MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 647: 211–227, 2020https://doi.org/10.3354/meps13389

Published August 13

1. INTRODUCTION

Two culturally and economically valuable speciesof salmon—coho Oncorhynchus kisutch and Chi-nook O. tshawytscha—have declined to criticallylow numbers in the Salish Sea (i.e. Puget Sound,Strait of Juan de Fuca and Strait of Georgia;Nehlsen et al. 1991, Beamish et al. 2010, 2012). Dif-ferent biotic and abiotic explanations have beenproposed to explain their declines, such as overfish-ing (Rutter 1997), loss of vital habitat (Magnusson &Hilborn 2003), interspecific competition (Ruggerone

& Nielsen 2004), changes in ocean conditions(Beamish et al. 1995) and changes in prey composi-tion and availability (Ruzicka et al. 2011). However,none of these possible explanations are conclusivelysupported. Attempts to increase coho and Chinookby releasing large numbers of hatchery-raised fishand reducing commercial and recreational ex -ploitation rates have been unsuccessful at restoringhistoric abundances. Both species of salmon havere mained at low levels and continue to present sig -nificant economic and conservation challenges(Lindley et al. 2009).

© Inter-Research 2020 · www.int-res.com*Corresponding author: h.all@disroot.org

Harbour seals responded differently to pulses ofout-migrating coho and Chinook smolts

Hassen Allegue1,4,*, Austen C. Thomas1,2, Yang Liu3, Andrew W. Trites1

1Marine Mammal Research Unit, Institute for the Oceans and Fisheries, and Department of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada

2Molecular Division, Smith-Root, Inc., Vancouver, WA 98686, USA3Department of Statistics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada

4Present address: Département des Sciences Biologiques, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada

ABSTRACT: There is increasing evidence that predation by harbour seals on out-migratingsalmon smolts may be responsible for the low return of adult coho and Chinook salmon in the Sal-ish Sea. However, little attention has been given to understanding where and when this predationoccurs and the extent to which it might be conducted by few or many seals in the population. Weequipped 17 harbour seals with data loggers to track seal movements and used accelerometryto infer prey encounter events (PEEs) following the release of ~384000 coho (May 4, 2015) and~3 million Chinook (May 14, 2015) smolts into the Big Qualicum River. We found a small propor-tion (5.7%) of all PEEs occurred in the estuary where salmon smolts entered the ocean — and thatonly one-quarter of the seals actively fed there. PEE counts increased in the estuary after both spe-cies of smolts were released. However, the response of the seals was less synchronous andoccurred over a greater range of depths following the release of the smaller-bodied and moreabundant Chinook smolts. Harbour seals feeding in the estuary appeared to target coho smolts atthe beginning of May but appeared to pursue predators of Chinook smolts in mid-May. PEEcounts in the estuary increased as tide height rose and were higher at dusk and night — especiallyduring full moonlight. Such fine-scale behavioural information about harbour seals in relation topulses of out-migrating smolts can be used to design mitigation strategies to reduce predationpressure by seals on salmon populations.

KEY WORDS: Phoca vitulina · Pacific salmon smolts · Predator−prey interaction · Biologging ·Accelerometry · Movement tracking

Resale or republication not permitted without written consent of the publisher

Mar Ecol Prog Ser 647: 211–227, 2020

The recovery of harbour seals Phoca vitulina fol-lowing intensive culling and hunting in BritishColumbia led to an exponential increase in harbourseal populations (Olesiuk 2010). This increase in har-bour seal numbers — in addition to other environ-mental changes (e.g. surface temperature and windstrength) — correlates with the decline in numbersand poor marine survival rates of coho and Chinooksalmon (Beamish et al. 1995, 2010, Olesiuk 2010) andled to speculation that predation by seals might beimpeding recovery of these salmon species (Chascoet al. 2017, Thomas et al. 2017, Nelson et al. 2019b).Harbour seals consume both adult and juvenilesalmon (smolts and subadults) but generally have notbeen thought to consume large amounts of them (butsee Lance et al. 2012). While predation on returningadult salmon is generally low relative to numbers ofreturning fish, there is evidence that high mortality ofcoho and Chinook salmon is occurring in the earlymarine stage (i.e. smolt stage) as the fish move down-stream and enter the ocean (Neville et al. 2015).

Harbour seals are the most abundant and the onlyyear-round resident pinniped in the Strait of Georgia(Olesiuk 2010). They are generalist predators thatfeed on a variety of fish and cephalopod species butshow preferences for Pacific herring Clupea pallasii,walleye pollock Gadus chalcogrammus, Pacific hakeMerluccius productus and salmonid species (Tollitet al. 1997, Lance et al. 2012). Within seal pop -ulations, individuals exhibit distinguishable dietspecialization associated with sex and size differ-ences (Bjorkland et al. 2015, Schwarz et al. 2018).Harbour seals are also believed to vary their diet sea-sonally and annually according to locally abundantprey (Middle mas et al. 2006, Lance & Jeffries 2007,Luxa & Acevedo-Gutiérrez 2013).

In the Strait of Georgia, scats (faeces) of harbourseals contain the remains of many prey species —including juvenile coho, Chinook and sockeye(O. nerka) salmon during spring when smolts are out-migrating (Thomas et al. 2017). The seals appear totarget these 3 species of salmon over the smaller-bodied juvenile chum O. keta and pink O. gorbuschasalmon (Thomas et al. 2017). Based on DNA metabar-coding and hard-part analyses of the seal scats, these3 species of juvenile salmon seem to comprise rela-tively small percentages of the seal diet (~10.5% inthe spring; Thomas et al. 2017). However, convertingthese percentages into numbers of individuals con-sumed suggests it may represent a significant sourceof mortality on salmon populations—particularly forcoho and Chinook salmon that are of conservationconcern (Irvine et al. 2009).

The majority of studies to date that have evaluatedpredation by seals on salmon smolts have focused ondocumenting what harbour seals eat and the poten-tial impact this has on salmon populations (Lance etal. 2012, Howard et al. 2013, Thomas et al. 2017). Yetrelatively little attention has been given to under-standing where and when this predation occurs (butsee Berejikian et al. 2016) and the extent to which itmight be by a small or a large proportion of the har-bour seal population. Documenting and assessingthe temporal and spatial foraging behaviour of sealsduring the smolt migration is needed to fully under-stand predator−prey dynamics and guide the devel-opment of adequate conservation actions that may benecessary to enhance salmon numbers (Caro 2007).

