Avian Predator Buffers Against Variability in Marine Habitats with Flexible Foraging Behavior

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Avian predator buffers against variability in marine habitats with ﬂexible foraging behavior

Article in Marine Biology · February 2018 DOI: 10.1007/s00227-018-3304-4

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Avian predator bufers against variability in marine habitats with fexible foraging behavior

Sarah K. Schoen1 · John F. Piatt1 · Mayumi L. Arimitsu2 · Brielle M. Hefin2 · Erica N. Madison1 · Gary S. Drew1 · Martin Renner3 · Nora A. Rojek4 · David C. Douglas2 · Anthony R. DeGange1

Received: 11 September 2017 / Accepted: 31 January 2018 © This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2018

Abstract How well seabirds compensate for variability in prey abundance and composition near their breeding colonies infuences their distribution and reproductive success. We used tufted pufns (Fratercula cirrhata) as forage fsh samplers to study marine food webs from the western Aleutian Islands (53°N, 173°E) to Kodiak Island (57°N, 153°W), Alaska, during August 2012–2014. Around each colony we obtained data on: environmental characteristics (sea surface temperature and salinity, seafoor depth and slope, tidal range, and chlorophyll-a), relative forage fsh biomass (hydroacoustic backscatter), and seabird community composition and density at-sea. On colonies, we collected pufn chick-meals to characterize forage communities and determine meal energy density, and measured chicks to obtain a body condition index. There were distinct environmental gradients from west to east, and environmental variables difered by ecoregions: the (1) Western-Central Aleutians, (2) Eastern Aleutians, and, (3) Alaska Peninsula. Forage fsh biomass, species richness, and community composition all difered markedly between ecoregions. Forage biomass was strongly correlated with environmental gradients, and environmental gradients and forage biomass accounted for ~ 50% of the variability in at-sea density of tufted pufns and all seabird taxa combined. Despite the local and regional variability in marine environments and forage, the mean biomass of prey delivered to pufn chicks did not difer signifcantly between ecoregions, nor did chick condition or pufn density at-sea. We conclude that pufns can adjust their foraging behavior to produce healthy chicks across a wide range of environmental conditions. This extraordinary fexibility enables their overall success and wide distribution across the North Pacifc Ocean.

Introduction

Seabirds inhabit nearly all marine environments from the Responsible Editor: Y. Cherel. tropics to the poles. Physiological and morphological adaptations of individual species to those environments shape Reviewed by C. Cotté and an undisclosed expert. their behavior, ecology, and demography (Schreiber and Electronic supplementary material The online version of this Burger 2001), and ultimately determine the marine ecore- article (https://doi.org/10.1007/s00227-018-3304-4) contains gions in which they can survive. Seabird life history charac- supplementary material, which is available to authorized users. teristics have evolved to account for the energetic constraints they face in supplying food to their chicks at centralized * Sarah K. Schoen [email protected] colonies while foraging for patchily distributed prey in sur- rounding waters (Lack 1968). For example, generalists with 1 US Geological Survey Alaska Science Center, 4210 fexibility in diet and foraging location can compensate for University Ave, Anchorage, AK 99508, USA variation in prey availability by adjusting their time budg- 2 US Geological Survey Alaska Science Center, 250 Egan Dr, ets and provisioning strategies to optimize breeding success Juneau, AK 99801, USA (Piatt et al. 2007; Ainley et al. 2014). 3 Tern Again Consulting, 811 Ocean Drive Loop, Homer, Aspects of seabird breeding biology (e.g., diet, reproduc- AK 99603, USA tive success, chick growth, fedging success) and distribu- 4 US Fish and Wildlife Service Alaska Maritime National tion and density at sea have been correlated with changes in Wildlife Refuge, 95 Sterling Hwy, Homer, AK 99603, USA

Vol.:(0123456789)1 3 47 Page 2 of 14 Marine Biology (2018) 165:47 food supply and direct or indirect (via food supply) efects To address this hypothesis, we studied tufted pufns at of marine climate (e.g., Gjerdrum et al. 2003; Frederiksen 25 colonies (each on a diferent island) located between et al. 2005; Piatt et al. 2007; Renner et al. 2012; Gladics the western Aleutian Islands and Kodiak Island, Alaska et al. 2015; Sydeman et al. 2017). The use of seabird diets (Fig. 1). Piatt and Springer (2007) proposed several ecore- to study forage fsh communities can be an efective method gion boundaries within this area based on mesoscale pat- for assessing the status of marine food webs and ecosystem terns in biological indicators and topographic, bathymetric, health over space and time (Sydeman et al. 2017; Piatt et al. and oceanographic features, including (Fig. 1): Amchitka 2018). Tufted pufns (Fratercula cirrhata) are a particularly Pass separating the Central Aleutians from the Western useful species to study because of their wide distribution Aleutians; Samalga Pass separating the Eastern Aleutians across a large range of environmental and prey conditions from the Central Aleutians; and Unimak Pass separating the from California to Japan, and from the subtropics to the Arc- Alaska Peninsula from the Eastern Aleutians. Samalga Pass, tic (Piatt and Kitaysky 2002; Drew et al. 2015). In addition, in particular, has been identifed as a demarcation of “pro- they are a colonial piscivore with a broad diet, and they feed found ecosystem change” in terms of oceanography (Hunt their chicks whole food items, which can be easily identi- and Stabeno 2005; Ladd et al. 2005a), zooplankton (Coyle fed and measured (Piatt and Kitaysky 2002). Unlike many 2005), fsh (Logerwell et al. 2005; Sydeman et al. 2017), seabirds that depend on just a few select forage species in seabirds (Byrd et al. 2005; Jahncke et al. 2005; Ladd et al. their breeding range (Ainley et al. 2002; Gladics et al. 2015), 2005b) and marine mammals (Sinclair et al. 2005). tufted pufns are generalist predators whose diverse diets Against this backdrop of distinct ecoregions, we assessed refect the availability of a variety of prey species (Piatt and local food webs from the diets of tufted pufns breeding Kitaysky 2002; Sydeman et al. 2017). Indeed, in the Gulf at 25 colonies across the entire area. We then character- of Alaska and the Aleutian Islands pufns feed their chicks ized local forage fsh communities with respect to marine more than 40 species of forage fsh, including 16 main prey habitats (e.g., Abookire and Piatt 2005; Logerwell et al. groups (Sydeman et al. 2017). We hypothesized that, along 2005). We collected data on environmental variables that with some key foraging adaptations (e.g., multiple prey load- have been shown to infuence upper trophic levels, including ers, burrow-nesters), the diversity in diet of tufted pufns seabird diets, hatch dates, growth rates, and fedging success during chick rearing may help them bufer against regional (Gjerdrum et al. 2003; Renner et al. 2012; Gladics et al. diferences in habitat and prey quality. 2015). We also estimated forage fsh biomass (hydroacoustic

Fig. 1 Tufted Pufn colonies sampled during August, 2012–2014 dots. Important island passes are denoted with double lines and from in the Aleutian Islands and Gulf of Alaska. Colonies within difer- west to east are: (1) Buldir, (2) Amchitka, (3) Samalga, and (4) Uni- ent marine ecoregions [Western-Central Aleutians (WCA), Eastern mak passes. Bathymetry is displayed with darker colors representing Aleutians (EA), and Alaska Peninsula (AP)] are denoted by colored deeper depths

