Filters: partyWithName: Michael C Duniway (X)
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A raster dataset representing multi-year mean (1998-2018) capacity factors (CF) for a solar photovoltaic system based on current technology, for the Conterminous United States. These data are calculated using ½ hourly irradiance values from the National Solar Radiation Database (NSRDB) Sengupta et al. (2018), and the Systems Advisor Model (Blair et al. 2014). Cell values represent the estimated capacity factor (a ratio of net generation to the maximum generation) for photovoltaic energy production for a 1-axis tracking system (technology details found in Maclaurin et al. 2019). The continuous raster were put into 8 quantile bins for interpretation and reporting. For more information and further data, please visit...
A raster dataset representing the soil organic carbon content of surface soil horizons (top 15 cm or ~6 inches) in the conterminous United States. Soil organic carbon is a readily component of soil organic matter, which plays an important role the functioning of soils, including formation of soil structure, soil nutrient content, soil moisture retention, and carbon sequestration. Soil carbon content here is measured as percent by mass. This dataset was created using the soil percent organic carbon 100 m spatial resolution predictive rasters for 0, 5, and 15 cm depths developed by Ramcharan et al. (2018). The average soil organic carbon over the top 15 cm was calculated using the trapezoidal rule, and then put into...
These data were compiled to assess the recovery of vegetation on reclaimed oil and gas sites. Objective(s) of our study were to assess patterns in reclamation outcomes relative to 1) soil attributes, climate, and time since 39 reclamation and 2) plant and soil reference benchmarks. These data represent observations of vegetation and soil cover from 134 reclaimed oil and gas well pads and 583 AIM reference plots. These data were collected on lands impacted by oil and gas development on the Colorado Plateau as well as Arizona and New Mexico Plateau of New Mexico, Colorado, and Utah. Data was collected from July- September of 2020 and May-September of 2021. These data were collected by Assessment Inventory and Monitoring...
Categories: Data;
Tags: AIM reference plots,
Arizona and New Mexico Plateau,
Assessment Inventory and Monitoring (AIM),
Botany,
Colorado,
Knowledge of where energy resources occur and where there is existing development or new development potential, in conjunction with model-predicted golden eagle relative nest site density (Dunk et al. 2019), can be used to identify areas with higher or lower potential resource conflict. Depicted on the map is a 16-class raster that displays the spatial overlap of wind resources (4 classes, low to high) and golden eagle relative nest site density (4 classes, lower to higher). This raster displays the intersection of multi-year mean capacity factors (MCF) for wind turbines and the golden eagle relative nest site density within ecoregion raster. We have divided each probability into equal intervals, and then intersected...
Soil fertility in deserts: A review on the influence of biological soil crusts and the effect of soil surface disturbance on nutrient inputs and losses, credited to Duniway, Michael C, published in 2003. Published in Desertification in the Third Millennium, on pages 245 - 252, in 2003.
Categories: Publication;
Types: Book Citation,
Citation;
Tags: Desertification in the Third Millennium,
Swets & Zeitlinger
Explore climate change impacts on vegetation across the Desert and Southern Rockies LCCs using historical monitoring data collected from 23 sites across the Sonoran, Chihuahuan, Mojave and Colorado Plateau deserts for 30-50 years. This data will then be combined with ecosystem water balance model simulations to establish features of water availability critical for plant species response. Results will allow managers to identify species and communities at risk under future climate scenarios based on predicted changes in plant water availability. Due to the high variability in soils, incorporating a detailed understanding of soil water availability beyond bioclimatic envelope approaches in the desert Southwest is essential...
Categories: Data,
Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2012,
AZ-02,
AZ-03,
AZ-04,
Academics & scientific researchers,
A raster dataset representing slope in the conterminous United States. This dataset was created from the radian slope raster of 100-meter spatial resolution developed by Ramcharan et al. (2018). Those data were derived from a conterminous 100-m Digital Elevation Model (DEM) for the United States (http://nationalmap.gov/) using SAGA GIS software. Slope values are put into 9 slope classes to facilitate interpretation and reporting. Ramcharan, A., Hengl, T., Nauman, T., Brungard, C., Waltman, S., Wills, S., and Thompson, J., 2018, Soil Property and Class Maps of the Conterminous United States at 100-Meter Spatial Resolution: Soil Science Society of America Journal, v. 82, p. 186-201. http://dx.doi.org/10.2136/sssaj2017.04.0122.
