Effects of sea ice fragmentation on polar bear migratory movement in Hudson Bay

Biddlecombe, Brooke A.; Bayne, Erin M.; Lunn, Nicholas J.; McGeachy, David; Derocher, Andrew E.

doi:10.3354/meps13684

Cited by 9 publications

(10 citation statements)

References 75 publications

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“…We hypothesized that greater percentages of open water and lower percentages of sea ice concentration would increase UDs as bears would move greater distances in response to increased habitat fragmentation. Such increases in UDs in response to fragmentation could reflect northward movements of bears away from deteriorating sea ice toward stable ice over the deep waters of the Arctic Basin (Ware et al 2017, Durner et al 2019, Pagano et al 2020 as well as higher rates of sea ice drift experienced on low concentration sea ice (Durner et al 2017, Biddlecombe et al 2021.…”

Section: Introductionmentioning

confidence: 99%

Effects of sea ice decline and summer land use on polar bear home range size in the Beaufort Sea

et al. 2021

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Animals responding to habitat loss and fragmentation may increase their home ranges to offset declines in localized resources or they may decrease their home ranges and switch to alternative resources. In many regions of the Arctic, polar bears (Ursus maritimus) exhibit some of the largest home ranges of any quadrupedal mammal. Polar bears are presently experiencing a rapid decline in Arctic sea ice extent and a change in sea ice composition. For the Southern Beaufort Sea subpopulation of polar bears, this has resulted in a divergent movement pattern where most of the subpopulation remains on the sea ice in the summer melt season while the remainder move to land. We evaluated the effects of summer land use and maternal denning on the annual and seasonal utilization distribution size (i.e., home range) of adult female polar bears in the Southern Beaufort Sea subpopulation over 30 yr during a period of rapid sea ice decline. For bears that remained on the summer sea ice, model-derived mean annual utilization distributions were 64% larger in 1999-2016 (x = 176,000 km 2 ) relative to 1986-1998 (x = 107,000 km 2 ). This increase was primarily driven by increases in summer utilization distributions that encompassed increased amounts of open water and decreased amounts of preferred sea ice. The mean centroid of summer utilization distributions for bears that remained on the sea ice was 193 km further northnortheast in 1999-2016. In contrast, bears that summered on land during 1999-2016 exhibited 88% smaller mean annual utilization distribution sizes (x = 22,000 km 2 ) relative to bears that remained on the summer sea ice during the same period. Our findings highlight the impacts of sea ice declines on polar bear space use and the increasing importance of land as an alternative summer refuge.

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Section: Introductionmentioning

confidence: 99%

Effects of sea ice decline and summer land use on polar bear home range size in the Beaufort Sea

et al. 2021

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“…We hypothesized two effects of ice concentration on polar bear foraging. First, lower ice concentrations are more energetically costly to move through, wherein bears may have to travel longer distances to avoid swimming (Sahanatien and Derocher, 2012;Biddlecombe et al, 2021), which use significantly more energy than walking (Durner et al, 2011;Griffen, 2018). Second, ice concentration may influence the distribution 20 and accessibility of seals.…”

Section: State Probabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Reduction in sea ice has led to increased the energetic cost of travel. Greater habitat fragmentation has increased polar bear path tortuosity (Biddlecombe et al, 2021), more open water has increased the frequency of long-distance swimming events (Pilfold et al, 2016; Pagano et al, 2020), and increased ice drift speed has increased the cost of station-keeping (Mauritzen et al, 2003; Auger-Méthé et al, 2016; Durner et al, 2017). Further, polar bears have exhibited shifts in distribution (Lone et al, 2018), reduced access to prey (Stirling et al, 2008; Ware et al, 2017; Florko et al, 2020b), a longer fasting period (Rode et al, 2021), increased exposure to zoonotic pathogens (Pilfold et al, 2021), higher levels of cortisol (Boonstra et al, 2020), reduced body condition (Stirling and Parkinson, 2006; Rode et al, 2021), reduced access to denning habitat (Rode et al, 2021; Merkel and Aars, 2022), reduced reproduction (Stirling et al, 1999), and consequently reduced abundance in several populations (Regehr et al, 2007; Lunn et al, 2016; Regehr et al, 2016; Obbard et al, 2018; Bromaghin et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Drivers of polar bear behavior, and the possible effects of prey availability on foraging strategy

