cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/36795e9d-2380-465c-947b-3c9ae26f92d0
title: Leaf phenology synchrony for Meso- and South America

description: The leaf phenology product presented here shows the amplitude of annual cycles observed in MODIS (Moderate Resolution Imaging Spectroradiometer) normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) 16-day time-series of 2000 to 2013 for Meso- and South America. The values given represent a conservative measure of the amplitude after the annual cycle was identified and tested for significance by means of the Fourier Transform. The amplitude was derived for four sets of vegtation indices (VI) time-series based on the MODIS VI products (500m MOD13A1; 1000m MOD13A2). The amplitude value can be interpreted as the degree in which the life cycles of individual leaves of plants observed within a pixel are synchronised. In other words, given the local variation in environment and climate and the diversity of species leaf life cycle strategies, an image pixel will represent vegetation communities behaving between two extremes: 
* well synchronized, where the leaf bud burst and senescence of the individual plants within the pixel occurs near simultaneously, yielding a high amplitude value. Often this matches with an area of low species diversity (e.g. arable land) or with areas where the growth of all plants is controlled by the same driver (e.g. precipitation).
* poorly synchronized, where the leaf bud burst and senescence of individual plants within a pixel occurs at different times of the year, yielding a low amplitude value. Often this matches with an area of high species diversity and/or where several drivers could be controlling growth.
description: The key underlying method is the Fourier Transform (FT) a well established and efficient methodology to analyse time series data. The FT can be used for the detection of regular cycles, even when hidden in a noisy background and when the time series in question contains data gaps. The FT estimates a power spectrum that indicates the average variance in a time series at different time scales or frequencies. Standard linear de-trending of the data before application of the FT allows an analysis of a 'stationary' time series as the mean and variance should ideally be more-or-less constant. 

We used two approaches to evaluate the amplitude values. The first involved comparing the full extent of the amplitude data grids with the independent International Geosphere-Biosphere Programme (IGBP) land cover map. This was done with histograms showing the distribution of the amplitude values found within each of the IGBP cover classes. The second approach compared published in situ site observations that describe canopy leaf life cycles through leaf flushing and falling, LAI and litter fall or other observations, with the corresponding amplitude values of these sites.
DOI: 10.5285/5e9fe20b-8d00-4bd3-99cb-7989fa781348
title: Wood specific gravity for trees in Ankeniheny Zahamena forest corridor, Madagascar

description: Data comprise wood specific gravity (WSG) and density at 12% moisture content (D12) in wood cores sampled from trees in the Ankeniheny Zahamena forest corridor, the remains of the evergreen forest of eastern Madagascar. The data also include date of sample collection, zone identifier, core identifier, local and scientific tree name, tree height and diameter. Samples were analysed by UFR Sciences du bois de l'ESSA-forêts, Université d'Antananarivo.

Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Work package 4, P4GES project
description: Full materials and methods available from Supporting Information (Manual_4_Wood_Specific_Gravity).

In the field.
Following discussion with local botanist (to find trees that grow locally and to check that local tree names matched scientific tree names) healthy trees, i.e. trees that were neither hollow nor suffering from decay inside the trunk were selected.
15 mm-diameter wood cores were collected using an electric drill powered by a generator (to avoid harvesting trees). Samples were taken at 1.3 m above ground.

In the lab.
To determine the wood specific gravity (WSG) and density at 12% moisture content in the wood cores, a one-centimetre long segment (without bark) from each core was cut. Segments were stabilised in a climatic chamber at 20°C and 65% relative humidity for 7 days to obtain 12% moisture content (MC). Samples were considered stable at 12% moisture content when the weights were constant for 3 consecutive days.
DOI: 10.5285/cf10ea9a-a249-4074-ac0c-e0c3079e5e45
title: Weekly water quality data from the River Thames and its major tributaries (2009-2017)

description: This data set comprises weekly water quality monitoring data of seven sites along the River Thames, UK, and sixteen of its major tributaries from March 2009 to September 2017.  Parameters measured were phosphorus and nitrogen species, dissolved reactive silicon, water temperature, pH, Gran alkalinity, suspended solids, chlorophyll and major dissolved anions (fluoride, chloride, bromide, sulphate) and cations (sodium, potassium, calcium, magnesium, boron).  Dissolved and total iron, manganese, zinc and copper concentrations have also been produced from August 2010 to February 2013.  The accompanying daily river flow data are also supplied.  Samples were taken as part of the UK Centre for Ecology & Hydrology's Thames Initiative monitoring programme. 

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: All water samples were collected by fieldworkers from the Centre for Ecology & Hydrology (CEH), Wallingford.  All chemical analysis was carried out by the Nutrient Chemistry Laboratories at CEH Wallingford.  Daily mean flow data that accompany the data set were produced by the Environment Agency, and downloaded from the National River Flow Archive in January 2019. 

