bioRxiv2020
Endemic species are important for biodiversity conservation. Yet, quantifying endemism remains challenging because endemism concepts can be too strict (i.e., pure endemism) or too subjective (i.e., near endemism). We propose a data-driven approach to objectively estimate the proportion of records inside a given the target area (i.e., endemism level) that optimizes the separation of near-endemics from non-endemic species. We apply this approach to the Atlantic Forest tree flora using millions of herbarium records retrieved from multiple sources. We first report an updated checklist of 5044 species for the Atlantic Forest tree flora and then we compare how species-specific endemism levels obtained from herbarium data match species-specific endemism accepted by taxonomists. We show that an endemism level of 90% separates well pure and near-endemic from non-endemic species, which in the Atlantic Forest revealed an overall endemism ratio of 45% for its tree flora. We also found that the diversity of pure and near endemics and of endemics and overall species was congruent in space. Our results for the Atlantic Forest reinforce that pure and near endemic species can be combined to quantify regional endemism and therefore to set conservation priorities taking into account endemic species distribution. We provided general guidelines on how the proposed approach can be used to assess endemism levels of regional biotas in other parts of the world.