Marine fish, algae and invertebrate invasive alien species (IAS) data from Akrotiri and Dhekelia, Cyprus. Data were collected during an 19-month monitoring period starting in February 2017 and ending in September 2018. Sampling occurred seasonally, approximately once every 3 months, and used an underwater visual census (UVC) method. The UVC involved divers swimming at a steady pace along three 25m transects, with each transect separated by a 5m gap. The transects were randomly placed, covering a variety of habitats such as seagrass beds and rocky habitats where possible. Fish species were recorded and abundance estimated within 2.5m on each side of the transect. Benthic species (algae and invertebrates) were recorded from quadrats placed every 1m along each 25m transect. Sampling carried out by the University of Cyprus and volunteer divers from the Western Sovereign Base Area Sub Aqua Club as part of a Defra Darwin Initiative Plus project to ascertain baseline data on native and non-native marine species in the Sovereign Base Area of Akrotiri. Full details about this dataset can be found at https://doi.org/10.5285/519d42bf-51cc-42a4-8673-5f2044cfa19a

Data are presented showing grass productivity as grammes per 100 square centimetres under four different nutrient treatments (water, nitrogen, phosphorus and nitrogen & phosphorus combined). An experimental hillslope in the Conwy catchment was selected in August 2016. Three transects, were identified across the hillslope. Along each transect, a 1 x 1 square metre quadrat was used to delineate randomly selected sampling areas. Within each quadrat 5 individual 10 x 10 x 10 centimetre (cm) swards were collected using a spade and transported to the laboratory in Bangor University for the nutrient addition. Three different harvests at different stages (initial cut, first harvest, second harvest) were conducted in order to measure grass productivity. Harvest included removal of all vegetation within the quadrat down to approximately 1 cm in height. The data were collected to identify the nutrient limitations within the hillslope by trained members of staff from Bangor University and the Centre for Ecology & Hydrology. The data were collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at https://doi.org/10.5285/6e395915-ab5c-43f4-b4de-c9a3c5c1b956

The data within this repository contains results from IODP-ICDP Expedition 364 which drilled the Peak Ring of the Chicxulub Crater, offshore Mexico. The offshore phase of this expedition occurred in April-May 2016, while the onshore phase occurred in October 2016. Further details of the IODP expedition can be found in the expedition report (https://doi.org/10.14379/iodp.proc.364.2017). The data within the repository is sorted into 4 separate folders: 1 - Optical_Images 2 - SEM_Image_Processing 3 - UStage 4 - Numerical_Models 1 - Optical_Images This folder contains two sub-folders: Optical_WholeSection, which contains whole thin-section plane- and cross-polarised stitched images of thin sections from Hole M0077A, acquired using a Zeiss optical microscope at 4x magnification at Curtin Univesity, Perth. Section names follow IODP standard sample naming convention. Optical_Photos, which contains sub-sub-folders delimiting samples, each of which contains individual images of features of interest in thin sections from Hole M0077A, magnification and a brief description of the feature are indicated by the file name and scale bars are provided on the image. 2 - SEM_Image_Processing This folder contains 10 sub-folders, specific to the individual analysed section. Each sub-folder contains a whole thin-section Back-Scattered Electron (BSE) Scanning Electron Microscope (SEM) stitched tiff image with a pixel width of 750nm. Data was acquired using a Zeiss Ultra Plus SEM at the NHM London. The images were then processed to analyse pore spaces within the thin sections. All folders contain a text file called “TOTAL.txt” which records data from every pore within the thin section. If the thin section contained any cataclasite bodies, two additional text files “CATACLASITE.txt” and “CATACLASITE_TOTALAREA.txt” can be found, the former contains the pore analysis of the selected cataclasite area, the latter indicates the size of the selected cataclasite area. All image analysis was carried out using the ImageJ software package. 3 - UStage This folder contains one .xlsx file that summarises the results of universal-stage optical microscope analysis of quartz planar deformation features of thin sections within hole M0077A. 4 - Numerical Models This folder contains 5 text files. “asteroid.inp” and “material.inp” are the input model parameters of the iSALE shock physics code (http://www.isale-code.de/redmine/projects/isale), these inputs were used to model the Chicxulub impact. Post-processing of the data was achieved using python to track the Stress-Strain-time paths of peak ring material, the remaining three .txt files contain the results of that analysis at different temporal resolutions.

