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18,820 results for “northing”
North Temperate Lakes LTER: Vilas County Property Tax Records 1997 - 2004
Each year, the county government in Vilas County, WI, assembles data on each parcel of property in the county for various governmental administrative purposes. These records serve the register of deeds, the department of taxation, and other county departments, as well as private citizens or businesses, such as realtors, who seek information on properties in the county. These records include assessments of the value of land and built improvements, their location, the name and mailing address of the owner, and other data. LTER has begun to collect these data each year from the county as a means of monitoring owners, and the social identities of owners (whether they are state agencies, private individuals, corporations, non-profit/conservation organizations, etc.). These data have already proved useful as a sampling frame for social science surveys. This data set includes property tax records for Vilas County for the years 1997, 1998, 2001, 2003, and 2004. Sampling Frequency: annually Number of sites: 15 Townships of Vilas County, WI, USA
Cascade Project at North Temperate Lakes LTER: Weekly dissolved methane profiles (2018, 2019, and 2024)
Weekly profiles of dissolved methane concentrations, dissolved oxygen, temperature, and light were measured during three summers (2018, 2019, and 2024) in two north temperate lakes. One of the lakes was experimentally enriched with nitrogen and phosphorus during two summers (2019 and 2024), and darkened using a blue dye in one summer (2024). The other lake was an unmanipulated reference. Using this series of whole-lake enrichment and shading experiments across three years with varying ice phenology, we assessed how eutrophication and ice cover affect within-year methane storage.
Cascade Project at North Temperate Lakes LTER: Primary Production 1984 - 1990
CASCADE Primary Production Dataset Sampling Frequency: varies Number of sites: 3
Cascade Project at North Temperate Lakes LTER: Piscivore Fish 1984 - 2003
Fish collected for the Casade Project. Sampling Frequency: varies Number of sites: 9
Landscape Position Project at North Temperate Lakes LTER: Chemical Limnology 1998 - 2000
Parameters characterizing the chemical limnology and spatial attributes of 51 lakes were surveyed as part of the Landscape Position Project. Parameters are measured at or close to the deepest part of the lake. The following parameters are measured one meter from the surface and two meters from the bottom of the lake: pH, total phosphorus, total nitrogen, total silica. The following parameters are measured one meter from the surface: dissolved organic carbon, total organic carbon, dissolved inorganic carbon, total inorganic carbon, spectrophotometric absorbance (color scan), major anions and cations, alkalinity. Sampling Frequency: once for conservative parameters (major ions, carbon, color, alkalinity); monthly for one summer for other parameters (chlorophyll, nitrogen, phosphorus, pH, silica, temperature, dissolved oxygen, and conductivity) Number of sites: 51
Landscape Position Project at North Temperate Lakes LTER: Chlorophyll 1998 - 2000
Parameters characterizing the chemical limnology and spatial attributes of 49 lakes were surveyed as part of the Landscape Position Project. Most parameters are measured at or close to the deepest part of the lake. Chlorophyll is measured by collecting separate integrated samples from the epilimnion, metalimnion, and hypolimnion Sampling Frequency: generally monthly for one summer; for some lakes, one or two samples in one summer Number of sites: 51
Landscape Position Project at North Temperate Lakes LTER: Lake Characteristics 1998 - 2000
Parameters characterizing the chemical limnology and spatial attributes of 47 lakes were surveyed as part of the Landscape Position Project. Lake characteristics compiled here include lake area and perimeter, catchment area, mean and maximum depth, shoreline development factor, elevation and percent wetlands within catchment area. Lake order was determined using a modification of the method of Riera et al. (2000). Lake order is a numerical surrogate for groundwater influx and hydrological position along a drainage network, with the highest number indicating the lake lowest in a watershed. Lake order for each lake was determined by field visit with presence/absence of streams confirmed, not base solely on topographic maps. Riera, Joan L., John J. Magnuson, Tim K. Kratz, and Katherine E. Webster. 2000. A geomorphic template for the analysis of lake districts applied to Northern Highland Lake District, Wisconsin, U.S.A. Freshwater Biology 43:301-18. Number of sites: 49
Landscape Position Project at North Temperate Lakes LTER: Vertical Lake Profiles 1998 - 1999
Parameters characterizing the chemical limnology and spatial attributes of 45 lakes were surveyed as part of the Landscape Position Project. Parameters are measured at or close to the deepest part of the lake. A vertical profile of temperature, dissolved oxygen, and conductivity are collected at 1 meter increments Sampling Frequency: generally monthly for one summer; for some lakes, one or two samples in one summer Number of sites: 45
Landscape Position Project at North Temperate Lakes LTER: Benthic Invertebrate Abundance 1998 - 1999
Benthic invertebrate assemblages of 32 lakes were surveyed as part of the Landscape Position Project. We used modified Hester-Dendy colonization substrates to sample benthic invertebrate communities. Each sampling device consisted of a 3"x3" top plate, alternating layers of course and fine mesh, a ''choreboy'' commercial scrubbing puff, alternating layers of coarse (6.35 mm) and fine (3.18 mm) black plastic mesh, and a 3"x3" bottom plate. Two Hester-Dendy samplers were set at a depth of one meter on each of three substrate types (cobble, sand and silt) within each lake for four weeks in late June through late July in either 1998 or 1999. Within each lake, areas of different substrate types were identified using WI-DNR depth contour lake maps, and substrate type was verified by direct observation. Different substrates were sampled to account for invertebrate associations with specific substrate characteristics. Lake order was determined using a modification of the method of Riera et al. (2000). Lake order is a numerical surrogate for groundwater influx and hydrological position along a drainage network, with the highest number indicating the lake lowest in a watershed. Riera, Joan L., John J. Magnuson, Tim K. Kratz, and Katherine E. Webster. 2000. A geomorphic template for the analysis of lake districts applied to Northern Highland Lake District, Wisconsin, U.S.A. Freshwater Biology 43:301-18. Sampling Frequency: one survey on each lake in late June through late July of 1998 or 1999 Number of sites: 32
Landscape Position Project at North Temperate Lakes LTER: Fish Growth and Mercury Contaminant Data 1998 - 1999
As part of the Landscape Position Project, yellow perch were collected for mercury and isotope analysis by a combination of angling, beach seining, vertical gill net, fyke net and electrofishing in the summers of 1998 and 1999. A total of 86 yellow perch from 25 lakes were analyzed. Scales were used to determine age and length at ages 1 to 3 years. The nitrogen stable isotope signature indicates the relative food-web position of the fish relative to cladocerans collected from the same lake. The N_SIGNATURE value divided by 3.2 gives trophic position relative to cladoceran Sampling Frequency: one survey on each lake in late June through late July of 1998 or 1999 Number of sites: 25
Landscape Position Project at North Temperate Lakes LTER: Fish Mercury Level 1998 - 1999
As part of the Landscape Position Project, yellow perch were collected for mercury and isotope analysis by a combination of angling, beach seining, vertical gill net, fyke net and electrofishing in the summers of 1998 and 1999. A total of 183 yellow perch from 43 study lakes with approximate length of 150 mm were analyzed. Sampling Frequency: one survey on each lake in late June through August of 1998 or 1999 Number of sites: 43
15N (Nitrate and Ammonium) Uptake by Spartina Alterniflora Sourced from Plum Island Estuary, MA and North Inlet, SC
15N uptake measurements were taken from Spartina alterniflora plants grown from seeds originating from six march locations in PLUM Island Estuary (PIE) and North Inlet, SC. All sites were Spartina alterniflora dominated marsh. 15N uptake was measured after 60 minutes in Nitrate, Ammonium, or control treatments. Seeds were collected in Fall 2022, reared Winter-Summer 2023, and uptake measured in Summer 2023.
North Sea Wave Database (NSWD) 2005-2011
<p>North Sea Wave Database (NSWD)<br> The dataset contains each year of spectral metocean condition for Significant Wave Height (HSIGN) and wave energy period (TMM10), in meters and seconds.<br> Each variable has a year timestap which the data corresponds too i.e 1980. The latitudes and longitudes of the dataset have resolution of 0.025 degrees at each direction. Latitude starting coordinate is 50 degrees and Longitude 0.</p> <p>For more information on the process that developed the dataset, the methodogies followed, calibration, valdiation and sensitivity analysis, <br> see: </p> <p>Lavidas, G., & Polinder, H. (2019). North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments. Atmosphere, 10(9), <a href="https://doi.org/10.3390/atmos10090551">https://doi.org/10.3390/atmos10090551 </a></p> <p>Lavidas, G., & Polinder, H. (2019). Wind effects in the parametrisation of physical characteristics for a nearshore wave model. Proceedings of the 13th European Wave and Tidal Energy Conference 1-6 September 2019, Naples, Italy.</p> <p>The dataset was produced by Dr George Lavidas during the WAVe Resource for Electrical Production (WAVREP, which received funding from the European Union's Horizon 2020 research & innovation programme under the Marie Sklodowska-Curie grant agreement No 787344.