Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data.

ABSTRACT: Accurate predictions of species abundance remain one of the most vexing challenges in ecology. This observation is perhaps unsurprising, because population dynamics are often strongly forced and highly nonlinear. Recently, however, numerous statistical techniques have been proposed for fitting highly parameterized mechanistic models to complex time series, potentially providing the machinery necessary for generating useful predictions. Alternatively, there is a wide variety of comparatively simple model-free forecasting methods that could be used to predict abundance. Here we pose a rather conservative challenge and ask whether a correctly specified mechanistic model, fit with commonly used statistical techniques, can provide better forecasts than simple model-free methods for ecological s

SUBMITTER: Perretti CT 

PROVIDER: S-EPMC3612644 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature