\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{New biologging approach reveals unique flightless moult strategies of
Atlantic puffins}



\author[1]{Jamie Darby}%
\author[2]{Mike Harris}%
\author[3]{Sarah Wanless}%
\author[1]{John Quinn}%
\author[4]{Vegard Sandøy Bråthen}%
\author[5]{Annette Fayet}%
\author[6]{Manon clairbaux}%
\author[7]{Tom Hart}%
\author[8]{Tim Guilford}%
\author[9]{Robin Freeman}%
\author[1]{Mark Jessopp}%
\affil[1]{University College Cork}%
\affil[2]{Centre for Ecology \& Hydrology}%
\affil[3]{NERC Centre for Ecology and Hydrology}%
\affil[4]{Norwegian Institute for Nature Research}%
\affil[5]{Oxford University}%
\affil[6]{University College Cork College of Science Engineering and Food Science}%
\affil[7]{University of Oxford}%
\affil[8]{Oxford}%
\affil[9]{Zoological Society of London Institute of Zoology}%


\vspace{-1em}



  
  \date{June 15, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Animal-borne telemetry devices provide essential insights into the
life-history strategies of far-ranging species and allow us to
understand how they interact with their environment. Many species in the
seabird family Alcidae undergo a synchronous moult of all primary flight
feathers during the non-breeding season, making them flightless and more
susceptible to environmental stressors, including severe storms and prey
shortages. However, the timing and location of moult remains largely
unknown, with most information coming from studies on birds killed by
storms or shot at sea. Using light-level geolocators with saltwater
immersion loggers, we develop a method for determining flightless
periods in the context of the annual cycle. Four Atlantic puffins
(Fratercula arctica) were equipped with geolocator/immersion loggers on
each leg to attempt to overcome issues of leg-tucking in plumage while
sitting on the water, which confounds the interpretation of logger data.
Light level and saltwater immersion time-series data were combined to
correct for this issue. This approach was adapted and applied to 40
puffins equipped with the standard practice deployments of geolocators
on one leg only. Flightless periods consistent with moult were
identified in the dual-equipped birds, whereas moult identification in
single-equipped birds was less definitive and should be treated with
caution. Within the dual-equipped sample, we present evidence for two
flightless moult periods per non-breeding season in two puffins that
undertook more extensive migrations (\textgreater{} 2000km), and were
flightless for up to 76 days in a single non-breeding season. A biannual
flight feather moult is highly unusual among non-passerine birds, and
may be unique to birds that undergo catastrophic moult, i.e. become
flightless when moulting. Though our conclusions are based on a small
sample, we have established a freely available methodological framework
for future investigation of the moult patterns of this and other seabird
species.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Biologging and telemetry studies have greatly advanced our knowledge of
the behaviour and distribution of far-ranging animal species (e.g.
Jouventin \& Weimerskirch 1990, Kooyman 1966). They have also provided
insights into their behaviour especially when direct observation is
impossible or impractical (e.g. Wilson et al. 1991, Michel et al. 2022),
which is often the case for the many marine species that spend prolonged
periods at sea far from land (e.g. Weimerskirch et al. 2006, Doyle et
al. 2015, Bennison et al. 2019, Brooke 2018). Long-term device
attachment allows us to explore distribution and behaviour over broad
timescales, such as diel patterns of movement (Seyer et al. 2021), and
describe life-history strategies, such as migration (Am\selectlanguage{ngerman}élineau et al.
2021) or periodic moult (Grissot et al. 2018). By looking at the
behaviour of an animal in relation to its spatial and temporal
distribution, it is possible to identify key areas of conservation
concern, and identify drivers of declines (Frederiksen et al. 2012,
Fayet et al. 2021).

Many of the world's seabirds are threatened and declining (Dias et al.
2019, Paleczny et al. 2015), creating a pressing need to better
understand vulnerable stages of their annual cycle. Seabirds tend to be
highly susceptible to the impacts of climate change, including sea
temperature rise and shifts in prey distribution and abundance (Durant
et al. 2003, Sandvik et al. 2005), as well as extreme weather events
(Clairbaux et al. 2021), with large wrecks recorded following severe
winter storms at sea (Harris et al. 2014, Morley et al. 2017,
Anker-Nilssen et al. 2018). Larger members of the seabird
family\emph{Alcidae} (hereafter alcids) moult all their primary flight
feathers simultaneously (Peery et al. 2008) leading to a protracted
flightless period, placing them at greater risk from such dynamic
stressors. Alcids are often the most common species washed ashore in
storm wrecks in the northern hemisphere (Morley et al. 2017). Obligatory
flightless moult places them at greater risk from storm events, as they
would not be able to fly to avoid the storm track. Their vulnerability
to predation may be increased by their silhouette in downwelling light,
which can provide a visual cue to underwater predators (Ulman et al.
2015, Doyle et al. 2015) that they may struggle to escape from when
flightless. It may also increase their vulnerability to surface
pollutants, because of the increased time spent on the water surface and
the inability to escape expansive films of harmful substances such as
petroleum oil (Robertson et al. 2012).

The Atlantic puffin (\emph{Fratercula arctica} ), hereafter puffin, is a
seabird species that has undergone rapid population declines across most
of their European breeding range during the 2000s (Harris \& Wanless
2011), leading to their classification as Endangered in Europe by the
European Red List Assessment in 2015 (BirdLife International, 2015).
Puffins must carefully time and locate their moult to coincide with
sufficient food availability, which can be patchily distributed at sea
(Fauchald 2009, Jessopp et al. 2013). Clairbaux et al. (2021) calculated
the fasting endurance of puffins as 6.5 (±2.5) days in mid-autumn, and
4.6 (±0.6) days in winter. Local depletion of food during moult
therefore puts puffins at risk of starvation. Anker-Nilssen et al.
(2018) found that most puffins washed ashore in a post-storm wreck in
southwest Norway in early 2016 were in the late stage of primary moult,
and almost all individuals were emaciated. Even though many would have
been able to fly by the time they were washed ashore, moult may have
prevented them from escaping the storm when they were flightless, during
which they clearly struggled to find food, despite a highly varied diet
(Baillie \& Jones 2004), especially during the non-breeding season (Falk
et al. 1992, Harris et al. 2015).

