AndreaBozzo/ceres-open-data-index huggingface dataset:
Data release: Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes

&lt;p&gt;Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles and optical habitat in 881 lakes in Minnesota during 1980-2018. &lt;br/&gt; &lt;br/&gt;The data are organized into these items:&lt;/p&gt; &lt;ol&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e5c1c1ce4b01d50924f27e7"&gt;Lake Information&lt;/a&gt; - A lake metadata file and one shapefile of polygons for all 881 lakes in this study&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e5d0b68e4b01d50924f2b32"&gt;Observations&lt;/a&gt; - Temperature observations the lakes used in this study&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e5c1c36e4b01d50924f27ea"&gt;Model Configurations&lt;/a&gt; - Model parameters&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e5d0b96e4b01d50924f2b34"&gt;Model Inputs&lt;/a&gt; - Data used to drive predictive models&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e5d0bb9e4b01d50924f2b36"&gt;Model Predictions&lt;/a&gt; - Predictions for water temperature and near-surface irradiance&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e774324e4b01d509270e29f"&gt;Model Evaluation&lt;/a&gt; - Evaluation of model performance for water temperature predictions&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.sciencebase.gov/catalog/item/5e774355e4b01d509270e2a1"&gt;Habitat Estimates&lt;/a&gt; - Estimates of thermal habitat, optical habitat, and thermal-optical habitat area&lt;/li&gt; &lt;br/&gt; &lt;p&gt;This research was funded by the Department of the Interior Northeast and North Central Climate Adaptation Science Centers, a Midwest Glacial Lakes Fish Habitat Partnership grant through F&amp;WS Access to computing facilities was provided by USGS Advanced Research Computing, USGS Yeti Supercomputer (https://doi.org/10.5066/F7D798MJ). We thank North Temperate Lakes Long-Term Ecological Research (NSF DEB-1440297) and Global Lake Ecological Observatory Network (NSF #1702991).&lt;/p&gt;

Tags: climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, minnesota, mn, modeling, reservoirs, sd, south-dakota, temperate-lakes, temperature, thermal-profiles, united-states, us, usgs-5e5c1b4fe4b01d50924f27e1, water, water-resources
Organization: Department of the Interior
oahu_oha - Overall Hazard Assessment in the coastal zone of Oahu, Hawaii

Overall Hazard Assessment in the coastal zone of Oahu,
Hawaii

Tags: agents-of-coastal-change, assessment, coast, coastal, coastal-processes, continental-island-shore-complex, geoscientificinformation, hawaii, hawaii-ecoregion, hazard, hazards, island, kauai, lanai, maui, molokai, oahu, oceans, oceans-and-coastal, oceans-and-estuaries, overall, pacific, risk-assessment, usgs-5e549d60-9290-4f46-bd36-daf1c71e9272
Organization: Department of the Interior
Records of selected wells within the Fairport-Lyons Channel System and Adjacent Areas in Wayne, Ontario, and Seneca Counties, New York

This dataset contains the well records compiled for this study.

Tags: fairport, hydrogeology, lyons, new-york, ontario-county, seneca-county, united-states, usgs-5e5d54d3e4b01d50924f2cb7, wayne-county
Organization: Department of the Interior
Differential Optical Absorption Spectroscopy data acquired during the 2018 rift eruption of Kīlauea Volcano

A fissure eruption occurred in Kīlauea Volcano’s Lower East Rift Zone (LERZ) from April to September 2018. During this event, volcanic gases were emitted from three active areas on the volcano. The most intense degassing occurred at the active fissures in the LERZ, thus causing parts of Hawaiʻi Island’s Puna district to be exposed to life-threatening sulfur dioxide (SO2) concentrations. At the same time, gas emissions from the volcano’s summit and East Rift Zone (ERZ) slowly declined from their decade-long averages as magma drained from the volcano’s shallow plumbing system. Throughout the eruption, the USGS used a Mobile Differential Optical Absorption Spectrometer (Mobile DOAS) to record ultraviolet (280 – 420 nm) spectra of downwelling scattered solar radiation passing through volcanic gases overhead. Mounted on a vehicle or carried by a hiking geologist, the instrument was passed beneath volcanic plumes emitted from each of the three active areas throughout the 2018 eruption. The recorded spectra were later used to retrieve SO2 vertical column densities in transects perpendicular to the plume propagation direction. SO2 emission rates could then be calculated from these, thereby tracking the volcano’s gas output as the eruption progressed. The resulting gas emission rates are published in the Bulletin of Volcanology (https://doi.org/10.1007/s00445-020-01390-8). All recorded spectra were stamped with GPS time and location. Each spectrum is saved in a separate ASCII file which includes 2048 radiances recorded across the spectral window of the spectrometer along with relevant metadata associated with each acquisition

