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LAGOS-US RESERVOIR: Data module classifying conterminous U.S. lakes 4 hectares and larger as natural lakes or reservoirs
The LAGOS-US RESERVOIR data module (hereafter, RESERVOIR) classifies all 137,465 lakes > 4 hectares in the conterminous U.S. into one of the following three categories using a machine-learning predictive model based on visual interpretation of lake outlines and a classification rule based on lake shape. Natural Lakes (NLs) are defined as lakes that are likely to be entirely or mostly naturally-formed and that do not have large, flow-altering structures on or near them; Reservoir Class A’s (RSVR_A) are defined as lakes that are likely to be either human-made or highly human-altered by the presence of a relatively large water control structure that appears to significantly change the flow of water; and Reservoir Class B’s (RSVR_Bs) are lakes that are likely to be entirely human-made based on isolation from rivers and a highly angular shape that is rarely, if ever, seen in natural lakes also often. We trained the machine learning models on 12,162 manually-classified lakes to assign probabilities of a lake being in 1 of 2 of the categories (NL or RSVR), then we further classified the RSVR classification into either A or B based on NHD Fcodes, isolation, and angularity. The data module includes a detailed User Guide, metadata tables, and a data table that includes information such as location, lake geometry, surface water connectivity class, and official name. Using our definition, our classification indicates that over 46 % of lakes > 4 ha in the conterminous U.S. are reservoir lakes. These data can be combined with other LAGOS-US data modules and U.S. national databases using unique lake identifiers to study both reservoir lakes and natural lakes at broad scales.
LAGOS-US GEO v1.0: Data module of lake geospatial ecological context at multiple spatial and temporal scales in the conterminous U.S.
The LAGOS-US GEO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The GEO module contains data on the geospatial and temporal ecological setting (e.g., land use, terrain, soils, climate, hydrology, atmospheric deposition, and human influence) quantified at multiple spatial divisions (e.g., equidistant buffers around lakes, watersheds, hydrologic basins, political boundaries, and ecoregions) relevant to the LAGOS-US lake population defined in the LAGOS-US LOCUS module. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and LIMNO (in situ lake physical, chemical, and biological measurements through time) that are each found in their own data packages.
LAGOS-US HUMAN v2: Data module of human population(1990-2020), urbanization classification, and lake access in the conterminous U.S.
The LAGOS-US HUMAN v1 data package is an extension module of the LAGOS-US research platform that includes data characterizing human population (population count, race, ethnicity, socioeconomic information), urbanization, and lake access of 479,950 lakes larger than or equal to 1 ha in the conterminous U.S. (48 states plus the District of Columbia). This data module contains four data tables linked through the unique lake identifier for the LAGOS-US research platform, lagoslakeid. Human population characteristics (race, ethnicity, and socioeconomic factors) were derived from U.S. census data for 1990, 2000, 2010, and 2020. Lakes were classified as urban or not using two different classifications: one based on the ‘Developed’ land category in the National Land Cover Dataset; and another based on the 2020 Census Urban Areas category. Metrics for lake access were developed from national datasets on public boat launches, transportation, and public lands. LAGOS-US HUMAN v1 provides a link between lake data and human contexts, facilitating interdisciplinary research in limnology, urban ecology, environmental justice, and conservation. To facilitate such studies, users are encouraged to use the other three core data modules of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds); GEO (geospatial ecological context at multiple spatial and temporal scales); and LIMNO (in situ lake physical, chemical, and biological measurements through time) that are each found in their own data packages.
LAGOS-US LIMNO: Data module of surface water chemistry from 1975-2021 for lakes in the conterminous U.S.
The LAGOS-US LIMNO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The LIMNO module contains in situ observations of 47 parameters of lake physics, chemistry, and biology (hereafter referred to as chemistry) from lake surface samples (defined as observations taken from the epilimnion of a lake) obtained from the Water Quality Portal, the National Lakes Assessment (2007, 2012, 2017), and NEON programs. LIMNO provides 3,511,020 observations across all parameters collected between 1975 and 2021 from 20,329 lakes; the number of observations per lake ranged from 1 to 20,605 with a median of 32. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other, as well as other comprehensive lake data products such as the USGS NHD), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and GEO (characteristics defining geospatial and temporal ecological setting quantified at multiple spatial divisions) that are each found in their own data packages.
