BERNARDETE CRONOBIOLOGIA DE COPING STYLES NA … · AURATA): COMPREENSÃO DA VARIABILIDADE...

Universidade de Aveiro

2016

Departamento de Biologia

BERNARDETE LOPES RODRIGUES

CRONOBIOLOGIA DE COPING STYLES NA DOURADA (S. AURATA): COMPREENSÃO DA VARIABILIDADE INDIVIDUAL NOS RITMOS BIOLÓGICOS CHRONOBIOLOGY IN COPING STYLES OF GILTHEAD SEABREAM (S. AURATA): UNDERSTANDING INDIVIDUAL VARIATION IN BIOLOGICAL RHYTHMS

DECLARAÇÃO

Declaro que este relatório é integralmente da minha autoria, estando

devidamente referenciadas as fontes e obras consultadas, bem como

identificadas de modo claro as citações dessas obras. Não contém, por isso,

qualquer tipo de plágio quer de textos publicados, qualquer que seja o meio

dessa publicação, incluindo meios eletrónicos, quer de trabalhos académicos.

Universidade de Aveiro

2016

Departamento de Biologia

BERNARDETE LOPES RODRIGUES

CRONOBIOLOGIA DE COPING STYLES NA DOURADA (S. AURATA): COMPREENSÃO DA VARIABILIDADE INDIVIDUAL NOS RITMOS BIOLÓGICOS CHRONOBIOLOGY IN COPING STYLES OF GILTHEAD SEABREAM (S. AURATA): UNDERSTANDING INDIVIDUAL VARIATION IN BIOLOGICAL RHYTHMS

Dissertação apresentada à Universidade de Aveiro para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Biologia Aplicada, realizada sob a orientação científica do Professor Doutor João Serôdio do Departamento de biologia da Universidade de Aveiro e da Doutora Catarina C. V. Oliveira, investigadora pós doutoral no Centro de Ciências do Mar.

Apoio financeiro da Comissão Europeia no âmbito do 7º programa quadro – projecto COPEWELL (FP7-KBBE-2010-4, contrato nº 265957)

o júri

presidente Prof. Doutora Maria Adelaide de Pinho Almeida professora auxiliar com agregação do Departamento de Biologia da Universidade do Aveiro

Doutora Catarina C. V. Oliveira investigadora pós doutoral do CCMAR - Centro de Ciências do Mar, Universidade do Algarve

Doutor Ricardo Calado investigador principal do CESAM - Centro de Estudos do Ambiente e do Mar, Universidade de Aveiro

agradecimentos

Gostaria de expressar os meus sinceros agradecimentos a todos os que

contribuíram, directa ou indirectamente, para a realização desta tese.

Tenho a agradecer, antes de mais, ao Aquagroup – CCMAR, por me terem

recebido e por todo o apoio profissional. Quero agradecer especialmente à

team Ramalhete, em particular ao João Reis e Cristóvão, mas não

esquecendo todos os meus outros colegas: Ana, Cátia, Xana, André, Safia,

Dani, Juan e todos os outros que não conseguiria mencionar aqui, que muito

contribuíram para o desenvolvimento deste trabalho e para o meu

desenvolvimento profissional.

Quero agradecer à minha família por todo o apoio ao longo destes anos.

Tenho também que expressar a minha profunda gratidão a todos os que, ao

longo destes anos, nunca desistiram comigo: aos meus queridos amigos

Cosmin, Dani, Guilherme & companhia, Diana, Inês, Magda, Zuhâl, Liliane e a

todos aqueles que comigo foram caminhando.

Não posso deixar de agradecer todo o apoio e compreensão do Prof. João

Serôdio.

Por último, quero ainda exprimir a minha eterna gratidão à Doutora Catarina

Oliveira pela oportunidade de integrar a sua equipa. Agradeço com carinho

todo o seu apoio e orientação que contribuíram de forma fundamental para o

meu crescimento profissional. Sem a sua ajuda e compreensão, esta tese não

teria sido realizada.

palavras-chave

Teleóstio, ritmos diários e circadianos, actividade locomotora, zeitgeber, fotoperíodo, características comportamentais.

resumo

Os ritmos diários e circadianos têm sido amplamente estudados em peixes

teleósteos, sendo o ciclo diário luz-escuridão considerado um dos

sincronizadores biológicos mais importantes. Neste trabalho, apresenta-se a

mais completa descrição, até à data, da influência deste ciclo nos ritmos

diários e circadianos de atividade locomotora em dourada.

Com o objetivo de determinar de que forma os coping styles contribui para a

variabilidade obtida em muitos estudos cronobiológicos, monitorizaram-se os

ritmos diários de atividade locomotora em 3 grupos de douradas com coping

styles opostos: destemidos (Bold), tímidos (Shy) e intermédios (Intermediate).

Foram também testados 2 grupos controlo: um com uma mistura dos 3 coping

styles (Control), e outro com coping styles desconhecidos (Naïve).

Foram observadas diferenças claras entre os padrões comportamentais dos

diferentes coping styles de dourada. Numa primeira experiência, quando

mantidos sob um ciclo padrão de escuridão-luz (DL), as douradas

demonstraram uma clara ritmicidade diária, com prevalência de actividade

diurna. Quando expostas a uma mudança de 12 h no fotoperíodo (LD), tanto

as douradas Bold como as Shy rapidamente se ressincronizaram com o novo

fotoperíodo, enquanto que as Intermediate se ressincronizaram gradualmente

até uma completa sincronização ao novo ciclo LD. Numa segunda experiência,

quando os peixes foram sujeitos a condições de escuridão constante (DD), os

grupos Bold, Intermediate e ambos os controlos exibiram uma ritmicidade

circadiana na actividade locomotora. Curiosamente, os peixes Intermediate

demonstraram um ritmo de atividade em curso livre com uma periodicidade de

23:22 h, enquanto o grupo Shy mostrou uma completa ausência de

ritmicidade.

Tendo em consideração os resultados anteriores, os ritmos diários de atividade

em dourada parecem ser controlados endogenamente pelo sistema circadiano,

e fortemente moduladas pela luz: o ciclo luz-escuridão parece ser o

sincronizador mais potente dos ritmos diários de atividade nesta espécie. A

consistência dos padrões comportamentais observada em cada coping style

sugere que este possa realmente ser um fator de variabilidade inter-individual

na adaptabilidade a condições ambientais. Este trabalho, ao promover uma

sincronização ideal entre os ritmos dos peixes e seu ambiente de cultura, irá

contribuir para o bem-estar animal em aquacultura.

keywords

Teleost, daily and circadian rhythms, locomotor activity, zeitgeber, photoperiod, behavioural traits.

abstract

Diel and circadian rhythms have been extensively studied in teleost fish, with

the light-dark cycle being considered one of the most important synchronizers

of biological daily rhythms. This work presents the most comprehensive

description of the influence of the light-dark cycle in diel and circadian

locomotor activity rhythms for gilthead seabream to date.

In order to determine to which extent coping styles are contributing to the

variability reported in numerous chronobiological studies, daily locomotor

activity rhythms were investigated in 3 groups of seabream presenting opposite

coping styles: Bold, Shy, and Intermediate. Two other groups were also tested

as controls: a control group with mixed coping styles (Control), and another

with unknown coping styles (Naïve).

Conspicuous differences in behavioural patterns amongst seabream presenting

opposite coping styles were observed. In a first experiment, when initially

reared under a standard dark/light cycle (DL), seabream displayed an overt

daily rhythmicity with prevalent diurnal activity. When fish were subsequently

exposed to a 12 h photoperiod shift (LD), both Bold and Shy, as well as

controls, rapidly resynchronized to the new photophase whereas a gradual

resynchronization was observed for Intermediate fish before a complete

entrainment to the new LD cycle. In a second experiment, Bold, Intermediate,

and control groups exhibited circadian rhythmicity in locomotor activity when

reared under constant conditions (DD). Curiously, Intermediate fish displayed a

distinctive free-running activity rhythm of 23:22 h, whereas Shy seabream,

conversely, showed complete arrhythmicity.

Taken altogether, these observations suggest that activity rhythms in gilthead

seabream seem to be endogenously driven by a circadian system, and strongly

modulated by light: light-dark cycle seemed to be the most important

synchronizer of the observed diel rhythms. Consistent behavioural patterns of

opposing seabream coping styles observed in the present work indicate that

different coping styles might explain differences in adaptability to environmental

cues. This work will further benefit the state of welfare in aquaculture by

promoting an optimal synchronization between fish rhythms and their culture

environment.

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Table of contents

1. Introduction .................................................................................................................................. 1

2. Objectives .................................................................................................................................... 10

3. Material and Methods .................................................................................................................. 11

3.1. Ethics statement .................................................................................................................. 11

3.2. Experimental animals, housing and feeding ....................................................................... 11

3.3. Coping styles’ screening ..................................................................................................... 12

3.4. Experimental design and procedures ................................................................................. 12

3.4.1. Locomotor activity assessment .............................................................................. 12

3.4.2. Experiment I: Daily activity rhythms of divergent coping styles and coping

abilities towards photoperiod shifts .................................................................................. 13

3.4.3. Experiment II: Circadian activity rhythms of divergent coping styles in

gilthead seabream ........................................................................................................... 14

3.5. Data Analysis ...................................................................................................................... 16

4. Results ......................................................................................................................................... 18

4.1. Experiment I: Daily activity rhythms of divergent coping styles and coping abilities

towards photoperiod shifts ......................................................................................................... 18

4.2. Experiment II: Circadian activity rhythms of divergent coping styles in gilthead

seabream ................................................................................................................................... 24

5. Discussion ................................................................................................................................... 30

5.1. Daily activity rhythms of divergent coping styles and coping abilities towards

photoperiod shifts ....................................................................................................................... 30

5.2. Circadian activity rhythms of divergent coping styles in gilthead seabream ....................... 33

6. Final Remarks ............................................................................................................................. 37

7. References .................................................................................................................................. 39

8. Appendices .................................................................................................................................. 44

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List of figures

Figure 1. Representation of the circadian system ........................................................................... 4

Figure 2. Gilthead seabream ........................................................................................................... 8

Figure 3. Average temperature (ºC) and DO (%) throughout experiment I ..................................... 14

Figure 4. Average temperature (ºC) and DO (%) throughout experiment II .................................... 15

