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- Description:
- This dataset contains the behavioral and neurophysiological data supporting the manuscript “Evidence that interval-counting neurons play a critical role in call recognition by Cope’s gray treefrogs.” Together, these datasets provide a direct link between behavioral selectivity for species-specific advertisement calls and the response properties of specialized temporal processing neurons., Behavioral dataset(20240815_MixedIntervalPhonotaxis_Kamath.xlsx): Binary phonotaxis responses of female Hyla chrysoscelis collected during the 2024 breeding season. Each row represents an individual frog, and columns report responses (1 = positive phonotaxis, 0 = no response) across standard and temporally disrupted advertisement call conditions (1X, MI=2X, MI=3X, AI=2X, AI=3X)., and Neurophysiology dataset (20250815_ExtracellularICN_LIN_Kamath.xlsx): In vivo extracellular single-unit recordings from three classes of auditory midbrain neurons—interval-counting neurons (ICNs), long-interval neurons (LINs), and temporally non-selective neurons—collected between July 2024 and August 2025. Each sheet reports neuron metadata (recording date, ID, frequency sensitivity, pulse rate, pulse number threshold for ICNs) and normalized spike responses to standard and temporally disrupted stimuli (MI and AI paradigms).
- Keyword:
- Neural basis of numerosity, Neural correlates of behavior, Neurophysiology, Temporal processing, Inferior colliculus, and Acoustic communication
- Subject:
- Acoustic communication, Neuroethology, Neurophysiology, and Animal behavior
- Creator:
- Kamath, Vinayak G.
- Contributor:
- Bee, Mark A., Alluri, Rishi K., Rose, Gary J., Acord, A. Sage, and Mukhopadhyay, Anwesha
- Owner:
- Based Near Label Tesim:
- Ramsey, Minnesota, United States, Saint Paul, Minnesota, United States, and Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 08/19/2025
- Date Modified:
- 08/21/2025
- Date Created:
- 2024-05-01 to 2025-08-15
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-7mt5-z18h
-
- Description:
- The simulations related to the present dataset investigate the effects of heterogeneity in tall vegetated canopies, designed to emulate structural and aerodynamic characteristics of the Amazon rainforest. A total of 15 canopy configurations are considered, all assuming neutral stratification and a boundary layer height of zi = 1000 m. Fourteen configurations are driven by a geostrophic wind speed of 9 m/s, with a friction velocity of u* = 0.313 m/s. In contrast, the configuration Hom_eq_gaps_pfx_9mps is forced by a streamwise pressure gradient normalized as (1/ρ)(∂p/∂x) = 1, where ρ denotes hydrostatic density. This normalization employs a reference friction velocity of u* = 0.58 m/s and the same boundary layer height zi = 1000 m, such that ∂p/∂x ∼ (u*)^2/zi. and See README file for data retrieval instructions.
- Keyword:
- Large Eddy Simulations, TKE budget, traditional turbulence statistics, and Vegetated canopies
- Subject:
- Turbulence, Computational fluid dynamics , and Atmospheric science
- Creator:
- Salmaso, Giulia and Calaf, Marc
- Owner:
- Kaylee Alexander
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 06/09/2025
- Date Modified:
- 06/18/2025
- Date Created:
- 2022-01-01 to 2025-05-29
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-n96s-3gkr
-
- Description:
- This dataset contains measurements from an OTT PARticle SIze and VELocity (PARSIVEL) disdrometer which was installed on the roof of Highland High School in Salt Lake City, Utah, USA (40.724486°N; 111.843723°W; 1372 m MSL) during the cool seasons (November 15 – April 30) ending 2023 through 2024.
- Keyword:
- Orographic precipitation, Snow, Disdrometer, and PARSIVEL
- Subject:
- Atmospheric Science, Precipitation, and Snow
- Creator:
- Kingsmill, David E., Veals, Peter G., Wasserstein, Michael L., Evans, Ashley, and Steenburgh, Jim
- Owner:
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 06/05/2025
- Date Modified:
- 06/10/2025
- Date Created:
- 2022-11-26 to 2024-05-10
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-8vtz-5fsn
-
- Description:
- This dataset contains precipitation measurements from an OTT PARticle SIze and VELocity (PARSIVEL) disdrometer which was installed at the Atwater snow study plot in the town of Alta, Utah, USA (40.591269°N; 111.637789°W; 2682 m MSL) during the cool seasons ending 2023 through 2024.
- Keyword:
- Orographic precipitation, Snow, Disdrometer, and PARSIVEL
- Subject:
- Atmospheric Science, Precipitation, and Snow
- Creator:
- Evans, Ashley, Wasserstein, Michael L., Kingsmill, David E., Steenburgh, Jim, and Veals, Peter G.
- Owner:
- Based Near Label Tesim:
- Alta, Utah, United States
- Language:
- English
- Date Uploaded:
- 06/05/2025
- Date Modified:
- 06/10/2025
- Date Created:
- 2022-11-15 to 2024-05-15
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-wtpn-az0j
-
- Description:
- This is data from a Micro Rain Radar (MRR) that was deployed at Highland High School in Salt Lake City, UT from 2022–2024. The MRR is a vertically pointing Doppler radar that operates at a frequency of 24 GHz (K-band). The radar collects time series of equivalent reflectivity, Doppler velocity, and Doppler velocity spectrum width, all in 1-dimension (the vertical).
