AndreaBozzo/ceres-open-data-index huggingface dataset:
Working Lands View

◦Overview: A key principle of Landscape Conservation Design is that “Stakeholders design landscape configurations that promote resilient and sustainable social-ecological systems” (Campellone et al, 2018). From Campellone et al: (2018): “A beneficial aspect of stakeholder engagement in spatial design is the development of a deeper trust that the models used to identify priorities integrate their interests with other information and knowledge, which furthers social learning and collective agreement on resource allocation and landscape objectives” (Melillo et al., 2014). Overall, the co-development of a spatial design helps organize landscape elements while maintaining and improving stakeholder buy-in” (De Groot, Alkemade, Braat, Hein, & Willemen, 2009; Melillo et al., 2014).” ◦Analytical Question: Create a prototype landscape design (blueprint) that integrates multiple values on the landscape including wildlife conservation, forest and agriculture production, recreation, cultural and human health. The prototype will be created based upon readily available data.This analysis will be used to understand landscape-scale conservation and working landscape priorities, while incorporating other important values.The blueprint will be used to represent a sustainable landscape in the future. ◦Desired Outcome: A map or maps that represents a balance of multiple values on the landscape, with a focus on conservation and working landscape values.
Eastern Time Stamps

This storymap visualizes data from Piping Plovers that were tagged at nesting areas in southern New England and tracked during fall migration using the Motus network (www.motus.org). The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Explore the map below to see how Piping Plovers take flight and make their away across the Atlantic--sometimes flying as fast as 80 km an hour. For migrating plovers, wind and weather conditions play an important role in their flight departures; and stopover sites in the Mid-Atlantic provide critical habitat for rest and refueling. Here in this map, you can look at how nano-tagged Piping Plovers from Rhode Island and Massachusetts timed their migration flights with wind conditions. The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Story Map Created by Alex Cook, USFWS Directorate Fellowship Program 2020 Cohort
2017 Piping Plover Migrations

This storymap visualizes data from Piping Plovers that were tagged at nesting areas in southern New England and tracked during fall migration using the Motus network (www.motus.org). The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Explore the map below to see how Piping Plovers take flight and make their away across the Atlantic--sometimes flying as fast as 80 km an hour. For migrating plovers, wind and weather conditions play an important role in their flight departures; and stopover sites in the Mid-Atlantic provide critical habitat for rest and refueling. Here in this map, you can look at how nano-tagged Piping Plovers from Rhode Island and Massachusetts timed their migration flights with wind conditions. The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Story Map Created by Alex Cook, USFWS Directorate Fellowship Program 2020 Cohort
MOTUS Radio Towers

This storymap visualizes data from Piping Plovers that were tagged at nesting areas in southern New England and tracked during fall migration using the Motus network (www.motus.org). The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Explore the map below to see how Piping Plovers take flight and make their away across the Atlantic--sometimes flying as fast as 80 km an hour. For migrating plovers, wind and weather conditions play an important role in their flight departures; and stopover sites in the Mid-Atlantic provide critical habitat for rest and refueling. Here in this map, you can look at how nano-tagged Piping Plovers from Rhode Island and Massachusetts timed their migration flights with wind conditions. The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Story Map Created by Alex Cook, USFWS Directorate Fellowship Program 2020 Cohort
Tagging Locations

This storymap visualizes data from Piping Plovers that were tagged at nesting areas in southern New England and tracked during fall migration using the Motus network (www.motus.org). The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Explore the map below to see how Piping Plovers take flight and make their away across the Atlantic--sometimes flying as fast as 80 km an hour. For migrating plovers, wind and weather conditions play an important role in their flight departures; and stopover sites in the Mid-Atlantic provide critical habitat for rest and refueling. Here in this map, you can look at how nano-tagged Piping Plovers from Rhode Island and Massachusetts timed their migration flights with wind conditions. The storymap is available at the following link: [https://storymaps.arcgis.com/stories/5bab01fc5fa445f58ee54c062b4d2f3d] Story Map Created by Alex Cook, USFWS Directorate Fellowship Program 2020 Cohort
AFSI_focal_geo

