This dataset shows potential carbon storage as modelled for the urban areas of Milton Keynes/Newport Pagnell, Bedford, and Luton/Dunstable, UK. The modelling approach used the ‘InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) 3.1.0’ ecosystem service model suite, raster land cover maps at two spatial resolutions (5 m and 25 m) and published literature values for carbon storage by land cover. The resulting data are presented in the form of two ‘GeoTIFF’ raster map files (and associated metadata and spatial information files required by software) that can be viewed and manipulated in Geographic Information Software. The units are kg C per square meter. The purpose of the modelling was to help assess and visualise the value that urban green space represents to urban residents and natural systems in just one of many ecosystem services. This research was conducted as part of the larger 'Fragments, Functions, Flows and Urban Ecosystem Services' (F3UES) programme. Detailed methods and results of this analysis are published in: Grafius DR, Corstanje R, Warren PH, et al (2016) The impact of land use/land cover scale on modelling urban ecosystem services. Landsc Ecol 31:1509–1522. doi: 10.1007/s10980-015-0337-7. Full details about this dataset can be found at https://doi.org/10.5285/9209af2c-24f6-4e37-98fe-550032e97a2c

This view shows a 1km resolution raster version of the Land Cover Map 2007 for Great Britain. The data consists of 23 bands. Each band represents a target class, broadly representing a Broad Habitat, and within the band each 1km pixel represents a percentage cover value of that class. The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2007 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

Ecological field data for a variety of biodiversity indicators were collected from commercial fields of both crops. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Future policies are likely to encourage more land use under energy crops: principally willow, grown as short rotation coppice, and a tall exotic grass Miscanthus. These crops will contribute to the UK's commitment to reduce CO2 emissions. However, it is not clear how decisions about appropriate areas for growing the crops, based on climate, soil and water, should be balanced against impacts on the landscape, social acceptance, biodiversity and the rural economy. This project integrated social, economic, hydrological and biodiversity studies in an interdisciplinary approach to assessing the impact of converting land to Miscanthus grass and short-rotation coppice (SRC) willows. Two contrasting farming systems were focused on: the arable-dominated East Midlands; and grassland-dominated South West England. Ecological field data for a variety of biodiversity indicators were collected from commercial fields of both crops. The public attidues questionnaire data from this study are available at the UK Data Archive under study number 6615 (see Supplemental). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see Supplemental).

This data contains values of bare sand area, modelled wind speed, aspect and slope at a 2.5 m spatial resolution for four UK coastal dune fields, Abberfraw (Wales), Ainsdale (England), Morfa Dyffryn (Wales), Penhale (England). Data is stored as a .csv file. Data is available for 620,756.25 m2 of dune at Abberfraw, 550,962.5 m2 of dune at Ainsdale, 1,797,756.25 m2 of dune at Morfa Dyffryn and 2,275,056.25 m2 of dune at Penhale. All values were calculated from aerial imagery and digital terrain models collected between 2014 and 2016. For each location, areas of bare sand were mapped in QGIS using the semi-automatic classification plugin (SCP) and the minimum distance algorithm on true-colour RGB images. The slope and aspect of the dune surface at each site was calculated in QGIS from digital terrain models. Wind speed at 0.4 m above the surface of the digital terrain model at each site was calculated using a steady state computational fluid dynamics (CFD). Data was collected to statistically test the relationship between bare sand and three abiotic physical factors on coastal dunes (wind speed, dune slope and dune slope aspect). Vertical aerial imagery was sourced from EDINA Aerial Digimap Service and digital terrain models from EDINA LIDAR Digimap Service. Wind speed data was generated and interpreted by Dr Thomas Smyth (University of Huddersfield). Full details about this dataset can be found at https://doi.org/10.5285/972599af-0cc3-4e0e-a4dc-2fab7a6dfc85

