cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/49a26df5-6b50-41f2-8d3a-c235eedc5cd1
title: Soil respiration data from Climoor fieldsite in Clocaenog Forest

description: This dataset contains soil respiration data from the Climoor fieldsite in Clocaenog forest, north-east Wales. Measurements began in March 1999 at the field site, and were repeated in approximately bi-weekly intervals until Oct 2013 (although there are some larger gaps for technical or logistical reasons in this 14 year dataset). The data were collected using 3 different methods/machines over the years: static chambers, soil respiration chamber and EGM-4 (from PP Systems), and soil respiration chamber and Li8100 (from Licor Biosciences). The method used is detailed in the data and described further in the supporting documentation.
description: Three soil collars were installed per plot (5-10cm into the soil) in the plots in 1999. Any above-ground plan growth within the collars was removed on a regular basis. A soil respiration chamber connected to an EGM-4 from PP Systems was used prior to 2008, here data were downloaded from the EGM, and converted from the units provided (gCO2 m-2 hr-1) into mg CO2-C m-2 hr-1. From 2008, a survey soil respiration chamber and Li-8100 (Licor biosciences) were used. Data was downloaded from the Li-8100 into a raw data file. Within the raw data file linearity of the measurement was checked visually using the li-8100 software and the checked data was then saved under a separate file name. Following this, data was converted from the units provided (umol/m2/s) to mg CO2-C m-2 hr-1. For all time periods, measrements from the 3 soil collars in each plot were meaned to give an experimental plot average.
DOI: 10.5285/9feab716-0642-4ab9-a363-d73d135a48b9
title: Soil microbial communities, soil, environmental and forest structural properties across old-growth forest and naturally regenerating or actively restored selectively logged tropical forest in Sabah, Borneo, March 2018

description: This dataset contains information on soil microbial communities, soil physicochemical properties, forest structural and environmental characteristics across a contiguous area of forest  that has undergone contrasting logging disturbance and restoration in Sabah, northern Malaysian Borneo. Sampling was conducted as part of a study investigating soil microbial community responses to either active restoration (enrichment planting) or passive restoration (natural regeneration) of selectively logged forest, relative to old-growth soil microbial communities.

This work was supported through the UK Natural Environment Research Council (NERC) Human Modified Tropical Forests Programme (Biodiversity and Land-use Impacts on Tropical Ecosystem Function (BALI) consortium [NE/K016253/1]), ENVISION Doctoral Training Scheme [NE/L002604/1] and NC International Programme [NE/X006247/1].
description: Soil samples and forest structural and environmental data were collected at nine sites during one campaign in  March 2018 . Three sampling sites were chosen in each of three forest types of old-growth, naturally regenerating and actively restored logged forest. Old-growth forest was located in the Danum Valley Conservation Area, and logged forest sites were situated within the adjacent Innoprise Face Foundation Rainforest Rehabilitation Project (INFAPRO) area. A geospatial transect design was employed for soil sampling and measurement of microclimate variables at each site to assess variation in microbial communities over cm to m scales. This comprised three transects radiating out from one centre point positioned at 120 ° to one another. Sampling points were located at the centre point, then at increasing distances of 10 cm, 30 cm, 90 cm, 2.7 m, 8.4 m and 24.3 m along each transect relative to the centre. The circumferences of all tree stems with diameter at breast height (DBH) >5 cm within a 2.5 m buffer of all transects were recorded at each site for site-level calculation of stem density and basal area. Soil physicochemical properties were analysed at the Sabah Forest Research Centre, Sepilok. Organic layer soil microbial community data were generated by 16S and ITS amplicon sequencing at UKCEH Wallingford, and Phospholipid Fatty Acid (PLFA) analysis at Lancaster University in the UK. Fungal functional guild classifications were assigned to fungal sequences using the FUNGuild annotation tool. Alpha diversity indices for microbial groups and relative abundances of fungal guilds were generated after rarefying by minimum read counts for each group . Rates of spatial turnover in soil microbial taxa for different microbial groups were calculated using the distance decay approach via linear modelling.
DOI: 10.15156/bio/sh0169956.10fu
title: SH0169956.10FU

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: 10.5285/2998b066-6a35-4e4f-ae39-16838781856b
title: Changes in gene expression and encapsulation in Drosophila melanogaster caused by exposure to parasitoid wasps

description: Data consists of gene expression estimates and encapsulation rates in wild caught Drosophila melanogaster larvae following exposure to different treatments. Treatments include injection with wasp homogenate, injection with oil and no injection. Also provided are functional enrichment categories for differentially expressed genes and library generation and read mapping metrics. 

