Vol. 612: 193–208, 2019 MARINE ECOLOGY PROGRESS SERIES Published March 7 https://doi.org/10.3354/meps12877 Mar Ecol Prog Ser

Physical and ecological factors explain the distribution of Weddell seals during the breeding season

Michelle A. LaRue1,*, Leo Salas2, Nadav Nur2, David G. Ainley3, Sharon Stammerjohn4, Luke Barrington5, Kostas Stamatiou6, Jean Pennycook3, Melissa Dozier6, Jon Saints6, Hitomi Nakamura7

1Department of Earth Sciences, University of Minnesota, Minneapolis, MN 55455, USA 2Point Blue Conservation Science, Petaluma, CA 94954, USA 3H. T. Harvey and Associates Ecological Consultants, Los Gatos, California 95032, USA 4Institute of Arctic and Alpine Research, University of Colorado-Boulder, Boulder, CO 80303, USA 5Google, Mountain View, CA 94043, USA 6DigitalGlobe, Inc., Westminster, CO 80234, USA 7Polar Geospatial Center, University of Minnesota, St. Paul, MN 55108, USA

ABSTRACT: Weddell seal Leptonychotes weddellii populations can potentially serve as indicators of change in food web structure, but tracking populations at regional to continen- tal scales has so far been impossible. Here, we combined citizen science with remote sensing to learn about environmental and biological factors that explain fine-scale distribution of Weddell seal haul-outs in the Ross Sea, . We employed the crowd-sourcing platform Tomnod (DigitalGlobe) to host high-resolution (~0.5−0.6 m) satellite imagery of the Antarctic fast ice dur- ing November in 2010 and 2011 and asked volunteers to identify seals on images. We created a 5 km × 5 km grid of seal presence per year, and modeled habitat suitability for seals using a gen- eralized linear model. The top Ross Sea-wide model that best explained seal presence included proximity to fast-ice cracks, deep water, and emperor penguin Aptenodytes forsteri colonies. This model also revealed that seal presence decreased with proximity to Adélie penguin Pygoscelis adeliae colonies and size of the nearest emperor penguin colony, suggesting the potential for trophic competitive exclusion by large penguin colonies. With respect to 3 sub-regions within the Ross Sea (North and South in the western Ross Sea, and in the east), we found that 3 habitat variables differed in their effects among sub-regions: proximity to emperor penguin colonies, proximity to deep water, and relative ice width. Our results represent a step toward effectively monitoring Weddell seal population trends, and disentangling biological and environmental factors influencing locations of Weddell seal haul-outs around Antarctica.

KEY WORDS: Leptonychotes weddellii · Antarctica · Citizen science · Generalized linear model · High-resolution satellite imagery · Trophic interaction · Tomnod

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1. INTRODUCTION adaptations to cope with such variability (Laws 1964; see also Siniff et al. 2008). Fast ice (ice ‘fas- The Antarctic sea ice zone is especially dynamic tened’ to the Antarctic coastline) occurs mostly both seasonally and inter-annually, and Weddell where the coastline is sheltered from strong winds seals Leptonychotes weddellii have developed or currents, and is an extremely limited habitat geo-

*Corresponding author: [email protected] © Inter-Research 2019 · www.int-res.com 194 Mar Ecol Prog Ser 612: 193–208, 2019

graphically (in some cases, also temporally), but 2011, Ainley et al. 2015a). Given that the diet of Weddell seals show unique adaptations for using it Weddell seals depends on the commercially impor- (summarized by Siniff et al. 2008, Southwell et al. tant Antarctic toothfish (Ponganis & Stockard 2007, 2012), such as breath-holding capacity that allows Ainley & Siniff 2009, Salas et al. 2017) and silverfish the use of tide cracks many kilometers away from (one of the principal forage fish in coastal Antarctic open water. Hence, Weddell seals may be among waters; La Mesa & Eastman 2012), the ability to the most vulnerable species to climate change (Siniff assess population size and distribution of Weddell et al. 2008) because fast-ice prevalence is sensitive seals at regional scales may render the species a to changes in temperature and strength and persist- reliable indicator of ocean health, and thus a target ence of wind (Massom et al. 2009, Ainley et al. 2010, of the Convention for the Conservation of Antarctic Fraser et al. 2012, Nihashi & Ohshima 2015, Kim et Marine Living Resources (CCAMLR) Ecosystem Moni- al. 2018). As climate models predict continued win- toring Program (CEMP; www.ccamlr.org) and/or the ter warming and increasing winds, Weddell seal incipient Research and Monitoring Program for the habitat will likely continue to shrink and could alter Ross Sea Region Marine Protected Area (Dunn et al. the distribution and abundance of Weddell seals 2017). (Siniff et al. 2008). Given recent dramatic swings in Herein we investigated the distribution of Weddell Antarctic climate, describing the baseline distribu- seals in the Ross Sea using a combination of VHR, tion of Weddell seals is particularly important and citizen science, and crowd-sourcing. Based on seal time sensitive (Ainley et al. 2010, Turner & Comiso presence/absence data derived from searches con- 2017). ducted by the crowd of citizen scientists and an The natural history, physiology, and demography expert, we sought to understand the environmental of Weddell seals of the Ross Sea’s Erebus Bay have and biological variables that explain locations of been studied for nearly 50 yr (Stirling 1969b, Weddell seal haul-outs (5 km spatial scale). We chose Cameron & Siniff 2004, Chambert et al. 2015); how- to study Weddell seals during the November pup- ever, very limited information exists for other popula- ping season, when the species is most concentrated tions of this species (e.g. Lindsey 1937, Stirling 1969c, on fast ice (Stirling 1971). We compared the predic- Ainley et al. 2015a). Enumerating seal populations tive relationships among 3 sub-regions: the north- beyond the local level (Southwell et al. 2004, 2012) is west, southwest, and eastern portions of the Ross difficult due to logistical challenges associated with Sea. These sub-regions differ in several parameters surveying fast ice zones. During the 1960−1980s, var- that are potentially of great importance to the Wed- ious regional attempts were made to estimate seal dell seals, as the southwest sub-region is entirely on populations in pack-ice habitat, relate those numbers the continental shelf, while the northwestern and to physical factors such as ice floe characteristics, and eastern sub-regions have both shelf and continental then produce a density estimate to extrapolate to slope waters. larger areas (e.g. Erickson et al. 1971, Gilbert & We evaluated the hypothesis that physical factors Erickson 1977, Erickson & Hanson 1990). That work such as cracks constrain the presence of reproductive made use of strip censuses from ice breakers, helicop- females. Other factors (such as proximity and size of ters, or fixed-wing aircraft, which are logistically com- penguin colonies) could be an additional constraint plex (e.g. Bengtson et al. 2011, Forcada et al. 2012, via competition or niche partitioning, or may reflect a Southwell et al. 2012). As a result, the regional distri- preference if similar habitat features attract compet- butions of colonies and their habitat features are not ing species. In that regard, Adélie penguins Pygoscelis well understood, especially in areas far from major adeliae prefer immediate proximity to open water research facilities (e.g. Lake et al. 2008, Ainley et al. (Ainley 2002), in contrast to emperor penguins Apten- 2015a). odytes forsteri that prefer fast ice (Burns & Kooyman More recently, monitoring of Antarctic ice-obligate 2001). Under a ‘constraint’ hypothesis, physical vari- species has been attempted through remote sensing ables would be more important than the ecological (Weddell seals: LaRue et al. 2011; penguins: Fret - variables. We hypothesized that physical and oceano - well et al. 2012, LaRue et al. 2014, Lynch & LaRue graphic variables, such as cracks in the ice and prox- 2014). Because Weddell seals are dark and large imity to shore, would be the primary factors in ex- (400−600 kg, 1.5 × 3−4 m), very high-resolution plaining seal presence, and be consistently important (VHR) satellite imagery has been used to quantify across sub-regions, while ecological effects would be their distribution and numbers even in the most less important and more variable in their influence remote sections of the Antarctic coast (LaRue et al. among sub-regions. LaRue et al.: Weddell seal breeding distribution 195