A detailed description of the dataset and how it was produced is given in Bowes MJ, Armstrong, LK, Harman SA, Wickham, HD, et al.  Weekly water quality monitoring data for the River Thames (UK) and its major tributaries: the Thames Initiative research platform. Earth Syst Sci Data (2018) 10(3):1637-1653.  

Interpretation of this data set can be found in the following :
 - Bowes MJ, Gozzard E, Johnson AC, Scarlett PM, Roberts C, Read DS, et al. Spatial and temporal changes in chlorophyll-a concentrations in the River Thames basin, UK: Are phosphorus concentrations beginning to limit phytoplankton biomass? Sci Total Environ (2012) 426: 45-55.  https://doi.org/10.1016/j.scitotenv.2012.02.056
 - Bowes MJ, Jarvie HP, Naden PS, Old GH, Scarlett PM, Roberts C, et al. Identifying priorities for nutrient mitigation using river concentration-flow relationships: The Thames basin, UK. J of Hydrol (2014) 517: 1-12. https://doi.org/10.1016/j.jhydrol.2014.03.063
 - Bowes MJ, Loewenthal M, Read DS, Hutchins MG, Prudhomme C, Armstrong LK, et al. Identifying multiple stressor controls on phytoplankton dynamics in the River Thames (UK) using high-frequency water quality data. Sci Total Environ (2016) 569-570: 1489-1499. https://doi.org/10.1016/j.scitotenv.2016.06.239
DOI: 10.15156/bio/sh0169961.10fu
title: SH0169961.10FU

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: 10.5285/399ed9b1-bf59-4d85-9832-ee4d29f49bfb
title: Daily and sub-daily hydrometeorological and soil data (2013-2023) [COSMOS-UK]

description: This dataset contains daily and sub-daily hydrometeorological and soil moisture observations from COSMOS-UK (cosmic-ray soil moisture) monitoring network from October 2013 to the end of 2023. 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 sensors 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), provide at daily resolution.

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. Snow water equivalents are derived by Python scripts at the end of the day from the hydrometeorological data according to Wallbank et al., 2020. 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 Crop evapotranspiration - Guidelines for computing crop water requirements - FAO Irrigation and drainage paper 56). All data (including raw, quality controlled and derived) is saved in an Oracle database.
DOI: 10.5285/6da95899-f3b8-4089-b621-560818aa78ba
title: Gridded (1km) physical river characteristics for the UK

description: The dataset includes five files of UK physical river characteristics including four files of gridded data at 1km × 1km resolution and one comma separated table. The data includes: 
 - Outflow drainage directions (D8)
 - Catchment areas (km2)
 - Widths of bankfull rivers (m)
 - Depths of bankfull rivers (m)
 - NRFA gauging station locations (easting (m), northing (m))

The comma separated NRFA (National River Flow Archive) gauging station locations table provides the best locations of 1499 river flow gauging stations on the 1km grids, together with the approximate error in the 1km × 1km gridded delineation of the upstream catchment area. All datasets are provided on the British National Grid.
description: The 1km × 1km outflow drainage direction and catchment areas datasets are generated from a 50m × 50m resolution digital terrain: IHDTM (Integrated Hydrological Digital Terrain Model). Bankfull river widths on a 1km × 1km grid are generated using the OS MasterMap Water Network Layer width data in a regression relationship with geomorphic and rainfall characteristics. The 1km × 1km gridded bankfull river depth dataset is generated using observed measurements from a range of sources in a regression relationship with geomorphic and rainfall characteristics. Finally, the NRFA gauging station location dataset on a 1km × 1km grid is generated by identifying the location (easting, northing) on the catchment areas dataset that best represents the true gauging station location. An indication of the quality of these data is provided by the % error between the 1km-derived and the IHDTM catchment areas. See supporting information for more details.
DOI: 10.15156/bio/sh0169962.10fu
title: SH0169962.10FU

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: 10.5285/02c98a4f-8e20-4c48-8167-1cd5044c4afe
title: The Isle of May long-term study (IMLOTS) seabird annual breeding success 1982-2016

