Find research datasets worth reusing

opencc-by-4.0Apr 2022View details →

Age and Masculinities During the Neo-Assyrian Period Data

Files accompanying the article 'Age and Masculinities During the Neo-Assyrian Period'. All files relating to the creation of the textual corpus, PMI measurement, Gephi visualisations, and analysis are included. Version 2. It is recommended to read the ReadMe.txt and Workflow.txt files first, and then explore the folders according to the stage of the method you are interested in. Please cite as Bennett, E. 2023. "Age and Masculinities During the Neo-Assyrian Period Data".

opencc-by-4.0Mar 2023View details →

Supplementary data for "Influence of prey availability on habitat selection during the non-breeding period in a resident bird of prey"

Abstract Background: For resident birds of prey in the temperate zone, the cold non-breeding period can have strong impacts on survival and reproduction with implications for population dynamics. Therefore, the non-breeding period should receive the same attention as other parts of the annual life cycle. Birds of prey in intensively managed agricultural areas are repeatedly confronted with unpredictable, rapid changes in their habitat due to agricultural practices such as mowing, harvesting, and ploughing. Such a dynamic landscape likely affects prey distribution and availability and may even result in changes in habitat selection of the predator throughout the annual cycle. Methods:  In the present study, we 1) quantified barn owl prey availability in different habitats across the annual cycle, 2) quantified the size and location of barn owl breeding and non-breeding home ranges using GPS-data, 3) assessed habitat selection in relation to prey availability during the non-breeding period, and 4) discussed differences in habitat selection during the non-breeding period to habitat selection during the breeding period. Results: The patchier prey distribution during the non-breeding period compared to the breeding period led to habitat selection towards grassland during the non-breeding period. The size of barn owl home ranges during breeding and non-breeding  were similar, but there was a small shift in home range location which was more pronounced in females than males. The changes in prey availability led to a mainly grassland-oriented habitat selection during the non-breeding period. Further, our results showed the importance of biodiversity promotion areas and undisturbed field margins within the intensively managed agricultural landscape.  Conclusions: We showed that different prey availability in habitat categories can lead to changes in habitat preference between the breeding and the non-breeding period. Given these results we show how important it is to maintain and enhance structural diversity in intensive agricultural landscapes, to effectively protect birds of prey specialised on small mammals. Hereafter we provide the datasets and R script to reproduce the resource selection functions.

opencc-by-4.0Mar 2023View details →

Spatial predictions of suitable environments for palsas and peat plateaus in the Northern Hemisphere for recent and future periods

Here we provide raster files of suitable environments for palsas and peat plateaus in the Northern Hemisphere. These files are results of a scientific study by Könönen et al. (2022, preprint). Files are provided in TIFF-format, and they describe the occurrence probability of the suitable environments for palsas and peat plateaus.   Könönen, O. H., Karjalainen, O., Aalto, J., Luoto, M., and Hjort, J.: Environmental spaces for palsas and peat plateaus are disappearing at a circumpolar scale, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-135, in review, 2022.

Data and Software for "Gullies on Mars could have formed by melting of water ice during periods of high obliquity"

Code, movies and climate model outputs for "Gullies on Mars could have formed by melting of water ice during periods of high obliquity" by Dickson et al. Science, 2023.

Radiographic outcomes for Biodentine group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Radiographic outcomes for Biodentine group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Clinical outcome for TheraCal LC group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Clinical outcome for TheraCal LC group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Clinical outcome for MTA group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Clinical outcome for MTA group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Radiographic outcomes for MTA group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Radiographic outcomes for MTA group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Clinical outcome for Biodentine group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

Clinical outcome for Biodentine group for postoperative pain, tenderness, and neural sensibility at the patient recall period of 21 days, 3 months, and 12 months

opencc-by-4.0Jul 2023View details →

AdriSC Climate Model Data - For the article: Projecting expected growth period of bivalves in a coastal temperate sea

The recent implementation, development and successful runs of the kilometer-scale atmosphere-ocean Adriatic Sea and Coast (AdriSC) climate model for the historical period of 1987-2017 and for an extreme climate projection (RCP 8.5) for the 2070-2100 period, have provided the necessary dataset to better understand the potential impact of climate change within the Adriatic basin. Here, temperature, salinity and ocean currents were extracted and formatted from the AdriSC ocean model at 1 km resolution. This dataset was then used to reproduce in the past (1987-2017 period) and project in the future (2070-2100 period) the expected growth of five bivalve species in the northern Adriatic Sea at two different locations: Barbariga and along the western coast of Istria.