Figure 5. Representative actograms and respective mean waveforms of gilthead seabream

locomotor activity rhythms in experiment I ...................................................................................... 19

Figure 6. Average daily vs nightly activity of gilthead seabream in experiment I ............................ 20

Figure 7. Representative actograms of gilthead seabream locomotor activity rhythms,

onsets, offsets, and respective acrophases in experiment I ........................................................... 21

Figure 8. Representative actograms and respective chi-square periodograms of gilthead

seabream locomotor activity rhythms in experiment I ..................................................................... 22

Figure 9. Representative actograms and respective mean waveforms of gilthead seabream

locomotor activity rhythms in experiment II ..................................................................................... 25

Figure 10. Average daily vs nightly activity of gilthead seabream in experiment II ......................... 26

Figure 11. Representative actograms of gilthead seabream locomotor activity rhythms,

onsets, offsets, and respective acrophases in experiment II .......................................................... 27

Figure 12. Representative actograms and respective chi-square periodograms of gilthead

seabream locomotor activity rhythms in experiment II .................................................................... 28

Chronobiology in coping styles of gilthead seabream (S. aurata)

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1. Introduction

Overview

Biological rhythms are, undoubtedly, one of the most ubiquitous phenomena found in

nature. Spanning from one cycle per millisecond to one cycle per several years, not only

biological rhythms have been observed in an array of biological systems (at molecular,

cellular, whole-organism, or population scales), they have also been observed in a

multiplicity of living organisms ranging from prokaryotes to eukaryotes (Aschoff, 1981;

Dvornyk et al., 2003). Moreover, the survival of living beings crucially relies on the

temporal coordination of internal biological rhythms with exogenous environmental cycles

(Panda et al., 2002).

Cyclical changes of environmental factors, resultant of Earth’s perpetual rotations and

revolutions, have imposed a temporal structure in biological systems, driving the evolution

of rhythmic timing in virtually every living organism. In order to adapt to such a challenging

environment, organisms have thusly developed biological clocks, which control biological

rhythms, providing them the ability to keep time and anticipate relatively periodic changes

(Hut & Beersma, 2011). Likewise, the development of oscillating physiological and

behavioural mechanisms enable organisms to predict and, consequently, prepare for

relatively regular environmental fluctuations (Merrow et al., 2005), and contribute to the

optimization of the underlying biological processes.

With the daily light cycle being the most dramatic and immediate environmental change,

circadian biological rhythms are the most conspicuous rhythms observed in animals. The

term, coined by Franz Halberg (from Latin circa = about and dies = day), refers to partly

endogenous rhythms that recur in approximately 24 hours intervals. And, as a result of

evolutionary pressures, nearly all taxa have developed circadian timing systems that show

persistent oscillations for many of the molecular processes (Hut & Beersma, 2011).

Circadian rhythms are inherent and pervade in living systems, becoming fundamental

features of their organization. Such is their importance, that if deranged, an organism will

be impaired (Pittendrigh, 1960). Therefore, it is not surprising that they are the main object

of study in many chronobiological experimental works. Nevertheless, in chronobiology

such subject does not exist without controversy. Reportedly great variability in animal

biological rhythms has been observed in a number of studies, suggesting a degree of

behavioural plasticity interrelated to individual responses to challenges (Reebs 2002;

Øverli et al., 2007).


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Chronobiology

Although rhythmic phenomena have been empirically acknowledged and reported in living

organisms since ancient times, only recently the study of biological rhythms has emerged

as a scientific discipline known as Chronobiology. Experimental studies conducted during

the 1960’s by researchers such as Aschoff, Hamner and Takimoto, and Pittendrigh laid

the fundamental scientific foundations for the establishment of chronobiology as a

legitimate field of study (Reinberg & Smolensky, 1983). Furthermore, the development of

chronobiology as a discipline (Daan, 2010) has closely paralleled the advent of

exponential technological progress and consequent development of novel and improved

research methodologies.

Within the past few years, progress in understanding how biological clocks work in an

array of organisms has been exponential, culminating in an eruption of data that has

largely disproven the assumptions and permanently changed the face of the field (e.g.

Dunlap, 1999). Far from its early definition (see Halberg et al., 1977), chronobiology is,

nowadays, a comprehensive research field that studies rhythms across multiple

organizational levels of biological systems. In a strict sense, chronobiology, addresses the

underlying mechanisms of the biological endogenous timekeeping systems and its

entrainment by external time cues. Conversely, in its broadest sense, it comprehends all

research areas centring on biological rhythms, from the molecular basis to the influence

on physiology and behaviour of whole organisms and populations. As a result,

chronobiology is itself an interdisciplinary science.

Biological rhythms: Daily vs Circadian

The day-night geophysical cycle is, perhaps, the most evident and conspicuous cycle on

Earth, and it seems to fundamentally govern life in its various aspects. Almost all

organisms exhibit daily rhythms in their physiology and behaviour. Presently, the

existence of an endogenous time keeping mechanism controlling the overt rhythmic

changes in living organisms is well acknowledged.

At its molecular basis, circadian systems are generally composed of multiple oscillators

that interact in negative feedback loops (Dunlap, 1999; Loros & Dunlap, 2001) within the

organism. Such oscillators appear to be pervasive amongst multicellular eukaryotes (e.g.

cyanobacteria, fungi, insects, and mammals; reviewed in Dunlap, 1999; Harmer et al.,

2001; Bell-Pedersen et al., 2005). The aforementioned oscillators are so important, they


3

represent both a nearly ubiquitous aspect of cellular regulation and a molecular regulatory

process that has clear and immediate effects on organismal behaviour (Dunlap, 1999).

Additionally, contemporary findings suggest that clock genes are plastic components that

can serve diverse purposes, presumably to best adapt organisms to their particular

environmental and temporal niches (Harmer et al., 2001).

The neuroendocrine machinery underlying circadian systems has been extensively

studied in vertebrates. In mammals (Reppert & Weaver 2002), rhythms displayed by cells

and tissues appear to be controlled by a “master” pacemaker located in the

suprachiasmatic nucleus (SCN) of the hypothalamus (Herzog & Takahashi, 1998).

Conversely, nonmammalian vertebrates are characterized by a network of more or less

powerful and interconnected light-sensitive oscillatory units, including the eye, pineal

gland, and probably brain (Falcón et al., 2007; Falcón et al., 2009).

In teleost species (e.g., Oliveira et al., 2009), the pineal gland is a direct photoreceptor, an

endogenous pacemaker, which contains photoreceptor cells that are responsible for

transducing environmental cues, such as the light-dark cycle, through the biosynthesis

and release of rhythmic messengers, such as melatonin. In fact, the rhythmic secretion of

melatonin, which is produced in high amounts during the night and immediately secreted

to the bloodstream, codifies the duration of night and day. Furthermore, this hormone

might also be responsible for the synchronization of different circadian oscillators within

the pineal organ itself as well as outside (Ekström & Meissl, 1997; Falcón, 1999; Falcón et

al., 2007; Falcón et al., 2009).

In general, circadian systems are mostly controlled by internal molecular oscillators which

synchronize (or entrain) to an environmental cycle by a recurring exogenous time cue (or

“Zeitgeber”, from the German “time-giver”). When expressed in the absence of any

external time cue, or in constant environmental conditions, endogenous clocks are said to

be free-running, demonstrating the endogenous nature of biological oscillations (Aschoff,

1981).

Certainly, the ubiquity of circadian systems resultant of their underlying mechanisms and

convergent biology strongly suggests an adaptive significance. Several studies (e.g.

DeCoursey et al., 2000; Beaver et al., 2002; Ouyang et al., 1998) seem to indicate that

organisms with disrupted circadian rhythms suffer reduced performance and fitness. On

the other hand, studies (reviewed in Yerushalmi & Green, 2009) performed on organisms

in their natural environments, showed that species not only display adaptations in their


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circadian systems that correlate with their natural environment, but also show phenotypic

plasticity to match the organism’s demands of their physical and social environment

(MacDougall-Shackleton et al., 2015). Therefore, circadian clocks may present some

selective advantage (Hut & Beersma, 2011) by allowing organisms to anticipate and

prepare for environmental changes, thereby increasing their fitness (Merrow et al., 2005).

Figure 1. Representation of the circadian system. Environmental cues, such as the light-dark cycle are

transduced via input pathways to entrain the oscillator, here represented by a seabream individual. For diel

changing conditions, the period of the circadian rhythm for the oscillator is approximately 24 h. Under

continuous conditions, in the absence of environmental cues, the oscillator shows a free-running rhythm close

to 24 h, reflecting an endogenous rhythm.

The circadian system of fish is known to follow the same general design as in other

vertebrates and invertebrates (Zhdanova & Reebs, 2006). Diel and circadian rhythms

have been extensively investigated in fish, with circadian rhythms described for a wide

range of physiological and behavioural variables in fish (Oliveira & Sánchez-Vázquez,

2010; López-Olmeda & Sánchez-Vázquez, 2010).

The light-dark (LD) cycle is generally considered the dominant synchronizer amongst

animals (Daan, 2010). Nonetheless, other environmental factors such as water

temperature, food availability, social interaction, or even predation risk are also

considered to be potential synchronisers in fish (see Zhdanova & Reebs, 2006). Amongst

these, feeding seems to be the main factor of entrainment for the circadian timing system

(e.g. Montoya et al., 2010b). In fact, from evidences currently available it seems that only

LD alternation and time-restricted feeding with a period of 24 hours act as true zeitgebers

of fish circadian rhythms (Madrid et al., 2001).


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In order to investigate the ability of LD cycles to entrain behavioural rhythms and

characterize locomotor activity patterns, the number of transient cycles required to re-

synchronize locomotor activity to a shifted cycle are examined (e.g. Paladino et al., 2013).

On the other hand, to assess the existence of endogenous control of the behavioural

rhythms constant environmental conditions, constant light (LL) or constant darkness (DD)

are commonly employed.

A set of characteristics define the physical nature of rhythms. For instance, biological

circadian rhythms can be thought of as a wave, and as such they are commonly

characterized by four parameters: period, amplitude, phase, and MESOR (or mean level).

Although many rhythms may be endogenously driven, its parameters are modulated by

periodic events in the environment. One of the most distinctive characteristic of a

circadian rhythm is the stability of the period. Results from studies with diverse species,

especially genetically altered mutants, have demonstrated that the period of a biological

rhythm is an inherited trait (Koukkari & Sothern 2006).

