Just learned this masterpiece got published today and couldn’t be more excited about it!! During my first PhD semester at UMich back in 2019 Willy gave an amazing talk about this project, setting the bauplan of the kind of research I have tried to do since!
scholarlypress.si.edu/store/all/co...
📣 Introducing MorphSim: an R package for simulating discrete morphological data along phylogenetic trees, built for fossil-inclusive phylogenetics, with all the complexity of real morphological data baked in 🪨🌿
besjournals.onlinelibrary.wiley.com/doi/10.1111/...
Very well-timed publication of my most recent work at @royalsociety.org Proc B showcasing the backbone of my future research at @stonybrooku.bsky.social!
There is still much to learn about ray-finned fish neurocranial evolution and the diversity of ways brain and endocasts interact in this lineage!
Check out our new paper comparing node calibrations and unresolved FBD for dating molecular phylogenies using crocs and firefly datasets as case studies 🐊
My new paper with @gdarlim.bsky.social and @hoehna.bsky.social is now out in Proceedings B! We set out to compare two different approaches to time-calibrate a molecular phylogeny: traditional node calibrations, and unresolved FBD... @royalsocietypublishing.orgdoi.org/10.1098/rspb...
We also show the impact that the number of fossils included in the unresolved FBD analysis has on node ages. Turns out that you need a substantial number of fossils (in our croc example, >20 in total) to have effective priors that are more informative than those induced by flat node calibrations.
Ultimately, to time-calibrate a molecular phylogeny, we recommend using the unresolved FBD approach when several extinct species are sampled in the focal group, or sampled fossils are taxonomically uncertain. In other cases (e.g. few fossils), we favor the use of classic node-dating approaches.
In the unresolved FBD (fossilized birth-death), extinct species (fossils) are treated as tips in the tree, providing chronostratigraphic data to the analysis. No morphological data is included, so fossils are constrained based on expert knowledge, similarly to how node calibrations are designed.
We looked at two study cases (crocodylians and fireflies), comparing effective prior and posterior distributions on node ages. We show that effective priors induced by unresolved FBD are extremely similar to those induced by flat node calibrations when only one fossil per calibrated clade is used.
Out now in Contributions from me and @gilespalaeo.bsky.social, a deep dive into an early member of the sturgeon and paddlefish lineage. Bear with me, but there’s a long backstory highlighting uncertainty about the anatomy of living species and how well-studied fossils can still yield new insights.
Osteichthyans--the bony fishes--are by far the most diverse group of living jawed vertebrates. Two papers out today in @nature.com feature remarkable new Chinese fossils that paint a picture of substantial morphological diversity among stem osteichthyans.
New paper out from @hoehna.bsky.social Lab, led by the brilliant @bjorntko.bsky.social! We applied the Pesto software (Kopperud & Höhna, 2025) to look at lineage-specific shifts in diversification rate on large, densely-sampled phylogenies across the Tree of Life doi.org/10.1093/evle...
New paper out from @hoehna.bsky.social Lab, led by the brilliant @bjorntko.bsky.social! We applied the Pesto software (Kopperud & Höhna, 2025) to look at lineage-specific shifts in diversification rate on large, densely-sampled phylogenies across the Tree of Life doi.org/10.1093/evle...
- Shifts in diversification rate happen more frequently in younger phylogenies
- Groups with faster diversification overall also show higher variability in diversification rates
- Flowering plants appear to experience larger (and more frequent) shifts than any other group we analyzed
New paper out from @hoehna.bsky.social Lab, led by the brilliant @bjorntko.bsky.social! We applied the Pesto software (Kopperud & Höhna, 2025) to look at lineage-specific shifts in diversification rate on large, densely-sampled phylogenies across the Tree of Life doi.org/10.1093/evle...
A few key findings:
- Shifts in diversification rate are ubiquitous across the Tree of Life: the process of diversification is highly heterogeneous
- Upshifts are way more common than downshifts (but this is likely due to lack of power in detecting downshifts with extant phylogenies)
Our new paper 'A covarion model for phylogenetic estimation using discrete morphological datasets,' is out in SysBio!
We introduce the "covariomorph" model in RevBayes to capture character and lineage specific rates of morphological traits.
🔗 doi.org/10.1093/sysb...
I'll be presenting a poster at #2025SVP#SVP2025 about my recently published work on how many characters are needed to reconstruct a phylogeny. Come by at the poster session this Thursday if you want to chat about it! royalsocietypublishing.org/doi/abs/10.1...
Out now in Biology Letters, my latest paper tackles an apparently simple question: how many characters are needed to reconstruct a phylogeny? TL;DR: in most cases between 100 and 500, more than a substantial portion of morphological datasets, but the story is more complex... doi.org/10.1098/rsbl...
An important point: the 100-500 chars threshold refers to an ideal scenario where we know under which model the data evolved (no model misspecification), this model is relatively simple (few parameters to infer), and there is no missing data. Thus, this should be taken as a very minimum number.
Problem: a lot of empirical morphological datasets have fewer than 100 characters, and way fewer than 500. Possible solutions? Continuous characters; total-evidence datasets; more funding, hiring, training targeted towards characterization and digitization of interspecific morphological diversity.
