Ecological forecasts reveal limitations of common model selection methods: predicting changes in beaver colony densities.

ABSTRACT: Over the past two decades, there have been numerous calls to make ecology a more predictive science through direct empirical assessments of ecological models and predictions. While the widespread use of model selection using information criteria has pushed ecology toward placing a higher emphasis on prediction, few attempts have been made to validate the ability of information criteria to correctly identify the most parsimonious model with the greatest predictive accuracy. Here, we used an ecological forecasting framework to test the ability of information criteria to accurately predict the relative contribution of density dependence and density-independent factors (forage availability, harvest, weather, wolf [Canis lupus] density) on inter-annual fluctuations in beaver (Castor canadensis)

SUBMITTER: Johnson-Bice SM 

PROVIDER: S-EPMC7816246 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature