Find research datasets worth reusing

opencc-by-4.0Apr 2024View details →

Comparing recent PTA results on the nanohertz stochastic gravitational wave background - full noise and GWB parameter comparison plots

A full collection of plots comparing the noise properties of individual pulsars and gravitational wave background parameters discussed in the companion paper Comparing recent PTA results on the nanohertz stochastic gravitational wave background (IPTA 2024). <code>Section4_GWB_comparison.zip</code> supplements and expands section 4.1, "Comparing the published GWB measurements," of IPTA (2024). It contains parameter difference distributions for GWB model parameters.  There are four different models included. The HD correlated powerlaw (PL) model make up the basis for Figure 2.  Additionally, there are three comparisons not included in IPTA (2024).  First, comparisons the common uncorrelated red noise (CURN) PL model are included.  Finally,  comparisons of two free spectral (FS) models (HD and CURN) are included.  These comparisons fit the HD and CURN FS posteriors using the <code>ceffyl</code> software package, and then compare the parameters of the resulting powerlaw fits. <code>Section5_Noise_comparison.zip</code> supplements section 5, "Comparing Pulsar Noice Properties," of IPTA (2024).  It contains plots for 27 pulsars timed by more than one PTA collaboration, including the plots for PSR J1012+5307, which are presented in Figure 7.  The plots include noise parameter posteriors, time domain GP realizations, TOA residuals, and TOA radio frequency.

Edge length of land use classes aggregated from Corine 2012 in 100 - 5000 meter radius areas around Landklif study plots

Based on CORINE land cover data 2012, we aggregated the original land use classes into 8 classes: urban, agriculture, grassland, broad-leaved forest, coniferous forest, mixed forest, natural/seminatural vegetation, and water (see clc_legend.txt). Based on this new land use classification, we calculated the edge length of landuse patches (total length of edges between different habitat in meter) for 100 - 5000 meters (100-1000 meters with 100 meter interval, 1000 - 5000 meter with 500 meter interval) buffer area around LandKlif plots. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

Edge length of land use classes aggregated from Corine 2018 in 100 - 5000 meter radius areas around Landklif study plots

Based on CORINE land cover data 2018, we aggregated the original land use classes into 8 classes: urban, agriculture, grassland, broad-leaved forest, coniferous forest, mixed forest, natural/seminatural vegetation, and water (see clc_legend.txt). Based on this new land use classification, we calculated the edge length of landuse patches (total length of edges between different habitat in meter) for 100 - 5000 meters (100-1000 meters with 100 meter interval, 1000 - 5000 meter with 500 meter interval) buffer area around LandKlif plots. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

Landscape composition and shannon diversity of landuse classes aggregated from corine 2018 in 100 - 5000 meter radius areas around Landklif study plots

Based on CORINE land cover data from 2018, we aggregated the original land use classes into 8 classes: urban, agriculture, grassland, Broad-leaved forest, Coniferous forest, Mixed forest, natural/seminatural vegetation, and water (see clc_legend.txt). We calculated the landscape composition (percentage of each land use type according to corine land type) for 100 - 5000 meters (100-1000 meter with 100 meter intervals, 1000 - 5000 meter with 500 meter interval) buffer area around landklif plots. LandKlif is funded by the Bavarian State Ministry of Science and the Arts within the Bavarian Climate Research Network (bayklif).  Within the five year funding period of bayklif, five interdisciplinary senior research associations and five junior research groups are be financed with a total sum of 18 million Euro. LandKliF, as one of the five interdisciplinary senior research associations, addresses the effects of climate change on biodiversity and ecosystem services in semi-natural, agricultural and urban landscapes.

3D Stereo Body Pose Estimation - Evaluation Plots

Evaluation plots for the "3D Stereo Body Pose Estimation" project, aimed at estimating 3d keypoints from humans captured using a OAK-D camera. The project is originated in the context of the activities of the postgraduate course IA904 - Model Project in Visual Computing, offered in the first semester of 2024, at Unicamp, under the supervision of Prof. Dr. Leticia Rittner and Prof. Paula D. Paro Costa, both from the Department of Computer and Automation Engineering (DCA) of the Faculty of Electrical and Computer Engineering (FEEC). The <a href="https://github.com/Disciplinas-FEEC/IA904-2024S1/tree/main/projetos/3DStereoBodyPoseEstimation">project page</a> have a full description of the project (portuguese).

