Forecasting the relative influence of environmental and anthropogenic stressors on polar bears
Abstract Effective conservation planning requires understanding and ranking threats to wildlife populations. We developed a Bayesian network model to evaluate the relative influence of environmental and anthropogenic stressors, and their mitigation, on the persistence of polar bears (Ursus maritimus...
Published in: | Ecosphere |
---|---|
Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2016
|
Subjects: | |
Online Access: | https://doi.org/10.1002/ecs2.1370 https://doaj.org/article/de856aa6239c4f29bd19159d182ee46e |
id |
ftdoajarticles:oai:doaj.org/article:de856aa6239c4f29bd19159d182ee46e |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:de856aa6239c4f29bd19159d182ee46e 2023-05-15T14:29:20+02:00 Forecasting the relative influence of environmental and anthropogenic stressors on polar bears Todd C. Atwood Bruce G. Marcot David C. Douglas Steven C. Amstrup Karyn D. Rode George M. Durner Jeffrey F. Bromaghin 2016-06-01T00:00:00Z https://doi.org/10.1002/ecs2.1370 https://doaj.org/article/de856aa6239c4f29bd19159d182ee46e EN eng Wiley https://doi.org/10.1002/ecs2.1370 https://doaj.org/toc/2150-8925 2150-8925 doi:10.1002/ecs2.1370 https://doaj.org/article/de856aa6239c4f29bd19159d182ee46e Ecosphere, Vol 7, Iss 6, Pp n/a-n/a (2016) Arctic Bayesian network climate change conservation greenhouse gas emissions influence analysis Ecology QH540-549.5 article 2016 ftdoajarticles https://doi.org/10.1002/ecs2.1370 2022-12-31T03:16:53Z Abstract Effective conservation planning requires understanding and ranking threats to wildlife populations. We developed a Bayesian network model to evaluate the relative influence of environmental and anthropogenic stressors, and their mitigation, on the persistence of polar bears (Ursus maritimus). Overall sea ice conditions, affected by rising global temperatures, were the most influential determinant of population outcomes. Accordingly, unabated rise in atmospheric greenhouse gas (GHG) concentrations was the dominant influence leading to worsened population outcomes, with polar bears in three of four ecoregions reaching a dominant probability of decreased or greatly decreased by the latter part of this century. Stabilization of atmospheric GHG concentrations by mid‐century delayed the greatly reduced state by ≈25 yr in two ecoregions. Prompt and aggressive mitigation of emissions reduced the probability of any regional population becoming greatly reduced by up to 25%. Marine prey availability, linked closely to sea ice trend, had slightly less influence on outcome state than sea ice availability itself. Reduced mortality from hunting and defense of life and property interactions resulted in modest declines in the probability of a decreased or greatly decreased population outcome. Minimizing other stressors such as trans‐Arctic shipping, oil and gas exploration, and contaminants had a negligible effect on polar bear outcomes, although the model was not well‐informed with respect to the potential influence of these stressors. Adverse consequences of loss of sea ice habitat became more pronounced as the summer ice‐free period lengthened beyond four months, which could occur in most of the Arctic basin after mid‐century if GHG emissions are not promptly reduced. Long‐term conservation of polar bears would be best supported by holding global mean temperature to ≤ 2°C above preindustrial levels. Until further sea ice loss is stopped, management of other stressors may serve to slow the transition of populations to ... Article in Journal/Newspaper Arctic Basin Arctic Climate change Sea ice Ursus maritimus Directory of Open Access Journals: DOAJ Articles Arctic Ecosphere 7 6 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic Bayesian network climate change conservation greenhouse gas emissions influence analysis Ecology QH540-549.5 |
spellingShingle |
Arctic Bayesian network climate change conservation greenhouse gas emissions influence analysis Ecology QH540-549.5 Todd C. Atwood Bruce G. Marcot David C. Douglas Steven C. Amstrup Karyn D. Rode George M. Durner Jeffrey F. Bromaghin Forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
topic_facet |
Arctic Bayesian network climate change conservation greenhouse gas emissions influence analysis Ecology QH540-549.5 |
description |
Abstract Effective conservation planning requires understanding and ranking threats to wildlife populations. We developed a Bayesian network model to evaluate the relative influence of environmental and anthropogenic stressors, and their mitigation, on the persistence of polar bears (Ursus maritimus). Overall sea ice conditions, affected by rising global temperatures, were the most influential determinant of population outcomes. Accordingly, unabated rise in atmospheric greenhouse gas (GHG) concentrations was the dominant influence leading to worsened population outcomes, with polar bears in three of four ecoregions reaching a dominant probability of decreased or greatly decreased by the latter part of this century. Stabilization of atmospheric GHG concentrations by mid‐century delayed the greatly reduced state by ≈25 yr in two ecoregions. Prompt and aggressive mitigation of emissions reduced the probability of any regional population becoming greatly reduced by up to 25%. Marine prey availability, linked closely to sea ice trend, had slightly less influence on outcome state than sea ice availability itself. Reduced mortality from hunting and defense of life and property interactions resulted in modest declines in the probability of a decreased or greatly decreased population outcome. Minimizing other stressors such as trans‐Arctic shipping, oil and gas exploration, and contaminants had a negligible effect on polar bear outcomes, although the model was not well‐informed with respect to the potential influence of these stressors. Adverse consequences of loss of sea ice habitat became more pronounced as the summer ice‐free period lengthened beyond four months, which could occur in most of the Arctic basin after mid‐century if GHG emissions are not promptly reduced. Long‐term conservation of polar bears would be best supported by holding global mean temperature to ≤ 2°C above preindustrial levels. Until further sea ice loss is stopped, management of other stressors may serve to slow the transition of populations to ... |
format |
Article in Journal/Newspaper |
author |
Todd C. Atwood Bruce G. Marcot David C. Douglas Steven C. Amstrup Karyn D. Rode George M. Durner Jeffrey F. Bromaghin |
author_facet |
Todd C. Atwood Bruce G. Marcot David C. Douglas Steven C. Amstrup Karyn D. Rode George M. Durner Jeffrey F. Bromaghin |
author_sort |
Todd C. Atwood |
title |
Forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
title_short |
Forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
title_full |
Forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
title_fullStr |
Forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
title_full_unstemmed |
Forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
title_sort |
forecasting the relative influence of environmental and anthropogenic stressors on polar bears |
publisher |
Wiley |
publishDate |
2016 |
url |
https://doi.org/10.1002/ecs2.1370 https://doaj.org/article/de856aa6239c4f29bd19159d182ee46e |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Basin Arctic Climate change Sea ice Ursus maritimus |
genre_facet |
Arctic Basin Arctic Climate change Sea ice Ursus maritimus |
op_source |
Ecosphere, Vol 7, Iss 6, Pp n/a-n/a (2016) |
op_relation |
https://doi.org/10.1002/ecs2.1370 https://doaj.org/toc/2150-8925 2150-8925 doi:10.1002/ecs2.1370 https://doaj.org/article/de856aa6239c4f29bd19159d182ee46e |
op_doi |
https://doi.org/10.1002/ecs2.1370 |
container_title |
Ecosphere |
container_volume |
7 |
container_issue |
6 |
_version_ |
1766303371145248768 |