Ty Nietupski1, Becky Kerns1,2, Hailemariam Temesgen1 and Robert Kennedy3
1Oregon State University, College of Forestry, 280 Peavy Hall, Corvallis, OR, 97331, USA
2USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR, USA
3Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, OR, USA
Many non-native plant species have been introduced to the semi-arid landscape of the United States’ interior Pacific Northwest. However, some of the greatest ecological and economic impacts have resulted from exotic annual grass introduction. Cheatgrass (Bromus tectorum), an invasive annual grass, has been extensively studied and documented for its disturbance regime altering impacts, especially in sagebrush steppe ecosystems. However, other exotic annual grasses have been introduced to the region and have become abundant across the landscape. One such species is ventenata (Ventenata dubia). This species was first documented in eastern Washington in the 1950’s and has subsequently spread throughout much of the western United States. Once thought of as a purely agricultural pest, ventenata has become recognized by land managers for its potential to colonize openings between forested areas, resulting in a more continuous and abundant fuel distribution. Concern has developed that changes to fire behavior, similar to those for cheatgrass, may occur. Land managers need spatially explicit information about populations of ventenata to address the effects of the invasion and its potential to change the landscape.
In the recent past, remote sensing products have been successfully used to identify and locate invasive plants across broad areas. Landscape phenology has been employed with remote sensing data to distinguish exotic species from native plants in some ecosystems. Sensors like MODIS have commonly been used for mapping invasive plant populations because of their high temporal resolution that allows for phenological characterization. However, the spatial resolution (250–1000 meters) of this sensor means that individual populations must be abundant in large patches in order to be identified. Another sensor commonly used to study similar land surface properties is Landsat, but the temporal resolution (16-day revisit) of this product is inadequate for capturing the annual phenological pattern. To help characterize phenological patterns at a 30-meter spatial resolution, we used spatio-temporal data fusion to generate a dense time series of observations of land surface reflectance. This data was used to extract phenological metrics for each pixel in the Blue Mountains Ecoregion of the interior Pacific Northwest. Using this information, along with other biophysical parameters, we modeled the presence and absence of ventenata across the region. In cases with adequate abundance, preliminary results showed that ventenata exhibited a unique phenological pattern when compared to other land cover types in the region, and incorporating phenological information resulted in improved model performance. The results of this project can be used to help land managers to plan for fire activity across this landscape in places where fine fuel biomass has increased in abundance or continuity as a result of this grass invasion.