The duration, timing, and location of moult in puffins has proven
difficult to determine, because it occurs during the non-breeding season
when birds are away from their colonies. In other alcids, moult takes
place shortly after the breeding season (Gaston \& Jones 1998, Peery et
al. 2008), facilitating observation of moulting individuals. Harris et
al. (2014) assessed moult stage based on feather development of puffins
either washed ashore during storm wrecks or shot at sea. They reported
primary flight feather moult in puffins at any time from September to
March, with peaks in October and March, which is considerably more
variable than that of other alcid species that undergo flightless moult
(Gaston \& Jones 1998). Identifying the flightless period of surviving
individuals using biologging studies has so far proven difficult.
Leg-mounted saltwater immersion loggers are commonly used to classify
seabird behaviour during the non-breeding season. Reduced time spent
flying, during flight feather moult for instance, is usually reflected
by an elevated proportion of time the leg and logger are wet (Grissot et
al. 2019). Puffins, like other alcids, repeatedly tuck their legs into
the plumage when on the water (Harris et al. 2010, Linnebjerg et al.
2014, I. Sempere, Oceanário de Lisboa, pers. comms, figure 1),
confounding simple behaviour classification using these loggers.

This study uses light-level geolocators with integrated saltwater
immersion switches deployed on puffins to identify patterns of behaviour
thought to be consistent with flightless moult. By combining data from
four individuals with a geolocator on each leg (dual-equipped birds), we
developed a behavioural classification method using raw light and
saltwater immersion data. We show that we can use results from
dual-equipped birds to quantify and correct for behaviours that would
confound traditional methods, therefore identify flightless periods
assumed to represent moult. We then adapt and validate this method for
single-equipped birds, for which there are far more data. This approach
may help us to identify overwintering strategies and areas of
conservation concern for puffins and other alcids, whose highly
restricted mobility during flightless moult may compound the negative
impacts of environmental threats.

\textbf{Methods}

\textbf{Deployment and recovery of geolocator devices}

Geolocators (seven BAS Mk18-L, and one Mk14) were deployed on both legs
of four adult puffins during the 2010 summer breeding season on Skomer
Island, Wales (51.737N, 5.297W). Single geolocators (31 Biotrack
(2012)/Lotek (2020) Mk4083 and 12 BAS Mk18 (2010)) were deployed on 40
adult puffins during the breeding season in 2010, 2012 and 2020 on
Skellig Michael, Ireland (51.771N, 10.539W). Birds at both colonies were
captured during chick-rearing either using purse nets at burrow
entrances or by hand from the burrow, weighed and fitted with
geolocators before being released back to their burrow. Capture and
handling times were kept to a minimum. Geolocators were attached to a
coloured plastic ring fitted around the tarsus, with total deployment
weight (devices plus leg ring and cable tie attachment) always
\textless{} 2\% body mass, under 6g for dual-equipped loggers, and under
3g for single-equipped loggers. These devices measured light every
minute in 6-bit units from 0 (light is below civil twilight, sun
\textgreater{} \textasciitilde{} 6 degrees below the horizon) to 64 (sun
is well above the horizon) and saved the maximum light level sampled in
5-minute intervals, or 10-minute intervals for the single Mk14 logger
used. Saltwater immersion data were sampled every 3 seconds as binary
units of 0 (dry) or 1 (wet) and the number of wet samples in 10-minute
intervals were saved as values between 0 (all dry) or 200 (all wet).
Devices were recovered from birds during the subsequent breeding
seasons. All work was carried out under licence from the British Trust
for Ornithology (CO/6143, C/5311), with work in Ireland further licenced
by the National Parks and Wildlife Service (06/2020, C41/2020, 26/2010,
C051/2011, C116/2012, C039/2013, 11/2013). Attachment of dual-equipped
geolocators was granted ethical approval by the British Trust for
Ornithology Unconventional Methods Technical Panel, with ethical
approval for handling and tagging in Ireland also approved by the
University College Cork Animal Ethics Committee. All analyses were
performed using R version 4.1.2 (R Core Team, 2021), and all code to run
these analyses are available online
(github.com/JamieHDarby/puffin\_moult).

\textbf{Location data}

Positions were obtained from light-level data using a threshold method
(supporting information) following established procedures (Lisovski et
al. 2019). Areas of apparent residency were identified over the
non-breeding season (August to March) using Lavielle segmentation,
following methods from Amelineau et al. (2021), and mean distance to the
colony of each area of residency was calculated. Migratory effort was
described as the distance to the furthest point of residency from the
colony.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1: Different puffin at-sea behaviours and the position of the
tarsus during each. Loggers were mounted on the tarsus of study
individuals. Puffins trail their tarsus in flight (a), which leaves the
geolocator exposed to light and dry. Puffins sitting on the surface of
the water may lower one or both legs for paddling and balance (b), which
leaves the tarsus submerged and exposed to light. Puffins inactive on
the water may also tuck one leg into their plumage (c), obscuring the
tarsus from daylight and keeping it dry. Puffins hunting for prey
underwater will have their tarsus submerged and exposed to light levels
attenuated by water (d), though this is unlikely to reduce actual light
readings, which are taken as a maximum over 5 or 10 minute intervals.

\textbf{Accounting for leg-tucking behaviour}

Puffins tend to tuck their legs into their plumage while resting on the
water, usually just one at a time, but sometimes both (supporting
information figure S1, pers. obs.), leaving the logger dry despite the
puffin being on the water surface (figure 1). This means it can be
difficult to distinguish between flight and rest from a geolocator
immersion signal alone (Fayet et al. 2016). We developed a new method
that identified and accounted for leg-tucking using concurrent light
signals. This works on the basis that light levels recorded by the
logger will be lower than expected for a given solar angle if the logger
is obscured (supporting information), i.e. tucked into plumage (figure
1). Solar angles were calculated based on astronomical formulae using
date, time, and location. These lower-than-expected light fixes were
classified as tucking, and were appended to concurrent immersion data
using a time series merge implemented using the \emph{xts} package (Ryan
\& Ulrich 2020) to account for missing or delayed points in either data
stream. The immersion data points associated with these fixes were
adjusted to 100\% wet, to reflect that they were assumed to be resting
on water despite the logger reading fully or partially dry. This
correction could only be applied to data occurring during daylight hours
(solar angle \textgreater{} -6 degrees) and not during the hours of
darkness.

\textbf{Combining data from dual-equipped loggers}

Immersion data from both leg tags were combined for each dual-equipped
puffin, again using a time series merge implemented using the
\emph{xts}package. Proportions of time spent wet were compared pairwise
for each fix interval and the higher value retained in a single data
stream. This meant that even if one leg recorded dry and the other
recorded wet for the same time interval, the ``wet fix'' was
preferentially retained. If one leg was submerged, then the puffin must
have been resting on the water, and the ``dry fix'' was an instance of
leg-tucking not captured by methods described in the previous section.

