Draft Reassessing abundance of Southern Hudson Bay polar bears by aerial survey : effects of climate change at the southern edge of the range

15 The Southern Hudson Bay polar bear (Ursus maritimus Phipps, 1774) subpopulation is 16 considered stable but conflicting evidence lends uncertainty to that designation. Capture17 recapture studies conducted 1984-86 and 2003-05 and an aerial survey conducted 2011/12 18 suggested abundance was likely unchanged since the mid-1980s. However, body condition and 19 body size declined since then, and duration of sea ice decreased by about 30 days. Due to 20 conflicting information on subpopulation status and ongoing changes in sea ice, we conducted 21 another aerial survey in 2016 to determine whether abundance had changed. We collected data 22 via mark-recapture distance sampling and double-observer protocols. Results suggest abundance 23 declined 17% from 943 bears (95% CI 658-1350) in 2011/12 to 780 (95% CI 590–1029) in 2016. 24 The proportion of yearlings declined from 12% of the population in 2011 to 5% in 2016, whereas 25 the proportion of cubs remained similar (16% in 2011 vs. 19% in 2016) suggesting low survival 26 of the 2015 cohort. In a warming Arctic, duration of sea ice is predicted to continue to decline in 27 Hudson Bay affecting all ice-dependent wildlife; therefore, further monitoring of this 28 subpopulation is warranted. We recommend a conservative approach to harvest management 29 and repeating the aerial survey in 2021. 30 31


Introduction
Declines in the duration and distribution of sea ice in the Arctic have been implicated in large changes in several polar bear (Ursus maritimus Phipps, 1774) subpopulations.These changes include those at the level of individuals such as declines in body condition (Stirling et al. 1999;Rode et al. 2012;Obbard et al. 2016) and decreases in body size (Rode et al. 2010).
Changes at the population level have also been related to declines in sea ice; these include shifts in distribution (Durner et al. 2009) and declines in survival rates and abundance (Regehr et al. 2007;Regehr et al. 2010;Bromaghin et al. 2015;Lunn et al. 2016).The Southern Hudson Bay (SH) subpopulation occurs at the southern edge of the species' range in eastern Hudson Bay and James Bay (Fig. 1) in an area where, depending on criteria used to define break-up and freeze-up dates, break-up has advanced 3.0 to 5.0 days/decade and freeze-up has been delayed by 3.6 to 5.0 days/decade since 1980 (Obbard et al. 2016;Stern and Laidre 2016).
Results of capture-recapture studies conducted on the Ontario mainland 1984-1986 and 2003-2005 suggested that abundance of the Southern Hudson Bay polar bear subpopulation was unchanged in that 20-year period from 634 (95% CI = 390-878) to 673 bears (95% CI = 396-950) (Obbard et al. 2007;Obbard 2008).Model-averaged survival estimates provided only weak evidence for a decline in total apparent survival of all age and sex classes between 1984-86 and 1999-2005(Obbard et al. 2007).Nonetheless, a decline in survival rates was consistent with the hypothesis that the SH population was under stress as suggested by declines in body condition between 1984-86 and 2003-2005(Obbard et al. 2006)).Obbard (2008) suggested that such declines in body condition would eventually have negative demographic consequences because of the high sensitivity of polar bear population growth rates to changes in adult female survival.
Because of the conflicting information indicating declines in body condition and survival but no D r a f t 4 declines in abundance, combined with the view of traditional knowledge holders that the population was stable or increasing, an aerial survey of the entire range of the SH subpopulation was conducted in 2011 and 2012 (Obbard et al. 2015).The abundance estimate for the entire SH subpopulation from that aerial survey (conducted on the Ontario mainland and Akimiski Island in 2011, and on the Québec coastline and nearshore islands and on the islands in eastern Hudson Bay and remaining islands in James Bay in 2012) was 943 bears (95% CI 658-1350; Obbard et al. 2015).
Results from the 2011/2012 aerial survey and the two capture-recapture studies conducted 1984-86 and 2003-2005 suggested that abundance in SH likely remained stable over about the previous 25 years.Nevertheless, both the duration of sea ice within the bounds of SH (Hochheim and Barber 2014;Stern and Laidre 2016) and body condition of bears (Obbard et al. 2016) declined over the same period.In addition, duration of sea ice is expected to continue to decline in Hudson Bay in the future (Castro de la Guardia et al. 2013).Worldwide, polar bear abundance is expected to decline by 30% over the next three generations or 36 years (Regehr et al. 2016).Within the Hudson Bay region, habitat models predict major declines in distribution and abundance of polar bears in this area by mid-century (Amstrup et al. 2008).By 2012, polar bears in SH were already spending on average 30 days longer on land than bears did in 1980 (Obbard et al. 2016).
Although ecological change in the Arctic via changing duration and distribution of sea ice resulting from climate warming (Stirling and Derocher 2012) is currently considered the greatest threat to conservation of polar bears (PBSG 2010a:85), harvest remains an additional threat that is managed via measures such as quotas.Therefore, a current estimate of abundance is necessary to inform management and provide insight to sustainable harvest levels.In the D r a f t context of ongoing declines in body condition in SH, predictions of further declines in sea ice in Hudson Bay, predictions of declines in abundance in Hudson Bay and worldwide, and ongoing legal harvest, we conducted a second aerial survey of the entire range of the SH subpopulation in September 2016 to assess whether abundance had changed since the previous aerial survey.To enable direct comparison of results of the two aerial surveys we closely followed the design of the 2011/2012 survey.

