cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/5f3c1a02-d5c4-4faa-9353-e8b68ce2ace2
title: Grid-to-Grid model estimates of daily mean river flow for gauged catchments in Great Britain (1960 to 2015): observed driving data [MaRIUS-G2G-MORECS-daily]

description: This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and MORECS potential evaporation). It provides daily mean river flow (m3/s) for 260 catchments, for the period 1960 to 2015. The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/).

The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/).
description: The river flow estimates are output from the Grid-to-Grid hydrological model (Bell et al. 2009; https://doi.org/10.1016/j.jhydrol.2009.08.031). The meteorological inputs to the model were rainfall from CEH-GEAR (Tanguy et al. 2016; https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca) and potential evaporation from MORECS (Hough and Jones 1997; https://doi.org/10.5194/hess-1-227-1997). See Supporting Information for more details.
DOI: 10.15156/bio/sh0162747.10fu
title: SH0162747.10FU

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: 10.5285/86cd1a60-64f1-4087-a9f1-a3d8a9f8f535
title: Farm scale evaluations of herbicide tolerant genetically modified crops - beet

description: This dataset consists of a range of ecological measurements collected from a set of arable fields, each sown with a combination of genetically modified and conventional beet crops. Measurements include species counts in the following areas: weed seedbank, vegetation in the crop, field edge vegetation, invertebrates. The data were collected as part of the Farm Scale Evaluations (FSEs), a four-year programme of research by independent researchers aimed at studying the effect that the management practices associated with Genetically Modified Herbicide Tolerant (GMHT) crops might have on farmland wildlife, when compared with weed control used with non-GM crops. Data were collected by a consortium of: the Institute of Terrestrial Ecology  (now the Centre for Ecology & Hydrology), the Institute of Arable Crops Research (now Rothamsted Research) and the Scottish Crop Research Institute, SCRI (now the James Hutton Institute). Data were collected for four crops overall (Beet, Maize, Spring-sown Oilseed Rape and Winter-sown oilseed Rape).
description: Data were collected by a consortium of: the Institute of Terrestrial Ecology, ITE (now the Centre for Ecology & Hydrology, CEH), the Institute of Arable Crops Research (now Rothamsted Research, IACR) and the Scottish Crop Research Institute,SCRI. Data were collected for the four crops (Beet, Maize, Spring-sown Oilseed Rape and Winter-sown oilseed Rape) in the following areas: seedbank, vegetation in the crop, field edge vegetation, invertebrates.  Strict data entry and storage controls, data management controls and data analysis protocols were in place during the project. Key references: Refer to: The Farm Scale Evaluations of spring-sown genetically modified crops.  Papers of a Theme Issue.  Philosphical Transactions of the Royal Society of London, Series B, Vol. 358, Number 1439, 29th November 2003.
DOI: 10.5285/971671a6-98b4-4d80-b165-21dace7373b9
title: ITE Land Classification of Great Britain 1998

description: The Land Classification 1998 is a classification of Great Britain into a set of 40 environmental strata, termed land classes, to be used as a basis for ecological survey, originally developed by the Institute of Terrestrial Ecology (ITE) in the late 1970s and building upon a previous 1990 version. The strata were created from the multivariate analysis of 75 environmental variables, including climatic data, topographic data, human geographical features and geology data. The Land Classification can be used to stratify a wide range of ecological and biogeographical surveys to improve the efficiency of collection, analysis and presentation of information derived from a sample. The Land Classification 1998 provided stratification for the Countryside Survey of Great Britain 2000 and was adjusted from the 1990 version as a consequence of needing to provide National Estimates for habitats for Scotland from Countryside Survey 2000 in addition to GB as a whole. The dataset was later modified in 2007 during Countryside Survey 2007. Both the 1990 version and the 2007 version are also available. 
description: The 1998 version of the ITE Land Classification was developed from an earlier classification from 1990 which used environmental data from all 240,000 km squares in GB to create the stratification. It contains 40 classes or strata, distributed across Great Britain. Each stratum consists of areas with similar environmental characteristics. The classification differs from the 1990 version by splitting classes in England and creating additional classes in Scotland. Further information is provided in the supporting documents available in the Online Resources.
DOI: 10.15156/bio/sh0162748.10fu
title: SH0162748.10FU

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: 10.5285/3b90962e-6fc8-4251-853e-b9683e37f790
title: Grid-to-Grid model estimates of monthly mean flow and soil moisture for Great Britain: weather@home2 (climate model) driving data [MaRIUS-G2G-WAH2-monthly]

description: This dataset is a model output, from the Grid-to-Grid hydrological model driven by weather@home2 climate model data. It provides a 100-member ensemble of monthly mean flow (m3/s) and soil moisture (mm water/m soil) on a 1 km grid for the following time periods: historical baseline (HISTBS: 1900-2006), near-future (NF: 2020-2049) and far-future (FF: 2070-2099). It also includes a baseline period (BS: 1975-2004). 

