Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Ursus”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27Linked to original sources
USGS1980

The natural food habits of grizzly bears in Yellowstone National Park, 1973-74

The natural food habits of grizzly bears ( Ursus arctos horribilis Ord) in Yellowstone National Park were investigated in 1973-74 to identify the grizzly's energy sources and trophic level(s), nutrient use, and distribution. Food consumption was determined by scat analysis and field observations. Food quality and digestibility were estimated by chemical analysis. Grizzlies were distributed in 3 distinctive feeding economies: valley / plateau , a grass/rodent economy where grizzlies were intensive diggers; mountain , primarily a grass/springbeauty/root economy where grizzlies were casual diggers; and lake , primarily a fish/grass economy where grizzlies were fishers. The economies occurred in areas with fertile soils; distribution of bears within each was related to the occurrence of succulent plants. The feeding cycle in the valley/plateau and mountain economies followed plant phenology. Grizzlies fed primarily on meat before green-up and on succulent herbs afterwards; meat, corms, berries, and nuts became important during the postgrowing season. Succulent grasses and sedges with an importance value percentage of 78.5 were the most important food items consumed. Protein from animal tissue was more digestible than protein from plant tissue. Storage fats were more digestible than structural fats. Food energy and digestibility were directly related. Five principle nutrient materials (listed with their percentage digestibilities) contributed to total energy intake: protein from succulent herbs, 42.8; protein and fat from animal material, 78.1; fat and protein from pine nuts, 73.6; starch, 78.8; and sugar from berries and fruits, digestibility undetermined. Protein from succulent herbs, with a nutritive value percentage of 77.3, was the grizzlies' primary energy source. Because succulent, preflowering herbs had higher protein levels than dry, mature herbs, grizzly use of succulent herbs guaranteed them the highest source of herbaceous protein. Low protein digestibility of succulent herbs was compenstated for by high intake. Grizzlies were digestively flexible and maximized use of protein from plant and animal sources. They were adapted to the most constant and abundant sources of protein: succulent herbs and animal material from open, fertile grasslands. Competition among grizzlies for animal food during the pregrowing season may be regulatory for the grizzly population. The grizzly population level can be partially accounted for by the grizzlies' status as secondary consumers during pregreen-up periods and primary consumers during the growing and postgrowing seasons. The essential environmental requirement was the availability of fertile grasslands and herblands interspersed with cover and capable of maintaining artiodactyls, rodents, and abundant nutritious herbs as sources of food.

Yellowstone National Park↗
USGS1980

Movements of radio-instrumented grizzly bears within the Yellowstone area

Grizzly bear ( Ursus arctos horribilis ) movement patterns were studied with the aid of 18 radio-instrumented grizzly bears in 1975 and 1976. Five bears gave minimal information because of death, transmitter failure, or loss of transmitters. Seasonal home range information is presented for 13 bears. Two bears, trapped inside Yellowstone National Park, included areas outside of the park in their home ranges. Twelve bears trapped outside included parts of the park in their home ranges. Three females with young gave no indication of having smaller home ranges than other individuals. Movement patterns prior to denning and dates of denning varied among individual bears.

Yellowstone National Park↗
USGS1983

Possible relationships between trichinellosis and abnormal behavior in bears

Data compiled from parasite studies of grizzly bears ( Ursus arctos ) and black bears ( U. americanus ) in the Yellowstone and Glacier National Park populations and surrounding areas of Montana and Wyoming during 1969-79 are reviewed with reference to the possible influence of infection with the muscleworm Trichinella sp. on bear behavior. In grizzly bears, the high prevalence of this parasite (61% of 254 bears infected), the elevated larval concentrations in sensitive anatomical sites such as the tongue (average, 51 larvae per gram of tissue), and the chronic nature of bear infections as indicated by the tendency for highest infection rates to occur in older age classes (> 16 yrs.), suggest a potential behavior-modifying effect might exist. However, retrospective analysis of recent human attacks by 4 grizzlies and 2 black bears in the northern Rocky Mountain region failed to demonstrate a consistent connection between erratic conduct and levels of Trichinella larvae (trichinae) in bear tissues. Clinical similarities of trichinellosis in bears and humans are hypothesized, and possible behavioral effects of ursine trichinellosis are discussed.