2. MATERIALS AND METHODS square and others are long swaths of images ~15 km wide; from the Polar Geospatial Center) for Novem- 2.1. Study area ber 2010 and 2011 over the Landsat Image Mosaic of Antarctica basemap (Bindschadler et al. 2008). Dur- We focused our research along the coast of the Ross ing November, Weddell seals are the only seals pres- Sea (Fig. 1), the most productive region in the South- ent in coastal fast-ice areas (Smith 1965, Stirling ern Ocean (Arrigo et al. 1998, 1999), characterized by 1969b, Rotella et al. 2009). Note that there are small high-salinity Ross Sea shelf water that overlies the concentrations of non-breeding individuals, which continental shelf and upper slope (Smith et al. 2014). we cannot distinguish from the breeders, and pups The Ross Sea is covered by sea ice (mostly pack ice) are too small to be detectable on VHR in November for most of the year, except for the large or persistent (LaRue et al. 2011). We extracted image extents for polynyas located in front of the Ross Ice Shelf and in consideration using several criteria: existence of fast Terra Nova Bay and McMurdo Sound, with other ice, <20% cloud cover, panchromatic (i.e. black and smaller more ephemeral polynyas located over Pen- white), high quality (not over-exposed or striped), nell Bank and in the Ross Passage (see Jacobs & and of lowest off-nadir angle (the angle at which an Comiso 1989, Arrigo et al. 2015, Ni hashi & Ohshima image is acquired as the satellite passes over any 2015). Other areas, such as parts of southern Mc - given area; directly overhead would be 0° off-nadir). Murdo Sound, are covered by fast ice for most of Our search excluded areas such as gradually sloped every year (Kim et al. 2018). beaches, which are rare in the Ross Sea, as well as areas of steep topography, including areas in fronts of ice shelves, which are too steep for seal access. For 2.2. Geospatial data preparation the few beach areas that exist along the Ross Sea coastline (e.g. around Ross Island), seals are not To determine smaller, demarcated areas of interest found there during the pupping season. (AOIs) suitable for searching by citizen scientists via With the smaller subset of image extents, we then the crowd-sourcing platform Tomnod (www.tomnod delineated AOIs based on areas with known loca- com/; DigitalGlobe), we first overlaid the geospatial tions of seals (n = 18) and areas where seals had not image extents (called a ‘footprint,’ which can range been recorded previously (n = 18) along the coastline in size from ~300 to >1000 km, as some images are of the Ross Sea (Siniff & Ainley 2009). Search areas

Fig. 1. Grids (5 km × 5 km; red outline, n = 356) searched for Weddell seals within the Ross Sea, Antarctica, and 3 sub-regions within the Ross Sea used for analysis: (A) Eastern Ross Sea, (B) Western Ross Sea South, and (C) Western Ross Sea North 196 Mar Ecol Prog Ser 612: 193–208, 2019

ranged from 3.7−325 km2 in size (Table 1), as we Landsat 7 (up to 15 m resolution) from the NASA found it important to keep them small enough to Earth Data website (earthdata.nasa.gov; earthex- maintain citizen interest and search efficiency. Size plorer.usgs.gov) acquired during November 2010 of AOIs was also dependent on the extent of fast ice. and 2011. We provided the catalog ID (unique identifier for each VHR) and shapefile AOI data to Tomnod, which hosted the citizen science search. Citizen scientists 2.3. Citizen science search and were asked to tag any seals apparent in the image detection of seal haul-outs using a set of tutorials and instructions (see Supple- ment 1 at www. int-res. com/articles/ suppl/m612p193 Knowing that we can reliably detect Weddell seals _ supp .pdf). We also delineated the fast ice extent by on VHR (LaRue et al. 2011, Ainley et al. 2015a), we using Moderate Resolution Imaging Spectroradiome- recruited citizens to search available and suitable ter (MODIS; 250 m resolution, acquired daily) and images (spatial resolution ~0.3−0.6 m; DigitalGlobe) via the crowd-sourcing platform Tomnod. We soli - Table 1. Sizes and locations of areas of interest (AOIs, in al- cited volunteers through Tomnod’s email distribution phabetical order), for searching for Weddell seals in the Ross list (>1 million addresses), the social media sites Sea via the crowd-sourcing platform Tomnod. We also noted Facebook and Twitter, kindergarten to grade 12 whether each AOI had previously been known to have seals present or not. Known locations derived from Siniff & Ainley classrooms, and SciStarter (scistarter.com), which is (2008) an online hub for informal research projects. We pro- vided citizen scientists with a set of instructions Colony Area (km2) Known location? about how to identify and tag seals on the imagery, using online tools provided on the Tomnod website Adare Peninsula 47.5 No (Fig. 2). Data regarding maps searched and seal Bay of Whales 176.7 No presence were recorded and stored by Tomnod in a Borchgrevink Glacier 46.7 No Butter Point 78.4 Yes Postgres database, exported as CSV and geojson Campbell Glacier 21.9 Yes files, and converted to geospatial shapefiles and 325.0 No databases within ArcGIS 10.4. To ensure quality and Cape McCormick 32.2 No accuracy of citizen scientist acquired data, we used Cape Phillips 33.4 No Tomnod’s CrowdRank (CR) algorithm to identify Cape Reynolds 55.0 Yes Cape Roberts 51.7 Yes features in the imagery tagged as seals to inform the 28.3 Yes statistical estimation of seal presence or absence in 50.4 No images (Barrington et al. 2011; see Supplement 2). Cape Wheatstone 35.9 Yes Coulman Island 23.1 No Dunlop Island 99.0 Yes Edisto Inlet 20.5 Yes 2.4. Determining presence and absence Edmondson Point 54.7 Yes Erebus Bay 124.4 Yes We then used the Geospatial Modeling Environ- Fenwick Ice Piedmont 25.1 No Franklin Island 3.7 No ment to create a grid of 5 km × 5 km cells as a single Granite Harbor 43.3 Yes GIS polygon shapefile covering the entirety of the Hallet Peninsula 39.0 No Ross Sea. We selected 5 km as our grid cell size due 24.1 Yes to the approximate distances between haul-out loca- Lewis Bay 48.8 Yes tions within well-studied Erebus Bay, such that each Marble Point 52.2 Yes Mariner Glacier 96.6 No grid cell contains 1−2 of these known haul-out loca- Moubray Bay 31.7 Yes tions (see LaRue et al. 2011 for haul-out locations Mount Armitage 56.3 Yes within Erebus Bay). We believe the 5 km × 5 km cell Mount Joyce 56.3 Yes size would capture any important microhabitat dif- Nordenskjold 38.4 Yes Possession Island 17.7 No ferences, without generating potentially erroneous Robertson Bay 55.7 Yes results that could occur if the grid cell sizes were too Suter Glacier 133.3 No small, or the potential for including irrelevant details Sven Foyn Island 11.6 No if the grid cell sizes were too large. We loaded the Tinker Glacier 112.3 No Tripp Ice Tongue 65.8 No grid shapefile into ArcGIS 10.4 and extracted 356 Wood Point 19.8 No grid cells that were assigned a 0 (absence) or 1 (pres- ence) based on detections by the citizen scientist LaRue et al.: Weddell seal breeding distribution 197

Fig. 2. Screenshot from the active campaign to ‘tag’ seals in the Ross Sea using very high resolution satellite imagery via Tomnod (www.tomnod.com). Weddell seals resting on the fast ice can be seen as black dots in the middle of the image, with a tide crack running diagonally from the iceberg (at the top of the screenshot) toward the bottom left corner

(18%) or senior author (50%) or both (32%). For each negative. We evaluated 15 candidate variables that grid cell, we also recorded a large set of covariates we believed would help explain seal presence along (Table 2). Cell distances to each feature shapefile the Ross Sea coast. The justifications and hypotheses were conducted using the ‘Near’ tool within ArcTool- with respect to each variable included in our models box, and represent the closest distance from the edge (summarized in Table 2) are as follows: of each grid cell to a point shapefile representing an (1) Presence of cracks (CRACK). We hypothesized environmental variable. that locations of breeding seals will be associated with cracks in the fast ice. Weddell seals rely on sea- sonally persistent fast ice, but need to have constant 2.5. Statistical analyses and hypotheses ocean access to feed and teach their pups to swim. The presence of cracks was determined by viewing We used the statistical software R (R Core Team the high-resolution satellite imagery. 2017) to run logistic regression models to determine (2) AOIs (TOMNODAOI). This variable accounts the most effective set of environmental covariates to for our pre-selection of areas known to have breed- explain seal presence/absence in the 25 km2 grid ing seals in the past (n = 18) relative to areas not cells. The variables we examined can be divided into known to have seals (n = 18; Siniff & Ainley 2008). 4 categories of hypotheses to explain differences in (3) Expert search (EXPSEARCH). Given that fast probability of seal presence: those reflecting who ice, and therefore seal presence, may have been analyzed the image (TOMNODAOI, EXP SEARCH; more extensive than delineated in the AOIs, we man- see Table 2), annual differences (YEAR), those eval- ually searched 268 grid cells that covered areas of uating possible ecological interactions (LGNEAR_ potential habitat not provided to Tomnod partici- ADPE, LGDI_ADPE), and those evaluating the ef - pants. We also inspected AOIs that were provided to fects of the physical environment (all other variables, the participants where no features were tagged. Be - e.g. CRACK, MIN_DEPTH, SLOPE, ICE WIDTH). We cause the expert search deliberately targeted areas interpret our results with respect to whether they that were not searched by the crowd as well as spe- indicate preference for certain environmental condi- cific areas for which the crowd identified no features tions or reflect constraints imposed by the environ- (i.e. seals), we included this variable to account for ment or the species’ life history. lower probability of seal presence in areas searched by All distances were natural log-transformed prior to the expert. model fitting; we added a constant before log-trans- (4) Year (YEAR). We evaluated the hypothesis that forming so that all log distance values were non- presence of breeding seals in the Ross Sea at the spa- 198 Mar Ecol Prog Ser 612: 193–208, 2019

tial scale of 5 km grid cells varies between years. Seal abundance at the local scale can vary by year depending on environmental con- ditions, as per ‘extreme environ- mental perturbations’(Chambert et al. 2015). ambert et al. (2015) (5) Minimum depth (MIN_ DEPTH). Goetz et al. (2017) Fretwell et al. (2014) Fuiman et al. (2002)

