Population response to climate change: Linear vs. non-linear modeling approaches

Alicia M. Ellis, Eric Post

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Background: Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. Results: The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Conclusions: Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

Original languageEnglish (US)
Article number2
JournalBMC Ecology
StatePublished - Mar 31 2004

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • General Environmental Science


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