cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/ba4406f296172a0297d87522f6e2faa3
title: North Temperate Lakes LTER: Northern Wisconsin Lake Resident Survey 2005

description: The purpose of this 2005 survey was to understand what lake characteristics people value most, what activities they enjoy most, and what they expect for the future of northern Wisconsin lakes. Questions covered aspects such as the property search process individuals went through leading up to their purchase of lakeshore property in Vilas County WI, what activities the individual's household participate in on lakes in Vilas County WI, their attitude about the future of their lake, their perception of the current state of their lake, and lake qualities they would like improved on their lake. Demographics of the respondents and background information about their lake were also collected. Two types of surveying methodologies were used for this survey, one being an internet-based survey, while the other was a mail survey. The dataset includes 1554 observations. Summary of results.
DOI: 10.57777/kgm2022000056
title: 도로009(보도블럭-red(old))
DOI: 10.6073/pasta/83befca04cf9fac2d1111eaf0dc3702f
title: North Temperate Lakes LTER: Spatially Distributed Water Temperature (2004,2006) and Sediment Temperature (2006) of Lake Wingra

description: Profiles of water and sediment temperature were measured during the summer months in Lake Wingra, Dane County, WI, USA at several locations. During the months July through September, 2004, water temperature profiles were measured. For the months, June through August, 2006, sediment temperatures were measured along with the water temperature profiles. Sampling Frequency: 2 minutes and 4 minutes Number of sites: 3 sites each summer Instrument: http://www.microdaq.com/occ/u22/underwater_temperature_data_logger.php - Underwater Temperature Data Logger
DOI: 10.5519/qd.yaqnv8er
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6073/pasta/dce7644fca754f29788733bd7103a0ab
title: North Temperate Lakes LTER: Spatial Variability of Wind Field at Lake Wingra (2004)

description: Wind speed and direction were measured at multiple locations around Lake Wingra. Two data tables are provided. The first has wind speed and direction measured at 7 sites around Lake Wingra, Dane County, WI, USA during the month of March, 2004 at a frequency of 10 minutes. The latter data table contains wind speed and direction measured at Vilas beach, Lake Wingra for the months July through September 2004 at a frequency of 2 minutes. Sampling Frequency: 2 minutes and 10 minutes Number of sites: 7 locations around Lake Wingra Instrument: http://www.campbellsci.com/03001-wind-sentry -- 03001-L R.M. Young Wind Sentry set
DOI: 10.6084/m9.figshare.21507189.v4
title: GAN2000 - MODEL WEIGHTS

description: 2022-11-5 network-snapshot-000800.pkl - StyleGAN2 weight of melanocyticnevus_256x256 network-snapshot-000800_256.zip - result images <br> network-snapshot-000200.pkl - melanocyticnevus_512x512 network-snapshot-000200_512.zip - result images <br> <br> 2022-11-7 : network-snapshot-20221107.pkl melanocyticnevus; 512x512 <br> 2022-11-8 : GAN2000-main.zip Training images url Download script Stylegan3-cpu code (not for training; for generating fakes) <br> 2022-11-8 : syn10000.zip 10,000 nevus images using network-snapshot-20221107.pkl
DOI: 10.5281/zenodo.7352613
title: Experimental superposition of time directions

description: Experimental dataset for "Experimental superposition of time directions"
DOI: 10.57777/kgm2022000057
title: 화성암(백악기 각섬석화강암(Khgri))
DOI: 10.5281/zenodo.7343786
title: Weng et al._Single Cell Raman Microspectroscopy Data

description: Single Cell Raman Microspectroscopy Data for Stable Isotope Probing of bacterial carotenoids and other biomass.
DOI: 10.5281/zenodo.7343787
title: Weng et al._Single Cell Raman Microspectroscopy Data

description: Single Cell Raman Microspectroscopy Data for Stable Isotope Probing of bacterial carotenoids and other biomass.
DOI: 10.6073/pasta/2990a07b59d7d4c45c965f1ba1fbfe1e
title: North Temperate Lakes LTER: Current Velocity of Lake Wingra (2004)

description: Profiles of current velocity are measured in Lake Wingra, Dane County, WI, USA at 3 locations. High-frequency data are averaged over at least 30 minutes recording period to obtain the average current velocity. Sampling Frequency: 2 Hz. Number of sites: 3 sites in Lake Wingra Instrument: http://www.rdinstruments.com/sen.html - 600 KHz Sentinel Acoustic Doppler Current Profiler from RD instrument
DOI: 10.6073/pasta/b9f054c609d3ce82840272ae18c29706
title: Biocomplexity at North Temperate Lakes LTER; Coordinated Field Studies: Coarse Woody Habitat Data 2001 - 2009

description: These data were collected to test for changes in the population dynamics and the food webs of the fish populations of Little Rock and Camp lakes, Vilas County, WI, USA. Little Rock Lake was the site of a whole-lake removal of coarse woody habitat in 2002 and Camp Lake was the site of a whole-lake coarse woody habitat addition in 2004. Sampling began in May of 2001 and ended in August of 2006. Some sampling was repeated from 2007 to 2009. Number of sites: 4. Two lakes with reference and treatment basin in each lake.
DOI: 10.6073/pasta/c856b99c8d97a19e73c688278610e306
title: Biocomplexity at North Temperate Lakes LTER; Whole Lake Manipulations: Aquatic Macrophytes 2001 - 2010

description: Macrophyte surveys were conducted on Sparkling Lake, Vilas County, Wisconsin in mid-July of the years 2001 to 2004 and 2007 to 2009. Eight sites were chosen that corresponded to trap survey sites for rusty crayfish and represented the range of macrophyte communities in the lake. At each site, we swam a transect perpendicular to shore from 0 to 4 m depths. A tape measure extended from shore to the 4 m depth contour, and buoys were placed at the 1, 2, 3, and 4 m depth contours. Quadrats were placed along each transect at 1 m intervals.We visually estimated the percent cover of each macrophyte species within a 1 meter-squared quadrat. Transect: corresponds to trap survey site number. Quadrat: occur at 1 m intervals starting from shore (0) and going until you reach the 4 m depth contour (highest number). Substrate: substrate within the quadrat categorized as muck, sand, gravel, cobble, logs, leaves, or any combination of these. Abundance: percent cover of each species within the quadrat determined by visual estimation. The percent covers of all species within a quadrat do NOT necessarily add to 100. Depth Interval: depth interval that each quadrat was in. Quadrats between 0 and 1 m deep are in depth interval 1, those between 1 and 2 m deep are in depth interval 2, etc. Number of sites: 8 Sampling Frequency: annually during summer
DOI: 10.57777/kgm2022000058
title: 도로014(타일-화강암-연마안됨(1))
DOI: 10.6084/m9.figshare.21507189.v5
title: GAN2000 - MODEL WEIGHTS

description: GAN2000-main.zip <br> Training images url Download script Stylegan3-cpu code (not for training; for generating fakes) <br> <br> MN500.mp4 <br> <br> PKLs.zip <br> <br> <br> <br>
DOI: 10.57777/kgm2022000059
title: 도로010(블록-황색1)
DOI: 10.6073/pasta/dfb85008ccb325150e06e4f90b77bb54
title: Biocomplexity at North Temperate Lakes LTER; Whole Lake Manipulations: Exotic Crayfish Removal 2001 - 2010

