Rob Massatti Sarah Sterner Daniel Winkler 20231114 vector data Flagstaff, AZ U.S. Geological Survey Additional information about Originators: Massatti, Rob, https://orcid.org/0000-0001-5854-5597; Sterner, Sarah, https://orcid.org/0000-0001-7984-967X; Winkler, Daniel, https://orcid.org/0000-0003-4825-9073 https://doi.org/10.5066/P98X9GRB Daniel Winkler Sarah Sterner John B. Bradford Adrienne M. Pilmanis Rob Massatti 2023 journal manuscript TBD (online) TBD These data were compiled to support and inform the Bureau of Land Management’s Colorado Plateau Native Plant Program and to guide future management action when selecting regions to collect and increase seed for native plant materials development. The objective of our study was to develop geospatial datasets to aid land managers and restoration practitioners in identifying areas that will need to be restored in the future (currently disturbed) as well as areas to source new native plant materials for propagation with increased climate similarity to these areas across the Colorado Plateau, Arizona/New Mexico Mountains, and Arizona/New Mexico Plateaus. These data represent species distribution models for 12 high priority restoration species on the Colorado Plateau and environs, source locations of commonly available germplasms for those 12 high priority restoration species, climatic suitability of those restoration species based on the source locations, areas disturbed by grazing, energy production, and wildfires, as well as climatic partitions within each species habitat to illustrate areas for new collections for grow out. This data was collected and analyzed electronically. Disturbance data was collected from the US Energy Information Administration, Homeland Infrastructure Foundation Level Data, the Bureau of Land Management, the US Forest Service, and the National Interagency Fire Center. Species distribution models were created using species occurrence data sourced from SEINET, 19 bioclimatic variables sourced from the WorldClim historical dataset, and were created using MaxEnt software. Climate similarity (referred to as well suited habitat throughout) and climate partitioning models were created using the Seed Mapping Toolkit. This data can be used to investigate suitable habitat for priority restoration species, identify landscape level disturbances, identify suitability of currently available native plant materials (NPMs), and to prioritize locations for seed collection to fill gaps in existing native plant material suitability. The purpose of these datasets are to help land managers and restoration practitioners prioritize locations for seed collection to fill the gaps in existing native plant materials (NPM) suitability across the Colorado Plateau, Arizona/New Mexico Mountains, and Arizona/New Mexico Plateaus by identifying unsuitable habitat for native plant materials (NPMs) and locating climatically similar partitions within that unsuitable habitat to source new materials from. These data were created to aid land managers and restoration practitioners in identifying areas that will need to be restored in the future as well as areas to source new native plant materials based on the unsuitability of currently available germplasms. These data could be used by future researchers to investigate suitable habitat for priority restoration species, identify landscape level disturbances, identify suitability of currently available native plant materials (NPMs), and to prioritize locations for seed collection to fill gaps in existing native plant material suitability. The various spatial data layers for each species are specifically described in this metadata record. The methods for how these data were created are thoroughly described in the process steps and provide enough detail for a potential data user to recreate these data from reading the metadata alone. Source data is documented for potential data users to acquire the same data that we used to create these spatial data products. Limitations to these datasets are that they are specific to the region tested, the land management boundary utilized, the species this study focused on, and the disturbance layers that are already out of date given the time that has passed since the original layers were developed and acquired for use in this study. Data users should read the metadata record, acquire the ‘Larger Work Citation’, and review the 'Cross References' to have a complete understanding of how these data were created and used. Methods describing each processing step and output of all layers are described in detail in the instructional, step-by-step guides in the two appendices associated with this data product and its associated publication. The data are specific to the uses identified in this metadata record, as described in the ‘Larger Work Citation’, and any other use of these data may be inappropriate. See 'Distribution liability' statements for more information. 2021 2022 ground condition Complete None planned -114.1800 -105.3400 40.9000 32.4000 USGS Thesaurus biogeography biodiversity bioremediation climate change habitat alteration and disturbance ecological processes energy resources fires modeling native species natural gas resources natural resource management plants (organisms) specimen collecting USGS Metadata Identifier USGS:6202cbe1d34e622189dcd6f5 USGS information products data release ISO 19115 Topic Categories biota climatologyMeteorologyAtmosphere None Achnatherum hymenoides Astragalus lonchocarpus bioclimatic variables Bouteloua gracilis Cleome lutea Cleome serrulata climate similarity climate partitioning models climatic suitability coal mine disturbance data disturbed areas Elymus elymoides energy production gas well germplasms grazing Heliomeris multiflora Heterotheca villosa landscape level disturbances Machaeranthera canescens native plant material native plant material suitability native plant restoration natural gas pipeline oil well Pleuraphis jamesii priority restoration species plant species restoration seed collection seed sourcing source locations species distribution models species habitat species occurrence data Sphaeralcea parvifolia Sporobolous cryptandrus suitable habitat wildfires Geographic Names Information System (GNIS) Arizona Colorado New Mexico Utah None Arizona/New Mexico Mountains Arizona/New Mexico Plateaus Colorado Plateau Four Corners Region Intermountain Region Intermountain West Southwest US Southwest none none Robert T Massatti U.S. Geological Survey Research Ecologist mailing and physical

2255 North Gemini Drive