The objectives of our study were to (1) track anddocument movements of harbour seals in the Strait ofGeorgia and (2) map their feeding distribution inspace and time during the out-migration of coho andChinook smolts. We predicted that harbour sealswould concentrate their feeding efforts in the rivermouth and estuary areas, where smolts occur indenser schools and are spatially constrained (thus,more vulnerable to predation), as opposed to openwater areas (Yurk & Trites 2000). We therefore cap-tured and equipped 20 harbour seals within 20 km ofthe Big Qualicum estuary (BQE) in the Strait of Geor-gia (British Columbia, Canada) with data loggers andtracked the seals during and after the release of thou-sands of coho and Chinook smolts from the BigQualicum (BQ) hatchery. We were thereby able tomap and analyze feeding intensity (particularly inthe estuary area) relative to the releases of salmonsmolts based on seal movements and prey encounterevents (PEEs) identified from changes in body accel-eration. Such information is needed to assess poten-tial mitigation strategies designed to reduce preda-tion pressure by harbour seals on the smolts of thesesalmon species of conservation concern.

2. MATERIALS AND METHODS

2.1. Study location

The study was conducted in the vicinity of the BQRiver (49° 26’ 58” N, 124° 31’ 43” W) in the Strait ofGeorgia, British Columbia, Canada (Fig. 1). The BQRiver is an important spawning river for ChinookOncorhynchus tshawytscha, coho O. kisutch, pinkO. gorbuscha, chum O. keta and steelhead O. mykisssalmon. In addition to wild Pacific salmon popula-tions, the BQ hatchery artificially enhances the coho

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and Chinook salmon stocks in the river to increaserecreational and commercial fishing opportunities(Cross et al. 1991). In the spring of 2015, when weconducted our study, the BQ hatchery passively re -leased approximately 384000 coho smolts on May 4and ~3 million Chinook smolts on May 14. From allreleased coho smolts, the BQ hatchery tagged 37000individuals (i.e. 9.6%) with passive integrated trans -ponders (PIT tags) and recorded when they left thehatchery using RFID reader antennas. Chinook smoltswere not PIT-tagged due to their small body size.Several harbour seal Phoca vitulina haul-out sitessurround the BQ area and are less than 30 km fromwhere smolts leave the BQ River and enter the estu-ary (49° 23’ 55.7” N, 124° 36’ 33.1” W). All these haul-out sites are within foraging distance of the rivermouth (Peterson et al. 2012) and are estimated to beused by over 1000 harbour seals (Olesiuk 2010).

2.2. Device deployment and data collection

We captured 20 harbour seals in the BQ area fromApril 21 to May 1, 2015, using either a specializedbeach seine (Jeffries et al. 1993) or a low-tech boatrush method at 4 locations (Fig. 1D): BQE (n = 9), NorrisRocks (n = 9), Maude Reef (n = 1) and Flora Islet (n = 1).All seals were in dividually transported in hoop netsand carried to a restraining board where they weresedated with an intramuscular injection of 0.1 to0.2 mg kg−1 of butorphanol. The weight (±0.2 kg) andthe total length (i.e. snout to end of tail) to the nearest0.5 cm were measured. Seals that weighed >60 kgwere equipped with a floating logger package totheir dorsal midline between the shoulders using aquick-drying epoxy (Devcon). The logger packages(340 g and 168.4 × 111.8 × 36.2 mm) included a GPSsatellite tag (Splash 10-F; Wildlife Computers), a Daily

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Fig. 1. (A,B) Habitat use and (C) feeding density maps of all 17 tracked harbour seals constructed from a kernel densityanalysis of seal locations every 15 min (A,B) and prey encounter event (PEE) locations (C) from May 2 to June 2, 2015.(A−C) Colour scale ranges from low density (95% kernel density contour) to high density (5% kernel density contour).(C) Feeding hotspot polygons (i.e. 30% kernel density contour) are delimited by black contours. (D) Locations whereseals were captured: (1) Big Qualicum estuary (49.399°, –124.608°; n = 9), (2) Norris Rocks (49.484°, –124.648°; n = 9), (3)Maude Reef (49.499°, –124.684°; n = 1)

Mar Ecol Prog Ser 647: 211–227, 2020

Diary tag (Wildlife Computers), a very high fre-quency (VHF) transmitter (MM190B; Advanced Tele -metry Systems) and a flotation device (Fig. S1 in theSupplement at www. int- res. com/ articles/ suppl/ m647p211 _ supp. pdf).

The Daily Diary tags were set to sample and archivedepth at 1 Hz, earth’s magnetic field at 8 Hz and ac-celeration at 16 Hz. The GPS satellite tags were setto sample and archive Fastloc GPS snapshots every20 min in May and June 2015. In July and August2015, loggers were set to transmit previously recordedGPS locations through a satellite (Argos) as a backupif they were not physically recovered. To synchronizeall the data, every device was set to UTC. We locatedand recovered the logger packages using the VHF ra-dio signal after they had detached and the seals weremoulting (i.e. from August to October 2015). All dataprocessing and analysis, un less mentioned, were con-ducted in R v.3.6.3 (R Core Team 2020).

2.3. Track reconstruction

We divided each seal’s time series into either haul-out (i.e. resting on land) or at-sea state using thewet−dry sensor on the Daily Diary tag. The haul-outstate started when the tag was dry for at least 10 minand ended when the tag was wet for more than 40 s(Russell et al. 2015). The seals were considered in theat-sea state the remainder of the time. Data loggerscan experience memory errors during which no dataare recorded. Ten of the Daily Diary tags failed torecord data during <1% of the study period (exceptseal no. 1), which we assumed did not significantlyaffect the outcome of our results. Although the DailyDiary tag of seal no. 1 failed for ~2% of the studyperiod, we also assumed it did not affect our resultsbecause this individual spent all of its time in HoweSound outside our main study area (i.e. BQ area).

The seals were equipped with a Fastloc GPS whichprovided high-resolution locations even during shortsurface intervals (Costa et al. 2012). We applied themethod outlined in Austin et al. (2003) to filter GPSlocations. We used a traveling speed threshold of2.78 m s−1— the maximum swimming speed recordedby Lesage et al. (1999) in free-living harbour seals.We also conducted a final visual inspection andremoved all GPS locations on land. Overall, less than0.5% of locations were removed.

We used the dead reckoning method to reconstructthe seal pseudo-tracks between every 2 consecutiveGPS locations (Wilson et al. 2007). We ran the deadreckoning pseudo-tracks using the function Dead-

Reckoning from the R package TrackReconstructionand extracted the inclination and declination of theearth’s magnetic field for May 15, 2015, and the lati-tude and longitude of approximately the center of theStrait of Georgia (49° 24’ 00.0” N, 124° 06’ 00.0” W)using the World Magnetic Model 2010 calculatorfrom the British Geological Survey (www. geomag.bgs. ac. uk/ data_ service/ models _ compass/ wmm_ calc.html). We also used a 3 s running mean window toestimate the dynamic acceleration due to animalmovement (Shepard et al. 2008) and 2.78 m s−1 for themaximum speed threshold (Lesage et al. 1999).

