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\begin{document}

\title{HPAIV outbreak triggers long-distance movements in breeding Northern
gannets -- implications for disease spread}



\author[1]{Jana Jeglinski}%
\author[2]{Jude Lane}%
\author[3]{Stephen Votier}%
\author[4]{Robert Furness}%
\author[5]{Keith Hamer}%
\author[1]{Dominic McCafferty}%
\author[1]{Ruedi Nager}%
\author[6]{Maggie Sheddan}%
\author[7]{Sarah Wanless}%
\author[1]{Jason Matthiopoulos}%
\affil[1]{University of Glasgow}%
\affil[2]{Royal Society for the Protection of Birds}%
\affil[3]{Heriot-Watt University School of Energy Geoscience Infrastructure and Society}%
\affil[4]{MacArthur Green}%
\affil[5]{University of Leeds}%
\affil[6]{Scottish Seabird Centre}%
\affil[7]{UK Centre for Ecology \& Hydrology}%


\vspace{-1em}



  
  \date{May 15, 2024}


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\selectlanguage{english}
\begin{abstract}
Animal movement is a fundamental driver of disease spread. We show that
an outbreak of high pathogenicity avian influenza (HPAI) is coincident
with unprecedented behavioural changes in GPS tracked Northern gannets.
Previously characterised by strong fidelity to their nest sites and
foraging areas (2015 -- 2019; n = 120), breeding gannets tracked before,
during and after the 2022 outbreak showed half of ten birds stopped
transmitting and most likely died, while the survivors instigated
unusual long-distance movements. Two adults visited one - three other
gannetries -- the first such incidence of prospecting in this age class.
Our findings suggest the HPAIV outbreak triggered changes in space use
patterns of possibly infected individuals that amplified the
epidemiological connectivity among colonies and may generate
super-spreader events that accelerate disease transmission across the
metapopulation. Such self-propagating transmission from and towards high
density animal aggregations may explain the rapid pan-European spread of
HPAIV in the gannet.%
\end{abstract}%



\sloppy


Running title: HPAIV outbreak modifies gannet space use patterns

\par\null

HPAIV outbreak triggers long-distance movements in breeding Northern
gannets -- implications for disease spread

Jana W.E. Jeglinski\textsuperscript{1}, Jude Lane\textsuperscript{2},
Steven C. Votier\textsuperscript{3}, Robert W.
Furness\textsuperscript{4,} Keith C. Hamer\textsuperscript{5}, Dominic
J. McCafferty\textsuperscript{1}, Ruedi G. Nager\textsuperscript{1},
Maggie Sheddan\textsuperscript{6}, Sarah Wanless\textsuperscript{7} and
Jason Matthiopoulos\textsuperscript{1}

\textsuperscript{1}School of Biodiversity, One Health and Veterinary
Medicine, University of Glasgow, Glasgow, UK

\textsuperscript{2}RSPB Centre for Conservation Science, The Royal
Society for the Protection of Birds, Sandy, United Kingdom

\textsuperscript{3}School of Energy, Geoscience, Infrastructure and
Society, The Lyell Centre, Herriot Watt University, Edinburgh, UK

\textsuperscript{4}MacArthur Green, Glasgow, UK

\textsuperscript{5}University of Leeds, Leeds, UK

\textsuperscript{5}Scottish Seabird Centre, North Berwick, UK

\textsuperscript{7}UK Centre for Hydrology \& Ecology Edinburgh,
Penicuik, UK

Author statement: JJ and RN conceived the original study for which the
data was collected, in discussion with DMC and SW; JJ, JL, RWF, MS and
SV collected the GPS tracking data in 2022 and JL and KM supplied GPS
tracking data from previous years; JJ and JM interpreted the data in the
context of the HPAIV outbreak and designed the analysis, JJ analysed the
data; JJ wrote the manuscript with support from JL, SV and JM, all
co-authors contributed critically to the final version.

Keywords: avian influenza, bio-logging, conservation, disease ecology,
information centre, metapopulation, Morus bassanus, pathogen spread,
seabird, super-spreading events

Data accessibility statement: Upon publication and with an embargo
period of one year, the data that support the findings of this study are
openly available in the Movebank repository at www.movebank.org,
reference number 2658220054 and 2658117564 and, upon request, from the
Seabird Tracking database.

