Skip to main content
Advanced Search

Filters: Tags: data.gov Great Plains LCC (X) > partyWithName: Playa Lakes Joint Venture (X)

20 results (21ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
These data represent 1 sq. mile Hexagons and are derived from the Western Governors Association Crucial Habitat Assessment Tool. The hexagons have been attributed with summary values from the datasets described above. Field names correspond to the number datasets above as follows: {1:’wetland_deds’, 2:’wetland_ceds’, 3:’cropland_ceds’, 4:’lasp_grsp_casp_suit’, 5:’lasp_grsp_suit’, 6:’riparian_suit’, 7:’mean_sat_thick_ft’, 8:’tillage_suit’, 9:’wind_suit’, 10:’ann_aq_deplet_ft’, 11:’wetland_deds_2040’, 12:’wetland_ceds_2040’, 13:’lbgrasslands_2017’, 14:’lbgrasslands_2022’, 15:’lbgrasslands_2027’, 16:’mean_sat_thick_2050_ft’, 17:’tillage_suit_2050’}. Zonal statistic attribution methods are as follows: {1:’SUM’, 2:’SUM’,...
thumbnail
The tillage suitability product is a per-crop, per-pixel (30 square-meters) model representation of the predicted probability (0.00-1.00) that an area can support commodity crop development for a suite of crop types commonly grown in the LCD landscape. The values for each grid cell are interpreted as a probability, with any value greater-than 0.50 suggesting an area should be suitable for crop development based on observations of 2.5 million farmed areas around the LCD geography. To demonstrate composite suitability (“tillage”) for all crops, we added the individual probabilities for our modeled from cover classes (cereals, corn, cotton, and beans), which represents the overall proportion of votes for “crop” vs....
thumbnail
These data represent areas defined as large block grasslands according to a model developed by PLJV (McLachlan 2008). The model is based on literature derived Lesser Prairie-Chicken habitat preferences and considers habitat composition within a 2,000 ha area. Any pixel with more than 58% grass, less than 36% cropland, less than 2% woodland/ shrubland, less than 5 % secondary roads, and no 4 lane roads within a 2,000 ha surrounding area is counted as a large block grassland pixel.
thumbnail
Habitat hotspots were mapped for migratory birds ‘guilds’ across the LCD region using species presence/absence data collected from citizen-science datasets and modelled habitat conditions from the LANDFIRE program (Rollins, 2009). For presence/absence data, we used the eBird Reference Dataset (ERD, accessed October 1st, 2016; summarized in Sullivan et al., 2009) to model guild-level response to prevailing vegetation structure (e.g., percent-cover grass, tree, shrub, vegetation height), topography, and water availability for priority migratory bird species outlined in the Rio Mora NWR Land Protection Plan. We parsed eBird species “checklists” for species observed within a ~ 500 kilometer radius of the Rio Mora NWR....
thumbnail
The aquifer saturated thickness product is a per-pixel (250 square-meters) model representation of the combined fluid and soil matrix volume of water available in a given area, represented in units of linear feet. The prediction of available water is made using a network of over 9,300 monitoring wells located throughout the High Plains aquifer region. These wells are part of an annually updated long-term water-level monitoring study being conducted by United States Geological Survey hydrologists and other partners (https://ne.water.usgs.gov/ogw/hpwlms/). We used the source well depth-to-water data, as well as information on the base elevation of the aquifer (USGS Report : ofr98-393), surface elevation (NED-DEM),...
thumbnail
These data represent a potential future condition of large block grasslands if CRP lands expire and the land-use reverts back to cropland. Data layers for 2022 and 2027 were calculated by reclassing CRP lands scheduled to expire prior to these years to cropland and recalculating the large block grasslands layer as described above.
thumbnail
These data represent the long term average (27 year) amount of duck energy days available in wetlands. Data were produced as part of the PLJV waterfowl implementation plan. We used data from recently completed studies investigating food resource availability in a variety of wetland types in the PLJV. Beheny (2017) completed a study of food energy availability in five different wetland types in northeastern Colorado. Clark (2016) investigated food resource availability in stock ponds in BCR 19 in Texas. For the wetland DED values reported in both studies, we assumed these values were appropriate for use across the whole Joint Venture region. We used Landsat 5 data to determine wetness frequency over 27 years (1985-2012)...
