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Research in the biological sciences is hampered by the Linnean shortfall, which describes the number of hidden species that are suspected of existing without formal species description. Using machine learning and species delimitation methods, we built a predictive model that incorporates some 5.0 × 10 5 data points for 117 species traits, 3.3 × 10 6 occurrence records, and 9.1 × 10 5 gene sequences from 4,310 recognized species of mammals. Delimitation results suggest that there are hundreds of undescribed species in class Mammalia. Predictive modeling indicates that most of these hidden species will be found in small-bodied taxa with large ranges characterized by high variability in temperature and precipitation. As demonstrated by a quantitative analysis of the literature, such taxa have long been the focus of taxonomic research. This analysis supports taxonomic hypotheses regarding where undescribed diversity is likely to be found and highlights the need for investment in taxonomic research to overcome the Linnean shortfall.
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Biological knowledge shortfalls impede conservation efforts in poorly studied taxa—A case study of Laboulbeniomycetes
Abstract Most empirical research on biological shortfalls has focused on vertebrate taxa. This is important given many species in poorly studied groups such as invertebrates, plants, and fungi are predicted to possess high conservation risk. Here, we focus on Laboulbeniomycetes: a class of microfungi that are understudied. We examined four shortfalls: Linnean (knowledge gaps in species diversity), Wallacean (knowledge gaps in distributions), Latimerian (knowledge gaps in species persistence), and the newly introduced Scottian (knowledge gaps in species conservation assessments) shortfalls. The Linnean shortfall in Laboulbeniomycetes is hard to predict due to inconsistent species description rates. Analysis of distribution patterns indicates Laboulbeniomycetes are likely to experience an extremely high Wallacean shortfall, with many species having highly disjunct known distributions. Latimerian shortfall analysis shows over half (51%) of Laboulbeniomycetes have not been recorded in >50 years, while the group has a collective Scottian shortfall of 100%, given none of the 2454 described species have received an IUCN threat assessment. We suggest continued study of natural history collections, expanded citizen science programmes, and machine‐learning identification approaches as important tools for reducing knowledge shortfalls in both Laboulbeniomycetes and poorly studied taxa more generally.
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- PAR ID:
- 10480740
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Biogeography
- Volume:
- 51
- Issue:
- 1
- ISSN:
- 0305-0270
- Format(s):
- Medium: X Size: p. 29-39
- Size(s):
- p. 29-39
- Sponsoring Org:
- National Science Foundation
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