The raw dead reckoning tracks were generated atthe magnetometer resolution of 8 Hz and thenrescaled to each minute to maximize computationalspeed. We georeferenced the raw dead reckoningtracks by forcing them through GPS locations usingthe function GeoRef (from the R package TrackRe-construction), which uses the conventional bias cor-rection equation from Wilson et al. (2007):

(1)

where is the corrected path in 1 dimension (i.e.easting or northing) at time t = 1,2,...,T between 2GPS locations, xt is the dead reckoning coordinate attime t = 1,2,...,T and yT is the GPS location at time T.In this equation, we assumed that x1 = y1 = 0. Whengeoreferencing the dead reckoning tracks, we con-verted GPS locations from longitude and latitude toeasting and northing in kilometers. While the sealswere hauled out (i.e. on land), we forced their posi-tion to the GPS location recorded during that haul-out time interval. Georeferencing allows correctionsfor error in the dead reckoning tracks, which growsover time because each dead reckoning locationdepends on the previous one (Bidder et al. 2012).Although GPS tags were set to record a locationevery 20 min, the GPS sampling rate was on average1 location every 65 ± 61 min (mean ± SD). We suspectthat the GPS sampling rate was lower than expectedbecause data logger packages were glued to thebacks of the seals, which might not be above thewater at every surface bout and therefore couldincrease the failure rate of GPS transmissions.

Based on visual examination of the reconstructedpseudo-tracks, we surmised that there were insuffi-cient GPS locations to effectively correct for the errorinduced by the dead reckoning, especially forpseudo-tracks that lasted for more than an hour. Weobserved multiple pseudo-tracks crossing land.Therefore, we applied an additional custom correc-tion algorithm to the georeferenced tracks based on

η = +−−

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geographical features constraining seal movement(i.e. land and bathymetry). This correction algorithmwas run in 2 steps. First, multiple pseudo-tracks weregenerated between each pair of GPS locations basedon the original shape of the georeferenced pseudo-track in Eq. (1). To do so, we added an extra parame-ter, α , into Eq. (1):

(2)

where the parameter α proportionally modifies theoriginal georeferenced track between 2 GPS loca-tions while preserving its global movement shape.When α = 1, , and the new pseudo-track is thesame as the original georeferenced pseudo-track.When α = 0, is a straight line between the 2 GPSlocations (i.e. y1 and yT). We generated 21 pseudo-tracks for each interval between 2 GPS locations withan α that ranged from −1 to 1 with a step of 0.1.

The second part of our correction algorithm reliedon selecting the most likely pseudo-track between 2GPS locations. To do so, we conducted a stepwisefiltering process. First, we removed all pseudo-trackswhere the seals exceeded the speed threshold of2.78 m s−1 (Lesage et al. 1999). Second, we selectedtracks that minimized the error due to the pseudo-track passage on land while the seals were diving.

To quantify the pseudo-track error on land, weused the root mean squared error (RMSE):

(3)

where εt is the error difference at time t between theseal diving depth and the surface (i.e. at 0 depth)when the estimated seal location is on land, dt is theseal diving depth at time t and T is the number oftime steps between the 2 GPS locations. Finally, weselected the pseudo-tracks that minimized the errordue to the seal diving below the bathymetry depth:

(4)

where δt is the error difference at time t between theseal diving depth and the bathymetry depth, dt is theseal diving depth at time t, bt is the bathymetry valueat time t and T is the number of time steps betweenthe 2 GPS locations. If at this stage more than 1pseudo-track remained, the pseudo-track with theclosest α parameter to 1 (i.e. to the original georefer-enced pseudo-track) was selected. We used a leave-one-out cross-validation method to estimate the ac -

curacy of our track correction algorithm. To do so, wesequentially removed each GPS location (except thefirst and the last ones) for each seal and calculatedthe error as the distance between the estimated loca-tion and the GPS location which we considered thetrue value. The bathymetry data of the Strait ofGeorgia had a resolution of 3 arcseconds and wasobtained from NOAA (https: // data. noaa. gov/ dataset/british- columbia- 3 - arc - second - bathymetric - digital -elevation - model).

2.4. PEEs

The acceleration-based method developed byViviant et al. (2010) uses high head or jaw accelera-tion data to identify possible PEEs (Iwata et al. 2012,Volpov et al. 2015). In seals, this method was shownto provide similar PEE detections with head- andback-mounted accelerometers (correlation coeffi-cient = 93%; Le Bras et al. 2016). Hence, we used thesame method of PEEs from back-mounted accelero -meters as a proxy to quantify feeding intensity.

First, we extracted the 3 axes (i.e. heave, surge andsway) of the dynamic acceleration (i.e. animal move-ment) by subtracting the static acceleration (i.e. grav-ity) from the total acceleration (m s−2, at 16 Hz). Thestatic acceleration was calculated from a 2 s runningmean window on total acceleration. Second, we cal-culated the variance of the 3 dynamic accelerationsover a 2 s moving window to identify high levels of ac-celeration variance. The 3 variance axes were com -bined into 1 dimension from the vector norm. Finally,we performed a k-mean clustering with 2 means onthe variance data to separate it into low and high ac-celeration variance. We considered occurrence of aPEE when a sequence of samples, separated by <1 s,was classified into the high-variance cluster, reflectinga bout of higher body acceleration (Fig. S2). To mini-mize PEE false positive detections due to high bodyaccelerations that were not related to foraging behav-iour (e.g. interacting with a conspecific at the surfaceor mounting a rocky site to haul out), we excluded allPEEs when the wet−dry sensor was at dry and 10 minbefore and after the seals were hauled out.

Depth sensors commonly drift over time (Spence-Bailey et al. 2007). We applied a zero-offset correc-tion over an hour window and with 0.5 m surfaceerror using the software provided by the manufac-turer (Wildlife Computers). We also observed quickspikes in the Daily Diary depth data caused by theArgos transmissions from the Splash tags (WildlifeComputers pers. comm.). We applied a 5 s rolling

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Mar Ecol Prog Ser 647: 211–227, 2020

median on the depth data to remove these spikes asrecommended by the manufacturer.

2.5. Feeding intensity

We considered the number of PEEs as a proxy forfeeding intensity. It is important to keep in mind thatPEEs were not validated in the wild. PEEs are there-fore not necessarily successful feeding events butshould be considered as relative proxies for preyencounters. We conducted a kernel density analysisof the locations of the PEEs to highlight geographicalregions of increasing feeding intensity. We also appliedthe kernel density analysis to all seal locations (1 loca-tion every 10 min for each seal) to visualize the over-all space used by all tagged seals. We used the Rpackage ks to estimate the kernel density distribu-tions for which we used an unconstrained bandwidthmatrix and a smoothed cross-validation bandwidthselector as recommended by Duong (2007). We high-lighted high feeding density areas (i.e. feeding hot -spots) as areas encompassing the top 30% of thekernel density distribution (e.g. Kitchen et al. 2000).

