Folders: ROOT > ScienceBase Catalog > Invasive Annual Grasses ( Show direct descendants )
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Description: This product is a continuous surface of herbaceous (annual and perennial, forbs and grasses) percent cover. Species: All herbaceous species Spatial extent: Great Basin and Southwest United States; all or part of 14 states. Spatial resolution: 30-m pixels Recentness: 2020; Model is updated three times a year (spring, summer, and fall). Author-suggested use: The need to address seasonal variations of fine fuels (herbaceous and shrubs) in the Great Basin Southwest U.S. was made apparent by fire and fuels specialists at LANDFIRE “After Action Reviews” and various other meetings. The notion that increases in winter and spring precipitation in these areas increases herbaceous production and...
Tags: SageDAT-data
We mapped eleven years of cheatgrass dieoff in the northern Great Basin. If we estimated that a dieoff occurred in a pixel anytime during that eleven year period, then the pixel was coded as dieoff. If no dieoff occurred, the pixel was coded as a non dieoff. The cheatgrass dieoff probability map was produced by inputting the coded data into a decision-tree model along with topographic data, edaphic data, land cover data, and climate data. A proxy for latitude was included. The resulting model was input into a mapping application that generated a map of cheatgrass dieoff probability.
Description: This product represents the predicted distribution of invasive annual grasses; in five cover classes (trace–5%, 5–15%, 25–45%, 25–45%, >45%). Species: Introduced annual grasses Spatial extent: Cold desert eco-regions of the western United States including: Eastern Cascades slopes and foothills, Blue Mountains, Columbian Plateau, Northern Basin and Range, Wyoming Basin, Central Basin and Range, Colorado Plateaus, and Snake River Plain. Spatial resolution: 90-m pixels Recentness: 2016 Author-suggested use: The spatial output layers are meant to assist with rangeland restoration and decisions involving placement of infrastructure and vegetation treatments where further surface disturbance...
Tags: SageDAT-data
We developed habitat suitability models for invasive plant species selected by Department of Interior land management agencies. We applied the modeling workflow developed in Young et al. 2020 to species not included in the original case studies. Our methodology balanced trade-offs between developing highly customized models for a few species versus fitting non-specific and generic models for numerous species. We developed a national library of environmental variables known to physiologically limit plant distributions and relied on human input based on natural history knowledge to further narrow the variable set for each species before developing habitat suitability models. We developed models using five algorithms...
Tags: SageDAT-data
Description: This product is a continuous estimate of 16-day and annual above ground annual herbaceous biomass (lbs/acre) with values ranging from 0-4511. Species: Annual herbaceous species Spatial extent: The western United States Spatial resolution: 30-m pixels Recentness: 2019, annual products available 1986-2019 Author-suggested use: The methods and data presented provide a means to understand the finer scale phenological and productivity dynamics of rangelands that are missed when using single, pixel-level estimates. Understanding this heterogeneity across space and through time is critical for rangeland conservation and management actions, for example creating grazing plans and strategies,...
Tags: SageDAT-data
Description: This product is a continuous estimate of annual herbaceous cover. Species: Annual herbaceous species Spatial extent: The western United States Spatial resolution: 30-m pixels Recentness: 2019, annual products available 1984-2019 Author-suggested use: This product will allow managers, researchers, policy makers and planners to evaluate the outcomes of past management efforts and plan future efforts accordingly.
Tags: SageDAT-data
Probability map of cheatgrass (Bromus tectorum) occurrence in relation to vegetation, abiotic and anthropogenic features.
Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic annual grass cover and dynamics over large areas requires the use of remote sensing that can support early detection and rapid response initiatives. Here, we integrated in situ observations, weekly composites of harmonized Landsat and Sentinel-2 (HLS) data, maps of biophysical variables (e.g. soils and topography) and machine learning techniques to develop fractional estimates of exotic annual grass cover at a 30-m spatial resolution from 2016 to 2018....