1 3 Marine Biology (2018) 165:47 Page 3 of 14 47 backscatter index) and seabird densities at sea around each Kitaysky 2002) and 70 km for Atlantic pufns (Harris et al. colony. At colonies, we collected data on tufted pufn chick 2012), although most birds probably forage much closer body condition. The specifc objectives of our study were to: to colonies (e.g., < 40 km) as adults try to minimize the (1) assess geographic variability in pufn diet in relation to amount of time spent commuting to provision chicks (Piatt variation in marine habitat, (2) relate the at-sea density of et al. 2007; Harris et al. 2012). We believe that our surveys, tufted pufns and marine birds to marine habitat characteris- conducted in close proximity to colonies, provide a reason- tics and prey availability, and, (3) assess which (if any) envi- able proxy for the marine habitats likely to be encountered ronmental and food factors infuence pufn chick condition. by pufns foraging at somewhat greater distances from their colonies. In addition to environmental data, we collected data on tufted pufn chicks at each colony. We selected colo- Materials and methods nies for sampling based on biological (colony size, historical data, etc.) and logistical (weather, accessibility, etc.) consid- Study area erations. We attempted to sample each of 23 colonies during the middle of chick-rearing (approximately August 7–22) in Our study area spanned 2400 km from the terminus of the 2012, 2013 and 2014 (Table 1; Fig. 1). We also included puf- Aleutian Archipelago eastward along the Alaska Peninsula fn chick diet information collected by the Alaska Maritime to Kodiak Island in the northern Gulf of Alaska (Fig. 1). National Wildlife Refuge (AMNWR) on Aiktak and Buldir The Alaska Coastal Current, driven by alongshore winds islands during August 2–30 in 2012 and 2013, respectively and freshwater discharge, fows west along the continental (Table 1; Fig. 1). Owing to the large geographic scope of the shelf of the Gulf of Alaska, transporting nutrient-depleted, study we needed to sample over multiple years in order to low salinity water southwest along the Alaska Peninsula and sample all colonies during the same stage of chick-rearing. into the Aleutian Islands (Stabeno et al. 2004; Mordy et al. We acknowledge that we are therefore unable to disentangle 2005; Stabeno et al. 2016). The faster moving, colder and potential inter-annual efects from geographic ones. more nutrient-rich Alaskan Stream travels southwest along the continental shelf-edge and westward along the south Environmental variables side of the Archipelago to at least Amchitka Pass (Fig. 1; Mordy et al. 2005; Stabeno and Hristova 2014). Waters from Sea surface temperature (SST) and salinity (SSS) were the North Pacifc are forced northward into the Bering Sea measured continuously during at-sea surveys using a hull- through several major passes between the islands, including mounted (3.7 m below surface) thermosalinograph (Sea- Amchitka, Amukta, Samalga, and Unimak passes (Fig. 1; Bird Electronics Inc ® SBE 21). We did not collect thermo- Hunt and Stabeno 2005; Ladd et al. 2005b), merging into salinograph data from Aiktak Island, but used data from the east-ward fowing Aleutian North Slope Current (Sta- Kaligagan Island as a proxy (~ 5.6 km separating islands). beno et al. 2009). Passes between Aleutian Islands vary from We measured the average of additional environmental vari- shallow and narrow to wide and deep, with depths generally ables within a 50 km2 area centered on each pufn colony, decreasing from west to east (Hunt and Stabeno 2005). The excluding land area within the circle. Ocean depths (m) and continental shelf (200 m depth contour) is wide on the south slope of sea foor (°) were derived from NOAA’s ETOPO1 side of the Alaska Peninsula (~ 100 km), and narrows con- Global Relief Model (http://ngdc.noaa.gov/mgg/global/), siderably (< 25 km) along the Aleutian chain. tidal ranges were collected from NOAA tide tables (annual minimum to maximum height), and chlorophyll-a (chl-a) Data collection and processing standing stock concentrations (mg m−3; 4 km pixel resolu- tion) were generalized from MODIS Aqua estimates aver- We sampled on and around islands with tufted pufn colo- aged over the months of May–August 2003–2011 (http:// nies using the US Fish and Wildlife Service 36-m R/V oceancolor.gsfc.nasa.gov). See also Piatt et al. 2018 for Ti ĝ la x̂ . At each site we conducted at-sea surveys in a radial details on characterizing these environmental variables. pattern centered on islands (hereafter “spokes”) to study local marine environments (Kitayksy et al. 2000). Spokes Forage fsh biomass (hydroacoustic backscatter) were usually constrained in number ( x̄ = 11) and length ( x̄ = 4.7 km; range 0.3–10.1 km) by local geography and A hull-mounted 38–120 kHz split-beam hydroacoustics bathymetry (e.g. islands or reefs precluding vessel passage), system (SIMRAD EK500 in 2012 and EK60 in 2014) was and were usually surveyed during daylight hours between used to measure hydroacoustic backscatter continuously in 0800 and 1600 AKDT. Our survey transects were smaller the water column along survey spokes around each pufn than the potential maximum foraging range of a pufn, colony. An equipment malfunction precluded hydroacoustic which is approximately 100 km for tufted pufns (Piatt and sampling in 2013, and due to a technical error during data

1 3 47 Page 4 of 14 Marine Biology (2018) 165:47 ) −1 3.72 4.16 4.01 4.13 4.01 3.21 4.24 4.08 4.10 3.96 3.69 3.64 n/a n/a n/a 3.80 n/a Chick cond. Chick mass/wing (g mm 3.00 3.89 4.28 4.58 4.63 n/a n/a 4.30 - 22 (67) 14 (28) 17 (36) 19 (45) 12 (26) 28 (40) 25 (35) 16 (35) 24 (40) 24 (31) 24 (50) 14 (15) 0 (32) 3 (6) 0 (3) 15 (30) n/a Chicks (bur Chicks checked) rows 28 (54) 25 (44) 27 (56) 26 (71) 23 (58) n/a n/a 25 (57) ) −1 36.4 17.6 27.5 34.4 30.1 33.6 110.6 36.5 59.5 79.3 28.0 53.6 n/a n/a n/a n/a n/a Mean energy Mean energy density (kJ g 24.0 67.2 44.3 42.8 34.9 46.8 20.8 36.1 10.9 7.1 10.1 11.3 10.9 8.8 26.7 14.0 15.3 20.9 8.5 17.1 n/a n/a n/a n/a n/a Mean meal mass (g) 8.5 20.8 10.1 9.7 9.3 14.4 8.9 11.0 b 0.07 0.17 0.19 0.14 0.16 0.20 0.16 0.25 0.17 0.12 0.13 0.25 n/a n/a n/a n/a n/a 0.18 0.29 0.10 0.12 0.08 n/a n/a 0.29 CPUE (356) (34) (74) (211) (n/a) c c c c e 3 8 7 0 5 21 (289) 55 (330) 52 (275) 42 (299) 41 (250) 78 (395) 27 (171) 86 (339) 41 (247) 26 (223) 35 (271) 40 (158) 89 (496) 87 (304) 26 (265) 34 (273) 16 (197) 13 (n/a) 104 (n/a) 102 (349) Chick meals Chick set) (screens ) −2 km 11.0 14.3 TUPU density (birds 247.5 n/a 72.8 n/a 27.0 26.9 3.0 39.9 16.0 2.4 12.5 188.4 30.7 7.4 44.9 42.9 84.4 50.9 9.0 11.5 n/a n/a 16.7 ) −2 km 34.7 35.7 Bird density Bird (birds 352.8 n/a 118.8 n/a 28.7 93.7 195.6 178.8 299.1 162.7 430.7 1267.1 80.9 12.7 334.2 139.2 162.0 107.6 45.8 66.1 n/a n/a 41.7 ) −2 nmi

2 (m

a n/a n/a 2.11 n/a 1.21 n/a n/a 2.33 n/a 2.64 n/a n/a n/a 3.27 n/a 0.37 1.08 1.17 0.80 0.79 n/a 1.01 n/a n/a 1.28 Forage fsh biomass Forage index d d 8/17/2013 8/16/2013 8/2012 8/21/2012 8/20/2012 8/19/2012 8/20/2012 8/14/2012 8/17/2012 8/2013 8/21/2013 8/18/2012 8/15/2013 8/19/2013 8/20/2013 8/15/2012 8/16/2012 8/15/2014 8/14/2014 8/16/2014 8/7/2014 8/8/2014 8/13/2013 8/9/2014 8/10/2014 Sampling date Sampling Ecological variables measured during August, 2012–2014 on or within during measured Ecological variables 50 km of tufted pufn (TUPU) colonies in the August, Aleutian Islands and Gulf of Alaska Catch per unit efort (CPUE): number of chick meals collected divided by number of screens set; only calculated for those colonies on which we collected more than collected more 15 chick-meals we those colonies on which calculated for only set; number of screens meals collected divided by per unit efortCatch (CPUE): number of chick on Aiktakof 2013, and 8/20 8/15, 8/19, and on 8/2, 8/6, 8/14, conducted on Buldir Sampling data8/15, 8/16, 8/24, and 8/28 of 2012; 8/3, 8/5, 8/9, 8/12, on the from Alaska Maritime National Gibson Savage Hydroacoustic backscatter (Nautical Area Scattering Coefcient) data from 120 kHz echosounder; data < 25 m Scattering Area Coefcient) data (Nautical 120 kHz echosounder; from backscatter Hydroacoustic in analyses be considered meals to few Too sites abandoned (see “ Materials”) and methods Nest Aiktak Kaligagan Pufn Egg Baby Round Bogoslof Buldir Whip Vsevidof Nizki Chitka Unalga Chagulak Anangula Cathedral Suklik Ugauishak Midun High Little Kiska Sozavarika Peterson

