The persistent multi-dimensional biases of biodiversity digital accessible knowledge of birds in China

Abstract

The taxonomic, spatial and temporal biases in digital accessible knowledge (DAK) are important considerations for macroecological research, effective biological conservation and the sustainable use of biological resources. Here, for the first time, we quantify the gaps in bird data in China and determine the effectiveness of national datasets in complementing the large authoritative data portal at the national scale in terms of taxonomic, geographical, temporal, zoogeographical and ecoregional coverage. In this study, we integrated more than 2.5 million bird occurrence records in China from three main data portals, the Global Biodiversity Information Facility (GBIF), the BirdReport (BR) and three sub-platforms containing information on bird specimens in the National Specimen Information Infrastructure (NSII) in China. The results demonstrated extremely low coverage in the taxonomic, spatial and temporal dimensions in both the GBIF dataset and the integrated dataset; moreover, the complementary effectiveness of additional datasets was quite limited. Our results emphasize the importance of research to fill the data gaps at national, regional and local scales. Effective strategies to improve the availability of DAK not only in China but also throughout the world are proposed.