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\begin{document}

\title{Fine scale foraging habitat selection by two diving central place
foragers in the Northeast Atlantic}



\author[1]{Mathilde Huon}%
\author[1]{Yann Planque}%
\author[2]{Mark Jessopp}%
\author[2]{Michelle Cronin}%
\author[1]{Florence Caurant}%
\author[1]{Cécile Vincent}%
\affil[1]{Université de La Rochelle}%
\affil[2]{University College Cork}%


\vspace{-1em}



  
  \date{June 16, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
1. Understanding the animal-habitat relationship at local scale is
crucial in ecology, particularly to develop strategies for wildlife
management and conservation. As this relationship is governed by
environmental features and intra and inter-specific interactions,
habitat selection of a population may vary locally between its core and
edges. 2. This is particularly true for central place foragers, such as
grey and harbour seals, whose trends in numbers vary among different
regions in the Northeast Atlantic. Here, we aimed at studying how
foraging habitat selection may vary locally with the influence of
population trends and physical habitat features 3. Using GPS/GSM tags
deployed in grey and harbour seal colonies of contrasting sizes, we
investigate spatial patterns and foraging habitat selection by comparing
trip characteristics and home range similarities, and fitting GAMM to
the seal distribution and environmental data respectively. 4. We show
that grey seal foraging habitat selection and spatial patterns differed
markedly between regions. Grey seals may select environmental
characteristics for their foraging habitat accounting for local
differences in prey consumed. Spatial patterns were different might
depend on local seal density and regional productivity, located from
inshore to offshore areas for the limit ranges and core population
respectively. Our results on foraging habitat selection reflected the
coastal and sedentary behaviour of harbour seals. We found no difference
in spatial patterns between colonies, except for the Inner Hebrides
where seals foraged further, potentially reflecting density dependence
pressure, as the number in this colony is higher. 5. These results
suggest that local conditions might have a strong influence on
population spatial ecology, highlighting as well the relevance of
studying foraging habitat selection based on foraging behaviour at fine
geographical scale, particularly if species are managed within regional
units.%
\end{abstract}%



\sloppy


Fine scale foraging habitat selection by two diving central place
foragers in the Northeast Atlantic

Huon M.\textsuperscript{1*}, Planque Y.\textsuperscript{2}, Jessopp,
M.\textsuperscript{3,4}, Cronin M.\textsuperscript{3,4}, Caurant,
F.\textsuperscript{2}, Vincent C.\textsuperscript{2}

1. Observatoire Pelagis, UMS 3462 CNRS - La Rochelle Universit\selectlanguage{ngerman}é, 5 allée
de l'Océan, 17 000 La Rochelle, France, 2. Centre d'Etudes Biologiques
de Chizé, UMR 7372 CNRS -- La Rochelle Université, 79 360 Villiers en
Bois, France, 3. MaREI Centre, Environmental Research Institute,
University College Cork, Cork, Ireland, 4. School of Biological, Earth
\& Environmental Sciences, University College Cork, Cork, Ireland

*mathilde.huon@univ-lr.fr

ABSTRACT

\begin{enumerate}
\tightlist
\item
  Understanding the animal-habitat relationship at local scale is
  crucial in ecology, particularly to develop strategies for wildlife
  management and conservation. As this relationship is governed by
  environmental features and intra and inter-specific interactions,
  habitat selection of a population may vary locally between its core
  and edges.
\item
  This is particularly true for central place foragers, such as grey and
  harbour seals, whose trends in numbers vary among different regions in
  the Northeast Atlantic. Here, we aimed at studying how foraging
  habitat selection may vary locally with the influence of population
  trends and physical habitat features
\item
  Using GPS/GSM tags deployed in grey and harbour seal colonies of
  contrasting sizes, we investigate spatial patterns and foraging
  habitat selection by comparing trip characteristics and home range
  similarities, and fitting \emph{GAMM} to the seal distribution and
  environmental data respectively.
\item
  We show that grey seal foraging habitat selection and spatial patterns
  differed markedly between regions. Grey seals may select environmental
  characteristics for their foraging habitat accounting for local
  differences in prey consumed. Spatial patterns were different might
  depend on local seal density and regional productivity, located from
  inshore to offshore areas for the limit ranges and core population
  respectively. Our results on foraging habitat selection reflected the
  coastal and sedentary behaviour of harbour seals. We found no
  difference in spatial patterns between colonies, except for the Inner
  Hebrides where seals foraged further, potentially reflecting density
  dependence pressure, as the number in this colony is higher.
\item
  These results suggest that local conditions might have a strong
  influence on population spatial ecology, highlighting as well the
  relevance of studying foraging habitat selection based on foraging
  behaviour at fine geographical scale, particularly if species are
  managed within regional units.
\end{enumerate}

\emph{Key words} : Central place foragers; diving behaviour; foraging
activity; grey seal; GPS/GSM telemetry; habitat selection; harbour seal;
local scale.

