cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/49ae11ec-e4e5-4e4a-b091-976d18c4ee3e
title: National-scale geodatabase of catchment characteristics in the Philippines

description: This dataset contains a national-scale geodatabase of stream network and river catchment characteristics in the Philippines. It presents detailed information on 128 medium- to large-sized catchments (catchment area > 250 km2). The quantitative descriptions provide context for enabling geomorphologically-informed sustainable river management. The geodatabase provides a baseline understanding of fundamental topographic characteristics in support of varied geomorphological, hydrological and geohazard susceptibility applications.

Data sets include:
 1) GIS shapefiles with river catchment properties;
 2) GIS shapefiles with stream network properties;
 3) spreadsheets containing morphometric and topographic characteristics (n = 91);
 4) example MATLAB code and topographic data to replicate the analysis for a selected catchment.

The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312/1.
description: The analysis used a nationwide digital elevation model (DEM) acquired in 2013 and generated through airborne Interferometric Synthetic Aperture Radar (IfSAR), with a 5 m spatial resolution and 1 m root-mean-square error vertical accuracy.
Catchment and stream network properties were calculated using TopoToolbox V2.

The web-application was designed using the ArcGIS Web AppBuilder.

The data set is fully described in Boothroyd et al. (2023) https://doi.org/10.1371/journal.pone.0281933 .
DOI: 10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f
title: The percentage of total pasture land, by country, subject to water scarcity in 2050 as estimated from a multi-model ensemble

description: This dataset contains the percentage of the total pasture area in each country classified as vulnerable to water scarcity (annual run-off is declining and the water shed is defined as water scarce in 2050). Projections of global changes in water scarcity with the current extent of pasture land were combined to identify the potential country level vulnerabilities of pasture land to water scarcity in 2050. The data relate to an analysis of the impact changes in water availability will have on pasture availability in 2050.
description: Global maps, of the change in annual runoff (%) and water scarcity (index value between 1and 4, where 1 represents not water scarce and 4 is severely water scarce) were as estimated based on projections from five different general circulation models/ global climate models (GCMs) were obtained directly from Prof. N. Arnell (University of Reading).

Global maps of the current cropland area were directly downloaded from www.earthstat.org, which is an open access platform that hosts the most up to date versions of data. Maps of croplands were created based on a mixture of satellite derived data mixed with national, state and country census statistics, and were expressed on a global 5 arc-minute grid.

Data used in this study was collected from several sources and cited in the supporting documentation.
DOI: 10.5285/f5f85f15-8f3a-474c-ae58-7cdeab2a53ca
title: Water chemistry samples from Durleigh Reservoir 2018

description: This dataset contains water chemistry and phytoplankton cell counts collected from 3 different depths at 3 different sites in Durleigh Reservoir in Somerset, England, during 2018. Water samples were collected on 22 Feb, 5 Apr, 20 Apr, 30 May, 13 Jun, 27 Jun, 9 Jul, 24 Jul, 20 Aug, 21 Aug, 22 Aug, 23 Aug, 24 Aug, and 5 Oct 2018. The data available to download includes phytoplankton cell counts (cells/ml), turbidity (NTU), pH, Ammonia (mg/l), total oxidised nitrogen (mg/l) nitrite (mg/l), nitrate (mg/l), ammonium (mg/l), orthophosphate (mg/l), silica (mg/l), Potassium (mg/l), Calcium (mg/l), Geosmin (ng/l), 2-MIB (ng/l), total and soluble manganese, iron, copper, magnesium, zinc, and aluminium (all: mg/l). 
description: The 3 sampling locations varied in water depth and distance from artificial mixing devices (surface mixers) in Durleigh. Location 1 was closest to the surface mixers (25 m) and deepest (6.6 m on 22 February 2018). Location 2  was 60 m from the surface mixers and 6 m deep (22 February 2018). Location 3 was 435 m from the surface mixers and the shallowest at 4 m deep on 22 February 2018. A boat was used to access all sampling locations, which were each marked by a buoy. On 5 April 2018, access to location 3 was not possible, hence missing values in the dataset. Water samples were collected from the surface, middle, and bottom of the water column using a Van Dorn sampler. Water samples were analysed at Wessex Water Scientific Centre, Saltford.
DOI: 10.5285/87412c44-f11a-4182-b182-47d872ad7ebd
title: Ozone flux, dynamic global vegetation, and carbon storage modelled data of tropical forests using the Joint UK Land Environment Simulator (JULES), 1900-2015

description: This dataset includes spatially-explicit input, output and summary data from the use of dynamic global vegetation model, the Joint UK Land Environment Simulator (JULES V5.6). This includes the spatial extent of extant, current-secondary and potential- secondary forests, as well as both preindustrial (1900-1910) and recent (2005-2014) average O3 concentrations resampled at a spatial resolution of 1.25 deg latitude by 1.875 deg longitude. Output data includes the modelled impact of O3 on net-primary productivity (NPP) of tropical forests under current O3 concentrations as well as the cumulative impact on the global carbon cycle. 

