An automated approach for systematic detection of Key Biodiversity Areas

Abstract

The new Key Biodiversity Areas (KBA) standard is an important method for identifying regions of the planet hosting unique biodiversity. KBAs are identified through the implementation of threshold-based criteria that can be applied to any target species and region. Efficient methods to rapidly assess the existence of potential KBAs in different areas of the planet are still missing, although they are needed to accelerate the KBA identification process for large numbers of species globally. We developed a methodology to scan geographical regions and detect potential KBAs under multiple criteria. We tested the methodology on 59 species of reptiles and amphibians in Italy through the application of selected KBA criteria. Potential KBAs were identified for multiple species under most criteria, covering 1.4% to 12% of the study area, depending on analytical settings. Unit size used to identify KBAs played an important role in shaping the distribution of potential KBAs, also affecting the degree of overlap between areas triggered by different criteria. New potential KBAs identified in this study are only partially nested within current KBAs in Italy (previously identified for birds) and within the national protected areas.