AndreaBozzo/ceres-open-data-index huggingface dataset:
Classified Annualized Burn Probability within Sagebrush Ecological Integrity Core Sagebrush Areas and Growth Opportunity Areas and Low Resilience or Resistance Map

For millennia, wildfire has helped shape the sagebrush biome of the western United States. Over recent decades, historical fire regimes have been altered by several factors, including contemporary climate and fuel conditions, leading to the loss or degradation of hundreds of thousands of hectares (ha) of sagebrush each year. In response to wildfire threats, extensive fuel treatment investments are proposed across the region. To help inform strategic and cost-effective investments, we conducted a quantitative assessment of wildfire risk for the sagebrush biome. We used a geospatial fire modeling approach, customized for the sagebrush biome, to estimate spatially explicit burn probability and expected average annual area burned within three Sagebrush Ecological Integrity classes under the Sagebrush Conservation Design: Core Sagebrush Areas (CSAs), Growth Opportunity Areas (GOAs), and Other Rangeland Areas. We further used indices of ecological resilience to disturbance and resistance to invasive grasses to characterize fire risk and recovery potential. Our approach indicates that nearly 530,000 ha are likely to burn in a typical contemporary fire year across the highest integrity Sagebrush Ecological Integrity classes (7% in CSAs and 31% in GOAs). Of the CSAs and GOAs likely to burn, nearly 9000 and 66000 ha, respectively, are expected to have low resilience or resistance and therefore highest loss potential. Cost-effective conservation investments should include wildfire protection for high-integrity sagebrush with low resilience or resistance. Protection objectives may be met with strategically placed fuel breaks intended to enhance fire prevention and containment efforts. Fuel treatments, including prescribed fire and mechanical activities outside of fuel breaks, are by contrast best suited for high-integrity areas with relatively high resilience and resistance. Those activities should be risk-informed and intended to maintain or improve ecological integrity and resilience to wildfire rather than to exclude fire altogether. For ease of interpretation, we created a classed version of the continuous BP dataset using breaks that produced four categories similar to the R|R data: 1) low, 2) moderately low (mod-low), 3) moderate, and 4) moderately high to high (mod-high). The low probability class included values up to 0.0001, which represents a 1-in-10000 annualized probability of burning under contemporary conditions for its maximum pixel value. The maximum pixel values in the mod-low, moderate, mod-high, and high categories were 0.001, 0.01, 0.1, and 1, respectively, such that each represented a ten-fold increase in BP. However, the maximum BP value for the entire analysis area was 0.112, and there were very few pixels in the highest (>0.1) category—hence the reason that the moderately high and high classes were combined to form the mod-high class. These data were used to create Figure 3 B–D in Crist et al. 2024.
Classified Annualized Burn Probability within Sagebrush Ecological Integrity Core Sagebrush Areas and Low Resilience or Resistance Map

