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Bruce G. Marcot

Publications and source records attributed to Bruce G. Marcot.

At least 19 recordsLinked to original sources
USGS2025

Causal networks to inform decisions for ecological restoration

The release of contaminants into the environment can occur from anthropogenic activities, such as oil extraction and transportation, mining, and industrial processes. Remediation associated with reducing contaminant concentrations, and restoration that improves animals and supporting habitat, are often needed to restore ecosystems to their pre-release, baseline condition. We demonstrated the application of Bayesian Decision Networks (BDNs) with two Natural Resource Damage Assessment and Restoration (NRDAR) case studies. We use a stylized case study of riparian restoration following the remediation of a mine-impacted site to evaluate proposed restoration actions aimed at restoring Song Sparrow ( Melospiza melodia ) populations to baseline conditions. We then use a settled NRDAR case with implemented restoration in the Upper Arkansas River (UAR, Colorado, USA) to demonstrate the application of BDNs to evaluate and forecast restoration effectiveness for Brown Trout ( Salmo trutta ) (i.e., restoration effectiveness assessment). The riparian restoration model showed differences in the effects of restoration actions on Song Sparrow populations, with the time to reach baseline generally reduced with increased restoration costs, indicating trade-offs between costs and expected recovery. The UAR model showed recovery of Brown Trout populations (i.e., uplift) in response to improved instream habitat restoration, along with forecasted improvements. While the BDNs we developed were specific to two case studies, the structure is adaptable to a diversity of sites, resources, and actions. We suggest that causal network modeling can provide restoration practitioners with a decision advisory tool useful for a wide range of projects.

Environmental Management↗
USGS2025

Assessing the combined influence of biotic and anthropogenic stressors on polar bears to inform conservation planning

Developing conservation strategies for species vulnerable to the effects of climate change, like polar bears ( Ursus maritimus ), can be challenging given the uncertainty of future environmental conditions. Effective conservation planning requires identifying and ranking threats to the persistence of polar bears throughout their circumpolar range and then assessing the ability of mitigative actions to aid in meeting plan objectives. We used a Bayesian network model to (1) characterize the relative importance of multiple biotic and anthropogenic stressors on four ecoregional polar bear populations, at two future decadal time periods, and based on two Intergovernmental Panel on Climate Change (IPCC) greenhouse gas emissions scenarios (Shared Socioeconomic Pathways [SSPs] 2.6 [low] and 8.5 [high]); and (2) identify achievable management actions that may enhance the prospects of long-term persistence. Normative model runs indicated that populations in all four ecoregions incurred increasing probabilities of being decreased or greatly decreased over time. The probabilities of polar bear populations being decreased or greatly decreased from mid- to end of the century ranged from ~55% to 87% for the SSP 2.6 emissions scenario, and 82% to 94% for the SSP 8.5 emissions scenario among ecoregions. Arctic sea ice conditions and marine prey availability had the greatest influences on future polar bear population outcomes and overrode any relative influence from all other stressors. Hunting mortality was the most influential individual anthropogenic stressor in the Archipelago and Seasonal Ice Ecoregions, whereas terrestrial refugia quality grouped with various anthropogenic activities or factors (e.g., resource extraction, oil spill) was most influential for the Polar Basin Divergent Ice and Polar Basin Convergent Ice ecoregions. Our findings indicate that near-term proactive management of multiple anthropogenic stressors could cumulatively reduce the decline in populations such that if future sea ice habitat loss is eventually curtailed, population abundance would be greater than it would have been otherwise. Additionally, our findings suggest that there is value in tailoring management actions to address ecoregion-specific threats, which may prove useful in informing the development of future circumpolar conservation plans.

Ecosphere↗
USGS2024

RE-ARMing salt marshes: A resilience-experimentalist approach to prescribed fire and bird conservation in high marshes of the Gulf of Mexico

