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Nicholas J. Matzke

Researcher at University of Auckland

Publications -  77
Citations -  10329

Nicholas J. Matzke is an academic researcher from University of Auckland. The author has contributed to research in topics: Biological dispersal & Biogeography. The author has an hindex of 29, co-authored 74 publications receiving 8349 citations. Previous affiliations of Nicholas J. Matzke include University of California, Davis & University of Tennessee.

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Has the Earth’s sixth mass extinction already arrived?

TL;DR: Differences between fossil and modern data and the addition of recently available palaeontological information influence understanding of the current extinction crisis, and results confirm that current extinction rates are higher than would be expected from the fossil record.
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Model Selection in Historical Biogeography Reveals that Founder-Event Speciation Is a Crucial Process in Island Clades

TL;DR: The re-implementing of the Dispersal-Extinction-Cladogenesis model of LAGRANGE is modified to create a new model, DEC + J, which adds founder-event speciation, the importance of which is governed by a new free parameter, and the results indicate that the assumptions of historical biogeography models can have large impacts on inference and require testing and comparison with statistical methods.
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Probabilistic historical biogeography: new models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing

TL;DR: This work uses BioGeoBEARS on a large sample of island and non-island clades to show that founder-event speciation is a crucial process in almost every clade, and that most published datasets reject the non-J models currently in widespread use.
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Bayesian Analysis of Biogeography when the Number of Areas is Large

TL;DR: A Bayesian approach for inferring biogeographic history that extends the application of biogeographical models to the analysis of more realistic problems that involve a large number of areas, and develops this approach in a Bayesian framework, marginalizing over all possible biogeography histories using Markov chain Monte Carlo.