Open-Source tools in R for forestry and forest ecology
| Authors: | Jeff W. Atkins, Atticus E.L. Stovall, Carlos Alberto Silva |
| Year: | 2022 |
| Type: | Scientific Journal |
| Station: | Southern Research Station |
| DOI: | https://doi.org/10.1016/j.foreco.2021.119813 |
| Source: | Forest Ecology and Management |
Abstract
Forestry and forest ecology research potentially lags behind related fields such as ecology, biodiversity, and conservation research in the employment of open-source software solutions, specifically the R programming language. A direct comparison of the last decade of published research literature from the top 20 ecology and forestry journals shows that R is utilized in over 30% of the literature for ecology, yet in less than 10% of the forestry literature. Open-source computing environments, such as R, Python, and Julia, increase the visibility and reproducibility of scientific research and foster collaborations through the removal of proprietary software restrictions. The lag in adoption of open-source software in forestry and forest ecology could be hindering collaboration, data sharing, and reproducibility. Here we survey the available packages in the R programming language with specific utility for forest-related research. We found more than 100 available packages which we systematically categorized by research category: community analysis; dendrochronology; forest mensuration and inventory; hydrology; informatics/IoT; modeling; phenology; and remote sensing. We present worked examples for a subgroup of R software packages for each category to demonstrate their potential and utility. In these examples we used open-source data sets of our own selection. Additionally, we collected this information into an R metapackage, ForestAnalysisInR, an R Shiny-based solution that allows users to query the R packages we have identified to find those best suited for their analysis needs in a quick and efficient way.