This dataset consists of an ecology-focused survey of stillwaters along the rivers Yure and Swale and sediment flux measurements recorded at sites along the river Esk. The dataset results from a study which was part of the Rural Economy and Land Use (RELU) programme. The project analysed the complex network of natural and socio-economic relationships around angling in the river environment, including institutions of governance and land use practices at a range of interconnected scales. The sustainability, integrity and ecological value of river catchments are currently major issues for science. The management of freshwaters and their ecologies requires addressing processes that work across the boundaries between the natural environment, economy and society. This research focused upon these cross-cutting processes in an interdisciplinary, holistic assessment of river environments through the case of angling. Angling benefits from and influences river quality, design and management. It also links urban and rural environments and is an economic driver for the rural economy, involving about 4 million people in England and Wales and contributing 6 billion pounds to the economy through freshwater angling alone. This research aimed to provide insights into how environmental and socio-economic drivers for rural change work. This project therefore aimed to identify and analyse the complex network of influences and feedbacks around angling in the rural environment. These include natural and socio-economic influences, interdisciplinary research from both natural and social science disciplines (aquatic ecology, geomorphology, anthropology, sociology, human geography), as well as stakeholders from government, NGOs and the local community. This project focused upon three rivers in northern England - the Esk, Ure and Swale - in the course of an integrated and fine-grained study. The postal survey and business interviews from this study are available at the UK Data Archive under study number 6580 (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).
The dataset consists of the world's longest fluvial dissolved organic carbon (DOC) record (1883-2014). The data have been measured at the outlet of the Thames basin, upstream of London (UK) and are reported monthly. The River Thames basin is a temperate, lowland, mineral soil-dominated catchment of 9,948 km2. Water colour data have been measured between 1883 and 1990, and DOC between 1990 and 2014. DOC until 1990 has been estimated through calibration between water colour and DOC for the period 1899-1905 when OC measurements were available. The fluvial DOC concentration shows an upward trend throughout the period. The data are presented as one table and one supporting file containing metadata and are summarised and presented in the Journal of Geophysical Research - Biogeosciences doi: 10.1002/2016JG003614. Full details about this dataset can be found at https://doi.org/10.5285/57943561-4587-4eb6-b14c-7adb90dc1dc8
This is a spatial dataset containing polygons representing different geology types in the Moor House National Nature Reserve, northern Pennines, England. The survey was undertaken by G.A.L. Johnson under a grant by The Nature Conservancy in the 1950s and 1960s. Full details about this dataset can be found at https://doi.org/10.5285/0e3aefb2-ce86-4d09-8ff0-6d165dfd48db
This dataset consists of computer code transcripts for two proprietary flood risk models from a study as part of the NERC Rural Economy and Land Use (RELU) programme. This project was conceived in order to address the public controversies generated by the risk management strategies and forecasting technologies associated with diffuse environmental problems such as flooding and pollution. Environmental issues play an ever-increasing role in all of our daily lives. However, controversies surrounding many of these issues, and confusion surrounding the way in which they are reported, mean that sectors of the public risk becoming increasingly disengaged. To try to reverse this trend and regain public trust and engagement, this project aimed to develop a new approach to interdisciplinary environmental science, involving non-scientists throughout the process. Examining the relationship between science and policy, and in particular how to engage the public with scientific research findings, a major diffuse environmental management issue was chosen as a focus - flooding. As part of this approach, non-scientists were recruited alongside the investigators in forming Competency Groups - an experiment in democratising science. The Competency Groups were composed of researchers and laypeople for whom flooding is a matter of particular concern. The groups worked together to share different perspectives - on why flooding is a problem, on the role of science in addressing the problem, and on new ways of doing science together. We aimed to achieve four substantive contributions to knowledge: 1. To analyse how the knowledge claims and modelling technologies of hydrological science are developed and put into practice by policy makers and commercial organisations (such as insurance companies) in flood risk management. 2. To develop an integrated model for forecasting the in-river and floodplain effects of rural land management practices. 3. To experiment with a new approach to public engagement in the production of interdisciplinary environmental science, involving the use of Competency Groups. 4. To evaluate this new approach to doing public science differently and to identify lessons learnt that can be exported beyond this particular project to other fields of knowledge controversy. This dataset consists of computer code transcripts for two proprietary flood risk models. Flood risk and modelling interview transcripts from this study are available at the UK Data Archive under study number 6620 (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 a digital soil map of the Moor House - Upper Teesdale National Nature Reserve. Mapped polygons represent a range of soil types. The site lies in the North Pennine uplands of England and has an area of 74 km2. It is England's highest and largest terrestrial National Nature Reserve (NNR), a UNESCO Biosphere Reserve and a European Special Protection Area. Habitats include exposed summits, extensive blanket peatlands, upland grasslands, pastures, hay meadows and deciduous woodland. Altitude ranges from 290 to 850 m. Moor House - Upper Teesdale is part of the Environmental Change Network (ECN) whcih is the UK's long-term environmental monitoring programme. Full details about this dataset can be found at https://doi.org/10.5285/b36357bd-988c-41fa-a3a8-3b21cef5f0b6
This dataset comprises enchytraeid worm abundance and Delta 13C values from enchytraeid cholesterol. The data were collected as a component of the NERC Soil Biodiversity Programme, consisting of a one year study of the diversity and activity of Enchytraeid worms, small relatives of the earthworm. These worms are very common in upland soils and often outweigh all other fauna, including sheep. The project focused on investigating the importance of Enchytraeid species, or group diversity, in maintaining soil carbon cycling. The NERC Soil Biodiversity Thematic Programme was established in 1999 and was centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (now the James Hutton Institute)'s farm at Sourhope in the Scottish Borders. During this time, the site was monitored to assess changes in aboveground biomass production (productivity), species composition and relative abundance (diversity). Full details about this dataset can be found at https://doi.org/10.5285/0a443a55-28b6-4d82-9042-5a35bfdbebe0
This dataset contains water flow velocity, discharge, and suspended sediment compositions of the Irrawaddy (Ayeyarwady) River at Pyay, Myanmar and the Salween (Thanlwin) River at Hpa-An, Myanmar. The suspended sediment samples and the hydrological data were collected both during peak monsoon conditions (August 2017 and August 2018) and peak dry season conditions (February 2018 and May 2019). Water velocity was measured using Acoustic Doppler Current Profiler (ADCP) while collecting suspended sediment samples at various depths in the river. Additional flow velocity data was collected while laterally crossing the river channel from bank to bank, and was used to calculate total river discharge at these sites. The dataset includes suspended sediment concentrations, particulate organic carbon concentrations, and particle size distributions of sediment samples collected at various depths and locations in the two river channels. Full details about this dataset can be found at https://doi.org/10.5285/86f17d61-141f-4500-9aa5-26a82aef0b33
[This dataset is embargoed until January 31, 2022]. This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at a lowland valley fen located on Anglesey, North Wales, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 1st January 2015 and 10th October 2018. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. 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/10.5285/00ff0c86-80c2-4bb4-a38b-1cef38ce80b3