The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Gordon B. Stenhouse - One of the best experts on this subject based on the ideXlab platform.
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mapping recreation and tourism use across Grizzly Bear recovery areas using social network data and maximum entropy modelling
Ecological Modelling, 2021Co-Authors: Tristan R H Goodbody, Nicholas C Coops, Sean P Kearney, Vivek Srivastava, Bethany Parsons, Gregory J M Rickbeil, Gordon B. StenhouseAbstract:Abstract Understanding biodiversity pressures associated with recreation and tourism is a major challenge for conservation planning and landscape management. While estimates of landscape use are often collected using mechanisms such as park entry fees and traffic density estimates, these data do not provide substantial detail about the spatial location or intensity of recreation and tourism across biodiversity management areas. To better predict patterns of recreation and tourism likelihood to support conservation planning, we used social network data from Facebook(™), Flickr(™), Google(™), Strava(™), and Wikilocs(™) along with a suite of remote-sensing-derived environmental covariates in a maximum entropy (MaxEnt) presence-only modelling framework. Social network samples were compiled and processed to reduce sampling bias and spatial autocorrelation. Road access, climate data, and remote sensing covariates describing vegetation greenness, disturbance, topography, and moisture were used as predictor variables in the MaxEnt modelling framework. Our focus site was a Grizzly Bear (Ursus arctos) management area in west-central Alberta, Canada. Individual models were developed for each social network dataset, as well as a combined model including all the samples . Mean cross-validated AUC, partial ROC, and true skill statistics (TSS) were used to evaluate model accuracy. Results indicated that the covariates proposed were able to best model Strava and Wikilocs activity (TSS = 0.69 and 0.50, respectively), while samples from Flickr or the combination of all social networks were least accurate (TSS = 0.32). The “access” covariate was most important for MaxEnt training gain across a number of social network models, highlighting the importance of access for recreation and tourism likelihood. The summer heat moisture index and normalized burn ratio were also useful spatial covariates in many predictions. Recreation and tourism likelihood maps were combined with Grizzly Bear telemetry data to examine how recreation and tourism may affect Grizzly Bear behaviour. All social network models found a similar influence on Grizzly Bear behaviour, with increasing recreation and tourism use resulting in decreased foraging behaviour and increased rapid movement, suggesting that the models developed here are useful tools for predicting Grizzly Bear behaviour and planning conservation strategies for the species.
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harvested forests as a surrogate to wildfires in relation to Grizzly Bear food supply in west central alberta
Forest Ecology and Management, 2020Co-Authors: Christopher M Souliere, Gordon B. Stenhouse, Sean C P Coogan, Scott E. NielsenAbstract:Abstract Grizzly Bear (Ursus arctos) populations residing in interior ecosystems of North America are known to frequent harvested areas and areas burnt by wildfires, as both disturbances encourage growth of early seral vegetation preferred by them. This is especially evident in places where there is a paucity of large natural openings and areas with a long history of wildfire suppression, such as the foothill forests of west-central Alberta. Little has been done, however, to directly quantify and compare Grizzly Bear food-supply in both disturbance types and at early stages of forest regeneration. In this paper, we explore whether harvested areas can act as surrogates to wildfires for Grizzly Bear food-supply in west-central Alberta, Canada. We sampled known fruit-Bearing and herbaceous Grizzly Bear foods for their occurrence, productivity, and digestible energy supply among post-harvest, post-fire, and mature forests disturbance types, and across very young (~5 yrs), young (~20 yrs), and mid (~60 yrs) age-classes for post-harvest and post-fire disturbances. A variety of foods occurred at greater frequency in post-harvest stands, with the occurrence of most foods explained by the main effects of disturbance and age-class, or in combination with one environmental covariate. Overall, fruit productivity and digestible energy from fruits were highest in the young age-class, whereas forb productivity and digestible energy from forbs were highest in the very young age-class. There were no significant differences in total available digestible energy (fruit + forb) between post-harvest and post-fire stands within any age-class, but significant differences were evident between age-classes. These results suggest that harvested areas can potentially act as a surrogate to wildfires in relation to Grizzly Bear food-supply, but human access remains a key challenge for harvests given their association with roads. We suggest that harvested areas could be used as management tool to maintain or enhance Grizzly Bear food-supply and thus contribute to population recovery efforts, especially in areas of wildfire suppression.