Out now in Biology Letters, my latest paper tackles an apparently simple question: how many characters are needed to reconstruct a phylogeny? TL;DR: in most cases between 100 and 500, more than a substantial portion of morphological datasets, but the story is more complex... doi.org/10.1098/rsbl...
Overall, between 100 and 500 variable characters are necessary to reach sufficient accuracy and precision of phylogenetic estimates for as low as 20 taxa. This is relevant not only for morphological phylogenetics, but also for gene trees and SNP-based estimates, and for Bayesian phylolinguistics.
One intriguing empirical application of these findings is that, for more than 50 taxa, characters that change multiple times independently across the tree (homoplastic characters) improve tree reconstruction compared to characters that change only once (synapomorphies and autapomorphies).
Out now in Biology Letters, my latest paper tackles an apparently simple question: how many characters are needed to reconstruct a phylogeny? TL;DR: in most cases between 100 and 500, more than a substantial portion of morphological datasets, but the story is more complex... doi.org/10.1098/rsbl...
I designed this simulation study in RevBayes to perfectly match the models used for sim and inference. Any differences between the true tree generating data and the inferred tree(s) are due to dataset size. Parameters that varied across sims are: # characters, # taxa, tree length, and # states.
Three different metrics of accuracy and precision were used to evaluate how good was the phylogenetic inference. General resulting patterns: more characters are better; more states are better (but this has little effect for >50 taxa); more taxa are worse for short trees, but better for long trees.
Just in time for #FossilFriday 🦖 What are the big questions in #paleontology today?
dx.doi.org/10.1017/pab.2025.10042
Nearly 200 scientists worldwide came together to map where our field is headed. Here’s the story 👇
What are the biggest questions in #paleontology? New paper out today in Paleobiology led by Smith & Kiessling with ~200 coauthors on the relevance of our field, methods, & museum collections to climate & biodiversity research🦖 #FossilFriday@paleosoc.bsky.social 🔗: www.cambridge.org/core/journal...
Ever wondered how to incorporate fossils as tips in a phylogenetic tree?
Our new paper provides a comprehensive guide!
#EarlyFossilFriday#FossilFriday#TipDating#Phylogeny#EvolutionaryBiology
I am extremely happy to see that our review on fossil tip-dating is out in early view in Systematic Biology! A huge thanks to all the authors of this massive project (@heckeberg.bsky.social, @basantakhakurel.bsky.social, Gustavo Darlim, and @hoehna.bsky.social)! academic.oup.com/sysbio/advan...
Non-exhaustive list of things you can find in our paper:
- A survey of all fossil tip-dating studies published until 2023
- A flowchart with all the steps to set up a tip-dating analysis
- Detailed discussion of all the elements making up a tip-dating analysis, from molecular alignment to FBD models
We hope that our contribution will not only be a useful reference for all researchers wanting to perform a tip-dating analysis on their favorite group of organisms, but also a starting point of discussion to further improve this class of methods and its application to empirical data!
We (me, @barankarapunar.bsky.social, @sinjinis.bsky.social and @harriedrage.bsky.social) organized a symposium for the next IPC (Cape Town 2026!) on evolution, diversity and ecology in marine ecosystems throughout the Phanerozoic.
Contact us if you would like to participate or to know more about it!
Symposia 🔍
Among our 29 themed symposia + 1 open symposium, we are pleased to feature:
✨ Life in the Phanerozoic Oceans: Evolution, diversity and ecology in deep time marine ecosystems✨
📩 To participate in this symposium or get more information, contact the conveners: 👇
No, it is not a dream. This actually happened!!! We had a *fantastic* #CPEGCPB26 meeting and I cannot articulate any other adjective to describe it until I recover from it. Thanks to everyone who attended and everyone who helped making this happen. @kristinakocakova.bsky.social
The CPEG & CPB meeting is officially underway! 🎉
We kicked things off with two fantastic workshop sessions:
📊 R-based open data science in palaeobiology and ecology
🧠 Deep learning for macroevolutionary analyses
Big thanks to all our speakers and participants - spot yourself below!
#CPEGCPB25
We now have protein sequences from rhino enamel that are >20 million years old! I am extremely excited and grateful to have been part of this project. The incredible thing: these sequences are informative enough to place this ancient species in the rhino tree! www.nature.com/articles/s41...
According to our analysis, Elasmotherium (the "Siberian unicorn") and modern rhinos share a common ancestor in the Oligocene (more recently than previously thought), and they are more closed related to each other than to our aceratherine from the High Arctic.
Here is a Nature News writeup on our work, covering also another remarkable new paper on extremely old enamel proteins by Daniel Green and colleagues. www.nature.com/articles/d41...
We now have protein sequences from rhino enamel that are >20 million years old! I am extremely excited and grateful to have been part of this project. The incredible thing: these sequences are informative enough to place this ancient species in the rhino tree! www.nature.com/articles/s41...
Our protein-based tip-dated phylogenetic analysis (a combination of words that would have been totally absurd until recently) shows that this aceratherine ("hornless rhino") belonged to an early-diverging lineage in the rhino family tree.
Moderate extinctions and slow recovery of non-marine teleost fishes across the Cretaceous–Paleogene boundary, with a systematic appraisal of early Paleocene teleost fishes from Saskatchewan, Canada, and Montana, USA. Palaeontologia Electronica, 28(2):a28. 🐟🧪
palaeo-electronica.org/content/2025...