Code to access the data used in the analysis, to run the analyses and to
generate the figures in this manuscript is supplied in the GitHub
repository https://github.com/JanaJeglinskiR/gannet\_movements\_HPAIV

and will be made publicly available with a doi on Zenodo upon
publication.

\par\null

Abstract

Animal movement is a fundamental driver of disease spread. We show that
an outbreak of high pathogenicity avian influenza (HPAI) is coincident
with unprecedented behavioural changes in GPS tracked Northern gannets.
Previously characterised by strong fidelity to their nest sites and
foraging areas (2015 -- 2019; n = 120), breeding gannets tracked before,
during and after the 2022 outbreak showed half of ten birds stopped
transmitting and most likely died, while the survivors instigated
unusual long-distance movements. Two adults visited one - three other
gannetries -- the first such incidence of prospecting in this age class.
Our findings suggest the HPAIV outbreak triggered changes in space use
patterns of possibly infected individuals that amplified the
epidemiological connectivity among colonies and may generate
super-spreader events that accelerate disease transmission across the
metapopulation. Such self-propagating transmission from and towards high
density animal aggregations may explain the rapid pan-European spread of
HPAIV in the gannet.

Introduction

Animal movement is a fundamental driver of disease spread in domestic
and wild species . Individuals regularly move across the landscape for
multiple purposes including foraging, dispersal and migration. During
migration, animals perform regular long-distance movements across large
spatial scales, congregate in high densities at stopover sites and thus
may carry diseases to geographically distant locations and habitats .
For example, migrating wild ducks, geese and swans appear to have
introduced High Pathogenicity Avian influenza (HPAI H5Nx) from Asia to
Europe, Russia, Africa and North America over the last two decades .
Dispersing or prospecting movements of animals occur over smaller
spatial scales, connect different subpopulations and can facilitate
disease spread between them . Further, foraging movements have the
potential to influence disease ecology and transmission via
inter-population overlap, but are poorly studied in this context. The
latter appears particularly pertinent for central-place foraging animals
such as pinnipeds, bats and seabirds where animals breed in segregated
high-density colonies but forage widely with the potential to transmit
diseases. In seabirds, some species forage in areas that overlap between
neighbouring colonies whereas others have colony-specific
non-overlapping foraging ranges . These differences are likely to
influence disease transmission risk among colonies. Furthermore, many
animal species display age- and stage-specific movement patterns that
influence their propensity for disease transmission. For example,
prospecting is a behaviour that entails visits by individuals to
breeding areas where they do not currently breed but might settle in the
future . In seabirds, the behaviour is characteristic for immatures,
failed breeders or nonbreeders whereas breeders are typically faithful
to their breeding, foraging and wintering sites within and between years
.

Disease may also trigger changes in movement behaviour that influence
onward transmission. Studies on experimentally immune-challenged or
infected animals have shown that sick animals may become more lethargic
(Adelman et al 2010), reduce the complexity of their movements and
foraging behaviour and move slower and for shorter distance . Such
reduced movement can lower social network connectivity and disease
containment . Conversely, there is also evidence for a lack of lethargy
in sick birds despite elevated immune responses to a pathogen. Of
course, under the extreme scenario of a highly lethal disease outbreak,
many animals simply die in mass mortality events . However, beyond the
direct physiological effects of disease on the affected animal,
outbreaks also alter and disturb the environment that surviving animals
inhabit. For example, breeding sites may be littered with sick, dying
and dead animals, these deaths may lead to changes in the density and
distribution of breeding sites or territories and facilitate access by
predators through thinning of previously dense breeding aggregations.
All these cues are very likely perceivable to surviving animals and thus
may impact their behaviour. Disturbances can drastically alter the
behaviour and movement of healthy individuals , as evidenced by global
patterns across species of modifications to movement and space use or
shifting activity patterns towards nocturnality due to human
disturbances . Movement responses can be as deleterious as evasion
movements of cetaceans disturbed by naval sonar exercises that lead to
mass stranding events or so evidently different from normal behaviour
that changes in movement behaviour have been proposed as early warning
signals to the presence of poachers . Changes to animal movement
patterns as response to disturbances can also have pronounced
consequences for the transmission of diseases. For example, logging of
forest increased the use of agricultural/farmland in long-tailed
macaques, \emph{Macaca fascicularis} , that tested positive
for\emph{Plasmodium knowlesi} , thus increasing disease transmission to
humans . Culling, as an effort to control disease, instead promoted
pathogen spatial spread in vampire bats, \emph{Desmodus rotundus} , and
badgers, \emph{Meles meles} , since the disturbance associated with
culling increased dispersal . However, questions remain over the
possibility for positive feedbacks between infection, mobility and
subsequent increased transmissivity. Evidence for the potential of
self-propagation of disease through changes in animal movement
associated with the disturbance generated by disease outbreaks is rare,
probably because monitoring fine-scale animal movement rarely coincides
with such unpredictable events.