As we were interested in the harbour seal responseto the smolt release in the BQ River, we focused onanalyzing the variability of PEEs in the BQE hotspotand its vicinity (see Section 3). Out-migrating salmonsmolts more likely swim close to the surface (<50 m)as they reach estuaries, with the highest density atthe top ~5 m from the surface (Beamish et al. 2000,Emmett et al. 2004). Our data showed that most ofthe PEE detections in the BQE area occurred withinthe first 5 m depth (Fig. S3). Thus, we assumed thatfeeding on smolts was more likely to happen in thatdepth range. We separated the data within the BQEhotspot into 3 depth categories (0−5, 5−80 and >80 m).Depth thresholds were extracted visually from thefigure of the distribution of PEE counts over depth byseparating depth ranges of high PEE density (i.e.local peaks; Fig. S3).

Using generalized linear mixed-effects models, wemodeled the seal feeding intensity (counts of PEEs)in the BQE hotspot after the coho and Chinook smoltswere released. First, we fitted the count of PEEs perday as a function of the post-smolt release periods tocompare feeding intensity between both releaseperiods. Second, we fitted the count of PEEs per houras a function of the time of day, tide height and post-smolt release period. And third, we fitted the count ofPEEs per hour that occurred at night as a function oftide height and fraction of moon illumination. Weused a subset of the data from the day following the

release of the coho smolts (May 5) to May 24 to stan-dardize the number of days (10 d) after each smoltrelease period. Time periods when seals were out-side the BQE hotspot were not included in the model.

As the distribution of the count of PEEs per hour ishighly zero inflated, we applied a hurdle model thatcombines 2 distinct models. The first model fits theprobability of detecting at least 1 PEE per hour (pres-ence−absence of PEEs) following a binomial distribu-tion with a logit link—while the second model fitsthe count of PEEs per hour (PEE intensity) when atleast 1 PEE was detected. These counts of PEEs perhour follow a zero-truncated negative binomial dis-tribution with a log link and a quadratic parameteri-zation. We used a negative binomial distribution witha log link and a quadratic parameterization for themodel that fits the counts of PEEs per day.

Time of day was separated into 4 periods: day,dusk, night and dawn. The daily time limits of eachperiod were obtained from the R package maptoolswhere twilight phases were set according to the nau-tical twilight (i.e. the angle of the geometric center ofthe sun is between 0 and 12° below the horizon).Mean hourly tide height estimates were downloadedfrom the Fisheries and Oceans Canada website(https:// tides.gc.ca) at the Point Atkinson station. Asthe range of the tide height is not the same betweentime periods (see Fig. 5), we normalized it (i.e. re scaledto a mean of 0 and a variance of 1) within each periodfor a better comparison. The moon- illuminated frac-tion (i.e. from 0 for new moon to 1 for full moon) wasdownloaded from the R package oce and then nor-malized. We also in cluded the seal identity as a ran-dom effect to control for repeated measurements anddate and time (rounded per hour or per day) to con-trol for temporal autocorrelation. All model analy-ses were fit with the R package glmmTMB (Brooks etal. 2017), and we used the Akaike’s information crite-rion corrected for small sample sizes to select thefixed-effect combination.

3. RESULTS

3.1. Telemetry performance and general spatialdistribution

Of the 20 harbour seals captured in the BQ areafrom April 21 to May 1, 2015, 15 were males and 5were females. The seals weighed on average 91.7 ±13.9 kg and were 155.3 ± 9.5 cm long (Table S1 in theSupplement). Although we were able to recover GPSlocations for all 20 equipped seals either from satel-

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lite transmission (Argos; n = 1) or from the deviceitself (n = 19), we recovered full data for only 17 of the20 seals. Missing data for the remaining 3 seals weredue to equipment failure (n = 2) and tag loss (n = 1).Recording periods (48.2 ± 2.8 d) varied between sealsdue to variation in capture dates and battery life ofthe devices (Table S1). To keep all seal data consis-tent over time, we limited all our analyses from May2 to June 2 (i.e. 32 d) during which we had completedata for 17 seals. The data from the 3 other seals wereexcluded from our analysis.

During the study period, we collected an average of231 ± 14 GPS locations per day and per seal. The ac-curacy of the estimated locations from track reconstruc-tion between GPS locations averaged 0.4 ± 0.57 km(median 0.26 km). Most of the seals we tracked (n = 16of 20) limited their movements within the capturearea in the BQ area (<70 km) where they generallyused a primary haul-out site (e.g. Norris Rocks andFlora Islet) but also occasionally other secondaryhaul-out sites (e.g. Seal Bay and Mud Bay). The rest ofthe seals (n = 4) used the BQ area but also travelledlong distances (>100 km) and used other distant areassuch as the Malaspina Strait (seal no. 5), Mistaken Is-land (seal no. 13), Howe Sound (seal no. 1) and DeepCove (seal no. 20; Fig. 1A).

3.2. Total feeding intensity

Based on body accelerations, harbour seals madean average of 222 ± 160 PEEs per day (Table S1) dur-ing the study period (from May 2 to June 2). The ker-nel density analysis of the PEE locations revealeddiscrete patches of increasing feeding density withinthe Strait of Georgia that matched with the generalspace use distribution (Fig. 1). Most of the detectedPEEs were in the BQ area mainly around HornbyIsland but also occurred in the open water up to BQE(Fig. 1C). Additional feeding patches of isolated indi-vidual seals also occurred in other areas such as Mis-taken Island, Howe Sound and Deep Cove (Fig. 1).

Feeding hotspots (i.e. areas encompassing the top30% of the kernel density distribution) occurred in 3distinct patches. The first and largest feeding hotspotrepresented an area of 84.5% (5.61 km2) of totalhotspot sizes and was located around Norris Rockswhere there were 20440 (24%) PEEs by 13 (76%)individual harbour seals (Table 1). These PEEsoccurred throughout the water column (0−242 m)but were mainly between ~0−30 and ~120−170 m(Fig. S4). The second feeding hotspot (1.02 km2;15%) was in the BQE (Fig. 1C) and included 4798(5.7%) PEEs by 8 (47%) harbour seals (Table 1). ThesePEEs ranged from the surface to 236 m depth but oc -curred primarily within the first 5 m depth (Fig. S4).Finally, the last feeding hotspot (0.01 km2; 0.15%)was in the Deep Cove area and included 92 (0.1%)PEEs from 1 individual (Table 1). PEEs in the DeepCove hotspot ranged from close to the surface to 52 mdepth and were denser between ~20 and ~40 m(Fig. S4).

