Fine scale foraging habitat selection by two diving central place
foragers in the Northeast Atlantic
Huon M.1*, Planque Y.2, Jessopp,
M.3,4, Cronin M.3,4, Caurant,
F.2, Vincent C.2
1. Observatoire Pelagis, UMS 3462 CNRS - La Rochelle Université, 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
- 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.
- 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
- 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.
- 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.
- 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.
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 (i.e.species’ physiological tolerance, dispersal and reproductive strategies)
and external factors (i.e. environmental features, regional
richness 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 (Halichoerus grypus ) and
harbour seals (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
(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 ( 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
(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 (ICS ), the Irish Sea, the Firth of Tay
(FoT , representing the core population), the Eastern English
Channel (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 theBaie du Mont Saint Michel (BdM) , the Baie des Veys (BdV)and the 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
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).
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 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.
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).
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
(EMODnet ), with a grid size resolution of 0.125*0.125 minutes
(http://www.emodnet.eu/bathymetry, ). Sediment data were
obtained from the 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 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 (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 (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-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 LC.dist function from the Marmap package (Pante and
Simon-Bouhet, 2013) in R 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 v 10.5 (Environmental Systems
Research Institute, Inc., Redlands, CA, 2017) “Nearest “
function.
2.3 Foraging habitat selection
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 < 3 meters and a dive duration
< 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 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 (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.
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 sp R package. These random
points were created in each study area within buffers three times the
size of the Minimum Convex Polygon (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 EEC and
the FoT , where both species were present, one buffer was created
for each species.
Modelling analyses – We fitted Generalized Additive Mixed
Models (GAMM) to the data, with the gam function mgcv R
package. We used a binomial family argument with a logit-linkfunction to estimate the parameters of an 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
(Variance
Inflection Factor , Kutner et al., 2004). The best model was selected
using the AIC criteria
(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 functionsshapiro.test and bartlett.test from the 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 aov and kruskal.test function).
When the inter-variability was validated, a post-hoc test was used for
pairwise comparison. We used a Tukey HSD test (tukey HSDfunction) in the case of ANOVA; and the dunn test (dunn.testfunction in the dunn.test R package) in the case of Kruskal
Wallis. We used the 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
(i.e. no overlap or complete segregation) to 1 (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 Kerneloverlaphr function of theadehabitatHR R package (Calenge, 2006).
RESULTS
3.1 Foraging habitat selection
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.
Harbour seal 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, 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
(p< .05); leading to the use of the non-parametric
Kruskal Wallis test, and Dunn-test as a post-hoc test.
Grey seals’ trip characteristics – Medians of trip durations
were significantly different between sites (p <0.05,
Table 1, Fig 3, Appendix 4). Most of the pairwise-site comparisons were
significantly different (8/10, p <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<0.001, Table 4). All
pairwise comparisons were significantly different
(p <0.05) except for the EEC vs FoT (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).
Harbour seals’ trip characteristics – Medians of trip duration
were significantly different between study areas
(p <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<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).
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 (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.