During spring and summer 2022, an unprecedented HPAIV outbreak
dramatically impacted the global metapopulation of Northern
gannets\emph{Morus bassanus} (hereafter gannet), with tens of thousands
of birds dying in the Northwest and Northeast Atlantic (Lane et al.
submitted, . On the 4\textsuperscript{th} June 2022, the first clinical
symptoms of HPAIV were observed on the Bass Rock, UK (M. Sheddan, pers.
obs.), the world's largest gannet colony with \textasciitilde{} 75,000
breeding pairs . Subsequent tissue analysis from four gannets by the
Animal and Plant Health Agency (APHA) confirmed that all birds were
positive for clade 3.2.4.4b HPAIV H5N1 (Lane et al., submitted). The
disease outbreak rapidly devastated the colony over the course of the
following month, reducing the breeding population by 72 \%, suppressing
adult survival to 0.455 \% (compared to 0.94 - 0.95 in previous years;
Lane et \emph{al} . 2020, Wanless \emph{et al.} 2010), and breeding
success to 0.25\% compared to 0.72 \% in normal years Lane et al.
submitted). HPAIV spread rapidly across the entire gannet metapopulation
and affected all monitored colonies (40 out of 53) bar one (Lane et al.
submitted), but the transmission dynamics and likely vectors of
transmission are unknown.

The movement ecology of adult breeding gannets, particularly from Bass
Rock, is exceptionally well studied with satellite and GPS tracking from
1998 and many years to the present . Adult gannets are highly
site-faithful, returning each year to the same colony and mostly the
same nest site . If a breeding attempt fails, birds continue nest site
ownership (Lane et al pers. obs.) and maintain a regular routine of
commuting between colony and foraging sites at sea . Incubating and
chick-rearing birds display highly predictable movements to
individual-specific foraging areas . The gannet is one of the species
that has been shown to forage in colony-specific, non-overlapping
foraging ranges during the breeding season (Wakefield et al 2013). Taken
together, these space use characteristics suggest limited potential for
contact among breeding colonies, making adult gannets unlikely
candidates for disease transmission across the metapopulation.

Here, we investigate the impact of an HPAIV outbreak on the short-term
adult gannet movement behaviour before, during and shortly after the
epidemic at Bass Rock. By using GPS-GSM devices we show that adult
gannets drastically changed their space use patterns concomitant with
the outbreak. These movement behaviour modifications increased the
potential for inter-colony contact, both at sea and on land, and might
have directly contributed to the rapid transmission of HPAIV across the
gannet metapopulation, through multiple direct or indirect contact
routes.

Materials and methods

\emph{GPS tracking -- 2022 (HPAIV year)}

We captured five breeding pairs of gannets on 29\textsuperscript{th} and
30\textsuperscript{th} April 2022 at Bass Rock, UK (56\selectlanguage{ngerman}° 04', 2° 29'),
about one month before the HPAIV outbreak at this colony. Territorial
pairs were caught before egg-laying (Jeglinski et al, in prep.). We also
captured 10 breeding adults with 2 -- 8 weeks old chicks between the
11\textsuperscript{th} -- 14\textsuperscript{th} August 2022, about 2.5
months after the start of the HPAIV outbreak on the Bass Rock. A
detailed analysis of the August dataset is described in Grémillet et al.
(in review).

