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*Time is more complex near the sea than in any other place, for in addition to the circling of the sun and the turning of the seasons, the waves beat out the passage of time on the rocks and the tides rise and fall as a great clepsydra.*

John Steinbeck - Tortilla Flat
# Chapter II:
The circadian clock of diatoms

This second chapter is devoted to my study of circadian rhythmic processes in diatoms and, more precisely, in *Phaeodactylum tricornutum*. The text is divided into four sections (subchapters II.a to II.d) as follows.

The first subchapter is devoted to a general description of rhythmic phenomena in the oceans and endogenous clocks in the organisms that inhabit them. The text presented is a review written for the journal *Annual Reviews of Marine Science* of which I am co-first author. This paper was written in collaboration with the research group of Kristin Teßmar-Raible, of the Max Perutz Laboratory at the University of Vienna, leaders in the characterization of lunar rhythms in marine animal models. The review provides an in-depth overview of the biological and ecological questions in which my research work has been embedded: the oceans are a complex and highly dynamic environment characterized by a series of rhythmic phenomena with different periodicity (tidal, diurnal, lunar and seasonal). Organisms must adapt to them in order to maximize their fitness and ensure evolutionary success. The text provides an overview of rhythmic biological processes in animals and eukaryotic algae, as well as of the endogenous molecular mechanisms that regulate such rhythmicity. This first subchapter completes what has already been introduced on biological rhythmic processes in Chapter I and places them in the marine ecological context. This first subchapter also delves into how environmental changes (natural and anthropogenic) can affect endogenous clocks and rhythmic biological phenomena. At the time of the completion of this manuscript, the review is under peer review.

The following three subchapters provide a description of the experimental work I performed to characterize biological rhythmicity in my model organism of choice, *P. tricornutum*. As in other photosynthetic organisms, a fine response to light stimuli is of paramount importance to *P. tricornutum*. For this, the daily rhythmic stimuli of light and dark have a major influence on the biology of this diatom on multiple levels: gene expression, metabolism, and cell division are the most prominent examples of processes synchronized with the external photocycles. Through my Ph.D. work, I contributed to discover how two bHLH-PAS proteins, bHLH1a and bHLH1b, play a role in regulating these processes by participating in the endogenous timekeeper machinery of *P. tricornutum*.

Subchapter II.b contains a first publication I co-authored in which the influence of bHLH1a (renamed RITMO1) on the transcriptional profile of *P. tricornutum* is described for the first time by using lines overexpressing this protein. In this work, my main contribution consisted in the refinement of a protocol for the analysis of cellular fluorescence rhythms by flow cytometry. This technique allowed to demonstrate that *P. tricornutum* presents diurnal oscillations in the content of fluorescent pigments per-cell, oscillations that persist after the release of the cultures in continuous light. The
novelty of this work consisted in clearly demonstrating that *P. tricornutum* presents an endogenous
oscillator that controls cellular physiology and in identifying by transcriptomic exploration of the
rhythmic TF the first possible regulator of these rhythms. In addition, phylogenetic analysis revealed
a wide distribution of RITMO1-like proteins in the genomes of diatoms, suggesting a possible
conservation of function in these phototrophs.

The following subchapter II.c presents a detailed investigation of *P. tricornutum* rhythmicity
in response to different environmental photoperiods and light irradiance intensities. The role of
RITMO1 has also been investigated through the generation of KO mutant lines. Obliteration of this
protein leads to a major alteration in the persistence of the rhythms of in cellular fluorescence in cells
released under continuous light, thus confirming that RITMO1 plays a role in the circadian clock
machinery. More importantly, through a time-resolved analysis of the expression levels of a set of
rhythmic genes, I was able to demonstrate how obliteration of RITMO1 eliminates the persistence
of the transcriptional oscillations exhibited by the wild type line in free run conditions. This suggests
that RITMO1 represents indeed a central transcriptional regulator in the pacemaker of *P. tricornutum* and allows to propose it as a central clock component of this alga. To conclude, by
exploiting a technique based on chlorophyll fluorescence analysis, I was also able to demonstrate that
the circadian clock exerts control over the photosynthetic machinery in *P. tricornutum*, as mutation
of RITMO1 results in a loss of the oscillations in free-running maximal photosynthetic capacity.

Finally, subchapter II.d provides a preliminary characterization of the bHLH1b protein in
the circadian clock of *P. tricornutum*. The analysis by Yeast Two Hybrid (Y2H) assay indicates that
RITMO1 and bHLH1b can physically interact at the level of their bHLH domain, corroborating
their co-implantation in the same molecular process. Furthermore, KO mutants for this protein show
altered cellular fluorescence rhythmicity similar to that presented by RITMO1 mutants, although to
a lesser extent, suggesting a similar implication in endogenous clock regulation. These assays
represent the first effort aimed at molecular dissection of the circadian clock in diatoms, as well as
the first characterization of the function of bHLH-PAS proteins in these algae.
Chapter II.a:

Rhythms and clocks
in marine organisms

N. Sören Häfker<fnref n="1" />,<fnref n="2" />*, Gabriele Andreatta<fnref n="1" />,<fnref n="2" />*, Alessandro Manzotti<fnref n="3" />*, Angela Falciatore<fnref n="3" />*, Florian Raible<fnref n="1" />,<fnref n="2" />*, and Kristin Tessmar-Raible<fnref n="1" />,<fnref n="2" />*

Keywords: endogenous oscillators, environmental cycles, climate change, circadian,
circatidal, circalunar, circannual, algae, animals

This chapter has been written upon invitation by Annual Reviews of Marine science and is
currently under peer-review.

I was responsible for the conception and editing of paragraph 3, *Rhythms in the life of marine algae*, as well as for the conception and editing of Figures 2 and 3, Tables 1 and 2 and Table Supplementary S1.

<footnote n="1">¹Max Perutz Labs, University of Vienna, Vienna BioCenter, Dr. Bohr-Gasse 9/4, 1030 Vienna, Austria</footnote>

<footnote n="2">²Research Platform “Rhythms of Life”, University of Vienna, Vienna BioCenter, Dr. Bohr-Gasse 9/4, A-1030 Vienna, Austria</footnote>

<footnote n="3">³ Laboratoire de Biologie du chloroplaste et perception de la lumière chez les micro-algues, UMR7141, CNRS, Sorbonne Université, Institut de Biologie Physico-Chimique, Paris, 75005, France</footnote>

<footnote>*equal contribution</footnote>

<footnote>* contacts:</footnote>

<footnote>angela.falciatore@ibpc.fr
florian.raible@univie.ac.at
kristin.tessmar@mfpl.ac.at</footnote>
Abstract

The regular movements of waves and tides are obvious representations of the oceans'
rhythmicity. But the rhythms of marine life span across ecological niches and time scales, including
short (in the range of hours) and long periods (in the range of days and months). These rhythms
regulate physiology and behavior of individuals, as well as their interactions with each other and the
environment. This review highlights examples of rhythmicity in marine animals and algae that
represent important groups of marine life and different habitats. The examples cover ecologically
highly relevant species and a growing number of laboratory model systems that are used to disentangle
key mechanistic principles. The review introduces fundamental concepts of chronobiology, such as
the distinction between rhythmic and endogenous oscillator-driven processes. It also addresses the
relevance of studying diverse rhythms and oscillators, as well as their interconnection, for better
predictions of how species will respond to environmental perturbations, including climate change. As
the review aims to address scientists from the diverse fields of marine biology, ecology and molecular
chronobiology, which all have their own scientific terms, we provide a term glossary at the end of the
text.
# 1. Cycles of the sun and moon cause a multitude of biological rhythms

"The blue marble" is the title of a series of images produced during various NASA missions, starting with the Apollo 17 mission in 1972. The view of Earth from space (Fig. 1a) not only prominently pictures the fact that marine environments are dominating Earth, but is also a reminder that as part of the solar system, our planet is exposed to regular astronomical and geophysical cycles. The most relevant of these are the rhythmic impacts of sun and moon, which shape physico-chemical cycles that organisms have been exposed to since the dawn of life. Adaptations to these cycles have therefore likely been a fundamental aspect for survival. The relative positions of sun, moon and earth results in cycles with a complexity of different period lengths, ranging from tidal periods in the range of 12 hours, over diel and monthly periods to annual/seasonal cycles (Fig. 1g,h). Furthermore, these cycles differ depending on geographic location (Fig. 1b-f).

Life is commonly assumed to have originated in the marine environment, and thus in an ecosphere dominated by periodicity on these different time scales. A broad number of species indeed make use of distinct cycles generated by sun and moon to adjust their behavior and physiology, as detailed below. In chronobiology, the regular re-occurrence of a distinct physiological, behavioral or cellular event is referred to as a "biological rhythm". Periodicities of these rhythms approximate those of the underlying natural cycles (Fig. 1g,h). An important conceptual distinction concerns the question of how biological rhythms are elicited: on the one hand, biological rhythms can result from direct organismal responses to environmental cycles. On the other hand, biological rhythms are often caused by endogenously driven

cellular/molecular oscillators, also referred to as inner "clocks" or "calendars". Such endogenous oscillators, in turn, are synchronized to the respective environmental cycles by a process called "entrainment". Endogenous oscillators allow organisms to anticipate predictable changes in their environment, and therefore adjust their behavior and physiology before the actual changes occur (Dodd et al. 2014). In many scenarios, this ability is likely advantageous for the fitness of a species (Dodd et al. 2005; Johnson & Golden 1999; Krittika & Yadav 2020; Ouyang et al. 1998; Sanchez et al. 2011). The general mechanistic principle of such oscillators are positive-negative feedback loops, using different cell-biological processes. So far, circadian clocks in land organisms are the only clocks understood in molecular mechanistic detail. Whereas animals, plants and fungi all rely on transcriptional/translational feedback loops (TTFLs) for their central clock machinery, and phosphorylation/de-phosphorylation cycles play critical roles, the exact molecular factors in these three groups are not homologous, or only to a limited extent (Brenna & Albrecht 2020; Narasimamurthy & Virshup 2021; Saini et al. 2019; Yan et al. 2021; Yildirim et al. 2022). Furthermore, also non-TTFL-based ~24hr oscillatory systems exist. Even though these were originally uncovered in the marine alga *Acetabularia* (Sweeney et al. 1967), they are mainly investigated in terrestrial systems (Edgar et al. 2012), and knowledge on their molecular mechanisms remains scarce. The understanding of other oscillatory systems (e.g. circatidal,
<figure><img src="image_18.png" /><figcaption>Figure 1. Complex rhythms emerge from solar and lunar cycles in marine ecosystems.</figcaption></figure>

(a) Earth and moon as seen from space; arrows highlight coordinates used in panels d-f; (b, c) Summary of weekly solar and lunar photocycles, with the perimeter indicating hours of the day, and concentric circles representing consecutive days (1-7). The daily cycles of solar light cause the well-known diel light cycle of ~24 hours. The gradual shifts of moonrise and moonset cause an independent – lunidian – photocycle, with an average period of ~24.8h. (d-f) Exemplary 7-day diagrams covering one month (new moon, waxing moon, full moon, waning moon) around summer (top) and winter (bottom) solstices on three distinct coastal locations of different latitude, illustrating the complexity of superimposed solar and lunar light cycles; (g) overview over the period lengths of major natural cycles and in italics the associated (endogenous) biological rhythms generated by the solar (top) and lunar (bottom) photocycles; (h) period lengths of major natural cycles and associated biological rhythms generated by the lunar gravitational cycles. Tidal cycles have a basic period length of half a lunar day (~12.4h), while the mutual constellation of moon, earth and sun also causes a longer cycle (semilunar, ~14.8 days, spring tides).
circalunar, circannual) is less advanced and
particularly for the interplay between solar and
lunar timing systems, marine systems have
been helping significantly to advance our
understanding (see below).

