A Web-Based Software Platform for Restoration-Oriented Species Selection Based on Plant Functional Traits - Wang, Chen; Jian, Shuguang; Ren, Hai; Yan, Junhua; Liu, Nan (Frontiers in Ecology and Evolution, 2021)
Plant functional traits are fundamental to the understanding of plant adaptations and distributions. Recently, scientists proposed a trait-based species selection theory to support the selection of suitable plant species to restore the degraded ecosystems, to prevent the invasive exotic species and to manage the sustainable ecosystems. Based on this theory, in a previous study, we developed a species screening model and successfully applied it to a project where plant species were selected for restoring a tropical coral island. However, during this process we learned that a software platform is necessary to automate the selection process because it can flexible to assist users. Here, we developed a generalized software platform called the “Restoration Plant Species Selection (RPSS) Platform.” This flexible software is designed to assist users in selecting plant species for particular purposes (e.g., restore the degraded ecosystems and others). It is written in R language and integrated with external R packages, including the packages that computing similarity indexes, providing graphic outputs, and offering web functions. The software has a web-based graphical user interface that allows users to execute required functions via checkboxes and buttons. The platform has cross-platform functionality, which means that it can run on all common operating systems (e.g., Windows, Linux, macOS, and others). We also illustrate a successful case study in which the software platform was used to select suitable plant species for restoration purpose. The objective of this paper is to introduce the newly developed software platform RPSS and to provide useful guidances on using it for various applications. At this step, we also realized that the software platform should be constantly updated (e.g., add new features) in the future. Based on the existing successful application and the possible updates, we believe that our RPSS software platform will have broader applications in the future.