Exotic Annual Grass (EAG) Phenology estimates for Western U.S. Rangelands based on 30-m HLS for 2017 - 2025

Monitoring plant life stages (i.e., phenology) is pertinent to land management as phenological dynamics reflect the vegetation response to changes in weather and disturbance and to changes in vegetation composition. Exotic Annual Grass (EAG) invasion has threatened habitats and economies across the western U.S. The phenology of EAG species, such as cheatgrass, differs from native perennial grasses and shrubs. Understanding EAG phenology helps managers to better temporally target treatment efforts and potentially signal early invasion when treatments are likely to be more effective. Our objective is to model the phenology of just EAG species, separate from the phenology of any co-occurring vegetation. Datasets from 2017 to 2025 were developed using 2017-2024 AIM plots and additional training data selected from sites with at least 20% mapped EAG cover from Benedict et al. (2023) interpreted training data. Phenology metrices were mapped using 30-m Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2025 (Dahal et al., 2022). Metrics were processed using these 2 steps: (1) Training data selection and phenometric calculation and (2) Modeling, mapping, and post-processing. The EAG phenology model produced four critical temporal metrics; Start of Season Time (SOST), End of Season Time (EOST), and Maximum Time (MAXT), and Duration (DUR) based on identifying the sustained growth characteristics of 15 EAG species throughout the western U.S. rangeland for 2017 to 2025.