If or not a rhythm is endogenous,
needs to be experimentally determined: a
hallmark of inner oscillators is a “free-
running” biological rhythm even under
environmental conditions that do not provide
regular cues for the entrainment of the
investigated rhythm. The individual cases
highlighted in the following sections argue that
molecular oscillators are likely present across
a diverse array of marine species and period
lengths. By contrast, most of our molecular
and cellular knowledge about the molecular

sensors and timing systems still stems from
terrestrial model systems. We will outline
below that such models have natural
limitations for marine chronobiology; in turn,
chronobiological research in marine
organisms can help to understand phenomena
still present in non-marine species. To cover
at least a part of the marine species diversity,
this review focuses on animals and the
polyphyletic group of eukaryotic algae.
Chronobiological research on these groups
has particularly advanced during recent years,
they represent different levels of marine
environments (Fig. 2) and the food web, and
the comparative overview also begins to
address biodiversity and evolution of
timekeepers in eukaryotic organisms.

2. Other places, other rhythms: The
oceans harbor multiple and diverse
habitats with very different properties from
land

As outlined in the preceding section,
the regular cycles of sun and moon produce
the principle physical framework that
generates regular environmental cycles, but
the exact nature of these cycles depends on the
habitat and its chemo-physical properties.
This aspect is particularly relevant when
considering the rhythmic biological processes
present in terrestrial vs. marine environments
and across the diversity of marine habitats
(Fig.2). Temperature is a prominent cyclic cue
for terrestrial organisms, both for diel and
annual cycles (Buhr et al. 2010; Chen et al.
2015; Watson & Smallman 1971; Yocum et al.
2016). In marine environments, however,
temperature rhythms (on daily and yearly
scales) are mainly restricted to tidal habitats
and uppermost surface layers (d'Alcalà et al.

2004). At which exact depth temperature
changes rhythmically differs between locations
and depends on water currents and mixing,
which can even vary between days (Moum
2021). Moreover, temperature can be quite
strongly off-set from photoperiod (Häfker et
al. 2018b): for instance, Mediterranean
seawater at the Gulf of Naples in 50-70m
depths is warmest between October-
December and cooler throughout the rest of
the year (d'Alcalà et al. 2004). Furthermore,
seasonal temperature cycles and the timing of
sea ice break-up/formation in polar regions
are typically delayed relative to the
photoperiod cycle (Kahru et al. 2010; Wallace
et al. 2010). As we will discuss in section 5, the
fact that temperature is a less predictable cue
in marine environments, but at the same time
<figure><img src="image_19.png" /><figcaption>Figure 2. Overview of the diverse marine habitats and discussed exemplary organisms.</figcaption></figure>

Important subdivisions of marine habitats include open waters (pelagic) vs. sea floor (benthic), as well as
nearshore shelf seas (neritic) vs. the open ocean (oceanic). Temporary air exposure defines the intertidal zone.
Differences in light penetrance further separate euphotic (typically 0-200m depth), dysphotic (200-1000m
depth) and aphotic (>1000m) zones. Each of these zones exhibits different combinations of rhythmic factors
relevant to its inhabitants.

strongly influences biomass production, also
has significant consequences for the effects of
climate change on marine ecosystems.

Light is another cyclic cue that is of
relevance for the rhythmicity of organisms,
and its penetrance is an important factor for
the definition of marine habitats (Fig. 2). In
those accessible by light, the outlined
astronomical photocycles (Fig. 1) define basic
patterns of rhythmicity that can be used by
marine organisms. However, position,
especially water depth, as well as distance to
coast, strongly impact on the overall amount
and spectral quality (Austin & Petzold 1986).
Moreover, the biological rhythmicity itself can
have secondary effects on light. For instance,
seasonal phytoplankton blooms significantly
affect light penetrance to deeper habitats. In
addition, many marine organisms do not only
move (actively or passively) horizontally, but
also in depth, and thereby between habitats.

Such vertical migrations can span across
several hundred meters within a single day
(Brierley 2014; van Haren 2007). For
planktonic organisms, this phenomenon,
known as diel vertical migration (DVM), is
likely under circadian clock control (Häfker et
al. 2017). Besides plankton, many other
marine organisms exhibit vertical migrations,
including top predators like fish, squids and
whales (Chambault et al. 2021; Christiansen et
al. 2019; Gilly et al. 2006; Sims et al. 2005).
How are the entrainment mechanisms of any
potential endogenous oscillator adapted to the
drastic environmental changes that occur
during such vertical migrations?

Besides light or temperature,
additional cues such as salinity, mechanical
forces, pressure or magnetic field changes
(Aguzzi et al. 2011; Hewson-Browne 1973)
can provide a rhythmic framework
unparalleled on land. Taken together, it is
therefore obvious that research on terrestrial
model systems can only provide limited
mechanistic insights into the chronobiology of
marine species. In order to understand more
about these mechanisms, biological analyses
on marine species amenable to functional
molecular investigations need to be
interconnected with long-term measurements
of environmental parameters. For instance,
systematic long-term quantification of light

conditions in a benthic habitat and
corresponding laboratory experiments with
molecular read-outs have unraveled a new role
of UVA-light for seasonal adjustments (Veedin
Rajan et al. 2021).
3. Rhythms in the life of marine algae

<figure><img src="image_20.png" /><figcaption>Figure 3. Established and emerging marine microalgal model systems for chronobiology.</figcaption></figure>

Evolutionary position of established and emerging marine microalgal model systems in the eukaryotic tree of life. The groups including microalgae are reported in colors. SAR clade, including *Stramenopila*, *Alveolata*, and *Rhizaria*, is highlighted. Adapted from (Brodie et al. 2017).

The word “alga” subsumes highly diverse photosynthetic species widely distributed in the photic zone (Fig. 2). Derived by a series of endosymbiotic events (Blaby-Haas & Merchant 2019; Brodie et al. 2017; Keeling 2013), algae are positioned throughout the major groups of the eukaryotic tree of life (Fig. 3). A crucial ecological role in the marine environment is played by phytoplankton, also known as microalgae, which produce at least 50% of the world’s oxygen and primary organic biomass (Pierella Karlusich et al. 2020).

A variety of biological rhythms have been described in algae. Strong diurnal and circadian regulation of gene expression has been described under laboratory conditions in different taxa (e.g. (Corellou et al. 2009;

Poliner et al. 2019; Sorek et al. 2013), Suppl.Table 1) and diurnal rhythmicity of gene expression has been recently found in plankton communities from the natural environment (Coesel et al. 2021; Kolody et al. 2019). Rhythmic cell division is well documented for algae (e.g. (Chisholm & Brand 1981; Moulager et al. 2007; Sweeney & Hastings 1958), and Suppl.Table 1), as in plants (Fung-Uceda et al. 2018) and animals (Matsuo 2003), suggesting that this circadian function is critical for environmental adaptations. For algae, light not only serves as environmental information source, but is also the primary source of energy for photosynthesis. Consistent with this notion, endogenous daily rhythms of photosynthetic activity and related processes have been described in most algae (e.g. (Brand 1982;
Hastings et al. 1961; Ragni & d' Alcalà 2007), Supp.table 1), suggesting that the tight temporal control of energy metabolism by a circadian clock is advantageous for algae, as previously shown for plants (Dodd et al. 2005). Photosynthesis may, in turn, represent an input for the regulation of the algal circadian clock itself as already shown in plants (Haydon et al. 2017) and similar to food cues in animals (Asher & Sassone-Corsi 2015).

Periodic changes in algal photosynthetic metabolism also impacts on symbiotic associations with animal partners. These associations supply the heterotroph host with organic products of photosynthesis to match energy needs, and are especially relevant in waters where nutrient levels are low (Muller et al. 2009). In corals that facultatively host the photosynthetic dinoflagellate *Symbiodinium sp.*, the dinoflagellate's photosynthesis follows endogenously-regulated circadian rhythms (Sorek & Levy 2012). These persist during association with the coral hosts, unlike other circadian processes such as cell division and motility that are rhythmic only in free living algae (Sorek et al. 2013). In turn, the aposymbiotic anemone *Aiptasia diaphana* shows dominant circatidal transcriptional dynamics, but these change to predominantly circadian patterns when anemones are associated with the symbiont (Sorek et al. 2018).

In different algae, the circadian clock also contributes to the regulation of population behavior (SuppTable 1). Phytoplankton exhibits diurnal vertical migrations (Sournia 1975), but on a much smaller scale compared to zooplankton (see also section 4 below). Endogenous rhythms of bioluminescence (Hastings & Sweeney 1957) and cellular aggregation (Hastings & Sweeney 1957; Roenneberg et al. 1989; Roenneberg & Morse 1993) have also been described.

In addition, algae also exhibit moon-related cycles. Migratory rhythms in intertidal

sediments synchronized with diurnal and tidal cycles have been reported in different diatom species (Mitbavkar & Anil 2004; Round & Palmer 1966) and semidiurnal (12-h) gene expression periodicity has been documented in the diatom *Seminavis robusta* (Bilcke et al. 2021), likely reflecting adaptations to the tides in coastal ecosystems. Sexual reproduction is another process tangled with moon rhythms in algae. Multicellular algae have long been known to show synchronous gamete release patterns following lunar or semilunar periodicity (Andersson et al. 1994; Brawley & Johnson 1992).