INTRODUCTION

Understanding species distribution and their relationship with habitat
is central in ecology and to the development of strategies for wildlife
management and conservation (Morris, 2003; Rhodes et al., 2005). This is
particularly true in marine ecosystems, as nowadays oceans face
increasing threats from overexploitation and habitat destruction
(Halpern et al., 2008; Jones et al., 2018). In this ecosystem,
distribution of a species is shaped by interactions between internal
(\emph{i.e.}species' physiological tolerance, dispersal and reproductive
strategies) and external factors (\emph{i.e.} environmental features,
regional richness \emph{etc.} ). Intra and inter-specific interactions
can also drive species distribution. For example, competition, through
resource exploitation and then reduction of limited resource ( i.e. prey
depletion, Vance, 1984), leads to spatial and temporal segregation,
and/or diet specialization among individuals or species (Leung et al.,
2012). In a metapopulation composed of different local populations in
distinct geographical areas, these interactions will vary locally due to
variation in physical habitat features and community structures (Thomas
et al., 1999). The local abundance of species, particularly in
top-predator case, tends to be greater towards the centre of their
ranges, increasing the consumption pressure on prey resources, therefore
leading to a higher degree of density dependence (Oliver et al., 2009).
Subsequently, individuals living in the core population use a wider
range of subordinate habitats (Brown, 1988). Depending on these
different pressures, individuals disproportionately use the available
conditions and resources, defining habitat selection (Mayor et al.,
2009). This habitat selection differs from use or association, it
implies choice, and is commonly measured as use relative to availability
or as use versus non-use (Mayor et al., 2009). Understanding the causes
of variations in habitat selection for local populations, and
determining how trends in selection can be organized in space and time
represents a major challenge in ecology (Fortin et al., 2008).

Selection of resources can be regarded as the expression of different
behaviour forms (i.e. dispersal, migration etc.) of an animal in a
particular environment (Schoener, 1969). It is important to consider
behaviour when studying habitat selection. At local scale, foraging
behaviour is perceived as the major behaviour which ultimately
influences reproductive success and survival rates (Breed et al., 2009),
and was already taken into account in different studies focusing on
habitat selection (Donazar et al., 1993; Duchamp et al., 2004; Monsarrat
et al., 2013). Recently, several studies on the ecology of marine
central place foragers, such as pinnipeds and seabirds, used telemetry
devices to incorporate foraging behaviour in their analyses (Guinet et
al., 1997; Hamer et al., 2001; Jonsen et al., 2007; Shiel et al., 1999).

In the Northeast Atlantic, grey seals (\emph{Halichoerus grypus} ) and
harbour seals (\emph{Phoca vitulina} ) are two sympatric species
occurring along the European continental, Irish and British coasts, with
differing population trends (SCOS, 2017). Grey seals and harbour seal's
core populations are located in the UK with an estimated 141,000 and
43,500 seals respectively (SCOS, 2017). In France and Ireland, colonies
of both species are located at their southern and western range limit
respectively. They are located across a range of habitats, local
abundances at the colonies and trends in abundance. Seals move regularly
between colonies and can remain at sea for a long period. However, they
display a high degree of site fidelity with foraging concentrated around
their haulout sites (Cronin et al., 2013; Huon et al., 2015; McConnell
et al., 1999; Sjöberg and Ball, 2000).

This context represents an excellent case for comparing intra and
inter-specific of seals' foraging habitat selection and spatial usage.
Many grey and harbour seals have been tracked from different colonies in
the Northeast Atlantic , some of these data were already used to study
habitat selection of both species, separately at the colony scale
(\emph{i.e.} local) from only one or two study sites (Aarts et al.,
2008; Bailey et al., 2014; Huon et al., 2015); or at the population
scale ( \emph{i.e.} global, Jones et al., 2015) pooling multiple
datasets. In this study, we will combine for the first time several
datasets for the assessment of foraging habitat selection at a local
scale. Incorporating the results in a global context together represents
a unique opportunity to bring new key elements on grey and harbour
seal's ecology in the Northeast Atlantic. We aimed at 1) studying the
foraging habitat selection of grey and harbour seals at a colony
(\emph{i.e.} local) scale, and 2) investigating the influence of
population trends in contrasted haulout areas and physical habitat
features on the seals' spatial patterns and foraging habitat selection.

MATERIALS AND METHODS

2.1 Study areas

Grey seals were tracked in 5 regions (Fig 1, Appendix 1): the Irish
Continental Shelf (\emph{ICS} ), the Irish Sea, the Firth of Tay
(\emph{FoT} , representing the core population), the Eastern English
Channel (\emph{EEC} ) and the Iroise Sea (, where grey seals are at
their southern limit range). Local seal numbers in these studied
colonies are 1,200 (Cronin et al., 2013), 800 (Cronin et al., 2016),
10,000 (SCOS, 2017), 100 , and 130 (Vincent et al., 2017) seals
respectively. Harbour seals were tracked in 4 regions: the Kenmare Bay,
the Inner Hebrides, the Firth of Tay and the English Channel, including
the haulout sites of the\emph{Baie du Mont Saint Michel (BdM)} , the
\emph{Baie des Veys (BdV)}and the \emph{Baie de Somme (BdS)} . Colony
numbers of harbour seals in these regions are 390 (Kavanagh et al.,
2010), 1,500, 280 (SCOS, 2017), 80, 200, and 600 (Vincent et al., 2017)
seals respectively. Within all regions where both species are breeding
(Inner Hebrides, FoT and EEC), we obtained tracking data from both
species at FoT and EEC, providing the opportunity to study potential
influence of interspecific interactions on foraging habitat selection
and spatial usage.