Increased variability in precipitation, including frequency of drought, is predicted for many arid and semiarid regions globally. The ability of soils to retain water can increase resilience by buffering vegetation communities against precipitation extremes. Little is known, however, about water retention by carbonate-cemented soil horizons, which occur extensively in arid and semiarid ecosystems. It has been speculated that they may significantly modify vertical and temporal distribution of plant-available water (PAW). To investigate this hypothesis, PAW was monitored at three sites in a mixed shrub-grass community in southern New Mexico, USA, across soils with differing degrees of carbonate horizon development:...
Categories: Publication;
Types: Citation,
Journal Citation;
Tags: Calcic,
Chihuahuan Desert,
Climate change,
Desert grassland,
Oecologia,
A raster dataset representing wind speed in km per hour at 100-meter height for the Conterminous United States, averaged from 2007 to 2013 using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution. Data from Draxl et al. (2015), and then put into 8 quantile bins for interpretation and reporting. For more information and further data, please visit https://maps.nrel.gov/. Draxl, C., Clifton, A., Hodge, B.-M., and McCaa, J., 2015, The Wind Integration National Dataset (WIND) Toolkit: Applied Energy, v. 151, p. 355-366. https://doi.org/10.1016/j.apenergy.2015.03.121.
A raster dataset representing multi-year mean (2007 to 2013) capacity factors (CF) for a 5.5 MW, 175 meter rotor-diameter, 120 meter hub-height wind turbine (turbine details are from Lopez at al. Forthcoming) for the Conterminous United States. The weather data are modeled using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution (Draxl et al. 2015). Cell values represent the estimated capacity factor (a ratio of net generation to the maximum generation) for wind energy turbine production using the Systems Advisor Model (Blair et al. 2014). The continuous raster were put into 8 quantile bins for interpretation and reporting. For more information...
This is a 16-class categorical raster that displays the intersection of oil and gas probability map from the work by Copeland et al. (2009) and the greater sage grouse breeding habitat probability raster. We have divided each probability into quartiles, and then intersected those two 4-class rasters to create a new raster that classifies most areas in the intermountain west into joined oil and gas development and greater sage grouse breeding habitat probability (0-25, 25-50, 50-75, and 75-100 % for both; 16 classes). Copeland, H.E., Doherty, K.E., Naugle, D.E., Pocewicz, A., and Kiesecker, J.M., 2009, Mapping oil and gas development potential in the US Intermountain West and estimating impacts to species: PloS...
Abstract: Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences...
Categories: Data,
Publication;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2012,
AZ-02,
AZ-03,
AZ-04,
Academics & scientific researchers,
A raster dataset representing the clay content of surface soil horizons (top 15 cm or ~6 inches) in the conterminous United States. Soil texture, which is described by the proportion of sand, silt, and clay in the non-rock portion of the soil (soil particles < 2mm), is an important determinate of plant suitability, water movement into the soil, erosion vulnerability, and many other things. Clays are the finest soil particle size class and includes soil particles less than 0.002 mm in diameter. This dataset was created using the percent clay 100-meter spatial resolution predictive rasters for 0, 5, and 15 cm depths developed by Ramcharan et al. (2018). The average percent clay over the top 15 cm was calculated using...
Knowledge of where energy resources occur and where there is existing development or new development potential, in conjunction with model-predicted golden eagle relative nest site density (Dunk et al. 2019), can be used to identify areas with higher or lower potential resource conflict. Depicted on the map is a 16-class raster that displays the spatial overlap of solar resources (4 classes, low to high) and golden eagle relative nest site density (4 classes, lower to higher). This raster displays the intersection of multi-year mean capacity factors (MCF) for solar photovoltaic systems and the golden eagle relative nest site density within ecoregion raster. We have divided each probability into equal intervals, and...