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Grizzly Bear response to fine spatial and temporal scale spring snow cover in western alberta
PLOS ONE, 2019Co-Authors: Ethan E Berman, Nicholas C Coops, Sean P Kearney, Gordon B. StenhouseAbstract:Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow dynamics. This study examines Grizzly Bear (Ursus arctos) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-scale snow cover data, this research tests a hypothesis that Grizzly Bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31st). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of Grizzly Bear selection during the spring. Comparing four different models fit to 62 individual Bear-years, we found that the inclusion of fractional snow covered area improved model fit 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate Grizzly Bear habitat use in response to snow and environmental attributes, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results indicate Grizzly Bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened Grizzly Bear populations in consideration of changing climatic conditions. This study is an example of how fine spatial and temporal scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.
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Covariates used in models and references to studies linking variables to Grizzly Bear habitat selection and use.
2019Co-Authors: Ethan E Berman, Nicholas C Coops, Sean P Kearney, Gordon B. StenhouseAbstract:Covariates used in models and references to studies linking variables to Grizzly Bear habitat selection and use.
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using spatial mark recapture for conservation monitoring of Grizzly Bear populations in alberta
Scientific Reports, 2018Co-Authors: John Boulanger, Scott E. Nielsen, Gordon B. StenhouseAbstract:One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five Grizzly Bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing Bear distribution. Here we used models of Grizzly Bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of Bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher Bear density in the north, whereas mortality risk was most associated (negatively) with density of Bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of Bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.
Charles C. Schwartz - One of the best experts on this subject based on the ideXlab platform.
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re evaluation of yellowstone Grizzly Bear population dynamics not supported by empirical data response to doak cutler
Conservation Letters, 2014Co-Authors: Frank T Van Manen, Mark A. Haroldson, Gary C. White, Richard B Harris, Michael R Ebinger, Megan D Higgs, Steve Cherry, Charles C. SchwartzAbstract:Doak and Cutler critiqued methods used by the Interagency Grizzly Bear Study Team (IGBST) to estimate Grizzly Bear population size and trend in the Greater Yellowstone Ecosystem. Here, we focus on the premise, implementation, and interpretation of simulations they used to support their arguments. They argued that population increases documented by IGBST based on females with cubs-of-the-year were an artifact of increased search effort. However, we demonstrate their simulations were neither reflective of the true observation process nor did their results provide statistical support for their conclusion. They further argued that survival and reproductive senescence should be incorporated into population projections, but we demonstrate their choice of extreme mortality risk beyond age 20 and incompatible baseline fecundity led to erroneous conclusions. The conclusions of Doak and Cutler are unsubstantiated when placed within the context of a thorough understanding of the data, study system, and previous research findings and publications.
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Influence of overnight recreation on Grizzly Bear movement and behavior in Yellowstone National Park
Ursus, 2013Co-Authors: Tyler H. Coleman, Charles C. Schwartz, Kerry A. Gunther, Scott CreelAbstract:Abstract Interactions among recreational users and Grizzly Bears (Ursus arctos) are a continuous challenge for Bear managers. Yellowstone National Park, Wyoming, USA uses a system of designated backcountry campsites to manage overnight use and provides Bear-resistant food-storage devices for recreational users. Few studies have evaluated how this type of management and recreation influences Grizzly Bear behavior. We used global positioning system (GPS) data for humans and Bears to determine how overnight use influenced Grizzly Bear movement behavior. We determined times of day campsites were occupied and contrasted Grizzly Bear locations to random locations near occupied campsites. We conducted a similar analysis ignoring campsite occupancy to assess the utility of including a temporal variable. Grizzly Bears were 0.35 times as likely as random locations to be ≤200 m from occupied campsites (95% CI = 0.19–0.62, P ≤ 0.001). Conversely, when human occupancy was ignored, Bears were 2.11 times more likely t...