Togunov

Derocher

Lunn

et al. 2022

Preprint

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Change in behavior is one of the earliest measurable responses to variation in habitat suitability, making the study of factors that promote behaviors particularly important in areas undergoing environmental change. We applied hidden Markov models to remote movement data of 14 polar bears, Ursus maritimus, from Western Hudson Bay, Canada between 2011 and 2021 during the foraging season (January--June) when bears inhabit the sea ice. The model incorporated bear movement and orientation relative to wind to classify three behaviors (stationary/drifting, area-restricted search, and olfactory search), and investigated 11 factors to identify conditions that may promote these behaviors. In contrast to other polar bear populations, we found high levels of evening activity, with active behaviors peaking around 20:00. We identified an increase in activity as the ice-covered season progressed. This apparent shift in foraging strategy from still-hunting to active search corresponds to a shift in prey availability (i.e., increase in haul-out behavior from early winter to the spring pupping and molting seasons). Last, we described spatial patterns of distribution with respect to season and ice concentration that may be indicative of variation in habitat quality and segregation by bear age that may reflect competitive exclusion. Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings compared to other populations could be explained by variation in regional or temporal variation in resource abundance or distribution. Our findings and methodology can help identify periods, locations, and environmental conditions associated with habitat quality and can improve our understanding polar bear behavioral ecology and aid conservation.

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“…Reduction in sea ice has led to an increase in the energetic cost of travel. Greater habitat fragmentation has increased polar bear path tortuosity [ 9 ], more open water has increased the frequency of long-distance swimming events [ 105 , 115 ], and increased ice drift speed has increased the cost of station-keeping [ 5 , 34 , 90 ]. Further, polar bears have exhibited shifts in distribution [ 85 ], reduced access to prey [ 45 , 147 , 160 ], a longer fasting period [ 127 ], increased exposure to zoonotic pathogens [ 116 ], higher levels of cortisol [ 13 ], reduced body condition [ 127 , 144 ], reduced access to denning habitat [ 96 , 127 ], reduced reproduction [ 146 ], and consequently reduced abundance in several populations [ 14 , 87 , 101 , 123 , 124 ].…”

Section: Introductionmentioning

confidence: 99%

Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy

et al. 2022

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Background Change in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remote tracking can be used to study ethology when direct observation is not possible. Methods We used movement data from 14 polar bears (Ursus maritimus) in Hudson Bay, Canada, during the foraging season (January–June), when bears inhabit the sea ice. We developed an error-tolerant method to correct for sea ice drift in tracking data. Next, we used hidden Markov models with movement and orientation relative to wind to study three behaviors (stationary, area-restricted search, and olfactory search) and examine effects of 11 covariates on behavior. Results Polar bears spent approximately 47% of their time in the stationary drift state, 29% in olfactory search, and 24% in area-restricted search. High energy behaviors occurred later in the day (around 20:00) compared to other populations. Second, olfactory search increased as the season progressed, which may reflect a shift in foraging strategy from still-hunting to active search linked to a shift in seal availability (i.e., increase in haul-outs from winter to the spring pupping and molting seasons). Last, we found spatial patterns of distribution linked to season, ice concentration, and bear age that may be tied to habitat quality and competitive exclusion. Conclusions Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings and other populations could be explained by regional or temporal variation in resource availability. Our novel movement analyses and finding can help identify periods, regions, and conditions of critical habitat.

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Effects of sea ice fragmentation on polar bear migratory movement in Hudson Bay

Cited by 9 publications

References 75 publications

Effects of sea ice decline and summer land use on polar bear home range size in the Beaufort Sea

Effects of sea ice decline and summer land use on polar bear home range size in the Beaufort Sea

Drivers of polar bear behavior, and the possible effects of prey availability on foraging strategy

Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy

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