cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/31ae71aa-74a9-466b-9a3a-25d2b1a9406e
title: River style characterisation, hydromorphological attributes, catchment properties and stream power analysis for the Bislak Catchment, Philippines, 2020

description: The shapefiles contain the classification and locations of each river style determined by the authors. The data were used to characterise the river styles in Bislak River, Philippines. Shapefiles were clipped to the catchment boundary from different national government agencies to produce different thematic maps. Catchment properties such as land use (from the National Mapping and Resource Information Authority (NAMRIA)), geology (from the Mines and Geosciences Bureau), fault (from Philippine Institute of Volcanology and Seismology, rainfall isohyets, slope map, and the digital elevation model (also from NAMRIA) were used for regional and catchment analysis. The data only covers the whole Bislak catchment, Philippines. The CSV contains data used for the stream power analysis where stream power is a factor of slope and discharge.
description: The shapefiles used for the regional and catchment analyses were clipped from the national data provided by different Philippine government agencies while the river styles data were delineated and classified using the River Styles Framework as a guide. These data can be used as guidance for characterisation of other rivers in the Philippines.
DOI: 10.5285/8385f864-dd41-410f-b248-028f923cb281
title: UK Environmental Change Network (ECN) carabid beetle data: 1992-2015

description: Carabid beetle data from the UK Environmental Change Network (ECN) terrestrial sites. The count of individual species is recorded. These data are collected by pitfall traps at all of ECN's terrestrial sites using a standard protocol. They represent continuous fortnightly records from 1992 to 2015. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage.
description: Data are collected by pitfall traps at all of ECN's terrestrial sites using a standard protocol. Prior to deposit of the data in the EIDC, data are managed by the ECN Data Centre at CEH Lancaster according to defined protocols. 

Verification steps include numeric range checks (i.e. checking if a value falls within a specified range), categorical checks (e.g. checking that a species code appears on the standard code list), formatting (i.e. that the dataset conforms to the specified data format) and logical integrity checks (i.e. checking the data make sense, e.g. that the dates in one dataset match those in a related dataset).

Appropriate range settings for ECN variables have been selected following discussion with specialists in each field. Where data fall outside these ranges, a cautious approach has been adopted towards discarding data on the principle that apparent errors may be valid outliers. Such values are discarded only if there is a clear explanation (e.g. an instrumentation error) and corrections are made where possible. If the reason is unclear, the values are stored, but are qualified using pre-defined quality codes or free-text descriptions. Data providers also use these codes or free text to describe factors affecting sampling outside their control, instrument damage or site management effects.
DOI: 10.5285/8a668a4f-3526-4443-9e77-cea67f04ca19
title: Rift Valley fever virus seroprevalence data from people involved in a cross-sectional survey in Tana River and Garissa counties, Kenya (December 2013 - February 2014)

description: These data include results from serological analysis carried out on serum collected from randomly recruited subjects, merged with household and subject level data about the subjects. The subject and household data collected included occupation of the household head, size of the household, and occupation, gender and age of the subject. Samples were collected from 303 people based in irrigated areas, 728 people from pastoral areas and 81 people from riverine areas along River Tana in Tana River and Garissa counties, Kenya. Field surveys were implemented in December 2013 to February 2014 and laboratory analyses were completed in June 2015. 

Serum samples were harvested from blood samples obtained from randomly recruited subjects and screened for anti-RVF virus immunoglobulin G using inhibition ELISA (enzyme-linked immunosorbent assay) immunoassay. The household and subject metadata was collected using Open Data Kit (ODK) (https://opendatakit.org) loaded into smart phones.

The aim of the project was to determine the risk of Rift Valley Fever virus exposure in people living in areas with different land use and socio-ecological settings. 
The data were collected by experienced researchers from the International Livestock Research Institute (Kenya), the Department of Disease Surveillance and Response, Kenyatta National Hospital

