Journal of Animal Ecology

2009,

78

, 880–889 doi: 10.1111/j.1365-2656.2009.01549.x

© 2009 The Authors. Journal compilation © 2009 British Ecological Society

Blackwell Publishing Ltd

Fine-scale foraging behaviour of a medium-ranging

marine predator

K. C. Hamer

1

*, E. M. Humphreys

1,2

, M. C. Magalhães

1,3

, S. Garthe

4

, J. Hennicke

5

, G. Peters

6

,

D. Grémillet

7

, H. Skov

8

and S. Wanless

9

1

Institute of Integrative & Comparative Biology, University of Leeds, Leeds LS2 9JT, UK;

2

British Trust for Ornithology Scotland, School of Biological and Environmental Sciences, Stirling University, Stirling FK9 4LA, UK;

3

Department of Oceanography and Fisheries, University of the Azores, 9901-862 Horta, Faial, Portugal;

4

Centre for Research and Technology Westkuste, University of Kiel, 25761 Busum, Germany;

5

Institute of Zoology, University of Hamburg, 20146 Hamburg, Germany;

6

Earth & Ocean Technologies, Krummbogen 32, 24113 Kiel, Germany;

7

Centre d’Ecologie Fonctionnelle et Evolutive Equipe Ecologie Spatiale des Populations, CNRS, 34293 Montpellier, France;

8

DHI Water and Environment, Agern Alle 5, DK-2970 Hørsholm, Denmark;

9

NERC Centre for Ecology and Hydrology, Bush Estate,

Penicuik, Midlothian EH26 0QB, UK

Summary

1.

Movement patterns of predators should allow them to detect and respond to prey patches at differentspatial scales, particularly through the adoption of area-restricted search (ARS) behaviour. Here weuse fine-scale movement and activity data combined with first-passage time (FPT) analysis to examinethe foraging strategy of northern gannets

Morus bassanus

in the western North Sea, and to test thefollowing hypotheses: (i) birds adopt a hierarchical foraging strategy characterized by nested ARSbehaviour; (ii) the locations and characteristics of ARS zones are strongly influenced by physicaloceanography; (iii) the initiation of ARS behaviour is triggered by the detection and pursuit of prey; (iv)ARS behaviour is strongly linked to increased foraging effort, particularly within nested ARS areas.

2.

Birds on 13 of 15 foraging trips adopted ARS behaviour at a scale of 9·1 ± 1·9 km, and birds on10 of these 13 trips adopted a second, nested ARS scale of 1·5 ± 0·8 km, supporting hypothesis 1above. ARS zones were located 117 ± 55 km from the colony and over half were within 5 km of atidal mixing front ~50 km offshore, supporting hypothesis 2 above.

3.

The initiation of ARS behaviour was usually followed after only a short time interval (typically~5 min) by the commencement of diving. Gannets do not dive until after they have located prey, andso this pattern strongly suggests that ARS behaviour was triggered by prey detection, supportinghypothesis 3 above. However, ~33% of dives in mixed coastal water and 16% of dives in stratifiedwater were not associated with any detectable ARS behaviour. Hence, while ARS behaviourresulted from the detection and pursuit of prey, encounters with prey species did not inevitablyinduce ARS behaviour.

4.

Following the initiation of ARS behaviour, dive rates were almost four times higher within ARSzones than elsewhere and almost three times higher in zones with nested ARS behaviour than inthose without, supporting hypothesis 4 above and suggesting that the foraging success of birds waslinked to their ability to match the hierarchical distribution of prey.

Key-words:

biological oceanography, optimal foraging, scale dependence, seabirds, wildlifetelemetry.

Introduction

Foraging behaviour is an important part of the daily routinesof many species and forms an essential link between preyavailability and predator reproductive success. A central issue

in this context is the variability in foraging behaviour acrossheterogenous landscapes used by predators (Nams 2005;Bailey & Thompson 2006). Prey often occur in patches andthese are typically nested within larger-scale patches, formingnested patch hierarchies within the landscape (Wu & Loucks1995; Fauchald & Erikstad 2002). Movement patterns ofpredators should therefore allow them to detect and respond

*Correspondence author. E-mail: k.c.hamer@leeds.ac.uk

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,

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, 880–889

to prey patches at different spatial scales (Fauchald 1999;Fritz, Saïd & Weimerskirch 2003). To understand the foragingbehaviour of predators, it is thus crucial to determine theirscales of interaction with the environment, particularly innested scale systems where large-scale patterns tend to maskpatterns at finer scales (Fauchald, Erikstad & Skarsfjord 2000).

In models of foraging behaviour in heterogenous landscapes,it is generally assumed that predators adjust their movementpattern in response to prey density by reducing their speed oftravel or increasing turn rate once prey have been encounteredor in response to environmental cues, adopting a so-calledarea-restricted search (ARS) behaviour (Kareiva & Odell 1987;Farnsworth & Beecham 1999). In a hierarchically structuredsystem, predators should also display scale-dependent ARSpatterns that match the spatial structure of their environment(Fauchald 1999). There is strong evidence of ARS behaviourin a wide range of species (Frair

et al

. 2005; Johnston, Westgate& Read. 2005), but fewer studies have examined nested ARSbehaviour at different spatial scales (Pinaud & Weimerskich2005; Fauchald & Tveraa 2006). Moreover, empirical evidencethat ARS behaviour results from individuals detecting preyis derived mainly from studies of insects foraging oversmall-scale habitats (Wiens, Schooley & Weeks 1997). Theconditions that lead longer-ranging predators to initiateARS behaviour have received little attention, especially forvertebrates, and one recent study of a long-ranging predatorfound little association between ARS behaviour and preyencounter (Weimerskirch

et al.

2007).Marine prey resources occur at a wide range of spatial and

temporal scales of distribution and abundance, reflecting scale-dependent interactions between ocean currents, bathymetryand other physical and biological processes that promotethe growth and retention of plankton, leading to zones ofenhanced productivity (Hunt & Schneider 1987; Sims &Quayle 1998). Several recent studies have found relationshipsbetween large-scale movements of marine predators andmajor oceanographic features such as continental shelf slopesand major frontal zones (Hyrenbach, Fernández & Anderson2002; Pinaud & Weimerskich 2007), while some studies havealso revealed nested search behaviour over scales of 10s to100s kms in long-ranging pelagic predators with foragingranges of 1000s kms (Pinaud & Weimerskich 2005; Fauchald& Tveraa 2006). Few studies, however, have examined fine-scalemovements of species with narrower foraging ranges that donot include such large-scale oceanographic features. At thissmaller scale, aggregation of predators is found in predictableregions of enhanced productivity such as bathymetric gradients,fronts and tidal eddies (Hunt

et al.

1998; Hamer

et al.

2000)but evidence of nested search behaviour is very limited.Becker & Beissinger (2003) recorded scale-dependent habitatselection in a near-shore predator, the marbled murrelet

Brachyramphus marmoratus

(Gmelin), but their study wasbased on marine survey data and so they were not able toexamine search strategies of individual birds. Moreover, therelationship between prey encounter and search behaviourhas not previously been examined for any marine predatorswith this scale of foraging range.

Northern gannets

Morus bassanus

(Linn) (hereafter gannets)are medium-ranging foragers, capable of travelling > 1000 kmon a single round-trip to obtain food for themselves and theiroffspring (Garthe

et al.

2007; Hamer

et al.

2007), althoughtypical ranges of trips (< 200 km) are much shorter thanthose of long-distance pelagic foragers (Weimerskirch &Cherel 1998; Magalhães, Santos & Hamer 2008). Adultsexploit a wide range of species and sizes of prey, obtainedusing several distinct capture techniques (vertical plunge-diving,underwater pursuit, scooping from the surface and scavengingdiscards from fishing vessels; Garthe, Benvenuti & Montevecchi2000; Hamer

et al.

2000; Lewis

et al.

2003). Birds at one of thelargest colonies of gannets (~48 000 breeding pairs; Wanless,Murray & Harris 2005), at Bass Rock, south-east Scotland(56

°

6

′

N, 2

°

36

′

W), were recorded to forage repeatedly over anarrow range of bearings before switching to a separate rangeof bearings in a markedly different direction from the colony,providing strong evidence that individuals learned andremembered the directions to feeding sites and used thatknowledge on subsequent foraging trips (Hamer

et al.

2001,2007). However, it was not known whether or not adults alsoadopted ARS behaviour at sea or if so, how this related tooceanography or to what extent it was associated with detectionof prey.

