AndreaBozzo/ceres-open-data-index huggingface dataset:
SARP AOP Barrier Feedback Database public expanded view

SARP's [Aquatic Connectivity Teams] (ACTs) work within states to collaborate on aquatic organism passage projects. This database to captures feedback from users, especially users in Aquatic Connectivity Teams, on the accuracy and quality of SARP's Aquatic Organism Passage Barrier inventory and prioritization scenarios. The feedback is used to update the inventory and develop updated prioritization scenarios to better reflect the priorities of the conservation community interested in aquatic organism passage across the US. The feature service is shared through various ACT online tools.
Aquatic_Barrier_Prioritization_Dams_v4.1.0

This dataset is the national output of dams from the Aquatic Barrier Prioritization Tool (aquaticbarriers.org). This dataset is a compilation of dams from across the country from both living and static sources. Dams are updated from living sources 4X per year into a master feature service which is available for QAQC and social feasibility analysis. This master then is downloaded and run through several scripts in a connectivity analysis ([GitHub - astutespruce/sarp-connectivity: Southeast Aquatic Barrier Prioritization Tool]) to produce indicators for prioritization at aquaticbarriers.org. This is the output of the latest analysis 3.13.0; 10/17/2024. Data is incomplete while this project is ongoing. New dams are discovered every day. Data and prioritization maintained by the Southeast Aquatic Resources Partnership.
Aquatic_Barrier_Prioritization_RoadBarriers_v4.1.0

This dataset is the national output of assessed road stream crossings from the Aquatic Barrier Prioritization Tool (aquaticbarriers.org). This dataset is a compilation of dams from across the country from both living and static sources. Dams are updated from living sources 4X per year into a master feature service which is available for QAQC and social feasibility analysis. This master then is downloaded and run through several scripts in a connectivity analysis ([GitHub - astutespruce/sarp-connectivity: Southeast Aquatic Barrier Prioritization Tool]) to produce indicators for prioritization at aquaticbarriers.org. This is the output of the latest analysis 3.13.0; 10/17/2024. Data is incomplete while this project is ongoing. New dams are discovered every day. Data and prioritization maintained by the Southeast Aquatic Resources Partnership.
Rainwater Basin Wetland Complex Supplemental Water (Pumping) Database: Public View

[DESCRIPTION]Seasonal ponding extent of Rainwater Basin wetlands achieved through supplemental water pumping. This data is used for documentation of Ducks Unlimited (DU) Water Fund expenditures. The DU Water Fund is an endowment that provides public (Nebraska Game and Parks Commission and U.S. Fish and Wildlife Service) wetland managers with funding for public wetland water supplementation.[/DESCRIPTION] [CONTACTS]For inquiries about the Ducks Unlimited Rainwater Basin Water Fund, please contact John Denton, Director of Conservation Programs Colorado, Kansas, Nebraska, Wyoming (jdenton@ducks.org, (308) 258-4682) or Tom Peterson, Manager of Conservation Programs Wyoming and Nebraska (tpeterson@ducks.org, (308) 218-8160). For technical issues regarding geospatial data and services, please contact Roger Grosse, RWBJV GIS Specialist, 308-382-8112, Roger_Grosse@fws.gov[/CONTACTS] [DMP]For internal FWS staff, please reference this Data Management Plan.[/DMP]
Invasive Annual Grass Prioritization Model Sagebrush Biome

File-based data for download: [https://www.sciencebase.gov/catalog/item/676d824dd34e3ce2f6084e8e] In the last 20 years, the North American sagebrush biome has lost over 500 000 ha of intact and largely intact sagebrush plant communities on an annual basis. Much of this loss has been associated with expansion and infilling of invasive annual grasses (IAGs). These species are highly competitive against native perennial grasses in disturbed environments, and create fuel conditions that increase both the likelihood of fire ignition and the ease of wildfire spread across large landscapes. Given the current rate of IAG expansion in both burned and unburned rangelands, we propose a range-wide paradigm shift from opportunistic and reactive management, to a framework that spatially prioritizes maintenance of largely intact, uninvaded areas and improvement of invaded habitats in strategic locations. We created a framework accompanied by biome-wide priority maps using geospatial overlays that target areas to MAINTAIN large, uninvaded areas as natural resource anchors through activities to prevent IAGs, IMPROVE areas where management success in restoring large, intact landscapes is most likely, and CONTAIN IAG infestations where necessary. We then offer three case studies to illustrate the use of these concepts and map products at multiple scales. Our map products operate at the biome scale using regional data sources and additional data sources will be needed to inform local conservation planning. However, the basic strategic management principles of (1) maintaining the intact and uninvaded areas that we can least afford to lose to IAGs, (2) improving areas where we have a reasonable likelihood of restoration success, and (3) containing problems where we must, are timely, relevant, and scalable from the biome to local levels.
Hanford Reach NM White Bluffs Landslides 1996-2021