This dataset is part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC). The research was funded by NERC project no NE/J001570/1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA). Additional funding was provided by the Consultative Group on International Agricultural Research (CGIAR) Research Program Agriculture for Nutrition and Health. 
description: Serum samples were harvested from blood samples obtained from randomly recruited subjects and screened for anti-RVF virus immunoglobulin G using inhibition ELISA (enzyme-linked immunosorbent assay) immunoassay. Samples were preserved in the field and while in-transit in dry ice, and were immediately transferred into liquid nitrogen tanks on arrival at the research laboratories at the International Livestock Research Institute, Nairobi. 
Household and subject level data were collected using a short questionnaire, held on a smart phone, administered to the subject on the day of sampling. 
The dataset was created by merging the household and subject level data with the laboratory serological analysis results. Both of these datasets were stored initially in Microsoft Excel; they were converted later to csv for ingestion. In the field, quality assurance was ensured by using bar coded sample containers and using Open Data Kit (ODK) for data collection to avoid recording errors. In the lab, quality assurance was done by running serological tests in duplicates.
DOI: 10.5285/b8efacd7-c849-40e1-a2d8-5c8355e95179
title: Surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a data from Blelham Tarn, UK, 2024

description: This is part of an ongoing long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from fortnightly sampling at Blelham Tarn in Cumbria, England, that began in 1945 for some variables. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise surface temperature (TEMP) in degree Celsius, surface oxygen saturation (OXYG) in % air-saturation, Secchi depth (SECC) in metres, alkalinity (ALKA) in µg per litre as CaCO3 and pH. Total ammoniacal nitrogen (NH4N), total oxidised nitrogen (TON), soluble reactive phosphate (PO4P), total phosphorus (TOTP), dissolved reactive silicon expressed as SiO2 (SIO2) and phytoplankton chlorophyll a (TOCA) are all given in µg per litre. Water samples are based on a sample integrated from 0 to 5 m. Water chemistry values below the detection limit, are indicated by a < sign in the column titled ‘sign(if<LOD)’. Measurements are made from a boat at a marked location (buoy) at the deepest part of the lake. When it was not possible to visit the buoy, samples were taken from the shore along with surface temperature and oxygen measurements. Water samples were not integrated on these occasions, marked as Flag 2.All data are from January 2024 until the end of 2024.
description: Please note that the data presented here are raw data that have not yet been quality-controlled and calibrated. However, data for TEMP, OXYG, SECC, ALKA, pH, PO4P and TOCA has been double entered by different people into excel from field notebooks or laboratory paper record sheets and validated by a database manager. The database manager checked all data visually (line graphs). Missing data are due to weather conditions, equipment limitations, or staff shortages.
DOI: 10.5285/bb785c19-3cf6-4483-9fe5-13829d489a83
title: Countryside Survey 2007 mapped estimates of Broad Habitat areas in Great Britain

description: This dataset consists of stock (area) data for Broad Habitats across Great Britain in 2007 in a 1km grid format. The data are national estimates generated by analysing the sample data from 591 1km squares surveyed for the Countryside Survey long term monitoring project, then scaling up to a national level. The data are presented as percent habitat per 1km square for 17 different habitat types. The Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to habitat areas, vegetation species data, soil data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey.
description: The data were recorded using electronic data capture devices in the summer of 2007 by surveyors. Data were recorded from 591 1km squares sited across Britain, selected by random stratified sample. The areas of UK Biodiversity Action Plan (UK BAP). The data were used to generate national estimates of the stock of Broad Habitats for Great Britain using the standard Countryside Survey methodology (refer to the online documentation). Estimates are presented by ITE Land Class (2007 version), as percentage values per 1km square.
DOI: 10.5285/72ed6237-aedf-43a7-b9e3-eef95320a2bb
title: Chemical contaminants in White-tailed sea eagle eggs - Predatory Bird Monitoring Scheme (PBMS)

description: Data from analyses of addled and deserted sea eagle eggs collected by licensed collectors in Scotland. Contaminants reported include polychlorinated biphenyls (PCBs), organochlorine pesticides or their persistent metabolites, and a range of metals and metaloids. The white-tailed sea eagle has been re-introduced to a number of Scottish Islands since the 1980s. The Predatory Bird Monitoring Scheme (PBMS) is a long-term, national monitoring scheme that quantifies the concentrations of contaminants in the livers and eggs of selected species of predatory and fish-eating birds in Britain. 
description: Addled and deserted sea eagle eggs are collected by licensed collectors in Scotland. Eggs are cracked, the contents homogenised and samples are 1) sent for analysis by the Centralised Analytical Chemistry facility at CEH Lancaster and 2) retained for archive purposes at -20 degrees C. Samples were analysed for polychlorinated biphenyls (PCBs), organochlorine pesticides or their persistent metabolites, and a range of metals and metaloids.  Data are entered by technician onto a MSAccess form which uploads directly to an Oracle database. Batch files containing concentrations of pesticides in tissues load directly to Oracle database.
DOI: 10.5285/25d34c83-e939-40fd-aa16-6962efb4c731
title: Water temperature measurements from Durleigh Reservoir 2018

