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Evidence of low spatial overlap between grey seals and a specific whitefish
fishery off the west coast of Ireland
M.A. Cronin
a,
⇑
, H.D. Gerritsen
b
, D.G. Reid
b
a
Coastal and Marine Research Centre, University College Cork, Naval Base, Haulbowline, Cobh, Co. Cork, Ireland
b
Marine Institute, Rinville, Oranmore, Co. Galway, Ireland
article info
Article history:
Received 26 September 2011
Received in revised form 13 February 2012
Accepted 15 February 2012
Keywords:
Competition
Fastloc GPS
Habitat use
Pinnipeds
Telemetry
VMS
abstract
Competition between seals and man for valuable fish resources is a long-standing contentious issue and
of concern with fish stocks in global decline. Estimating resource overlap between seals and fisheries is
difficult and generally achieved by comparing seal consumption with fisheries catches and stock size;
however spatial partitioning may mean that marine mammals and fisheries are not actually depleting
the same local stocks. With the relatively recent availability of fine scale fishing effort data from Vessel
Monitoring System (VMS) it is now possible to study the spatial overlap between fisheries and predators
in more detail. We used VMS and fast acquisition GPS to compare the distribution of fisheries and seals in
Irish waters on the same spatial and temporal scales to quantify overlap. Our findings suggest a signifi-
cantly low rate of spatial overlap between a sample of female grey seals (Halichoerus grypus) and the off-
shore whitefish fishery on the Irish continental shelf, suggesting direct competition for the resource may
be far less than expected, if the sample is representative. Seal/fisheries interactions in Irish waters could
therefore be more of an issue at the operational and individual level suggesting population control mea-
sures such as culling will be ineffective and therefore unjustifiable. The approach could be applied else-
where to examine spatial overlap of humans and key marine species such as turtles, seals and seabirds,
providing critical data for the development of mitigation measures which will ultimately contribute to
the conservation of these species, many of which are fundamental for healthy ecosystem functioning.
Ó2012 Elsevier Ltd. All rights reserved.
1. Introduction
Seals and humans are both top predators in many marine
ecosystems, often targeting the same food resource. With global
declines in fish stocks (Worm et al., 2009) their interactions are
arousing considerable interest, among scientists, fishers and NGOs.
Cod stocks have declined markedly off the west coast of Scotland
and are now considered to be at an all time low, whilst the esti-
mated consumption by grey seals has increased (Hammond and
Harris, 2006). The concerns of the Irish fishing industry about the
impact of seals on fisheries were highlighted recently at the
European Committee for Fisheries (Cronin et al., 2010). Both seal
species in Ireland, the grey seal and harbour seal (Phoca vitulina
vitulina), are listed as Annex II species under the 1992 European
Union’s Habitats Directive (92/43/EC) and the European Communi-
ties (Natural Habitats) Regulations (1997) which affords strict
protection to both species and habitats within the Irish Exclusive
Fisheries Zone (EFZ). With frequent calls for seal culls made by a
fishing industry (Cronin et al., 2010) struggling with dwindling fish
stocks and decreased quotas (Marine Institute, 2011), the interests
of conservationists, resource managers, industry and policy makers
conflict and the situation urgently needs addressing.
Interactions between seals and fisheries could be operational
and/or biological. Operational interaction would be in terms of
interference e.g. marine mammals taking fish out of nets. Biological
interactions imply competition for resources, either directly or indi-
rectly via the wider food web (Abrams et al., 1996; Northridge and
Hoffman, 1999). Research to date on seal and fisheries interactions
in Ireland has dealt with operational interactions because competi-
tion at the ecosystem level is much more difficult to study and
quantify as the extent of the shared resource overlap must be deter-
mined. Traditionally, resource overlap has been assessed by com-
bining estimates of marine mammal energy requirements with
empirically determined estimates of their diet composition and
the energy content of the prey (e.g. Trites et al., 1997; Boyd,
2002). However quantifying competition by simply comparing
predator consumption and fisheries catches is likely to be mislead-
ing and spatial partitioning may mean that marine mammals and
fisheries are not actually depleting the same local stocks (Matthio-
poulos et al., 2008). With advances in telemetry technologies it is
now possible to track marine predators at sea for extended periods
and relate their distribution to that of the resource (Reid et al., 2004;
0006-3207/$ - see front matter Ó2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.biocon.2012.02.013
⇑
Corresponding author. Tel.: +353 0214703114; fax: +353 021703132.