Uncertainty, complexity, and dynamic changes present challenges for conservation and natural resource management. Evidence-based approaches grounded in reliable information and rigorous analysis can enhance the navigation of the uncertainties and trade-offs inherent in conservation problems. This study highlights the importance of collaborative efforts and evidence-based decision-making, specifically implementing the Resilience-Experimentalist school of adaptive management (RE-ARM), which emphasizes stakeholder involvement, shared understanding, and experimentation. Our goal was to develop an adaptive management framework to reduce the uncertainty around the use of prescribed fire to manage the habitat for eastern black rails ( Laterallus jamaicensis jamaicensis ) and mottled ducks ( Anas fulvigula ) in saltmarshes of the Gulf of Mexico. Supported by discussions at a series of workshops, we used a value of information analysis to select a fire management hypothesis to test, developed an influence diagram to represent the system under fire management, used the influence diagram to develop a Bayesian decision network (BDN), and conducted a power analysis to guide management experiments and monitoring. Value of information analysis identified fire return interval as the critical uncertainty. Our BDN provided valuable insight into how managers believe prescribed fire influences vegetation characteristics and how vegetation influences both eastern black rail occupancy and mottled duck abundance. The results of the power analysis indicated that a standard occupancy modeling framework was more useful to compare 2- and 5-year fire return intervals for black rails than two alternative designs (removal and conditional). Our BDN can be used to predict the probability of achieving the desirable vegetative response to increase the occupancy probability of black rails and abundance of mottled ducks, and monitoring data can be used to update the BDN (learn) and improve best management practices for prescribed burns (adapt). Linking the value of information, BDNs, and power analysis enhances our understanding of the system, improves management decision-making, and builds trust among scientists, interested parties, and decision-makers. This approach lays the groundwork for knowledge co-production and adaptive management.

Frontiers in Conservation Science↗
USGS2023

Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast

Context Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands. Objectives We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area. Methods We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington. Results We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t. Conclusions All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.

California, Oregon, Washington↗
USGS2023

A novel approach to assessing natural resource injury with Bayesian networks

Quantifying the effects of environmental stressors on natural resources is problematic because of complex interactions among environmental factors that influence endpoints of interest. This complexity, coupled with data limitations, propagates uncertainty that can make it difficult to causally associate specific environmental stressors with injury endpoints. The Natural Resource Damage Assessment and Restoration (NRDAR) regulations under the Comprehensive Environmental Response, Compensation, and Liability Act and Oil Pollution Act aim to restore natural resources injured by oil spills and hazardous substances released into the environment; exploration of alternative statistical methods to evaluate effects could help address NRDAR legal claims. Bayesian networks (BNs) are statistical tools that can be used to estimate the influence and interrelatedness of abiotic and biotic environmental variables on environmental endpoints of interest. We investigated the application of a BN for injury assessment using a hypothetical case study by simulating data of acid mine drainage (AMD) affecting a fictional stream-dwelling bird species. We compared the BN-generated probability estimates for injury with a more traditional approach using toxicity thresholds for water and sediment chemistry. Bayesian networks offered several distinct advantages over traditional approaches, including formalizing the use of expert knowledge, probabilistic estimates of injury using intermediate direct and indirect effects, and the incorporation of a more nuanced and ecologically relevant representation of effects. Given the potential that BNs have for natural resource injury assessment, more research and field-based application are needed to determine their efficacy in NRDAR. We expect the resulting methods will be of interest to many US federal, state, and tribal programs devoted to the evaluation, mitigation, remediation, and/or restoration of natural resources injured by releases or spills of contaminants

Integrated Environmental Assessment and Management↗
USGS2023

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 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.

Ecological Indicators↗
USGS2021

Using decision science for monitoring threatened western snowy plovers to inform recovery

Western Snowy Plovers ( Charadrius nivosus nivosus ) are federally listed under the US Endangered Species Act as Threatened. They occur along the US Pacific coastline and are threatened by habitat loss and destruction and excessive levels of predation and human disturbance. Populations have been monitored since the 1970s for distribution, reproduction, and survival. Since the species was federally listed in 1993 and a recovery plan was approved under the US Fish and Wildlife Service in 2007, recovery actions have resulted in growing populations with increased presence at breeding and wintering sites throughout their Pacific Coast range. This success has created logistical challenges related to monitoring a recovering species and a need for identifying and instituting the best monitoring approach given recovery goals, budgets, and the likelihood of monitoring success. We devised and implemented a structured decision analysis to evaluate nine alternative monitoring strategies. The analysis included inviting plover biologists involved in monitoring to score each strategy according to a suite of performance measures. Using multi-attribute utility theory, we combined scores across the performance measures for each monitoring strategy, and applied weighted utility values to show the implications of tradeoffs and find optimal decisions. We evaluated four scenarios for weighting the monitoring objectives and how risk attitude affects optimal decisions. This resulted in identifying six strategies that best meet recovery needs and were Pareto optimal for cost-effective monitoring. Results were presented to the US Fish and Wildlife Service, responsible for monitoring as well as for consideration to ensure consistent monitoring methods across the species’ range. Our use of structured decision-making can be applied to cases of other species once imperiled but now on the road to recovery.

