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Environmental Informatics Archives

ISSN 1811-0231 / ISEIS Publication Series Number P002

Copyright © 2006 ISEIS. All rights reserved.



  Paper EIA06-005, Volume 4 (2006), Pages 56-66 = complimentary

Nonlinear Dynamics Detection in Ecological Systems

J. H. Dontje*

Sustainability and Environmental Studies Program, Berea College, Berea, KY 40404. *Corresponding author: james_dontje@berea.edu.



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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