Although biological rhythms can be observed across a wide range of time scales, they are

commonly grouped in three broad domains according to their periodicity: ultradian (<20h),

circadian (20-28h), and infradian (>28h) (see Koukkari & Sothern 2006). Nevertheless, the

vast majority of research on biological rhythms to date has focused on rhythms associated

with diel environmental oscillations, i.e. daily or circadian rhythms. Moreover, daily activity

patterns in fish have been generally classified as diurnal, nocturnal, crepuscular, or a

combination of them (Reebs et al., 2002; López-Olmeda & Sánchez-Vázquez, 2010), in

accordance with the phase of the day that they are more active. Eriksson (1978) and

Sánchez-Vázquez et al., (1996) defined as nocturnal, patterns where respectively more

than 67 or 65% of total activity occurs during the dark phase of a cycle, as diurnal, those

with less than 33 or 35% activity during this phase, and as indifferent, those falling

between these values (in Volpato & Trajano, 2005).

Behavioural traits: a source of variability in chronobiology?

Individual behaviour may, in fact, be one main source of variability in chrobiological

studies. Indeed, individuals may react in different ways to a shift in an environmental cue,

with some displaying a greater ability to adapt than others. A number of studies in fish

(e.g. Sánchez-Vázquez et al., 1996; Hurd et al., 1998) have reported high behavioural

heterogeneity amongst individuals.


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More recently, Vera et al. (2006), reported an individual variability in locomotor activity

patterns of sharpsnout seabream: only 40% of the fish spontaneously switched from

diurnal to nocturnal activity, i.e., displaying a dual pattern of locomotor activity. Moreover,

a large inter-individual variability of behavioural patterns was also observed for Nile tilapia

(Vera et al., 2009). Individuals showed differences in re-synchronization to a shift in LD

cycle: out of 12 fish, 3 displayed an immediate change of the phase of locomotor activity,

while 4 other fish showed a gradual re-synchronization. Such examples illustrate well an

inherent plasticity of behavioural activity patterns (Madrid et al., 2001; Reebs, 2002;

Volpato & Trajano, 2005) characteristic of teleost fish, and little is known about

mechanisms underlying such individual variability in fish.

Studies on animal behaviour have demonstrated that individuals actually differ in

behavioural traits. For example, Coppens et al. (2010) argued that individual variations in

the activity pattern of underlying causal physiological mechanisms are likely to be

reflected by animal personalities or behavioural syndromes. Such behavioural traits, or

coping styles, may be an explanation to differences in adaptability to environmental

challenges, as showed by Ruiz-Gomez et al. (2011). Actually, a study carried out in mice

(Benus et al., 1988) showed that individual differences in aggressiveness (a component

trait of coping styles) may explain differences in the rate of re-entrainment, in terms of

locomotor activity, after a 12 h shift in the photoperiod. But so far this topic has not been

explored in fish.

Coping styles

In the past few years, individual differences in physiological and behavioural responses to

stress have been documented for a large number of animal groups. Stress coping

behaviours are widely regarded as adaptive responses which are vital for the survival of

animals living under continuous environmental changes. In fact, there are several

evidences supporting that inter-individual diversity of stress behavioural and cognitive

responsiveness is maintained by natural selection (Korte et al., 2005; Øverli et al., 2007).

There has been a growing interest in fish personality, and, consequently a number of

studies have been carried out on the subject. Moreover, the existence of coping styles is

fish is, nowadays, widely recognized (e.g. Øverli et al., 2004; Ruiz-Gomez et al., 2011;

Vaz-Serrano et al., 2011; Castanheira et al., 2013a, 2015, 2016).


7

Behavioural responses to stress can generally be categorized in discrete behavioural

phenotypes more or less persistent. Termed as coping styles, (also behavioural

syndromes or personalities) these were defined by Koolhaas et al. (1999) as correlated

set of coherent physiological and behavioural traits consistently linked over time and

across situations, which define the ability of the organism to cope with stress.

Essentially, two main coping styles are recognized in fish: proactive (bold, active coping or

“fight–flight”) and reactive (shy, passive coping or “nonaggressive”). Proactive individuals

(henceforth Bold), as reviewed by Castanheira et al. (2015), are behaviourally

characterized by a high active avoidance, aggression, exploration, risk-taking and an

active attempt to counteract stressful stimulus, as opposed to reactive (henceforth Shy)

coping style. In addition, proactive and reactive individuals seem to exhibit distinct

physiological and neuroendocrine characteristics, and have been reported to differ in

cognitive and emotional traits. The two stress coping behaviours also differ in more

general ways: proactive animals are characterized by low flexibility with a tendency to a

high level of routine formation, whereas reactive animals tend to be highly flexible

(Koolhaas et al., 1999; Ruiz-Gomez et al., 2011). With all this in mind, it is reasonable to

think that proactive and reactive individuals would respond differently to a shift in

environmental cues.

In addition to physiological and behavioural characteristics, different cognitive and

emotional traits have also been reported for proactive and reactive fish. For example,

Martins et al. (2011) provided evidence that individual's coping style is predictive of how

stimuli are appraised and the subsequent degree of avoidance behaviour. Such results

support the inclusion of emotional or affective states (in this case fear) as essential

component of coping styles in fish.

Concerning the evolutionary basis of stress coping styles and the respective underlying

physiology, an extensive overview is given by Øverli et al., 2007. Evidences suggest that

inter-individual diversity of stress behavioural and cognitive responsiveness is maintained

by natural selection over a wide range of animal groups. The fact that stress behavioural

traits have also been identified in fish, suggesting that these traits have been evolutionary

conserved in vertebrates, seems to highlight its importance to the fitness of a species.


8

Seabream: a chronobiology case study

Gilthead seabream (Sparus aurata, Linnaeus 1758) is a benthopelagic, euryhaline and

eurytherm species, commonly found on the coastal warm waters of the Mediterranean

and Eastern Atlantic shores. With a production of 158 389 tons (FAO, 2015-2016), S.

aurata represents one of the most important species for Mediterranean aquaculture.

Given its commercial importance, this species has been profusely studied and its biology

is nowadays very well known.

Seabream has also been the focus of many chronobiological studies, with daily rhythms of

locomotor activity and feeding being reported for this species by several authors

(Velázquez & Martínez, 2004; Sánchez et al., 2009; Montoya et al., 2010b). Interestingly,

like many other fish species, gilthead seabream was traditionally considered diurnal,

however, more recently a dual behaviour was documented for this species. An animal is

considered dualistic when it exhibits the ability to shift behavioural patterns from diurnal to

nocturnal and vice versa at some stages throughout their lifecycle (López-Olmeda &

Sánchez-Vázquez, 2010). Indeed, when reared under natural oscillating conditions,

seabream is known to alter their demand-feeding activity pattern, shifting from diurnal

activity in the warmest months of the year to crepuscular and nocturnal in the coldest

months (Velázquez et al., 2004). Furthermore, when seabream self-feeding rhythms were

documented by López-Olmeda et al. (2009), this species demonstrated self-feeding in

either light or dark phase, depending only on the feeding schedule.

Figure 2. Gilthead seabream in aquaculture (photo on the left (courtesy of Alexandra Alves). A seabream

exemplar is displayed on the top right (photo in FAO.org).


9

In addition, endocrine rhythms entrained by LD and feeding cycles have also been studied

in seabream (e.g. cortisol and melatonin, Montoya et al., 2010a). For example, recent

studies described a daily rhythm of cortisol secretion in this species, which was influenced

by feeding and feeding behaviour under both LD and LL (López-Olmeda et al., 2009). In

the field of reproduction, overt daily rhythms of plasma lutheinizing hormone and

spermatozoa motility have been recently described (Oliveira et al., 2013), while Meseguer

et al. (2008) described a very clear daily rhythm of spawning during several consecutive

days, with eggs being repeatedly laid during late afternoon. This rhythm was shown to be

entrainable by photoperiod, since animals had the ability to gradually re-synchronize the

rhythm after a 12 h shift in the photoperiod, delaying the acrophase almost 12 h.

Interestingly, reported rhythms for seabream are often distinct, in many aspects, from this

species known physiology and behaviour. Such evidence seems to imply the existence of

individual behavioural variation; and despite of the amount of evidence on daily rhythms of

locomotor activity reported in seabream, to date, little is actually known about its individual

behaviour.

More recently, a number of studies have demonstrated the presence of coping styles in

seabream. Castanheira et al. (2013a) found that individual differences in behavioural

responses towards challenges reflect the presence of personalities in seabream. They

also found consistency over time and across-context in behavioural responses to

challenges using individual and grouped-based tests. Moreover, seabream juveniles also

seem to exhibit pronounced individual differences in cortisol responsiveness and

aggression that are interrelated and likely to be distinctive traits of coping styles

(Castanheira et al, (2003b). Conversely, recent evidences have shown that homogenous

groups of proactive and reactive individuals do not exhibit consistent behavioural

responses over time (Castanheira et al., 2016). Such results seem to indicate an

underlying variability interrelated with social contexts.

Although daily and circadian rhythms have been described for both behaviour (feeding

and locomotor activity) and physiology (cortisol, melatonin) of seabream, the influence of

the light-dark cycle in locomotor activity behavioural patterns has not yet been

methodically investigated for this species. More interestingly, the extent to which coping

styles are contributing to the variability reported in many chronobiological studies remains

unknown. Seabream presenting opposite coping styles would, accordingly, exhibit

differential responses in behaviour to environmental challenges demonstrating their

fundamental ability to adapt to their surroundings.


10

2. Objectives

As previously noted, there is a growing interest in fish behavioural studies. While many

physiological and endocrinological, and, to a lesser extent, behavioural aspects of

seabream have been well described, there is still a poor understanding of the

mechanisms underlying the individual variability reported in many studies.

Previous chronobiological studies seem to indicate that inter-individual behavioural

variability is, at least in part, responsible for observed differences in the adaptability to

shifts in the external factors, whether it is LD, feeding or temperature cycles. Therefore,

differences in coping styles may be an explanation to differences in adaptability to

environmental challenges.

Using a teleost model such as S. aurata, a species of great interest in Mediterranean

aquaculture, will help to bridge the gap between behavioural traits that underlie its

reported individual behavioural variability. Therefore, this work aims to investigate if

gilthead seabream presenting opposite coping styles:

(1) differ in locomotor activity rhythms;

(2) differ in the resynchronization to photoperiod shifts;

(3) present or not circadian rhythmicity.


