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There is an urgent need for transformational change in global and UK agriculture. Current practices undermine the long-term future of farming and impoverish ecosystems in the UK and elsewhere. However, change is not happening at the scale and pace which is needed. Work by David Abson, drawing on ideas by Donella Meadows, explored this failure of progress and proposed a research agenda focused on transformational leverage points which influence sustainability. These points are centred on three realms of leverage: reconnecting people to nature, restructuring institutions and rethinking how knowledge is created and used in pursuit of sustainability. In this paper, these ideas are explored through a combined researcher/stakeholder workshop focused on transformational change in UK livestock systems. Workshop participants were asked to discuss and identify potential levers of change under the three realms identified by Abson. The multiplicity of levers identified and the interactions across realms emphasise the need for new kinds of knowledge creation which are highly transdisciplinary, as well as emphasising the complexity of levers which are likely to play a role in the transformation of livestock food systems in the UK and elsewhere. [ABSTRACT FROM AUTHOR]

The Glastir Monitoring and Evaluation Programme (GMEP) ran from 2013 until 2016, and was probably the most comprehensive programme of ecological study ever undertaken at a national scale in Wales. The programme aimed to (1) set up an evaluation of the environmental effects of the Glastir agri-environment scheme and (2) quantify environmental status and trends across the wider countryside of Wales. The focus was on outcomes for climate change mitigation, biodiversity, soil and water quality, woodland expansion and cultural landscapes. As such, GMEP included a large field survey component, collecting data on a range of elements including vegetation, land cover and use, soils, freshwaters, birds and insect pollinators from up to 300 1 km squares throughout Wales. The field survey capitalised upon the UKCEH Countryside Survey of Great Britain, which has provided an extensive set of repeated, standardised ecological measurements since 1978. The design of both GMEP and the UKCEH Countryside Survey involved stratified-random sampling of squares from a 1 km grid, ensuring proportional representation from land classes with distinct climate, geology and physical geography. Data were collected from different land cover types and landscape features by trained professional surveyors, following standardised and published protocols. Thus, GMEP was designed so that surveys could be repeated at regular intervals to monitor the Welsh environment, including the impacts of agri-environment interventions. One such repeat survey is scheduled for 2021 under the Environment and Rural Affairs Monitoring and Modelling Programme (ERAMMP). Data from GMEP have been used to address many applied policy questions, but there is major potential for further analyses. The precise locations of data collection are not publicly available, largely for reasons of landowner confidentiality. However, the wide variety of available datasets can be (1) analysed at coarse spatial resolutions and (2) linked to each other based on square-level and plot-level identifiers, allowing exploration of relationships, trade-offs and synergies. This paper describes the key sets of raw data arising from the field survey at co-located sites, 2013 to 2016. Data from each of these survey elements are available with the following Digital Object Identifiers. Landscape features, https://doi.org/10.5285/82c63533-529e-47b9-8e78-51b27028cc7f, https://doi.org/10.5285/9f8d9cc6-b552-4c8b-af09-e92743cdd3de, https://doi.org/10.5285/f481c6bf-5774-4df8-8776-c4d7bf059d40; Vegetation plots, https://doi.org/10.5285/71d3619c-4439-4c9e-84dc-3ca873d7f5cc; Topsoil physico-chemical properties, https://doi.org/10.5285/0fa51dc6-1537-4ad6-9d06-e476c137ed09; Topsoil meso-fauna, https://doi.org/10.5285/1c5cf317-2f03-4fef-b060-9eccbb4d9c21; Topsoil particle size distribution https://doi.org/10.5285/d6c3cc3c-a7b7-48b2-9e61-d07454639656; Headwater stream quality metrics, https://doi.org/10.5285/e305fa80-3d38-4576-beef-f6546fad5d45 ; Pond quality metrics, https://doi.org/10.5285/687b38d3-2278-41a0-9317-2c7595d6b882; Insect pollinator and flower data, https://doi.org/10.5285/3c8f4e46-bf6c-4ea1-9340-571fede26ee8; Bird counts, https://doi.org/10.5285/31da0a94-62be-47b3-b76e-4bdef3037360. [ABSTRACT FROM AUTHOR]

The Countryside Survey (CS) of Great Britain (GB) provides a unique and statistically robust series of datasets, consisting of an extensive set of repeated ecological measurements at a national scale, covering a time span of 29 years. CS was first undertaken in 1978 to provide a baseline for ecological and land use change monitoring in the rural environment of GB, following a stratified random design, based on 1 km squares. Originally, eight random 1 km squares were drawn from each of 32 environmental classes, thus comprising 256 sample squares in the 1978 survey. The number of these sites increased to 382 in 1984, 506 in 1990, 569 in 1998 and 591 in 2007. Detailed information regarding vegetation types and land use was mapped in all five surveys, allowing reporting by defined standard habitat classifications. Additionally, point and linear landscape features (such as trees and hedgerows) are available from all surveys after 1978. From these stratified, randomly located sample squares, information can be converted into national estimates, with associated error terms. Other data, relating to soils, freshwater and vegetation, were also sampled on analogous dates. However, the present paper describes only the surveys of landscape features and habitats. The resulting datasets provide a unique, comprehensive, quantitative ecological coverage of extent and change in these features in GB. Basic results are presented and their implications discussed. However, much opportunity for further analyses remains. [ABSTRACT FROM AUTHOR]