California, Oregon, Washington↗
USGS2020

Strategic habitat conservation for beach mice: Estimating management scenario efficiencies

The Perdido Key beach mouse ( Peromyscus polionotus trissyllepsis ), Choctawhatchee beach mouse ( P. p. allophrys ), and St. Andrew beach mouse ( P. p. peninsularis ) are 3 federally endangered subspecies that inhabit coastal dunes of Alabama and Florida, USA. Conservation opportunities for these subspecies are limited and costly. Consequently, well‐targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30‐m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post‐storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. The St. Andrew beach mouse required 5.14 km 2 of additional critical habitat to be protected and occupied. The St. Andrew beach mouse habitat objective might be achieved by first restoring protected critical habitat to good dune conditions and then protecting or restoring the unprotected critical habitat with the highest predicted probability of beach mouse presence. This scenario provided a 28% increase in management efficiency compared to a scenario that randomly protected or restored undeveloped unprotected critical habitat. In total, when coupled with established downlisting criteria, these quantitative and spatial decision support tools could provide insight into how much habitat is available, how much more is needed, and targeted conservation or restoration efforts that might efficiently achieve habitat objectives.

Alabama, Florida↗
USGS2020

Habitat of the endangered salt marsh harvest mouse (Reithrodontomys raviventris) in San Francisco Bay

Understanding habitat associations is vital for conservation of at‐risk marsh‐endemic wildlife species, particularly those under threat from sea level rise. We modeled environmental and habitat associations of the marsh‐endemic, Federally endangered salt marsh harvest mouse ( Reithrodontomys raviventris , RERA) and co‐occurrence with eight associated small mammal species from annual trap data, 1998–2014, in six estuarine marshes in North San Francisco Bay, California. Covariates included microhabitat metrics of elevation and vegetation species and cover; and landscape metrics of latitude–longitude, distance to anthropogenic features, and habitat patch size. The dominant cover was pickleweed ( Salicornia pacifica ) with 86% mean cover and 37 cm mean height, and bare ground with about 10% mean cover. We tested 38 variants of Bayesian network (BN) models to determine covariates that best account for presence of RERA and of all nine small mammal species. Best models had lowest complexity and highest classification accuracy. Among RERA presence models, three best BN models used covariates of latitude–longitude, distance to paved roads, and habitat patch size, with 0% error of false presence, 20% error of false nonpresence, and 20% overall error. The all‐species presence models suggested that within the pickleweed marsh environment, RERA are mostly habitat generalists. Accounting for presence of other species did not improve prediction of RERA. Habitat attributes compared between RERA and the next most frequently captured species, California vole ( Microtus californicus ), suggested substantial habitat overlap, with RERA habitat being somewhat higher in marsh elevation, greater in percent cover of the dominant plant species, closer to urban areas, further from agricultural areas, and, perhaps most significant, larger in continuous size of marsh patch. Findings will inform conservation management of the marsh environment for RERA by identifying best microhabitat elements, landscape attributes, and adverse interspecific interactions.

California↗
USGS2018

Estimates of tidal-marsh bird densities using Bayesian networks

Conserving tidal-marsh bird communities requires strategies to address continuing pressures from human development to the effects of increasing rates of sea-level rise. Knowing tidal-marsh bird distributions and population sizes are important for developing these strategies. In the Northeast United States, where estimates of sea-level rise are 3 times higher than the global average, 5 bird species are tidal-marsh specialists: clapper rail (Rallus crepitans), willet (Tringa semipalmata), Nelson's sparrow (Ammospiza nelsoni), saltmarsh sparrow (A. caudacuta), and seaside sparrow (A. maritima). We used a regional marsh bird survey to develop Bayesian network models to identify factors that influence patch-scale species density and to estimate regional population sizes. We modeled species density as a function of habitat covariates at the patch, local, landscape, and regional spatial scales. Densities were most sensitive to patch location and dimension, patch geomorphic setting, indices of human development, and changes in mean sea level. We estimated 110,000 clapper rails (95% CI = 61,000–159,000), 111,000 willets (95% CI = 70,000–152,000), 7,000 Nelson's sparrows (95% CI = 4,000–10,000), 60,000 saltmarsh sparrows (95% CI = 40,000–80,000), and 234,000 seaside sparrows (95% CI = 112,000–356,000) from the United States–Canada border to, and including, the mouth of the Chesapeake Bay, Virginia, USA. Our abundance estimates can be used to identify priority conservation areas at multiple geographic scales and our models help identify key habitat and landscape components for tidal-marsh restoration and management to benefit tidal-marsh birds and can be modified for other species.

