Statistical significance and biological relevance: A call for a more cautious interpretation of results in ecology

Unfortunately it is quite common to find papers in ecology journals in which the authors confound statistical significance with biological relevance or with strength of evidence against the null hypothesis. These mistakes are not trivial semantic problems because they may finally lead to wrong scientific conclusions, and hence to prevent long-term knowledge accumulation in ecology. Using correlation analysis as an example I present the four possible interactions that can take place between biological relevance (based on the value of the correlation coefficient as an effect size metric) and statistical significance (based on p-values). Importantly, I recall that the strength of evidence that supports the parameter estimate or the null hypothesis, given our data, can only be assessed by means of Bayesʹ rule.