Flagstaff AZ 86001 United States 928-556-7304 rmassatti@usgs.gov These data were created by staff at the U.S. Geological Survey Southwest Biological Science Center with support and direction from Adrienne Pilmanis at the Bureau of Land Management's Colorado Plateau Native Plant Program. Jason L. Brown 2014 British Ecological Society (online) Methods in Ecology and Evolution https://doi.org/10.1111/2041-210X.12200 Jason L. Brown Connor French Joseph Bennett 2021 SDM Toolbox (online) Jason L. Brown http://www.sdmtoolbox.org/ Stephen E. Fick Robert J. Hijmans 2017 Royal Meteorological Society (online) International Journal of Climatology https://doi.org/10.1002/joc.5086 Kyle Doherty Caitlin Andrews Rob Massatti 2021 U.S. Geological Survey (online) U.S. Geological Survey https://www.usgs.gov/apps/seed-toolkit/ No formal attribute accuracy tests were conducted No formal logical accuracy tests were conducted Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. No formal positional accuracy tests were conducted No formal positional accuracy tests were conducted Worldclim 2020 Raster dataset Worldclim.org Worldclim https://www.worldclim.org/data/worldclim21.html digital raster data 1970 2020 publication date 30 second bioclimatic variables data (bio 30s) These 19 WorldClim Bioclimatic variables data was used to create species distribution models SEINet Portal Network, The Arizona – New Mexico chapter 2021 tabular dataset SEINet data portal - Arizona – New Mexico chapter (online) SEINet https://swbiodiversity.org/seinet/ digital tabular data 1995 2021 publication date species occurrence data These species occurrence data was used to create species distribution models National Interagency Fire Center 2020 vector dataset National Interagency Fire Center- NIFC Open Data Site (online) National Interagency Fire Center https://data-nifc.opendata.arcgis.com/ digital vector data 20000101 20191231 ground condition wildfire polygons These wildfire polygon data was used in the creation 'species abbreviation'_disturb shapefiles. Bureau of Land Management 2020 vector dataset U.S. Geological Survey - ScienceBase (online) Bureau of Land Management https://www.sciencebase.gov/catalog/item/5d810644e4b0c4f70d056dad digital vector data 20200801 20200831 ground condition BLM grazing allotments These BLM grazing allotment polygon data was used in the creation 'species abbreviation'_disturb shapefiles. U.S. Department of Homeland Security - Geospatial Management Office 2020 vector dataset U.S. Department of Homeland Security - Geospatial Management Office (online) U.S. Department of Homeland Security - Geospatial Management Office https://hifld-geoplatform.opendata.arcgis.com/datasets/oil-and-natural-gas-wells/explore?location=35.143428%2C-109.717264%2C2.99 digital vector data 20200801 20200831 ground condition Oil and natural gas well data These oil and natural gas well point data was used in the creation 'species abbreviation'_disturb shapefiles. US Energy Information Administration 2020 vector dataset US Energy Information Administration, U.S. Energy Atlas U.S. Energy Information Administration https://atlas.eia.gov/datasets/eia::crude-oil-pipelines/explore?location=33.475744%2C-95.221420%2C4.64 digital vector data 20200101 20201231 ground condition Oil pipeline data These oil pipeline polyline data was used in the creation 'species abbreviation'_disturb shapefiles. U.S. Forest Service 2020 ESRI geodatabase USFS Chief Information Office, Enterprise Data Warehouse U.S. Forest Service http://data.fs.usda.gov/geodata/edw/datasets.php digital data 20200101 20201231 ground condition USFS grazing allotments These USFS grazing allotment polygon data was used in the creation 'species abbreviation'_disturb shapefiles. Development of 'species abbreviation'_disturb shapefiles: **** Step 1: acquire source data from 3 data providers. Livestock grazing allotment shapefile data was acquired from the Bureau of Land Management and the U.S. Forest Service (BLM: https://www.sciencebase.gov/catalog/item/5d810644e4b0c4f70d056dad; USFS: https://data.fs.usda.gov/geodata/edw/datasets.php - select the file is Range: Allotment). Oil and gas well data was acquired from the Homeland Infrastructure Foundation Level Database (https://hifld-geoplatform.opendata.arcgis.com/datasets/oil-and-natural-gas-wells). Coal mines, crude oil pipelines, and natural gas pipelines was acquired from the US Energy Information Administration (https://www.eia.gov/maps/layer_info-m.php). Lastly, wildfire polygon data (wildfires that burned between 2000 and 2019) from the National Interagency Fire Center (https://data-nifc.opendata.arcgis.com/). **** Step 2: prepare source data for further data processing using ESRI ArcMap. For the livestock grazing allotment data, use the Clip tool (Analysis Tools/Extract toolset) to extract the polygons in each grazing dataset (input features) with each 'species abbreviation'_habitat shapefile (clip feature). Second, the 12 species/BLM grazing and 12 species/USFS grazing polygon shapefiles were combined to create a single shapefile with both BLM and USFS livestock grazing allotment polygons for each species (12). The Merge tool (Data Management Tools/General toolset) was used to combine the clipped BLM grazing shapefiles with each of the clipped USFS grazing shapefiles. Lastly, the Dissolve tool (Data Management Tools/General toolset) was used to create one polygon of all of the livestock grazing allotment areas within each species habitat. Shapefile names are 'species abbreviation'_grazing. For the wildfire data, use the Clip tool (Analysis Tools/Extract toolset) to extract the wildfire polygons (input features) with each 'species abbreviation'_habitat shapefile (clip feature). Second, the Dissolve tool (Data Management Tools/General toolset) was used to create one polygon of all of the wildfires within that occurred in each species habitat between 2000 and 2019. Shapefile names are 'species abbreviation'_wildfire. For the oil and gas well data, use the Clip tool (Analysis Tools/Extract toolset) to extract the oil and gas well features (input features) with each 'species abbreviation'_habitat shapefile (clip feature). Second, the Buffer tool (Analysis Tools/Proximity toolset) was used to create a 400 meter buffer around each oil and gas well. The Dissolve Type (optional) paramater "All" was selected to dissolve the oil and gas well buffers together into a single feature, and remove any overlap. Shapefile names are 'species abbreviation'_well. For the coal mine data, use the Clip tool (Analysis Tools/Extract toolset) to extract the coal mine features (input features) with each 'species abbreviation'_habitat shapefile (clip feature). Second, the Buffer tool (Analysis Tools/Proximity toolset) was used to create a 400 meter buffer around each coal mine. The Dissolve Type (optional) paramater "All" was selected to dissolve the oil and coal mine buffers together into a single feature, and remove any overlap. Shapefile names are 'species abbreviation'_coal. For the crude oil pipeline and natural gas pipeline data, use the Clip tool (Analysis Tools/Extract toolset) to extract the natural gas pipeline features (input features) with each 'species abbreviation'_habitat shapefile (clip feature). Second, the Buffer tool (Analysis Tools/Proximity toolset) was used to create a 400 meter buffer around each natural gas pipeline. The Dissolve Type (optional) paramater "All" was selected to dissolve the crude oil pipeline buffers together into a single feature, and remove any overlap. Shapefile names are 'species abbreviation'_pipeline. For the oil and gas well, coal mine, and crude oil pipeline and natural gas pipeline buffer shapefiles, the Merge tool (Data Management Tools/General toolset) was used to combine all of the buffered features for the 3 energy types. Second, the Dissolve tool (Data Management Tools/General toolset) was used to create one polygon of all of the energy types that occurred in each species habitat. The Dissolve Type (optional) paramater "All" was selected to dissolve the energy type buffers together into a single feature, and remove any overlap. Shapefile names are 'species abbreviation'_energy. At this point, three disturbance shapefiles with a single polygon for each feature (grazing, wildfire, energy) have been created for each species habitat. **** Step 3: create the disturbance shapefiles. For all shapefiles (grazing, wildfire, energy) for each species habitat add a field "disturb" to each attribute table. Populate the "disturb" attribute field for all shapefiles (grazing, wildfire, energy) with the appropriate disturbance type, either grazing, wildfire, or energy. For each species habitat, the Merge tool (Data Management Tools/General toolset) was used to combine all of the features for the 3 disturbance types into a single output