Siniff & Ainley (2008) Siniff & Ainley (2008) We hypothesized that the probabil- NA

Stirling (1969a,b,c) ity of seal presence increases with increasing depth. Ocean depth in-

NA fluences foraging behavior in Wed- nd 2011. Literature cited column refers dell seals, as prey are associated with certain features and depths within the water column (Fuiman et al. 2002, Goetz et al. 2015). (6) Distance to deep water (LGDI_ DEEP). We hypothesized that the presence of breeding seals would be associated with proximity to deep water (≥300 m; Davis et al.

without known seal presence). 2003), as it reflects access to more diverse and abundant prey, and a Lynch & LaRue (2014) Lynch e

s Literature cited greater ability to forage efficiently ce

nearest emperor penguin colony because of (Goetz 2015, Goetz et al. 2017). (7) Slope (SLOPE). We hypothe- sized that Weddell seal presence of the nearest Adélie penguin colony because of would be greater in proximity to because of trophic competition Ainley et al. (2015b) of fast ice requirements, OR seals are farther from em- peror penguin colonies because of trophic competition searched by expert NA due to differences in ice conditions Chambert et al. (2015) bathymetric contour Fuiman et al. (2007) tropic competition Fretwell et al. (2014) trophic competition Ainley et al. (2015b) areas with steep bathymetric slopes. Goetz (2015) reported that Weddell Fretwell et al. (2012); d seals disproportionately selected for underwater canyons and troughs, where sub-surface currents are stronger and where benthic, filter- feeding communities are richer (Barry et al. 2003). (8) Width of fast ice (ICEWIDTH). We hypothesized that seal pres- ence would be higher in areas with Bindschadler et al. (2008); c moderate ice width (the perpendi- cular distance from the shore to the edge of the ice). Fast ice is required as a platform to remain out of the ocean and protected from preda-

Binomial indicating the presence of cracks in Seal presence is associated with cracks in Binomial indicating if the cell was searched on Seal presence reflects choice of area of interest Binomial to identify cells searched by expert Seal presence lower in areas selected to be of image acquisition (2010 or 2011)Year Seal presence probability differs among years Minimum bathymetric depth (m) within grid cell Seal presence is associated with deep waters Ln(distance to <250 m bathymetric contours, m) Seal presence is in proximity to 250 m bathymetric slope (m) within grid cellAverage Seal presence is associated with steep bathymetry Perpendicular distance from edge of continent to Seal presence is associated with moderate widths Ch Ln(distance to shore, including coastal islands Seal presence is more likely closer to the shoreline Ln(distance to coastal glacier/ice tongue, km) Seal presence is more likely closer to outlet glaciers Ln(size of nearest emperor penguin colony, Seals are less likely to be found with increased size breedingLn(size of nearest Adélie penguin colony, Seals are less likely to be found with increased size tors (i.e. killer whales Orcinus orca; to the justification for hypotheses, whereas the source refers to the source of the data for analysis. NA: not available Arndt et al. (2013); b d

e Pitman & Durban 2010, Ainley et al. Ln(ratio of distance to edge/ice width) Seal presence is highest at optimal ice widths a a c Ln(distance to nearest km) emperor penguin colony, Seals are located closer to emperor penguins because a

Ln(distance to nearest Adélie penguin colony, km) Ln(distance to nearest Adélie penguin colony, Seals are located farther from Adélie penguin colonies 2017a), but too much distance be- b c a a b a tween cracks and open water may a

b make cracks unreachable (seals this study; a a can hold their breath for ~75 min; Kooyman 1981). Thus, we hypo - thesized an optimal ice width, such Covariate Definition Hypothesi

fast ice within grid cell the fast i by citizen scientists Tomnod (18 with and 18 edge of fast ice each year of fast ice and offshore Beaufort & Franklin Islands) breeding pairs) of the pairs) 10 LGDI_SHORE 2 TOMNODAOI 3 EXPSEARCH 9 LG_ICERATIO Sources: 15 LGDI_ADPE 6 LGDI_DEEP 11 LGDI_GLAC 4 YEAR 5 MIN_DEPTH 7 SLOPE 8 ICEWIDTH 12 LGNEAR_EMPE 13 LGNEAR_ADPE 14 LGDI_EMPE 1 CRACK

Table 2. List of covariates considered Seals in the Ross Sea during November 2010 a Table for modeling habitat suitability of Weddell that too little ice would provide LaRue et al.: Weddell seal breeding distribution 199

inadequate protection, while too extensive ice would the presence of nearby emperor penguin colonies is preclude access to cracks (i.e. cracks beyond seal indicative of conditions that are favorable to both breath-holding ability). Weddell seals and penguins, as both require stable (9) Ratio of distance to ice edge/ice width (LG_ fast ice for their breeding cycle. The location of ICERATIO). Because seals are found on fast ice of emperor penguin colonies in the Ross Sea appears to different widths, we hypothesized that what matters be stable (e.g. Barber-Meyer et al. 2008), although in is that the cracks are present at a certain proportional 2016, the emperor penguin colony (instead of absolute) distance to the ice edge, after disappeared and apparently moved to accounting for the effect of ice width (i.e. after ac - (D.G. Ainley pers. obs.). Clearly, fast ice capable of counting for the presence of a minimum ice width). supporting emperor penguin colonies would be sta- (10) Distance to shore (LGDI_SHORE). We hypoth- ble enough to provide habitat for Weddell seals, and esized that Weddell seal presence would be greater therefore we considered proximity of an emperor closer to the shoreline, based on previous personal penguin colony a proxy for stable fast ice. Under this experience (LaRue et al. 2011, Ainley et al. 2015a), hypothesis, we expected the likelihood of breeding aerial surveys (Siniff & Ainley 2009), and historic ac- Weddell seals to decrease with increasing distance to counts (Stirling 1969b,c). When fast ice meets the the closest emperor penguin colony. However, under shore, be it continental or insular (or ice tongues and the trophic competition hypothesis (see no. 12 above), large grounded icebergs), it causes tidal cracks that we would expect Weddell seal presence to be more provide access to/from the ocean, and proximity to likely as distance to the nearest emperor penguin the shore is inherently as far from the ice edge as colony increases. The empirical, statistical relation- possible given the location. ship between distance to the nearest emperor colony (11) Distance to glacier tongues (LGDI_GLAC). We and Weddell seal presence, whether negative or hypothesized that Weddell seal presence would be positive, respectively, would provide support to 1 of more likely closer to glacier tongues. Pressure via the 2 hypotheses, or may fail to support either glacier tongues against the fast ice leads to tidal hypothesis. cracks, leeward refuge from strong katabatic winds, (15) Distance to nearest Adélie penguin colony and a feature to which fast ice can adhere. (LGDI_ADPE). Under the trophic competition hypo - (12 & 13) Population sizes of emperor (LGNEAR_ thesis (see no. 13 above), we predicted the probabil- EMPE) and Adélie penguin colonies (LGNEAR_ ity of Weddell seal presence to increase with increas- ADPE), both log-transformed. We hypothesized that ing distance to the nearest Adélie penguin colony. At the presence of Weddell seals would be inversely the same time, extensive sea ice (fast or consolidated correlated with increasing population size of em - pack ice) is problematic for Adélie penguins (Ainley peror and Adélie penguin colonies. Weddell seals 2002), in contrast to emperor penguins. Proximity to and the 2 penguins eat similar prey, especially Adélie colonies is not indicative of conditions neces- Antarctic silverfish. Moreover, both the seals and sary or favorable to breeding Weddell seals. Thus, emperor penguins are capable of deep dives to we evaluated the prediction of a positive relationship exploit a similar habitat volume (the seals slightly between Weddell seal presence and distance to the deeper, maximum dive is ~800 m; Burns & Kooyman nearest Adélie penguin colony, rather than the inter- 2001). During November, both the seals and Adélie play between positive and negative influences, as is penguins are central place foragers, and both species expected for emperor penguin colonies. For each demonstrate intraspecific competition that results in penguin species, we additionally evaluated the reduced prey availability (cf. Testa et al. 1985, Ainley hypothesis that there is a statistical interaction be - et al. 2015b). Moreover, under the assumption of tween penguin colony size and distance to the near- trophic competition, we expected the negative rela- est seal presence. tionship of seal presence and penguin colony size to Our first step in analysis was to develop the basic be stronger among Adélie penguins compared to logistic regression model that predicts Weddell seal emperor penguins because the largest Ross Sea probability of presence. The model was constructed Adélie colonies are an order of magnitude greater with a stepwise procedure that used the Bayesian than the largest emperor colonies (cf. Fretwell et al. Information Criterion (BIC, penalty = log(N)) to de - 2012, Lynch & LaRue 2014). termine the inclusion/exclusion of any variable into (14) Distance to nearest emperor penguin colony the model. We opted to use BIC for the stepwise (LGDI_EMPE). Here we evaluated 2 hypotheses with analysis because it results in the most parsimonious contrasting predictions. The first hypothesis is that explanatory model. Akaike’s information criterion (AIC) 200 Mar Ecol Prog Ser 612: 193–208, 2019

