Earth and Atmospheric Sciences, Department of


First Advisor

Ross Secord

Date of this Version



Hock, D.G., 2018. A Taxon-Free, Multi-Proxy Model for Making Paleoecological Interpretations of Neogene North American Faunas. M.S. Thesis, Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Nebraska, USA.


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Earth and Atmospheric Sciences, Under the Supervision of Professor Ross Secord. Lincoln, Nebraska: June, 2018

Copyright (c) 2018 Devra G. Hock


Proxies used for interpreting the paleoecology of extinct vertebrate communities are usually based on modern ecosystems, with many developed from Old World ecosystems. However, because no model is completely taxon-free and phylogenetic influences cannot be entirely discounted, these proxies may not be appropriate for paleoecological interpretations of North American ecosystems. Additionally, many proxies based on modern vertebrate communities exclude small-bodied mammals. Here I explore several new paleoecological models based on the frequency of mammalian traits within three ecological categories: locomotion, diet, and body mass. Since these models are intended for interpreting paleoenvironments occupied by Neogene North American mammals, the data used to develop the models are from historical North American faunas. Pre-existing datasets were augmented with locomotion, diet, and body mass information from a variety of sources. Mammalian geographic occurrences were assigned to digital maps of Bailey’s Ecoregions of North America in ESRI ArcMap and ecoregions were combined into broader biomes in an iterative process using preliminary Principle Component Analysis (PCA). Taxa were sorted by biome and two datasets were created, one where the number of individual occurrences were used to weight traits, and one where only a single taxonomic occurrence was used for each biome. Taxonomic analyses were conducted on unweighted taxa both with and without rodents and lagomorphs. PCA was conducted using frequencies of trait classifications per biome for all datasets. Stacked area charts were created to visualize changing trait frequencies among biomes.

PCA analyses using unweighted data without the smallest mammals (<500 >g) provides the strongest separation of biomes. High frequencies of grazer, cursorial, and size class G traits (<10500 >g) are correlated traits in the grassland biome. Size classes C (500-1000 g) and D (1000 – 1500 g) are the second group of correlated traits, plotting in the opposite direction in grassland. High frequencies of arboreal/scansorial, omnivore, and granivore traits make up key indicators for the forest biome. Weighted datasets without small-bodied mammals (<500 >g) work well to distinguish among biomes. I conclude that unweighted analyses excluding small-bodied mammals should provide the best separation of biomes and be most appropriate for certain paleoecological applications in North America.

Advisor: Ross Secord

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