Study Area
Polar bear subpopulations are delineated based on a combination of ice movement patterns, tag returns from harvested bears, capture-recapture studies, and conventional and satellite radio-telemetry (Lunn et al. 2010).The boundaries of SH span much of eastern and southern Hudson Bay and all of James Bay (Fig. 2), extending from the coastlines of Ontario and Québec to inland regions where bears are known to construct maternity dens (Jonkel et al. 1976;Kolenosky and Prevett 1983;Obbard and Walton 2004;Obbard and Middel 2012).The inland portion of the management unit includes areas up to 200 km inland, though documented use of sites >120 km inland is rare (Kolenosky and Prevett 1983;Obbard and Walton 2004;Obbard and Middel 2012).The Western Hudson Bay (WH) and Foxe Basin (FB) subpopulations border SH to the west and north, respectively (Fig. 2).Small nearshore and offshore islands in James Bay and eastern Hudson Bay are also included within SH.In total, the subpopulation covers about 465,000 km 2 of the surface area of Hudson Bay and James Bay and about 1,270 and 1,731 km of the coastlines of Ontario and Québec respectively (Fig. 2).

D r a f t 6
During the late summer and fall ice-free season in Hudson Bay (Markham 1988;Wang et al. 1994a,b) polar bears in SH are confined to land, demonstrating strong fidelity to particular geographic regions (Obbard and Walton 2004;Stirling et al. 2004;Obbard and Middel 2012) and remaining segregated from neighbouring subpopulations in Foxe Basin and Western Hudson Bay.Pregnant bears in SH typically enter maternity dens between the last week of October and mid-November (Middel 2014); the earliest that a bear appeared to localize at a den location was September 17; the next earliest was October 8. Therefore, following Obbard et al. (2015) we conducted our aerial survey in September when most bears in the subpopulation would be available to be counted.
Except for total counts of bears on very small islands, we simultaneously collected data for both sight-resight (i.e., double-observer; Pollock and Kendall 1987) and distance sampling (Buckland et al. 2001).We implemented a double-observer platform in which 2-person teams of front and rear observers worked independently to sight bears.We erected an opaque partition between front and rear observers to ensure that sightings by the front team did not cue rear observers, and sightings were only announced after both teams were afforded a full opportunity to spot a bear.We defined a group (hereafter cluster) of bears as individuals whose sightings were non-independent (i.e., spotting one bear led to the observation of others; e.g., family groups comprised of an adult female and 1 or more dependent young or a group of male bears).For each sighting, we recorded the number of bears in a cluster, and the bear's activity (e.g., running, sitting) when first spotted; we also estimated field age class (adult, subadult, yearling, cub-ofthe-year), body condition (1-5; Stirling et al. 2008), and other covariates that could affect detection probabilities.These latter covariates included vegetation height within a 30-m radius (<1 m, 1-3 m, >3 m), vegetation density at the same spatial scale (1 = sparse tundra, 2 = D r a f t 7 moderate, 3 = dense), visibility (1 = poor [e.g., dense fog or rain], 2 = fair [e.g., light fog, light rain, overcast, excessive glare], 3 = excellent [e.g., clear and sunny, partly cloudy]).We used GPSs to record flight paths and bear locations.

Survey of Québec coast and coastal inland transects
Following Obbard et al. (2015) we designed and implemented a systematic helicopterbased line transect aerial survey of the Québec coast and nearshore islands.We used an A Star 350 BA helicopter, flown at a target altitude of 150 m above ground level (AGL) and a ground speed of approximately 150 km/hr.We modified the methodology of this portion of the survey slightly from Obbard et al. (2015) based on additional input from traditional knowledge holders in Inukjuak, Umiujaq, and Kuujjuarapik collected by the Nunavik Marine Region Wildlife Board in 2016 (NMRWB 2018).Coverage of the coastline and nearshore islands was the same as in 2012, but we added coverage to include inland habitats believed to be occasionally used by polar bears in late summer.To achieve this, we flew a series of 20-km inland transects, oriented perpendicular to the coastline and spaced 6 km apart (for comparability with the Ontario mainland and Akimiski Island portion of the overall survey), from Pointe Louis XIV/Long Island at the junction of James Bay and Hudson Bay to north of Inukjuak, except for the Lake Tasiujaq area (Lac Guillaume-Delisle) where the lake shoreline was surveyed instead of flying over extensive areas of open water.We surveyed all nearshore islands (i.e., those within 5 km of the coast) as well as the Québec coastline (Fig. 3).