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Hazards Affecting Grizzly Bear Survival in the Greater Yellowstone Ecosystem
Journal of Wildlife Management, 2010Co-Authors: Charles C. Schwartz, Mark A. Haroldson, Gary C. WhiteAbstract:During the past 2 decades, the Grizzly Bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded its range. Early efforts to model Grizzly Bear mortality were principally focused within the United States Fish and Wildlife Service Grizzly Bear Recovery Zone, which currently represents only about 61% of known Bear distribution in the GYE. A more recent analysis that explored one spatial covariate that encompassed the entire GYE suggested that Grizzly Bear survival was highest in Yellowstone National Park, followed by areas in the Grizzly Bear Recovery Zone outside the park, and lowest outside the Recovery Zone. Although management differences within these areas partially explained differences in Grizzly Bear survival, these simple spatial covariates did not capture site-specific reasons why Bears die at higher rates outside the Recovery Zone. Here, we model annual survival of Grizzly Bears in the GYE to 1) identify landscape features (i.e., foods, land management policies, or human disturbances factors) that best describe spatial heterogeneity among Bear mortalities, 2) spatially depict the differences in Grizzly Bear survival across the GYE, and 3) demonstrate how our spatially explicit model of survival can be linked with demographic parameters to identify source and sink habitats. We used recent data from radiomarked Bears to estimate survival (1983-2003) using the known-fate data type in Program MARK. Our top models suggested that survival of independent (age L yr) Grizzly Bears was best explained by the level of human development of the landscape within the home ranges of Bears. Survival improved as secure habitat and elevation increased but declined as road density, number of homes, and site developments increased. Bears living in areas open to fall ungulate hunting suffered higher rates of mortality than Bears living in areas closed to hunting. Our top model strongly supported previous research that identified roads and developed sites as hazards to Grizzly Bear survival. We also demonstrated that rural homes and ungulate hunting negatively affected survival, both new findings. We illustrate how our survival model, when linked with estimates of reproduction and survival of dependent young, can be used to identify demographically the source and sink habitats in the GYE. Finally, we discuss how this demographic model constitutes one component of a habitat-based framework for Grizzly Bear conservation. Such a framework can spatially depict the areas of risk in otherwise good habitat, providing a focus for resource management in the GYE.
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trajectory of the yellowstone Grizzly Bear population under alternative survival rates
Wildlife Monographs, 2006Co-Authors: Richard B Harris, Charles C. Schwartz, Mark A. Haroldson, Gary C. WhiteAbstract:The Grizzly Bear population inhabiting the GYE is of national and international interest. Although this population has increased in size and extent in recent years (Eberhardt et al. 1994, Eberhardt 1995, Boyce et al. 2001, Schwartz et al. 2002), isolation from other Grizzly Bear populations and continuing human development along its geographic margins justify continued concern about its future. Since the adoption of the federal recovery plan for Grizzly Bears in the United States (U.S. Fish and Wildlife Service 1993), mortality of grizzlies in the GYE has been monitored and a standard for acceptable mortality limit established. One important component of the limits of acceptable mortality is an estimate of the maximum human-caused mortality sustainable by a Grizzly Bear population (Harris 1986). This level was generated for a generic Bear population, but recent information specific to the GYE population now allows for improvements to this estimate. Here, we use data from the period 1983–2002 (Haroldson et al. 2006, Schwartz et al. 2006a,c) as the basis for deterministic calculations and short-term stochastic projections of the GYE Grizzly Bear population under a range of survival rates for independent females (i.e., those no longer under the care of their mothers) that might apply in the future. Our approach to stochastic simulations was to produce a series of basic projections using parsimonious interpretations of data from Schwartz et al. (2006a,c) and Haroldson et al. (2006). We faced a number of different ways to project populations and interpret results, and we considered them as alternatives explored through sensitivity analyses. In generating trajectories, we wished to estimate not only the expected (or most likely) outcome but also the probability of decline (because declines are possible even when expected k . 1). Thus, we emphasized appropriate treatment of yearly variability in vital rates. Although analyses by Schwartz et al. (2006a,c) and Haroldson et al. (2006) identified strongly supported environmental covariates, these failed to explain the full range of yearly variation in vital rates. A mechanistic model that simulated these environmental factors directly (and linked vital rates to them) would have yielded less yearly variation than was observed during 1983–2002. We therefore integrated all factors contributing to yearly variation (both identified and unknown) via our estimates of the true process variance (yearly variation of the population only, excluding sampling variation). Because our objective was to understand survival rates that minimized the risk that k would decline below 1.0, we focused on females. However, male mortality rates are relevant to more general conservation concerns, so we also examined the behavior of simulated populations under alternative male survival schedules. We claim no ability to predict future reproductive or survival rates as environmental or management factors change. We can, however, use our knowledge of patterns in vital rates from 1983 to 2002 to understand population trajectories associated with a range of plausible future vital rates.