\textbf{Identifying moult periods in dual-equipped birds}

We then assumed the corrected proportion of time spent dry per day was
time in flight (prop\textsubscript{flight}) and calculated the 5-day
rolling average of this (prop\textsubscript{flight-5}). Only values with
a predicted solar angle of \textgreater{} -6 were used for this
analysis, as some anomalous sustained dry periods were retained in
nocturnal data points. Though these periods could in fact be due to
sustained flight occurring at night, it is more likely due to puffins
tucking both legs at once (Robertson et al. 2012, pers. obs.), or visits
to the nest burrow approaching the breeding season. The tucking
correction applied earlier will not have captured this on either leg's
logger, as the expected light level at these low solar angles
(\textless{} -6 degrees) is zero. An inferred flightless period of
minimum 30 consecutive days was identified as a persistently low set of
values of prop\textsubscript{flight-5}, identified using an incrementing
threshold. Put simply, days with prop\textsubscript{flight-5} below this
threshold value were defined as flightless. This value was iteratively
increased from 0 by 0.0002 increments until a minimum sequence of 30
consecutive days were defined as flightless. This minimum duration was
defined according to previous estimates of this species (Harris et al.
2010) and observations of captive puffins (D. Dial, National Aquarium
USA, pers. comms). Moult was therefore defined as a continuous period of
at least 30 days, during which little to no flight was inferred to have
occurred by the processed immersion data. The same process was repeated,
omitting any initially identified moult, to explore the possibility of a
second flightless moult.

\textbf{Testing single leg data in dual-equipped birds}

A similar moult identification method was attempted using data from each
dual-equipped logger in isolation. As before, the proportion of time
spent wet was corrected for tucking behaviour using raw light signals.
Any points with a solar angle below -3 degrees were omitted for this
analysis, to ensure that leg-tucking was sufficiently captured using
light data. Prop\textsubscript{flight} and
prop\textsubscript{flight-5}were again calculated, and the same
incrementing threshold method was used to identify putative moult
periods of minimum 30 days duration. A maximum threshold value of 1\%
prop\textsubscript{flight-5} was applied to restrict the likelihood of
falsely identifying moult from noisy immersion time series. This meant
that the 5-day rolling average of corrected flight, or
prop\textsubscript{flight-5}, had to remain below 1\% for a period to be
considered as moult. Independently derived inferred moult periods were
compared to combined data from dual-equipped loggers. Based on limited
but good agreement (see results), the process was then applied to the
geolocator data collected from 40 individuals equipped with single
loggers from Skellig Michael, Ireland.

\textbf{Observations from captive puffins}

Several aquaria house captive puffins as part of displays. Aquarists
from 3 of these facilities provided observations about moulting habits
of their captive puffins to contextualise our results and test whether
our conclusions were physiologically viable. We spoke to aquarists from
Tierpark Bern, Switzerland, the National Aquarium, USA, and Ocean\selectlanguage{ngerman}ário de
Lisboa, Portugal. All described variation in moulting behaviour, see
details in supporting information. Further relevant observations are
referenced as personal communications in the main text.

\textbf{Results}

\textbf{Accounting for leg-tucking behaviour}

Leg tucking was identified using raw light and immersion data streams
from loggers from both single- and dual-equipped birds. Clear
differences in raw immersion data can be seen from each leg of a single
puffin, largely down to leg-tucking (figure 2A \& 2B). Though we capture
and account for much of the daylight leg-tucking using concurrent light
data from the same logger (figure 2C), differences between corrected
immersion time series from each leg suggests that not all leg-tucking is
accounted for in this method (figure 2D \& 2E). Data from both legs are
therefore likely necessary to accurately identify flightless periods,
i.e. primary feather moult (figure 2F). Using the dual-equipped loggers,
we calculated that puffins spent 20.3\% (SD = 18.9) of daylight hours
tucking either or both legs, 10 times greater than the time spent in
flight (1.9\%, SD = 5.5). Puffins spent less than 1\% of daylight hours
in flight for 75\% of days during the non-breeding period. Although the
small sample size precluded detailed analysis, the proportion of time
spent leg-tucking also varied with individual, time of year, and leg
(supporting information).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 2: Geolocator data process for a dual-equipped puffin (EJ47625)
prior to moult identification, accounting for leg-tucking using raw
light signals, and combining data from loggers on each leg. All data are
displayed as a 2D rasterised time series. The x-axis represents calendar
date, and the y-axis represents time in Universal Time Zone. A and B are
the raw saltwater immersion signals from the puffin's left and right leg
respectively. C highlights the data points inferred as leg-tucking using
the raw light signals. D and E show the immersion data corrected for
leg-tucking events shown in C, again for the puffin's left and right
leg-mounted loggers, respectively. F shows the combined minimum of D and
E, which represents the most accurate estimate of flight activity, given
the data available. In F, data with a predicted solar angle of less than
-6 are made semi-transparent to highlight the time series retained for
moult detection. Consistent 0 values at night in F during April probably
represent time spent in the burrow, i.e. neither leg wet.

\textbf{Identifying moult periods from dual deployment birds}

Table 1: Flightless moult periods identified in the four dual-equipped
individuals. 1\textsuperscript{st} moult refers to the moult inferred by
the first pass of the moult identification process, and
2\textsuperscript{nd} moult by the second pass of the same. A range of
results are presented for each puffin, as results vary depending on
which logger's time-series (left or right leg) is used as the basis for
the combination of data.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
ID & 1\textsuperscript{st} moult start & 1\textsuperscript{st} moult
duration & 2\textsuperscript{nd} moult start & 2\textsuperscript{nd}
moult duration\tabularnewline
\midrule
\endhead
EJ47625 & 8\textsuperscript{th} - 16\textsuperscript{th} Sep & 35 - 45
days & 20\textsuperscript{th} - 21\textsuperscript{st} Feb & 31 - 32
days\tabularnewline
EL60569 & 9\textsuperscript{th} Sep & 48 - 54 days & - &
-\tabularnewline
EL60573 & 17\textsuperscript{th} - 19\textsuperscript{th} Sep & 33 - 35
days & 9\textsuperscript{th} - 13\textsuperscript{th} Feb & 33 - 37
days\tabularnewline
EL60648 & 19\textsuperscript{th} -- 21\textsuperscript{st} Sep & 38 - 46
days & - & -\tabularnewline
\bottomrule
\end{longtable}