Rhythmicity in algae also extends to cycles of longer period length: Composition and dynamics of phytoplanktonic populations exhibit strong seasonal patterns. Different taxa show seasonal bursts (algal blooms) in a specific area, generally interspersed with periods of apparent absence from the water column. External cues such as nutrients, light or predators (Reynolds 2006), photoperiodic variations or temperature changes (Lambert et al. 2019) can act as important drivers of community dynamics. In certain cases, there is even evidence for endogenous control on an annual scale, like in kelp (belonging to Stramenopiles) where growth was shown to be under circannual control (Lüning 1991; Schaffelke & Lüning 1994; tom Dieck 1991). Moreover, the activation of resting cysts of the dinoflagellate *Alexandrium* appears to follow an internal, circannual timing system (Matrai et al. 2005). The discovery of biannual patterns of sexual reproduction in the marine diatom *Pseudo-nitzschia multistriata* (D'Alelio et al. 2010) additionally highlights the robust long-term organization of the phytoplanktonic life cycle. Research into the dissection of the mechanisms that orchestrate algal rhythmicity on different timescales is not only scientifically promising, but also of tremendous relevance for ocean ecosystems.
Algal models for the elucidation of marine time-keeping mechanisms

As outlined above, a variety of ecologically
crucial biological rhythms have been
described in algae. By contrast, far less
information is available on the underlying algal
timekeepers. Below, we briefly summarize the
available knowledge on the molecular clock of
these models (Fig. 3, Table 1). Important
insights into algal timing systems were derived
from research on the pykoeukaryote
*Ostreococcus tauri*, the smallest known free-
living marine eukaryote (Courties et al. 1994).
The small genome of this green alga (13Mbps,
(Derelle et al. 2006)) harbors a minimal
timekeeper that is formed by only two
transcription factors: TOC1 and CCA1
(Corellou et al. 2009). Both factors are
homologous to central circadian clock
components of land plants (Creux & Harmer
2019) and of the fresh water green alga
*Chlamydomonas reinhardtii* (Schulze et al.
2010). CCA1 is also conserved in the
thermoacidophilic red alga *Cyanidioschyzon
merolae* (Miyagishima et al. 2014). This
indicates that critical TTFL components
might have a common origin in
Archaeplastida.

Regarding the SAR (*Stramenopila*,
*Alveolata*, *Rhizaria*) supergroup, information
on the circadian clock is emerging from the
study of diatoms, prominent aquatic
microalgae evolved by secondary
endosymbiosis (Falciatore et al. 2020).
Remarkably, the genomes of these algae lack
clear homologues of bacteria, plants or animal
circadian clock components, with the
exception of cryptochromes and casein
kinases (see below) (Farré 2020; Poliner et al.
2019). A survey for rhythmic transcription
factors of the diatom *Phaeodactylum
tricornytum* (Pt) identified proteins with
bHLH and PAS domains as putative circadian
clock components (Annunziata et al. 2019),
reminiscent of animal circadian clocks that

make use of bHLH-PAS domain transcription
factors (Gekakis 1998). The additional
presence of RITMO1-like proteins in other
Stramenopiles (e.g. *Nannochloropsis*,
*Ectocarpus*), as well as in Alveolates
(Annunziata et al. 2019; Farré 2020; Thiriet-
Rupert et al. 2016), is consistent with a
circadian function of these transcription
factors among the SAR. Another putative
regulator of the diatom circadian clock is the
blue-light sensor animal-like
cryptochrome/photolyase 1 of *P. tricornutum*
(*Pt-CPF1*). This protein and its *O. tauri*
ortholog can function as transcriptional
repressors in mammalian cell culture by
interacting with the mammalian core circadian
clock components CLOCK:BMAL (Coesel et
al. 2009; Heijde et al. 2010). This suggests a
conserved involvement of
cryptochrome/photolyase in circadian TTFL
processes of animals and algae. However,
while *Ot-CPF1* is functionally involved in the
maintenance of the *O. tauri* circadian clock,
this alga misses bHLH-PAS transcription
factors, as do other Archaeplastida (Heijde et
al. 2010), pointing at possible limitations in the
interpretation of heterologous cell culture
studies.

Studies in algae have also contributed
to reveal the existence of transcription-
independent oscillators (TIOs). Initial insights
derived from enucleated unicellular green alga
*Acetabularia spp.* (Mergenhagen & Schweiger
1975; Sweeney & Haxo 1961), were followed
by the discovery of endogenous
bioluminescence rhythmicity in the
dinoflagellate *Lingulodinium polyedrum*
(formerly *Gonyaulax polyedra*) (Hastings
2007; Morse et al. 1989a,b). In this alga,
luciferase bioluminescence is regulated via a
transcription-independent mechanism relying
on an RNA-binding protein named Circadian-
Controlled Translational Regulator (CCTR).
CCTR represses the translation of luciferin
binding protein (LBP) in a circadian fashion,
by rhythmically binding a target sequence in
the 3'UTR of the respective mRNA (Mittag et
al. 1994). Moreover, work on *O. tauri*
identified rhythmic oxidation of
peroxiredoxin (PRX) (Bouget et al. 2014;
O'Neill et al. 2011). PRX rhythms persist in
constant darkness, a condition under which *O.
tauri* transcription stops. PRX rhythms were
found to be conserved across many kingdoms
of life, including cyanobacteria, archaea, fungi
and animals (Edgar et al. 2012; O'Neill et al.
2011). Given the role of PRX in the
detoxification of Reactive Oxygen Species
(ROS) by-products of cellular metabolism, it
has been proposed that the evolutionary origin
of circadian timekeeping might be linked to
diel cycles of redox stress, and that more
species-specific *TTFL* clockworks evolved
independently later in the different eukaryotic
lineages (Edgar et al. 2012).

As in other organisms, the circadian
clock of algae is entrained by cyclic

environmental signals. Physiological analyses
provide evidence that blue and red light play
an important role in the entrainment (e.g.
(Poliner et al. 2019; Roenneberg & Hastings
1988). Diverse blue-light absorbing proteins
have been identified in the genome of algal
model systems, and their involvement in
circadian regulation has been demonstrated in
some species. By contrast, red/far red light-
sensitive phytochromes have only been found
in some diatom species (Fortunato et al.
2016), possibly due to the strong attenuation
of long wavelengths underwater.

In addition to light, fundamental
concepts on the temperature compensation of
the circadian oscillators arose from early
studies on the bioluminescence of *L.
polyedrum* (Hastings & Sweeney 1957). More
recent studies on circadian clock features of
*Nannochloropsis spp.* (Poliner et al. 2019)
and of coral-symbiotic algae (Sorek & Levy
2012) support this notion. The pathways
implicated in these mechanisms, however,
remain to be elucidated.
<table><caption>Table 1. Characterized regulators, central clock system components and rhythmic outputs of marine algal models.</caption><thead><tr><th>Marine algal models</th><th>Photoreceptors and modulators</th><th>Clock components</th><th>Rhythmic circadian biomarkers</th><th>References</th></tr></thead><tbody><tr><td>Ostreococcus tauri (green alga, mamiellophyceae)</td><td>CPF1 Cry-DASH LOV-HK Ot-HKR CK</td><td>Evidences for TTFL CCA1/TOC1 Evidences for TIO</td><td>gene expression (LUC reporter), endogenous fluorescence, cell division, magnesium fluxes, PRX redox state</td><td>Heijde et al. 2009; Luck et al. 2019; Djouani-Tahri et al. 2011; Corellou et al. 2009; Moulager et al. 2007; Feeney et al. 2016; Le Bihan et al. 2015; O'Neill et al. 2011; Derelle et al. 2006; Lozano et al. 2014; van Ooijen et al. 2011, 2013</td></tr><tr><td>Acetabularia spp. (green alga, ulvophyceae)</td><td>ARI ARII</td><td>Evidences for TIO</td><td>cloroplast migration, photosynthesis, oxygen production</td><td>Tsunoda et al. 2006; Wada et al. 2011; Sweeney et al. 1961; Koop et al. 1978; Neuhaus et al. 1986; Leebens-Mack et al. 2019</td></tr><tr><td>Phaeodactylum tricornutum (diatom)</td><td>CPF1 CryP Cry-DASHs AUREOs RHO DPH CK</td><td>Evidences for TTFL bHLH/PAS (RITMO1)</td><td>photosynthesis, cellular fluorescence, pigment synthesis, gene expression</td><td>Coesel et al. 2009; Fortuntato et al. 2016; König et al. 2017; Mann et al. 2020; Palmer et al. 1964; Ragni et al. 2007; Annunziata et al. 2019; Bowler et al. 2008; Falciatore et al. 2020</td></tr><tr><td>Nannochloropsis spp. (eustigmatophyte)</td><td>AUREOs CPF Cry-DASH CK</td><td>Evidences for TTFL bHLH/PAS</td><td>gene expression (LUC reporter), photosynthesis, pigment synthesis, cell division</td><td>Vieler et al. 2012; Wang et al. 2014; Braun et al. 2014; Poliner et al. 2018; Poliner et al. 2019; Farré 2020</td></tr><tr><td>Lingulodinium polyedrum (formely Gonyaulax polyedra, dinoflagellate)</td><td>CRYs Cry-DASH putative red light sensor CCTR protein phosphorylation</td><td>Evidences for TIO</td><td>cell division, swimming, aggregation, endogenous bioluminescence, photosynthesis</td><td>Roenneberg et al. 1997, 1988, 1989, 1993; Hastings et al. 1957, 1958, 2007; Sweeney 1958; Mittag et al. 1994; Johnson et al. 1984; Morse et al. 1989; Mackenzie et al. 2011; Comolli et al. 2003; Beauchemin et al. 2012</td></tr><tr><td>Symbiodinium spp. (dinoflagellate, coral symbiont)</td><td>CRYs RHO putative red light sensor</td><td></td><td>cell division, motility, gene expression, photosynthesis, oxygen production, pigment synthesis</td><td>Fitt 1983; Sorek et al. 2012a, 2012b, 2013, 2014; Liu et al. 2018; Aranda et al. 2016; Lin et al. 2015; Shoguchi et al. 2013</td></tr></tbody></table>

Components for which a role in circadian rhythm regulation has been demonstrated are reported in green, while putative regulators for which an empirical characterization is missing are reported in red. Background colors refer to the supergroups of Fig.3. Abbreviations: CPF, Cryptochrome Photolyase Family; CRY-DASH, Cryptochrome-DASH; LOV-HK, LOV-Histidine Kinase, ot-HKR, Ostreococcus tauri Rhodopsin Histidine Kinase; CK, casein Kinase; ARI and ARII, Acetabularia Rhodopsin I and II; CryP, Plant-like cryptochrome; AUREO, Aureochrome; RHO, Rhodopsin; DPH, Diatom Phytochrome; CCTR, Circadian-Controlled Translational Regulator; TIO, transcription-independent oscillator; CCA1, Circadian Clock Associated 1; TOC1, Timing of CAB expression 1; bHLH-PAS, basic Helix-Loop-Helix/Per-ARNT-SIM protein; LUC, luciferase; PRX, peroxiredoxin. Table adapted from (Noordally & Millar 2015). Although not directly related to algae chronobiology, in the "references" column we are reporting additional useful works concerning genomic and mutagenesis/transgenesis resources in the respective model organisms.
4. Animal models for marine
chronobiology

In this section we present examples of
prominent rhythmic phenomena, as well as
animal models that have helped to start
disentangling a variety of marine biological
timers. We especially cover the naturally

highly relevant interplay of solar and lunar
timing cues.