This dataset contains information on activity parameters obtained from automated radiotelemetry data collected on individual birds of six passerine species (European robin, Eurasian blackbird, great tit, blue tit, dunnock, common chaffinch). Birds were caught via mistnetting at 4 sites along a 35 km urban gradient in Glasgow, Scotland, in autumn and winter of two years: 2020 and 2021. Once tagged, each bird was monitored for approximately 3-4 weeks. Raw telemetry data was processed and analysed in order to extract activity traits. The activity traits were: onset of morning activity, end of evening activity, total amount of daily activity. Data were collected to investigate the effects of urbanisation on daily activity patterns, reproductive traits and population dynamics of passerine birds. Full details about this dataset can be found at https://doi.org/10.5285/1b55a4eb-30be-4bd1-9144-cb7f8ba83b4e

Land use/land cover (LULC) map of a 20 km^2 agricultural landscape centred on the Hillesden Estate, Buckinghamshire, UK. The map is based on remote sensed data (LiDAR and hyperspectral sensors) with manual updates and the addition of spring and summer floral cover data from comprehensive field surveys. The remote sensed data was generated in August 2007. The manual updates and summer floral data were from field visits in July and August 2011, and the spring floral data were from field visits in April 2011 and 2012. The map was created as part of a project led by the Centre for Ecology & Hydrology, funded under the Insect Pollinators Initiative. Full details about this dataset can be found at https://doi.org/10.5285/0667cf06-f2c3-45c1-a80a-e48539b52427

Data on resilience of wheat yields in England, derived from the annual Defra Cereals and Oilseeds production survey of commercial farms. The data presented here are summarised over a ten-year time-series (2008-2017) at 10km x10km grid cell (hectad) resolution. The data give the mean yield, relative yield, yield stability and resistance to an extreme event (the poor weather of 2012), for all hectads with at least one sampled farm holding in each year of the time-series (i.e. the minimum data required to calculate the resilience metrics). These metrics were calculated to explore the impact of landscape structure on yield resilience. The data also give the number of samples per year per hectad, so that sampling biases can be explored and filtering applied. No hectads are included that contain data from <9 holdings across the time series (the minimum level required by Defra to maintain anonymity is <5). The data were created under the ASSIST (Achieving Sustainable Agricultural Systems) project by staff at the UK Centre for Ecology & Hydrology to enable exploration of the impacts of agriculture on the environment and vice versa, enabling farmers and policymakers to implement better, more sustainable agricultural practices. Full details about this dataset can be found at https://doi.org/10.5285/7dbcee0c-00ca-4fb2-93cf-90f2a5ca37ea

The study is part of the NERC Rural Economy and Land Use (RELU) programme. This project investigated the links between quality food production and biodiversity protection by asking the question: can production systems that use and maintain biodiverse natural grasslands, translate that into a source of additional product value in the production of meat and cheese and therefore benefit rural economies? The aim was to inverse the conventional understanding of landscape or environmental quality as the outcome of well managed farming to explore the idea of natural grassland biodiversity as an input into more sustainable farming and as an integral component of product quality. This dataset consists of the grassland botanical composition and chemical soil analyses resulting from this project. A botanical field survey of a number of sample grazing sites on selected case study farms records the plant species present within a representative area of phytosociologically homogeneous vegetation and the percentage cover that each species vertically projects onto the ground surface. Soil analyses of sample sites determines soil composition, pH and minerals. Land management, consumer opinion and nutritional data from this study are available at the UK Data Archive under study number 6159 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Northern Ireland. It describes Northern Ireland's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2019 20m classified pixels dataset. All further LCM2019 datasets for Northern Ireland are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value and a range of per-parcel pixel statistics to help assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. 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. Full details about this dataset can be found at https://doi.org/10.5285/6e67cba0-c872-4146-bc09-d6c98731f3b3

This dataset contains information on reproductive events of blue and great tits recorded by manually inspecting approximately 300 to 500 nestboxes annually along a 35 km urban gradient in and around Glasgow, Scotland from 2014 to 2022. The datasets contain annually aggregated values per nestbox on clutch initiation, clutch size, number of hatchlings and fledglings. Data were collected to investigate the effects of urbanisation on daily activity patterns, reproductive traits and population dynamics of passerine birds. Full details about this dataset can be found at https://doi.org/10.5285/bb13cc09-5d6c-4f6a-bda8-de1915fa3cc0