11

3. Material and Methods

3.1. Ethics statement

All experiments in this study were conducted in accordance with the Guidelines of the

European Union Council (86/609/EU) and Portuguese legislation for the use of laboratory

animals, and approved by the ethics committee from the Veterinary Medicines Directorate,

the Portuguese competent authority for the protection of animals, Ministry of Agriculture,

Rural Development and Fisheries, Portugal (Permit number 0420/000/000-n.99-

09/11/2009). Fish were handled in conformity with rules and regulations which protect

experimental animals from unnecessary pain and suffering. Furthermore, the 3 R’s

(Replacement, Reduction and Refinement, 2010/63/UE) guidelines were thoroughly taken

in consideration while planning all the experimental procedures.

3.2. Experimental animals, housing and feeding

Gilthead seabream (Sparus aurata) juveniles, were obtained from a seabream producer

(MARESA Mariscos de Esteros SA, Huelva, Spain) and reared at Ramalhete Research

Station (Faro, Portugal) facilities under standard rearing conditions until the start of the

experiments. Fish were individually weighted (116,0 ± 22,5 g), randomly grouped in

several 100 L circular stock tanks at a low rearing density. Water parameters such as

salinity, water temperature, and dissolved oxygen were monitored daily to assure a high

quality of the rearing water.

Fish were fed ad libitum, by hand, a single meal per day of a standard commercial diet

(STD 3-5 mm, Aquasoja, Sorgal SA, Portugal; 42.0% crude protein, 17.0% crude fat,

9.5% ash, 2.5% crude fibres, 2.0% calcium, 1.4% phosphorous). Naturally oscillating

cycles of temperature were maintained at all times.

Prior to the start of the experimental procedures, fish (n=100) were anaesthetised with a

200 ppm 2-phenoxyethanol (Prolabo, VWR International, USA) bath, and as soon as they

lost equilibrium, were individually identified with a PIT tag system (ID100 Implantable

Transponder, Trovan ®, Netherlands). PIT tags were injected into the muscle (upper-

frontal side) with an IM-200 syringe implanter (Trovan ®, Netherlands). After recovery,

marked fish were returned to their holding stock tank where they were randomly grouped

and kept until the start of the trials.


12

A small group of gilthead seabream juveniles (n=20), randomly selected prior to the

tagging procedure, were left unmarked (Naïves) and grouped in a single 100 L circular

stock tank.

3.3. Coping styles’ screening

Individual behaviours, such as risk taking or escape during restraining or confinement,

have been shown to correlate with personality traits indicative of coping styles in several

fish species (Castanheira et al., 2013a, 2015; Martins et al., 2011, Millot et al., 2014, Silva

et al., 2010, Øverli et al., 2006). However, escape response during a restraining test was

shown to be highly consistent over time in gilthead sea bream, being this a recommended

and suitable test for coping styles’ screening in this species (Castanheira et al., 2013a).

Having this in consideration, in the present study, screening for individuals’ coping styles

was performed using this test. Briefly, the restraining test (according to Castanheira et al.,

2013a) consisted of holding each fish individually in an emerged net visually isolated from

one another by plastic partitions, for one minute. While in the net, behaviours were video

recorded (TVCCD-623-COL, Monacor®, Denmark) and later the following parameters

were measured: i) latency to escape (time in seconds taken by each fish to show an

escape attempt; escape attempt was defined as an elevation of the body from the net); ii)

number of escape attempts and iii) total time spent on escape attempts (total time in

seconds taken by each fish escaping since the first to the last escape attempts).

3.4. Experimental design and procedures

3.4.1. Locomotor activity assessment

Experiments were carried out inside an isolated room in order to avoid the influence of

external environmental factors and disturbance of fish by noises, which could act as

synchronisers of activity. For this, fish were housed in 80 L glass aquaria (70 cm length ×

40 cm width × 30 cm depth) in an open water circuit and under artificial white lighting (51,7

± 16.5 lux). All aquaria’s panes were lined with black plastic keeping fish visually isolated

from one another and from the observer.


13

Gilthead seabream were distributed among nine aquaria (according to their total biomass)

and divided into three experimental groups according to coping styles previously

screened: proactive (Bold), reactive (Shy), and intermediate (Inter). Two other groups

were also tested as controls: a control group with seabream of mixed coping styles, (Ctrl),

and another group with unmarked fish of unknown coping styles (Naïve). Each group had

three replicates.

Locomotor activity was monitored during 24 h a day using infrared photoelectric sensors

(E3S-A,-B, OMRON, Japan), installed one outside each aquarium, approximately at the

centre of the frontal pane, as previously optimized by Vera et al. (2009). Each photocell

was connected to a relay in a small electrical circuit, and from there to a motherboard

(USB-1024HLS, Measurement Computing TM, Massachusetts, USA), which in turn was

connected to a computer where data was stored (figure I, appendices). Every time a fish

interrupted the infrared light beam emitted by the photocell, an output signal was

produced, which was then converted into a digital signal by the motherboard, and stored

in 10 min bins using PC-based specialized software (DIO98USB, University of Murcia,

Spain).

Water quality parameters were maintained according to the species standards and were

monitored daily. Fish were hand-fed once a day using a standard commercial feed. At the

end of each experiment, fish were individually weighted and returned to their holding stock

tanks. Initially, all fish were fed 1% of body weight; however, the feed quantity was

regularly adjusted during the course of this experiment based on daily visual inspections

of the aquaria and waste monitoring.

3.4.2. Experiment I: Daily activity rhythms of divergent coping styles and coping

abilities towards photoperiod shifts

A first experiment was carried out for 32 days between the 23rd of June 2015 and 29th of

September 2015 at Ramalhete Research Station (Faro, Portugal).

Sixty fish were distributed among the nine 80 L aquaria (4 fish per aquarium) according to

their coping style, during two consecutive runs until all 5 groups were tested: Bold, Shy,

Intermediate, Control and Naïve (3 replicates per group). Gilthead seabream were

maintained under a 12:12 h DL cycle (lights on at 08:00 h) for approximately 2 weeks in

order to firstly characterize each group’s daily rhythm of locomotor activity. After this


14

period and in order to ascertain the robustness of the activity rhythms under shifting LD

cycles, a 12 h inversion of the photoperiod was applied, with lights turned on at 20:00 h

and off at 08:00 h. These conditions were maintained until a total resynchronization to the

new photophase was observed. Afterwards, the initial 12:12 h DL cycle was restored in

order to evaluate the capacity of fish to resynchronize to the initial conditions.

Throughout the whole experiment, fish were hand-fed a single meal per day around 10:00

h, independently of the photoperiod phase, to avoid confusing results in terms of the

synchrony effect of meal time. Salinity (37,4 ± 0,5), water temperature (23,7 ± 2,2 °C), and

dissolved oxygen (82,9 ± 4,2 %) were monitored daily, and water flow rate (196,3 ± 85,1

L/h) was checked periodically, as displayed in figure 3.

Figure 3. Average temperature (ºC) and DO (%) throughout experiment I. Data are presented as mean ± SD.

3.4.3. Experiment II: Circadian activity rhythms of divergent coping styles in

gilthead seabream

A second experiment was carried out for 27 days between the 2nd of November 2015 and

2nd of December 2015 at Ramalhete Research Station (Faro, Portugal).


15

In this second experimental phase, 45 gilthead seabream juveniles were distributed

among the nine 80 L aquaria (3 fish per aquarium) and reared under a 12:12 h LD cycle

with lights on at 08:00 h. As in the previous experiment, fish were maintained under these

experimental conditions for about 2 weeks in order to characterize their daily locomotor

activity rhythms. Afterwards, fish were exposed to constant darkness (DD) conditions for

approximately two more weeks in order to evaluate the persistence or not of the daily

rhythms of locomotor activity and thus ascertain about its circadian rhythmicity.

Fish were hand-fed a single meal at random times every day, to avoid a synchronization

effect from meal time. Like in the previous experiment, all fish were initially fed 1% of body

weight of a standard commercial feed, and the feed quantity was regularly adjusted based

on daily visual inspections of the aquaria and waste monitoring. Likewise, salinity (35,7 ±

0,9 ‰), water temperature (16,6 ± 1,7 °C), and dissolved oxygen (94,5 ± 3,0 %) were also

monitored daily, and water flow rate (196,3 ± 85,1 L/h) was checked periodically, as

displayed is figure 4.

Figure 4. Average temperature (ºC) and DO (%) throughout experiment II. Data are presented as mean ± SD.


16

3.5. Data Analysis

For coping styles’ screening, behaviours measured were collapsed into first principal

component scores using Principal Components Analysis (PCA) in order to obtain a score

allowing the characterisation of coping styles using SPSS® statistical package.

Data bases of the recorded locomotor activity were created using Excel®. The raw

locomotor data was plotted in the form of chronograms for first assessment of rhythmicity

and for screening of recording artefacts. To avoid potential errors, values exceeding 250

counts/10 min were removed from the analysis.

After visual inspection for periodicity, data of each groups was then plotted in the form of

actograms using a software for chronobiology analysis (El temps©, Prof. A. Diéz-Noguera,

University of Barcelona, Spain). Each actogram is a graphical representation of the

locomotor activity along a two time axis with successive day cycles plotted on successive

horizontal lines, and providing an easy way to identify rhythm patterns. For better

identification of locomotor activity patterns all actograms are double-plotted. Light and

dark phases are also displayed in the form of white and black bars on top of the

actograms.

Despite its restricted application to highly uniform and noise-free time series, measures of

data centrality or flanks, daily onsets and offsets were also determined, since they are

convenient markers for the rhythm phase (Díez-Noguera, 2013). The method consisted

simply in determining the time at which the series has its highest or lowest value and was

performed using El temps©. Statistical significance of daily locomotor activity rhythms was

also tested using the single-component Cosinor analysis, by which cosine curves with

known periods are fitted by approximation to the data by the least squares as an estimate

of the rhythmicity pattern. Several parameters are estimated to assess the significance of

the respective rhythm: mesor (the time series mean), amplitude (a measure of half the

extent of predictable variation within a cycle), period, τ, (the rhythm cycle length – 24 h in

the case of diel rhythmicity), and acrophase (the phase of the highest repeatable value

assumed by the curve, i.e., the time of the rhythm activity peak (Refinetti et al., 2007;

Cornelissen, 2014).