dataset and save each shapefile dataset as 'species abbreviation'_disturb.shp for a total of 12 shapefiles. **** Step 4: project 'species abbreviation'_disturb shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_disturb_germplasms shapefiles: All 'species abbreviation'_habitat, 'species abbreviation'_disturb, and 'species abbreviation'_germplasms shapefiles are required before creating the 'species abbreviation'_disturb_germplasms shapefiles. Each shapefile contains individual polygons that represent a disturbance type (wildfire, grazing, or energy) and a germplasm that is well suited to exist within those disturbed areas. All data processing used ESRI ArcMap **** Step 1: use the Intersect tool (Analysis Tools/Intersect toolset) to compute the geometric intersection of the germplasm ('species abbreviation'_germplasms) and disturbance ('species abbreviation'_disturb) shapefiles to identify the overlap where each germplasm has well suited habitat within areas that are disturbed by livestock grazing, wildfire, and energy production. **** Step 2: add a field to the 'species abbreviation'_disturb_germplasms shapefiles. Open the attribute table for each shapefile and select 'Add field...' and name this new field, "dist_germ". Select Data Type = Text and Length = 50. **** Step 3: populate the "germplasm" attribute field. With the attribute table open, right click the "dist_germ" field, select the Field Calculator, select VB Script, and concatenate the disturbance (disturb) and "germplasm" fields using the code: dist_germ = [disturb] & " " & [germplasm]. **** Step 4: aggregate the polygon features on a specified attribute (dist_germ) using the Dissolve tool (Data Management Tools/Generalization toolset) to create 24 individual polygons that represent a disturbance type (wildfire, grazing, or energy) and a germplasm for each species. Save the dissolved polygon shapefiles for each species as, 'species abbreviation'_disturb_germplasms.shp. **** Step 5: project 'species abbreviation'_disturb_germplasms shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_disturb_unsuitable shapefiles: All 'species abbreviation'_disturb and 'species abbreviation'_unsuitable_germplasms shapefiles are required before creating the 'species abbreviation'_disturb_unsuitable shapefiles. **** Step 1: extract the 'species abbreviation'_disturb features that overlay the 'species abbreviation'_unsuitable_germplasms features. Save the clip polygons features for each species as, 'species abbreviation'_disturb_clip.shp. **** Step 2: aggregate the polygon features on a specified attribute in the 'species abbreviation'_disturb_clip shapefiles using the Dissolve tool (Data Management Tools/Generalization toolset) to create a single polygon representing disturbed areas that DO NOT have well suited (unsuitable) commercially available germplasms. Save the dissolved polygon shapefiles for each species as, 'species abbreviation'_disturb_unsuitable.shp. **** Step 5: project 'species abbreviation'_disturb_unsuitable shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_germplasms shapefiles: The Native Plant Seed Toolkit (https://www.usgs.gov/apps/seed-toolkit/) was used to create these shapefiles. **** Step 1: Choose application - select the Seed Selection Tool **** Step 2: Define a geographic area - select Spatial Polygon to upload a spatial polygon. Browse to the folder with the all 12 'species abbreviation'_habitat shapefiles. Upload each species habitat shapefile individually to visualize the climatic similarity between a restoration material’s (RM’s) location of origin and a defined geographic area. Shapefiles were uploaded as zipped folder that included the following components: .cpg, .dbf, prj, .shp, .shx. **** Step 3: Select a seed source - select 'Select from table of restoration materials' and then use the Search feture to return results based on a single "Species" and a single "Release". Select the Restoration Materials for : one species and one "Release" name. **** Step 4: Weight climate variables - select all 7 of the climate variables with the same weight = 1. **** Step 5: Match Seed to Climate, press to run the Seed Selector Tool. **** Step 6: When the results appear, scroll up to the top of the web page to view the map. Select the Hotspots (from What type of map?) and toggle the climate similarity threshold slider bar to 80 which represents an 80% climate similarity match to the source location of a germplasm for the selected species. **** Step 7: After selecting the 80% climate similarity threshold, scroll down to the bottom of the web page. Select the Download Results and Data button and download the ZIP file to the SeedSelectionTool/'species abbreviation' folder. The downloaded results and data for a single species and a single "Release" name (with the germplasm locations for that species) will produce a ZIP file (climate_partitioning_data_yyyy-mm-dd.zip). Rename the ZIP file to 'species abbreviation'_'germplasm'_climate_partitioning_data_yyyy-mm-dd.zip. Extract the folder (tmp) in the ZIP file using a file archiver utility (such as 7-Zip, WinZip). Inside the tmp folder is another folder with 7 files inside. * Create a copy of the hotspot.tif file and rename it 'species abbreviation'_'germplasm abbr'_hotspot.tif **** Step 8: create a polygon shapefile from the 'species abbreviation'_'germplasm abbr'_hotspot.tif using ESRI ArcMap by converting the raster datasets in ArcMap using the Raster to Polygon tool (Conversion Tools/From Raster toolset). Select the following paramaters: Input Raster ('species abbreviation'_hotspot.tif); Field (optional) (select field 'Value'; Output Polygon Features ('species abbreviation'_hotspot_poly); Simplify polygons (optional). Save the polygon shapefiles for each species as 'species abbreviation'_hotspot.shp. Openning the attribute table for the polygon shapefile ('species abbreviation'_'germplasm abbr'_hotspot.shp) created from the 80% threshold, there are many polygons for ease of analysis. Save the polygon shapefiles as, 'species abbreviation'_'germplasm abbr'_poly.shp. When openning the attribute table for the polygon created from the 80% threshold, notice that there are many polygons for further processing. * germplasms locations: Amethyst, Antelope Creek, Asotin, Bonneville, Borden, CRNG, Delta, Fish Creek, Hachita, La Plata, Lovington, Massedona, Nezpar, Paloma, Pleasant Valley, Pueblo, Rattlesnake, Rimrock, Sand Hallow, Shaniko Star Lake, Toe Jam Creek, Turkey Lake, Tusas, Viva, Wapiti, Western, White River **** Step 9: aggregate the polygon features on a specified attribute in ArcMap using the Dissolve tool (Data Management Tools/Generalization toolset) to create one species germplasm polygon for one species and one release. Select the following paramaters: Input Features ('species abbreviation'_'germplasm abbr'_poly); Output Feature Class ('species abbreviation'_'germplasm abbr'_diss); Dissolve_Field (optional) (select 'gridcode'). **** Step 10: attribute table editing using 'Add Field...' and 'Calculate'. Open the attribute table for a 'species abbreviation'_'germplasm abbr'_diss shapefile and select 'Table Options/Add Field...' to open the 'Add Field' dialog box. Provide the following parameters: Name: (id); Type: (Text), Field Properties/Length (50). Calculate the "gridcode" attribute field for all 'species abbreviation'_'germplasm abbr'_diss shapefiles based on the following (see assignment.val.key.csv in 'species abbreviation'_'germplasm abbr'_climate_partitioning_data_yyyy-mm-dd.zip: Example Accession Raster Value 'species abbreviation'_Bonneville 1 'species abbreviation'_Delta 2 'species abbreviation'_La Plata 3 'species abbreviation'_Nezpar 4 'species abbreviation'_Paloma 