3.3. Spatiotemporal variation in feeding intensityin the BQ area

A kernel density analysis of PEE locations overtime revealed temporal and spatial synchrony be -tween the feeding intensity of the seals and therelease of ~384000 coho (on May 4) and ~3 millionChinook (on May 14) smolts from the BQ hatchery(Fig. 2, Fig. S5). Overall, the area around the NorrisRocks haul-out site experienced high PEE densityduring the whole study period. High PEE density wasalso observed in the BQE area particularly followingthe release of the coho and Chinook smolts (Figs. 2 &3A). Intermediate PEE patches next to the BQE incoastal and open water habitats occurred after theChinook smolts were released and seemed to movegradually towards Norris Rocks. Two new high PEEspots appeared at the end of the study on the north-ern side of Hornby Island (from May 25 to June 2)and at Flora Islet (from May 30 to June 2; Fig. 2).

217

Hotspot No. of seals (%) No. of PEEs (%) Area (km2) Latitude (°) Longitude (°)

Norris Rocks 13 (76) 20440 (24.2) 5.61 49.484 –124.655Big Qualicum Estuary 8 (47) 4798 (5.7) 1.02 49.399 –124.607Deep Cove 1 (6) 92 (0.1) 0.01 49.332 –122.936

Table 1. Summary information on feeding hotspots accounting for the top 30% of the kernel density distribution of prey en-counter events (PEEs) of 17 seals from May 2 to June 2, 2015. The number of seals (and percentage over the total number ofseals) that used the hotspot, number of PEEs (and percentage over the total number of PEEs) detected inside the hotspot, area

size and latitude and longitude of the polygon centroid are presented

Mar Ecol Prog Ser 647: 211–227, 2020

The BQE hotspot included 5.7% of all PEEs, ofwhich 86% occurred <5 m from the surface. Eight(47.0%) of the 17 seals had PEEs in the BQE area,but only 4 accounted for >90% of all PEEs in thatarea (seal nos. 2, 11, 12 and 17; Fig. 4). The dailycount of PEEs in the BQE hotspot peaked 4 d afterthe coho smolts were released (Fig. 3A) and can bemostly attributed to 3 seals (seal nos. 2, 11 and 17;Fig. 4) who fed within the upper 5 m of the water col-umn. The peak in PEE counts after the release ofcoho smolts overlapped with the number of passiveintegrated transponder-tagged coho smolts that werescanned leaving the BQ hatchery. On May 14, theday of the Chinook smolt release, PEE countsincreased again but were highly variable on subse-quent days, with daily PEE peaks on May 16, 21 and23 (Fig. 3A). After May 24, PEE counts remained lowuntil the end of the study. Although most detectedPEEs in the BQE area occurred within the first 5 mdepth, deeper PEEs also occurred and were con-ducted primarily by seal no. 12 on the 4 consecutivedays that followed the release of Chinook smolts(Fig. 4). Additional sporadic deeper daily PEEswere also detected by other seals, e.g. seal no. 11on May 31 and seal no. 17 on May 23. The mean

daily counts of PEEs during the post-Chinook releaseperiod (10 d) did not differ from the post-cohorelease period (z = −0.9, p = 0.4, Bayes factor = 1;Tables S2 & S3, Fig. S6).

The probability of detecting PEEs per hour de -pended on the 3-way interaction between tideheight, time of day and post-smolt release period(Table 2, Table S4). After the release of coho smolts,the probability of PEEs per hour increased with thetide height at dusk and night (Figs. S7 & S8) wherethe highest probability occurred at high tide and atdusk (Fig. S9). After the release of Chinook smolts,tide height did not affect the probability of PEEs perhour. Compared to the post-coho release period, thepost-Chinook probability of PEEs per hour washigher during the day at low and average tide andwas lower at night and high tide (Fig. S9). The countof PEEs per hour increased with tide height and washigher at night and dusk during the post-cohorelease period but did not differ between time peri-ods during the post-Chinook release period (Table 2,Table S5, Fig. S10). When considering PEEs only atnight, the probability of PEEs per hour increasedwith tide height and moon illumination (Table S7,Fig. S11). The count of PEEs per hour at night did

218

-124.7 -124.6 -124.5 -124.7 -124.6 -124.5 -124.7 -124.6 -124.5

-124.7 -124.6 -124.5

49.40

49.45

49.50

49.55

49.40

49.45

49.50

49.55

Longitude (°)

Latit

ude

(°)

Low High

Feeding density

Hornby Island

0 3km

*Coho release (May 04) *Chinook release (May 14)May 02 to 04 May 05 to 09 May 10 to 14 May 15 to 19

May 20 to 24 May 25 to 29 May 30 to June 02

Fig. 2. Feeding density maps of harbour seals in the Big Qualicum area in 2 to 4 d intervals from May 2 to June 2. Coho(~384000 smolts) were released on May 4 and Chinook (~3 million smolts) were released on May 14 from the Big Qualicumhatchery. Feeding densities were constructed from a kernel density analysis on all prey encounter event locations over thestudy period. Colour scale ranges from low density (95% kernel density contour) to high density (5% kernel density contour).

Feeding hotspot polygons (i.e. 30% kernel density contour) are delimited by black contours

Allegue et al.: Harbour seal foraging behaviour

not change with tide height and fraction of moonillumination (Table S6).

4. DISCUSSION

We collected data from 17 harbour seals andused track reconstructions paired with body accel-eration to identify areas of high feeding intensitiesduring the out-migration of hatchery-reared cohoand Chinook salmon smolts from the BQ River inthe Strait of Georgia. We found high feedingpatches within the BQ area but less feeding thanexpected within the estuary area (on average 5.7%)where smolts first enter the ocean. A second unex-pected finding was that feeding intensity of har-bour seals did not increase significantly in theestuary in response to the 8-fold greater numbersof Chinook released compared to coho smolts re -leased (i.e. 3 million Chinook smolts vs. 384000

coho smolts; Fig. 3A). These findings raise ques-tions about factors influencing seal foraging andthe relative profitability of alternative salmonid preyspecies.

4.1. Feeding in the BQ area

Contrary to our expectations, only a small fraction(5.7%) of all the feeding activity of all seals trackedoccurred in the BQE. Approximately half of the seals(n = 8) that stayed within the BQ area conducted atleast 1 PEE in the estuary. Nevertheless, the maxi-mum number of tagged seals that used the rivermouth per day was 3.6 of the 17 seals (Fig. 3B). Theseresults suggest that out-migrating smolts enteringthe BQE were not a major resource pulse for the over-all local harbour seal population but may have beenan important source of nutrition for a small portion ofthe seals (<20% of the 17 tagged seals).