Offshore islands in James Bay and eastern Hudson Bay
For safety reasons, a twin-engine platform was required to access the offshore islands in Hudson Bay and James Bay (Fig. 3); therefore, these areas were surveyed using a de Havilland DHC-6 Twin Otter with 2 pilots and 4 observers in the rear of the aircraft.Pilots did not D r a f t contribute to the count, nor did they alert observers to bears seen by them.When bears were sighted, we recorded the covariates mentioned above and data were entered immediately onto a field computer.The aircraft flew at a planned height of 150 m AGL and at a planned speed of 150 km/h.We surveyed the Belcher Islands, located in southeastern Hudson Bay, using a combination of overland, perpendicular transects and coastal contours, which facilitated sampling about 50 % of the shoreline.Surveys of other islands in eastern Hudson Bay such as the Ottawa, Sleeper, and King George islands complexes were spatially comprehensive.The coverage and methodology for the eastern Hudson Bay offshore islands was identical to that in Obbard et al. (2015) except for a small area added in the coverage of the Belcher Islands region following input from the Hunters and Trappers Organisation of Sanikiluaq.Protocols enabled the simultaneous collection of data for both sight-resight (double-observer) and distance sampling analyses as above.However, for the distance sampling analysis, we used a clinometer to measure the angle from the aircraft to the bear, once the aircraft was perpendicular to the bear, to estimate its distance because the exact position of the bears when sighted could not be recorded with the fixed-wing aircraft.We recorded the same covariates as in other portions of the survey.
Coverage of the James Bay islands was similar to the 2012 survey except for a few small nearshore islands that were added (Paint Hills Islands, Moar Bay, Old Factory Bay) based on input from traditional and local knowledge holders collected by the Eeyou Marine Region Wildlife Board in 2016.We surveyed larger islands in James Bay (Charlton, South Twin, North Twin) using transects spaced 3 km apart.Finally, we comprehensively surveyed small offshore islands in James Bay and eastern Hudson Bay (Fig. 3).

D r a f t
Following methods of Obbard et al. (2015) we designed and implemented a systematic helicopter-based line transect aerial survey of the Ontario mainland and Akimiski Island in James Bay.Our survey area extended from the boundary of SH near the Ontario/Manitoba border to the Ekwan River on James Bay (Fig. 3).Polar bears occur rarely south of the Ekwan River during the ice-free season (Obbard and Walton 2004) so we did not survey this area.For bears outfitted with GPS collars between 2007 and 2011 during August-October, the maximum distance from the coast for any bear was 49.8 km ‫̅ݔ(‬ = 5.9 km, n = 13,132 locations; Middel 2014).A few maternity dens have been recorded >100 km inland in Ontario (Kolenosky and Prevett 1983), but most denning occurs within our defined study area.For example, based on winter aerial surveys, Kolenosky and Prevett (1983) documented 12 of 19 dens <60 km from the coast.More recently, data from satellite or GPS-collared bears indicated that from 2002 to 2011, 22 of 23 bears, whose den locations were checked by site visits after they were abandoned the following spring, denned within 60 km of the coast ‫̅ݔ(‬ = 37.1 km); the 23rd bear denned 62.7 km inland from the coast (Obbard and Middel unpublished data).Therefore, consistent with Obbard et al. (2015), we defined 2 inland strata in Ontario, including a high-density zone extending from the coastline to 20 km inland, and a low-density stratum extending 20-60 km inland (Fig. 3).We also delineated a coastal zone that included land within 500 m of the shoreline, tidal flats, nearshore islands and spits.We used both overland transects, oriented perpendicular to the coastline, and coastal contour transects.Because polar bears congregate near the shore during the ice-free season and are less frequent farther inland (Derocher and Stirling 1990a,b;Obbard and Walton 2004;Towns et al. 2010), arranging the overland (hereafter perpendicular) transects along this density gradient minimized estimate bias and improved precision (Buckland et al. 2001;Stapleton et al. 2014).We extended perpendicular transects over D r a f t exposed tidal flats so that we could estimate abundance without the coastal contours.We spaced perpendicular transects at 6-km intervals in the high-density stratum.Every other pair of transects was extended through the low-density stratum (i.e., to 60 km inland), such that transect spacing there averaged 12 km (Fig. 3).
We used a Eurocopter EC-130 helicopter and flew at a planned altitude of 150 m AGL and a speed of 150 km/h.Data were recorded using a double-observer protocol for the coastal transects, and following a distance sampling protocol for inland transects perpendicular to the coast.We erected an opaque screen between front and rear observers.The helicopter pilot was one of the front observers.When we sighted bears we recorded covariates as described above, and data were recorded immediately on a field computer.We used a GPS to record flight paths and bear locations and adapted procedures from Marques et al. (2006) to measure distances from the transect lines to sightings in a GIS (ArcMap 9.3; Environmental Systems Research Institute, Redlands, CA, USA).All data were entered at the time of the observation into a Panasonic Toughbook running ESRI ArcPad version 8.0; the Toughbook had a built-in GPS that recorded all track files.Because fuel caches were located close to the coast, operationally we divided the area to be surveyed into approximately 2-h legs, in part based on fuel capacity of the helicopter.
We started a leg at a fuel cache and flew the coastal contour transect first, then we flew all perpendicular transects back to the fuel cache.In this way, we minimized the possibility that bears might move large distances between when the coastal transect was flown and when perpendicular transects were flown, thereby minimising the possibility that bears might be counted more than once.