opencc-by-4.0Jul 2024View details →

Vegetation of post-mining areas, Upper Silesia, Poland (Floristic composition of the plots_November_2022)

The data set containing a list of plant species in the research plots along with their percentage coverage. The selection of plots took into account the occurrence of the dominant species (cover > 40% of the study plot area). The dominant species represent functional groups: monocots, forbs and legumes.

opencc-by-4.0Nov 2018View details →

Grand Mesa Study Plot

Cleaned (quality checked) and continuous hourly records of snow energy and mass balance variables from Grand Mesa Study Plot (GMSP).  GMSP is located in an opening in a pine forest on the northern rim of the Grand Mesa (39.050802, -108.061435) in west central Colorado at 3239 m.  The site was funded by the USGS (poc: Jayne Belnap), installed by the Center for Snow and Avalanche Studies (poc: Jeff Derry), and is maintained by the Snow Optics Laboratory at NASA- JPL (poc: Thomas Painter). The study plot is primarily used to assess the spatial variability in the hydrologic impacts of dust on snow (see Skiles et al., 2015, DOI: 10.1002/hyp.10569). Real time data can be retried from MesoWest (station ID: GMSPC). The study plot consists of a snow profile plot that contains a tower holding the instrumentation array. Tower measurements include wind speed and direction, air temperature and relative humidity, snowpack depth, incoming and outgoing broadband (BB; 0.285–2.800 μm) and near-infrared/shortwave-infrared (NIR/SWIR; 0.695–2.800 μm) solar radiation, and incoming longwave radiation values. Precipitation is from the nearby ‘Mesa Lakes’ Snow Telemetry site (SNOTEL; NRCS), which is located approximately 500m north of GMSP at 3048m under the assumption that precipitation is similar at the two sites. Variables are accompanied by notes in adjacent columns to indicate if the value is measured, interpolated, or 'cleaned' (i.e snow depths are set to 0 after the snow depletion date).  Note: Grand Mesa was a field site for the NASA SnowEx field campaign in Year 1 (2017), and will be again Year 3 (2019). GMSP is/was within airborne flight domains. Dataset point of contact: S. McKenzie Skiles, Department of Geography, University of Utah (m.skiles@geog.utah.edu)

opencc-by-4.0Jan 2024View details →

Terrestrial laser scan data of a experimental plot in Forstamt Billenhagen, 340 a31 (Mecklenburg-Vorpommern, Germany 2023) v2

The area was surveyed using terrestrial laser scanning, and the subsequent derivation of individual tree yield data (BHD, tree height, volume, etc.) was carried out as part of a study to assess the ecosystem services of different forest stands (recorded in March 2023). In this version of the data, transmission errors and unit errors were corrected.

opencc-zeroOct 2024View details →

Weekly plots of Great Britain's half-hourly electrical system weather dependent generation, net imports and overall demand from 2008-11-10

Plots that show the electrical system transition of Great Britain, they were created to form the individual frames for a video of the transition.

opencc-by-4.0Oct 2024View details →

Shrub inventory data such as shrub identity, height and biomass in a 20x5m core plot at Mt. Kilimanjaro

This dataset describes position and sizes of all shrubs above 130 cm high in all plots, also fruiting and flowering events in KiLi project. -999999 represents NA in numeric variables.  The shrub inventory was carried out within a 5 × 20 m subplot in the centre of each plot. Within this subplot, the shrub layer was defined as consisting of all woody stems exceeding 1.3 m in height, but below 10 cm dbh and thus not included in the tree inventory. We measured dbh at 1.3 m with a diameter tape (Forestry Suppliers; for dbh's above 3 cm) or a caliper (for dbh's below 3 cm) and the height of each shrub with a hypsometer. The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.

opencc-by-4.0Oct 2024View details →

Tree inventory data such as tree identity, position in the plot, height, architecture and biomass on Mt. Kilimanjaro

