Masting, mixtures, and modes: are two models better than one?

19 February 2014

Tanentzap, Andrew; Lee, William; Coomes, David; Mason, Norman

A key hypothesis in population ecology is that synchronous and intermittent seed production, known as mast seeding, is driven by the alternating allocation of carbohydrates and mineral nutrients between growth and reproduction in different years, i.e. 'resource switching'. Such behaviour may ultimately generate bimodal distributions of long-term flower and seed production, and evidence of these patterns has been taken to support the resource switching hypothesis. Here, we show how a widely-used statistical test of bimodality applied by many studies in different ecological contexts may fail to reject the null hypothesis that focal probability distributions are unimodal. Using data from five tussock grass species in South Island, New Zealand, we find clear evidence of bimodality only when flowering patterns are analyzed with probabilistic mixture models. Mixture models provide a theory oriented framework for testing hypotheses of mast seeding patterns, enabling the different responses underlying medium- and high- versus non- and low-flowering years to be modelled more realistically by associating these with distinct probability distributions. Coupling theoretical expectations with more rigorous statistical approaches will empower ecologists to reject null hypotheses more often.