E-mail addresses: michelle.cronin@ucc.ie (M.A. Cronin), hgerritsen@marine.ie
(H.D. Gerritsen), dreid@marine.ie (D.G. Reid).
Biological Conservation 150 (2012) 136–142
Contents lists available at SciVerse ScienceDirect
Biological Conservation
journal homepage: www.elsevier.com/locate/biocon
Pichegru et al., 2009). Emerging research in this area focuses on
comparing predator and resource overlap. However, it is difficult
to obtain spatially and temporally discrete resource (i.e. fish stock)
distribution data. The main source for fish distribution data is from
stock assessment surveys. These are commonly conducted once a
year, and often target only part of the fish assemblage e.g. in bottom
trawl surveys. Spatially and temporally explicit data is, however,
available for fishing activity from VMS (Vessel Monitoring System).
Using this we have the potential to study the spatial and temporal
overlap between fisheries and predators in detail, and to examine
whether overlap in space and time can be interpreted in terms of re-
source exploitation overlap. Historically this was not possible due
to the low resolution data available for fishing effort (based on ICES
statistical rectangles). Since January 2005, VMS data has been col-
lected for all fishing vessels >15 m in European waters, and this
can provide much higher resolution data. The general application
of VMS to scientific research has been delayed by data security is-
sues, but this has not prevented analytical approaches being devel-
oped (Lees et al., 2010; Gerritsen and Lordan, 2011). VMS data were
recently used for the first time to relate fishing effort to cetacean
distribution in the North Sea (Herr et al., 2009). Recent advances
in telemetry technologies have also provided a means to evaluate
seal at-sea distribution and habitat use more accurately. A long-
standing Achilles heel for marine studies was that, for animals that
surface only briefly (e.g. seals) there was insufficient time to gener-
ate GPS locations (Rutz and Hays, 2009). A novel fast tracking GPS
system allowing rapid acquisition of GPS ephemeris, which can be
relayed remotely via mobile-phone networks, provides opportuni-
ties to track marine animals for extended time periods and to assess
fine scale patterns of space use. These tags provide very similar res-
olution positional data for seals as VMS does for fishing boats. Using
these two sources of information we set out to examine the use of
space by grey seals off the west coast of Ireland, and how that use
related to the spatial pattern of the fishing vessels. The study fo-
cused on seals from a colony of national importance on the south-
west coast of Ireland, being the second largest breeding and moult
colony (Ó Cadhla and Strong, 2007; Ó Cadhla et al., 2007), and the
most significant fishery on the western Irish seaboard in terms of ef-
fort and landings, accounting for 70% of the total Irish fishing effort
off the west coast and 77% of the landings of demersal species. This
fishery targets mixed whitefish (monkfish Lophius piscatorius and
Lophius budegassa, hake Merluccius merluccius, megrim Lepidorhom-
bus whiffiagonis and Lepidorhombus boscii, haddock Melanogrammus
aeglefinus, whiting Merlangius merlangus) and Nephrops on the Irish
continental shelf.
2. Methods
2.1. Seal capture and tag deployment
Capture of grey seals and deployment of Fastloc/GSM tags was
carried out at haul-out sites on the Trá Bán on the Great Blasket Is-
land, in Co. Kerry, southwest Ireland (52°06
0
26N 10°30
0
43W) in
February 2009. Up to 1000 grey seals occur at the capture site on
the Great Blasket Island during the moult period between Decem-
ber and April each year, almost 20% of the national moult popula-
tion estimate (Ó Cadhla and Strong, 2007). The tags were glued to
the animals’ fur and therefore tagging was conducted in late Febru-
ary to coincide with the completion of the female moult and to
maximise the period of tag attachment. Due to sex-related differ-
ences in the timing of the grey seal moult and the significant ef-
forts required to capture seals at an offshore exposed site,
tagging efforts focused on females only.
