cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.x9335s
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Crypsis vaginiflora",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 13 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008540-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c65xzk
title: Occurrence Download

description: A dataset containing 249 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Crypsis vaginiflora",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 249 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008541-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0169972.10fu
title: SH0169972.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/5ba28b53-6b20-4e31-9c0f-ba234ddc55ef
title: Water table depth data from Climoor fieldsite in Clocaenog Forest

description: This dataset includes manual measurements of water table depth at the Climoor fieldsite in the Clocaenog Forest, north-east Wales. Water table depth was collected via water permeable tubes installed through the soil profile down to bedrock. Measurements were taken, usually every two weeks, using a tape measure and head torch to assist in seeing the water level in the tube. Data are available from May 2009 to January 2014.
description: Data was collected manually by measuring with a tape measure the depth of water table, accessible via water permeable pipes installed down to the bedrock within the soil profile (maximum depth 39cm). Data was written on fieldsheets in the field, then manually entered into the raw data master file on return to the office.
DOI: 10.5285/7079d6e8-6184-4f80-89b4-4db924ec8b05
title:  Grid-to-Grid model estimates of river flow for Northern Ireland driven by UK Climate Projections 2018 (UKCP18) Regional (12km) data (1980 to 2080)

description: Gridded hydrological model river flow estimates on a 1km grid over Northern Ireland for the period Dec 1980 - Nov 2080. The dataset includes monthly mean river flow, annual maxima of daily mean river flow (water years Oct - Sept), along with the date of occurrence, and annual minima of 7-day mean river flow (years spanning Dec-Nov), along with the date of occurrence (units: m3/s). The data are provided in gridded netCDF files. 

There is one file for each variable and ensemble member. To aid interpretation, two additional spatial datasets are provided: a) digitally-derived catchment areas and b) estimated locations of flow gauging stations both on the 1km x 1km grid and c) a 1km x 1km grid identifying majority lake cells. 

The data were produced as part of UK-SCAPE (UK Status, Change And Projections of the Environment, Work Package 2: Case Study - Water) a NERC-funded National Capability Science Single Centre award.
description: This dataset is a model output from the Grid-to-Grid hydrological model (Bell et al. 2009; https://doi.org10.1016/j.jhydrol.2009.08.031) driven by meteorological data derived from the United Kingdom Climate Projections 2018 (UKCP18) Regional (12km) projections (Met Office Hadley Centre 2018, catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604). The projections comprise a 12-member perturbed parameter ensemble (PPE) of the Met Office Hadley Centre Regional Climate Model (RCM) under representative concentration pathway (RCP) scenario RCP8.5. The meteorological variables used were daily precipitation, daily min and max temperature, and daily PE derived from other meteorological variables (using the Penman-Monteith scheme). See Supporting Information for more details.
DOI: 10.5285/b5c190e4-e35d-40ea-8fbe-598da03a1185
title: Daily and sub-daily hydrometeorological and soil data (2013-2019) [COSMOS-UK]

description: This dataset contains daily and sub-daily hydrometeorological and soil observations from COSMOS-UK (cosmic-ray soil moisture) monitoring network from October 2013 to the end of 2019. These data are from 51 sites across the UK recording a range of hydrometeorological and soil variables.

Each site in the network records the following hydrometeorological and soil data at 30 minute resolution: Radiation (short wave, long wave and net), precipitation, atmospheric pressure, air temperature, wind speed and direction, humidity, soil heat flux, and soil temperature and volumetric water content (VWC), measured by point senors at various depths.

Each site hosts a cosmic-ray sensing probe; a novel sensor technology which counts fast neutrons in the surrounding atmosphere. In combination with the recorded hydrometeorological data, neutron counts are used to derive VWC over a field scale (COSMOS VWC), at two temporal resolutions (hourly and daily).
The presence of snow leads to erroneously high measurements of COSMOS VWC due to all the extra water in the surrounding area. Included in the daily data are indications of snow days, on which, the COSMOS VWC are adjusted and the snow water equivalent (SWE) is given.

The potential evapotranspiration (PE), derived from recorded hydrometeorological and soil are also included at daily resolution.

Two levels of quality control are carried out, firstly data is run through a series of automated checks, such as range tests and spike tests, and then all data is manually inspected each week where any other faults are picked up, including sensor faults or connection issues. Quality control flags are provided for all recorded (30 minute) data, indicating the reason for any missing data.