thumbnail
To estimate wetland DEDs available in the future (2040) we used data from Bartuszevige et al. 2016 which estimates changes in playa functionality as a result of sedimentation, potential wind development, and tillage. Playas estimated to be impacted by these drivers were eliminated from the wetland landcover map and the process of calculating duck energy days described above was repeated.
thumbnail
These data represent a potential future condition of large block grasslands if CRP lands expire and the land-use reverts back to cropland. Data layers for 2022 and 2027 were calculated by reclassing CRP lands scheduled to expire prior to these years to cropland and recalculating the large block grasslands layer as described above.
thumbnail
These data represent Conservation Reserve Program (CRP) lands and their scheduled expiration date. CRP lands are those with a cropping history that have been enrolled in a program to plant grass cover for wildlife, erosion, and other benefits. CRP contracts are normally 15 years in length. These data are proprietary to the Farm Service Agency and are available to PLJV through an MOU that prohibits their dissemination. Analyses derived from these data will be available to refuge staff and MOUs may be developed in the future to share the data directly.
thumbnail
Habitat hotspots were mapped for migratory birds ‘guilds’ across the LCD region using species presence/absence data collected from citizen-science datasets and modelled habitat conditions from the LANDFIRE program (Rollins, 2009). For presence/absence data, we used the eBird Reference Dataset (ERD, accessed October 1st, 2016; summarized in Sullivan et al., 2009) to model guild-level response to prevailing vegetation structure (e.g., percent-cover grass, tree, shrub, vegetation height), topography, and water availability for priority migratory bird species outlined in the Rio Mora NWR Land Protection Plan. We parsed eBird species “checklists” for species observed within a ~ 500 kilometer radius of the Rio Mora NWR....
thumbnail
The wind energy development suitability product is a per-pixel (30 square-meters) model representation of the predicted probability (0.00-1.00) that an area can support wind energy development. The result is represented as a percentage, such that any value greater-than 0.5 would be classified as suitable for wind energy development in model space. To model suitability for wind energy development, we used 9,399 observations of ‘windmills’ taken from the FAA Digital Obstruction File (http://bit.ly/dof_12549; accessed June, 2016). Because the extent of the LCD region is limited to the panhandle region of Texas, we excluded all windmill observations outside of Texas from consideration during model building. To generate...
thumbnail
The tillage suitability product is a per-crop, per-pixel (30 square-meters) model representation of the predicted probability (0.00-1.00) that an area can support commodity crop development for a suite of crop types commonly grown in the LCD landscape. The values for each grid cell are interpreted as a probability, with any value greater-than 0.50 suggesting an area should be suitable for crop development based on observations of thousands of farmed areas around the LCD. To demonstrate composite suitability (“tillage”) for all crops, we added the individual probabilities for our modeled from cover classes (cereals, corn, cotton, and beans; described below), which represents the overall proportion of votes for “crop”...
thumbnail
To estimate wetland CEDs available in the future (2040) we used data from Bartuszevige et al. 2016 which estimates changes in playa functionality as a result of sedimentation, potential wind development, and tillage. Playas estimated to be impacted by these drivers were eliminated from the wetland landcover map and the process of calculating crane energy days described above was repeated.
thumbnail
Habitat hotspots were mapped for migratory birds ‘guilds’ across the LCD region using species presence/absence data collected from citizen-science datasets and modelled habitat conditions from the LANDFIRE program (Rollins, 2009). For presence/absence data, we used the eBird Reference Dataset (ERD, accessed October 1st, 2016; summarized in Sullivan et al., 2009) to model guild-level response to prevailing vegetation structure (e.g., percent-cover grass, tree, shrub, vegetation height), topography, and water availability for priority migratory bird species outlined in the Rio Mora NWR Land Protection Plan. We parsed eBird species “checklists” for species observed within a ~ 500 kilometer radius of the Rio Mora NWR....
thumbnail
These data represent the average annual depletion rate of the Ogallala aquifer from 1980 to 2009. These data were calculated by averaging spatially explicit 5 year depletion rates reported in McGuire et al. 2012.