2.2 Data description

\emph{Seal handling and tagging} - One hundred and two seals were caught
and tagged in total (all tagging sites combined) between 2008 and 2014
by the University of La Rochelle (France), the Sea Mammal Research Unit
(St Andrews University, UK) and University College Cork (Ireland),
representing 46 grey seals and 56 harbour seals (Table 1). Seals were
caught around and/or on their haulout sites and fitted with Fastloc
GPS/GSM tags developed by the Sea Mammal Research Unit. These tags
collect data and information on animal diving, haulout activities and
location, and relayed through onboard mobile phone with GSM modem (Sea
Mammal Research Unit, St Andrews University, full specifications
available at
http://www.smru.st-and.ac.uk/Instrumentation/downloads/GPS\_Phone\_Tag22.pdf).

\emph{Breeding and moulting period} -- During the breeding and moulting
periods, seals tend to strongly reduce their foraging activities,
increasing the amount of time spent hauled out, or staying close to
their haulout sites (Boness, 1984; Caudron et al., 2009; Lidgard et al.,
2003). As we aimed to focus on their foraging activities to model
habitat selection, data obtained during the breeding (September to
December for grey seals) and early moulting (January to February for
grey seals) periods were excluded from the analyses. All harbour seal
data were obtained outside the species' breeding and moulting seasons.
Changes in the diving and haulout behaviour were tracked during the
reproductive and moulting periods with the \emph{MamVisAd} software (Sea
Mammal Research Unit, Saint Andrews University). When a strong reduction
in proportion of time in diving was observed during these two periods
and the seal hauled out for prolonged periods in a known breeding or
moulting area, the data were excluded.

\emph{Return-trip selection} -- In the Northeast Atlantic, harbour seals
are relatively sedentary, showing short movements from their haulout
sites (10-20 Km) and long-term fidelity (Ries et al., 1997; Tollit et
al., 1998; Vincent et al., 2010). In contrast, telemetry on grey seals
showed frequent movements between colonies (McConnell et al., 1999).
They can alternate return trips to their haulout site in specific areas
(within areas where most of their foraging activities occur) but they
also frequently travel over hundreds of kilometres to distinct haulout
site (SCOS, 2017). To study habitat selection and spatial usage of grey
seals, we chose to focus on foraging trips and therefore only selected
return trips to the same haulout areas (McConnell et al., 1999).

\emph{Explanatory variables} - We used three environmental variables to
identify the foraging habitat selection of grey and harbour seals
(Appendix 2). These variables were chosen due to their expected role in
the seals' foraging ecology (Aarts et al., 2008; Bailey et al., 2014;
Huon et al., 2015). Bathymetry was obtained from the European Marine
Observation and Data Network (\emph{EMODnet} ), with a grid size
resolution of 0.125*0.125 minutes
(\emph{http://www.emodnet.eu/bathymetry,} ). Sediment data were obtained
from the \emph{MESH\_EUNIS} model (Mapping European Seabed Habitat
project), which predicts habitat types with a spatial resolution of 300
meters. Sediment types were based on a simplified FOLK classification
system (Folk, 1954) and limited to the most dominant types: rock, mud,
sand, gravel, coarse, and mixed sediments. We used different tidal
current datasets for Irish, Scottish and French areas, scaled to similar
resolutions for inter-site comparisons. Datasets for the French study
areas were obtained from \emph{Previmer} (Lecornu and De Roeck, 2009)
for the tracking period. These were created from the MARS 2D model with
a resolution of 250m and were available at an hourly scale. The Irish
Marine Institute provided tidal current data for the Irish Continental
Shelf and the Irish Sea (\emph{https://www.marine.ie/Home/home} ). Data
was obtained from a numerical model with a spatial resolution varying
between 1.2 Km and 1.5 Km and corresponded to surface tidal current at 3
hours interval. This dataset did not cover the Kenmare bay (for which no
tidal current data was available). We averaged model datasets for the
French and Irish areas respectively, in order to represent the tidal
strength in space irrespective of instant tidal phases (ebb, slack or
rising tide). Tidal current data for Scottish sites was obtained from
the Web vision renewable website and was calculated from the ABP mer
model (\emph{Atlas of UK marine Renewable Energy Resources 2008. ABP
mer, http://renewables-atlas.info/} ). This data corresponded to the
peak current speed of a mean spring tide (m.s\textsuperscript{-1}), with
a spatial resolution decreasing from 200m to 5 Km from inshore to
offshore areas.