Each dual-equipped puffin had a moult period inferred to begin in
September, while two had a second inferred moult period beginning in
mid-February (table 1 \& figure 3). There was some variation in the
duration of moult, from 31 to 54 days. During inferred moult periods,
the percentage of time spent dry according to raw immersion signals was
12.4\%, while it was reduced to 4.2\% when adjusted for leg tucking
using data from a single leg. When data streams from both legs were
corrected for tucking and combined, the proportion of time spent dry
during inferred moult was 0.1\%, compared to 2.4\% for the rest of the
non-breeding season. There was no marked increase in percentage of time
spent leg tucking when undergoing moult (supporting information),
consistent with observations of captive puffins (M. Huwiler, Tierpark
Bern, pers. comm).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 3: Inferred timing of flightless moult in four dual-equipped
puffins. Immersion data were combined between two geolocators for each
puffin. The green line represents time spent dry per day
(prop\textsubscript{fligth}) and the blue line is the 5-day rolling
average of this (prop\textsubscript{flight-5}). The blue bar underneath
each plot represents moult inferred on the first pass of the moult
identifiation process, the red bar represents a potential second
flightless moult identified by the second pass.

All moult periods occurred close to equinox periods, when the
latitudinal accuracy of light level geolocation is greatly reduced. The
average position of inferred moult was used to graphically represent
moult location (figure 4), given that puffins are unlikely to move
extensively when flightless, and most of the variation in location
during moult is almost certainly due to error in location estimates.
Both individuals with two inferred moult periods had more extensive
migrations than those with one (table 2), with the autumn flightless
moult occurring when they were furthest from their colony and the spring
moult when much closer to the colony (figure 4).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 4: Puffin tracks and associated moult periods. Each plot
represents one individual and their mean moult locations, with a track
derived from each logger. Geolocator positioning accuracy is reduced
around the equinoxes, negatively affecting the latitudinal accuracy of
moult locations, which were all inferred to occur around the equinoxes.
The red dot corresponds to the colony location, Skomer, Wales. Note that
portions of the track apparently crossing land are products of the
inaccuracy of geolocator location estimates around the equinoxes, and
associated smoothing.

Table 2: Metrics for each dual-equipped bird relating to migratory
effort and moult periods. Residencies were described using Lavielle
segmentation of net-sqaured displacement from the colony. Number of
inferred moult periods and time spent in inferred moult altogether are
also shown.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Bird ID & Most distant residency (dist / time) & Inferred moults & Total
time in moult\tabularnewline
\midrule
\endhead
EJ47625 & 2054km / 49 days & 2 & 76 days\tabularnewline
EL60569 & 728km / 41 days & 1 & 54 days\tabularnewline
EL60573 & 3040km /42 days & 2 & 66 days\tabularnewline
EL60648 & 1250km / 39 days & 1 & 46 days\tabularnewline
\bottomrule
\end{longtable}

\textbf{Identifying moult using single leg data}

Using single logger data streams, only 1 moult period was identified
from the 4 dual-equipped individuals, on the left leg of puffin EJ47625.
The dates of this, 16\textsuperscript{th} September to
30\textsuperscript{th} October, exactly matched the moult period
identified using data from both loggers. The percentage of time spent
dry in this moult period was 0.4\%. No second inferred moult period was
detected on the second pass of the moult identification method.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Figure 5: Timing and location of inferred moult of Skellig Michael
puffins. On the left, the proportion of time spent dry per day is
graphed over the non-breeding season. The green line represents time
spent dry per day (prop\textsubscript{flight}) and the blue line is the
5-day rolling average of this (prop\textsubscript{flight-5}). The blue
bar underneath each plot represents putative moult inferred by the moult
identifiation process. On the right, the corresponding inferred moult
location is shown by a diamond shape, overlaid on the migratory path of
the individual. The red dot represents Skellig Michael, their breeding
colony. Note that portions of the track apparently crossing land are
products of the inaccuracy of geolocator location estimates around the
equinoxes, and associated smoothing.

Of the 40 single-equipped individuals from Skellig Michael, inferred
moult periods were only apparent in 3 individuals. Periods of
sufficiently reduced flight consistent with moult were not detected by
our method in any of the other individuals (supporting information).
These moult periods were 35, 52 and 72 days in duration and occurred in
midwinter, starting in December or January, and took place either beyond
the Irish Atlantic shelf margin (n = 2) or in the Mediterranean Sea (n =
1) (figure 5 \& supporting information). Puffins from Skellig Michael
showed reduced leg-tucking activity around midwinter, especially for
puffins tagged in 2020, which corresponds with the moult periods
inferred for this group (supporting information). This suggests that
moult is more easily identifiable at this time of year due to an
apparent reduction in leg-tucking behaviour, so the temporal
distribution of moult inferred here is likely biased towards this
period. These 3 individuals all moved approximately 2000 km from the
colony to their furthest point of residency (supporting information),
comparable to one of the Skomer birds that was inferred to have
completed two moults.

\textbf{Discussion}

\textbf{Methodology}

To identify moult in puffins, we have developed a new method combining
multiple data streams from geolocator loggers to more accurately
identify year-round behaviours of seabirds. While this seems to work
reasonably well for dual-equipped individuals, it also highlights some
shortcomings of using standard single-deployment geolocators to identify
fine-scale behaviours. Halpin et al. (2021) show how species' behaviour
can unpredictably influence location estimates using light-level
geolocators. Leg-tucking in alcids presents a similar problem for the
interpretation of behaviours from saltwater immersion loggers on the
same devices (Fayet et al. 2017, Linnebjerg et al. 2014). We provide a
method to partially correct for this behavioural classification issue
using concurrent light and immersion data. The limitations of this
partial correction are reflected in the low success rate of moult
inference in single-logger birds. Because puffins and some other alcids
spend very little time in flight even when not undergoing moult (see
results, Dunn et al. 2020), flightless moult is impossible to identify
without relatively accurate behavioural data, and the few individuals
for which moult periods were detected using a single logger are likely
biased towards times of the year when leg tucking behaviour is less
prevalent. Despite these constraints, our methods provide insights into
the behaviour and life-history traits of a threatened species, and
progresses our knowledge surrounding the timing and location of a highly
vulnerable period in their annual cycle.

