Determining the minimal background area for species distribution models: MinBAR package

• Published in: Ecological modelling Vol. 439; p. 109353
• Main Authors: Rotllan-Puig, Xavier, Traveset, Anna
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2021
• Subjects: Background area; Calibration area; Ecological niche model; MaxEnt; Species distribution model; Calibration area; Background area; Species distribution model; Ecological niche model; MaxEnt
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2020.109353

•The background area is key to fit reliable only-presence Species Distribution Models.•A fraction of the species distribution characterises its conditions to survive.•Fitting SDMs with part of the distribution often perform better than with the whole.•MinBAR calculates the minimum background area to fit good only-presence SDMs. One of the crucial choices when modelling species distributions using pseudo-absences and background approaches is the delineation of the background area to fit the model. We hypothesise that there is a minimum background area around the geographical centre of the species distribution that characterises well enough the range of environmental conditions needed by the species to survive. Thus, fitting the model within this geographical area should be the optimal solution in terms of both quality of the model and execution time. MinBAR is an R package that calculates the optimal background area by means of sequentially fitting several concentric species distribution models (SDMs) until a satisfactory model in terms of the included metrics is reached. The version 1.1.2 is implemented for MaxEnt (using either maxnet or the original java program) and uses Boyce Index as a metric to assess models performance. Three case studies are presented to test the hypothesis and assess package's functionality. We show how partial models trained with part of the species distribution often perform equal or better than those fitted on the entire extent. MinBAR is a versatile tool that helps modellers to objectively define the optimal solution.