The North Sea is a semi-enclosed shelf sea where theinteraction between bathymetry, tidal currents, solar irradia-tion and wind patterns creates a mosaic of mixed, stratifiedand frontal regions (Scott

et al

. 2006). The main frontal zonein the region of the Bass Rock is a tidal mixing front locatedabout 50 km offshore, at a distance between the shelf breakand the coast where the water is shallow enough for tidalmixing to reach the surface (Fig. 1; Skov

et al

. 2008). Inshoreof the front, the water is mainly mixed while beyond the front,the water is stratified during the summer (Daunt

et al

. 2006).Primary and secondary production are typically concentrated atfrontal regions (Sims & Quayle 1998) and there is evidencethat this front may be a focus for the foraging activity ofmarine predators in the region, including gannets (Daunt

et al

. 2006; Skov

et al

. 2008). Marine survey data indicatedthat gannets captured prey at shallower depths inshore ofthe tidal mixing front than offshore (Camphuysen, Scott &Wanless 2006), but it was not known how this differencerelated to the movement patterns or overall foraging strategiesof birds.

This paper uses fine-scale movement and activity datafrom global positioning system (GPS) loggers combined withrecently developed first-passage time (FPT) analysis (Fauchald& Tveraa 2003) to examine the spatial scales of foraging andnested search strategy of gannets in relation to the physicaloceanography of the western North Sea. FPT is based onthe time taken by a foraging animal to cross a circle of givenradius, providing a scale-dependent index of search effort andallowing identification of the spatial scales at which effortis concentrated by increases in sinuosity and/or decreases inspeed of movement. Detection and pursuit of prey by gannetsis indicated by the initiation of diving behaviour (Garthe

et al

.2000; Lewis

et al

. 2002) and here, we test the following

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,

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, 880–889

hypotheses: (i) birds adopt a hierarchical foraging strategycharacterized by nested ARS behaviour; (ii) the locations andcharacteristics of ARS zones are strongly influenced byphysical oceanography; (iii) the initiation of ARS behaviouris triggered by the detection and pursuit of prey; (iv) ARSbehaviour is strongly linked to higher foraging effort, partic-ularly within nested ARS areas.

Materials and methods

Field work on the Bass Rock took place between mid-July andmid-August 2003. One chick-rearing adult from each of 13 nestswith hatching dates ±2 weeks from the annual mode was captured atthe nest using a 6-m telescopic pole with a brass noose. A GPSlogger with an external temperature and depth probe (Earth &Ocean Technologies, Kiel, Germany) weighing 70 g (< 3% of adultmass) was attached to the feathers on the back of each bird usingwaterproof tape (Tesa AG, Hamburg, Germany), such that thewings of the bird protected the device during plunge diving. Thetemperature and depth sensor was located at the end of an externalwire, secured with an L-shaped piece of thermoplastic and waterprooftape so that it hung beneath the tail feathers. Attachment of tagstook ~15 min and after release, birds returned to the nest almostimmediately. After release, birds were tracked for 1–4 days each overa period of 1 month during mid chick rearing, after which time thebird was recaptured and the tag removed. Loggers had no discernibleimpacts on trip durations or body masses of birds in comparison tountagged controls (Hamer

et al

. 2007).

GPS loggers provided location data at intervals of 3 min (accuracywithin 20 m for 90% of all fixes) while the external probe measuredtemperature (resolution 0·01

°

C) and pressure (resolution within 0·1 m)every 2 s. Locations of birds at sea were examined in

arc-view gis

. Weused the furthest recorded location from the colony to separate outwardand return portions of each trip, and we calculated total distancetravelled as the sum of distances between consecutive locations at sea.To identify zones of ARS, we used the adehabitat and ade4 packagesin software

r

2·7·0 (R Development Core Team 2007) to apply FPTanalysis, following Fauchald & Tveraa (2003). To ensure that pointsalong foraging tracks were equally represented (Pinaud 2008), weinterpolated locations to obtain a uniform distance interval of 1 km.FPT was then calculated for every 1 km for a radius

r

from 1 to 100 km.A plot of log (FPT) against

r

(using log-transformation to ensurethat the variance was independent of the magnitude of the mean;Fauchald & Tveraa 2003) allowed identification of the ARS scales ofeach foraging trip by peaks in the variance. Inclusion of overnightperiods when birds remain sitting on the water (Hamer

et al

. 2000;Lewis

et al.