Maine, New Hampshire, Massachusetts, Rhode Island,↗
USGS2017

Five-year external reviews of the eight Department of Interior Climate Science Centers: Alaska Climate Science Center

This report primarily addresses the first two purposes of the review while providing comments on the third as identified by the science review team (SRT). A separate report of recommendations for the recompetition, based upon compiled observation from all three reviews conducted in 2016, was submitted to NCCWSC on April 15, 2016 to assist with the development of recompetition documents. To further address host-university administrative competencies and efficiencies, separate interviews of host-university faculty and administrators were conducted by NCCWSC staff in conjunction with the on-site component of the reviews.

Alaska↗
USGS2016

Forecasting the relative influence of environmental and anthropogenic stressors on polar bears

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 progressively worsened outcomes, and improve the prospects for their long-term persistence.

Ecosphere↗
USGS2016

The impacts of human recreation on brown bears (Ursus arctos): A review and new management tool

Increased popularity of recreational activities in natural areas has led to the need to better understand their impacts on wildlife. The majority of research conducted to date has focused on behavioral effects from individual recreations, thus there is a limited understanding of the potential for population-level or cumulative effects. Brown bears (Ursus arctos) are the focus of a growing wildlife viewing industry and are found in habitats frequented by recreationists. Managers face difficult decisions in balancing recreational opportunities with habitat protection for wildlife. Here, we integrate results from empirical studies with expert knowledge to better understand the potential population-level effects of recreational activities on brown bears. We conducted a literature review and Delphi survey of brown bear experts to better understand the frequencies and types of recreations occurring in bear habitats and their potential effects, and to identify management solutions and research needs. We then developed a Bayesian network model that allows managers to estimate the potential effects of recreational management decisions in bear habitats. A higher proportion of individual brown bears in coastal habitats were exposed to recreation, including photography and bear-viewing than bears in interior habitats where camping and hiking were more common. Our results suggest that the primary mechanism by which recreation may impact brown bears is through temporal and spatial displacement with associated increases in energetic costs and declines in nutritional intake. Killings in defense of life and property were found to be minimally associated with recreation in Alaska, but are important considerations in population management. Regulating recreation to occur predictably in space and time and limiting recreation in habitats with concentrated food resources reduces impacts on food intake and may thereby, reduce impacts on reproduction and survival. Our results suggest that decisions managers make about regulating recreational activities in time and space have important consequences for bear populations. The Bayesian network model developed here provides a new tool for managers to balance demands of multiple recreational activities while supporting healthy bear populations.

PLoS ONE↗
USGS2015

Projected changes in wildlife habitats in Arctic natural areas of northwest Alaska

We project the effects of transitional changes among 60 vegetation and other land cover types (“ecotypes”) in northwest Alaska over the 21st century on habitats of 162 bird and 39 mammal species known or expected to occur regularly in the region. This analysis, encompassing a broad suite of arctic and boreal wildlife species, entailed building wildlife-habitat matrices denoting levels of use of each ecotype by each species, and projecting habitat changes under historic and expected accelerated future rates of change from increasing mean annual air temperature based on the average of 5 global climate models under the A1B emissions scenario, and from potential influence of a set of 23 biophysical drivers. Under historic rates of change, we project that 52 % of the 201 species will experience an increase in medium- and high-use habitats, 3 % no change, and 45 % a decrease, and that a greater proportion of mammal species (62 %) will experience habitat declines than will bird species (50 %). Outcomes become more dire (more species showing habitat loss) under projections made from effects of biophysical drivers and especially from increasing temperature, although species generally associated with increasing shrub and tree ecotypes will likely increase in distribution. Changes in wildlife habitats likely will also affect trophic cascades, ecosystem function, and ecosystem services; of particular significance are the projected declines in habitats of most small mammals that form the prey base for mesocarnivores and raptors, and habitat declines in 25 of the 50 bird and mammal species used for subsistence hunting and trapping.

Alaska↗
USGS2015

Projected changes in diverse ecosystems from climate warming and biophysical drivers in northwest Alaska

Climate warming affects arctic and boreal ecosystems by interacting with numerous biophysical factors across heterogeneous landscapes. To assess potential effects of warming on diverse local-scale ecosystems (ecotypes) across northwest Alaska, we compiled data on historical areal changes over the last 25–50 years. Based on historical rates of change relative to time and temperature, we developed three state-transition models to project future changes in area for 60 ecotypes involving 243 potential transitions during three 30-year periods (ending 2040, 2070, 2100). The time model, assuming changes over the past 30 years continue at the same rate, projected a net change, or directional shift, of 6 % by 2100. The temperature model, using past rates of change relative to the past increase in regional mean annual air temperatures (1 °C/30 year), projected a net change of 17 % in response to expected warming of 2, 4, and 6 °C at the end of the three periods. A rate-adjusted temperature model, which adjusted transition rates (±50 %) based on assigned feedbacks associated with 23 biophysical drivers, estimated a net change of 13 %, with 33 ecotypes gaining and 23 ecotypes losing area. Major drivers included shrub and tree expansion, fire, succession, and thermokarst. Overall, projected changes will be modest over the next century even though climate warming increased transition rates up to 9 fold. The strength of this state-transition modeling is that it used a large dataset of past changes to provide a comprehensive assessment of likely future changes associated with numerous drivers affecting the full diversity of ecosystems across a broad region.