opencc-by-4.0Jul 2023View details →

Chironomid taxa relative abundance information and lake identifiers for: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period

File 1: Relative abundances for chironomid taxa used in the manuscript: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period. Lake_ID corresponds to the lake IDs attributed to each lake sampled as part of the LakePulse Network File 2: Lake_ID, lake name, latitude, longitude, sampling date, province, and ecozone for the 69 lakes examined in the manuscript: Changes in midge assemblages reflect climate and trophic gradients across north temperate and boreal lakes since the pre-industrial period.

opencc-by-4.0Aug 2023View details →

A 500m-Resolution Agricultural Drought Area Dataset for the period 2006–2019 in the North China Plain

Agricultural drought has caused huge loss in crop production in the recent decades and will continue to occur with increased frequency and severity in the upcoming future period. However, lack of reliable historic agricultural drought information at finer spatiotemporal resolutions constrains the effective formulation strategy for prevention and mitigation of agricultural drought, especially for monitoring and early/warming. Hence, we generated a 500 m-resolution agricultural drought area dataset with three degrees (drought covered, drought damaged, and crop failure) for summer-harvest crops and autumn-harvest crops encompassing the whole NCP.

opencc-by-4.0Sep 2023View details →

ECHAM6-wiso nudged simulation water isotopes and precipitation for the period 1990-2020 at the EastGRIP drilling location, Greenland

This model dataset contains output produced with the isotope-enabled atmosphere GCM ECHAM6-wiso at T127L95 spatial resolution, nudged to the ERA-5 reanalysis product. The 6-hourly model output is provided for the period 01/1990-12/2020 for the grid cell containing EastGRIP drilling location in Greenland, centered at 75.27N, -36.57 E. The complete description of the simulation can be found in: Cauquoin, A. and Werner, M., 2021. High‐Resolution Nudged Isotope Modeling With ECHAM6‐Wiso: Impacts of Updated Model Physics and ERA5 Reanalysis Data. Journal of Advances in Modeling Earth Systems, <a href="https://doi.org/10.1029/2021MS002532">https://doi.org/10.1029/2021MS002532</a> The provided files (netCDF) contain the ECHAM6-wiso model data used as input for the SNOWISO snow pack model in: Dietrich, L.J., Steen-Larsen, H.C., Wahl, S., Jones, T.R., Town, M.S. and Werner, M., 2023. Snow-atmosphere humidity exchange at the ice sheet surface alters annual mean climate signals in ice core records. Geophysical Research Letters,  <a href="https://doi.org/10.1029/2023GL104249">https://doi.org/10.1029/2023GL104249</a>. The provided variables are:         d18O_vapor: delta value for 18O (&permil;) in the vapor of the lowest atmospheric layer (ECHAM level 95).         dD_vapor: delta value for H2 (D) (&permil;) in the vapor of the lowest atmospheric layer (ECHAM level 95).         aprt: total precipitation (mm water equivalent per month)         d18O_precip: delta value for 18O (&permil;) in the precipitation         dD_precip: delta value for H2 (D) (&permil;) in the precipitation Data usage notice: If you use any of these data you should refer to: Cauquoin, A. and Werner, M., 2021. High‐Resolution Nudged Isotope Modeling With ECHAM6‐Wiso: Impacts of Updated Model Physics and ERA5 Reanalysis Data. Journal of Advances in Modeling Earth Systems, <a href="https://doi.org/10.1029/2021MS002532">https://doi.org/10.1029/2021MS002532</a>

opencc-by-4.0Oct 2023View details →

Results of the test for the sampling period described in D7.3: Madrid pilot report

This datasets provides further information about section 9.4 Monitorisation and results of D7.3. This public deliverable describes Madrid pilot project report. CARTIF share this dataset with the results of the test carried out during the sampling period regarding particulate matter and nitrogen oxides.

