Assessing drivers of vegetation change across landscapes of the western USA

Drylands in the western U.S. support a variety of plant species that are instantly recognizable and define some of our most beautiful landscapes. These plant species depend on rainfall arriving in particular amounts and at certain times. As these conditions change from year to year, it is uncertain how these plant species will be affected in terms of growth and survival. Dryland systems may be either more resilient to drought, or more vulnerable, due to their overall lack of precipitation and unique evolutionary histories of the plant species contained in these ecosystems. This project produces relevant answers to management questions such as which ecosystem types, plant communities, plant functional groups, or plant species are at particular risk of future drought impacts. The project makes use of a unique, high quality, multi-year inventory of plant species in national parks, and applies advanced analytical methods that go beyond standard statistical analyses. Training in valuable data skills is provided to students, and outreach will be delivered to the general public regarding the role of plant species in national parks. The goals of this project are: (1) to identify the key drivers of changes in species occurrence and cover across many plant species, functional types, and ecosystem types, and (2) to evaluate how species responses propagate to plant community dynamics across the western U.S. The approach advances flexible and rigorous Bayesian statistical and machine learning approaches for integrating datasets from multiple data networks. This integration has been difficult to achieve due to different sampling methods and sparse data related to detection or observer error. These advanced analytical methods improve our understanding of region-wide changes to plant communities. The project develops flexible and rigorous statistical approaches for integrating long-term inventory and monitoring data, providing valuable insights for landscapes of the western U.S. The methodological innovations produced in this project are applicable across vegetation science and plant community ecology. This project advances NSF’s priorities in Artificial Intelligence. 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: 2622152 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Kiona Ogle | Institution: Northern Arizona University, FLAGSTAFF, AZ | Award Amount: $1,057,729 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2622152 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2622152.html