Vertical migrations in the pelagic zone

As mentioned above, one of the
Earth's largest regular biomass movements is
the diel vertical migration (DVM) of marine
plankton (Brierley 2014). This very
heterogeneous group of species represents a
key component of the ocean food network.
Commonly, zooplankton migrates to the water
surface at dusk, returning to depths at dawn,
thought to represent the balance between
feeding needs and predator avoidance (Fortier
et al. 2001; Pearre 2003; van Haren &
Compton 2013).

Although solar light represents the
main reported stimulus synchronizing DVM
(Kaartvedt 2010; van Haren & Compton
2013), moonlight also affects its rhythm,
especially during polar nights, when
periodicity shifts from the solar-cycle (24 hrs)
to the lunidian-cycle (24.8hrs) (Gilly et al.
2006; Kaartvedt 2010; Last et al. 2016, 2020).
Solar and lunar eclipses (Strömberg et al.
2002; Tarling et al. 1999), as well as other
phenomena, presumably influencing local
light intensities (i.e. storms and clouds) have
been shown to also affect the dynamics of
vertical migrations (Omand et al. 2021). Of
note, DVMs persist during the darkest part of
the polar night (Berge et al. 2009, 2015; Last
et al. 2020), and in the deep sea (van Haren &
Compton 2013), suggesting the existence of an
endogenous oscillator coordinating these
migration events.

Among the marine models that are
used to investigate the molecular mechanisms
of DVM are the Northern and Antarctic krill
(Cohen et al. 2021; Piccolin et al. 2020) and
the copepod *Calanus finmarchicus* (Häfker et
al. 2017). Studies on these organisms are
consistent with an involvement of the
conventional circadian clock in DVM
regulation (Biscontin et al. 2017; Häfker et al.
2017; Teschke et al. 2011). Putative core
circadian clock genes of both krill and *Calanus*
species show a diel/circadian transcriptional
oscillation both in the field, laboratory LD and
DD conditions (Häfker et al. 2017; Teschke
et al. 2011). Transcriptional dynamics
(including core circadian clock gene
expression) showed ~24hr rhythms even
under the polar “midnight sun” in *C.
finmarchicus*, but also several ultradian
patterns (including circatidal frequencies) in
ice-covered areas (Hüppe et al. 2020; Payton
et al. 2020). Consistently, DVM rhythms of
the Antarctic krill (*Euphausia superba*) shifted
from ~24 hrs in LD to ~12 hrs in DD (Piccolin
et al. 2020). ~50% of the krill transcriptome
oscillated with a ~24 hrs rhythm in LD, while
under DD conditions, the dominant
molecular signature exhibited frequencies of
~12-15 hrs (~40% of the transcripts)
(Biscontin et al. 2019). Taken together, these
data indicate a possible plastic nature of a
circatidal/circadian/circalunidian clock in
zooplankton and/or polar species (for more
details see below).

Whereas DVMs occur at any latitude,
another type of vertical migration, yet with
annual period, occurs mostly in temperate and
polar regions, and is typically associated with
diapausing strategies. In copepods, a
facultative diapause occurs during times of low
productivity in autumn/winter. Individuals
migrate to large depths, where they will spend
several months (Baumgartner & Tarrant 2017;
Lenz & Roncalli 2019). Despite several
phenotypic and (high-throughput) gene
expression studies (Aruda et al. 2011;
Baumgartner & Tarrant 2017; Christie et al.
2016; Clark et al. 2013; Häfker et al. 2018b;
Lenz & Roncalli 2019; Roncalli et al. 2018;
Schründer et al. 2013; Tarrant et al. 2016) the
underlying mechanisms are still unclear. This
includes the question if endogenous
oscillator(s) or direct
environmental/physiological cues are
responsible for this annual rhythm. Similarly,
seasonal-dependent signatures have been
identified in the transcriptome of the Antarctic
krill *E. superba*, when the species enters
winter quiescence, a state of metabolic
reduction (Höring et al. 2021), but the driving
forces remain to be determined. Considering
the key position of copepods and krill in
pelagic food webs, understanding the factors

Rhythms in the deep sea

The deep sea had long been
considered an arrhythmic environment with
low and steady biological rates due to
darkness, average temperatures below 4°C,
high pressure, and limited food availability or
driven by “spontaneous” hydrothermal vent
activity, caused by plate tectonics.
Chronobiological studies require either
long(er)-term or repeated measurements,
while ensuring that those measurements do
not distort the results. Indeed, sample
collection takes several hours to just bring on
board, while camera observations will generate

and mechanisms driving their diel and
seasonal rhythms is highly relevant (see also
section 5 for a discussion on adaptability).

The regular migrations of zooplankton communities often drive similar phenomena in their mesopelagic and epipelagic predators, such as fish and sharks. Indeed, DVMs have been documented in the European hake *Merluccius merluccius* (De Pontual et al. 2012), the glacier lanternfish *Benthosema glaciale* (Dypvik et al. 2012a,b), the Pacific cod *Gadus macrocephalus* (Nichol et al. 2013), the Japanese eel *Anguilla japonica* (Chow et al. 2015), the jumbo squid *Dosidicus gigas* (Gilly et al. 2006) and the deepwater bluntnose sixgill shark *Hexanchus griseus* (Coffey et al. 2020). Modern strategies, including pop-up satellite transmitters and machine learning approaches, facilitate the assessment of diel, seasonal, or other migratory dynamics in larger animals like eels (Chang et al. 2020), bigeye thresher (*Alopias superciliosus*) (Coelho et al. 2015), whale sharks (Andrzejaczek et al. 2021), and sperm whales (Chambault et al. 2021).

There are many rhythms and possible
endogenous oscillators that critically
determine the interaction within and across
marine species that await mechanistic analyses.

unnatural light exposure. This has
complicated studies about possible temporal
components in deep sea life.

However, evidence for environmental
rhythms, such as seabed currents with periodic
changes in velocity and direction, as well as
temperature changes are emerging (Wagner et
al. 2007). Deep sea tidal changes (“internal
tides”) occur when coastal/surface tides
propagate vertically across water layers with
different properties (often cold and warm,
respectively), along the water column (Garrett
2003). The advance of observatory technology and long-term infrastructure investments identified tidal (Cuvelier et al. 2017), diel, lunar (Mercier et al. 2011) and seasonal rhythms in different categories of animal life, covering behavior, growth rates, abundance and reproduction (Aguzzi et al. 2011; Baillon et al. 2014).

Molecularly, circatidal oscillations in melatonin levels from isolated pineal glands and retinae were observed in deep-sea fish (Wagner et al. 2007). Transcriptome sequencing from vent crabs and mussels started to set up resource to understand the molecular mechanism underlying the adaptation to the extreme hydrothermal vent habitat, including conventional animal core

circadian clock genes (Hui et al. 2017; Zheng et al. 2017). Such transcriptomic sequencing combined with repeated deep-sea on-site organism fixation and behavioral observations under red light allowed the identification of correlational tidal signatures in the behavior and transcriptome of the gill tissue of the vent mussel *Bathymodiolus azoricus* (Mat et al. 2020). Of note, the putative core circadian clock genes *period*, *timeless* and *cry1* (a *dCry/L-Cry* ortholog) exhibited ~tidal rhythms in field samples (Mat et al. 2020), suggesting plasticity of the ~24hr oscillator. Similarly, putative core circadian clock genes showed daily and/or tidal oscillations in the Arctic scallop *Chlamys islandica* during equinox and polar night (Perrigault et al. 2020).

## A plastic clock to time daily and tidal rhythms

In the marine environment, behavior and physiology are often synchronized with relatively short environmental cycles (in the range of hours), which comprise tidal (~12.4 hrs), diel (~24 hrs), and lunidian (~24.8 hrs) cycles, including the examples raised above, but also many others (Fig. 1g,h, Table 1,2 and (Andreatta & Tessmar-Raible 2020; Rock et al. 2022).

Tidal variations at the coast cause remarkably regular, but cause drastic changes in immersion, temperature, salt concentrations, oxygen and food availability, etc. As it is of utmost importance for organisms to not be “surprised” by those environmental changes, circatidal clock mechanisms to anticipate the imminent tidal variation are of high adaptive advantage (Rock et al. 2022). Circatidal locomotor rhythms have been described in a variety of animal taxa, such as crustaceans (Mehta & Lewis 2000; Naylor 1996; Palmer 1991; Williams 1998); insects (Evans 1976; Foster & Moreton 1981; Satoh 2017; Satoh et al. 2006, 2008); *Limulus* (Chabot et al. 2016; Chabot &

Watson 2010), polychaetes (Last et al. 2009),acoel worms (Arboleda et al. 2018), limpets (Schnytzer et al. 2018), and fish (Pülmanns et al. 2018). Valve opening activity rhythms in the oyster *Crassostrea gigas* shifted from a predominantly circadian (~24 hrs) to a circatidal pattern (~12.4 hrs) during constant lab condition in darkness, suggesting a control by both the environment, as well as an endogenous circatidal oscillator (Perrigault & Tran 2017). Diel and tidal rhythms have also been documented in the amphipod *Parhyale hawaiensis* (Hunt 2016; Ramos et al. 2019), and the starlet sea anemone *Nematostella vectensis* (Hendricks et al. 2012; Oren et al. 2015; Tarrant et al. 2019). Dominance of either circadian or circatidal activity rhythms in *Nematostella* depends on light conditions (blue/green light versus red light/DD, respectively) (Leach & Reitzel 2020).

The mechanisms underlying circatidal oscillators have been debated as evidence for different models exists. Indeed, circatidal rhythms could rely on a) a unimodal circatidal clock (~12.4 hrs) which coexists
independently from the circadian clock (Naylor 2010), and does not even require to interact with the latter (Williams 1998) the superposition of two unimodal antiphase circalunidian (~24.8 hrs) clocks (Palmer 1995, 2000) a single bimodal clock orchestrating both circadian and circatidal rhythms (~24 hrs/~12.4 hrs) (Enright 1976; Tran et al. 2020).