The data contains site characteristics (water body type, elevation, catchment area) and water chemistry data (pH, dissolved and particulate organic carbon concentrations (DOC and POC)). The composition of DOM extracted by different methods was analysed by elemental analysis; there are data for carbon, hydrogen and nitrogen content. The dataset result from an experiment to determine the reliability of various methods to extract dissolved organic matter (DOM) from freshwaters in the UK. Full details about this dataset can be found at https://doi.org/10.5285/3c77e7bf-78a0-433c-b260-b630e9a36cc0

General soil chemical, physical and microbial properties are presented for soil samples at six depths collected from a field experiment in the Conwy catchment. Samples were collected in May 2015. Core samples were taken along three transects by trained members of staff the Centre for Ecology & Hydrology and Bangor University. General soil chemical, physical and microbial properties were measured at six depths by trained members of staff, using recognised procedures at the laboratories of the School of Environment, Natural Resources and Geography, Bangor University. The samples were taken to provide supporting information for assessing the relationship between soil microbial populations and soil properties. The data were collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at https://doi.org/10.5285/f7b2beaa-08cf-48db-9b07-c55118d11506

This set of data includes records of vegetation species and characteristics, soil quality metrics and aspects of farm management relating to a single field on each sampled farm. Data were collected in 2018, from farms across Great Britain belonging to the Pasture Fed Livestock Association (PFLA). The data were collected by the UK Centre of Ecology & Hydrology, during a project funded by the BBSRC, seeking to evidence the impacts of pasture fed livestock approaches on grassland parameters, in particular, sward composition and associated soil qualities. Full details about this dataset can be found at https://doi.org/10.5285/78ca9a01-107b-4f33-8561-9c3e64db7e02

This web map service shows bee nectar plant richness across Great Britain . The source data uses counts of bee nectar plants in Countryside Survey area vegetation plots in 2007 and extrapolates to 1km squares across GB using a generalised additive mixed model. Co-variables used in the model are Broad Habitat (the dominant broad habitat of the 1km square), air temperature, nitrogen deposition, precipitation and altitude. The map has the following layers: plantCount = a modelled estimate of the count of all bee nectar plants within a 1km by 1km square, SEM = a measure of the variance of the plantCount attribute Understanding the distribution of bee nectar plants does provide valuable information on the potential distribution of pollinators and hence pollination.

Data comprise monitoring records of a population of Gryllus campestris, a flightless, univoltine field cricket that lives in and around burrows excavated among the grass in a meadow in Asturias (North Spain). The area has an altitude range from around 60 to 270 metres above sea level. The data include birth and death days, age at capture, air temperature and calling activity. Data were collected from 2006 to 2016. Full details about this dataset can be found at https://doi.org/10.5285/5c8c8f74-5287-4251-87f7-2b965b400624

This dataset is a product of the raw HEA (household economy approach) data that were collected in sixteen communities in the Katakwi district, and the raw IHM (individual household method) data that was collected with 42 households in the community of Anyangabella, and 51 households in the community of Kaikamosing. These data were collected in December 2020 and shows the crop calendars of the Katakwi district. These data consist of quantitative information relating to crop and fishing production timelines throughout a typical agricultural year. The data were collected to support the analysis of vulnerability levels of different to further support livelihood impact modelling, and the development of targeted policies to support resilience at household and community level. The data collection team comprised of local, Ugandan partners. All data were collected in the local language and translated into English. Full details about this dataset can be found at https://doi.org/10.5285/d91bd655-ad51-42c1-a8d0-91923246244b

This web map shows positive plant habitat condition indicators across Great Britain (GB). This data provides a metric of plant diversity weighted by the species that you would expect and desire to have in a particular habitat type so indicates habitat condition. In each Countryside Survey 2007 area vegetation plot the number of positive plant habitat indicators (taken from a list created from Common Standards Monitoring Guidance and consultation with the Botanical society of the British Isles (BSBI)) for the habitat type in which the plot is located are counted. This count is then divided by the possible indicators for that habitat type (and multiplied by 100) to get a percentage value. This is extrapolated to 1km squares across GB using a generalised additive mixed model. Co-variables used in the model are Broad Habitat (the dominant broad habitat of the 1km square), air temperature, nitrogen deposition, sulphur deposition, precipitation and whether the plot is located in a Site of Special Scientific Interest (SSSI) (presence or absence data).