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Predictions of raven occurrence in the absence of anthropogenic environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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This dataset provides spatial predictions of habitat suitability for current (1950 – 2000 yr) and mid-Holocene (8.3 ka – 4.2 ka) intervals using hindcasting, and three separate paleo-distributions calibrated on the packrat midden archive: those without bias correction (naïve), those created with a standard method (standard), and those created with a novel alternative (modeled) incorporating a three-stage model of bias. The raster layers contained here accompany the manuscript Inman et al. 2018 and were used to evaluate utility of a novel bias correction method (modeled) over classic methods. Spatial predictions of habitat suitability were created using MaxEnt version 3.4.0 (Phillips et al., 2006), a widely-used...
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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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Predictions of raven occurrence in the absence of natural environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
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As part of a 2018 Northwest Climate Adaptation and Science Center project, USGS researchers are releasing a series of spatially-explicit land-cover projections for the period 2018-2050 covering part of the northern Great Basin (Beaty Butte Herd Management Area, Hart Mountain National Antelope Refuge, and Sheldon National Refuge). The dataset contains an empirically-based business-as-usual (BAU) and an RCP8.5 climate change scenario executed for shrub, herbaceous, and bare cover types. Each scenario is executed 30 times (i.e. Monte Carlo simulations) to account for variability across historical change estimates derived from annual fractional cover maps generated by the National Land Cover Database. The map dates...
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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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Disclaimer: Data release is currenlty under revision 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...
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Western U.S. rangelands have been quantified as six fractional cover (0-100%) components over the Landsat archive (1985-2018) at 30-m resolution, termed the “Back-in-Time” (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. We leverage field data observed concurrently with HRS imagery over multiple years and locations in the Western U.S. to dramatically expand the spatial extent and sample size of validation analysis relative to a direct comparison to field observations and to previous work. We compare HRS and BIT data in the corresponding space and time. Our objectives were to evaluate the temporal and spatio-temporal relationships between HRS and BIT data, and to compare...
This presentation aired as part of the Great Basin LCC webinar series on November 29, 2017. The presentation was given by Bruce Roundy of Brigham Young University.In this webinar, Dr. Bruce Roundy of Brigham Young University discusses climatic conditions that favor cheatgrass and those that favor desirable perennial herbs. He explains why conditions that favor cheatgrass are associated with less resistance and those that favor perennial herbs are associated with more resilience. The presentation suggests ways to increase resistance to weeds and system resilience when planning fuel control treatments in sagebrush steppe.
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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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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To map the baseline distribution of riparian forest and shrublands, we all included LANDFIRE Existing Vegetation Types (EVT) where the type contained the word "riparian", "woodland", "ravine" and "swamp". We also included aspen woodlands at elevations below 1524 m using ReGAP values, as these areas, upon inspection were found to be introduced vegetation and not aspen. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness,...
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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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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A hierarchical occupancy model adapted from Royle & Dorazio (2008) and Rota et al. (2011) for use in R. References: Royle, J.A. and Dorazio, R.M., 2008. Hierarchical modeling and inference in ecology: the analysis of data from populations, metapopulations and communities. Academic Press. doi:10.1016/B978-0-12-374097-7.50001-5 J. Andrew Royle, Robert M. Dorazio, Rota, C. T., Fletcher Jr, R. J., Dorazio, R. M. and Betts, M. G. (2009), Occupancy estimation and the closure assumption. Journal of Applied Ecology, 46: 1173-1181. doi:10.1111/j.1365-2664.2009.01734.x
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This file represents the final version of an assessment of the extent, condition, and distribution of grassland types in Arizona as indicated by expert interviews and field verification. Coverage includes the state of Arizona, Southwestern portions of the state of New Mexico, and the Northern portion of Sonora, Mexico.
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The Desert Landscape Conservation Cooperative (LCC) is a partnership formed and directed by resource management entities as well as interested public and private entities in the Mojave, Sonoran, and Chihuahuan Desert and montane sky island regions of the southwestern United States and northern Mexico. Desert LCC science depends on access to transboundary base datasets. Given the importance of vegetation such as grasslands and riparian vegetation in conservation science, a bi-national, landscape-scale vegetation data layer with classes relevant to Desert LCC research is crucial. One objective of this project is to investigate appropriate methodologies and landscape scales to create a Desert LCC binational land cover...
Categories: Data, Project; Tags: 2014, AZ-01, AZ-02, AZ-03, AZ-04, All tags...
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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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
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...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...


map background search result map search result map Arizona grasslands Desert LCC Land Cover Map Pilot Project Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Hierarchical Occupancy Model Code for R and Accompanying Files Spatial predictions of habitat suitability for present-day (1950 – 2000 yr) and mid-Holocene (8.3 ka – 4.2 ka) time intervals BLM REA WYB 2011 Ch10 Riparian Temporal and Spatio-Temporal High-Resolution Satellite Data for the Validation of a Landsat Time-Series of Fractional Component Cover Across Western United States (U.S.) Rangelands Spatially-explicit land-cover scenarios of federal lands in the northern Great Basin: 2018-2050 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Annual Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Bare Ground Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Litter Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Sagebrush Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Shrub Products for the Western U.S., 1985 - 2018 National Land Cover Database (NLCD) 2016 Shrubland Fractional Components for the Western U.S. (Under Revision) Spatially-explicit land-cover scenarios of federal lands in the northern Great Basin: 2018-2050 Arizona grasslands Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Temporal and Spatio-Temporal High-Resolution Satellite Data for the Validation of a Landsat Time-Series of Fractional Component Cover Across Western United States (U.S.) Rangelands Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Hierarchical Occupancy Model Code for R and Accompanying Files Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) BLM REA WYB 2011 Ch10 Riparian Desert LCC Land Cover Map Pilot Project Spatial predictions of habitat suitability for present-day (1950 – 2000 yr) and mid-Holocene (8.3 ka – 4.2 ka) time intervals Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Annual Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Bare Ground Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Litter Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Sagebrush Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Shrub Products for the Western U.S., 1985 - 2018 National Land Cover Database (NLCD) 2016 Shrubland Fractional Components for the Western U.S. (Under Revision)