description: This dataset contains calculated breeding success rates for six seabird species from representative colonies on the Isle of May, off the East coast of Scotland. Annual breeding success has been measured as the number of chicks fledged per active nest for the Atlantic puffin (Fratercula arctica, since 1982), common guillemot (Uria aalge, since 1982), razorbill (Alca torda, since 1982), European shag (Phalacrocorax aristotelis, since 1987), black-legged kittiwake (Rissa tridactyla, since 1987) and northern fulmar (Fulmarus glacialis, since 1987). The number of active nests recorded are also provided. Data were collected as part of the Isle of May long-term study (IMLOTS), which aims to identify the impact of environmental change on seabirds and their associated ecosystems. This monitoring has been ongoing since 1974, by essentially the same team of scientists, using the same well-documented methods throughout this time.
description: Data were collected by staff of the Institute for Terrestrial Ecology staff, led by Mike Harris, until 2000, when this organisation merged with several others to form the Centre for Ecology & Hydrology (CEH). The same research group has continued the work since then. For each species data were collected on numbers of active nests and numbers of successfully fledged chicks from those nests. The data provided are the success rates for each species for each year, which are calculated as number of successful chicks divided by the number of breeding pairs. The full methodology is available in the contextual metadata, which can be found attached to this record. These data are quality checked by scientific staff as part of their preparation for presentation in annual reports to the Joint Nature Conservation Committee (JNCC), as part of the UK national Seabird Monitoring Programme network. These data should be used after consultation with the appropriate CEH staff.
DOI: 10.5285/ac687a66-135e-4c65-8bf6-c5a3be9fd9aa
title: Long-term multisite Scots pine trial, Scotland: mother tree, cone and seed phenotypes, 2007

description: Phenotypes for Scots pine mother trees and their cones/seed from 21 populations across Scotland in 2007. The seed was used to establish a long-term multisite common garden trial at three nurseries/field sites.
description: Twenty-one Caledonian pinewood populations were visited in 2007 and cones collected from 10 trees (known as ‘mother trees’) per population. Phenotypes (including height, DBH, soil depth, competition and altitude) were recorded for each mother tree. The size and weight of cones (10 per mother tree) and seeds (all seeds within each cone: total number, percentage viability and weight) were also recorded.
DOI: 10.15156/bio/sh0169963.10fu
title: SH0169963.10FU

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/sh0169964.10fu
title: SH0169964.10FU

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: 10.5285/1fb2cda3-cb49-414f-ad84-4a2f88ecce15
title: Historic grassland survey data with contemporary spatial habitat data for semi-natural grasslands across England

description: This dataset compares historic grassland survey data with contemporary spatial data of habitats in England. The NVC community and grassland type were determined for 848 quadrats surveyed at grassland sites in England between 1960 and 1981. A 100m buffer was generated around each individual quadrat which matched the spatial accuracy (±100m) of the quadrat location, to represent a grassland site. These sites were intersected with Natural England's Priority Habitats' Inventory in ArcGIS, to indicate the percentage cover of priority habitats found at the grassland sites in 2013.
description: The historic quadrat data was recorded at grassland sites in England between 1960 and 1981, using a standardised methodology. The vegetation in each quadrat was assigned to one of the British National Vegetation Classification (NVC) communities using Tablefit. Quadrats were further classified into one of four grassland types; calcareous grassland, lowland heath and dry acid grassland, mesotrophic grassland and wet grassland. The location of each quadrat surveyed was imported into ESRI ArcGIS v10. A 100m buffer was generated around each individual quadrat to represent a grassland site. To indicate the coverage of semi-natural grassland habitats in 2013, Natural England's Priority Habitats' Inventory was used. The percentage and type of priority habitat contained within each site was calculated in ArcGIS, using the tabulate intersection function in the spatial analyst toolbox. The percentage of each site designated as a SSSI was also calculated using Natural England's digital boundary data for SSSIs.
DOI: 10.5285/faa526cc-52f5-4468-97bb-295660bcea34
title: Macroinvertebrate taxonomic abundance, water quality, river flow, air temperature and environmental site descriptors from English rivers, 1965-2018

description: This data product combines macroinvertebrate taxonomic abundance for 1,519 monitoring sites across English rivers for the period between 1965 and 2018, with concentrations of 41 water quality determinands, river flow measurements and air temperature derived values. It also includes site variables such as sewage effluent exposure, habitat quality, land cover in the upstream catchment and other physical parameters measured at the sampling point such as altitude, slope, distance from source, width and depth of the channel, and type of substrate.  
Developed as part of the ChemPop (2018-2023), a NERC-funded project investigating the impact of chemical exposure on wildlife populations in rivers, this research output is an open data product for use in a broad spectrum of environmental data and modelling analyses.
description: This data product was created by processing and combining survey data of national extent collected by the Environment Agency (EA), such as freshwater macroinvertebrate survey data, water quality data, habitat quality metrics and river flow; as well as datasets produced by UKCEH such as Land Cover Map 2015, CHESS-met air temperature and estimated sewage effluent exposure. 
The spatial distribution of this product matches the spatial extent of the macroinvertebrate data. Its time stamps correspond to the dates of macroinvertebrate sampling. The completeness of this product is determined by the spatio-temporal availability of the data sources.
Due to the different data structures and file formats of the data sources, a range of data processing tools was used. However, the same methodology of processing and integration was followed. This involved three steps: first, spatial matching of sampled locations along the river network; second, spatial integration of model-generated variables, including wastewater effluent, land cover and air temperature; and third, temporal matching of environmental observations, such as water quality concentrations and river flow, along with modelled variables such as air temperature.