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Grizzly Bear human conflicts in the greater yellowstone ecosystem 1992 2000
Ursus, 2004Co-Authors: Kerry A. Gunther, Mark A. Haroldson, Kevin L. Frey, Steven L. Cain, Jeffrey P. Copeland, Charles C. SchwartzAbstract:Abstract For many years, the primary strategy for managing Grizzly Bears (Ursus arctos) that came into conflict with humans in the Greater Yellowstone Ecosystem (GYE) was to capture and translocate the offending Bears away from conflict sites. Translocation usually only temporarily alleviated the problems and most often did not result in long-term solutions. Wildlife managers needed to be able to predict the causes, types, locations, and trends of conflicts to more efficiently allocate resources for pro-active rather than reactive management actions. To address this need, we recorded all Grizzly Bear–human conflicts reported in the GYE during 1992–2000. We analyzed trends in conflicts over time (increasing or decreasing), geographic location on macro- (inside or outside of the designated Yellowstone Grizzly Bear Recovery Zone [YGBRZ]) and micro- (geographic location) scales, land ownership (public or private), and relationship to the seasonal availability of Bear foods. We recorded 995 Grizzly Bear–human ...
Scott E. Nielsen - One of the best experts on this subject based on the ideXlab platform.
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Problem Perspectives and Grizzly Bears: A Case Study of Alberta’s Grizzly Bear Recovery Policy
Frontiers in Ecology and Evolution, 2020Co-Authors: Courtney Hughes, Nicholas T. Yarmey, Andrea T. Morehouse, Scott E. NielsenAbstract:Since their threatened species listing in 2010, Grizzly Bear recovery has been a controversial policy issue in Alberta, Canada particularly because this charismatic carnivore represents a diverse set of values, both positive (e.g., an icon of beauty and the wilderness) and negative (e.g., a safety threat and economic risk to peoples’ livelihoods). Previous human dimensions research on Grizzly Bear conservation has accounted for the values and attitudes different groups of people hold for these Bears, as well as their views on conflict mitigation strategies. However, the conservation literature is more limited in assessing the perspectives different people hold for Grizzly Bear conservation in a policy context. Arguably, understanding the policy landscape in which carnivore conservation occurs is important to achieve desired goals and objectives for species and the people expected to live with them and implement policy action. Using a case study approach between 2012-2014 and borrowing from the policy sciences problem-oriented framework, we identify the dominant problem perspectives in Alberta’s Grizzly Bear recovery policy using document review and interviews with participants from government, the natural resource sector, and environmental non-governmental organizations. We identify that ordinary and constitutive problem perspectives share common features across participants in this study, including frustrations with lack of policy clarity, implementation inefficiencies and committed political and financial action, and perhaps even more important, the challenges in policy decision-making and governance. We discuss the importance of meaningful engagement of people who live with large carnivores and the impacts of conservation policy, which is applicable to both a local and global scale, as success in large carnivore conservation must include the people who will ultimately implement conservation action.
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problem perspectives and Grizzly Bears a case study of alberta s Grizzly Bear recovery policy
Frontiers in Ecology and Evolution, 2020Co-Authors: Courtney Hughes, Nicholas T. Yarmey, Andrea T. Morehouse, Scott E. NielsenAbstract:Since their threatened species listing in 2010, Grizzly Bear recovery has been a controversial policy issue in Alberta, Canada particularly because this charismatic carnivore represents a diverse set of values, both positive (e.g., an icon of beauty and the wilderness) and negative (e.g., a safety threat and economic risk to peoples’ livelihoods). Previous human dimensions research on Grizzly Bear conservation has accounted for the values and attitudes different groups of people hold for these Bears, as well as their views on conflict mitigation strategies. However, the conservation literature is more limited in assessing the perspectives different people hold for Grizzly Bear conservation in a policy context. Arguably, understanding the policy landscape in which carnivore conservation occurs is important to achieve desired goals and objectives for species and the people expected to live with them and implement policy action. Using a case study approach between 2012-2014 and borrowing from the policy sciences problem-oriented framework, we identify the dominant problem perspectives in Alberta’s Grizzly Bear recovery policy using document review and interviews with participants from government, the natural resource sector, and environmental non-governmental organizations. We identify that ordinary and constitutive problem perspectives share common features across participants in this study, including frustrations with lack of policy clarity, implementation inefficiencies and committed political and financial action, and perhaps even more important, the challenges in policy decision-making and governance. We discuss the importance of meaningful engagement of people who live with large carnivores and the impacts of conservation policy, which is applicable to both a local and global scale, as success in large carnivore conservation must include the people who will ultimately implement conservation action.
