Known knowns and unknowns in biology |
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Authors: | Hugh D. Loxdale Belinda J. Davis Robert A. Davis |
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Affiliation: | 1. School of Biosciences, Cardiff University, Cardiff, UK;2. School of Plant Biology, University of Western Australia, Crawley, Western Australia, Australia;3. Botanic Gardens and Parks Authority, West Perth, Western Australia, Australia;4. School of Natural Sciences, Edith Cowan University, Joondalup, Western Australia, Australia;5. School of Animal Biology, University of Western Australia, Crawley, Western Australia, Australia |
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Abstract: | Here we present a knowledge‐data framework based on the politico‐military statement by Donald Rumsfeld (below) which has, we believe, direct relevance to ecological conservation. Ecological examples of four of the identified categories are provided with discussion of the conservation risks to a species through knowledge or data loss and movement through the categories. We show that so‐called known knowns in terms of global biodiversity are not as accurately known as thought, despite 500 years or more of world‐wide collecting and recording of eukaryotic species. In addition, as fast as new species, living or fossil, are discovered (unknown unknowns), some of which have revolutionised concepts about the biology of particular taxa, meanwhile, sadly other living species are being extirpated, or are assumed to be so (unknown knowns). These often have a high probability of ultimately being rediscovered, especially if small and/or living in remote, under‐sampled regions. Furthermore, we suggest that in some cases it may be possible to predict the existence of known species in new habitats, or the existence of unknown co‐evolved animal species (known unknowns). We discuss how technological advances (e.g. molecular markers and DNA sequencing) are inflating current estimates of biodiversity by identifying the existence of cryptic species. We believe the knowledge‐data matrix provides another tool for conservation practitioners to focus data collection on bridging knowledge gaps for more effective conservation outcomes. |
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Keywords: | biodiversity ecosystems extant species extinction geographical range predicting species species decline species richness |
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