Factors influencing biodiversity within organic and conventional systems of arable farming – methodologies and preliminary results

This report was presented at the UK Organic Research 2002 Conference. This paper describes the approaches and preliminary results of a study that is designed to provide a large amount of data at a range of scales in order to investigate the potential factors influencing biodiversity on arable farmland on comparable organic and conventional farms. In particular, the study examines the role of non-crop habitats within the different farming systems and how the extent and management of non-crop habitats differs between them. A detailed description of the methodologies being employed to establish differences in non-crop habitat, plant, invertebrate and bird diversity is given. The study remains in its early stages as a result of the impact of Foot and Mouth disease on the fieldwork schedule during 2001. The process of setting up the study revealed that the numbers of farmers growing cereals organically are low as a proportion of the organic sector as a whole, despite recent large increases in numbers of farmers converting to organic production. Preliminary results from the first year of fieldwork on plants reveal significant differences between organic and conventional farms in terms of the numbers of weed species on fields and non-significant differences in numbers of species found on non-crop habitats

Land cover and vegetation data from an ecological survey of `key habitat' landscapes in England, 1992-1993

Since 1978, a series of national surveys (Countryside Survey, CS) have been carried out by the Centre for Ecology and Hydrology (CEH) (formerly the Institute of Terrestrial Ecology, ITE) to gather data on the natural environment in Great Britain (GB). As the sampling framework for these surveys is not optimised to yield data on rarer or more localised habitats, a survey was commissioned by the then Department of the Environment (DOE, now the Department for Environment, Food and 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 (calcareous) grasslands, coasts and uplands. The information recorded allowed an assessment of the extent and quality of a range of habitats defined during the project, which can now be translated into standard UK broad and priority habitat classes. The survey, known as the "Key Habitat Survey", followed a design which was a series of gridded, stratified, randomly selected 1 km squares taken as representative of each of the four landscape types in England, determined from statistical land classification and geological data ("spatial masks"). The definitions of the landscapes are given in the descriptions of the spatial masks, along with definitions of the surveyed habitats. A total of 213 of the 1 km2 square sample sites were surveyed in the summers of 1992 and 1993, with information being collected on vegetation species, land cover, landscape features and land use, applying standardised repeatable methods. The database contributes additional information and value to the long-term monitoring data gathered by the Countryside Survey and provides a valuable baseline against which future ecological changes may be compared, offering the potential for a repeat survey. The data were analysed and described in a series of contract reports and are summarised in the present paper, showing for example that valuable habitats were restricted in all landscapes, with the majority located within protected areas of countryside according to different UK designations. The dataset provides major potential for analyses, beyond those already published, 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 dataset makes it highly valuable for evaluating the status of ecological elements within the associated landscapes surveyed. 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

Improving and expanding hedgerows - recommendations for a semi-natural habitat in agricultural landscapes

•1. Hedgerows provide habitat, shelter and resources for many species including functionally important taxa and threatened species. Hedgerows store carbon both above- and below-ground and provide a range of other ecosystem services. Policies incentivizing increases in the extent and quality of hedgerows require evidence to determine how these increases may best support a wide range of taxa and to improve hedgerow habitat quality. •2. Here, available evidence for increasing hedgerow extent and improving their quality is discussed in the context of current conservation policy. Moderate evidence supports a substantial increase in average hedgerow extent from 4.2 km/km2 to around 10 km/km2 in the United Kingdom, to optimize support for many wildlife taxa, habitat connectivity and carbon storage. •3. Evidence also supports the development of wider and structurally denser hedges with more diverse structures and management approaches, and hedgerow networks that are well connected with each other and with other semi-natural habitats. •4. However, barriers may hinder the implementation of hedgerow policies, and there remain substantive gaps in the evidence base. Knowledge gaps include the current quality or condition of UK hedges, understanding in which landscape contexts new hedges would best be planted to support biodiversity, the role of hedgerows in connectivity as species' ranges change under a future climate, and whether an increase in hedgerow extent might increase the spread of invasive species, tree pests or diseases. •5. These gaps must be filled if conservation policies, including future agri-environment schemes, are to ensure that hedgerows reach their considerable potential in aiding nature's recovery and addressing climate change

The Heavy Vehicle Study: a case-control study investigating risk factors for crash in long distance heavy vehicle drivers in Australia

Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network

Pasture age impacts soil fungal composition while bacteria respond to soil chemistry

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 bacterial and fungal communities show within field heterogeneity that varies by land management and distance metric

Increasing interest in the use of microbial metrics to evaluate soil health raises the issue of how fine-scale heterogeneity can affect microbial community measurements. Here we analyse bacterial and fungal communities of over 100 soil samples across 17 pasture farms and evaluate beta diversity at different scales. We find large variation in microbial communities between different points in the same field, and if Aitchison distance is used we find that within-field variation is as high as between-farm variation. However, if Bray-Curtis or Jaccard distance are used this variation is partially explained by differences in soil pH and vegetation and is higher under mob grazing for fungi. Hence, field scale variation in microbial communities can impact the evaluation of soil health

An analytical framework for spatially targeted management of natural capital

A major sustainability challenge is determining where to target management to enhance natural capital and the ecosystem services it provides. Achieving this understanding is difficult, given that the effects of most actions vary according to wider environmental conditions; and this context dependency is typically poorly understood. Here, we describe an analytical framework that helps meet this challenge by identifying both why and where management actions are most effective for enhancing natural capital across large geographic areas. We illustrate the framework’s generality by applying it to two examples for Britain: pond water quality and invasion of forests by rhododendron

Phosphorus and nitrogen limitation and impairment of headwater streams relative to rivers in Great Britain: a national perspective on eutrophication

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

The relative value of field survey and remote sensing for biodiversity assessment

1. 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. 2. 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. 3. 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%, aver aged 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. 4. 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