Testing relationships between multiple regional features and biogeographic processes of speciation, extinction, and dispersal

The spatial and environmental features of regions where clades are
evolving are expected to impact biogeographic processes such as
speciation, extinction, and dispersal. Any number of regional features
(such as altitude, distance, area, etc.) may be directly or indirectly
related to these processes. For example, it may be that distances or
differences in altitude or both may limit dispersal rates. However, it is
difficult to disentangle which features are most strongly related to rates
of different processes. Here, we present an extensible Multi-feature
Feature-Informed GeoSSE (MultiFIG) model that allows for the simultaneous
investigation of any number of regional features. MultiFIG provides a
conceptual framework for incorporating large numbers of features of
different types, including categorical, quantitative, within-region, and
between-region features, along with a mathematical framework for
translating those features into biogeographic rates for statistical
hypothesis testing. Using traditional Bayesian parameter estimation and
reversible-jump Markov chain Monte Carlo, MultiFIG allows for the
exploration of models with different numbers and combinations of
feature-effect parameters, and generates estimates for the strengths of
relationships between each regional feature and core process. We validate
this model with a simulation study covering a range of scenarios with
different numbers of regions, tree sizes, and feature values. We also
demonstrate the application of MultiFIG with an empirical case study of
the South American lizard genus Liolaemus, investigating sixteen regional
features related to area, distance, and altitude. Our results show two
important feature-process relationships: a negative distance/dispersal
relationship, and a negative area/extinction relationship. Interestingly,
although speciation rates were found to be higher in Andean versus
non-Andean regions, the model did not assign significance to Andean- or
altitude-related parameters. These results highlight the need to consider
multiple regional features in biogeographic hypothesis testing.