Collaborative Research: Investigating the roles of social influence in innate animal migrations

About This Grant

This collaboration between researchers at the University of Michigan and the University of Pittsburgh will study the mechanisms of animal migration termination using a novel logger and analytics platform (mSAIL). Migratory species such as monarch butterflies are uniquely threatened, and understanding how and why they choose different habitats will be important for helping us mediate threats. This research will provide novel insight into how social and environmental information are integrated to guide decisions and shape migratory ecosystems. Broader impacts of this work include raising scientific literacy through public engagement and broad cross-disciplinary training opportunities. Community volunteers directly contribute data that enable machine learning algorithm development for mSAIL. This work will provide cross-disciplinary training opportunities for multiple student participants in biology and engineering. The project contributes to the bioeconomy and to biotechnology through the development and honing of a data logger small enough to be carried by an insect that will be of interest to other scientists and engineers outside of this project. Migratory animals often terminate their migrations in specific places. How and why specific wintering/estivating habitats are chosen is not well understood yet is important to know given the unique threat that migratory species face. This research will use mSAIL, a multi-modal integrated biologger and analytics platform, to monitor monarch butterflies as they terminate their iconic annual migrations at their overwintering sites. The recently developed mSAIL technology will be modified to capture multi-modal environmental data with higher spatial and temporal resolution, allowing behavioral inference. This work will contribute to our broader understanding of how and why migratory species are distributed as they are and how different sources of information (environment and social cues) are integrated to determine these patterns. 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.