Keyword

Biota

1257 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
Scale
Resolution
From 1 - 10 / 1257
  • Agilent gene expression microarrays (Bham Chlamydomonas reinhardtii Agilent-029192 15k v1) were used to profile transcriptional changes afeter exposure of Chlamydomonas reinardtii algae to cerium dioxide nanoparticles. The data are generated from NERC-funding but not held by EIDC. This data is held by ArrayExpress with accession reference E-MTAB-2454.

  • This data is NERC-funded but not held by the EIDC. This data is archived in the NCBI Sequence Read Archive (SRA). The dataset contains unprocessed single cell sequence from hemocytes in Drosophila melanogaster populations highly resistant or highly susceptible to the parasitic wasp Leptopilina boulardi. Wild caught D. melanogaster females were collected from Cambridge, UK, to establish an outbreed population. From this, three replicated populations were selected for resistance to L. boulardi strain NSRef for 26 generations (Selection). Another three populations were maintained in the laboratory for 26 generations without being exposed to parasitoid-associated selection pressures (No Selection). At generation 26, second instar D. melanogaster larvae (48-63 hours after fertilization) from each population were infected with L. boulardi for three hours (Infection) or maintained without infection (No infection). 48 hours after, circulating hemocytes from third instar D. melanogaster larvae (96-111 hours after fertilization) from each population were collected in PBS and cleaned in OptiPrep solution (1.09g/ml). 10X Single Cell GEX v2 libraries were prepared and sequenced. CellRanger v2 was used to generate sample cell count matrices. Seurat v3 was used to integrate, normalise and cluster the cell types.

  • Genotype-by-sequencing and chloroplast genome sequencing were carried out for 192 accessions of wild and landrace wheat accessions. This produced 10 nuclear DNA sequences, each 10-20 kb in length, and one 80 kb chloroplast DNA sequence, from each of 192 accessions of wild or domesticated emmer wheat. NB The data are stored in the European Nucleotide Archive (ENA) with accession number Study PRJEB42105 ena-STUDY-UOM-23-08-2017-14:32:05:787-517 and can be accessed at https://www.ebi.ac.uk/ena/browser/view/PRJEB42105

  • Data comprise plot location (latitude, longitude, elevation), taxonomic family and species names and measurements of trees (diameter, height, health). Presence of lianas (vines) and their measurements were also recorded. Funder: NERC - Brazil (CONFAP) Newton Fund: “Dry forest biomes in Brazil: biodiversity and ecosystem services” (NE/N000587/1) Full details about this dataset can be found at https://doi.org/10.5285/aa3babe9-072c-42ce-9ea5-9dbb921a922d

  • Samples were collected from the slurry tank of a 200-cow dairy farm in the East Midlands once per month between June and October 2017 (n=5). Triplicate extractions were performed on each sample using two extraction kits: PowerFecal Kit (Qiagen) and Isolate II Fecal DNA kit (BioLine) (30 extractions in total). DNA was quantified using a Qubit fluorometer (Invitrogen) while quality was assessed via Nanodrop (ThermoFisher). Extracted DNA was stored at 4˚ C pending sequencing. Metagenomic shotgun sequencing of extracted slurry DNA was performed and demultiplexed by Edinburgh Genomics using the Illumina NovaSeq platform (150bp paired end library). Viral metagenomes were prepared firstly by homogenising cattle slurry in PBS. The homogenate was ultracentrifuged to pellet unwanted solids and bacteria. To further remove bacteria, the supernatant was passed sequentially through 0.45um and 0.22um filters. The filtrate was concentrated on an Amicon column and DNA was extracted using a standard phenol-chloroform extraction. Sequencing was conducted using Illumina Novaseq with a 2x150bp library. This data is NERC-funded but not held by the EIDC. This data is archived in the European Nucletotide Archive.

  • The data describe: Genome sequencing of desiccating bdelloid rotifers Population genomics of bdelloid rotifers Comparative genomics of bdelloid rotifers: evaluating the effects of asexuality and desiccation tolerance on genome evolution This data is NERC-funded but not held by the EIDC. This data is archived in the Environmental Nucleotide Archive

  • This data set includes longitudinal occurrence of bird species at 36 forest plots – half of which burned during the 2015-16 El Niño drought – distributed across a gradient of prior human disturbance in the Brazilian Amazon. Data was collected in 2010 and 2016 (around 6 years before, and one year after the 2015-16 El Niño, respectively) as part of the projects ‘Assessing ENSO-induced Fire Impacts in tropical Rainforest Ecosystems’ (AFIRE) and ‘Biodiversity and Ecosystem Functioning in degraded and recovering Amazonian and Atlantic Forests’ (ECOFOR), within the NERC Human-Modified Tropical Forest (HTMF) programme. Full details about this dataset can be found at https://doi.org/10.5285/4b05caee-a3c8-46a7-b675-e5a94554bd9f

