B3GET: A new computational approach for understanding and exploring ecology, evolution, and behavior
2021-12
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B3GET: A new computational approach for understanding and exploring ecology, evolution, and behavior
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2021-12
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Biological anthropologists seek to understand the origin and evolution of distinctively human traits, including language, cumulative culture, and intensely cooperative societies. To understand the evolution of human behavior, we need a viable theory of socioecology. Studies of our primate relatives provide opportunities to develop and test socioecological models which can in turn help explain the evolution of human behavior. However, it has become increasingly clear that current socioecological models do not fully explain primate social behavior. Among many important limiting factors are the sheer number of variables to track and the difficulty of operationalizing ecological concepts such that they can be measured feasibly in the field. Microscale (i.e., agent-based) models have great potential for advancing the field because they can handle many different variables and incorporate individual variation, stochasticity, and emergent properties. I reviewed the existing literature on microscale models in behavioral ecology to better understand the state-of-the-art for models relevant to primate socioecology. I found that models are often designed for a single species or single area of research, limiting their application to broader questions. Many models also do not consider important biological constraints such as spatial relationships or rules for birth and death that depend on individual characteristics, nor are they often validated for accuracy. As a contribution towards a more complete understanding of primate socioecology, I developed B3GET, a microscale model that incorporates important biological constraints and can track key socioecological variables in simulated primates. These virtual primates possess decision-making rules encoded in simulated diploid chromosomes, which dictate movement, body growth, inclination to mate, eat, and other behaviors. I developed these rules based on primate socioecological data from the literature and my own field observations. The virtual primate environment consists of a landscape of plants that can vary in their quality and distribution. B3GET users can edit the starting genotype and population files to create different virtual populations with different behaviors, and then collect simulation data for hypothesis testing. I simulated four primate species – chimpanzees, geladas, hamadryas baboons, and olive baboons – and showed that these simulated species display typical real-life behaviors in their group composition, dispersal patterns, and mating strategies. I built upon recent model-validation frameworks to analyze B3GET using a series of tests. Some important findings include: Hamilton's rule emerged under some, but not all, simulation conditions; individuals appeared to have the highest fitness in medium-sized groups; and spatial relationships do matter: primates living in aspatial simulations committed infanticide 10 times more frequently than identical primates in spatial simulations. Because B3GET can viably simulate other primate species, it is a promising approach for investigating the origins of distinctively human behaviors.
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University of Minnesota Ph.D. dissertation. 2021. Major: Anthropology. Advisors: Michael Wilson, Clarence Lehman. 1 computer file (PDF); 528 pages.
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Crouse, Kristin. (2021). B3GET: A new computational approach for understanding and exploring ecology, evolution, and behavior. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/226655.
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