</p> <p>The dataset is accompanied by two publication that (i) present the calibration-validation and production (ii) analysis of the dataset.</p> <p>The official CORDIS website is https://cordis.europa.eu/project/id/787344<br> A list of outcomes for the NSWD and the WAVREP project is found at the researcher's page:<br> <a href="https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP ">https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP </a></p> <p>It can also be found at the official CORDIS website<br> <a href="https://cordis.europa.eu/project/id/787344">https://cordis.europa.eu/project/id/787344</a></p> <p>Sharing and Access information<br> Creative Commons Attribution (CC BY-SA). <br> The Creative Commons Attribution license allows others remix, tweak, and build upon your work, as long as they credit you and license their new creations under the identical terms.</p>
North Sea Wave Database (NSWD) 1989-1997
<p>North Sea Wave Database (NSWD)<br> The dataset contains each year of spectral metocean condition for Significant Wave Height (HSIGN) and wave energy period (TMM10), in meters and seconds.<br> Each variable has a year timestap which the data corresponds too i.e 1980. The latitudes and longitudes of the dataset have resolution of 0.025 degrees at each direction. Latitude starting coordinate is 50 degrees and Longitude 0.</p> <p>For more information on the process that developed the dataset, the methodogies followed, calibration, valdiation and sensitivity analysis, <br> see: </p> <p>Lavidas, G., & Polinder, H. (2019). North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments. Atmosphere, 10(9), <a href="https://doi.org/10.3390/atmos10090551">https://doi.org/10.3390/atmos10090551 </a></p> <p>Lavidas, G., & Polinder, H. (2019). Wind effects in the parametrisation of physical characteristics for a nearshore wave model. Proceedings of the 13th European Wave and Tidal Energy Conference 1-6 September 2019, Naples, Italy.</p> <p>The dataset was produced by Dr George Lavidas during the WAVe Resource for Electrical Production (WAVREP, which received funding from the European Union's Horizon 2020 research & innovation programme under the Marie Sklodowska-Curie grant agreement No 787344.</p> <p>The dataset is accompanied by two publication that (i) present the calibration-validation and production (ii) analysis of the dataset.</p> <p>The official CORDIS website is https://cordis.europa.eu/project/id/787344<br> A list of outcomes for the NSWD and the WAVREP project is found at the researcher's page:<br> <a href="https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP ">https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP </a></p> <p>It can also be found at the official CORDIS website<br> <a href="https://cordis.europa.eu/project/id/787344">https://cordis.europa.eu/project/id/787344</a></p> <p>Sharing and Access information<br> Creative Commons Attribution (CC BY-SA). <br> The Creative Commons Attribution license allows others remix, tweak, and build upon your work, as long as they credit you and license their new creations under the identical terms.</p>
North Sea Wave Database (NSWD) 2012-2017
<p>North Sea Wave Database (NSWD)<br> The dataset contains each year of spectral metocean condition for Significant Wave Height (HSIGN) and wave energy period (TMM10), in meters and seconds.<br> Each variable has a year timestap which the data corresponds too i.e 1980. The latitudes and longitudes of the dataset have resolution of 0.025 degrees at each direction. Latitude starting coordinate is 50 degrees and Longitude 0.</p> <p>For more information on the process that developed the dataset, the methodogies followed, calibration, valdiation and sensitivity analysis, <br> see: </p> <p>Lavidas, G., & Polinder, H. (2019). North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments. Atmosphere, 10(9), <a href="https://doi.org/10.3390/atmos10090551">https://doi.org/10.3390/atmos10090551 </a></p> <p>Lavidas, G., & Polinder, H. (2019). Wind effects in the parametrisation of physical characteristics for a nearshore wave model. Proceedings of the 13th European Wave and Tidal Energy Conference 1-6 September 2019, Naples, Italy.</p> <p>The dataset was produced by Dr George Lavidas during the WAVe Resource for Electrical Production (WAVREP, which received funding from the European Union's Horizon 2020 research & innovation programme under the Marie Sklodowska-Curie grant agreement No 787344.</p> <p>The dataset is accompanied by two publication that (i) present the calibration-validation and production (ii) analysis of the dataset.</p> <p>The official CORDIS website is https://cordis.europa.eu/project/id/787344<br> A list of outcomes for the NSWD and the WAVREP project is found at the researcher's page:<br> <a href="https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP ">https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP </a></p> <p>It can also be found at the official CORDIS website<br> <a href="https://cordis.europa.eu/project/id/787344">https://cordis.europa.eu/project/id/787344</a></p> <p>Sharing and Access information<br> Creative Commons Attribution (CC BY-SA). <br> The Creative Commons Attribution license allows others remix, tweak, and build upon your work, as long as they credit you and license their new creations under the identical terms.</p>
A Lagrangian study of the contribution of the Canary coastal upwelling to the nitrogen budget of the open North Atlantic
<p>The attached datasets constitute the particle trajectory data produced in the experiment for Hailegeorgis et al..</p> <p>The "traj_upwell_1d_70m_1d-variables.nc" contains variables that describe different aspects of each upwelled particle (mostly regarding a particle's release or its initial or final conditions).</p> <p>The rest of the files with the format "traj_upwell_1d_70m_XXX-traj.nc" describe an attribute XXX (location or nutrient concentration) along the trajectory of upwelled particles tracked as part of the experiment.</p> <p>With ARIANE, particles are released and tracked in a ROMS simulation of the Canary coastal upwelling region. Out of the ~10M particles, the trajectories of the ~353K (~3.6%) that upwell are included. The variable "index_in_full_exp" in file "traj_upwell_1d_70m_1d-variables.nc" shows the index of each of these upwelling particles in the larger pool of released particles. For each upwelled particle, out of the 720-day trajectories starting from its release into the coast, the values from its upwelling step to its exit from the experiment are included, with the values outside this range being filled with a generic value (1.e20). An upwelled particle exits the experiment when it leaves the regional ROMS simulation altogether or when it leaves the coast and returns to the coast to re-upwell (more details in the paper).</p> <p>Be mindful of the different values of time. In "traj_upwell_1d_70m_1d-variables.nc", the variable "release_time" tells each particle's release time, in days since onset of the ROMS simulation, while variable "coast_exit_time" tells each particle's day of exiting coast, in days since its release. In each particle's trajectory (in traj_lon, traj_lat, etc), the first and last steps with valid values are the same as the days of its upwelling and its exit, respectively, since its release.</p> <p>The files contain the name and description of each variable. Along with the details in the publication, the descriptions here should be enough to fully interpret the information and replicate our analysis.</p>
Hubble and Spitzer data around a z=7.2 quasar in the GOODS-North Field
<p>This dataset provides 10-arcminute HST and Spitzer mosaics of the GOODS-North survey field, centered on the z=11.1 galaxy GNz11 (<a href="https://ui.adsabs.harvard.edu/abs/2016ApJ...819..129O/abstract">Oesch et al. 2016</a>) and including a z=7.2 quasar (Fujimoto et al., in prep). Complete mosaics are available at https://s3.amazonaws.com/grizli-v1/Mosaics/index.html.</p> <p>The mosaics were produced with the <a href="https://github.com/gbrammer/grizli">grizli</a> (HST) and <a href="https://github.com/gbrammer/golfir">golfir</a> (Spitzer) software modules.</p> <p>Also included are the 2D extracted grism spectra (gnz7qso_16155.beams.fits) that can be analyzed with grizli.</p> <p><strong>Table 1:</strong> HST exposure summary</p> <pre><strong>Filter N t(ks) Proposal ID</strong> f435w 6 7.2 9583 f606w 23 9.3 9583,10339,12443,13779 f775w 35 19.1 9583,9727,9728,10339,11600 f814w 42 23.8 12442,12443,12444,12445,13420 f850lp 82 36.9 9583,9727,9728,10189,10339,12444,13063 f105w 6 3.3 12442,13420 f125w 8 4.4 12443,12444,12445 f140w 6 1.2 11600 f160w 8 5.4 12443,12444,12445 g102 4 5.0 13420 g141 8 8.6 11600 </pre>
Modelled distributions of fish and epibenthic invertebrates in the southern North Sea
<p>These data include distribution maps of fish and invertabrate species in the southern North Sea from 2014 until 2023. The maps are modelled using point data of presence/absence and biomass (per trawled km²) from scientific fisheries surveys to estimate the distribution of the probability of occurrence (POC) or biomass (kg per km²), respectively. Also included are forecasts of species' distributions assuming increasing water temperatures in the southern North Sea according to the ICCP scenario RCP8.5.</p> <p>Each files contains a raster stack with layers for each species. The data can be read into the R using the 'stack'-command from the 'raster'-package. The raster stacks contain layers with headers, which code the species and size group. For some species of relevance to fisheries managment, Numbers behind the latin names of the species give information on the included size classes in cm with 'no' indicating no size class information was available.