Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series

Jake M. Ferguson, José M. Ponciano

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series.

Original languageEnglish
Pages (from-to)251-259
Number of pages9
JournalEcology Letters
Volume17
Issue number2
DOIs
StatePublished - Feb 2014

Keywords

  • Autocorrelation
  • Community effects
  • Extinction
  • First passage time
  • Moving-average model
  • PVA
  • Time series

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics

Fingerprint

Dive into the research topics of 'Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series'. Together they form a unique fingerprint.

Cite this