea age at maturityof the returns has increased in 59 Norwegian rivers over the cohorts 1991–2005. By means of linear mixed-effects models we found that the proportion of1SW fish spawning in Norway has decreased concomitant with the increasingsea surface temperature experienced by the fish in autumn during their firstyear at sea. Furthermore, the decrease in the proportion of 1SW fish was influ-enced by freshwater conditions as measured by water discharge during summermonths 1 year ahead of seaward migration. These results suggest that part ofthe variability in age at maturity can be explained by the large-scale changesoccurring in the north-eastern Atlantic pelagic food web affecting postsmoltgrowth, and by differences in river conditions influencing presmolt growth rateand later upstream migration.

Introduction

Recent climate change is promoting multiple effects atpopulation, community, and ecosystem levels inducingextensive ecological changes well documented from vari-ous terrestrial, freshwater, and marine systems (Letcher2009). The impacts of climate variability on aquatic eco-systems are diverse and affect key life history processes,including reproduction and maturation of fish (Rijnsdorpet al. 2009). Age at reproduction is among the mostimportant life history traits, having profound fitnesseffects and also important demographic implications(Stearns 1992). In fish, age at maturity has a significantadditive genetic component (Carlson and Seamons 2008),

but is also highly plastic (Hutchings 2011). This is alsothe case for the Atlantic salmon (Salmo salar) (Garcıa deLeaniz et al. 2007), a highly charismatic species with greateconomic and social value. It is therefore of great concernthat Atlantic salmon production has been declining acrossmost of the species’ distributional range over the pastrecent decades (Hindar et al. 2011).The life history of Atlantic salmon is complex (Thorstad

et al. 2011). Spawning occurs in freshwater in October–January. After hatching in spring the juveniles (parr) stayin freshwater 1–6 years before transforming into smolt.The smolts then leave their rivers to pursue oceanicfeeding migrations during spring and early summer. Post-smolt Atlantic salmon spend 1–4 years at sea until the

2192 ª 2012 The Authors. Published by Blackwell Publishing Ltd. This is an open access article under the terms of the CreativeCommons Attribution Non-Commercial License, which permits use, distribution and reproduction in any medium, providedthe original work is properly cited and is not used for commercial purposes.

Can migrants escape from density-dependence? Francisco Marco-Rius1, Pablo Caballero2, Paloma Morán1, Carlos Garcia de Leaniz3 1Universidad de Vigo, Departamento de Bioquímica, Genética e Inmunología, Vigo 36310, Spain. 2Xunta de Galicia, Consellería de Medio Rural, Servizo de Conservación da Natureza, Pontevedra 36071, Spain 3Swansea University, Department of BioSciences, Swansea SA2 8PP, UK

Keywords: Individual approach, brown trout, statistical modelling, growth, density, migration. Correspondence Carlos Garcia de Leaniz, Swansea University, Department of BioSciences, Swansea SA2 8PP, UK; E-mail: [email protected] Funding Information Funding for this work was provided by grants from Ministerio de Ciencia y Tecnología (CGL2007-60572 and CGL2010-14964), and Fondos FEDER (PGIDIT03PXIC30102PN; Grupos de Referencia Competitiva, 2010/80). Francisco Marco-Rius was supported by a doctoral scholarship from the Spanish Government (BES-2008-001973). Received: 11 February 2013.

Abstract 1. Migration is thought to maximize growth by enabling individuals to escape from density-dependence, but this has rarely been tested at the individual level in natural populations. 2. We employed linear mixed modelling of the spacing between consecutive scale growth rings to reconstruct individual growth profiles of a paradigmatic fish migrant, the sea trout (Salmo trutta) and related these to estimates of year class strength over a 13-year period. 3. Variation in scale growth was 1.3 times greater among individuals than within individuals in freshwater, and 10 times greater at sea. Scale growth was inversely related to year class strength, but density-dependence was c. 2.5 times stronger in freshwater (before migration) than at sea (after migration). 4. Competition for patchily distributed resources is the most plausible explanation for the negative density-dependent growth observed in freshwater and, to a lesser extent, in the marine environment. 5. Our study provides some of the strongest evidence for a role of density-dependence in determining partial migrations because although migrants can maximize growth by moving into the sea, they do not appear to become free from density-dependence constraints completely. This has implications for conservation and suggests that sea trout and other anadromous fish displaying partial migrations may not be best managed on a river by river basis, but rather from a broader, coastal perspective.

Introduction Understanding temporal fluctuations in the abundance and growth of organisms has long been a key challenge in population ecology (Krebs 2009) and density-

dependence is perhaps one of the most ubiquitous endogenous regulators (Brook & Bradshaw 2006). Consideration of density-dependence regulation is also important for managing exploited populations because harvest mortality can have markedly

2

different effects depending on density (Minto, Myers & Blanchard 2008). Yet, the effects of density-dependence may not become noticeable unless one repeatedly samples at the individual level (Vøllestad & Olsen 2008) because most organisms become more mobile as they grow, and ontogenetic changes in per capita resource requirements can cause the relationship between density and resource abundance to change over time (Begon, Mortimer & Thompson 1996). This is particularly the case for migratory species, where individuals may be able to ‘escape’ competition by moving between habitats (Poethke, Pfenning & Hovestadt 2007; Mobæk et al. 2009), thereby making it difficult to detect density-dependence regulation. Salmonids are well suited for studying density-dependence because juveniles pass through a critical time for survival soon after emergence from spawning redds (Elliott 1994; Garcia de Leaniz, Fraser & Huntingford 2000) when competition for food and space is intense (Van Zwol, Neff & Wilson 2012), and many populations include both resident and migratory individuals (partial migration, Wysujack et al. 2009; Acolas et al. 2012). Most density-dependence studies have made use of time series based on stock-recruitment relationships to infer density-dependent regulation at the early juvenile stage. For example, researchers have compared egg densities against juvenile survival (Nicola et al. 2008), or against body size (Einum, Sundt-Hansen & NIslow 2006). However, this approach assumes that density is a valid metric of the intensity of competition experienced by individuals, which may not be the case if resources are patchily distributed and sampling area is unrelated to the spatial scale of the species (Berryman 2004). An effect of density on growth may also be difficult to detect in such studies if resident fish have a larger than average size or emigration is size-dependent (Elliott 1994; Jenkins et al. 1999). Density needs to be measured in relation to the mobility of the organism under study (Jenkins et al. 1999) and the spatial distribution of resources (Berryman 2004; Finstad et al. 2009), but these may not always be known. A second limitation

of observational studies is that fitness metrics, such as survival or growth, are often collected for a small subset of individuals, typically over a short time period. For example, density estimates of juvenile salmonids are typically inferred (and scaled up) from a necessarily limited number of small sampling stations, which can restrict statistical inferences. Similar limitations also exist for growth studies because the number of individuals that can be recaptured is typically small, which seriously limits the number of repeated measures that can be obtained. In addition, small alevins are usually difficult or even impossible to mark individually (Kaspersson et al. 2009), which is unfortunate since this the stage where the impact of density on fitness is most likely to be manifested (Elliott 1994). Fitness is a relative concept that needs to be interpreted in relation to conspecifics’ performance and which is useful to the extent that one can quantify trait variation among individuals (Wilson 2004). The analysis of the spacing between consecutive growth rings (circuli) found in bone structures such as scales or otoliths can be used to reconstruct the growth trajectories of individuals with much more detail than is usually possible through mark and recapture (Campana & Thorrold 2001). In addition, because the analysis of growth circuli represents repeated measures on the same individuals, linear mixed effects models can be used to increase the power and accuracy of statistical inferences (van de Pol 2012). Here we used a 13-year time series with estimates of year class strength for two populations of migratory brown trout (Salmo trutta) to test the hypothesis that early freshwater growth, but not marine growth, is suppressed at high population densities. We employed upstream trap records of sea trout returning to rivers to spawn to estimate year class strength based on the number of adults caught each year, standardized to a common body size. We tested for density-dependence by examining changes in juvenile growth reconstructed from scale analysis in relation to parental abundance. Freshwater systems are typically more resource limited than marine environments (Ross 1986), and density-dependent

3

Table 1. Parameter estimates of mixed-effects modelling of intercirculi spacing (square root) during the first year in freshwater. Random effects are indicated by the standard deviation of slope and intercept. Minimal adequate linear mixed effects model (LMM): Intercirculi spacing)0.5 = River + Year class strength + Circuli No.

Effects Estimate SE t-value P-value Fixed

Intercept 0.167 0.813 10-3 207.70 <0.001 Circuli No. -0.002 3.703 10-5 -47.78 <0.001 River 0.305 10-2 8.567 10-4 3.56 <0.001 Year class strength -6.310 10-6 2.711 10-6 -2.32 0.020

Random (SD) Intercept 0.011 Slope (Circuli) 0.001 Residual 0.018


Corr 0.267

growth is thought to be caused by exploitative competition for food, rather than by interference competition for space in freshwater (Grant & Imre 2005), though both mechanisms may operate and result in identical density-growth relationships (Ward et al. 2007). In the sea, in contrast, the effect of density on salmonid growth is thought to be mediated exclusively through completion for food (Peterman 1984) as it is assumed that it would be difficult for fish to monopolize space or defend marine resources (Snover, Watters & Mangel 2005). Our expectation, therefore, was that variation in freshwater growth would track changes in year class strength, whereas variation in marine growth would be largely independent of density if juveniles migrate to ‘escape’ competition. Materials and methods Study populations We examined temporal variation in density-dependent growth in two contrasting populations of migratory brown trout (sea trout) from Galicia (NW Spain), one from a large watershed (R. Ulla – 2,804 km2) and one with a much smaller catchment (R. Lerez – 449 Km2). Sea trout were caught in upstream traps on their returning marine migration each year during 1999-2010, the body size was measured (fork length, mm) and a sample of scales collected before the fish were returned upstream by fishery officers. The two rivers differ markedly in accessible stream length for sea trout (R. Lerez – 25 Km, R. Ulla – 102 Km) and

estuary size (R. Lerez – 99 Km2, R. Ulla – 238 Km2), and also likely in the strength of density-dependent effects (Caballero, Cobo & Gonzalez 2006; Marco-Rius et al. 2012). Thus, sea trout from the much smaller River Lerez migrate to sea at a smaller size (mean 174 ± 9.1 mm) and younger age (mean 2.04 ± 0.13 yrs) than those from the larger R. Ulla (mean smolt size 220 ± 12.4 mm, mean smolt age 2.12 ± 0.12 yrs; Marco-Rius et al. 2012). Scale analysis and growth profiles We randomly chose scales from 60 individuals per river and year from the historical scale collection, and selected 2-5 scales with clear (non–regenerated) nuclei for each fish to prevent bias due to loss of the first few growth rings. We made acetate impressions of the scales withthe aid of a pressure roller, scanned these with a Minolta MS 6000 microfilm scanner at 23-50x magnification, and saved them as high resolution TIFF images as in Kuparinen et al. (2009). Image-J v. 1.4.1 (Abramoff, Magalhães & Ram 2004) was employed to digitize the position of each growth ring, to identify the annual growth rings (annuli), and to measure the inter-circuli spacing along the 360º scale axis with reference to a calibrated scale bar in order to derive measures of scale growth (Marco-Rius et al. 2012). The freshwater and marine ages were determined based on the number of annuli and the point of entry of smolts into the sea (beginning of marine phase) was

4

Table 2. Parameter estimates of mixed-effects modelling of intercirculi spacing (square root) during the first marine growing season (post-smolt growth). Random effects are indicated by the standard deviation of slope and intercept. Minimal adequate linear mixed effects model (LMM): Intercirculi spacing)0.5 = River + Smolt Year strength + Circuli No.