WCA (Western-Central Aleutians) (Western-Central WCA 1 Table - ecore Colonies by gion (west–east) a b c d e Wildlife Refuge, USFWS, Homer, Alaska Homer, USFWS, Refuge, Wildlife EA (Eastern Aleutians) AP (Alaska Peninsula)

1 3 Marine Biology (2018) 165:47 Page 5 of 14 47 collection in 2012 we applied the most recent calibration set- delivered by adults (Table 1). We considered all prey items tings for the EK500 system (2008; Dragoo pers. comm.) to delivered to each screen a chick “meal”, although it is pos- those data. In 2014, we calibrated the EK 60 system prior to sible that an adult could have dropped only a portion of their surveys by suspending a 38.1 mm diameter tungsten carbide bill load at the burrow entrance. Few meals were collected at sphere below each transducer following Foote et al. (1987). Gibson, presumably because of rat predation on pufn eggs Hydroacoustic backscatter from the 120-kHz transducer and chicks; rat feces and urine were present at most burrow was echointegrated into Nautical Area Scattering Coefcient entrances as well as several partially depredated chicks. No (NASC; m2 nmi−2), a proxy for forage fsh biomass, over the meals were collected at the Cathedral colony, as there were water column from 9 m (Vsevidof only, where surface noise few active and accessible nests. Brown bears had destroyed permeated deeper into the water column) or 7 m (all other nesting habitat, as evidenced by extensive sign (trails and colonies) below the surface to 1 m above the seafoor using day beds) across the island and bear scat full of feathers. EchoView ver. 5.4 (Myriax Pty Ltd, Hobart, Tasmania, For all other colonies, chick meals were brought back to the Australia, 2013). This frequency can provide information ship’s lab where prey samples were measured and identifed on smaller organisms including fsh and zooplankton (Sim- to the lowest possible taxon. Prey items were measured indi- monds and MacLennan 2005) that are common in the diets vidually (total length, mm) and total meals were weighed to of seabirds. We applied the background noise removal tool the nearest 0.1 g. For common species, we measured mass using 5 × 5 ping smoothing, a minimum signal to noise ratio of a subsample from each colony, and estimated mass from of 10 (De Robertis and Higginbottom 2007), and a minimum length for remaining fsh using linear regression. threshold of − 80 dB (De Robertis and Cokelet 2012). Data We calculated the number of chick meals delivered per were exported at 100 m horizontal and 25 m vertical bins screen set, which we assumed to represent the catch per to a maximum depth of 225 m, and then averaged by depth unit efort (CPUE) at each colony. We attempted to only strata (< 25, < 50, < 100, and < 225 m) at each colony. set screens at active burrows, although we were unable to determine actual occupancy given time constraints, so CPUE Seabird composition and density at sea estimates are approximate. Chick diet data were summarized by chick-meal rather than individual prey items, and We conducted seabird surveys using standard strip transect frequency (number of prey items), biomass (g), and energy protocols (Tasker et al. 1984; Gould and Forsell 1989) to density (kJ g−1) of prey were used for analyses. We simpli- evaluate seabird density and distribution at sea. Our survey fed diet data by grouping taxa into the 11 most common strip width was 300 m to one side of the ship’s centerline groups for both number and biomass: Atka mackerel (Pleu- (based on visibility) and included birds out to 300 m in front rogrammus monopterygius), capelin (Mallotus villosus), of the vessel. Vessel ground speed was usually ~ 18 km h−1. cephalopod (Cephalopods), euphausiids (Euphausiidae), One observer and one recorder identifed and counted birds greenling (Hexagrammos sp.), Pacifc cod (Gadus macro- on transects. Sightings were recorded using a computer- cephalus), Pacifc sand lance (Ammodytes personatus), pink based system (dLog, R. G. Ford Consulting, Portland, salmon (Oncorhynchus gorbuscha), prowfsh (Zaprora sile- Oregon) that assigned GPS positions to observations in real nus), rockfsh (Sebastes sp.), and walleye pollock (Gadus time. The observer identifed and enumerated all birds on the chalcogrammus). Forage fsh not among those most com- water continuously and conducted snapshot counts of fying mon groups represented < 5% of diet items for both number birds every 60 s at usual ship speed (above). Both counts and biomass and were lumped into an “other” category. The (on water and snapshot counts) were combined to calculate mean energy density delivered to chicks per colony was esti- seabird densities (number of birds km−2). mated by multiplying the mean biomass of the major prey group (listed above) from each island by published energy Chick diet density values for forage fsh (Electronic Supplementary Material) of similar lengths to those in our study. For the We sampled the diets of tufted pufn chicks and measured “other” category of fsh, we used energy density values for chick body size on one day at each colony between 0800 the species representing the greatest biomass within the and 1800 AKDT. To obtain chick meals, we placed wire- “other” category. mesh screens over the entrance of pufn burrows so adults returning with food for chicks could not enter their burrows, Chick condition and subsequently dropped chick-meals at burrow entrances (Hatch and Sanger 1992). We placed screens at several hun- We removed tufted pufn chicks from burrows (Table 1) and dred (where possible) burrow-entrances, left the screens in measured their mass (g) and length of wing chord (mm). place for 2–4 h, and then retrieved all screens and collected Feather growth rate is a relatively fxed function of chick prey items on the fraction of screens at which food had been age (Wehle 1980), so we can use these measurements to

1 3 47 Page 6 of 14 Marine Biology (2018) 165:47 calculate an index of chick condition (Benson et al. 2003). conducted hierarchical clustering on the frst principal com- We considered body condition to be a good proxy for ulti- ponent of these environmental variables (PC1 envALL), used mate reproductive success because poor growth is strongly the clusters as guides for our ecoregion delineation, and then correlated with low success (Gjerdrum et al. 2003). An tested for diferences between ecoregions using ANOVA and index of colony occupancy was calculated by dividing the Tukey’s tests. number of burrows with chicks by the number of burrows checked (Table 1). Forage fsh biomass (hydroacoustic backscatter)