This dataset describes position and sizes of all trees above 10 cm diameter at breast height in all plots, also fruiting and flowering events and if it is a canopy tree or not in KiLi project. -999999 represents NA in numeric variables.  Within each plot, all trees wider than 10 cm diameter at breast height (dbh) were marked with aluminium tags and their dbh and height were measured. The dbh was measured with a diameter tape (Forestry Suppliers, USA) at 1.3 m for normally shaped trees and 20 cm below or above when branches or irregular shapes impeded measurement at that height. The 1.3 m height was measured from the highest ground level around the stem to standardize measurements taken on slopes. For trees which were strongly buttressed or too big to measure by hand, a laser dendrometer (Criterion RD 1000 with TruPulse 200/200, Centennial, USA) was used to measure the tree above the buttresses and at 1.3 m. Lianas above 10 cm in diameter were also marked and their dbh was measured. Tree height was measured using an ultra-sonic hypsometer (Vertex IV Hypsometer, Haglöf, Langsele, Sweden) or a laser rangefinder (TruPulse 200/200). The tree inventories were carried out between December 2010 and March 2013. The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.

opencc-by-4.0Feb 2023View details →

Data for threshold plot in "Finite-rate sparse quantum codes aplenty"

This dataset contains the quantum error correcting codes that were sampled to render the threshold plot under the erasure noise channel in the article. They are sorted by batch corresponding to different jobs on the computing cluster. Each batch contains many codes sorted by length. There are also three extra metadata files. The inputs that were given to sample codes (inputs.json), the CSP solver output (output.csv) and the result of the decoding simulation (decoding.json). Each file named code.json contains the sparse list of X and Z stabilizers. That is, each stabilizer is given by a list of integers corresponding to the index of the qubits supporting the stabilizer.

opencc-by-4.0May 2023View details →

Data and R scripts for KCC plots in Douville and Willett (2023)

CMIP6 data (historical and scenario SSP5-8.5, run 1 only), observation and R scripts to plot Fig.1 and Fig.2 of Douville and Willett (Sc. Adv., 2023)

opencc-by-4.0Jun 2023View details →

'Danum Revised' forest field plot data for thirty-five 0.28 hectare field plots, measured in 2020