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harvested forests as a surrogate to wildfires in relation to Grizzly Bear food supply in west central alberta
Forest Ecology and Management, 2020Co-Authors: Christopher M Souliere, Gordon B. Stenhouse, Sean C P Coogan, Scott E. NielsenAbstract:Abstract Grizzly Bear (Ursus arctos) populations residing in interior ecosystems of North America are known to frequent harvested areas and areas burnt by wildfires, as both disturbances encourage growth of early seral vegetation preferred by them. This is especially evident in places where there is a paucity of large natural openings and areas with a long history of wildfire suppression, such as the foothill forests of west-central Alberta. Little has been done, however, to directly quantify and compare Grizzly Bear food-supply in both disturbance types and at early stages of forest regeneration. In this paper, we explore whether harvested areas can act as surrogates to wildfires for Grizzly Bear food-supply in west-central Alberta, Canada. We sampled known fruit-Bearing and herbaceous Grizzly Bear foods for their occurrence, productivity, and digestible energy supply among post-harvest, post-fire, and mature forests disturbance types, and across very young (~5 yrs), young (~20 yrs), and mid (~60 yrs) age-classes for post-harvest and post-fire disturbances. A variety of foods occurred at greater frequency in post-harvest stands, with the occurrence of most foods explained by the main effects of disturbance and age-class, or in combination with one environmental covariate. Overall, fruit productivity and digestible energy from fruits were highest in the young age-class, whereas forb productivity and digestible energy from forbs were highest in the very young age-class. There were no significant differences in total available digestible energy (fruit + forb) between post-harvest and post-fire stands within any age-class, but significant differences were evident between age-classes. These results suggest that harvested areas can potentially act as a surrogate to wildfires in relation to Grizzly Bear food-supply, but human access remains a key challenge for harvests given their association with roads. We suggest that harvested areas could be used as management tool to maintain or enhance Grizzly Bear food-supply and thus contribute to population recovery efforts, especially in areas of wildfire suppression.
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using spatial mark recapture for conservation monitoring of Grizzly Bear populations in alberta
Scientific Reports, 2018Co-Authors: John Boulanger, Scott E. Nielsen, Gordon B. StenhouseAbstract:One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five Grizzly Bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing Bear distribution. Here we used models of Grizzly Bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of Bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher Bear density in the north, whereas mortality risk was most associated (negatively) with density of Bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of Bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.
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Grizzly Bear connectivity mapping in the canada united states trans border region
Journal of Wildlife Management, 2015Co-Authors: Michael F. Proctor, Wayne F. Kasworm, Christopher Servheen, Scott E. Nielsen, Thomas G Radandt, Grant A Machutchon, Mark S. BoyceAbstract:Fragmentation is a growing threat to wildlife worldwide and managers need solutions to reverse its impacts on species' populations. Populations of Grizzly Bears (Ursus arctos), often considered an umbrella and focal species for large mammal conservation, are fragmented by human settlement and major highways in the trans-border region of southern British Columbia, northern Montana, Idaho, and northeastern Washington. To improve prospects for Bear movement among 5 small fragmented Grizzly Bear subpopulations, we asked 2 inter-related questions: Are there preferred linkage habitats for Grizzly Bears across settled valleys with major highways in the fragmented trans-border region, and if so, could we predict them using a combination of resource selection functions and human settlement patterns? We estimated a resource selection function (RSF) to identify high quality backcountry core habitat and to predict front-country linkage areas using global positioning system (GPS) telemetry locations representing an average of 12 relocations per day from 27 Grizzly Bears (13F, 14M). We used RSF models and data on human presence (building density) to inform cost surfaces for connectivity network analyses identifying linkage areas based on least-cost path, corridor, and circuit theory methods. We identified 60 trans-border (Canada–USA) linkage areas across all major highways and settlement zones in the Purcell, Selkirk, and Cabinet Mountains encompassing 24% of total highway length. We tested the correspondence of the core and linkage areas predicted from models with Grizzly Bear use based on Bear GPS telemetry locations and movement data. Highway crossings were relatively rare; however, 88% of 122 crossings from 13 of our Bears were within predicted linkage areas (mean = 8.3 crossings/Bear, SE = 2.8, range 1–31, 3 Bears with 1 crossing) indicating Bears use linkage habitat that could be predicted with an RSF. Long-term persistence of small fragmented Grizzly Bear populations will require management of connectivity with larger populations. Linkage areas identified here could inform such efforts. © 2015 The Wildlife Society.