2002) could have dramatically inflated the variance inFPT at small spatial scales (Weimerskirch

et al

. 2007), and so thisanalysis was restricted to hours of daylight (4·00–23·00 BST) duringforaging trips. By plotting FPT values at appropriate ARS scales asa function of time elapsed since leaving the colony, we identifiedwhere and when birds entered and left ARS zones. We then estimatedthe area of each ARS zone by using the maximum distance betweenany two points within each zone as a measure of diameter. Next, werepeated the FPT analysis at a finer spatial scale (every 100 m fora radius from 100 m to 10 km) to search for nested ARS behaviourwithin each larger-scale ARS zone.

Fig. 1. National Oceanic and AtmosphericAdministration (NOAA) Advanced VeryHigh Resolution Radiometer (AVHHR)sea-surface temperature (SST) image for 13July 2003 showing typical positions of mainwater masses and surface frontal features inthe western North Sea. Reproduced fromSkov et al. (2008), with permission.

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, 880–889

The timing, duration and maximum depth attained during diveswere analysed using

mt-dive

4·0 (Jensen Software, Loehe, Germany).Apparent dives < 0·3 m were excluded because many of these wereprobably nonforaging movements associated with bathing (Garthe

et al

. 2000). Durations and depths of dives were highly correlated(

r

S

= 0·8,

n

= 420,

P

< 0·01) and so only depths are presented here. Otheractivities at sea were identified from a combination of location andtemperature data: time on the sea surface was indicated by more-or-lessconstant temperature and was confirmed, for periods exceeding 3 min,by checking that the bird had not moved from its previous location.Flight was indicated by rapid changes in location, accompanied by largefluctuations in temperature. These data were used to locate dives atsea and to calculate the proportion of time spent in different activities.

We recorded many dives and, in some cases, several ARS zonesper trip. To examine individual variation in foraging behaviour andto take account of potential pseudoreplication of data, we thereforeused generalized linear models (GLM) with trip identity included asa random effect. We also initially included sexes of birds but therewas no difference between sexes in ARS behaviour or dive rate(

P

> 0·3 in all cases) and so this variable was dropped from all models.We used the position of the tidal mixing front during July 2008(Fig. 1) to indicate the boundary between mixed coastal water andseasonally stratified water (see Skov

et al

. 2008 for method ofestimating position of front). Data were tested for normality and,where necessary, log-transformed before statistical tests. Meanvalues are given ±1 SD unless otherwise stated.

Results

The mean duration of foraging trips was 21·5 ± 6·7 h (range= 11·1–34·9 h,

n

= 15 trips from 13 birds), with a meandistance covered per trip of 439·8 ± 234·4 km (range = 159–984 km) and a mean foraging range of 155·2 ± 65·3 km (range =

68–276 km; Fig. 2). On average, birds spent 41·6 ± 11·7%(range = 22·0–60·4 %,

n

= 14) of each foraging trip in flight,with an average flight speed of 44·7 ± 7·2 km h

–1

(range =33·4–60·2 km h

–1

,

n

= 14; one logger did not record activity data).Trips encompassed both mixed coastal water and seasonallystratified water east of the tidal mixing front: nine trips wererestricted largely to coastal or frontal water and six tripsextended well over stratified water beyond the front (Fig. 2).Most trips had more or less direct flight paths, leaving andreturning to the colony along similar routes, but two trips hadmore elliptical paths (Fig. 2).

AREA

-

RESTRICTED

SEARCH

BEHAVIOUR

ARS zones detected by the FPT method were found on all buttwo foraging trips, both extending over seasonally stratifiedwater, which had very low dive rates (see below) suggestinglittle success in locating prey. For these two birds, the variancein log FPT decreased linearly with increasing spatial scale,suggesting random foraging with no distinct ARS behaviour(Fauchald & Tveraa 2006). All other trips had a clear peakin the variance of log FPT, indicating the scale of ARSbehaviour, at radii of 4·1–57·4 km (back-transformed meanlog radius = 9·1 ± 1·9 km; logs used to normalize data).There was a significant positive relationship between ARSscale and maximum foraging range (GLM using log radius;

F

1,10

= 14·2,

n

= 13 trips,

P

< 0·01). However, there was nodifference in the scale of ARS of trips that extended overstratified water and those that did not (

F

1,10

= 1·1,

P

= 0·3).We identified up to four ARS zones per trip (mean = 1·9 ±

0·9). A further six apparent zones that closely matched hours

Fig. 2. Foraging tracks of northern gannetsfrom the Bass Rock in 2003.

