Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling
Journal
Proceedings of the National Academy of Sciences of the United States of America
Journal Volume
112
Journal Issue
13
Pages
E1569-E1576
Date Issued
2015
Author(s)
Abstract
It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner-recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts.
Subjects
Ecosystem forecasting; Empirical dynamic modeling; Fisheries ecology; Nonlinear dynamics; Physical-biological interactions
SDGs
Other Subjects
Article; Canada; Colombia; controlled study; dynamics; ecosystem; empirical dynamic modeling; environmental factor; fishery; forecasting; nonbiological model; nonhuman; nonlinear system; Oncorhynchus; Oncorhynchus nerka; priority journal; river; spawning; time series analysis; animal; ecosystem; environmental monitoring; female; fishery; population dynamics; salmonine; sea; species difference; theoretical model; Oncorhynchus nerka; Animals; British Columbia; Ecosystem; Environmental Monitoring; Female; Fisheries; Models, Theoretical; Nonlinear Dynamics; Oceans and Seas; Population Dynamics; Rivers; Salmon; Species Specificity
Type
journal article