title: Global species richness estimates have not converged.
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.
authors.affiliation: Australian Institute of Marine Science, PMB 3, Townsville MC, Queensland, Australia. Electronic address: j.caley@aims.gov.au.
authors.forename: M Julian
authors.initials: MJ
authors.lastname: Caley
authors.affiliation: Australian Institute of Marine Science, PMB 3, Townsville MC, Queensland, Australia.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Fisher
authors.affiliation: School of Mathematical Sciences, Queensland University of Technology, GPO Box 2434, Brisbane, Qld 4001, Australia.
authors.forename: Kerrie
authors.initials: K
authors.lastname: Mengersen
mesh_terms: D001499:Bayes Theorem; D044822:Biodiversity; D008954:Models, Biological; D035501:Uncertainty
keywords: Bayesian analysis; adaptive learning; biodiversity; global species richness