A tectonically driven 60 million-year biogeochemical redox cycle paces marine biodiversity
Data files
Mar 27, 2026 version files 15.86 MB
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Data_Table_1.xlsx
57.16 KB
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Data_Table_2.xlsx
56.01 KB
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Data_Table_3.csv.zip
15.67 MB
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Data_Table_4.xlsx
62.03 KB
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README.md
12.30 KB
Abstract
The fossil record shows a prominent 60 million-year biodiversity cycle during the Phanerozoic Eon, the origin of which is still unknown. Here we use time-series analysis and correlation of empirical and model datasets of Earth’s interior and surficial processes to demonstrate that this cycle is a pervasive feature in marine animal genus-level diversity data that dominates in the Paleozoic Era. Our results suggest that extinctions are likely the primary driver of this observed cyclicity. We detected a correlatable 60 million-year cyclicity in global tectonics, and in marine 87Sr/86Sr and δ34S isotopes, all of which are dominant in the Paleozoic. We conclude that continental weathering driven by global tectonic degassing and building of continental arcs may have in turn controlled paleo-seawater redox cycling during the Paleozoic when oceans were likely less saturated with respect to oxygen. In particular, we suggest that the 60 million-year fluctuations in biotic diversity are responses of shallow marine habitats to the combined effects of continental weathering and redox cycling, under global tectonic control.
Dataset DOI: 10.5061/dryad.v41ns1s7j
Description of the data and file structure
Supplementary Information Data Tables Guide on:
A tectonically driven 60 million-year biogeochemical cycle paces marine biodiversity
Slah Boulila1,2*, Shanan E. Peters3, R. Dietmar Müller4, Andrew Zaffos5, Juraj Farkaš6, Bilal U. Haq1,7
1 Sorbonne Université, CNRS, Institut des Sciences de la Terre Paris, ISTeP, F-75005 Paris, France.
2 ASD/IMCCE, CNRS-UMR8028, Observatoire de Paris, PSL University, Sorbonne Université, 77 Avenue Denfert-Rochereau, 75014 Paris, France.
3 Department of Geoscience, University of Wisconsin–Madison, Madison, Wisconsin, USA.
4 EarthByte Group, School of Geosciences, University of Sydney, Sydney, New South Wales 2006, Australia.
5 Arizona State Geological Survey, University of Arizona, Tucson, Arizona, USA.
6 Metal Isotope Group, Department of Earth Sciences, School of Physical Sciences, University of Adelaide, Adelaide, SA, Australia.
7 George Mason University, Fairfax VA, USA.
*Corresponding author: Slah Boulila
Email: slah.boulila@sorbonne-universite.fr
Description of Initial Data
The raw data supporting this study come from two major geoscience databases - paleobiodb.org (a.k.a., PBDB; The Paleobiology Database) and macrostrat.org. Both websites allow users to dynamically query their database and download data through a REST API.
The REST query used for the primary Paleobiology Database dataset was https://paleobiodb.org/data1.2/occs/list.csv?base_name=metazoa&envtype=marine&show=class,coords,env.
The REST queries used for the primary Macrostrat dataset was derived from the https://macrostrat.org/api/v2/units API endpoint.
All sediments comes from the query https://macrostrat.org/api/units?lith_class=sedimentary&lith_type=metasedimentary&project_id=1&format=csv and marine units come from query https://macrostrat.org/api/units?environ_class=marine&project_id=1&format=csv.
The exact Macrostrat data used can be found in Data_Table_4.xlsx, which contains three worksheets that depict 1) total marine sediments; 2) total marine carbonates; and 3) dominant (more than 50%) carbonates.
An alternative, secondary Paleobiology Database dataset was also generated for the supplements that defined "marine" fossils based on their taxonomic affiliation rather than by the environment in which the fossils were collected. This data table does not directly correspond to a PBDB API query, because there was significant manual curation to remove terrestrial or freshwater families — a static copy of that taxa used in that dataset is therefore included here in Data_Table_3.csv.zip.
Description of Derived Tables (analyses)
The raw data tables of taxonomic occurrences downloaded from the Paleobiology Database (e.g., Table 3) were then used to calculate various diversity and turnover metrics. These metrics were calculated using the divDyn() package for R. The results of these analyses are included in Data_Table_1.xlsx and Data_Table_2.xlsx.
Each excel file contains three worksheets that include the output metrics from divDyn() for 1) global fossil richness as calculated through Shareholder Quorum Subsampling divDyn::subsample([data],q=0.7,type="sqs",tax="Taxa",bin="Bins",iter=50); 2) various turnover metrics for origination and extinction as caclulated using divDyn([data],tax="Taxa",bin="Bins",revtime=TRUE); and 3) a simple tabulation of the number of fossil occurrences per bin using the R native table() function.
Data Table Fields
The following is a breakdown of the fields in each respective supplementary data table.