Across the western U.S., pinyon and juniper trees are expanding into sagebrush and grassland plant communities. This vegetation change has been perceived to have a significant impact on the economic value of these grasslands, which support activities such as livestock grazing and hunting, but expanding pinyon and juniper forests may also lead to increased risk of fire. Over the past several decades pinyon-juniper forests have been removed across large areas of land to improve wildlife habitat and grazing land productivity while reducing risks of wildland fire. What isn’t known is whether these strategies are effective in reaching this goal, especially given that our future climate will likely be hotter and drier...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2022,
CASC,
Data Visualization & Tools,
Data Visualization & Tools,
Forests,
This data release presents data used for analyzing spatial and temporal differences in soil surface roughness within selected biocrust communities. These records were collected by ground-based lidar for 121, 1m x 3m soil plots with biological soil crusts (biocrusts). Roughness was estimated from 5 mm resolution data (CloudCompare v. 2.10.2, 2019) for two Great Basin Desert sites (UTTR-1; UTTR-2) in December 2015 and one Chihuahuan Desert site (JER) in February 2016. Data were again collected in June 2018 for UTTR-1 and UTTR-2. Additional field and laboratory data were included within this study to understand differences in soil surface roughness between UTTR and JER as well as between the 2016 and 2018 surveys at...
A 4.5 km resolution raster dataset representing mean Global Horizontal Irradiance (GHI) in kWh (kilowatt-hours) per square-meter per day at each point in the National Solar Radiation Database (NSRDB) from 1998 to 2018 as calculated by Sengupta et al. (2018), and then put into 8 quantile bins for interpretation and reporting. For more information and further data, please visit https://maps.nrel.gov/. Sengupta, M., Xie, Y., Lopez, A., Habte, A., Maclaurin, G., and Shelby, J., 2018, The National Solar Radiation Data Base (NSRDB): Renewable and Sustainable Energy Reviews, v. 89, p. 51-60. https://doi.org/10.1016/j.rser.2018.03.003.
A raster dataset representing the sand content of surface soil horizons (top 15 cm or ~6 inches) in the conterminous United States. Soil texture, which is described by the proportion of sand, silt, and clay in the non-rock portion of the soil (soil particles < 2mm), is an important determinate of plant suitability, water movement into the soil, erosion vulnerability, and many other things. Sand includes soil particles between 0.05 and 2.0 mm in diameter. This dataset was created using the percent sand 100-meter spatial resolution predictive rasters for 0, 5, and 15 cm depths developed by Ramcharan et al. (2018). The average percent sand over the top 15 cm was calculated using the trapezoidal rule, and then put into...
This is a 16-class categorical raster that displays the intersection of multi-year mean capacity factors (CF) for wind (from the work by Blair et al. 2016 and Maclaurin et al. 2019) and the greater sage grouse breeding habitat probability raster (Doherty 2016). We have divided each probability into quartiles, and then intersected those two 4-class rasters to create a new raster that classifies most areas in the intermountain west into joined wind system development and greater sage grouse breeding habitat probability (<25, 25-50, 50-75, and >75% for both; 16 classes). For more information and further renewable data, please visit https://maps.nrel.gov/. The purpose of this dataset is to represent the matrix of wind...
This is a 16-class categorical raster that displays the intersection of multi-year mean capacity factors (MCF) for wind (Maclaurin et al. 2019) and the pygmy rabbit habitat probability raster (Smith et al. 2019). We have divided each source continuous raster into four classes, and then intersected those two 4-class rasters to create a new raster that classifies most areas in the Intermountain West into joined wind system development and pygmy rabbit habitat probability (four quantiles for wind MCF and <0.3167, 0.3167-0.4661, 0.4661-0.67073, and >0.67073 for habitat probability; 16 classes). For more information and further renewable data, please see: https://maps.nrel.gov/. Maclaurin, G, Grue, N., Lopez, A., Heimiller,...
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