Modelling ecological communities as if they were DNA

TL;DR

This paper introduces a novel method inspired by DNA substitution models to estimate historical interactions and turnover rates in ecological communities, addressing computational challenges in modeling community changes over time.

Contribution

It presents a new approach for modeling ecological community dynamics based on DNA substitution models, with implementation and real data application.

Findings

Method can detect signals in real butterfly community data

Simulation shows limitations of the approach

Open source code available for implementation

Abstract

Ecologists are interested in understanding and predicting how ecological communities change through time. While it might seem natural to measure this through changes in species' abundances, computational limitations mean transitions between community types are often modelled instead. We present an approach inspired by DNA substitution models that attempts to estimate historic interactions between species, and thus estimate turnover rates in ecological communities. Although our simulations show that the method has some limitations, our application to butterfly community data shows the method can detect signal in real data. Open source C++ code implementing the method is available at http://www.github.com/willpearse/lotto.