opencc-by-4.0Oct 2023View details →

Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints

This dataset consists of a collection of self-consistent radial seismic Earth models. The models are derived by inverting a large set of normal-mode centre-frequencies, quality factors, and geodetic data, including mass, moment of inertia, and tidal response.The dataset is accompanied by a research paper titled "Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints" (DOI: <a href="https://doi.org/10.1093/gji/ggad254">10.1093/gji/ggad254</a>). The paper presents the methodology and findings related to the development of the models.This version (V0.2) of the dataset replaces the previous version (V0.1). Dataset DetailsThe dataset includes confidence intervals (CIs) for these parameters at 25%, 50%, and 75% levels that are representative of the uncertainty of the sampled model parameters. For example, the files <a href="https://zenodo.org/api/files/fa9f19f0-bf6a-41a8-8ca7-489a5b1b9c49/screm-25p-high.dat?versionId=b3b349c2-0a0b-48cc-b1f3-90137b8d1dcb">screm-25p-high.dat</a> and <a href="https://zenodo.org/api/files/fa9f19f0-bf6a-41a8-8ca7-489a5b1b9c49/screm-25p-low.dat?versionId=81db34f2-29f4-48aa-95c4-bb73b050a47f">screm-25p-low.dat</a> contain the upper and lower bound of the 25% CI sampled model range. A python plotting script is available, which plots the CIs.The dataset files are provided in comma-separated values (CSV) format, containing the following columns:<ol><li>Radius (km): Radial distance from the center of the Earth.</li><li>Depths (km): Depth from the surface of the Earth.</li><li>Density (g/cm³): Radial density structure.</li><li>P-wave velocity (vp) (km/s): Radial compressional (P) wave velocity structure</li><li>S-wave velocity (vs) (km/s): Radial shear (S) wave velocity structure.</li><li>Qkappa: Radial bulk attenuation structure.</li><li>Qmu: Radial shear wave attenuation structure.</li><li>Bulk Modulus (K) (GPa): Radial bulk modulus structure.</li><li>Shear Modulus (Mu) (GPa): Radial shear modulus structure.</li><li>Pressure (GPa): Radial pressure profile.</li><li>Temperature (K): Radial geothermal profile.</li></ol>CitationIf you use this dataset in your research or refer to the models, please cite the following paper:Title: Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints Authors: J. Kemper, A. Khan, G. Helffrich, M. van Driel, D. Giardini Journal: Geophysical Journal International Year: 2023 DOI: <a href="https://doi.org/10.1093/gji/ggad254">10.1093/gji/ggad254</a>Please also acknowledge the dataset by providing a link to the Zenodo repository and its DOI.Bibtex: @article{Kemper_etal23, author = {Kemper, J and Khan, A and Helffrich, G and van Driel, M and Giardini, D}, title = "{Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints}", journal = {Geophysical Journal International}, pages = {ggad254}, year = {2023}, month = {06}, issn = {0956-540X}, doi = {10.1093/gji/ggad254}, url = {https://doi.org/10.1093/gji/ggad254}, }

opencc-zeroMay 2019View details →

Distribution of invasive alien species of Union concern (Regulation (EU) 1143/2014) in Belgium for the reporting period 2015-2018