Analyses of the plasticity of the conventional circadian oscillator and possible other oscillatory mechanisms in the diel/lunidian/tidal range have thus been of particular interest. Functional molecular investigations of the isopod *Eurydice pulchra* revealed an at least partial dissociation of circadian and circatidal oscillations (Zhang et al. 2013) and predominantly circatidal rhythms in metabolic dynamics were uncovered (O'Neill et al. 2015). Similarly, in the cricket *Apteronemobius asahinai* several genes involved in metabolic processes cycled in the transcriptome predominantly in a circatidal fashion, yet presumptive core circadian clock genes showed no evident rhythmicity (Satoh & Terai 2019). Furthermore, RNAi-mediated downregulation of the core circadian clock genes *period* and *clock* in the cricket revealed impaired circadian, but not circatidal rhythms in this species (Takekata et al. 2012, 2014), in line with RNAi experiments targeting the *period* gene in *E. pulchra* (Zhang et al. 2013). These findings suggest that if molecular overlaps between circadian and circatidal oscillators exist, they might only be partial.

Dominant circadian signatures have been observed in mussels both at the transcript and protein levels under natural and simulated tidal environment (Connor & Gracey 2011; Elowe & Tomanek 2021). Oyster classical circadian clock genes showed circatidal expression in the field, a signature maintained under dark-dark (DD) conditions, but became diel in animals exposed to light-dark (LD) cycles under lab conditions (Tran

et al. 2020). This is very similar to observations of transcriptional core circadian clock gene oscillations in the Antarctic krill under different conditions, where the changes also matched with changes in diel-vertical migration behavior and metabolism (Piccolin et al. 2020).

Although these findings do not resolve the circatidal oscillator riddle, they indicate a plastic clock machinery which 1) times in the range of hours, and 2) differentially integrates environmental cues (e.g. light, tides). Independent input pathways might modulate the period length of the endogenous oscillator(s) by acting on different molecular loops of what at present is all considered the “conventional circadian clock”. These loops could resonate either with circadian or circatidal frequency, depending on the dominant environmental input. Additionally, such a scenario might be confined to specific cells, with others maintaining a classical circadian period. Finally, it is possible that the ticking of a still elusive metabolic oscillator is at the core of circatidal rhythms, directly or indirectly modulating oscillations of conventional core circadian clock genes.

Evidence that at least the conventional circadian clock can function individually in cells of marine organisms is well documented for the chromatophores of the annelid *Platynereis dumerilii*. These cells oscillate on molecular and phenotypic level independently of the worms' central head oscillator (Arboleda et al. 2019). Moreover, work on the integration of solar and lunar light cues for the exact timing of spawning hour shed further insight on the plasticity of the conventional circadian clock in *P. dumerilii*. At least in mature worms this clock can change its period length depending on exposure to either naturalistic sunlight or a combination of naturalistic (full/waning) moonlight and sunlight. This circadian/circalunidian plasticity allows the worms to spawn exactly at the darkness window between sunset and
moonrise, the exact time of which changes
across the month (Zurl et al. 2021). Functional
genetic analyses demonstrate that the
combination of two light receptors, L-CRY
and r-Opsin1, is critical for the correct
interpretation of light valence (i.e. sun- or
moonlight) and moon phase (Zurl et al. 2021).
Of note, light-dependent plasticity of ~24h
clock period length has long been observed
across a wide range of aquatic and terrestrial
organisms, including humans (Aschoff 1960,
1965), but its biological relevance had
remained unclear. Studies under more
naturalistic conditions, including those on
marine organisms, will provide a better
understanding of oscillators that time specific
hours.

Plasticity of the ~24hr clock not within
the same individual, but between different

individuals builds the basis for the marine
midge *Chunio marinus* to adapt its hour of
adult emergence to local tidal regimes. In
order to find the best substrate for zygote
deposition, *C. marinus* emerges at the lowest
low tide (Neumann 1966, 1968, 1988).
However, the exact hours of the lowest low
tide vary predictably along the coast.
Polymorphisms in the *CaMKII.1* gene cause
differential splicing and subsequent functional
differences of the [Ca²⁺]-dependent kinase.
Those variances result in different circadian
clock periods and ultimately in distinct
emergence times, which match the local tidal
conditions (Kaiser et al. 2016).

In summary, evidence for plasticity of
~24hr oscillators exists that could be sufficient
to explain rhythms in the tidal, diel and
lunidian range.
<table><thead><tr><th>Marine animal models</th><th>Photoreceptors and modulators with functionally-tested roles in chronobiology</th><th>Putative core ~24h clock components</th><th>Rhythmic biomarkers</th><th>References</th></tr></thead><tbody><tr><td>Acropora digitifera<br>Acropora millepora</td><td></td><td>cry 1-3, clk 1-3<br>clk-like, bmal/cyc,<br>pdp1-like 1-3,<br>tim/tmo</td><td>diel, lunar and seasonal spawning,<br>lunar phase-dependent transcriptional oscillation,<br>lunar transcriptional oscillation in the field and LL,<br>diel, lunar and seasonal transcriptional oscillation</td><td>Levy et al. 2007; Shoguchi et al. 2013;<br>Brady et al. 2011, 2016;<br>Rosenberg et al. 2017; Wuitchik et al. 2019</td></tr><tr><td>Nematostella vectensis</td><td>CK1δ/ε (circadian timing)</td><td>clk, tim/tmo, cry1a,<br>cry1b, cry2,<br>bmal/cyc</td><td>circadian locomotor activity,<br>diel transcriptional oscillation,<br>diel melatonin and serotonin variation,<br>chromatin accessibility in LD and DD,<br>circadian bacterial community abundance,<br>circadian O₂ consumption,<br>circatidal locomotor activity,<br>diel variation in body length,<br>plastic circadian/circatidal locomotor activity</td><td>Hendricks et al. 2012; Tarrant et al. 2019;<br>Reitzel et al. 2010, 2013;<br>Peres et al. 2014; Oren et al. 2015;<br>Maas et al. 2016; Leach et al. 2018, 2019;<br>Leach & Reitzel, 2019, 2020;<br>Reuven et al. 2021; Renfer et al. 2010;<br>Ikmi et al. 2014; Renfer & Technau, 2017;<br>Weizman et al. 2019</td></tr><tr><td>Clytia hemisphaerica</td><td>Opsin 9, MIHR<br>(light-dependent timing)</td><td></td><td>light-dependent oocyte maturation and spawning</td><td>Quiroga-Artigas et al. 2018; 2020;<br>Takeda et al. 2018</td></tr><tr><td>Platynereis dumerilii</td><td>I-cry (sunlight and moonlight<br>discriminator), r-Opsin 1<br>(moonlight detection in<br>circadian/circalunidian timing),<br>c-Opsin1 (seasonality),<br>CK1δ/ε (circadian but not<br>circadian/semijunar timing,<br>Gs-Opsin1 (not<br>involved), pt-cry (not involved)</td><td>bmal, clk, tr-cry<br>(in vitro assay for<br>positive and<br>negative circadian<br>clock loop<br>transcription),<br>per, tim, pdp1,<br>vr, tmo</td><td>(semi)monthly/circadian/semijunar spawning,<br>(semi)monthly epitoky entry,<br>plastic circadian/circalunidian swarming,<br>circadian activity rhythm,<br>circadian and lunar transcriptional oscillation,<br>circalunar transcriptional and protein oscillation,<br>circadian pigment dispersion,<br>diel swimming behavior</td><td>Zantke et al. 2013; Arboleda et al. 2019;<br>Poehn et al. 2021; Zurl et al. 2021;<br>Andreatta et al. 2020; Tosches et al. 2014;<br>Tsukamoto et al. 2017; Ayers et al. 2018</td></tr><tr><td>Crassostrea gigas</td><td></td><td>bmal, per, clk,<br>cry1, cry2, tim,<br>ror, rev-erb</td><td>plastic circadian/circatidal valve opening activity<br>semilunar, lunar, annual valve opening activity<br>plastic circadian/circatidal transcriptional oscillation</td><td>Tran et al. 2011, 2020;<br>Mat et al. 2012, 2016;<br>Bernard et al. 2016; Perrigault & Tran, 2017;<br>Payton et al. 2017a,b; Wu et al. 2018;<br>Payton & Tran, 2019; Zhang et al. 2012;<br>Peñaloza et al. 2021; Feng et al. 2019</td></tr><tr><td>Bathymodiolus azoricus</td><td></td><td>bmal, per, clk, tim,<br>tmo, cry1a, cry1b,<br>cry2</td><td>circatidal transcriptional oscillation,<br>diel transcriptional oscillation</td><td>Mat et al. 2020</td></tr><tr><td>Eurydice pulchra</td><td>CK1δ/ε (circadian and circatidal<br>timing)</td><td>clk, cry2, bmal1,<br>per, tim (in vitro<br>assay for positive<br>and negative<br>circadian clock loop<br>transcription)</td><td>circatidal swimming activity,<br>circadian pigment dispersion,<br>~12h transcriptional oscillation,<br>~12h O₂ consumption and enzymatic activity,<br>semilunar activity and O₂ consumption</td><td>Hastings, 1981; Zhang et al. 2013;<br>O’Nelli et al. 2015</td></tr><tr><td>Clunio marinus<br>Clunio tsushimensis</td><td>CaMKII.1 (circadian timing)</td><td>clk, cyc (in vitro<br>assay for positive<br>circadian clock loop<br>transcription),<br>tim, tim2, per, cry2,<br>vr, pdp1,<br>rev-erb/eip75b</td><td>circadian and circadian/semijunar eclosion,<br>circasimilunar imaginal disc development,<br>lunar changes in shielding pigment transparency</td><td>Kaiser et al. 2011, 2012, 2016;<br>Neumann & Spindler, 1991;<br>Fleissner et al. 2008;<br>Neumann, 1988, 1995;<br>Kaiser and Haeckel, 2012</td></tr><tr><td>Apteronemobius asahinai</td><td></td><td>per, clk (circadian<br>but not circatidal<br>timing), tim, cyc,<br>cry1, cry2</td><td>plastic circadian/circatidal locomotor activity,<br>plastic circadian/circatidal transcriptional oscillation</td><td>Satoh et al. 2008;<br>Takekata et al. 2012, 2014;<br>Satoh & Terai, 2019; Satoh et al. 2021</td></tr><tr><td>Calanus finmarchicus</td><td>CK1δ/ε (circadian timing)</td><td>clk, cyc, per1,<br>per2, tim, cry1,<br>cry2, vr</td><td>circadian vertical migration<br>circadian O₂ consumption<br>annual vertical migration and diapause,<br>circadian transcriptional oscillation,<br>plastic circadian/ultradian transcriptional oscillation</td><td>Lenz et al. 2014; Häfker et al. 2017;<br>Payton et al. 2020, 2021, 2022;<br>Hüppe et al. 2020; Porter et al. 2017;<br>Christie et al. 2013; Häfker et al. 2018a,b</td></tr><tr><td>Euphausia superba</td><td>cry1 (in vitro assay for<br>light-sensitivity in<br>circadian clock resetting)</td><td>clk, cyc, cry2,<br>per, tim1<br>(in vitro assay for<br>positive and<br>negative circadian<br>clock loop<br>transcription)</td><td>plastic circadian/circatidal vertical migration,<br>plastic circadian/circatidal transcriptional oscillation,<br>seasonal O₂ consumption,<br>quiescence and transcriptional oscillation,<br>seasonal changes in body length in LD and DD,<br>seasonal O₂ consumption,<br>seasonal changes in enzymatic activity in LD and<br>DD, plastic circadian/circatidal O₂ consumption,<br>circatidal enzymatic activity</td><td>Kaartvedt, 2010; Teschke et al. 2011;<br>Biscontin et al. 2017, 2019;<br>Höring et al. 2018, 2021;<br>Piccolin et al. 2020;<br>Huang et al. 2020; Meyer et al. 2017;<br>Biscontin et al. 2016; Piccolin et al. 2018;<br>De Pittà et al. 2013</td></tr><tr><td>Amphiprion ocellaris<br>Amphiprion percula</td><td></td><td>bmal1, clocka,<br>cry1b, per1b,<br>per2, per3</td><td>diel locomotor activity,<br>diel transcriptional oscillation<br>lunar, semilunar, trient-lunar spawning</td><td>Tan et al. 2018; Schalm et al. 2021;<br>Mitchell et al. 2021a,b;<br>Madhu & Madhu, 2007; Seymour et al. 2018</td></tr><tr><td>Siganus guttatus<br>Siganus argenteus<br>Siganus canaliculatus</td><td></td><td>Cry1a, Cry1b, Cry2,<br>Cry3, Per1, Per2a,<br>Per2b, Per3,<br>Clock1a, Clock1b,<br>Bmal1, Bmal2</td><td>diel and lunar spawning rhythms,<br>diel transcriptional oscillation,<br>lunar phase-dependent and circalunar<br>transcriptional oscillation,<br>diel hormone levels,<br>lunar phase-dependent hormone levels</td><td>Rahman et al. 2003; 2004a,b;<br>Park et al. 2007a,b;<br>Sugama et al. 2008; Fukushima et al. 2011;<br>Kashiwagi et al. 2013; Takeuchi et al. 2018;<br>Jiang et al. 2019</td></tr></tbody></table>
<caption>Table 2. Overview of a comprehensive selection of different marine animals studied for their rhythms.</caption>

