Collaborative Research: LTREB Renewal: Predicting the success of montane species in an era of environmental upheaval

Life on Earth has been challenged repeatedly by periods of catastrophic change that shift the structure and function of communities and ecosystems. The consequences of environmental upheaval have traditionally been studied by paleontologists reconstructing the appearance and disappearance of species in the fossil record. That approach has revealed much about extinction as a process, but has left questions unanswered about the properties of species that lead to persistence. Contemporary changes in the abundance of wild plants and animals provide biologists with the opportunity to track and study natural populations responding to environmental fluctuations that include extremes of weather and drought. This project builds on one of North America's longest-running observational studies of insect populations by continuing data collection at six sites in the Sierra Nevada Mountains of Northern California and Nevada. Encompassing more than 500 species of butterflies and moths, researchers are investigating habitat use by adult butterflies and by caterpillars to better understand direct and indirect effects of temperature and precipitation on insect populations. Results from this work will advance the use of artificial intelligence (AI) in forecasting insect populations, and will continue to inform our understanding of the health and stability of pollinators and other insects that are crucial for national health and prosperity. Project participants interact with the public through talks, field days, and a novel forecasting website, as well as with local school groups and teachers, supporting science education in urban and rural communities. The coming years of this project represent the completion of a decadal plan to advance and expand upon fifty years of research in a dynamic system that has played an important role in our understanding of insects in the Anthropocene. Ongoing work with this long-term dataset suggests that the impacts of environmental extremes, including drought, are in some cases as important as the effects of habitat loss and degradation through pesticide accumulation and other processes; additional discoveries include organismal traits that mediate abiotic effects in ways that are population-specific and predictable. In addition to observations of adult butterflies that have been recorded for decades, other lines of information being gathered include phenology of plant communities and fine-scale environmental data on microsites associated with caterpillar occurrence. Heterogeneous lines of information are being integrated into a statistical modeling framework that will take advantage of neural networks and other approaches in artificial intelligence (AI) to forecast insect populations, with real-time, publicly available model validation. Outcomes from this project will include interdisciplinary tools for prediction with heterogeneous data sources, as well as advances on ecological theories of animals interacting with topographic complexity while responding to novel environmental conditions. 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. NSF Award ID: 2553946 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Zachariah Gompert | Institution: Utah State University, LOGAN, UT | Award Amount: $107,271 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2553946 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2553946.html