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, 880–889

of darkness and contained no dives (see below) were excludedfrom the data. Birds spent time overnight in 46% of 25 recog-nized ARS zones but all such occasions also included at least2 h of daylight and began (and sometimes also ended) with asequence of dives, and so were not the result of birds restingon the water overnight. ARS zones were typically characterizedby increased sinuosity of foraging tracks in addition to longpassage times (Fig. 3) and were all on the outward phases oftrips before reaching the maximum foraging range (Fig. 3), ata mean distance of 117·0 ± 55·0 km from the colony (range =35–275 km). ARS zones occurred over both mixed coastalwater and stratified water, with over half (58%) within 5 km ofthe tidal mixing front (Fig. 4). The estimated areas of ARSzones (22·6 ± 14·1 km

2

) differed consistently among individuals(GLM;

F

12,11

= 3·4,

P

< 0·05) but did not differ between mixedcoastal water (including the region of the tidal mixing front)

and stratified water beyond the front, and were not related todistance from the colony (

P

= 0·9 in both cases).

NESTED

ARS

BEHAVIOUR

Nested fine-scale ARS behaviour was detected within 15 of 25ARS zones (60%) during 10 of 13 trips, with a mean radiusof 1·5 ± 0·8 km (range = 0·5–3 km). There was no differencebetween mixed coastal and stratified water or among birdsin the proportion of ARS zones showing nested searchbehaviour (

P

> 0·5 in each case; four apparent nested ARSzones completely occupying hours of darkness were excludedfrom these data). Where such behaviour was present, therewere up to four nested search areas within each ARS zone(mean = 1·8 ± 0·9) and birds spent 49 ± 45 min (range 12–180 min) in each nested ARS search area.

Fig. 3. Detailed view of two typicalforaging tracks showing positions of area-restricted search zones (light grey circles)plus locations of deep dives (≥ 2 m; solidcircles) and shallow dives (< 2 m; dark greycircles) along tracks (up to 10 dives perlocation). Arrows indicate direction oftravel. Square indicates Bass Rock. Notedifference in foraging ranges of trips andone ARS zone without dives.

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, 880–889

ARS

AND

D IV ING

BEHAVIOUR

The first dive of each trip was 53·9 ± 45·7 km from the colony(range = 3·6–148·0 km,

n

= 420) and 67·0% of dives were onthe outward phase of the trip before reaching the maximumforaging range. Birds did not dive overnight. The two birdswith no detectable ARS behaviour (see above) had very lowdive rates compared to birds that had ARS (0·4 ± 0·3 dives h

–1

and 1·7 ± 1·5 dives h

–1

, respectively;

t

-test using unequal varianceestimate;

t

8·5

= 2·5,

P

< 0·05).All but two large-scale ARS zones (92%) included dives

and the mean interval between entering ARS and commencingdiving was 7·0 ± 7·6 min. However, 27·1 ± 24·3% of dives pertrip were not in ARS zones (Fig. 5), and the mean intervalbetween the final dive outside an ARS zone and the subsequentinitiation of ARS behaviour was 56·9 ± 4·8 min. The proportionof dives within ARS zones was 17% higher in stratified waterbeyond the tidal mixing front than in mixed coastal water(Fig. 5; GLM using arcsine-square root transformed propor-tions for each trip;

F

1,6

= 15·7,

P

< 0·01) and also differedsignificantly among trips (

F

11,6

= 5·1,

P

< 0·05). However,intervals between initiation of ARS behaviour and divingevents did not differ among trips or between water bodies,whether considering dives before or after birds entered ARS(

P

≥

0·5 in all cases).Following the initiation of ARS behaviour, the mean dive

rate during hours of daylight within ARS zones (3·8 ± 4·6dives h

–1

) was almost four times that outside ARS zones(1·0 ± 0·9 dives h–1; Fig. 6; GLM; F1,20 = 13·2, P < 0·01). More-over, 82·7 ± 27·9% of dives within large-scale ARS zones werein nested small-scale ARS areas, and daytime dive rates werealmost three times higher in zones with such nested ARSbehaviour than in those without (Fig. 6; F1,10 = 8·4, P = 0·01).Dive rate also varied consistently among birds (F11,10 = 5·2,P < 0·01) but did not differ between ARS zones in mixedcoastal water and in stratified water beyond the tidal mixingfront (F1,10 = 0·03, P = 0·9).

