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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
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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.
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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)
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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
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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.
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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.
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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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i
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
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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
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Chronobiology in coping styles of gilthead seabream (S. aurata)
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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).
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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.
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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).
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Chronobiology in coping styles of gilthead seabream (S. aurata)
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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.
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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.
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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.
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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.
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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
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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).
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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.
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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).
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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.
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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).
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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.
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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
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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.
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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.
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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.
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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
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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.
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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.
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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.
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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.
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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.
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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
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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
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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
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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,
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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.
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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
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Chronobiology in coping styles of gilthead seabream (S. aurata)
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.
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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.
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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.
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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.
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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.
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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
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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)
Amplitude (counts/10min)
Acrophase (min)
% Ve pMESOR
(counts/10min)
Amplitude (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
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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.
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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
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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)
Amplitude (counts/10min)
Acrophase (min)
% Ve pMESOR
(counts/10min)
Amplitude (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