Behavioral ecologists and other evolutionary biologists seek to explain the origin and maintenance of phenotypes, and a substantial portion of this research is accomplished by thorough study of individual species. Thus progress in evolutionary biology depends in large part on drawing appropriate inferences in studies of individual species. However, obstacles to sound inferences may be common. I present here a case study of such obstacles to progress in evolutionary biology. I located all published papers examining plumage color and variables related to sexual selection hypotheses in a well-studied European songbird, the blue tit (Cyanistes caeruleus). Researchers have estimated over 1200 statistical relationships with plumage color of blue tits in 53 studies.
Results/Conclusions
More than 400 relationships eligible for inclusion in this meta-analysis were reported without details of strength and direction, and apparently many others remain unpublished. These hidden results appear to be a biased sample, especially for comparisons of plumage color to age and individual quality. Further, type I error was elevated by the large number of statistical comparisons, the frequent use of iterative model building, and a willingness to interpret a wide variety of results as support for a hypothesis. Type I errors were made more problematic because blue tit plumage researchers only rarely attempted to replicate important findings. Last, researchers often developed ad hoc explanations for unexpected results. Revising hypotheses in light of data is appropriate, but these revised hypotheses were rarely tested with new data. The only robust biological conclusion supported by my analyses is the relatively trivial observation that male blue tits have more colorful plumage patches than do females. Various other effects, including condition-dependence of plumage color expression, remain uncertain. These obstacles to progress in the blue tit plumage literature are likely common in behavioral ecology and beyond, and so I recommend changes which may improve progress towards scientific understanding.