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Computational convenience has led to widespread use of Bayesian inferencewith vague or flat priors to analyze state-space models in ecology. Vaguepriors are claimed to be objective and to let the data speak. Neither of theseclaims is valid. Statisticians have criticized the use of vague priors fromphilosophical to computational to pragmatic reasons. Ecologists, however,dismiss such criticisms as empty philosophical wonderings with no practicalimplications. We illustrate that use of vague priors in population viabilityanalysis and occupancy models can have significant impact on the analysis andcan lead to strikingly different managerial decisions. Given the wide spreadapplicability of the hierarchical models and uncritical use of non-informativeBayesian analysis in ecology, researchers should be cautious about using thevague priors as a default choice in practical situations.

Is non-informative Bayesian analysis appropriate for wildlife management: survival of San Joaquin Kit Fox and declines in amphibian populations