Abstract
Many paleontologists have noticed the broadly similar patterns between the changes in Cenozoic mammalian diversity and taxonomic dominance and climate changes. Yet detailed studies of fossil population samples with fine-scale temporal resolution during episodes of climate change like the Eocene-Oligocene transition in the White River Group, and the late Pleistocene at Rancho La Brea tar pits, demonstrates that most fossil mammal species are static and show no significant microevolutionary response to major climate changes. This mismatch between patterns seems best explained by species sorting. As the punctuated equilibrium model demonstrated, over long time spans most fossil species are stable and do not respond to climate change. Instead, change occurs at the next hierarchical level, with species sorting adding and subtracting to the total diversity pattern revealed by coarse-scale taxon counting, apparently responding to longer-term changes in climate as revealed by proxies like the oxygen isotope record.
Highlights
It has been asserted that the record of Cenozoic mammals is strongly affected by climate change
Geosciences 2012, 2 became available as a proxy for North American climates, the claim that there was a strong association between climate and mammalian diversity appeared in papers such as those by Webb [4,5] and especially in papers by Janis [6,7,8] and Vrba [9,10]
Eocene-Oligocene transition occurs in the White River Group of the High Plains, best known from its richly fossiliferous exposures in the legendary Big Badlands of South Dakota
Summary
It has been asserted that the record of Cenozoic mammals is strongly affected by climate change. Alroy [19,20,21], using similar methods of analysis but different statistical methods, concluded that there was no statistical relationship between North American mammalian diversity and Cenozoic climate proxies, such as the oxygen isotope curve. Most these studies are based on counting the presence or absence of taxa in specific faunas, or in databases (such as the Paleobiology DataBase [22]) that are aggregates of many faunas. Using this approach allows a scientist to generalize over all the instances of poor data quality and look at broad-scale patterns that would otherwise be unobtainable
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