Interagency Ecological Program and US Fish and Wildlife Service: San Francisco Estuary Enhanced Delta Smelt Monitoring Program Data, 2016-2024
The Enhanced Delta Smelt Monitoring Program (EDSM) was initiated by the U.S. Fish and Wildlife Service in 2016. The main purpose of EDSM is to provide information about endemic Delta Smelt (Hypomesus transpacificus) population sizes and distributions within the upper San Francisco Estuary. To track the life cycle of this annual species, larval trawling with a fine-mesh (20 mm) net is conducted during the spring months, and Kodiak trawling for juveniles and adults occurs during the summer, fall, and winter months. Sampling sites are chosen via a stratified random sampling design. A minimum of two tows are conducted at each site, and field staff typically sample between 18 and 41 sites weekly. All fish collected are identified and enumerated, and a subset are measured for body length. Environmental data (water temperature, conductivity, dissolved oxygen, turbidity, depth) are also measured. In addition to Hypomesus spp., this long-term monitoring dataset can also be useful in evaluating the status and trends of other species of interest, especially pelagic fishes. For more information: https://www.fws.gov/office/lodi-fish-and-wildlife
Gender and ethnic diversity of members of US university natural resource program external advisory board members, 2017-2022
This dataset contains deidentified demographics information for the members of external advisory boards that serve university natural resource programs. Data collected in 2017 and 2022 represents a sample of land-grant, National Association of University Forestry Program-affiliated, TIMES-ranked universities and colleges. Each row represents a member of an advisory board. Data collection was completed in two years: 2017 and 2022. Data was collected from department webpages and lists of advisory board members provided by department personnel. As needed, information was augmented through internet searches for public LinkedIn pages, organizational pages, local news stories, etc. Data include a unique respondent ID, a code for the university they are from, their employer affiliation (e.g., NGO, federal government, NR business, etc.) and their gender and ethnicity measured as binary variables.
Application of eDNA as a tool for assessing fish population abundance, Northern Wisconsin, US, 2017 - 2018
Environmental DNA concentrations, WDNR/GLIFWC mark-recapture population estimates, and abiotic lake data on 24 lakes in Wisconsin's Ceded Territory used to evaluate the relationship between walleye abundance and environmental DNA density and its application as a fisheries management tool.
Dataset for: A continuous classification of the 480,000 lakes of the conterminous US based on geographic archetypes
<p>These datasets were used in a journal article with the goal of developing a new geographic classification approach for ~480,000 lakes ≥ 1 ha in the conterminous U.S. based on archetypes defined as endmembers with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. We identified seven lake archetypes; each study lake was then assigned weights for each of the archetypes. The data used to develop the archetypes, archetype weights, and variables used in associated analyses is provided in three data tables. The first includes the lake-specific transformed predictors used to generate the seven archetypes, the weights corresponding to each archetype, the archetype with the maximum weight and the weight of that maximum archetype. The second provides lake-specific raw values for each predictor and for the 19 response variables used to explore aspects of the archetype classification. The final metadata table provides a data dictionary for all columns in the previously mentioned data tables.</p>
PsPM-TC: SCR, ECG, EMG and respiration measurements in a discriminant trace fear conditioning task with visual CS and electrical US.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times from 18 healthy unmedicated participants (8 males and 10 females aged 23.89+/-2.52 years) participating in a classical (Pavlovian) discriminant trace fear conditioning task. CS were a red and a blue rectangle presented for 3 seconds. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 10 Hz frequency. SOA between the CS onset and US was 4 s. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-VC7B: SCR and PSR measurements in a delay fear conditioning task with visual CS and electrical US.
<p>This dataset includes pupil size response (PSR) and skin conductance response (SCR) measurements. Also included are CS and US information, keypress responses, keypress response times, key correctness and shock ratings for each of 21 healthy unmedicated participants (6 males and 15 females aged 27.9+/-5.5 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Four sets of CS+/CS- were used. Simple CS consisted of Gabor patches rotated to the left or to the right; complex CS consisted of plaids created from two Gabor patches that were overlaid on each other with a 230° angle, rotated to the left or to the right. US consisted of a train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants’ dominant forearm through a pin-cathode/ring-anode configuration. SOA between the CS and US is 3.5 s. The ITI is randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-DoxMemP: SCR, ECG and respiration measurements in a delay fear conditioning task with visual CS and electrical US.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times for 20 healthy unmedicated participants (7 males and 13 females aged 26.15+/-4.15 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS were a red and a blue rectangle. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 10 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-FR: SCR, ECG and respiration measurements in a delay fear conditioning task with visual CS and electrical US.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times for 31 healthy unmedicated participants (09 males and 23 females aged 23.32+/-3.61 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS were a red and a blue rectangle. US consisted of 0.5 s square electric pulses with 0.2-ms duration and 10 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. During extinction phase, an auditory startle probe (ST) was delivered 3.8 s after CS onset via headphones (100 dB, 50 ms duration with 2ms on- and offset ramp). The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p> <p> </p>
PsPM-PubFe: Pupil size response in a delay fear conditioning procedure with auditory CS and electrical US.
