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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 European Union's 'Green Deal' proposes an ambitious roadmap towards climate neutrality by 2050 and the adoption of a circular economy. Functional AgroBiodiversity (FAB) measures, which balance food production with minimised impacts on nature, are a promising way to achieve this on farmland. Here, we undertake a rapid evidence assessment to highlight Functional Agro-Biodiversity (FAB) management measures which help to realise biodiversity, climate neutrality, efficiency in use of natural resources and the circular economy. We report evidence on the effectiveness of 10 common FAB measures employed in Europe following a resurgence of interest and increased availability of data on their impact. The review found that the outcomes of implementing FAB measures were largely positive, with a number of mixed effects. There are evidence gaps, e.g., the impact of FAB measures on yield, the magnitude and timescale of impacts, the effect of landscape context. We signpost the most relevant and well-documented FAB measures, providing a reference for land managers and practitioners to select FAB measures to achieve specific ecological and agricultural outcomes. It is also important to note that a combination of measures implemented in a strategic way can enhance the output success. [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 three-hundred 1 km survey squares throughout Wales. The field survey capitalised upon the UK Centre for Ecology & Hydrology (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 & 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 (DOIs): Landscape features (Maskell et al., 2020a–c), 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 (Smart et al., 2020), https://doi.org/10.5285/71d3619c-4439-4c9e-84dc-3ca873d7f5cc ; Topsoil physico-chemical properties (Robinson et al., 2019), https://doi.org/10.5285/0fa51dc6-1537-4ad6-9d06-e476c137ed09 ; Topsoil meso-fauna (Keith et al., 2019), https://doi.org/10.5285/1c5cf317-2f03-4fef-b060-9eccbb4d9c21 ; Topsoil particle size distribution (Lebron et al., 2020), https://doi.org/10.5285/d6c3cc3c-a7b7-48b2-9e61-d07454639656 ; Headwater stream quality metrics (Scarlett et al., 2020a), https://doi.org/10.5285/e305fa80-3d38-4576-beef-f6546fad5d45 ; Pond quality metrics (Scarlett et al., 2020b), https://doi.org/10.5285/687b38d3-2278-41a0-9317-2c7595d6b882 ; Insect pollinator and flower data (Botham et al., 2020), https://doi.org/10.5285/3c8f4e46-bf6c-4ea1-9340-571fede26ee8 ; and Bird counts (Siriwardena et al., 2020), 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]

This paper presents an alternative approach for high spatial resolution vegetation productivity mapping at a regional scale, using a combination of Normalised Difference Vegetation Index (NDVI) imagery and widely distributed ground-based Above-ground Net Primary Production (ANPP) estimates. Our method searches through all available single-date NDVI imagery to identify the images which give the best NDVI-ANPP relationship. The derived relationships are then used to predict ANPP values outside of field survey plots. This approach enables the use of the high spatial resolution (30 m) Landsat 8 sensor, despite its low revisit frequency that is further reduced by cloud cover. This is one of few studies to investigate the NDVI-ANPP relationship across a wide range of temperate habitats and strong relationships were observed (R² = 0.706), which increased when only grasslands were considered (R² = 0.833). The strongest NDVI-ANPP relationships occurred during the spring "green-up" period. A reserved subset of 20% of ground-based ANPP estimates was used for validation and results showed that our method was able to estimate ANPP with a RMSE of 15-21%. This work is important because we demonstrate a general methodological framework for mapping of ANPP from local to regional scales, with the potential to be applied to any temperate ecosystems with a pronounced green up period. Our approach allows spatial extrapolation outside of field survey plots to produce a continuous surface product, useful for capturing spatial patterns and representing small-scale heterogeneity, and well-suited for modelling applications. The data requirements for implementing this approach are also discussed. [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]