To determine daily and circadian rhythmicity, a spectral analysis with periodograms were

implemented. Chi-squared Sokolove-Bushell with a Bonferroni correction periodograms

were performed for every studied group. Values were expressed as percentages of

explained variance for each period (τ).


17

Additional statistical and graphical analysis was performed using R statistical software.

The Wilcoxon signed-rank test was used to statistically compare differences in locomotor

activity between each phase. To compare differences between groups, non-parametric

Kruskall-Wallis tests were conducted. Follow-up pairwise comparisons using Wilcoxon

rank sum test with a Bonferroni correction to account for multiple comparisons were

conducted among groups. Data are reported as mean ± SD.


18

4. Results

4.1. Experiment I: Daily activity rhythms of divergent coping styles and coping

abilities towards photoperiod shifts

Under a 12:12 DL photoperiod, all locomotor activity raw data records showed a pattern of

oscillation of approximately 24 h for all gilthead seabream groups, albeit the detection of

some biological noise (figure II, appendices). The actograms of locomotor activity rhythms

showed that all groups were predominantly active during the light phase, presenting overt

diel rhythmicity, although some conspicuous differences were observed between the

experimental groups (figure 5). Overall, seabream displayed diurnalism (defined by to

Sánchez-Vázquez et al., (1996) as more than 65 % of locomotor activity occurring during

the photophase), with 78,2 ± 8,7 % of locomotor activity occurring during the photophase,

whereas during the scotophase the groups averaged 21,8 ± 8,7 % for the entrained DL

cycle. However, in general, Bold seabream displayed greater activity throughout the whole

experiment, whereas Shy showed lower locomotor activity during all the experimental

phases (figure 6). A Kruskal Wallis test revealed significant differences between groups’

total locomotor activity (χ2(4) = 244,2; p < 0,001). The post-hoc showed significant

differences between groups as presented in table II, appendices.

During the first phase of this experiment (12:12 DL Cycle) seabream displayed an overall

lower locomotor activity for the photophase (47,7 ± 29,8 counts/10 min), with Shy clearly

exhibiting the lowermost activity of all the groups (figure 6). When the photocycle was

shifted by 12 h (LD cycle), both Bold and Shy fish showed a rapid and abrupt

resynchronization of the activity rhythm to the new LD photoperiod, with no noticeable

alteration of the respective mean waveform. Conversely, the Intermediate group showed a

gradual resynchronization to the zeitgeber shift. In fact, the latter displayed approximately

5 transient cycles before complete resynchronization to the new LD cycle. Such gradual

transition can easily be observed in the actogram in figure 5 (Inter). Complete entrainment

to the new LD cycle was observed in all the seabream groups. Lastly, to study how fish

groups resynchronized again to the initial DL cycle, photoperiod was restored during the

last phase of this experiment. All seabream groups showed a rapid and strong

resynchronization to the initial photoperiod. Moreover, under the resynchronized DL cycle,

both Bold, Shy, and Intermediate displayed a complete entrainment and a greater

locomotor activity of all the three experimental phases (figure 6).


19

Figure 5. Representative actograms and respective mean waveforms (on the right) of locomotor activity

rhythms of gilthead seabream groups presenting opposite coping styles: Bold, Shy, Intermediate (Inter),

Control (Ctrl) and Naïve exposed to scheduled feeding and photoperiod shifts. Actograms are double-plotted

for better visualization and horizontal lines correspond to experimental days. White and black bars at the top

of both actograms and mean waveforms indicate light and dark phases, respectively. Locomotor activity is

represented in the waveforms as the mean locomotor activity counts per 10 min along a 24 h cycle (in grey) +

SD (in white). A grey vertical bar highlights the time of schedule feeding.


20

For better analysis of the rhythm phase shifts during this experiment, daily onsets and

offsets of activity are presented in figure 7. Interestingly, onsets and offsets coincided

relatively well with light-on and light-off times, respectively, for all the experimental groups

and phases. However, a considerable variation of the onset of locomotor activity is, during

the first experimental phase, while the offset of locomotor activity

Figure 6. Average daily (white bars) vs nightly activity (grey bars) of gilthead seabream experimental groups:

Bold, Shy, Intermediate (Inter); and control groups: Control (Ctrl), and Naïve, during the three photoperiod

phases (DL, LD, and DL). Data are represented as mean ± SD. Significant differences were found between

dark and light for all groups during the three experimental phases (*** p < 0,001).

clearly aligns with the end of the photophase. For the rest of the experimental phases, the

activity onsets and offsets appear to be aligned with the zeitgeber on an almost straight

line, indicating that there is no difference in phase for all the groups.

Additionally, the significance of the daily rhythms was tested through a cosinor analysis,

indicating a significant diel rhythm for all experimental groups during all experimental

phases (table III, appendices). Most seabream groups displayed a slight peak

approximately 2 h after light-onset (around feeding time) in the mean waveform (figure 5).

However, acrophases were observed later in the light phase of the DL cycle (with mean

acrophase at ~18:00 h), that is, approximately 2 h before light-off time (acrophases, figure

7). When the photoperiod was reversed, seabream groups exhibited an almost complete


21

Figure 7. Representative actograms of locomotor activity rhythms of gilthead seabream groups (Bold, Shy,

Inter, Ctrl, and Naïve) exposed to scheduled feeding and photoperiod shifts. Mean time of onset (green line)

and offset of activity (red line), as well as the acrophase (blue line) are displayed. Such parameters of

centrality and flanks determination are calculated for each daily activity rhythm. Polar representations of the

cosinor analysis depicting acrophase and amplitude for each of the three experimental phases (right side) are

also exhibited. Vectors point to the moment the acrophase occurred, and its length represents the amplitude.

Acrophase interval is also shown. Black bars represent the night phase of the cycle.


22

Figure 8. Representative actograms and respective chi-square periodograms (on the right) of locomotor

activity of gilthead seabream groups (Bold, Shy, Inter, Ctrl, and Naïve) exposed to schedule feeding and

photoperiod shifts. The significant component of the period (τ), expressed in min, is indicated above each

periodogram. On the Y axis, the % of variance that explains the period is represented. Horizontal lines

represent the level of significance of % of variance, above which major significant components of rhythmicity

are represented.


23

shift in the daily rhythm, with mean acrophase at ~ 05:00 h, i.e., approximately 3 hr before

light-off time. Although the pattern of activity rhythms patterns was relatively prominent,

rhythm amplitudes were quite variable between the experimental groups, with Shy

presenting the lowest amplitude for all the photoperiod phases, followed by Intermediate

during the shifted photophase (LD). Nevertheless, acrophases of activity rhythm showed a

consistent displacement throughout all the photocycle phases for all the experimental

groups.

To further test the locomotor activity rhythmicity of the seabream groups, periodograms for

all photoperiod phases were also computed as extended plexograms of the cosinor

analysis (figure 8). The results of such analysis are presented in figure 8, permitting to

follow the evolution of the main period (τ) over time. When a period of 1440 min was

tested, periodograms showed a significant component of ~ 24 h explaining most of total

variance for all the groups (table IV, appendices), except for the Intermediate fish.

Interestingly, the former group displayed a period with two components of ~ 24 h and ~ 25

h, with only the latter being significant. However, it is noteworthy that former period

explained the least total variance, indicating that this might not be the true period for the

Intermediate group.

Both control groups (Naïve and Control) displayed the same overall patterns of locomotor

activity rhythmicity throughout all photoperiod phases. Moreover, in control groups fish

seemed to have the most overt rhythmic patterns, with Control group exhibiting the

highest average locomotor activity for all experimental phases with a maximum of activity

during the shifted photophase of 105,12 ± 12,31 (counts/10min) (figure 6). Both groups

also showed a rapid resynchronization to the complete inversion oh the photocycle and

the most consistent acrophases throughout the experiment. Indeed, for the Control fish,

the onset and offset of activity appears to have aligned perfectly in a straight line with the

synchronizer. Both groups displayed very similar patterns of locomotor activity to Bold

group. Likewise, periods of the control groups did not differ from experimental groups,

exhibiting a major component around 24 h.

Lastly, a small peak of activity was observed for all experimental groups and in all

experimental phases, resulting from the maintenance of the feeding schedule throughout

the experiment. However, the feeding time did not produce any apparent effect in overall

rhythmicity in any case.


24

4.2. Experiment II: Circadian activity rhythms of divergent coping styles in gilthead

seabream

A periodicity of locomotor activity of approximately 24 h was also detected in the raw data

records of all gilthead seabream groups in the second experiment, despite the lower

quality of the activity signal and the presence of biological noise (figure III, appendices).

The actograms of locomotor activity for all seabream groups are represented in figure 9.

The overall pattern of activity is less significant in all groups, with seabream displaying

more pronounced nocturnal (32,9 ± 1,6 %) and less pronounced diurnal activity (67,1 ± 1,

6 %).

Still, all fish displayed 65 % or more activity during the photophase, therefore exhibiting

overall diurnalism (table V, appendices). Differences in activity patterns were quite evident

amongst all the experimental groups, with Bold displaying the lowermost activity

throughout the experiment (figure 10). Interestingly, seabream registered higher locomotor

activity on the subjective day, as opposed to the subjective night. A Kruskal Wallis test

revealed significant differences between groups’ total locomotor activity (χ2(4) = 270,9; p <

0,001). The post-hoc showed significant differences between groups as presented in table

VI, appendices.

Under the 12:12 h DL cycle, gilthead seabream showed less synchronization to the light

phase, displaying of total of 41,8 ± 13,9 counts/10min average daily locomotor activity.

Shy and Intermediate showed a greater entrainment to the photophase, exhibiting mean

waveforms with a clear daily pattern (DL mean waveforms, figure 9). Curiously, before

completely entrained to DL cycle, Shy displayed approximately 5 arrhythmic cycles. When

the LD cycle was supressed by imposing constant dark conditions (DD cycle),

conspicuous differences in activity behaviour between experimental groups were

observed. Both Bold and Intermediate maintained rhythmicity, with Intermediate displaying

a significant free-running activity rhythm. Conversely, Shy seabream did not display any

rhythmicity, exhibiting very similar activity patterns during both subjective night (23,0 ± 2,7

counts/10min) and subjective day (25,4 ± 2,8 counts/10min) periods (figure 10).