The data were produced under the grant: NE/P00184X/1
description: Drosophila melanogaster larvae obtained from a wild caught population were exposed injected with wasp homogenate, oil or no manipulation was made. Encapsulation rates were measured in each case in the fly larvae. For RNA-sequencing, hemocyte and fat body tissues were isolated from third instar larvae 24 hours post experimental manipulation. RNA was isolated for sequencing. Sequenced reads were trimmed, mapped to the dm6 genome, number of reads mapping to each gene was counted, differential expression tests were applied and functional enrichment was done.
DOI: 10.15156/bio/sh0169957.10fu
title: SH0169957.10FU

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: 10.5285/9275ab7e-6e93-42bc-8e72-59c98d409deb
title: Potential evapotranspiration derived from HadUK-Grid 1km gridded climate observations 1969-2021 (Hydro-PE HadUK-Grid)

description: Gridded potential evapotranspiration calculated from HadUK-Grid gridded observed meteorological data at 1 km resolution over the United Kingdom for the years 1969-2021. This dataset contains two potential evapotranspiration variables: daily total potential evapotranspiration (PET; kg m-2 d-1) and daily total potential evapotranspiration with interception correction (PETI; kg m-2 d-1). The units kg m-2 d-1 are equivalent to mm d-1.

The data are provided in gridded netCDF files. There is one file for each variable, for each calendar month.

These data were generated as part of NERC grant NE/S017380/1 (Hydro-JULES: Next generation land surface and hydrological prediction.)
description: This dataset was derived from the HadUK-Grid gridded observed meteorological dataset v1.0.3.0 at 1 km resolution over the United Kingdom for the years 1969-2020 and v1.1.0.0 for 2021. (https://catalogue.ceda.ac.uk/uuid/4dc8450d889a491ebb20e724debe2dfb). HadUK-Grid is a gridded dataset derived from observed meteorological station data. The daily total potential evapotranspiration (PET; kg m-2 d-1) was calculated using the Penman-Monteith equation parameterised for a well-watered grass surface. The daily total potential evapotranspiration with interception correction (PETI; kg m-2 d-1), was calculated as PET then a correction added for interception by a grass canopy on days with non-zero precipitation. 
The HadUK-Grid meteorological variables used were: daily maximum and minimum air temperature at 1.5 m (°C), daily precipitation (mm d-1), monthly mean water vapour pressure (hPa), monthly mean sea level pressure (hPa), monthly total sunshine hours (hours) and monthly mean wind speed at 10 m (m s-1). Other variables used were the surface elevation (m) and Ångström coefficients a, b and c. A description of the methodology is available in the supporting documentation.
DOI: 10.5285/dd4dfc72-dafe-44a2-af2b-0118d949d7ad
title: Litterfall data from Climoor fieldsite in Clocaenog Forest

description: This dataset includes litterfall data from the experimental plots at the Climoor field site in the Clocaenog forest, NE Wales. Litterfall (natural senesced plant material) was collected in litterfall traps (12 x 7.5cm pots standing slightly proud of the soil/litter surface, emptied monthly). Litterfall was calculated by drying the contents of the traps and weighing the samples; values were calculated for each quadrat (total weight (g) only) and for each plot (total weight (g) and weight per metre squared (g/m2)). Data spans the periods Oct 1999 to Jan 2004 and July 2008 to June 2011.
description:  Litterfall was estimated using litterfall traps. Traps measured 7.5 cm diameter and 12 were placed in each plot in 3 different quadrats (D3, E4 and E7). Traps were emptied on a monthly basis from 1999 to 2002. After 2002, litter was not emptied on a monthly basis, and occasionally was left out in the trap for a few months (this was for the same duration for all plots, ie there was always consistency across the treatments). Once collected in, the litterfall was first air dried before removal from the trap. Litter was pooled for each of quadrats (for example, the litter collected from the four pots in each quadrat was pooled, so you would end up with samples from plot 1 quadrat D3, plot 1 quadrat E4 and plot 1 quadrat E7, and so on) prior to oven drying at 75 oC overnight and weighing. Data processing Data was manually typed into and stored in an MASTER Excel file. Mean litterfall per quadrat was calculated for each plot (ie the mean of the weight of litter collected in D3, E4 and E7). Data was then multiplied by 56.6 to convert data into the units g litter m-2.
DOI: 10.15156/bio/sh0169958.10fu
title: SH0169958.10FU

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: 10.5285/8dc7a85a-9eb2-4888-938d-dd41fce39ea4
title: Peatland stream water chemistry data from the MERLIN project, Hare Moss, Scotland, 2022-2023

description: This dataset comprises water chemistry data, including dissolved organic carbon (DOC), total dissolved nitrogen (TdN), particulate organic carbon (POC), total phosphorus (TP), soluble reactive phosphorus (SRP), absorbance at 254nm (Abs 254), specific ultraviolet absorbance (SUVA), and dissolved CH4, CO2, N2O, collected bi-weekly from peatland streams near Penicuik, Scotland, in 2022 and 2023. Data were obtained via collection of water samples in situ, and concentrations were derived via subsequent sample processing and analysis.  

