Re-evaluating the general dynamic theory of oceanic island biogeography

The general dynamic model of oceanic island biogeography integrates temporal changes in ecological circumstances with diversification processes, and has stimulated current research in island biogeography. In the original publication, a set of testable hypotheses was analysed using regression models: specifically, whether island data for four diversity indices are consistent with the ‘B~ATT2’ model, in which B is a diversity index, A is log(area) and T is time. The four indices were species richness, the number and percentage of single‐island endemic species, and a diversification index. Whether the relationships between these indices and time are unimodal (i.e., ‘hump‐shaped’) was a key focus, based on the characteristic ontogeny of a volcanic oceanic island. However, the significance testing unintentionally used zero, rather than the mean of the diversity index, as the null hypothesis, greatly inflating F‐ values and reducing P‐values compared with the standard regression approach. Here we first re‐analyze the data used to evaluate the general dynamic model in the seminal paper, using the standard null hypothesis, to provide an important qualification of its empirical results. This supports the significance of about half the original tests, the rest becoming non‐significant but mostly suggestive of the hypothesized relationship. Then we expand the original analysis by testing additional, theoretically derived functional relationships between the diversity indices, island area and time, within the framework of the ATT2 model and using a mixed‐effects modelling approach. This shows that species richness peaks earlier in island life‐cycles than endemism. Area has a greater effect on species richness and the number of single‐island endemics than on the proportion of single‐island endemics and the diversification index, and was always better fit as a log–log relationship than as a semi‐log one. Finally, the richness–time relationship is positively skewed, the initial rise happening much more quickly than the later decline