The distance between each GPS location and the last haulout and the
distance to the shore were also included as explanatory variables to
describe accessibility to the environment (Aarts et al., 2008). The
geodesic distance to the last haulout visited was calculated using the
\emph{LC.dist} function from the \emph{Marmap} package (Pante and
Simon-Bouhet, 2013) in R \emph{v 3.3.3} (R core Team 2017). Distance
from shore was calculated as the straight-line distance to the closest
point along the coast using ArcGIS \emph{v 10.5} (Environmental Systems
Research Institute, Inc., Redlands, CA, 2017) ``\emph{Nearest} ``
function.

2.3 Foraging habitat selection

\emph{Assessment of the seals' foraging locations} - We analysed the
seals' dives to identify their foraging behaviour following (Planque et
al., 2020). Dives with a maximum depth \textless{} 3 meters and a dive
duration \textless{} 30 seconds were removed, considering that very
shallow and short dives are unlikely representing foraging behaviour. We
applied two diving criteria related to the seals' benthic foraging
behaviour: the dive shape and vertical descent speed (Vincent et al.,
2016). These criteria were determined for each individual because of
possible inter-individual variability in diving strategies linked with
physiological or behavioural characteristics (Austin et al., 2006; Beck
et al., 2003). Dive-shape was assessed through the \emph{Time Allocation
at Depth} index (TAD, Fedak et al., 2001), usually varying from 0 and 1,
where 0 correspond to dives close to the surface and 1 to ``U-shape''
dives. These square dives are assumed to represent foraging (Bjørge et
al., 1995; Hindell et al., 1991; LeBoeuf et al., 1988; Thompson et al.,
1991). We set a minimum TAD threshold to the 3rd quartile
(\emph{i.e.}75\% of dives) of each individual dive distribution
according to their shape in order to select 25\% most U-shaped
individual dives (Planque et al., 2020). Long duration dives with a very
low vertical descent speed (assumed to be sleeping dives) were excluded
from the analysis for each individual: we excluded 10\% of the most
U-shaped dives characterized by the lowest vertical descent speeds.

\emph{Use-availability design} -- Following the use-availability design
(Keating and Cherry, 2004), we assessed the foraging habitat selection
by comparing the environmental characteristics of points (i.e. foraging
dive locations) to those of randomly generated points, representing the
habitat availability (Aarts et al., 2008; Johnson et al., 2006; Keating
and Cherry, 2004; Lele and Keim, 2006). Two random points per foraging
dive point were created locally within the different study areas using
the \emph{sp} R package. These random points were created in each study
area within buffers three times the size of the Minimum Convex Polygon
(\emph{MCP} , Burgman and Fox, 2003) of the seals' dive locations in
each study area, limited by the continental shelf (seals do not travel
further). For the \emph{EEC} and the \emph{FoT} , where both species
were present, one buffer was created for each species.

\emph{Modelling analyses} -- We fitted \emph{Generalized Additive Mixed
Models} (GAMM) to the data, with the \emph{gam} function \emph{mgcv} R
package. We used a binomial family argument with a
\emph{logit-link}function to estimate the parameters of an
\emph{inverse-logit} selection model based on seal foraging dives and
random points (Johnson et al., 2006). Foraging dives and random points
were the response variable, taking the value 1 and 0 respectively. To
consider the intra-individual autocorrelation, we treated the individual
as a random effect. Environmental variables were treated as fixed
effects. The bathymetry, tidal current, distance from shore, and
distance from the last haulout were included as discrete variables;
sediments were treated as categorical variable. When one sediment type
was over-represented, the model was forced to consider this sediment
type as reference level (otherwise reference sediment type was included
alphabetically). The multi-collinearity between covariates was assessed
using the VIF value (\emph{Variance Inflection Factor} , Kutner et al.,
2004). The best model was selected using the AIC criteria
(\emph{Akaike's Information Criteria} ,Akaike, 1973). Furthermore, we
calculated the importance of each covariate with the prediction function
of the GAMM, providing an index of the relative importance of each
covariate in the chosen model. The maps of habitat selection predicted
by the model were created with ArcGIS for all sites.