Conserving Shorebirds in the Atlantic Flyway. This storymap presents how partners are addressing threats to shorebirds and working to meet the Atlantic Flyway Shorebird Initiative's conservation goal of increasing focal shorebird populations 10% by 2025. For more information about the storymap or specific projects, contact Debra_Reynolds@fws.gov Please see the storymap at this link: [Conserving Shorebirds in the Atlantic Flyway (arcgis.com)] The great migration... Shorebirds cross thousands of miles each year from the barren tundra of the arctic to the wind swept beaches of Tierra del Fuego in the southern hemisphere. The majority of shorebirds breeding in Alaska and Canada spend their non-breeding period in South American or Caribbean countries. During migration, shorebirds face a multitude of challenges including: * finding sufficient food sources to fuel their long distant migrations; * avoiding predators; * competing for limited habitat; * adapting to a changing climate; and * succumbing to sport and subsistence hunting.
Cascades to Coast Landscape Collaborative: Threats

◦Overview: A key principle of Landscape Conservation Design is that “Stakeholders design landscape configurations that promote resilient and sustainable social-ecological systems” (Campellone et al, 2018). From Campellone et al: (2018): “A beneficial aspect of stakeholder engagement in spatial design is the development of a deeper trust that the models used to identify priorities integrate their interests with other information and knowledge, which furthers social learning and collective agreement on resource allocation and landscape objectives” (Melillo et al., 2014). Overall, the co-development of a spatial design helps organize landscape elements while maintaining and improving stakeholder buy-in” (De Groot, Alkemade, Braat, Hein, & Willemen, 2009; Melillo et al., 2014).” ◦Analytical Question: Create a prototype landscape design (blueprint) that integrates multiple values on the landscape including wildlife conservation, forest and agriculture production, recreation, cultural and human health. The prototype will be created based upon readily available data.This analysis will be used to understand landscape-scale conservation and working landscape priorities, while incorporating other important values.The blueprint will be used to represent a sustainable landscape in the future. ◦Desired Outcome: A map or maps that represents a balance of multiple values on the landscape, with a focus on conservation and working landscape values.
Historic_SeaOtter_Range

The following map shows the historic range of the Sea Otter around the pacific rim before the fur trade that extended from the Russian coast to the California coast during the colonization period where they population had almost went extinct. The sea otter’s brush with extinction began far away from those rocky shores, in the Russian Far East. Aboard the ship Svyatoy Petr (Saint Peter), Vitus Bering’s second Kamchatka expedition foundered in storms and wrecked near an uninhabited island, later named after Bering himself, who was buried there. From the moment Bering’s men returned home to Russia with sea otter pelts, the species was in mortal danger. It was 1742. With more hairs per square inch than those of any other mammal, the thick, lush furs fetched enormous sums.
Wells_All

The California Department of Conservation, Division of Oil, Gas and Geothermal Resources publishes a GIS feature class of well locations and its associated records across the state for use by the public. Data provided are projected in Teal Albers California North American Datum of 1983 for shapefiles and WGS84 Web Mercator projection for web feature service. Well Attributes include API Number, Operator Well Number, Well Status, Well Type, Operator Code, Operator Name, Lease Name, Field Name, Area Name, District, County, Section, Township, Range, Base Meridian, Latitude, Longitude, Elevation, Total Depth, Redrill Footage, Redrill Cancel Flag, Location Description, Comments, GIS Source, Dry Hole, Confidential Well, Directionally Drilled, Hydraulically Fractured, BLM Well, EPA Well, Spud Date, Completion Date, Abandoned Date.Well location values were collected using a submeter-accurate gps receiver (i.e., Trimble GeoXT). Some of the data provided herein are also displayed in the Division's WellFinder application (http://maps.conservation.ca.gov/doggr/index.html).
FWS MB Re-establishing Wedge-tailed Shearwater Colonies on Maui Nui

