Identifying blackspots of wildlife collisions on the Swedish railroad

Detta är en Master-uppsats från SLU/Dept. of Ecology

Sammanfattning: The number of wildlife collisions on the Swedish railroads is increasing at a rate unmatched by the development of wildlife populations and expansion of the railroad traffic. It is therefore essential to identify areas where the yearly risk of collisions is great (blackspots), to be able to allocate mitigating efforts in areas where they are most essential and effective. The aim of this report was to develop a method to iden-tify blackspots for roe deer and moose collisions on railroads. Incidents are reported by segments, which are partitioned sections of the railroads. I defined a segment as a blackspot when it had continuously high number of incidents. Four different sets of blackspots were created. Segments were defined as blackspots if they were 10 or 13 years above the 60th percentile of the national distribution of incidents per km, or 10 or 13 years above the 70th percentile. The segments within these four sets where then ranked. To evaluate the different sets, I performed separate logistic regression for each set of defined blackspots where the dependent variables were the blackspots (1) and segments below the 50th percentile for all years (0). To further analyse the difference of the sets, receiver operating characteristics (ROC) - curves were calculated for each final model which is a statistical tool used to assess a logistic model’s ability to differentiate between, in this case, blackspots and low-frequency segments. For both species, 13 years above the 70th percentile resulted in models with the greatest ability to discriminate between blackspots and low-frequency segments and held the highest number of incidents per total length of railroads. Future analysis of which percentile to use and how many years the segment should be above that percentile is needed. However, I have developed a method to identify the segments that are in the biggest need of mitigating efforts. The strength of my approach to identify blackspots is that it can be adjusted to different needs and purposes, and is flexible to suit many different goals.

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