description: This dataset contains water temperature measurements at two different locations in Durleigh Reservoir in Somerset, England. Water temperatures were measured using RBR SoloT thermistors (measured in deg C) and HOBO TidbiT v2 loggers (measured in deg F). The dataset consists of water temperature measurements from two  locations at Durleigh reservoir between 22 February 2018 and 5 October 2018. Measurements were taken at 10 minute intervals.
description: The first site, labelled location 2, is closer to the artificial mixing devices (surface mixers) installed in the reservoir (60 m away) and deeper, with a water depth of 6 m when on deployment (latitude: 51.1210, longitude: -3.0403). The second site, labelled location 3, is farther away from the artificial mixing devices installed in the reservoir (435 m away) and in a shallower region, with a water depth of 4 m on deployment (latitude: 51.1215, longitude: -3.0445). At location 2, RBR SoloT thermistors (measured in deg C) were positioned at 1 m intervals from the surface (0 m depth) to the bottom of the water column (6 m). However, in the dataset temperature measurements from thermistors positioned at 1 m, 2 m, and 3 m are missing due to corrupted files. At location 3, HOBO TidbiT v2 loggers (measured in deg F) were positioned at 1 m intervals from the surface (0 m depth) to the bottom of the water column (4 m depth). All water temperature measurements were taken at 10-minute intervals. Both temperature chains consisted of a buoy (A2 size) attached to a 10 kg weight using a rope, and the thermistors were attached onto the rope. All thermistors were deployed between 22 February and 5 October 2018.
DOI: 10.5285/e5854431-6fa4-4ff0-aa02-3de68763c952
title: Data on immunological expression and phenotypes in a natural population of field voles in Kielder Forest, UK 2015-2017

description: Data comprise morphometric measurements, sex determination, maturity and immunological analysis of blood pathogens from wild field voles (Microtus agrestis) in Kielder Forest, Northumberland, UK in 2015-17.


description: Wild field voles Microtus agrestis were trapped in Kielder Forest, Northumberland, UK. Trapping was conducted over a total of 46 sessions from March to October in 2015-17, at approximately two week intervals. At each session we trapped voles at four different sites at least 1 km apart. During the course of the study, three sites were reassigned due to practical constraints, giving a total of seven different sampling sites. At each site, 197 Ugglan traps were laid out in a grid pattern with approximately 5m between traps. Trapping sessions lasted three days, with traps checked morning and afternoon.

Voles were marked with unique PIT tags on first capture. On the first capture of each session for a given individual, we recorded sex and reproductive status (ascended or descended testes for males; pregnant, lactating, perforate or imperforate vagina for females) from visual inspection. We measured body length from snout to vent and total body mass. A small blood sample (up to 50 µl) was taken from the tip of the tail and stored in RNAlater at -20°C for a maximum of 5 days before being transferred to -80°C for longer term storage.
DOI: 10.5285/522309f8-59b1-4982-85df-cb3171c2a062
title: Simulated streamflow, demands and aquifer levels in the Cauvery Basin, India, 1986-2080 using the Global Water Availability Assessment Model (GWAVA) 

description: The data resource contains daily time-series of simulated streamflow, ground water levels and estimated demands, from humans, livestock, irrigation and industry, across the Cauvery Basin, India. The data were generated using the Global Water Availability Assessment (GWAVA) Model 5. A baseline of 1986-2005 is presented along with two future time slices (2041-2060 and 2061-2080) for these variables. The data were produced to help predict how rapid economic development and population growth in the region would impact on future water security. The data resource was produced by the data authors.

The research was funded by NERC research grant NE/N016491/1 Upscaling Catchment Processes for Sustainable Water Management in Peninsular India
description: The model was calibrated at 14 gauging stations across the basin against available observed streamflow using the SIMPLEX auto-calibration routine. This routine utilises four parameters (a surface and groundwater routing parameter, a probability distribution model (PDM) parameter that describes spatial variation in soil moisture capacity and a multiplier to adjust rooting depths). The model was then validated across the same 14 gauging stations (over a different time period to the calibration) and 200 groundwater observational wells.
DOI: 10.5285/7815291a-ee3e-49a7-8ef1-e8baa81f4964
title: Vegetation composition data from UK saltmarshes, 2018 to 2021

description: The dataset details vegetation composition of UK saltmarshes measured from quadrats across UK saltmarshes. Between 2018 and 2021, vegetation surveys were carried out at 460 sites across 33 saltmarshes as part of the Carbon Storage in Intertidal Environments (C-SIDE) project to develop an understanding the linkages between saltmarsh soil organic carbon and vegetation. Sites were chosen to represent contrasting habitats types in the UK, in particular sediment types, vegetation and sea level history. The dataset comprises of percentage species cover, plant height, plant richness and plant diversity data from 33 UK saltmarshes.

