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  • This data collection results from abundance surveys of 7 species of weeds in ca. 500 lowland arable fields in 49 farms over three years. Each field was divided into large grids of 20x20 metre cells, and the density of seven species was estimated three times a year. The study is part of the NERC Rural Economy and Land Use (RELU) programme. In the context of changing external and internal pressures on UK agriculture, particularly those associated with the ongoing reform of the EU Common Agricultural Policy, it is imperative to determine whether all of the various dimensions of sustainability - including the relevant economic and environmental objectives as well as social and cultural values - can be integrated successfully at the farm and landscape levels. Although the ways in which economic, technological, and regulatory changes are likely to affect the profitability and management of farms of varying size are reasonably well understood, there is not the knowledge or understanding to predict the resulting effects on biodiversity. For example, the effect of changes in arable farming practices on field weeds and, in turn, on habitats and food supply required to sustain farm birds is a case in point. This knowledge is critical, however, if we are to understand the ecological consequences of changes in agricultural policy. Furthermore, it is also important if we are to design and justify changes in farming methods that can not only enhance nature conservation, but do this is ways that are practical and appealing from a farmer's point of view. This understanding is essential if we are to achieve an agriculture that is sustainable in both economic and environmental terms and is widely perceived to have social and cultural value. A consistent theme in all components of this research project is to understand the behaviour (of farmers, weeds or birds) and then use this information to produce predictive models. Whilst there have been a number of models of economic behaviour, weed populations and bird populations - including many by the research team here - the really novel component of this research is to integrate these within one framework. Farmer interviews on economic attitudes and preferences associated with and importance of different land-use objectives to lowland arable farmers are available at the UK Data Archive under study number 6728 (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).

  • Cloud properties derived from the AATSR instrument on ENVISAT by the ESA Cloud CCI project. The L3U datasets consists of cloud properties from L2 data granules remapped to a global space grid of 0.1 degree in latitiude and longitude, without combining any observations from overlapping orbits; only sampling is done. Common notations for this processing level are also L2b and L2G. Data is provided with a temporal resolution of 1 day. This dataset is version 1.0 data from Phase 1 of the CCI project.

  • This dataset comprises seven ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0.1° × 0.1° grid (approximate grid of 10 km × 10 km) across West Africa for historical (1950 to 2005) and projected future (2006 to 2099) periods. This dataset is the output from the Hydrological Modelling Framework for West Africa, or “HMF-WA” model. The ensembles correspond to historical and three projected future climate scenarios (RCP2.6, RCP4.5 and RCP8.5) with two future scenarios of water use. The scenarios of water use are (i) future water use that varies in line with projected population increases, and (ii) future water use is the same as present day. This dataset is an output from the regional scale hydrological modelling study from African Monsoon Multidisciplinary Analysis-2050 (AMMA-2050) project. Full details about this dataset can be found at https://doi.org/10.5285/6429828f-6a06-4d2d-8f50-4910b18f7ff4

  • Data are presented from an ozone exposure experiment performed on five African crops. The crops (Beans, cowpea, finger millet, pearl millet and wheat) were exposed to three different levels of ozone in the UK CEH Bangor solardomes. Wheat was grown at UK ambient temperature, whereas the solardomes were heated for the other crops to better mimic tropical conditions. The experiment ran from May 2017 to September 2017. The crop plants were grown from seed in pots in solardomes. The aim of the experiment was to investigate the impact of ozone exposure on the crop yield and plant health. The dataset comprises of manually collected data on plant physiology, biomass and yield. In addition the automatically logged data of ozone concentration and meteorological variables in the solardomes are presented. Plant physiology data is stomatal conductance of individual leaves, measured on an ad-hoc basis. The dataset includes the associated data measured by the equipment (relative humidity, leaf temperature, photosynthetically active radiation). Soil moisture of the pots was always measured at the same time, and chlorophyll content of the measured leaf was usually, but not always, determined at the same time. Yield was determined for each plant, in addition to yield-related metrics including mass per bean and 100 grain weight. For finger millet and pearl millet yield is expressed as weight of seed heads and number of seed heads, rather than explicitly as seed weight. The ozone and meteorological dataset is complete, but with some gap-filling for short periods when the computer was not logging data. The work was carried out as part of the NERC funded SUNRISE project (NE/R000131/1). Full details about this dataset can be found at https://doi.org/10.5285/f38beff1-993f-4785-8a97-1de21e3e19c0