maximizes predictive ability of a model, but it is more seals present was similar between years (2010: 41%; likely to include extraneous covariates (Aho et al. 2011: 40%). 2014). Since our objective was a model that included We established that if seals were present in an all variables needed to explain variation in seal image (as verified by expert inspection), users invari- presence, but excluded irrelevant variables, we used ably identified them. Thus, we assumed that when no BIC. We evaluated goodness-of-fit with the Hosmer- seals were identified, seals were absent with 100% Lemeshow test (Hosmer et al. 2013) and then ex- probability. Expert review of >21 000 search areas plored the use of quadratics to improve the fit for all also inspected by the crowd, from the Ross Sea and relevant covariates. We first analyzed the effect of all elsewhere in Antarctica, found this assumption to candidate variables across the Ross Sea, while statis- hold true for all but 3 areas (i.e. 99.987% of maps; tically controlling for differences among the 3 sub- unpubl. data). We also assumed that when 1 or sev- regions that we had identified a priori: (1) the Eastern eral features were identified in an image, seals were Ross Sea (ERS, which included Cape Colbeck, Marie present. It is likely that this assumption is wrong in Byrd Land, and the Bay of Whales, eastern Ross Ice some cases, as there may be seal-sized rocks or other Shelf); (2) the Western Ross Sea North (WRSN, which non-seal items (e.g. melt holes) in an image that the included coastal areas north of the Drygalski Ice volunteers may have tagged. However, after expert Tongue); and (3) the Western Ross Sea South (WRSS, inspection, we expect this error to be relatively small which included areas to the south of the Drygal - (<5%) and the assumption to be reasonable. ski Ice Tongue, around to the eastern Ross Ice Shelf; In the preferred model characterizing the relation- Fig. 1). ship between seal presence and habitat variables, 6 For each of the physical and ecological variables of the 8 candidate physical variables and 2 of the 4 identified in our Ross Sea-wide model, we then candidate ecological variables were retained (as well examined whether the effect of that variable differed as additional interactions as described below). Based among the 3 sub-regions by testing for the statistical on the BIC criterion and model coefficient signifi- interaction of sub-region and the relevant covariate. cance values, the model described in Table 3 had the By comparing the Ross Sea-wide model to the model best support from the data. We first briefly describe with sub-region-specific effects, we identified those the effects of the individual variables, and then fur- variables that varied in their effects across the Ross ther below we discuss the modeled relations, as esti- Sea. mated across all sub-regions or allowing for effects to To quantify the effects of covariates among the 3 vary among sub-regions. sub-regions, we examined partial dependence plots. AOIs (TOMNODAOI) had a strong positive effect These were generated by using the span of values in (p < 0.0001), while expert search had a strong nega- the data for a parameter and holding all other para - tive effect (p < 0.0001; Table 3). The latter thus indi- meters constant at their global mean value, and pre- cates that seals were less likely to be found in areas dicting presence probability for each Ross Sea not previously known to host them, and in areas region. All R analysis code and data are found in where the citizen scientists did not search for them. the following GitHub repository: https://github.com/ The top model also revealed a strong inter-annual leosalas/WeddellSeal_SOS. effect, with higher probabilities of detecting seals in 2011 vs. 2010, once all other variables were ac- counted for (p < 0.001). Probability of seal presence 3. RESULTS was explained strongly by the presence of cracks (p < 0.0001) across the Ross Sea, ranging from probabili- We involved >5000 citizen scientists over the ties of ~55−65% where fast-ice cracks were apparent course of 54 d in our Tomnod image search of the to 20−55% where no cracks were evident. Therefore, coastal Ross Sea. Volunteers searched 43 images on presence of cracks was the strongest of all physical or average 5 times to ensure images were searched in ecological variables. their entirety. During 2010, a total area of 17 799 km2 Three other physical variables also contributed to of fast ice was available, and the crowd searched the presence of seals: qualities of the fast ice beyond within 230 grid cells (5750 km2); in 2011, an area of mere presence; proximity of the fast ice to the 22 070 km2 of fast ice was available as potential Wed- anchoring shore; and proximity to deep water. Seals dell seal habitat, and the crowd searched 304 grid prefer fast ice cracks near shores, including edges of cells (7600 km2). Fast ice extent was greater in 2011 glaciers and, where fast ice is suitable, seals were than in 2010, although the proportion of cells with found relatively close to the fast-ice edge. At the LaRue et al.: Weddell seal breeding distribution 201

Table 3. Results of the top logistic regression model testing the effects of physical and biotic variables on the location of Wed- dell seal pupping colonies in the Ross Sea (model deviance = 303.6, df = 16, p < 0.0001; Hosmer-Lemeshow GOF test: 11.202, df = 8, p = 0.191); see Table 2 for the variable definitions. Base level for ‘Region’ is the Western Ross Sea South. Results are sorted by explained deviance, comparing the full model to a reduced model that omits each of the covariates one at the time

Variable Estimate SE z Pr(>|z|) Deviance explained

Intercept −2157.036 611.295 −3.529 0.0004 CRACK 2.511 0.341 7.359 <0.0001 104.948 TOMNODAOI 2.709 0.382 7.085 <0.0001 98.498 EXPSEARCH −2.432 0.408 −5.955 <0.0001 76.433 LGDI_GLAC −0.471 0.123 −3.820 0.0001 49.571 LGNEAR_EMPE 3.682 2.422 1.520 0.1284 LGNEAR_EMPE2 −0.273 0.143 −1.906 0.0567 47.945a YEAR 1.067 0.304 3.508 0.0005 47.331 LGDI_SHORE2 −0.250 0.091 −2.745 0.0060 44.543 RegionERS 1.915 0.922 2.077 0.0378 RegionWRSN 1.842 0.882 2.089 0.0367 41.898b LGICEWIDTH 0.546 0.208 2.628 0.0086 41.336 LGDI_DEEP 0.708 0.276 2.568 0.0102 LGDI_DEEP2 −0.162 0.063 −2.574 0.0101 40.855c LGDI_ADPE2 0.078 0.034 2.316 0.0206 39.577 LGICE_RATIO −0.170 0.078 −2.180 0.0292 38.858 LGDI_EMPE −0.227 0.118 −1.924 0.0544 37.925 aLikelihood ratio test of significance of linear + quadratic form of LGNEAR_EMPE to the model, chi-squared = 13.888, df = 2, p = 0.0010 bDeviance explained by the additive regional effects cLikelihood ratio test of significance of linear + quadratic form of LGDI_DEEP to the model, chi-squared = 6.798, df = 2, p = 0.0334

same time, they are more likely found in areas with substantially, from ~90 to near 0%, as distance to the wider fast ice. Also, seal presence reflects locations shore increased from 1 to ~100 km (Fig. 3A, p = proximate to deep water, peaking at an intermediate 0.006). Distance to glacier tongues had a highly sig- value, as discussed below. Probability of seal pres- nificant effect as well (Fig. 3C, p < 0.001), and change ence increased with closer proximity to the nearest in distance from a glacier tongue from ~5 to 150 km emperor penguin colony, consistent with the hypoth- changed the probability from ~70 to ~25%. Distance esis that proximity to an emperor colony is a proxy for to Adélie penguin colonies also showed a significant stable and predictable fast ice. In contrast to proxim- effect (Fig. 3B, p < 0.05) on seal presence: the ity to the nearest emperor penguin colony, the other likelihood of seal presence increased in a quadratic, 2 biological variables included in the model indi- accelerating function from 20% when the penguin cated the effects of trophic competition: the probabil- colonies were adjacent to the cell, to over 90% as dis- ity of seal presence decreased as the size of the near- tance from the cell increased to >250 km. Fast-ice est emperor colony increased and as distance to the width had a significant positive effect (Fig. 3D, p < nearest Adélie penguin colony decreased. 0.01): as fast-ice width increased from <1 to 50 km, predicted probability of seal presence increased from 20 to 70%. Lastly, the probability of seal presence 3.1. Ross Sea-wide effects was significantly higher if the size of the nearest emperor penguin colony was smaller (Fig. 3E, p < Our top model explaining seal presence in the Ross 0.005). The drop in probability in relation to emperor Sea, considering the effects of habitat variables esti- penguin colony size followed a quadratic shape, such mated across all sub-regions, included effects of dis- that if the colony size increased 10-fold from 2200 to tance to shore, distance to glacier tongue, and dis- 22 000 individuals, it caused a drop in seal presence tance to colonies of both penguin species (Table 3: probability from 60 to 20%. Neither the size of the model deviance: 303.6, df = 16, p < 0.0001; Hosmer- nearest Adélie penguin colony, nor slope nor depth Lemeshow goodness-of-fit test: 11.202, df = 8, p = of bathymetry, showed an overall significant effect in 0.191). Predicted probability of seal presence varied predicting seal presence. 202 Mar Ecol Prog Ser 612: 193–208, 2019

and WRSN, respectively). The effect of dis- tance to emperor penguin colonies also varied by region (Fig. 4). Although overall, the effect was a moderate linear decrease in probability of seal presence as the dis- tance to the emperor penguin colony in - creased, the effect was significantly stronger in the ERS (p = 0.01). The top model also includes differences among regions with regard to the effect of propor- tional distance from the cell to the fast ice edge (Fig. 4). In the case of the ERS, seal presence declined most steeply as the proportional distance to the edge of the fast ice increased. In the WRSN, on the other hand, seal presence decreased very slightly with regard to the proportional dis- tance to the ice edge. Finally, in the WRSS, Fig. 3. Estimated probability of the presence of Weddell seals in 5 km × the effect of proportional distance to the 5 km cells in the Ross Sea during November 2010 and 2011 from general- fast ice edge was intermediate (Fig. 4C). ized linear modeling in relation to: (A) log(distance to shore), (B) log(dis- tance to nearest Adélie penguin [ADPE] colony), (C) log(distance to near- While the slope for WRSS is not signifi- est glacier tongue), (D) log(width of fast ice), and (E) log(size of nearest cantly different from the slopes for ERS emperor penguin [EMPE] colony). Shading indicates ±1 SE of the estimate and WRSN, that the preferred model (by BIC) includes an interaction by region for this variable indicates differences among 3.2. Region-specific effects

