General Information Metadata for 2022 MESM Group Project Title of Dataset: Estimating Mountain Lion Habitat Connectivity to Guide Wildlife Conservation at The Nature Conservancy’s Jack and Laura Dangermond Preserve Author Information Data Manager I Contact Information: Name: Nikole Vannest Institution: UCSB Bren School Email: nvannest@bren.ucsb.edu Alternative Email: nikolevannest@gmail.com Data Manager II Contact Information: Name: Grace Kumaishi Institution: UCSB Bren School Email: gkumaishi@bren.ucsb.edu Date Collected: 2021-05-01 to 2022-03-01 Geographic Location of Data: Northwest coordinates (Lat/Long): 36.9741° N, 122.0308° W (Santa Cruz) Southeast Coordinates (Lat/Long): 34.0195° N, 118.4912° W (Santa Monica) Sharing/Access Information No licenses/restrictions are associated with this dataset. Data, Sources & Methods NASA | USGS | JPL-CalTech: NASA Shuttle Radar Topography Mission (SRTM) SRTM data is a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA), as well as German and Italian space agencies. The goal of SRTM is to produce a digital elevation model (DEM) of the Earth at a near-global scale. This data is provided by NASA (JPL) at a resolution of 1-arc second (~30m). We will use this data to aid in determining the suitability of the landscape for mountain lions along the Central and Southern California coastline. To do this we need to pull two variables utilizing scripts written in Javascript via GUI Google Earth Engine (GEE): Slope and Elevation. The variables below can be downloaded from the GEE script here: https://code.earthengine.google.com/a4f9383002943e57fa34c2c2c7a79ace?noload=true. 1. Elevation.asc - Elevation from the year 2000, defined by a DEM with a resolution of approximately 30m. In .asc format for use in Maxent. 2. Slope.asc - Slope derived from elevation band in the year 2000, defined in degrees. In .asc format for use in Maxent. Conservation Science Partners (CSP): Ecologically Relevant Geomorphology (ERGo) Data The CSP ERGo contains datasets whose goal is to provide applicable maps that are useful for climate adaptation planning. ERGo datasets are derived from SRTM DEM 30m satellite data. We plan to use three layers from the CPS, Landform, mTPI, and TD (described below). We will use this data to aid in determining the suitability of the landscape for mountain lions along the Central and Southern California coastline. To do this we need to pull two variables utilizing scripts written in Javascript via GUI Google Earth Engine (GEE): Slope and Elevation. The variables below can be downloaded from the GEE script here: https://code.earthengine.google.com/a4f9383002943e57fa34c2c2c7a79ace?noload=true. 1. Landform.asc - The SRTM landform dataset makes available landform classes by combining the Continuous Heat-Insolation Load Index (CHILI) and the multi-scale Topographic Position Index (mTPI) datasets. Landform provides a categorical layer differentiating slope and ridge categories across the landscape. In the form of an .asc file for use in Maxent. 2. Td.asc - Topographic Diversity is a variable that represents moisture and temperature conditions as they vary within and across habitats. A higher variety of diverse niches should support a higher diversity of species, especially plants, and foster a more resilient system to climate change. TD was calculated using mTPI (T’) to determine hillslope position, then combined with the square root of mTPI and the standard deviation of CHILI calculated at multiple scales (C’): TD = 1 - ((1-T’) * (1-C’)). In .asc format for use in Maxent. California Department of Fish and Wildlife (CDFW): BIOS datasets Provided from a variety of researchers. Layers vary in date, resolution, and source but are all collected through CDFW. 1. Dellinger_resistance.tif - Resistance layer was created using a suitability layer as described by Dellinger et al. 2020. This layer will be used as a comparison to our results. CalFish: A California Cooperative Anadromous Fish and Habitat Data Program Information about water systems in California. The data was collected as a combined effort from CDFW, Pacific States Marine Fisheries Commission and their partners. 1. Streams.asc - California Streams was developed using NHD High Resolution linework at 1:24,000 scale or better. CDFW aims to update the dataset to reflect NHD improvements. In .asc format for use in Maxent. California Department of Forestry and Fire Prevention (CalFire): Land Use CalFire’s mission is to assess and protect the natural resources of California, which is accomplished through observation, assessment and study through the CalFire Resource Assessment Program (FRAP). We are utilizing two layers from CalFire, Landcover and Land Ownership to better understand the barriers that stand between a mountain lion and its ability to move across the Central and Southern California coastline. 1. Landcover (fVeg) - A raster layer of compiled ‘best available’ categorical land cover data, updated in 2015. We have used this data set to derive ‘distance to’ variables including: distance to shrub, forest cover, and open landscape using a Euclidean Distance tool in post-processing. Files in the form of: Barren_new.asc and Shrub.asc in .asc format for use in Maxent. United States Geological Survey (USGS): National Land Cover Database (NLCD) The NLCD is based on 30m Landsat satellite imagery and is created by the Multi-Resolution Land Characteristics (MRLC) Consortium - a partnership of federal agencies led by the USGS. NLCD images are classified into land cover types: urban, forest, shrub, water, etc. Urban classes rely on the imperviousness data layer and the rest on a decision tree classification. We pulled the urban layer from this dataset in order to determine the distance-to urban/impervious surfaces via the Euclidean distance tool in post-processing. Data was packaged and downloaded using Javascript via GUI Google Earth Engine (GEE): https://code.earthengine.google.com/a4f9383002943e57fa34c2c2c7a79ace?noload=true. The variables below can be downloaded from the GEE script here: This will help us determine probable barriers to mountain lion movement. 1. Urban_new.asc - Defined by the percent of a pixel covered by developed impervious surface(0- 100%), images last updated in 2016. In .asc format for use in Maxent. US Census: Data from the United States Census Bureau Shapefiles are updated yearly by the census bureau. Current layers are updated as of January 1, 2021. 1. Road_new.asc-LayerofallprimaryroadsintheUS.Filtersonthewebsiteallowforonlythe primary roads within California to be downloaded. Road categories include: county, interstate, common name, other, state recognized, and U.S. This layer was modified to calculate the Euclidean distance to roads within California. In .asc format for use in Maxent. Miscellaneous: 1. Additional files created by group project members. 2. ROI_raster.tif - ROI was created in GEE using coordinates of interest and exported to be used in ArcGIS. Area encompassing nodes of interest in analysis spanning the Central and Southern California coast. 3. Resistance_270.tif - resistance layer created using habitat suitability model and a negative exponential equation in ArcGIS. 4. Regional_analysis.ipynb - script used in Julia coding language to create Omniscape analysis results based on resistance_270.tif data.