219

0

100

200

300

400

500

0

1

2

3

4

02 04 06 08 10 12 14 16 18 20 22 24 26 28 30 01

Date

Prey

enc

ount

er e

vent

sSe

als

Coho sm

olts

Depth <5m 5-80m >80mCoho (~384k) Chinook (~3M)A

B

0 x 0

1 x 4

2 x 4

3 x 4

4 x 410

10

10

10

10

May

-02

May

-04

May

-06

May

-08

May

-10

May

-12

May

-14

May

-16

May

-18

May

-20

May

-22

May

-24

May

-26

May

-28

May

-30

June

-01

Fig. 3. (A) Daily counts of prey encounter events (PEEs; left y-axis) and (B) number of tagged seals inside the Big Qualicum es-tuary (BQE) hotspot from May 2 to June 2. (A) Daily PEE counts were tallied within 3 depth ranges: <5 m of the surface, be-tween 5 and 80 m and >80 m. Dashed vertical lines show when ~384000 coho smolts (on May 4) and ~3 million Chinook smolts(on May 14) were released from the Big Qualicum hatchery, while the orange line shows the numbers of passive integratedtransponder (PIT)-tagged coho smolts (right y-axis) that left the Big Qualicum hatchery each day. Approximately 37000 cohosmolts were PIT tagged prior to release (i.e. 9.6% of all released coho smolts). (B) The number of seals in the BQE hotspot

was corrected by the proportion of time seals spent each day inside that area

Mar Ecol Prog Ser 647: 211–227, 2020220

May

-02

May

-04

May

-06

May

-08

May

-10

May

-12

May

-14

May

-16

May

-18

May

-20

May

-22

May

-24

May

-26

May

-28

May

-30

June

-01

0

150

300

450

0

150

300

450

0

150

300

450

0

150

300

450

0

150

300

450

0

150

300

450

0

150

300

450

0

150

300

450

Date

Prey

enc

ount

er e

vent

s

Depth <5 m 5-80 m >80 m

Seal

#11

Seal

#17

Seal

#12

Seal

#2

Seal

#16

Seal

#3

Seal

#10

Seal

#9

May

-02

May

-04

May

-06

May

-08

May

-10

May

-12

May

-14

May

-16

May

-18

May

-20

May

-22

May

-24

May

-26

May

-28

May

-30

June

-01

0

1

2

3

4

0

1

2

3

4

0

1

2

3

4

0

1

2

3

4

0

1

2

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4

0

1

2

3

4

0

1

2

3

4

0

1

2

3

4

Date

Tim

e (%

) in

BQE

area

Coho (~384k) Chinook (~3M) Coho (~384k) Chinook (~3M)

Fig. 4. Daily counts of prey encounter events (PEEs) (left panel) and proportion of time each individual seal spent inside the BigQualicum estuary (BQE) hotspot (right panel) from May 2 to June 2, 2015. Daily PEE counts are separated into 3 depth ranges:<5 m depth, between 5 and 80 m depth and >80 m depth. Light grey bars in the background show the cumulative data for allseals. Dashed vertical lines indicate when ~384000 coho smolts (May 4) and ~3 million Chinook smolts (May 14) were released

into the river from the Big Qualicum hatchery

Allegue et al.: Harbour seal foraging behaviour

The BQE is a relatively small estu-ary in the Strait of Georgia comparedto others such as the Fraser River estu-ary, the Cowichan estuary, the Pun-tledge River estuary or the CampbellRiver estuary. Thus, our results shouldbe carefully interpreted given thatseal behavioural responses may varyin larger estuaries characterized withdifferent types of habitats. For in -stance, larger estuaries have longersmolt residency times compared withsmall ones — and are important areasfor salmon growth (McCabe et al.1986, Bottom et al. 2005). These differ-ences in smolt time residency and bodygrowth rates in estuaries may impactthe foraging behaviour of seals.

Optimal foraging theory suggeststhat a predator should maximize itslong-term energy gain by balancingthe energy provided by the preyenergy and by temporal and cognitiveconstraints associated with feeding oncertain prey (Stephens & Krebs 1986).In our case, the seals feeding on smoltsin small estuaries and rivers similar tothe BQ would have had very low tem-poral and energy constraints associ-ated with foraging in the confines of ashallow narrow river mouth. The sealswould have avoided all energy ex -penditure associated with diving andtime spent searching for prey, which ishighly significant when foraging inthe open water (Ramasco et al. 2015).In rivers, harbour seals can hold theirposition in the water and interceptout-migrating smolts in high numberswith minimal movements and henceminimum energy expenditure (Yurk &Trites 2000). However, feeding onsmolts in rivers and estuaries maypresent some constraints in terms offoraging efficiency. For instance, theBQ is a relatively small estuary whichmay limit the number of seals feed-ing at one time on out-migratingsmolts and consequently increaseintra-specific com petition. Other smoltpredators such as birds (Wood 1987) arealso abundant in the BQE and mayincrease inter-specific competition.

221

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(p <

0.0

5)

Mar Ecol Prog Ser 647: 211–227, 2020

Although salmon smolts migrate in high numbersand densities, their en ergy density (~5.04 kJ g−1 forcoho and ~3.98 kJ g−1 for Chinook; Roby et al. 2003) islower than other important prey in the Strait of Geor-gia such as Pacific herring (~5.9 kJ g−1; Anthony et al.2000). However, energy densities of smolts are higherthan those of other seal prey species such as walleyepollock (~3.5 kJ g−1; Anthony et al. 2000). As a conse-quence of the small size and intermediate energydensity of the salmon smolts relative to other prey,the seals would need to consume a large number ofindividuals (~100 smolts d−1) to meet their dailyenergy requirements (Howard 2009).

In addition to feeding efficiently in the river mouth,the seals using these areas presumably need somecognitive capability to predict the migration timingsif they are to take full advantage of the smolt pulses(Bell 1990, Willson & Womble 2006). How seals pre-dict the timing of these pulses and how they assessuncertainty have presumable consequences on theirforaging success and efficiency (Dall & Johnstone2002) considering that the peak of the smolt pulses insmall estuaries like the BQ may have a short timewindow of only a few days or weeks. Predators mayuse environmental (Real 1992) and social (Danchin etal. 2004) cues and information to optimize their for-aging decisions, such as relying on water temperatureand lunar cycles to anticipate the downstream migra-tion of 0 yr salmon (Roper & Scarnecchia 1999) — orthey may simply have learned to predict annual pat-terns in the release timing of hatchery salmon smolts(Nelson et al. 2019a) compared to the high inter-annual variability in the timing of wild salmon smoltmigrations (Holtby et al. 1989). Such reduced inter-annual variability in the timing of hatchery smoltreleases would increase the abilities of seals toexploit these pulses given that pinnipeds have highlearning and memory capacities that influence theirfuture behavioural decisions even after a long time(Reichmuth Kastak & Schusterman 2002).