This data depicts the locations of re-establishing Wedge-tailed Shearwater colonies, including their jurisdiction, across Maui Nui, Hawai'i. This data comes from a USFWS and USGS breeding seabird database as well as data provided by Maui Nui Seabird Recovery Project.
ProjectAreasFishnetFeb12_2021

This layer is made up of cells that are approximately 40 acres in size that will be used to summarize the waterfowl accessibility to the specific cell that will also help create an updated pair accessibility map that is used to create a prioritization layer for use to direct conservation on the ground. The Realty division uses these maps in evaluations when considering areas for purchasing an easement on a piece of property. The layer is used to also help in allocation of Duck Stamp dollars throughout Regions 3 and 6. Migratory Bird Conservation Stamp dollars are used to purchase easements throughout the Regions.
2023 Carlsbad FWO Section 6 Acquisitions_WFL1

The U.S. Fish and Wildlife Service, in conjunction with our partners, provided funding through Section 6 grants to purchase lands in Riverside and San Diego Counties for conservation. These properties provide habitat and other import functions for numerous Threatened, Endangered or sensitive species. These layers included in this feature layer show the general locations of the properties that were acquired. Some locations also include the cost of the property, the habitat and/or species that will be protected, and the Congressional District where the property is located. Please visit our Carlsbad Fish and Wildlife 2023 Highlights report located here - [https://storymaps.arcgis.com/stories/b3fa89173d8e44b9bbc5f7fa8c7fe071], where you can learn about some of the accomplishments the Carlsbad Fish and Wildlife Office had during Fiscal Year 2023.
FWS MB Lanai 100 Feet Elevation Contours

The layer depicts 100 feet elevation contours for Lanai, Maui Nui, Hawai'i. Data is originally from the Hawaii Statewide GIS Project. Additional information and metadata can be obtained by contacting Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
FWS MB Maui County Major Roads

This layer depicts the road centerlines for Maui County as of October, 2018. Data is originally from the Hawaii Statewide GIS Program. Additional information and metadata can be obtained by contacting Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
FWS MB Wedge-tailed Shearwater Fallout Locations on Maui Nui

This dataset contains Wedge-tailed Shearwater fallout locations across Maui Nui. Data was provided by Maui Nui Seabird Recovery Project, who responds to reports of downed seabirds across Maui Nui. Data is from 2012 through 2020. The purpose of this data layer is to display all of the locations where fallout Wedge-tailed Shearwaters are reported and highlight the major fallout hotspots across Maui Nui.
ACJV_Project_tracking_objectives_activities_2023

This dashboard draws upon a live spreadsheet maintained by the ACJV to track progress towards goals identified in the Saltmarsh Bird, Saltmarsh Sparrow, Black Rail, and American Black Duck Conservation Plans. All plans are accessible [here]. This dashboard identifies all Strategies, Objectives, and Actions in each of the plans and tracks the ACJV’s progress in attaining these goals. The ACJV staff meet annually to update the information contained in this tool. This tool was last updated in October 2023. The next planned update will occur in October 2024. This dashboard draws upon a live spreadsheet maintained by the ACJV to track progress towards goals identified in the Saltmarsh Bird, Saltmarsh Sparrow, Black Rail, and American Black Duck Conservation Plans. All plans are accessible [here]. This dashboard identifies all Strategies, Objectives, and Actions in each of the plans and tracks the ACJV’s progress in attaining these goals. The ACJV staff meet annually to update the information contained in this tool. This tool was last updated in October 2023. The next planned update will occur in October 2024.
Idaho and Montana Terrestrial Priorities

This layer includes priorities from the Idaho Crucial Habitat Assessment and the Montana State Wildlife Action Plan. We used the Western Association of Fish and Wildlife Agencies’ Critical Habitat Assessment Tool to identify Idaho state wildlife priorities. From CHAT statewide data, we selected hexagons where terrestrial species of concern (ter_soc) rank = 1 OR terrestrial species of economic or cultural importance (ter_seri) rank = 1. We dissolved results to produce polygons. We identified Montana wildlife priorities based on the State Wildlife Action Plan’s terrestrial focal areas. We extracted those areas within our analysis area and merged with the Idaho priority areas to create a region-wide layer. Please see any use limitations on web sites https://www.wafwachat.org/ and https://gis-mtfwp.hub.arcgis.com/datasets/0b4106262f154e5295fda61ef6c8f1cf_0/explore
High Divide LCD Boundary

