2019

  • Freyman WA and S Höhna: Stochastic Character Mapping of State-Dependent Diversification Reveals the Tempo of Evolutionary Decline in Self-Compatible Onagraceae Lineages, Systematic Biology, 2019, 68 (3), 505–519, link
  • Silvestro D, MF Tejedor, ML Serrano-Serrano, O Loiseau, V Rossier, J Rolland, A Zizka, S Höhna, A Antonelli and N Salamin: Early Arrival and Climatically-Linked Geographic Expansion of New World Monkeys from Tiny African Ancestors, Systematic Biology, 2019, 68 (1), 78–92, link
  • Hsiang AY, Brombacher A, Rillo MC, Mleneck-Vautravers MJ, Conn S, Lordsmith S, Jentzen A, Henehan MJ, Metcalfe B, Fenton I, Wade BS, Fox L, Meilland J, Davis CV, Baranowski U, Groeneveld J, Edgar KM, Movellan A, Aze T, Dowsett H, Miller G, Rios N, Hull PM. (2019) Endless Forams: >34,000 modern planktonic foraminiferal images for taxonomic training and automated species recognition using convolutional neural networks, Paleoceanography and Paleoclimatology, 2019, 34, link
  • Field DJ, Berv JS, Hsiang AY, Lanfear R, Landis MJ, Dornburg A. Timing the extant avian radiation: The rise of modern birds, and the importance of modelling molecular rate variation, PeerJ Preprints, 2019, 7, e27521v1, link

2018

  • Condamine FL, J Rolland J, S Höhna, FAH Sperling and I Sanmartin I: Testing the Role of the Red Queen and Court Jester as Drivers of the Macroevolution of Apollo Butterflies, Systematic Biology, 2018, 67 (6), 940–964, link
  • Martin CH and S Höhna: New evidence for the recent divergence of Devil’s Hole pupfish and the plausibility of elevated mutation rates in endangered taxa, Molecular Ecology, 2018, 27 (4), 831–838, link
  • Höhna S, LM Coghill, G Mount, R Thomson and JM Brown: P3: Phylogenetic Posterior Prediction in RevBayes, Molecular Biology and Evolution, 2018, 35 (4), 1028–1034, link
  • Freyman WA and Höhna S: Cladogenetic and Anagenetic Models of Chromosome Number Evolution: a Bayesian Model Averaging Approach, Systematic Biology, 2018, 67 (2), 195–215, link

2017

  • Höhna S, MJ Landis and TA Heath: Phylogenetic Inference using RevBayes. Current Protocols in Bioinformatics, 2017, 57:6.16.1-6.16.34, link
  • Martin CH, S Höhna, JE Crawford, BJ Turner, EJ Richards and LH Simons: The complex effects of demographic history on the estimation of substitution rate: concatenated analysis results in no more than 2-fold overestimation, Proceedings of the Royal Society B, 2017, 284: 20170537, link

2016

  • Moore BR, S Höhna, MR May, B Rannala and JP Huelsenbeck: Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures. Proceedings of the National Academy of Sciences, 2016, 113 (34), 9569-9574, link
  • Höhna S, MJ Landis, TA Heath, B Boussau, BR Moore, N Lartillot, JP Huelsenbeck and F Ronquist: RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Speci cation Language, Systematic Biology, 2016, 65 (4), 726-736, link
  • Conroy CR, JL Patton, M Lim, M Phuong, B Parmenter and S Höhna: Following the rivers: historical reconstruction of California voles (Microtus californicus, Muridae, Rodentia) in the deserts of eastern California, Biological Journal of the Linnean Society, 2016, 119 (1), 80–98, link
  • Höhna S, MR May and BR Moore: TESS: an R package for efficiently simulating phylogenetic trees and performing Bayesian inference of lineage diversification rates, Bioinformatics, 2016, 32 (5): 789-791, link