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Species richness on coral reefs and the pursuit of convergent global estimates
Fisher, R.; O'Leary, R.A.; Low-Choy, S.; Mengersen, K.; Knowlton, N.; Brainard, R.E.; Caley, M.J. (2015). Species richness on coral reefs and the pursuit of convergent global estimates. Curr. Biol. 25(4): 500-505. https://dx.doi.org/10.1016/j.cub.2014.12.022
In: Current Biology. Cell Press: London. ISSN 0960-9822; e-ISSN 1879-0445
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| Auteurs | | Top |
- Fisher, R.
- O'Leary, R.A.
- Low-Choy, S.
- Mengersen, K.
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- Knowlton, N.
- Brainard, R.E.
- Caley, M.J.
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| Abstract |
Global species richness, whether estimated by taxon, habitat, or ecosystem, is a key biodiversity metric. Yet, despite the global importance of biodiversity and increasing threats to it (e.g., [1-4]), we are no better able to estimate global species richness now than we were six decades ago [5]. Estimates of global species richness remain highly uncertain and are often logically inconsistent [5]. They are also difficult to validate because estimation of global species richness requires extrapolation beyond the number of species known [6-13]. Given that somewhere between 3% and >96% of species on Earth may remain undiscovered [4], depending on the methods used and the taxa considered, such extrapolations, especially from small percentages of known species, are likely to be highly uncertain [13, 14]. An alternative approach is to estimate all species, the known and unknown, directly. Using expert taxonomic knowledge of the species already described and named, those already discovered but not yet described and named, and those still awaiting discovery, we estimate there to be 830,000 (95% credible limits: 550,0001,330,000) multi-cellular species on coral reefs worldwide, excluding fungi. Uncertainty surrounding this estimate and its components were often strongly skewed toward larger values, indicating that many more species on coral reefs is more plausible than many fewer. The uncertainties revealed here should guide future research toward achieving convergence in global species richness estimates for coral reefs and other ecosystems via adaptive learning protocols whereby such estimates can be tested and improved, and their uncertainties reduced, as new knowledge is acquired. |
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