For millennia, wildfire has helped shape the sagebrush biome of the western United States. Over recent decades, historical fire regimes have been altered by several factors, including contemporary climate and fuel conditions, leading to the loss or degradation of hundreds of thousands of hectares (ha) of sagebrush each year. In response to wildfire threats, extensive fuel treatment investments are proposed across the region. To help inform strategic and cost-effective investments, we conducted a quantitative assessment of wildfire risk for the sagebrush biome. We used a geospatial fire modeling approach, customized for the sagebrush biome, to estimate spatially explicit burn probability and expected average annual area burned within three Sagebrush Ecological Integrity classes under the Sagebrush Conservation Design: Core Sagebrush Areas (CSAs), Growth Opportunity Areas (GOAs), and Other Rangeland Areas. We further used indices of ecological resilience to disturbance and resistance to invasive grasses to characterize fire risk and recovery potential. Our approach indicates that nearly 530,000 ha are likely to burn in a typical contemporary fire year across the highest integrity Sagebrush Ecological Integrity classes (7% in CSAs and 31% in GOAs). Of the CSAs and GOAs likely to burn, nearly 9000 and 66000 ha, respectively, are expected to have low resilience or resistance and therefore highest loss potential. Cost-effective conservation investments should include wildfire protection for high-integrity sagebrush with low resilience or resistance. Protection objectives may be met with strategically placed fuel breaks intended to enhance fire prevention and containment efforts. Fuel treatments, including prescribed fire and mechanical activities outside of fuel breaks, are by contrast best suited for high-integrity areas with relatively high resilience and resistance. Those activities should be risk-informed and intended to maintain or improve ecological integrity and resilience to wildfire rather than to exclude fire altogether. For ease of interpretation, we created a classed version of the continuous BP dataset using breaks that produced four categories similar to the R|R data: 1) low, 2) moderately low (mod-low), 3) moderate, and 4) moderately high to high (mod-high). The low probability class included values up to 0.0001, which represents a 1-in-10000 annualized probability of burning under contemporary conditions for its maximum pixel value. The maximum pixel values in the mod-low, moderate, mod-high, and high categories were 0.001, 0.01, 0.1, and 1, respectively, such that each represented a ten-fold increase in BP. However, the maximum BP value for the entire analysis area was 0.112, and there were very few pixels in the highest (>0.1) category—hence the reason that the moderately high and high classes were combined to form the mod-high class. These data were used to create Figure 3 B–D in Crist et al. 2024.
Delaware River Watershed boundary, Northeast Region

This dataset represents the Delaware River Watershed created by merging two hydrologic unit code (HUC) 6 watersheds from the complete digital hydrologic unit boundary layer of the Basin (6-digit) 3rd level for the entire United States. The source data consists of geo-referenced digital data and associated attributes created in accordance with the "Federal Guidelines, Requirements, and Procedures for the National Watershed Boundary Dataset; Chapter 3 of Section A, Federal Standards, Book 11, Collection and Delineation of Spatial Data; Techniques and Methods 11-A3" (04/01/2009). http://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/water/watersheds/?cid=nrcs143_021630 . Polygons are attributed with hydrologic unit codes for 4th level sub-basins, 5th level watersheds, 6th level subwatersheds, name, size, downstream hydrologic unit, type of watershed, non-contributing areas and flow modification. The data are currently updated through the USGS National Hydrography Dataset (NHD) Program and replicated to NRCS twice per year.
Rangewide SNPL Window Survey Form 2.0

This is a feature layer created from the Survey123 form to collect a baseline of data for the Western Snowy Plover during annual window surveys. This data is designed for use across the entire west coast portion of the species range, in collaboration with partners and cooperators. The form was created based on an initial version that was field tested in Recovery Unit 2. This form will similarly be tested across the range for it's field usability and data format creation. The intent is to continue to take feedback and improve the form for use across all recovery units. [Western Snowy Plover] (Charadrius nivosus nivosus; plover) Census and Monitoring Surveys – United States Fish and Wildlife Service (Service). This project focuses on electronic data collection (using Survey123) for Western Snowy Plover annual monitoring surveys in all Recovery Units (1-6) which covers coastal California, Oregon and Washington. The plover was listed as a federally threatened species under the Endangered Species Act in 1993. The U.S. Fish and Wildlife Service’s Western Snowy Plover Pacific Coast Population Recovery Plan was published in 2007. The 2007 Recovery Plan provides reasonable actions believed to be required to recover and/or protect plovers. The first action needed from the Recovery Plan is to monitor breeding and wintering populations and habitats of the Pacific coast population of the western snowy plover to determine progress of recovery actions to maximize survival and productivity. The census and monitoring surveys are critical data for determining if the recovery criteria have been met. Recovery criteria for delisting the plover includes: 1) An average of 3,000 breeding adults has been maintained for 10 years and 2) A yearly average productivity of at least one (1.0) fledged chick per male has been maintained in each recovery unit in the last 5 years prior to delisting. The survey effort is a collaboration between multiple FWS Field Offices, contracted partners, and official volunteers. For more information: Here is a direct link to the [Data Management Plan] for this project, the [ServCat reference] page, the [Survey123 link], and a link to the relevant program page for [Arcata Fish & Wildlife Office].
JV Breeding Waterbirds (Pxl)

