This dataset consists of phenology observations of red brome (Bromus rubens) and cheatgrass (Bromus tectorum) collected at long-term monitoring sites and using daily timelapse camera imagery in the western United States. These observations include the location and day of year that flowering or senescence was observed per species. For timelapse camera images, 'flowering' observations denote the date that 75% of individual plants in the camera viewshed had open, mature flowers, and 'senescence' observations denote dates when 75% of individuals in the camera viewshed exhibited color change of leaves.

Cheatgrass (Bromus tectorum) cover data were derived from the Bureau of Land Management’s Assessment Inventory, and Monitoring data and paired with geospatial data representing climate, weather, and disturbances. We derived covariates to capture both the climatic averages (1981-2010) that underlie long-term suitability, hereafter referred to as climate, and conditions during the year of observation, hereafter referred to as weather, that can drive annual variation in invasive grass cover (e.g., fall germination conditions were matched to cheatgrass cover sampled the following spring). Custom variables reflected cheatgrass natural history. Covariates describing geological context (e.g., aspect, elevation, soils), plant communities based on geophysical conditions and natural disturbance regimes, fire history (binary burned or unburned), human disturbance and infrastructure, and management history were used to represent processes that may limit or facilitate cheatgrass invasion

Cheatgrass (Bromus tectorum) cover data were derived from the Bureau of Land Management’s Assessment Inventory, and Monitoring data and paired with geospatial data representing climate, weather, and disturbances. We derived covariates to capture both the climatic averages (1981-2010) that underlie long-term suitability, hereafter referred to as climate, and conditions during the year of observation, hereafter referred to as weather, that can drive annual variation in invasive grass cover (e.g., fall germination conditions were matched to cheatgrass cover sampled the following spring). Custom variables reflected cheatgrass natural history. Covariates describing geological context (e.g., aspect, elevation, soils), plant communities based on geophysical conditions and natural disturbance regimes, fire history (binary burned or unburned), human disturbance and infrastructure, and management history were used to represent processes that may limit or facilitate cheatgrass invasion

This dataset provides a near-real-time estimate of 2018 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 July 1, 2018. This is the second iteration of an early estimate of herbaceous annual cover for 2018 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/P9KSR9Z4). The pixel values for this most recent estimate ranged from 0 to100% with an overall mean value of 9.23% and a standard deviation of +/-11.35. The model's test mean error rate (n = 1664), based on nine different randomizations, equaled 5.2% with a standard deviation of +/- 0.09. Overall statistics between the May and June datasets were similar. However, some individual pixel differences can be considerable and are attributed to changing conditions on the ground that are reflected in the satellite data. These changes can influence how the models relate the dependent variable to the independent variables. Both datasets were generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied a mask to areas above 2250-m elevation because annual grasses are unlikely to exist at substantial cover above this threshold. To target likely sagebrush ecosystems, the mask also covered pixels classified as something other than shrub or grassland/herbaceous by the 2011 National Land Cover Dataset (NLCD). The model was not trained on any masked pixels. Cheatgrass (Bromus tectorum) is the most common annual grass in the study area, but red brome (Bromus rubens), medusahead (Taeniatherum caput-medusae), and ventenata (Ventenata dubia) are also problematic. They grow from seed, usually in spring, mature quickly, produce seed, and die. After dying, these annual grasses contribute fine fuels that facilitate fire ignition and spread throughout sagebrush ecosystems. These fires remove sagebrush stands. Increasing fire frequencies, land management practices, and development have all contributed to the fragmentation of the once expansive sagebrush ecosystems. These ecosystems are critical for water quality, reduced fire threats, and the survival of sagebrush-dependent wildlife.

This dataset provides a near-real-time estimate of 2018 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 July 1, 2018. This is the second iteration of an early estimate of herbaceous annual cover for 2018 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/P9KSR9Z4). The pixel values for this most recent estimate ranged from 0 to100% with an overall mean value of 9.23% and a standard deviation of +/-11.35. The model's test mean error rate (n = 1664), based on nine different randomizations, equaled 5.2% with a standard deviation of +/- 0.09. Overall statistics between the May and June datasets were similar. However, some individual pixel differences can be considerable and are attributed to changing conditions on the ground that are reflected in the satellite data. These changes can influence how the models relate the dependent variable to the independent variables. Both datasets were generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied a mask to areas above 2250-m elevation because annual grasses are unlikely to exist at substantial cover above this threshold. To target likely sagebrush ecosystems, the mask also covered pixels classified as something other than shrub or grassland/herbaceous by the 2011 National Land Cover Dataset (NLCD). The model was not trained on any masked pixels. Cheatgrass (Bromus tectorum) is the most common annual grass in the study area, but red brome (Bromus rubens), medusahead (Taeniatherum caput-medusae), and ventenata (Ventenata dubia) are also problematic. They grow from seed, usually in spring, mature quickly, produce seed, and die. After dying, these annual grasses contribute fine fuels that facilitate fire ignition and spread throughout sagebrush ecosystems. These fires remove sagebrush stands. Increasing fire frequencies, land management practices, and development have all contributed to the fragmentation of the once expansive sagebrush ecosystems. These ecosystems are critical for water quality, reduced fire threats, and the survival of sagebrush-dependent wildlife.