Effects Estimate SE t-value P-value Fixed

Intercept 0.020 0.727 10-3 27.57 <0.001 Circuli No. 1.504 10-4 1.011 10-5 14.88 <0.001 River 1.797 10-2 0.036 10-3 4.98 <0.001 Smolt Year strength -2.550 10-6 1.278 10-6 -1.98 0.048

Random (SD)

Intercept 2.718 10-3 Slope (Circuli) 3.949 10-5 Residual 8.565 10-3


Corr 0.564

noted based on the change from a concave to a convex curvature of the first marine circulus (Marco-Rius et al. 2012). We considered scale growth patterns between the scale focus and the first freshwater winter as a measure of early juvenile growth in freshwater, and between the point of entry into the sea and the first marine winter as a measure of early marine growth (post smolt growth, PSG; Friedland et al. 2006). Using only the first part of the freshwater and marine phases (common to all individuals) avoids problems due to age effects and assumes that inter-cohort density-dependent effects are similar for yearling and under-yearling individuals in terms of growth potential (Kvingedal & Einum 2011). The first three scale circuli were not taken into account in the analysis due to the possibility of scale regeneration during early growth. In total we analysed scales of 453 sea trout from the R. Lerez and 490 sea trout from the R. Ulla. Reliability of scale analysis A paired t-test was used to assess non-random deviations in scale radii between the original scales and their acetate impressions (n = 30) in order to quantify potential bias in scale measurements arising from pressure from the hand roller. To ascertain the precision of the scale analysis, we estimated the repeatability of the point of entry into the sea and of the end of the first freshwater growing season by measuring the scales of 30 individuals

twice in a double blind fashion and calculating the intra-class correlation coefficient (α-Cronbach) as per Kuparinen et al. (2009). The Pearson correlation coefficient was used to evaluate the strength of the association between scale radius and body size of fish in each river. The coefficients of variation (CV) were then examined to compare the precision of body size and scale measurements. Precision in scale measurements (0.01 mm; CV = 17.1%) was better than that of body size measurements (cm; CV = 19.2%), and the former was therefore preferred to examine growth variation among migratory trout. Scale measurements were not converted to body size measurements as this introduces additional errors resulting from relatively crude measurements of body size taken in the field. Data analysis We modelled variation in year class strength by considering the annual number of returning sea trout caught in two upstream traps at the end of the fishing season (R. Lerez, mean trap catch = 347 sea trout/year, range: 203-610; R. Ulla mean trap catch = 350 sea trout/year, range: 212-596), standardized to a common body size (Lerez, 347.3 mm; Ulla, 350.3 mm) in order to factor in variation in size-dependent fecundity. We assumed that annual variation in trap catches reflected variation in spawning escapement (and thus on egg deposition) and derived

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Lerez, 1997 Lerez, 1998 Lerez, 1999 Lerez, 2000 Lerez, 2001 Lerez, 2002

Lerez, 2003 Lerez, 2004 Lerez, 2005 Lerez, 2006 Lerez, 2007 Lerez, 2008

Lerez, 2009 Ulla, 1997 Ulla, 1998 Ulla, 1999 Ulla, 2000 Ulla, 2001

Ulla, 2002 Ulla, 2003 Ulla, 2004 Ulla, 2005 Ulla, 2008 Ulla, 2009

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indices of year class strength for each cohort and smolt year (i.e. year of seaward migration) taking into account the age structure of these populations (Marco-Rius et al. 2012) to factor in the relative contribution of overlapping age years classes. We employed linear mixed modeling to assess individual variation on the spacing between consecutive growth circuli (inter-circuli spacing) using the protocol described in Zuur et al. (2009) for nested data using the Bayesian Information Criteria (BIC). The effects of river and year class strength on freshwater inter-circuli spacing was examinedwith the following fixed effects saturated model: I ~ C x SH x R where I is the freshwater inter-circuli spacing (until the first freshwater winter), C is the circuli pair being considered, SH is the standardized year class strength at hatching adjusted for variation in adult body size and juvenile age structure, and R is the river identity. All the possible interactions were included in the model. Likewise, to model variation in marine scale growth we considered the following

saturated structure: I ~ C x R x SM x FW where I is the marine inter-circuli spacing (until the first marine winter), C is the circuli pair being considered, SM is the standardized year class strength at smolting (taking into account the smolt age of the population) adjusted for variation in adult body size, R is the river identity, and FW is the scale radius at the end of the first winter in freshwater. As previously, all interactions were included in the model. We used the squared root of the dependent variable in every model to help normalize error terms. Random effects were tested in both saturated models, and these were assumed to be independent among individuals and to follow a normal distribution with mean zero and variances σ2

a and σ2b, respectively; the observation

error εi,j, was also assumed to be independent and normally distributed. We calculated variance components todetermine the relative strengths of within and among individual differences in inter-circuli spacing, and allowed for autocorrelation in inter-circuli spacing by considering an autoregressive (AR) model of order one in the autocorrelation structure. This provided a better fit to the data than a model without correlated serial errors. We run models incorporating the effect of year class strength at various time lags (-4 to +4) to account for the fact that competition experienced by migrants at sea may also be affected by earlier and later year classes. All analyses were performed on R 2.15.0 language (R Development Core Team 2012) using the nlme 3.1-103 package (Pinheiro et al. 2012). Results Scale reliability There was no significant distortion of scale radius due to the impression process (t29 = 0.547, P = 0.465), indicating that acetate impressions gave an accurate, unbiased representation of scale size. Repeatabilities of scale size were high,

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Figure 2. Temporal changes in scale growth (mm, mean ± 95 CI) of sea trout during the first year in freshwater (A-B) and during the first marine growing season (post-smolt growth, C-D ) in the rivers Ulla and Lerez.

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both for smolt scale length (α-Cronbach = 0.879) and for scale size attained at the end of the first freshwater growing season (α-Cronbach = 0.898). Figure 3. Fitted values of mixed effects model describing inter-circuli spacing during the first year in freshwater according to year of hatching.

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Scale radius and fork length were positively correlated (r = +0.747, P = 0.001), and the relationship was not different among rivers (F1,941 = 0.326, P = 0.568) allowing us to use scale measurements to reconstruct changes in body size regardless of river identity. Determinants of individual variation in freshwater growth Inspection of freshwater growth profiles, obtained by plotting circuli number against cumulative scale length (Figure 1), reveals considerable variation in growth slopes among individuals, as well as between rivers and years. Annual scale growth differed significantly among years, both in freshwater (R. Ulla F9,489 = 2.82, P = 0.005, Figure 2A; R. Lerez F11,452 = 7.15, P < 0.001, Figure 2B) and in the sea (R. Ulla F11,489 = 3.43, P < 0.001, Figure 2C; R. Lerez F11,452 = 1.89, P = 0.04, Figure 2D). The minimal adequate model of inter-circuli spacing in freshwater included all three main effects, i.e. circuli number, year class strength, and river identity (BIC= -94350). None of the interactions were significant, and these were removed from the model following Zuur et al. (2009). The inclusion of an autocorrelation structure, as well as of random intercepts and slopes, was found necessary to adequately describe the freshwater growth of sea trout. Inspection of parameter estimates (Table 1) and fitted values (Figure 3) indicates that there is considerable variation in the growth slope of individuals within the same cohort, and that early scale growth decreases rapidly from the first summer until the first freshwater winter. Freshwater growth differs significantly between the two neighbouring rivers, with sea trout from the R. Ulla growing faster (i.e. displaying wider inter-circuli spacing) than those from the R. Lerez. Determinants of individual variation in marine growth As with freshwater growth, the minimal adequate model of inter-circuli spacing during the first marine growing season

7

included the effects of circuli number, year class strength and river identity (BIC= -106635.4). The terms capturing variation in freshwater size, as well as all the interactions, were not significant and were removed. As with freshwater growth, the inclusion of random effects and a correlation structure was necessary to adequately describe marine growth of sea trout (Table 2). Inspection of fitted values during the first summer at sea displayed in all cases a positive slope, reflecting a period of rapid, accelerated growth (Figure 4). Parameter estimates indicated that sea trout from the R. Ulla grew faster in the sea (as they did in freshwater) than those from the R. Lerez. Figure 4. Fitted values of mixed effects model describing inter-circuli spacing during the first marine growing season (post smolt growth, PSG) according to year of smolting. For comparisons, circulus number one represents transition into the marine environment for all fish.

1997 1998 1999 2000 2001

2002 2003 2004 2005

2006 2007 2008 2009

0.025

0.030

0.035

0.040

0.025

0.030

0.035

0.040

0.025

0.030

0.035

0.040

0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40Circuli

Fitte

d Va

lues

Partition of variance components Analysis of variance components indicated that variation among individuals in freshwater inter-circuli spacing (R. Lerez 25%, R. Ulla 29%) was larger than within individual variation (R. Lerez 23%, R. Ulla 19%), although differences were small. In

contrast, variation in marine growth was much higher among individuals (R. Lerez 27%, R, Ulla 32%) than within individuals (R. Lerez 2%, R. Ulla 3%). Density-dependent growth The negative, statistically significant sign of the parameter estimates for year class strength on inter-circuli spacing indicates that parental abundance (and thus likely offspring abundance) had a negative effect on the subsequent growth of juveniles, though the density-dependent effect on growth was c. 2.5 times stronger in freshwater (Table 1, parameter estimate -6.31 x 10-6, P = 0.020) than at sea (Table 2, parameter estimate -2.55 x 10-6, P = 0.048). The absence of significant interaction terms suggests that the negative effect of density on growth was the same for both rivers. On the other hand, models of marine scale growth lagged at 1-4 years were not significant, with model fitting decreasing with increasing time-lags (BIC lag1= -96965.25, BIC lag 2= -82305.8, BIC lag3= -71133.14, BIC lag4= -63639.08) suggesting that there was little, if any, evidence for interference competition at sea among individuals of different smolt years. Discussion Our study suggests that growth of juvenile sea trout, a species exhibiting partial migrations (Wysujack et al. 2009; Acolas et al. 2012) is suppressed at high population densities, not only in freshwater, butto a lesser extent also in the marine environment. Under the assumption that scale size and inter-circuli spacing are both positively related to somatic growth – assumptions that are generally upheld by empirical evidence in salmonids (Marco-Rius et al. 2012) and other fishes (Cheung et al. 2007), we found that temporal fluctuations in year class strength had a marked effect on juvenile growth at two different life-history stages, and at two different spatial scales. Annual fluctuations in salmonid abundance are usually large (Nicola et al. 2008) and can be expected to have large effects on intra- and inter-cohort competition (Einum

8

et al. 2011), which should be manifested in changes in individual growth (Parra et al. 2011). Yet, density-dependent growth has been difficult to detect at the individual level in the wild because growth data derived from mark and recapture are often restricted to a few time events and tend to provide only a snapshot of growth performance (Vincenzi, Satterthwaite & Mangel 2008). In contrast, growth circuli continue to be deposited over the entire lives of many fishes, and once formed, remain unchanged (Cheung et al. 2007). These characteristics afford the fine resolution necessary to quantify individual variation in fish growth, and as our study shows, to test for density-dependent effects at the individual level. Selection can act strongly on salmonid body size (Garcia de Leaniz et al. 2007) and we found large differences in scale growth increments of sea trout from two neighbouring rivers, highlighting the marked effect that spatial heterogeneity and local conditions can have on salmonid growth (Foldvick, Finstad & Einum 2010). In general, density–dependent effects were stronger in freshwater than at sea, and also stronger in the river Lerez (with less accessible area and poorer juvenile growth) than in the much larger River Ulla. These results are consistent with resource competition being the chief reason for negative density-dependent effects on salmonid fitness (Finstad et al. 2009). Migratory salmonids typically move in small shoals when they enter the sea in order to minimize predation (Dutil & Coutu 1988) and are able to exploit a wider range of prey resources than in freshwater (Hansen & Quinn 1998), marked density-dependent effects are perhaps less likely to occur at sea. Density-dependent growth at sea has not been reported before for anadromous brown trout, but this may reflect the difficulty of detecting such a process in a coastal species with a relatively short marine phase, as well as the limited power of simple scale growth analysis (Marco-Rpus et al. 2012). Negative density-dependent marine growth appears to be relatively common among other migratory salmonids (e.g. Atlantic salmon - Hansen & Quinn 1998; coho salmon – Emlen et al.