CHARACTERISTICS OF DIVES

Birds dived up to 19 m below the sea surface but 58% of diveswere to depths < 2 m. The frequency distribution of divedepths was bimodal with two peaks in depth usage at 0·3–1 mand 6–7 m, indicating a clear separation between shallowdives (< 2 m) and deep dives (≥ 2 m). Overall, birds used deepand shallow dives with similar frequencies (mean proportionof shallow dives per trip = 55·2 ± 25·0%, n = 14 trips), butthere was marked variation between individuals in thisrespect (range = 14–94%), which was related to where birdsforaged but not to ARS behaviour: the mean proportion of

Fig. 4. Positions of area-restricted searchzones (open circles; size of circle indicatesscale of ARS) plus locations of deep dives(≥ 2 m; solid circles) and shallow dives(< 2 m; grey circles) of northern gannetsfrom the Bass Rock (up to 10 dives perlocation). Squares indicates position ofcolony. Dashed line shows approximateposition of tidal mixing front.

Fig. 5. Proportions of dives by northern gannets within ARS zones(solid bars) and not associated with ARS behaviour (grey bars), inmixed coastal water (inshore) and in seasonally stratified waterbeyond the tidal mixing front (offshore). Based on 420 dives from12 foraging trips; data from two birds that did not show any ARSbehaviour not included.

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shallow dives per trip was nine times higher in mixed coastalwater (81·6 ± 26·5%) than in stratified water beyond thetidal mixing front (9·0 ± 8·7%; Fig. 4; GLM; F1,22 = 24·7,P < 0·001) but was no different within and outside ARS zones(F1,22 = 0·07, P = 0·8).

Shallow dives were significantly shallower within ARSzones than elsewhere (mean = 0·67 ± 0·39 m, n = 167 and0·78 ± 0·37 m, n = 66, respectively; GLM; F1,216 = 5·1,

P < 0·05) but did not differ between water bodies or times ofday (P = 0·1 in both cases). Deep dives were significantlydeeper in stratified water (5·2 ± 2·7 m, n = 140) than in mixedcoastal water (4·3 ± 1·7 m, n = 47; F1,172 = 7·2, P < 0·01) butdid not differ with respect to ARS behaviour (F1,172 = 0·3,P = 0·6). Deep dives were also deeper during the main part ofthe day (7:00–19:00 h BST; mean = 5·5 ± 2·9 m, n = 114)than in the early morning and evening (3:00–7:00 h and19:00–23:00 h; mean = 4·2 ± 1·2 m, n = 73; F1,172 = 7·7, P <0·01). Depths of both shallow and deep dives also differedsignificantly among trips (F13,216 = 6·6, P < 0·001 and F10,172 =8·4, P < 0·001, respectively).

Discussion

This study provides strong evidence that gannets used anested search strategy to locate prey, in support of hypothesis1 above. Birds typically concentrated their search effort at aspatial scale of about 10 km and within these large-scalesearch areas, they often searched more intensively at a scale ofabout 1 km. This hierarchical search strategy was similar tothat seen over much larger spatial scales (100 s to 10 s km) inlong-ranging petrels and albatrosses (Pinaud & Weimerskich2005; Fauchald & Tveraa 2006). In gannets, the largest scaleof ARS behaviour during foraging trips was positively relatedto the maximum range of each trip, indicating that birdssearched for prey over larger spatial scales during trips thatextended further from the colony, as also found in yellow-nosedalbatrosses Thallasarche carteri (Rothschild) (Pinaud &Weimerskich 2005) and Antarctic petrels Thalassoica antarctica(Gmelin) (Fauchald & Tveraa 2006). Moreover, combiningdata from this study with previous data for other species,there was a significant positive relationship between the meandistance of ARS zones from the colony and mean ARS scale(Fig. 7; F1,7 = 17·7, P < 0·01, β = 0·05 ± 0·01, R2 = 0·72), sug-gesting a positive relationship between foraging distance andARS scale both within and among species.