We then evaluated which variables dif- fered in their effects among the sub- regions of the Ross Sea. Our top model identified 3 variables whose effects dif- fered among sub-regions: proximity to deep water (i.e. <300 m depth), distance to emperor penguin colonies, and propor- tional distance from the cell to fast ice edge (Fig. 4, Table 4: model deviance: 337.65, df = 21, p < 0.001; Hosmer- Lemeshow test: 9.607, df = 8, p = 0.294). Proximity to deep water displayed a sig- nificant quadratic relationship, such that the probability of presence was highest at an intermediate distance to deep waters (linear and quadratic terms each signifi- cant in the Ross Sea-wide model, p = 0.010, Table 3); however, where the peak occurred in the statistical distribution var- ied by region (Fig. 4). For the ERS, the peak was at 0 km (i.e. the minimum dis- tance), for WRSN the peak was at 4 km, Fig. 4. Estimated probability of the presence of breeding female Weddell and for WRSS the peak was at 16 km; the seals in 5 km × 5 km cells in the Ross Sea during 2010 and 2011 via general- ized linear modeling in relation to region (Eastern Ross Sea, and Western difference in location of the peak among Ross Sea North and South) and 3 interacting covariates (distances to regions was significant (p < 0.05 and p < edge/ice width, deep water, and emperor penguin [EMPE] colony). Shad- 0.001, for comparison of WRSS with ERS ing indicates ±1 SE of the estimate LaRue et al.: Weddell seal breeding distribution 203

Table 4. Results of the top logistic regression model testing the effects of physical and biotic variables on the location of Wed- dell seal pupping colonies in the Ross Sea, considering the effects of regions (ERS: Eastern Ross Sea, WRSN: Western Ross Sea North, reference region [base level]: Western Ross Sea South) (model deviance: 337.65; df = 21, p < 0.0001; Hosmer-Lemeshow GOF test: 9.607, df = 8, p = 0.294); see Table 2 for the variable definitions. Results are sorted by explained deviance, comparing the full model to a reduced model that omits each of the covariates one at the time.

Variable Estimate SE z Pr(>|z|) Deviance explained

Intercept −2603.094 678.456 −3.837 0.0001 TOMNODAOI 2.868 0.414 6.924 <0.0001 64.350 CRACK 2.446 0.368 6.651 <0.0001 56.762 EXPSEARCH −2.522 0.433 −5.827 <0.0001 41.023 LGDI_DEEP – WRSS 1.186 0.307 3.867 0.0001 32.314a RegionERS × LGDI_DEEP −5.467 2.236 −2.445 0.0145 RegionWRSN × LGDI_DEEP −0.520 0.154 −3.368 0.0008 LGDI_EMPE – WRSS −0.123 0.575 −0.214 0.8307 20.098b RegionERS × LGDI_EMPE −6.304 2.498 −2.523 0.0116 RegionWRSN × LGDI_EMPE 0.032 0.603 0.053 0.9574 RegionERS 37.034 13.508 2.742 0.0061 19.301c RegionWRSN 1.576 2.512 0.627 0.5304 YEAR 1.296 0.338 3.839 0.0001 16.360 LGDI_SHORE2 −0.332 0.103 −3.216 0.0013 12.667 LGNEAR_EMPE2 −0.057 0.018 −3.158 0.0016 10.484 LGDI_DEEP2 −0.210 0.067 −3.143 0.0017 10.082 LGICE_RATIO – WRSS −0.355 0.260 −1.366 0.1721 9.190d RegionERS × LGICE_RATIO −0.554 0.484 −1.145 0.2523 RegionWRSN × LGICE_RATIO 0.323 0.269 1.200 0.2301 LGDI_ADPE2 0.103 0.035 2.960 0.0031 9.048 LGDI_GLAC −0.431 0.149 −2.887 0.0039 8.836 LGICEWIDTH 0.556 0.225 2.473 0.0134 6.408 aDeviance explained by the interaction between LGDI_DEEP and region (2 df, p = 0.0018) bDeviance explained by the interaction between LGDI_EMPE and region (2 df, p = 0.0001) cDeviance explained by the additive regional effects (2 df, p < 0.0001) dDeviance explained by the interaction between LGICE_RATIO and region (2 df, p = 0.053) sub-regions in the effect of relative distance to the no cracks was substantially lower (about 20%). Thus, fast-ice edge. for the ERS and WRSN, the presence of a visible The WRSS also differed in that the probability of crack more than doubled the probability of seal pres- seal presence was ~50% within grid cells containing ence, whereas in the WRSS, the difference was only no visible cracks compared to >70% in cells with vis- a relative increase of about 40%. ible cracks (Fig. 5), in contrast to the other 2 sub- regions in which the probability of seals in cells with 4. DISCUSSION

We describe for the first time the environmental factors that help explain the presence of Weddell seal haul-outs during the pupping season in the Ross Sea region. Herein, we provide an efficient framework for large-scale assessments of their habitat and, ulti- mately, indices of populations through time at a full range of geographic scales.

4.1. Factors affecting seal haul-out presence

Fig. 5. Probability of the presence of breeding Weddell seals in relation to the presence of cracks in the fast-ice habitat in 3 The most important factor describing the presence sub-regions of the Ross Sea. Cracks in the fast ice were as - of Weddell seals during the breeding season was the sociated with greater probability of seal presence (p < 0.0001) presence of cracks in fast ice (Table 3). Nursing 204 Mar Ecol Prog Ser 612: 193–208, 2019

mothers need to access the ocean and rest on the ice (Table 4). Indeed, we found a greater probability of in order to raise their young during austral spring seal presence significantly closer to emperor penguins (Stirling 1971; see also Kooyman 1981), so we were only in ERS − distance to colony was not a significant not surprised that the presence of cracks was a strong effect in either section of the WRS − but the quadratic predictor of seal presence. Importantly, however, we effect of size of the nearby emperor penguin colony found that not all grid cells containing cracks con- was significant across all sub-regions. This is an tained seals, indicating that crack presence alone is important finding for 2 reasons: first, such nuance not enough for predicting and understanding habitat between models indicates that when scaling up to a for Weddell seals. continent-wide habitat model for Weddell seals, Perhaps one of the most interesting results of our maintaining fine-scale detail within regional modeling models is the apparent nuance in probability of seal may be required. Second, if we assume that close presence as it pertains to distance and size of penguin proximity to emperor penguins represents a surrogate colonies. Starting with the top regional model (Table for fast-ice stability, perhaps what we have uncovered 3), we found an effect of distance to emperor penguin here is a trade-off: there is some spatial overlap be- colonies (marginally significant, p = 0.0544), and also tween penguins and seals because both species re- an effect of the size of the nearest emperor penguin quire fast ice (Stonehouse 1953, Stirling 1969b,c, colony—a result that likely indicates association with Burns & Kooyman 2001), but large, concentrated the quality/annual longevity of fast-ice habitat. Like numbers of emperor penguins may competitively ex- Weddell seals, emperor penguins require fast ice for a clude seals. This may be due to interspecific competi- major aspect of their life cycle as they return to areas tion, given that both species are deep divers and can of fast ice each winter to breed and raise young thus access similar prey (Goetz 2015, Goetz et al. 2018). (Stonehouse 1953, 1975). Emperor penguins are par- Emperor penguins are not the only potential com- ticularly sensitive to fast-ice conditions, as they re- petitors of Weddell seals in the Ross Sea, as seal pres- quire a breeding platform for a longer time than the ence was lower near large concentrations of Adélie seals (3 mo for the seals, 8 mo for the penguins; Stone- penguins (Table 4). Weddell seals and penguins prey house 1953, Burns & Kooyman 2001). Indeed, Fretwell heavily on Antarctic silverfish, although Weddell et al. (2014) found that in years of relatively poor seals and emperor penguins can dive much deeper fast-ice conditions during the onset of winter, a few than Adélie penguins (cf. Goetz 2015, Ainley et al. emperor penguin colonies relocated to the nearest 2017b, Goetz et al. 2018). There are millions of glacier or ice shelf. Where persistent fast ice has dis- Adélie penguins contained within 34 colonies in the appeared entirely, Weddell seals have decreased sig- Ross Sea (Lynch & LaRue 2014), but only ~150 000 nificantly (Siniff et al. 2008) as have emperor penguin emperor penguins in 6 colonies (Barber-Meyer et al. colonies (Trathan et al. 2011). In that regard, Thomas 2008, Fretwell et al. 2012), making the sheer number & Demaster (1983) found that Weddell seal pup sur- of Adélie penguins that may be competing with vival was highest with more stable fast ice during Weddell seals at least an order of magnitude greater weaning; Cornet & Jouventin (1980) found 45% mor- than competition with emperor penguins. The forag- tality in seal pups at Pointe Géologie during years of ing areas of the large Adélie colonies negatively early break-up of fast ice; and a few studies have influence adjacent and smaller Adélie colonies (Ain- noted that greater fast-ice extent negatively influences ley et al. 1995). We therefore suggest that not only do population size in Erebus Bay (Cameron & Siniff 2004, the largest colonies of Adélie penguins competitively Chambert et al. 2015). In the context of a habitat opti- exclude Weddell seals from their foraging range but mum and given that Weddell seals rely on annual fast that, conversely, seals and emperor penguins can ice as a platform, we would expect stability, quality, coexist, to some degree, due both to their need for and duration to be important for habitat selection, stable fast ice and lower, more dispersed populations. and an important driver in the evolution of their life These results support the very close coupling appar- history. Note that multiyear fast ice can have a nega- ent in the trophic relationships of all Ross Sea meso- tive effect on seal presence (Siniff et al. 2008, Cham- predators (Ainley 2007). bert et al. 2012). Thus, close proximity to emperor We also found that seals were present near deep penguins would make sense, if for no other reason waters (>300 m), though to varying effect depending than as a proxy for annual fast-ice stability. on sub-region (Table 4). Indeed, the population of Upon separating the Ross Sea into 3 subsections, seals within Erebus Bay has been consistently pres- more detail arose regarding the relationship be- ent since it was first visited and exploited by explor- tween seal presence and nearby emperor penguins ers in the early 1900s (Stirling 1969a), and is adjacent LaRue et al.: Weddell seal breeding distribution 205

