Roads, while central to the function of human society, create barriers to animal movement through collisions and habitat fragmentation. Barriers to animal movement affect the evolution and trajectory of populations. Investigators have attempted to use traffic volume, the number of vehicles passing a point on a road segment, to predict effects to wildlife populations approximately linearly and along taxonomic lines; however, taxonomic groupings cannot provide sound predictions because closely related species often respond differently. We assess the role of wildlife behavioral responses to traffic volume as a tool to predict barrier effects from vehicle‐caused mortality and avoidance, to provide an early warning system that recognizes traffic volume as a trigger for mitigation, and to better interpret roadkill data. We propose four categories of behavioral response based on the perceived danger to traffic: Nonresponders, Pausers, Speeders, and Avoiders. Nonresponders attempt to cross highways regardless of traffic volume. Pausers stop in the face of danger so have a low probability of successful crossing when traffic volume increases. Hence, highway barrier effects are primarily due to mortality for Nonresponders and Pausers at high traffic volumes. Speeders run away from danger but are unable to do so successfully as traffic volume increases. At moderate to high volume, Speeders are repelled by traffic danger. Avoiders face lower mortality than other categories because they begin to avoid traffic at relatively low traffic volumes. Hence, avoidance causes barrier effects more than mortality for Speeders and Avoiders even at relatively moderate traffic volumes. By considering a species’ risk‐avoidance response to traffic, managers can make more appropriate and timely decisions to mitigate effects before populations decline or become locally extinct.

Densely vegetated environments have hindered collection of basic population parameters on forest‐dwelling ungulates. Our objective was to develop a mark–recapture technique that used DNA from fecal pellets to overcome constraints associated with estimating abundance of ungulates in landscapes where direct observation is difficult. We tested our technique on Sitka black‐tailed deer (Odocoileus hemionus sitkensis) in the temperate coastal rainforest of Southeast Alaska. During 2006–2008, we sampled fecal pellets of deer along trail transects in 3 intensively logged watersheds on Prince of Wales Island, Alaska. We extracted DNA from the surface of fecal pellets and used microsatellite markers to identify individual deer. With genotypes of individual deer, we estimated abundance of deer with moderate precision (±20%) using mark–recapture models. Combining all study sites, we identified a 30% (SE = 5.1%) decline in abundance during our 3‐year study, which we attributed to 3 consecutive severe winters. We determined that deer densities in managed land logged >30 years ago (7 deer/km2, SE = 1.3) supported fewer deer compared to both managed land logged <30 years ago (10 deer/km2, SE = 1.5) and unmanaged land (12 deer/km2, SE = 1.4). Our study provides the first estimates of abundance (based on individually identified deer) for Sitka black‐tailed deer and the first estimates of abundance of an unenclosed ungulate population using DNA from fecal pellets. Our tool enables managers to accurately and precisely estimate the abundance of deer in densely vegetated habitats using a non‐invasive approach. © 2011 The Wildlife Society.

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