D r a f t
To ensure comparability between the previous aerial survey (2011/2012) and this study, the design, sampling protocols, and analytical methods followed Obbard et al. (2015) as closely as possible.We used distance sampling (Buckland et al. 2001) to derive an abundance estimate from perpendicular transects in mainland Ontario, Akimiski Island, and the large islands around Sanikiluaq. Perpendicular transects used to sample smaller islands in southeastern Hudson Bay were tightly spaced (<3 km intervals between transects), such that sampling was essentially spatially comprehensive.In addition, because these islands were very small, transects often included large portions of the coastline, at times running approximately parallel to the shore.
Because bears congregate on or near the coastline during the late summer ice-free season, they may partially reflect this density gradient rather than the actual detection function (Stapleton et al. 2014;Obbard et al. 2015).Hence, these data were inappropriate for distance sampling and were analyzed via double observer analyses (see below).We also note that extensive sampling of mainland Québec yielded no sightings from perpendicular transects, so these transect data and the associated study area were not included in distance sampling analyses.
Because bears along the shoreline or on tidal flats could be sighted from both coastal contour and perpendicular transects, we compiled two datasets that included and excluded the coastal zone sightings from the perpendicular transect data.Histograms summarizing sightings distances from the flight path suggested support for a distance-based detection function (Figs. 4,5).In addition, preliminary double observer analyses suggested that detection at distance zero approximated unity (i.e., the probability that at least one observer sighted a cluster bear at near the transect line was >0.95), a fundamental assumption of distance sampling.As such, we proceeded with multiple covariate distance sampling analyses, allowing us to incorporate environmental covariates that could explain variability in detection probabilities.

D r a f t
We completed distance sampling analyses in program Distance (Version 7.0, Release 1; Thomas et al. 2010).We first fit conventional distance sampling models with uniform, halfnormal, and hazard rate key functions and associated series expansion terms (cosine, simple polynomial and Hermite polynomial), enabling us to evaluate general model fit and examine potential cluster size bias in detection.For both datasets, we right-truncated data at ~5% (i.e., the most distant 5% of observations were discarded), as recommended to improve model fit (Buckland et al. 2001).
We conducted all additional modeling in the MRDS engine of program Distance and specified the single observer analysis.This protocol enabled us to derive an empirical estimate of variance via the Innes et al. (2002) method (facilitated by the MRDS engine), rather than estimate variance via bootstrapping simulations.
Because initial analyses indicated that cluster size did not significantly impact detection, we used mean cluster size for estimating abundance.We examined three covariates potentially influencing detection, including visibility and vegetation height and density within 30 m of the sighting.Although the latter two covariates were highly correlated, we considered both independently in modeling to evaluate which best explained variation in detection.
We incorporated covariates via forward stepwise selection and selected the most highly supported models using Akaike's Information Criterion (Burnham and Anderson 2002).The two datasets yielded estimates of abundance that reflected the entire region surveyed with perpendicular transects (i.e., including the coastal data) and the region inland of the coastal zone (i.e., excluding the coastal data).We used double-observer data collected along coastal contour transects to generate an independent estimate of abundance for the coastal zone.As in Obbard et al. (2015), the Huggins model (Huggins 1989;1991), a capture-recapture model, enabled us to include covariates in modeling and to estimate individual detection probabilities.We surveyed the region 500 m inland of the shoreline, as well as the exposed tidal flats, small nearshore islands, and spits across Ontario and Québec.

Coastal Contours and Nearshore Islands
We completed all double-observer modeling in Program MARK (White and Burnham 1999) and employed AIC c for model selection.We defined polar bear clusters as the sampling unit and specified that detection probabilities either remained constant or varied between observer teams.We used forward stepwise selection to evaluate four covariates: visibility, cluster size, vegetation height, and vegetation density.Because of under-representation of some values, we condensed visibility, vegetation height and vegetation density to binary parameters.To estimate the number of clusters present in the study area, the parameter estimates from the most supported models in each dataset were input with a generalized Horvitz-Thompson estimator.
We estimated the number of individuals by incorporating the mean observed group size for each dataset, calculated group size sampling variance following Buckland et al. (2001), and propagated and multiplied variances via the Delta method (Powell 2007).