5 'species abbreviation'_Rimrock 6 'species abbreviation'_Star Lake 7 'species abbreviation'_White River 8 Then, Calculate the "id" attribute field for all 'species abbreviation'_'germplasm abbr'_diss shapefiles based on the following: Example Raster Value id 1 Bonneville 2 Delta 3 La Plata 4 Nezpar 5 Paloma 6 Rimrock 7 Star Lake 8 White River **** Step 11: Finally, for the 'species abbreviation'_'germplasm abbr'_diss shapefiles, the Merge tool (Data Management Tools/General toolset) was used to combine all features for each release type into a single species shapefile with 8 individual polygons. Save each shapefile as, 'species abbreviation'_germplasms.shp. The 'species abbreviation'_germplasms shapefile contains various polygons, one for each of species habitat. **** Step 12: project 'species abbreviation'_germplasm shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_germplasm_locs shapefiles: The Native Plant Seed Toolkit (https://www.usgs.gov/apps/seed-toolkit/) and ESRI ArcCatalog was used to create these shapefiles. **** Step 1: Choose application - select the Seed Selection Tool **** Step 2: Define a geographic area - select Lat/Long Slider Bars. Leave the geographic area bounding box to it's preset extent: Latitude Extent = 32, 40 Longitude Extent = -115, -105 **** Step 3: Select a seed source - select 'Select from table of restoration materials' and then use the Search feture to return results based on a single "Species". Select the Restoration Materials for : one species and all "Release" names. **** Step 4: Weight climate variables - select all 7 of the climate variables with the same weight = 1. **** Step 5: Match Seed to Climate, press to run the Seed Selector Tool. **** Step 6: Select the Download Results and Data button and download the ZIP file to the SeedSelectionTool/'species abbreviation'/All folder. The downloaded results and data for a single species and all "Release" names will produce a ZIP file (climate_partitioning_data_yyyy-mm-dd.zip). Rename the ZIP file to All_'release abbr'_climate_partitioning_data_yyyy-mm-dd.zip. Extract the folder (tmp) in the ZIP file using a file archiver utility (such as 7-Zip, WinZip). Inside the tmp folder is another folder with 7 files inside. * the accession.data.csv: file contains the x,y coordinates for the restoration material’s that refer to any type of seed used in a restoration treatment (e.g., germplasms, cultivars, wild-collected, source-identified, etc.). **** Step 7: create the 'species abbreviation'_germplasm_locs shapefiles. In ArcCatalog, navidate to the location of the accession.data.csv for each species and right-click on the accession.data.csv file. Select Create Feature Class > From XY Table. Select the following paramaters: X Field: (x); Y Field (y); Z Field (<None>); select the 'Coordinate System of Input Coordinates' and navigate to Geographic Coordinate Systems > World > WGS 1984; Output ('species abbreviation'_germplasm_locs, Save as type: Shapefile). Select 'Advanced Geometry Options' to review the 'Use a different spatial reference' as GCS_WGS_1984, then select 'OK'. 2021 Development of 'species abbreviation'_habitat shapefiles: These shapefiles were created from a raster species distribution modelc that was developed using ecological analysis software MAXENT (https://biodiversityinformatics.amnh.org/open_source/maxent/). The raster species distribution models were then converted to a polygon based on a minimum threshold value using ESRI ArcMap. **** Step 1: acquire source data for each species from SEINET (swbiodiversity.org) and remove occurrences recorded prior to 1995 as georeferencing prior to this time is often estimated based on herbarium label descriptions and may be inaccurate (put in 1_SourceData/SEINET folder, and name files 'species abbreviation'_SEINET). Next acquire bioclimatic variables from WorldClim's historical climate dataset, selecting 30 seconds (bio 30s) (https://www.worldclim.org/data/worldclim21.html) (put in 1_SourceData/WorldClim folder). Last, acquire a polygon shapefile of the Colorado Plateau, Arizona/New Mexico Mountains, and Arizona/New Mexico Plateaus from the U.S. Environmental Protection Agency, Level III and IV Ecoregions of the Continental United States (https://www.epa.gov/eco-research/level-iii-and-iv-ecoregions-continental-united-states) (put in 1_SourceData/EPA folder). **** Step 2: Open ESRI ArcMap and add the 19 bioclim variables to the table of contents. Add the SDM Toolbox v2.4 (http://www.sdmtoolbox.org/) to ArcToolbox. Then, extract the cells of the raster datasets (19 bioclim variable grids) that correspond to the areas defined by a mask of the Colorado Plateau (polygon shapefile in 1_SourceData/EPA folder) using '1a. Extract by Mask (Folder)' script tool (SDM Toolbox v2.4/Basic Tools/Raster Tools) and save these 19 bioclim variable raster datasets to a new folder (Habitat/2_Mask) with the file name ('bioclim variable name'_Mask). **** Step 3: in the SDM Toolbox v2.4 use the 2a. Raster to ASCII script tool (SDM Toolbox v2.4/Basic Tools/Raster Tools) to convert all 19 masked bioclim variable rasters (Habitat/2_Mask/'bioclim variable name'_Mask) that were created in Step 2 to ASCII files of the same name ('bioclim variable name'_Mask.asc). The 19 bioclimatic variables are now ready to be used in MAXENT application. Save these ASCII files to the Habitat/3_ASCII folder. **** Step 4: calculate climate heterogeneity using 3 principal componant analysis. Open the 2a. Calculate Climate Heterogeneity: Step 1- Principal Component Analysis script tool in the SDM Toolbox v2.4 (SDM Toolbox v2.4/SDM Tools/1. Universal Tools/Spatially Rarefy Occurence Data for SDMs). Apply the following script tool parameters: Input Climate Rasters (19 masked bioclim variable rasters from Habitat/2_Mask folder); Output Folder (create a new folder (Habitat/4_PCA/'species abbreviation') to save the results); Output Filename (name each text file 'species abbreviation'_Summary_PCA.txt). **** Step 5: calculate climate heterogeneity to use for rarefying occurrence data at several distances using the 2b. Calculate Climate Heterogeneity: Step 2- Heterogeneity Calculation script tool from the SDM Tools toolbox. Individually input each output PCA raster dataset that was created in Step 4 (Habitat/4_PCA folder, 'species abbreviation'_Summary_PCA.txt file). Tool parameters: Neighborhood Values (select Rectangle); Neighborhood Settings (Height - 19, Width - 19, Units - cell); Percent of Eigenvalues of PC1 (from the previous step, open the 'species abbreviation'_Summary_PCA.txt file and go to the bottom of the text file to locate the section “PERCENT AND ACCUMULATIVE EIGENVALUES” and input the the Percent of Eigenvalues for PC Layer = 1); Percent of Eigenvalues of PC2 (from the previous step, open the 'species abbreviation'_Summary_PCA.txt file and go to the bottom of the text file to locate the section “PERCENT AND ACCUMULATIVE EIGENVALUES” and input the the Percent of Eigenvalues for PC Layer = 2); Percent of Eigenvalues of PC3 (from the previous step, open the 'species abbreviation'_Summary_PCA.txt file and go to the bottom of the text file to locate the section “PERCENT AND ACCUMULATIVE EIGENVALUES” and input the the Percent of Eigenvalues for PC Layer = 3); Output Folder (create a climate heterogeneity folder for the raster datasets (Habitat/5_CH/'species abbreviation'); Output Filenam (name each text file 'species abbreviation'_CH). **** Step 6: create an unbiased sample of the species occurrence data using the 1. Spatially Rarefy Occurence Data for SDMs (reduce spatial autocorrelation) script tool to remove spatially autocorrelated occurrence points by reducing multiple occurrence records