Measuring and modeling ecological rates with neutral theory
The pace of change in ecological communities is central to classic and emerging problems in paleobiology and ecology. Yet measuring rates of change in community composition is problematic: when measured as ecological distance divided by time, rates appear faster when measured over shorter time intervals, preventing straightforward interpretation of rates when timescales vary. Similar problems arise when richness or sample size varies. We develop an approach that mitigates these issues using Hubbells neutral theory, a model in which species abundances change through stochastic births and deaths in a community with a fixed number of individuals J. Change in community composition is faster for smaller J, so 1/J provides a process-based rate metric that can be estimated from empirical time-series. We derive the likelihood for changes in community composition under neutral theory. Our approach accurately estimates rates in simulated data even when timescale, richness, and sample size vary. We use Quaternary pollen assemblage timeseries to demonstrate the power of this method for comparing rates between sites and through time and testing for rate shifts. Our approach can be flexibly adapted to test hypotheses on the causes of ecological change, including tests of coordinated stasis, neutral theory, and the timing of anthropogenic change.