In this table we included a collection of the animal models that provided some of the major advances in marine
chronobiology, both considering phenotypic/behavioral and molecular aspects. Box colors distinguish different
phylogenetic groups (beige = cnidarians; light green = spiralians; light blue = ecdysozoans; light orange =
chordates, more specifically vertebrates). In the second column, we focused on the photoreceptors and
modulators of biological rhythms (but not part of the core molecular oscillators) that have been functionally
validated (in green), using in vivo (i.e. mutagenesis, RNAi), in vitro (cell culture-based assays), or pharmacological
approaches (agonists/antagonists). In the column "putative core ~24h clock components", we focused on the
genes characterized by clear orthology with known core circadian clock genes in animals (being this machinery
well characterized in flies and mammals), and we distinguish between functionally-validated players (green, see
above for the experimental evidence considered) or only putatively involved in the circadian oscillator of that
species (red). Although not directly related to animal chronobiology, in the "references" column we are reporting
additional useful works concerning genomic and mutagenesis/transgenesis resources in the respective model
organisms.

Timing reproduction with an inner calendar

Below we briefly focus on ~monthly
and ~semimonthly cycles (Andreatta &
Tessmar-Raible 2020). In animals,
circasemilunar (semimonthly)/circalunar
(monthly) rhythms have been well
documented (Table 2, (Andreatta & Tessmar-
Raible 2020; Raible et al. 2017; Tessmar-
Raible et al. 2011). For several species ranging
from annelids (*Platynereis dumerilii*,
*Typosyllis prolifera*), molluscs (e.g. *Haliotis
asinina*), crustaceans (e.g. *Eurydice pulchra*),
insects (e.g. *Clunio marinus/tsushimensis*,
*Pontomyia oceana*) to fishes (e.g. *Fundulus
heteroclitus/grandis*, *Oncorhynchus mykiss*)
they have been shown to persist in the absence
of (semi)monthly cues and hence be
controlled by endogenous oscillators (Kaiser
& Neumann 2021). For some, the entraining
stimuli are known, and for members of
annelids, insects and fishes evidence for
temperature compensation has been provided
(Kaiser & Neumann 2021).

Here, we consider lunar and
semilunar rhythms (and their underlying
oscillators) as output modifications of the
same mechanisms, because it has been shown
that both periods can variably occur within the
same insect and worm lab strains, depending
on the entraining light conditions (Kaiser et al.

2021; Poehn et al. 2021). Importantly, this
does, however, not necessarily imply the same
oscillatory mechanisms across species.

Circa(semi)lunar clocks might rely on:
1) oscillators with a ~15/~30 day periodicity;
2) rhythms generated by the superposition of a
circadian and a circatidal or circalunidian
clocks (beat hypothesis);
3) ~15/~30 circadian
cycles counter mechanism (frequency
demultiplication hypothesis) (Kaiser &
Neumann 2021). The latter two mechanism
imply that each circadian clock change would
also influence the (semi)monthly oscillator,
while an independent circa(semi)lunar
oscillator would provide more flexibility for
independent adjustments of diel and monthly
timing. Many correlational studies on
transcript, and some on protein, level exist
(reviewed in detail in (Andreatta & Tessmar-
Raible 2020), but mechanistic molecular
insight still remains largely open.

The first knock-out studies on an
organism with a circa(semi)lunar oscillator, the
marine annelid *P. dumerilii*, suggests that the
worms' cryptochrome L-Cry is critical to
provide the organism with information if a
given light comes from the sun or moon, and
as such functions as a natural light interpreter
or valence detector (Poehn et al. 2021). Depending on light intensity and/or spectrum Pdu-L-Cry assumes distinct biochemical “moonlight” and “sunlight” states that coincide with distinct subcellular (stable nuclear versus cytoplasmic/nuclear degradation, respectively) localizations. Biochemically, L-Cry only reaches its full “moonlight” state under at least 6hrs of naturalistic moonlight, allowing it not only to discriminate between sun and moonlight, but also moon phases (Poehn et al. 2021). This enables the system to work independently of photoperiods and is in line with classical work that showed that nocturnal light duration, not its exact timing is relevant (Hauenschild 1960). Interestingly, the specific biochemically “moonlight state” properties of L-Cry are not present in its ortholog dCry of the diurnal/crepuscular insect *Drosophila melanogaster*, which does not possess a moon-controlled (semi)monthly oscillator (Zurl et al.

2021). It will be attractive to test cryptochromes of other species with moonlight-controlled rhythms for their biochemical and cellular properties. This is particularly interesting for corals due to the long-standing proposal of the involvement of a cryptochrome in lunar light-controlled spawning synchronization (Levy et al. 2007). Reef-building corals have been extensively studied for their extremely precise spawning, often occurring only once per year (Babcock et al. 1986), highlighting the required complex coordination of diel, monthly and annual cues (Wuitchik et al. 2019). While this complex multi-timer coordination is likely widespread, the reefs' ecological relevance makes corals critical model systems to study the anthropogenic impacts on the timing of fundamental physiological and behavioral aspects of marine organisms (Fogarty & Marhaver 2019).
5. Marine rhythms and clocks under
climate change

In this section, we review past and
present effects of climate change on biological
rhythms, and elaborate how climate effects on
rhythms and timing systems can affect fitness,
species interactions and ecosystem
functioning. We discuss how organismic
plasticity and genetic adaptability of timing
system might favorably impact on species
survival in an environment, whose cyclic
conditions change (Häfker & Tessmar-Raible
2020).

Artificial light at night (ALAN) is
another important and historically
unprecedented anthropogenic environmental
stressor. Nocturnal light pollution by e.g.
human settlements can affect various aspects
of biological rhythmicity in marine habitats
(Ayalon et al. 2020; Berge et al. 2020; Duarte
et al. 2019). ALAN is not directly connected
to ‘climate change’ and for conciseness, we will
not cover ALAN here, but refer to other
reviews that address this important topic in
appropriate detail (e.g. (Davies et al. 2014;
Hölker et al. 2021).

Changes of marine rhythms in the past

Earth has gone through numerous
climate changes. It is difficult to deduce how
biological rhythms responded to such
changes, as fossils do not provide temporal
information. They might, however, provide
information about lifestyles (e.g. diurnal vs.
nocturnal based on eye size) or – if sufficient
DNA is recoverable – about putative clock
genes and their sequence evolution. One
famous example comes from nocturnal
mammals, which, likely after the decline of
dinosaurs, occupied new temporal niches in
all environments, including the oceans. The
spread of activity across the day-night cycle
allowed for a higher diversity (Gerkema et al.
2013; Maor et al. 2017).

The last major change in
environmental conditions was the warming
after the last glacial maximum (LGM) 20,000
years before present (BP) and the associated
retreat of the polar ice caps. Population
analysis in the marine midge *Chunio marinus*
showed that the species' habitat-specific,
genetically encoded circadian and
circa(semi)lunar rhythmicity (see section 4)

likely evolved between the LGM and 8,000
BP from a single population that spread
throughout the European coast (Kaiser et al.
2010). Along the European Atlantic coast
these midges have adapted to different
temporal niches, characterized by the monthly
and diel combination of the lowest low tides
optimal for adult emergence and zygote
deposition (Kaiser et al. 2016, 2021).

Other evidence for favorable
plasticity in timing stems from the
Arctic/northern Atlantic *Calanus* complex.
The boreal copepod *Calanus finmarchicus*
maintained its population size throughout the
LGM, while its Arctic congener *C. glacialis*
experienced an ~1000-fold increase in
population size since the LGM (Provan et al.
2009; Weydmann et al. 2018). This was likely
due to increased availability of shelf habitats
which *C. glacialis* prefers. Although it is not
possible to proof past changes in copepod
rhythmicity, it is likely that since the last ice age
species of the *Calanus* complex experienced
major latitudinal shifts and thus adapted to
changes in light conditions (e.g. photoperiod) and other rhythmic cues.

