Multidimensional biases, gaps and uncertainties in global plant occurrence information

Plants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Glaring biases, gaps, and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations have never been assessed globally. In this synthesis, we propose a conceptual framework for analyzing information biases, gaps and uncertainties along taxonomic, geographical, and temporal dimensions and apply it to all c. 370,000 species of land plants. To this end, we integrated 120 million point-occurrence records with independent databases on plant taxonomy, distributions, and conservation status. We find that different data limitations are prevalent in each dimension. Different information metrics are largely uncorrelated, and filtering out specific limitations would usually lead to extreme trade-offs for other information metrics. In light of these multidimensional data limitations, we critically discuss prospects for global plant ecological and biogeographical research, monitoring and conservation, and outline critical next steps towards more effective information usage and mobilization. We provide an empirical baseline for evaluating and improving global floristic knowledge and our conceptual framework can be applied to the study of other hyperdiverse clades.