The White Bluffs Landslides geospatial dataset was produced by the Department of Geology at Portland State University in 2024 for Central WA National Wildlife Refuge Complex, U.S. Fish and Wildlife Service. Using orthorectified aerial photographs from 1996 to 2019, supplemented by airborne lidar and field verification, landslides were mapped digitally in GIS at ~1:2000 scale with boundary accuracy of ±5 meters. Landslides were classified according to characteristic features and types, including earth flows, rotational slides, compound slides, and earth spread. Each landslide was assigned to the year it first appeared in photographs, noting that actual occurrence may be earlier, and regrowth of vegetation can obscure mapping after several years. The mapping process included identification of new landslides and expansion events, with boundaries refined using lidar and in-field observations. This dataset is intended to inform resource management decisions within the White Bluffs region of the Hanford Reach National Monument. ServCat Project: [https://iris.fws.gov/APPS/ServCat/Reference/Edit/193322] This description was drafted with the assistance of Copilot AI, May, 2026, using a final report submitted by Adam Booth, Department of Geology at Portland State University to fulfill an Agreement between USFWS and Portland State University.
NWI Mapper PDF Prints Polygons

This dataset shows the extent of maps printed from the USFWS Wetlands Mapper ([https://www.fws.gov/wetlands/]) in fiscal year 2025. The U.S. Fish and Wildlife Service’s National Wetlands Inventory (NWI) is a publicly available resource that provides detailed information on the abundance, characteristics and distribution of America’s wetlands. One of the ways the wetlands data is provided to the public is via an interactive Wetlands Mapper ([https://www.fws.gov/wetlands/data/Mapper.html]). The [Wetlands Mapper] delivers an easy-to-use, map-like view of America’s wetland resources. It spatially integrates NWI data with additional natural resource information and political boundaries to produce a robust decision support tool. From 2015-2026, over 2.5 million maps have been printed from the NWI Wetlands Mapper. The geographic extent of these maps illuminate certain patterns of how NWI data are used by the public. Being aware of how the public uses NWI data will allow the program respond to user needs, learn where updates might be most appreciated, and help guide future project planning. For questions or comments on this information, please contact the NWI Data Team (wetlands_team@fws.gov).
SWFL_RW_Top3_May1_June30_2025

The SWFL satellite model outputs a continuous range of model probabilities (Hatten and Paradzick, 2003). In this layer, a probability threshold was set at 40 percent. Thus, areas with model probabilities less than 40% were considered less suitable breeding habitat and were excluded from the map. Model probabilities greater than 40% were aggregated into three probability classes: 40 - 60% (class 3), 60.1 – 80% (class 4), 80.1 - 100% (class 5). Studies have shown that SWFL territories increase exponentially as class value increases. For a complete description of methods and interpretation of maps, see Hatten and Paradzick, 2003; Hatten, 2016. The layer title (SWFL_RW_Top3cl_May1_June30_2025) is interpreted as follows: SWFL = Southwestern Willow Flycatcher; RW = Rangewide application of satellite model (56 Landsat-9 scenes) ; Top3cl = top three probability classes displayed on map (locations with a value less than 40% are not shown on the map); May1_June30 = range of dates that an image mosaic was created from Landsat 9 imagery, with the least cloudy images selected; 2025 = year of image selection; Version 5 (v5) was used as the mask to mask out background noise (i.e., non-riparian features that could confuse the model). Hatten, J.R., and C.E. Paradzick. 2003. A multiscaled model of southwestern willow flycatcher breeding habitat. Journal of Wildlife Management, 67: 774-788. [https://www.jstor.org/stable/3802685?seq=1] Hatten, J.R., 2016, A satellite model of Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat and a simulation of potential effects of tamarisk leaf beetles (Diorhabda spp.), Southwestern United States: U.S. Geological Survey Open-File Report 2016–1120, 88 p., [https://pubs.er.usgs.gov/publication/ofr20161120]
Aquatic_Barrier_Prioritization_Dams_Crossings_Indicators_v4.1.0

This dataset is the national output of dams and assessed road stream crossings of moderate and worse severity from the Aquatic Barrier Prioritization Tool (aquaticbarriers.org). This dataset is a compilation of dams and assessed crossings (only those that were shown to be barriers of moderate or worse severity) from across the country from both living and static sources. Dams and crossings are both feature services that are updated from living sources 4X per year into a master feature service which is available for QAQC and social feasibility analysis. This master then is downloaded and run through several scripts in a connectivity analysis ([GitHub - astutespruce/sarp-connectivity: Southeast Aquatic Barrier Prioritization Tool]) to produce indicators for prioritization at aquaticbarriers.org. This is the output of the latest analysis 4.1.0; 3/30/2026. Data is incomplete while this project is ongoing. New dams and crossing barriers are discovered every day. Data and prioritization maintained by the Southeast Aquatic Resources Partnership.
Alaska National Wildlife Refuge Land Status