Statistical analyses Prey becomes less accessible to birds beyond their normal diving depth. Alcids are among the deepest diving seabirds, We conducted many analyses on variables that help to char- and tufted pufns are one of the deepest diving alcids with acterize the environment, forage fsh, seabirds at sea, and maximum depth of ~ 130 m, although typical foraging dives chick diets and condition. All the variables and results of all are < 60 m (Piatt and Kitaysky 2002). To determine the analyses are summarized in the Electronic Supplementary depth of forage biomass that best predicted bird densities, we Material. All statistical analyses were conducted using JMP ® conducted ordinary least squares regression (OLS) between ver. 5 statistical software (SAS Institute Inc., Cary, NC the average forage biomass per island at various depth strata 1989–2007) and R ver. 2.15.1 (R Core Development Team). and the average density of pufns and other seabirds around Data were transformed as necessary to meet the assumption colonies. All data were normalized with log transformations. of normality, as detailed below. Levene’s test was used to The at-sea density around colonies of tufted pufns and all assess equality of variance, and we assumed independence birds combined was best explained by the forage biomass between colonies and ecoregions, depending on the test. found at depths of < 25 m (Table 2), and, therefore, this Although in some cases colonies were relatively close to biomass stratum was used for further analyses. We tested each other (e.g. Aiktak and Kaligagan were ~ 5.6 km apart), whether there was a spatial gradient in forage biomass (log- pufns have breeding site fdelity (Piatt and Kitaysky 2002), transformed; < 25 m) against longitude using a regression and nearby seabird colonies have shown diferences in popu- (OLS), and tested for diferences between the Eastern Aleu- lation dynamics attributed to similarly scaled oceanographic tian (EA) and Alaska Peninsula (AP) ecoregions using a Stu- processes (Speckman et al. 2005), suggesting that colonies dent’s t test (Table 1). Chagulak was the only island sampled operate independently even when in close proximity. We in the Western-Central Aleutian ecoregion (WCA) so we considered results to be signifcance with α = 0.05. were unable to conduct a full ecoregion analysis (Table 1). We examined univariate relationships between each Environmental variables environmental variable and forage biomass (log-transformed; < 25 m) at each colony. All environmental vari- We used ArcGIS to calculate average SST and SSS values ables were significantly (p < 0.05) correlated with forage in 3 km2 blocks along spokes centered around each colony biomass (results not shown), so we included all variables ( x̄ = 17 blocks), and then we calculated the average SST in a PCA to calculate the first principal component of and SSS values per colony by computing the mean of all environmental variables from colonies for which for- block values. Prior to analyses, erroneous (outlier) SST val- age biomass data were also collected (PC1 envH; the sub- ues were identifed and eliminated when the water pump script H indicates the availability of hydroacoustic data; was turned of and values were artifcially high; most of those values occurred with the ship was stationary. Errone- Table 2 ous (outlier) SSS values were identifed and eliminated using Regression of the index of forage biomass [hydroacous- ® tic backscatter; nautical area scattering coefcient (NASC)] at proprietary software (SeaBird Wild Edit; frst pass 1 SD, varying depths against all bird, and Tufted Pufn (TUPU) densities second pass 5 SD). (birds km−2) at the sea surface To distinguish ecoregion boundaries across the study Depth of Log density (no. km−2) area, we frst conducted a Principal Components Analysis (PCA) on a correlation matrix of environmental variables Forage biomass index All birds TUPU (SST, SSS, ocean depth, slope, tidal range, and chl-a) meas- (NASC) r2 p r2 p ured at all colonies (with the exception of Buldir, for which Log < 25 m 0.28 0.08 we were lacking SST and SSS data; Table 1). Because units 0.46 0.01 Log < 50 m 0.30 0.06 0.16 0.20 of measurements for the variables difered, we used the cor- Log < 100 m 0.27 0.09 0.23 0.12 relation matrix which standardized variables. SST and tidal Log < 225 m 0.21 0.13 0.14 0.23 range were reciprocally transformed, and ocean depth and slope were log-transformed to normalize the data. We then Results in bold text were signifcant at the p < 0.05 level

1 3 Marine Biology (2018) 165:47 Page 7 of 14 47

Table 1). Ocean depth and slope were log-transformed to Chick diet meet assumptions of normality. Log-transformed forage biomass was regressed (OLS) on the first principal com- Only colonies with > 12 meal deliveries (Table 1) were ponent of environmental variables (PC1envH). included in analyses. We used ANOVA to test for diferences in CPUE at colonies between ecoregions. To assess spatial variation in forage fsh community structure, we Seabird composition and density at sea compared the average composition (% number or biomass of prey groups) of chick diets between ecoregions using In order to simplify the bird community data for analy- perMANOVA. We compared the total number of individu- ses, we grouped species into six categories: puffins, ful- als and biomass (sum total from all prey items), the energy mars, shearwaters, auklets, murres, and all other species. density of forage fsh (log-transformed for normality), and We investigated spatial variability in bird communities the average species richness per colony between ecoregions by comparing the average density of the different bird using ANOVA, and used Tukey’s tests to compare means. groups between ecoregions using permutational multivariate analysis of variance (perMANOVA). Additionally, we Chick condition investigated differences in bird species richness (number of species), log of tufted puffin density, and log of bird Across all colonies and years, all of the chicks had hatched density (all species) between colonies within ecoregions and none were ready to fedge. We included measurements with ANOVA. of live chicks to calculate condition from colonies where To assess the relationship between seabird density sample size was ≥ 12 chicks. We calculated an index of and environmental variables across the entire study chick condition by dividing chick mass (g) by wing chord area, we conducted a PCA on a correlation matrix of all length (mm; Benson et al. 2003), averaged chick condition environmental variables (SST, SSS, ocean depth, slope, per colony, and then compared chick condition (Table 1) tidal range, and chl-a) measured at colonies with seabird between ecoregions using ANOVA. Last, we used OLS densities (Table 1). To normalize the data, SST and tide regression to determine what proportion of variability in were reciprocally transformed and depth was log-trans- chick condition could be explained by environmental vari- formed. We then regressed (OLS) puffin and bird densi- ables, the mean biomass or log-energy density of forage fsh ties on the first principal component for environmental in meals, CPUE (of forage fsh meals on screens), burrow variables (PC1envALL-B; the subscript ALL-B indicates occupancy, or at-sea density of pufns or all birds combined. all colonies with bird data). For those colonies at which we collected forage biomass data, we examined relationships between bird density, environmental variables, and Results forage biomass. We used a PCA of those environmental variables exhibiting significant univariate correlations Environmental variables with log-transformed bird or puffin densities (SSS, SST, tidal range, and chl-a; results not shown), a PCA of the The frst principal component for all environmental variables aforementioned environmental variables plus forage bio- (PC1envALL) measured across the entire study area captured mass, and forage biomass alone. Forage biomass was 65% of the variance in the data, and loadings were simi- log-transformed to normalize the data. We then regressed larly weighted across variables (PCA; Table 3). Hierarchi- (OLS) tufted puffin and all bird log-densities against the cal clustering of PC1envALL identifed three groups: group 1 first principal component for environmental variables included colony islands Savage, Gibson, Nizki, Little Kiska, (PC1 envH-B; the subscript H-B indicates the availability Chitka, Unalga, Whip, and Chagulak, which are all in the of hydroacoustic data and environmental variables corre- western and central Aleutians; group 2 included Round from lated with bird densities), the first principal component of the central Aleutians and Anangula, Vsevidof, Bogoslof, environmental variables plus forage biomass (PC1envHF-B; Baby, Egg, Pufn, Kaligagan, and Aiktak from the eastern the subscript HF-B indicates the availability of hydroa- Aleutians; and group 3 included Peterson, Sozavarika, High, coustic data and environmental variables correlated with Midun, Ugauishak, Suklik, and Cathedral from the Alaska bird data plus forage data), and forage biomass alone. We Peninsula. With the exception of Round, all of the colony tested for differences in PC1 envH-B and PC1 envHF-B between PC1 scores were consistent with simple geographic cluster- ecoregions (EA and AP only) using Student’s t test. ing from west to east. Round is the second colony that we sampled west of Samalga Pass (Fig. 1), and compared to other colonies in the western and central Aleutians group, it has a shallower depth and smaller slope (i.e., characteristics

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Table 3 Loadings of principal components analyses First principal SST SSS Depth Slope Tidal range Chl-a Forage fsh Eigenvalue % variance # colonies components biomass index explained

a b b a PC1envALL 0.40 0.48 0.38 0.37 0.38 − 0.42 3.91 65 24 b b PC1envH 0.46 − 0.48 − 0.34 − 0.33 0.43 0.37 3.79 63 12

PC1envH-B 0.53 − 0.53 0.50 0.44 3.26 81 12 b PC1envHF-B 0.47 − 0.47 0.44 0.40 − 0.45 4.04 81 12 a b a PC1envALL-B 0.40 0.46 0.37 0.40 0.40 − 0.41 4.25 71 21 a Reciprocally transformed for normality b Log-transformed for normality which are more similar to the eastern Aleutian colonies). Round is an outlier for the ecoregion in which it lies, but we chose to group Round with the rest of the western and central Aleutian colonies to simplify analyses and because Samalga Pass is a well-described boundary for marked ecosystem change (Hunt and Stabeno 2005; Piatt and Springer 2007), which warrants using it to demarcate the boundary for the ecoregion groupings indicated in Table 1 (i.e., Western- Central Aleutians, Eastern Aleutians, and Alaska Peninsula). Average PC1envALL scores difered between ecoregions (ANOVA, F (2, 21) = 103.36, p < 0.001), and all ecoregions difered from each other (Tukey’s test, q = 2.52). We found diferences in average SST (Welch’s ANOVA, F (1, 21) = 92.86, p < 0.001) and SSS (Welch’s ANOVA, F (1, 21) = 55.54, p < 0.001) values between the three ecoregions, with strong gradients in temperature [increasing; x̄ Fig. 2 (°C) in WCA = 8.20; EA = 7.83; AP = 13.68] and salinity Response of hydroacoustic backscatter [Nautical Area Scat- x̄ tering Coefcient (NASC)], an index of forage fsh biomass, to the (decreasing; in WCA = 32.94; EA = 32.30; AP = 31.25) sum of variability from multiple environmental factors (PC1 envH; see from west to east. Additionally, there were strong gradients “Materials and methods”) near tufted pufn colonies in the Aleutian in other environmental properties from west (deeper, more Islands and Gulf of Alaska. Colonies are color coded by ecoregion: slope, smaller tides, lower chl-a) to east (shallower, less Western-Central Aleutians (WCA, orange), the Eastern Aleutian colonies (EA, gold), and the Alaska Peninsula colonies (AP, purple) slope, larger tides, higher chl-a).