Seals were captured at the haul-out site using hoop nets. These
consisted of a 1 m diameter hoop made of 20 mm plastic hosing
and a funnel net of 10 mm mesh attached. Researchers approached
the haul-out site by sea using high speed zodiac boats. The direc-
tion and speed of approach was designed to maximise the likeli-
hood of landing researchers ashore before the seals entered the
water. Adult female seals were selected and individuals captured
in hoop nets. The captured seals remained in the hoop nets
throughout the administration of the anaesthetic and prior to the
tagging procedure. Seals were weighed to the nearest 0.1 kg and
anaesthetised using 0.05 ml of Zoletil (ÓVirbac) per 10 kg deliv-
ered intravenously. If intravenous administration of the anaes-
thetic proved difficult (as with a struggling animal) an intra-
muscular dose of 0.1 ml of Zoletil per 10 kg was delivered instead.
Length (from nose to end of tail) and girth (immediately posterior
to the fore-flippers) of the animal were measured to the nearest
cm. The fur was dried with paper towels and degreased using ace-
tone and the tag was secured in place using fast setting epoxy resin
at the base of the skull (Fig. 1). All seal handling and tagging pro-
cedures were conducted under NPWS License No. C35/2008.
Tags incorporate a Fastloc GPS system (Wildtrack Telemetry
Systems, Leeds) which captures GPS pseudo-range data that are
compressed into 30 byte records and post-processed with archived
orbitography data to calculate location. The significant advantage
of this system is that the required data capture requires less than
half a second at the surface enabling frequent and relatively accu-
rate positions being acquired at sea (up to 26 m accuracy, depend-
ing on number of satellites available (Hazel, 2009)). The tags are
programmed to attempt a location fix every 30 min but will only
successfully do so if this coincides with the animal being at the sur-
face. When the seal comes within range of the coastal GSM zone,
after a period of perhaps days, weeks or even months offshore,
the records are sent ashore via a data link call (Cronin and
McConnell, 2008).
2.2. Estimating fishing effort
Since 1 January 2005, all EC fishing vessels exceeding 15 m in
overall length have been required to transmit their position at least
every 2 h (EC, 2003). Data were used from Irish Registered vessels,
fishing with otter bottom trawls (this is the dominant gear type
used in the study area) during the same time period that the
tagged seals were observed (February–December 2009). The fish-
ing effort associated with each VMS ping was defined as the time
interval since the previous record (generally 2 h). Speed criteria
were applied to remove all records where the vessels were inactive
or steaming; only vessels moving at instantaneous speeds between
1.5 and 4.5 kn were considered to be fishing. Gerritsen and Lordan
(2011) estimated that these speed criteria identified vessel activity
Fig. 1. A female grey seal tagged with a Fastloc GPS/GSM tag on the Great Blasket
Island, Co Kerry, Ireland in February 2009.
M.A. Cronin et al. / Biological Conservation 150 (2012) 136–142 137
correctly with an accuracy of 88%. The effort estimates of the VMS
records that were deemed to correspond to fishing were aggre-
gated on a grid of 0.02°latitude by 0.02°longitude which corre-
sponds approximately 3 km
2
.
2.3. Estimating spatial patterns in seal at-sea distribution
Location data for the seals were filtered for at-sea locations de-
fined as starting and ending when the seal crossed a certain thresh-
old based on Euclidean distance from the haul-out site (1 km) and
only when the seal was determined to be not hauled-out (from a
wet/dry sensor in the tag) to avoid inflating the number of trips
as a result of seals using the water in the immediate vicinity of
the haul-out as a result of disturbance or shifting position with
changing tide height. A haul-out event starts when the tag is con-
tinuously dry for 10 min and ends when continuously wet for 40 s.
Effort, defined as number of hours per grid cell, was estimated
according to the Gerritsen and Lordan (2011) method however
any records with time intervals of more than 12 h were removed
to avoid assigning a disproportionate amount of effort to records
that follow a period of missing data. Effort estimates were
aggregated on the same grid as the human fishing effort data. An
aggregate map of effort for seals and fisheries was created as well
as per individual seal. The analysis was carried out in R V 2.8.1 (R
Development Core Team, 2009) and ArcGIS V 9.3. (ESRI, 2011).
Spatial patterns and overlap between seals and fisheries were
compared across the entire study area (area 1) and in five
sub-areas (areas 2–6). The selection of the sub-areas was based
on fishing grounds and/or areas of importance to seals e.g. proxim-
ity to primary haul-out sites (Fig. 2). The extent of study area 1
approximately represents the minimum convex polygon of the
distribution of the entire tagged sample of seals in Irish waters.