This dataset was created to model predicted impacts of ozone (O3) on tropical forests across the globe between 1900 and 2015, and is supported by NERC PROJECT:  NE/R001812/1 Ozone impacts on tropical vegetation; implications for forest productivity (Trop-Oz).
description: These data were produced using the Joint UK Land earth simulator (JULES v5.6) run on the UK's JASMIN computer facility.

Model simulations were run assuming a homogeneous O3 susceptibility of tropical trees to one of the three levels identified (i.e. low, moderate, high) by associated empirical work. Simulations prescribed dynamic vegetation, allowing Plant functional type (PFT) fractional cover and Leaf Area Index (LAI) to change with varying environmental conditions over the last century. Standard inputs across simulations included variation in [CO2] and land-use land-cover change as used in the Global Carbon Budget 2020, meteorology and forcing data from CRU-JRA v 2.3 with either pre-industrial O3 concentrations or a transient O3 concentration supplied by UKESM1 part of Coupled Model Intercomparison Project Phase 6 (CMIP6). Model simulations were compared to standard models used as part of the CMIP6 with runs including static or transient O3 being compared to determine the impact of change in O3 between 1900 and 2015 on NPP and thereby the terrestrial carbon stocks.
DOI: 10.5285/b86585cf-76cd-42c8-8db9-57ebc750f1de
title: Daily automatic weather station (AWS) data from Climoor fieldsite in Clocaenog Forest 2022-2023

description: This dataset holds daily data from one automated weather station (AWS) located at the Climoor field site in Clocaenog forest, North East Wales. The data are on relative humidity (percent), air temperature (degrees Celsius), rainfall (millimetres), air pressure (millibars), net radiation (millivolts), solar radiation (kilowatts per square metre per second), photosynthetic active radiation (PAR; micromol per square metre per second), wind speed (metres per second) and wind direction (degrees).

The data is an extension for the AWS datasets 1999-2015, 2015-2016 and 2016-2021 covering the time period January 2022 to December 2023. Data are logged in minute intervals, averaged to half-hourly. The data are sent from the field site to a UKCEH server. A working copy is created, quality assurance checks carried out and daily averages calculated from half-hourly records. Data which were not recorded are marked with “NA”, faulty data were replaced by “-9999”. Note, the rainfall sensor was broken during this time period, but the column is kept in the datafile for consistency with previous data records. Data collection, processing and quality checking was carried out by members of UKCEH staff.

The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes. The reported data are collected to monitor site specific environmental conditions and their development over time. These data are important to interpret results that are collected from the climate change manipulations imposed in the field.

description: Data were recorded every minute, then automatically averaged to half-hourly data by the data-logger. The half-hourly data were transferred from loggers at the field site onto UKCEH Bangor servers via remote telemetry. Each morning, the previous day’s data was transferred to the server. Data were then averaged to daily values. An automated script transferred the data into the project shared area of the shared network drive. Data quality checking was performed at the end of each calendar year. Telemetered data were processed using R. Data were averaged to daily values and inspected visually. Erroneous values were removed taken into account the annual cycle. A .csv file was produced from the quality assessed data. The following measures were taken with sensors from Campbell Scientific: relative humidity and air temperature are recorded with an HMP45C sensor. Rainfall sums are measured with an ARG100 Tipping bucket, air pressure is measured with a CS100 Barometer and net radiation is measured with an NR-Lites sensor. Further, Solar radiation and PAR are measured using a Skye SP1110 pyranometer and a SKP215 quantum sensor from Skye Instruments. Wind direction and speed are recorded using a windsonic 2D Ultrasonic Anemometer from Windsonic.
DOI: 10.5285/03d36ac4-4cf4-46d9-a608-866ba0aab458
title: Mealworm predation rates in Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) plots, Kandista and Ujun Tanjung estates, Indonesia