Alaska↗
USGS2015

Activity-specific ecological niche models for planning reintroductions of California condors (Gymnogyps californianus)

Ecological niche models can be a useful tool to identify candidate reintroduction sites for endangered species but have been infrequently used for this purpose. In this paper, we (1) develop activity-specific ecological niche models (nesting, roosting, and feeding) for the critically endangered California condor ( Gymnogyps californianus ) to aid in reintroduction planning in California, Oregon, and Washington, USA, (2) test the accuracy of these models using empirical data withheld from model development, and (3) integrate model results with information on condor movement ecology and biology to produce predictive maps of reintroduction site suitability. Our approach, which disentangles niche models into activity-specific components, has applications for other species where it is routinely assumed (often incorrectly) that individuals fulfill all requirements for life within a single environmental space. Ecological niche models conformed to our understanding of California condor ecology, had good predictive performance when tested with data withheld from model development, and aided in the identification of several candidate reintroduction areas outside of the current distribution of the species. Our results suggest there are large unoccupied regions of the California condor’s historical range that have retained ecological features similar to currently occupied habitats, and thus could be considered for future reintroduction efforts. Combining our activity-specific ENMs with ground reconnaissance and information on other threat factors that could not be directly incorporated into empirical ENMs will ultimately improve our ability to select successful reintroduction sites for the California condor.

California, Oregon, Washington↗
USGS2015

Evaluating and ranking threats to the long-term persistence of polar bears

The polar bear ( Ursus maritimus ) was listed as a globally threatened species under the U.S. Endangered Species Act (ESA) in 2008, mostly due to the significant threat to their future population viability from rapidly declining Arctic sea ice. A core mandate of the ESA is the development of a recovery plan that identifies steps to maintain viable populations of a listed species. A substantive evaluation of the relative influence of putative threats to population persistence is helpful to recovery planning. Because management actions must often be taken in the face of substantial information gaps, a formalized evaluation hypothesizing potential stressors and their relationships with population persistence can improve identification of relevant conservation actions. To this end, we updated a Bayesian network model previously used to forecast the future status of polar bears worldwide. We used new information on actual and predicted sea ice loss and polar bear responses to evaluate the relative influence of plausible threats and their mitigation through management actions on the persistence of polar bears in four ecoregions. We found that polar bear outcomes worsened over time through the end of the century under both stabilized and unabated greenhouse gas (GHG) emission pathways. Under the unabated pathway (i.e., RCP 8.5), the time it took for polar bear populations in two of four ecoregions to reach a dominant probability of greatly decreased was hastened by about 25 years. Under the stabilized GHG emission pathway (i.e., RCP 4.5), where GHG emissions peak around the year 2040, the polar bear population in the Archipelago Ecoregion of High Arctic Canada never reached a dominant probability of greatly decreased, reinforcing earlier suggestions of this ecoregion’s potential to serve as a long-term refugium. The most influential drivers of adverse polar bear outcomes were declines to overall sea ice conditions and to the marine prey base. Improved sea ice conditions substantively lowered the probability of a decreased or greatly decreased outcome, while an elevated marine prey base was slightly less influential in lowering the probability of a decreased or greatly decreased outcome. Stressors associated with in situ human activities exerted considerably less influence on population outcomes. Reduced mortality from hunting and defense of life and property interactions resulted inmodest 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 point-source pollution had negligible effects on polar bear outcomes, but that could be attributed to uncertainties in the ecological relevance of those specific stressors. Our findings suggest adverse consequences of loss of sea ice habitat become more pronounced as the summer ice-free period lengthens beyond 4 months, which could occur in portions of the Arctic by the middle of this century under the unabated pathway. The long-term persistence of polar bears may be achieved through ameliorating the loss of sea ice habitat, which will likely require stabilizing CO 2 emissions at or below the ceiling represented by RCP 4.5. Management of other stressors may serve to slow the transition of polar bear populations to progressively worsened outcomes, and improve the prospects of persistence, pending GHG mitigation.

Open-File Report↗