Relationships Among Grizzly Bears, Roads and Habitat in the Swan Mountains Montana

Mace, Richard D.; Waller, John S.; Manley, Timothy L.; Lyon, I. J.; Zuuring, H.

doi:10.2307/2404779

Cited by 250 publications

(208 citation statements)

References 24 publications

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“…Roads may interact with habitat to influence the observed distribution of wildlife . The value of incorporating habitat information has been demonstrated in previous road-impact studies involving grizzly bears (Ursus arctos) (Mace et al 1996, Ciarniello et al 2007, Roever et al 2008, mule deer (Odocoileus hemionus) (Sawyer et al 2006), and elk (Cervus elaphus) (Sawyer et al 2007). These studies collectively illustrate that animals avoided preferred habitats with increasing levels of traffic, with potential repercussions on forage availability, individual fitness, and ultimately population productivity.…”

Section: Percent Increase In Vehicular Activitymentioning

confidence: 97%

Evaluating the road-effect zone on wildlife distribution in a rural landscape

Shanley

Pyare

2011

Ecosphere

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Abstract. The road-effect zone is the area in which ecological effects extend outward from a road.Dispersed off-highway vehicle (OHV; e.g., four-wheelers and snowmachines) activity on rural road networks creates a disturbance that reduces the effective amount of wildlife habitat and therefore has the potential for an extensive road-effect zone. Consequently, land managers must consider the trade-offs between rural road development and the conservation of habitat for species of concern. We conducted a spatially-explicit study of moose, Alces alces, occurrence in relation to rural roads and OHV routes in rural Alaska, U.S.A. We used logistic regression and AIC model selection criterion to develop resource selection functions (RSFs) for male and female moose at three spatial scales (250 m, 500 m, and 1000 m) in two seasons (summer and fall). To evaluate an ecological disturbance threshold from increasing route activity on the probability of animal occurrence, the RSFs were plotted against an index of route activity derived from interviews with OHV users, and fit with logarithmic functions. The variable for route activity improved the fit of RSF models for both sexes at all spatial scales and in both seasons. A negative relationship was found between moose occurrence and routes or areas in which routes were in close proximity to primary forage, with the exception of male moose at the 1000-m scale in the fall. Therefore, among the spatial scales of analysis, the road-effect zone for male moose was determined to be between 500 m and 1000 m, and .1000 m for female moose. Furthermore, route activity ,0.25 km of vehicle travel/km 2 / day was a threshold value at which moose sustained a high probability of occurrence (0.60 to 0.91). The results of our study suggest that the dispersed ecological effect of rural roads and OHV routes should be considered in transportation and land-management planning efforts. Relatively low levels of vehicular activity may create extensive road-effect zones for sensitive species.

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Section: Percent Increase In Vehicular Activitymentioning

confidence: 97%

Evaluating the road-effect zone on wildlife distribution in a rural landscape

Shanley

Pyare

2011

Ecosphere

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“…Behavioral decisions, driven by factors such as territoriality (Moorcroft and Lewis 2006) or fear-driven habitat avoidance, may prevent or reduce the chance of dispersal be-tween patches. For example, large predators, such as bears, may avoid road crossings when moving between forest patches (e.g., Mace et al 1996). In this case, the degree to which the predator avoids long-distance dispersal between patches, rather than movement speed or home-range size, will determine how strongly populations of the predator interact.…”

Section: What Movement Mechanisms Can Lead Tomentioning

confidence: 99%

Nonhierarchical Dispersal Promotes Stability and Resilience in a Tritrophic Metacommunity

Pedersen

Marleau

Granados

et al. 2016

The American Naturalist

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Community interactions (e.g., predation, competition) can be characterized by two factors: their strengths and how they are structured between and within species. Both factors play a role in determining community dynamics. In addition to trophic interactions, dispersal acts as an interaction between separate populations. As with other interactions, the structure of dispersal can affect the stability of a system. However, the primary structure that has been studied in consumer-resource models has been hierarchical dispersal, where between-patch dispersal rates increase with trophic level. Here we use analytical, numerical, and simulation approaches on a two-patch, three-species metacommunity model to investigate the relationship between structure and community stability and resilience. We show that metacommunity stability is greater in systems with both weak and strong dispersal rates. Our system is stabilized by the formation of patterns when predators disperse frequently and herbivores disperse rarely, and via asynchrony when both predators and herbivores disperse infrequently. Our results show how interaction strengths within both trophic and spatial networks shape metacommunity stability.

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“…For many mammal populations, the main demonstrated impact of roads to date has been in terms of increased disturbance or mortality. Avoidance of otherwise suitable habitats in close proximity to roads has been shown to occur for brown bears (Ursus arctos) and wolves (Canis lupus) in the U.S.A. (McLellan and Shackleton 1988, Mace et al 1996, Mech et al 1988. For some mammal species, roads have been shown to act also as a considerable barrier to dispersal (Mader 1984).…”

Section: Introductionmentioning

confidence: 99%