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One continuous experiment has been run in macroevolution: the evolution of life on the planet. Therefore, a difficulty in studying macroevolution is the inability to perform controlled experiments over million-year timescales. Model-based approaches provide a powerful alternative avenue in answering questions regarding the deep time evolution of the various diversity and disparity of traits observed in both living and fossil taxa. In my dissertation, I develop and apply novel model-based approaches in investigating drivers of trait evolution over macroevolutionary timescales. Chapter 1 examines how North American mammalian predators responded to climate change over the past 65 million years. Using model selection, I show mammalian predators undergo a shift to more carnivorously adapted assemblages following the expansion of grasslands in North America 33.9 million years ago.Chapter 2 studies the drivers and constraints of color diversity in the bird family Thraupidae (tanagers). As color is a non-linear measurement, I develop a wrapped Brownian motion model for circular datasets. Rates of color evolution in tanagers are lowest in the wings compared to those in the head, throat, breast, and other body patches, signaling the potential structural constraint of flight driving how tanagers navigate through color space.Chapter 3 explores the macroevolutionary ratchet as a mechanism of decline using simulations. Clades evolving under a macroevolutionary ratchet will exhibit distinct tree shape. However, after removing fossil taxa, the signature of the macroevolutionary ratchet quickly disappears, prevent accurate detection of such scenarios using only extant taxa.Overall, this dissertation research showcases the flexibility and power of model-based approaches in understand the evolution of various traits. The development of such quantitative methods will allow for additional macroevolutionary questions to be addressed by the broader research community and give further insights into the drivers of trait evolution in deep time.

Supplementary tables for Dillon et al. Paleobiology:Challenges and directions in analytical paleobiology Abstract:Over the last 50 years, access to new data and analytical tools has expanded the study of analytical paleobiology, contributing to innovative analyses of biodiversity dynamics over Earth’s history. Despite—or even spurred by—this growing availability of resources, analytical paleobiology faces deep-rooted obstacles that stem from the need for more equitable access to data and best practices to guide analyses of the fossil record. Recent progress has been accelerated by a collective push toward more collaborative, interdisciplinary, and open science, especially by early career researchers. Here, we survey four challenges facing analytical paleobiology from an early career perspective: (1) accounting for biases when interpreting the fossil record; (2) integrating fossil and modern biodiversity data; (3) building data science skills; and (4) increasing data accessibility and equity. We discuss recent efforts to address each challenge, highlight persisting barriers, and identify tools that have advanced analytical work. Given the inherent linkages between these challenges, we encourage discourse across disciplines to find common solutions. We also affirm the need for systemic changes that reevaluate how we conduct and share paleobiological research. This article is accompanied by two supplementary tables.For each, we provide a .csv file and a formatted .xlsx file. Supplementary Table 1. Examples of databases and online data portals used for paleobiological and (paleo)ecological research, along with their primary temporal, spatial, and taxonomic scope. N/A indicates that the corresponding information was either not applicable, undefined, or not readily available. The 'Modern' time period refers to last ~400 years unless otherwise specified. File names: Supplementary Table 1_Dillon et al. Paleobiology_2022.csv Supplementary Table 1 formatted_Dillon et al. Paleobiology_2022.xlsx Supplementary Table 2. Examples of programming packages and tools that are commonly used to analyze and visualize paleo data. Tools are grouped by their primary functionality. File names: Supplementary Table 2_Dillon et al. Paleobiology_2022.csv Supplementary Table 2 formatted_Dillon et al. Paleobiology_2022.xlsx Supplementary References. Full references for articles and software cited in the supplementary tables can be found in the supplementary references. File names: Supplementary References_Dillon et al. Paleobiology_2022.txt