Severe gaps and biases in digital accessible information (DAI) of species distributions hamper prospects of safeguarding biodiversity and ecosystem services and reliably addressing central questions in ecology and evolution. Accordingly, governments have agreed on improving and sharing biodiversity knowledge by 2020 (United Nations Convention on Biological Diversity’s Aichi target 19). To achieve this target, gaps in DAI must be identified, and actions prioritized to address their root causes. We take terrestrial vertebrates, an iconic and comparatively well-studied group, as a model and present the first globally comprehensive assessment of patterns and drivers of gaps in DAI, based on an integration of 157 million validated point records with 21,170 expert-based distribution maps. We demonstrate that outside a few well-sampled regions, DAI provides a very limited and spatially highly biased inventory of actual biodiversity. Coarser spatial grains result in more complete inventories, but provide insufficient detail for conservation and resource management. Surprisingly, large emerging economies are particularly under-represented in global DAI, even more so than species-rich, developing countries in the tropics. Multi-model inference reveals that completeness is mainly limited by distance to researchers, locally available research funding, and political participation in data-sharing networks, rather than transportation infrastructure, or size and funding of Western data contributors as often assumed. Our study provides an empirical baseline to advance strategies of enhancing the global information basis of biodiversity. In particular, our results highlight the need for targeted data integration from non-Western data holders and intensified cooperation to more effectively address societal biodiversity information needs.

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.

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. AbstractPlants 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.PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1326v2 | CC-BY 4.0 Open Access |

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. AbstractPlants 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.PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1326v2 | CC-BY 4.0 Open Access |

Severe gaps and biases in digital accessible information (DAI) of species distributions hamper prospects of safeguarding biodiversity and ecosystem services and reliably addressing central questions in ecology and evolution. Accordingly, governments have agreed on improving and sharing biodiversity knowledge by 2020 (United Nations Convention on Biological Diversity’s Aichi target 19). To achieve this target, gaps in DAI must be identified, and actions prioritized to address their root causes. We take terrestrial vertebrates, an iconic and comparatively well-studied group, as a model and present the first globally comprehensive assessment of patterns and drivers of gaps in DAI, based on an integration of 157 million validated point records with 21,170 expert-based distribution maps. We demonstrate that outside a few well-sampled regions, DAI provides a very limited and spatially highly biased inventory of actual biodiversity. Coarser spatial grains result in more complete inventories, but provide insufficient detail for conservation and resource management. Surprisingly, large emerging economies are particularly under-represented in global DAI, even more so than species-rich, developing countries in the tropics. Multi-model inference reveals that completeness is mainly limited by distance to researchers, locally available research funding, and political participation in data-sharing networks, rather than transportation infrastructure, or size and funding of Western data contributors as often assumed. Our study provides an empirical baseline to advance strategies of enhancing the global information basis of biodiversity. In particular, our results highlight the need for targeted data integration from non-Western data holders and intensified cooperation to more effectively address societal biodiversity information needs.