Book chapter↗
USGS1995

Appraising status of the Yellowstone grizzly bear population by counting females with cubs-of-the-year

The grizzly bear ( Ursus arctos horriblilis ) in the lower United States was declared threatened in 1975 under the Endangered Species Act of 1973 (16 U.S.C. 15-31-1544). According to that Act, the U.S. Fish and Wildlife Service had to prepare a plan to recover populations to levels where the species could be conserved and delisted from its threatened status. The Recovery Plan (U.S. Fish and Wildlife Service 1993) uses counts of distinct females with cubs-of-the-year as a recovery parameter in several grizzly bear ecosystems. The total number of these females is assumed to be the minimum number with cubs born in the current year. To our knowledge, this technique, its methodology, and value as a population indicator have never been adequately explained or discussed. Thus, we describe the methodology and assess its potential for continued use in the Yellowstone ecosystem.

Wildlife Society Bulletin↗
USGS2004

Oak-black bear relationships in southeastern uplands

Bears ( Ursus americanus ) primarily occur in upland habitats in the Southeast because uplands were the last to be developed for agriculture and were more likely to become publicly owned. National parks and forests created in the early to mid-1900s served as sources to supply surrounding uplands with bears. Bears could not survive in southeastern uplands without oak mast. Bear reproductive and mortality rates in the region have been shown to be directly linked with acorn production. Masting is thought to be an adaptation by oaks to satiate predators during good acorn years, thus ensuring that the remainder will germinate. Acorn predator populations, however, cannot respond numerically to increased acorn production because the masting is episodic and synchronous. Consequently, bears have developed physiological, behavioral, and ecological adaptations to cope with such food shortages. Despite such adaptations, upland hardwood forests in the Southeast are of lower quality than they once were. The loss of the American chestnut ( Castanea dentata ), higrading, and soil degradation have markedly decreased the carrying capacity for bears and other wildlife. Other changes such as recent forest management practices, forest fragmentation, invasion by the gypsy moth ( Lymantria dispar ), and oak decline threaten to further degrade the capability of southeastern uplands to support bears.

Report↗
USGS1994

A demographic comparison of two black bear populations in the Interior Highlands of Arkansas

The Ozark and Ouachita mountain regions of western Arkansas, collectively known as the Interior Highlands, historically supported large numbers of black bears ( Ursus americanus ). Indiscriminate killing of bears by early settlers and subsequent habitat reductions due to extensive logging and changes in land use resulted in their decline (Smith et al. 1991). By the late 1940's, bears had been extirpated from both regions (Holder 1951). Between 1958 and 1968, Arkansa Game and Fish Commission (ACFC) Officials trapped 254 black bears in northern Minnesota and Manitoba, Canada and released them in the Interior Highlands (Rogers 1973, Smith et al. 1991d). Since then, bear numbers have dramatically increased, making the Arkansas reintroduction the most successful attempted for black bears (Smith et al. 1991). Hunts have been conducted each autumn or winter since 1980. Because little was known about bear demographics and sustainable harvest in the Interior Highlands, however, hunting regulations have been restrictive with 5-31 bears harvested/year (J.D. Clark, AGFC Annu. Harvest Rep., 1980-1988). Bears now range throughout the Ozark Mountains and Ouachita Mountains, but these regional populations are allopatric, separated by the Arkansas River Valley and Interstate 40 (J.D. Clark, unpubl. data). Past reintroduction strategies and harvest levels differed between the 2 regions, with more intensive restocking and hunting in the Ozark region. Habitat also differs with the Ozark Mountains primarily oak-hickory ( Quercus spp.- Carya spp.) upland forest compared to pine ( Pinus spp.) and mixed pine-hardwood forest in the Ouachita Mountais (Smith 1989). Because habitat quality has been shown to be the major factor affecting black bear productivity (Rogers 1976, Bunnell and Tait 1981, Elowe and Dodge 1989) and bear populations are susceptible to overharvest, our objectives were to: 1) estimate population growth and sustainable yield for populations in both regions and 2) determine whether different environmental conditions in the 2 regions resulted in differences in demographic parameters.