For better visualization of rhythmicity patterns in locomotor activity along experiment, daily

onsets and offsets of activity are presented in figure 11. However, due to the highly noisy

and irregular locomotor activity series, onsets and offsets did not reveal a strong

association with light-onset -offset times for all the experimental groups with the exception

of Shy seabream. The former group displayed a clear alignment of the


25

Figure 9. Representative actograms and respective mean waveforms (on the right) of locomotor activity

rhythms of gilthead seabream groups presenting opposite coping style: Bold, Shy, Intermediate (Inter), Control

(Ctrl) and Naïve exposed to an DL cycle and constant conditions (DD). Actograms are double-plotted for

better visualization and horizontal lines correspond to experimental days. White and black bars at the top of

both actograms and mean waveforms indicate light and dark phases, respectively. Locomotor activity is

represented in the waveforms as the mean locomotor activity counts per 10 min along a 24 h cycle (in grey) +

SD (in white). For the DD phase, a vertical dotted line divides the cycle in subjective night and subjective day.


26

Figure 10. Average daily (white bars) vs nightly activity (grey bars) of gilthead seabream experimental

groups: Bold, Shy, Intermediate (Inter); and control groups: Control (Ctrl), and Naïve, during the DL phase and

constant conditions (DD). For the DD cycle, the subjective night, SN (left bar), and subjective day, SD (right

bar), are shown. Data are represented as mean ± SD. Significant differences are presented as asterisks (*** p

< 0,001; * p < 0,05).

activity onset and offsets with the DL cycle, showing the strongest entrainment to the

zeitgeber.

Cosinor analysis estimation was significant for all the experimental groups except for Shy

fish under DD conditions (table VII, appendices). Nevertheless, both Bold and Shy groups

displayed an acrophase later in the light phase of the DL cycle, with Bold activity peaking

at approximately 19:30 h (i.e., ~ half hour before light-off time), and Shy activity peaking at

18:30 h (1:30 h before light-off) (acrophases, figure 11). Intermediate seabream locomotor

activity, on the other hand, peaked at approximately 15:00 h (acrophase 5 h before the

light-off time). When constant conditions (DD) where applied, Intermediate seabream

exhibited a consistent delay in the acrophase throughout the free-running rhythm (blue

line, figure 11). Indeed, a shift in the acrophase of the respective activity rhythm was

observed at the end of the trial (at ~ 12:20 h), strongly indicating an advance in

rhythmicity. On the other hand, Bold group seemed to maintain rhythmicity under DD

conditions displaying an acrophase of the rhythm later in the day at ~ 19:30 h, exhibiting a

consisting acrophase. Conversely, Shy displayed no rhythmicity under DD conditions.

Rhythm amplitudes were also very low for all the experimental groups.


27

Figure 11. Representative actograms of locomotor activity rhythms of gilthead seabream groups (Bold, Shy,

Inter, Ctrl, and Naïve) exposed to random feeding and photoperiod shifts. Mean time of onset (green line) and

offset of activity (red line), as well as the acrophase (blue line) are displayed. Such parameters of centrality

and flanks determination are calculated for each daily activity rhythm. Polar representations of the cosinor

analysis depicting acrophase and amplitude for each of the two experimental phases (right side) are also

exhibited. Vectors point to the moment the acrophase occurred, and its length represents the amplitude.

Acrophase interval is also shown. Black bars represent the night phase of the cycle.


28

Figure 12. Representative actograms and respective chi- square periodograms (on the right) of locomotor

activity of gilthead seabream groups (Bold, Shy, Inter, Ctrl, and Naïve) exposed to random feeding and

photoperiod shifts. The significant component of the period (τ), expressed in min, is indicated above each

periodogram. On the Y axis, the % of variance that explains the period is represented. Horizontal lines

represent the level of significance of % of variance, above which major significant components of rhythmicity

are represented.


29

To estimate the periods of the rhythms of locomotor activity, and more precisely to

estimate the true period (τ) of Intermediate seabream free-running rhythm, periodograms

were calculated. Periodograms for all the experimental groups and phases are

represented in figure 12. When kept in a DL cycle, all the groups’ periodograms exhibited

a significant component of τ, although some variability between periods was observed.

Bold fish maintained their period at ~ 24 h, Shy and Intermediate advanced their periods

(23:46 and 23:52, respectively). On the other hand, under DD conditions Shy showed a

complete loss of its rhythmicity, while Intermediate displayed a significant period of 23:22

h. Nevertheless, it should be noted that the period of ~ 24 h exhibited by Bold seabream

explained the least variance present, indicating the presence of a weak rhythmicity.

Interestingly, both control groups (Naïve and Control), displayed different behavioural

patterns during the experimental phases, with Naïve displaying an overt rhythmicity under

a daily DL cycle and the maximum of locomotor activity of 51,9 ± 12,3 counts/10 min,

figure10). Moreover, it displayed the best overall entrainment to the zeitgeber as seen by

the clear alignment of the offset of activity (red line, figure 11) with the light-off time during

DL cycle, and a more consistent acrophase throughout the experiment (blue line, figure

X). Control seabream, on the other hand, showed a poor entrainment to the photocycle.

Under constant conditions (DD), both groups have apparently maintained rhythmicity.

Cosinor results were also significant for both groups in both experimental phases (table

VII, appendices). Furthermore, under DL cycle both Naïve and Control groups exhibited

the respective peak of locomotor activity later in the photophase, with Naïve displaying an

acrophase approximately 2 h before the offset-light (at ~ 18:00 h) and Control fish

displaying a slightly earlier acrophase at ~ 16:30 h (i.e., ~ 3:30 h before light-off time).

When kept in DD, both groups also displayed a slight delay in the acrophase of

approximately 40 min. Similarly, control groups’ periodograms displayed a major circadian

component of approximately 24 h.


30

5. Discussion

In recent years, numerous studies have consistently reported the existence of inter-

individual variability in physiological and behavioural responses to external challenges

(Iigo & Tabata 1996; Hurd et al., 1998; Vera et al., 2006, 2009), positively correlated with

the presence of divergent coping styles (Andersson et al., 2011; Ruiz-Gomez et al., 2011).

In gilthead seabream, fish personalities have recently been identified and characterized

over time and across different contexts (Castanheira et al., 2013a, 2013b).

However, to date, how fish presenting opposite coping styles differ in their biological

rhythms and adaptability to shifts in environmental synchronizers, has not yet been

addressed. Therefore, by studying daily and circadian rhythms of Sparus aurata juveniles

presenting divergent coping styles and under different photoperiod regimes, the present

work contributes with new insights on how different coping styles correlate with observed

variability in the respective behavioural patterns.

5.1. Daily activity rhythms of divergent coping styles and coping abilities towards

photoperiod shifts

In the study of daily rhythmicity, all seabream groups presenting opposite coping styles

exhibited very clear daily rhythms in locomotor activity under a DL cycle, although

conspicuous differences on behavioural patterns were indeed observed between coping

styles. For instance, when initially entrained to a standard 12:12 DL cycle, conversely to

Intermediate, both Bold and Shy fish exhibited a low synchronization to the zeitgeber.

Nevertheless, diurnal behavioural patterns were generally observed, with most of the

groups displaying more than 65% of their daily activity during DL. Shy, on the other hand,

seemingly exhibiting most of their activity during the photophase, did not met the

diurnalism criterion with only 64% of activity during such phase, which is not surprising

given that the former group also displayed the lowermost daily activity for the light phase

of the DL cycle.

It is also interesting to notice that for both Bold, Shy and Intermediate, activity onsets

mostly succeeded light-onset times, that is, seabream seemed to display a delay in

diurnal activity relatively to the lights-on cue. On the contrary, activity offsets mostly

coincided with light-offset times marking the end of seabream activity much more clearly,

translated in a much more sudden decrease of locomotor activity. This appears to indicate


31

that offsets would be a better suited marker (as opposed to onsets) of the phase of

seabream activity rhythm.

When subjected to a complete LD cycle shift, intriguingly, both Bold and Shy fish exhibited

a rapid resynchronization to the new photophase along with a concomitant activity

increase. Conversely, Intermediate seabream appeared to have decreased their activity

due to the occurrence of transient cycles. Indeed, these fish exhibited a gradual

resynchronization, taking approximately 5 days (transient cycles) to reentrain to the

zeitgeber. Transient cycles have been widely studied as they provide information about

the underlying mechanisms of a rhythm. Previous studies have shown that in fish few

transient cycles are usually needed to resynchronize to a shifted cycle (e.g., Lague &

Reebs, 2000; Meseguer et al., 2008), or even that fish can display an almost immediate

resynchronization (Herrero et al., 2003), suggesting a strong effect of masking by light.

This might be the case for Bold and Shy fish that rapidly adjusted to the new photocycle.

When the DL photoperiod was subsequently restored, a complete and immediate phase

shift was observed for all coping styles. Seabream not only displayed a rapid adaptation to

the new photophase but also a stable entrainment with highest locomotor activity. In fact,

Shy fish only displayed a truly diurnal behavioural pattern in this phase. Compared with

other species (e.g., Herrero et al., 2003), such abrupt resynchronization seems to indicate

that daily activity rhythms in seabream could result from direct responses to the zeitgeber.

Interestingly, seabream exhibited a peak of activity later in the photophase remarkably

consistent throughout the experiment, with complete shifts occurring for the acrophase.

Prior studies have also demonstrated the existence of peaks occurring late in the light

phase in physiological and behavioural rhythms of seabream. A daily rhythm in glucose,

irrespective of feeding, with its acrophase at the end of the light phase has been

previously described by Pavlidis et al. (1997). The same authors have also observed a

hormonal (thyroxine T4) peak occurring in the evening (18:00 h). Likewise, a clear daily

rhythm of spawning during several consecutive days, with eggs being repeatedly laid

during late afternoon, has also been described (Meseguer et al., (2008). Such

observations seem to contribute with evidence of a biological peak naturally occurring

later in the day in seabream, reinforcing the idea of a strong rhythmicity of biological

processes in this species.

