A Reproducible, Data-Driven Approach to Mapping Species Distributions Using Presence-Only Data and Biogeographic...

Area of Science:

• Macroecology and Biogeography
• Spatial Ecology
• Biodiversity Informatics

Background:

• Expert-derived range maps are standard in macroecological and biogeographic studies.
• These maps suffer from subjectivity, taxonomic bias, and inconsistent handling of species absences.
• Existing methods lack scalability and consistency for large-scale biodiversity assessments.

Purpose of the Study:

• To develop a reproducible, data-driven approach for estimating species' extent of occurrence (EOO).
• To create objective and scalable range maps as an alternative to expert-derived maps.
• To assess the approach's applicability across diverse taxa and spatial scales.

Main Methods:

• Utilized presence-only data and Australian subregions (Interim Biogeographic Regionalization for Australia - IBRA).
• Employed a Gaussian kernel density estimator calibrated for spatial coherence and ecological realism.
• Applied the method to Australian birds and validated against expert-derived maps, then extended to other taxa.

Main Results:

• The data-driven EOO maps showed variable concordance with expert maps, higher for terrestrial birds.
• Richness estimates varied by spatial scale, with lower errors at coarser biogeographic scales.
• The approach successfully generated EOO maps for birds, amphibians, mammals, reptiles, and vascular plants, revealing subpopulations.

Conclusions:

• The developed approach offers an objective, scalable, and consistent alternative to expert-derived range maps.
• It minimizes sampling bias and internal discontinuities in EOO estimation.
• The adaptable method supports large-scale ecological research and biodiversity conservation efforts.