2.4 Influence of intra and interspecific interactions on spatial
patterns and home range segregation

Trip characteristics and measure of similarity between home ranges were
used to evaluate the influence of intra and inter-specific interactions
on spatial patterns, to get complemental information to foraging habitat
selection. For each species, trips with duration lower than 3h were
removed as they were considered to be in the vicinity of haulout sites
(Cronin et al., 2013). We used trip duration and maximum extent from the
haulout sites (values were log transformed to correct for non-normal
distribution). Interpolated tracks were used for these trip
characteristics. To reduce sampling bias (between areas where seals
spend more time diving or out of the water), we interpolated all GPS
locations every 20 minutes using straight-line interpolation. We assumed
that each trip made by an individual seal was independent from the
others. Shapiro and Bartlett tests were firstly used to test the
normality and homoscedasticity of the data by using the
functions\emph{shapiro.test} and \emph{bartlett.test} from the
\emph{Stat} R package. If the normality and homoscedasticity were
validated, ANOVA was used for inter-specific site comparison; if not, we
used a Kruskal Wallis test (respectively \emph{aov} and
\emph{kruskal.test} function). When the inter-variability was validated,
a post-hoc test was used for pairwise comparison. We used a Tukey HSD
test (\emph{tukey HSD}function) in the case of ANOVA; and the dunn test
(\emph{dunn.test}function in the \emph{dunn.test} R package) in the case
of Kruskal Wallis. We used the \emph{Bhattacharyya's affinity} index
(BA, (Bhattacharyya, 1943) to quantify home range spatial overlap. This
method quantifies the spatial overlap between two population spatial
distribution (Fieberg et al., 2005) and provides a value ranging from 0
(\emph{i.e.} no overlap or complete segregation) to 1
(\emph{i.e.}complete overlap). We applied the BA on the 95\% Kernel
density of foraging dive locations between individuals of the same
colony to study the influence of colony size (i.e. indirectly the
density dependence), and between species when both species were tracked
around the same colony (i.e. FoT and EEC) to study the influence of
inter-specific interactions. We used the \emph{Kerneloverlaphr} function
of the\emph{adehabitatHR} R package (Calenge, 2006).

RESULTS

3.1 Foraging habitat selection

\emph{Grey seal foraging habitat selection} -- 438,314 dive points were
identified as foraging dive locations for all study areas (Table 1,
Appendix 3). The details of the model selected for each site are
presented (Table 2). The explained deviances for all sites were
relatively high (Table 2), varying between 31\% (for the EEC) and 78\%
(for the Iroise Sea). For most sites, the distance from the last haulout
accounted for most of the explained variance, varying from 45\% (FoT) to
76\% (Iroise Sea). The second variable having a strong influence on the
habitat selection was the bathymetry, varying from 15\% (Iroise Sea) to
40\% (FoT) of the explained deviance. These two parameters had a
negative influence on foraging habitat selection, grey seals tended to
select foraging habitat close to their haulout sites and in shallower
waters. Distance from shore, tidal current and sediments combined
accounted for less than 10\% of the explained deviance, but the
influence of these variables differed among sites. In the EEC and ICS,
grey seals selected habitat further than 20Km and 150Km from shore
respectively. Conversely, grey seals selected their foraging habitat
less than 50Km from shore in the Irish Sea. Tidal current speed had a
positive influence on grey seals' foraging habitat selection in the
Irish Sea. In the ICS, they selected an optimum tidal current of 0.15
m/s. For the other sites, seals selected a minimum value of tidal
current speed (0.4 m/s for the Iroise Sea and the FoT, and 0.6m/s for
the EEC). Grey seals selected different types of sediments in the
different study areas. Habitat close to the colonies was highly selected
in all study areas (Fig 3). This was particularly true for the Iroise
Sea and the Irish Sea, where grey seals mainly selected their foraging
habitat in shallow waters around tidal areas, where they haul out.

\emph{Harbour seal} \emph{foraging habitat selection} -- 359,001 dives
points were identified as foraging dive locations for all study area
(Table 1, Appendix 3). Details of the models selected for each site are
presented in Table 3. The overall explained deviance (ED) was relatively
high (Table 3) varying from 30.9\% (BdV) to 78.3\% (BdM). Distance from
the last haulout (91\% of ED for the Inner Hebrides), the distance from
shore (92\% of ED for the BdS), and the bathymetry (62\% of ED for the
BdV) predominantly explained the deviances. The distance from the last
haulout had a negative influence for all sites, \emph{i.e} . harbour
seals selected their foraging habitat close to their haulout sites. The
influence of distance from shore and bathymetry were more contrasted.
For BdS and Kenmare bay, harbour seals selected short distances from
shore. Nevertheless, in the Inner Hebrides and FoT, harbour seals
selected their foraging habitat at 40 Km from the coast. Harbour seals
selected habitat in shallow waters in the BdM and the BdV. In the Inner
Hebrides and the FoT, they selected depths at 20 and 25m respectively.
Tidal current and sediment together only explained less than 10\% of the
deviance, except for the Firth of Tay where tidal current explained 55\%
of the deviance. Habitat selection was highest along the coastline for
the BdS, and within the bays for the BdM, the BdV and Kenmare bay (Fig
3). In the Inner Hebrides and the FoT, harbour seals selected their
foraging habitat in inshore and in distance to the shore.

3.2 Influence of intra and inter-specific interaction on spatial usage
and home range segregation

For each site and species, the hypotheses of normality and
homoscedasticity of trip duration and maximum extent were rejected
(\emph{p\textless{}} .05); leading to the use of the non-parametric
Kruskal Wallis test, and Dunn-test as a post-hoc test.