For the captures, we used a 6 m telescopic pole with a hook or noose
attached to the end and restrained the birds in a custom-designed
`gannet-jacket' that allows efficient handling and weighing to minimize
capture stress for the bird. We weighed birds with a digital scale
(Kern, precision 0.1 kg), and took morphometric measurements with a
metal ruler (precision 1 cm) and a digital calliper (precision 0.01 mm),
respectively. As far as possible, we targeted previously colour-ringed
birds with known successful breeding status in previous years, and
ringed unmarked birds with a British Trust for Ornithology metal ring
and a blue-white high impact acrylic colour ring with a unique
alphanumeric combination. Birds were assumed to form a pair because they
performed courtship behaviours and attended the same breeding site and
all pairs consisted of at least one previously marked individual so that
the sex of each bird was known or inferred based on the sex of its
partner. We attached nanofix GPS GSM tags (Pathtrack Ltd., Otley, UK,
18g) to the central three tail feather using TESA 4651 tape. Tags were
programmed to record the birds' location every 15 minutes and scheduled
to send 12-hourly data packages via the mobile phone network to a
server, from where we accessed data in near real-time. The tags are
solar powered and have a built-in dynamic algorithm that adjusts the GPS
fix frequency depending on battery charge.

The total handling time lasted \textasciitilde{} 10 minutes. Once
released, most birds returned immediately to their nests. We monitored
all birds after capture and on subsequent trips to verify pair
continuity and nest status. We confirmed in late May that all pairs
tagged in April were incubating an egg. One pair had split up or been
erroneously captured as a pair, but both birds were incubating an egg
with unmarked partners. Access to the colony following the August
captures was restricted due to the HPAIV outbreak, but we resighted one
GPS tagged bird captured in August with a chick in late September -- the
others were not resighted, but chicks might have already fledged at this
late stage of the breeding season.

\emph{GPS tracking -- non HPAIV years}

For comparison with the data from the HPAIV year 2022, we used GPS
tracking data for incubating or breeding Bass Rock gannets collected
during 2015 -- 2019 (150 deployments; n = 120 individual birds).
Briefly, the capture methodology was very similar to the approach we
took in 2022, but instead of GPS-GSM tags, small GPS loggers
(igotU-GT600, Mobile Action Technology, Taipei, Taiwan, 33 g) with a
fixed sampling interval of 2 minutes were deployed, both before
incubation in late April (2017 -- 2019) and at chick rearing from
mid-July (2015 -- 2019). Tags deployed on birds during April were
retrieved mainly in June, tags deployed during chick-rearing were
retrieved after 7 - 14 days .

\emph{Maximum daily distance to capture colony}

Prior to any spatial data analyses, we transformed all spatial data into
the Lambert Azimuth Equal Area LAEA (EPSG code 3035) projection. We
curtailed GPS data to the 30\textsuperscript{th} September 2022 to omit
GPS locations associated with the onset of migration.

We calculated the maximum daily distance to the Bass Rock breeding
colony as a measure of the extent of the space used by each bird. First,
using the function \emph{gridDistance} (R package raster, Hijmans,
2022), we generated a distance raster with a resolution of 1 km that
originated at the Bass Rock and that excluded land thus reflecting
biologically realistic travel distances . Overlaying the GPS locations
on the distance raster, we extracted the distance (measured in km) of
each GPS location to the Bass Rock using the function
\emph{st\_extract}(R package stars, Pebesma, 2022). We calculated the
`julian day' of each GPS location using the function \emph{yday} (R
package lubridate, Grolemund \& Wickham 2011) and used the maximum
distance for each day, for each bird in each year as response variable
for our model. Prior to the statistical analysis (see below), we
filtered the dataset to include only maximum distances \textgreater{} 0,
to omit colony visits.

\emph{Colony visits}

For each GPS location, we calculated the nearest distance to any known
gannet breeding colony using the \emph{st\_nn} function (R package
nngeo, Dorman, 2022). Since gannets congregate in `rafts' in the
vicinity of colonies and the majority of rafting events were
concentrated within a 2 km radius around a colony , we defined a `colony
visit' as a visit of more than 15 minutes (two subsequent GPS locations
for 2022 and seven for previous years when sampling rate was higher)
within a 2 km radius of a gannet breeding colony. We retained the
identity of any visited colony and calculated the duration of the colony
visit as the difference between the earliest timestamp of a GPS location
within the 2 km radius and the first timestamp of the subsequent
location outside of it.

\emph{Statistical analysis}

We fitted a mixed-effect generalised additive model using the
function\emph{gam} (R package mgcv, to the data to quantify potential
non-linear variation in the relationship between `maximum daily
distance' (response variable) and Julian day (explanatory variable). We
fitted an interaction between smoothed Julian-day and the factor `HPAIV
status', classifying all years prior to 2022 as `non-HPAI' and the year
2022 as ``HPAI''. We accounted for the non-independence of repeated data
points from the same bird by fitting a random effect for Bird ID on the
intercept.