Gary C. White - One of the best experts on this subject based on the ideXlab platform.
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re evaluation of yellowstone Grizzly Bear population dynamics not supported by empirical data response to doak cutler
Conservation Letters, 2014Co-Authors: Frank T Van Manen, Mark A. Haroldson, Gary C. White, Richard B Harris, Michael R Ebinger, Megan D Higgs, Steve Cherry, Charles C. SchwartzAbstract:Doak and Cutler critiqued methods used by the Interagency Grizzly Bear Study Team (IGBST) to estimate Grizzly Bear population size and trend in the Greater Yellowstone Ecosystem. Here, we focus on the premise, implementation, and interpretation of simulations they used to support their arguments. They argued that population increases documented by IGBST based on females with cubs-of-the-year were an artifact of increased search effort. However, we demonstrate their simulations were neither reflective of the true observation process nor did their results provide statistical support for their conclusion. They further argued that survival and reproductive senescence should be incorporated into population projections, but we demonstrate their choice of extreme mortality risk beyond age 20 and incompatible baseline fecundity led to erroneous conclusions. The conclusions of Doak and Cutler are unsubstantiated when placed within the context of a thorough understanding of the data, study system, and previous research findings and publications.
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Hazards Affecting Grizzly Bear Survival in the Greater Yellowstone Ecosystem
Journal of Wildlife Management, 2010Co-Authors: Charles C. Schwartz, Mark A. Haroldson, Gary C. WhiteAbstract:During the past 2 decades, the Grizzly Bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded its range. Early efforts to model Grizzly Bear mortality were principally focused within the United States Fish and Wildlife Service Grizzly Bear Recovery Zone, which currently represents only about 61% of known Bear distribution in the GYE. A more recent analysis that explored one spatial covariate that encompassed the entire GYE suggested that Grizzly Bear survival was highest in Yellowstone National Park, followed by areas in the Grizzly Bear Recovery Zone outside the park, and lowest outside the Recovery Zone. Although management differences within these areas partially explained differences in Grizzly Bear survival, these simple spatial covariates did not capture site-specific reasons why Bears die at higher rates outside the Recovery Zone. Here, we model annual survival of Grizzly Bears in the GYE to 1) identify landscape features (i.e., foods, land management policies, or human disturbances factors) that best describe spatial heterogeneity among Bear mortalities, 2) spatially depict the differences in Grizzly Bear survival across the GYE, and 3) demonstrate how our spatially explicit model of survival can be linked with demographic parameters to identify source and sink habitats. We used recent data from radiomarked Bears to estimate survival (1983-2003) using the known-fate data type in Program MARK. Our top models suggested that survival of independent (age L yr) Grizzly Bears was best explained by the level of human development of the landscape within the home ranges of Bears. Survival improved as secure habitat and elevation increased but declined as road density, number of homes, and site developments increased. Bears living in areas open to fall ungulate hunting suffered higher rates of mortality than Bears living in areas closed to hunting. Our top model strongly supported previous research that identified roads and developed sites as hazards to Grizzly Bear survival. We also demonstrated that rural homes and ungulate hunting negatively affected survival, both new findings. We illustrate how our survival model, when linked with estimates of reproduction and survival of dependent young, can be used to identify demographically the source and sink habitats in the GYE. Finally, we discuss how this demographic model constitutes one component of a habitat-based framework for Grizzly Bear conservation. Such a framework can spatially depict the areas of risk in otherwise good habitat, providing a focus for resource management in the GYE.