description: Data comprise mealworm predation rates measured after 24 hours exposure to invertebrates in mature oil palm (2014), and mature and replanted oil palm (2016-2017) plots as part of a large-scale ecological experiment programme (the Biodiversity and Ecosystem Function in Tropical Agriculture project, established in 2013). Eighteen plots were examined across three estates - plots in Ujung Tanjung and Kandista estates were planted in 1987 to 1992 and are mature or over-mature oil palm, while Libo plots (2016-2017 dataset only) were replanted in 2014. Plots were organised in triplets and in in Ujung Tanjung and Kandista, for each triplet one plot was assigned to each of three vegetation treatments: Reduced vegetation cover, normal vegetation management and enhanced vegetation cover. Freshly-killed mealworms (larvae of darkling beetles, Tenebrionidae sp.) were glued onto oil palm fronds trimmed so that ca. 10 cm of each of six leaflets remained. Exclusion and stratum treatments in factorial combinations were applied: caged and uncaged, canopy and ground. The cage exclusion treatments were designed so that most invertebrates could access the fronds but vertebrates could not.
description: Predation was measured three times in mature oil palm 2014 and six times in both mature and replanted oil palm during 2016-2017. The basic unit for the predation tests was six freshly-killed mealworms (larvae of darkling beetles, Tenebrionidae sp.) glued onto a piece of oil palm frond which had been trimmed so that ca. 10 cm of each of six leaflets remained. Exclusion and stratum treatments were applied in factorial combinations: caged and uncaged, canopy and ground. The cage exclusion treatment was designed such that most invertebrates could access the fronds but vertebrates could not: rat traps held closed with one frond unit inside and one tied to the outside as a control. The traps were metal grid boxes approximately 35 x 20 x 14 cm, with no holes wider than 1cm. One was hoisted into the palm crown while the other was placed at the edge of the harvesting circle under the same palm, to test whether predation rates varied with vertical stratum. Three sets of treatment combinations were placed in each plot, using palms selected by random-number generator. Samples were placed out in the field for approximately 24 hours before being assessed. Basic data checks were carried out (checks for impossible values, such as 11 of 10 seeds remaining). We have error-checked 50% of the data entry against the original field sheets, finding an acceptable error rate of <1% and correcting errors when we encountered them. All changes were recorded and that information remains with the dataset.
DOI: 10.5285/33a66d6a-dd9b-4a19-9026-cf1ffb969cdb
title: Traits data for the butterflies and macro-moths of Great Britain and Ireland, 2022

description: Here, we present a comprehensive traits database for the butterflies and macro-moths of Great Britain and Ireland. The database covers 968 species in 21 families. Ecological traits fall into four main categories: life cycle ecology and phenology, host plant specificity and characteristics, breeding habitat, and morphological characteristics. The database also contains data regarding species distribution, conservation status, and temporal trends for abundance and occupancy. This database can be used for a wide array of purposes including further fundamental research on species and community responses to environmental change, conservation and management studies, and evolutionary biology.

A more recent version of the dataset is available at https://doi.org/10.5285/dbc7cc17-cbbd-49dd-bab4-8e8855768d66 entitled 'Traits data for the butterflies and macro-moths of Great Britain and Ireland, 2024'.
description: Data were collated from a range of referenced sources as described in the metadata. Where required expert opinion was used to determine traits, for example regarding habitat.
DOI: 10.5285/efa2a84b-3505-4221-a7da-12af3cdc1952
title: Bulk density, carbon and nitrogen content in soil profiles from permafrost in subarctic Canada

description: This dataset consists of measurements of bulk density, carbon and nitrogen content in soil profiles from permafrost in subarctic Canada. Soil cores were sampled during early summer in 2013 and 2014. Soil cores were sampled from a peatland plateau and thawing features of the peatland plateau, and from an unburnt and burnt black spruce forest, and additional sites in Yukon and Northwest Territories.
description: Soil cores were cut and samples were analysed for bulk density, carbon and nitrogen content. Samples were freeze dried and weighted to calculate bulk density. Values of bulk density are expressed in grams of dry soil per cm3 of wet soil. For carbon and nitrogen content, a ground sample was weighted and combusted in a C and N analyser. Standards were analysed in each run and a batch specific calibration was used to calculate the carbon and nitrogen content of the samples. Values of carbon and nitrogen content are expressed as percentage of dry soil mass.
DOI: 10.5285/58b248a8-6e34-4ffb-ae32-3744566399a2
title: UK ecological status map version 2