  • A measure of the extent and complexity of riprian vegetation upstream of chalkstream sites derived from Light Detection and Ranging (LiDAR) data for 15 discrete chalkstreams distributed along a white chalk geology extending from Dorset in the south west, through Wiltshire, to Hampshire in the north east. For each site there is an estimate of the minimum, maximum, mean and standard deviation height of vegetation along the banks for a range of distances upstream from the sampling location. Information on the extent and complexity of riparian vegetation upstream of chalkstream sites were used to better understand the relationships between in-stream biological communities and catchment and riparian land use. Stream sites surveyed represented a sample of chalkstreams across a gradient of catchment land cover intensification from catchments dominated by extensive calcareous grassland and woodland to those dominated by arable and improved grasslands. LiDAR data were obtained from the Environment Agency in April 2014. This dataset was created as part of work package 3.1 of the Wessex Biodiversity & Ecosystem Service Sustainability (BESS) project. Full details about this dataset can be found at https://doi.org/10.5285/49792936-9f11-4df6-98b3-9a9de595ee69

  • The dataset includes data on vegetation composition, flower counts, berry availability over winter, pollinator visitation rates, invertebrate, hedge structure and hedgerow regrowth from a set of long running hedgerow experiments. There were three experiments in total. Experiment 1 was based in Monks Wood, Cambridgeshire, and was used to investigate the long-term effects of timing and frequency of cutting on resource provision for wildlife. Experiment 2 was based at 5 sites across Oxfordshire, Buckinghamshire and Devon and was used to investigate the effect of timing, intensity and frequency of hedgerow cutting. Experiment 3 was based at 5 sites across Cambridgeshire, Northamptonshire, Buckinghamshire and Oxfordshire and was used to investigate the effects of different rejuvenation techniques on hedgerows. All three experiments were randomised plot experiments (full details of plots and their treatments can be found in the supporting documentation. The majority of the data was collected between 2010 and 2016 but for one experiment there is data from 2005. The long running hedgerow experiments had two linked aims focused on management to maintain and restore the hedgerow resource under the agri-environment schemes: • to examine the effects of simple cutting management regimes promoted by Entry Level Stewardship (ELS) and Higher Level Stewardship (HLS) on the quality and quantity of wildlife habitat, and food resources in hedgerows; and • to identify, develop and test low-cost, practical options for hedgerow restoration and rejuvenation applicable at the large-scale under both ELS and HLS. This research was funded by Defra (project number BD2114: Effects of hedgerow management and restoration on biodiversity) and managed by the UK Centre for Ecology & Hydrology (UKCEH). Full details about this dataset can be found at https://doi.org/10.5285/95259623-f0b6-4328-a0e3-4aec09ede5b5

  • This dataset includes laboratory and field measurements of carbon fluxes and spectral reflectance for peatland vegetation including Sphagnum species. It also includes satellite data relating to the development and use of a Temperature and Greenness (TG) model, and an annual Temperature, Greenness and Wetness (TGWa) model. The laboratory data includes Gross Primary Productivity (GPP) and respiration data from samples of Sphagnum capillifolium and Sphagnum papillosum which were collected from the Forsinard Flows RSPB reserve (Northern Scotland) and subjected to different rainfall simulations, including total drought, in the laboratory. Spectral reflectance of the samples was also measured throughout the experiment, and the vegetation indices calculated are recorded. The field data includes carbon fluxes and spectral reflectance measurements, in this case taken from collars located at three sites within the Forsinard Flows Reserve during the main growing season of 2017 (March to September). Associated measurements of temperature, Photosynthetically Active Radiation (PAR), and moisture content were recorded. The species composition of the collars is also given in the data. The satellite data include Land Surface Temperature (LST) and Normalised Difference Vegetation Index (NDVI) products from the Moderate Resolution Imaging Spectroradiometer (MODIS) used to develop a TG model over the Forsinard Flows reserve, and the Glencar bog in Ireland. The dataset also includes bands used to calculate the Normalised Difference Water Index (NDWI) to develop the TGWa model. The MODIS data used in the implementation of this model to assess restoration progress, and also upscaling effectiveness, are included in the dataset. The work was carried out during a PhD project part-funded by the NERC SCENARIO DTP (Grant number: NE/L002566/1) at the University of Reading, and part-funded by The James Hutton Institute. Full details about this dataset can be found at https://doi.org/10.5285/ab9f47f9-9faf-4403-a57e-25e31f581ed0