Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1016/j.ecolmodel.2004.12.015
Title (Primary) Predicting when animal populations are at risk from roads: an interactive model of road avoidance behavior
Author Jaeger, J.A.G.; Bowman, J.; Brennan, J.; Fahrig, L.; Bert, D.; Bouchard, J.; Charbonneau, N.; Frank, K. ORCID logo ; Gruber, B.; Tluk von Toschanowitz, K.
Source Titel Ecological Modelling
Year 2005
Department OESA; NSF
Volume 185
Issue 2-4
Page From 329
Page To 348
Language englisch
Abstract Roads and traffic affect animal populations detrimentally in four ways: they decrease habitat amount and quality, enhance mortality due to collisions with vehicles, prevent access to resources on the other side of the road, and subdivide animal populations into smaller and more vulnerable fractions. Roads will affect persistence of animal populations differently depending on (1) road avoidance behavior of the animals (i.e., noise avoidance, road surface avoidance, and car avoidance); (2) population sensitivity to the four road effects; (3) road size; and (4) traffic volume. We have created a model based on these population and road characteristics to study the questions: (1) what types of road avoidance behaviors make populations more vulnerable to roads?; (2) what types of roads have the greatest impact on population persistence?; and (3) how much does the impact of roads vary with the relative population sensitivity to the four road effects? Our results suggest that, in general, the most vulnerable populations are those with high noise and high road surface avoidance, and secondly, those with high noise avoidance only. Conversely, the least vulnerable populations are those with high car avoidance only, and secondly, high road surface and high car avoidance. Populations with low overall road avoidance and those with high overall road avoidance tend to respond in opposite ways when the sensitivity to the four road effects is varied. The same is true of populations with high road surface avoidance when compared to those with high car and high noise avoidance. The model further predicted that traffic volume has a larger effect than road size on the impact of roads on population persistence. One potential application of our model (to run the model on the web or to download it go to or or contact the first author) is to generate predictions for more structured field studies of road avoidance behavior and its influence on persistence of wildlife populations.
Persistent UFZ Identifier
Jaeger, J.A.G., Bowman, J., Brennan, J., Fahrig, L., Bert, D., Bouchard, J., Charbonneau, N., Frank, K., Gruber, B., Tluk von Toschanowitz, K. (2005):
Predicting when animal populations are at risk from roads: an interactive model of road avoidance behavior
Ecol. Model. 185 (2-4), 329 - 348 10.1016/j.ecolmodel.2004.12.015