Arkansas↗
USGS2016

New challenges for grizzly bear management in Yellowstone National Park

A key factor contributing to the success of grizzly bear Ursus arctos conservation in the Greater Yellowstone Ecosystem has been the existence of a large protected area, Yellowstone National Park. We provide an overview of recovery efforts, how demographic parameters changed as the population increased, and how the bear management program in Yellowstone National Park has evolved to address new management challenges over time. Finally, using the management experiences in Yellowstone National Park, we present comparisons and perspectives regarding brown bear management in Shiretoko National Park.

Bulletin of the Shiretoko Museum↗
USGS2006

A model for autumn pelagic distribution of adult female polar bears in the Chukchi Seas, 1987-1994

We made predictions of polar bear (Ursus maritimus) autumn distribution in the Chukchi Sea with a Resource Selection Function (RSF) developed from 1198 satellite radio-collar locations on 124 adult female polar bears, 1987 – 1994. The RSF was created to assist in an aerial survey design for polar bears proposed by the U.S. Fish and Wildlife Service. The RSF was based on bathymetry and daily sea ice covariates extracted from passive microwave satellite imagery within the pelagic region > 25 km from shore. The RSF indicated that polar bears selected habitats with intermediate amounts (~50%) of ice cover in close proximity to higher ice concentrations, and over relatively shallow waters. The RSF showed good predictive abilities for the years of its construct, worked best in October, and was robust to inter-annual variability. When evaluated with recent (1997 – 2005) data, the RSF performed well for October and November but poorly in September. This loss of predictive abilities appeared to be related to recent changes in habitat due to longer melt seasons and younger sea ice, and testing the retrospective model with a small sample of recent polar bears locations from a limited region of the Chukchi Sea. Contemporary applications of this RSF must consider three factors that could limit its utility: 1) 2 different sea ice phenology; 2) distributions of males and sub-adults; and 3) occupancy in nearshore habitats.

Report↗
USGS1996

Mass and body-dimension relationships of polar bears in northern Alaska

Models developed from morphometric parameters are useful for estimating body mass (M) of captured wild ursids. The accuracy of those models, however, may depend on sex, season, and geographic location of the population. We tested the suitability of reported models to predict mass of polar bears ( Ursus maritimus ) captured in northern Alaska, but found that models developed for other populations performed poorly. Hence, we derived new models from field measurements of axillary girth (AG), straight-line body length (SLBL), condylobasal length (CL), and zygomatic width (ZW). Our equations accurately predicted body mass for polar bears captured during spring and autumn. The equation for spring-captured polar bears was M = 0.000078 * AG 1.6026 * SLBL 1.3579 (R 2 =0.97), while the equation for autumn-captured polar bears was M = 0.000250 * AG 1.4967 * SLBL 1.2468 (R 2 =0.97). Our results suggest that investigators should verify the accuracy of reported equations when applied to each situation and if necessary, develop models specific for the population in question.

