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Understanding the physiological impacts of climate change on arid lands species is a critical step towards ensuring the resilience and persistence of such species under changing temperature and moisture regimes. Varying degrees of vulnerability among different species will largely determine their future distributions in the face of climate change. Studies have indicated that Northern Mexico and the Southwestern United States are likely to become climate change hotspots, experiencing significantly drier and warmer average conditions by the end of the 21st century. However, relatively few studies have examined specifically the physiological effects of climate change on species inhabiting this region. This manuscript...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2014, AZ-01, AZ-02, AZ-03, AZ-04, All tags...
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To determine if invasive annual grasses increased around energy developments after the construction phase, we calculated an invasives index using Landsat TM and ETM+ imagery for a 34-year time period (1985-2018) and assessed trends for 1,755 wind turbines (from the U.S. Wind Turbine Database) installed between 1988 and 2013 in the southern California desert. The index uses the maximum normalized difference vegetation index (NDVI) for early season greenness (January-June), and mean NDVI (July-October) for the later dry season. We estimated the relative cover of invasive annuals each year at turbine locations and control sites and tested for changes before and after each turbine was installed. These data were used...
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These data were compiled for the creation of a continuous, transboundary land cover map of Bird Conservation Region 33, Sonoran and Mojave Deserts (BCR 33). Objective(s) of our study were to, 1) develop a machine learning (ML) algorithm trained to classify vegetation land cover using remote sensing spectral data and phenology metrics from 2013-2020, over a large subregion of the Sonoran and Mojave Deserts BCR, 2) Calibrate, validate, and refine the final ML-derived vegetation map using a collection of openly sourced remote sensing and ground-based ancillary data, images, and limited fieldwork, and 3) Harmonize a new transboundary classification system by expanding existing land cover mapping resources from the United...
We assessed the impacts of co-occurring invasive plant species on fire regimes and postfire native communities in the Mojave Desert, western USA by analyzing the distribution and co-occurrence patterns of three invasive annual grasses known to alter fuel conditions and community structure: Red Brome (Bromus rubens), Cheatgrass (Bromus tectorum), and Mediterranean grass (Schismus spp.: Schismus arabicus and Schismus barbatus), and an invasive forb, red stemmed filaree (Erodium cicutarium) which can dominate postfire sites. We developed species distribution models (SDMs) for each of the four taxa and analyzed field plot data to assess the relationship between invasives and fire frequency, years postfire, and the impacts...
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We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands, and non-wetland cover. In Google Earth Engine (GEE) we developed a random forest model that combined the training data with spatially explicit predictor variables of vegetation greenness indices, wetness indices, seasonal index variation, topographic variables, and hydrologic parameters. The final product is a wall-to-wall map of...
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This raster dataset represents spatially explicit predictions of burn severity (dNBRPredict.tif) in the Mojave Desert based on models developed from data on the difference normalized burn ratio (dNBR) within perimeters of fires greater than 405 hectares that burned between 1984 to 2010. Raster resolution equals 30 meters, projection equals UTM Zone 11N.
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This U.S. Geological Survey data release consists of 3 raster datasets representing estimates of probability of ignition (ProbIgnitPredict.tif), fire frequency (FrequencyPredictRF.tif), and burn severity (dNBRPredictRF.tif) in the Mojave Desert from 1984 to 2010. The data include: (1) A shapefile of the Mojave Desert that was used as our study area boundary (MojaveEcoregion_TNS_UTM83.shp). The original shapefile was obtained from NatureServe in 2009; (2) Three Tagged-Interchange Format (TIF) raster datasets representing probability of ignition, fire frequency, and burn severity. Resolution equals 30 meters, projection equals UTM Zone 11N. These data support the following publication: Klinger, R., Underwood, E.C.,...
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This raster dataset represents spatially explicit predictions of probability of ignition in the Mojave Desert based on models developed from data on perimeters of fires greater than 405 hectares that burned between 1972 to 2010. Raster resolution equals 30 meters, projection equals UTM Zone 11N.
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The U.S. Army Fort Irwin National Training Center (NTC), approximately 35 mi north-northeast of Barstow, California, covers approximately 1,177 square miles, and is comprised of ten groundwater basins, three of which have been subdivided into subbasins on the basis of additional hydrologic testing. Since the early 1990s, the U.S. Geological Survey (USGS) has been studying water resources issues at Fort Irwin. One issue of concern is the potential effect of groundwater development resulting from planned training expansion and infrastructure at the NTC on natural springs and seeps, an important water source for wildlife. In 2010, the USGS entered into cooperative agreements with the U.S. Army to complete studies of...