Offshore Islands
Small, offshore islands in James Bay and Hudson Bay were analyzed separately using double observer modeling as outlined above.We examined visibility and cluster size covariates to explain variability in detection on the James Bay islands and those off the coasts of Ontario and Québec.In eastern Hudson Bay we incorporated covariates for cluster size and whether the cluster was observed on land or in the sea.Other covariates were not explored due to a lack of D r a f t 14 variability.Some very small islands were comprehensively surveyed; these total counts were added to the final abundance estimate (without an estimate of variance).

Total Abundance
Double sampling the coastal zone enabled us to obtain two partially independent abundance estimates.First, we added estimates from offshore islands across Ontario, Québec and Nunavut, the perpendicular transect analysis that included the coastal zone, and small islands that were comprehensively surveyed.Second, we summed the abundance estimates from the offshore islands, the complete coastal contour transects, the perpendicular transects analysis that excluded the coastal zone, and the small, comprehensively-surveyed islands.We then averaged the two point estimates equal weights) and used a model-averaging framework (Burnham and Anderson 2002) to estimate unconditional variance, yielding a final abundance estimate and associated error estimates for SH.

Survey effort and sightings
We completed the survey of the Québec coast and coastal inland transects from 6-13 September, 2016.We surveyed progressively northward from Pointe Louis XIV to north of Inukjuak except for a small section north of Umiujaq that was skipped due to bad weather conditions and completed on the last surveying day.We flew a total of 32 hours on transect and surveyed a total of 5,126 km, including about 3,181 km on inland transects, 1,452 km on nearshore islands and 574 km of coastline.Though many sections of the coastline were covered several times during ferrying flights, only the first surveying occasion was included in the survey effort calculation.We observed a total of 4 polar bears in this section of the survey, including 2 single adults and one adult female accompanied by a yearling, all of them on nearshore islands.

D r a f t
We surveyed the islands in James Bay (except for Akimiski Island; see below) on 13 September 2016.We flew a total of 7.4 hours on transect.Raw counts were a total of 44 bears, including cubs and yearlings.
We surveyed islands in eastern Hudson Bay from 15-18 September.We flew a total of 20.3 hours on transect and surveyed a total of 4,236 km over the Belcher Islands and surrounding offshore islands including the Ottawa, Sleeper and King George island complexes.Raw counts were 38 bears on the Ottawa Islands and 11 bears in the vicinity of the Belcher Islands.
We flew the Ontario mainland and Akimiski Island portions from 15-25 September.
Sampling progressed systematically from Akimiski Island in James Bay, northwards along the James Bay coast of Ontario to Cape Henrietta Maria, thence westward to the SH boundary with WH.The survey occurred over 81 total flight hours and covered 4,527 km along perpendicular transects, including sampling 2,631 and 1,896 km in the high-density and low-density strata, respectively.
We documented a total of 540 sightings in SH that were incorporated in analyses, including 487 sightings in Ontario and the James Bay islands, and 49 on and near islands in eastern Hudson Bay (Fig. 6).Extensive sampling of the coastline and interior of Québec yielded sightings of 4 bears comprising 3 clusters, all observed on islands near the junction of James Bay and Hudson Bay (Fig. 6).As in the 2011/2012 aerial survey, most sightings were concentrated on mainland Ontario near the shoreline, although bears were occasionally spotted >10 km from the coastline.Because we independently sampled the coastline of Ontario with both perpendicular and contour transects, despite our operational protocol to minimize double counting, bears near the coast may have been sighted twice, and we were unable to calculate the number of unique sightings.

Perpendicular Transects
We surveyed about 5,100 km of perpendicular transects during the 2016 aerial survey, including ~2,632 km in the high-density stratum, ~1,896 km in the low-density strata, and ~570 km of islands in James Bay and eastern Hudson Bay.Although sampling from perpendicular transects occurred on mainland Québec, no bears were observed from those transects; therefore, these data were not included in analyses.After right-truncating the data at 1,750 m (i.e., the distance at which the farthest ~5% of observations were censored), we incorporated 104 polar bear clusters in the distance sampling analysis that included the coastal zone data and 67 clusters in the analysis that excluded coastal sightings.We included 204 transects for variance estimation.
For both datasets, the most highly supported models included vegetation density as a covariate; both hazard rate and half-normal key functions were supported in model selection (Table 1).All highly supported models yielded adequate overall Chi-square goodness-of-fit statistics (P > 0.05; Table 1) and showed suitable fit with additional metrics (Kolmogorov-Smirnov and Cramér-von Mises tests: all P > 0.65).Because there was some variability in density estimation depending on key function, we model-averaged the 2 most highly supported models in each dataset (representing both hazard rate and half-normal key functions) to derive an estimate of abundance, which allowed us to exclude those models with uninformative parameters (i.e., models that did not appreciably improve AIC c scores with an additional parameter; Arnold 2010).We estimated 599 bears (Standard Error: 124.7; 95% lognormal Confidence Interval: 400-897) and 411 bears (SE: 90.6; 95% CI: 268-630) with the datasets including and excluding the coastal zone, respectively.D r a f t 17

Ontario
We included 137 clusters in the double observer analysis with sightings from the coastal zone and small nearshore islands.The most highly supported model included no covariates and estimated a constant detection probability for front and rear observers ‫:(‬ 0.74, SE: 0.03), with an overall inclusion probability of ~0.93.After multiplying by mean cluster size ‫̅ݔ(‬ : 1.51) and inflating variances, we estimated 221 bears (SE: 12.8) in Ontario's coastal zone.

