This project will test how the age of social partners in a population determines social behavior and adaptation. As individuals age, their own behavioral expression changes, meaning that populations with older members represent a substantially different environment than populations with younger ones. Population age structure can thereby determine how individuals interact with conspecifics, alter which traits determine fitness, and ultimately determine the strength and form of natural and sexual selection. Understanding how age structure generates and maintains behavioral diversity requires a multilevel approach that tests how individuals change their current phenotypic expression, as well as how selection shapes behavior over evolutionary time. This work will be the first to evaluate the importance of population age structure as a demographic driver of behavioral evolution. The project will advance NSF priorities in artificial intelligence by developing and using AI-assisted video tracking and morphological measurement and to quantify animal movement and social interactions at a scale that would be difficult to achieve by hand. These tools will allow the research team to extract fine-scale behavioral data from large numbers of beetles and build a more precise understanding of how social environments shape evolution. This project further develops a training pipeline to provide research opportunities in field biology for undergraduates, including community-college transfer students, expands K–12 evolution education, and strengthens public outreach in STEM. Using a well-established invertebrate model system, the forked fungus beetle, replicated laboratory and seminatural field experiments will manipulate population level demographic features to explicitly test which factors are most important in determining how individual behavior is expressed, how social networks form, and which traits are favored by natural and sexual selection. A series of behavioral assays will