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trajectory of the yellowstone Grizzly Bear population under alternative survival rates
Wildlife Monographs, 2006Co-Authors: Richard B Harris, Charles C. Schwartz, Mark A. Haroldson, Gary C. WhiteAbstract:The Grizzly Bear population inhabiting the GYE is of national and international interest. Although this population has increased in size and extent in recent years (Eberhardt et al. 1994, Eberhardt 1995, Boyce et al. 2001, Schwartz et al. 2002), isolation from other Grizzly Bear populations and continuing human development along its geographic margins justify continued concern about its future. Since the adoption of the federal recovery plan for Grizzly Bears in the United States (U.S. Fish and Wildlife Service 1993), mortality of grizzlies in the GYE has been monitored and a standard for acceptable mortality limit established. One important component of the limits of acceptable mortality is an estimate of the maximum human-caused mortality sustainable by a Grizzly Bear population (Harris 1986). This level was generated for a generic Bear population, but recent information specific to the GYE population now allows for improvements to this estimate. Here, we use data from the period 1983–2002 (Haroldson et al. 2006, Schwartz et al. 2006a,c) as the basis for deterministic calculations and short-term stochastic projections of the GYE Grizzly Bear population under a range of survival rates for independent females (i.e., those no longer under the care of their mothers) that might apply in the future. Our approach to stochastic simulations was to produce a series of basic projections using parsimonious interpretations of data from Schwartz et al. (2006a,c) and Haroldson et al. (2006). We faced a number of different ways to project populations and interpret results, and we considered them as alternatives explored through sensitivity analyses. In generating trajectories, we wished to estimate not only the expected (or most likely) outcome but also the probability of decline (because declines are possible even when expected k . 1). Thus, we emphasized appropriate treatment of yearly variability in vital rates. Although analyses by Schwartz et al. (2006a,c) and Haroldson et al. (2006) identified strongly supported environmental covariates, these failed to explain the full range of yearly variation in vital rates. A mechanistic model that simulated these environmental factors directly (and linked vital rates to them) would have yielded less yearly variation than was observed during 1983–2002. We therefore integrated all factors contributing to yearly variation (both identified and unknown) via our estimates of the true process variance (yearly variation of the population only, excluding sampling variation). Because our objective was to understand survival rates that minimized the risk that k would decline below 1.0, we focused on females. However, male mortality rates are relevant to more general conservation concerns, so we also examined the behavior of simulated populations under alternative male survival schedules. We claim no ability to predict future reproductive or survival rates as environmental or management factors change. We can, however, use our knowledge of patterns in vital rates from 1983 to 2002 to understand population trajectories associated with a range of plausible future vital rates.
Mark S. Boyce - One of the best experts on this subject based on the ideXlab platform.
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the role of human outdoor recreation in shaping patterns of Grizzly Bear black Bear co occurrence
PLOS ONE, 2018Co-Authors: Andrew Ladle, Robin Steenweg, Brenda Shepherd, Mark S. BoyceAbstract:Species' distributions are influenced by a combination of landscape variables and biotic interactions with other species, including people. Grizzly Bears and black Bears are sympatric, competing omnivores that also share habitats with human recreationists. By adapting models for multi-species occupancy analysis, we analyzed trail camera data from 192 trail camera locations in and around Jasper National Park, Canada to estimate Grizzly Bear and black Bear occurrence and intensity of trail use. We documented (a) occurrence of Grizzly Bears and black Bears relative to habitat variables (b) occurrence and intensity of use relative to competing Bear species and motorised and non-motorised recreational activity, and (c) temporal overlap in activity patterns among the two Bear species and recreationists. Grizzly Bears were spatially separated from black Bears, selecting higher elevations and locations farther from roads. Both species co-occurred with motorised and non-motorised recreation, however, Grizzly Bears reduced their intensity of use of sites with motorised recreation present. Black Bears showed higher temporal activity overlap with recreational activity than Grizzly Bears, however differences in Bear daily activity patterns between sites with and without motorised and non-motorised recreation were not significant. Reduced intensity of use by Grizzly Bears of sites where motorised recreation was present is a concern given off-road recreation is becoming increasingly popular in North America, and can negatively influence Grizzly Bear recovery by reducing foraging opportunities near or on trails. Camera traps and multi-species occurrence models offer non-invasive methods for identifying how habitat use by animals changes relative to sympatric species, including humans. These conclusions emphasise the need for integrated land-use planning, access management, and Grizzly Bear conservation efforts to consider the implications of continued access for motorised recreation in areas occupied by Grizzly Bears.