Alaska↗
USGS1998

Satellite telemetry: A new tool for wildlife research and management

The U.S. Fish and Wildlife Service and the Alaska Department of Fish and Game have cooperated since 1984 to develop and evaluate satellite telemetry as a means of overcoming the high costs and logistical problems of conventional VHF (very high frequency) radiotelemetry systems. Detailed locational and behavioral data on caribou ( Rangifer tarandus ), polar bears ( Ursus maritimus ), and other large mammals in Alaska have been obtained using the Argos Data Collection and Location System (DCLS). The Argos system, a cooperative project of the Centre National d'Études Spatiales of France, the National Oceanic and Atmospheric Administration, and the National Aeronautics and Space Administration, is designed to acquire environmental data on a routine basis from anywhere on earth. Transmitters weighing 1.6-2.0 kg and functioning approximately 12-18 months operated on a frequency of 401.650 MHz. Signals from the transmitters were received by Argos DCLS instruments aboard two Tiros-N weather satellites in sun-synchronous, nearpolar orbits. Data from the satellites were received at tracking stations, transferred to processing centers in Maryland and France, and made available to users via computer tape, printouts, or telephone links. During 1985 and 1986, more than 25,000 locations and an additional 28,000 sets of sensor data (transmitter temperature and short-term and long-term indices of animal activity) were acquired for caribou and polar bears. Locations were calculated from the Doppler shift in the transmitted signal as the satellite approached and then moved away from the transmitter. The mean locational error for transmitters at known locations (n - 1,265) was 829 m; 90% of the calculated locations were within 1,700 m of the true location. Caribou transmitters provided a mean of 3.1 (+5.0. SD) locations per day during 6h of daily operation, and polar bear transmitters provided 1.7 (+6.9SD) locations during 12h of operation every third day. During the first 6 months of operation, the UHF (ultra-high frequency) signal failed on three of 32 caribou transmitters and 10 of 36 polar bear transmitters. A geographic information system (GIS) incorporating other databases (e.g., land cover, elevation, slope, aspect, hydrology, ice distribution) was used to analyze and display detailed locational and behavioral data collected via satellite. Examples of GIS applications to research projects using satellite telemetry and examples of detailed movement patterns of caribou and polar bears are presented. This report includes documentation for computer software packages for processing Argos data and presents developments, as of March 1987, in transmitter design, data retrieval using a local user terminal, computer software, and sensor development and calibration.

Resource Publication↗
USGS1999

Comparison of aerial survey procedures for estimating polar bear density: Results of pilot studies in northern Alaska

The U.S. Marine Mammal Protection Act (MMPA) and International Agreement on the Conservation of Polar Bears mandate that boundaries and sizes of polar bear ( Ursus maritimus ) populations be known so they can be managed at optimum sustainable levels. However, data to estimate polar bear numbers for the Chukchi/Bering Sea and Beaufort Sea populations in Alaska are limited. We evaluated aerial line transect methodology for assessing the size of these Alaskan polar bear populations during pilot studies in spring 1987 and summer 1994. In April and May 1987 we flew 12.239 km of transect lines in the northern Bering, Chukchi, and western Beaufort seas. In June 1994 we flew 6.244 km of transect lines in a primary survey unit using a helicopter, and 5,701 km of transect lines in a secondary survey unit using a fixed-wing aircraft in the Beaufort Sea. We examined visibility bias in aerial transect surveys, double counts by independent observers, single-season mark-resight methods, the suitability of using polar bear sign to stratify the study area, and adaptive sampling methods. Fifteen polar bear groups were observed during the 1987 study. Probability of detecting bears decreased with increasing perpendicular distance from the transect line, and probability of detecting polar bear groups likely increased with increasing group size. We estimated population density in high density areas to be 446 km 2 /bear. In 1994, 15 polar bear groups were observed by independent front and rear seat observers on transect lines in the primary survey unit. Density estimates ranged from 284 km 2 /bear to 197 km 2 /bear depending on the model selected. Low polar bear numbers scattered over large areas of polar ice in 1987 indicated that spring is a poor time to conduct aerial surveys. Based on the 1994 survey we determined that ship-based helicopter or land-based fixed-wing aerial surveys conducted at the ice-edge in late summer-early fall may produce robust density estimates for polar bear populations in the Chukchi/Bering and Beaufort seas.

