This repo contains the R code used to analyse the effect of sampling strategy on the precision (variance) and accuracy (bias) of response curves estimated by species distribution models.

Scripts and content:

• Bio_Elev_data: script reporting code to get and process elevation and bioclimatic (CHELSA) data used in the simualtions;
• Sampling_strategies: script reporting code for generating data and functions used to simulate the tested sampling approaches (random, proportional stratified, proximity-to-road, uniform within the environmental space, systematic within the geographical space, topographic);
• Dianthus_sperandii, Dianthus_tundrae: scripts reporting code used for simulations related to the virtual specis having a wide (D. sperandii) and a narrow (D. tundrae) geographical distribution;
• Figures: script reporting code for reproducing some of the figures presented in the manuscript (e.g., simulated species' response curves and geographical distributions);
• Review: script reporting new analyses that cosist in: 1) testing the effect of missing covariates on the performance of the sampling strategies; 2) testing the impact of incompletely sampling the environmental space on the performance of the uniform approach; 3) testing the effect of randomly sampling the environmental space; and 4) analysing the impact of having a (low) amount of sampling units consistently (i.e., across simualtions) collected by the uniform approach on the estimator of the variance of regression coefficients.

The order in which the code should be run is the following: Bio_Elev_data -> Sampling_strategies -> Dianthus_sperandii -> Dianthus_tundrae -> Figures. Code in the Review script depends on all the previous, but Figures.

R version used: R version 4.1.0 (2021-05-18)

Version of the main R packages used:

• raster ‘3.5.9’
• sf ‘1.0.0’
• ggplot2 ‘3.3.5’
• elevatr ‘0.4.2’
• car ‘3.0.11’