Geographic boundary for the High Divide LCD in Montana and Idaho. The High Divide region located in eastern Idaho and western Montana, covers approximately 138,000 km2, contains the headwaters of the Missouri and Columbia watersheds and is vital for maintaining current and potential connectivity across privately owned lands between the Greater Yellowstone Ecosystem, the Central Idaho Wilderness, and the Crown of the Continent ecosystem. The High Divide collaborative has successfully worked to protect and sustain spawning habitat for anadromous fish from the Pacific Ocean, the region’s outstanding opportunities for outdoor recreation, and its working ranchlands in a region susceptible to entrenched, polarized views on conservation. The Landscape Conservation Design process provides a framework to continue to bring many of these seemingly opposing interests together over a common concern for the High Divide to produce a shared, long-term, strategic landscape vision that ensures people living and working in the region can take action that will be sustained by the whole community. Without it, conservation endeavors would be disjointed between interest groups, and would most likely not have the input of the local communities, ultimately leading to patchwork and thus ineffective conservation efforts.
Grizzly Bear Connectivity polygon

Modeled grizzly bear pathways: Sells et al. (2023) modeled grizzly bear pathways based on sex in western Montana. We used Female_Directed and reclassified the top 33% of values as suitable. Reference: Sells, S. N., Costello, C. M., Lukacs, P. M., Roberts, L. L., & Vinks, M. A. (2023). Predicted connectivity pathways between grizzly bear ecosystems in Western Montana. Biological Conservation, 284, 110199. https://doi.org/10.1016/j.biocon.2023.110199
Ecological Integrity

From Belote et al. 2022, we used the middle tolerance scenario with a 150 m moving window and reclassified raster based on the mean value (.727). Everything above the mean was considered "suitable" connectivity. The layer was clipped to the analysis area and converted into a polygon. Dreiss et al. (2022) extracted raw data values on connectivity and climate flow for areas that were IDed as climate-informed corridors based on categorical connectivity and climate flow dataset (TNC 2020). The remaining values were rescaled to fall between 0 and 1. A second climate corridor dataset (Carroll et al. 2018) was similarly rescaled. These two datasets were combined and locations in the 80th percentile of the distribution of combined values were analyzed. Higher values in the dataset indicate more optimal climate corridors. From Dreiss et al. 2022, here we took the upper 66% of values from the climate-informed wildlife corridors, as the top 33% and 50% were both insufficient to show data in the region given the dataset's national scale. The layer was clipped to the analysis area and converted into a polygon. These two layers were combined using the Count Overlap tool.
SASRI High Resolution Spruce from 2018 NAIP Imagery

Source Data [The National Agriculture Imagery Program (NAIP) Color Infrared Imagery, captured in 2018] Processing Methods 1. downloaded NAIP imagery tiles for all Southern Appalachian sky islands with spruce forest type present. 2. Mosaiced individual imagery tiles by sky island. This step resulted in a single, seamless imagery raster dataset for each sky island. 3. Changed the raster band combination of the mosaiced sky island imagery to visually enhance the spruce forest type from the other forest types. Typically, the band combination was Band 2 for Red, Band 3 for Green, and Band 1 for Blue. 4. Utilizing the ArcGIS Pro Image Analyst extension, performed an image segmentation of the mosaiced sky island imagery. Segmentation is a process in which adjacent pixels with similar multispectral or spatial characteristics are grouped together. These objects represent partial or complete features on the landscape. In this case, it simplified the imagery to be more uniform by forest type present in the imagery, especially for the spruce forest type. 5. Utilizing the segmented mosaiced sky island imagery, training samples were digitized. Training samples are areas in the imagery that contain representative sites of a classification type that are used to train the imagery classification. Adequate training samples were digitized for every classification type required for the imagery classification. The spruce forest type was included for every sky island. 6. Classified the segmented mosaiced sky island imagery utilizing a Support Vector Machine (SVM) classifier. The SVM provides a powerful, supervised classification method that is less susceptible to noise, correlated bands, and an unbalanced number or size of training sites within each class and is widely used among researchers. This step took the segmented mosaiced sky island imagery and created a classified raster dataset based on the training sample classification scheme. 7. Reclassified the classified dataset only retaining the spruce forest type and shadows class. 8. Converted the spruce and shadows raster dataset to polygon.
SpruceFir_1996_SAMAB_SouthernAppalachianAssessment