Permanent forest plot data from Sabah, Malaysia. Danum Valley Conservation Area. Here we provide a brief description of the permanent plot data collected following the same protocols utilized within the Kuamut forest reserve.Twenty circular field plots with a 30 m radius that were established across the protected area as part of a collaboration between SEARRP and the Carnegie Airborne Observatory (CAO) in 2017. See <a href="https://doi.org/10.5281/zenodo.8042050">'Danum Revised' forest field plot data for twenty 0.28 hectare field plots, measured in 2017</a>In 2020 we added an additional 15 plots as part of work for Keller et al. 'Biodiversity consequences of long-term active forest restoration in selectively-logged tropical rainforests', and so this dataset is the full 35 field plots measured in 2020.These plots were surveyed following the same protocols as those described by the Kuamut conservation project. The field protocol is provided. The original 20 Field plot locations where selected using airborne LiDAR to specifically target both high Aboveground Carbon Density (ACD) areas, and also areas with different ACD predictions based on a draft set of carbon mapping  models. See Asner et al. (2017) and Jucker et al. (2018) for further details.In 2020 we selected existing these additional 15 plot points using a high resolution biomass map (see: Asner et al. 2017; Asner et al. 2021). In order to represent the entirety of the area sufficiently, we chose plot locations to represent the average biomass value and variation around it of the majority of the managed area (<a href="https://doi.org/10.1126/science.aay4490">cf. Philipson et al. (2020) for regional values</a>). The plot location further must have fulfilled the following criteria: (1) plots had to be at least 100 m away from noticeable features such as roads to avoid edge effects (but for logistic reasons they nevertheless had to be in the vicinity of roads); (2) plots had to be spread out as much as logistically feasible; (see Keller et al. (submitted), for full details). Note Keller et al. (submitted), used 30 plots for a balanced design between naturally regenerating and actively restored areas. Here we present all 35 plots measured in 2020. Plot locations where additionally updated using an SXblue GPS differential with SBAS augmentation. These locations are provided.Use of these data require citation of this dataset, the associated publication (Keller et al. submitted), as well as the <a href="https://doi.org/10.5281/zenodo.8042050">2017 dataset</a> (which describes the full set up process),.  We also require that you inform us of the use of the data would also appreciate the opportunity to be involved in work making use of this data. The required citations are follows:Philipson, Christopher D., Brodrick, Philip G., Milne, Sol, Murus, Remmy, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Asner, Gregory P. (2023). 'Danum Revised' forest field plot data for twenty 0.28 hectare field plots, measured in 2017 (1.0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.8042050">https://doi.org/10.5281/zenodo.8042050</a>Keller et al. (submitted). 'Biodiversity consequences of long-term active forest restoration in selectively-logged tropical rainforests',This work would not be possible without the incredibly hard work and dedication of the entire SEARRP field team, including Philip Ak Ulok; Hii Siew Yee; Remmy Bin Murus; Alexander Karolus; Andy Brian Karolus; Frederica Karolus; Zidey Fulgentius; Welday Bin Girang; Mohamad Taufiq Bin Sumin, Mohd Fadil Bin Abd Karim, Joulu Rasion, and Japin Bin Rasion.  We are very grateful to the help of all the field staff not specifically mentioned here. ReferencesAsner, Gregory P., Philip G. Brodrick, Christopher Philipson, Nicolas R. Vaughn, Roberta E. Martin, David E. Knapp, Joseph Heckler, et al. 2017. "Mapped Aboveground Carbon Stocks to Advance Forest Conservation and Recovery in Malaysian Borneo." Biological Conservation 217 (June 2017): 289–310. <a href="https://doi.org/10.1016/j.biocon.2017.10.020">https://doi.org/10.1016/j.biocon.2017.10.020</a>Jucker, Tommaso, Gregory P. Asner, Michele Dalponte, Philip G. Brodrick, Christopher D. Philipson, Nicholas R. Vaughn, Yit Arn Teh, et al. 2018. "Estimating Aboveground Carbon Density and Its Uncertainty in Borneo's Structurally Complex Tropical Forests Using Airborne Laser Scanning." Biogeosciences 15 (12): 3811–30. <a href="https://doi.org/10.5194/bg-15-3811-2018">https://doi.org/10.5194/bg-15-3811-2018</a>Keller, Nadine, Pascal A Niklaus, Jaboury Ghazoul, Tobias Marfil, Elia Godoong, and Christopher D Philipson. 2023. "Biodiversity Consequences of Long-Term Active Forest Restoration in Selectively-Logged Tropical Rainforests." Forest Ecology and Management 549: 4. <a href="https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fdoi.org%2f10.1016%2fj.foreco.2023.121414&c=E,1,CfW3xjatfMP0AonRryjLaKUmg50KQQtF2-n0UPlyW_NATChUbrP9yczm8IQKqWaiNSMtm0g3HuVHyW8N7CKr84VGIQokuIogx-7OG-AAY5epGc0i&typo=1">https://doi.org/10.1016/j.foreco.2023.121414</a>.Philipson, Christopher D., Mark E.J. Cutler, Philip G. Brodric, Gregory P. Asne, Doreen S. Boy, Pedro Moura Costa, Joel Fiddes, et al. 2020. "Active Restoration Accelerates the Carbon Recovery of Human-Modified Tropical Forests." Science 369 (6505): 838–41. <a href="https://doi.org/10.1126/science.aay4490">https://doi.org/10.1126/science.aay4490</a>Philipson, Christopher D., Brodrick, Philip G., Milne, Sol, Murus, Remmy, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Asner, Gregory P. (2023). 'Danum Revised' forest field plot data for twenty 0.28 hectare field plots, measured in 2017 (1.0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.8042050">https://doi.org/10.5281/zenodo.8042050</a>

opencc-by-4.0Aug 2023View details →

Exoplanet Occurrence Rates Plot

Everyone knows the obligatory semi-major axis vs mass plot that every exoplanet scientist is required by law to show in every talk. We wondered how literature occurrence rates would look overlaid on this plot. So we made it.   The script for generating this plot is located at <a href="https://github.com/logan-pearce/occurrence-rate-plot">https://github.com/logan-pearce/occurrence-rate-plot</a>, so you can adjust the colors and the plot to your heart's content.

opencc-by-4.0Sep 2023View details →

BgMA-ESy: Expert system for automatic classification of vegetation plots of subalpine tall-herb vegetation (class Mulgedio-Aconitetea) from Bulgaria

