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Global species richness estimates have not converged

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dc.contributor Australian Institute Of Marine Science
dc.contributor Queensland Univ Technol
dc.contributor Queensland University Of Technology (qut)
dc.contributor Sch Math Sci
dc.contributor Australian Inst Marine Sci
dc.contributor.author MENGERSEN, KERRIE
dc.contributor.author CALEY, M. JULIAN
dc.contributor.author FISHER, REBECCA
dc.date.accessioned 2014-04-01T00:52:43Z
dc.date.accessioned 2014-04-01T00:52:43Z
dc.date.accessioned 2017-03-21T01:07:44Z
dc.date.accessioned 2019-05-09T01:03:35Z
dc.date.available 2017-03-21T01:07:44Z
dc.date.available 2017-03-21T01:07:44Z
dc.date.available 2014-04-01T00:52:43Z
dc.date.available 2019-05-09T01:03:35Z
dc.date.issued 2014-04-01
dc.identifier.citation Caley MJ, Fisher R, Mengersen K (2014) Global species richness estimates have not converged. Trends in Ecology and Evolution 29(4): 187-188 en_US
dc.identifier.issn 0169-5347
dc.identifier.uri http://epubs.aims.gov.au/11068/10309
dc.description.abstract We demonstrate that after more than six decades, estimates of global species richness have failed to converge, remain highly uncertain, and in many cases, are logically inconsistent. Convergence in these estimates could be accelerated by adaptive learning methods where the estimation of uncertainty is prioritised and used to guide future research.
dc.description.uri http://www.sciencedirect.com/science/article/pii/S0169534714000263 en_US
dc.language English
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartof Null
dc.subject Global Species Richness
dc.subject Ecology
dc.subject Bayesian Analysis
dc.subject Evolutionary Biology
dc.subject Biodiversity
dc.subject Environmental Sciences & Ecology
dc.subject Genetics & Heredity
dc.subject Adaptive Learning
dc.title Global species richness estimates have not converged
dc.type journal article en_US
dc.identifier.doi 10.1016/j.tree.2014.02.002
dc.identifier.wos WOS:000335488100002


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