We used R version 4.2.2 (R Core Team, 2021) for all data processing and
analyses.

Results

\emph{Fate of breeding gannets tagged during the HPAIV outbreak}

GPS transmission for five birds, three males and two females, each from
a different pair, ended abruptly, only 3.4 ± 2.9 days after the outbreak
started on the 4\textsuperscript{th} of June 2022 (range -1 -- 6 days,
Figure 1D). Since tail-mounted TESA deployments can last up to five
months (J. Jeglinski, unpublished), these short transmission periods
suggest that the birds died and that all pairs were broken up by the
death of one partner. Indeed, one of these birds (Bird Id 18244) was
found long dead in Swedish waters on the 21\textsuperscript{st} July
2022 (Figure 1D). The remaining birds transmitted data for 42 ± 35.8
days following the outbreak (range 18 -- 101 days, Figure 1D). Three
(18220, 18233, 18247) out of the 10 birds tagged in April prior to
incubation were sighted alive during subsequent visit to the colony 58,
111 and 112 days after the start of the outbreak, respectively; all
three birds had lost the GPS tag and 18220's right eye had turned black
(Figure 1D).

\emph{Variation in maximum movement range in HPAI and non HPAI years}

Breeding gannets that survived the first few days of the outbreak
instigated long-distance movements away from the Bass Rock on the
4\textsuperscript{th} June (n = 5 individuals, mean ± sd, 369 ± 221 km,
max 933 km, Figure 1 A, B). These differed from the regular trips during
the incubation period before the outbreak, after the peak of the
outbreak from August 2022 onwards, and also from the regular trips
during incubation and chick rearing in 2015 - 2019 (Figure 1A, B). The
interaction between Julian day and the year's HPAIV status was highly
significant (Julian day:HPAIV year, edf = 8.21, F = 30.41, p \textless{}
0.01; Julian day: non-HPAIV year, edf = 4.42, F = 12.62, p \textless{}
0.01), suggesting that the slopes of the non-linear relationship between
Julian day and maximum daily distance differed significantly between
2022 and all previous years (Figure 1 E). In 2015-2019, birds travelled
further from the colony during incubation than whilst chick-rearing,
with maximum distances peaking in late May (before
4\textsuperscript{th}June or Julian day 155) before decreasing and
levelling off over time as chick-rearing progressed (Figure 1C). In the
HPAIV year, birds continued to increase the maximum distance travelled
from the colony through June while the HPAIV outbreak was ongoing on
Bass Rock. Their maximum distances from the colony peaked in mid-July
and decreased to below incubation-period distances around 2.5 months
after the onset of the outbreak, to increase again towards the end of
the breeding season (Figure 1E).

\emph{Colony visits}

During the HPAIV outbreak (i.e. between 4\textsuperscript{th} June and
31\textsuperscript{st} July), two of the surviving GPS-tracked gannets
visited other colonies, with one bird (bird ID 18247m female) visiting
three colonies (Troup Head, St. Kilda, and Ailsa Craig), and a second
(bird ID 18220, female) visiting Heligoland (Figure 1 B, SM1 Figure S1
-- S5). A third bird (bird ID 18226, male) flew to the Norwegian coast,
moved \textasciitilde{} 50 km inland, visiting several freshwater lakes,
then returned to the coast where transmission ceased (Figure 1 B, SM1
Figure S6 - S7). None of the 120 birds tracked between 2015 and 2019
visited a different breeding colony. None of the other GPS tracked
gannets has ever been recorded flying inland and frequenting freshwater
bodies.

Discussion

We found evidence that surviving adult breeding gannets that had lost
their egg/chick and likely also their partner at the start of the HPAIV
outbreak on the Bass Rock modified their regular movement and space use
patterns by instigating long-distance movements towards geographic
locations beyond well-documented previous ranges, including visiting
inland freshwater lakes and prospecting several other gannet breeding
colonies.

