This dataset consists of soil data for 64 field sites on paired farm sites, with 29 variables measured for soil texture and structural condition, aggregate stability, organic matter content, soil shear strength, fuel consumption, work rate, infiltration rate, water quality and hydrological condition (HOST) data. The study is part of the NERC Rural Economy and Land Use (RELU) programme. A move to organic farming can have significant effects on wildlife, soil and water quality, as well as changing the ways in which food is supplied, the economics of farm business and indeed the attitudes of farmers themselves. Two key questions were addressed in the SCALE project: what causes organic farms to be arranged in clusters at local, regional and national scales, rather than be spread more evenly throughout the landscape; and how do the ecological, hydrological, socio-economic and cultural impacts of organic farming vary due to neighbourhood effects at a variety of scales. The research was undertaken in 2006-2007 in two study sites: one in the English Midlands, and one in southern England. Both are sites in which organic farming has a 'strong' local presence, which we defined as 10 per cent or more organically managed land within a 10 km radius. Potential organic farms were identified through membership lists of organic farmers provided by two certification bodies (the Soil Association and the Organic Farmers and Growers). Most who were currently farming (i.e. their listing was not out of date) agreed to participate. Conventional farms were identified through telephone listings. Respondents' farms ranged in size from 40 to 3000 acres, with the majority farming between 100 and 1000 acres. Most were mixed crop-livestock farmers, with dairy most common in the southern site, and beef and/or sheep mixed with arable in the Midlands. In total, 48 farms were studied, of which 21 were organic farmers. No respondent had converted from organic to conventional production, whereas 17 had converted from conventional to organic farming. Twelve of the conventional farmers defined themselves as practicing low input agriculture. Farmer interview data from this study are available at the UK Data Archive under study number 6761 (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 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 dataset consists of tick sampling and microclimate data from Exmoor, Richmond and New Forest study sites; as well as ARCGIS risk maps that model tick abundance driven by climate surfaces and host abundance. Tick sampling data (91 files, each representing a day of sampling) indicate tick abundance (distinguishing larvae, nymphs, adult males and adult females), vegetation height, soil moisture, temperature and relative humidity. Static risk map files indicate modeled tick abundance: 251 landcover files for the three sites, as well as 36 ArcView map files. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Many people take pleasure from activities in forests and wild lands in the UK and others are being encouraged to participate. Unfortunately, there are risks and one of the most insidious is the possibility (albeit tiny) of acquiring a disease from wild animals; for example, ticks can be vectors of the bacterial infection leading to Lyme Disease. Both diagnosis and treatment can be problematic so prevention of acquiring such disease is highly desirable. Surprisingly little is known about how best to warn countryside users about the potential for disease without scaring them away or spoiling their enjoyment. Answering such questions was the goal of this project, and required the integration of a diverse set of scientific skills, and an understanding of the views of those who manage countryside, those who have contracted zoonotic diseases and those who access the land. This project combined knowledge from three strands of work, namely risk assessment, risk perception and communication, and scenario analysis. The study sites were selected to provide a range of environmental conditions and countryside use. Peri-urban parkland, accessible lowland forest and heath and remote upland forest were chosen as represented by Richmond Park on the fringe of Greater London, the New Forest in Southern England, and Exmoor in South West England. The following additional data from this same research project are available at the UK Data Archive under study number 6892 (see online resources): Lyme disease risk perception data resulting from tick imagery vignette experiments, Lyme disease patient interviews and surveys, residents and countryside staff focus groups, forest manager interviews, and multiple scoring procedures of animal social representation; as well as Lyme and tick risk communication data resulting from interviews with organisations and content analysis of risk warning information leaflets, 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).

Hydrological monitoring data in this data collection result from dipwells installed at studied flood defence scheme, where electronic gauges monitored water-table fluctuations over time. Ecological data contain species sighting records of birds, butterflies, dragonflies and damselflies recorded during site visits to flood defence schemes in summer 2007. These data aim to show the relationship between water regimes and habitat potential.The study is part of the NERC Rural Economy and Land Use (RELU) programme. Agricultural Flood Defence Schemes in floodplain and coastal areas were once an important element of Government support for farmers in Britain. More recently, however, changing priorities in the countryside, concern about environmental quality and perceptions of increased flood risk in lowland areas, in part linked to climate change, have promoted a re-appraisal of land management options and policies for floodplain areas. Eight agricultural flood defence schemes, previously studied by the research team in the 1980s, have been re-examined to identify and explain changes in land and water management that have occurred over the last 40-years. This involved stakeholder and institutional analysis, farmer interviews, ecological surveys, field observations and modelling of hydrological and related ecological processes. Generic land use scenarios have been developed to consider management options that focus on single objectives, such as maximising agricultural production, maximising biodiversity and minimising flood risk in the catchment. The scenarios examined the impacts of changes in rural land use on ecosystem goods and services. The influence of agricultural policy, interacting with farmer circumstances and motivation, on land use has also been explored. The project also evaluated the impacts of the summer 2007 floods on agriculture and rural communities. The results revealed opportunities for achieving a wide range of benefits relating to farming, biodiversity, amenity, flood management, water quality and the wider rural economy. The study informed strategies for floodplain management, helping to develop approaches that are appealing to major stakeholders. Historical data on the studied flood defence schemes, farm business survey data and interviews with farmers at flood defence schemes, and interviews with farmers and rural businesses affected by summer floods in 2007 are available at the UK Data Archive under study number 6377 (see related 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 consists of ecology data from 16 paired field sites; each pair consisting of an organic and conventional farm. A multiscale sampling design was employed to assess the impact of (i) location-within-field (field margin vs. edge vs. centre), (ii) crop type (arable cereal vs. permanent pasture), (iii) farm management (organic vs. conventional) and (iv) landscape-scale management (landscapes that contained low or high fractions of organic land) on a wide range of taxa. Studied taxa include birds, insect pollinators (hoverflies, bumblebees and solitary bees), epigeal arthropods, aphids and their natural enemies, earthworms and plants. The study is part of the NERC Rural Economy and Land Use (RELU) programme. A move to organic farming can have significant effects on wildlife, soil and water quality, as well as changing the ways in which food is supplied, the economics of farm business and indeed the attitudes of farmers themselves. Two key questions were addressed in the SCALE project: what causes organic farms to be arranged in clusters at local, regional and national scales, rather than be spread more evenly throughout the landscape; and how do the ecological, hydrological, socio-economic and cultural impacts of organic farming vary due to neighbourhood effects at a variety of scales. The research was undertaken in 2006-2007 in two study sites: one in the English Midlands, and one in southern England. Both are sites in which organic farming has a 'strong' local presence, which we defined as 10 per cent or more organically managed land within a 10 km radius. Potential organic farms were identified through membership lists of organic farmers provided by two certification bodies (the Soil Association and the Organic Farmers and Growers). Most who were currently farming (i.e. their listing was not out of date) agreed to participate. Conventional farms were identified through telephone listings. Respondents' farms ranged in size from 40 to 3000 acres, with the majority farming between 100 and 1000 acres. Most were mixed crop-livestock farmers, with dairy most common in the southern site, and beef and/or sheep mixed with arable in the Midlands. In total, 48 farms were studied, of which 21 were organic farmers. No respondent had converted from organic to conventional production, whereas 17 had converted from conventional to organic farming. Twelve of the conventional farmers defined themselves as practicing low input agriculture. Farmer interview data from this study are available at the UK Data Archive under study number 6761. Soil data from agricultural land under differing crop and management regimes,are also available. 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 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 consists of palaeoecological measurements taken at sites in the Peak District and NW Sutherland during the NERC Rural Economy and Land Use (RELU) programme. This data collection includes the results from four interlinked projects combining quantitative and qualitative evidence to assess long-term ecological data at local to national levels: Project 1 synthesises existing information on historical environmental changes in the uplands with relevance to current management and policy Project 2 used high resolution palaeoenvironmental analyses to reconstruct ecological changes and land-use histories of four contrasting moorland systems in the Peak District (England) over the last c.200-1300 yrs. Sites were selected in consultation with stakeholders and the results provide the basis for comparison with ecological survey results and knowledge of current managers. Project 3 used similar methods to reconstruct ecological and land-use changes in NW Sutherland (Scotland) over the last c.400 yrs. Site selection was based on discussion with stakeholders and results were compared with stakeholder knowledge and preferences for landscape change. Project 4 used three choice experiments to assess the response of different communities to long-term evidence as a potential source of information to inform preferences for upland management. Project 4a used a choice experiment to assess the influence of long-term evidence on management preferences of residents of the Peak District. Project 4b used choice experiments to present long-term evidence to ecologists from government, NGO, research and practitioner communities in conjunction with established sources of ecological evidence used in upland management (ecological monitoring and ecological research) and with stakeholder preferences for upland management, since this is increasingly becoming embedded in decision-making. The upland woods and peatlands were used as the contexts for two choice experiments. This dataset consists of palaeoecological measurements taken at sites in the Peak District and NW Sutherland, as part of projects 2 and 3 as listed above. The choice experiment data from this study are available at the UK Data Archive under study number 6791 (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 data set consists of the tabulated results of bird surveys on Peak District farms and moorlands. Bird abundance and distribution on Peak District farms and moorlands, 2007-2008 The study is part of the NERC Rural Economy and Land Use (RELU) programme. The project used the Peak District National Park as a case study to examine the impact of hill farming practices on upland biodiversity (using birds as an indicator group); how hill farms were responding to ongoing and future changes to policies and prices; what this would in turn imply for upland biodiversity; what the public wanted from upland ecosystems and how policies could be designed better to deliver public goods from hill farms. To answer these questions, the project team conducted ecological and economic surveys on hill farms; used survey results to parameterise ecological and economic models of this farming system; developed new ways to integrate these into coupled ecological and economic models and paid particular attention to interactions across farm boundaries; used the models to evaluate the performance of existing policies and to test designs that could lead to more effective policies; and conducted a range of choice experiments with different cross-sections of the general public to evaluate their preferences for upland landscapes. Choice experiment, socio-economic survey and model data from this study are available at the UK Data Archive under study number 6363 (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 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).

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 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).