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Description: This product is a continuous sum of % cover estimates for all species identified as exotic annual grass. Species: Invasive annual grasses Spatial extent: The majority of sage-steppe vegetation in southeastern Oregon. Spatial resolution: 30-m pixels Recentness: 2012–2017 (single estimate of condition) Author-suggested use: This work was conducted while building an imputed vegetation map to support greater sage-grouse (GRSG) conservation efforts in the state of Oregon. It is unique in that it provides detailed habitat information that is relevant to seasonal habitats in a spatially consistent way across the full range of GRSG in Oregon. Their analysis shows how aggregations of threshold‐defined...
Tags: SageDAT-data
Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are unknown. While a number of studies have projected the impacts of climate change using several modeling approaches, none has evaluated impacts to fractional component cover at a 30-m resolution across the full sagebrush (Artemisia spp.) biome. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2018 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate...
Data are cross-listed on https://rangelands.app/cheatgrass/ Cheatgrass (Bromus tectorum) and other invasive annual grasses represent one of the single largest threats to the health and resilience of western rangelands. To address this challenge, the Western Governors Association (WGA)-appointed Western Invasive Species Council convened a cheatgrass working group to develop a new regional vision for invasive annual grass management across the West. Foundational to implementing this new vision is the creation of a common spatial map to guide strategic actions. The WGA cheatgrass working group sought to develop a 30-m base map of annual herbaceous cover to support a common spatial strategy for tackling invasive annual...
Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution...
Categories: Data,
Data Release - Revised;
Tags: AZ,
Arizona,
Arizona Plateau,
Black Hills,
Blue Mountains,
Description: This product is a continuous surface of predicted % cover cheatgrass, converted to occurrence of high cheatgrass (>15%) cover (categorical). Species: Cheatgrass (Bromus tectorum) Spatial extent: The hydrographic Great Basin; https://nhd.usgs.gov/ Spatial resolution: 250-m pixels Recentness: 2001–2016 (single average estimate of condition) Author-suggested use: A more rigorous field testing and training dataset was used compared to previous works. The relationship between percent cover of cheatgrass and fire frequency and seasonality, along with links to anthropogenic ignition sources, was assessed over a broader region than had previously developed models.
Tags: SageDAT-data
This dataset provides a near-real-time estimate of 2019 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through June 24, 2019. This is the second iteration of an early estimate of herbaceous annual cover for 2019 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through April 28, 2019 (https://doi.org/10.5066/P9ZEK5M1). The pixel values for this most recent estimate ranged from 0 to100%...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Bromus rubens,
Bromus tectorum,
California,
Colorado,
Desert,
We integrated 250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) with land cover, biogeophysical (e.g., soils, topography) and climate data into regression-tree software (Cubist®). We integrated this data to create a time series of spatially explicit predictions of herbaceous annual vegetation cover in sagebrush ecosystems, with an emphasis on annual grasses. Annual grass cover in sagebrush ecosystems is highly variable year-to-year because it is strongly dependent on highly variable weather patterns, particularly precipitation timing and totals. Annual grass cover also reflects past disturbances and management decisions. We produced 17 consecutive...
Description: This product is a categorical surface of existing vegetation type (EVT). For the purpose of identifying invasive annual grasses we suggest focusing on the following vegetation types: Great Basin & Intermountain Introduced Annual Grassland and Great Basin & Intermountain Ruderal Shrubland. Descriptions of EVT ruderal classes can be found at: https://www.landfire.gov/documents/LANDFIRE_Ruderal_NVC_Groups_Descriptions_CONUS.pdf Species: Annual herbaceous species Spatial extent: Great Basin and Southwest United States Spatial resolution: 30-m pixels Recentness: 2016 Author-suggested use: These data products have been used to model the potential impacts of fire on the landscape, the wildfire...
Tags: SageDAT-data
Description: This product is a continuous estimate of the probability of medusahead occurrence. Species: Medusahead (Taeniatherum caput-medusae) Spatial extent: The western United States; six-level II EPA ecoregions in the arid and semi-arid western United States. Spatial resolution: ~94-m (3-arc-second) pixels Recentness: 2020 Author-suggested use: These model outputs are intended as a resource for prioritizing monitoring and management at moderate to broad spatial scales (e.g. subwatershed) in conjunction with local knowledge and field verification. Predictions of species presence outside the model training areas represent hypotheses for where the species may occur next.
Tags: SageDAT-data
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