Four of the seals travelled to Scotland during the study, however
data in UK waters were not included as the VMS data were avail-
able for Irish waters only. The tagged seals used similar water
depths to where the main fishing effort occurred. Almost 30% of
all the fishing effort off the west coast took place in bottom depths
less than 150 m and tagged seals mainly undertook benthic dives
to depths of 40 m-160 m.
Differences in spatial pattern and overlap were compared using
combined data from the eight seals and also for individuals. The
minimum convex polygon area of each individual was used to de-
fine the boundary of each individual’s study area and the fishery
and seal effort data within this area compared.
2.4. Spatial overlap of seals and fisheries
We used two separate indices to compare seal and fisheries dis-
tribution. An index of difference in spatial pattern (IDSP) was firstly
used, which has been used previously to compare fishing effort dis-
tributions in UK waters (derived from VMS data) between years
and gear types (Lee et al., 2010). The value pdenotes proportion
of either seal (p
s
) or fisheries (p
f
) effort by grid cell. To compare
two maps of effort the absolute differences in proportion of effort
per-grid cell was calculated, summed for the entire grid and di-
vided by 2. This provides an index of difference of spatial pattern
varying from zero, where spatial patterns are identical for a given
grid cell resolution, to one where spatial patterns maximally
different.
IDSP ¼
R
jp
f
p
s
j
2
The Morisita Horn Index of overlap C
MHf
was also used which is
unbiased with respect to sample size and diversity since the
numerator is rescaled by the summed inner products of p
f
and p
s
(Herr et al., 2009). This index has been used to compare harbour
porpoise distribution to fishing effort distribution from VMS data
in the German EEZ (Herr et al., 2009). The proportion of either seal
or human fishing effort by grid cell is denoted by p. Low values of
C
MHf
suggest low overlap.
C
MHf
¼2
R
p
f
p
s
R
p
2
f
þ
R
p
2
s
A randomization test was employed to test the significance of
our C
MHf
estimate. Any appreciable spatial autocorrelation must
be accounted for to draw valid inference about C
MHf
. The resam-
pling was performed on spatial blocks with a size selected to give
spatially independent units (e.g. Fortin and Jacques, 2000). The
appropriate size of block was determined by autocorrelation func-
tions, which gave estimates of the radial distance from a point re-
quired to give correlations not significantly different from zero. A
total of 9999 randomisations were performed on these blocks to
give a reference distribution of C
MHf
under the Null Hypothesis.
Significance levels for C
MHf
were subsequently derived by assessing
where the value fell within this reference distribution.
3. Results
3.1. Tag deployment and operation
Eight female grey seals were captured and tagged on the Great
Blasket Island, Co. Kerry, in February 2009. Weights of captured
seals ranged from 68.2 kg to 121.2 kg. Tags operated for an average
duration of 226 days, with a maximum duration of 325 days and
minimum of 149 days. In total 1813 days of data were collected
from the 8 grey seals with up to 12 location fixes per day per seal.
Fig. 2. Spatial distribution of individual grey seals and Irish registered bottom trawl
vessels >15 m during 2009. Effort is shown in hours per grid cell (approx. 3 km
2
) for
seals (yellow–red) and human fishery (blue) during the tagging period.
138 M.A. Cronin et al. / Biological Conservation 150 (2012) 136–142
Fig. 3. Spatial distribution of 8 grey seals (Figs. a–h) and Irish registered bottom trawl vessels >15 m during 2009. Effort is shown in hours per grid cell (approx. 3 km
2
) for
seals (yellow–red) and human fishery (blue) during the tagging period. Area 1 = Entire study area; 2 = Aran Grounds
; 3 = West of Arans
; 4 = West Galway and Mayo
;
5 = West Donegal
; 6 = West Kerry
.(
Associated with discrete fishing grounds and
Associated with significant grey seal mainland colonies).