Forage fsh biomass (hydroacoustic backscatter) Seabird composition and density at sea

There was a strong trend for forage biomass to decrease from We observed a wide range in densities of tufted pufns and 2 west to east (OLS, r = 0.73, F (1, 10) = 26.56, p < 0.001), all birds combined between colonies (Table 1). Whereas corresponding to marked diferences in marine habitats the abundance of six bird taxa groups fuctuated consider- between the EA and AP ecoregions. Forage biomass was sig- ably between colonies (Fig. 3), neither community com- nifcantly greater in the EA than in the AP ecoregion [Stu- position (perMANOVA, F (2, 18) = 1.18, p = 0.282) nor ̄ 2 −2 dent’s t test: t = 4.21, p = 0.002; x (m nmi ) in EA = 2.07; species richness (ANOVA, F (2, 18) = 0.32, p = 0.731) AP = 0.93]. Among colonies for which we measured for- difered signifcantly between ecoregions ( x̄ # species in age biomass, the frst principal component of environmen- WCA = 14.78; EA = 14.60; AP = 13.29). Measured across tal variables (PC1envH) captured 63% of the variance, and the entire study area, PC1 envALL-B captured 71% of the loadings were similarly weighted across variables (PCA; variance in environmental data (PCA; Table 3), but did not Table 3). We found that higher forage biomass was associ- explain variability in either tufted pufn (OLS, r2 = 0.07, F ated with cooler SST, higher SSS, deeper sea foor, steeper (1, 19) = 1.32, p = 0.264) or bird densities (OLS, r 2 = 0.09, slope, lower tide range, and lower chl-a, as indicated by a F (1, 19) = 1.96, p = 0.177). Average tufted pufn densities 2 strong linear relationship to PC1envH (OLS, r = 0.90, F (1, difered marginally [ANOVA, F (2, 18) = 3.11, p = 0.069; 10) = 90.46, p < 0.001; Table 3; Fig. 2).

1 3 Marine Biology (2018) 165:47 Page 9 of 14 47

Fig. 3 The absolute density of diferent bird groups near tufted pufn colonies in the Aleutian Islands and Gulf of Alaska. Colonies are arranged from west to east and Western-Cen- tral Aleutians (WCA), Eastern Aleutians (EA), and Alaska Peninsula (AP) ecoregions are separated by dashed lines

(PC1envHF-B; Table 3; Fig. 4) explained about half the variation in density of tufted pufns (OLS, r2 = 0.50, F (1, 10) = 9.87, p = 0.011; OLS, r2 = 0.47, F (1, 10) = 8.84, p = 0.014, respectively) and all birds (OLS, r2 = 0.50, F (1, 10) = 10.14, p = 0.010; OLS, r2 = 0.53, F (1, 10) = 11.06, p = 0.008, respectively). Higher tufted pufn and bird densities were associated with colder SST, higher SSS, smaller tide ranges, and lower chl-a. Forage biomass alone marginally explained tufted pufn density (OLS, r2 = 0.28, F (1, 10) = 3.87, p = 0.078) and explained slightly less variability in the density of all birds (OLS, r2 = 0.46, F (1, 10) = 8.65, p = 0.015) than PC1envH-B and PC1envHF-B. Chick diet

We collected 1038 chick meals and 6139 prey items across Fig. 4 Response of log-transformed density of tufted pufns (solid circles) and all birds (open circles) to the sum of variability from all sampling sites. The number of meals delivered to chicks multiple environmental factors and hydroacoustic biomass (PC1HF-B; also difered between colonies, leading to high variability of see “Materials and methods”) near tufted pufn colonies in the Aleu- CPUE values (range 0.07–0.29) between colonies (Table 1), tian Islands and Gulf of Alaska although there was no diference in mean CPUE between ecoregions (ANOVA, F (2, 15) = 1.520, p = 0.251; x̄ in Fig. 3; x̄ (birds km−2) in WCA = 1.11; EA = 1.75; WCA = 0.13; EA = 0.19; AP = 0.18). AP = 1.44], and seabird densities did not difer signifcantly The composition (by biomass or number) of forage fsh between ecoregions [ANOVA, F (2, 18) = 0.40, p = 0.673; meals delivered to chicks varied widely between colonies x̄ (birds km−2) in WCA = 2.10; EA = 2.15; AP = 1.92], (Fig. 5) and varied by ecoregion both in terms of biomass although seabird densities varied among sites more in the of prey (perMANOVA, F (2, 17) = 7.60, p < 0.001) and WCA compared to the other ecoregions. In contrast to other number of prey (perMANOVA, F (2, 17) = 7.34, p < 0.001). species, tufted pufns were found in moderate abundance at Dominant prey included Atka mackerel and cephalopods all colony sites, and exhibited the least variability in abun- (primarily squid) in the WCA ecoregion, walleye pollock dance among sites (Fig. 3). in the EA ecoregion, and capelin and Pacifc sand lance at For the subset of colonies with forage biomass data, most colonies in the AP ecoregion (Fig. 5). Diet richness PC1 and PC1 each captured 81% of the vari- difered between ecoregions [ANOVA, F (2, 17) = 5.60, envH-B envHF-B ̄ ance in the environmental data, without or with, respec- p = 0.014; x (# species) in WCA = 6.17; EA = 12.13; tively, forage biomass data included with the environmental AP = 11.00], with fewer species in the WCA than the EA variables (PCA; Table 3). In turn, environmental variables ecoregion (Tukey’s test: q = 2.57). The average biomass F p (PC1 envH-B) and environmental variables plus forage biomass (ANOVA, (2, 17) = 2.02, = 0.163; Table 1) of meals

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Fig. 5 The proportion of distinct forage fsh taxa delivered to tufted pufn chicks in terms of prey biomass (top panel) and the number of prey items (bottom panel) at tufted pufn colonies in the Aleutian Islands and Gulf of Alaska. Colonies are arranged from west to east and Western-Central Aleutians (WCA), Eastern Aleutians (EA), and Alaska Peninsula (AP) ecoregions are separated by dashed lines

delivered to chicks was similar between ecoregions [ x̄ (g) in WCA = 1.18; EA = 1.03; AP = 1.04], but higher num- bers of fsh (mostly young of the year walleye pollock) were delivered to chicks in the EA ecoregion than elsewhere [ANOVA, F (2, 17) = 6.82, p = 0.007, q = 2.57; x̄ (# fsh) in WCA = 4.64; EA = 7.87; AP = 3.62], and the mean energy density of meals delivered to chicks was higher in the WCA and lower in the EA compared to AP ecoregions [ANOVA, F (2, 17) = 3.69, p = 0.047, q = 2.56; x̄ (kJ g−1) in WCA = 1.73; EA = 1.48; AP = 1.60; Table 1].