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Grizzly Bear connectivity mapping in the canada united states trans border region
Journal of Wildlife Management, 2015Co-Authors: Michael F. Proctor, Wayne F. Kasworm, Christopher Servheen, Scott E. Nielsen, Thomas G Radandt, Grant A Machutchon, Mark S. BoyceAbstract:Fragmentation is a growing threat to wildlife worldwide and managers need solutions to reverse its impacts on species' populations. Populations of Grizzly Bears (Ursus arctos), often considered an umbrella and focal species for large mammal conservation, are fragmented by human settlement and major highways in the trans-border region of southern British Columbia, northern Montana, Idaho, and northeastern Washington. To improve prospects for Bear movement among 5 small fragmented Grizzly Bear subpopulations, we asked 2 inter-related questions: Are there preferred linkage habitats for Grizzly Bears across settled valleys with major highways in the fragmented trans-border region, and if so, could we predict them using a combination of resource selection functions and human settlement patterns? We estimated a resource selection function (RSF) to identify high quality backcountry core habitat and to predict front-country linkage areas using global positioning system (GPS) telemetry locations representing an average of 12 relocations per day from 27 Grizzly Bears (13F, 14M). We used RSF models and data on human presence (building density) to inform cost surfaces for connectivity network analyses identifying linkage areas based on least-cost path, corridor, and circuit theory methods. We identified 60 trans-border (Canada–USA) linkage areas across all major highways and settlement zones in the Purcell, Selkirk, and Cabinet Mountains encompassing 24% of total highway length. We tested the correspondence of the core and linkage areas predicted from models with Grizzly Bear use based on Bear GPS telemetry locations and movement data. Highway crossings were relatively rare; however, 88% of 122 crossings from 13 of our Bears were within predicted linkage areas (mean = 8.3 crossings/Bear, SE = 2.8, range 1–31, 3 Bears with 1 crossing) indicating Bears use linkage habitat that could be predicted with an RSF. Long-term persistence of small fragmented Grizzly Bear populations will require management of connectivity with larger populations. Linkage areas identified here could inform such efforts. © 2015 The Wildlife Society.
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Grizzly Bear diet shifting on reclaimed mines
Global Ecology and Conservation, 2015Co-Authors: Bogdan Cristescu, Gordon B. Stenhouse, Mark S. BoyceAbstract:Paper published in July 2015 issue of Global Ecology and Conservation, from the fRI Grizzly Bear Program
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Mad cow policy and management of Grizzly Bear incidents
Wildlife Society Bulletin, 2012Co-Authors: Joseph M. Northrup, Mark S. BoyceAbstract:Protection of humans and livestock from disease has been used to justify many aggressive and costly wildlife control programs. Recent regulatory changes on livestock carcass disposal aimed at controlling the spread of bovine spongiform encephalopathy in Canada have led to substantial increases in exposed livestock carcass dumps. Such ''boneyards'' are known to attract Grizzly Bears (Ursus arctos), which leads to human-Bear conflict. We compiled data on human-Grizzly Bear interactions in an agricultural landscape in southwestern Alberta over a 12-year time period (1999-2010) overlapping regulatory changes. Boneyards increased markedly after regulations were enacted and Grizzly Bear incidents increased correspondingly, particularly those related to dead livestock. The high rate of conflict results in frequent management captures, relocations, and translocations that create a likely population sink. Although work is underway to reduce human-Bear interactions, revisions are needed to recent regulatory changes, such that they take wildlife into account. When combined with programs aimed at ensuring proper storage of attractants, we believe that such policy reforms will make it possible for humans to coexist with Grizzly Bears in southwestern Alberta. 2012 The Wildlife Society.
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Grizzly Bear movements relative to roads application of step selection functions
Ecography, 2010Co-Authors: Carrie L Roever, Mark S. Boyce, Gordon B. StenhouseAbstract:Access management is among the most important conservation actions for Grizzly Bears in North America. In Alberta, Canada, nearly all Grizzly Bear mortalities are caused by humans and occur near roads and trails. Consequently, understanding how Bears move relative to roads is of crucial importance for Grizzly Bear conservation. We present the first application of step-selection functions to model habitat selection and movement of Grizzly Bears. We then relate this to a step-length analysis to model the rate of movement through various habitats. Grizzly Bears of all sex and age groups were more likely to select steps closer to roads irrespective of traffic volume. Roads are associated with habitats attractive to Bears such as forestry cutblocks, and models substituting cutblocks for roads outperformed road models in predicting Bear selection during day, dawn, and dusk time periods. Bear step lengths increased near roads and were longest near highly trafficked roads indicating faster movement when near roads. Bear selection of roads was consistent throughout the day; however, time of day had a strong influence over selection of forest structure and terrain variables. At night and dawn, Bears selected forests of intermediate age between 40 and 100 yr, and Bears selected older forests during the day. At dawn, Bears selected steps with higher solar radiation values, whereas, at dusk, Bears chose steps that were significantly closer to edges. Because Grizzly Bears use areas near roads during spring and most human-caused mortalities occur near roads, access management is required to reduce conflicts between humans and Bears. Our results support new conservation guidelines in western North America that encourage the restriction of human access to roads constructed for resource extraction.