M.A. Cronin et al. / Biological Conservation 150 (2012) 136–142 139
3.2. Seal-fisheries spatial overlap
The maps of distribution of seals and fishing effort clearly show
different patterns in spatial distribution. The seals used different
areas than the Irish otter trawl fishery used in 2009 (Fig. 3a–i)
and in some cases e.g. seal 10957 (Fig. 3a) appear to skirt around
the fishing grounds. All areas (Fig. 2) show a significantly smaller
overlap between seals and fisheries than overlap expected with a
random distribution of seal at-sea locations (p< 0.05 to
p< 0.001). The Morisita–Horn Index (MHI) of overlap was low
(0.001–0.062). The Index of Difference in Spatial Pattern (IDSP)
suggests that space use of seals and fisheries were almost maxi-
mally different with values close to 1.0 (Table 1).
All of the seals other than seal 11108 had significantly smaller
overlap with fisheries than one would expect from a randomly dis-
tributed effort, suggesting an avoidance of areas with high fishing
effort (p< 0.05–p< 0.001) (Table 1). And even though p> 0.05 for
seal 11108, its MHI value is low (0.033) and IDSP value is high
(0.913) suggesting low overlap.
4. Discussion
Tracking technologies such as VMS and fast acquisition GPS pro-
vided fine scale data on the distribution of fisheries and seals in Ir-
ish waters on the same spatial and temporal scale and enabled us to
quantify the scale of overlap. This is the first study to utilise data
from VMS and fast acquisition GPS simultaneously to study top
predator and fishery overlap. Our findings suggested a significantly
low rate of spatial overlap between a tagged sample of grey seals
and the offshore Irish fishery targeting mixed whitefish and Nephr-
ops on the Irish continental shelf. If this sample is representative of
the population of seals using Irish waters, it suggests that direct
competition for the resource, at least in the offshore fishery off
the west coast of Ireland, may be far less than expected. However,
lack of overlap between seals and the commercial fishery does
not exclude the possibility that they are targeting the same stock
which might migrate between the areas. Data on fish mobility in
this area is scarce, however many commercial species are known
to migrate on both small and large scales e.g. in the case of demersal
fish in the North Sea (Righton and Mills, 2008; West et al., 2009).
In general, studies of grey seal diet on both sides of the North
Atlantic suggest that most of the commercial species consumed
are pre-recruits to the commercial fishery (Benoit and Bowen,
1990; Hammond et al., 1994). In Ireland research suggest that with
the exception of whiting (M. merlangus), commercial gadoid spe-
cies are relatively uncommon in the diet of grey seals (BIM,
1997; Kiely et al., 2000) however, these studies are out-dated, suf-
fer from widely accepted limitations of traditional diet analyses
techniques (DaSilva and Neilson, 1985; Harvey and Antonelis,
1994; Yonezaki et al., 2003) and with limited spatial coverage to
make inferences at the population level. Furthermore they have
been strongly criticised by the fishing industry as misrepresenta-
tive (Cronin et al., 2010). Consumption of commercially exploited
fish species by grey seals is apparently increasing on the west coast
of Scotland (Hammond and Harris, 2006) and estimates of annual
consumption of cod by seals in ICES division VIa have raised con-
cern (Pope and Holmes, 2008). Currently there are no estimates
of fish consumption by seals in Irish waters due to the lack of data.
A range-wide description of seal diet is necessary for such an esti-
mate, taking into account geographic region, sampling condition,
age group and year (Lundstrom et al., 2010). In the absence of ro-
bust data on grey seal diet in Ireland, studies such as this on pred-
ator and fisheries overlap can prove useful as an indicator of
potential resource competition.
The fisheries effort data were limited to Irish vessels using
demersal trawls. However these vessels represent the vast majority
of effort in the study area and fishing effort of other nations in Irish
waters is generally concentrated further offshore Anon (2009). In all
areas except area 3, Irish vessels represent more than 90% of the
international effort. Bottom otter trawlers account for the majority
of fishing effort to the west of Ireland, representing 77% of the land-
ings of demersal species in the study area in 2009 (Marine Institute,
unpublished analysis of VMS data). Although there was large vari-
ation between individual seals’ ranges all but one seal showed sig-
nificantly low use of the areas corresponding with high fishing
effort. This seal (11108) spent some time, repeatedly diving to the
bottom indicating foraging behaviour, along the edge of a heavily
fished area approximately 100 km west of Blasket Islands. The anal-
ysis was conducted on approximately a 3 km
2
grid cell size which
may obscure this seal/fisheries boundary. It is possible that this is
an area where both seals and vessels were foraging closely in space
but may not actually overlap (as the MHI value suggests). Finer
scale analysis may result in an even lower overlap index.