Several recent studies of the movement patterns of predatorsin relation to the distribution of prey patches on a single scalehave suggested that predators employ a form of random walktermed a Lévy flight pattern, characterized by large numbersof short movements interspersed with occasional muchlonger displacements (Viswanathan et al. 1999). More recently,mathematical simulations have suggested that this pattern ofmovement maximizes encounter rates with randomly dis-tributed patches of prey and may be ubiquitous amongmarine predators (Sims et al. 2008). However, a hierarchicalsearch strategy will also generate this type of pattern, with alarge number of short movements within small-scale preypatches and occasional long displacements between large-scalepatches (Fauchald 1999; Fauchald & Tveraa 2006). In thecurrent study, most gannets did not choose displacementdistances at random but used a nonrandom nested searchstrategy, as also found in other species (e.g. Pinaud &Weimerskich 2005). Moreover, birds at this colony do notchoose foraging trajectories at random but forage repeatedlyover a narrow range of bearings on successive trips (Hamer

Fig. 6. Daytime dive rates of northern gannets within ARS zonesshowing nested ARS behaviour (solid bars), within ARS zones notshowing such nested search behaviour (pale grey bars) and outsideARS zones (dark grey bars), in mixed coastal water (inshore) and inseasonally stratified water beyond the tidal mixing front (offshore).Based on 420 dives from 12 foraging trips.

Fig. 7. Relationship between mean distance to ARS zones (km)and mean ARS scale (km) during foraging trips by eight species ofmedium- to long-ranging seabird. 1, Amsterdam albatross; 2, black-browed albatross; 3, light-mantled albatross; 4, sooty albatross;5, wandering albatross from Crozet Island; 6, wandering albatrossfrom Kerguelen; 7, white-chinned petrel; 8, Indian yellow-nosed albatross;9, northern gannet. Data from Table 1 in Pinaud & Weimerskich(2007) plus this study.

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et al. 2001). In view of the ubiquity of hierarchical spatialstructures in nature (Kotliar & Wiens 1990; Wu & Loucks1995) we agree with the suggestion by Fauchald & Tveraa(2006) that nested search strategies are likely to occur in awide range of species in both terrestrial and marine ecosystems,and this merits further study.

The importance of physical oceanography in driving spatialheterogeneity in pelagic marine ecosystems is well known(Hunt & Schneider 1987; Hofmann & Murphy 2004). In thisstudy, ARS zones of gannets were strongly associated with thetidal mixing front offshore from the colony, supportinghypothesis 2 above. This pattern is consistent with a previousanalysis of habitat suitability based solely on dive locations(Skov et al. 2008) and suggests that similar biophysical processesto those that concentrate predators over much larger scaleswithin pelagic marine ecosystems are also important atsmaller spatial scales within coastal seas. Birds in 2003 preyedextensively on sandeels (mainly Ammodytes marinus Raitt;> 50% of the diet by mass; Hamer et al. 2007), which are con-centrated in the region of the front and frequently driven closeto the surface by predatory fish, cetaceans and pursuit-divingseabirds (Camphuysen et al. 2006). In other years, birdspreyed less on sandeels and their foraging activity was focusedmore on other oceanographic features including sandbanksand deeps at greater distance from the colony (Hamer et al.2000, 2007). Despite marked differences between years in tripdurations, foraging ranges and total distances travelled,gannets did not appear to alter their overall search strategy orsinuosity of foraging paths (i.e. the extent of deviation from astraight-line course) between years in relation to trip durationor foraging range (Hamer et al. 2007). These data are consistentwith the suggestion that patterns of search behaviour are afeature of individual species and foraging habitats, not greatlyaffected by annual variation in environmental conditions(Pinaud & Weimerskich 2007), but further data are needed toexamine the nested search strategies of gannets under differentenvironmental conditions.

