Simulated biodiversity hotspots from traditional ecological knowledge and Western metrics do not always overlap

Abstract

As global change reshapes ecosystems, establishing conservation priorities is crucial for managing threatened areas with limited resources. Biodiversity hotspots, often defined by high endemism, are key in conservation management. However, these may not capture other dimensions of biodiversity, including functional and phylogenetic diversity or knowledge from Indigenous communities. Here, we demonstrate that different metrics identify different hotspots using simulated plant communities as a case study. We compiled existing data on 318 plant species, including functional trait data and Traditional Ecological Knowledge on Indigenous plant names and uses. We simulated 100,000 communities by randomly assembling species that naturally co-occur within an ecoregion, and calculated taxonomic, phylogenetic, functional, and Traditional Ecological Knowledge-based biodiversity metrics. The metrics cluster into two groups based on shared hotspot identification, with phylogenetic and functional metrics distributed between groups, and Traditional Ecological Knowledge-based metrics aligning with some metrics, but not all. This suggests that integrating Traditional Ecological Knowledge into conservation planning can expand the scope of biodiversity assessments and help recognize places of cultural significance that might otherwise be overlooked.