A Taxon-Free, Multi-Proxy Model for Making Paleoecological Interpretations of Neogene North American Faunas

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 (\u3c500 \u3eg) provides the strongest separation of biomes. High frequencies of grazer, cursorial, and size class G traits (\u3c10500 \u3eg) 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 (\u3c500 \u3eg) 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 Secor

A Taxon-Free, Multi-Proxy Model for Making Paleoecological Interpretations of Neogene North American Faunas

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 (\u3c500 \u3eg) provides the strongest separation of biomes. High frequencies of grazer, cursorial, and size class G traits (\u3c10500 \u3eg) 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 (\u3c500 \u3eg) 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 Secor

Exploring the Relationships Between Mammalian Functional Trait Distributions and Regional Biomes, With Application to Miocene Paleoecology

Paleoecology relies on understanding relationships between modern animals and their environment. Animals are adapted to niches in their environments, and those physical adaptations, or functional traits, are utilized as proxies to interpret aspects of paleo-ecosystems. Much is known about individual functional traits in extant mammals and their relationship to the environment. Less is known about how multiple functional traits across a community can be utilized for paleoecological interpretations. I develop models utilizing traits in mammalian communities at the biome level. For Chapter 1, I build a model for North American regional biomes using mammalian trait frequencies. I quantify changes in trait frequency distributions from historical (1832-1899) to modern (2008-2020) times across twelve regional biomes. Results indicate broad species loss across all taxonomic levels and decreased trait frequencies in all biomes due to widespread range contractions. For Chapter 2, I develop models of North American and African mammalian trait distributions. Additionally, I use the models to make paleoecological interpretations of a middle Miocene (late Barstovian; Ba2) Great Plains fauna. Many established paleoecological proxies use African data, even for North American environments. I compare and evaluate these models to determine which is most appropriate for North American paleoecological interpretations. North American and African trait distributions of similar biomes are distinctly different. The African model provides a paleoecological interpretation of the Ba2 Great Plains fauna consistent with past interpretations. For Chapter 3, I apply trait distributions from three Miocene Nebraskan mammalian assemblages to the paleoecological North American and African models developed in Chapter 2. Miocene assemblages are more similar to each other than to modern communities, representing fundamental underlying differences in trait distributions. Both models appear unsuited to make interpretations of local assemblages. Species richness and geographic scale contribute to differences in trait distributions of local assemblages, as does sampling and taphonomic biases against small mammals. However, the African model is the best option for making paleoecological interpretations of Miocene assemblages, though differences still remain