Offshore Islands
We incorporated 51 and 36 clusters for modeling detection on the islands of James Bay and along the Québec coast of Hudson Bay, and on the islands in eastern Hudson Bay, respectively.In the James Bay-Québec analysis, the most highly supported model included a covariate for cluster size and estimated constant detection between front and rear observers ‫:(‬ 0.83, SE: 0.05).Before inflating the raw counts with the estimates of detection via the Horvitz-Thompson estimator, we added two clusters that were not used to estimate detection because the location of observers who sighted the bear (i.e., front, rear, or both) was not recorded.We multiplied by mean cluster size ‫̅ݔ(‬ : 1.58), and inflated variances, yielding an estimate of 89 bears (SE: 8.0) in the James Bay-Québec offshore islands.For the eastern Hudson Bay islands, the best model also incorporated constant detection for front and rear observers, but included covariates for cluster size and sighting location (i.e., in the water or on land; ‫:‬ 0.81, SE: 0.07).
Multiplying by mean cluster size ‫̅ݔ(‬ : 1.33) yielded an estimate of 53 bears (SE: 6.4) on the islands in eastern Hudson Bay.We also spotted 22 bears on spits and small islands offshore of Ontario that were comprehensively surveyed; these areas were considered total counts (i.e., no estimate of variance).

Total Abundance
We summed the results of the perpendicular transect analysis including the coastal zone with the estimates of bears on small islands, yielding 763 bears (SE: 125.1).We obtained an estimate of 796 bears (SE: 92.1) by adding the estimates from the coastal contour transects, the perpendicular transects excluding the coastal region, and small islands.Averaging these figures yielded an estimate of 780 bears (SE: 111.1; 95% CI: 590-1029) in SH during the 2016 ice-free season.

Comparison to 2011/12 survey
The estimate from the current survey is not significantly different from the abundance estimate for the 2011/12 survey of 943 bears (95% CI 658-1350; Obbard et al. 2015) based on the confidence intervals overlapping the means.However, because polar bears are listed as Threatened in Ontario under the Endangered Species Act, we wished to better inform managers about the status of the subpopulation.To do this, we used Monte Carlo simulations to explore the difference between the two estimates.We specified a lognormal distribution defined by the point estimates and SEs of the two surveys and randomly sampled from each of these distributions to represent potential population sizes for the two surveys (n = 1,000,000 iterations).Sixty-one percent of iterations yielded a difference (i.e., a decline) of >100 between the estimates for 2011/12 and 2016 (Figs.7a, b).In terms of proportional differences, 63% of the runs showed a decline of > 10% between 2011/12 and 2016, 43% showed > 20% decline and 32% showed > 25% decline.

D r a f t 19
Litter sizes averaged 1.46 (SD: 0.50; n = 72) for cubs, and 1.32 (SD: 0.48; n = 22) for yearlings, based on all sightings included in analyses.Cubs comprised 19% of all observations and yearlings comprised 5% of all observations (Table 2).