</p> <p>The file names are composed of the follwing elements:</p> <p>'bio' = biomass</p> <p>'poc' = probability of occurrence</p> <p>'emp' = observed occurrence/abundance data from fisheries surveys with employed spatial smoother</p> <p>'sdm' = modelled distributin data from random forests</p> <p>'fc' = forecast distributions based on temperature predictors according to RCP8.5</p> <p>'rel.ca2' = core areas (CA) of distribution representing values > then the mid-point of modelled POC value range</p> <p>Year numbers give the time frame of empirical data or model predictions. </p> <p> </p> <p><strong>You can access the .tiff-files with the following R-commands using the directory path where you have stored the files:</strong></p> <p><em><strong>library(raster)</strong></em></p> <p><em><strong>poc<-stack("your_path/poc.sdm.2014_2023.tiff")</strong></em></p> <p><em><strong>poc$gadus.morhua_5_113 </strong># Plots distribution of Atlantic cod as probability of occurrence observed at a size range from 5 - 113 cm tail length</em></p>
Dataset to: Organic carbon stocks, quality and prediction in permafrost-affected forest soils in North Canada (CATENA) - Version 2 (Corrected)
<p><strong>Version update: Coordinates were not correct in previsous version and have been corrected now in version 2</strong></p> <p> </p> <p>Dataset to the manuscript: Schiedung et al. (2022, Catena) Organic carbon stocks, quality and prediction in permafrost-affected forest soils in North Canada ( <a href="https://doi.org/10.1016/j.catena.2022.106194">https://doi.org/10.1016/j.catena.2022.106194</a> )</p> <p>Data files, variables and parameter are described in <em>Var_names_dd_all.csv</em> for all data on each sample and <em>Var_names_dd_composites.csv </em>for all data on composited samples per site and depth. DRIFT data and corresponding explenation are in <em>Schiedung_CATENA_DRIFT_v1.1.zip.</em></p> <p> </p> <p><strong> </strong></p>
Urban Riparian Wetland Hydrology Dataset_Stormwater Capture in Beaver-mediated Wetlands along Walnut Creek, Raleigh, North Carolina, USA
<p>This is the initial release of a <strong>hydrology</strong> dataset pertaining to the <strong>riparian floodplain wetlands</strong> alongside Walnut Creek in Raleigh, North Carolina USA. Walnut Creek is the main drainage channel in an <strong>urbanized watershed</strong> (HUC-12: 030202011101) in central North Carolina. There are several riparian floodplain wetlands along the creek which are largely supplied by <strong>urban stormwater</strong> runoff including directed <strong>storm sewer flows</strong> and regular <strong>overbank flooding</strong> events. In many of these wetlands local water retention and residence time in the surface ponds is mediated by the damming activity of <strong>North American beavers (<em>Castor canadensis</em>)</strong>. This dataset contains data specific to the hydrology of Walnut Creek, and the surface ponds and groundwater at the <strong>Walnut Creek Wetland Park</strong> which is actively influenced by resident beavers. The period of this dataset is from <strong>January 22, 2023 through January 30, 2024</strong>. </p> <p>The core of the dataset is water stage measured in five surface pond sites and six groundwater monitoring wells within Walnut Creek Wetland Park. This data was collected using synchronized Solinst Levelogger pressure transducer sensors at 15-minute intervals, compensated with corrections for barometric pressure measured locally using a Solinst Barologger sensor. In addition to this data collected by the authors, this dataset also includes publicly available stream stage and precipitation data obtained from the <strong>US Geological Survey,</strong> and weather and soils data from the <strong>North Carolina State Climate Office</strong>. In total, this dataset aims to provide a comprehensive view of surface and subsurface hydrology in the studied wetlands as it connects with precipitation events, antecedent moisture conditions, directed stormwater flows and overbank flood events. </p> <p>This hydrology dataset is intended to accompany the <u>separate</u> <strong>water quality dataset</strong> published on Zenodo at URL: <a href="https://doi.org/10.5281/zenodo.10888463">https://doi.org/10.5281/zenodo.10888463</a>. Together, these datasets are meant to support an improved understanding of the water availability and water quality found in connection with beaver-mediated stormwater capture in an urbanized watershed in the North Carolina Piedmont.</p> <p>This dataset resulted from research supported with a Graduate Student Research Grant awarded by the <strong>North Carolina Water Resources Research Institute (WRRI)</strong>, under Project Number 23-10-W: "Stormwater Diversion, Storage, and Treatment by Beaver-enhanced Floodplain Wetlands in Piedmont Urban Watersheds". </p> <p>This material is based upon work supported by the <strong>National Science Foundation (NSF)</strong> Graduate Research Fellowship Program (GRFP) under Grant No. (DGE 2137100). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.</p> <p>Special thanks to <strong>Raleigh Parks</strong> and <strong>Walnut Creek Wetland Park</strong> for making this work possible.</p>
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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.