***** BgMA-ESy is an expert system that classifies vegetation plots of the class Mulgedio-Aconitetea (<a href="https://doi.org/10.1111/avsc.12257">Mucina et al. 2016</a>) occurring in Bulgaria. The expert system can be run using the JUICE program (<a href="https://doi.org/10.1111/j.1654-1103.2002.tb02069.x">Tichý 2002</a>; <a href="https://www.sci.muni.cz/botany/juice/">https://www.sci.muni.cz/botany/juice/</a>). The aggregation of vascular plants included within the BgMA-ESy is adopted from EUNIS-ESy (<a href="https://doi.org/10.1111/avsc.12519">Chytrý et al. 2020</a>; <a href="https://doi.org/10.5281/zenodo.4812736">https://doi.org/10.5281/zenodo.4812736</a>), and in a few cases, it is adjusted. ***** Specifications The analyzed data (vegetation plots) cannot:  <ul> <li>include scrub vegetation (cover of tall shrub species > 8%; e.g., Pinus mugo, Salix spp.).</li> <li>contain tree species with cover > 1% (e.g., Fagus sylvatica, Picea abies).</li> <li>contain Pteridium aquilinum as a dominant species.</li> </ul> The expert system was trained on vegetation plots with 5–100 m2 area that occur above 1000 m a. s. l. * Exceptions from EUNIS-ESy aggregation: Heracleum sphondylium agg. does not include H. sphondylium subsp. verticillatum.   ***** When using this work, please cite: Szokala D., Kočí M. & Vassilev K. (2024): Subalpine tall-herb vegetation in Bulgaria: diversity and ecology. – Plant Biosystems 158: 490–510. <a href="https://doi.org/10.1080/11263504.2024.2327865">https://doi.org/10.1080/11263504.2024.2327865</a>. *****

openCC (other)Nov 2021View details →

Hawaii Dry Forest Plot Data

Fourteen closed-canopy dry forest sites in the Hawaiian Islands (four on Kaua'i, two on O'ahu, one on Moloka'i, three on Lanā‘i, one on Maui, and three on Hawai‘i) were selected and surveyed in 2004–2006 to assess their diversity and structure in relationship to climate, and to identify relationships with satellite vegetation indices. Field measurements of woody plant species at all sites followed Gentry (1988). ‘Gentry transects’ consist of belt transects totaling 1000 m2 (0.1 ha). Each sample consisted of 10 belt transects (2 m · 50 m) 10 m apart in which all woody plants greater than or equal to 2.5 cm diameter at breast height (d.b.h.) rooted in the sample area were identified (Gentry, 1988). We documented the floristic composition and quantified species richness, density, basal area, and canopy height for each site. Data were collected while S.P. was a graduate student at UCLA in the Department of Geography. There are 16 csv files in this data set that include a summary table, a locations table, and a separate table for each of the 14 sites. Each ‘site’ contains one 0.1ha plot.

openCC (other)Apr 2022View details →

University of Kansas Field Station: Forest demography, 1980 – 2015. On ten study plots established on three management units all live trees with a dbh > 7.5 cm (3 in) were identified to species, measured, and tagged. Trees were initially measured in 1980/1981 and re-measured in three successive time periods: 1993/95; 2002/03; and 2014/15. Trees will be measured again in 2025/26.

In 1980 researchers at the University of Kansas initiated a long-term experiment monitoring the composition of oak-hickory forest communities at the University’s field station near Lawrence, Kansas. The purpose of the study was to determine how forest species composition varied temporally across distinct habitats that varied in topography, elevation, sun exposure, management history and successional stage. Ten permanent sites were sampled approximately each decade with data collection periods of 1980/81, 1993/95, 2002/03, and 2014/15. Trees with a minimum diameter at breast height (dbh) of ≥ 7.5 cm were tagged, identified to species and measured. Trees will be measured again in 2025/26.

openCC0Oct 2022View details →

Soil extracellular enzyme activities in plots dominated by trees that associate with arbuscular mycorrhizal or ectomycorrhizal fungi in the N fertilized and reference watershed at the Fernow Experimental Forest, WV.

Our objective was to detect possible differences in N fertilization responses of soil extracellular enzymes in plots dominated by trees that associate with arbuscular mycorrhizal fungi (AM) or ectomycorrhizal fungi (ECM). To do this, we established a plot network of 6 AM and 6 ECM dominated 10 x 10 m plots in both the reference and N fertilized watersheds (N=24 plots) at the Fernow Experimental Forest, Parsons, WV. We assayed the potential activity of hydrolytic enzymes that release N (N-acetylglucosaminidase; NAG), phosphorus (acid phosphatase; AP), and simple carbon (ß-glucosidase; BG). In addition, we measured microbial allocation to complex C degrading oxidative enzymes phenol oxidase and peroxidase. The activities of these enzymes were measured separately in bulk mineral, rhizosphere, and organic horizon soils during the growing season in 2017.