The Countryside Survey (CS) of Great Britain (GB) provides a unique and statistically robust series of datasets, consisting of an extensive set of repeated ecological measurements at a national scale, covering a time span of 29 years. CS was first undertaken in 1978 to provide a baseline for ecological and land use change monitoring in the rural environment of GB, following a stratified random design, based on 1 km squares. Originally, eight random 1 km squares were drawn from each of 32 environmental classes, thus comprising 256 sample squares in the 1978 survey. The number of these sites increased to 382 in 1984, 506 in 1990, 569 in 1998 and 591 in 2007. Detailed information regarding vegetation types and land use was mapped in all five surveys, allowing reporting by defined standard habitat classifications. Additionally, point and linear landscape features (such as trees and hedgerows) are available from all surveys after 1978. From these stratified, randomly located sample squares, information can be converted into national estimates, with associated error terms. Other data, relating to soils, freshwater and vegetation, were also sampled on analogous dates. However, the present paper describes only the surveys of landscape features and habitats. The resulting datasets provide a unique, comprehensive, quantitative ecological coverage of extent and change in these features in GB. Basic results are presented and their implications discussed. However, much opportunity for further analyses remains. Data from each of the survey years are available via the following DOIs: Landscape area data 1978: http://doi.org/10.5285/86c017ba-dc62-46f0-ad13-c862bf31740e, 1984: http://doi.org/10.5285/b656bb43-448d-4b2c-aade-7993aa243ea3, 1990: http://doi.org/10.5285/94f664e5-10f2-4655-bfe6-44d745f5dca7, 1998: http://doi.org/10.5285/1e050028-5c55-42f4-a0ea-c895d827b824, and 2007: http://doi.org/10.5285/bf189c57-61eb-4339-a7b3-d2e81fdde28d; Landscape linear feature data 1984: http://doi.org/10.5285/a3f5665c-94b2-4c46-909e-a98be97857e5, 1990: http://doi.org/10.5285/311daad4-bc8c-485a-bc8a-e0d054889219, 1998: http://doi.org/10.5285/8aaf6f8c-c245-46bb-8a2a-f0db012b2643, and 2007: http://doi.org/10.5285/e1d31245-4c0a-4dee-b36c-b23f1a697f88; Landscape point feature data 1984: http://doi.org/10.5285/124b872e-036e-4dd3-8316-476b5f42c16e, 1990: http://doi.org/10.5285/1481bc63-80d7-4d18-bcba-8804aa0a9e1b, 1998: http://doi.org/10.5285/ed10944f-40c8-4913-b3f5-13c8e844e153, and 2007: http://doi.org/10.5285/55dc5fd7-d3f7-4440-b8a7-7187f8b0550b. [ABSTRACT FROM AUTHOR]

Pasture is a globally important managed habitat providing both food and income. The way in which it is managed leads to a wide range of impacts on soil microbial communities and associated soil health. While there have been several studies comparing pasture farming to other forms of land use, we still have limited understanding of how the soil microbial communities vary between pasture farms and according to management practices. Here we present the results of a field survey across 56 UK livestock farms that are managed by members of the Pasture fed Livestock Association, using amplicon sequencing of the 16S and ITS regions to characterise the soil bacterial and fungal community within fields that have been under pasture for differing durations. We show that grazing management intensity has only limited effects upon microbial community structure, while the duration of pasture since ploughing (ranging from 1 year to over 100 years) impacted the fungal community structure. The impact of management duration was conditional upon soil physicochemical properties, particularly pH. Plant community effects on upon soil bacterial and fungal composition appear to also interact with the soil chemistry, highlighting the importance of plant-soil interactions in determining microbial community structure. Analyses of microbial indicators revealed proportionally more fungal taxa that responded to multiple ecosystem health associated properties than bacterial taxa. We also identified several fungal taxa that both acted as indicators of soil health related properties within our dataset and showed differentiation between grassland types in a national survey, indicating the generality of some fungal indicators to the national level. Members of the Agaricomycetes were associated with multiple indicators of soil health. Our results show the importance of maintaining grassland for the development of plant-soil interactions and microbial community structure with concomitant effects on soil and general ecosystem health. • Soil bacteria and fungi from > 50 pastures were analysed using DNA metabarcoding. • Duration of pasture since ploughing impacted fungal community composition. • Bacteria were more associated with soil physicochemical properties than fungi. • Plant effects on soil microbes were through interactions with soil chemistry. • Microbial indicators of soil health were disproportionately fungal taxa. [ABSTRACT FROM AUTHOR]