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Abstract
Addressing Uncertainties in Machine Learning Predictions of Conservation Status.
Extinction risk assessments are increasingly important to many stakeholders (Bennun et al. 2017) but there remain large gaps in our knowledge about the status of many species. The IUCN Red List of Threatened Species (IUCN 2019, hereafter Red List) is the most comprehensive assessment of extinction risk. However, it includes...Walker, Barnaby ; Leão, Tarciso ; Bachman, Steven ; Lucas, Eve ; Nic Lughadha, Eimear
Conservation assessment, Machine learning, Natural history collections, Uncertainty, and IUCN Red List
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Journal article
Harnessing the potential of integrated systematics for conservation of taxonomically complex, megadiverse plant groups
The value of natural history collections for conservation science research is increasingly recognized, despite their well-documented limitations in terms of taxonomic, geographic, and temporal coverage. Specimen-based analyses are particularly important for tropical plant groups for which field observations are scarce and potentially unreliable due to high levels of diversity-amplifying identification...Nic Lughadha, Eimear ; Graziele Staggemeier, Vanessa ; Vasconcelos, Thais ; Walker, Barnaby ; Canteiro, Cátia …
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Journal article
Enhancement of conservation knowledge through increased access to botanical information
Herbarium specimens are increasingly recognized as an important resource for conservation science and virtual herbaria are making specimens freely available to a wider range of users than ever before. Few virtual herbaria are designed with conservation use as a primary driver. Exceptionally, Brazil's Reflora Virtual Herbarium (RVH) was created to...Canteiro, Cátia ; Barcelos, Laísa ; Filardi, Fabiana ; Forzza, Rafaela ; Green, Laura …