[Joint Ventures] (JVs) are bird conservation partnerships, established to achieve the goals of the [North American Waterfowl Management Plan] (NAWMP). There are 22 bird habitat JVs in North America, and our JV, the [Upper Mississippi/Great Lakes Region Joint Venture] (UMGL JV) is located in the Midwest, in a pivotal location in the [Mississippi Flyway], for people involved in [migratory bird] conservation. We are a collaborative, regional group of government agencies, tribes, nonprofit organizations, corporations, universities, and individuals that conserve habitat for the benefit of migratory birds, other wildlife, and people. Our landscape includes eastern Minnesota; all of Wisconsin and Michigan; eastern Nebraska and Kansas; western, southern and eastern Iowa; northern Missouri, Illinois and Indiana; and northwestern Ohio. To address Waterbird habitat limitation during the breeding period and improve population trend in our JV, we aim to maximize focal species recruitment through conservation of high quality breeding habitats. To help achieve this objective, we combined spatial datasets of eight breeding focal species (see breeding habitat density and distribution maps in Appendix A of the strategic plan) using fuzzy overlay analysis and produced a model highlighting the areas having the most important waterbird breeding habitats for retention and expansion. Finally, we converted the original raster datset of this model to TIFF format (this product) to improve data visualization, assessment, and interactivity online. The raster map was published in the JV Waterbird Habitat Conservation Strategy – 2018 Revision (Figure 10A). This product shows the distribution and relative density (scale of 0 – 1; values of low – high) of the most valuable areas (pixel neighborhoods) across the JV region, to acquire or manage whatever the required conservation action at the local scale is (i.e., retention, protection, and or restoration). Aggregate-priority-areas, emphasized mostly across Bird Conservation Region (BCR) 12 and 23, were predicted to produce the most value for the decision makers. This product can be scaled-down (i.e., stepped-down to state, watershed, county, or any smaller target area) and supplemented with additional local data for customized output maps depicting best areas for Waterbird breeding habitat restoration vs. retention vs. enhancement. See the JV website and related step-down publications for details. Links: * To download this TIFF dataset and related data, metadata, and documentation, please [browse the UMGL JV online folder in the U.S. Geological Survey's ScienceBase repository]. * To view and explore this TIFF dataset and related data, please [visit the online experience of the UMGL JV Decision Support Tools]. References: * Model codes and final steps (for internal use of UMGLJV staff): (i) Hcs17Wb8SppBreedYs_FzyOvrlyOr_Hlshd1Sd25Gm25_021518_R1DST_Ready = albers_Jv18WbBrdYs. (ii) albers_Jv18WbBrdYs → converted to TIFF and projected on-the-fly to WGS84 → renamed to Jv18WbBrdYsR. * For internal use of USFWS staff: Data Management Plan (DMP) ID = 714; Title: UMGL JV Breeding Waterbird Distribution.
SEImpoundments_04/13/2021

In 2018 Amy Almond, a DFP intern, worked on the project "Coastal Impoundment Mapping in the Southeast". An impoundment is defined as an area within which water levels are actively managed to benefit wetland-dependent wildlife. The goal was to create a comprehensive GIS map layer of impoundments within the Southern Atlantic Coastal Plain. Amy contacted managers of National Wildlife Refuges and state-managed lands within the range (NC, SC, GA, FL) for information about impoundments on their lands. The information provided by the project will help determine potential locations to manage for Black Rails or to work with partners to create new habitat. This information will also benefit other waterbirds and waterfowl since their habitat overlaps. In order to obtain the impoundment information, Amy emailed each of the land managers with a short data request. She asked them to send any GIS shapefiles they had of impounded areas on their lands and sent a Google Form questionnaire to ask specific questions about how they manage these areas, like primary species management, vegetation, and water depth. Most of the land managers responded to the Google Form we created to collect descriptive management data. Some folks sent an email or management plan document, which did not contain the same information as the Google Form. Total impoundments: 750 Total impoundment acreage: 121,129.52 Total impoundment hectares: 49,019.37 Federal Impoundments Refuge Complexes: 15 Refuges: 63 Impoundments: 329 Acres: 63,977 Hectares: 25,890.57 State Impoundments States: 4 State-managed lands: 48 Impoundments: 421 Acres: 57,152.52 Hectares: 23,128.8 North Carolina Impoundments Impoundments: 143 Acres: 19,699.88 Hectares: 7,972.26 South Carolina Impoundments Impoundments: 322 Acres: 50,451.69 Hectares: 20,597.08 Georgia Impoundments Impoundments: 93 Acres: 7,116.85 Hectares: 2,880.08 Florida Impoundments Impoundments: 192 Acres: 43,861.1 Hectares: 17,749.96
Stream Crossing Rapid Assessment Protocol (SCA) Surveys