to a single record within the specified distance before importing it into MAXENT. Select the 1. Spatially Rarefy Occurence Data for SDMs (reduce spatial autocorrelation) script tool (SDM Toolbox v2.4/SDM Tools/Spatially Rarefy Occurence Data for SDMs). Complete the following parameters: Input Point Shapefile of Occurrence Data (each species occurrence point shapefile acquired from the SEINet data portal (1_SourceData/SEINET folder, and files 'species abbreviation'_SEINET); Species Field (select species from the shapefile table); latitude Field (select latitude from the shapefile table); Longitude Field (select longitude from the shapefile table); Output Folder (create and select an output folder, Habitat/6_SRO/'species abbreviation'); Output Name (name the spatially rarefied occurrence data files, 'species abbreviation'_SRO); Resolution to Rarefy Data (default setting of 10 kilometers); Equidistance Projection (based on the mask of the Colorado Plateau, select Continent: USA Contiguous Equidistant Conic projection based). Open the 'Optional Parameters' and check the box to use multiple rarefying distances; Input the Heterogeneity Raster (optional) (select a 'species abbreviation'_CH.tif raster created Step 5); Number of Heterogeneity Classes (select 5); Classification Type (select NATURAL_BREAKS); Maximum Distance (select 25 kilometers); Minimum Distance (select 2 kilometers). The result will create a .csv file ('species abbreviation'_SRO.csv) of the spatially rarefied species occurrences for each species in the Habitat/6_SRO/'species abbreviation' folder. **** Step 7: The final step is to create maximum entropy modelling of each species’ geographic distributions using the MaxEnt program (https://biodiversityinformatics.amnh.org/open_source/maxent/). In Maxent, for "Samples" individually select a .csv file for one species of spatially spatially rarefy occurence (Habitat/6_SRO/'species abbreviation'_SRO.csv). Browse to the "Directory/File" folder (Habitat/2_Mask) with the bioclim variables that were masked to the Colorado Plateau and selct all 19 bioclim variables for the "Environmental Layers" parameter. Select "Create response curves" and “Make pictures of predictions” parameters. Select "Output format" (Logistic) and "Output file type (.asc). For the Output Directory parameter, Indicate the location (Output directory parameter) where each species distribution model will be saved (Habitat/7_Maxent/'species abbreviation'). For the Projection layers directory/file parameter, select the folder containing the 19 bioclim variables in ASCII format (Habitat/3_ASCII). Next, select 'Settings parameter' and input 20 in the “Random test percentage” parameter with the Replicated run type: Crossvalidate. Then, press the “Run” button. The folder created by Maxent (7_Maxent/'species abbreviation') for the output files will have the 20 cross validations as well as a raster dataset (.tif) of the average of all cross validations. The file labeled 'species abbreviation'_avg.tif is the species distribution raster used in this analysis and is the final output. **** Step 8: reclassify the 'species abbreviation'_avg.tif (7_Maxent/'species abbreviation') in ArcMap using the Reclassify tool (Spatial Analyst Tools/Reclass). First, open the EXCEL file labeled 'species abbreviation'_maxentResults.xls (7_Maxent/'species abbreviation' folder) and locate the row labeled 'species abbreviation' (average) and the column labeled "Minimum training presence Logistic threshold". The value in the corresponding cell indicate the values in the raster data where the species is not projected to exist based on a generous threshold model. Then, open the Reclassify tool, input each 'species abbreviation'_avg.tif file individually, delete all of the rows and then using the 'species abbreviation'_maxentResults.xls file with the value in the "Minimum training presence Logistic threshold" column reclassify the raster as follows: row 1) Old values: enter 0 – (Minimum training presence Logistic threshold value) | New values: NoData row 2) Old values: enter (Minimum training presence Logistic threshold value) – 1 | New values: 1 row 3) Old values: enter NoData | New values: NoData. Save the output reclassified raster dataset to the Habitat/8_Reclass folder and name each raster 'species abbreviation'_reclass. **** Step 9: create a polygon shapefile for each species habitat on the Colorado Plateau by converting the reclassified raster datasets in ArcMap using the Raster to Polygon tool (Conversion Tools/From Raster toolset) which represent only the predicted species habitat (based on the "Minimum training presence Logistic threshold"). Select the following paramaters: Input Raster ('species abbreviation'_reclass from the Habitat/8_Reclass folder); Field (optional) (select field 'gridcode'; Output Polygon Features ('species abbreviation'_poly); Simplify polygons (optional). Save the polygon shapefiles for each species to the Habitat/9_Poly_Shp folder. **** Step 10: aggregate the polygon features on a specified attribute in ArcMap using the Dissolve tool (Data Management Tools/Generalization toolset) to create one species habitat polygon for each species. Select the following paramaters: Input Features ('species abbreviation'_poly from the Habitat/9_Poly_Shp folder); Output Feature Class ('species abbreviation'_dissolve); Dissolve_Field (optional) (select 'gridcode'). Save the dissolved polygon shapefiles for each species to the Habitat/10_Poly_Shp_Dissolve folder. **** Step 10: using ArcCatalog, copy each dissolved species habitat polygon shapefile ('species abbreviation'_dissolve in the Habitat/10_Poly_Shp_Dissolve folder) to the Habitat/11_Final folder and rename each species habitat polygon shapefile ('species abbreviation'_habitat). **** Step 11: project 'species abbreviation'_habitat shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_unsuitable_3partitions shapefiles: The 'species abbreviation'_habitat and 'species abbreviation'_unsuitable_germplasms shapefiles are required before creating the 'species abbreviation'_unsuitable_3partitions shapefiles. The Native Plant Seed Toolkit (https://www.usgs.gov/apps/seed-toolkit/) was used to create these shapefiles. **** Step 1: Choose application - select the Climate Partitioning Tool which divides climate space into a selected number of most-differentiated groups across a defined geographic area. **** Step 2: Define a geographic area - select Spatial Polygon to upload a spatial polygon. Browse to the folder with the all 12 'species abbreviation'_habitat shapefiles. Upload each species habitat shapefile individually to visualize the climatic similarity between a restoration material’s (RM’s) location of origin and a defined geographic area. Shapefiles were uploaded as zipped folder that included the following components: .shp, .shx, .dbf, prj. **** Step 3: Select a seed source - do not select a seed source. **** Step 4: Select number of partitions - select 3 climate partitions. **** Step 5: Weight climate variables - select all 7 of the climate variables with the same weight = 1. **** Step 6: Generate Partitions - press to run the Climate Partitioning Tool. After the Climate Partitioning Tool has completed processing, select the Download Results and Data button and download the ZIP file to the ClimatePartitionsTool/'species abbreviation' folder. The downloaded results and data for a single species habitat will produce a ZIP file (climate_partitioning_data_yyyy-mm-dd.zip). Rename the ZIP file to 'species abbreviation'_climate_partitioning_data_yyyy-mm-dd.zip. Extract the folder (tmp) in the ZIP file using a file archiver utility (such as 7-Zip, WinZip). Inside the tmp folder is another folder