Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic
Updating predictions of the response of high-profile, at-risk species to climate change and anthropogenic stressors is vital for informing effective conservation action. Here, we review two prior generations of Bayesian network probability models predicting changes in global polar bear (Ursus mariti...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23012724 |
| _version_ | 1797643576768724992 |
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| author | Bruce G. Marcot Todd C. Atwood David C. Douglas Jeffrey F. Bromaghin Anthony M. Pagano Steven C. Amstrup |
| author_facet | Bruce G. Marcot Todd C. Atwood David C. Douglas Jeffrey F. Bromaghin Anthony M. Pagano Steven C. Amstrup |
| author_sort | Bruce G. Marcot |
| collection | DOAJ |
| description | Updating predictions of the response of high-profile, at-risk species to climate change and anthropogenic stressors is vital for informing effective conservation action. Here, we review two prior generations of Bayesian network probability models predicting changes in global polar bear (Ursus maritimus) population status, and provide a contemporary update based on recent research findings and sea-ice projections by newer climate models. We compare predictions of polar bear population response from all 3 models among four circumpolar Arctic ecoregions, using sea ice projections based on three IPCC greenhouse gas emissions scenarios (SSP2.6, 4.5, 8.5). Consistent with the previous two model generations, polar bears will continue to experience increasing probability of declining or greatly declining populations throughout the 21st century, varying by emission scenario. Populations within the Polar Basin Divergent Ice Ecoregion have the highest predicted probability of declines, but predictions were slightly less dire relative to the previous model generation. Most of the influence, denoted by model sensitivity analysis, is from expected degradation and loss of sea ice and reduced access to marine prey. The lack of terrestrial prey adequate to substitute for loss of access to marine prey, as well as human-caused bear morality associated with hunting and defense of life and property encountered when polar bears are increasingly forced ashore also contributed to predicted declines. Although some tidewater glacial fjords and other localized onshore resources may provide local refugia, their benefit is transient. Our findings continue to inform priorities for inventory, monitoring, and research needs, and suggest that similar updates to models of other at-risk species can capitalize on the comparison framework we present here. |
| first_indexed | 2024-03-11T14:16:50Z |
| format | Article |
| id | doaj.art-1313f571458d474ea33243419b5fcf60 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-11T14:16:50Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-1313f571458d474ea33243419b5fcf602023-11-01T04:46:35ZengElsevierEcological Indicators1470-160X2023-12-01156111130Incremental evolution of modeling a prognosis for polar bears in a rapidly changing ArcticBruce G. Marcot0Todd C. Atwood1David C. Douglas2Jeffrey F. Bromaghin3Anthony M. Pagano4Steven C. Amstrup5Pacific Northwest Research Station, U.S. Forest Service, Portland, OR 97204 USA; Corresponding author at: Portland Forestry Sciences Laboratory, Pacific Northwest Research Station, U.S. Forest Service, 1220 SW 3rd Ave., Suite 1410, Portland, Oregon 97204 USA.Alaska Science Center, U.S. Geological Survey, Anchorage, AK 99508 USAAlaska Science Center, U.S. Geological Survey, Juneau, AK 99801 USAAlaska Science Center, U.S. Geological Survey, Anchorage, AK 99508 USAAlaska Science Center, U.S. Geological Survey, Anchorage, AK 99508 USAPolar Bears International®, Bozeman, Montana 59772 USAUpdating predictions of the response of high-profile, at-risk species to climate change and anthropogenic stressors is vital for informing effective conservation action. Here, we review two prior generations of Bayesian network probability models predicting changes in global polar bear (Ursus maritimus) population status, and provide a contemporary update based on recent research findings and sea-ice projections by newer climate models. We compare predictions of polar bear population response from all 3 models among four circumpolar Arctic ecoregions, using sea ice projections based on three IPCC greenhouse gas emissions scenarios (SSP2.6, 4.5, 8.5). Consistent with the previous two model generations, polar bears will continue to experience increasing probability of declining or greatly declining populations throughout the 21st century, varying by emission scenario. Populations within the Polar Basin Divergent Ice Ecoregion have the highest predicted probability of declines, but predictions were slightly less dire relative to the previous model generation. Most of the influence, denoted by model sensitivity analysis, is from expected degradation and loss of sea ice and reduced access to marine prey. The lack of terrestrial prey adequate to substitute for loss of access to marine prey, as well as human-caused bear morality associated with hunting and defense of life and property encountered when polar bears are increasingly forced ashore also contributed to predicted declines. Although some tidewater glacial fjords and other localized onshore resources may provide local refugia, their benefit is transient. Our findings continue to inform priorities for inventory, monitoring, and research needs, and suggest that similar updates to models of other at-risk species can capitalize on the comparison framework we present here.http://www.sciencedirect.com/science/article/pii/S1470160X23012724Model evolutionPolar bearClimate changeArctic sea iceBayesian network |
| spellingShingle | Bruce G. Marcot Todd C. Atwood David C. Douglas Jeffrey F. Bromaghin Anthony M. Pagano Steven C. Amstrup Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic Ecological Indicators Model evolution Polar bear Climate change Arctic sea ice Bayesian network |
| title | Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic |
| title_full | Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic |
| title_fullStr | Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic |
| title_full_unstemmed | Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic |
| title_short | Incremental evolution of modeling a prognosis for polar bears in a rapidly changing Arctic |
| title_sort | incremental evolution of modeling a prognosis for polar bears in a rapidly changing arctic |
| topic | Model evolution Polar bear Climate change Arctic sea ice Bayesian network |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23012724 |
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