Chick condition

Fig. 6 We obtained data on chick body condition from 19 of The mean (± SE) body condition of tufted pufn (TUPU) chicks at colonies in the Aleutian Islands and Gulf of Alaska. Colo- 25 colonies (Table 1). The amount of efort necessary to nies are arranged from west to east and Western-Central Aleutians fnd chicks varied greatly between colonies due to difer- (WCA), Eastern Aleutians (EA), and Alaska Peninsula (AP) ecore- ences in burrow depth, density, substrate, and occupancy. gions are separated by dashed lines Although there was some variability in chick condition among individual colonies across the study area (e.g., occupancy, CPUE, meal mass, energy density, or density lower body condition at Bogoslof and Suklik; Fig. 6), over- of pufns or seabirds at-sea) or as multivariate indices of all variability was low (CV = 10.2%) and the mean condi- environmental conditions (frst principal components from tion of chicks did not difer between ecoregions [ANOVA, PCAs) could explain variability in chick condition at the F p x̄ −1 (2, 16) = 0.52, = 0.603; (g mm ) in WCA = 3.92; colony level. EA = 3.89; AP = 4.11]. None of our possible explana- tory variables, tested individually (SST, SSS, tidal range, depth, slope, chl-a, forage biomass, energy density, burrow

1 3 Marine Biology (2018) 165:47 Page 11 of 14 47

Discussion (PC1envALL-B), which itself difered between ecoregions. This suggests that environmental factors may infuence We delineated three marine ecoregions in our study area, seabird communities diferently between ecoregions, or demarcated by Unimak and Samalga passes, and based seabirds may be infuenced by factors that we did not on spatial variability in environmental variables. These measure, or by parameters unrelated to marine habitat. ecoregion boundaries have been described by previous For example, seabird distribution and densities at sea may studies (Hunt and Stabeno 2005; Piatt and Springer 2007). have been confounded by factors such as nesting habitat In contrast to Piatt and Springer (2007), however, we did availability, or the distribution of predators currently or not fnd an ecoregion boundary at Amchika Pass that could in the past (Byrd et al. 2005). Seabirds are particularly be used to diferentiate the Central Aleutians. The west sensitive to introduced mammalian predators such as Arc- to east increase in SST, decrease in SSS, and increase in tic fox (Vulpes lagopus) and Norway rat (Rattus norvegi- chl-a that we observed were consistent with other stud- cus), which severely reduced populations of ground and ies and likely driven by the diferent source waters and burrow-nesting seabirds in the Aleutians and along the AP, mixing regimes among ecoregions (Ladd et al. 2005a, and played an important role in changing the distribution c; Mordy et al. 2005). The stable surface waters of the and size of colonies (Bailey 1993; Byrd et al. 2005). We Alaska Coastal Current fow along the shelf to the east observed evidence of recent top-down efects of terrestrial of Samalga Pass and have high net primary production, predators on nesting colonies. The once large (ca. 10,000 whereas the Alaska Stream to the west has turbulent mix- birds; USFWS 2008) pufn colony on Cathedral Island, ing in the passes and iron defcits that limit primary pro- which is within easy swimming distance (~ 1 km) for duction around the islands (Ladd et al. 2005a, c; Mordy brown bears (Ursus arctos) from Kodiak Island (Paetkau et al. 2005). These persistent spatial patterns result from et al. 1998), had been destroyed by bears and abandoned relatively permanent large-scale topographic and oceano- by pufns by mid-August. Brown bear presence and pre- graphic features described above, and generally outweigh dation was noted by bear trails, day beds, excavated bur- temporal variability on annual time scales (Hunt and Sta- rows, and bear scats containing pufn bones and feathers beno 2005; Speckman et al. 2005). at the colony, and the density of seabirds around Cathedral These geographic gradients in habitat characteristics Island was the lowest of all colonies. On Gibson Island in have a similarly strong structuring efect on upper trophic the far western Aleutians, the odor of rat urine permeated levels of food webs across the study area (see also Loger- the colony, and we found many predated eggs and chick well et al. 2005; Sydeman et al. 2017; Piatt et al. 2018). carcasses. Predation by invasive rats likely hastened aban- We detected structure in environmental gradients, forage donment of the colony and reduced survival of remaining biomass, and bird densities across ecoregions. For the birds. colonies with hydroacoustic biomass data, both indices of Forage fsh communities difered considerably between environmental variability without and with forage biomass ecoregions as indicated from the composition of the tufted included as a habitat parameter (PC1envH-B and PC1envHF-B, pufn diets that we sampled. Pelagic Atka mackerel and respectively) explained a signifcant proportion (47–53%) shelf-edge cephalopods were the prevalent prey items deliv- of the variability in at-sea densities of both tufted pufns ered to chicks in the WCA, which was characterized by small and all seabirds combined. Moreover, our forage biomass shelves and deeper depths, whereas the bulk of chick diets index exhibited a strong decreasing gradient from west in the EA, with its more extensive shelf habitat, were young to east (just west of the EA to the AP), and the index of of the year walleye pollock. Catch of age-1 walleye pollock environmental variability (PC1envH) explained 94% of the in the Gulf of Alaska indicated that recruitment in 2012 variance in forage biomass among colonies. These results (the year we sampled the EA) was the highest it has been suggest that the abundance of both forage fsh and sea- since 2006 (Dorn et al. 2015). Pufn diets can show vari- birds is strongly infuenced by bottom up processes in this ation in composition over time, however prey composition region, as suggested by others (Coyle 2005; Sinclair et al. has been shown to be more variable over space than time 2005), and for other regions of Alaska (Abookire and Piatt (Sydeman et al. 2017). For example, gadids, like pollock 2005; Renner et al. 2012; Arimitsu et al. 2016). have been an important prey item in pufn diets in the EA In contrast to the structure observed at the ecoregional since monitoring began in the mid 1980s, although sand spatial scale (above), seabird community composition, lance eclipsed pollock as the dominant prey for a period in bird species richness, and the density of tufted pufns the late 1990s and early 2000s (Sydeman et al. 2017). Pufn (or all seabirds) did not vary across ecoregions. Nor was diets were more stable across other sites, however, with sand tufted pufn or seabird log-density signifcantly correlated lance dominating prey at the Semidi Islands (along the AP) with the index of environmental conditions at all colonies in all sample years (1979–1995), and squid and hexagram- mids (primarily Atka mackerel) dominating pufn diets in