Conference Paper↗
USGS2002

Predators

Calving caribou ( Rangifer tarandus ) of the Central Arctic herd, Alaska, have avoided the infrastructure associated with the complex of petroleum development areas from Prudhoe Bay to Kuparuk (Cameron et al. 1992, Nellemann and Cameron 1998, and Section 4 of this document). Calving females of the Porcupine caribou herd may similarly avoid any oil field roads and pipelines developed in areas traditionally used during the calving and post-calving periods. This may displace the caribou females and calves to areas east and south of the 1002 Area of the Arctic National Wildlife Refuge. Increased calf mortality could occur if calving caribou are displaced into areas that have a higher density of predators, higher rates of predation, or where a higher proportion of the predators regularly use caribou as a food source (Whitten et al. 1992). Our study assessed predation risks to caribou calving in the 1002 Area versus calving in potential displacement areas. Due to funding constraints, our research focused on grizzly bears ( Ursus arctos ), with wolves (Camus lupus) and golden eagles ( Aquila chrysaetos ) receiving only cursory attention. Our research objectives were 1) to compare relative abundance of predators within the 1002 Area with that in adjacent peripheral areas, 2) to determine factors affecting predator abundance on the calving grounds, and 3) to quantify the use of caribou as a food source for predators and the importance of caribou to the productivity of predator populations using the coastal plain of the Arctic National Wildlife Refuge.

Alaska, Northwest Territories, Yukon Territory↗
USGS2003

The use of sea ice habitat by female polar bears in the Beaufort Sea

Polar bears ( Ursus maritimus ) depend on ice-covered seas to satisfy life history requirements. Modern threats to polar bears include oil spills in the marine environment and changes in ice composition resulting from climate change. Managers need practical models that explain the distribution of bears in order to assess the impacts of these threats. We used stepwise procedures to create resource selection models of habitat use for radio-collared female polar bears in the Beaufort Sea. Sea ice characteristics and ocean depths at known polar bear locations were compared to the same features at randomly selected locations. Models generated for each of four seasons confirmed complexities of habitat use by polar bears and their response to numerous factors. Bears preferred shallow water areas where ice concentrations were > 80 % and different ice types intersected. Variation among seasons was reflected mainly in differential selection of ice stages, floe sizes, and their interactions. Water depth, total ice concentration and distance to the nearest interface between different ice types were significant terms in models for most seasons. Variation in ice stage and form also appeared in three models, and several interaction effects were identified. Habitat selection by polar bears is likely related to prey abundance and availability. Use of habitats in shallow water possibly reflects higher productivity in those areas. Habitat use in close proximity to ice edges is probably related to greater access of prey in those habitats.

Conference Paper↗
USGS2004

Using discrete choice modeling to generate resource selection functions for female polar bears in the Beaufort Sea

Polar bears ( Ursus maritimus ) depend on ice-covered seas to satisfy life history requirements. Modern threats to polar bears include oil spills in the marine environment and changes in ice composition resulting from climate change. Managers need practical models that explain the distribution of bears in order to assess the impacts of these threats. We explored the use of discrete choice models to describe habitat selection by female polar bears in the Beaufort Sea. Using stepwise procedures we generated resource selection models of habitat use. Sea ice characteristics and ocean depths at known polar bear locations were compared to the same features at randomly selected locations. Models generated for each of four seasons confirmed complexities of habitat use by polar bears and their response to numerous factors. Bears preferred shallow water areas where different ice types intersected. Variation among seasons was reflected mainly in differential selection of total ice concentration, ice stages, floe sizes, and their interactions. Distance to the nearest ice interface was a significant term in models for three seasons. Water depth was selected as a significant term in all seasons, possibly reflecting higher productivity in shallow water areas. Preliminary tests indicate seasonal models can predict polar bear distribution based on prior sea ice data.