1990;sockeye salmon - Martinson et al. 2008), though it is most readily apparent during the late marine phase (Ruggerone et al. 2006). Unlike in freshwater, where density-dependent growth is well explained by territorial behaviour and interference competition, similar underlying mechanisms at sea remain obscure (Snover, Watters & Mangel 2005). Seasonal migrations can result in high concentrations of sea trout close to shore as the species rarely moves more than 100 km offshore in this area (Caballero, Cobo & Gonzalez 2006). Productivity in these coastal waters is regulated by short, localized upwelling episodes that reappear with a frequency of 14 ± 4 days (Álvarez-Salgado et al. 2000) resulting in patchily distributed and temporally abundant prey that provide the conditions necessary for marine density-dependence effects to develop. On the other hand, we found no evidence for lagged effects on marine growth, suggesting that density-dependence at sea results chiefly from the effect of single smolt cohorts (i.e. smolts entering the sea on the same year) rather than from the effects of multiple year classes. Although our study did not consider the potential effect of other marine fish (including sea trout from other nearby populations, as well as other marine fishes), the two study populations occupy adjacent estuaries and are the largest in the area (Caballero, Cobo & Gonzalez 2006; Marco-Rius et al. 2012). It could also be argued that if marine growth of sea trout depended on the presence of other, unaccounted fish competitors, failure to include these would have likely introduced random noise, making it more difficult (not less) to detect density-dependent marine growth. Our analysis of variance components indicates that variation in inter-circuli spacing was larger between individuals than within-individuals, both in freshwater and at sea. This supports the contention that inter-circuli spacing is a good indicator of individual growth performance (Marco-Rius et al. 2012) and can be used to examine how individuals respond to density-dependence regulation. Migration has been viewed as a strategy to ‘escape’

9

from harsh conditions (Hebblewhite & Merrill 2009) which can protect offspring against density-dependence (Economou 1991). Salmonid alevins are thought to benefit from dispersal early in life through improved growth at the expense of increased risk of predation (Einum et al. 2011), and our study indicates that seaward migration may confer similar benefits as sea trout smolts appear to benefit from reduced density-dependence during the first marine growing season. This is consistent with the existence of marine compensatory growth, whereby individuals that grow poorly in freshwater are able to catch up later during their marine life (Marco-Rius et al. 2012), presumably because competition is weaker during the post-migratory than the pre-migratory phase (Snover, Watters & Mangel 2005). However, our results also indicate that sea trout do not escape completely from density-dependence constraints by migrating into the sea, and that their marine growth is still impacted by the presence of conspecifics, presumably due to competition for food (Peterman 1984). Recent models predict that density-dependence could help maintain partial migrations if, as our study of sea trout indicates, resident and migratory individuals are subjected to density-dependent forces of varying strength before and aftermigration (Taylor & Norris 2007). The findings of our study have implications for conservation and management because despite strong homing behaviour on this species, the existence of negative density-dependent growth at sea suggests that sea trout should not be managed on a river by river basis and that populations may be better conserved taking a wider, coastal perspective. Acknowledgements We thank Pilar Alvariño and Laura Cal for technical assistance and Sonia Consuegra for helpful comments on the manuscript. References Abramoff, M.D, Magalhães, P.J. & Ram, S.J.

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92!!


Insights for planning an effective stocking program in

anadromous brown trout (Salmo trutta)

1

Insights for planning an effective stocking program in anadromous brown trout (Salmo trutta) Francisco Marco-Rius, Graciela Sotelo, Pablo Caballero, Paloma Morán

Abstract: Brown trout is a salmonid species with a high socio-economic value related with recreational fishing. Because of that, stocking programs have been developed in many populations, although have focused on resident populations. In order to explore which factors promote that migratory behaviour when implementing stocking actions, 28 brown trout artificial crosses were carried out in a non-commercial hatchery, and the returning success of their offspring was further evaluated. Return rate was examined attending to: male phenotype (anadromous vs. resident), mean egg size, parents’ similarity at major histocompatibility complex (MHC) class II β-gene, and stocking procedure. At the end of the experiment, 35 of the captured returning adults (9.4%) belonged to 14 of those crosses. Return success shows significantly affected by parental MHC similarities, stocking procedure and male phenotype. Our results indicate that planting fertilized eggs in nursery areas of the river, together with the selection of anadromous males as brood stock and mate pairs with higher similarity at the MHC locus can be an appropriate option to increase the migratory part of trout populations. In addition, nursery areas can allow an important decrease in the cost per stocked individual, being 32 times less expensive than the cost per hatchery-reared individuals.

Introduction

Conservation of native populations is an important challenge for managers (Waples and Hendry 2008). For instance, many salmonid populations have declined dramatically during

the last century because of overexploitation (Almodovar and Nicola 2004; Saura et al. 2010), habitat degradation (Miranda et al. 2012), or climate change (Kennedy and Crozier

Received 11 February 2013. Accepted 13 May 2013. Paper handled by Associate Editor Alistair Coulthard. F. Marco-Rius1 and P. Morán. Universidad de Vigo, Departamento de Bioquímica, Genética e Inmunología, Vigo 36310, Spain. G. Sotelo. CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBio, Universidade do Porto, 4485-661 Vairão, Portugal. P.Caballero. Consellería de Medio Rural, Servizo de Conservación da Natureza, Xunta de Galicia, Pontevedra, Spain. 1Corresponding author (e-mail: [email protected]).

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2010). Therefore, different solutions have been proposed as habitats restoration (Anton et al. 2011) or population enhancing by supportive breading programs (Saura et al. 2006). In the planning of latter, the component of anadromy is never taken into account and a specific program for anadromous brown trout enhancement is not available for management. In this study, we propose the baseline for develop a program for anadromous populations based on selecting the brood stock, the use of different ages for stocking and the relationship with the returning rate after sea migration and the economic cost. Brown trout (Salmo trutta) is often subjected to stocking due to recreational fishing (Juanes et al. 2011). For this reason, captivity bred trout are released into rivers and lakes to enhance local populations (Jonsson and Jonsson 2011). Various authors have addressed pros and cons of this method (Fleming et al. 1997; Jonsson et al. 2003) and the results appear largely dependent on the parental stock used, where offspring success is reduced when domesticated trout are used (Moran et al. 1991; Martinez et al. 1993; Dahl et al. 2006). Moreover, hatchery environments often favour completely different traits than natural selection does in the wild (Rogell et al. 2012). One of the traits affected by hatchery environments is the component of anadromy of brown trout populations (Serrano et al. 2009). Brown trout is a partly migratory species, i.e. both migratory and resident individuals co-occur in the same population (Jonsson and Jonsson 1993). Migratory individuals return to their natal river (Jonsson and Jonsson 2012) for reproduction after spending one or more years in seawater, where they can attain up to ten times larger size at maturity than resident individuals do (Jonsson 1985). Furthermore, females migrate more than males (Milner et al.

2003), probably because female fitness is most directly related to body size (Jonsson & Jonsson 2011). However, the mechanisms controlling trout migrations are not fully understood, although it is thought that both genetic and environmental factors play important roles (Ferguson 2006; Giger et al. 2006). It has been reported that hatchery-reared trout are less migratory than wild conspecifics (Serrano et al. 2009). Thus, stocking may reduce the migratory predisposition of populations. However, supportive breeding and stocking are still important long-term conservation tools for sustaining harvestable populations (Saura et al. 2006). Stocking of hatchery fish is economically expensive. For example, in Atlantic salmon (Salmo salar) the cost varies from 0.022€ per eyed ova to 1.063€ per one-year-old smolt or 2.127€ per two-year-old smolt in UK (Aprahamian et al. 2003). Hatchery conditions for brown trout are approximately the same and the rearing cost will be equivalent. But still, supportive breeding is assumed necessary in rivers where Atlantic salmon are exterminated. In such cases, the brood stock should be taken from a neighbouring river with similar environmental conditions (Hansen et al. 2006). Iberian Peninsula represents the southern distribution limit of anadromous brown trout. There, many populations have declined due to dams’ construction (Ayllon et al. 2006; Juanes et al. 2011) with negative effects for sport angling while resident trout is still fairly common and exhibit high genetic variability (Campos et al. 2007). In such cases, supportive breading could be the only way to maintain or recover the populations present. Indeed, Atlantic salmon stocks have been restored in rivers where they became extinct in the 1990s (Hervella and Caballero 1999; Saura et al.

3

2006), reflecting the increased damage of anadromous populations. In order to provide a logical framework to develop a successful supportive breeding program for sea trout populations, different brown trout artificial crosses were performed in a non-commercial hatchery in northwest Spain. Only large migratory sea trout females were used , mainly because the high number of eggs that they produce compared to resident females (Jonsson and Jonsson1993). Although age and size at maturity or residency are partly inherited traits, some additional benefits (related with maternal effects) may be expected when using large-sized females. For example, eggs produced by larger females are larger than those produced by small-sized females, and fry from large eggs usually experience lower mortality (Einum and Fleming 1999). On the other hand, both migratory and resident males were included in the crosses. Under natural conditions, males compete for access to females during spawning and as a consequence, large males tend to breed with large females (Jacob et al. 2007). Secondly, in addition to these parental effects, it has been suggested that major histocompatibility complex (MHC) is subject to selection, and ultimately related to local adaptation, through different processes related with class I and II subfamilies. The role of MHC polymorphism in pathogen resistance and reproductive success has been tested in several vertebrates. For example, in rhesus macaques (Macaca mulatta), heterozygous sires in MCH class II showed better reproductive success than homozygous sires (Sauermann et al. 2001). Also, the survival of Chinook salmon (Oncorhynchus tshawytscha) was increased by heterozygosity of the MHC class IIB genes when infected by the haematopoietic necrosis virus (IHNV) (Arkush

Fig. 1. Rivers/streams used in the study: The brood stocks were captured in Tea and Deza, the eyed ova were stocked at Cabanelas and the hatchery-reared one-year old brown trout were stocked at Lerez.