to deep water unlike locations on the opposite, conti- cells were inspected in 2011 and not in 2010, and 44 nental side of McMurdo Sound (Arndt et al. 2013). of these were found to be occupied (35%). Mean- Proximity to deep areas allows a greater exploitable while, 52 cells were only inspected in 2010 and only volume of water in which the 2 prey species most 13 of these were occupied (25%). Therefore, our important in the lactating seal diet (Antarctic silver- results of an increased probability of seals present in fish and toothfish) are found, which are virtually the a cell in 2011 may simply reflect a sampling bias. The only fish in the water column of the Ross Sea shelf availability of cells for inspection in one year and not (Eastman 1985). There are plenty of benthic fish spe- in the other was due to the pictures not being taken. cies, of lower energy density (Lenky et al. 2012), but The bias was caused by cells available for inspection these would be far easier to deplete by a persistently in 2011 and not in 2010 that had a higher rate of seal located group of seals (Testa et al. 1985, Buckley presence than cells available in 2010 and not in 2011. 2013). Increased foraging time leads to energy loss, We note that our efforts here were specifically to which needs to be replenished, especially for females describe presence of haul-outs at the scale of a who are regaining the 40% of body mass lost during 25 km2 grid. No doubt detecting seal presence, and pup rearing (Salas et al. 2017). The effect of distance surely abundance and population trends, eventually to deep water was greatest in the ERS. By sheer will be possible to describe patterns at both larger virtue of the bathymetry in ERS, where the shelf and smaller scales. For example, while we found break (at 800 m) is very close to the continental some interesting patterns new to our understanding shore, fast ice in that area happens to occur over of Weddell seal occurrence, we have much more to deep water. Moreover, Brooks et al. (2018) confirmed learn. Indeed, 1 seal present in a 5 km grid in this a likely nursery ground for silverfish in the Bay of study is treated equally to a 5 km grid containing Whales (within the ERS), and given that silverfish are potentially hundreds of seals. Do the locations where critical prey for seals and that there are no Adélie more seals persist year after year have similar physi- colonies, just a single emperor colony, perhaps ERS is cal variables? For a few areas, the answer is yes (e.g. inhabited by seals primarily due to abundant prey. Ainley et al. 2015a and references therein), but what Surely variation in prey abundance will affect habitat about all other areas where the best seal habitat fac- selection among years and thus population variation. tors are present? Can we predict seal source and We therefore caution whether this apparent, strong sinks via metapopulation modeling? That is, are effect of distance to deep water is itself explanatory there ‘core’ areas of high abundance, with smaller of seal presence, or whether it too is a proxy for numbers in nearby outlying areas (as in Adélie factors we cannot address here. penguins; Ainley et al. 1995)? These are ecological/ At first glance, our results of significant effects of demographic questions that cannot necessarily be year on the probability of seal presence in a cell may answered at a 25 km2 grid scale, nor by presence/ suggest a greater number of pupping seals present in absence modeling alone. Thus, the appropriate the population in 2011 than in 2010. We note that signal and scale by which to ascertain more speci- pupping seals are philopatric and will tend to be fic ecologically relevant information remains to be found in the same location over time (Siniff et al. investigated. 1977). Of 356 cells inspected overall, only 178 cells were examined in both years: 55 of these were occu- pied in both years, 75 were never occupied, 26 were 4.2. Lessons from citizen science in detecting seals occupied in 2010 but not 2011, and 22 were occupied in 2011 but not 2010. Thus, cells that were occupied Our findings here advance our understanding of in 2010 tended to be occupied in 2011 (68%) and seal presence on the fast ice during the breeding those that were unoccupied in 2010 tended to remain season in the Ross Sea. It is important to highlight unoccupied (77%). These results may reflect a the strategy through which our data collection took philopatric tendency (albeit not marked), but they place: a combination of remote sensing, citizen sci- may also indicate that habitat suitability was con - ence, and crowd-sourcing, important for several rea- sistent from one year to the next in these 130 cells. sons. First, engaging with citizen scientists democra- Moreover, the year effect we report could be inter- tizes science, allowing volunteers to not only provide preted as an increased number of pupping seals in feedback and understand the scientific method, but 2011 than 2010, or perhaps the same number of seals also to ask us questions and gain context about how spreading into areas becoming suitable in 2011. their efforts advance research. Second, by using However, closer inspection of the data shows that 126 Tomnod, we were able to avoid the time-consuming 206 Mar Ecol Prog Ser 612: 193–208, 2019