Prospecting provides colonial animals with information on site quality,
which can inform recruitment . In seabirds, adults tend to be
philopatric following recruitment and prospecting is primarily
associated with immatures . However, breeding failure may initiate
prospecting in some instances, although evidence points primarily
towards Laridae which frequently breed in ephemeral habitats (e.g.
coastal shingle) and thus tend to have lower philopatry than other
seabird taxa . In contrast, gannet colonies are more stable over time,
some having existed for hundreds of years . Indeed, based on data from
the many hundreds of breeding gannets tracked from 16 colonies over more
than two decades, we are unaware of any similar prospecting or
wide-ranging movements by adults (e.g., Hamer, 2000, 20001, 2007, 2009,
Lane 2020, Garthe 2007, Waggitt 2014, Votier 2017, Warwick Evans 2015,
Clark 2019, Pettex 2012, Gremillet 2006, Wakefield 2013, Peschko 2021).
Previous tracking of failed breeders revealed they are less constrained
than breeders but did not show the long-distance and inter-colony
movements described here (Votier et al 2017). Moreover, Cape
gannets,\emph{Morus capensis} maintain nest sites and foraging ranges
under extreme food stress and mass breeding failure . Gannets acquire
their breeding sites over a period of years, which often involves
vigorous fighting and near-continuous displaying and it is possible that
the high investment involved in this prolonged process may generally not
be traded off against rushed site abandonment. It appears that the
outbreak of a highly lethal disease, and the resulting severe and
obvious decay in the quality of the breeding habitat around them, may be
a sufficiently drastic disturbances to their environment that has the
potential to decrease the site faithfulness of gannets.

The HPAIV outbreak triggered long-distance movements of gannets into
geographic areas that breeding gannets did not frequent before or after
the outbreak or in any of the five other years we had tracking data for
the study colony. `Fleeing' is one of several behaviours that animals
may show in response to a disturbance . However, direct responses to the
disturbance caused by disease outbreaks are poorly understood since this
requires serendipitous animal observations or tracking concurrent with
severe disease outbreaks. One rare example is a record of long-distance
movements of a white-tailed deer, \emph{Odocoileus virginianus} , away
from a chronic wasting disease outbreak which may serve as rapid
long-distance dispersal mechanism of the disease . Similarly, unusual
long-distance migratory movements of harp seals \emph{Phoca
gronelandica} may have brought morbillivirus into the European harbour
seal \emph{Phoca vitulina} population, and long-distance movements of
asymptomatic grey seals, \emph{Halichoerus gryphus} , may have spread
the virus across large geographic scales, resulting in two severe
phocine distemper outbreaks with thousands of dead seals in the last
three decades . At the height of the HPAIV outbreak, disorientated sick
gannets that later died have been observed at highly unusual inland
locations, for example on a farm in Dorset (N. Baker, in litt.) and it
is possible that the gannet movements towards inland Norway illustrate
such a case.

Long-distance movements are only relevant for disease transmission
dynamics if the moving animal is infectious at the time of movement. We
do not have these data for our GPS-tracked gannets since they were
captured well before the disease outbreak. However, the GPS-tracked
animals nested in an area where we recorded severe mortality of adult
breeders (Lane et al. submitted), where gannets, incapacitated by
clinical HPAIV symptoms such as uncontrollable body jerks and spasms,
tumbled through the breeding birds and were attacked by breeders leading
to direct physical contact (Clifford. S, pers. obs.). It is highly
likely that the GPS tracked birds were exposed to the virus, also
evidenced by the immediate cessation of data transmission and likely
death of half of our study birds. The duration of viral shedding for
HPAIV for seabirds is unknown, but data from six experimentally infected
wild duck species suggests that live virus can be shed from 1-2 days
after inoculation, for periods between 5 and 14 days . Surviving gannets
in our study travelled rapidly over the course of a few days to novel
locations during the HPAIV outbreak, thus may well have been infectious
over that period.

The unusual long-distance movements described above involved gannets
spending time in other gannet colonies and in foraging ranges of gannets
from other colonies as well as visiting inland lakes, which may have
brought a sick gannet into contact with waterfowl that gannets would
normally never have encountered. Given our small sample size, the number
of birds that performed these movements is astonishingly high. If the
individual-level responses we describe here scale up to the colony
level, the outbreak of HPAIV may self-propagate transmission through the
gannet metapopulation, and potentially beyond, by altering gannet
movement that enhance the connectivity between different gannet colonies
and different habitat types with different susceptible animal
communities. Long-distance movements in diverse directions across the
metapopulation have the potential to lead to superspreading events . In
disease ecology, super spreaders are individuals that are responsible
for disproportionally large numbers of secondary cases , for example
through increased contact rates. Super spreaders have the potential to
profoundly alter disease dynamics because they play a pivotal role in
the shaping the speed, distance and magnitude of epidemics . In the
specific case of the HPAIV epidemic in gannets, such super-spreading,
even by a small number of individuals, might explain the rapid spread
through the gannet colony networks in the West and East Atlantic (Lane
et al., submitted).