Over the last 10 -- 15 years, hundreds of alcids have been tagged with a
single geolocator throughout their biogeographic range (Fayet et al.
2017, Reiertsen et al. 2021), but our method does not have the power to
identify moult in a sufficient proportion of individuals to robustly
investigate population-wide patterns. More involved methods, for
instance using machine learning to identify flightless stopovers
(Guilford et al. 2009), usually require large amounts of pre-assigned
training data to confidently infer behaviour, but may even then be
liable to misclassification due to individual- or colony-level
differences in behaviour (Bennison et al. 2018). Finer resolution data,
such as from accelerometers, would allow us to identify flight with much
more confidence (e.g. Patterson et al. 2019). GPS loggers would record
far more accurate locations, potentially allowing us to identify imposed
residency due to flightless moult. To date, none of these alternative
devices are small or efficient enough for year-round deployment on
puffins. Geolocators that record temperature can also be used to help
correct for leg-tucking (Elliot \& Gaston 2014, Dunn et al. 2020),
though like the light-based corrections used in this study,
temperature-based corrections do not fully capture all instances of
leg-tucking. A ventrally mounted immersion switch would provide a truer
representation of flight/non-flight behaviour, but despite being light
enough for long-term deployment, techniques to mount devices long term
on the body, as opposed to on a leg-ring, that do not affect the bird's
performance, have not been developed (Lameris et al. 2018). For now,
dual-equipped geolocators are probably the most viable method to
investigate the flightless moult of puffins and other alcids. As
technology improves and devices become smaller, the combined weight of
two loggers will have less impact on an animal. Stable isotope analysis
of moult feathers may also be used to coarsely gauge the location of the
most recent primary moult (e.g. St. John Glew et al. 2018) and to
validate geolocator based findings. To complement this, a relatively
accurate geolocator-informed moult timing and location tells us where
and when flight feathers were formed, allowing us to analyse the trophic
position of food consumed during feather formation using stable isotope
analysis (St. John Glew et al. 2019). It may also provide information on
the prevalence of toxic chemicals in marine food webs at the time and
location of moult by looking at chemical composition of feathers (Fort
et al. 2016).

\textbf{Biological findings}

We have shown that the flightless moult strategy of breeding puffins
varies markedly between individuals, and possibly colonies, despite
usually being a fixed life-history trait within migratory bird species
(Barta et al. 2008). We also found evidence that some individuals may
undergo flightless moult twice in a non-breeding season, with this
strategy possibly tied to more extensive migrations, though this
relationship is based on a very small sample size. If this is the case,
our results provide the first potential evidence for two flightless
moult periods per year in a wild volant bird species (Beltran et al.
2018).

The exploration-refinement hypothesis (Guilford et al. 2011) suggests
development over time of a fixed migration strategy that exploits
predictable prey availability in space and time, leading to
inter-individual variation (e.g. Harris et al. 2015). More extensive
migration may allow puffins to exploit reliable food resources (Jessopp
et al. 2013), especially during moult when their diving abilities are
likely compromised (Bridge 2004). Prolonged flight during migratory
phases may lead to accelerated feather wear and reduced flight
efficiency for a bird with an already high wing-loading (Navarro \&
Gonz\selectlanguage{ngerman}ález-Solís, 2007, Greenewalt 1975), whose burrow nesting habits
likely accelerate flight feather wear during the breeding season.
Increased energy requirements for long-distance migrants also requires
increased foraging effort and dive rates (Fayet et al. 2016),
potentially further wearing wing feathers. This may result in two moults
in one non-breeding season to maintain flight feather condition and
retain flight efficiency (Barta et al. 2008). It may be that one or both
moults are incomplete, allowing the puffins to remain partially volant.
Small alcids in the genus \emph{Aethia} forego synchronous moult,
instead staging the replacement of primary flight feathers, allowing
them to continue flying throughout moult (e.g. Bond et al. 2013). Some
storm-wrecked puffins have shown evidence of a similar partial primary
moult (M. Harris, unpublished data), though this has only been observed
in a very small proportion of a very large sample of recovered birds, so
is likely an anomaly or due to poor health. Biannual synchronous
flightless moults have been observed in captive juvenile puffins
(Swennen 1977, M. Huwiler, Tierpark Bern, pers. comm.), and while it is
uncertain how these observations relate to wild breeding adults
(Thompson \& Kitaysky, 2004), it does highlight that this strategy is
physiologically possible. In contrast, the two Skomer individuals that
stayed closer to the colony (\textless{} 1500km) during the non-breeding
season clearly underwent a single flightless moult in autumn, not long
after the summer breeding season. Flight feather moult is energetically
demanding (Guillemette et al. 2007) and reduces foraging efficiency
(Bridge 2004), so there are potential advantages in strategies that
forego a second flight feather moult where possible. A trade-off likely
exists between the energy required to undergo long-distance migration to
highly productive areas, potentially necessitating two flightless
moults, versus reduced migration effort and a single flightless moult,
while also remaining in an area where feeding conditions may be poorer.
Put simply, moult strategy in puffins could be dichotomous (biannual
versus annual moult) associated with high versus low energy intake and
expenditure, reflected in the activity budgets of long- and
short-distance migrants (Fayet et al. 2017).

Previous studies, based on birds recovered dead rather than those from
birds equipped with loggers that survived the non-breeding season,
described an early/late bimodal distribution of puffin moult timings in
the North Sea and around the Faroes Islands, with peaks in October and
March (Harris et al. 2014). This timing largely agrees with our findings
from Skomer individuals. It may be that dead birds identified as
moulting in March were going through a second moult, though many more
suitable tracking data, e.g. from dual-equipped puffins, would be
required to suggest this with any confidence. The inferred moult of
three Skellig Michael individuals occurred once, from December to
February, with no evidence that this follows an earlier post-breeding
flightless moult, although again, this is based on a small sample where
moult could be resolved from single logger data streams. Similar moult
timings were observed by Anker-Nilssen et al. (2018), who found that
most puffins found following storm wrecks on the coast of Norway in
February/March 2016, likely originating from colonies on the east coast
of the UK, were in the latter stages of moult and had only recently
become volant. Birds found dead are more likely to have been wintering
relatively close to land, and so may not provide an unbiased sample of
the wider population (Fayet et al. 2017). It is also possible that
storms disproportionately affect moulting puffins that cannot fly to
escape storm tracks, with reduced foraging efficiency during moult
further compromised by storm conditions (Clairbaux et al. 2021). This
does not seem to universally be the case, with a high proportion of
moulting birds found in one wreck on the Norwegian coast (Anker-Nilssen
et al. 2018) and a low proportion in another in the Bay of Biscay
(Morley et al. 2017), despite both wrecks occurring at a similar time of
year.

