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Filters: Tags: product (X) > Types: Downloadable (X) > partyWithName: Southern Rockies Landscape Conservation Cooperative (X)

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An estimated value for the ability of managers to dirct actions to protect, restore, or mitigate species and habitats. We recognize that our preliminary estimates are arbitrary and fairly approximate, but argue that making these explicit within a framework will enable stakeholders and managers to conduct subsequent analyses to better support their decision making.
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This data product contains estimates of habitat quality for black bear. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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Our objective was to model specific mean daily flow (mean daily flow divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate.We used a random forest modeling approach to model the relation between specific mean daily flow on gaged streams (115 gages) and environmental variables. We then projected specific mean...
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Our objective was to model specific minimum flow (mean of the annual minimum flows divided by drainage area [cubic feet per second per square mile]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between specific minimum flow on gaged streams (115 gages) and environmental variables. We then projected...
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Our objective was to model the risk of becoming intermittent under drier climate conditions on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a conditional inference modeling approach to model the relation between intermittency status on gaged streams (115 gages) and selected mean and minimum flow metrics. We then projected intermittency status and if a stream...
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This data product contains estimates of habitat connectivity for desert bighorn sheep. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance...
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An estimated value for the ability of managers to dirct actions to protect, restore, or mitigate species and habitats. We recognize that our preliminary estimates are arbitrary and fairly approximate, but argue that making these explicit within a framework will enable stakeholders and managers to conduct subsequent analyses to better support their decision making.
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This data product contains estimates of habitat quality for pronghorn. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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An estimated value for the ability of managers to dirct actions to protect, restore, or mitigate species and habitats. We recognize that our preliminary estimates are arbitrary and fairly approximate, but argue that making these explicit within a framework will enable stakeholders and managers to conduct subsequent analyses to better support their decision making.
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This data product contains estimates of habitat quality for mule deer. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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Our objective was to model mean annual number of zero-flow days (days per year) for small streams in the Upper Colorado River Basin under historic hydrologic conditions on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between zero-flow days per year on gaged streams (115 gages) and environmental variables....
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This data product contains estimates of habitat connectivity for pronghorn. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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This data product contains estimates of habitat quality for desert bighorn sheep. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance...
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We represent vulnerability as matrix that relates impacts with adaptive capacity. Vulnerability is high when impact is high and adaptive capacity is low. Vulnerability is moderate when either the impact is high and adaptive capacity is high, or if impact is low and adaptive capacity is low. Vulnerability is low when impact is low and adaptive capacity is high. We represent these conceptually as categorical for ease of discussion, but in reality there is continuum of vulnerabilities, and a different adaptation strategies and likely conservation actions, depending on the characteristics of the vulnerability.
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Our objective was to model 7-day minimum flow (mean of the annual minimums of a 7-day moving average for each year [cubic feet per second]) on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a random forest modeling approach to model the relation between 7-day minimum flow on gaged streams (115 gages) and environmental variables. We then projected 7-day minimum...
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This data product contains estimates of habitat connectivity for mule deer. The analysis area was a 236,000 square kilometers that encompassed the Navajo Nation, which includes portions of Arizona, New Mexico, and Utah. The estimates of habitat quality were created with spatially explicit habitat variables and either an expert-based linear combination process (for mountain lion and mule deer) or a generalized linear mixed model-based estimation that used radio-collar telemetry data (for desert bighorn sheep, black bear, and pronghorn; collected between 2005-2011). Habitat variables varied among species but included vegetation type, terrain ruggedness, topographic position index (TPI), road density, distance to water,...
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We represent vulnerability as matrix that relates impacts with adaptive capacity. Vulnerability is high when impact is high and adaptive capacity is low. Vulnerability is moderate when either the impact is high and adaptive capacity is high, or if impact is low and adaptive capacity is low. Vulnerability is low when impact is low and adaptive capacity is high. We represent these conceptually as categorical for ease of discussion, but in reality there is continuum of vulnerabilities, and a different adaptation strategies and likely conservation actions, depending on the characteristics of the vulnerability.


map background search result map search result map Riparian Vulnerability, RCP 4.5 Riparian Vulnerability, RCP 8.5 Riparian Impact Combined, RCP 4.5 Terrestrial Impact Combined, RCP 4.5 Terrestrial Impact Combined, RCP 8.5 Adaptive Capacity, High Range Adaptive Capacity, Low Range Adaptive Capacity, Preliminary Bighorn Sheep Habitat Connectivity Bighorn Sheep Habitat Quality Black Bear Habitat Quality Mule Deer Habitat Connectivity Mule Deer Habitat Quality Pronghorn Habitat Connectivity Pronghorn Habitat Quality Predicted 7-day minimum flow Predicted specific mean daily flow Predicted specific minimum flow Predicted hydrology (intermittency) under drier climate conditions Predicted mean annual number of zero-flow days Bighorn Sheep Habitat Connectivity Bighorn Sheep Habitat Quality Black Bear Habitat Quality Mule Deer Habitat Connectivity Mule Deer Habitat Quality Pronghorn Habitat Connectivity Pronghorn Habitat Quality Predicted hydrology (intermittency) under drier climate conditions Predicted 7-day minimum flow Predicted specific mean daily flow Predicted specific minimum flow Predicted mean annual number of zero-flow days Riparian Vulnerability, RCP 4.5 Riparian Vulnerability, RCP 8.5 Riparian Impact Combined, RCP 4.5 Terrestrial Impact Combined, RCP 4.5 Terrestrial Impact Combined, RCP 8.5 Adaptive Capacity, High Range Adaptive Capacity, Low Range Adaptive Capacity, Preliminary