Cabanelas

Lerez

Deza ´

kilometers

0 10 205

Galicia Spain

Tea

et al. 2002). Moreover, associations between certain MHC class II alleles and the bacterial infection (forunculosis) were found in Atlantic salmon, suggesting that different alleles are related with high resistance and low resistance to infection (Langefors et al. 2001). Balancing selection has been proposed as the most likely mechanism maintaining genetic variation within and among populations (reviewed in Bernatchez and Landry 2003) and we expect that the same holds for brown trout. In the present experiment we measured the return-rate of adult sea trout either (1) planted

4

Table 1. Number of returned adults captured by the trap located in river Lérez, between 2010 and 2011. It is reported the cross identity, the stocking type performed, the amino acid distances and the male phenotype used (‘A’, anadromous, and ‘R’, resident).

Number of returned adults

Cross number Stocking type AA distance Male

phenotype 1 1 Eyed ova 0.010 A 2 3 Eyed ova 0.169 R 1 4 1-year-old 0.161 R 1 5 1-year-old 0.161 R 6 6 Eyed ova 0.005 3 1-year-old A 2 7 1-year-old 0.030 A 1 8 Eyed ova 0.198 R 2 10 Eyed ova 0.165 R 1 12 Eyed ova 0.222 R 1 19 Eyed ova 0.156 A 3 20 Eyed ova 0.067 1 1-year-old A 1 24 Eyed ova 0.202 1 1-year-old A 5 27 Eyed ova 0.061 A 1 28 Eyed ova 0.156 A

as eggs in a small nursery tributary stream, or (2) released the fish as hatchery-reared one-year-old juveniles in the main river. We assessed three parameters: (a) male phenotype (as paternal effect), (b) eggs size (as maternal effect) and (c) MHC similarities.

Materials and methods

Experimental design In December 2007, adult trout were caught before the spawning season in an upstream trap located in the low part of Tea and Deza streams (northwest Spain; Fig.1). These streams support two neighbour populations where the anadromous populations abundance have been maintained stable during the last years (Hervella and Caballero 1999). Both streams have an upstream trap to provide samples. A

total of 18 anadromous females, nine anadromous males and 17 resident males were selected for the experiment (Table S1). Each trout was individually identified with a passive integrated transponder (PIT) tag and a small piece of a pelvic fin was clipped and stored in ethanol for subsequent genetic analysis. A total of 28 artificial pair-crosses were done at the hatchery resulting in a total of 8 full-sib families and 20 half-sib families. Eleven crosses involved migratory males, and 17 crosses involved resident males. Egg size was estimated by taking 30 random eggs from each cross and a calliper (0.1mm of precision) was used for the measurement. Then, the average size of the eggs was calculated. Finally, eggs were reared during 30 days in the hatchery using a recirculation system between 5° and 9° C.

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Table 2. GLM parameter estimates, using a Poisson distribution for number of returned adults between 2010 and 2011. The reference group of the factor is in parenthesis.In February 2008, 35,000 eyed eggs were transported and planted intra-gravel with the help of a plastic tube as described in Palm et al. (2009), at Cabanelas stream, a small tributary of the river Lérez (main river; Northwest Spain, Fig. 1).

Estimate Std. Error z value Pr(> |z|)

Intercept -6.2515 5.8832 -1.06 0.2880

MHC -8.3593 2.6422 -3.16 0.0016

Stock Type (stock 1+) -0.9808 0.3909 -2.51 0.0121

Phenotype (Resident) -1.1221 0.5119 -2.19 0.0284

Egg size 0.1429 0.1099 1.30 0.1936

The remaining 78,000 eggs were reared in the hatchery until spring 2009, resulting in 23,109 one-year-old individuals. Due to space problems in the hatchery, fry from different crosses were mixed in five tanks of 5,000 litres subjected to the same water temperature and daily food quantity. However, this procedure did not allow monitoring the survival achieved by each single cross. These fish, after adipose fin clipping (performed to further distinguish them from planted individuals), were released in March 2009 in the middle course of the main river, very close to the mouth of Cabanelas stream (Fig. 1). We released one-year-old hatchery trout. According to Jokikokko and Jutila (2004), this maximizes smolt production. All sea trout returning between January 2010 and December 2011 were monitored in a trap located 4 km upstream of the river mouth. Each returning adult was measured, weighted and marked with a PIT tag in order to identify possible recaptures of the same individual in subsequent years. The presence/absence of adipose fin was recorded; and a small piece of

a pelvic fin was clipped for the genetic analysis. MHC sequencing and MHC diversity analysis To estimate the MHC diversity of the experimental crosses, a 298-301 (253-256 bp excluding primers) bp fragment of the exon 2 of a MHC class II B gene was amplified for parental fish using the primers CL007 (5´-GATCTGTATTATGTTTTCCTTCCAG-3´) and AL100 (5´-CACCTGTCTTGTCCAGTA TG-3´) (Olsén et al. 1998). PCR reaction was carried out in a total volume of 20 µl, containing 1 µl of genomic DNA, 2 µl of reaction buffer (10× buffer), 0.5 mM dNTP, 2.5 mM MgCl2, 0.35 µM of each primer and 1 U of Taq DNA polymerase (Bioline). Cycling conditions consisted of 35 cycles of 30 s denaturation at 95 ºC, 30 s annealing at 57 ºC and 45 s extension at 72 ºC, followed by a final 7 min extension at 72 ºC. PCR products were cloned using pGEM®-T Vector System (Promega). Twenty white colonies per cloned product were amplified by PCR using primers T7 and M13.

6

Fig. 2. Relationship between returning success (adults captured between 2010 and 2011) and MHC parental similarity (based on amino acid sequences, see main text). The solid line represents the trend line fitted by GLM and the dash line is a loess line.

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Resulting PCR fragments were run in SSCP gels as described in Campos et al. (2006) to identify homozygous/heterozygous individuals. For each identified allelic variant, different PCR products were cleaned and sequenced using a dRhodamine terminator cycle sequencing kit and an automated sequencer ABI PRISM 3100. The MHC diversity of each cross was calculated, following Landry et al. (2001), as the mean pairwise distance between the four

parental alleles considering the four allelic combinations (i.e., genotypes) that could be carried by the offspring, in both nucleotide and amino acid sequences. The distances were computed as uncorrected p-distances using Mega 5.05 (Tamura et al., 2011). However, only one of the sequences is presented in the results (the amino acid sequences) due to the high correlation between the sequences (cor=0.993, t12=27.89, P<0.0001).

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Microsatellites genotyping and parentage assignment To assign returning fish to parental/ experimental crosses both, parents and returning fish, were genotyped using eight microsatellites loci: Str591INRA, Str85 (Presa and Guyomard, 1996), Str60 (Estoup et al. 1993), Satr-UBA (Grimholt et al. 2002), SSsp2201 (Patterson et al. 2004), Ssa85, Ssa197 (O’Reilly et al. 1996) and SsaD157 (King et al. 2005). Microsatellites were amplified by PCR (polymerase chain reaction) in three multiplex reactions: Str60, Str591INRA and Str85 in multiplex I, Ssa85, Ssa197 and Satr-UBA in multiplex II, and SSsp2201 and SsaD157 in multiplex III. PCR reactions were carried out in a final volume of 20 μL, containing 2 μL of extracted genomic DNA, 0.2 μl of Taq polymerase (Green Taq polymerase 5U/μl), 1 μl of MgCl2 50 mM, 1 μl of dNTPs Mix 10mM, and 10mM primer volumes of 0.35 μl (SSsp2210, SsaD157), 0.5 μl (Str60), 0.6 μl (Str85) and 1 μl (Str591INRA, Ssa85, Ssa197, Satr-UBA). Each reaction was carried out for 35 cycles, with the following conditions: for 20 s at 95°C; 20 s at 55°C, and 20 s at 72°C, for multiplex I; 20 s at 95°C; 20 s at 58°C, and 20 s at 72°C, for multiplex II; and 50 s at 95°C; 50 s at 58°C, and 80 s at 72°C, for multiplex III. PCR products were prepared into a final volume of 20 μL. The mix, together with Rox 400, was denatured at 95 °C for 5 min and immediately put on ice. Allele size of fluorescently labelled fragments was measured in a 3100 ABI PRISM (Applied Biosystems, Foster City, CA, U.S.A.) automated sequencer followed by analysis with GeneMapper 3.7 Software (Applied Biosystems). Parentage assignment was done using the software PASOS (Duchesne et al. 2005). This program combines an approach based on

parental pair likelihoods with a filtering procedure. The allocation of a descendant in PASOS is based on the search for the most likely pair among all potential pairs of known parents. Putative parent–offspring pairs sharing alleles at the eight loci, or having as maximum one mismatch in one locus, were assigned to parent pairs. To evaluate cross diversity at neutral markers, microsatellite similarity of each cross was calculated as an average correlation coefficient (Rij) between allele sizes for homologous gene copies from two individuals (Streiff et al. 1998), given that, for microsatellite loci evolving under a stepwise mutation model, differences in allele size contain more evolutionary information than just allele identity. This index was computed using SPAGeDi v. 1.4 (Hardy and Vekemans 2002). Statistical analysis A generalized linear model (GLM) with a Poisson distribution was used in order to explore the differences in the number of returning adults (R) captured in the upstream trap: R = M+E+D+T; where M was the male phenotype used in the cross (resident or migratory/anadromous), E was the mean egg size of artificial crosses, D was the MHC diversity of the parental cross estimated from amino acid MHC sequences, and T was the stocking type (planted eggs or released as juveniles) used in the recaptured individual. All interactions were included in the saturated model and model selection was done according Akaike information criteria (AIC). We used the residual deviance to perform a goodness of fit test for the overall model. The Pearson correlation coefficient was used to evaluate the association between cross similarities at MHC class IIB locus and cross

8

diversity at neutral markers to evaluate whether or not values of similarities at MHC locus between parents are caused by similarities in genetic background and hence, biasing the MHC similarities values. Finally, length and weight of the returning trout were compared attending to the stocking procedure used to explore benefits or costs over the final body size in hatchery and wild recaptured individuals. Data were analyzed using the software R 2.15.1 (R Development Core Team 2012). Results The final alignment of the exon 2 of the MHC class II β-gene for the 44 individuals involved in the 28 artificial crosses consisted of 256 bp, and resulted in 63 alleles. They were defined by 99 polymorphic sites, including a 3 bp deletion (positions 189-191) present in 33 out of the 63 alleles. Only 12 of the isolated alleles were observed in more than one individual while the remaining 51 were singletons. Among the analysed parents, 12 were homozygous and 32 were heterozygous. When translated into protein sequences, the alignment rendered 59 alleles, 32 comprising 84 amino acids and 27, 85 (due to the mentioned deletion), with a total of 51 polymorphic positions observed. Sixteen alleles were present in more than one individual and 43 were singletons, and among the 44 parents, 14 were homozygous and 30, heterozygous. All the parental trout were successfully genotyped for the eight microsatellites loci. No genotyping errors due to null alleles, large allele dropout or stutter bands were observed. Microsatellite loci were highly polymorphic, and the number of alleles per locus varied from 6 at Str591INRA to 45 at SSsp2201 and the

numbers of alleles did not differ between both neighbouring streams used as brood stock. The 28 experimental crosses worked out, and the eggs produced by each female varied approximately between 3,000 and 13,000. Mortality during the first 30 days of rearing conditions varied between 5% and 7%, and it occurred mostly during the first ten days. Between 2 and 4 years after the commencement of the experiment, a total of 351 sea trout adults were recaptured in the upstream trap of the main river. All the fish were successfully genotyped for the eight microsatellites loci and assigned unambiguously to parental crosses. The percentage of analysed individuals that were allocated to experimental crosses was 9.4% (n=33); corresponding to 14 out of 28 crosses (see table 1). Of these 33 individuals, 24 (72.7 %) had been stocked as planted eyed ova, while only 9 had been released as one-year-olds, meaning that hatchery-reared fish contributed only up to the 27.3% of returned adults. Moreover, parental analysis showed that 25 individuals belonged to crosses involving anadromous males, and eight to crosses involving resident males. As well, crosses with more similar MHC alleles showed the highest number of returned individuals, for both stocking procedures (Figure 2). Crosses number 6, 20 and 27 turn to be the most successful in the return rate: they accounted for 15 out of the 33 returning adults (45.5%). Cross 6 was the pair with more similar male-female MHC alleles (p-distance of 0.05), cross 27 was the fourth (p-distance of 0.061) and cross 20 was the fifth in this ranking (p-distance of 0.067) among all performed at the hatchery. The three crosses were performed by use of a single, although different, sea-run male..