The Sediment Risk Index (SRI) was developed as a model for prioritizing stream crossings (SCs) in the Choctawhatchee watershed within southeast Alabama from 2006 to 2007. Over seventy-three variables were collected from SCs including information on waterway conditions, crossing structures, road approaches, and roadside soil erosion features that promote sediment delivery. These findings were summarized into a 12-metric index (the SRI), modeled after Karr’s Index of Biotic Integrity (IBI) for fish and other assemblages (Karr, 1981). The goal of condensing SC data into an index was to reduce the time and manpower investment of collecting data. Each metric of the SRI is standardized with scores 1 (most-impacted), 3 (moderately-impacted), or 5 (least-impacted) (Stewart et al., 2006) The scores for the 12 metrics are summed into a single SRI value ranging from 12 to 60, which is used for determining site rank and condition. We are now applying the SRI and Stream Crossing Rapid Assessment Protocol (SCA) across the state of Alabama and in surrounding states at high priority restoration areas referred to as Strategic Habitat AND River Reach Units (SHU and SRRU) This protocol has been developed in collaboration with the Southeast Aquatic Resources Partnership (SARP). SARP is a regional collaboration of natural resource and science agencies, conservation organizations and private interests developed to strengthen the management and conservation of aquatic resources in the southeastern United States. In partnership with American Rivers, SARP developed the Southeast Aquatic Connectivity Program to improve aquatic connectivity in the Southeast. With partners, SARP implements the three components of the Aquatic Connectivity Program: inventory, prioritization, and Aquatic Connectivity Teams. Components of SARPs crossing evaluation methodology have been incorporated into the protocol described in this manual. For additional information please see SARP’s Aquatic Connectivity Program at their website https://southeastaquatics.net/sarps-programs/aquatic-connectivity-program-act. The SCA may be used within the context of watershed management plans to create a priority listing of SCs and focus resources on the most impacted sites. The SRI may also be used in conjunction with other data collection methods to create comprehensive monitoring plans. Site evaluations with the SCA can also be used independently to target SCs, gauge BMPs, or assess trends.
regional_points_gdb

Points on each of the USFWS regions. The main purpose of this layer is to feed into the NWI 50th anniversary storymap. It enables users to click on each USFWS region and get a detailed look at NWI data age. A picture of the NWI data age summary dashboards is attached to each point to feed into the 50th storymap data age overview map and should be updated each year. The URL dashboard link does not need to be updated. It was included to test adding a pop-up enabled map on the storymap which was not used. Maintained by Lauren Healey at lauren_healey@fws.gov.
Well-Connected Core Areas Retain Ecological Integrity of Sagebrush Ecosystems (2018–2021)

