Aim: Biodiversity on islands is affected by various geo-physical processes and sea-level fluctuations. Oceanic islands (never connected to a landmass) are initially vacant with diversity accumulating via colonisation and speciation, followed by a decline as islands shrink. Continental islands have species upon formation (when disconnected from the mainland) and may have transient land-bridge connections. Theoretical predictions for the effects of these geo-processes on rates of colonisation, speciation and extinction have been proposed, but methods of phylogenetic inference assume only oceanic island scenarios without accounting for island ontogeny, sea-level changes or past landmass connections. Here, we analyse to what extent ignoring geodynamics affects the inference performance of a phylogenetic island model, DAISIE, when confronted with simulated data that violate its assumptions. Location: Simulation of oceanic and continental islands. Methods: We extend the DAISIE simulation model to include: area-dependent rates of colonisation and diversification associated with island ontogeny and sea-level fluctuations, and continental islands with biota present upon separation from the mainland, and shifts in rates to mimic temporary land-bridges. We quantify the error made when geo-processes are not accounted for by applying DAISIE's inference method to geodynamic simulations. Results: We find that the robustness of the model to dynamic island area is high (error is small) for oceanic islands and for continental islands that have been separated for a long time, suggesting that, for these island types, it is possible to obtain reliable results when ignoring geodynamics. However, for continental islands that have been recently or frequently connected, robustness of DAISIE is low, and inference results should not be trusted. Main conclusions: This study highlights that under a large proportion of island biogeographic geo-scenarios (oceanic islands and ancient continental fragments) a simple phylogenetic model ignoring geodynamics is empirically applicable and informative. However, recent connection to the continent cannot be ignored, requiring development of a new inference model.

Aim Biodiversity on islands is influenced by geophysical processes and sea‐level fluctuations. Oceanic islands (never connected to a landmass) are initially vacant with diversity accumulating via colonisation and speciation, and then declining as islands shrink. Continental islands have species upon disconnection from the mainland and may have transient land‐bridge connections. Theoretical predictions for the effects of these geophysical processes on rates of colonisation, speciation, and extinction have been proposed. However, paleogeographic reconstructions are currently unavailable for most islands, and phylogenetic models overlook island ontogeny, sea‐level changes, or past landmass connections. We analyse to what extent ignoring geodynamics in the inference model affects model predictions when confronted with data simulated with geodynamics. Location Simulations of oceanic and continental islands. Taxa Simulated lineages. Methods We extend the island biogeography simulation model DAISIE to include: (i) area‐dependent rates of colonisation and diversification associated with island ontogeny and sea‐level fluctuations, (ii) continental islands with biota present upon separation from the mainland, and (iii) shifts in colonisation to mimic temporary land‐bridges. We quantify the error of ignoring geodynamic processes by applying DAISIE's inference method to geodynamic simulations. Results Robustness of the model to dynamic island area is generally high for oceanic islands and for continental islands that have been separated for a long time, suggesting that it is possible to obtain reliable results when ignoring geodynamics. However, for continental islands that have been recently or frequently connected, robustness of the model is low. Main conclusions Under many island biogeographic geodynamic scenarios (oceanic islands and ancient continental fragments) a simple phylogenetic model ignoring geodynamics is empirically applicable and informative. However, recent connection to the continent cannot be ignored, requiring new model development. Our results show that for oceanic islands, reliable insights can be obtained from phylogenetic data in the absence of paleogeographic reconstructions of island area.

Understanding macroevolution on islands requires knowledge of the closest relatives of island species on the mainland. The evolutionary relationships between island and mainland species can be reconstructed using phylogenies, to which models can be fitted to understand the dynamical processes of colonisation and diversification. But how much information on the mainland is needed to gain insight into macroevolution on islands? Here we first test whether species turnover on the mainland and incomplete mainland sampling leave recognisable signatures in community phylogenetic data. We find predictable phylogenetic patterns: colonisation times become older and the perceived proportion of endemic species increases as mainland turnover and incomplete knowledge increase. We then analyse the influence of these factors on the inference performance of the island biogeography model DAISIE, a whole-island community phylogenetic model that assumes that mainland species do not diversify, and that the mainland is fully sampled in the phylogeny. We find that colonisation and diversification rate are estimated with little bias in the presence of mainland extinction and incomplete sampling. By contrast, the rate of anagenesis is overestimated under high levels of mainland extinction and incomplete sampling, because these increase the perceived level of island endemism. We conclude that community-wide phylogenetic and endemism datasets of island species carry a signature of mainland extinction and sampling. The robustness of parameter estimates suggests that island diversification and colonisation can be studied even with limited knowledge of mainland dynamics.