Formation binning: a new method for increased temporal resolution in regional studies, applied to the Late Cretaceous dinosaur fossil record of North America
Cite this dataset
Dean, Christopher; Chiarenza, A. Alessandro; Maidment, Susannah (2020). Formation binning: a new method for increased temporal resolution in regional studies, applied to the Late Cretaceous dinosaur fossil record of North America [Dataset]. Dryad. https://doi.org/10.5061/dryad.tmpg4f4vg
The advent of palaeontological occurrence databases has allowed for detailed reconstruction and analyses of species richness through deep time. While a substantial literature has evolved ensuring that taxa are fairly counted within and between different time periods, how time itself is divided has received less attention. Stage-level or equal-interval age bins have been frequently used for regional and global studies in vertebrate palaeontology. However, when assessing diversity at a regional scale, these resolutions can prove inappropriate with the available data. Herein, we propose a new method of binning geological time for regional studies that intrinsically incorporates the chronostratigraphic heterogeneity of different rock formations to generate unique stratigraphic bins. We use this method to investigate the diversity dynamics of dinosaurs from the Late Cretaceous of the Western Interior of North America prior to the Cretaceous–Palaeogene mass extinction. Increased resolution through formation binning pinpoints the Maastrichtian diversity decline to between 68–66 Ma, coinciding with the retreat of the Western Interior Seaway. Diversity curves are shown to exhibit volatile patterns using different binning methods, supporting claims that heterogeneous biases in this time-frame affect the pre-extinction palaeobiological record. We also show that apparent high endemicity of dinosaurs in the Campanian is a result of non-contemporaneous geological units within large time bins. This study helps to illustrate the utility of high-resolution, regional studies to supplement our understanding of factors governing global diversity in deep time and ultimately how geology is inherently tied to our understanding of past changes in species richness.
Additional Data for this manuscript consists of three, zipped supplementary folders:
1. Supplementary Information 1. Folder contains all necessary R code and datasets to run Formation Binner, including a README guide. Data folder consists of a .csv file of dinosaur occurrences, downloaded from the PBDB (Occurrences_Final); a .csv file of dinosaur bearing formations, with information gathered from the available literature (Formations_Final); and a .csv file of references for the updated formation information (References). This dataset can also be found at https://github.com/ChristopherDavidDean/Formation_Binner.
2. Supplementary Information 2. Folder contains all results generated using Formation Binner and used for this project. Data is either produced using Score Grid 1 (folder SG1), Score Grid 2 (folder SG2), or using Standard Binning (folder Standard_Binned). For SG1 and SG2, data was produced at 3 different resolutions: 2, 3 or 4 million years. Within these folders, data is split into Images (plots of results) or Tables (raw results). Results generated using SG1 and SG2 at all resolutions were also carried out using three methods (M1, M2 and M3), which each include plots of diversity and collections (named Div, Colls, or div_colls), Goods' U (named Goodsu) and SQS (named SQS). Also available is the plot of suitability scores (named 0.001_res) and plots of Formations through time (named FormationGraph). Standard Bin results are instead split into either Stage or Substage resolutions (Stage_Bins and SubStage_bins respectively), and then produced using either Formation Ages or PBDB ages (FormAges and PBDB) and binned using every bin the occurrence appears within or using the midpoint of its age range (Allbins and Mid).
3. Figure_S1. Contains supplementary Figure S1 as well as the appropriate figure caption.
For a guide on how to run R script for Formation Binner, a full READ.ME can be found at https://github.com/ChristopherDavidDean/Formation_Binner