thumbnail
These data represent the forecast saturated thickness of the Ogallala aquifer in 2050 based on the linear rate of depletion calculated previously. Using the model-based annual predictions of aquifer saturated thickness (described above), we built annual water-level transition matrices (e.g., Turner, 1987) that were then projected out through 2050.
thumbnail
These data represent 1 sq. mile Hexagons and are derived from the Western Governors Association Crucial Habitat Assessment Tool. The hexagons have been attributed with summary values from the datasets described above. Field names correspond to the number datasets above as follows: {1:’wetland_deds’, 2:’wetland_ceds’, 3:’cropland_ceds’, 4:’lasp_grsp_casp_suit’, 5:’lasp_grsp_suit’, 6:’riparian_suit’, 7:’mean_sat_thick_ft’, 8:’tillage_suit’, 9:’wind_suit’, 10:’ann_aq_deplet_ft’, 11:’wetland_deds_2040’, 12:’wetland_ceds_2040’, 13:’lbgrasslands_2017’, 14:’lbgrasslands_2022’, 15:’lbgrasslands_2027’, 16:’mean_sat_thick_2050_ft’, 17:’tillage_suit_2050’}. Zonal statistic attribution methods are as follows: {1:’SUM’, 2:’SUM’,...
thumbnail
These data represent the amount of crane energy days derived from croplands that are available within a 10km distance. These data were calculated by reclassing the NASS Cropland Data Layer to reflect energetic carrying capacity for cranes reported by Johnson et. al 2017. I.e Winter Wheat: 2588 CEDs/ ha, Corn: 1034 CEDs / ha, Sorghum: 496.5 CEDs / ha. A 10km moving windows analysis with a circular window was applied to the resulting CED raster to sum the CED values within a 10km area.
thumbnail
These data represent the long term average (27 year) amount of crane energy days (CED) available in wetlands. CEDs were calculated in the same way as wetland duck energy days describe above except that different habit energy density values were used. Based on the PLJV waterbird plan (2008) Appendix A, we estimated wetland CED density values for wetland habitats by dividing energetic carrying capacities for waterfowl by 3.37 to reflect the difference in mean body mass between mallards and sandhill cranes.


    map background search result map search result map Future Wetland cud BCR 18 in 2040 Driver for Future Projections: CRP Expiration Future Tillage Suitability 2050 Driver for Projections - Aquifer Annual Change 1980 to 2013 Driver for Projections Wind Suitability in Texas 2016 Conservation Parcels Scored - Rio Mora Crucial Habitat Assessment Future Wetland dud BCR 18 in 2040 Conservation Parcels Scored - Muleshoe Crucial Habitat Assessment Future Large Block Grasslands in 2022 Future Large Block Grasslands in 2027 Driver for Projections Tillage Suitability 2016 Aquifer Saturation Thickness 2013 Future Aquifer Saturation Thickness in 2050 Large Block Grasslands 2017 Bird Habitat Suitability - Riparian Bird Habitat Suitability Lark and Grasshopper Bird Habitat Suitability Lark, Grasshopper, and Cassin's Sparrow Cropland dud BCR 18 Wetland dud BCR 18 Wetland cud BCR 18 Future Wetland cud BCR 18 in 2040 Driver for Future Projections: CRP Expiration Future Tillage Suitability 2050 Driver for Projections - Aquifer Annual Change 1980 to 2013 Driver for Projections Wind Suitability in Texas 2016 Future Wetland dud BCR 18 in 2040 Conservation Parcels Scored - Muleshoe Crucial Habitat Assessment Future Large Block Grasslands in 2022 Future Large Block Grasslands in 2027 Driver for Projections Tillage Suitability 2016 Aquifer Saturation Thickness 2013 Future Aquifer Saturation Thickness in 2050 Large Block Grasslands 2017 Bird Habitat Suitability - Riparian Bird Habitat Suitability Lark and Grasshopper Bird Habitat Suitability Lark, Grasshopper, and Cassin's Sparrow Cropland dud BCR 18 Wetland dud BCR 18 Wetland cud BCR 18 Conservation Parcels Scored - Rio Mora Crucial Habitat Assessment