  • This data is NERC-funded but not held by the EIDC. The data is archived in European Nucleotide Archive under primary accession reference PRJEB33721. This dataset is the DNA sequences from Illumina MiSeq sequencing of the bacterial 16S and fungal ITS2 genes in climate manipulated soils from the Climoor field experiment. Soil samples were collected in 2003 and 2017 after 4 and 18 years of manipulation, respectively. The experimental field site consists of three untreated control plots, three plots where the plant canopy air is artificially warmed during night time hours, and three plots where rainfall is excluded from the plots at least during the plants' growing season (March to September). The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes and has been running since 1999. The microbial community data aims to understand how changes in soil hydrological and chemical properties have influenced the soil microbial composition and the implications of this for biogeochemical cycling. The data were collected as part of NERC project NEC05670 CWI-STU Fiona Seaton as part of the NERC Soils Training And Research Studentships Centre for Doctoral Training (STARS)

  • [THIS DATASET HAS BEEN WITHDRAWN]. 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. It also covers Northern Ireland and 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, incorporating land cover classes sought by other users. LCM2007 is produced in both vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. This dataset consists of the vector product, containing each individual parcel, as classified. (Great Britain only). Full details about this dataset can be found at https://doi.org/10.5285/1d78e01a-a9c1-4371-8482-1c1b57d9661f

  • This dataset includes ecological information recorded from within 18 birch woodlands surveyed in the Spey Valley, Scotland between 1971 and 1974. Data collected includes plant species composition in the canopy and ground flora, soil pH, habitat management and a wide range of other descriptors at a site level and in more detail from 16 - 40 200m2 sample plots located at random within the 18 woods. The survey was undertaken by the Nature Conservancy/Institute of Terrestrial Ecology. Full details about this dataset can be found at https://doi.org/10.5285/c84961e3-b9dc-4c92-b316-36295b8a3330

  • The dataset comprises of above ground vegetation cut to ground level and dried to give indication of standing crop biomass in a 50 centimetre (cm) x 25cm area (taken within a 1metre (m) x 1m quadrat) . Sampling was conducted at six salt marsh sites at four spatial scales: 1 m (the minimal sampling unit) nested within a hierarchy of increasing scales of 1-10 m, 10-100 m and 100-1000 m. Three of the sites were in Morecambe Bay, North West England and three of the sites were in Essex, South East England. All samples were taken during the winter and summer of 2013. This data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. BESS is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Full details about this dataset can be found at https://doi.org/10.5285/87114da4-3189-471f-9832-00b3e759232f

  • This dataset consists of the 25m raster, Land Cover Change 1990 - 2015 product for Northern Ireland. The dataset is produced from the Land Cover Map (LCM) 25m raster versions of LCM1990 and LCM2015 and reports Land Cover Change between 1990 and 2015 in six simplified classes. The product consists of five bands: Band 1 – a raster version of LCM1990 in the six simplified classes; Band 2 – a raster version of LCM2015 in the six simplified classes; Band 3 – a binary layer, where 0 means no change between 1990 and 2015 and 1 means change between 1990 and 2015; Band 4 – shows the 'change from' class; Band 5 – provides the 'change to' class. Full details of the Land Cover Change dataset are provided in the Land Cover Change dataset documentation, which users should consult. 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/a747aa7a-c875-42e1-ac31-984f6571f446

  • This dataset compares historic grassland survey data with contemporary spatial data of habitats in England. The National Vegetation Classification (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. This dataset supersedes the previous version. Full details about this dataset can be found at https://doi.org/10.5285/a75b9569-948a-4bb2-97a5-6863717881c8