Revisiting the sedimentary record of the rise of diatoms
Cite this dataset
Westacott, Sophie; Planavsky, Noah; Zhao, Ming-Yu; Hull, Pincelli (2021). Revisiting the sedimentary record of the rise of diatoms [Dataset]. Dryad. https://doi.org/10.5061/dryad.hx3ffbgcb
Diatoms are a major primary producer in the modern oceans and play a critical role in the marine silica cycle. Their rise to dominance is recognized as one of the largest shifts in Cenozoic marine ecosystems, but the timing of this transition is debated. Here, we use a diagenetic model to examine the effect of sedimentation rate and temperature on the burial efficiency of biogenic silica over the past 66 million years (i.e., the Cenozoic). We find that the changing preservation potential of siliceous microfossils during that time would have overprinted the primary signal of diatom and radiolarian abundance. We generate a taphonomic null hypothesis of the diatom fossil record by assuming a constant flux of diatoms to the sea floor and having diagenetic conditions driven by observed shifts in temperature and sedimentation rate. This null hypothesis produces a late Cenozoic (~5-20 Ma) increase in the relative abundance of fossilized diatoms that is comparable to current empirical records. This suggests that the observed increase in diatom abundance in the sedimentary record may be driven by changing preservation potential. A late Cenozoic rise in diatoms has been causally tied to the rise of grasslands and baleen whales and to declining atmospheric CO2 levels. Here we suggest that the similarity among these records primarily arises from a common driver—the cooling climate system—that drove enhanced diatom preservation as well as the rise of grasslands and whales, rather than a causal link amongst them.
Data is sourced from published literature (citations in ReadMe file and in Related Works). The only processing they have undergone is to remove undesired variables and to rename columns.
Code and datasets (csv and txt files) for all analyses and figures. Using included RProject is recommended. ReadMe file provides order of operations (code must be run in sequence) and data source citations.