The Wright Lab


Here is some helpful information for students looking to join the lab. Below, you can read about what the Wright lab is all about.

Research Interests

Broadly, the Wright lab is interested in statistical phylogenetics, particularly the integration of molecular and morphological information to answer evolutionary questions.

Fossils and Phylogeny

I’m very interested in the best practices for estimating phylogenetic trees from combined molecular and morphological datasets (including information from the fossil record). Fossil data present many challenges for researchers investigating phylogenetic and macroevolutionary questions. Missing data, biases in preservation and model adequacy are all topics in which I have an interest. Keep an eye on my blog for tutorials and other hosted materials on this topic.

Relevant papers:

WrightAM, Lloyd, GT. 2020. Bayesian analyses in phylogenetic paleontology: Interpreting the posterior sample. Palaeontology. doi:10.1111/pala.12500

Wright AM. 2019. A systematist’s guide to estimating Bayesian phylogenies from morphological data. Insect Systematics and Diversity 3. doi:10.1093/isd/ixz006.

Wright AM, Lloyd GT, Hillis DM. 2016. Modeling character change heterogeneity in phylogenetic analyses of morphology through the use of priors. Syst. Biol. 65: 602-611.

Wright AM and Hillis DM. 2014. Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data. PLoS One 9:10.

Putting Fossils in Time Trees

How can we best make use of fossil data when estimating divergence dates? How can current methods, such as ‘tip-dating’ methods, be applied to paleontological information? Along with collaborators, I am developing empirical projects to address this question.

Relevant papers:

Wright AM, Wagner PJ, and Wright DF. 2021. Testing character evolution models in phylogenetic paleobiology: a case study with Cambrian echinoderms. Cambridge: Cambridge University Press. doi:10.1017/9781009049016

Warnock RCM, Wright AM. 2020. Understanding the tripartite approach to Bayesian divergence time estimation. Elements of Paleontology. Cambridge: Cambridge University Press. doi:10.1017/9781108954365

Bapst DW, Wright AM Lloyd GT, Matzke NJ. 2016. Topology, divergence dates, and macroevolutionary inferences vary between different tip-dating approaches applied to fossil theropods (Dinosauria). Biol. Lett. 12: 7.

Estimation and Use of Phylogenetic Trees

If you can put a tree on it, I’m interested. I’m a part of several projects including phylogenomic studies of population history and examining the contribution of topological uncertainty in modeling the evolution of complex traits.

Relevant Papers:

Mueller UG, Kardish MR, Ishak HD, Wright AM, Solomon SE, Bruschi SM, Carlson AL, Bacci M. 2018. Phylogenetic patterns of ant-fungus associations indicate that farming strategies, not only a superior fungal cultivar, explain the ecological success of leafcutter ants. Molecular Ecology.

Meirelles L, Solomon S, Bacci M, Wright AM, Mueller, U, Rodrigues, A. 2015. Shared Escovopsis infections destabilize the tripartite co-evolution hypothesis in the higher-attine fungus-growing ant symbiosis. R. Soc. Open Sci. 2:9.

Wright AM, Lyons KM, Brandley MB, Hillis DM. 2015. Which Came First? Robustness in Phylogenetic Reconstruction of Ancestral States. J Exp Zool B 324: 504-516.

Computational Literacy and Education

I’m probably most vocally interested in the pedagogy of computation and increasing the participation of underrepresented groups in this field. My courses taught page is frequently updated with course materials, all of which are CC-BY. Feel free to use these materials as you see fit (but attribute me!), or get in touch with me to talk more about them.

Relevant papers:

Harris B, McCarthy P,Wright AM, Schutz H, Boersma K, Shepherd S, Manning L, Malisch J, Ellington R. 2020. From panic to pedagogy: Using online active learning to promote inclusive instruction in ecology and evolutionary biology courses. Ecology and Evolution 10: 12581-12593. doi:10.1002/ece3.6915

Barido-Sottani J, Saupe E, Smiley TM, Soul LC,Wright AM, Warnock RCM. 2020. Seven rules for simulations in paleobiology. Paleobiology, 1-10. doi:10.1017/pab.2020.30

Wright AM, Schwartz RS, Oaks JM, Newman CM, and Flanagan SP. 2020. The Why, When, and How of Com-puting in Biology Classrooms. F1000Research 2020, 8:1854. doi:10.12688/f1000research.20873.1