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The U.S. Army Fort Irwin National Training Center (NTC), approximately 35 mi north-northeast of Barstow, California, covers approximately 1,177 square miles, and is comprised of ten groundwater basins, three of which have been subdivided into subbasins on the basis of additional hydrologic testing. Since the early 1990s, the U.S. Geological Survey (USGS) has been studying water resources issues at Fort Irwin. One issue of concern is the potential effect of groundwater development resulting from planned training expansion and infrastructure at the NTC on natural springs and seeps, an important water source for wildlife. In 2010, the USGS entered into cooperative agreements with the U.S. Army to complete studies of...
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Water levels were measured during March 2014 in wells in the Antelope Valley and Fremont Valley groundwater basins, southwestern Mojave Desert, California, in cooperation with the Antelope Valley-East Kern Water District, Palmdale Water District, and Littlerock Creek Irrigation District. These data document recent conditions and, when compared with previous data, changes in groundwater levels. A regional water-table map was constructed using data from about 200 wells.
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The U.S. Army Fort Irwin National Training Center (NTC), approximately 35 mi north-northeast of Barstow, California, covers approximately 1,177 square miles, and is comprised of ten groundwater basins, three of which have been subdivided into subbasins on the basis of additional hydrologic testing. Since the early 1990s, the U.S. Geological Survey (USGS) has been studying water resources issues at Fort Irwin. One issue of concern is the potential effect of groundwater development resulting from planned training expansion and infrastructure at the NTC on natural springs and seeps, an important water source for wildlife. In 2010, the USGS entered into cooperative agreements with the U.S. Army to complete studies of...
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This raster dataset represents spatially explicit predictions of fire frequency in the Mojave Desert based on models developed from data on perimeters of fires greater than 405 hectares that burned between 1972 through 2010. Raster resolution equals 30 meters, projection equals UTM Zone 11N.


    map background search result map search result map Physiological Effects of Climate Change on Species within the Desert LCC Electrical Resistivity Tomography Data at Fort Irwin National Training Center, San Bernardino County, California, 2015 and 2017 Electrical Resistivity Tomography Data Electrical Resistivity Tomography Inverted Models Invasive Plant Cover in the Mojave Desert, 2009 - 2013 (ver. 2.0, April 2021) Data supporting Landsat time series assessment of invasive annual grasses following energy development Species distribution model of the invasive annual grass Bromus rubens (red brome) in the Mojave Desert Species distribution model of the invasive annual forb Erodium cicutarium (red-stemmed filaree) in the Mojave Desert Species distribution model of the invasive annual grass Schismus spp (Mediterranean split grass) in the Mojave Desert Species distribution model of the invasive annual grass Bromus tectorum (cheatgrass) in the Mojave Desert Fire Regimes in the Mojave Desert (1972-2010) Predictive Model of Burn Severity (dNBR) in the Mojave Desert Regional water table Contours of the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014 Predictive Model of Fire Frequency in the Mojave Desert Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 – December 2020 Predictive Model of Probability of Ignition in the Mojave Desert Mojave Desert Ecoregion Wetlands in the state of Arizona Electrical Resistivity Tomography Data at Fort Irwin National Training Center, San Bernardino County, California, 2015 and 2017 Electrical Resistivity Tomography Data Electrical Resistivity Tomography Inverted Models Regional water table Contours of the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014 Data supporting Landsat time series assessment of invasive annual grasses following energy development Fire Regimes in the Mojave Desert (1972-2010) Invasive Plant Cover in the Mojave Desert, 2009 - 2013 (ver. 2.0, April 2021) Mojave Desert Ecoregion Predictive Model of Burn Severity (dNBR) in the Mojave Desert Predictive Model of Fire Frequency in the Mojave Desert Predictive Model of Probability of Ignition in the Mojave Desert Species distribution model of the invasive annual grass Bromus rubens (red brome) in the Mojave Desert Species distribution model of the invasive annual forb Erodium cicutarium (red-stemmed filaree) in the Mojave Desert Species distribution model of the invasive annual grass Schismus spp (Mediterranean split grass) in the Mojave Desert Species distribution model of the invasive annual grass Bromus tectorum (cheatgrass) in the Mojave Desert Random forest classification data developed from multitemporal Landsat 8 spectral data and phenology metrics for a subregion in Sonoran and Mojave Deserts, April 2013 – December 2020 Wetlands in the state of Arizona Physiological Effects of Climate Change on Species within the Desert LCC