A final consideration that may influence predationrates is the presence of suitable sites for the seals tohaul out, which were lacking near the BQE. Timeashore (i.e. either on sand and cobble beaches, rockyshelves, tidal sand and mud bars or human-madestructures) is important for harbour seals during theirmating, pupping and moulting periods but also on adaily basis for resting, thermoregulation, predatoravoidance, social interaction and parasite reduction(Boulva & McLaren 1979, Watts 1996). The BQE haslimited haul-out space on a rocky shelf that is onlyavailable at low tide and a cobble beach that is dis-turbed by humans from a nearby campground.

Therefore, seals that foraged in the estuary eitherhad to use less suitable haul-out sites or had to travelback and forth between the BQE and other more dis-tant haul-out sites (e.g. either Norris Rocks or FloraIslet). This constraint of frequently travelling in theopen water, in addition to energetic constraints, in -creases the vulnerability of seals to predation bykiller whales Orcinus orca (Ford et al. 1998), whichpresumably influences their behaviour and foragingdecisions (Welton et al. 2003).

4.2. Feeding on coho vs. Chinook smolts

The number of PEEs in the BQE hotspot showed aclear peak 4 d following the release of coho smoltsfrom the BQ hatchery (Fig. 3A), which suggests theseals were quick to detect the coho smolt arrival andpreyed on them as they left the BQ River. However,there was no clear corresponding peak in the PEEcounts for Chinook smolts similar to the one thatoccurred after the release of the coho smolts despiteseals being present in that area. Instead, high num-bers of PEE counts were dispersed over time. Themean daily PEE numbers did not differ between thepost-coho and the post-Chinook release periods(Fig. S6) even though Chinook smolts were releasedin much higher numbers (~3 million) than coho smolts(~384000). The seals did not appear to re spond to therelease of the Chinook smolts as they did for therelease of the coho smolts. This unexpected behav-iour of harbour seals could be ex plained in 2 ways.One is that the harbour seals preferred feeding oncoho rather than Chinook smolts, and the other isthat consumption of Chinook smolts was constrainedby environmental factors.

The inference that the seals may prefer feedingon coho compared to Chinook smolts could be ex -plained by differences in sizes and energy densitiesof the 2 species of smolts leaving the river. Measure-ments of smolts sampled before their release showedthat the coho smolts were substantially bigger thanthe Chinook smolts. The coho smolts were 1.6 timeslonger and 3.8 times heavier than the Chinook smolts(i.e. coho averaged ~12.9 cm and ~22.6 g, while Chi-nook averaged ~8.0 cm and ~5.9 g). Harbour sealsmay prefer prey ranging between 10 and 16 cm inlength (Tollit et al. 1997), which could explain theapparent preference for coho smolts over Chinooksmolts. In addition, coho smolts are energy denser(~5.04 kJ g−1 or ~113.9 kJ ind. −1) than Chinook smolts(~3.98 kJ g−1 or 23.5 kJ ind.−1), which means that con-suming 1 coho smolt was 4.8 times more energetically

222

Allegue et al.: Harbour seal foraging behaviour 223

beneficial to a harbour seal in the estuary than con-suming a Chinook smolt (Roby et al. 2003). Chinooksmolts are considerably smaller than coho smoltswhen entering saltwater and tend to spend more timein the estuary or in nearshore habitats before reach-ing the open ocean (Myers & Horton 1982, Dumbauldet al. 2015). During this time, Chinook gain body massand store lipid, which would make them a more ener-getically beneficial prey for predators later in theyear. This is consistent with dietary and modellingstudies that suggest Chinook mortality rates due toseal predation peak later in the summer (July), incontrast to the coho mortality rates that are high in Mayand June (Thomas et al. 2017, Nelson et al. 2019b).

The presence of the seals in the BQE hotspot andthe variability in PEE counts following the release ofChinook smolts suggest that the seals may have beentargeting aggregations of other Chinook smolt pred-ators such as the Pacific hake, spiny dogfish, riverlamprey, adult Chinook salmon, lingcod and walleyepollock (Beamish & Neville 2001, Emmett & Sampson2007). Consistent with this hypothesis is that PEE in -tensity by the seals increased in the open water nextto the estuary as the Chinook smolts were migratingand that PEEs occurred mostly below 70 m (Fig. 2).An increase in deeper PEEs (>80 m depth) was alsodetected in the BQE hotspot after the release of theChinook smolts, which suggests the seals fed onother species instead of salmon smolts (Orsi & Wert -heimer 1995, Emmett et al. 2004). Two of the 3 sealsthat contributed the most to the PEE peak followingthe release of the coho smolts lowered their daily PEEcounts after the Chinook smolts were re leased, eventhough they seemed to spend as much time as beforein the BQE hotspot (Fig. 4). The lower PEE countscould reflect satiation and consumption of larger preybut seem unlikely to be a lagged effect of having con-sumed the large pulse of coho smolts 10 d earlier.

The unexpected low response to Chinook smolts byharbour seals could also be explained by differencesin environmental factors between the post-coho andpost- Chinook smolt release periods. Out-migratingsalmon smolts tend to minimize predation risk by mi -grating at higher numbers at night when luminosityis low (Furey et al. 2016). Harbour seals have beenseen gathering in river mouths at night and using arti-ficial lights to take advantage of out-migrating smolts(Yurk & Trites 2000). The higher probability and in -tensity of PEEs we observed at dusk and at night inthe BQE hotspot are consistent with this, althoughthe nearby campground provided little artificial light.Another source of light that can influence predationis moonlight. We found that PEE counts increased in

the BQE hotspot as the nightly fraction of the illumi-nated moon increased. This suggests that moonlightmight have improved seal visibility to detect theirprey. Tide height is another environmental factor thataffects seal predation on smolts in the river mouth. TheBQ River is a relatively small river that seals cannotaccess at low tide. At low tide, the seals cannot takeadvantage of the higher densities of spatially con-strained smolts (Yurk & Trites 2000). This is consistentwith our finding that the prob ability and the intensityof PEEs in BQE hotspot increased with tide height.