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Fig.3. Box plots of fork length and weight of returned adults (at capture), according to the type of stocking used: planted as eyed ova versus released as one-year-old individuals. No significant differences were observed between stocking types for any trait/measure.

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leng

th (m

m)

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The GLM model that best fitted the data was: R= M+E+D+T (AIC= 105.83) with no significant interaction present (Table 2). The goodness of fit test showed that this model fitted reasonably well because the chi-squared test was not statistically significant (Res. deviance= 54.86, df=51, P= 0.33). No significant effect of the average egg size was observed on adult return; while MHC parental dissimilarities, stocking type and male phenotype showed significant influences on the returning rate (Table 2). Among parents distance at the MHC locus, evaluated in terms of amino acid sequences, was the most

important factor, followed by stocking procedure and male phenotype (Table 2). Correlation coefficient between similarities at MHC locus and microsatellites was not significant (cor=0.147, t13=0.538, P=0.599). This result means that differences associated to MHC dissimilarities are independent from similarities in genetic background and hence, similarities in parental MHC locus reflect that they can be used as specific factor to explore differences in returning rate. Finally, differences in length or mass among the individuals belonging to the experiment were not significantly different regarding the stocking method used (F1,30=1.07, P=0.31 and

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F1,30=0.77, P=0.39 respectively), which suggests that adult length and mass was not improved by rearing conditions at the hatchery (Fig. 3). Discussion We have evaluated several factors that can be manipulated at the initial stages of a brown trout enhancing program in order to maximise the migratory success of released brown trout individuals. The factors showing an influence on returning success were in order of importance: similarities at MHC class B locus between parents, stocking procedure and male phenotype. On the other hand, no relationship was observed regarding maternal effects (i.e., egg size). Genetic background is an important factor determining a restoration achievement in brown trout populations, as has been previously tested in resident populations (Lepori et al. 2005; Araguas et al. 2009). However, due to difficulties in seaward migration and return rate monitoring, it is difficult to evaluate the genetic background of anadromous populations. In this study we have observed that male selection can determine the achievement or failure of a restoration program together with MHC dissimilarities and stocking procedure. Beyond genetic background, these factors are specific characteristics of the individuals that can be easily manipulated at the hatchery in order to produce more suitable crosses to enhance anadromous populations. However, allele introgression has to be taken into account, trying to conserve the genetic structure as far as possible. Response to climate warming can disrupt the adaptation of natural populations, especially at the southern limit (Horreo et al. 2011) and the use on non-native brood stock in conservation programs cannot be used over existent native populations

(Almodovar et al. 2001). Here we have used two neighbouring with no differences in allelic number. Indeed, spatial scale of local adaptation in brown trout have been tested using microsatellites markers and outliers test for selection, suggesting that differences in adaptation cannot be understood at the level of individual population (Meier et al. 2011). In addition, studies over five microsatellites in Atlantic salmon in the north west of Spain indicated that allelic number, allelic richness and observed and expected heterozygosities did not differ significantly between rivers in recently analysed populations (Saura et al. 2006), suggesting that introgression effects may be small and if existent, an obstacle for the offspring derived from the experiment due to the lower adaptation to the local environment (reviewed in Garcia de Leaniz et al. 2007). Maternal effect First, size at migration represents a threshold that individuals have to reach in order to complete smoltification and survive to marine conditions (Økland et al. 1993). Anadromous brown trout smolt typically at age-2 in Spain, and possible maternal effects may be diluted by this time or in the subsequent sea-sojourn (Heath and Blouw 1998).. Thus, benefits related with egg size (Einum and Fleming 1999) could not be detected in relation to the number of returned adults, despite that maternal effects are crucial in the survival in early stages of life (i.e. emerged fry or alevins; Heath and Blouw 1998; Kamler 2005). Male phenotype When anadromous males are used in artificial crosses performed at the hatchery (together with anadromous females), the possibility that offspring return to the river to spawn increases,

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representing in this study the 68.8% of the total returned individuals. As pointed out by previous rearing experiments in brown trout, proportion of migratory offspring was higher with anadromous parents than with resident parents (Skrochowska 1969), suggesting that there are some genetic factors in offspring born from both anadromous male and female which may produce (a) more susceptible individuals to migrate and/or (b) individuals with better adaptations to smoltification and sea life conditions. More specifically, many experiments have shown that there are genetic factors inherent to stocks that have a primary influence on migration or on the spatial marine distribution in salmonids (Kallio-Nyberg et al. 1999; Kallio-Nyberg et al. 2002), suggesting that differences in migration success among crosses could be related with differences in tendencies to migrate of different stocks. In our study, due to the lack of a downstream trap for sampling the individuals that started the migration, we cannot distinguish if differences in migratory success among families are because the corresponding offspring remain in the river (do not migrate) or because they experience higher mortality rates at sea. In both cases, the final result is a lower proportion of migrants that come back to the river to spawn. Also Kalio-Nyberg et al. (2010) used resident trout with success when restoring a population of sea trout.. Thus, although anadromous individuals are the most appropriate to be used in order to increase the migratory population of brown trout, also resident individuals can be used when anadromous individuals are exterminated. This suggests that life history variation is influenced by complex interactions between genetic and environmental factors in brown trout (Ferguson 2006), and not only the genetic factors will determine the migratory

behaviour (Jonsson and Jonsson 1993; Forseth et al. 1999). This becomes essential in hatchery management because the potential anadromous brood stock from wild populations can become extinct or near extinction due to different processes as contaminations (Kallio-Nyberg et al. 2010) or dams construction (Ayllon et al. 2006; Juanes et al. 2011). In these cases, resident individuals can be used as a first step in the recovery of anadromous populations. In addition, sea trout males represent a lower proportion of migrants, male:female sex ratio is 1:2.2 in the Atlantic Spanish coast (Caballero et al. 2006; Caballero et al. 2012) and 2:3 in the North Sea area (Jonsson and Jonsson 1993), representing an additional difficulty to find the anadromous males for the crosses. In these cases, resident males represent a feasible option. MHC parental similarities Performing artificial crosses taking into account parental similarities at MHC class II B can help to enhance sea trout populations by increasing the offspring’s survivorship at both freshwater and seawater stages. Differences at MCH class II B showed that offspring born from the most similar parents exhibited the best return rate to the river. Although no studies have reported positive relation between MHC class II B similarities and benefits in freshwater or seawater, MHC class I studies performed in Atlantic salmon showed that (i) divergence in MHC class I was positively related with uninfected fish after sea migration (Consuegra and Garcia de Leaniz 2008) or (ii) MHC class I polymorphism was positive associated with resistance to bacterial and viral diseases (Grimholt et al. 2003). However, a recent study carried out in brown trout has observed that balancing selection acts on variation at MHC class I in wild populations

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suggesting that not only the most dissimilar crosses are favoured by selection but also the most similar (O’Farrell et al. 2012). According to our results and the balancing selection acting over brown trout MHC locus, there is reasonable evidence that return rate of sea trout is mediated in part by similarities at parental MHC locus. In the future, although difficult, it would be desirable to test dissimilarities at MHC loci in resident and migratory full-sibs in order to explore if individuals carrying the most similar allele combinations tend to migrate to the sea more than those with most dissimilar ones. Stocking procedure Stocking procedure had a significant effect over the number of returned adults: 24 returning individuals (6.9 % of total return captures) were recovered from a stocking effort of 35,000 eyed ova. If we take into account the area used for the experiment (0.61 km2), it represents a density of 0.163 one-year-old ind m-2 in the tributary. Monitoring programs implemented by the Spanish government in river Lérez have estimated that mean brown trout density is around 0.285 ind m-2 in a total watershed of 449 km2 (Hervella and Caballero 1999). Thus, our stocking effort of 35000 eggs performed in the 0.13% of the total watershed obtained the 6.9% of total returning adults, while juveniles’ density was lower than registered in the main river. These results suggest that the problem imposed by domestication on anadromy of hatchery-reared individuals can be partially overcome when eyed ova are planted in the river instead of individuals being maintained in the hatchery for later release. Therefore, selecting brood stock from the native river and using tributaries or small channels as nurseries is suggested here as one of the best solutions due to several

reasons: (i) because a low stocking effort can result in a relatively high number of sea trout returning adults as observed in this experiment (75% of the total returning adults that belonged to the experiment), (ii) we avoided genetic impacts of hatcheries in wild populations that affects the fitness of hatchery-reared individuals (iii) we avoid direct and indirect effects in wild and hatchery populations when they interact (reviewed in Naish et al. 2008; Seamons et al. 2012) and (iv) we avoid the sea mortality associated to distance from releasing site of brown trout smolts (Jonsson and Jonsson 2012). In addition, as shown in Aprahamian et al. (2003), the difference in economic cost between individuals reared until the first year and the stoked eggs is 32 times more expensive per unit, representing a total saving of 23,800€ at the same time that both returning rates and diversity in the crosses experimented by planted individuals are higher. Thus, the expected advantage of “helping” the fish at the hatchery to increase size and promote survival in the wild is not a prudent measure for brown trout conservation or for increasing the number of migratory individuals and in addition, it results in a non-economically viable management plan Here we have reported that by manipulating parental MHC dissimilarities, stocking procedure and male phenotype we can obtain significant results in the context of returning rate and they are easily manipulated at the hatchery. Moreover, stocking programs have to be combined with sustainable management according to the FAO-EIFAC Code of Practice for Recreational Fisheries (EIFAC 2008). Water quality (Griffiths et al. 2011), habitat conditions (Anton et al. 2011) combined with a regulated fishing effort is critical for maintaining the brown trout populations.

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Acknowledgments We wish to thank two anonymous referees and the associate editor for useful comments on previous versions of this manuscript. Funding for this work was provided by grants from Ministerio de Ciencia y Tecnología (CGL2007-60572 and CGL2010- 14964), and Fondos FEDER (PGIDIT03PXIC30102PN; Grupos de Referencia Competitiva, 2010/80). Francisco Marco-Rius was supported by a doctoral scholarship from the Spanish Government (BES-2008-001973). References Almodóvar, A., and Nicola, G. G. 2004.

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110!!