and costly methods associated with remote sensing Ainley DG (2002) Adélie penguin: bellwether of climate (e.g. downloading data, preparing for analysis using change. Columbia University Press, New York, NY Ainley DG (2007) Insights from study of the last intact neritic proprietary software, etc.). Third, and perhaps most marine ecosystem. Trends Ecol Evol 22: 444−445 impressive, were the efficiencies gained in both in Ainley DG, Siniff DB (2009) The importance of Antarctic time and space. Traditional survey methods for ice- toothfish as prey of Weddell seals in the Ross Sea. obligate seals include aerial, ship-board, or ground Antarct Sci 21: 317−327 Ainley DG, Nur N, Woehler EJ (1995) Factors affecting the surveys (e.g. Siniff et al. 1977, Bester et al. 2002, size and distribution of pygoscelid penguin colonies in Southwell et al. 2004, Bengtson et al. 2011), all of the Antarctic. Auk 112: 171−182 which can be hindered by time, safety, and cost con- Ainley DG, Russell J, Jenouvrier S, Woehler EJ, Lyver POB, cerns. For example, a full survey conducted by a field Fraser WR, Kooyman GL (2010) Antarctic penguin re- crew in Erebus Bay (~400 km2) can take upwards of sponse to habitat change as Earth’s troposphere reaches 2°C above pre-industrial levels. Ecol Monogr 80: 49−66 16 h (J. Rotella pers. comm.). This represents thou- Ainley DG, LaRue MA, Stirling I, Stammerjohn S, Siniff DB sands of person-hours and substantial logistics and (2015a) An apparent population decrease, or change in field costs for a single season. Comparatively, our distribution, of Weddell seals along the Victoria Land surveys of the Ross Sea (including Erebus Bay) by coast. Mar Mamm Sci 31:1338−1361 Ainley DG, Ballard G, Jones RM, Jongsomjit D, Pierce SD, VHR were conducted by ~5000 volunteers who cov- Smith WO Jr, Veloz S (2015b) Trophic cascades in the ered the equivalent space of Erebus Bay more than western Ross Sea, Antarctica: revisited. Mar Ecol Prog 10 times in just a few weeks. We are careful to note Ser 534: 1−16 that research questions addressed in the field are dif- Ainley DG, Lindke K, Ballard G, Lyver PO’B and others ferent and inherently require more time than our (2017a) Spatio-temporal occurrence patterns of ceta - ceans near Ross Island, Antarctica, 2002–2015: implica- efforts here. The comparison we are making is only tions for food web dynamics. Polar Biol 40: 1761−1775 appropriate from the perspective of gaining effi- Ainley DG, Crockett EL, Eastman JT, Fraser WR and others ciency in determining presence and location of seals (2017b) How overfishing a large piscine mesopredator on a given landscape. explains growth in Ross Sea penguin populations: a framework to better understand impacts of a controver- Finally, the success of this project demonstrates the sial fishery. Ecol Model 349: 69−75 utility of our approach and suggests a feasible strat- Arndt JE, Schenke HW, Jakobsson M, Nitsche FO and egy for similar surveys in the future (i.e. for ice- others (2013) The International Bathymetric Chart of the obligate species in other regions or at larger spatial Southern Ocean (IBCSO) version 1.0—a new bathy - metric compilation covering circum-Antarctic waters. scales). Indeed, our goals are to apply our method Geophys Res Lett 40:3111−3117 toward a full census of Weddell seals, adding to sim- Arrigo KR, Worthen D, Schnell A, Lizotte MP (1998) Primary ilar censuses of the 2 Antarctic penguin species production in Southern Ocean waters. J Geophys Res (Fretwell et al. 2012, Lynch & LaRue 2014). We aim to 103: 15587−15600 learn from our experiences here, adapt our methods, Arrigo KR, Robinson DH, Worthen DL, Dunbar RB, DiTullio GR, Van Woert M, Lizotte MP (1999) Phytoplankton com- and continue to engage with the public to conduct munity structure and the drawdown of nutrients and CO2 science that has never before been possible. in the Southern Ocean. Science 283: 365−367 Arrigo KR, van Dijken G, Strong AL (2015) Environmental controls of marine productivity hot spots around Ant - Acknowledgements. We are indebted to the thousands of arctica. J Geophys Res 120: 5545−5564 volunteers who helped us search for seals on VHR images Barber-Meyer SM, Kooyman GL, Ponganis PJ (2008) Trends using Tomnod; we appreciate their indispensable labor. We in western Ross Sea emperor penguin chick abundances are grateful for funding from the National Science Founda- and their relationships to climate. Antarct Sci 20:3–11 tion (collaborative proposal Nos. 1543311, 1543230, and Barrington L, Ghosh S, Greene M, Har-Noy S and others 1542791) and Hogwarts Running Club in partnership with (2011) Crowd-sourcing earthquake damage assessment the Antarctic and Southern Ocean Coalition; the University using remote sensing imagery. Ann Geophys 54: ag-5324 of Minnesota, DigitalGlobe Foundation, and SciStarter fur- Barry JP, Grebmeier JM, Smith J, Dunbar RB (2003) Oceano- ther supported this research. We thank the Polar Geospatial graphic versus seafloor-habitat control of benthic mega - Center for assistance in gathering image metadata, provid- faunal communities in the SW Ross Sea, Antarctica. In: ing GIS maps, and for general geospatial assistance and Ditullio GR, Dunbar RB (eds) Biogeochemistry of the advice. Finally, we thank 3 anonymous reviewers for their Ross Sea, Vol 78. American Geophysical Union, Wash- feedback on a previous version of this manuscript. ington, DC, p 327–353 Bengtson JL, Laake JL, Boveng P, Cameron MF, Hanson MB, Stewart BS (2011) Distribution and abundance of LITERATURE CITED pack-ice seals in the Amundsen and Ross Seas, Antarc- tica. Deep-Sea Res II 58: 1261−1276 Aho K, Derryberry D, Peterson T (2014) Model selection for Bester MN, Ferguson JWH, Jonker FC (2002) Population ecologists: the worldviews of AIC and BIC. Ecology 95: densities of pack ice seals in the Lazarev Sea, Antarctica. 631−636 Antarct Sci 14: 123−127 LaRue et al.: Weddell seal breeding distribution 207

Bindschadler R, Vornberger P, Fleming A, Fox A and others Gilbert JR, Erickson AW (1977) Distribution and abundance (2008) The Landsat image mosaic of Antarctica. Remote of seals in the pack ice of the Pacific sector of the South- Sens Environ 112: 4214−4226 ern Ocean. In: Llano GA (ed) Adaptations within Ant - Brooks CM, Caccavo JA, Ashford J, Dunbar R, Goetz K, La arctic ecosystems, Smithsonian Institute, Washington, Mesa M, Zane L (2018) Early life history connectivity of DC, p 703−740 Antarctic silverfish (Pleuragramma antarctica) in the Goetz KT (2015) Movement, habitat, and foraging behavior Ross Sea. Fish Oceanogr 27: 274−287 of Weddell seals (Leptonychotes weddellii) in the west- Buckley BA (2013) Rapid change in shallow water fish spe- ern Ross Sea, Antarctica. PhD dissertation, University of cies composition in an historically stable Antarctic envi- California, Santa Cruz, CA ronment. Antarct Sci 25:676–680 Goetz KT, Burns JM, Hückstädt LA, Shero MR, Costa DP Burns JM, Kooyman GL (2001) Habitat use by Weddell seals (2017) Temporal variation in isotopic composition and and emperor penguins foraging in the Ross Sea, Antarc- diet of Weddell seals in the western Ross Sea. Deep Sea tica. Am Zool 41: 90−98 Res II 140: 36−44 Cameron MF, Siniff DB (2004) Age-specific survival, abun- Goetz KT, McDonald BI, Kooyman GL (2018) Habitat prefer- dance, and immigration rates of a Weddell seal (Leptony- ence and dive behavior of non-breeding emperor pen- chotes weddellii) population in McMurdo Sound, Ant - guins in the eastern Ross Sea, Antarctica. Mar Ecol Prog arctica. Can J Zool 82: 601−615 Ser 593: 155−171 Chambert T, Rotella JJ, Garrott RA (2012) Environmental Hosmer DW, Lemeshow S, Sturdivant RX (2013) Applied extremes versus ecological extremes: impact of a mas- logistic regression, 3rd edn. Wiley, New York, NY sive iceberg on the population dynamics of a high-level Jacobs SS, Comiso JC (1989) Sea ice and oceanic processes Antarctic marine predator. Proc R Soc B 279:4532−4541 on the Ross Sea continental shelf. J Geophys Res 94: Chambert T, Rotella JJ, Garrott RA (2015) Female Weddell 18195−18211 seals show flexible strategies of colony attendance re lated Kim S, Saenz B, Scanniello J, Daly K, Ainley D (2018) Local to varying environmental conditions. Ecology 96: 479−488 climatology of fast ice in McMurdo Sound, Antarctica. Cornet A, Jouventin P (1980) Le phoque de Weddell (Lep- Antarct Sci 30: 125−142 tonychotes weddelli) a pointe geologie et sa plasticite Kooyman GL (1981) Weddell seal: consummate diver. Cam- sociale. Mammalia 44:497–521 bridge University Press, London Davis RW, Fuiman LA, Williams TM, Horning M, Hagey W La Mesa M, Eastman JT (2012) Antarctic silverfish: life (2003) Classification of Weddell seal dives based on 3- strategies of a key species in the high-Antarctic eco - dimensional movements and video-recorded observa- system. Fish Fish 13: 241−266 tions. Mar Ecol Prog Ser 264:109–122 Lake S, Burton H, Barker R, Hindell M (2008) Annual repro- Dunn A, Vacchi M, Watters G (2017) The Ross Sea region ductive rates of Weddell seals in eastern Antarctica from Marine Protected Area research and monitoring plan. 1973 to 2000. Mar Ecol Prog Ser 366: 259−270 SC-CAMLR-XXXVI/20. CCAMLR, Hobart LaRue MA, Rotella JJ, Garrott RA, Siniff DB and others Eastman JT (1985) Pleuragramma antarcticum (Pisces, (2011) Satellite imagery can be used to detect vari - Noto theniidae) as food for other fishes in McMurdo ation in abundance of Weddell seals (Leptonychotes Sound, Antarctica. Polar Biol 4:155−160 weddellii) in Erebus Bay, Antarctica. Polar Biol 34: Erickson AW, Hanson MB (1990) Continental estimates and 1727−1737 population trends of Antarctic seals. In: Kerry KR, LaRue MA, Lynch HJ, Lyver POB, Barton K and others Hempel G (eds) Antarctic ecosystems: ecological change (2014) A method for estimating colony sizes of Adélie and conservation. Springer-Verlag, Berlin, p 253−264 penguins using remote sensing imagery. Polar Biol 37: Erickson AW, Hofman RJ, Oehlenschlager RJ, Otis J, Kuehn 507−517 D (1971) Seal population studies in the Ross Sea. Antarct Laws RM (1964) Comparative biology of Antarctic seals. In: J US 6:98−99 Carrick R, Holdgate M, Prevost J (eds) Antarctic biology. Forcada J, Trathan PN, Boveng PL, Boyd IL and others Hermann, Paris, p 445–454 (2012) Responses of Antarctic pack-ice seals to environ- Lenky C, Eisert R, Oftedal OT, Metcalf V (2012) Proximate mental change and increasing krill fishing. Biol Conserv composition and energy density of nototheniid and myc- 149: 40−50 tophid fish in McMurdo Sound and the Ross Sea, An - Fraser AD, Massom RA, Michael KJ, Galton-Fenzi BK, tarctica. Polar Biol 35: 717−724 Lieser JL (2012) East Antarctic land-fast sea ice distri - Lindsey AA (1937) The Weddell seal in the Bay of Whales, bution and variability, 2000–08. J Clim 25: 1137−1156 Antarctica. J Mammal 18:127–144 Fretwell PT, LaRue MA, Morin P, Kooyman GL, and others Lynch HJ, LaRue MA (2014) The first global census of the (2012) An emperor penguin population estimate: the first Adélie penguin. Auk 131: 457−466 global, synoptic survey of a species from space. PLOS Massom RA, Hill K, Barbraud C, Adams N, Ancel A, Emmer- ONE 7: e33751 son L, Pook MJ (2009) Fast ice distribution in Adélie Fretwell PT, Trathan PN, Wienecke B, Kooyman GL (2014) Land, : interannual variability and impli- Emperor penguins breeding on ice shelves. PLOS ONE cations for emperor penguins Aptenodytes forsteri. Mar 9: e85285 Ecol Prog Ser 374:243−257 Fuiman LA, Davis RW, Williams TM (2002) Behavior of mid- Nihashi S, Ohshima KI (2015) Circumpolar mapping of water fishes under Antarctic ice: observations by a pred- Antarctic coastal polynyas and landfast sea ice: relation- ator. Mar Biol 140:815–822 ship and variability. J Clim 28: 3650−3670 Fuiman LA, Madden KM, Williams TM, Davis RW (2007) Pitman RL, Durban JW (2010) Cooperative hunting behav- Structure of foraging dives by Weddell seals at an off- ior, prey selectivity and prey handling by pack ice killer shore isolated hole in the Antarctic fast-ice environment. whales (Orcinus orca), type B, in Deep Sea Res II 54:207–289 waters. Mar Mamm Sci 30:16−36 208 Mar Ecol Prog Ser 612: 193–208, 2019