\emph{Grey seals' trip characteristics} -- Medians of trip durations
were significantly different between sites (\emph{p} \textless{}0.05,
Table 1, Fig 3, Appendix 4). Most of the pairwise-site comparisons were
significantly different (8/10, \emph{p} \textless{}0.05). Trip durations
were higher for the Irish Sea (median=3.17 hours; IQR=1.98 hours) and
shorter in the EEC (median=1.92 hours; IQR= 1.17 hours). Medians of
maximum extent differed among areas (p\textless{}0.001, Table 4). All
pairwise comparisons were significantly different (\emph{p}
\textless{}0.05) except for the EEC vs FoT (\emph{p} =0.09). Maximum
extents were longer for the FoT (median=2.70 Km; IQR=2.63 Km) and lower
for the ICS (median=0.626 Km; IQR=4.30 Km).

\emph{Harbour seals' trip characteristics} -- Medians of trip duration
were significantly different between study areas (\emph{p}
\textless{}0.001, Table 2, Fig 3, Appendix 5). Most of the pairwise-site
comparisons were significant. Trip durations were higher for the Inner
Hebrides (median=2.90 hours; IQR=1.29 hours), where the individual range
was also high) and lower for the FoT (median=2.26 hours; IQR=1.19).
Median maximum extents differed among sites (p\textless{}0.05). Ten
pair-sites over were significantly different (Table 5, Fig 4). The trip
maximum extents were higher for the Inner Hebrides (median=1.94 Km;
IQR=1.94 Km) and lower in the Firth of Tay (median=1.53 Km; IQR=1.37
Km).

\emph{Measure of similarity in home ranges} -- Within each site, grey
seals individually segregated their spatial usage, indicated by a
relative low BA values varying from 0.02±0.12 (Irish Sea) to 0.18±0.18
(ICS), (Fig 4). Overlaps of individual spatial usage were highlighted
for harbour seals in the BdM (0.87±0.12), BdV (0.75±0.19), BdS
(0.73±0.15) and the Kenmare Bay (0.65±0.19). Conversely, a low BA value
was observed for the Inner Hebrides (0.04±0.22). The interspecific
comparison between grey seals and harbour seals showed low median value
for the FoT (0.01±0.05) and the EEC (0.09±0.17), indicating spatial
segregation.

DISCUSSION

This study highlighted the importance of considering the local scale in
the understanding of the relationship between animal and its
environment; particularly in the case of meta-populations where local
population trends and physical habitat features vary regionally. By
incorporating tracking data from contrasted colonies in the Northeast
Atlantic (\emph{i.e.} core population versus limit range), our study
provides new knowledge on local foraging habitat selection of grey and
harbour seals. To avoid the problem of homogenization (Matthiopoulos,
2017), we chose to create a model for each haulout group in order to
consider local habitat availability and difference of intraspecific
interactions. Furthermore, we chose to focus on foraging activities by
using dive characteristics as seals are predominantly considered as
benthic divers (Gosch et al., 2019).This is the first time that habitat
modelling on harbour and grey seals was performed by considering likely
foraging behaviour while diving.

\emph{Grey seal foraging habitat selection and spatial patterns}

The distance from the last haulout was the most important factor
influencing the foraging habitat selection of grey seals in all study
areas (from 45\% to 76\% of the explained deviance in the model
respectively for the FoT and the Iroise Sea). Our data shows that when
performing return trips, they spend the majority of their time close to
the haulout sites. These results are consistent with previous studies
throughout the range of grey seals in the Northeast Atlantic. Grey seals
in the North Sea spent 43\% of their time within 10Km of the haulout
sites (McConnell et al., 1999) and preferentially selected habitat
closer to haulout-sites with a gradual decrease of habitat selection
beyond tens of kilometres (Aarts et al., 2008). In the Baltic Sea,
Sjöberg and Ball, (2000) noted short distance trips (from 10 to 15 Km),
grey seals spending 75\% of their time within a radius smaller than 50Km
around their haulout sites. In the Iroise Sea, grey seals mostly
undertook trips within 40Km of haulout sites (Huon et al., 2015).
Foraging habitat selection by grey seals was negatively influenced by
bathymetry, but to a lesser extent than distance from haulout sites
(varying from 10 to 40\% in the explained deviance). Depending on study
sites, the depth selection decreased until a depth of 50m (Irish and
Iroise Sea) and 100m (FoT). These results are consistent with previous
studies on grey seals habitat selection, with usual dive depth between
10 to 80 m (Aarts et al., 2008; Tollit et al., 1998). Grey seals are
generally considered as benthic feeders (Beck et al., 2003; Lydersen et
al., 1994) and the influence of bathymetry on foraging habitat selection
will presumably vary locally depending on the seabed topography and
sediment type. Furthermore, distance from the shore and tidal current
must also influence the behaviour of seals, as they use them to
orientate, to move, and to forage (Zamon, 2003, 2001). These three
variables did not contribute much to the explained deviance of the
models, and their influence varied among sites. Distribution of seals'
prey resources was not included in the model, as the data were not
available for some of the study areas.

