Phylogenetic inferences using combined datasets of both extant and extinct species have grown increasingly popular, in part thanks to the development of the fossilized birth–death (FBD) process. The FBD process provides a powerful model for the evolution of past and present lineages and can be used for both inference and simulation. Simulations in particular are very helpful for new users to gain better understanding of the model and its different components. In this work, we present FossilSimShiny, a visual application for simulating phylogenies, fossil samples, and fossil taxonomies under the FBD process. The app integrates a wide range of simulation models and presents the simulation results in clear, customizable figures. As a teaching tool, FossilSimShiny allows lecturers to create illustration plots and students to directly experiment with the model. For research applications, the app can help researchers save time and effort by testing and calibrating simulation setups before running them on a large scale.

Phylodynamic models can be used to estimate diversification trajectories from time-calibrated phylogenies. Here we apply two such models to phylogenies of non-avian dinosaurs, a clade whose evolutionary history has been widely debated. Although some authors have suggested that the clade experienced a decline in diversity, potentially starting millions of years before the end-Cretaceous mass extinction, others have suggested that the group remained highly diverse right up until the Cretaceous-Paleogene (K-Pg) boundary. Our results show that model assumptions, likely with respect to incomplete sampling, have a large impact on whether dinosaurs appear to have experienced a long-term decline or not. The results are also highly sensitive to the topology and branch lengths of the phylogeny used. Developing comprehensive models of sampling bias, and building larger and more accurate phylogenies, are likely to be necessary steps for us to determine whether dinosaur diversity was or was not in decline before the end-Cretaceous mass extinction.

Data compilations expand the scope of research; however, data citation practice lags behind advances in data use. It remains uncommon for data users to credit data producers in professionally meaningful ways. In paleontology, databases like the Paleobiology Database (PBDB) enable assessment of patterns and processes spanning millions of years, up to global scale. The status quo for data citation creates an imbalance wherein publications drawing data from the PBDB receive significantly more citations (median: 4.3 ± 3.5 citations/year) than the publications producing the data (1.4 ± 1.3 citations/year). By accounting for data reuse where citations were neglected, the projected citation rate for data-provisioning publications approached parity (4.2 ± 2.2 citations/year) and the impact factor of paleontological journals (n = 55) increased by an average of 13.4% (maximum increase = 57.8%) in 2019. Without rebalancing the distribution of scientific credit, emerging “big data” research in paleontology—and science in general—is at risk of undercutting itself through a systematic devaluation of the work that is foundational to the discipline.

Simulations are playing an increasingly important role in paleobiology. When designing a simulation study, many decisions have to be made and common challenges will be encountered along the way. Here, we outline seven rules for executing a good simulation study. We cover topics including the choice of study question, the empirical data used as a basis for the study, statistical and methodological concerns, how to validate the study, and how to ensure it can be reproduced and extended by others. We hope that these rules and the accompanying examples will guide paleobiologists when using simulation tools to address fundamental questions about the evolution of life.

Estimating speciation and extinction rates is essential for understanding past and present biodiversity, but is challenging given the incompleteness of the rock and fossil records. Interest in this topic has led to a divergent suite of independent methods—paleontological estimates based on sampled stratigraphic ranges and phylogenetic estimates based on the observed branching times in a given phylogeny of living species. The fossilized birth–death (FBD) process is a model that explicitly recognizes that the branching events in a phylogenetic tree and sampled fossils were generated by the same underlying diversification process. A crucial advantage of this model is that it incorporates the possibility that some species may never be sampled. Here, we present an FBD model that estimates tree-wide diversification rates from stratigraphic range data when the underlying phylogeny of the fossil taxa may be unknown. The model can be applied when only occurrence data for taxonomically identified fossils are available, but still accounts for the incomplete phylogenetic structure of the data. We tested this new model using simulations and focused on how inferences are impacted by incomplete fossil recovery. We compared our approach with a phylogenetic model that does not incorporate incomplete species sampling and to three fossil-based alternatives for estimating diversification rates, including the widely implemented boundary-crosser and three-timer methods. The results of our simulations demonstrate that estimates under the FBD model are robust and more accurate than the alternative methods, particularly when fossil data are sparse, as the FBD model incorporates incomplete species sampling explicitly.

The two major approaches to studying macroevolution in deep time are the fossil record and reconstructed relationships among extant taxa from molecular data. Results based on one approach sometimes conflict with those based on the other, with inconsistencies often attributed to inherent flaws of one (or the other) data source. Any contradiction between the molecular and fossil records represents a failure of our ability to understand the imperfections of our data, as both are limited reflections of the same evolutionary history. We therefore need to develop conceptual and mathematical models that jointly explain our observations in both records. Fortunately, the different limitations of each record provide an opportunity to test or calibrate the other, and new methodological developments leverage both records simultaneously. However, we must reckon with the distinct relationships between sampling and time in the fossil record and molecular phylogenies. These differences impact our recognition of baselines and the analytical incorporation of age estimate uncertainty.

Turtles have served as a model system for molecular divergence dating studies using fossil calibrations. However, because some parts of the fossil record of turtles are very well known, divergence age estimates from molecular phylogenies often do not differ greatly from those observed directly from the fossil record alone. Also, the phylogenetic position and age of turtle fossil calibrations used in previous studies have not been adequately justified. We provide the first explicitly justified minimum and soft maximum age constraints on 22 clades of turtles following best practice protocols. Using these data we undertook a Bayesian relaxed molecular clock analysis establishing a timescale for the evolution of crown Testudines that we exploit in attempting to address evolutionary questions that cannot be resolved with fossils alone. Some of these questions, such as whether the turtle crown originated in the Triassic or Jurassic, cannot be resolved by our analysis. However, our results generate novel age-of-origination estimates for clades within crown Testudines. Finally, we compare our fossil calibrations and posterior age estimates to those from other studies, revealing substantial differences in results and interpretation.