The Global Biodiversity Information Facility (GBIF) provides copious species occurrence records, and our submission harnesses these data to generate high-quality models that estimate a species’ niche requirements and suitable geographic areas. Although highly useful for pressing environmental issues, such models suffer from major obstacles, such as ameliorating sampling bias and identifying optimal model complexity.

With collaborators, we recently authored two R packages (spThin and ENMeval) that automate solutions to these obstacles. For this second-round submission, we used the R package shiny to create an updated version of “Wallace: An R-based Modular Web App to Harness Biodiversity Data for Spatial Modeling,” which integrates these packages with GBIF data via a Graphical User Interface (GUI).

We have made major improvements regarding: future expandability, guidance for the user, the user interface, new functions, and documentation and reproducibility.

Researchers can download and map GBIF occurrence data, remove questionable and clustered records, access climatic variables, build and evaluate BIOCLIM and Maxent models, visualize predictions, save results, and download a file that provides R code to reproduce the analyses.

Wallace, beta version 0.2 is organized as modules that facilitate future expansion and can be run online or locally (PC/Mac). It maintains clear linkages to specific R packages, hopefully enticing the future addition of more functionalities (e.g. databases/variables, data-cleaning, and modeling algorithms).

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