The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1.
description: Across 33 UK saltmarshes 460 vegetation surveys were undertaken using 1m x 1m quadrats. The location of each quadrat was recorded using Differential Global Positioning System (DGPS). Within each quadrat percentage cover of each plant species was estimated by eye. Plant height was measured at 10 random points within each quadrat. The mean plant height and standard deviation for each quadrat was calculated and reported.  Plant species richness was recorded as the number of species present per quadrat and plant diversity was estimated using the Shannon-Wiener Index. Vegetation data were recorded in the field and transferred into an Excel file. Results were exported as comma separated value (.csv) files for ingestion into the EIDC.
DOI: 10.5285/7c2b2878-1d15-4ddd-9d7e-cf50bd65f652
title: Understory herbaceous plant cover in secondary woodlands on the Isle of Wight, 2021

description: A species by quadrat matrix showing the percentage cover of understory herbaceous plants in ancient and recent woodlands varying in age and isolation. Percentage cover was calculated for each species individually.

The data was collected on the Isle of Wight, woodlands spanned the entire island and were not situated in one area.

All data was collected in the summer of 2021 over a period of 3 weeks covering the last 2 weeks of may May and the first week of June. This time was chosen as this is when a large subset of woodland plants are in flower.

Woodlands were sampled in blocks of three, each block contains an ancient woodland, a recent woodland adjacent to the ancient woodland and another recent woodland of similar age and size but isolated from the ancient woodland. Each woodland had six quadrats taken, systematically placed at four corners and two in the centre. Within each quadrat the percentage cover of all understory herbs was recorded.

This data was collected to measure the colonisation credit of recently planted woodlands, and to observe how much this might vary under differing degrees of isolation. This data could also be used to compare all sorts of biodiversity metrics between connected and isolated recent woodlands. It could also be used to compare beta diversity metrics between woodlands of varying degrees of isolation

description: Data were collected in field surveys on the isle of wight during the summer of 2021. Plants were identified using a dichotomous key and percentage cover was estimated subjectively using marks around the quadrat for assistance. 

Units in the core matrix of the data is percentage cover, any plant covering less than 5% of the quadrat was marked as <5.

There were no processing steps undertaken on this data, values were typed into csv format straight from the paper.  

All quality control had to be undertaken in the field, using a dichotomous key to identify each plant and being careful and consistent with percentage cover estimations ensured all data were correct. However, there may be limitations in that a plant may have been misidentified through human error.
DOI: 10.5285/7f54018c-3071-4213-8cee-78f8bd57977d
title: Nitrous oxide fluxes from an intensively managed grazed grassland in Scotland

description: This data set contains terrestrial fluxes of N2O from an intensively managed grazed grassland in Scotland measured using eddy covariance and chamber methods . The effect of a tillage event and two nitrogen fertilizer applications were investigated by comparing N2O fluxes from two adjacent intensively managed grazed grasslands , one of which was tilled. An eddy covariance system mounted at 2.4 m was used to measure fluxes of N2O, H2O and CO2 using a quantum cascade laser (QCL) gas analyser. Flux measurements were made over a six month period starting at the end of March, 2012. Chamber measurements were also made using both static and dynamic chambers. The data was collected as part of the GHG Platform project AC0116 funded by DEFRA.

description: Eddy covariance raw data from the QCL and sonic anemometer was recorded in tandem using a Labview program. This data was then processed using the Eddypro software version 5.2.1. The data was filtered through a quality control system as described in Cowan, N. J., Levy, P. E., Famulari, D., Anderson, M., Drewer, J., Carozzi, M., Reay, D. S., and Skiba, U. M.: The influence of tillage on N~2~O fluxes from an intensively managed grazed grassland in Scotland, Biogeosciences, 13, 4811-4821, https://doi.org/10.5194/bg-13-4811-2016, 2016.
Raw concentration data for the chamber methods was processed to calculate fluxes. These fluxes were calculated using the HMR package in the statistical environment R.
Met data from the Easter Bush site was collected in 2012 by various methods and quality control was carried out by comparison with nearby met stations.