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  • Climatic data from four sites (Newton Rigg, Widdybank Fell, Moor House and Great Dun Fell) along an altitudinal gradient in Cumbria 1952-1990. Standard Meteorological Office procedures were used. Full details about this dataset can be found at https://doi.org/10.5285/ab42fb7d-809f-4492-9ba5-c8aeebdee838

  • This dataset comprises hydrographic data profiles, collected by a conductivity-temperature-depth (CTD) sensor package, during July - August 1992. It incorporates CTD anchor stations and grid surveys in the Humber Estuary, Humber Plume and the Wash plus some additional casts further east in the Southern North Sea. The data were collected by the Ministry of Agriculture, Fisheries and Food Lowestoft Fisheries Laboratory as part of the Joint Nutrient Study I (JoNuS).

  • This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Northern Ireland. It describes Northern Ireland's land cover in 2018 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2018 20m classified pixels dataset. All further LCM2018 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 to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019. 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/10.5285/35f15502-d340-4ab5-a586-abd42f238b6e

  • The UK Argo programme data set comprises measurements of ocean temperature and salinity and provides information of surface and subsurface Lagrangian (measuring movement by tracing the path of a passively drifting object) displacement enabling the derivation of currents. The data set includes a mixture of near-real-time (quality controlled to operational ocean forecasting standards) and delayed mode (quality controlled to climate research standards) data collected by profiling floats. The UK floats from part of a global array throughout the world oceans. Real-time data are available within 24 hours of the float surfacing while delayed mode data become available within 12 months of the profile date. Floats drift at their parking depth (between 1000m and 2025m) for 5 or 10 days depending on float programming. Traditionally floats measured temperature and conductivity at regular intervals during their rise to the surface. In October 2007, the Argo programme achieved its goal to have (and maintain) more than 3000 active floats. As of 2012, some newly deployed floats are being programmed to collect data whilst drifting at their parking depth and during their ascent and additional oceanographic parameters, for example fluorescence, optical backscatter, and dissolved oxygen are being trialled for inclusion in the data set. The data has a variety of uses including assimilation into operational weather forecasts in near-real-time to climate research with the delayed mode data. The data set also includes Argo floats deployed by Mauritius, Saudi Arabia (one float in the Red Sea) Ireland and Portugal, as the British Oceanographic Data Centre manages the data from these floats in addition to those of the UK Argo programme.

  • [This dataset is embargoed until December 31, 2021]. This dataset is the first phenological trait data for Moringa oleifera and M. stenopetala trees from provenances collected in Kenya and planted at Ramogi. Trees were measured and scored for survival, height, diameter at breast height, fruiting and damage by three field surveyors. Full details about this dataset can be found at https://doi.org/10.5285/668f9f95-f367-4600-b93a-ffc24b67ce7f

  • 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).

  • This dataset comprises 11 hydrographic data profiles, collected by a conductivity-temperature-depth (CTD) sensor package, in October 1993 from stations in the NE Atlantic between 45 - 50 N, 5 - 15 W. A complete list of all data parameters are described by the SeaDataNet Parameter Discovery Vocabulary (PDV) keywords assigned in this metadata record. The data were collected by the Royal Netherlands Institute for Sea Research as part of the Ocean Margin Exchange (OMEX) I project.

  • The dataset contains a diverse range of environmental data ranging from estuary properties including geomorphology, water depth and habitat characterisation to detailed time series of parameters such as salinity and chemical and nutrient concentrations. The data are stored in a database containing a directory of existing data sources for estuaries; data for the broad properties of 79 UK estuaries; and detailed hydrodynamic, bathymetric, and sedimentary information for six estuaries: Blackwater, Humber, Mersey, Ribble, Southampton Water and Tamar. The data range from 1965 to 2002 and include both historic datasets and those collected during a recent effort (1997-2002) to enhance our knowledge of estuaries. Data collection employed a variety of instrumentation and techniques, including water, biota and sediment sample collection and analysis and the deployment of hydrographic instruments such as sea level, temperature, salinity and optical backscatter recorders. The Estuaries Research Programme (ERP) began in 1997 with the EMPHASYS project, which aimed to improve our understanding of processes operating in estuaries and use this knowledge to enhance broad scale modelling techniques that can be applied to estuarine processes. This work was funded by the Environment Agency/Department for Environment, Food and Rural Affairs (DEFRA) Flood and Coastal Defence Research and Development Programme. The data are managed by the British Oceanographic Data Centre (BODC) and are available on CD-ROM.

  • 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 2 hydrographic data profiles, collected by a conductivity-temperature-depth (CTD) sensor package, in September 1994 from stations in the Ria de Vigo between 42 - 43 N, 8.5 - 9.5 W. A complete list of all data parameters are described by the SeaDataNet Parameter Discovery Vocabulary (PDV) keywords assigned in this metadata record. The data were collected by the Institute of Marine Research, Vigo as part of the Ocean Margin Exchange (OMEX) I project.