Resilience and risk: a demographic model to inform conservation planning for polar bears

Abstract

For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment-visit http://www.usgs.gov or call 1-888-ASK-USGS (1-888-275-8747) For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.Suggested citation: Regehr, E.V., Wilson, R.R., Rode, K.D., and Runge, M.C., 2015, Resilience and risk-A demographic model to inform conservation planning for polar bears: U.S. Geological Survey Open-File Report 2015-1029, 56 p., http://dx.doi.org/10.3133/ofr20151029. ISSN 2331ISSN -1258 iii Table 5. Range of survival rates that must be maintained, in conjunction with sufficient recruitment, to achieve a 90-percent probability of persistence over 100 years . Executive SummaryClimate change is having widespread ecological effects, including loss of Arctic sea ice. This has led to listing of the polar bear (Ursus maritimus) and other ice-dependent marine mammals under the U.S. Endangered Species Act. Methods are needed to evaluate the effects of climate change on population persistence to inform recovery planning for listed species. For polar bears, this includes understanding interactions between climate and secondary factors, such as subsistence harvest, which provide economic, nutritional, or cultural value to humans.We developed a matrix-based demographic model for polar bears that can be used for population viability analysis and to evaluate the effects of human-caused removals. This model includes densitydependence (the potential for a declining environmental carrying capacity), density-independent limitation, and sex-and age-specific harvest vulnerabilities. We estimated values of adult female survival (0.93-0.96), recruitment (number of yearling cubs per adult female; 0.1-0.3), and carrying capacity (>250 animals) that must be maintained for a hypothetical population to achieve a 90-percent probability of persistence over 100 years.We also developed a state-dependent management framework, based on harvest theory and the potential biological removal method, by linking the demographic model to simulated population assessments. This framework can be used to estimate the maximum sustainable rate of human-caused removals, including subsistence harvest, which maintains a population at its maximum net productivity level. The framework also can be used to calculate a recommended sustainable harvest rate, which generally is lower than the maximum sustainable rate and depends on management objectives, the precision and frequency of population data, ...

Demography of an apex predator at the edge of its range: impacts of changing sea ice on polar bears in Hudson Bay

“…These findings emphasize the importance of understanding and incorporating the complexities of relationships between vital rates and environmental conditions in demographic assessments for management and conservation planning (Regehr et al. ), while highlighting the sensitivity of such assessments to variation and uncertainty in future environmental conditions.…”

“…, ), may not be suitable tools for addressing local management questions over shorter timeframes (e.g., setting of subsistence harvest levels) or for understanding how climate change and management actions interact to affect population viability (Regehr et al. ).…”

Conservation status of polar bears (Ursus maritimus) in relation to projected sea-ice declines

“…Future global population assessments could explore the use of hierarchical models [22], integrate data from multiple sources [23], model population processes (e.g. density-dependent interactions between harvest and habitat loss; [17]), consider cumulative effects on polar bear health [24] or consider nonlinear or spatial responses [25]. …”

“…Approach 3 estimated a separate ice – N relationship for each polar bear ecoregion using a dataset that was similar to approach 2 but included longer time series of N available for four subpopulations. All approaches assumed that changes in N were mediated primarily through changes in K or density-independent habitat effects, and that the ratio N / K was stable relative to other factors [17]. These assumptions were established on the basis that polar bears depend fundamentally on sea ice, that sea-ice changes represent the main source of habitat modification for the species [5], and that other potential stressors are either secondary (e.g.…”

Polar bear attacks on humans: Implications of a changing climate

“…Subsequent to 1973, measures implemented by the Range States, such as increased research and monitoring, cooperative harvest management programs, and establishment of protected areas, were presumed to have either stabilized, or led to the recovery of, subpopulations that had experienced excessive unregulated harvest (Amstrup et al , Prestrud and Sterling ). Today, polar bears are legally harvested by Indigenous peoples in Alaska, Canada, and Greenland, and harvest levels in most subpopulations are well managed and occur at a rate that does not have a negative effect on population viability (Obbard et al , Regehr et al ).…”