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Ecol Lett. 2016 Aug;19(8):992-1006. doi: 10.1111/ele.12624. Epub 2016 Jun 2.

Multidimensional biases, gaps and uncertainties in global plant occurrence information.

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Biodiversity, Macroecology and Conservation Biogeography Group, Faculty of Forest Sciences, University of Göttingen, Büsgenweg 1, 37077, Göttingen, Germany.
Synthesis Centre (sDiv), German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany.


Plants are a hyperdiverse clade that plays a key role in maintaining ecological and evolutionary processes as well as human livelihoods. Biases, gaps and uncertainties in plant occurrence information remain a central problem in ecology and conservation, but these limitations remain largely unassessed globally. In this synthesis, we propose a conceptual framework for analysing gaps in information coverage, information uncertainties and biases in these metrics 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 metrics of information coverage and uncertainty are largely uncorrelated, and reducing taxonomic, spatial or temporal uncertainty by filtering out records would usually come at great costs to coverage. In light of these multidimensional data limitations, we discuss prospects for global plant ecological and biogeographical research, monitoring and conservation and outline critical next steps towards more effective information usage and mobilisation. Our study provides an empirical baseline for evaluating and improving global floristic knowledge, along with a conceptual framework that can be applied to study other hyperdiverse clades.


Data bias; Global Biodiversity Information Facility; Global Strategy for Plant Conservation; Wallacean shortfall; data deficiency; data uncertainty; herbarium specimens; knowledge gaps; species distributions; survey effort

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