Spatial Functions for Heterogeneity and Climate Variability.

heterogen: An R package with spatial functions for heterogeneity and climate variability

P. Joser Atauchi & A. Townsend Peterson

Installation

heterogen is available from CRAN, so you can use install.packages("heteogen") to get the current released version. Current version was tested on Windows 11 and OSX 15+.

The easiest way to use the development version on Windows or MacOS, is to install it from github:

From source-code

To install from source-code, first install the Rcpp, RcppArmadillo, and RcppEigen package that heterogen depends on:

install.packages(c("Rcpp","RcppArmadillo","RcppEigen"))

And then continue based on the OS you are using.

Windows

On Windows, you need to first install Rtools to get a C++ compiler that R can use. You need a recent version of Rtools42.

MacOS

On macOS, you can use xcode syntax from terminal via homebrew.

sudo xcode-select --install

and Fortran v11.5.

R package

After installing dependencies, it can install heterogen via remote from github .

if (!require('remotes')) install.packages('remotes')
remotes::install_github("patauchi/heterogen")

Introduction

heterogen is an R package made to create heterogeneity layers as additional information in ecological niche models.

Getting Started

Environmental Data

In this approach, whatever climate data can be used such as WorldClim, Chelsa, MerraClim, etc.

Heterogeneity Layers

Repository

A complete set of raster layers was created to promote the use of spatial heterogeneity of environmental conditions. The datasets are available from Figshare Link.

Examples

Warnings

Performance

At this time, the core of the functions are constantly modified in order to reduce the time of data processing (large dataset: 1Mx1M matrices). Stable version are available from CRAN.

References

Atauchi, P. Joser; Peterson, A.Townsend. (202X). Incorporating spatial environmental heterogeneity as additional information on environmental and spatial context in ecological niche models. Ecological Modelling, XXXX.

Atauchi, P. Joser; Peterson, A. Townsend (2023). A global dataset of Heterogeneity at high resolution. figshare. Dataset. https://doi.org/10.6084/m9.figshare.23903574.v2