We conducted a case studies testing effectiveness of a soil borne bacteria, Pseudomonas fluorescens strain D7, in controlling Bromus tectorum (cheatgrass) and in affecting the density of sown desirable seedlings. Response variables (foliar cover, aboveground biomass, and density of B. tectorum; density of sown native plants) were measured for three years after treatment.

We conducted a case studies testing effectiveness of a soil borne bacteria, Pseudomonas fluorescens strain D7, in controlling Bromus tectorum (cheatgrass) and in affecting the density of sown desirable seedlings. Response variables (foliar cover, aboveground biomass, and density of B. tectorum; density of sown native plants) were measured for three years after treatment.

Invasive annual grasses (IAGs) present a persistent challenge for the ecological management of rangelands, particularly the imperiled sagebrush biome in western North America. Cheatgrass (Bromus tectorum), medusahead (Taeniatherum caput-medusae), and Ventenata spp. are spreading across sagebrush rangelands and already occupy at least 200,000 kilometers squared (km sq.) of the intermountain west. The loss and degradation of native plant communities caused by IAGs threatens the persistence of sagebrush obligate species such as the Greater Sage-grouse (Centrocercus urophasianus) and pygmy rabbit (Brachylagus idahoensis). IAGs convert sagebrush landscapes to monocultures of non-native grasslands that substantially increase the risk of wildfire and degrade important ecosystem services including forage production and quality, soil stability, and carbon sequestration. As a result, the economic consequences of IAGs are substantial. Successful management of IAG invasions depends on extensive and accurate geospatial data that is accessible and interpretable by those charged with managing landscapes across the sagebrush biome. The past decade has seen a rapid growth in these products, yet researchers and managers both report a persistent research-implementation gap between the availability of products and their application. To address this problem, we first conducted a systematic literature review to inventory spatial products released over the past decade that map cheatgrass, medusahead, and Ventenata within the western U.S. at regional and national scales. We then developed a series of informational data resources to guide land managers in understanding and selecting the best available spatial data for their management needs. This Excel-readable .xlsx file version database product represents a searchable, filterable, and sortable collection of summary information for each IAG spatial data product, published from January 2010 to February 2021, we summarized as part of our review. An additional, machine-readable .csv file version of the database is also available for users.

Invasive annual grasses (IAGs) present a persistent challenge for the ecological management of rangelands, particularly the imperiled sagebrush biome in western North America. Cheatgrass (Bromus tectorum), medusahead (Taeniatherum caput-medusae), and Ventenata spp. are spreading across sagebrush rangelands and already occupy at least 200,000 kilometers squared (km sq.) of the intermountain west. The loss and degradation of native plant communities caused by IAGs threatens the persistence of sagebrush obligate species such as the Greater Sage-grouse (Centrocercus urophasianus) and pygmy rabbit (Brachylagus idahoensis). IAGs convert sagebrush landscapes to monocultures of non-native grasslands that substantially increase the risk of wildfire and degrade important ecosystem services including forage production and quality, soil stability, and carbon sequestration. As a result, the economic consequences of IAGs are substantial. Successful management of IAG invasions depends on extensive and accurate geospatial data that is accessible and interpretable by those charged with managing landscapes across the sagebrush biome. The past decade has seen a rapid growth in these products, yet researchers and managers both report a persistent research-implementation gap between the availability of products and their application. To address this problem, we first conducted a systematic literature review to inventory spatial products released over the past decade that map cheatgrass, medusahead, and Ventenata within the western U.S. at regional and national scales. We then developed a series of informational data resources to guide land managers in understanding and selecting the best available spatial data for their management needs. This Excel-readable .xlsx file version database product represents a searchable, filterable, and sortable collection of summary information for each IAG spatial data product, published from January 2010 to February 2021, we summarized as part of our review. An additional, machine-readable .csv file version of the database is also available for users.

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% with an overall mean value of 8.24% and a standard deviation of +/-9.39. The model's test mean error rate (n = 1664), based on nine different randomizations, equaled 5.2% with a standard deviation of +/- 0.09. Overall statistics between the May and June datasets were similar. However, some individual pixel differences can be considerable and are attributed to changing conditions on the ground that are reflected in the satellite data. These changes can influence how the models relate the dependent variable to the independent variables. Both datasets were generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied a mask to areas above 2250-m elevation because annual grasses are unlikely to exist at substantial cover above this threshold. To target likely sagebrush ecosystems, the mask also covered pixels classified as something other than shrub or grassland/herbaceous by the 2011 National Land Cover Dataset (NLCD). The model was not trained on any masked pixels. Cheatgrass (Bromus tectorum) is the most common annual grass in the study area, but red brome (Bromus rubens), medusahead (Taeniatherum caput-medusae), and ventenata (Ventenata dubia) are also problematic. They grow from seed, usually in spring, mature quickly, produce seed, and die. After dying, these annual grasses contribute fine fuels that facilitate fire ignition and spread throughout sagebrush ecosystems. These fires remove sagebrush stands. Increasing fire frequencies, land management practices, and development have all contributed to the fragmentation of the once expansive sagebrush ecosystems. These ecosystems are critical for water quality, reduced fire threats, and the survival of sagebrush-dependent wildlife