Since 1978, a series of national surveys (Countryside Surveys) have been carried out by the Centre for Ecology and Hydrology (formerly the Institute of Terrestrial Ecology) to gather data on the natural environment in Great Britain. As the sampling framework for these surveys is not optimised to yield data on rarer or more specialised habitats, a survey was commissioned by the then Department of the Environment (DOE, now the Department for Environment Food & Rural Affairs, DEFRA), in the 1990s to carry out additional survey work in English landscapes which contained semi-natural habitats that were perceived to be under threat, or which represented areas of concern to the Ministry. The landscapes were: lowland heath, chalk and limestone grasslands, coasts and uplands. These landscapes were chosen from a list identified as 'key habitats' in the Countryside Stewardship Scheme, an agri-environment scheme initiated in 1991. The survey design was a series of gridded, stratified, randomly selected 1 km squares taken as representative of classes derived from environmental classifications (or spatial masks) for each of the four landscape types in England determined from a statistical land classification. This resulted in a total of 213 of these squares being surveyed in the summers of 1992 and 1993, with information being collected regarding vegetation species, land cover, landscape features and land use. Data from the survey were collected using standardised, repeatable methods, with the database now providing a valuable baseline against which future ecological changes, resulting from a range of different drivers, may be compared. Following the surveys, the data were analysed and described in a series of contract reports showing that valuable habitats were restricted in all landscapes and that the majority were within designated land. The data set provides major potential for analyses, beyond those published in the reports published in 1996, for example in relation to climate change, agri-environment policies and land management. Precise locations of the plots are restricted, largely for reasons of landowner confidentiality. However, the representative nature of the data set makes it highly valuable for evaluating the status of the associated landscapes and vegetation covered. Both land cover data and vegetation plot data were collected during the surveys in 1992 and 1993, and are available via the following DOI: https://doi.org/10.5285/7aefe6aa-0760-4b6d-9473-fad8b960abd4. The spatial masks are also available from: https://doi.org/10.5285/dc583be3-3649-4df6-b67e-b0f40b4ec895. [ABSTRACT FROM AUTHOR]

The Countryside Survey (CS) of Great Britain provides a globally unique 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 monitor ecological and land use change in Britain using standardised procedures for recording ecological data from representative 1 km squares throughout the country. The same sites, with some additional squares, were used for subsequent surveys of vegetation undertaken in 1990, 1998 and 2007, with the intention of future surveys. Other data records include soils, freshwater habitats and invertebrates, and land cover and landscape feature diversity and extents. These data have been recorded in the same locations on analogous dates. However, the present paper describes only the details of the vegetation surveys. The survey design is a series of gridded, stratified, randomly selected 1 km squares taken as representative of classes derived from a statistical environmental classification of Britain. In the 1978 survey, 256 one-kilometre sample squares were recorded, increasing to 506 in 1990, 569 in 1998 and 591 in 2007. Initially each square contained up to 11 dispersed vegetation plots but additional plots were later placed in different features so that eventually up to 36 additional sampling plots were recorded, all of which can be relocated where possible (unless the plot has been lost, for example as a consequence of building work), providing a total of 16 992 plots by 2007. Plots are estimated to have a precise relocation accuracy of 85 %. A range of plots located in different land cover types and landscape features (for example, field boundaries) are included. Although a range of analyses have already been carried out, with changes in the vegetation being related to a range of drivers at local and national scales, there is major potential for further analyses, for example in relation to climate change. Although the precise locations of the plots are restricted, largely for reasons of landowner confidentiality, sample sites are intended to be representative of larger areas, and many potential opportunities for further analyses remain. [ABSTRACT FROM AUTHOR]

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower dispersal abilities generally. The evidence for interactions among landscape and farming system in their effects on spiders highlights the importance of developing strategies for managing farmland at the landscape-scale for most effective conservation of biodiversity. [ABSTRACT FROM AUTHOR]

The importance of habitat for biodiversity is well established, but the two most commonly used methods to measure habitat (field survey and remote sensing) have seldom been explicitly compared., We compare high-resolution sample-based field survey (Countryside Survey) with medium-resolution remotely sensed habitat data (the highest resolution of Land Cover Map available) for Great Britain. Variation in abundance of 60 bird species from 335 1 km squares was modelled using habitat predictors from the two methods. Model comparisons assessed the explanatory power of (i) field survey vs. remotely sensed data and (ii) coarse information on habitat areas (Broad Habitats) vs. fine-grained information on Landscape Features., Field survey data (combining Broad Habitat and Landscape Feature predictors) explained more variation in bird abundance than remotely sensed data (comprising Broad Habitat predictors only) for 57 species and had significantly higher mean explanatory power, averaged across 60 species models. The relative explanatory power of remote sensing, as a proportion of that provided by field data, was measured at 73%, averaged across 60 species models. Predictions from field survey Broad Habitat data were more accurate than those from either remotely sensed Broad Habitat data or field survey Landscape Feature data, averaged across 60 species models., High-resolution data generate more reliable models of predicted local population responses to land use change than lower resolution remotely sensed data. Collection of field data is typically costly in time, labour and resources, making use of remote sensing more feasible for assessment at larger spatial extents if data of equivalent value are produced, but the cost-benefit threshold between the two is likely to be context specific. However, integration of field survey with remotely sensed data provides accurate predictions of bird distributions, which suggests that both forms of data should be considered for future biodiversity surveys. [ABSTRACT FROM AUTHOR]