To aid interpretation, two additional spatial datasets are provided:
 -	Digitally-derived catchment areas on a 1km x 1km grid
 -	Estimated locations of flow gauging stations on a 1km x 1km grid and as a csv file.

The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity. 
description: The flow and soil moisture estimates are output from the Grid-to-Grid hydrological model (Bell et al. 2009; https://doi.org/10.1016/j.jhydrol.2009.08.031). The meteorological inputs to the model were the weather@home2 bias-corrected precipitation and potential evaporation (Guillod et al. 2018; https://doi.org/10.5285/0cea8d7aca57427fae92241348ae9b03). See Supporting Information for more details.
DOI: 10.5285/68f4a12f-740d-4705-9c27-6a7fb7127046
title: Vyrnwy research catchment hydrochemistry

description: This dataset includes weekly data from monitoring of stream, rainfall and groundwater hydrochemistry in the Vyrnwy research catchment between 1994 and 2001. Data for over 50 chemical determinands are presented alongside data for some in-situ measurements such as water temperature. Full descriptions of the analytical methods used for each determinand is included. Intensive and long-term monitoring within the catchments underpins a wealth of hydrological and hydro-chemical research; other linked datasets include river flow, meteorology and a variety of detailed spatial datasets representing the topography, soils and rivers of the catchments. Monitoring is funded by the Centre for Ecology & Hydrology.
description: Originally designed to improve understanding of water use by coniferous forests, monitoring within the Plynlimon/Vyrnwy research catchments has subsequently developed into a multi-disciplinary project underpinning a wealth of hydrological research. The stream hydrochemistry dataset is a combination of chemical determinands and in-situ physical properties. Samples are taken on an approximately weekly basis and analysed in laboratories for approximately 50 chemical determinands. The laboratory analysis has been undertaken at different locations using different equipment during the years of monitoring represented within the dataset. Details of the analytical methods used for each determinand are included within the dataset. The information provided is presented as raw data which have not been modified to include "less than" values when the numbers are less than the lowest quotable value. This is done so as to allow the data to be used for research purposes including detailed statistical analysis where inclusion of less than values would be problematic. The data are thus "uncensored" for research purposes and include in places values that are negative due to analytical uncertainties and the extremely low concentrations of some of the determinands. The data are provided in good faith with the expectation that they will be used in a positive and constructive manner. It is up to the user to resolve which way to use and interpret the data and information on full methodologies and less than values is provided within the metadata files. We whole heartedly encourage the use of these data for research and educational purposes bearing in mind that it is uncensored data and that over the years research directions have evolved to reflect changing project and funding priorities while analytical methodologies have changed. The data provide a legacy from many years' research involving scientists, analysts and field workers who in many cases have now retired. While we have done our best to provide all the information possible, in many cases it will be not be possible to respond to detailed enquiries about the earlier parts of the record.
DOI: 10.15156/bio/sh0162749.10fu
title: SH0162749.10FU

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/c76096d6-45d4-4a69-a310-4c67f8dcf096
title: Water, carbon and energy fluxes simulation for Great Britain using the JULES Land Surface Model and the Climate Hydrology and Ecology research Support System meteorology dataset (1961-2015) [CHESS-land]

description: The dataset contains daily and monthly surface water, energy and carbon fluxes, and state variables for Great Britain over the period between 1961 and 2015. The data was obtained from a 55 years simulation with the JULES Land Surface Model, at 1 km spatial resolution and driven by the meteorological dataset CHESS-met v1.2 (Robinson et al., 2017; https://doi.org/10.5285/b745e7b1-626c-4ccc-ac27-56582e77b900). The data comes in both monthly (all variables) and daily (only variables with no z dimension) averages. The variables are: total evapotranspiration and components (kg m-2 s-1), runoff (kg m-2 s-1), surface temperature (K), soil moisture (kg m-2), soil temperature (K), snow mass (kg m-2). latent and sensible heat (W m-2), net and gross primary productivities (kg C m-2 s-1), plant respiration (kg C m-2 s-1). The z dimension may refer, if present, to tile (surface type), pft (plant functional type) or soil (soil layer).

This simulation forms the basis for new research paper by Blyth et al (2017, under review).
description: This data has been produced using the JULES land surface model (model version: vn4.5; branch r3488_albmar_spdm), at 1 km spatial resolution over Great Britain and driven by the CHESS-met v1.2 (Robinson et al., 2017; https://doi.org/10.5285/b745e7b1-626c-4ccc-ac27-56582e77b900). The simulation covers a total of 55 years (1961-2015). The model configuration (parameters and rest of input data) can be accessible through the MetOffice JULES repository (https://code.metoffice.gov.uk/trac/jules), on the Rose suite u-au394.
DOI: 10.15156/bio/sh0162750.10fu
title: SH0162750.10FU

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/d6a8bc3d-b6fb-47bc-a693-612e2454cf50
title: Mimetic host shifts in a social parasite of ants: Behavioural study

description: This dataset derives from cross-over experiments using ant worker rescue behaviour towards caterpillars of the socially parasitic butterfly from two host-ecotypes.  The data comprise datasets collected from four 4 experiments 3 hours after testing and from 4 experiments 7 days later. They all include nest numbers, the order of retrieval ranked by the attention of nurse ants to the ant pupae, large larvae and small larvae and the adult Maculinea rebeli. The data give the rank order of test items as they were rescued in order to explain social status achieved in natural and unnatural host colonies. 

