Road characteristics best predict the probability of vehicle collisions with a non-native, hyperabundant ungulate
These datafiles are used in analyses contained in the manuscript Tanner, A.L., Leroux, S.J., and Saunders, P.W. [submitted]. Road characteristics best predict the probability of vehicle collisions with a non-native, hyperabundant ungulate. These data include information on environmental variables at...
| Main Authors: | , , |
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| Format: | Dataset |
| Language: | unknown |
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figshare
2015
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| Online Access: | https://dx.doi.org/10.6084/m9.figshare.1481062.v3 https://figshare.com/articles/dataset/Road_characteristics_best_predict_the_probability_of_vehicle_collisions_with_a_non_native_hyperabundant_ungulate/1481062/3 |
| Summary: | These datafiles are used in analyses contained in the manuscript Tanner, A.L., Leroux, S.J., and Saunders, P.W. [submitted]. Road characteristics best predict the probability of vehicle collisions with a non-native, hyperabundant ungulate. These data include information on environmental variables at 600 moose-vehicle collision locations, and 3296 randomly selected locations in Newfoundland, Canada. There are three buffer sizes (500m, 2736m, and 5471m) used for all variables that require buffered areas. This file also contains the R code that we used to conduct the analyses. We have included comments throughout the code in order to understand the operations being performed. When importing a new dataset (either: spatialall.csv or spatialallcorr.csv) while running the R code, be sure to set the Please read Metadata file carefully before using any of this data. |
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