Data Tables 1 & 2
Definitions for supplementary Data_Table_1.xlsx and supplementary Data_Table_2.xlsx. These two data tables use the exact same field definitions and format.
| Worksheet | Field | Type | Definition |
|---|---|---|---|
| 1a_Diversity | GTS2020 age (Ma) | Integer | Geologic age, millions of years ago |
| 1a_Diversity | Range-through (RT) | Integer | Genus richness (number of genera) |
| 1a_Diversity | SQS | Numeric | Sampled-in-bin species richness, calculated using Sharehodler Quorum Subsampling Method |
| 1b_Extinction_Origination | GTS2020 age (Ma) | Integer | Geologic age, millions of years ago |
| 1b_Extinction_Origination | extPC | Rate | Per Capita Extinction Rate |
| 1b_Extinction_Origination | oriPC | Rate | Per Capita Origination Rate |
| 1b_Extinction_Origination | ext2f3 | Rate | Extinction rate via "second-for-third" method |
| 1b_Extinction_Origination | ori2f3 | Rate | Origination rate via "second-for-third" method |
| 1c_Global_Occs | GTS2020 age (Ma) | Integer | Geologic age, millions of years ago |
| 1c_Global_Occs | Global occurrences | Integer | Number of global fossil occurrences |
Data Table 3
Definitions for supplementary Data_Table_3.csv.zip. More detail on the nature of these fields can be obtained from the Paleobiology Database documentation. https://paleobiodb.org/data1.2/occs/list_doc.html. Note that the geographic coordinates were not relevant for this particular study and are included simply for completeness.
| Field | Type | Definition |
|---|---|---|
| (blank) | Integer | Primary Key, Row Number, Index |
| occurrence_no | Integer | Occurrence's ID in the Paleobiology Database |
| collection_no | Integer | Paleobiology Database collection where the occurrence was reported |
| reference_no | Integer | Reference ID for the occurrence |
| phylum | String | Taxonomic Phylum of the occurrence |
| class | String | Taxonomic Class of the occurrence |
| order | String | Taxonomic Order of the occurrence |
| family | String | Taxonomic Family of the occurrence |
| genus | String | Taxonomic Genus of the occurrence |
| accepted_name | String | Most granular taxonomic name (i.e., species or above) available for the occurrence |
| early_interval | String | Earliest (oldest) geologic interval that the occurrence possibly dates from |
| late_interval | String | Latest (youngest) geologic interval that the occurrence possibly dates from |
| max_ma | Numeric | Maximum (oldest) numeric date (in millions of years) that the occurrence possibly dates from |
| min_ma | Numeric | Minimum (youngest) numeric date (in millions of years) that the occurrence possibly dates from |
| lng | Numeric | Longitude of the occurrence's coordinate point, present day |
| lat | Numeric | Latitude of the occurrence's coordinate point, present day |
| plaeolng | Numeric | Inferred Longitude of the occurrence's coordinate point, at the time taxon was alive |
| paleolat | Numeric | Inferred Latitude of the occurrence's coordinate point, at the time taxon was alive |
| geoplate | Integer | The tectonic plate ID that the occurrence is found on in the Paleobiology Database's paleogeographic rotation model |
Data Table 4
Definitions for supplementary Data_Table_4.xlsx
| Worksheet | Field | Type | Definition |
|---|---|---|---|
| 4a_total marine sediments | GTS2020 age (Ma) | Integer | Geologic age, millions of years ago |
| 4a_total marine sediments | total_cols | Integer | Total number of Macrostrat columns |
| 4a_total marine sediments | total_packages | Integer | Total number of Macrostrat packages |
| 4a_total marine sediments | total_area | Numeric | Total area of rock measured in square kilometers |
| 4b_total marine sediments | GTS2020 age (Ma) | Integer | Geologic age, millions of years ago |
| 4b_total marine carbonates | total_cols | Integer | Total number of Macrostrat columns |
| 4b_total marine carbonates | total_packages | Integer | Total number of Macrostrat packages |
| 4b_total marine carbonates | total_area | Numeric | Total area of rock measured in square kilometers |
| 4c_total marine carbonates | GTS2020 age (Ma) | Integer | Geologic age, millions of years ago |
| 4c_total dominant carbonates | total_cols | Integer | Total number of Macrostrat columns |
| 4c_total dominant carbonates | total_packages | Integer | Total number of Macrostrat packages |
| 4c_total dominant carbonates | total_area | Numeric | Total area of rock measured in square kilometers |
Code/software
Three files are in Microsoft Excel (xlsx) format and one is provided as a zipped Comma Separated Values (CSV) file. The files themselves were generated within the R software environment.
Access information
Other publicly accessible locations of the data:
- none
Data was derived from the following sources:
- Paleobiology Database (PBDB)
- All PBDB data are accessible via its API (reference below), which is updated continuously as new data are acquired.
- Macrostrat database
- All Macrostrat data are accessible via its API (reference below), which is updated continuously as new data are acquired.
Peters, S. E. & McClennen, M. The Paleobiology Database application programming interface. Paleobiology 42 (1), 1–7 (2016).
Peters, S. E., Husson, J. M., & Czaplewski, J. (2018). Macrostrat: A platform for geological data integration and deep-time earth crust research. Geochemistry, Geophysics, Geosystems, 19, 1393–1409. https://doi.org/10.1029/2018GC007467