DOI: 10.5683/sp3/0xmutw
title: Walking the line: Investigating biophysical characteristics related to wildlife use of linear features

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p&gt;Habitat restoration is a necessary component of wildlife conservation in anthropogenic landscapes. To ensure restoration initiatives achieve the desired effects on wildlife communities, it is useful to investigate how animals use landscape features. Understanding the relationships between wildlife use and ecological cues provides specific and measurable targets that can be used to measure restoration success. In western Canada, linear feature networks formed by seismic lines, pipelines, and roads have altered the boreal forest landscape and resulted in population declines for woodland caribou. Restoration is aimed at supporting caribou recovery by deterring linear feature use by caribou predators and ungulate competitors. Information on how linear feature characteristics facilitate or deter wildlife use supports restoration initiatives by providing specific targets for restoration. Here, we used wildlife track and sign data to investigate biophysical characteristics related to the use of linear features by canines, bears, deer, elk, and moose in caribou ranges of west-central and north-western Alberta and British Columbia. We built generalized linear mixed models consistent with three hypotheses that could explain likely mechanisms for use: 1) ease of movement, 2) risk avoidance, and 3) resource availability (prey and forage).&lt;/p&gt;
&lt;p&gt;Moose, deer, elk, and bears were more likely to use linear features with either human or game trails. Bears and canines were less likely to use seismic lines with greater lateral vegetation cover and taller vegetation, respectively. Moose, deer, and elk were more likely to use linear features with greater cover of ungulate forage taxa such as willow, birch, sedges, and forbs. These results suggest that restoration focusing on trails, online vegetation structure, and online vegetation type should deter predators and ungulate prey species to the overall benefit of caribou. Our study corroborates the findings of other research recommending structural and functional restoration utilizing high-intensity line blocking and vegetative regeneration. We provide specific targets for linear feature restoration to assist in prioritization according to restoration objectives, which translates to a broader goal of linking local-level restoration actions to landscape-level conservation goals. This approach to restoration has implications for any major system experiencing anthropogenic landscape change.&lt;/p&gt;
description: &lt;b&gt;Methods&lt;/b&gt;&lt;br /&gt;&lt;p&gt;&lt;span lang="EN-US"&gt;&lt;span lang="EN-US"&gt;The study areas consisted of caribou ranges in west-central and north-western Alberta and British Columbia, Canada. The west-central area included four caribou ranges – Little Smoky, A la Peche, and the Alberta portions of Redrock-Prairie Creek and Narraway outside of protected areas (-117˚ W to -120˚ W, 53˚ N to 55˚ N). The north-western area included the Chinchaga range on both sides of the provincial border (-117˚ W to -122˚ W, 56˚ N to 58˚ N; Fig. 1). The areas totaled 47,100 km2 and contained over 92,943 km of linear features, including seismic lines, pipelines, and inactive forestry roads.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;
&lt;p&gt;&lt;span lang="EN-US"&gt;The primary goal of field data collection was to collect information on human use of linear features&lt;/span&gt;&lt;span lang="EN-US"&gt;. Using a geographic information system (GIS) and a random number generator, we selected linear features that intersected access roads. We created a unique identifier for each linear feature (&lt;em&gt;LineID&lt;/em&gt;) and established three plots at 0m, 100m, and 500m away from the intersecting access road. We visited all west-central and north-western seismic line sampling sites in June–October 2014, 2015, and north-western pipeline sites in August 2017 to record wildlife and human linear feature use, collect field measurements of linear feature and surrounding forest characteristics, and identify vegetation taxa. On the linear feature (‘online’), we identified tracks, scat, and any other wildlife and human sign. We classified canines (wolves and coyotes, &lt;em&gt;C. latrans&lt;/em&gt;), bears (black bears, &lt;em&gt;U. americanus&lt;/em&gt;, and grizzly bears, &lt;em&gt;U. arctos&lt;/em&gt;), and deer (white-tailed deer, &lt;em&gt;O. virginianus&lt;/em&gt;, and mule deer, &lt;em&gt;O. hemonius&lt;/em&gt;) at the genus level and caribou, moose, and elk at the species level&lt;/span&gt;&lt;span lang="EN-US"&gt;. &lt;/span&gt;&lt;span lang="EN-US"&gt;To account for weather impacts on tracks and signs,&lt;/span&gt; &lt;span lang="EN-US"&gt;we assigned a confidence level to each observation, and only included observations assigned confidence levels of ‘reasonably certain’ and ‘certain’ in statistical modelling. We measured an average online lateral vegetation cover from cover board measurements taken in both directions from the plot&lt;/span&gt;&lt;span lang="EN-US"&gt;, measured average vegetation height, recorded soil moisture, and the presence/absence of human and game trails (see &lt;/span&gt;&lt;span lang="EN-US"&gt;Pigeon et al., 2016&lt;/span&gt;&lt;span lang="EN-US"&gt; for details). In the surrounding forest (‘offline’, 15m from the linear feature), we again measured lateral vegetation cover and average tree height. To record vegetation composition data, we established online 10m&lt;sup&gt;2&lt;/sup&gt; and 1m&lt;sup&gt;2&lt;/sup&gt; subplots at the plot 100m from the access road; we only recorded vegetation composition data within this plot because of limited time and resources for field data collection. Within these subplots, we identified and recorded the percent ground cover of vegetation taxa used as forage by bears and caribou alternate competitors&lt;/span&gt;&lt;span lang="EN-US"&gt;. &lt;/span&gt;We standardized and scaled continuous and percent variables prior to modelling.&lt;/p&gt;
description: &lt;b&gt;Usage notes&lt;/b&gt;&lt;br /&gt;&lt;p&gt;All data were processed using R programming software (R Core Team, 2019).&lt;/p&gt;
description: <b>Dryad version number:</b> 4
<b>Version status:</b> submitted
<b>Dryad curation status:</b> Published
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