Alaska↗
USGS2016

Estimating black bear density in New Mexico using noninvasive genetic sampling coupled with spatially explicit capture-recapture methods

During the 2004–2005 to 2015–2016 hunting seasons, the New Mexico Department of Game and Fish (NMDGF) estimated black bear abundance (Ursus americanus) across the state by coupling density estimates with the distribution of primary habitat generated by Costello et al. (2001). These estimates have been used to set harvest limits. For example, a density of 17 bears/100 km2 for the Sangre de Cristo and Sacramento Mountains and 13.2 bears/100 km2 for the Sandia Mountains were used to set harvest levels. The advancement and widespread acceptance of non-invasive sampling and mark-recapture methods, prompted the NMDGF to collaborate with the New Mexico Cooperative Fish and Wildlife Research Unit and New Mexico State University to update their density estimates for black bear populations in select mountain ranges across the state. We established 5 study areas in 3 mountain ranges: the northern (NSC; sampled in 2012) and southern Sangre de Cristo Mountains (SSC; sampled in 2013), the Sandia Mountains (Sandias; sampled in 2014), and the northern (NSacs) and southern Sacramento Mountains (SSacs; both sampled in 2014). We collected hair samples from black bears using two concurrent non-invasive sampling methods, hair traps and bear rubs. We used a gender marker and a suite of microsatellite loci to determine the individual identification of hair samples that were suitable for genetic analysis. We used these data to generate mark-recapture encounter histories for each bear and estimated density in a spatially explicit capture-recapture framework (SECR). We constructed a suite of SECR candidate models using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We used Akaike’s Information Criterion corrected for small sample size (AICc) to rank and select the most supported model from which we estimated density. We set 554 hair traps, 117 bear rubs and collected 4,083 hair samples. We identified 725 (367 M, 358 F) individuals; the sex ratio for each study area was approximately equal. Our density estimates varied within and among mountain ranges with an estimated density of 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) for the NSC, 19.74 bears/100 km2 (95% CI: 13.77 – 28.30) in the SSC, 25.75 bears/100 km2 (95% CI: 13.22 – 50.14) in the Sandias, 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) in the NSacs, and 16.55 bears/100 km2 (95% CI: 11.64 – 23.53) in the SSacs. Overall detection probability for hair traps and bear rubs, combined, was low across all study areas and ranged from 0.00001 to 0.02. We speculate that detection probabilities were affected by failure of some hair samples to produce a complete genotype due to UV degradation of DNA, and our inability to set and check some sampling devices due to wildfires in the SSC. Ultraviolet radiation levels are particularly high in New Mexico compared to other states where NGS methods have been used because New Mexico receives substantial amounts of sunshine, is relatively high in elevation (1,200 m – 4,000 m), and is at a lower latitude. Despite these sampling difficulties, we were able to produce density estimates for New Mexico black bear populations with levels of precision comparable to estimated black bear densities made elsewhere in the U.S. Our ability to generate reliable black bear density estimates for 3 New Mexico mountain ranges is attributable to our use of a statistically robust study design and analytical method. There are multiple factors that need to be considered when developing future SECR-based density estimation projects. First, the spatial extent of the population of interest and the smallest average home range size must be determined; these will dictate size of the trapping array and spacing necessary between hair traps. The number of technicians needed and access to the study areas will also influence configuration of the trapping array. We believe shorter sampling occasions could be implemented to reduce degradation of DNA due to UV radiation; this might help increase amplification rates and thereby increase both the number of unique individuals identified and the number of recaptures, improving the precision of the density estimates. A pilot study may be useful to determine the length of time hair samples can remain in the field prior to collection. In addition, researchers may consider setting hair traps and bear rubs in more shaded areas (e.g., north facing slopes) to help reduce exposure to UV radiation. To reduce the sampling interval it will be necessary to either hire more field personnel or decrease the number of hair traps per sampling session. Both of these will enhance detection of long-range movement events by individual bears, increase initial capture and recapture rates, and improve precision of the parameter estimates. We recognize that all studies are constrained by limited resources, however, increasing field personnel would also allow a larger study area to be sampled or enable higher trap density. In conclusion, we estimated the density of black bears in 5 study areas within 3 mountains ranges of New Mexico. Our estimates will aid the NMDGF in setting sustainable harvest limits. Along with estimates of density, information on additional demographic rates (e.g., survival rates and reproduction) and the potential effects that climate change and future land use may have on the demography of black bears may also help inform management of black bears in New Mexico, and may be considered as future areas for research.