Thus, the rhythms and endogenous oscillators of marine organisms can adapt to

environmental changes. However, it remains unclear how much time is required for such adaptations and how they affect and are affected by population sizes. Likely, the answer is species-specific.

## Present-day climate effects on marine rhythmicity

Since the end of the 18th century, earth's climate has been experiencing major changes, at least partially caused by anthropogenic CO₂ emissions (IPCC 2014). These affect marine life through at least three major implications: (1) increase in water temperatures and associated decrease in polar sea ice cover, (2) decreasing water pH, due to

the uptake of atmospheric CO₂ and (3) expansion of marine oxygen minimum zones (Fig.4). While various studies addressed the impacts of this 'deadly trio' on e.g. physiology, ecosystem composition and fluxes, effects on biological rhythms and possible inner timing systems have been addressed to a much smaller extent.

## Temperature changes

Warming of tropical waters affects the synchronized mass spawning of reef-forming corals. Gamete maturation and release in these cnidarians show seasonal, lunar & diel coordination that is also reflected in corresponding rhythmic transcriptome changes (Hoadley et al. 2011; Oldach et al. 2017; Wuitchik et al. 2019) and circadian rhythmicity (Oren et al. 2015; Sorek et al. 2014). The seasonal phase of coral spawning is set primarily by a summer increase in water temperature (Keith et al. 2016). Besides desynchronization by artificial light (Ayalon et al. 2020), the overall increase in ocean temperature has been suggested to cause temporal desynchronization of gamete release in Red Sea corals. This implies that increasing temperatures do not only threaten coral reefs through direct effects (e.g. bleaching), but likely also by the disturbance of (reproductive) rhythms (Fig.4).

Increasing temperatures also result in a decline of polar sea ice cover and earlier ice break-up in spring/summer. Polar phytoplankton blooms start with the ice break-up and their peaks have shifted up to 50 days forward in one decade (Kahru et al. 2010). The reduction in Antarctic sea ice has been

connected to a decline in the stock of the Antarctic krill *Euphausia superba* (Atkinson et al. 2019; Meyer et al. 2017). In winter, krill larvae find shelter from predation at the underside of the sea ice and perform a 'reverse' DVM, sinking into the water column after sunset and drifting with the water current to find new under-ice food patches (Meyer et al. 2017). The decrease in krill stocks could thus be at least in part due to a loss of larval daytime refuge and consequently higher predation pressure in open water habitats. Polar phytoplankton growth is strong near the ice edge due to the seeding by algae released from the melting ice. As the ice edge retreats further poleward, so do the associated blooms. Together with the aforementioned forward shift of bloom timing, this could increase migration distance and impair the timing of seasonal latitudinal migrations that benefit from polar productivity (Jenouvrier et al. 2009). Baleen whales that visit boreal/polar regions in summer apparently show some adaptive plasticity in migratory timing, but it is unclear what the underlying mechanisms are and whether they can keep pace with the ongoing shifts in productivity, both on a latitudinal (Ramp et al. 2015; Visser et al. 2011) and temporal scale (Kahru et al. 2010)
(Fig.4). Warming in general has resulted in latitudinal distribution shift in a variety of marine species that, in an attempt to stay within their thermal niche, move closer towards the poles and thereby into habitats

with more extreme rhythmic environmental conditions (Atkinson et al. 2019; Beaugrand et al. 2003; Chivers et al. 2017; Kaartvedt & Titelman 2018; Melle et al. 2014; Sundby et al. 2016; Villarino et al. 2020).

## pH changes

Effects of ocean acidification on rhythms and clocks have so far hardly been investigated. A recent study found altered timing and synchronization in coral spawning under a combination of increased temperature and reduced pH (Liberman et al. 2021). Furthermore, reports of altered circadian clocks gene expression in fish at reduced pH-levels suggest a response by the circadian clock that regulates diel rhythms of osmoregulation in marine fishes (Jesus et al. 2017; Schunter et al. 2016). Ocean acidification can also impact on chemical detection and brain functioning in fish (Dixson et al. 2010; Schunter et al. 2018), and could thus impair rhythm entrainment

through chemical cues (e.g. pheromones) used to synchronize reproduction (Baghel & Pati 2015; Watson et al. 2003) and egg release (Caballes & Pratchett 2017; Tankersley et al. 2002). Reduced pH-levels were further shown to influence DNA methylation and chromatin condensation in corals and marine fish and could thereby also affect both, circadian (de Lima & Göndör 2018; Weizman et al. 2019) and circannual timing mechanisms (Stevenson & Lincoln 2017). While the potential effects of acidification on biological clocks have long been overlooked, they clearly warrant detailed investigation.

## Oxygen concentration changes

Oxygen minimum zones (OMZs) in the world's ocean are expanding both vertically and horizontally. Many species cannot inhabit OMZs while others are closely associated with them. Thus, the expansion of these zones can have profound effects on species, as shown for the depth distribution of the vertically migrating jumbo squid *Dosidicus gigas*, and other eastern Pacific top-predators (Rosa & Seibel 2008; Stramma et al. 2012). Similar to vertical distribution shift caused by OMZs, ocean warming can also affect vertical habitat usage due to downward shifts of thermoclines (Howard et al. 2020; Jorda et al. 2020). Vertical distribution shifts alter the experienced diel rhythms of light and other parameters (temperature, oxygen, pressure) (Fig.4). This could affect the entrainment of circadian clock systems, that can regulate DVM (Häfker et al. 2017), as well as potential photoperiod-based seasonal timing (Häfker et al. 2018a; Teuber et al. 2013). Altered diel and

seasonal vertical distribution patterns could further impact CO₂ sequestration to deep waters (Brun et al. 2019; Jónasdóttir et al. 2015). Additionally, horizontal OMZ spreading leads to latitudinal shifts of species specifically adapted to these zones, while species intolerant to low oxygen levels are forced to shift their habitat as well (Seibel et al. 2014; Stramma et al. 2012; Zeidberg & Robison 2007). The induced latitudinal shifts will again alter the light conditions the species encounter and could thus impair diel and/or seasonal timing (Fig.4).
<figure><img src="image_21.png" /><figcaption>Figure 4. Climate change effects on timing and how they could impact on species interactions and ecosystems.</figcaption></figure>

Changes in abiotic factors (here temperature, pH, oxygen) and/or the rhythmic environment create suboptimal conditions, forcing responses that can differ between species. A simplified 3 species system illustrates mismatches with the species 2 (red, intermediate trophic level) most severely affected. Dashed lines indicate potential of species 3 (blue, higher trophic level), if species 2 was not affected. The enlarged cycle for species 1 (yellow, lower trophic level) in the abundance mismatch scenario illustrates the reduced top-down control by species 2. In the more complex natural environment other species may compensate for, benefit from or suffer under some of the interspecies mismatches.

Generally, present-day temperature changes are especially pronounced at high latitudes (Cohen et al. 2014; Ducklow et al. 2007) and ocean acidification will also disproportionally affect these regions due to

higher CO₂ solubility in cold water (Fabry et al. 2009; Yamamoto-Kawai et al. 2009). Hence, it is likely that present and future changes in marine rhythms will be especially pronounced in polar habitats (Tougeron 2021).

## Adaptability of rhythms and clocks to future ocean conditions

Climatic conditions continue to change and marine organisms will have to respond either by adapting to them or by avoiding them through distribution shifts. Changes can affect a species' rhythmic environment, as well as a species' ability to respond to such changes (Fig.4). It is also

important to distinguish rhythms that are direct responses to environmental changes and those that are generated by endogenous timing systems, as the responses to ecological changes will differ significantly, e.g. due to temperature compensation.
Phenotypic adaptive capacity

As discussed above, climate change
can cause major latitudinal distribution shifts
in marine species, e.g. due to increasing
temperatures or expanding OMZs. However,
individual adaptive capacity and
photoperiodic range for clock functioning
(diel rhythmicity, seasonal photoperiodism)
are adjusted to a given habitat (Bradshaw &
Holzapfel 2001; Höring et al. 2018; Schneck
& Barreto 2020; Schwarzenberger et al. 2021)
and could hinder occupation of new higher
latitude habitats with different environmental
cycles (Huffeldt 2020; Kaartvedt & Titelman
2018; Saikkonen et al. 2012; Sundby et al.
2016). If species are unable to adjust their
timing systems to the altered environment or
cannot shift their distribution due to rigid
timing systems, they face suboptimal
environmental conditions and, as a
consequence, likely reduced fitness and
abundance (Deutsch et al. 2015; Hughes et al.
2019) (Fig.4). Furthermore, if a species does
not shift is distribution, temperature can
directly affect photoperiodic seasonal timing,
thus altering species phenology in spite of
unchanged light conditions (Hairston &
Kearns 1995; Watson & Smallman 1971)
(Fig.4). Generally, whether species exhibit
distribution shifts or not will depend on the
relative selection pressure exerted by the light
environment relative to other environmental
factors (Tougeron 2021).

Phenotypic rhythm/clock adaptability
to altered environments is difficult to predict.
Classical as well as recent work shows that
circadian period can be plastic, for instance
depending on ambient light intensities (see
section 4, (Aschoff 1960; Zurl et al. 2021)),
and photoperiods (Pfeuty et al. 2012; Piccolin
et al. 2018).

In contrast, circadian clock genes
peak at the same time under field
photoperiods of 16h (56°N) and almost 24h
(79°N) in the boreal copepod *C. finmarchicus*
(Häfker et al. 2018a,b). However, a significant
fraction of the *C. finmarchicus* transcriptome,
including presumptive core circadian clock
genes, showed semidiurnal cycling under
midnight sun conditions at 82.5°N (Hüppe et
al. 2020; Payton et al. 2020), either due to the
different light conditions or due to
entrainment by tidal food cues. A possible
adaptation to extreme photoperiods might
also be the ~tidal period of core circadian
clock gene transcript oscillations in the brain
of the Antarctic krill (*E. superba*) under
constant (darkness) conditions, which shifted
to a ~24hr period under light/dark cycles
(Piccolin et al. 2020). It is further possible that
latitudinal light changes could be compensated
for behaviorally through vertical distribution
adjustments.

