NSF Postdoctoral Fellowship in Biology FY 2020: Integrating biological collections and observational data sources to estimate long-term butterfly population trends

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2020, Research Using Biological Collections. The fellowship supports research and training of the Fellow that will use biological collections in innovative ways. Recent studies suggest the possibility of being in the middle of an “insect apocalypse,” but true rates of decline for most insect species are unknown because of data limitations.

For many insect species, biological collections (including digital specimens) are the only available long-term source of data on insect numbers and diversity. This postdoctoral research project aims to use biological collection data and other observational data sources to identify current trends and reasons for butterfly population changes. The project will also raise public awareness about conservation and the value of museum collections and promote additional museum-based research.

To broaden the impact of the work, a museum exhibit and educational module will be designed, and undergraduates will be mentored in research.

Biological collection's data exhibit spatiotemporal and collector-specific biases that make it difficult to estimate population trends using only digitized museum records. These biases have limited the use of museum records such that there is an untapped wealth of data available to evaluate the impacts of global changes on insects. This project evaluates the utility of newly developed data integration methods for estimating long-term population trends using multiple data sources, including digitized museum records, opportunistic citizen science observations, and structured count data from monitoring schemes that follow standardized protocols.

An extensive simulation study will be used to evaluate the conditions under which it is useful and reasonable to integrate these three data types to track long-term population trends. An empirical case study focuses on estimating long-term trends for 32 open-habitat butterfly species in the Midwest Plains. Achievement of these research objectives will result in a transferable modeling framework that allows researchers to use biological collections data to reconstruct population trends through time.

This research will also be used by the Lepidoptera of North America Network Thematic Collection’s Network to identify geographic regions in North America that are most amenable for inclusion in an integrated analysis and should be prioritized in future targeted digitization efforts. To broaden the impact of the work, undergraduates will be mentored in independent research, and an interactive museum display and K-12 educational module on butterfly ecology will be generated.

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.