Understanding the adequacy and representativeness of species distribution data

Species occurrence data is the fundamental unit of any species distribution analysis, biodiversity patterns, species extinction vulnerability, and temporal trends. This data is also a critical component of monitoring progress towards global biodiversity targets, such as those included in the Kunming-Montreal Global Biodiversity Framework (GBF) of the Convention on Biological Diversity (CBD). Recent years have seen massive growth and digitisation of global species occurrence datasets, yet the headline indicators of the GBF’s monitoring framework relies on the IUCN RedList index as the species conservation indicator. This paper explores the largest global species distribution databases, and outlines some of the remaining challenges to bringing these data together for enhanced decision making. Countries such as Japan and South Korea have seen dramatic expansions of data coverage, whilst North Africa, Central Asia, and the High Seas have not witnessed comparable growth. In the oceans, expanding geographic coverage partially comes from tracking data from a small number of species. In terms of environmental space, other types of sampling effort are disproportionately concentrated on the temperate continental shelf and slope areas of the north Atlantic. Most of the world's most biodiverse areas, especially in the Tropics, both on land and in the ocean still lack data, and concerted efforts will be needed to improve the coverage of these regions. Furthermore, few long-term monitoring programs exist, and accurately inferring change from small numbers of unstandardised collecting events resulting in a large quantity of uncurated data is challenging. Among other measures, journals should request standardised data be added to the key repositories to address biodiversity data gaps and barriers to usability. Governments should also support the sharing of species occurrence data through standardised data infrastructure, such as GBIF and OBIS, and also ensure support for data curation and quality control to minimize impacts of species misidentification records.