Overview This feature service provides a statewide land status and estate inventory for National Wildlife Refuges in Alaska. It compiles surface and subsurface ownership information used by the U.S. Fish and Wildlife Service, Region 7, Division of Realty to support refuge land records, conveyance tracking, and estate management. Feature Layers * Surface estate layers describe surface ownership and status across refuge lands, including parcels managed by USFWS, other federal agencies, selected lands, and patented lands. * Subsurface estate layers document subsurface ownership and status for the same refuge system, supporting management of mineral and related sbsurface estate interests. * Focused views provide filtered subsets of the land estate records for USFWS, other federal ownership, patented lands, and selected lands, helping users work with specific ownership categories. Core Content * Refuge name, refuge unit, and administrative management information * Conveyance and case tracking details used in land status records * Ownership, estate status, and source documentation references * Survey and tract references, acreage values, and notes for parcel-level context * Data source and document links that support land status interpretation Geographic Coverage The service covers National Wildlife Refuges in Alaska and includes refuge, administrative site, and related estate records across the state. Use Cases * Reviewing refuge land ownership and estate status * Supporting realty, conveyance, and boundary management workflows * Finding parcels by refuge, ownership category, or estate type * Linking land status records to supporting plats, deeds, and conveyance documents Source and Currency The information is compiled by USFWS Region 7, Division of Realty, with Bureau of Land Management Master Title Plats as a primary source. The service is updated as-needed, depending on the frequency of land status record changes. Typical update frequency is generally one to two times per month. License and Citation Use of the data is subject to the U.S. Fish and Wildlife Service Data Distribution Liability Statement. Recommended citation: U.S. Fish and Wildlife Service, Region 7, Division of Realty.
Lakes (Midwest Conservation Blueprint 2026 Indicator)

Definition This indicator represents lake health based on watershed condition within the Midwest Landscape. It prioritizes lakes and reservoirs greater than one hectare based on the amount of agriculture and development in a lake's upstream watershed. Pixels can take the following values: * 1 – Lake or reservoir with high disturbance (>60%) in upstream watershed. * 2 – Lake or reservoir with medium disturbance (>25-60%) in upstream watershed. * 3 – Lake or reservoir with low disturbance (0-25%) in upstream watershed. Selection This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative of other social and/or environmental values. Input Data & Mapping Steps This indicator originates from the LAGOS-US dataset, the National Land Cover Database, and Lapierre et al. Continuous Lake Classifications. To create this layer, MLI partners, members, and staff completed the following mapping steps: projected all input data to NAD83 (2011) UTM Zone 15N, joined LAGOS polygons with the Continuous Lake Classifications table, and converted the polygon layer to a raster based on the total percentage of agriculture and development in each lakeshed. We reclassified the raster into the following classes: 1 - Lake or reservoir with high disturbance (>60%) in upstream watershed, 2 - Lake or reservoir with medium disturbance (>25-60%) in upstream watershed, and 3 - Lake or reservoir with low disturbance (0-25%) in upstream watershed. Finally, we removed highly altered areas using our Highly Altered Areas mask. For full mapping details, please refer to the [Midwest Conservation Blueprint Development Process]. For a complete download of all Blueprint input and output data, visit the [Midwest Conservation Blueprint 2026 Data Download.]
Streams (Midwest Conservation Blueprint 2026 Indicator)

Definition This indicator represents stream health based on the risk of habitat degradation within the Midwest Landscape. It prioritizes stream reaches based on urban land use, impervious surface, human population and road density, agriculture, and point source pollution sites Pixels can take the following values: * 1 - Highest risk of habitat degradation * 2 - High risk * 3 - Medium risk * 4 - Low risk * 5 - Lowest risk Selection This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative of other social and/or environmental values. Input Data & Mapping Steps This indicator originates from the National Fish Habitat Partnership (NFHP) Cumulative Habitat Condition Indices scores. To create this layer, MLI partners, members, and staff completed the following mapping steps: projected all input data to NAD83 (2011) UTM Zone 15N, joined the NFHP Habitat Condition data to the NFHP 90m stream buffers using the "comid" field, and converted the 90m stream buffers to a 30m raster using the "lb_hci" field, which represents the local habitat condition index of each stream buffer. The resulting raster contained the values 1-5, with 1 being at the highest risk of habitat degradation while 5 had the lowest risk. Finally, highly altered areas were removed from the layer using our Highly Altered Areas mask. For full mapping details, please refer to the [Midwest Conservation Blueprint Development Process]. For a complete download of all Blueprint input and output data, visit the [Midwest Conservation Blueprint 2026 Data Download.]
Riparian Areas (Midwest Conservation Blueprint 2026 Indicator)