\textbf{Conclusion}

While limited to a small sample size, the results of this study markedly
advance our understanding of a vulnerable period in the non-breeding
season of a threatened species. We raise the intriguing possibility that
puffins have a unique biannual flightless moult, leaving them flightless
for 60-80 days over the course of a single non-breeding season,
accounting for 20-30\% of that total period. This highly unusual
strategy may be tied to migration effort, though this is speculative due
to our limited sample size. However, we have established a freely
available workflow to further analyse dual-equipped seabirds to improve
behaviour classification using geolocators. We hope this will promote
further research on the flightless moult of puffins and other alcids,
given that this life stage that leaves them are particularly vulnerable
to antagonistic impacts from reduced prey availability, surface
pollution and increased storm prevalence.

\textbf{Acknowledgements}

Thanks to Patrick Manley, Damien Haberlin, Dave Boyle, Ben Dean, and
Holly Kirk for field assistance. Fergus McCormick and the Office of
Public Works facilitated fieldwork on Skellig Michael, and Chris Taylor
and the Wildlife Trust for South and West Wales facilitated work on
Skomer. The SEATRACK programme provided numerous tracking devices, as
well as curating and processing data from Skellig Michael. Thanks to
Debra Dial of the National Aquarium, USA, Meret Huwiler of TierPark
Bern, Switzerland, and Ana Fereira and Irene Sempere of Oceanário de
Lisboa, Portugal, for insights into the behaviour and phenology of
captive puffins. JD was funded by the Irish Research Council as an
Enterprise Partnership Grant, cofounded by the Petroleum Infrastructure
Program (EPSPG/2019/469). Work on Skomer was supported by the Mary
Griffiths award. The authors declare no conflict of interest.

\textbf{Author contributions}

MPH, SW, MJ, VBS, ALF, TH and JD created the concept. Data were
collected by MJ, JD, JQ, ALF, TG and RF. JD led the analysis and writing
of the manuscript, with strong contributions from all authors.

\textbf{Data availability statement}

Upon publication, data will be made freely available from Birdlife
Seabird Tracking Database, and code is freely available at
github.com/JamieHDarby/gls\_puffin\_moult.