This dataset is part of the study of mimetic host shifts in an endangered social parasite of ants, which is a joint study of the NERC's Centre for Ecology & Hydrology (UK), the University of Oxford (UK), University of Bialystok (Poland), Polish Academy of Sciences (Poland) and UFZ Helmholtz Centre for Environmental Research (Germany). 

Detailed research method can be found in Thomas et al. (2012) Mimetic host shifts in an endangered social parasite of ants. Proc. R. Soc. B vol. 280 no.1751. (http://doi.org/10.1098/rspb.2012.2336)
description: We assessed the social status achieved by each form of M. rebeli within colonies of each Myrmica species in a standard bioassay that involved perturbing laboratory ant colonies and recording the order in which the ants' own brood or the mimetic caterpillars were rescued. Groups of 5 butterfly larvae from each region were adopted into matching colonies of niaive French M. schencki and M. sabuleti. Every test colony also contained 5 brood items each of kin ant pupae, large and small larvae, making a total of 20 immature individuals and 20 workers per replicate. Cultures were established in laboratory colonies containing a small moist sponge pad beneath an inverted 6 cm diameter saucer with a notched entrance, under which the ants gathered their brood and M. rebeli. Three hours after the M. rebeli caterpillars had been introduced, we perturbed the experimental colonies by uncovering the brood chamber and relocating it over another pad nearby; we then recorded the order in which the nurse ants rescued their 15 brood items or the 5 M. rebeli and carried them into the new nest. The same experiment was repeated 7 days later, which represents a sufficient period for M. rebeli caterpillars to attain their maximum potential integration with a host society, yet remaining a similar size to when first adopted, i.e. the same size or smaller than the Myrmica pupae and large larvae. The number of replicates for each ant-butterfly combination tested varied due to a lack of some ants and butterfly deaths (especially with unnatural hosts).
DOI: 10.5285/e911196a-b371-47b1-968c-661eb600d83b
title: Grid-to-Grid model estimates of monthly mean flow and soil moisture for Great Britain (1960 to 2015): observed driving data [MaRIUS-G2G-MORECS-monthly]

description: This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and MORECS potential evaporation). It provides monthly mean flow (m3/s) and soil moisture (mm water/m soil) on a 1 km grid for the period 1960 to 2015.

To aid interpretation, two additional spatial datasets are provided:
 * Digitally-derived catchment areas on a 1km x 1km grid
* Estimated locations of flow gauging stations on a 1km x 1km grid and as a csv file.

The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity.
description: The flow and soil moisture estimates are output from the Grid-to-Grid hydrological model (Bell et al. 2009; https://doi.org/10.1016/j.jhydrol.2009.08.031). The meteorological inputs to the model were rainfall from CEH-GEAR (Tanguy et al. 2016; https://doi.org/10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca ) and potential evaporation from MORECS (Hough and Jones 1997; https://doi.org/10.5194/hess-1-227-1997). See Supporting Information for more details.
DOI: 10.15156/bio/sh0162751.10fu
title: SH0162751.10FU

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: 10.5285/1a91c7d1-ec44-4858-9af2-98d80f169bbd
title: Observations of Fukushima fallout in Great Britain

description: Following the Fukushima accident in March 2011, grass samples were collected from 42 sites around Great Britain during April 2011. Iodine-131 was measurable in grass samples across the country with activity concentrations ranging from 10 to 55 Bq per kg dry matter. Concentrations were similar to those reported in other European countries. Rainwater and some foodstuffs were also analysed from a limited number of sites. Of these, I-131 was only detectable in sheep's milk (c. 2 Bq/kg). Caesium-134, which can be attributed to releases from the Fukushima reactors, was detectable in six of the grass samples (4-8 Bq/kg dry matter); 137Cs was detected in a larger number of grass samples although previous release sources (atmospheric weapons test and the 1986 Chernobyl and 1957 Windscale accidents) are likely to have contributed to this. All data and information for this sampling are available from this record. The data result from collaboration between CEH and the University of Stirling.
description: Fresh grass and other vegetation samples were finely chopped and accurately weighed into 950 ml plastic containers prior to gamma analyses. Milk (sheep and goat), rainwater and homogenised egg content samples were accurately weighed into either 150 ml or 950 ml plastic containers depending upon the sample volume available. To determine the activity concentration of gamma-emitting radionuclides, fresh samples were analysed on hyper-pure germanium detectors as soon as possible after sampling and counted for 1-2 days depending upon their 131I activity concentration. The detectors are calibrated against standards of various density and volume, and the facilities regularly participate in proficiency testing schemes.