Intriguingly, all seabream exhibited a relatively high basal level of locomotor activity during

the scotophase during this experiment, demonstrating that seabream activity is not rigidly


32

confined to the light phase, therefore providing evidence of the true dualistic nature of this

species behaviour. Indeed, traditionally regarded as a diurnal species gilthead seabream

has proven to display dual behaviour, on both self-feeding rhythms (López-Olmeda et al.,

2009), and demand-feeding activity patterns (Velázquez et al., 2004). Moreover, these

observations seem to further contribute to support the hypothesis of dualism being a

common feature amongst fish, thereby providing fish with a more adaptable response to

environmental changes (López-Olmeda et al., 2009).

It is interesting to note that the variability of behavioural patterns displayed by fish

personalities is in accordance with previous published data: Bold fish were characterized

by a high level of locomotor activity (Mas-Muñoz et al., 2011), as opposed to Shy (Van de

Nieuwegiessen et al., 2010), characterized by the lowest level of overall activity (Øverli et

al., 2002; Brelin et al., 2005). Furthermore, as shown by Ruiz-Gomez et al. (2011) for

rainbow trout, it would be expected that Bold fish, highly prone to routine formation and

characterized by low flexibility in behavioural responses would exhibit less adaptation

capability to an environmental challenge; whereas Shy fish, characterized as more

flexible, would readily adjust to environmental changes. In wild house mice, adaptation to

a new LD cycle took the aggressive (a behavioural trait associated to Bold coping style)

males twice as long as the non-aggressive ones (Benus et al., 1988). However, in

seabream, both coping styles presented a rapid adaptation to the shift of the zeitgeber,

although it is true that for Shy fish rhythms were not as overt as for Bold. Such fact might

be an evidence of the true inherent nature of the different behavioural coping strategies

exhibited by seabream.

It is noteworthy, a clear inconsistency between the results of the present work and

previous findings regarding seabream coping strategies towards environmental

challenges: Castanheira et al. (2013a) reported a longer recovery in feed intake time for

Bold fish, as opposed to Shy fish. The present findings are not in accordance with the idea

that Bold individuals are more rigidly organized, relying on predictions of the actual

environment (Coppens et al., 2010), and thereby showing a slower adaptation to the

challenge, as reported by Castanheira et al. (2013a). In fact, Bold was the group

exhibiting the strongest entrainment to both the shifted photophase (LD) and standard

photophase (DL). Conversely, with regard to Shy fish the present study seems to

corroborate the idea that Shy individuals may directly react to environmental stimuli

(Coppens et al., 2010), thereby displaying a faster adaptation to a new challenge.

Moreover, Intermediate fish displayed an apparent transitional behavioural response to


33

the zeitgeber shift. On one hand, Intermediate showed a slower entrainment to a shift in

the photophase (LD); on the other hand, this group presented the highest synchronization

to the restored standard photophase (DL). Taken together, these evidences seem to

indicate (or in the case of Shy corroborate) the existence of strong plasticity in behavioural

responses to challenges in all groups.

In a similar manner to what has been reported here, control groups, expected to be a

representative sample of the distribution of coping styles in seabream population, also

displayed analogous behavioural responses to environmental shifts. In fact, both Control

group (with mixed coping styles) and Naïve (unmarked fish with unknown coping styles),

followed a close locomotor activity pattern to Bold and Shy groups, respectively.

Moreover, not only these groups exhibited overt daily rhythms but also the highest

locomotor activity (i.e., Control group). It is interesting to note that such findings might

implicate other factors affecting behavioural responses (e.g., social context) as discussed

by Castanheira et al. (2016). Perhaps, such behavioural patterns might be a result of an

implicit effect of Bold social dominance over Shy fish (Ruiz-Gomez et al., 2008).

Lastly, although well beyond the scope of this work, it should be noted that despite the

fact that feeding time was maintained throughout the experiment, there was no effect in

seabream rhythmicity. Previous findings for this species demonstrated contradictory

evidences on the impact of scheduled feeding on activity patterns: on one hand, results

have shown that seabream displayed diurnal behaviour irrespective of feeding time

(López-Olmeda et al., 2009), on the other hand, seabream displayed a strong

synchronization with feeding time, modulating its behavioural patterns according to meal

time (Sánchez et al., 2009; Montoya et al., 2010a, 2010b; Vera et al., 2013). In our case,

the lack of effect of feeding time in seabream locomotor activity, suggests that

photoperiod might be the prevalent zeitgeber entraining gilthead seabream activity

rhythms.

5.2. Circadian activity rhythms of divergent coping styles in gilthead seabream

After knowing the locomotor activity rhythms of gilthead seabream presenting opposite

coping styles, the next step was to study its potentially endogenous origin. On this behalf,

a second experiment was conducted under constant darkness conditions (DD), with fish

previously entrained to a standard 12:12 DL cycle. Different patterns in behavioural

responses were observed, and, contrary to the results obtained in experiment I,


34

Intermediate fish exhibited the strongest entrainment to the zeitgeber. Curiously, although

Shy fish displayed the strongest entrainment to DL cycle, it took approximately 4 to 5

cycles for these fish to be fully entrained and present a stable daily rhythm under DL.

Despite the overall lower activity exhibited by all groups when initially reared under a DL

cycle, seabream displayed daily rhythms with a clear preference for being active during

daytime, with all fish displaying 65% or more of locomotor activity during the photophase

of the cycle. Nevertheless, with the exception of Bold, the levels of basal activity during

the scotophase were higher, when compared to the results obtained in the first

experiment. The observed change in behavioural patterns might be related with the lower

temperature registered during this experiment, in agreement with the fact that this species

is known to alter its behaviour along the year and according to temperature; e.g.,

Velázquez et al. (2004), demonstrated that, when subjected to natural oscillating

photoperiod and temperature, self-feeding seabream naturally alter their feeding pattern,

with demand activity decreasing during winter.

In the absence of any external daily synchronizer (constant darkness conditions, DD, and

random feeding), circadian rhythmicity in locomotor activity was observed in almost all

groups of seabream, suggesting the existence of an endogenous mechanism controlling

its activity. Moreover, conspicuous differences were also found among fish presenting

opposite coping styles, highlighting the correlation between underlying circadian

mechanisms and inherent behavioural traits. Indeed, Bold and Intermediate fish exhibited

self-sustained activity rhythms under DD, whereas a complete loss of rhythmicity was

observed for Shy seabream. Interestingly, Intermediate fish exhibited a seemingly

entrained activity rhythm for the first few cycles, before a clear variation was observed:

rhythm started to free-run during several days. Indeed, a significant advance of the rhythm

was observed in relation to other groups, with intermediate displaying a distinctive period

length of 23:22 h.

Closely analysing Bold fish circadian activity, reveals that the displayed rhythm mirrors, to

a certain extent, the previously entrained diurnal rhythm, since fish were mostly active

during the subjective day of the DD cycle. Curiously, such pattern was also observed in

the control groups. As previously discussed, both Control and Naïve groups exhibited

behavioural patterns very similar to those of Bold and Shy fish, respectively; although in

this case a circadian rhythm was observed for Naïve fish. Such evidence further

contributes to the idea of an endogenous clock driving such rhythm in seabream.


35

Furthermore, a comparison between the locomotor activity patterns in LD with those in DD

of Shy seabream suggests that a positive masking effect may be influencing its

behavioural rhythms. Positive masking as a direct response to light has been observed in

other species, such as zebrafish (Hurd et al., 1998). It is therefore interesting to consider

that, not only Shy group might rely almost exclusively on environmental cues to entrain its

rhythmicity, but also that light may be a strong synchronizer for seabream.

Circadian rhythms had already been described for gilthead seabream activity, e.g., Vera

et al. (2013), reported persistent circadian rhythmicity for randomly fed seabream under

DD and the same authors also demonstrated the existence of an endogenous control for

seabream, in accordance with our results. However, in what refers to gilthead seabream

rhythms, only a few works have attempted to describe locomotor activity to date.

Furthermore, not only those works mainly describe seabream activity rhythms entrained to

feeding schedules (López-Olmeda et al., 2009; Sánchez et al., 2009; Montoya et al.,

2010a, 2010b), they often report variable results. For instance, Montoya et al., 2010b

found that when randomly fed, seabream did not display clear diurnal behaviour and

rather sustained activity along the day, whereas Sánchez et al., 2009 described a higher

percentage of diurnal activity for seabream randomly fed. Additionally, López-Olmeda et

al. (2009), have reported that under an LL (Constant light) cycle seabream become

arrhythmic. The lack of comparative results for gilthead seabream or even reliable data

significantly limits behavioural comparisons and interpretations.

Other fish species such as goldfish (Iigo & Tabata, 1996), zebrafish (Hurd et al., 1998),

Nile tilapia (Vera et al., 2009) or tench (Herrero et al., 2003) have also been proven to

display circadian rhythmicity in locomotor activity under DD. Moreover, all the previous

authors also reported a great variability amongst individuals. For example, in Nile tilapia,

Vera et al. (2009) observed that immediately after subjecting the fish to DD some tilapia

displayed a free-running rhythm, whereas others only started to free-run after a few

arrhythmic cycles. Inherent behavioural variability might account for some of the reported

variability.

Distinct behavioural patterns were also observed in this experiment among coping styles.

However, such activity patterns seemed inconsistent with the results from the fist

experiment. In this second trial, under DL cycle, Shy fish presented a strong

synchronization with the zeitgeber. Such contradictory results have also been reported

regarding fish behaviour, as pointed by Castanheira et al. (2013a). Indeed, previous works

have shown that, during confinement, Shy fish display a higher level of locomotor activity


36

(e.g., Øverli et al., 2002). Nevertheless, although such activity patterns appear to be

inconsistent for gilthead seabream between the trials of this work, one could argue that

the underlying traits that characterize each coping style are still discernible irrespective of

activity levels. For instance, the fact that Shy fish were initially arrhythmic before stably

entrained to DL seems to support the hypothesis that this coping style reacted to the

zeitgeber and adjusted its behaviour accordingly. Additionally, a sustained diurnal pattern

observed in Bold fish when environmental conditions were supressed, highly prone to

routine formation and characterized by its environmental predictability, also support the

current hypothesis. Moreover, Intermediate fish seemed to exhibit a remarkable

behavioural consistence. In fact, Castanheira et al. (2016), recently demonstrated that

Intermediate and Control (1/3 of each coping style) groups displayed the best behavioural

consistency over time and across contexts. Furthermore, one should not discard the role

of behavioural flexibility reported to individual variation (as discussed by Coppens et al.,

2010), nor some degree of plasticity (see Sih et al., 2004).

