Quantifying

Several projects took on the challenge of measuring and quantifying interdisciplinarity through structured methods.

In some projects experts from different disciplines and key stakeholders scored and ranked the relevance of research findings, topics and factors to study. In others they put a value on the social and natural factors contributing to a particular problem.

By engaging experts from a wide range of disciplines and stakeholders with differing interests and concerns, researchers aimed to weigh up and numerically define the different disciplinary angles of the problems studied, whilst at the same time avoiding disciplinary bias.

CASE STUDY

Expert weighing of risk factors

The project studied microbial pollution risks of watercourses from livestock farming. Joint reasoning and learning about this environmental protection issue from different analytical and interpretive starting points was a fundamental aspect of the research process. Co-production of data, interpretations and outputs resulted in the development of a practical learning tool to mitigate microbial risks at both the farm and field levels. It also informed a process of citizen science for the public scrutiny of these risks.

Making sense of the underpinning drivers of pollution risks depends on a wide assessment of the various physical, social and economic characteristics of farms that can contribute to run-off and result in water pollution.

The team integrated the monitoring of watercourses for potential pathogens with determining E. coli mobilisation from faecal material; and desk-based identification of diffuse microbial pollution mitigation measures with interviewing farmers about their attitudes and practices towards livestock management. Farm maps were used during interviews to represent the character of, and reasoning behind, management actions.

Expert elicitation was used to prioritise and assign weighting to key social and natural risk factors that exist across farm systems. Such risk factors are categorised into four components: infrastructure characteristics of farms; E. coli burden; the run-off potential of farm land; and farmers approaches and attitudes towards manure, land and animal management.

The results were translated into a risk assessment tool - nick-named the 'kite' tool to reflect the four components that interact to influence risk - that can be used to graphically represent cumulative risks posed by any farm enterprise, so that decisive interventions can be put in place.

Risk also depends on a deeper and unresolved set of uncertainties regarding what might constitute appropriate levels of intervention, and where responsibilities for action and investment lie. The project investigated the scientific and political basis for action against these microbial risks through a citizens' jury, which reinforced the case for strong state support of microbial risk management, but also added weight to the case for cross-industry subsidies of mitigative action.

Sustainable and safe recycling of livestock waste
David Chadwick, Rothamsted Research, North Wyke

 

CASE STUDY

Best-worst scaling of interventions for infectious diseases

The researchers applied an established market research tool - best-worst scaling - to elicit and analyse perceptions of the effectiveness and practicality of interventions to manage E. coli O157 risk in farming and rural settings.

Candidate interventions were proposed by project team members based on findings from key stakeholder interviews. This generated 99 interventions to manage E. coli O157 risk. Experts from a broad cross-section of academic disciplines - public health sector, environmental microbiology, epidemiology, veterinary sciences and land management - as well as many farmers in the study regions, then commented on the relative effectiveness of the proposed interventions through best-worst scaling. This allowed each expert to give a differing perspective on the marking of the most effective process.

Best-worst scaling is a choice-based technique whereby respondents make repeated choices between sets of options. In this project, experts in a first instance assessed 12 options sets that each contained 5 interventions, indicating the most and least effective measures to reduce E. coli O157 in each set. This round reduced the number of interventions to the 30 interventions considered to be most effective. The process was then repeated with livestock farmers, who chose what they perceived to be the most and least practically implementable interventions in the field. Experts and farmers therefore combined their opinions on an equal footing to generate a list of interventions that were considered to be both effective and practical to implement.

A selection of the top 30 interventions was modelled using quantitative microbiological risk assessment to determine their potential to reduce E. coli O157 exposure to humans.

This technique has the potential to be applied to assess interventions associated with other infectious diseases.

Reducing E. coli risk in rural communities
Norval Strachan, University of Aberdeen

 

CASE STUDY

Sustainable appraisal framework

Future policies are likely to encourage more land use under energy crops - principally willow, grown as short rotation coppice, and the tall grass Miscanthus. These crops will make an important contribution to the UK's commitment to reducing CO2 emissions and are grown under low input agriculture.

However, they are quite different from the arable crops that we are used to and it is not clear how planning decisions based on climate, soil and water should be balanced against impacts on the landscape, social acceptance, biodiversity and rural economy. The problem is that these wider implications of land use change have not been investigated, and there has been no attempt to identify the full extent of the broad range of potential impacts, or more usefully, to highlight scenarios for land use change which can minimise negative impacts and accentuate positive impacts.

The dominant environmental governance goal over the last two decades has been the achievement of sustainable development. Such a goal is normally conceptualised in terms of social, economic and environmental 'pillars', and recognises the need for humanity to co-exist with nature. As such, an investigation of the implications of spatial change needs to combine evidence of impacts on the natural environment within a socio-economic and political setting that provides the context for sustainable land management decisions.

To combine the social and natural sciences, sustainability appraisal was used to incorporate social, economic and environmental criteria and data in a single framework. This uses a workshop approach that enables participants to question natural scientists, social scientists and economists to improve knowledge and understanding (the analytic component); thus facilitating more informed deliberation (the deliberative component) over the key sustainability criteria to include.

Sustainability appraisal is adapted from spatial planning. It relies on examining the sustainability implications of policy options in order to determine the best ones to take forward. Implications are determined by testing the options against social, economic and environmental sustainability objectives measured through the use of indicators.

In this project, the team agreed on scenarios to be tested (equivalent to policy options) with a broad range of stakeholders including growers, government agencies, energy companies, non-governmental organisations, union members, etc. The same broad stakeholder engagement was used to develop the sustainability appraisal framework and to interpret the results.

Impacts of increasing land use under energy crops
Angela Karp, Rothamsted Research

 

CASE STUDY

Choice experiment to value changes in upland landscapes

Recent work in the economics literature stemming from behavioural psychology suggests that the act of experiencing a 'good' impacts on preference. That means that, for a given individual, their forecast or memories of utility (relative satisfaction) are likely to differ from those stated at the moment of experience. But in the past this theory has only been tested using happiness-based measures of utility, and not for environmental goods.

This project applied the choice experiment technique to valuate changes in upland landscapes in the UK in order to identify whether experience, at that moment or in memory, impacts on the value associated with changes in ecosystem services under different management regimes. Four treatments were employed using the same sample to measure decision utility (off-site), experienced utility (on-site), and remembered utility at two different time intervals (off-site).

On-site treatment generates very different estimates of preferences than any of the off-site treatments. Whilst measurement of experienced utility is fraught with difficulties, the approach taken allowed the identification of experiential impacts on utility.

It was found that the act of experiencing an environmental good altered how individuals made decisions about environmental resources. They changed their views on the cost to the environment, with more emphasis placed on environmental goods. This result may have implications for the future use of experienced utility as a basis for the valuation of public goods.

The sustainability of hill farming
Nick Hanley and Dugald Tinch, University of Stirling