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  • 1
    In: Journal of Applied Ecology, Wiley, Vol. 49, No. 5 ( 2012-10), p. 1159-1167
    Abstract: Grizzly bear responses to traffic caused a departure from typical behavioural patterns, with bears in our study being largely nocturnal. In addition, bears selected private agricultural land, which had lower traffic levels, but higher road density, over multi‐use public land. These results improve our understanding of bear responses to roads and can be used to refine management practices. Future management plans should employ a multi‐pronged approach aimed at limiting both road density and traffic in core habitats. Access management will be critical in such plans and is an important tool for conserving threatened wildlife populations.
    Type of Medium: Online Resource
    ISSN: 0021-8901 , 1365-2664
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2012
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    detail.hit.zdb_id: 410405-5
    SSG: 12
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  • 2
    In: Ecology and Evolution, Wiley, Vol. 9, No. 18 ( 2019-09), p. 10801-10815
    Abstract: The influence of humans on large carnivores, including wolves, is a worldwide conservation concern. In addition, human‐caused changes in carnivore density and distribution might have impacts on prey and, indirectly, on vegetation. We therefore tested wolf responses to infrastructure related to natural resource development (i.e., human footprint). Location Our study provides one of the most extensive assessments of how predators like wolves select habitat in response to various degrees of footprint across boreal ecosystems encompassing over a million square kilometers of Canada. Methods We deployed GPS‐collars on 172 wolves, monitored movements and used a generalized functional response (GFR) model of resource selection. A functional response in habitat selection occurs when selection varies as a function of the availability of that habitat. GFRs can clarify how human‐induced habitat changes are influencing wildlife across large, diverse landscapes. Results Wolves displayed a functional response to footprint. Wolves were more likely to select forest harvest cutblocks in regions with higher cutblock density (i.e., a positive functional response to high‐quality habitats for ungulate prey) and to select for higher road density in regions where road density was high (i.e., a positive functional response to human‐created travel routes). Wolves were more likely to use cutblocks in habitats with low road densities, and more likely to use roads in habitats with low cutblock densities, except in winter when wolves were more likely to use roads regardless of cutblock density. Main conclusions These interactions suggest that wolves trade‐off among human‐impacted habitats, and adaptively switch from using roads to facilitate movement (while also risking encounters with humans), to using cutblocks that may have higher ungulate densities. We recommend that conservation managers consider the contextual and interacting effects of footprints when assessing impacts on carnivores. These effects likely have indirect impacts on ecosystems too, including on prey species.
    Type of Medium: Online Resource
    ISSN: 2045-7758 , 2045-7758
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2635675-2
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  • 3
    In: Oikos, Wiley, Vol. 119, No. 8 ( 2010-02-26), p. 1243-1254
    Type of Medium: Online Resource
    ISSN: 0030-1299
    Language: English
    Publisher: Wiley
    Publication Date: 2010
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    detail.hit.zdb_id: 207359-6
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Wiley ; 2022
    In:  The Journal of Wildlife Management Vol. 86, No. 1 ( 2022-01)
    In: The Journal of Wildlife Management, Wiley, Vol. 86, No. 1 ( 2022-01)
    Abstract: The decline of many woodland caribou ( Rangifer tarandus caribou ) populations is thought to be linked with habitat disturbances resulting from industrial development, including timber harvesting and its network of haul roads. Defining a disturbance‐abundance relationship offers a tool to assess and potentially manage for the influence of disturbance on caribou abundance. Defining this relationship is challenged by limited historical land use and abundance data, the choice of a disturbance measure, and variability in the relationship between subpopulations and across core versus matrix habitat. For 12 subpopulations of woodland caribou within the southern mountain population, we linked longitudinal caribou abundance data with historical forestry disturbances simulated from forest harvest data. We compared disturbance measures estimating the proportion of forested area commercially harvested with even‐aged, regeneration treatments (cutblocks) and converted to roads for transporting timber within subpopulation‐specific core and matrix habitats as predictors of caribou abundance. Non‐linear mixed models provided evidence that disturbances in matrix habitats negatively influenced caribou abundance, with the effects in core habitat being variable between subpopulations. Of the disturbance types evaluated, the best predictors included roads buffered by 50 m (R50), cutblocks ≤80 years old, and the cumulation of cutblocks ≤80 years old plus roads buffered by 50 m. The top‐ranked model was composed of R50 present in core and in matrix habitats. This model predicted a 42% (95% CI = 33–51%) reduction in caribou abundance for every 1% increase in matrix R50 (holding core R50 constant). Given the lack of pre‐forestry abundance data, we failed to directly derive critical disturbance thresholds; however, our models could be used to estimate subpopulation‐specific habitat‐disturbance thresholds necessary to achieve abundance targets. We recommend that in addition to existing protections of core habitat, few if any new roads should be built in core habitat, and that timber harvest in matrix habitat should be designed to minimize the establishment of associated roads.
    Type of Medium: Online Resource
    ISSN: 0022-541X , 1937-2817
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2066663-9
    SSG: 12
    SSG: 23
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