Tags: doas, geochemistry, spectroscopy, usgs-5dcc8303e4b0695797607f87, volcanology
Organization: Department of the Interior
Cross-validation results for five statistical methods of daily streamflow estimation at 1,385 reference streamgages in the conterminous United States, Water Years 1981-2017

This data release contains daily time series estimates of natural streamflow for 1,385 streamgages in 19 study regions in the conterminous U.S. from October 1, 1980, through September 30, 2017. These estimates are provided for gages from mostly undisturbed watersheds as defined by Falcone (2011), using five statistical techniques: nearest-neighbor drainage area ratio (NNDAR), map-correlation drainage area ratio (MCDAR), nearest-neighbor nonlinear spatial interpolation using flow duration curves (NNQPPQ), map-correlation nonlinear spatial interpolation using flow duration curves (MCQPPQ), and ordinary kriging of the logarithms of discharge per unit area (OKDAR).  Location information and basin characteristics for study gages were obtained from the "Reference" gages of the GAGES-II dataset (Falcone, 2011, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011).  Observed daily streamflow data were retrieved from the National Water Information System (NWIS) on September 7, 2018.  NNDAR, MCDAR, NNQPPQ, and MCQPPQ estimates were computed following methods described by Farmer and others (2014), with updates to the flow-duration curve modeling which is described by Over and others (2018).  OKDAR estimates were computed using pooled variograms for each study region following methods described by Farmer (2016).  Daily streamflow estimation was conducted in a leave-one-out-cross-validation approach where each streamgage was treated as if ungaged and all the remaining streamgages in a study region were used to calibrate each method and perform estimations at the "ungaged" site.  The observed streamflow records were compared to the five simulated streamflow records to help assess performance of each method.  These performance metrics are provided at each gage for all five statistical methods.
References cited:
Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow [digital spatial dataset] : U.S. Geological Survey Water Resources NSDI Node web page, https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011.
Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p., http://dx.doi.org/10.3133/sir20145231.
Farmer, W. H., 2016, Ordinary kriging as a tool to estimate historical daily streamflow records, Hydrology and Earth System Sciences, 20, 2721-2735, https://doi.org/10.5194/hess-20-2721-2016.
Over, T.M., Farmer, W.H., Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States; U.S. Geological Survey Scientific Investigations Report 2018–5072, https://doi.org/10.3133/sir20185072.

Tags: inlandwaters, reference-hydrology, statistical-analysis, streamflow, usgs-5df2c29ee4b02caea0f95b92
Organization: Department of the Interior
Data Release for the 1999 Alaska Seismic Hazard Model

Gridded ground motion data and mapped gridded ground motion values are available for the 1999 Alaska Seismic Hazard Model. Probabilistic seismic hazard data and maps of Alaska and the Aleutians for peak ground acceleration (PGA) and 0.2, 0.3, and 1.0 second spectral acceleration at probability levels of 2 percent in 50 years (annual probability of 0.000404) and 10 percent in 50 years (annual probably of 0.0021), assuming firm rock soil conditions at 760 m/s, are available. Development of the 1999 Alaska Seismic Hazard Model is documented in the USGS Open-File Report 99-36 (https://doi.org/10.3133/ofr9936).  
This dataset is considered a legacy dataset. The original dataset was uploaded to the USGS website at the time of publication of the seismic hazard model (1999) but was later moved over the the USGS ScienceBase Catalog (2019). The original dataset was assumed to be complete and accurate, but may contain inconsistencies when compared to more recent, actively maintained datasets.

Tags: alaska, earthquake-hazards-program, ehp, geologic-hazards-science-center, ghsc, ground-motion, hazard-curve, hazard-map, national-seismic-hazard-model, national-seismic-hazard-model-project, nehrp-site-classes, nshm, nshmp, spectral-period, u-s-seismic-hazard-maps, usgs, usgs-5db05ee3e4b0b0c58b56c193
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Coast Guard Beach, MA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, cape-cod, cape-cod-national-seashore, cmhrp, coast-guard-beach, coastal-and-marine-hazards-and-resources-program, coastal-processes, geomorphology, geospatial-analysis, geospatial-datasets, ma, massachusetts, north-america, oceans, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa3723e4b09fd3b0c9ce21, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Soil surface elevation change and vertical accretion data to support the Fruit Farm Creek Mangrove Restoration Project, Rookery Bay National Estuarine Research Reserve, Marco Island, Florida, 2015-2019

These data represent surface elevation change and vertical accretion time series collected from a series of degraded tidal wetland sites near Goodland, Florida, USA. Surface elevation was measured using a combination of rod surface elevation tables (SETs) and feldspar marker horizons. Here, we document mangrove forest and soil structural changes within transects established in tidally restricted areas on Marco Island (Collier County, Florida, USA), which has broad swaths of dead-standing or unhealthy mangroves.  Original data were collected in January 2015, and re-collected in August 2015, January 2016, July 2016, January 2017, June 2018 and June 2019.