Ponganis PJ, Stockard TK (2007) The Antarctic toothfish: board line transect surveys of crabeater seal abundance How common a prey for Weddell seals? Antarct Sci 19: in the pack ice off East Antarctica: evaluation of assump- 441−442 tions. Mar Mamm Sci 20:602−620 R Core Team (2017) R: a language and environment for Southwell C, Bengtson J, Bester M, Blix AS and others statistical computing. R Foundation for Statistical Com- (2012) A review of data on abundance, trends in abun- puting, Vienna. www.r-project.org dance, habitat use and diet of ice-breeding seals in the Rotella JJ, Link WA, Nichols JD, Hadley GL, Garrott RA, Southern Ocean. CCAMLR Sci 19:49−74 Proffitt KM (2009) An evaluation of density-dependent Stirling I (1969a) Tooth wear as a mortality factor in the Wed- and density-independent influences on population growth dell seal, Leptonychotes weddelli. J Mammal 50: 559−565 rates in Weddell seals. Ecology 90: 975−984 Stirling I (1969b) The ecology of the Weddell seal in Mc- Russell JL, Dixon KW, Gnanadesikan A, Stouffer RJ, Togg- Murdo Sound, Antarctica. Ecology 50: 573−586 weiler JR (2006) The Southern Hemisphere westerlies in Stirling I (1969c) Distribution and abundance of the Weddell a warming world: propping open the door to the deep seal in the western Ross Sea, Antarctica. NZ J Mar ocean. J Clim 19:6382−6390 Freshw Res 3:191−200 Salas L, Nur N, Ainley D, Burns J, Rotella J, Ballard G (2017) Stirling I (1971) Population aspects of Weddell seal har- Coping with loss of large, energy-dense prey: a potential vesting at McMurdo Sound, Antarctica. Polar Rec 15: bottleneck for Weddell Seals in the Ross Sea. Ecol Appl 653−667 27: 10−25 Stonehouse B (1953) The emperor penguin. Sci Rep Falkl Isl Siniff DB, Ainley DG (2008) Aerial surveys of Weddell seals Depend Surv 6 during 2007–08, with notes on the history of aerial cen- Stonehouse B (1975) The biology of penguins. McMillan suses in the Ross Sea and recommendations for contin- Press, London ued count effort. WG-EMM-08/23, CCAMLR, Hobart Testa JW, Siniff DB, Ross MJ, Winter JD (1985) Weddell Siniff DB, DeMaster DP, Hofman RJ, Eberhardt LL (1977) An seal-Antarctic cod interactions in McMurdo Sound, analysis of the dynamics of a Weddell seal population. Antarctica. In: Siegfried WR, Condy PR, Laws RM (eds) Ecol Monogr 47: 319−335 Antarctic nutrient cycles and food webs. Springer, Hei- Siniff DB, Garrott RA, Rotella JJ, Fraser WR, Ainley DG delberg, p 561−565 (2008) Projecting the effects of environmental change on Thomas JA, DeMaster DP (1983) Diel haul-out patterns of Antarctic seals. Antarct Sci 20: 425−435 Weddell seal (Leptonychotes weddelli) female and their Smith MSR (1965) Seasonal movements of the Weddell pups. Can J Zool 61:2084–2086 seal in McMurdo Sound, Antarctica. J Wildl Manag 29: Trathan PN, Fretwell PT, Stonehouse B (2011) First recorded 464−470 loss of an emperor penguin colony in the recent period of Smith WO Jr, Ainley DG, Arrigo KR, Dinniman MS (2014) Antarctic regional warming: implications for other The oceanography and ecology of the Ross Sea. Annu colonies. PLOS ONE 6: e14738 Rev Mar Sci 6:469−487 Turner J, Comiso J (2017) Solve Antarctica’s sea ice puzzle. Southwell C, de la Mare B, Borchers D, Burt L (2004) Ship- Nature 547: 275−277

Editorial responsibility: Elliott Hazen, Submitted: July 10, 2018; Accepted: January 22, 2019 Pacific Grove, California, USA Proofs received from author(s): February 26, 2019 The following supplement accompanies the article

Physical and ecological factors explain the distribution of Ross Sea Weddell seals during the breeding season

Michelle A. LaRue1,*, Leo Salas2, Nadav Nur2, David G. Ainley3, Sharon Stammerjohn4, Luke Barrington5, Kostas Stamatiou6, Jean Pennycook3, Melissa Dozier6, Jon Saints6, Hitomi Nakamura7

*Corresponding author: [email protected]

Marine Ecology Progress Series 612: 193–208 (2019)

Supplement 1. Instructions for Satellites Over Seals (SOS) Campaign #1, Spot Our Seals in the Ross Sea. OVERVIEW The Weddell seal is an iconic species that is important to the Antarctic ecosystem, but nobody knows how many there are. The Ross Sea in Antarctica is the most pristine part of the ocean left, but is threatened by a fishery that targets Chilean seabass – important food for the Weddell seal. We want to know whether the fishery is affecting the seal population; please help us count seals in the Ross Sea!

Weddell seal on fast ice (3-4 meters = 10-11 ft long), notice the distinct shape (elongated ‘tear drop’) and dark color.

1 Instructions:

1. Place a tag in the center of every seal you find. Seals will appear as dark, tear-drop shapes, usually near a crack in the ice. 2. If it appears there are two seals touching or almost touching, place only one tag at that location. The smaller individual is a nursing pup and usually has its head resting on its much larger mother. 3. Shadows of large seals may appear as two seals. Check for the distinct shape (probably smaller) of the supposed second seal; if it is smaller and grayer then it is a shadow.

An aerial photo of a group of Weddell seals (n = 24) around a breathing hole which is along a crack in the sea ice.

2

An aerial picture of Weddell seals (circled in red) along a crack in the fast ice (sea ice fastened to land) near an island.

3 A WV-01 satellite picture of Turtle Rock in Erebus Bay, Antarctica. Red circles indicate seals - they are dark and very close to cracks in the sea ice. Many items can be mistaken for seals, such as shadows, melt pools, and rocks. A helpful tip is to discard any dark-colored feature that is too big or a different shape than a seal.

4 A WV-01 satellite picture of seals (circled in red) along a tide crack on fast ice. Not all seals are circled. Compare the seals in this image with the close ups and aerial images shown earlier to generate an image in your mind of what a seal looks like, and how it relates to its environment, from different distances away.

5 Supplement 2.

CrowdRank algorithm. As “features” are tagged via the Tomnod online platform (in our case, presumptive seals; here we assume that a feature is a seal; Figure 2), the CR algorithm clusters the tags and calculates a score for each cluster (the “feature CR score”) as a metric of how much agreement exists among users that the cluster is a feature. The feature CR score is calculated as the joint users’ agreement on a feature for all users who identified it (by placing a tag on it), and those who inspected the area and did not tag it. Hence, the feature CR score is based on which users placed a tag in the cluster, and which users viewed the area but did not place a tag. The probability of correctly identifying a feature, or user accuracy score, is uniquely estimated for all Tomnod users and is calculated based on how much each user agreed with peers in identifying and tagging features (Barrington et al. 2011). Users who agree with each other on identifying and tagging the same features receive high probability values, with the clusters upon which they agree receiving a high CR score as well – meaning that such clusters are more likely to be signifying a feature on the icescape. By the same reasoning, users who disagree with other users receive low probability values and reduce the CR score of clusters they tag. This user accuracy score weights all the user's views and tags in the campaign. In summary, tags and views by high- score users are trusted, while those of only low-score users are distrusted (Barrington et al. 2011). Upon review of the features vis-a-vis expert search we are confident that any seal(s) in the images were most likely tagged, and that cells with no seals in them were accurately assigned no features.

6