with 5 files inside. Run the tool for the remaining 11 species habitats and save the zip files into the appropriate Climate_Partitioning/'species abbreviation' folder. **** Step 7: Open ESRI ArcCatalog, navigate to the first Climate_Partitioning/'species abbreviation' folder where the 6 files are and locate the assignment.tif raster dataset. **** Step 8: create a polygon shapefile for each species with the 3 climate partitions within a species habitat by converting each of the 12 species raster datasets (assignment.tif) in ArcMap using the Raster to Polygon tool (Conversion Tools/From Raster toolset). Save each polygon shapefile as 'species abbreviation'_assign_poly.shp. **** Step 9: aggregate the polygon features on a specified attribute in the 'species abbreviation'_assign shapefiles using the Dissolve tool (Data Management Tools/Generalization toolset) to create a single polygon that represents a single polygon for each of the 3 climate partitions. Select the following paramaters: Input Features ('species abbreviation'_assign_poly); Output Feature Class ('species abbreviation'_assign_diss); Dissolve_Field (optional) (select 'gridcode'). Save the dissolved polygon shapefiles for each species as, 'species abbreviation'_assign_diss.shp. **** Step 10: copy each 'species abbreviation'_assign_diss.shp to new shapefiles named, 'species abbreviation'_habitat_3partitions **** Step 11: use the Clip tool (Analysis Tools/Extract) to clip the 'species abbreviation'_unsuitable_germplasms.shp to the climate partitions polygon shapefile ('species abbreviation'_habitat_3partitions) and save the new shapefile as, 'species abbreviation'_unsuitable_3partitions.shp. **** Step 12: project 'species abbreviation'_unsuitable_3partitions shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_unsuitable_germplasms shapefiles: The 'species abbreviation'_habitat and 'species abbreviation'_germplasms shapefiles are required before creating the 'species abbreviation'_unsuitable_germplasms shapefiles. **** Step 1: copy the 'species abbreviation'_germplasms shapefiles and rename them as 'species abbreviation'_germplasms_2 **** Step 2: aggregate the polygon features on a specified attribute in the 'species abbreviation'_germplasms_2 shapefiles using the Dissolve tool (Data Management Tools/Generalization toolset) to create a single polygon that represents all of the areas within an individual species habitat where all currently existing germplasms are well suited to exist. Save the dissolved polygon shapefiles for each species as, 'species abbreviation'_germplasms_dissolve.shp. **** Step 3: use the Symmetrical Difference tool (Analysis Tools/Intersect toolset) to compute the geometric intersection of the input features ('species abbreviation'_germplasms_dissolve) and update features ('species abbreviation'_habitat). Features or portions of features in the input and update features which do not overlap were written to the Output Feature Class ('species abbreviation'_unsuitable_germplasms shapefiles). **** Step 4: if there are multiple polygons in the attribute tables of the 'species abbreviation'_unsuitable_germplasms shapefiles, it is recommended to aggregate the polygon features on a specified attribute using the Dissolve tool (Data Management Tools/Generalization toolset) to create a single polygon that represents the areas within each modeled species habitat where no germplasms are well suited to exist. **** Step 12: project 'species abbreviation'_unsuitable_germplasms shapefiles from GCS WGS84 to USA Contiguous Albers Equal Area Conic USGS and add geometry attributes (POLY_AREA, PERIMETER, and Area_sqkm). 2021 Development of 'species abbreviation'_shapefiles: **** Step 1: **** Step 2: **** Step 3: 2021 Data Quality Assessment and Quality Control (QAQC): Quality Assurance (QA) - Quality assurance measures were taken to ensure accurate processing of data and to ensure that data issues were prevented. Published written criteria, methods and processes from ESRI and documentation in the SDM Toolbox were followed to ensure the data products met specified quality standards. Spatial data was processed using various tools in ESRI ArMap, including tools from the SDM Toolbox (Brown et. al. 2021). This included following recommended data processing steps including using the correct transformation when projecting data and converting or geoprocessing geographic and raster data appropriately according to established tutorials and protocols (https://desktop.arcgis.com/en/arcmap/latest/analyze/main/what-is-geoprocessing.htm, https://desktop.arcgis.com/en/arcmap/latest/tools/main/a-quick-tour-of-geoprocessing-tool-references.htm and http://www.sdmtoolbox.org/technical-info). Quality Control (QC) – Established data quality control protocols and methods were employed to ensure that data issues were prevented. Published methods and protocols from ESRI and SDM Toolbox were followed to determine whether data meet overall quality goals and defined quality criteria for individual values before and after geoprocessing data. Each ArcGIS or SDM tool parameter was input correctly to conduct data processing for the correct output. If an error resulted from data processing, a review of the error code in the geoprocessing step from the 'Results' message was performed to understand the error (description), and solution. All data created from using geoprocessing tools were checked based on geometry and table results to ensure they were as expected based on the online geoprocessing tool reference. These steps were followed for each geoprocessing step until the final data product was created. Additionally, prior to spatial data processing all data, including source data, that were originally in GCS WGS84 were projected into USA Contiguous Albers Equal Area Conic USGS to perform spatial calculations. Raster datasets ('species name'_avg.tif) were converted to polygon shapefiles ('species name'_habitat) using the Raster to Polygon geoprocessing tool. The parameter "Simplify polygons (optional)" was not unchecked which resulted in polygons being smoothed into coarse and simpler shapes and did not conform exactly to the input raster's cell edges thus reducing the modeled habitat from Maxent to a smaller overall area. 2022 Finalize Data for Dissemination: Data sent to the Southwest Biological Science Center Data Steward for dissemination and preservation per USGS Data Management Policies SM 502.6, SM 502.7, SM 502.8 and SM 502.9 (1 October 2016). 2023 Vector USA Contiguous Albers Equal Area Conic USGS 29.5 45.5 -96.0 23.0 0.0 0.0 coordinate pair 0.000100 0.000100 meters North American Datum 1983 GRS 1980 6378137.0 298.257222101 'species name'_avg.tif These raster datasets represent the average of distribution model replicates for each species. The purpose of this raster dataset is to provide a cross-validated model for each species’ distribution and is to be converted to a binary (estimated presence or absence) raster in subsequent processing steps. Producer defined Value Decimal values represent each pixel’s modeled minimum logistic presence threshold value based on 20 model replicates performed using the Maxent software application. Producer defined 0.0000136665003083186 0.9915940165519714 decimal number 'species abbreviation'_disturb These shapefiles represent all areas within a modeled species habitat that are disturbed by one or many of the following disturbance types: wildfire (footprints of wildfires between 2000 and 2019), grazing (USFS and BLM active grazing allotments), and energy (disturbance present from energy production oil and gas wells, coal mines, and natural gas pipelines). These shapefiles have 3 polygons representing each of the disturbance types distributed across a species habitat. The purpose of these shapefiles are for land managers and restoration practitioners to visualize how much of a modeled species habitat is disturbed and will potentially need native plant restoration in the future. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 2 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. disturb The attribute in the shapefile table represents the type of disturbance isolated in each polygon. Producer defined energy The attribute value indicates areas that were disturbed by oil and natural gas wells, coal mines, and natural gas pipelines. Producer defined grazing The attribute value indicates active U.S. Forest Service and Bureau of Land Management livestock grazing allotments. Producer defined wildfire The attribute value indicates wildfire footprints that burned between 2000 and 2019. Producer defined Species The attribute in the shapefile table represents the species code for the species' habitat. Producer defined 'species abbreviation' depending on the species shapefile POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 6520913734.11 137721474339 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 11660277.803 41509417.3974 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 6520.91373411 137721.474339 square kilometers 'species abbreviation'_disturb_germplasms These shapefiles (ACHY, BOGR, ELEL, MACA, PLJA, SPCR only) represent all areas within a modeled species habitat that are disturbed that also have a commercially available germplasm modeled to have high suitability to exist in those disturbed areas. High suitability is defined as an area that has an 80% or greater climate similarity match as the source location for that germplasm (as modeled using the Native Plant Seed Toolkit: https://www.usgs.gov/apps/seed-toolkit/). These shapefiles contain 24 polygons, each representing a disturbance type (wildfire, grazing, or energy) and a germplasm that is well suited to exist within those disturbed areas. The purpose of these shapefiles are for land managers and restoration practitioners to visualize where a species commercially available germplasms are and can be used for restoration within specifically disturbed areas. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 23 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. dist_germ This attribute 'dist_germ' in the shapefile table represents the disturbance type (energy, grazing, or wildfire) and the modeled climate similarity (high suitability) within each area of disturbance. The attribute values represent each species commercially available germplasms isolated to where they are highly suited to exist within each of the specific disturbed areas. Producer defined 0 1 integer number POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 1864410.5126 82603009894.5 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 10572.7708558 33451033.0338 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 1.8644105126 82603.0098945 square kilometers 'species abbreviation'_disturb_unsuitable These shapefiles represent all areas within a modeled species habitat that have either one or multiple disturbances present (energy, wildfire, or grazing), that DO NOT have a commercially available germplasm well suited to exist in those disturbed areas. Well suited indicates the areas have at least an 80% climate similarity match the germplasm's source location as modeled using the Native Plant Seed Toolkit (https://www.usgs.gov/apps/seed-toolkit/). The purpose of this shapefile is for land managers or restoration practitioners to visualize disturbed areas where a species commercially available germplasms DO NOT have high suitability to source for native plant restoration work. These areas illustrate where new native plant material collections will be needed in the future. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 2 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. Species The attribute in the shapefile table represents the species code for the species' habitat. Producer defined USDA Plants Database https://plants.usda.gov/home POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 6520913734.11 137721474339 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 11660277.803 41509417.3974 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 6520.91373411 137721.474339 square kilometers 'species abbreviation'_disturb_unsuitable_3partitions These shapefiles represent disturbed (energy, wildfire, or grazing) areas within a modeled species habitat that do not have a commercially available germplasm well suited to exist divided into 3 climatically distinct partitions (areas with distinct environmental similarities across a geographic region). Well suited indicates areas that have at least an 80% climate similarity match to the germplasm's source location as modeled using the Native Plant Seed Toolkit's Seed Selection tool (https://www.usgs.gov/apps/seed-toolkit/). Climate partitions were created using the Native Plant Seed Toolkit's Climate Partitioning tool. The purpose of this shapefile is for land managers or restoration practitioners to visualize climatically similar partitions within disturbed areas unsuitable to a species commercially available germplasms to source new native plant material. These areas illustrate where new native plant material collections will be most needed for restoration as well as for the lack of available plant materials. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 2 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. gridcode This attribute in the shapefile table represents the climate partition number. The attribute values represent one of 3 climate partitions that were created using the Native Plant Seed Toolkit's Climate Partitioning tool (https://www.usgs.gov/apps/seed-toolkit/). Each climate partition represents areas with similar environmental gradients across a geographic region. Producer defined 1 3 integer number POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 3854877987.59 10378804148.1 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 5875830.40583 13724254.2536 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 3854.87798759 10378.8041481 square kilometers 'species abbreviation'_germplasms These shapefiles represent areas within a modeled species habitat where commercially available germplasms are well suited to exist. Well suited indicates areas that have at least an 80% climate similarity match to the germplasm's source location as modeled using the Native Plant Seed Toolkit's Seed Selection tool (https://www.usgs.gov/apps/seed-toolkit/). This shapefile contains 8 polygons, one for each species germplasm's well suited habitat. The purpose of this shapefile is to illustrate areas where land managers and restoration practitioners can use commercially available germplasms that are climatically well suited to exist. This shapefile is also intended to help pinpoint precisely which germplasm to order and utilize in native plant restoration. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 7 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. germplasm This attribute in the shapefile table represents the name of the germplasm for a polygon. A germplasm is a collection of genes for use in the improvement of plants. Producer defined This attribute values refer to the source location of the native plant material area: Amethyst, Antelope Creek, Asotin, Bonneville, Borden, CRNG, Delta, Fish Creek, Hachita, La Plata, Lovington, Massedona, Nezpar, Paloma, Pleasant Valley, Pueblo, Rattlesnake, Rimrock, Sand Hallow, Shaniko Star Lake, Toe Jam Creek, Turkey Lake, Tusas, Viva, Wapiti, Western, White River. POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 463454523.207 179145622335 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 403952.331596 27471900.975 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 463.454523207 179145.622335 square kilometers 'species abbreviation'_germplasm_locs These shapefiles (ACHY, BOGR, ELEL, MACA, PLJA, SPCR only) represent the source locations for each species available commercially released germplasms. Each location is labeled according to it's corresponding germplasm. The source location refers to the location a specific set of seed that was collected before being grown out for widescale harvest, production, and distribution. The germplasms were developed by the U.S. government and non-government plant materials programs to support restoration and reclamation. The purpose of this shapefile is for land managers and restoration practitioners to not only visualize the location of each germplasm's source material but to also use the locations for future climate similarity analysis. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 7 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as points. id A unique identifier which is a character string associated with the point feature. Producer defined This attribute values refer to the species code for the species' habitat and the source location of the native plant material area. Species The attribute in the shapefile table represents the species code for the species' habitat. Producer defined USDA Plants Database https://plants.usda.gov/home POINT_X The angular distance of the location of a point on the earth's surface, usually measured in degrees east or west of the Greenwich prime meridian. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI -115.7237432 -104.71 decimal degrees POINT_Y The angular distance of the location of a point on the earth's surface, usually measured in degrees north or south of the equator. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 35.7152472 45.97 decimal degrees 'species abbreviation'_habitat This shapefile represents a modeled species habitat. This species distribution model is used as the bounding polygon for the other shapefiles in a species dataset. The species distribution model was created using species occurrence data sourced from SEINET (www.swbiodiversity.org) and all 19 Bioclimatic variables from WorldClim's historical climate dataset (https://www.worldclim.org/data/bioclim.html ). The species distribution model was created using the bioanalytical software MAXENT (https://biodiversityinformatics.amnh.org/open_source/maxent/). The purpose of this shapefile is to illustrate areas on the Colorado Plateau and environs where a species has suitable habitat to exist. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 0 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. Species The attribute in the shapefile table represents the species code for the species' habitat. Producer defined USDA Plants Database https://plants.usda.gov/home POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 288935137616 288935137616 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 15931234.4235 15931234.4235 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 288935.137616 288935.137616 square kilometers 'species abbreviation'_unsuitable_3partitions These shapefiles represent a modeled species habitat that DOES NOT have a commercially available germplasm well suited to exist that are split into 3 climatically distinct partitions (areas with distinct environmental similarities across a geographic region). Well suited indicates areas have at least an 80% climate similarity match to the germplasm's source location as modeled using the Native Plant Seed Toolkit's Seed Selection tool (https://www.usgs.gov/apps/seed-toolkit/). Climate partitions were created using the Native Plant Seed Toolkit's Climate Partitioning tool to visualize the geographic distribution of environmental gradients across a region. The purpose of this shapefile is for land managers or restoration practitioners to visualize climatically similar partitions within disturbed areas unsuitable to a species commercially available germplasms to source new native plant material. These areas illustrate where new native plant material collections will be most needed for restoration as well as for the lack of available plant materials. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 2 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. gridcode This attribute in the shapefile table represents the climate partition number. The attribute represents one of 3 climate partitions that were created using the Native Plant Seed Toolkit's Climate Partitioning tool (https://www.usgs.gov/apps/seed-toolkit/). Each climate partition represents areas with similar environmental gradients across a geographic region. Producer defined 1 3 integer number POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 5391677437.85 22352961370.1 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 7361093.49522 20655280.1545 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 5391.67743785 22352.9613701 square kilometers 'species abbreviation'_unsuitable_germplasms These shapefiles (ACHY, BOGR, ELEL, MACA, PLJA, SPCR only) represent areas within a modeled species habitat where NONE of the commercially available germplasms are well suited to exist. Well suited indicates that an area must have at least an 80% climate similarity match to the germplasm's source location as modeled using the Native Plant Seed Toolkit's Seed Selection tool (https://www.usgs.gov/apps/seed-toolkit/). The purpose of this shapefile is for land managers and restoration practitioners to visualize how much of a species habitat is not suitable to currently available restoration materials. Producer defined FID In ArcGIS, a system-managed value that uniquely identifies a record or feature. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 0 0 integer number Shape In ArcGIS, the characteristic appearance or visible form of a geographic object as represented on a map. ESRI Geogrphic objects are represented as polygons. Species The attribute in the shapefile table represents the species code for the species' habitat. Producer defined USDA Plants Database https://plants.usda.gov/home POLY_AREA In ArcGIS, the area of polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 43875809337.8 43875809337.8 square meters PERIMETER In ArcGIS, the total length of the polygon perimeter. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. ESRI 37435903.2158 37435903.2158 meters Area_sqkm This attribute in the shapefile table represents the total area in square kilometers for each polygon. Minimum and maximum values are represented by the ACHY species only. Check each shapefile for the range of values. Producer defined 43875.8093378 43875.8093378 square kilometers GS ScienceBase U.S. Geological Survey mailing and physical

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov The author(s) of these data request that data users contact them regarding intended use and to assist with understanding limitations and interpretation. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. These zip files contain data available ESRI shapefile format (.shp), and tagged-image file format (.tif). The user must have software capable of uncompressing the zip files and displaying the vector feature class shapefiles and raster data. 20231114 Robert T Massatti U.S. Geological Survey Research Ecologist mailing and physical

2255 North Gemini Drive

Flagstaff AZ 86001 United States 928-556-7304 rmassatti@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998