Extracting exotic annual grass phenology and climate relations in western U.S. rangeland ecoregions

Biological Invasions
By: , and 



This research builds upon the extensive body of work to model exotic annual grass (EAG) characteristics and invasion. EAGs increase wildland fire risk and intensifies wildland fire behavior in western U.S. rangelands. Therefore, understanding characteristics of EAG growth increases understanding of its dynamics and can inform rangeland management decisions. To better understand EAG phenology and spatial distribution, monthly weather (precipitation, minimum and maximum temperature) variables were analyzed for 24 level III ecoregions. This research characterizes EAGs’ phenology identified by a normalized difference vegetation index (NDVI) threshold-based interpolation technique. An EAG phenology metric model was used to estimate a growing season dynamic for the years 2017–2021 for shrub and herbaceous land cover types in the western conterminous United States (66% of the area). The EAG phenology metrics include six growing season metrics such as start of season time, end of season time, and time of maximum NDVI during the growing season. The models’ cross validation results for Pearson’s r ranged from 0.88 to 0.95. Increased understanding of the effects that weather conditions have on EAG growth and spatial distribution can help land managers develop time-sensitive plans to protect entities deemed valuable to society like native habitat, wildlife, recreational areas, and air quality.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Extracting exotic annual grass phenology and climate relations in western U.S. rangeland ecoregions
Series title Biological Invasions
DOI 10.1007/s10530-023-03021-7
Volume 25
Issue 6
Year Published 2023
Language English
Publisher Springer
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 19 p.
First page 2023
Last page 2041
Country United States
Other Geospatial western rangeland ecoregions
Google Analytic Metrics Metrics page
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