\textbf{References}

Amélineau F, Merkel B, Tarroux A, Descamps S, Anker-Nilssen T, Bjørnstad
VS \ldots{} Strøm H (2021) Six pelagic seabird species of the North
Atlantic engage in a fly-and-forage strategy during their migratory
movements. \emph{Marine Ecology Progress Series 676}:127-144.
https://doi.org/10.3354/meps13872 Anker-Nilssen T, Harris M, Kleven O,
Langset M (2018) Status, origin, and population level impacts of
Atlantic Puffins killed in a mass mortality event in southwest Norway
early 2016. \emph{Seabird 30}:1-14. Baillie SM, Jones IL (2004) Response
of Atlantic Puffins to a decline in capelin abundance at the Gannet
Islands, Labrador. \emph{Waterbirds 27}:102-111. Barta Z, McNamara JM,
Houston AI, Weber TP, Hedenström A, Feró O (2008) Optimal moult
strategies in migratory birds. \emph{Philosophical Transactions of the
Royal Society of London. Series B, Biological Sciences}
\emph{363}(1490):211--229. https://doi.org/10.1098/rstb.2007.2136
Beltran RS, Burns JM, Breed GA (2018) Convergence of biannual moulting
strategies across birds and mammals. \emph{Proc. R. Soc. B.} \emph{285}:
20180318 http://doi.org/10.1098/rspb.2018.0318 Bennison A, Bearhop S,
Bodey TW, Votier SC, Grecian WJ, Wakefield ED, Hamer KC, Jessopp M
(2018) Search and foraging behaviors from movement data: A comparison of
methods. \emph{Ecology and Evolution8}(1):13--24
https://doi.org/10.1002/ece3.3593 Bennison A, Quinn JL, Debney A,
Jessopp M (2019) Tidal drift removes the need for area restricted search
in foraging Atlantic puffins.\emph{Biol. Lett.} \emph{15}(7).
https://doi.org/10.1098/rsbl.2019.0208 Birdlife International (2015)
\emph{European Red List of Birds}. Luxembourg: Office for Official
Publications of the European Communities https://doi.org/10.2779/975810
Bridge ES (2004) The effects of intense wing molt on diving in alcids
and potential influences on the evolution of molt patterns.\emph{Journal
of Experimental Biology} \emph{207}:3003-3014. Bond AL, Konyukhov NB,
Jones IL (2013) Variation in Primary Molt in the Least Auklet: Variation
de la Muda las Primarias en Aethia pusilla.\emph{The Condor}
\emph{115}(2): 348--355. https://doi.org/10.1525/cond.2013.110062 Brooke
M (2018) \emph{Far from Land: The Mysterious Lives of Seabirds}.
Princeton University Press. Clairbaux M, Mathewson P, Porter W, Fort J,
Strøm H, Moe B, \ldots{} Grémillet D (2021) North Atlantic winter
cyclones starve seabirds.\emph{Current Biology}
\emph{31}(17):3964-3971.e3.
https://doi.org/https://doi.org/10.1016/j.cub.2021.06.059 Dias
MP,~Martin R,~Pearmain EJ,~Burfield IJ,~Small C,~Phillips RA,~Yates
O,~Lascelles B,~Borboroglu, PG,~Croxall, JP (2019) Threats to seabirds:
A global assessment.~\emph{Biological
Conservation237}:525-537~https://doi.org/10.1016/j.biocon.2019.06.033
Doyle TK, Bennison A, Jessopp M, Haberlin D, Harman L (2015) A dawn peak
in the occurrence of `knifing behaviour' in blue sharks. \emph{Animal
Biotelemetry 3}:1-6. Dunn RE, Wanless S, Daunt F, Harris MP, Green JA
(2020) A year in the life of a North Atlantic seabird: behavioural and
energetic adjustments during the annual cycle. \emph{Scientific Reports}
\emph{10}(1) https://doi.org/10.1038/s41598-020-62842-x Durant JM,
Anker-Nilssen T, Stenseth NC (2003) Trophic interactions under climate
fluctuations: the Atlantic puffin as an example.\emph{Proceedings of the
Royal Society of London B: Biological Sciences 270}:1461-1466. Elliott
K, Gaston AJ (2014) Dive behaviour and daily energy expenditure in
Thick-billed Murres \emph{Uria lomvia} after leaving the breeding
colony. \emph{Marine Ornithology} \emph{42}(2):183-189 Falk K, Jensen
JK, Kampp K (1992) Winter diet of Atlantic puffins (\emph{Fratercula
arctica}) in the northeast Atlantic. \emph{Colonial Waterbirds
15}:230-235. Fauchald P (2009) Spatial interaction between seabirds and
prey: Review and synthesis. \emph{Mar. Ecol. Prog. Ser.}
\emph{391}:139--151. https://doi.org/10.3354/meps07818 Fayet AL, Freeman
R, Shoji A, Boyle D, Kirk HL, Dean BJ, Perrins CM, Guilford T (2016)
Drivers and fitness consequences of dispersive migration in a pelagic
seabird. \emph{Behavioral Ecology} \emph{27}(4): 1061--1072.
https://doi.org/10.1093/beheco/arw013 Fayet AL, Freeman R, Anker-Nilssen
T, Shoji A, Wanless S, Guilford T, \ldots{} Fifield D (2017) Ocean-wide
drivers of migration strategies and their influence on population
breeding performance in a declining seabird. \emph{Current Biology}
\emph{27}(24):3871-3878.e3. https://doi.org/10.1016/j.cub.2017.11.009
Fayet A, Clucas G, Anker-Nilssen T, Syposz M, Hansen ES (2021) Local
prey shortages drive foraging costs and breeding success in a declining
seabird, the Atlantic puffin. \emph{Journal of Animal Ecology90}(5):
1152--1164 https://doi.org/10.1111/1365-2656.13442 Fort J, Grémillet D,
Traisnel G, Amélineau F, Bustamante P (2016) Does temporal variation of
mercury levels in Arctic seabirds reflect changes in global
environmental contamination, or a modification of Arctic marine food web
functioning? \emph{Environmental Pollution} \emph{211}: 382--388.
https://doi.org/https://doi.org/10.1016/j.envpol.2015.12.061 Frederiksen
M, Moe B, Daunt F, Phillips R, Barrett R, Bogdanova M, Boulinier T
\ldots{} Anker-Nilssen, T (2012) Multicolony tracking reveals the winter
distribution of a pelagic seabird on an ocean basin scale.
\emph{Diversity and Distributions} \emph{18}: 530--542.
https://doi.org/10.1111/j.1472-4642.2011.00864.x Gaston AJ, Jones IL
(1998) The Auks. \emph{Oxford University Press, Oxford}. Greenewalt CH
(1975) The flight of birds: The significant dimensions, their departure
from the requirements for dimensional similarity, and the effect on
flight aerodynamics of that departure.~\emph{Transactions of the
American Philosophical Society}~\emph{65}(4):1--67.
https://doi.org/10.2307/1006161 Grissot A, Graham IM, Quinn L, Bråthen
VS, Thompson PM (2020) Breeding status influences timing but not
duration of moult in the Northern Fulmar~\emph{Fulmarus glacialis}.
\emph{Ibis, 162}:446-459.~https://doi.org/10.1111/ibi.12714 Guilford T,
Meade J, Willis J, Phillips RA, Boyle D, Roberts S \ldots{} Perrins CM
(2009) Migration and stopover in a small pelagic seabird, the Manx
shearwater \emph{Puffinus puffinus}: insights from machine learning.
\emph{Proceedings of the Royal Society B 276}:1215--1223.
https://doi.org/10.1098/rspb.2008.1577 Guilford T, Freeman R, Boyle D,
Dean B, Kirk H, Phillips R, and others (2011) A dispersive migration in
the Atlantic Puffin and its Implications for migratory navigation.
\emph{PLoS ONE 6}(7): e21336.
https://doi.org/10.1371/journal.pone.0021336 Guillemette M, Pelletier D,
Grandbois J, Butler P (2007) Flightlessness and the energetic cost of
wing molt in a large sea duck. \emph{Ecology 88}(11):2936-2945.
https://doi.org/10.1890/06-1751.1 Halpin LR, Ross JD, Ramos R, Mott R,
Carlile N, Golding N, \ldots{} Clarke RH (2021) Double-tagging scores of
seabirds reveals that light-level geolocator accuracy is limited by
