2018
DOI: 10.1016/j.foreco.2017.12.010
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Divergent patterns of understory forage growth after seismic line exploration: Implications for caribou habitat restoration

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Cited by 60 publications
(80 citation statements)
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“…In our system, we expect to observe these patterns in both ungulate species (caribou and moose), with a magnitude reflecting their respective vulnerability to wolf predation Mumma et al, 2017). Lastly, if anthropogenic LFs provide subsidies, as is the expectation for bears, another dominant predator in our system (Dawe, Filicetti, & Nielsen, 2017;Finnegan, MacNearney, & Pigeon, 2018;Tigner et al, 2014), we predict that individuals select these features and move slowly when they are on them. While LFs are predicted to provide subsidies that would also attract moose, we predict LFs are more strongly associated with risk.…”
mentioning
confidence: 73%
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“…In our system, we expect to observe these patterns in both ungulate species (caribou and moose), with a magnitude reflecting their respective vulnerability to wolf predation Mumma et al, 2017). Lastly, if anthropogenic LFs provide subsidies, as is the expectation for bears, another dominant predator in our system (Dawe, Filicetti, & Nielsen, 2017;Finnegan, MacNearney, & Pigeon, 2018;Tigner et al, 2014), we predict that individuals select these features and move slowly when they are on them. While LFs are predicted to provide subsidies that would also attract moose, we predict LFs are more strongly associated with risk.…”
mentioning
confidence: 73%
“…We targeted the snow‐free period because it is when bears are active and woodland caribou neonates and adults are most susceptible to predation (McLoughlin, Dzus, Wynes, & Boutin, ). This period is also when anthropogenic LFs are hypothesized to provide the biggest movement benefit to wolves (Finnegan et al, ) and deep, uncompacted snow conditions on unmaintained LFs are less favourable during winter months (Droghini & Boutin, ). All GPS data were screened for potential errors by excluding 3‐dimensional locations with a dilution of precision (DOP) >10 and 2‐dimensional locations with DOP > 5 (accounting for <0.3% of the total data from individuals monitored with 15‐min data), as well as based descriptors of movement following the methods of Bjørneraas, Van Moorter, Rolandsen, and Herfindal ().…”
Section: Methodsmentioning
confidence: 99%
“…Because of the small spatial extent of roads and pipelines (i.e., <5% of LFs), we did not test for effects of line type, rather we combined all LF data sources to create a parsimonious disturbance layer while retaining attributes describing relative disturbance age (≤2005 versus ≥2006). We buffered all disturbances by 20 m, a width incorporating the mean GPS measurement error estimated for a similar model of Lotek GPS collars (14 m;McKenzie et al 2009) and potential edge effects on vegetation composition and structure extending into the surrounding forest (Finnegan et al 2018). Locations falling within this buffered distance were therefore considered within the footprint.…”
Section: Environmental Covariatesmentioning
confidence: 99%
“…These hypotheses described whether LFs (i) increased forage availability, (ii) enhanced movement efficiency, or (iii) increased predation risk. Under the forage availability hypothesis, bison are predicted to select for LFs and move slower while on them because LFs have higher abundances of preferred forage (e.g., graminoids, forbs, and shrubs; Larter and Gates 1991; Jung 2015) compared with the surrounding forest (Leverkus 2015;Finnegan et al 2018). The movement efficiency hypothesis similarly predicts for LF selection, but movement on them will be faster (Dickie et al 2017b;Serrouya et al 2017).…”
Section: Introductionmentioning
confidence: 99%
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