I am a computational biologist - I address longstanding biological questions by developing new techniques. Currently my research follows two complementary strands:
with Matt Pennell, Amy Zanne, Peter Stevens, Dave Tank and Will Cornwell
Journal of Ecology, 2014. doi: 10.1111/1365-2745.12260
We tried to answer the simple question of what fraction of the world's plant species are woody: surprising the answer to this is not known. We surveyed researchers and found a huge range of estimates. We used a trait database that spanned 12% of plant diversity, and found that due to taxonomic patterns of woodiness, the estimates of woodiness were extremely biased. We used Monte Carlo (sampling) methods to correct this bias and found that just under half the world's vascular plant species are woody. Surprisingly this was much higher than estimates from researchers, even with significant botanical training.
All code and data to reproduce this paper are available on github, and an automatically generated analysis complete with code and figures is available here. This project uses continuous integration to ensure that it is fully reproducible.
Methods in Ecology and Evolution, 2012. doi:10.1111/j.2041-210X.2012.00234.x
This is the companion paper to my package diversitree. This paper outlines the overall design goals of the package. I introduce a new method, "MuSSE", for partitioning the effects that multiple traits may have on diversification. I also describe two new algorithms for fitting evolutionary models: a linear time algorithm for fitting continuous trait models based on Brownian Motion (always faster than the traditional cubic-time algorithm based on covariance matrices) and for fitting discrete traits with many levels (linear in the number of levels, rather than quadratic or worse).
All code and data to replicate the analysis are available on github. The package is available on CRAN and on github. Diversitree has now been used in over 100 studies, to answer questions I never dreamt of.
Systematic Biology, 2010. doi:10.1093/sysbio/syq053
I develop a new method, QuaSSE, to infer the effect of continuous traits such as body size on speciation and extinction rates, while simultaneously modelling the evolution of these traits. I show that under ideal situations with simulated data, the methods can infer patterns of diversification deep in the past, even while using only extant species data. I tested a long-standing hypothesis that species tend to become larger in size while large species diversify less rapidly than smaller species using a tree of all primates: I found little support for this hypothesis.
This method is implemented within diversitree
as make.quasse. The analysis from the paper is
replicated within the tutorial
(p 23 - 30, source).
This paper won the Systematic Biology "Publishers Award for
Excellence in Systematic Research".
with Wayne Maddison and Sally Otto
Systematic Biology, 2009 doi:10.1093/sysbio/syp067
In this paper I present ideas, algorithms and code for detecting the effect of species traits on rates of speciation and extinction. This generalised a new method (BiSSE) where only part of the structure of the phylogeny is known. This relaxes key assumptions in the original method and allowed BiSSE to be used on much broader classes of data than was previously possible.
This method is implemented within diversitree
as make.bisse. The analysis from the paper is
replicated within the tutorial
(p 15 - 20, source).