Abundance estimation
In order for us to evaluate status of the SH subpopulation it was important for us to be able to assess trend in abundance.To ensure that results would be directly comparable with the 2011/2012 survey we replicated its design and effort with the exception of inland transects along the Québec coast, a small area adjacent to the Belcher Islands, and a small number of nearshore islands in James Bay that were added to the study design based on input from traditional knowledge holders.Our study design incorporated coastal contour transects, which recognized that the clumped distribution of polar bears along the coast of Hudson Bay in Ontario and Manitoba during the ice-free season (Prevett and Kolenosky 1982;Derocher et al. 1990a,b;Obbard and Walton 2004;Towns et al. 2010) could bias results.Further, our study design also incorporated transects perpendicular to the coastline and following the density of bears, which decreases with distance away from the coast.Arranging the overland transects along this density gradient minimized estimate bias and improved precision (Buckland et al. 2001).Both features of our study design account for the known distribution of bears during the ice-free season and are important to minimize bias and thereby improve accuracy and precision.
Modest analytical and design differences between the two studies did not significantly influence the results nor our ability to evaluate population trend and status.In the previous survey, Obbard et al. (2015) used mark-recapture distance sampling (MRDS; Laake and Borchers 2004) rather than conventional or multiple covariate distance sampling (Marques and D r a f t 20 Buckland 2003) analyses because preliminary analyses indicated that detection at distance 0 was significantly less than 1, thereby violating a fundamental assumption of distance sampling (Buckland et al. 2001).MRDS integrates distance sampling and double-observer analytical methods, allowing for estimation of detection at distance 0 and subsequent correction of the abundance estimate.In the current study, our detection of bears on and near the transect line approximated unity, meaning that we were able to generate an accurate estimate of abundance with simpler multiple covariate distance sampling models.Although right-truncation distance differed between the two studies (Obbard et al. 2015: ~2%; here: ~5%), there was a negligible impact on results.The shoulders of the detection function (i.e., the sightings near the transect line) are most important for generating estimates of density and abundance (Buckland et al. 2001).Truncating the farthest sightings improves model fit by eliminating the need to estimate spurious bumps in this sightings 'tail', with only modest impacts on estimate precision and negligible impacts on the point estimate (Buckland et al. 2001).Small differences elsewhere, including more widespread sampling in Quebec in 2016 and the incorporation of techniques to estimate abundance for the James Bay islands in 2016 (rather than relying on raw counts) similarly had trivial impacts on the results.Both the previous and current surveys met the core assumptions of distance sampling including detection on the transect line; therefore, despite the small variations in the sampling and analytical methodology, the results from the two surveys are comparable thereby enabling us to assess trend and status.
Delineation of the study area to 60 km inland along the Ontario coast of Hudson Bay and James Bay as in the previous survey was based on available scientific and traditional knowledge of the distribution of bears during the ice-free season and of denning habitat.Although we did not survey the entire inland area of SH in Ontario, extending transects farther inland would have D r a f t 21 been very expensive for minimal returns.Truncating our transects at 60 km may have resulted in some slight negative bias in the abundance estimate, but all the evidence suggests that few bears are found that far inland in September and if any were there, they would not comprise a large proportion of the subpopulation.
Traditional knowledge holders indicated that bears were occasionally observed inland in the Québec portion of the study area north of Pointe Louis XIV/Long Island at the junction of James Bay and Hudson Bay (e.g., Laforest et al. 2018, NMRWB 2018).Based on this information, we adapted our study design slightly from the 2102 survey to provide better coverage of this region.However, despite our intensive survey (transects spaced at 6-km intervals), we observed no bears in the area.No doubt, bears occasionally occur here but their density must be very low and their number would make only a small difference to the total abundance estimate.
Our results suggest that abundance in the Southern Hudson Bay subpopulation declined by 17% between 2011/12 and 2016.It has been hypothesized that distribution of bears during the ice-free season along the shores of Ontario and Manitoba varies depending on where the last ice of the season persists resulting in an inverse correlation between counts from coastal strip surveys conducted at the same time in Ontario and Manitoba (Prevett and Kolenosky 1982).This argument suggests that polar bears, especially males, may choose to remain on the ice until late in the season and as a result they may simply occupy coastal areas closest to the location of residual ice once the ice melts completely.Location of residual ice in any year would then influence distribution of bears.Hence, one explanation for the decline in abundance that we noted for SH may be that the distribution of bears shifted due to ice conditions in 2016 such that more bears came ashore within the boundary of WH.However, using a longer dataset, Stirling D r a f t et al. ( 2004) found no significant correlations (negative or positive) between annual counts in Ontario and those in Manitoba bringing this explanation into doubt.Further, results of an aerial survey conducted in WH in 2016 at about the same time as our survey provided no evidence for an unusual number of bears in the eastern portion of the range of WH, in fact that survey suggested that subpopulation had also likely declined in abundance (Dyck et al. 2017).Lastly, the pattern of ice ablation in Hudson Bay is affected by prevailing northwesterly winds and counter-clockwise ocean currents resulting in residual ice moving south and east and gathering north of the Ontario coast (Hochheim et al. 2011).Bears remain on the ice as it drifts south and east during the melt season and eventually come to shore in Manitoba or Ontario (Parks et al. 2006;Middel 2014); there is no evidence of bears moving north as ice melts.Therefore, the decline in abundance in SH suggested by our results is unlikely to be due to a shift in distribution into WH or FB.
There are interesting parallels in trends between WH and SH.In both subpopulations changes in individual-level traits (e.g., declines in body condition; WH: Stirling et al.1999, SH: Obbard et al. 2016) preceded changes in population-level traits (e.g., declines in survival and in abundance; WH: Regehr et al. 2007;Lunn et al. 2016, SH: Obbard et al. 2007; this study).
However, these changes in morphometry and demography appear to have started sooner in WH than in SH.Because of the pattern of ice ablation and formation in Hudson Bay, on an annual basis bears from the two subpopulations are faced with a similar pattern of ice duration but it is out of synchrony by a few weeks.That is because the last sea ice usually remains off the northern Ontario coast in summer (Etkin 1991;Saucier et al. 2004); therefore, bears in SH leave the ice later in spring than bears in WH, but return to the ice later in the fall because ice forms off the Ontario coast later (Hochheim and Barber 2010) .On a long-term basis, changes in the D r a f t duration of ice cover appear to have started sooner in the western portions of Hudson Bay where bears from WH mainly occur during the ice-covered season compared to the eastern portions of Hudson Bay where bears from SH mainly occur (Gagnon and Gough 2005;Hochheim et al. 2010;Hochheim and Barber 2014).Thus, the two subpopulations appear to have followed similar trajectories in response to changes in duration of sea ice, though starting later in SH, and it seems likely that these trends will continue in the future.

