EIA 2006 |
Society for Environmental Information Sciences
Environmental Informatics Archives
ISSN 1811-0231 /
ISEIS Publication Series Number P002
2006 ISEIS. All
Paper EIA06-005, Volume 4
(2006), Pages 56-66
Nonlinear Dynamics Detection in Ecological Systems
J. H. Dontje*
Sustainability and Environmental Studies Program, Berea College, Berea, KY 40404. *Corresponding author: email@example.com.
While the fact that ecological systems often exhibit nonlinear dynamics is well-established, discrimination of those dynamics in data is can be obscured by limited data, variable conditions (nonstationarity), and measurement noise. In this study, a four-compartment nutrient web model that demonstrates non-linear dynamics was used to test a deterministic versus stochastic (DVS) algorithm that has been shown to discriminate between true nonlinear dynamics and dynamics produced solely by stochastic processes. Focusing on situations typical to ecological data sets -- limited data record and driving forces that are cyclical but variable in the short and long-term (e.g. solar radiation that varies daily due to atmospheric conditions but also across seasons) -- the limits of the DVS algorithm were explored. The DVS algorithm demonstrated potential to detect nonlinear dynamics in short (N=450) time series and the ability to accommodate seasonal-type variations.
Keywords: ecological models, nutrient, web models, nonlinear, nonlinear forecasting, nonlinear detection, nonlinear time series, dynamic noise
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