We found that the initiation of ARS behaviour was typicallyfollowed after only a short time interval (~5 min) by thecommencement of diving. Gannets do not dive until afterthey have located prey, and so this pattern strongly suggeststhat ARS behaviour was triggered by prey detection, supportinghypothesis 3 above. However, ~33% of dives in mixed coastalwater and 16% of dives in stratified water were not associatedwith any detectable ARS behaviour, suggesting that whileARS behaviour was triggered by the detection and pursuit ofprey, encounters with prey species did not necessarily induceARS behaviour. This absence of ARS was possibly the resultof unsuccessful dives, or of birds exploiting large prey such asmackerel Scomber scombrus Linn that quickly satisfied theirnutritional requirements, or of short-lived feeding opportunitiessuch as isolated food items, as found in wandering albatrossesDiomedea exulans Linn (Weimerskirch et al. 2007). Lewis et al.(2001) suggested that feeding opportunities of gannets closeto large colonies may be restricted by interference competitionwith conspecifics, as a result of prey taking evasive action inresponse to gannets plunge diving. This could explain the

lower proportion of dives within ARS zones in mixed coastalwater close to the colony, where competition with conspecificswithin prey patches is likely to have been higher (Lewis et al.2001). The extent of feeding within ARS zones may also havebeen underestimated in mixed coastal waters, where birdstake some prey by scooping from the surface without diving(Camphuysen et al. 2006).

Following the initiation of ARS behaviour, dive rates werealmost four times higher within ARS zones than elsewhereand almost three times higher in zones with nested ARSbehaviour than in those without. These data indicate that theadoption of ARS behaviour was strongly linked to enhancedforaging success, supporting hypothesis 4 above, particularlywithin nested small-scale ARS zones where birds may haveused the behaviour of other individuals to enhance preydetection (Hamer et al. 2000; Grünbaum & Veit 2003).

Gannets attained a maximum depth of 19 m during dives inthis study, which was similar to that recorded previously in theNorth Sea and elsewhere (Lewis et al. 2002; Garthe et al.2007). The overall dive rate on trips was also similar to thatrecorded at the colony in 2001 (Lewis et al. 2002), althoughthe latter study recorded relatively few shallow dives, coincidingwith a much lower occurrence of sandeel in the diet that year(Hamer et al. 2006) and so probably reflecting less feeding inmixed coastal waters where dives were shallower. Dives weremainly in the outward portion of trips in this study and ARSareas were all in the outward half, indicating that birdsreturned fairly directly to the colony without much searcheffort, as also suggested by Hamer et al. (2007) from a coarse-scale analysis of speeds of travel at sea. Lewis et al. (2004a)suggested that birds partitioned foraging effort fairly evenlybetween initial, middle and final sections of trips in terms oftime. However that study was not able to examine locations ofdives at sea and the adoption of ARS behaviour results inbirds attaining maximum range much later in the trip thanwould otherwise be expected. The absence of prey-searchingbehaviour during the return leg of foraging trips contrastswith the pattern recorded in Cape gannets Morus capensis(Lichtenstein) feeding in the Benguela current ecosystem,where adults frequently stopped to feed on the way back tothe colony during trips with an average duration of < 10 h(Ropert-Coudert et al. 2004). This difference probably reflectedthe much longer foraging ranges and trip durations of northerngannets, which resulted in pressure for adults to return to thenest as quickly as possible to relieve the partner at the nest(Hamer et al. 2007).

We have shown in this study that gannets increased theirsearch effort at nested hierarchical spatial scales, but withdifferences among individuals in this respect, which wereclosely associated with differences in dive rates during trips.Prey capture rate was not estimated in this study but, assumingthat at least some dives result in prey capture, this patternstrongly suggests that the foraging success of predators in ahierarchical system could be linked to the ability of individualsto track the system, as also found in yellow-nosed albatrosses(Pinaud & Weimerskich 2005). Differences in foraging successduring trips are likely to have consequences for individual

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fitness (Garthe, Grémillet & Furness 1999; Lewis et al. 2004b),emphasizing the importance of scale-dependent individualapproaches to understanding the links between prey dis-tribution and predator population processes in heterogenouslandscapes.

Acknowledgements

We thank Sir H. Hamilton-Dalrymple for access to the Bass Rock, J. Croxalland B. Nelson for assistance in developing the project and B. Nelson and theMarr family for continuing logistic support and advice. We thank S. Lewis forinvaluable assistance with deployment of loggers, and David Pinaud and oneanonymous reviewer for helpful comments on an earlier draft of the manuscript.This work was funded by a grant from the European Union (Interactionsbetween the marine environment, predators and prey: implications for sustainablesandeel fisheries (IMPRESS), Project Q5RS-2000-30864).

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Received 18 July 2008; accepted 10 March 2009Handling Editor: Henri Weimerskirch