Spruce/Fir layer developed as part of the 1996 SAMAB Southern Appalachian Assessment. Citation: Southern Appalachian Man and the Biosphere (SAMAB). 1996. The Southern Appalachian assessment. Reports 1-5. US Department of Agriculture, Forest Service, Atlanta.The Southern Appalachian Assessment URL: [https://www.landscapepartnership.org/ecosystem-risks-benefits/appalachian-assessments/the-southern-appalachian-assessment]
FWS MB Molokai 100 Feet Elevation Contours

The layer depicts 100 feet elevation contours for Lanai, Maui Nui, Hawai'i. Data is originally from the Hawaii Statewide GIS Project. Additional information and metadata can be obtained by contacting Hawaii Statewide GIS Program, Office of Planning, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
EcoConnectivityIntegrityDissolved

Integrity layer: This layer represents the composite count overlap of six polygon source data sets that consider ecosystem structure, function, and composition in order to estimate relative ecological integrity across the High Divide region. We define and estimate ecological integrity by assembling publicly available spatial data that describe “elements of composition, structure, function, and ecological processes” (after Parrish et al. 2003; Wurtzebach and Schultz 2016) as described below. Connectivity layer: From Belote et al. 2022, we used the middle tolerance scenario with a 150 m moving window and reclassified raster based on the mean value (.727). Everything above the mean was considered "suitable" connectivity. The layer was clipped to the analysis area and converted into a polygon. Dreiss et al. (2022) extracted raw data values on connectivity and climate flow for areas that were IDed as climate-informed corridors based on categorical connectivity and climate flow dataset (TNC 2020). The remaining values were rescaled to fall between 0 and 1. A second climate corridor dataset (Carroll et al. 2018) was similarly rescaled. These two datasets were combined and locations in the 80th percentile of the distribution of combined values were analyzed. Higher values in the dataset indicate more optimal climate corridors. From Dreiss et al. 2022, here we took the upper 66% of values from the climate-informed wildlife corridors, as the top 33% and 50% were both insufficient to show data in the region given the dataset's national scale. The layer was clipped to the analysis area and converted into a polygon. These two layers were combined using the Count Overlap tool.
Muddy Creek and Dead Creek Paths

This is a geospatial layer detailing the paths of Muddy Creek and Dead Creek for the portions of the creeks which fall within the Erie NWR boundary. It is comprised of two line features (creeks) and one polygon feature (the Erie NWR boundary). Muddy Creek is shown in light blue, Dead Creek is shown in purple, and the refuge boundary for Erie NWR is shown in orange. This map is used within the StoryMap entitled "A Virtual Tour Along the Dynamic Muddy Creek" to provide information to visitors about the two stream systems, their history, geology, habitats, and wildlife. [A Virtual Tour Along the Dynamic Muddy Creek (arcgis.com)]
FWS MB Maui Nui Established Wedge-tailed Shearwater Colonies

This layer primarily depicts the locations and population sizes of established Wedge-tailed Shearwater colonies across Maui Nui. Data was provided by Maui Nui Seabird Recovery Project and spans between 2012 to 2021. The layer also depicts other information relevant to the management and conservation of the shearwater colonies, such as the jurisdiction under which each colony lies, history of the colony, conservation measures currently being taken at the colony, invasive species present at the colony, and relevant environmental characteristics surrounding the colony.