As the releases of the coho and the Chinook smoltswere 10 d apart, the 2 post-release periods differed inthe timing of the tide height and the lunar cycle. Thecoho smolt release happened at full moon (i.e. thehighest visibility at night) and high tide matched,with dusk and nighttime offering favorable environ-mental conditions to feed efficiently on coho smolts(Fig. 5). However, 10 d later, the Chinook smoltrelease occurred 3 d before the new moon (i.e. lowvisibility at night) and tide was low at dusk and night.Thus, environmental conditions were less favourablefor seals to spatially constrain and visually detect theout-migrating Chinook smolts. However, as seals candetect their prey in the dark using their vibrissae(Hanke et al. 2013), we believe the temporal mis-match between the tide height and the dusk andnight periods would have reduced seal foraging effi-ciency but not foraging attempts. One means to testthis and the presumed preference for coho smoltswould be to reverse the order of release.

4.3. Study limitations

Although our study brings relevant insights intothe predator−prey dynamics between harbour sealsand out-migrating coho and Chinook smolts in theSalish Sea, our results are limited by low sample sizeand methodological considerations. For instance, thebehavioural feeding response we noted following thepulse of smolts entering the BQE hotspot is based on4 of 17 tagged seals. The power to detect a differencein feeding intensity between post-coho and post-Chi-nook release periods was just 15% (Table S3) andwould have required equipping more seals with tagsto increase statistical power. The age structure andsex ratio of our tracked seals were also skewedtowards older males, whose foraging ecology maydiffer from that of females and younger individuals(Schwarz et al. 2018).

Acceleration has become a common tool to quan-tify distinct behaviours in free-ranging animals —

Mar Ecol Prog Ser 647: 211–227, 2020

especially as a proxy for feeding effort (Jeanniard-du-Dot et al. 2017). However, accelerometry alonecannot determine feeding success. Additional dataon diet combined with movement and diving dataare needed to provide a complete understanding ofharbour seal foraging response to smolt pulses.

The placement of the accelerometer on an animalis also an important consideration when using ac -celerometry data. Many studies have approximatedforaging success with prey capture attempts by de -tecting head strokes (Volpov et al. 2015, Jeanniard-du-Dot et al. 2017). Due to logistical considerations,we placed the accelerometer on the backs of theseals and considered high body accelerations as PEEsto quantify feeding intensity. Given the variety ofprey species consumed by harbour seals (Lance &Jeffries 2007), it is conceivable that using body accel-eration instead of head acceleration led to incom-plete inferences about the relative numbers of preyconsumed. For example, seals swimming againstriver currents could hold their position in the water

and use minimal movements to intercept smoltsswimming towards them (Yurk & Trites 2000). Har-bour seals can also consume small prey using suctionfeeding in addition to biting (Marshall et al. 2014).The suction feeding tactic may not be detected by theback-mounted accelerometer and could thus under-estimate PEEs in rivers and estuaries. Hence, it istheoretically possible that the method we used to de -tect PEEs could explain the apparent low responseby seals to out-migrating Chinook smolts if less sealbody movement was required to catch Chinook smoltsthan to catch coho smolts.

5. CONCLUSIONS

Our results show that harbour seal predation onout-migrating smolts in the estuary was relativelysmall (23.5% of seals and 5.7% of all PEEs) comparedto the foraging effort of all tracked seals within theBQ area. The most intensive feeding occurred near

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Fig. 5. Counts of prey encounter events (PEEs) per hour inside the Big Qualicum estuary hotspot over tide height (y-axis) anddate and time (x-axis). Approximately ~384000 coho smolts (on May 4) and ~3 million Chinook smolts (on May 14) were re-leased from the Big Qualicum hatchery. The solid line shows tide height over time. Shaded time periods represent night (darkgrey), dawn and dusk (light grey) and daylight (white). Within each night period, the moon phase is represented by an icon

ranging from full moon (white circle) to new moon (black circle)

Allegue et al.: Harbour seal foraging behaviour

the southern part of Hornby Island around NorrisRocks. Those seals that travelled to the BQE re -sponded positively to the pulse of coho smoltsreleased from the BQ hatchery by increasing theirfeeding intensity. However, the seals did not respondas expected to the pulse of Chinook smolts, whichwere ~8 times more abundant than coho smolts. Theydid not appear to feed on the Chinook smolts in anysignificant way. Our findings suggest that the preda-tor responses we observed were affected by the mag-nitude of the resource pulses as well as by otherfactors that impact prey profitability (e.g. prey size,relative prey energy density and availability of alter-native prey) and predation efficiency (e.g. height andtiming of tide level and lunar cycle).

Dietary analysis indicates that predation by har-bour seals on coho and Chinook smolts likely has asubstantial impact on these salmon species (Chascoet al. 2017, Thomas et al. 2017). We inferred signifi-cant predation by a few seals on coho smolts thatentered the estuary, but predation pressure seemedmore relaxed on Chinook smolts. Instead, we suspectthe seals may have targeted predators of Chinooksmolts. In all likelihood, predation pressure by har-bour seals on Chinook smolts in the Strait of Georgiaoccurs later in the summer (July and August), oncethe fish have grown to a size that better fits thesearch image and energy requirement of harbourseals (Tollit et al. 1997).

Our findings bring new insight into the complexityof the interactions between harbour seals and out-migrating coho and Chinook smolts. They show thehighly individualistic nature of seal predation andsuggest that there may be complex indirect effectsassociated with seals consuming fish that also preyon juvenile salmon. They further suggest that thepredatory impacts of seals differ substantially be -tween juvenile coho and Chinook (at least spatiotem-porally) — and question whether the survival pat-terns of these 2 salmonids are tightly linked (as oftenassumed). Such confounding factors need to be ad -dressed when considering broad conservation meas-ures that might be taken against harbour seals toenhance the marine survival of salmonids.

Acknowledgements. We thank T. Jeanniard-du-Dot, B. Nel-son, C. Wabnitz, D. Rosen, B. Battaile and R. Joy for assis-tance in data analysis and for their conceptual feedback. Wealso thank the reviewers for their helpful comments andsuggestions. Field support was provided by the Washing-ton Department of Fish and Wildlife (WDFW) pinniped cap-ture team, the Department of Fisheries and Oceans Can-ada (DFO), Vancouver Aquarium, the Qual icum First Nation,The British Columbia Conservation Foundation and gradu-

ate and undergraduate students of the University of BritishColumba (UBC) Marine Mammal Research Unit. Specialthanks to S. Jeffries, M. Haulena, S. Trembley-Boyer and A.Carrier for fieldwork assistance. Funding was provided bythe Pacific Salmon Foundation (PSF) as part of the Salish SeaMarine Survival Project (SSMSP: publication 47). Additionalsupport was provided by the Fonds de Recherche Nature etTechnologies Québec (FRQNT). All data were collectedunder the University of British Columbia animal care permitno. A14-0322 and Fisheries and Oceans Canada permit no.XMM 2 2015.

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Editorial responsibility: Elliott Hazen, Pacific Grove, California, USA

Submitted: December 9, 2019; Accepted: June 11, 2020Proofs received from author(s): August 3, 2020