1 3 47 Page 12 of 14 Marine Biology (2018) 165:47 the western Aleutians for decades (1988–2012; Sydeman constrained by basic physical and biological factors (e.g., et al. 2017). Diets of other common marine predators, Steller prey dispersion and quality) in their ability to exploit prey sea lions (Eumetopias jubatus; data from 1976 to 2001) and resources (Piatt 1990; Cury et al. 2011), some species have adult Pacifc cod (data from 1980 to 2003), were similarly a capacity to adjust foraging behavior so that they can mini- dominated by walleye pollock in the EA and Atka mackerel mize variation in their own body condition, and that of their and squid in the WCA (Logerwell et al. 2005; Sinclair et al. chick’s, despite considerable variability in local food sup- 2005). We observed more varied tufted pufn diets along plies (Piatt et al. 2007). Similarly, tufted pufns in our study the AP, with capelin and sand lance in higher abundance, appeared to adjust foraging behavior to bufer against local and it was the only region where we observed salmon. This diferences in prey abundance and quality. Consequently, ecoregion had warmer, fresher water, more standing stock they were able to raise healthy chicks in good body condition of chlorophyll, and more tidal infuence. across a wide range of environmental conditions, and high Forage fsh species richness was lower in WCA versus the growth rates and body mass at fedging usually translate into EA, a pattern matched again in diets of Steller sea lions and high reproductive success (Gjerdrum et al. 2003). Despite adult Pacifc cod where fsh species richness increased from this compensation in the number of prey items delivered, west to east in the Aleutians (Logerwell et al. 2005; Sinclair the average energy density of prey was ~ 17% lower in the et al. 2005). Likewise, predator diet diversity was greater in EA than in the WCA (Table 4). We were unable to measure the EA, where passes are shallower compared with deeper chick feeding delivery rates per day, which typically range passes to the west (Sinclair et al. 2005). Although nutrient from 2 to 6 meals day−1 (Piatt and Kitaysky 2002), but we levels were higher in western passes, primary productivity suspect that adults in the EA may have delivered more meals was lower (Mordy et al. 2005). Iron limitation and mixing per day to compensate for lower prey quality. These behavio- of phytoplankton below the euphotic zone may be the rea- ral adaptations allow great fexibility for successful foraging son for the lower primary productivity observed in western and chick provisioning under diferent environmental and passes of the Aleutians (Mordy et al. 2005), and those difer- prey conditions. Other life history traits likely contributed ence in productivity may translate into lower fsh diversity. to the foraging and reproductive success of tufted pufns The condition of tufted pufn chicks was similar across we observed, including their deep diving ability (allowing colonies and ecoregions and was not correlated with any access to a wider prey base), their ability to deliver multiple of the environmental variables or multivariate indices we prey items to chicks simultaneously, and their strategy of measured. Likewise, there was no diference in the average raising chicks in protective burrows to full independence at biomass of meals delivered to tufted pufn chicks despite the colony (Piatt and Kitaysky 2002). geographical diferences in environmental variables, rela- Despite their apparent behavioral fexibility, tufted puf- tive prey abundance, and forage fsh community composition fns are not impervious to food stress or reproductive failure. between ecoregions. In the EA, where small low-lipid wall- At the edges of their range tufted pufns are not thriving eye pollock were the dominant prey, chicks were fed a larger (Piatt and Kitaysky 2002). In Washington, tufted pufns are number of prey items than in the other two ecoregions, where thought to have undergone an order of magnitude decline in fewer large and/or lipid-rich fsh (e.g., prowfsh, salmon, and the past few decades, leading to listing as “threatened” by capelin along the AP, or Atka mackerel and cephalopods in the state (Hanson and Wiles 2015). In our study, however, the WCA) were delivered (Table 4). Although seabirds are tufted pufns were successful in producing healthy chicks across a large geographic range with difering environmental conditions and food webs, which we attribute to their dietary Table 4 Summary of diferences in tufted pufn chick meals and fexibility and the diversity of forage fsh available to them environments between the Western-Central Aleutians (WCA), East- in the North Pacifc Ocean. Where seabirds rely on just a ern Aleutians (EA), and Alaska Peninsula (AP) ecoregions few forage species, such as in the Benguela and Humboldt WCA EA AP currents [where most seabirds feed heavily on sardines (Sar- dinops sagax) and anchovy (Engraulis encrasicolus; Cury ↓ prey richness et al. 2000)], or the North Sea [where many seabirds rely ↑ # prey heavily on lesser sandeels (Ammodytes marinus; Frederiksen ↑ prey energy ↓ prey energy et al. 2005)], they are far more vulnerable to the boom and Atka mackerel, Walleye pollock Capelin, sand cephalopods lance bust fuctuations in prey populations (Cury et al. 2000, 2011; Saline, ↑ chl-a, deep, Variables between Fresher, warmer Frederiksen et al. 2005; Robinson et al. 2015). Conversely, steep WCA and AP water, shallow tufted pufns are extremely fexible foragers known to con- sume a wide variety of prey taxa in the North Pacifc (e.g. this study; Piatt and Kitaysky 2002; Sydeman et al. 2017), and prey switching bufers the efects of high variability in

1 3 Marine Biology (2018) 165:47 Page 13 of 14 47 the abundance of any one prey species. In summary, dietary Byrd VG, Renner HM, Renner M (2005) Distribution patterns and and behavioral fexibility may be the key to the overall suc- population trends of breeding seabirds in the Aleutian Islands. Fish Oceanogr 14:139–159 cess of tufted pufns, and likely contributes to their wide Coyle KO (2005) Zooplankton distribution, abundance and biomass distribution (greater than any other breeding seabird) across relative to water masses in eastern and central Aleutian Island the northern North Pacifc Ocean (Piatt and Kitaysky 2002; passes. Fish Oceanogr 14:77–92 Drew et al. 2015). Cury PM, Bakun A, Crawford RJM, Jarre A, Quiñones R, Shannon L, Verheye H (2000) Small pelagics in upwelling systems: pat- Acknowledgements terns of interaction and structural changes in “wasp-waist” eco- This work was funded by the US Geological Sur- systems. ICES J Mar Sci 57:603–618. https://doi.org/10.1006/ vey (USGS), Ecosystems Mission Area, and the Landscape Conserva- jmsc.2000.0712 tion Cooperative (LCC) program of both USGS and the US Fish and Cury PM, Boyd IL, Bonhommeau S, Anker-Nilssen T, Crawford RJM, Wildlife Service (USFWS). The USFWS Alaska Maritime National Furness RW, Mills JA, Murphy E, Osterblom H, Paleczny M, Wildlife Refuge (AMNWR) and the Aleutian and Bering Sea Islands Piatt JF, Roux JP, Shannon L, Sydeman WJ (2011) Global seabird LCC also provided fnancial and logistic support. We are grateful responses to forage fsh depletion—one-third for the birds. Sci- to AMNWR personnel Steve Delehanty, Jef Williams, and Heather ence 334:1703–1706 Renner for program support and for the use of data from Aiktak and Ti ĝ la x̂ De Robertis A, Cokelet ED (2012) Distribution of fsh and macro- Buldir, and to Captain William Pepper and crew of the R/V zooplankton in ice-covered and open-water areas of the eastern for outstanding logistic support in the Aleutians. Additional advice Bering Sea. Deep Sea Res Part II 65–70:217–229. https://doi. and support was provided by Vernon Byrd, Scott Hatch, Lisa Spitler, org/10.1016/j.dsr2.2012.02.005 and Bill Sydeman. We are especially grateful to those who joined us De Robertis A, Higginbottom I (2007) A post-processing technique to in the feld work and contributed to our data collection: Josh Adams, estimate the signal-to-noise ratio and remove echosounder back- Allison Anholt, Amanda Gladics, Keith Hobson, Kelli Johnson, For- ground noise. ICES J Mar Sci 64:1282–1291 rest Piatt, Barry Sampson, Jane Sullivan, and Ajay Varma. Any use of Dorn M, Aydin K, Jones D, McCarthy A, Palsson W, Spalinger K trade, frm or product names is for descriptive purposes only and does (2015) Chapter 1: assessment of the walleye pollock stock in the not constitute endorsement by the US government. The fndings and Gulf of Alaska. In: NPFMC Gulf of Alaska SAFE Report. Alaska conclusions in this article are those of the author(s) and do not neces- Fisheries Science Center, Seattle sarily represent the views of the US Fish and Wildlife Service, but Drew GS, Piatt JF, Renner M (2015) User’s guide to the North Pacifc do represent the views of the US Geological Survey. All capture and Pelagic Seabird Database 2.0. US Geological Survey Open-File handling procedures were reviewed and approved by the US Geologi- Report 2015-1123, Anchorage, Alaska. https://doi.org/10.3133/ cal Survey Alaska Science Center Animal Care and Use Committee ofr20151123 (report). https://doi.org/10.5066/f7wq01t3 (number 2013-04). (database) Foote KG, Knudsen HP, Vestnes G, MacLennan D, Simmonds E (1987) Compliance with ethical standards Calibration of acoustic instruments for fsh density estimation: a practical guide. ICES Cooperative Research Report, Copenhagen Conflict of interest The authors declare that they have no confict of Frederiksen M, Wright PJ, Harris MP, Mavor RA, Heubeck M, Wanless Rissa tridactyla interest. S (2005) Regional patterns of kittiwake ( ) breeding success are related to variability in sandeel recruitment. Mar Ethical approval All applicable international, national, and/or institu- Ecol Prog Ser 300:201–211. https://doi.org/10.3354/meps3 00201 tional guidelines for the care and use of animals were followed. Gjerdrum CA, Vallée MJ, St. Clair CC, Bertram DF, Ryder JL (2003) Tufted pufn reproduction reveals ocean climate variability. Ecol- ogy 100:9377–9382 Gladics AJ, Suryan RM, Parrish JK, Horton CA, Daly EA, Peterson WT (2015) Environmental drivers and reproductive consequences References of variation in the diet of a marine predator. J Mar Syst 146:72–81. https://doi.org/10.1016/j.jmarsys.2014.06.015 Abookire AA, Piatt JF (2005) Oceanographic conditions structure Gould PJ, Forsell DJ (1989) Techniques for shipboard surveys of forage fshes into lipid-rich and lipid-poor communities in lower marine birds. US Fish and Wildlife Service Technical Report 25, Cook Inlet, Alaska, USA. Mar Ecol Prog Ser 287:229–240 Washington, DC Ainley DG, Nettleship DN, Carter HR, Storey AE (2002) Common Hanson T, Wiles GJ (2015) Washington state status report for the tufted murre (Uria aalge). In: Rodewald PG (ed) The birds of North pufn. Washington Department of Fish and Wildlife, Olympia, America online. Cornell Lab of Ornithology, New York. https:// p 62 doi.org/10.2173/bna.666 Harris MP, Bogdanova MI, Daunt F, Wanless S (2012) Using GPS Ainley DG, Adams P, Jahncke J (2014) Towards ecosystem based- technology to assess feeding areas of Atlantic Pufns (Frater- fshery management in the California current system—predators cula arctica). Ring Migr 27:43–49. https://doi.org/10.1080/03078 and the preyscape: a workshop. Point Blue Conservation Science, 698.2012.691247 Petaluma Hatch SA, Sanger G (1992) Pufns as samplers of juvenile walleye Arimitsu ML, Piatt JF, Mueter F (2016) Infuence of glacier runof on pollock (Gadus chalcogrammus) and other forage fsh in the Gulf ecosystem structure in Gulf of Alaska fords. Mar Ecol Prog Ser of Alaska. Mar Ecol Prog Ser 80:1–14 560:19–40. https://doi.org/10.3354/meps11888 Hunt GL, Stabeno PJ (2005) Oceanography and ecology of the Aleu- Bailey EP (1993) Introduction of foxes to Aleutian Islands: history, tian Archipelago: spatial and temporal variation. Fish Oceanogr efects on avifauna, and eradication. US Fish and Wildlife Service 14:292–306 Resource Publication 193, pp 1–53 Jahncke J, Coyle KO, Hunt GL (2005) Seabird distribution, abundance Benson J, Suryan RM, Piatt JF (2003) Assessing chick growth from a and diets in the central and eastern Aleutian Islands. Fish Ocean- single visit to a seabird colony. Mar Ornithol 31:181–184 ogr 14:160–177