Why the seals should tend to forage in different locations to
where the fishery is concentrated is not clear. It may be a result
of seals preferentially foraging on species that are not targeted
by the fishery e.g. sandeels, however, there are insufficient fishery
independent data to investigate this. Due to behavioural and phys-
iological constraints of seals the distribution of their foraging effort
is likely to be determined by accessibility from terrestrial sites as
well as habitat preference, whereas the distribution of fishing ef-
fort is, at least in part, constrained by bottom type (e.g. rocky
ground is unsuitable for trawling) and availability of the target
species. Additionally, the distance to harbour and fish markets
may affect accessibility and profitability of certain fishing grounds
(Matthiopoulos et al., 2008). The choice of foraging location for
both seals and vessels is most likely based on accessibility and
availability. It is possible that the seals may favour areas of high re-
lief, which might be unsuitable for bottom trawling. Such areas
may act as refugia and contain more or more diverse fish prey
(Jaworski et al., 2006; Wilhelmsson et al., 2006; Hunter and Sayer,
2009). Accessibility of seals to fishing habitat is not considered to
be a limiting factor as the data suggest seals foraged in similar
water depths to where the main fishing effort occurred. Almost
30% of all the fishing effort off the west coast took place in bottom
depths less than 150 m and tagged seals mainly undertook benthic
dives to depths of 40–160 m. Dietary and telemetry evidence from
other studies suggest grey seals are benthic foragers (Thompson
Table 1
Spatial overlap statistics for seals and fisheries on the western seaboard of Ireland.
All seals (IDSP) (MHI) pValue
Area
1 0.921 0.008 p< 0.001
2 0.945 0.004 p< 0.001
3 0.891 0.062 p< 0.001
4 0.983 0.001 p= 0.002
5 0.929 0.027 p< 0.001
6 0.827 0.019 p= 0.014
Individual seals
10957 0.963 0.014 p< 0.001
11015 0.973 0.0038 p= 0.002
11093 0.954 0.0043 p= 0.048
11095 0.977 0.002 p< 0.001
11108 0.913 0.033 p= 0.436
11113 0.982 0.003 p< 0.001
11100 0.947 0.007 p= 0.009
11101 0.991 0.0014 p< 0.001
The index of difference of spatial pattern (IDSP) varies from zero to one where
spatial patterns are identical to one where spatial patterns maximally different. The
Morisita Horn Index of overlap (MHI) C
MHf
also varies from zero to one but in this
case low levels suggest low overlap. Significance levels for C
MHf
are provided for
Cdata compared to Crandom.
140 M.A. Cronin et al. / Biological Conservation 150 (2012) 136–142
et al., 1991; Thompson and Fedak, 1993; Bowen and Harrison,
1994; Hammond et al., 1994).
It is also possible that the seals were actively avoiding fishing
vessels, rather than expressing a different habitat preferences to
the fishers. We suspect this is unlikely as fishermen have reported
seals following boats (Irish South West Fish Producers Organisa-
tion pers comm.). It is possible that seals respond to the presence
of boats at sea in the short term while en route to their foraging
grounds to potentially avail of discards. This may lead fishermen
into thinking that there is more resource competition with the
seals than the present study would suggest.
The data presented here only examined the overlap between
the offshore mixed whitefish fishery and only one of Irelands’
two species of seal. Feedback from the Irish fishing industry sug-
gests that seal/fishery operational interactions are a serious prob-
lem in the inshore (within 12 nm) static net fishery (e.g. gill and
tangle nets) (Cronin et al., 2010). Biological interactions may also
occur between seals and fisheries in inshore waters. Harbour seals
were shown to have a limited foraging range relative to the grey
seals in Ireland, with a more inshore distribution, mostly staying
within 20 km of their haul-out site (Cronin et al., 2008). With their
concentrated coastal distribution they could potentially have sig-
nificant impacts on the local inshore fisheries (which include ang-
lerfish, turbot, cod, pollack and hake) in terms of biomass removal,
besides damage to the catch in the nets. Estimated daily food
requirements of the harbour seal population in southwest Ireland
is approximately 6 tonnes, assuming a heterogenous population
by age and sex, and a diet comprised principally of gadoids (Cronin
et al., 2008). We have data on harbour seal foraging distribution in
southwest Ireland resulting from recent tagging efforts and it
would be interesting to conduct the overlap analysis on these data,
however in the absence of spatially explicit information on fisher-
ies effort in inshore waters (most of the inshore vessels are under
15 m and therefore not obliged to carry VMS), this is currently not
possible to ascertain.