description: As part of a whole-lake experiment to overexploit a rusty crayfish (O. rusticus) population in Sparkling Lake, Vilas County, Wisconsin, crayfish were intensively trapped and removed from the lake from early to mid June through late August starting from 2001through 2008. From 2001 to 2004, removal traps were concentrated on the southern and western shorelines of the lake, where cobble is prevalent and catch rates were highest. Starting in 2005, additional traps were used and trapping effort was spread around the entire perimeter of the lake. Additional traps (perimeter) were set on standard arrays at 43 sites around the lake at 1 m deep from 2001 through 2006. In 2001 and 2003, traps (depth transect) were also set on standard arrays that ranged from 0.5 to 12 m deep. From 2001-2004, trap_site corresponds to one of the 43 standard sites where the trap was set. For perimeter and depth transect trapping, one trap is set at a trap site. During the removal trapping, 10 traps are set at each of the standard trapping sites. The trap_id identifier contains more information about the spatial location of a removal trap. From 2005-2008, traps were numbered sequentially moving clockwise around the lake starting at site 1, with no reference to standard trapping sites from previous years. In 2009, traps were set at the 43 standard sites. Capture data were recorded in 2009 but crayfish were not removed. Daily catch statistics: The data table Crayfish Daily Capture Summary provides the number of each species captured each day in the perimeter and removal traps. Also included are data on the number of traps pulled on that day and the number of trap_days these traps represent. These data can be used to calculate capture rates. The data table Crayfish Daily Capture by Station has daily catch statictics for 2009 at the capture site level. Crayfish length measurements: Prior to 2005, a crayfish that was measured could be associated with the specific trap in which it was captured. These length data are included in the Crayfish Individual data table. Starting in 2005, carapace measurements were only taken on 50 randomly selected O. rusticus individuals each day. The data table Crayfish Carapace Length contains these data which are not associated with specific traps. Trap site locations: The data table Sparkling Lake Crayfish Trap Sites contains the location of the 43 standard crayfish trap sites. See Crayfish Removal Protocol for further explanation of TECHNIQUE and TRAP_ID fields. Number of sites: 43 trap sites Sampling Frequency: annually during summer
DOI: 10.6084/m9.figshare.21507189.v6
title: GAN2000 - MODEL WEIGHTS

description: GAN2000-main.zip <br> Training images url Download script Stylegan3-cpu code (not for training; for generating fakes) <br> <br> PKLs.zip C10000.pkl : Pretrained model; 10000 kimg M500.pkl : GAN20000; melanoma N500.pkl : GAN20000; melanoma MN500.pkl : For morphing; melanoma and nevus <br> <br> MN500.mp4 <br> <br> <br> <br> <br>
DOI: 10.6073/pasta/efdd73eef000778df93e9b18959bff1d
title: Biocomplexity at North Temperate Lakes LTER; Whole Lake Manipulations: Rainbow Smelt Removal 2001 - 2009

description: Rainbow smelt (Osmerus mordax) are a harmful invasive species in lakes of northern Wisconsin. Smelt were first detected in Sparkling Lake, Vilas county, WI in 1980 and their population has since increased dramatically. We attempt to remove rainbow smelt from Sparkling Lake through a combined strategy of harvest and predation. If successful, such a strategy might be employed to restore other Wisconsin lakes invaded by smelt to a more natural species assemblage without resorting to piscicides. The data sets presented here report the harvest component of smelt removal. An assessment of the rainbow smelt population, supplementing annual LTER data, was performed during the late summer of 2001. The spring removal effort began in 2002 at ice out using multiple gear types. In 2002, the removal effort also continued from mid to late summer using horizontal gill nets. However, from 2003-2009 we took advantage of smelt spawning behavior and our efforts were condensed to a spring removal at ice-off and we utilized only fyke nets. The total weight of each catch was recorded and length-weights as well as sex ratios were documented for a subset of the catch from each removal event. The removal effort resulted in the removal of the majority of the adult population multiple times. However, smelt are a robust species and the population continuously rebounded from large removal years. As a result, catches have fluctuated from 16kg to nearly two tons. We have observed an overall reduction in fish size and an increase in the proportion of males to females. Sampling Frequency: annually
DOI: 10.57777/kgm2022000060
title: 양파002
DOI: 10.6084/m9.figshare.21614028
title: Alternative paths to immune activation: the role of costimulatory risk genes for polygenic inflammatory disease in T helper cells

description: Count matrices for RNA-seq and ATAC-seq data, metadata, differential expression results and bias analysis results. <br> Data is from human primary CD4 T-cells that were stimulated for 24h under different costimulation conditions (with CD3+CD28, CD3+ICOS, CD3+CD6, CD3+CD27, CD3-only and mIgG2a isotype control).
DOI: 10.6073/pasta/24dd0a8392b9f1fa29b62fe509c02605
title: Primary Production and Species Richness in Lake Communities 1997 - 2000