Environmental induced methylation changes associated with

seawater adaptation in brown trout

Environmental induced methylation changes associated with seawateradaptation in brown trout

Paloma Morán a,⁎, Francisco Marco-Rius a, Manuel Megías b, Lara Covelo-Soto a, Andrés Pérez-Figueroa a

a Dpto. Bioquímica, Xenética e Inmunoloxía, Facultade de Bioloxía, Universidade de Vigo, Vigo 36310, Spainb Dpto. Bioloxía Funcional, Facultade de Bioloxía, Universidade de Vigo, Vigo 36310, Spain

a b s t r a c ta r t i c l e i n f o

Article history:Received 21 September 2012Received in revised form 30 January 2013Accepted 3 February 2013Available online 12 February 2013

Keywords:Salmo truttaEpigeneticDietMSAPSmoltificationSalt

Migratory trout (sea trout) and sedentary trout (freshwater trout) coexist and interbreed. However, themechanisms underlying the development of the migrant morphotype are still unclear. At one point parr–smolt transformation is initiated and, as a result, juvenile trout are ready to leave the river and migrate tothe sea. The smoltification process has been linked to various factors such as body size, growth rate andthe physiological state of the fish. In addition, the process is also strongly influenced by environmental factorssuch as year, seasonality, water temperature and flow rate. For example, hatchery environment can depressthe natural parr–smolt transformation and consequently, the success of the seawater migration of rearedtrout from these hatchery programmes might be adversely affected. We have investigated whether changesin DNA methylation, by means of MSAP (methylation-sensitive amplified polymorphism), could be involvedin anadromy. We identified dramatic differences in genome-wide methylation patterns between hatcheryreared and seawater brown trout. Furthermore, we demonstrated that salt enriched diets can triggershort-term genome-wide methylation changes in hatchery reared trout. However, these changes only lastedfor a short period of time. Determining the duration of this effect could result in increased survival ofhatchery-reared trout in seawater when fed on salt-enriched diets. Altogether, these results suggest thatsalt-induced alterations in DNA methylation patterns could play an important role in enabling fish acclima-tion to seawater conditions, potentially with important economic consequences for fish farming.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Two different morphotypes of brown trout (Salmo trutta L.) can befound in rivers from the European Atlantic coast and Baltic Sea: themigratory trout (sea trout) and the resident trout (freshwatertrout). Although both life-history forms present morphological, de-mographic and ecological differences (Bagliniere et al., 2000), theycoexist and interbreed (Ruzzante et al., 2001). Juveniles from bothmorphotypes are indistinguishable. To date, genetic differences be-tween sea trout and sedentary brown trout inhabiting the sameriver have not been reported (Charles et al., 2005; Cross et al., 1992;Hindar et al., 1991; Pettersson et al., 2001). Brown trout has little im-portance in commercial fisheries but an extraordinary value for recre-ational fisheries and hereby for the tourist industry. Consequently,many hatcheries are now focusing on raising stocks from wild parentfish. Under hatchery conditions some stocks of brown trout undergo adomestication process and can be successfully reared in captivity.However, domestication can result in lower fitness when individualsare returned back to the wild. The contribution of hatchery reared

trout to natural populations has been repeatedly shown to be rathersmall (reviewed by Hansen, 2002). Moreover, the artificial environ-ment in which the anadromous brown trout has been reared canalso depress the natural parr–smolt transformation and adversely af-fect the success of seawater migration and the survival of the fish inthe long-term (Sundell et al., 1998). This could represent an impor-tant failure of these expensive practices, especially when breedingmigratory sea trout populations represent the main goal of theenhancement programme. As an illustrative example, the cost of theAtlantic salmon breeding expenditure relative to the number ofcaptured salmons in a Spanish river has been estimated to be 4000Euros per captured individual (Horreo et al., 2012).

In natural conditions, the two trout morphotypes (i.e. migrant andresident) become well established during the second year of their livesthanks to the ability of some juveniles to undergo smoltification(Økland et al., 1993). This process involves important physiologicaland morphological adaptations to seawater, thus preparing the troutfor the ocean life prior to its downstreammigration. Changes in their ex-ternal morphology include variations in body shape and coloration pat-terns (Björnsson et al., 2011), those referring to physiological featuresinvolve increased salinity tolerance, olfactory sensitivity and changesin its metabolic and growth rates, as well as alterations in haemoglobinand visual pigment concentrations (McCormick et al., 1998).

Aquaculture 392-395 (2013) 77–83

⁎ Corresponding author. Tel.: +34 986813899; fax: +34 986812556.E-mail address: [email protected] (P. Morán).

0044-8486/$ – see front matter © 2013 Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.aquaculture.2013.02.006

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What natural selection mediated mechanism does underline themigration decision? Trout smoltification has been linked to variousinterrelated threshold factors such as body size, growth rate andphysiological conditions that could activate migratory pathways(Acolas et al., 2012; Jonsson and Jonsson, 1993). In addition, thesmoltification process is also strongly influenced by environmentalfactors, such as year, season, water temperature and flow rate(Jensen et al., 2012). The smoltification process involves high individ-ual costs but also high benefits in reproductive performance (Jonssonand Jonsson, 1997, 1998).

Increasing salinity tolerance requires differentiation and activationof the epithelial transport and the synthesis of new transport proteins(McCormick, 2001). Changes in Na+/K+-ATPase, Na+/K+/2Cl! co-transporter and in the distribution of the mitochondrial-rich cells(MRCs) have been recorded in the gills of the freshwater salmon(Salmo salar) when compared to the seawater morphotype (Hiroi andMcCormick, 2007). This is the result of MRCs being distributed on theprimary filaments and secondary lamellae of the freshwater salmonbut completely absent in those of the seawater salmon (Hiroi andMcCormick, 2007). In concordance with physiological changes, differ-ences in gene expression of several genes such as transaldolase 1, con-stitutive heat-shock protein HSC70-1 and endozepine have also beendescribed between migratory and sedentary brown trout belonging todifferent populations (Giger et al., 2008). Similar findings have alsobeen reported in populations of Atlantic salmon (Seear et al., 2010).

Different experiments have demonstrated the genetic basis ofsome components of anadromy. In rainbow trout (Le Bras et al.,2011) and Arctic charr (Norman et al., 2011), several QTLs (quantita-tive trait loci) on three linkage groups have been associated with fishperformance in the seawater environment. However, the seawatermorphotype can be externally induced and various features of theseawater gill phenotype could be induced by feeding freshwater rain-bow trout with a salt enriched diet (Perry et al., 2006). In addition, it iswell known that hatchery conditions substantially reduce smoltification(Aarestrup et al., 2000) and seawater migration compared to naturalconditions (Marco-Ríus et al., unpublished results). Thus, genetic andenvironmental factors underlie life-history strategies, which have ledto the consideration of anadromy in brown trout as a threshold quanti-tative trait (Ferguson, 2007).

Epigenetics can help in understanding the smoltification process inthe brown trout. Smoltification is a reversible process that can be stimu-lated by external conditions, for example, full-sib individualsmight showdifferent behaviours. Thus, we hypothesised that methylation might bepart of the acclimation mechanisms of the brown trout to the seawaterconditions, since themethylated state is usually associatedwith gene ex-pression inactivation and conversely, gene activation is associated withdemethylation (reviewed by Mazzio and Soliman, 2012).

Environmental stimuli are known to alter cytosine methylationthroughout the genome at specific loci. For example, Navarro-Martínet al. (2011) have shown that methylation of the gonadal aromatasepromoter is involved in temperature-dependent sex ratios in sea bass.In addition, emerging evidences strongly suggest that certain dietarybioactive food components can change gene expression via alterationsin DNA methylation and histone modifications (reviewed by Tammenet al., in press). In humans, it has been suggested that the bioactive nu-tritional component (also called epigenetic diet) could be incorporatedinto our regular dietary regimen and therapeutically used for medicalpurposes (Hardy and Tollefsbol, 2011).

In this study, we investigated whether changes in DNA methyla-tion might be involved in anadromy and whether the level of DNAmethylation might change in response to osmotic stresses inducedby environmental stimuli such as a salt enriched diet. Understandingexternal stimuli effects will allow for better fish management, and inturn, increasing or decreasing the smoltification rates.

To achieve this, we designed a hatchery experiment whereone-year-old trout were fed a salt enriched diet for a period from 2

to 28 days. Since gill is one of the most sensitive tissues responding tothe transition between freshwater and the marine environment, weemployed the methylation-sensitive amplified polymorphism (MSAP)methodology that allows detecting themethylation state of a particularrecognition sequence. Thus, any methylation changes in the gill tissuesin response to different diets and/or salinity concentrations could bemeasured. Physiological changes promoted by a salt enriched dietwere monitored in the gill tissue by inmunocytochemistry analysisusing the Na+/K+-ATPase antibody. This was done at different criticalphases of the experiment. In order to test the seawater proficiency ofthe hatchery trout fed with a salt enriched diet, these fish togetherwith a control group were transferred to seawater and the survivalrates compared.

The final goal of the study was to gain further knowledge aboutthe time from the hatchery until the onset of the migration to thesea, and to try to reduce mortality at this critical period by rearingtrout under the most optimal conditions.

2. Materials and methods

2.1. Experimental design

The experimental design included two stages. The first one aimedto explore the differences in methylation induced by a salt enricheddiet during one month. One-year-old hatchery reared trout wereused in this experiment. One hundred full-sibling individuals werebred in a circular fibreglass tank at the Carballedo hatchery facilities(Northwest Spain) and fed daily with commercial trout pellets. Twoweeks later six specimens were separated representing the freshwa-ter control group (FW-control). The remaining trout were fed usinga diet supplemented with 11% NaCl as described in Perry et al.(2006). Thereafter, six individuals were sampled 2, 4, 6, 8, 10, 14, 21and 28 days after the beginning of the treatment. Samples were la-belled as follows: FW-2, FW-4 FW-6, FW-8, FW-10, FW-14, FW-21,and FW-28. No mortality was recorded during the whole experimen-tal period. All fish involved in the experiment were euthanized usingMS-222 (Sigma) and the gill tissue removed. Those individuals whichwere not euthanized during the experiment were returned to theirnormal diet and no mortalities were recorded after one week ofdaily checks. Gills were fixed in ethanol for DNA extraction. Forimmunocytochemistry, gills were fixed in 4% paraformaldehyde inphosphate buffer 0.1 M pH 7.4 (PB) for two days at 4 °C and thenstored in PB.

The second part of the experiment intended to explore the differ-ences in seawater survival in relation to the diet. Following the sameprocedures described above, 100 fish of the same stock and age wereused. Fish were separated in two tanks (50 individuals per tank) andreared under the same environmental conditions. In one tank, troutwere fed with commercial trout pellets whereas in the other theywere fed using a diet supplemented with 11% NaCl as previously de-scribed. After 4 days, the adipose fin of those trout fed with commer-cial trout pellets was removed for identification purposes. Then, thetwo groups of trout were transported to the O Grove aquarium tobe transferred to the same seawater environment. Fish were accli-mated to salty water in two phases, starting from 0 ppt to 15 pptduring 24 h followed by a second increase from 15 ppt to 37 ppt byfilling the tank with natural sea water. During 24 days, the tank waschecked in the morning and mortality was recorded. Survival differ-ences were calculated using a mixed effect linear model with a Poissondistribution (Zuur et al., 2009) in the lme4 package (Pinheiro and Bates,2009) implemented in R 2.15.1 (R Development Core Team, 2012)where treatment (fed with salt or not) was a fixed factor and time(days of survival) a random effect.

Forty individuals (20 of each group), reared in seawater for a periodof 10 to 12 days, were analysed further using MSAP (group labelled asGROVE).

78 P. Morán et al. / Aquaculture 392-395 (2013) 77–83

2.2. DNA isolation and MSAP genotyping

DNA was extracted from gill tissue using the NucleoSpin® TissueKit (Macherey-Nagel). DNA quality was verified by electrophoresison 1% agarose gels. After DNA quantification using a Nanodrop 1000spectrophotometer (Thermo Fisher Scientific), samples were normal-ized to 100 ng μl!1.

