Limitations in global information on species occurrences

Abstract

Detailed information on species distributions is crucial for answering central questions in biogeography, ecology, evolutionary biology and conservation. Millions of species occurrence records have been mobilized via international data-sharing networks, but inherent biases, gaps and uncertainties hamper broader application. In my PhD thesis, I presented the first comprehensive analyses of global patterns and drivers of these limitations across different taxonomic groups and spatial scales. Integrating 300 million occurrence records for terrestrial vertebrates and plants with comprehensive taxonomic databases, expert range maps and regional checklists, I demonstrated extensive taxonomic, geographical and temporal biases, gaps and uncertainties. I identified key socio-economic drivers of data bias across different taxonomic groups and spatial scales. The results of my dissertation provide an empirical baseline for effectively accounting for data limitations in distribution models, as well as for prioritizing and monitoring efforts to collate additional occurrence information.