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Open Access Research article

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

Alicia M Ellis1 and Eric Post2*

Author affiliations

1 Department of Biological Science, Dartmouth College, Hanover, NH 03755 USA

2 Department of Biology, The Pennsylvania State University, 208 Mueller Lab, University Park, PA 16803 USA

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Citation and License

BMC Ecology 2004, 4:2  doi:10.1186/1472-6785-4-2

Published: 31 March 2004



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.


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.


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.