Evolutionary adaptation of clock and rhythms

Speed of evolutionary adaptation
depends on several factors including overall
population size, connectivity of populations,
generation time and selection pressure. Many
of these factors differ strongly between marine
and terrestrial habitats. Gene flow is typically
considered to be stronger in the oceans due to
the interconnection of water masses,
reproduction through broadcast spawning and
larval dispersal via currents. The zooplankton

species *C. finmarchicus* and *E. superba* both
have enormous overall population sizes and
inhabit vast areas of the northern Atlantic and
Southern Ocean, respectively. Nevertheless,
*C. finmarchicus* and its congener *C. glacialis*
show at best weak genetic differentiation
among populations (Provan et al. 2009; Unal
& Bucklin 2010; Weydmann et al. 2018) and
for *E. superba* there seems to be no genetic
differentiation at all (Deagle et al. 2015).
While high overall population size should increase the probability for the emergence of favorable alleles and rhythmic phenotypes, the high connectivity of habitats could hinder the genetic adaptation of rhythmicity to a new local regime as it occurred in e.g. the midge *C. marinus* (Kaiser et al. 2010, 2021). Low genetic differentiation among populations could be a trait of highly abundant species (e.g. *E. superba*, *Calanus*), while stronger differentiation may be found between populations of less conspicuous species (Peijnenburg & Goetze 2013). This would mean that species of high abundance and ecological relevance could struggle most to adapt their rhythmicity due to the high marine connectivity hindering genetic differentiation. Understanding the timing systems and adaptability of such keystone species is thus of particular importance.

Potentially rapid evolution of new
chronotypes in response to environmental

changes could occur through hybridization (Kaiser et al. 2010; Strelkov et al. 2007). *C. marinus* parents from populations with differing diel emergence timing produce offspring with intermediate timing rhythms (Neumann 1967). Although less studied, hybridization in marine environments seems to be just as common as in terrestrial ecosystems (Gardner 1997) and has been reported from numerous species like fish and bivalves (Montanari et al. 2016; Zbawicka et al. 2019). However, even for closely related species (e.g. *Calanus* complex) hybridization is not necessarily a given (Choquet et al. 2017, 2021) and it can furthermore be hindered by temporal reproductive isolation (Niehoff et al. 2002). Thus, determining the hybridization potential among closely related species and the rhythms of hybrid offspring could provide valuable insights on their adaptability to climate change.

Interspecies mismatches

Both, generation times and timing
mechanisms are species-specific and circadian
clocks can show mechanistic differences
between species, even when closely related
(Menegazzi et al. 2017; Tomioka &
Matsumoto 2015). It is thus likely that
phenotypic adaptive capacity and time needed
to evolve chronobiological adaptations will
strongly differ between species. This is even
more probable, if species use different timing
mechanisms, as suggested for seasonal
(Baumgartner & Tarrant 2017; Goldman et al.
2004), but also lunar rhythms (Kaiser &
Neumann 2021). Furthermore, as suboptimal
timing results in a loss in fitness and likely
reduced abundance (Dodd et al. 2005; Horn
et al. 2019; Spoelstra et al. 2016; Yerushalmi
& Green 2009), species with proper timing can
still be affected through *e.g.* trophic
interactions with suboptimally timed species
(Fig.4). Moreover, latitudinal shifts can

separate trophic interactors or lead to
encounters between species that were
previously separated (Chivers et al. 2017;
Kaartvedt & Titelman 2018; Thorne & Nye
2021) (Fig.4). If species adjust their seasonal
timing based on environmental cues (e.g.
temperature, food availability, light
intensity/spectrum, photoperiod) and/or
endogenous timing systems (circannual clock,
hourglass timer) this can cause mismatches in
response to climate change (Beaugrand et al.
2003; Durant et al. 2019; Edwards &
Richardson 2004; Régnier et al. 2019) (Fig.4).
For example, the onset of Arctic
phytoplankton bloom is gradually shifting to
earlier dates (Kahru et al. 2010), but seasonal
reproduction of the copepod *C. glacialis*,
which depends on the bloom as a food source,
could not adapt to changed bloom timing,
resulting in a seasonal mismatch with low
copepod abundance (Søreide et al. 2010).
Control of *Calanus* seasonal diapause is not
properly understood, but it is thought to rely
on endogenous cues like lipid content,
circannual clocks (Baumgartner & Tarrant
2017; Conover 1965; Fulton 1973) and/or
photoperiod (Häfker et al. 2018b).

At lower latitudes, seasonal
mismatches affecting a given species could be
compensated by other species becoming more
abundant (Atkinson et al. 2015), but high
latitude systems are often centered on a
limited number of highly abundant species,
which show precisely adjusted seasonal timing

due to the shorter productive period (Falk-
Petersen et al. 2009). Thus, temporal
mismatches might become more prominent in
temperate/polar seas with high seasonality,
which also harbor many of the most important
commercial fisheries. Some models suggest
that changes of high latitude habitats towards
possibly longer productive periods (due to
higher temperatures) and smaller species with
shorter generation lengths could result in
increased productivity (Feng et al. 2017;
Renaud et al. 2018). However, such models
typically lack considerations of climate effects
on the organisms' timing systems.

6. Conclusions and outlook

Marine environments are
characterized by numerous environmental
cycles, and biological rhythms are central in
shaping species interactions as well as
ecosystem functioning and productivity.
Periods span from diel vertical migrations of
pelagic organisms, to the seasonal productivity
rhythms of temperate and polar latitudes, to
moon-synchronized reproductions that results
in sudden burst of food abundance. Biological
rhythms are important for coastal organisms to
those at the bottom of the deep sea. Many of
these rhythms are under the control of
endogenous timing mechanisms and the
(emerging) model species highlighted in this
review have helped to identify general
principles of oscillators functioning of
relevance not just for marine habitats. Marine
models have also helped to uncover
fundamental insights, that still require further
understanding, such as the existence of a
~24hr metabolic oscillator, the remarkable
diversification of circadian clock systems in
polyphyletic algae and plasticity of the
"conventional" core circadian clock in animals
or the decoding of solar versus lunar light
input. It will be of increasing importance to
discriminate between truly endogenous
oscillator-driven rhythms and organismal

rhythms that directly follow environmental
changes. The impact of changing
environmental cues on both types of rhythms
is very different- e.g. due to the
presence/absence of temperature-
compensation, responses to environmental
cues as entrainment factors versus rhythm
drivers TUITION
Environmental changes will - either
directly or indirectly - affect marine rhythms
and timing systems, but to which extent they
can adapt to changes, and the time needed for
this, are still hardly explored. Effects of climate
change on marine rhythms could result in
major ecosystem restructuring and changes in
productivity that could also affect fishery yields
and marine CO2 storage.

It is evident that the quest for an
understanding of marine rhythms must not
stop at the descriptive, phenomenological
level, but move to the cellular/molecular
mechanistic level for which model systems can
pave the way. Such investigations will be
crucial to better understand and predict
consequences of climate change. Yet, proper
observations of environmental factors and
biological systems will also be essential for the
future, as particularly exemplified by the
recent discovery of rhythms in the deep sea.
After all, solid observations and descriptions
are the basis from which discoveries arise-

from the bottom of the deep sea to the surface
of the shores.

# Glossary: Rhythms and clocks in marine organisms

**aphotic zone:**

below ~1000 m. Light from sun or moon is completely absent.

**benthic:**

associated with the sea floor

**biological rhythm:**

cyclic change in an organism's biology ranging from behavior to rhythms in physiology and gene expression. The term does not specify whether a rhythm is evoked by external cues or controlled by an endogenous oscillator.

**central versus peripheral circadian clocks:**

Animals possess circadian oscillators in (almost) all tissues. Evidence from terrestrial (mouse, *Drosophila*) and marine (*Platynereis*) models shows that these peripheral clocks are coordinated by a central brain oscillator.

**conventional circadian clock:**

The molecular oscillator based on a TTFL and well-defined sets of functionally tested components is the main, but not only, endogenous driving force of diel rhythms. The involved molecules are typically conserved within a given eukaryote phylum, but rarely beyond.

**core (circadian) clock genes:**

genes who have functionally been shown to be part of a central (circadian) oscillatory network

As so far only the molecular mechanisms for the circadian clock are known, the term "clock genes" is often synonymously used for "circadian clock genes".

**dysphotic zone:**

~200-1000 m depth. Light (from sun/moon) is detectable, but insufficient for photosynthesis.

**endogenous oscillator:**

internal timing mechanism that is self-sustained, but can be entrained by environmental cues.

**entrainment:**

phase-adjustment ('synchronization') of an endogenous oscillator through environmental cues.

**environmental cycle:**

cyclic and predictable change of the environmental conditions affecting an organism. Cycles can be abiotic (e.g. light, temperature), but also related to biological rhythms (predation risk, food availability).
**(eu)photic zone:**

~0-200 m depth. There is enough light for sustained photosynthetic production.

**inputs:**

cues involved in the entrainment process

**mismatch:**

dissimilarity in the distribution, timing, abundance, etc. of two or more currently interacting species that often results in fitness reduction.

**neritic:**

associated with coastal shelf areas

**oceanic:**

shelf water or the open ocean

**outputs:**

biological processes whose rhythmicity is regulated by an endogenous oscillator

**pelagic:**

associated with the water column

**persistence/free-run:**

maintenance of rhythmicity in environments without time cues relevant to the tested oscillator

**phytoplankton:** large and highly diverse group of photosynthetic microorganisms found predominantly in aquatic environments

**plasticity of oscillator:**

variability in the period length of an endogenous oscillator. It can be read out on any output level (molecular, physiological or behavioral)

**temperature compensation:**

endogenous oscillators do not follow the Le Bel-Van 't Hoff rule, but are buffered against temperature changes.

**transcriptional/translational feedback loop (TTFL):**

autoregulation of genes via interactions of the translated proteins with other genes/proteins.
Acknowledgements

We apologize to colleagues whose work could not be cited due to limitations of space. Our research is supported by the following funding sources: Falciatore lab: the Fondation Bettencourt-Schueller (Coups d'élan pour la recherche française-2018), the "Initiative d'Excellence" program (Grant "DYNAMO," ANR-11-LABX-0011-01), the ANR-DFG Grant "DiaRhythm (KR1661/20-1) and ANR Grant ClimaClock (ANR-20-CE20-0024), Raible and Tessmar-Raible labs: The research leading to these results has received funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement 260304 (F.R.) and ERC Grant Agreement 337011 (K.T.-R.); the Horizon 2020 Programme ERC Grant Agreement 81995 (K.T.-R.); the research platforms 'Rhythms of Life' (K.T.-R., F.R.) and "Single-cell genomics of stem cells" (F.R.) of the University of Vienna; the Austrian Science Fund (FWF) START award, project Y413 (K.T.-R.); the Austrian Science Fund (FWF) projects P28970 (K.T.-R.) and I2972 (F.R.); the Austrian Science Fund (FWF) grant F78 (K.T.-R., F.R.). N.S.H. was supported by a Lise-Meitner fellowship from the FWF (M2820).
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