Analysis of biodiversity data suggests that mammal species are hidden in predictable places.

Abstract

SignificanceOnly an estimated 1 to 10% of Earth's species have been formally described. This discrepancy between the number of species with a formal taxonomic description and actual number of species (i.e., the Linnean shortfall) hampers research across the biological sciences. To explore whether the Linnean shortfall results from poor taxonomic practice or not enough taxonomic effort, we applied machine-learning techniques to build a predictive model to identify named species that are likely to contain hidden diversity. Results indicate that small-bodied species with large, climatically variable ranges are most likely to contain hidden species. These attributes generally match those identified in the taxonomic literature, indicating that the Linnean shortfall is caused by societal underinvestment in taxonomy rather than poor taxonomic practice.