Tracking and forecasting ecosystem interactions in real time

Evidence shows that species interactions are not constant but change as the ecosystem shifts to new states. Although controlled experiments and model investigations demonstrate how nonlinear interactions can arise in principle, empirical tools to track and predict them in nature are lacking. Here we...

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Bibliographic Details
Published inProceedings of the Royal Society. B, Biological sciences Vol. 283; no. 1822; pp. 1 - 9
Main Authors Deyle, Ethan R., May, Robert M., Munch, Stephan B., Sugihara, George
Format Journal Article
LanguageEnglish
Published THE ROYAL SOCIETY 13.01.2016
Subjects
Ecological competition
Ecosystem models
Ecosystems
Freshwater ecosystems
Jacobians
Marine ecosystems
Predators
Time series
Time series forecasting
Trophic relationships
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Summary:Evidence shows that species interactions are not constant but change as the ecosystem shifts to new states. Although controlled experiments and model investigations demonstrate how nonlinear interactions can arise in principle, empirical tools to track and predict them in nature are lacking. Here we present a practical method, using available time-series data, to measure and forecast changing interactions in real systems, and identify the underlying mechanisms. The method is illustrated with model data from a marine mesocosm experiment and limnologic field data from Sparkling Lake, WI, USA. From simple to complex, these examples demonstrate the feasibility of quantifying, predicting and understanding state-dependent, nonlinear interactions as they occur in situ and in real time—a requirement for managing resources in a nonlinear, non-equilibrium world.
ISSN:0962-8452
1471-2954