Genomic cytosine methylation in CCGG sites of different sampleswere analysed using MSAP techniques as described in Reyna-Lópezet al. (1997) and Xu et al. (2000). This methodology is based on theuse of the isoschizomers HpaII andMspI which recognise the same se-quence (5!-CCGG) but differ in their sensitivity to DNA methylation.

For each individual, 50 ng of DNA were independently digestedand ligated with both EcoRI/MspI and EcoRI/HpaII enzyme combina-tions (New England Biolabs). The reaction was performed in a finalvolume of 11 μl containing 5 U EcoRI, 1 U MspI (or HpaII), 5 pmolEcoRI adaptor, 50 pmol HpaI adaptor and 0.4 U of T4 DNA ligase(Roche). The mixture was incubated at 37 °C for a period of 2 h.

Preselective PCR reactions were then performed using 4 μl of 1:10ligation dilution in 20 μl volumes containing 2.5 mM of MgCl2,187.5 μM of each dNTP, 20 pmol of EcoRI-A and HpaII/MspI-Tpreselective primers and 1 U of Taq polymerase (Bioline) in 1! PCRbuffer (Bioline). PCR conditions for preselective PCR were as follows:72 °C for 2 min, 20 cycles of 94 °C for 20 s, 56 °C for 30 s, 72 °C for2 min, and a final step of 60 °C for 30 min. Selective PCR reactionswere performed in 20 μl using 1 μl of 1:200 preselective PCR dilution.Two primer combinations (EcoRI-AAG and HpaII/MspI-TC; EcoRI-ACTand HpaII/MspI-TC) were used. Primer sequences are available inMorán and Pérez-Figueroa (2011). PCR contains 2.5 mM of MgCl2,187.5 μM of each dNTP, 8.3 pmol of each selective primer and 1 Uof Taq polymerase in 1! PCR buffer. Cycling conditions for selectivePCR were 94 °C for 2 min, 10 cycles of 94 °C for 20 s, 66 °C for 30 s,and 72 °C for 2 min, followed by 20 cycles of 94 °C for 20 s, 56 °Cfor 30 s and 72 °C for 2 min, ending with 60 °C for 30 min.

Individual PCR products were analysed along with 500 ROX sizestandards (Applied Biosystems) in an ABI Prism 3130 Genetic Ana-lyzer (Applied Biosystems). Fragment analysis was performed usingGeneMapper v.3.7 software (Applied Biosystems). DNA fragmentsless than 100 bp in length, longer than 500 bp or less than 70 RFU(Relative Fluorescent Units) were excluded from the analysis dueto their low levels of reproducibility.

2.3. Data analyses

MSAP profiles, pooled from both primer combinations, wereanalysed using the R package msap (Pérez-Figueroa, in press. http://msap.r-forge.r-project.org). Every fragment was scored as follows:present in both EcoRI-HpaII and EcoRI-MspI products (1/1), denotinga non-methylated state; present only in either EcoRI-HpaII (1/0) orEcoRI-MspI (0/1) products, corresponding to a methylated state; orabsent from both EcoRI-HpaII and EcoRI-MspI products (0/0), whichwe considered as an hyper-methylation of the target. Because the in-vestigated hatchery pool shows high methylation rates (patterns 1/0and 0/1) and low genetic diversity, it seems reasonable to assume thatthe 0/0 pattern would be the result of hyper-methylation of the restrict-ed targets and not due to genetic differences (i.e. mutation). Individualfragments (loci)were, therefore, classified into “methylation-susceptibleloci” (MSL) if the observed proportion ofmethylated scores (1/0, 0/1 and0/0) exceeded a 5%, and “methylation-susceptible fragments” if themethylated state was the dominant marker (1 for the methylated stateand 0 for the non-methylated state). Only those fragments showingpolymorphism, with at least two occurrences of each state, were usedfor subsequent analyses (Herrera and Bazaga, 2010).

Analysis in msap followed a band-based strategy (Bonin et al.,2007). The amount of overall epigenetic variation was estimatedusing the Shannon diversity index (S). Epigenetic differentiation

among groups was assessed by means of principal coordinates analy-sis (PCoA) followed by analyses of molecular variance (AMOVA;Excoffier et al., 1992).

2.4. Inmunocytochemistry

Paraformaldehyde fixed gills were cryoprotected in 30% sucrosedissolved in PB for 24 h, embedded in OCT compound (Tissue-Tek),and rapidly frozen at !80 °C. Thereafter 20 μm thin sections wereobtained using a cryostat (Microm HM505 E) at!20 °C and collectedon superfrost slides (Menzel GmbH & Co.). This was followed by astandard immunocytochemistry. Briefly, sections were rinsed in aPB saline solution (PBS), then immersed in a blocking solutioncontaining 1% bovine serum albumin for 1 h and finally, incubatedovernight with a monoclonal anti-Na+/K+-ATPase alpha-1 subunitantibody raised against chicken Na, K-ATPase (1:100; alpha6F, Devel-opmental Studies Hybridoma Bank; Perry et al., 2006) at roomtemperature. Then, sections were washed with PBS and incubatedin a biotinylated goat anti-mouse antibody (1:100; Vector Laborato-ries) for 1 h. Sections were rinsed again in PBS and incubated in theavidin–biotin complex (ABC; 1:100; Vector Laboratories) for 1 h.Peroxidase activity was developed with 0.5% 3–3!-diaminobenzidinetetrahydrochloride (SIGMA) and 0.01% H202. The reaction was stoppedin PBS and sections were subsequently dehydrated and cover slipped.

Imnunoreactive cells on the primary filaments and secondary la-mellas were individually counted from sagittal sections of the trailingedge of gill filament. Twenty paired secondary lamellas and their cor-responding primary filaments were also counted in three differentareas of the gills of three fishes from each group: Control, FW-4,FW-8, FW-21, FW-28 and GROVE.

A mixed effect linear model (Zuur et al., 2009) was used in orderto explore the differences in density of immunoreactive cells. The lo-cation (primary filaments and secondary lamellas) and fish groupwere treated as fixed factors while effects of fish and gill areas weretreated as random effects.

3. Results

3.1. Seawater survival

Trout mortality was monitored daily after the first phase of accli-mation was completed. Mortality during the first 24 h (from 0 pptto 15 ppt) was significantly higher in the control group (9 out of 50trout) than in the FW-4 group (3 out of 50 trout) (Z14=15.25,pb0.001). Mortality progressively decreased over the first 15 daysbut remained higher in the control group than in the treatmentgroup(Fig. 1). Due to an unusual and unexpected increase in seawatertemperature, all fish died between 17 and 24 days.

3.2. Methylation analysis

The two primer combinations used in the MSAP analysis produceda total of 879 loci, with 875 of them being classified as MSL by themsap package. The frequency of polymorphic MSL was 47% and theShannon's diversity index was 0.425±0.180 (mean±SE).

The frequency of the different methylation states (expressed as apercentage) in the target sequence (hemimethylation, complete meth-ylation of internal cytosine, full methylation and non-methylated) ob-served in the different experimental groups is shown in Table 1.Important divergences (up to 10%) were observed in the case of thehemimethylation of the target sequence whereas subtle differences(around 5%) were observed in the other categories. This pattern sug-gests that during the first days of feeding on a salt enriched diet(FW-2, FW-4 and FW-6) there is an increase in both hemimethylationand internal methylation when compared to the full methylation

79P. Morán et al. / Aquaculture 392-395 (2013) 77–83

http://msap.r-forge.r-project.org

http://msap.r-forge.r-project.org

(partial demethylation) or unmethylated states (de novomethylation).In a later stage (FW-21, Fw-28), the normal pattern (control) isrestored.

Differences in the genome-wide methylation rates were staticallysignificant between all tested groups (AMOVA; !ST=0.380, pb0.001).Pairwise analyses (Table 2) revealed significant differences betweenhatchery trout groups, including control, and all the groups of troutfed with a salt enriched diet, themost different group those trout trans-ferred to seawater conditions (GROVE). Results also reflected a gradualchange in methylation patterns, with differences between groups be-coming less apparent when samples were close in time. Fig. 2 showsthe first and second principal coordinates resulting from PCoA whichindicates the epigenetic variation and the degree of differentiationamong groups. The first coordinate, accounting for 27.8% of the totalvariance, identified three distinct clusters: (i) control, FW-14, FW-21and FW-28, (ii) FW-2, FW-4 FW-6, FW-8, FW-10 and (iii) GROVEgroup. Furthermore, themost differentiated group is FW-4 and the clos-est is FW-10, suggesting a progressive and reversible methylationchange over time. This is also supported by the slight differences ob-served between the control group and FW-14, FW-21 and FW-28.

3.3. Immunocytochemistry

The existence of Na+/K+-ATPase imnunoreactivity in large cuboi-dal cells located in the primary filaments and secondary lamellas ofthe gills had been previously identified (Perry et al., 2006). Differ-ences in the number of positive cells distribution between the control

group and GROVE were remarkable (Fig. 3A,B). In hatchery trout, im-munoreactive cells were scattered throughout the primary filamentsand secondary lamellas, whereas in GROVE trout most immunoreac-tive cells were located in the primary filaments, with the differencesbeing statistically significant (Z54=2.70, pb0.01). The number ofpositive cells found in the primary filaments of the GROVE groupwas concentrated in the base of the lamellas, whereas in the hatcherytrout they were more dispersed. In addition, immunoreactive intensi-ty appeared to be higher in the GROVE trout, although this was notproperly quantified. Cell counting revealed temporal changes in theimmunoreactive cell distribution (Fig. 3C), with differences becomingsignificant in seawater after seven days (Z6=!3.27, p=0.016 andZ6=!4.37, p=0.005 respectively). It was also observed that thenumber of immunoreactive cells decreased during the first week oftreatment, in the primary filament and in the lamellas of both FW-4and FW-8 groups. However, the number of positive cells increasedprogressively in FW-14 and FW-28 groups until they nearly reachedthose of the control group.

4. Discussion

A growing number of evidences demonstrate the importance of epi-genetic factors in the modulation of phenotypic plasticity (reviewed byJohnson and Tricker, 2010). Most of the published literature focuses onDNAmethylation andmany studies use genome-widemethods such asMSAP in order to detectmethylation changes after exposure to differentenvironmental conditions (Cao et al., 2011, 2012; Da et al., 2012; Tan,2010; Wang et al., 2011). These experiments reveal important gaps inour understanding of the effects of diet contaminants, drought, etc. onthe individual performance.

During the seawater transition, trout undergo physiological transfor-mations involved in osmoregulation, lipidmetabolism, oxygen transportand body colour and shape,withmany genes involved in these processes(McCormick, 2001). Accordingly, we have observed dramatic differencesin genome-wide methylation patterns between hatchery-reared andseawater transferred trout, suggesting that gene activation/deactivationduring smoltification may be controlled, at least partially, by epigeneticmechanisms. Because theMSAP analysis only detects a subset of the epi-genetic variation caused by C-methylation in the CCGGmotif, our resultsmight have underestimated the magnitude of the epigenetic changes;however, they strongly suggest an important role of methylation in thesmoltification process.