The objective of this dataset is to provide background data to characterise differences in the baseline period before restoration at the sampling site occurs.
description: Fortnightly sampling took place at two locations from December 2021 to May 2022. An additional two locations were sampled from May 2022 to August 2022. One of the original sites was discontinued in August 2022 and the remaining three locations continued to be sampled until December 2023.

Samples were collected directly from each stream using a 60 ml syringe and were either dispensed directly unfiltered or, filtered with a cellulose acetate filter into their relevant containers before being returned to the lab and either frozen or refrigerated before analysis.

Dissolved greenhouse gas samples were collected using the headspace method. This involves filling a 60 ml syringe with 30 ml of stream water and 30 ml of ambient air and agitating it for one minute until equilibration of gases has occurred. The air sample is then injected into a sealed vial and returned to the lab for analysis.

All data were generated by the authors. During the generation of water chemistry data, calibration standards of known concentrations were used for quality control of instrument outputs.
DOI: 10.5285/b7a98440-8742-40d5-a518-46dc6420416e
title: Grid-to-Grid model estimates of river flow for Great Britain 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 Great Britain 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. 

The data were produced as part of UK-SCAPE (UK Status, Change And Projections of the Environment; www.ceh.ac.uk/ukscape, Work Package 2: Case Study – Water) programme, a NERC-funded National Capability Science Single Centre award number NE/R016429/1.
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: 10.15156/bio/sh0169959.10fu
title: SH0169959.10FU

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: 10.15156/bio/sh0169960.10fu
title: SH0169960.10FU

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: 10.5285/01592784-807b-453a-ac52-0478ad616484
title: Daily automated weather station (AWS) data from Climoor fieldsite in Clocaenog Forest

description: This dataset contains daily automated weather station (AWS) data from the Climoor field site in Clocaenog forest, NE Wales. It runs from 12/6/1999 until 31/12/2013, and contains air temperature (mean, minimum and maximum), rainfall, net radiation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction. The dataset has been quality checked, and incorrect or missing values removed, data has not been infilled.
description: Prior to 2008, daily data was recorded on loggers at the field site, and manually downloaded into the project files on the CEH Bangor server by project staff. After 2008, hourly data was transferred from loggers at the field site onto CEH Bangor's server via a remote telemetry system. Each morning, the previous days data was transferred via telemetry. An automated script transferred the data into the project shared area of the shared network drive. Data quality checking was done on a regular basis by an experienced member of the team who has worked at the field site and on data from the Clocaenog site for 14 years. Data was visually inspected using basic graphing tools, and erroneous values were removed, taking into account the weather at the site during the period in question. Data processing steps included using a macro to combine data from individual 24 hour periods into larger timed periods (post-2008), then data was cut/pasted into raw data files. Data here is collated raw data, and has only had erroneous values removed followed by basic average or summing (in the case of rainfall) calculations being carried out.
DOI: 10.5285/4260dc49-764f-4ba5-b215-dab7eaaf35c8
title: Daily micro-meteorological data from Climoor fieldsite in Clocaenog Forest

description: This dataset contains daily micro-meteorological data from the experimental plots at the Climoor field site in Clocaenog forest, NE Wales. It runs from 15/7/1999 until 31/12/2013, and contains air temperature, soil temperature at 2 depths (5 and 20cm) as well as soil moisture. The dataset has been quality checked, and incorrect or missing values removed, data has not been infilled. 
description: Prior to 2008, daily data was recorded on loggers at the fieldsite, and manually downloaded into the project files on the CEH Bangor server by project staff. After 2008, hourly data was transferred from loggers at the fieldsite onto CEH Bangor's server via a remote telemetry system. Each morning, the previous days data was transferred via telemetry. An automated script transferred the data into the project shared area of the shared network drive. Data quality checking was done on a regular basis by an experienced member of the team who has worked at the field site and on data from the Clocaenog site for 14 years. Data was visually inspected using basic graphing tools, and erroneous values were removed, taking into account the weather at the site during the period in question. Data processing steps included using a macro to combine data from individual 24 hour periods into larger timed periods (post-2008), then data was cut/pasted into raw data files. Data here is collated raw data, and has only had erroneous values removed followed by basic average or summing (in the case of rainfall) calculations being carried out.