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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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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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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...
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Expanding human enterprise across remote environments impacts many wildlife species, including sage-grouse (Centrocercus urophasianus), an indicator species whose decline is at the center of national conservation strategies and land use policies. Anthropogenic resources provide subsidies for generalist predators, potentially leading to cascading effects on sensitive prey species at lower trophic levels. In semi-arid western ecosystems, common ravens (Corvus corax) are expanding in distribution and abundance, and may be negatively affecting sage-grouse reproductive success at broad spatial scales. Ravens are a common predator of sage-grouse nests, and potentially prey on chicks as well. This research aimed to address...
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 RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Categories: Data; 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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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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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, All tags...
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Predictions of an anthropogenic influence on raven occurrence index intersected with sage-grouse concentration areas. The anthropogenic influence index indicates where resource subsidies are contributing the most to raven occurrence.
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Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the mean of the predicted posterior distribution for raven occurrence was used to visualize results.
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An index of anthropogenic influences on raven populations. 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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FY2014Avoiding cheatgrass dominance following tree-reduction treatments on woodland-encroached sagebrush communities is a priority for managers in the Great Basin. Perennial herbaceous and weedy annual cover have been related to site resilience after treatment and associated with soil climate regimes and site physical characteristics. Additional investigation of site characteristics associated with vegetation response will allow us to better decide which sites to treat and whether seeding is needed or not in conjunction with tree reduction treatments. Site-level planning also requires an understanding of how climate change may influence vegetation response to treatments. We propose to associate site-measured soil...


    map background search result map search result map Desert LCC Land Cover Map Pilot Project Using Soil Climate and Geospatial Environmental Characteristics to Determine Plant Community Resilience to Fire and Fire Surrogate Treatments Data from: Broad-scale occurrence of a subsidized avian predator: reducing impacts of ravens on sage-grouse and other sensitive prey Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Predicted probability of raven occurrence across the Great Basin, USA, 2007 – 2016 (Fig. 3) 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) Anthropogenic influence index for raven populations in the Great Basin, 2007-2016 (Fig. 4C) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Anthropogenic influence on raven occurrence index within sage-grouse concentration areas in the Great Basin, 2007-2016 (Fig. 5B) Hierarchical Occupancy Model Code for R and Accompanying Files National Land Cover Database (NLCD) 2016 Shrubland Fractional Components for the Western U.S. (ver. 3.0, July 2020) 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 Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020 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) Anthropogenic influence on raven occurrence index within sage-grouse concentration areas in the Great Basin, 2007-2016 (Fig. 5B) Using Soil Climate and Geospatial Environmental Characteristics to Determine Plant Community Resilience to Fire and Fire Surrogate Treatments Hierarchical Occupancy Model Code for R and Accompanying Files Predicted probability of raven occurrence across the Great Basin, USA, 2007 – 2016 (Fig. 3) Data from: Broad-scale occurrence of a subsidized avian predator: reducing impacts of ravens on sage-grouse and other sensitive prey 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) Anthropogenic influence index for raven populations in the Great Basin, 2007-2016 (Fig. 4C) Desert LCC Land Cover Map Pilot Project National Land Cover Database (NLCD) 2016 Shrubland Fractional Components for the Western U.S. (ver. 3.0, July 2020) Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2020