description: A spatial indicator of ecological status for valuation of biodiversity across the UK, based on species occurrence records for eleven taxonomic groups (Bees, Birds, Bryophytes, Butterflies, Carabidae, Hoverflies, Isopoda, Ladybirds, Moths, Orthoptera and Vascular plants) was developed. UK species occurrence data were collated from the Biological Records Centre (BRC). The mean ecological status was calculated across all taxonomic groups for the 2000 to 2013 time period, relative to the species richness maximums from the 1970-1990 time period. This version supersedes the dataset "UK ecological status map".
description: UK species occurrence data were collated from the Biological Records Centre (BRC). Data were gathered for 11 taxonomic groups (Bees, Birds, Bryophytes, Butterflies, Carabidae, Hoverflies, Isopoda, Ladybirds, Moths, Orthoptera and Vascular plants) at the 10km2 scale (hectad) over two separate time periods: 1970 to 1990 and 2000 to 2013. Bird species occurrence data for the breeding birds of the UK were acquired from the British Trust for Ornithology (BTO). We used data corresponding to the two time periods defined above, taken from the bird atlases of 1976 and 2001-2011 respectively. Estimating species richness and measuring ecological status: Separate analyses were undertaken for both time periods within each taxonomic group. For each hectad we compiled a species list and calculated species richness. We then applied a recently developed method (FRESCALO; Hill 2012) to account for the variation in recorder effort within different hectads. The ecological status of each hectad was calculated using a relative measure of estimated species richness. Each hectad was assigned to an environmental zone, determined by land cover type, climate, geology and topography. We assigned zones using the 2007 ITE land classification (Bunce et al. 2007), according to the dominant ITE land class (45 classes in total) present in individual hectads. A reference list of potential species was then compiled for each environmental zone, and the estimated species richness for any given hectad was compared as a proportion to the list of species that could potentially be there. The mean ecological status was calculated across all taxonomic groups for the 2000 to 2013 time period, relative to the species richness maximums from the 1970-1990 time period.
DOI: 10.5285/93207428-aace-4bb5-9073-2eb44ad632d1
title: Topsoil invertebrate density estimates from the Countryside Survey of Great Britain, 2007 using a generalized additive model

description: This dataset presents modelled estimates of soil invertebrate density (individuals m-2) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil invertebrate density data from 2007 and including climate, habitat, soil and spatial predictors. The model is based on soil invertebrate density data from 830 locations across Great Britain and is representative of 0-8 cm soil depth. Soil invertebrates were extracted from cores using a dry Tullgren extraction method and enumerated by microscope. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. 

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: The data used to model soil invertebrate density are taken from the Countryside Survey. The technical reports by Emmett et al. (2010) present full methodological details for the Countryside Survey soil sampling and analytical processes, and can be found at: 

http://nora.nerc.ac.uk/id/eprint/9354/1/CS_UK_2007_TR9.pdf
DOI: 10.5285/78c64025-1f8d-431c-bdeb-e69a5877d2ed
title: Energy and carbon dioxide fluxes, meteorology and soil physics observed at INCOMPASS land surface stations in India, 2016 to 2017

description: Eddy covariance (EC) observations of surface-atmosphere exchanges of sensible heat and latent heat, momentum and net ecosystem carbon dioxide exchange were measured at thirty minute resolution at three Land Surface Stations in India. 

The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. Meteorological observations include: the net radiation and its incoming and outgoing short- and long-wave components, air temperature, barometric pressure, relative humidity, wind speed and direction, and rainfall. Soil physics observations include: Soil heat fluxes, soil temperatures and soil volumetric water content.

Observations were collected under the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) Project between January 2016 and January 2018.
description: EC, weather and soil physics observations were collected using identical instrumentation at all three INCOMPASS Land Surface Stations. Quality Control of EC data involved removal of statistical outliers and tests that theoretical requirements for the successful application of the EC technique were not violated significantly. Quality control (QC) of meteorological variables included range checking and visual checks for spikes, dropouts and other clearly erroneous values. 

Further details are available in the supporting documentation.
DOI: 10.5285/b984a173-8d80-4781-8a53-bef7bcb0d198
title: Habitat suitability maps for Rhododendron ponticum across Scotland as reservoir host for Phytophthora

description: These spatial layers quantify the predicted habitat suitability for Rhododendron ponticum across Scotland. These layers were developed with reference to this species role as reservoir host for Phytophthora plant pathogens, but should have value for management of Rhododendron ponticum as a problematic invasive species. The models were developed by combining biological records of R. ponticum with climate, soil, elevation and woodland cover data. The dataset contains averaged estimates for R. ponticum presence, associated standard deviation for each estimate and locations where environmental conditions in the study region strayed too far from the training set data. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forest Research, Forestry Commission and Centre for Ecology & Hydrology (CEH).
description: Alexandra Schlenzig at SASA provided advice on premise types. Jim McCleod and Steve Albon from the Macaulary Land Use Research Institute provided the soil data. Prof. David Rogers and the Spatial Ecology and Epidemiology Group at Oxford University provided the MODIS data. Adam Butler at Biomathematics and Statistics Scotland (BioSS) provided statistical advice. Local Record Centres and their contributing biological recorders provided the R. ponticum data. Based on previous empirical studies of the habitat associations of R. ponticum, seven environmental predictors were selected apriori for modelling. R. ponticum data and environmental data were to run the Maximum Entropy (MaxEnt; version 3.3.3e) model. MaxEnt was selected to create the suitability maps from amongst Species Distribution Model techniques because it is specialised for presence-only biological records and is consistently competitive with the highest performing methods. More details on the data and model can be found in the supporting documentation.