Tags: accretion, collier-county, elevation, florida, goodland, marco-island, shoreline-accretion, usa, usgs-5db73e09e4b0b0c58b5a4927
Organization: Department of the Interior
Data Release for the 2003 Puerto Rico and U.S. Virgin Islands Seismic Hazard Model

Gridded seismic hazard curve data, gridded ground motion data, and mapped gridded ground motion values are available for the 2003 Puerto Rico and U.S. Virgin Islands Seismic Hazard Model. Probabilistic seismic hazard data and maps are available for peak ground acceleration (PGA) and 0.2, 0.3, and 1.0 second spectral acceleration at probability levels of 2 percent in 50 years and 10 percent in 50 years, assuming firm rock soil conditions at 760 m/s. Development of the 2003 Puerto Rico and U.S. Virgin Islands Seismic Hazard Model is documented at https://doi.org/10.1193/1.3277667. 
This dataset is considered a legacy dataset. The original dataset was uploaded to the USGS website at the time of publication of the seismic hazard model (2003) but was later moved over the the USGS ScienceBase Catalog (2019). The original dataset was assumed to be complete and accurate, but may contain inconsistencies when compared to more recent, actively maintained datasets.

Tags: earthquake-hazards-program, ehp, geologic-hazards-science-center, ghsc, ground-motion, hazard-curve, hazard-map, national-seismic-hazard-model, national-seismic-hazard-model-project, nehrp-site-classes, nshm, nshmp, puerto-rico, spectral-period, u-s-seismic-hazard-maps, u-s-virgin-islands, usgs, usgs-5daf656ae4b0b0c58b552f85
Organization: Department of the Interior
Selected environmental characteristics of sampled sites, watersheds, and riparian zones for the U.S. Geological Survey Regional Stream Quality Assessment, 2013 to 2017

In 2013, the Regional Stream Quality Assessment (RSQA) study was started as part of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project. One of the objectives of the RSQA is to characterize the relationships between water-quality stressors and stream ecology and subsequently determine the relative effects of these stressors on aquatic biota within the streams (Garrett and others, 2017; Journey and others, 2015; Coles and others, 2019; Sheibley and others, 2017; May and others, 2020). The study was implemented in five regions across the United States (U.S.); the Midwest (MSQA) in 2013, the southeast (SESQA) in 2014, the Pacific Northwest (PNSQA) in 2015, the northeast (NESQA) in 2016, and California (CSQA) in 2017. To meet this objective (correlations with and effects of stressors), a framework of fundamental geospatial data was required to develop physical and anthropogenic characteristics of each study region for the watersheds and riparian zones associated with each sampling location. This dataset includes 150 selected environmental characteristics for the 483 sites sampled across all regions of the study. The characteristics were derived over the five years (2013 to 2017) using geospatial summary techniques where spatial information is summarized based on spatial extents such as watersheds. The characteristics were developed using the geospatial data for the location of the water-quality sites, delineations of areas draining to the sites (watershed boundaries, including the boundaries of the lower 5 kilometers [km] of watershed [Lower Basin] for the NESQA and CSQA study regions), and riparian-zone boundaries defined from buffers along digitized riparian reaches (Qi and Nakagaki, 2020). This dataset consists of 3 tables: 1) the main data file containing the environmental characteristics of sites, watersheds (including the boundaries of the lower 5 km of watershed for the NESQA and CSQA study regions), and riparian zones, 2) the data dictionary that describes the variables in the data file, and 3) the full citations associated with the references cited in the data dictionary.

Tags: alabama, basin-characteristics, biota, california, connecticut, delaware, drainage-area-characteristics, environmental-characteristics, geographic-information-systems, georgia, geospatial-analysis, geospatial-datasets, illinois, indiana, inlandwaters, iowa, kansas, kentucky, massachusetts, midwest, minnesota, missouri, national-water-quality-assessment, nawqa, nebraska, new-jersey, new-york, north-carolina, northeast, ohio, oregon, pacific-northwest, pennsylvania, regional-stream-quality-assessment, rhode-island, riparian-zone-characteristics, rsqa, site-characteristics, south-carolina, southeast, united-states, usgs-5daf4071e4b0b0c58b552630, vermont, virginia, washington, watershed-characteristics, wisconsin
Organization: Department of the Interior
Data from in-situ displacement monitoring, Slumgullion landslide, Hinsdale County, Colorado