New Mexico↗
USGS2019

Yellowstone grizzly bear investigations: Annual report of the Interagency Grizzly Bear Study Team 2018

This annual report summarizes the results of grizzly bear ( Ursus arctos ) research and monitoring conducted in the Greater Yellowstone Ecosystem (GYE) by the Interagency Grizzly Bear Study Team (IGBST) during 2018. The research and monitoring program is focused on population estimation and demographics, food monitoring, and habitat monitoring. The report also contains a summary of grizzly bear management actions to address conflict situations and agency outreach efforts. This report is a summary of annual data collections. Data analyses, and summaries presented in this report supersede those published previously and may be subject to change contingent on additional information, future manuscript publications, and the peer review process.

Idaho, Montana, Wyoming↗
USGS2020

Using hair cortisol to assess physiological stress in Alaska polar bears

The concentration of cortisol in hair (HCC) of polar bears (Ursus maritimus) may provide a retrospective view of physiological stress they experience and a link to their response to environmental change. To understand this relationship, we assayed HCC from polar bears captured in the Alaska Beaufort, Bering and Chukchi seas during 1983–1989 and 2004–2016. Cortisol accumulated in hair through summer and autumn and into the subsequent winter. HCC was similar between adult males and adult females. No difference in HCC across regions suggested all bears responded similarly to the environment. HCC in spring was elevated following years with a high winter Arctic Oscillation index and highly variable wind speed. HCC increased non-linearly with increasing duration of the continental shelf summer open water period up to 50 days and then decreased. HCC of spring samples declined with increasing body size, indicating that the stress response was more active in smaller bears or those in poor body condition. HCC of spring samples was greater and more variable in 2004–2006 than during either 1983–1989 or 2008–2016, and significantly so for females with 1st year cubs and subadult females. Elevated HCC in 2004–2006 coincided with years of reduced survival of southern Beaufort Sea polar bears and suggests that unidentified environmental perturbations impacted Alaska polar bears. Because HCC may be obtained by relatively non-invasive means, it has potential use for assessing polar bear populations that are difficult to study by capturing. Hence, information gained from HCC can inform polar bear conservation, especially on the vulnerability of subadult females and adult females with new cubs, and possible future environmental perturbations impacts on bear physiology.

Alaska↗
USGS2021

Human-polar bear interactions

Human-wildlife interactions (HWI) are driven fundamentally by overlapping space and resources. As competition intensifies, the likelihood of interaction and conflict increases. In turn, conflict may impede conservation efforts by lowering social tolerance of wildlife, especially when human-wildlife conflict (HWC) poses a threat to human safety and economic well-being. Thus, mitigating conflict is one of the most consequential components of a wildlife management program, particularly for large carnivores. However, unlike other large carnivores, the causative factors and conservation consequences of interactions between humans and polar bears ( Ursus maritimus ) are poorly understood. Historically, mitigation of human-polar bear conflict has been a low management priority with the exception of a few locations where conflict had been a chronic concern. In part, this was because of low human densities in most of the Arctic and sea ice act as a physical barrier regulating the frequency of human-polar bear interactions. However, as the Arctic has warmed, anthropogenic activities have increased, and polar bears have become more reliant on land. As a result, mitigating interaction and conflict between humans and polar bears has become a growing concern. In this chapter, we explore the nexus of polar bear and human behavior and environmental change in driving the nature and intensity of human-polar bear interaction and conflict. We first provide an overview of behaviors that contribute to the occurrence of interactions and conflicts. We then review historical and contemporary drivers of interaction and conflict and examine how climate-mediated changes to Arctic marine and terrestrial environments are likely to influence distribution and types of future incidents. We close by proposing a conceptual framework that conservationists and managers can use to mitigate the likelihood of future human-polar bear conflict in a rapidly changing Arctic.

Book chapter↗