description: An understanding of the relationship between species richness and productivity is crucial to understanding biodiversity in lakes. We investigated the relationship between the primary productivity of lake ecosystems and the number of species for lacustrine phytoplankton, rotifers, cladocerans, copepods, macrophytes, and fish. Our study includes two parts: (1) a survey of 33 well-studied lakes for which data on six major taxonomic groups were available; and (2) a comparison of the effects of short- and long-term whole-lake nutrient addition on primary productivity and planktonic species richness Dodson, Stanley I., Shelley E. Arnott, and Kathryn L. Cottingham. 2000. The relationship in lake communities between primary productivity and species richness. Ecology 81:2662-79. Number of sites: 33
DOI: 10.6073/pasta/3f09694c310fc0a30a344e1fc894bdc3
title: Cross Lake Comparison at North Temperate Lakes LTER - Zooplankton Biomass Study 2006

description: This project investigates why zooplankton size, but not biomass, has been found to influence the phosphorus (TP) - chlorophyll a (chl a) relationship (Pace 1984, Carpenter et al. 1991, Carpenter et al. 2001).
DOI: 10.6073/pasta/b4a10f2b96c3799838a9193ac2cf5956
title: Crustacean Zooplankton Species Richness in 66 North American Lakes

description: Data from 66 North American lakes were collected to construct a model for predicting the number of crustacean zooplankton species expected in a lake. The chosen lakes have a range from 4 sq m to 80 x 10**9 sq m surface area, range from ultra-oligotrophic to hypereutrophic, and have zooplankton species lists based of several years of observation The number of crustacean zooplankton species in a lake is significantly correlated with lake size, average rate of photosynthesis (parabolic function) and the number of lakes within 20 km. A multiple linear regression model, using these three independent variables, explains approximately 75% of the variation in log species richness. Prediction of species richness is not enhanced by the knowledge of lake depth, salinity, elevation, latitude, longitude, or distance to nearest lake. The North American species area curve is statistically different from and steeper than the corresponding European curve. Number of sites: 69
DOI: 10.6073/pasta/a2634c05ffbf953901fdd6c4b2dda2ba
title: Zooplankton of Small Lakes and Wetland Ponds in Wisconsin - North Temperate Lakes LTER 1996

description: We sampled zooplankton communities from 54 small water bodies distributed throughout Wisconsin to evaluate whether a snap-shot of zooplankton community structure during early spring could be used for the purpose of differentiating lakes from wetlands. We collected a single set of zooplankton and water chemistry data during a one-month time window (synchronized from south to north across the state) from an open water site in each basin as a means to minimize and standardize sampling effort and to minimize cascading effects arising from predator-prey interactions with resident and immigrant aquatic insect communities. We identified 53 taxa of zooplankton from 54 sites sampled across Wisconsin. There was an average of 6.83 taxa per site. The zooplankton species were distributed with a great deal of independence. We did not detect significant correlations between number of taxa and geographic region or waterbody size. There was a significant inverse correlation between number of taxa and the concentration of calcium ion, alkalinity and conductivity. One pair of taxa, Lynceus brachyurus and Chaoborus americanus, showed a significant difference in average duration of sites of their respective occurrence. All other pairs of taxa had no significant difference in average latitude, waterbody surface area, total phosphorus, total Kjeldahl nitrogen, alkalinity, conductivity, calcium ion, sulfate, nitrate, silicate or chloride. Taxa were distributed at random among the sites - there were no statistically significant pairs of taxa occurring together or avoiding each other. Multivariate analysis of zooplankton associations showed no evidence of distinct associations that could be used to distinguish lakes from wetlands. Zooplankton community structure appears to be a poor tool for distinguishing between lakes and wetlands, especially at the relatively large scale of Wisconsin (dimension of about 500 km). The data suggest that a small body of water in Wisconsin could be classified as a wetland if it persists in the spring and summer for only about 4 months, and if it is inhabited by Lynceus brachyurus, Eubranchipus bundyi, and if Chaoborus americanus and Chydorus brevilabris are absent. Schell, Jeffery M., Carlos J. Santos-Flores, Paula E. Allen, Brian M. Hunker, Scott Kloehn, Aaron Michelson, Richard A. Lillie, and Stanley I. Dodson. 2001. Physical-chemical influences on vernal zooplankton community structure in small lakes and wetlands of Wisconsin, U.S.A. Hydrobiologia 445:37-50 Number of sites: 54
DOI: 10.6073/pasta/fd7eb93564c07879a7ea33a451da8dff
title: Zooplankton Communities of Restored Depressional Wetlands in Wisconsin - North Temperate Lakes LTER 1998

