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Gewählte Publikation:

Steiner, W; Schöll, EM; Leisch, F; Hackländer, K; .
(2021): Temporal patterns of roe deer traffic accidents: Effects of season, daytime and lunar phase.
PLoS One. 2021; 16(3):e0249082 FullText FullText_BOKU

Wildlife-related accidents, especially deer-vehicle accidents, pose a serious problem for road safety and animal protection in many countries. Knowledge of spatial and temporal patterns of deer-vehicle accidents is inevitable for accident analysis and mitigation efforts with temporal deer-vehicle accident data being much more difficult to obtain in sufficient data quality. We described the temporal patterns of roe deer (Capreolus capreolus) roadkills occurring in the period 2002-2006 in southeastern Austria. Using a comprehensive dataset, consisting of 11.771 data points, we examined the influence of different time units (i.e. season, month, day of week, day of year), illumination categories (coarse and fine temporal resolution) and lunar phases on deer-vehicle accidents by performing linear and generalized additive models. Thereby, we identified peak accident periods within the analyzed time units. Highest frequencies of deer-vehicle accidents occurred in November, May and October, on Fridays, and during nights. Relationships between lunar phases and roe deer-vehicle accidents were analysed, providing evidence for high frequencies of deer-vehicle accidents during full moon phases. We suggest that deer-vehicle accidents are dependent both on human activity in traffic and wildlife activity, which is in turn affected by phenology, intra- and interspecific competition, climatic and astronomical events. Our results highlight, that short-term mitigation measures (e.g. traffic controls and speed limits) can be highly effective to reduce deer-vehicle accidents, but should be flexibly adapted to specific temporal periods.
Autor*innen der BOKU Wien:
Hackländer Klaus
Leisch Friedrich
Schöll Eva Maria
Steiner Wolfgang
BOKU Gendermonitor:

Find related publications in this database (using NML MeSH Indexing)
Accidents, Traffic/statistics & numerical data*
Time Factors

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