Reproduction
The proportion of cubs in all observations was similar in the 2011 and 2016 surveys, but the proportion of yearlings dropped from 12% to 5% (sample size from the 2012 portion of the original survey is too small for comparison).We are not aware of any evidence of reproductive synchrony in polar bear populations that would infer large variation in size of the year class of cubs born.Therefore, the low proportion of yearlings in the 2016 survey suggests low survival of cubs born in 2015.Whether this represents an ongoing trend, or was the result of unusual conditions in spring and summer of 2015 is undetermined.However, breakup in eastern Hudson Bay was about 2 weeks later in 2015 than in 2010-2014 (Andrews et al. 2018) suggesting that ice conditions should not have had a negative influence on cub survival in 2015.The proportion of yearlings in the 2016 SH survey was similar to that observed in the WH surveys of 2011 and 2016 (3%).In contrast, subpopulations with robust vital rates have proportions of yearlings in the 10-12% range, such as FB and SH in 2011 (Obbard et al. 2015).
Long-lived animals should maximize their reproductive output, but should not do so at a risk to their own survival.Because the proportion of cubs remained high in 2016, many adult females in SH are still producing litters, but they may be less successful in raising cubs to yearling age.Obbard et al. (2016) suggested that because the rate of decline in body condition D r a f t was less for cubs of the year in SH than for their mothers, by the late 2000s adult females were allocating a greater proportion of their reserves to lactation than females did in the mid-1980s.If this is true, but cub survival is still dropping, then adult females may be putting themselves at increased risk, especially in the context of ongoing declines in duration of sea ice that can be expected to have further negative effects on body condition.A more adaptive strategy for a long-lived species with delayed implantation such as polar bears (Wimsatt 1974;Ferguson et al. 1996) would be for females to forego reproductive bouts entirely when a reproductive bout is unlikely to be successful.Because the number of litters of cubs observed in 2016 in Ontario and Akimiski Island was similar to the number observed in 2011, females may not yet be adopting that life history strategy.Further, the number of litters observed in SH in both 2011 and 2016 was about double the number observed in WH at the same time suggesting that a higher proportion of SH females continue to attempt to raise cubs successfully (given that population abundance in WH is similar to that of SH) (Lunn et al. 2016;Dyck et al 2017).The low number of litters of yearlings observed in 2016 compared to the number of litters of cubs suggests that much cub mortality may be via loss of entire litters.If females lose litters due to high neonatal mortality, in the absence of lactational suppression of estrus (Knott et al. 2017) they may become receptive again shortly after returning to the sea ice in spring, resulting in them having litters in consecutive years.This may be happening in SH and, in itself, would put additional energetic demands on adult females in this subpopulation for no increase in fitness.If such energetic costs are additive they could ultimately have negative consequences for survival of adult females.

Conclusions
Though the point estimates obtained for the 2011/12 and 2016 surveys were not significantly different, point estimates of abundance are typically used to assess status (PBSG D r a f t 25 2010b).The suggestion of a decline in abundance is supported by the Monte Carlo simulations where about one-third showed a greater than 25% decline between the two estimates.Further monitoring of this subpopulation is required to determine whether the decline in abundance was a short-term response to environmental conditions or a longer-term trend.Therefore, we recommend repeating the intensive aerial survey in 2021 with additional recruitment surveys in the interim, though managers should consider whether the cost of surveying the Québec coastline can be justified in future surveys.Derocher et al. (2013) discussed several options that might be achievable for management agencies where polar bears are forced to spend longer on land due to climate warming.These options included diversionary feeding to reduce human-bear conflict, supplemental feeding to help individual bears survive periods of food deprivation, and intentional population reduction to achieve a smaller but viable population at the lowered carrying capacity brought about by loss of habitat (Derocher et al. 2013).Careful consideration of all possible management options in consultation with all communities that are harvesting this population or could be affected by an increasing presence of nutritionally stressed bears on land will be necessary to identify the best management approach in the future.In a period of rapid environmental change and barring major mitigation of greenhouse gas emissions in the near future (Amstrup et al. 2010), managers should invoke the precautionary principle and consider conservative harvest levels for this subpopulation.

Fig. 2 .Fig. 3 .
Fig. 2. Boundaries and extent of the Southern Hudson Bay polar bear subpopulation in Ontario and Québec, including islands in James Bay and eastern Hudson Bay.Inset shows location in Canada.

Fig. 5 .
Fig. 5. Distances of polar bear sightings from the transect line of the Ontario mainland and Akimiski Island, 15-25 September 2016.Data exclude bears sighted from perpendicular transects in the coastal zone.

Table 2 .
Polar bear litter sizes and number of dependent young observed as proportion of all observations during the ice-free season in the Southern Hudson Bay (SH), Western Hudson Bay (WH), and Foxe Basin (FB) subpopulations.