Aims and scope Member State authorities are required to report on the distribution in their territory of each of the invasive alien species (IAS) of Union concern. These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). This distribution represents the official reporting under Article 24(1) of R.1143/2014 on invasive alien species for the period 2015–2018. Baseline distribution of these species has previously been reported and published (Adriaens et al. 2018, ). Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (9%), citizen science observatories (68%) and a range of other sources (23%) such as governmental agencies, water managers etc. More specifically the dataset includes: <ul> <li>The citizen science recording portals www.waarnemingen.be and www.observation.be which has a specific alert system for IAS where nature volunteers can report their observations (Adriaens et al. 2018);</li> <li>Data from the Research Institute for Nature and Forest (INBO), the Flemish government institute that coordinates N2000, WFD and BIrd Directive and IAS monitoring in the terrestrial, estuarine and freshwater environment;</li> <li>Data from the Flemish Environment Agency which performs management of muskrat and invasive water plants in Flanders, gathered with a dedicated smartphone app since 2015;</li> <li>Data from the Flemish provinces and Rato vzw that manage water plants, muskrat, giant hogweed etc.;</li> <li>Some smaller datasets from cities;</li> <li>Data from the Brussels Capital Region from the Brussels Environment data portal;</li> <li>Plant inventories of the ‘contrats de rivière’ along watercourses in Wallonia, making use of a dedicated application to collect data directly from the field (fulcrum);</li> <li>The government reporting portals for IAS of the ‘Observatoire wallon de la flore, de la faune et des habitats (Service Public de Wallonie)’;</li> <li>Some validated data from specific datasets on gbif (iNaturalist, Natusfera, Naturgucker).</li> </ul> Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). The mapping was assisted by dedicated software (SMARTIE) which was specifically written for the purpose of aggregating IAS data from various sources. Appropriate selection of records was performed based on the cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA). The technical format is in line with the <a href="http://cdr.eionet.europa.eu/help/ias_regulation/material/IAS-species-distribution-user-manual">guidelines</a> provided to the member states for the compilation of reports on Species Distribution (SD) of Invasive Alien Species of Union concern. File description The dataset contains a shapefiles (T1_Belgium_Union_List_Species.shp) with the distribution of the species of Union Concern at 10km2 (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level. The attributes table contains Cellcode (ETRS grid cell code) and Species (scientific name + authority). Date range The data reflects the distribution of the IAS of Union concern in Belgium in the first reporting period for the EU Regulation hence comprises observations of Union List invasive species between January 2015 (2015-01-01) and December 2018 (2018-12-31).  Validation procedure Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account unless for Chinese mitten crab Eriocheir sinensis, ruddy duck Oxyura jamaicensis, raccoon Procyon lotor, Siberian ground squirrel Tamias sibiricus, sacred ibis Threskiornis aethiopicus, Egyptian goose Alopochen aegyptiaca, Himalayan balsam Impatiens glandulifera, giant hogweed Heracleum mantegazzianum, muskrat Ondatra zibethicus and red-eared slider Trachemys spp. For these species, it was assumed all records were correct as they originate from dedicated sampling (E. sinensis) within research projects, were gathered by public bodies (e.g. muskrat), or represent species that are readily recognizable by people in the field. Data provided by EASIN in the care package and GBIF data were carefully checked. A visual check was performed on the resulting distribution maps by representatives of the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species. Data providers The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF).

openCC (other)Feb 2022View details →

Lake ecosystem metabolism estimates from 3 locations in Lake Sunapee, NH, USA during the summer stratified period from June to September 2018

Surface water lake ecosystem metabolism daily estimates during the 2018 summer stratified period (04 June - 22 Sept) at three locations within Lake Sunapee (NH, USA). Estimates at each site used previously published data from high-frequency temperature and dissolved oxygen sensors deployed in the lake: the Deep Site (LSPA et al., 2021a: full citation in Methods) and the Herrick Cove and Georges Mills sites (Ward et al., 2021: full citation in methods). The Deep Site was located near Loon Island in the main basin of the lake with 12 m total depth and the dissolved oxygen sensor was deployed 1 m below surface. The Herrick Cove site was in the north east cove of the lake with 6.5 m total depth at site and the dissolved oxygen sensor was deployed 1.75 m below surface. The Georges Mills site was in the northwest cove of the lake with 7 m total depth at site and the dissolved oxygen sensor deployed 1.75 m below surface. We used an inverse modeling approach, where the lake ecosystem model predicted diel changes in dissolved oxygen to estimate daily volumetric rates of gross primary production (GPP), respiration (R), and net ecosystem metabolism (NEM) using the in-lake buoy measurements at each site and wind and surface PAR from the meteorological station at the Deep Site buoy (LSPA et al., 2021b). Raw metabolism estimates were QA/QC'd to generate this final metabolism estimate dataset following protocols described in the Methods section of this dataset.

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.

openCC (other)Dec 2022View details →

Measurements of water column chemistry taken hourly over 24-hour periods at three sites in West Falmouth Harbor from 2006 to 2019

West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000’s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at stations throughout the harbor to examine nutrient concentrations along the gradient from the highest loaded areas of the site to the most well-flushed. Water samples were taken hourly over 24-hour periods at 3 stations between 2006 and 2019. Due to covid restrictions on field and laboratory work, samples were not collected in 2020-2021; sample collection resumed in 2022 and data will be added after analysis. One station is in the well-flushed outer basin (OH) and one in the inner basin closer to the dominant groundwater N source (Snug Harbor, SH). These two were sampled at least once per year between 2006 and 2019. In two years, samples in the OH were taken at a location approximately 140m from the long-term site from this dataset. Those data can be accessed at doi:10.6073/pasta/73408abf801827966041c219f4222c1f. A third station is in the middle between the two, and was sampled in 2016 and 2018. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus. On some dates, additional samples were run for silicate and chlorophyll. Salinity is reported for all samples. Samples were collected with an ISCO autosampler and stored on ice until analysis. Full analysis details and quality control methods are available in Hayn et al. 2014 (doi: 10.1007/s12237-013-9699-8).