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Data and code for: Diversity-dependent diversification in the history of marine animals

Citation

Foote, Michael (2022), Data and code for: Diversity-dependent diversification in the history of marine animals, Dryad, Dataset, https://doi.org/10.5061/dryad.02v6wwq6d

Abstract

By comparing detrended estimates of diversity (taxonomic richness) and rates of origination, extinction, and net diversification, I show that, at the global scale over the course of the Phanerozoic Eon, rates of diversification and origination are negatively correlated with diversity. By contrast, extinction rates are only weakly correlated with diversity for the most part. These results hold for both genus- and species-level data and for many alternative analytical protocols. The asymmetry between extinction on the one hand and origination and net diversification, on the other hand, supports a model whereby extinction is largely driven by abiotic perturbations, with subsequent origination filling the void left by depleted diversity. Diversity-dependence is somewhat weaker, but still evident, if the initial Ordovician radiation or rebounds from major mass extinctions are omitted from analysis; thus, diversity-dependence is influenced, but not dominated, by these special intervals of Earth history. In the transition from Paleozoic to post-Paleozoic time, diversity-dependence of origination weakens while that of extinction strengthens; however, diversity-dependence of net diversification barely changes in strength. Despite nuances, individual clades largely yield results consistent with those for the aggregate data on all animals. On the whole, diversity-dependent diversification appears to be a pervasive factor in the macroevolution of marine animal life.

Methods

Data and code for "Diversity-dependent diversification in the history of marine animals" (American Naturalist).

Author: Michael Foote

The main goal of the study is to test for negative diversity-dependence of origination, extinction, and net diversification rates.

Data are derived from the Paleobiology Database (paleodb.org). Author is responsible for data collation and code.

Methods are described in the main text of the paper and in the R code file.

 

FILES

1. TimeScale.csv gives a list of time intervals used in this study. These are mainly international stages, with some epochs and sub-epochs. It is based primarily on Gradstein et al. 2012 (The Geologic Time Scale 2012, Elsevier, Amsterdam) and Ogg et al. 2016 (A Concise Geologic Time Scale 2016, Elsevier, Amsterdam), cross-referenced with stratigraphic information associated with collections in the Paleobiology Database (paleodb.org).

2. Occurrences.genus-level.csv: Number of collections in which each genus is present in each time interval. Data source is the Paleobiology Database (paleodb.org).

3. Occurrences.genus-level.low-latitude.csv: Number of collections in which each genus is present in each time interval, including only collections with paleolatitude less than 30 degrees. Collections without paleolatitude information are excluded.

4. Occurrences.genus-level.high-latitude.csv: Number of collections in which each genus is present in each time interval, including only collections with paleolatitude greater than or equal to 30 degrees. Collections without paleolatitude information are excluded.

5. Occurrences.species-level.csv: Number of collections in which each species is present in each time interval.

6. R-Code.R: Code used to analyze data.

Usage Notes

Software required is R. No extra packages need to be loaded.

Funding

University of Chicago