Road Characteristics Best Predict the Probability of Vehicle Collisions with a Non-native Ungulate

These datafiles are used in analyses contained in the manuscript Tanner AL, Leroux SJ, and Saunders PW. [submitted]. Road Characteristics Best Predict the Probability of Vehicle Collisions with a Non-native Ungulate. These data include information on environmental variables at 600 moose-vehicle coll...

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Bibliographic Details
Main Authors: Tanner, Amy, Leroux, Shawn, Saunders, Paul
Format: Dataset
Language:unknown
Published: figshare 2016
Subjects:
Ecology
FOS Biological sciences
Canada
Leroux
Saunders
Newfoundland
Online Access:https://dx.doi.org/10.6084/m9.figshare.1481062.v10
https://figshare.com/articles/dataset/Road_characteristics_best_predict_the_probability_of_vehicle_collisions_with_a_non_native_hyperabundant_ungulate/1481062/10
Description
Summary:These datafiles are used in analyses contained in the manuscript Tanner AL, Leroux SJ, and Saunders PW. [submitted]. Road Characteristics Best Predict the Probability of Vehicle Collisions with a Non-native Ungulate. These data include information on environmental variables at 600 moose-vehicle collision locations and 1200 randomly selected locations in Newfoundland, Canada. There is one buffer size (5471m radius) 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. Be sure to import the new datasets (spatialallmvc.csv or spatialallrandom.csv). Please read Metadata file carefully before using any of this data.

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