<p>This dataset includes pupil size response (PSR), skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses, keypress response times and key correctness for each of 22 healthy unmedicated participants (7 males and 15 females aged 26.4+/-5.2 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS consists of two sine tones with constant frequency (220 Hz or 440 Hz, 50-ms onset and offset ramp). US is a train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. SOA betwen the CS and US is 3.5 s. The ITI is randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-SC4B: SCR, ECG, EMG, PSR and respiration measurements in a delay fear conditioning task with auditory CS and electrical US
<p>This dataset includes pupil size response (PSR), skin conductance response (SCR), electrocardiogram (ECG), electromyogram (EMG) and respiration measurements. Also included are CS and US information, keypress responses, keypress response times, key correctness and shock ratings for each of 21 healthy unmedicated participants (10 males and 11 females aged 22.9+/-3.0 years; discrepancies to published studies are due to misprints and exclusion of a subject with incomplete data, which was excluded in all conducted studies as well as here) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Two pairs of CS+ and CS-, either complex or simple, were delivered with headphones (HD518, Sennheiser, Wedemark-Wennebostel, Germany) at about 68 dB. Complex stimuli were a sequence of four rising (400 to 800 Hz) or falling (800 to 400 Hz) sounds lasting 1 s each. Simple stimuli were tones with constant frequency (400 or 800 Hz) presented for 4 s. US consisted of square electric pulses with 0.2-ms duration and 10 Hz frequency, resulting in a total US duration of 0.5 s. SOA betwen the CS and US was 3.5 s. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
Spatiotemporal data for spotted lanternfly occurrence in the US
<p>An aggregated data set containing anonymized, spatiotemporal occurrence data for the spotted lanternfly (<em>Lycorma delicatula</em>, White 1845) in the United States. More details on the data, and additional tools to visualize it, can be found here: https://github.com/ieco-lab/lydemapr, and in the related publication.</p>
MOD-LSP: MODIS-Based Parameters for Variable Infiltration Capacity (VIC) Model over the Continental US, Mexico, and Southern Canada
<p>The MOD-LSP project contains MODIS-based land and surface (soil and vegetation) parameters for the Variable Infiltration Capacity (VIC) model (Liang et al., 1994), release 5.0 and later (Hamman et al., 2018). The MOD-LSP spatial domain covers the continental United States, Mexico, and southern Canada; the associated domain files can be found in the <a href="https://zenodo.org/record/2564019">PITRI archive</a> (Bohn et al. 2018). This spatial domain and 0.625° (6 km) grid resolution are compatible with the gridded daily meteorological forcings of Livneh et al. (2015) ("L2015" hereafter) (http://ciresgroups.colorado.edu/livneh/data/daily-observational-hydrometeorology-data-set-north-american-extent), which can be disaggregated to hourly time step via the MetSim tool (Bennett et al. 2018) using the <a href="https://zenodo.org/record/2564019">aforementioned PITRI domain files</a> (Bohn et al. 2018).</p> <p>These parameters have two main purposes: (1) to improve upon previous widely-used parameters over the region (e.g., L2015) with updated, higher-resolution land cover maps and spatially explicit observations of surface properties; and (2) to expand from a single parameter set corresponding to one point in time to a series of parameter sets that account for temporal variability at seasonal to decadal scales.</p> <p>A detailed description of methods, the data sources and purposes of different VIC parameter sets within MOD-LSP, and how to use them with VIC, can be found in the MOD-LSP User Guide.pdf, included here. The scripts that were used to create the MOD-LSP parameters are archived on <a href="https://zenodo.org/record/3364149">Zenodo and GitHub</a> (Bohn 2019).</p> <p>If you wish to present or publish results that use these parameter sets, please cite the following paper:</p> <p>Bohn, T. J., and E. R. Vivoni, 2019b: MOD-LSP, MODIS-based land surface properties for assessing land cover variability and change over North America. Sci. Data, 6, 144, doi: 10.1038/s41597-019-0150-2.</p> <p>In addition, if you use the domain files associated with the PITRI precipitation disaggregation to accompany the MOD-LSP parameter files in VIC simulations, please cite the following paper:</p> <p>Bohn, T. J., K. M. Whitney, G. Mascaro, and E. R. Vivoni, 2019: A deterministic approach for approximating the diurnal cycle of precipitation for use in large-scale hydrological modeling. J. Hydrometeorol., 20, 297–317, doi:10.1175/JHM-D-18-0203.1.</p> <p>Contents:</p> <ul> <li>MOD-LSP User Guide v1.0.pdf - Explains how parameters were generated and how to set up the files for input in VIC simulations.