species idiosyncrasies and equatorial solar profiles. \emph{Methods in
Ecology and Evolution12}(11):2243--2255
https://doi.org/10.1111/2041-210X.13698 Harris M, Daunt F, Newell M,
Phillips R, Wanless S (2010) Wintering areas of adult Atlantic puffins
\emph{Fratercula arctica} from a North Sea colony as revealed by
geolocation technology. \emph{Marine Biology 157}:827-836. Harris MP,
Wanless S (2011) \emph{The puffin}. T. \& A. D. Poyser. Harris MP,
Wanles S, Jensen JK (2014) When are Atlantic Puffins\emph{Fratercula
arctica} in the North Sea and around the Faroe Islands flightless?
\emph{Bird Study} \emph{61}(2):182-192.
https://doi.org/10.1080/00063657.2014.909382 Harris MP, Wanless S,
Ballesteros M, Moe B, Daunt F, Erikstad KE (2015) Geolocators reveal an
unsuspected moulting area for Isle of May Common Guillemots \emph{Uria
aalge}. \emph{Bird Study}, \emph{62}(2):267--270
https://doi.org/10.1080/00063657.2015.1006164 Harris MP, Leopold MF,
Jensen JK, Meesters EH \& Wanless S (2015) The winter diet of the
Atlantic Puffin \emph{Fratercula arctica} around the Faroe Islands.
\emph{Ibis} \emph{157}\textbf{:}468-479. Jessopp M, Cronin M, Doyle T,
Wilson M, McQuatters-Gollop A, Newton S, Phillips R (2013) Transatlantic
migration by post-breeding puffins: A strategy to exploit a temporarily
abundant food resource? \emph{Marine Biology} \emph{160}(10):2755-2762.
https://doi.org/10.1007/s00227-013-2268-7 Jouventin P, Weimerskirch H
(1990) Satellite tracking of Wandering albatrosses. \emph{Nature}
\emph{343}(6260): 746--748. https://doi.org/10.1038/343746a0 Kooyman GL
(1966). Maximum Diving Capacities of the Weddell
Seal,\emph{Leptonychotes weddelli}. \emph{Science} \emph{151}(3717):
1553--1554. https://doi.org/10.1126/science.151.3717.1553 Lameris TK,
Müskens GJDM, Kölzsch A, Dokter AM, van der Jeugd HP, Nolet BA (2018)
Effects of harness-attached tracking devices on survival, migration, and
reproduction in three species of migratory waterfowl.\emph{Animal
Biotelemetry} \emph{6}(1) https://doi.org/10.1186/s40317-018-0153-3
Linnebjerg JF, Huffeldt NP, Falk K, Merkel FR, Mosbech A, Frederiksen M
(2014) Inferring seabird activity budgets from leg-mounted time-depth
recorders. \emph{Journal of Ornithology} \emph{155}(1):301--306
https://doi.org/10.1007/s10336-013-1015-7 Lisovski S, Bauer S, Briedis
M, Davidson SC, Dhanjal-Adams KL, Hallworth MT \ldots{} Bridge ES (2019)
Light-level geolocator analyses: A user's guide. \emph{Journal of Animal
Ecology} \emph{89}(1):221--236 https://doi.org/10.1111/1365-2656.13036
Michel L, Cianchetti-Benedetti M, Catoni C, Dell'Omo G (2022) How
shearwaters prey. New insights in foraging behaviour and marine foraging
associations using bird-borne video cameras. \emph{Marine
Biology169}(1):7. https://doi.org/10.1007/s00227-021-03994-w Morley T,
Fayet A, Jessop H, Veron P, Veron M, Clark J, Wood M (2017) The seabird
wreck in the Bay of Biscay and South-Western Approaches in 2014: A
review of reported mortality. \emph{Seabird}, \emph{29}:22--38. Navarro
J, González-Solís J (2007) Experimental increase of flying costs in a
pelagic seabird: effects on foraging strategies, nutritional state and
chick condition.~\emph{Oecologia}~\emph{151}\textbf{:}150-160.
https://doi.org/10.1007/s00442-006-0559-0 Patterson A, Gilchrist HG,
Chivers L, Hatch S, Elliott K (2019) A comparison of techniques for
classifying behavior from accelerometers for two species of seabird.
\emph{Ecology and Evolution9}(6):3030--3045
https://doi.org/10.1002/ece3.4740 Peery MZ, Henkel LA, Newman SH, Becker
BH, Harvey JT, Thompson CW, Beissinger SR (2008) Effects of rapid
flight-feather molt on postbreeding dispersal in a pursuit-diving
seabird. \emph{The Auk 125}:113-123. Peterson A (1976) Age of first
breeding in Puffin, \emph{Fratercula arctica}. \emph{Astarte 9}:43-50. R
Core Team (2021) R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria.
https://www.R-project.org/ Reiertsen T, Layton-Matthews K, Erikstad K,
Hodges K, Ballesteros M, Anker-Nilssen T \ldots{} Wanless S (2021).
Inter-population synchrony in adult survival and effects of climate and
extreme weather in non-breeding areas of Atlantic puffins. \emph{Marine
Ecology Progress Series} \emph{676}:219--231.
https://doi.org/10.3354/meps13809 Robertson, G. J., Canada, E.,
Montevecchi, W. A., \& Gaston, A. J. (2014). Miniaturized data loggers
and computer programming improve seabird risk and damage assessments for
marine oil spills in Atlantic.\emph{Journal of Ocean Technology}
\emph{7}(4):41-58 Ryan JA, Ulrich JM (2020) xts: eXtensible Time Series.
R package version 0.12.1. https://CRAN.R-project.org/package=xts Sandvik
H, Erikstad KE, Barrett RT, Yoccoz NG (2005) The effect of climate on
adult survival in five species of North Atlantic seabirds.\emph{Journal
of Animal Ecology 74}:817-831. Seyer Y, Gauthier G, Bêty J, Therrien J,
Lecomte N (2021) Seasonal variations in migration strategy of a
longdistance Arctic-breeding seabird. \emph{Marine Ecology Progress
Series} \emph{677}:1--16 https://doi.org/10.3354/meps13905 St John Glew
K, Wanless S, Harris MP, Daunt F, Erikstad KE, Strøm H, Trueman CN
(2018) Moult location and diet of auks in the North Sea inferred from
coupled light-based and isotope-based geolocation.\emph{Marine Ecology
Progress Series} \emph{599}: 239--251. https://doi.org/10.3354/meps12624
St John Glew K, Wanless S, Harris MP, Daunt F, Erikstad KE, Strøm H,
Speakman JR, Kürten B, Trueman CN (2019) Sympatric Atlantic puffins and
razorbills show contrasting responses to adverse marine conditions
during winter foraging within the North Sea. \emph{Movement
Ecology7}(1): 33. https://doi.org/10.1186/s40462-019-0174-4 Swennen, C
(1977).~\emph{Laboratory research on seabirds : report on a practical
investigation into the possibility of keeping seabirds for research
purposes}. Netherlands Institute for Sea Research, Texel Thompson CW,
Kitaysky AS (2004) Polymorphic flight-feather molt sequence in Tufted
Puffins (\emph{Fratercula cirrhata}): A rare phenomenon in birds.
\emph{The Auk 121}:35-45. Thompson CW, Wilson ML, Melvin EF, Pierce DJ
(1998) An unusual sequence of flight-feather molt in common murres and
its evolutionary implications. \emph{The Auk 115}(3):653-669.
https://doi.org/10.2307/4089414 Ulman SE, Hollmen T, Brewer R, Beaudreau
AH (2015) Predation on seabirds by Pacific Cod \emph{Gadus
macrocephalus} near the Aleutian Islands, Alaska. \emph{Marine
Ornithology 43}:231-233. Weimerskirch H, le Corre M, Ropert-Coudert Y,
Kato A, Marsac F (2006) Sex-specific foraging behaviour in a seabird
with reversed sexual dimorphism: The red-footed booby.
\emph{Oecologia146}(4):681--691
https://doi.org/10.1007/s00442-005-0226-x Wilson RP, Culik B, Spairani
HJ, Coria NR, Adelung D (1991) Depth utilization by Penguins and Gentoo
Penguin dive patterns. \emph{Journal of Ornithology}
\emph{132}(1):47--60 https://doi.org/10.1007/BF01640525

\selectlanguage{english}
\FloatBarrier
\end{document}