Grey seals in the Firth of Tay and in the Eastern English Channel made
longer trips but of shorter duration compared to grey seals in the other
sites. In the Northeast Atlantic, the core population is in the North
Sea with 141,000 individuals (SCOS, 2017). In this area, due to the
important pressure on prey resources located in inshore areas, grey
seals tend to travel long distances directly to offshore areas on
specific sandbanks where sandeel availability is high (Hammond et al.,
1994; McConnell et al., 1999; Wilson and Hammond, 2019). It may be a
process to reduce the effect of density dependence and to avoid the
indirect competition for resources with fisheries. This offshore
behaviour is in accordance with our results for the FoT. Grey seals in
the EEC performed their trips mostly in specific areas along the coast,
as the EEC is known to be a major ground for flatfish (Carpentier et
al., 2009; Riou et al., 2001; Selleslagh et al., 2009), which are
observed in grey seal diet (Planque \emph{pers. com)} . In the ICS and
Iroise Sea, grey seals made shorter trips. These two sites are known as
highly biologically productive regions in the Eastern North Atlantic
(upwelling and area enclosed by specific currents, respectively for the
ICS and the Iroise Sea (Hily and Glémarec, 1999; Raine and McMahon,
1998). Furthermore, grey seals in these areas mainly feed on fish
species not targeted by commercial fisheries (Ridoux et al., 2007;
Vincent et al., 2016), and as a result, a low spatial overlap and low
resource competition were found between seals and fisheries (Cronin et
al., 2012). This low degree of competition with fisheries and high prey
availability could explain the shorter trips performed by these grey
seals, as they can find sufficient resource close to their haulout
sites. Furthermore, in the Iroise Sea, this was also supported by the
size of the colony (\emph{i.e.} small local abundance at the southern
limit range), indicating a low effect of density dependence. Grey seals
in the Irish Sea adopted a different spatial usage compared to the four
other sites, with the highest trip duration. The numbers of seals
between the East and West parts of Ireland are of the same order of
magnitude (800 \emph{versus} 1200 respectively), so colony size may not
explain the difference in spatial usage. However, a high degree of
interactions (\emph{i.e.} spatial overlaps) between fisheries and grey
seals in the Irish Sea was recently highlighted (Cronin et al., 2016;
Gosch et al., 2019). These interactions with anthropic activities could
explain why grey seals made longer trips with an intermediate maximum
extent in this area compared to the other sites. But most of all, grey
seal selected foraging habitat matching those of their prey (Alheit and
Hagen, 1997; Gosch et al., 2014; Hammond et al., 1994; Ridoux et al.,
2007).

\emph{Harbour seal foraging habitat selection and spatial patterns}

Distance from the last haulout, distance from shore and/or bathymetry
explained an important part of the deviance (\textgreater{}90\%) in
harbour seal foraging habitat selection. These three variables had a
negative influence, but at different degrees depending on the site
configuration. Harbour seals were very coastal and sedentary in the six
study areas, which is consistent with previous findings on the species:
in the Moray Firth (East of Scotland) for instance, seals forage within
30 Km of their haulout sites and dive at a maximum depth of 50m (Bailey
et al., 2014; Tollit et al., 1998). This was also highlighted on the
other side of the Atlantic, in the Saint Laurent estuary (Lesage et al.,
2004), seals were coastal (with distances shorter than 11 Km from the
shore) and in shallow waters (\textless{}50m deep). Tidal current and
sediment types accounted less in the explained deviance than the other
variables. Their influence was generally very low, with the exception of
the tidal current for the FoT. Harbour seals feed on diverse fish
species and their diet vary locally (Hall et al., 1998). At their
southern limit range, in the English Channel, harbour seals mainly
selected foraging habitat over mixed sediments in front of estuaries,
corresponding to the habitat of juvenile of flatfish that constituted
most of harbour seal diet in BdS (Spitz et al., 2015). Seal diet in BdM
was not available, we could not compare seals' foraging habitat
selection and their main prey's habitat there. On the East coast of
Scotland, harbour seals selected habitat over sandy areas in front of
the Tay river mouth, corresponding to the habitat of sandeel - the main
harbour seal prey in the area (Wilson and Hammond, 2019). Harbour seals
were more pelagic in the Inner Hebrides, selecting habitat along the
sounds of the fjords, corresponding to the habitat of pelagic species
such as whiting, scads and herring (Wilson and Hammond, 2019). Sediment
and current features selected by harbour seals might correspond to the
habitat features of their prey.