Environmental conditions during early development have provedto alter the epigenetic patterns of fish embryos (reviewed by Faulkand Dolinoy, 2011), and many epigenetic changes with potential evo-lutionary implications can be inherited (Bossdorf et al., 2008). How-ever, methylation could affect the individual entire lifetime or belimited to certain stages of its life cycle because this process can re-spond very rapidly to environmental changes, allowing for increasingfish resistance to environmental stress (Angers et al., 2010). There-fore, knowing the time interval in which epigenetic variations mighttake place, would permit to design new breeding strategies inwhich environmental stimuli for inducing or repressing gene expres-sion can be applied.

By manipulating the fish food intake we have shown that a saltenriched diet can trigger genome-widemethylation changes, suggestingthat there could be a link between an external stimulus, smoltification,

Fig. 1. Survival rate of the control (normal diet) and treatment groups (salt-enricheddiet) in seawater. Individuals were acclimatised during the first day by mixing fresh-water and seawater to obtain between 0 ppt and 15 ppt seawater. After this, freshwa-ter was gradually replaced to obtain 37 ppt at the end of the second day.

Table 1Frequency (%) of the different states of methylation at the target sequence.

Target state (band pattern) Control FW-2 FW-4 FW-6 FW-8 FW-10 FW-14 FW-21 FW-28 GROVE

Unmethylated (HPA+/MSP+) 14.3 10.7 8.0 10.1 11.1 10.7 15.7 13.1 13.2 9.5Hemimethylated (HPA+/MSP!) 8.6 13.2 12.9 15.5 10.8 11.0 8.7 9.1 6.9 12.9Internal C methylation (HPA!/MSP+) 15.2 18.7 20.5 15.5 17.9 18.2 15.0 14.2 16.4 14.7Full methylation (HPA!/MSP!) 61.8 57.5 58.6 58.9 60.2 60.1 60.5 63.5 63.6 62.8


and epigenetics. In this study, epigenetic divergence between the con-trol group and the salt-fed trout increased sharply after two days. Thelargest differences were observed after 4 days of exposure to a saltydiet and progressively decreased during the following days. Our results(see Fig. 2) provide evidence that reversibility was an important charac-teristic of the genomic regions that experienced salt-induced epigeneticchanges. Surprisingly, after two weeks on the salt-enriched dietappeared to have no effect on the globalmethylation pattern, suggestingthat the epigenetic change induced by the salt was reversible. This find-ing is also supported by the observed changes in the distribution andnumber of Na+/K+-ATPase immunoreactive cells in the gill tissues. Im-portantly, greater methylation changes were preceded by larger differ-ences (FW-8) in Na+/K+-ATPase immunoreactive cells.

Although methylation changes were induced by a salt-enricheddiet, the methylation patterns in the freshwater reared trout are notidentical to those experienced by the seawater reared ones (seeFig. 2). However, our study provides clear evidence for salt intakeleading to physiological and morphological changes in freshwaterfish that could make them to resemble to the seawater morphotype,although only for a short period of time.

The seawater-transfer experiment performed at the O Groveaquarium showed that the survival rate of the salt-fed trout was

significantly higher than that of the control group during the firstdays. Although rearing conditions were not optimal, our results sup-port the idea of salt intake being able to supply the fish with the phys-iological tools required for a better adaptation to seawater. Overall,our experiment could also provide a more plausible explanation forthe hatchery practice of feeding salmonids with a salt enriched dietbefore releasing them into the river or the sea (Zaugg et al., 1983).

Li and Leatherland (2012) reviewed the reasons why epigenomicprogramming could have implications in aquaculture. Among severalfactors, they suggested that artificial fertilization and handling prac-tices produce changes in the endocrine system that could inducechanges in the epigenome, leading to a reduction in fitness. Thisidea is supported by the fact that salmonid fish raised in hatcheriesdo not often perform well in the wild (Araki et al., 2007). However,differences in the genome methylation between wild and hatcheryof certain species such as steelhead have not been found (Blouin etal., 2010). We, therefore, suggest that the tissue selected for the anal-ysis was probably not the most informative one, given that there aregreat differences in the methylation patterns between tissues (Moránand Pérez-Figueroa, 2011).

Our results also suggest that salt-induced alterations could play animportant role in enabling fish acclimation to seawater conditions.This process could facilitate the seawater migration of the hatchery-reared trout when released into the river as part of enhancingpopulation programmes, and potentially enhance the aquacultureproduction of the diadromous fish. Our results open new researchavenues to explore how changes in other external factors such asrearing temperature, day–night cycles or different diets, could also af-fect the methylation patterns and increase both fish harvesting andwelfare. However, more detailed studies are required since methyla-tion changes might only be temporary affected by environmentalchanges and potentially misinterpreted.

5. Conclusions

Different patterns of methylation have been observed for trout liv-ing in seawater when compared to those living in freshwater,suggesting that methylation plays a key role in the smoltification pro-cess. Salt intakes in the hatchery reared trout promote temporarygenome-wide methylation changes that make them more similar toseawater reared ones. This result is supported by the distribution ofthe Na+/K+-ATPase immunoreactivity cells in the gill tissue. Feedhatchery-reared trout with a salt-enriched diet increases survival inseawater. Our study reveals how induced epigenetic changes can besuccessfully applied in fish harvesting.

Acknowledgments

We wish to thank Pilar Alvariño, Nieves Santamaría and Ma. JesúsIglesias-Briones for their technical assistance. The hatchery experi-ment was carried out at the Carballedo hatchery (Xunta de Galicia).

Table 2Pairwise AMOVAs between all pairs of the experimental groups.

Control FW-2 FW-4 FW-6 FW-8 FW-10 FW-14 FW-21 FW-28 GROVE

Control 0.0022 0.0019 0.0019 0.0022 0.0020 0.0022 0.0043 0.0023 b0.0001FW-2 0.37 0.0331 0.0189 0.0071 0.0020 0.0024 0.0020 0.0023 b0.0001FW-4 0.39 0.09 0.0415 0.0124 0.0077 0.0025 0.0020 0.0020 b0.0001FW-6 0.36 0.06 0.06 0.3400 0.0173 0.0017 0.0020 0.0020 b0.0001FW-8 0.34 0.10 0.14 0.01 0.0153 0.0025 0.0017 0.0021 b0.0001FW-10 0.26 0.15 0.19 0.07 0.06 0.0021 0.0025 0.0022 b0.000FW-14 0.08 0.39 0.45 0.41 0.37 0.32 0.0023 0.0021 b0.0001FW-21 0.08 0.32 0.35 0.34 0.32 0.27 0.09 0.4429 b0.0001FW-28 0.10 0.39 0.44 0.40 0.38 0.32 0.08 0.00 b0.0001GROVE 0.54 0.41 0.31 0.35 0.42 0.43 0.59 0.50 0.54

!ST below the diagonal. p-values above the diagonal. Bolded values pb0.01.

Fig. 2. Results from Principal Coordinates Analysis (PCoA) for the epigenetic differenti-ation between the experimental groups. The first two coordinates (C1 and C2) aredisplayed with the indication of the percentage of variance explained in brackets.Scores represent individual samples. Labels indicate the centroids of each group. Ellip-ses represent the dispersion associated to each value. The long axis of the ellipse showsthe direction of maximum dispersion and the short axis, the direction of minimumdispersion.


Seawater experiments were done at the O Grove aquarium. The au-thors are also very grateful to Bluedisplay S.A. for allowing us theuse of the aquarium for our experiment. In particular, we would liketo thank the individual contributions of Ester Alonso for assistingus with trout handling and that of Pablo Caballero for obtaining thenecessary licences to carry out this experiment.

This work has been funded by grants from the Ministerio deCiencia y Tecnología (CGL2010-14964), and Fondos FEDER(PGIDIT03PXIC30102PN; Grupos de Referencia Competitiva, 2010/80,Xunta de Galicia).

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http://dx.doi.org/10.1111/j.1467-2979.2012.00486.x

118!!


FACTOR DE IMPACTO Y CALIDAD DE LAS PUBLICACIONES

119!!


FACTOR DE IMPACTO Y CALIDAD DE LAS PUBLICACIONES

El factor de impacto de una revista académica es una medida que refleja el

número medio de citas de artículos durante un año en particular o durante un

periodo concreto. Frecuentemente es usado como una aproximación de la

importancia relativa de la revista en su campo. Revistas con factor de impacto

superior se considerarán más importantes que las que lo tienen más bajo.

El cálculo para el año 2012 de una revista X se realiza de la siguiente forma:

A = Citas totales de la revista X en 2012

B = Citas en 2012 de artículos de la revista X publicados en el período 2010-11

(subconjunto de A)

C = Número de artículos publicados en la revista X durante el período 2010-11

D = B/C = Factor de impacto de 2012

Los trabajos incluidos en esta tesis doctoral se han publicado o están

aceptados en las siguientes revistas:

• PLoS ONE

• Aquaculture

• Canadian Journal of Fisheries and Aquatic Sciences

• Ecology and Evolution

120!!


Los datos más relevantes de las revistas se detallan a continuación:

• PLoS ONE: eISSN: 1932-6203

Revista electrónica de acceso abierto que funciona como una asociación entre

su personal interno, asesores internacionales y consejos de redacción. La

revista es editada mediante “Public Library Service” desde el año 2006 y su

país de publicación es Estados Unidos. La revista está incluida en el SCI

dentro de la categoría: Biología, en la que se sitúa, atendiendo al factor de

impacto, la 12ª de un total de 85 revistas. Se sitúa en el primer cuartil. Su

índice de impacto en 2011 fue 4.092 y su factor de impacto en los últimos cinco

años fue 4.537. En esta revista se han publicado dos artículos.

• Aquaculture: ISSN: 0044-8486

Revista internacional para la investigación en agua dulce y marina. Interesada

en la explotación, mejora y manejo de los recursos vivos acuáticos. La revista

es editada por “Elsevier Science BV” desde el año 1972 y su país de

publicación es Holanda. La revista está incluida en el SCI dentro de las

categorías: Pesquerías, en la que se sitúa, atendiendo al factor de impacto, la

11ª de un total de 50 revistas y Biología Marina y Agua dulce, en la que se sitúa

la 30ª de 97 revistas. Se sitúa en el primer y segundo cuartil respectivamente.

Su índice de impacto en 2011 fue 2.041 y su factor de impacto en los últimos

cinco años fue 2.696. En esta revista se ha publicado un artículo.

121!!


• Canadian Journal of Fisheries and Aquatic Sciences:

ISSN: 0706-652X

Revista internacional que publica perspectivas, discusiones, artículos y

comunicaciones rápidas relacionadas con investigaciones actuales en células,

organismos, poblaciones, ecosistemas y otros procesos que afecten a los

sistemas acuáticos. La revista es editada por “National Research Council of

Canada” desde el año 1901 y su país de publicación es Canada. La revista

está incluida en el SCI dentro de las categorías: Pesquerías, en la que se sitúa,

atendiendo al factor de impacto, la 6ª de un total de 50 revistas y Biología

Marina y Agua dulce, en la que se sitúa la 21ª de 97 revistas. Se sitúa en el

primer cuartil en ambos casos. Su índice de impacto en 2011 fue 2.213 y su

factor de impacto en los últimos cinco años fue 2.632. En esta revista se ha

publicado un artículo.

• Ecology and Evolution: ISSN 2045-7758

Revista internacional publicada por primera vez en 2011. EL ISI la ha

catalogado dentro de Contenidos Actuales / Agricultura y Biología y Ciencias

Ambientales. Ecology and Evolution recibirá su primer índice de impacto en

2013. La revista es editada por la “British Ecological Society” y publica bajo

licencia Creative Commons. En esta revista hay un articulo aceptado.

122!!


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