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ARS Home » Pacific West Area » Burns, Oregon » Range and Meadow Forage Management Research » Research » Research Project #435374

Research Project: Predicting Wildfire and Wildfire Effects on Great Basin Rangelands

Location: Range and Meadow Forage Management Research

Project Number: 2070-21630-003-009-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 1, 2018
End Date: Aug 31, 2023

Rangeland ecosystem dysfunction associated with increased wildfire activity, invasive annual grasses, and expanding conifers is negatively impacting agricultural production and a variety of ecosystem services across the western United States. These factors have severe economic implications; for example, federal fire suppression expenditures in FY 2017 approached $3 billion. The increasing frequency of wildfires across western rangelands remains a threat to ecosystem structure and function. In Great Basin rangelands, wildfire often creates a positive feedback by increasing invasive annuals and altering fuel loading. Understanding the dynamics of the plant community–both in response to wildfire and its role in wildfire occurrence–is critical to guide rangeland management in the face of fire, fuels, and invasive plants. At large spatial scales, existing fuel modeling efforts have shown that antecedent precipitation amount and pattern can be used to generalize wildfire probability. Missing from those efforts has been the incorporation of biotic status (e.g., plant community composition and functional group abundance) into predictive models. Incorporating current biotic information has the potential to dramatically improve the relevancy of empirically-derived models to on-the-ground management conditions and decision making. The objectives of this work are to 1) examine the biotic drivers of and responses to wildfire; and 2) examine the potential for incorporating biotic components into abiotically-driven (e.g., precipitation at various time lags) models for predicting wildfire and plant community responses. Objectives will apply across the Great Basin region.

Significant advances in big data and remote sensing analyses have increased the ability to monitor rangelands at multiple scales. Utilizing the latest machine learning technology, we are able to combine thousands of ground-based vegetation measurements with decades of satellite imagery and climate data and other abiotic variables to produce annual, moderate resolution (30m) maps of rangeland functional group cover (0-100%) from 1984 to present. Such an advancement creates the ability to analyze and monitor rangelands at pasture, landscape, and regional scales; plan management and conservation strategies; and evaluate management and conservation outcomes through time. Research will involve multi-scale geospatial analysis of Great Basin wildfires. The continuous rangeland functional group maps permit the examination of wildfires and their associated plant community dynamics beginning in 1984 and continuing to present. Specifically, the increase in invasive annuals across the Great Basin will be investigated, as well as their historical contribution to wildfires via fuel loading.