A Comparison of Remotely Sensed Environmental Predictors for Avian Distributions

This repository contains the code and data for recreating the experiments in:

L.M. Hopkins, T.A. Hallman, J. Kilbride, W.D. Robinson, R.A. Hutchinson (2022) Landscape Ecology
https://doi.org/10.1007/s10980-022-01406-y

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1. Download the all of the data and save it in your working directory.

2. Generate SDMs (RF models) and thier predictions.
   
   Run run_model.R
   
   Create a new "results" folder in your working directory. Withing the "results" folder, create a folder for each model and within each model, create folders for each species. The path should look like: <working_directory>\\<model>\\<species>. Moeve the .RData test table(s) created by run_model.R to the associated folder(s).

3. Evaluate models by comparing AUCs across species and spectral predictor sets.
   
   Run evaluation.R

4. Identifiy which spectral predictor sets performed best across the entire set of species and compare all pairs of spectral predictor sets with Nemenyi post-hoc analysis.
   
   Run statistical_analysis.R

5. (Optional) Generate plots.
   
   Run publication_plots.R