Our data suggest that the potential for super spreading in gannets
coincides with high virus circulation in colonies immediately following
the outbreak, but that such unusual movements appear to be short-term
responses rather than longer-term behavioural modifications (Figure 1 B,
C, E). Indeed, breeding gannets with chicks tracked several months after
the onset of HPAIV outbreaks in three gannet colonies did not show any
of the unusual space use patterns we found (Grémillet et al. in review).
It gives hope that the few breeding pairs with chicks that survived
appeared to maintain their established routines, but it remains to be
seen if a previous HPAIV infection may have other sub-lethal effects on
behaviour and physiology of surviving gannets in coming years.

\emph{Conclusions}

In 2022, HPAIV emerged, unexpectedly, which poses a severe threat to the
global gannet metapopulation and many other seabird species . Modelling
of avian cholera, a similarly threatening disease in common
eiders\emph{Somateria mollissima} , has shown that, at one colony, 30\%
mortality and more than four outbreaks per decade will lead to
extinction in 20 years . Gannet mortality in 2022 at Bass Rock was
\textgreater{} 50 \% (Lane et al. submitted) - if such mortality events
reoccur, the future for gannets looks bleak . Here we show that adult
gannets exhibit unusual movement behaviour during the HPAIV outbreak and
have the potential to act as super spreaders. Ignoring fine-scale animal
movements during disease outbreaks can mis-characterize transmission
risk and epidemiological dynamics . To better understand HPAIV
transmission dynamics, within and between species, therefore requires
collecting fine-scale movement data from populations at risk across
large spatial scales, in combination with epidemiological sampling,
demographic monitoring and epidemiological modelling.

Acknowledgements

We thank Sir Hew Dalrymple for the permission to conduct our research
project on the Bass Rock. We thank Ruth Jeavons and Shannon Clifford for
their help in collecting the GPS tracking data. We thank Jack Dale, John
McCarter and the Scottish Seabird Centre for logistical support. We
thank David Grémillet for comments on a previous version of this
manuscript. This work was funded by a NERC urgency grant to Steve
Votier, Jason Matthiopoulos and Jana Jeglinski. Jana Jeglinski and Jason
Matthiopoulos were part-funded by the UK Department for Business, Energy
and Industrial Strategy Offshore Energy Strategic Environmental
Assessment BEIS OESEA program. Equipment for this study was funded
through the Nature Restoration Fund to the Scottish Seabird Centre.

Permits

The fieldwork was performed in partnership with the Scottish Seabird
Centre with permission of the landowner of the Bass Rock, Sir Hew
Dalrymple, and under a special methods endorsement and ringing permit of
the British Trust for Ornithology BTO to Jana Jeglinski. Colour ringing
was performed under a permit to Jude Lane from the BTO. We conducted our
fieldwork under an exemption to the general ringing ban in seabird
colonies granted by NatureScot which permitted us to capture and tag
gannets during the HPAIV outbreak. All fieldwork was performed with the
required risk assessments and ethical approval in place.

Competing Interests

The authors declare no conflict of interest.

References

Figure headers

Figure 1 A) Movements of breeding adult gannets before the outbreak of
HPAIV on the Bass Rock on the 4\textsuperscript{th} of June, B) during
the outbreak up until 31\textsuperscript{st} July and C) after the
outbreak. Gannets GPS-tracked from April 2022 onwards are individually
coloured (see legend), positions for gannets tagged in 2015 -- 2019 and
from August 2022 in grey. Colony locations are indicated as open black
diamonds, colonies visited by GPS tracked birds are shown as orange
diamonds D) Maximum daily distances from the Bass Rock colony for gannet
pairs tracked during the HPAI outbreak, individual colours correspond
with movement data in A, B and C. The vertical black line indicates the
start of the HPAIV outbreak on the Bass Rock. E) The relationship
between maximum daily distance and Julian day for all other years (left)
and the HPAI year (right, gam prediction and confidence interval and raw
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