Michael J. Landis

Phylogenetic estimation of diversity-dependent biogeographic rates using deep learning

DDGeoSSE, a GeoSSE extension in which local species richness modulates speciation, extinction and dispersal, is fit with phyddle neural networks that detect diversity dependence in Anolis and Viburnum.

On the mapping between evolutionary scenarios and governing rules in state-dependent speciation-extinction models

This study maps evolutionary scenarios to governing rules in state-dependent speciation-extinction models and shows that different scenarios can produce identical stationary distributions.

Gene tree patterns help answer: vicariance or dispersal?

The paper shows gene tree patterns differ predictably between vicariance and founder event speciation, suggesting new methods to distinguish these drivers.

Synchronizing speciation, extinction, and dispersal to island paleodynamics through Bayesian phylogenetics in a Hawaiian plant radiation

The paper introduces a Bayesian phylogenetic framework to infer divergence times, ancestral ranges, and diversification rates in Hawaiian plants without fossil calibration.

Summarizing Evolutionary Trajectories from Phylogenetic Character Maps of Discrete Traits

This paper introduces a framework to summarize evolutionary trajectories of discrete traits using trajectory trees, applied to lizard biogeography and ecomorph evolution, revealing more unique paths than expected under standard models.

Assessing the Efficacy of Computational Workshops and Participatory Live Coding in Evolutionary Biology

The paper evaluates the effectiveness of computational workshops in evolutionary biology by assessing participant motivation and perceptions of instructional techniques.

EMPIRE: The Ellipse Model for Phylogenetic Inference of Range Evolution

The paper introduces EMPIRE, a model for inferring range evolution in phylogenetics, and applies it to skinks in Australia, finding speciation linked to aridification but not ecological partitioning in daughter lineages.

Ancestral state reconstruction with discrete characters using deep learning

This study uses deep learning to perform ancestral state reconstruction for phylogenetic models with intractable likelihoods, comparing performance to Bayesian inference on empirical datasets.

A Phylogenetic Model of Established and Enabled Biome Shifts

The paper introduces a phylogenetic model, RFBS, to distinguish between established and enabled biome affinities in species evolution and applies it to flowering plants.

Seventy-five Years of Systematic Biology: Looking Back, Moving Forward

The paper analyzes the evolution of systematic biology over 75 years using bibliometric and textual data from 5,150 articles.

phyddle: software for exploring phylogenetic models with deep learning

The paper introduces phyddle, a software tool using deep learning for phylogenetic modeling, and shows it accurately performs inference tasks even for models without tractable likelihoods.

PhyloJunction: a computational framework for simulating, developing, and teaching evolutionary models

This paper introduces PhyloJunction, a computational framework for simulating and teaching evolutionary models, with features for model prototyping and visualization.

Bayesian inference of admixture graphs on Native American and Arctic populations

The paper introduces a Bayesian MCMC method for inferring admixture graphs and applies it to Native American and Arctic populations, finding that the Koryak population, not Saqqaq, is the best proxy for gene flow into Athabascans.

Parallel power posterior analyses for fast computation of marginal likelihoods in phylogenetics

The paper introduces a parallelization strategy to speed up marginal likelihood estimation in Bayesian phylogenetics, reducing runtime significantly with multiple CPUs.