Conventional modes of environmental governance, which typically exclude those stakeholders that are most directly linked to the specific place, frequently fail to have the desired impact. Using the example of lake water management in Loweswater, a small hamlet within the English Lake District, we consider the ways in which new “collectives” for local, bottom-up governance of water bodies can reframe problems in ways which both bind lay and professional people to place, and also recast the meaning of “solutions” in thought-provoking ways. [ABSTRACT FROM AUTHOR]

SummaryExperimental grassland communities (turves) were exposed to supplemental levels of UV-B radiation (280–315 nm) at an outdoor facility, under treatment arrays of cellulose diacetate-filtered fluorescent lamps which also produce UV-A radiation (315–400 nm). Control treatments consisted of arrays of polyester-filtered lamps, which allowed for exposure to UV-A radiation alone, and arrays of unenergized lamps allowing for exposure to ambient levels of solar radiation. [ABSTRACT FROM AUTHOR]

ABSTRACT The achievements of the Green Revolution in meeting the nutritional needs of a growing global population have been won at the expense of unintended consequences for the environment. Some of these negative impacts are now threatening the sustainability of food production through the loss of pollinators and natural enemies of crop pests, the evolution of pesticide resistance, declining soil health and vulnerability to climate change. In the search for farming systems that are sustainable both agronomically and environmentally, alternative approaches have been proposed variously called ‘agroecological’, ‘conservation agriculture’, ‘regenerative’ and ‘sustainable intensification’. While the widespread recognition of the need for more sustainable farming is to be welcomed, this has created etymological confusion that has the potential to become a barrier to transformation. There is a need, therefore, for objective criteria to evaluate alternative farming systems and to quantify farm sustainability against multiple outcomes. To help meet this challenge, we reviewed the ecological theories that explain variance in regulating and supporting ecosystem services delivered by biological communities in farmland to identify guiding principles for management change. For each theory, we identified associated system metrics that could be used as proxies for agroecosystem function. We identified five principles derived from ecological theory: (i) provide key habitats for ecosystem service providers; (ii) increase crop and non‐crop habitat diversity; (iii) increase edge density: (iv) increase nutrient‐use efficiency; and (v) avoid extremes of disturbance. By making published knowledge the foundation of the choice of associated metrics, our aim was to establish a broad consensus for their use in sustainability assessment frameworks. Further analysis of their association with farm‐scale data on biological communities and/or ecosystem service delivery would provide additional validation for their selection and support for the underpinning theories. [ABSTRACT FROM AUTHOR]

This study provides a first national-scale assessment of the nutrient status of British headwater streams within the wider river network, by joint analysis of the national Countryside Survey Headwater Stream and Harmonised River Monitoring Scheme datasets. We apply a novel Nutrient Limitation Assessment methodology to explore the extent to which nutrients may potentially limit primary production in headwater streams and rivers, by coupling ternary assessment of nitrogen (N), phosphorus (P), and carbon (C) depletion, with N:P stoichiometry, and threshold P and N concentrations. P limitation was more commonly seen in the rivers, with greater prevalence of N limitation in the headwater streams. High levels of potential P and N co-limitation were found in the headwater streams, especially the Upland-Low-Alkalinity streams. This suggests that managing both P and N inputs may be needed to minimise risks of degradation of these sensitive headwater stream environments. Although localised nutrient impairment of headwater streams can occur, there were markedly lower rates of P and N impairment of headwater streams relative to downstream rivers at the national scale. Nutrient source contributions, relative to hydrological dilution, increased with catchment scale, corresponding with increases in the extent of agricultural and urban land-use. The estimated nutrient reductions needed to achieve compliance with Water Framework Directive standards, and to reach limiting concentrations, were greatest for the Lowland-High-Alkalinity rivers and streams. Preliminary assessments suggest that reducing P concentrations in the Lowland-High-Alkalinity headwater streams, and N concentrations in the Upland-Low-Alkalinity rivers, might offer greater overall benefits for water-quality remediation at the national scale, relative to the magnitude of nutrient reductions required. This approach could help inform the prioritisation of nutrient remediation, as part of a directional approach to water quality management based on closing the gaps between current and target nutrient concentrations. [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]