Definition This indicator represents riparian health within the Midwest Landscape. It prioritizes areas based on the percentage of natural landcover within floodplains. Pixels can take the following values: * 1 – 0-60% natural landcover * 2 – 60-70% natural landcover * 3 – 70-80% natural landcover * 4 – 80-90% natural landcover * 5 – >90% natural landcover Selection This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative of other social and/or environmental values. Input Data & Mapping Steps This indicator originates from the EPA Percentage of Land Area in Estimated Floodplains Classified as Natural layer and the EPA Estimated Floodplain Map of the Conterminous U.S. To create this layer, MLI partners, members, and staff completed the following mapping steps: projected all input data to NAD83 (2011) UTM Zone 15N, converted the Percentage of Land Area in Estimated Floodplains Classified as Natural layer to a 30m raster, reclassified the raster in the following classes: 1 – 0-60% classified as natural, 2 – 60-70% classified as natural, 3 – 70-80% classified as natural, 4 – 80-90% classified as natural, 5 – 90-100% classified as natural, and clipped the reclassed raster to the Estimated Floodplain boundaries. Finally, we removed highly altered areas using our Highly Altered Areas mask. For full mapping details, please refer to the [Midwest Conservation Blueprint Development Process]. For a complete download of all Blueprint input and output data, visit the [Midwest Conservation Blueprint 2026 Data Download.]
Intact Habitat Cores (Midwest Conservation Blueprint 2026 Indicator)

Definition This indicator identifies large, unfragmented patches of habitat within the Midwest Landscape. It prioritizes areas based on quality and protection status of habitat cores. Pixels can take the following values: * 1 – "Good" intact habitat core score * 2 – "Better" intact habitat core score * 3 – "Best" intact habitat core score, plus GAP 1-2 protected lands Selection This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative of other social and/or environmental values. Input Data & Mapping Steps This indicator originates from the Esri Green Infrastructure Intact Habitat Cores Layer and the Protected Areas Database. To create this layer, MLI partners, members, and staff completed the following mapping steps: projected all input data to NAD83 (2011) UTM Zone 15N, merged all state-level habitat core layers into a single, regional layer, deleted identical polygons, converted the layer to a 30m raster using the core score as the case field, and reclassified the resulting raster into the following classes: 1 – Good core (score of 1.6-3.31), 2 – Better core (score of 3.32-4.12), 3 – Best core (score of 4.13-4.5). We selected all polygons with a GAP status of 1 or 2 from the Protected Areas database, converted the selected polygons to a 30m raster, and mosaiced this raster with the Intact Habitat Cores raster. Finally, highly altered areas were removed using our Highly Altered Areas Mask. For full mapping details, please refer to the [Midwest Conservation Blueprint Development Process]. For a complete download of all Blueprint input and output data, visit the [Midwest Conservation Blueprint 2026 Data Download.]
Aquatic Network Connectivity (Midwest Conservation Blueprint 2026 Indicator)

Definition This indicator identifies the ability of aquatic species to access large, complex aquatic networks. It prioritizes areas based on the length of hydrologically connected flowlines and diversity of unfragmented aquatic habitat in the region. Pixels can take the following values: * 1 – Far below average * 2 – Below average * 3 – Slightly below average * 4 – Average * 5 – Slightly above average * 6 – Above average * 7 – Far above average Selection This indicator was chosen as a targetable, important feature of the MLI goals that will be used to track conditions over time and prioritize areas for conservation. Indicators were defined through elicitation and prioritization exercises with federal and state participants. Criteria for the indicators includes 1) actionable, 2) measurable, 3) relevant to multiple groups across the region, and/or 4) representative of other social and/or environmental values. Input Data & Mapping Steps This indicator originates from the Nature Conservancy's Resilient Rivers dataset and the USFWS National Wetlands Inventory (NWI). To create this layer, MLI partners, members, and staff completed the following mapping steps: projected all input data to NAD83 (2011) UTM Zone 15N, converted the Resilient Rivers data to a raster based on the Connectivity and Diversity score, and clipped the results of the previous step with the NWI data layer to represent actual water features on the landscape rather than flowlines. Finally, we removed highly altered areas from this layer using our Highly Altered Areas mask. For full mapping details, please refer to the [Midwest Conservation Blueprint Development Process]. For a complete download of all Blueprint input and output data, visit the [Midwest Conservation Blueprint 2026 Data Download.]