</li> <li>global_param.template - Template for global_parameter file, which lists the locations of the other input files and sets various simulation options. The template contains placeholders for some filenames and simulation options, which must be replaced with real values by the user.</li> <li>params.$DOMAIN.L2015.nc - VIC-5 compliant NetCDF parameter files with values taken from the L2015 project for domain $DOMAIN (which is one of "CONUS_MX" or "USMX").</li> <li>params.CONUS_MX.MOD_IGBP.mode.2000_2016.nc - VIC-5 compliant NetCDF parameter file over the CONUS_MX domain, with land cover fractions taken from the MODIS MCD12Q1.006 product and an annual cycle of land surface properties (LAI, Fcanopy, albedo) derived from the climatological mean of MODIS observations over the period 2000-2016.</li> <li>params.USMX.NLCD_INEGI.$LCID.2000_2016.nc - VIC-5 compliant NetCDF parameter file over the USMX domain, with land cover fractions taken from the NLCD_INEGI dataset, from year = $LCID, and an annual cycle of land surface properties (LAI, Fcanopy, albedo) derived from the climatological mean of MODIS observations over the period 2000-2016.</li> <li>params.USMX.NLCD_INEGI.$LCID.$YYYY_$YYYY.nc - VIC-5 compliant NetCDF parameter file over the USMX domain, with land cover fractions taken from the NLCD_INEGI dataset, from year = $LCID, and an annual cycle of land surface properties (LAI, Fcanopy, albedo) derived from the MODIS observations from a single year $YYYY.</li> <li>veg_hist.$DOMAIN.$LCTYPE.$LCID.2000_2016.nc - timeseries of monthly land surface properties (LAI, Fcanopy, albedo) from MODIS observations spanning years 2000-2016, over domain $DOMAIN, aggregated over land cover classification $LCTYPE from year $LCID.</li> </ul>
PsPM-FSS6B: SCR and PSR measurements in a delay fear conditioning task with somatosensory CS and electrical US
<p>This dataset includes skin conductance response (SCR) and pupil size response (PSR) measurements. Also included are CS and US information, keypress responses, keypress response times and key correctness for each of 18 healthy unmedicated participants (10 males and 8 females aged 25.7+/-5.0 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Simple and complex CS are delivered to the intermediate phalanges of the index and middle fingers of the non-dominant hand. Simple stimuli are stimulations to either index or middle finger, complex stimuli are stimulations of different temporal structure to both index and middle fingers. CS intensity is set to a perceivable but not unpleasant level. US is a train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. SOA between the CS and US is 3.5 s. The ITI is randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-LI: SCR, ECG, PSR and respiration measurements in a delay fear conditioning task with auditory CS and electrical US.
<p>This dataset includes pupil size response (PSR), skin conductance response(SCR), electrocardiogram (ECG) and respiration measurements for each of 20 healthy unmedicated participants (8 males and 12 females aged 22.8+/-3.3 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. (One additional participant in the initial sample in Korn et al. (2017) - but who did not finish the experiment and was not included into the analysis - is not contained in this dataset.) The acquisition data is separated into two sessions which were recorded consecutively with a break of approximately 5 min. CS consist of two sine tones with constant frequency (220 Hz or 440 Hz, 50-ms onset and offset ramp) and last for 6.5 s. US is a 0.5 s train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. SOA betwen the CS and US is 6 s. The ITI is randomly determined on each trial to be 7, 9, or 11 s.</p>
LAGOS-US DEPTH v1.0: Data module of observed maximum and mean lake depths for a subset of lakes in the conterminous U.S.
The LAGOS-US LAKE DEPTH v1.0 module (hereafter, called DEPTH) contains in situ measurements of lake depth for a subset of all lakes (n = 17,675) in the conterminous U.S. > 1 ha (3.7% of 479,950) that are in the LAGOS-US LOCUS v1.0 data module (Smith et al. 2021). All 17,675 lakes in DEPTH have a maximum depth value and 6,137 lakes have a mean depth. DEPTH includes approximately 65 data sources obtained from community, government, and university monitoring programs, as well as academic reports and commercial websites. DEPTH includes lake identifiers, lake location, lake area, lake depth (both maximum and mean depth when available), source information, and data flags. The unique lake identifier (lagoslakeid) for all lakes is the same one used in LAGOS-US LOCUS v1.0.
US_UMB and US_UMd Ameriflux towers biometric plot data at the University of Michigan Biological Station, Pellston, MI (1997 to 2024)
These are the annual leaf litterfall carbon fluxes and average soil respiration measurements for the two flux towers (reference, aka 'AmeriFlux' and treatment, aka 'FASET') at UMBS.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.