File-based downloads available at [https://www.sciencebase.gov/catalog/item/67aa1820d34e329fb204348b] Conservation of species’ mobility and ecological integrity is necessary for the productivity of the sagebrush biome in the western United States. Building on the recently developed Sagebrush Conservation Design (SCD) that mapped sagebrush ecological integrity (SEI)—defined as the higher cover of sagebrush and perennial grass and reduced threats due to invasive annual grass, tree encroachment, and human disturbance—we modeled the structural connectivity of sagebrush ecosystems to better incorporate the role of landscape-level processes into assessments of integrity. Because integrity can vary spatially, as well as temporally, we quantified both interannual variability and trends in variability in SEI from 2001–2021. We used the resultant map to identify areas with high structural landscape connectivity (i.e., “well-connected cores”), then determined the coincident core sagebrush areas (CSAs) that represent functioning sagebrush ecosystem with few landscape threats, and growth opportunity areas (GOAs) that represent functioning systems impacted by one or more threats as originally defined and mapped in the SCD. We found that CSAs were located in areas with higher landscape connectivity, and the biome-wide average of SEI declined by 30% from 2001 to 2021, although the structural connectivity biome-wide declined one-third less (by 20%). CSAs located in areas with high connectivity had 25% higher SEI values on average than those with low connectivity, and the trend in declining SEI values was slower. Our datasets of landscape connectivity can be combined with other SCD products to provide a broader ecosystem context—both spatially and temporally. Our results can be used to inform, refine, focus, and prioritize conservation and management efforts to those CSAs and GOAs we identified as particularly well connected and which may be more resilient to recently altered dynamics and declines—those that will serve to anchor efforts to conserve the sagebrush biome in light of changing land use and climate.
Median projected change in SEI class under RCP4.5  (2071-2100)

Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management. We assessed potential future changes in sagebrush ecological integrity (SEI) under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. This layer shows the median projected change in SEI class (i.e., Core Sagebrush Area, Growth Opportunity Area, Other Rangeland Area) under representative concentration pathway (RCP) 4.5 for 2071-2100. The future (i.e., 2071-2100) median projected SEI class was calculated as the pixel-wise median across results from 13 Global Climate Models. Change in SEI class, is relative to the SEI class during 2017-2020 time-period. Please see Holdrege et al. 2024 (https://doi.org/10.1016/j.rama.2024.08.003) for details on our methods (note that this layer is shown in Fig 1a of that manuscript). This layer (as well as layers for other variables, scenarios and time periods) can be downloaded from Science Base (https://doi.org/10.5066/P13RXYZJ). Please note that this layer is the 'c9_median' band of the 'c9_Default_RCP45_2071-2100.tif' file that is on Science Base.
Well-Connected Core Areas - Figure 2: Stable Landscape Level Cores

File-based downloads available at [https://www.sciencebase.gov/catalog/item/67aa1820d34e329fb204348b] Conservation of species’ mobility and ecological integrity is necessary for the productivity of the sagebrush biome in the western United States. Building on the recently developed Sagebrush Conservation Design (SCD) that mapped sagebrush ecological integrity (SEI)—defined as the higher cover of sagebrush and perennial grass and reduced threats due to invasive annual grass, tree encroachment, and human disturbance—we modeled the structural connectivity of sagebrush ecosystems to better incorporate the role of landscape-level processes into assessments of integrity. Because integrity can vary spatially, as well as temporally, we quantified both interannual variability and trends in variability in SEI from 2001–2021. We used the resultant map to identify areas with high structural landscape connectivity (i.e., “well-connected cores”), then determined the coincident core sagebrush areas (CSAs) that represent functioning sagebrush ecosystem with few landscape threats, and growth opportunity areas (GOAs) that represent functioning systems impacted by one or more threats as originally defined and mapped in the SCD. We found that CSAs were located in areas with higher landscape connectivity, and the biome-wide average of SEI declined by 30% from 2001 to 2021, although the structural connectivity biome-wide declined one-third less (by 20%). CSAs located in areas with high connectivity had 25% higher SEI values on average than those with low connectivity, and the trend in declining SEI values was slower. Our datasets of landscape connectivity can be combined with other SCD products to provide a broader ecosystem context—both spatially and temporally. Our results can be used to inform, refine, focus, and prioritize conservation and management efforts to those CSAs and GOAs we identified as particularly well connected and which may be more resilient to recently altered dynamics and declines—those that will serve to anchor efforts to conserve the sagebrush biome in light of changing land use and climate.