The approach we used here provided us with an estimate of the
seals use of space and enabled the quantification of spatial overlap
of fisheries and seals. An analysis of the seals’ dive and movement
behaviour would be useful for inferring foraging activity and data
could be filtered similarly to filtering the VMS data to identify fish-
ing effort for both seals and humans. This would be useful for sit-
uations where spatial overlap was moderate to high, to identify
and eliminate time spent at sea travelling and searching for food.
Considering that there are gender related differences in grey
seal foraging behaviour (Breed et al., 2009) caution is advised in
inferring population level foraging behaviour from the relatively
small sample of females in this study. As Weise et al. (2010) note
the occurrence of foraging specializations within a species and
age class has implications for quantitative modelling of popula-
tion-level predator–prey interactions and ecosystem structure. A
larger sample size balanced by gender and size, including seals
from other haul-out sites on the Irish coastline, should help prove
if the patterns shown by the eight tagged seals in this study truly
represents the population at large, as variation resulting not only
from gender and size but also location of breeding sites can affect
an animal’s foraging range (Robson et al., 2004). Furthermore, pat-
terns of habitat use may change over time; little is known about
seals’ fidelity to feeding grounds over extended periods of time
due to moult associated tag loss and difficulties recapturing indi-
viduals for successive deployments. Therefore the telemetry data
from the 8 seals may not represent the full spatial extent of the
seals range. Notwithstanding the small sample size, the same pat-
tern of low spatial overlap between seals and fisheries on the wes-
tern seaboard was evident in each one of the individuals studied
and warrants further investigation, as if this sample is truly repre-
sentative of the population of grey seals using Irish waters, it
suggests competition for the resource may be far less than ex-
pected and population control measures such as culling
unjustifiable.
Studies on the overlap of top marine predators and fisheries
have increased our understanding of resource competition and
by-catch (e.g. Reid et al., 2004; Goldsworthy and Page, 2007; Ha-
mel et al., 2008; Suryan et al., 2007). Measurement of the spatial
overlap between predators and their prey in marine systems is
highly dependent upon the measurement scale used (Reid et al.,
2004). With the availability of VMS and fastloc GPS data it is
now possible to examine overlap between predator and fishery
on finer spatial and temporal scales than was possible to date.
There are many studies now underway across the globe on marine
animal habitat use using fast acquisition GPS (Schofield et al.,
2007; Hazel, 2009) and fine scale information on predator distribu-
tion and space use will soon be available. But the approach we used
can be applied elsewhere when VMS data is made available to the
scientific community (although access to such data often remains
problematic because of legal and confidentiality constraints) to
examine spatial overlap of humans and key marine species such
as turtles, seals and seabirds. This will provide critical data for
the development of mitigation measures (e.g. for by-catch, over-
fishing) which will ultimately contribute to the conservation of
these species, many of which are fundamental for healthy ecosys-
tem functioning (Estes et al., 1998, 2009; Frank et al., 2005; Heit-
haus et al., 2008).
Acknowledgements
We would like to acknowledge the following for their valuable
contributions to the fieldwork elements of the project: David
Thompson (National Trust), Paddy Pomeroy, William Patterson
(SMRU), Clare Heardman, Declan O Donnell, Oliver O Cadhla, Frank
McMahon, Tim O Donoghue and Pascal Dower (NPWS). Thanks to
Diego delVillar for assistance with mapping and Tom Doyle and
Mark Jessopp (CMRC) for reviewing drafts. Thanks also to Carl
Donovan (CREEM) and Michael Cronin (UCC) for statistical advice.
The research was funded by a Beaufort Marine Research Award
carried out under the Sea Change Strategy and the Strategy for
Science Technology and Innovation, with the support of the Marine
Institute, funded under the Marine Research Sub-Programme of the
National Development Plan 2007–2013. Funding for the telemetry
devices was provided by the National Parks & Wildlife Service.
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