We monitored displacement of the Slumgullion landslide located in Hinsdale County, Colorado. We measured displacement at the ground surface between 12 August 2011 and 10 October 2018, and in the subsurface between 4 September 2016 and 7 December 2016. Both types of data were acquired at irregular time intervals. Displacement at the ground surface was measured at locations within the upper, middle, and lower parts of the landslide using electronic cable extension transducers (extensometers) with stated ±0.7 mm accuracy (Extensometer_data.csv). Subsurface displacement was measured near the middle of the landslide using a 16-sensor array of 30.48-cm-long tilt sensors (inclinometer) installed within a PVC-cased borehole. Each tilt sensor has stated 0.003 mm displacement resolution and long-term displacement accuracy of ±0.23 mm. Tilt sensor readings are provided (Inclinometer_data.csv) in terms of horizontal position relative to the array bottom. Sensors were oriented so that position values increased in the general direction of landslide movement and decreased in the opposite direction; the tilt sensor array did not penetrate the landslide base so measurements indicate potential differential displacement within the landslide body. Sensors are numbered from 1 to 16 with 1 being the deepest sensor and 16 being the shallowest. The inclinometer was installed within a depth range of 4.93-9.81 m from 4 September 2016 to 17 October 2016 and within a depth range of 0-4.88 m from 19 October 2016 to 7 December 2016. Data from the deeper installation of 4 September 2016 to 17 October 2016 revealed that differential displacement occurred there, with material at shallower depths having moved farther downslope than deeper material. However, data from the shallower installation of 19 October 2016 to 7 December 2016 revealed a general lack of differential displacement with depth, other than relaxation of backfill around the array that permitted tilting of some sensors in the direction opposite the landslide movement direction. These data support a study described in Hu, X., Bürgmann, R., Schulz, W.H., and Fielding, E.J., 2020, Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing: Nature Communications, v. 11, 2792, doi:10.1038/s41467-020-16617-7.

Tags: geology, usgs-5dae1933e4b09fd3b0c9db59
Organization: Department of the Interior
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cobb Island, VA, 2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Tags: atlantic-ocean, barrier-island, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, cobb-island, delmarva-peninsula, geomorphology, geospatial-analysis, geospatial-datasets, north-america, oceans, st-petersburg-coastal-and-marine-science-center, study-areas, u-s-geological-survey, united-states, usa, usgs, usgs-5daa37ace4b09fd3b0c9ceb5, va, virginia, virginia-coast-reserve, woods-hole-coastal-and-marine-science-center
Organization: Department of the Interior
Hawaii Island, Hawaiian hoary bat roosting ecology and detection 2018-2019

The Hawaiian hoary bat (Lasiurus cinereus semotus), a federally and state listed endangered subspecies, is the only extant native terrestrial mammal in the Hawaiian archipelago. It is an insectivorous, solitary and foliage-roosting species that generally roosts alone or in mother-pup family groups. A total of 58 bats (17 female; 41 male; 56 adult; 2 juvenile) were captured at multiple locations on the east side of Hawaii Island from May 2018 through September 2019. Radio transmitters were affixed to 56 bats including two individuals that were recaptured and radio-tagged twice. When possible, radio telemetry was used to locate bats in trees and forest stands used for day-roosting. 
A total of 23 trees were identified as bat day-roosts and used by 18 radio-tagged bats (10 male; 8 female; 17 adult; 1 juvenile). Additional bats were tracked to a broader scale; in total 45 bat day-roosts were identified to the level of forest stand and these were used by 33 radio-tagged bats (23 male; 10 female; 32 adult; 1 juvenile). Of these 33 bats, fidelity to a roost tree or stand, as measured by the number of distinct days with confirmed occupancy, ranged from 1 to 15 days (mean = 5.0 days). The use of multiple roosts at the stand-level were observed for eight bats. Three maternity roosts were confirmed and two were monitored using acoustic recording and thermal video stations. 
Finally, bats confirmed as present at a roost tree were used as “targets” to evaluate the efficacy of detecting bats with thermal imaging, and when not effective (i.e., during hotter parts of the day when the technique could not discern bats from warm vegetation), visual searching with binocular was also investigated. Bats were detected in 30 of 95 (32%) trials.
This data release consists of six tabular datasets: roost tree metrics, roost stand metrics, roost fidelity,  maternity roost acoustic monitoring, maternity roost thermal video monitoring, and roost detection trials.

Tags: biota, echolocation, forest-stand, hawaiian-hoary-bat, roost-tree, telemetry, thermal-imaging, usgs-5dae12cfe4b09fd3b0c9db3d
Organization: Department of the Interior