Lastly, it is important to emphasize the fact that activity rhythms persisted, with

Intermediate fish displaying a free-running rhythm, which points to the existence of an

endogenous circadian clock. Likewise, the locomotor activity arrhythmicity presented by

Shy gilthead seabream seems to imply that this groups’ daily activity rhythms are

exogenously driven by light. Furthermore, the light-dark cycle appears to be the most

important synchronizer of the observed diel changes in locomotor activity in gilthead

seabream.


37

6. Final remarks

This study provided the most comprehensive description of diel and circadian locomotor

activity rhythms for seabream to date. Furthermore, the present work also provided

surprising new insights on locomotor activity rhythms of gilthead seabream presenting

opposite coping styles.

When initially reared under a standard DL cycle all groups exhibited an overt daily

rhythmicity, with the exception of Shy, displaying a clear diurnal behavioural preference.

When subjected to a photoperiod shift, both Bold and Shy fish rapidly resynchronized to

the new photophase with a concomitant activity increase. Conversely, a gradual

resynchronization of approximately 5 cycles was observed for Intermediate fish before a

complete and stable synchronization to the zeitgeber. However, when the initial standard

photoperiod was restored all groups displayed a rapid adaptation to the new photophase

along complete phase shifts, strongly suggesting that daily activity rhythms in seabream

could result from direct responses to the zeigeber. Moreover, although the feeding

schedule was maintained, curiously there was no apparent effect in rhythmicity,

suggesting photoperiod as the prevalent zeitgeber entraining gilthead seabream activity

rhythms.

Circadian rhythmicity in locomotor activity of gilthead seabream reared under DD

conditions was observed in Bold, Intermediate and control groups suggesting the

existence of an endogenous mechanism controlling its activity. Interestingly, Intermediate

fish exhibited a distinctive free-running activity rhythm of 23:22 h. On the other hand, Shy

seabream displayed an arrhythmic behavioural pattern, suggesting that this group might

rely almost exclusively in external environmental cues to entrain its rhythmicity.

The evidence and understanding of behavioural traits as consistent coping styles in fish

has a concurrently growing interest and their biological relevance makes it an important

aspect to consider in fish farming. Indeed, individual variation has been admittedly

reported to have implications in a wide range of fields, including aquaculture and fish

welfare (Huntingford & Adams, 2005; Martins et al., 2012), with numerous studies

demonstrating a link between coping styles and growth performance, health and welfare

(reviewed in Castanheira et al., 2015). In this context, understanding seabream

behavioural rhythms will certainly contribute to an improvement of culture protocols by

promoting an optimal synchronization between fish rhythms and their culture environment.


38

In conclusion, activity rhythms in gilthead seabream seem to be endogenously driven by a

circadian system but also strongly modulated by light. More importantly, this study has

demonstrated consistent behavioural patterns of opposing seabream coping styles,

suggesting that different coping styles might explain differences in adaptability to

environmental cues. Such differences might also explain the inter-individual variability

found in previous studies. However, additional studies will be required to further

investigate the different behavioural patterns observed for gilthead seabream opposing

coping styles and its underlying oscillatory mechanisms. Such information will vastly

improve the current knowledge of the ecophyiological and evolutionary meaning of the

behavioural patterns observed in laboratory.


39

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8. Appendices

Figure I. Schematic representation of the experimental set-up of one experimental unit used to

monitor gilthead seabream locomotor activity. All aquaria’s panes were lined with black plastic

keeping fish visually isolated from one another and from the observer. Locomotor activity was

monitored using infrared photoelectric sensors, installed outside each aquarium. Every time a fish

interrupted the infrared light beam emitted by the photocell, an output signal was produced, which

was then converted into a digital signal by the motherboard, and stored in 10 min bins using PC-

based specialized software.

45

Figure II. Chronograms of raw locomotor activity data for each group tested (Bold, Shy,

Intermediate) and for control groups (Control and Naïve) in experiment 1, recorded as counts of

activity per 10 mins.

46

Table I. Day and night percentages of mean locomotor activity displayed by the 3 experimental

(Bold, Shy, and Intermediate) and 2 control groups (Control and Naïve) of seabream exposed to

12:12 h light-dark cycle shifts in experiment I. Percentages for dark phase are highlighted in grey.

night 34,32 35,77 16,08 16,01 20,62

day 65,68 64,23 83,92 83,99 79,38

day 79,90 59,52 60,75 84,42 72,97

night 20,10 40,48 39,25 15,58 27,03

night 16,85 18,71 11,52 18,11 20,81

day 83,15 81,29 88,48 81,89 79,19

Ctrl

Group% Locomotor

activity during

photoperiod

12:12 h

DL

12:12 h

LD

12:12 h

DL

Bold Shy NaïveInter

Table II. Post-hoc test using Wilcoxon rank test. Pairwise comparisons between the 3 experimental

(Bold, Shy, and Intermediate) and the 2 control groups (Control and Naïve) of seabream exposed

to a 12 h photoperiod shift in experiment I.

Bold Shy Inter Ctrl

Bold - - - -

Shy < 0,001 - - -

Inter 1,00 0,21 - -

Ctrl < 0,001 < 0,001 < 0,001 -

Naïve 0,15 < 0,001 < 0,001 < 0,001

47

Table III. Cosinor parameters results for each of the 3 experimental (Bold, Shy, and Intermediate) and control groups (Control and Naïve) for experiment I.

MESOR (counts/10min)

Amplitude (counts/10min)

Acrophase (min)

% Ve pMESOR

(counts/10min)


Acrophase (min)

% Ve pMESOR

(counts/10min)


Acrophase (min)

% Ve p

Bold 25,11 11,12 1082:9 76,36 < 0,001 52,91 44,31 334:19 81,21 < 0,001 49,21 43,46 1106:16 81,79 < 0,001

Shy 10,76 4,20 1124:91 49,71 < 0,001 36,15 9,20 302:78 82,55 < 0,001 36,79 31,90 1069:58 80,39 < 0,001

Inter 32,18 29,58 1117:34 73,78 < 0,001 35,41 10,23 253:77 70,22 < 0,001 53,00 56,17 1059:13 73,85 < 0,001

Ctrl 55,82 49,73 1078 83,73 < 0,001 62,27 56,41 373:01 78,48 < 0,001 61,78 56,84 1149:81 77,90 < 0,001

Naïve 27,68 22,71 1069:56 75,21 < 0,001 53,87 34,21 369:14 89,01 < 0,001 54,34 42,17 1086:73 83,99 < 0,001

Group

Photoperiod

DL LD DL

Table IV. Periods of locomotor activity of the 3 experimental (Bold, Shy, and Intermediate), and control groups (Control and Naïve) exposed to photoperiod

shifts in for experiment I. Asterisks indicate statistically significant differences (p < 0,001).

τ (min) %V sig. τ (min) %V sig. τ (min) %V sig.

1438 36,58 *** 1441 71,26 *** 1441 73,03 ***

1441 34,49 *** 1441 38,69 *** 1439 65,56 ***

1441 66,99 *** 1513 22,42 *** 1439 66,85 ***

1441 77,93 *** 1439 65,55 *** 1441 68,47 ***

1441 56,22 *** 1441 82,08 *** 1439 72,42 ***

Bold

Shy

Inter

Naïve

Ctrl

GroupPhotoperiod

DL LD DL

48

Figure III. Chronograms of raw locomotor activity data, recorded as counts of activity per 10 mins,

for each group tested (Bold, Shy, Intermediate) and for control groups (Control and Naïve) in

experiment II.

49

Table V. Day and Night percentages of mean locomotor activity displayed by the 3 experimental

(Bold, Shy, and Intermediate), and control groups (Control and Naïve) of seabream exposed to a

12:12 h light-dark cycle and constant darkness conditions in experiment II. Percentages for dark

phase and DD conditions are highlighted in grey.

night 31,88 32,75 35,25 33,42 31,06

day 68,12 67,25 64,75 66,58 68,94

subjective

night40,36 47,54 48,09 41,23 38,09

subjective

day59,64 52,46 51,91 58,77 61,91

12:12 h

DD

% Locomotor activity

during photoperiod

Group

Bold Shy Inter NaïveCtrl

12:12 h

DL

Table VI. Post-hoc test using Wilcoxon rank test. Pairwise comparisons between the 3

experimental (Bold, Shy, and Intermediate) and the 2 control groups (Control and Naïve) of

seabream exposed to a 12:12 h light-dark cycle and constant darkness conditions in experiment II.

Bold Shy Inter Ctrl

Bold - - - -

Shy < 0,001 - - -

Inter < 0,001 < 0,01 - -

Ctrl < 0,01 < 0,001 < 0,001 -

Naïve < 0,001 1,00 < 0,01 < 0,001

50

Table VII. Cosinor parameters results for each of the 3 experimental (Bold, Shy, and Intermediate)

and control groups (Control and Naïve) for experiment II.

MESOR (counts/10min)


Acrophase (min)

% Ve pMESOR

(counts/10min)


Acrophase (min)

% Ve p

Bold 15,88 9,19 1166:44 51,00 < 0,001 21,27 7,47 1177:39 70,93 < 0,001

Shy 36,79 17,91 1109:83 72,87 < 0,001 24,20 1,95 969:09 82,95 0,146

Inter 41,05 23,52 908:39 77,98 < 0,001 32,28 10,94 738:69 77,67 < 0,001

Ctrl 24,82 13,80 977:55 76,03 < 0,001 18,41 5,47 1014:52 74,31 < 0,001

Naïve 37,64 21,25 1068:74 73,91 < 0,001 23,75 8,64 1031:51 79,88 < 0,001

Group DL DD

Photoperiod

Table VIII. Periods of locomotor activity of the 3 experimental (Bold, Shy, and Intermediate), and

control groups (Control and Naïve) of seabream exposed to a 12:12 h light-dark cycle and constant

darkness conditions in experiment II. Asterisks indicate statistically significant differences (p <

0,001).

τ (min) %V sig. τ (min) %V sig.

1444 23,94 *** 1442 21,38 ***

1426 32,69 *** 1594 10,76 0,22

1432 52,06 *** 1402 38,56 ***

1436 38,56 *** 1424 20,68 ***

1439 39,76 *** 1447 28,01 ***

Shy

Inter

Naïve

Ctrl

Photoperiod

Group DL DD

Bold

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