- Keyword:
- MRR, Profiling Radar, Snow, and Precipitation
- Subject:
- Radar, Precipitation, Snow, and Atmospheric Science
- Creator:
- Veals, Peter G., Wasserstein, Michael L., and Steenburgh, Jim
- Owner:
- Kaylee Alexander
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 06/02/2025
- Date Modified:
- 06/06/2025
- Date Created:
- 2022-11-23 to 2024-05-10
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-n1jc-2d68
-
- Description:
- This is data from a Micro Rain Radar (MRR) that was deployed at Alta, UT from 2022–2024. The MRR is a vertically pointing Doppler radar that operates at a frequency of 24 GHz (K-band). The radar collects time series of equivalent reflectivity, Doppler velocity, and Doppler velocity spectrum width, all in 1-dimension (the vertical).
- Keyword:
- MRR, Profiling Radar, Snow, and Precipitation
- Subject:
- Radar, Precipitation, Snow, and Atmospheric Science
- Creator:
- Steenburgh, Jim, Wasserstein, Michael L., and Veals, Peter G.
- Owner:
- Kaylee Alexander
- Based Near Label Tesim:
- Alta, Utah, United States
- Language:
- English
- Date Uploaded:
- 06/02/2025
- Date Modified:
- 06/06/2025
- Date Created:
- 2022-10-28 to 2024-05-15
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-wern-v6kz
-
- Description:
- This repository includes a file containing polygon data for river channel data for eight study reaches (1, 2A, 2B, 2B short, 3A, 3B, 4A, 4B) across multiple years (1974, 1981, 1995, 2000, 2007 to 2017, and 2018 to 2022), along the Escalante River, Utah, USA. Each channel delineation is uniquely identified by year and reach. Historic imagery was collected from United States Geological Survey and Bureau of Land Management; sourced imagery was accessed through EarthExplorer ( https://earthexplorer.usgs.gov/#close); NAIP imagery from the USDA Geospatial Data Gateway ( https://datagateway.nrcs.usda.gov/GDGHome_DirectDownLoad.aspx); and ESRI imagery from World Imagery Wayback ( https://livingatlas.arcgis.com/wayback/#active=16681&mapCenter=-111.19835%2C37.64870%2C18)
- Keyword:
- Escalante River Watershed, Channel Delineation, GIS, and shapefiles
- Subject:
- Image processing, Water channels, Geographic Information Systems, and Rivers/streams
- Creator:
- McNeally, Phoebe, Scott, Michael L., Williams, Erin J., Friedman, Jonathan M. , and Spence, John R.
- Owner:
- Based Near Label Tesim:
- Escalante, Utah, United States
- Language:
- English
- Date Uploaded:
- 05/27/2025
- Date Modified:
- 05/29/2025
- Date Created:
- 2022 to 2023 (collected) and 1974, 1981, 1995, 2000, 2007 to 2017, 2018 to 2022 (sources)
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset and Map or Cartographic Material
- Identifier:
- https://doi.org/10.7278/S5d-hyk0-w2kf
-
- Description:
- We deployed a Nanometrics Trillium Compact 20-s, three-component broadband seismometer on the summit of Devils Tower between October 12-13, 2024. The instrument was hauled and carried to the summit by a team of climbers under an approved permit from the National Park Service. The seismometer (labelled station D) was located on the northern portion of the tower summit. It was placed on bare bedrock, with a dab of adhesive putty under each foot to aid coupling, leveled and oriented north, and then covered to prevent wind buffeting. The seismometer was paired with a 24-bit Nanometrics Centaur datalogger recording continuous data at 100 Hz. Two additional identical seismometer setups were also deployed: station C on bedrock near the base of the tower’s south wall, and station A on a large flat boulder embedded in colluvium ~200 m south of the tower. The various instruments had different run times: station D on top of the tower ran the longest for 21 hours from afternoon to late morning, while the overlapping duration of the three sensors was 19 hours (10/12 20:00 to 10/13 15:00 UTC).
- Keyword:
- national parks, modal analysis, and seismology
- Subject:
- seismology and modal response
- Creator:
- Moore, Jeffrey R., Vollinger, Kathryn, and Burjánek, Jan
- Owner:
- Jeff Moore
- Based Near Label Tesim:
- Devils Tower, Wyoming, United States
- Language:
- English
- Date Uploaded:
- 05/14/2025
- Date Modified:
- 05/28/2025
- Date Created:
- 2024-10-12 to 2024-10-13
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-ajvn-wqqq
-
- Description:
- This dataset includes the python scripts and data required to reproduce work outlined in Mayhew et al. 2025 “The Global Importance of Gas-phase Peroxy Radical Accretion Reactions”. The study investigates the effect of a new atmospheric chemical pathway, gas-phase peroxy radical (RO2) accretion reactions, on global secondary organic aerosol (SOA).
- Keyword:
- Peroxy radical, Climate, Air quality, Aerosol, Accretion reactions, and RO2
- Subject:
- Climate and Air quality
- Creator:
- Haskins, Jessica and Mayhew, Alfred
- Owner:
- Madison Golden
- Language:
- English
- Date Uploaded:
- 04/14/2025
- Date Modified:
- 07/16/2025
- Date Created:
- 2025-04-01
- License:
- CC BY – Allows others to use and share your data, even commercially, with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-80qm-kyjj
-
- Description:
- This data set contains 12-hour manual new snow and liquid precipitation equivalent (LPE) observations collected at the Alta-Collins (CLN) snow-study plot during the 2023/2024 cool season (October 1–April 30). CLN is located mid-mountain at Alta Ski Area in the Wasatch Range of northern Utah (approximately 111.63889W, 40.57607N) at an elevation of 2945 m.
- Keyword:
- atmospheric sciences and precipitation
- Subject:
- Precipitation
- Creator:
- Wasserstein, Michael L. and Steenburgh, Jim
- Owner:
- Based Near Label Tesim:
- Alta, Utah, United States
- Language:
- English
- Date Uploaded:
- 04/09/2025
- Date Modified:
- 04/25/2025
- Date Created:
- 2023-10-01 to 2024-04-30
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-dx7x-d8ay