description: Wisconsin has lost approximately 2 million hectares of wetland since statehood (1848). Through the combined efforts of state and federal agencies and private groups focused primarily on wetland restoration for waterfowl habitat management or compensatory mitigation, a fairly substantial gain in wetland area has been achieved. Much of the wetland restoration effort in Wisconsin has occurred on formerly agricultural lands. However, due to the nature of the past disturbance and possible residual effects not corrected by simply returning surface waters to these lands, there is some question regarding the resultant wetland quality or biological integrity. In an effort aimed at developing tools to measure wetland gains in terms of quality or ecological integrity, the Wisconsin Department of Natural Resources (WDNR) initiated a study of biological communities on restored wetlands in Wisconsin. We report on the community of microcrustaceans and arthropods that can be collected with a plankton net in open water in wetlands. We examined zooplankton community structure in restored wetlands in terms of richness, taxonomic representation, and Daphnia sexual reproduction and related these metrics to attributes on wetlands representing least-disturbed conditions and agriculturally impacted wetlands. We sampled 56 palustrine wetlands distributed across Wisconsin. These wetland sites were categorized as agricultural, least-impacted, and restored (recently withdrawn from agricultural usage). The wetlands were reasonably homogeneous in many ways, so that taxon richness was not correlated with basin origin, presence of adjacent roads, presence or absence of fish, water chemistry, or the size of the open water. We identified a total of 40 taxa.. We conclude that restoration of wetland watersheds works. Withdrawal of the watershed from agricultural usage is followed by an increase in taxon richness, and the sites resembled least-impacted sites in about 6-7 years. Dodson, S. I. and R. A. Lillie. 2001. Zooplankton communities of restored depressional wetlands in Wisconsin, USA. Wetlands 21:292-300. Number of sites: 58
DOI: 10.5281/zenodo.7344606
title: Doodleverse/Segmentation Zoo Res-UNet models for 4-class (water, whitewater, sediment and other) segmentation of Sentinel-2 and Landsat-7/8 5-band (RGB+NIR+SWIR) images of coasts.

description: These Residual-UNet model data are based on 5-band RGB+NIR+SWIR (red, green, blue, near-infrared, and short-wave infrared) images of coasts and associated labels. Models have been created using Segmentation Gym* using the following dataset**: https://doi.org/10.5281/zenodo.7344571 Classes: {0=water, 1=whitewater, 2=sediment, 3=other} <strong>File descriptions</strong> For each model, there are 5 files with the same root name: 1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym* to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym* function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym* function `seg_images_in_folder.py`. Models may be ensembled. 3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model 4. <strong> '_model_history.npz'</strong> model training history file: this numpy archive file contains numpy arrays describing the training and validation losses and metrics. It is created by the Segmentation Gym function `train_model.py` 5. <strong> '.png'</strong> model training loss and mean IoU plot: this png file contains plots of training and validation losses and mean IoU scores during model training. A subset of data inside the .npz file. It is created by the Segmentation Gym function `train_model.py` Additionally, BEST_MODEL.txt contains the name of the model with the best validation loss and mean IoU <strong>References</strong> *Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. https://doi.org/10.1029/2022EA002332 See: https://github.com/Doodleverse/segmentation_gym ** Buscombe, Daniel. (2022). Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, whitewater, sediment, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7344571