This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.
description: Hydrometeorological and soil observations are recorded at sites around the UK using an array of sensors. Every hour, the raw data collected is sent to UKCEH in Wallingford, where it is subject to quality control. Soil volumetric water content data are derived from 30 minute hydrometeorological data and data from the cosmic-ray sensing probe by Python scripts run every hour. The data are calculated using the method outlined in Evans et al. (2016, https://doi.org/10.1002/hyp.10929). Snow water equivalent are derived by Python scripts at the end of the day from the hydrometeorological data according to Wallbank et al. (2020, https://ui.adsabs.harvard.edu/abs/2019EGUGA..2116420W/abstract). Potential evapotranspiration data are derived by Python scripts at the end of the day from the hydrometeorological data according to the Penman-Monteith method (FAO 56, http://www.fao.org/3/X0490E/x0490e00.htm).

All data, that is raw, quality controlled and derived, is saved in an Oracle database.

See supporting documentation for further information.
DOI: 10.15156/bio/sh0169973.10fu
title: SH0169973.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/143e1a69-d4d7-4ae0-9650-6ffad9fd75b2
title: Vegetation survey data from Climoor fieldsite in Clocaenog Forest

description: This dataset contains vegetation survey data from an upland heath site in the Clocaenog Forest. Vegetation was surveyed in the experimental plots at the Climoor site in 1998, 1999, 2000, 2002, 2003, 2007, 2008, 2009, 2010, 2011 and 2012. The vegetation at the site is a typical UK upland heathland, dominated by Calluna vulgaris, with Vaccinium myrtillus and Empetrum nigrum also being present in the vegetation understory. In each year, measurements were taken at a time period of maximum growth, which was late August/early September. This was done by pin point methodology, and data includes both pin hits as well as measurements converted into plant biomass. Individual species can be examined, as well as the different components of the higher plants (i.e. leaf, stem, flower). 
description: Within each plot, three quadrats were chosen, and in each quadrat a grid of 100 pins was lowered through the multi-layered canopy. Permanent base pegs to mount the point quadrat grid frames were installed in each of the quadrats to ensure the same vegetation was surveyed each year. Every touch of vegetation was recorded, detailing the height of the hit, the species and the structure (i.e. leaf, stem, etc.). Multiple hits of the same species structure were only recorded once for each height (e.g. two V. myrtillus leaves touching at the same height would only be recorded once). Pin hits were recorded on dictaphones and transcribed back in the office into Excel. The transcribing stage was double checked to ensure no errors were made in data input. This is done using a combination of the filter tool in excel to look for misspelt species codes and to check all the rows/pins for each quadrat were included. The total number of pins recorded in each plot (should be 300) was double checked to make sure none were missed and the total number of hits for each of the data input codes determined. A summary sheet gives an overview of the number of hits in each plot for each data input code. It also adjusts for any missing pins. This is done very simply, if the number of pins deviates from the 300 that should have been recorded, each of the hit totals for each of the data input codes is adjusted by this ratio. The total number of hits for each data input code was copied/pasted into a main master file for the dataset. In this file, conversion factors are applied to the data to provide biomass (g/m2) numbers. The conversion factors were derived from 10 areas (each 0.5 m2) outside and surrounding the experimental plots. These were pin-pointed in an identical method to that carried out inside the plots in 2000, and then destructively harvested to determine calibration calculations between biomass and number of pin-hits.
DOI: 10.15156/bio/sh0169974.10fu
title: SH0169974.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/486f049b-c51b-4496-97e3-1d66137e4296
title: Daily and sub-daily hydrometeorological and soil data (2013-2016) [COSMOS-UK] v2

description: This dataset contains daily and sub-daily hydrometeorological and soil observations from COSMOS-UK (cosmic-ray soil moisture monitoring network) from the start of the network, in October 2013, to the end of 2016. These data are from 42 sites active across UK during this time, recording a range of hydrometeorological and soil variables. Each site in the network hosts a cosmic-ray sensing probe; a novel sensor technology which can be used, in combination with hydrometeorological data, to calculate the volumetric water content of soil over a field scale. The hydrometeorological and soil data are recorded at a 30 minute resolution and they include neutron counts from the Cosmic-ray sensing probe, humidity and atmospheric pressure data that are used to derive volumetric water content at two temporal resolutions (hourly and daily). Also included are soil heat flux, air temperature, wind speed and net radiation data which are used to derive potential evapotranspiration at a daily resolution.
description: Hydrometeorological and soil variables are recorded on site and telemetered to a central data system at CEH Wallingford every hour. These data are then loaded to an Oracle database and subject to quality control tests. Soil volumetric water content data are derived from 30 minute hydrometeorological data and data from the cosmic-ray sensing probe by python scripts run every hour and at the end of the day a daily value is calculated. The data are calculated using the method outlined in Evans et al. (2016). Potential evapotranspiration data are derived by python scripts at the end of the day from the hydrometeorological data according to the Penman-Monteith method (FAO 56).
See supporting documentation for further information.
DOI: 10.5285/f463bc5c-bb79-4967-a8dc-f662f57f7020
title: Long-term multisite Scots pine trial, Scotland: field phenotypes, 2013-2020