1 3 47 Page 14 of 14 Marine Biology (2018) 165:47

Kitayksy AS, Hunt GL Jr, Flint EN, Rubega MA, Decker MB (2000) Robben Island penguin colony. ICES J Mar Sci 72:1822–1833. Resource allocation in breeding seabirds: responses to fuctuations https://doi.org/10.1093/icesjms/fsv035 in their food supply. Mar Ecol Prog Ser 206:196–283 Schreiber EA, Burger J (2001) Biology of marine birds. CRC Press, Lack D (1968) Ecological adaptations for breeding in birds. Methuen, Boca Raton London Simmonds E, MacLennan D (2005) Fisheries acoustics: theory and Ladd C, Hunt GL, Mordy CW, Salo SA, Stabeno PJ (2005a) Marine practice, 2nd edn. Blackwell Science, Ames environment of the eastern and central Aleutian Islands. Fish Sinclair EH, Moore SE, Friday NA, Zeppelin TK, Waite JM (2005) Oceanogr 14:22–38 Do patterns of Steller sea lion (Eumetopias jubatus) diet, popula- Ladd C, Jahncke J, Hunt GL, Coyle KO, Stabeno PJ (2005b) Hydro- tion trend and cetacean occurrence refect oceanographic domains graphic features and seabird foraging in Aleutian passes. Fish from the Alaska Peninsula to the central Aleutian Islands? Fish Oceanogr 14:178–195 Oceanogr 14:223–242 Ladd C, Stabeno P, Cokelet ED (2005c) A note on cross-shelf exchange Speckman SG, Piatt JF, Minte-Vera CV, Parrish JK (2005) Parallel in the northern Gulf of Alaska. Deep Sea Res Part II 52:667–679 structure among environmental gradients and three trophic lev- Logerwell EA, Aydin K, Barbeaux S, Brown E, Conners ME, Lowe S, els in a subarctic estuary. Prog Oceanogr 66:25–65. https://doi. McDermott S, Orr J, Ortiz I, Reuter R, Spencer P, Thompson G org/10.1016/j.pocean.2005.04.001 (2005) Geographic patterns in the ichthyofauna of the Aleutian Stabeno PJ, Hristova HG (2014) Observations of the Alaskan Stream Islands. Fish Oceanogr 14:93–112 near Samalga Pass and its connection to the Bering Sea: 2001– Mordy CW, Stabeno PJ, Ladd C, Zeeman S, Wisegarver DP, Salo SA, 2004. Deep Sea Res I 88:30–46 Hunt GL (2005) Nutrients and primary production along the east- Stabeno PJ, Bond NA, Hermann AJ, Kachel NB, Mordy CW, Overland ern Aleutian Island Archipelago. Fish Oceanogr 14:55–76. https JE (2004) Meteorology and oceanography of the northern Gulf of ://doi.org/10.1111/j.1365-2419.2005.00364.x Alaska. Cont Shelf Res 24:859–897 Paetkau D, Shields GF, Strobeck C (1998) Gene fow between insu- Stabeno PJ, Ladd C, Reed RK (2009) Observations of the Aleutian lar, coastal and interior populations of brown bears in Alaska. North Slope Current, Bering Sea, 1996–2001. J Geophys Res Mol Ecol 7:1283–1292. https://doi.org/10.1046/j.1365- 114:C05015. https://doi.org/10.1029/2007JC004705 294x.1998.00440.x Stabeno PJ, Bell S, Cheng W, Danielson S, Kachel NB, Mordy CW Piatt JF (1990) Aggregative response of common murres (Uria aalge) (2016) Long-term observations of Alaska Coastal Current in the and Atlantic pufns (Fratercula arctica) to their prey. Stud Avian northern Gulf of Alaska. Deep Sea Res II 132:24–40. https://doi. Biol 14:36–51 org/10.1016/j.dsr2.2015.12.016 Piatt JF, Kitaysky AS (2002) Tufted pufn (Fratercula cirrhata). In: Sydeman WJ, Piatt JF, Thompson SA, García-Reyes M, Hatch SA, Poole A (ed) The birds of North America online. Cornell Lab of Arimitsu ML, Slater L, Williams JC, Rojek NA, Zador SG, Ren- Ornithology, New York. https://doi.org/10.2173/bna.708 ner HM (2017) Pufns reveal contrasting relationships between Piatt JF, Springer AM (2007) Marine ecoregions of Alaska. In: Spies R forage fsh and ocean climate in the North Pacifc. Fish Oceanogr (ed) Long-term ecological change in the northern Gulf of Alaska. 26:379–395. https://doi.org/10.1111/fog.12204 Elsevier, Amsterdam, pp 522–526 Tasker ML, Jones PH, Dixon T, Blake BF (1984) Counting seabirds at Piatt JF, Harding A, Shultz M, Speckman SG, van Pelt TI, Drew GS, sea from ships: a review of methods employed and a suggestion Kettle A (2007) Seabirds as indicators of marine food supplies: for a standardized approach. Auk 101:567–577 Cairns revisited. Mar Ecol Prog Ser 352:221–234. https://doi. USFWS, US Fish and Wildlife Service (2008) North Pacifc seabird org/10.3354/meps07078 colony database, interactive map service. US Fish and Wildlife Piatt JF, Arimitsu MA, Sydeman WJ, Thompson SA, Renner H, Zador Service, Anchorage. https://www.fws.gov/alaska/mbsp/mbm/ S, Douglas D, Hatch SA, Kettle A, Williams JC (2018) Biogeog- northpaci f cseabirds /colon ies/defau lt.htm . Accessed 18 Jun 2016 raphy of pelagic food webs in the North Pacifc. Fish Oceanogr Wehle DHS (1980) The breeding biology of the pufns: Tufted Puf- (in press) fn (Lunda cirrhata), Horned Pufn (Fratercula corniculata), Renner M, Arimitsu ML, Piatt JF (2012) Structure of marine predator Common Pufn (F. arctica), and Rhinoceros Auklet (Cerorhinca and prey communities along environmental gradients in a glaci- monocerata). Dissertation, University of Alaska, Fairbanks ated ford. Can J Fish Aquat Sci 69:2029–2045 Robinson WML, Butterworth DS, Plaganyi EE (2015) Quantifying the projected impact of the South African sardine fshery on the

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