Skip to main content
Advanced Search

Filters: Contacts: Colorado Natural Heritage Program (X)

17 results (22ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
These are the original hexagons created for the 2013 Crucial Habitat Assessment Tool (CHAT) for Colorado, but the attributes have been updated with the 2015 revision to reflect the revised (2015 SWAP Revision) list of Tier 1 Species of Greatest Conservation Need (SGCN), and to incorporate updated occurrence data and improved distribution data for some species. CNHP developed species distribution models for 17 Tier 1 SGCN. Both documented and modeled distribution data for Tier 1 animal and plant SGCN have been combined at the resolution of 640 acre hexagons across the state. Each hexagon is then placed into one of six CHAT priority categories based on rules developed by the Western Governor's Association CHAT member...
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped pinyon occupied...
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped J. osteosperma...
Projected suitable habitat models were constructed in Maxent (version 3.3; Phillips et al. 2004, 2006) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped...
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped J. osteosperma...
Projected suitable habitat models were constructed in Maxent (version 3.3; Phillips et al. 2004, 2006) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped...
Projected suitable habitat models were constructed in Maxent (version 3.3; Phillips et al. 2004, 2006) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped...
The Colorado Natural Heritage Program (CNHP) of Colorado State University (CSU) proposes to use its expertise in wetland mapping to digitize original National Wetland Inventory (NWI) maps for the Colorado portion of the Southern Rockies Landscape Conservation Cooperative (SRLCC). Over the past five years, CNHP has worked with the U.S. Fish and Wildlife Service(USFWS)'s NWI Regional Coordinator for Region 6 to digitize original NWI maps for a total of 596 U.S. Geological Survey (USGS) topographic quadrangles (quads) covering several areas of Colorado. This proposal will apply that experience to the Colorado portion of the SRLCC to digitize original NWI maps for the remaining 316 quads that lack digital wetland data....
thumbnail
Projected suitable habitat models were constructed in Maxent (version 3.3; Phillips et al. 2004, 2006) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped...
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped pinyon occupied...
Projected suitable habitat models were constructed in Maxent (version 3.3; Phillips et al. 2004, 2006) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped...
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped J. osteosperma...
Projected suitable habitat models were constructed in Maxent (version 3.3; Phillips et al. 2004, 2006) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped...
thumbnail
Without reliable spatial data for wetland and riparian areas, it is impossible for land managers to accurately assess the distribution of critical aquatic habitats and model potential impacts caused by climate change. Wetlands in the Southern Rockies are particularly important for wildlife habitat, as they are often far more productive than the surrounding uplands. In addition, wetlands are an integral component of regional hydrologic cycles through their role in flood abatement, storm water retention, groundwater recharge, and water quality improvement.Colorados wetlands were mapped by the FWS early 1980 and in late 1990, and though the maps exist, they were created for print and most are not useful as digital...
Without reliable spatial data for wetland and riparian areas, it is impossible for land managers to accurately assess the distribution of critical aquatic habitats and model potential impacts caused by climate change. Wetlands in the Southern Rockies are particularly important for wildlife habitat, as they are often far more productive than the surrounding uplands. In addition, wetlands are an integral component of regional hydrologic cycles through their role in flood abatement, storm water retention, groundwater recharge, and water quality improvement.Colorados wetlands were mapped by the FWS early 1980 and in late 1990, and though the maps exist, they were created for print and most are not useful as digital...
Without reliable spatial data for wetland and riparian areas, it is impossible for land managers to accurately assess the distribution of critical aquatic habitats and model potential impacts caused by climate change. Wetlands in the Southern Rockies are particularly important for wildlife habitat, as they are often far more productive than the surrounding uplands. In addition, wetlands are an integral component of regional hydrologic cycles through their role in flood abatement, storm water retention, groundwater recharge, and water quality improvement.Colorados wetlands were mapped by the FWS early 1980 and in late 1990, and though the maps exist, they were created for print and most are not useful as digital...
Projected suitable habitat models were constructed in randomForest (R package, version 4.6-10) using a set of presence points for the species derived from element occurrence and herbarium records, together with temperature, precipitation, and soil variables. The current distribution used modeled historic period (1970-2000) climate variables from the appropriate matching GCM model run. These model parameters were then used with projected climate data to get future (2020-2050) modeled suitable habitat for each scenario. Modeled past suitable habitat and modeled future suitable habitat are combined to show areas of change, using various thresholds to distinguish change categories, as well as current mapped pinyon occupied...
    map background search result map search result map National Wetland Inventory Mapping for the Colorado Portion of the SRLCC Colorado - Priority Habitat for Tier 1 Terrestrial Animal and Plant SGCN Artemisia tridentata spp. vaseyana Feast/Famine Scenario Change Categories (2035) Artemisia tridentata spp. vaseyana Feast/Famine Scenario Change Categories (2035) Colorado - Priority Habitat for Tier 1 Terrestrial Animal and Plant SGCN National Wetland Inventory Mapping for the Colorado Portion of the SRLCC