description: Phenotypes (growth and phenology) for Scots pine trees in a long-term common garden trial planted in three sites in Scotland, surveyed annually from 2013 to 2020.
description: A multi-site field trial was established at three sites in Scotland in 2012 using five year old Scots pine trees. Each site contains 8 families from each of 21 native Caledonian pinewood provenances. Two of the sites (FE and FS) have four randomised blocks and the other (FW) has three randomised blocks.
Tree height and basal stem diameter were measured at the end of each growing season from 2013 to 2020 for trees growing at two of the field sites (FE and FW) and in 2020 for trees growing at the third (FS). 
Phenology assessments were performed in spring at each site from 2015 to 2019 (the survey was not completed in 2020 due to the COVID-19 pandemic).
DOI: 10.15156/bio/sh0169975.10fu
title: SH0169975.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da
title: High-resolution global topographic index values

description: The topographic index is a hydrological quantity describing the propensity of the soil at landscape points to become saturated with water as a result of topographic position (i.e. not accounting for other factors such as climate that also affect soil moisture but are accounted for separately). Modern land surface models require a characterisation of the land surface hydrological regime and this parameter allows the use of the TOPMODEL hydrological model to achieve this .This Geographic Information System layer is intended for use as topographic ancillary files for the TOPMODEL routing model option within the Joint UK Land Environment Simulator (JULES) land surface model. The topographic index variable here is directly comparable to the compound topographic index available from United States Geological Survey's Hydro1K at 30 sec resolution. 
description: The GA2 algorithm has been used to calculate these topographic index values, using base data layers provided by the HydroSHEDS suite of GIS layers. All files were generated using FORTRAN 90 at 15 arc-sec resolution (cells circa 450 m x 450 m at the Equator).
DOI: 10.5285/e4d566bf-b571-460e-816e-0efa1ab3335a
title: Trait responses of aquatic organisms from microfibre exposure studies published 2015-2024

description: The resource includes data extracted from published laboratory studies investigating the impacts of microfibres (fibres < 5 mm in size) on various traits within aquatic organisms. Data were accessible on 19/06/2024 and represent studies from 2015 to 2024.

The dataset includes measured responses in a range of aquatic organisms after microfibre exposure. Measures correspond to the following defined traits: 
1.	Development - healthy molting and growth of organs and structures. 
2.	Fecundity - number of offspring and quality of gametes.
3.	Feeding - intake handling and egestion of resources.
4.	Growth - change in organism weight, length or derived measures.
5.	Hatching - number, emergence time and morphology of offspring.
6.	Health - indices and measures of general organism wellbeing.
7.	Survival - organisms alive at a particular time point.

This dataset was created to collate microfibre study findings for meta-analyses and to identify gaps within the literature. This work was supported by NERC (NE/Y003985/1) as part of the Future Fibres Network project.

description: The dataset was generated from an initial Web of Science database search of studies investigating the exposure impacts of microfibres (small fibres < 5 mm in size) on the responses of aquatic organisms. Web of Science results were evaluated and then the citing and cited studies from these results also screened. Finally, the compiled results were then assessed for eligibility as detailed in the supporting information and only eligible responses extracted.

Quality assurance (QA) steps were used to exclude a number of studies and responses as outlined in the resource supporting information.
DOI: 10.15156/bio/sh0169976.10fu
title: SH0169976.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/f27cf73b-65f0-4838-b6ad-efe865a4188c
title: Campanula rotundifolia cytotype, distribution and first flowering dates

description: This dataset comprises information of location and cytotype of over 1300 samples of Campanula rotundifolia L. from the northern hemisphere (mostly from Britain and Ireland) and data from a common garden study in which British and Irish cytotypes were grown together and their flowering phenology and growth were assessed. Campanula rotundifolia L. is a widespread polyploid perennial herbaceous plant, with diploid, tetraploid, pentaploid and hexaploid cytotypes. 
description: Cytotype samples were collected by Centre for Ecology & Hydrology (CEH) or sent in by members of the public. The common garden study was conducted at CEH in Edinburgh. See supporting documentation for further information.
DOI: 10.15156/bio/sh0169977.10fu
title: SH0169977.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.