2014/03/29 by William D. Pearse, Andy Purvis, Pearse, William D. +5
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Environmental Science · #Ecology and Vegetation Dynamics Studies #FOS: Biological sciences #Plant and animal studies #Populations and Evolution (q-bio.PE) #Quantitative Methods (q-bio.QM) #Species Distribution and Climate Change #q-bio.PE #q-bio.QM
paper · pdf · doi:10.48550/arxiv.1403.7668
arxiv created 2014/03/29 · openalex publication_date 2014/03/29 · arxiv updated 2014/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.