Oikos kindly featured our latest paper. See below!
Bimodality – the characteristic of a continuous variable having two distinct modes – is of widespread interest in data analysis. This is because, in some cases, we can use the presence or absence of bimodality to infer something about the underlying processes generating the distribution of a variable that we are interested in studying. In ecology, tests of bimodality have been used in many different contexts, such as to understand body size distributions, functional traits, and transitions among different ecosystem states. But a lack of evidence for bimodality has been reported in many studies. Our paper “Masting, mixtures and modes: are two models better than one?”, now shows that a widely-used statistical test of bimodality can fail to reject the null hypothesis that focal probability distributions are unimodal. We instead promote the use of mixture models as a theory oriented framework for testing hypotheses of bimodality.
Our interest in…
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