Collaborative research: RUI: age structure of social groups as a critical demographic factor in the evolution of behavior

The National Science Foundation Division of Emerging Frontiers awarded Swarthmore College $1,207,910 on May 1, 2026, under the Biological Sciences program (CFDA 47.074) to investigate how population age structure drives the evolution of social behavior and shapes individual behavioral expression across generations.

The research uses the forked fungus beetle as a model organism to conduct replicated laboratory and seminatural field experiments that manipulate population-level demographic features. The work tests how the age composition of social groups determines social interactions, alters trait fitness, and influences the strength and form of natural and sexual selection. The project develops AI-assisted video tracking and morphological measurement tools to extract fine-scale behavioral data from large numbers of beetles, enabling analysis at a scale difficult to achieve manually.

The award funds a training pipeline providing undergraduate research opportunities in field biology, including community-college transfer students, alongside expanded K–12 evolution education and public outreach in STEM. Performance runs from May 1, 2026, through April 30, 2030, at Swarthmore, Pennsylvania.

Abstract

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 examine how social effects on behavioral expression scale up from individuals to social networks to population patterns of interaction. Dyadic interactions between individuals of different ages will be used to test whether age dependent behavior results from ontogenetic changes within focal subjects or plastic responses to partners of different ages. Focal subjects assayed in populations with manipulated age structures will test how behavioral plasticity results when individuals reside in group contexts with different age structures. A multi-year selection experiment will separately manipulate operational SEX ratio, density, and age structure to quantitatively test which of these contexts has the strongest effects on individual and social selection targeting social behavior and social network phenotypes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.