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Burn probability (BP) raster dataset predicted for the 2080-2100 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway.
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Burn probability (BP) for Fireline Intensity Class 6 (FIL6) with flame lengths in the range of 3.7-15 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
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Burn probability (BP) for Fireline Intensity Class 2 (FIL2) with flame lengths in the range of 0.6-1.2 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Burn probability (BP) for Fireline Intensity Class 4 (FIL4) with flame lengths in the range of 1.8-2.4 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Conclusions: In fragmented watersheds, macrohabitat attributes measured at the patch scale were far more effective in predicting trout translocation success than measurements taken at the landscape scale Thresholds/Learnings: As a course filter indicator of cutthroat trout translocation success, the study found that translocations have a greater than 50% chance of fruitful establishment in watersheds >14.7km2 in area. Synopsis: This study aimed to identify stream-scale and basin-scale macrohabitat attributes limiting successful translocation and persistence of native cutthroat trout populations in fragmented landscapes along the Rio Grande. The study developed models of habitat attributes measured at two scales...
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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There is a need to understand how alteration of physical processes on the Rio Grande River have impacted aquatic biota and their habitats, and a need to predict potential future effects of climate change on biotic resources in order to prescribe research and management activities that will enhance conservation of aquatic species. We propose a project with the goal of developing monitoring recommendations and identifying research needs for aquatic ecological resources in the Big Bend region of the Rio Grande. This goal will be targeted by synthesizing and analyzing available data and literature for aquatic species in the project region. In particular, we will work to develop time series of abundance and population...
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This project had two primary goals: 1) To develop a process for integrating data from multiple sources to improve predictions of climate impacts for wildlife species; and 2) To provide data on climate and related hydrological change, fire behavior under future climates, and species’ distributions for use by researchers and resource managers.We present within this report the process used to integrate species niche models, fire simulations, and vulnerability assessment methods and provide species’ reports that summarize the results of this work. Species niche model analysis provides information on species’ distributions under three climate scenarios and time periods. Niche model analysis allows us to estimate the...
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This point vector dataset represents 10 climate stations used for analysis of annual and seasonal precipitation, analysis of monthly measured reference evapotranspiration, and comparison of simulated potential evapotranspiration with measured reference evapotranspiration within the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico.
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This dataset contains monthly crop irrigation requirement (CIR) values from March 1940 through 2014 for the 20 virtual land-use units, including the seven canal service units, in the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM). CIR values are presented in units of feet per day.


map background search result map search result map Minimum habitat requirements for establishing translocated cutthroat trout populations. Ecological changes in aquatic communities in the Big Bend reach of the Rio Grande: Synthesis and future monitoring needs Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area FSA 10:1 NAIP Imagery m_3710619_se_13_1_20150918_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710620_se_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710622_sw_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710630_ne_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710632_sw_13_1_20150911_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710636_nw_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710636_se_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710637_se_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710639_nw_13_1_20150911_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710640_nw_13_1_20150911_20151102 3.75 x 3.75 minute JPEG2000 from The National Map Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Climate Stations for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico RGTIHM CIR FSA 10:1 NAIP Imagery m_3710619_se_13_1_20150918_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710620_se_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710622_sw_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710630_ne_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710632_sw_13_1_20150911_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710636_nw_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710636_se_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710637_se_13_1_20150912_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710639_nw_13_1_20150911_20151102 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3710640_nw_13_1_20150911_20151102 3.75 x 3.75 minute JPEG2000 from The National Map Ecological changes in aquatic communities in the Big Bend reach of the Rio Grande: Synthesis and future monitoring needs Climate Stations for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico RGTIHM CIR Minimum habitat requirements for establishing translocated cutthroat trout populations. Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change