Coastal behaviour of harbour seals in the Northeast Atlantic was also
identified in their spatial usage for each study area. The median
distance from the last haulout was highest for the BdM with 6 Km.
However, two patterns were highlighted when performing intraspecific
comparisons of spatial distribution of foraging areas for each study
sites (BA index). The FoT, Kenmare bay and the study areas in the
English Channel showed a high degree of intraspecific spatial overlap
(high BA values; \selectlanguage{english}[?]0.65). Prey resources might be sufficient to sustain
all individuals around these colonies, suggesting a low influence of
density dependence. Even though the species is capable of long trips at
sea (Lesage et al., 2004), harbour seals in the FoT and Kenmare bay may
not need to perform such long trips to find their prey. Conversely, we
highlighted a lower degree of intraspecific spatial overlap in the Inner
Hebrides (BA value=0.04+-0.22). The individual range of trip duration and
maximum extent were higher. These results may be explained by the
influence of intraspecific interactions, as the colony number in this
area is more important than the others (15,200 \emph{versus} few
hundreds, SCOS, 2017). Inter-specific interactions may also have an
impact on harbour seals' spatial usage, as grey seals also breed in the
Inner Hebrides (( i.e. 8,700 individuals, Duck et al., 2013; SCOS, 2017;
Wilson and Hammond, 2019). This suggests that harbour seals in this area
may use a larger area in order to reduce intra- and interspecific
indirect competition for resources.

The number of harbour seals at some colonies in the North Sea declined
during the last decade (Thompson et al., 2019). The decline of sandeel
numbers (main prey of harbour seals around these colonies) and the
interspecific competition with grey seals were suggested as potential
causes in local harbour seal declines (Wilson and Hammond, 2019). In our
study, grey seals and harbour seals were tracked in two areas, where
both species haul-out. In this context, it was interesting to compare
the two species' foraging habitat selection and spatial usage. Spatial
partitioning between seal species was highlighted in habitat selection
and spatial patterns in the FoT and EEC, where both species coexist and
were tracked. Grey seals made longer trips than harbour seals (15 Km for
median maximum extents in grey seals in both areas, versus 5Km and 4 Km
respectively for harbour seals in the EEC and FoT). In both cases,
harbour seals tended to forage in inshore areas, while grey seals went
further offshore. The two species also selected distinct sediment types.
In the EEC, grey seals selected muddy seabed and harbour seals sand,
rock and mixed sediments. These findings are in accordance with previous
studies, that also found differences in the use of marine environment
between these two species (Jones et al., 2015; Sharples et al., 2012).

In the North Atlantic, grey seals and harbours seals are managed at
local scales, and in the absence of genetic information on population
structuring, haulout groups are often considered as ``Seal Management
Units'' (Russell et al., 2013). Both species are considered as
generalist, using a variety of habitat and prey. This study highlights
the importance of studying foraging habitat selection at local scale,
and considering the variability between colonies, as physical habitat
features and seals' prey resources vary between regions. As marine top
predators, both seal species are listed in the Annex II of the European
habitat directive requiring establishment of protected areas to maintain
favourable conservation status. At a local scale, our predictive maps of
foraging habitat selection could be used by managers to implement
specific areas of conservation to maintain a good ecological state of
their habitat and prey resources potentially at risk due to anthropic
activities. Such a foraging habitat selection analysis could be applied
and/or adapted for other central place foraging species, in both the
marine and terrestrial ecosystems.

ACKNOWLEDGEMENTS

This work was funded by the French ministry in charge of Research
(Ministere de l'enseignement superieur et de la recherche MESR). Seal
tracking in France was funded by the Parc naturel marin d'Iroise (PNMI)
and the Regional Council of Poitou-Charentes (France), and we
acknowledge SMRU, the PNMI, the Office National de la Chasse et de la
Faune Sauvage (ONCFS), the Obervatoire PELAGIS, the Zoo de La Fleche,
and Oceanopolis for their help in the field. Irish tracking data was
funded by Inland Fisheries Ireland (IFI); Department of Communications,
Marine and Natural Resources (DCMNR); Higher Education Authority of
Ireland (HEA); National Parks and Wildlife Service (NPWS), and National
Geographic Global Exploration Fund. We would like to thanks the Sea
Mammal Research Unit for providing telemetry data for grey seals and
harbour seals in UK. Seals were caught under licences issued by the
French ministry of the environment for France (Licences Nos :
01/161/AUT, 01/525/AUT, 03/380/AUT, 05/475/AUT, 05/485/AUT, 06/82/AUT,
07/481/AUT, 08/346/DEROG, 08/347/DEROG, 10/102/DEROG,
11/873/DEROG,11/874/DEROG, and 13/422/DEROG.); by the National Parks \&
Wildlife Service (Licence Nos: C35/2008, C014/2012, C0019/2011,
C04/C023/2013, and C016/2014), the Irish Health Products Regulatory
Authority for Ireland (Project Licence AE19130/P004); licence provided
by Uk home office under the Animals (Scientific Procedure) Act 1986 and
the Scottish Executive under the Conservation of Seals Act for Uk.1970.

AUTHORS' CONTRIBUTION

MH and CV conceived the ideas and developed the methodology with the
help of YP. CV, MC and MJ collected the data. MH analysed the data and
led the writing of the manuscript. All authors contributed critically to
the drafts and have final approval for publication.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study will be available on
GitHub as manuscript will be accepted.

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