Stakeholder engagement

Interdisciplinary working enabled closer engagement with stakeholders in the research and incorporation of their expertise.

Stakeholders were involved in data collection, ground truthing research findings, modifying and validating models and scrutinising findings. Through their interdisciplinary teams the researchers developed new methods of participatory research. Ecologists said that being able to work more closely with stakeholders was one of the main benefits of working with social scientists


Stakeholders ground truth ecological models

Most kinds of natural resources are best managed collaboratively. In a free-for-all, a resource is likely to be over-exploited with each user attempting to extract his or her maximum benefit in the short term. But simply knowing that collaboration is a good idea does not guarantee that it can be achieved.

Red deer management is an excellent case study to investigate collaboration because deer provide both societal benefits and costs: wild deer are not owned by anybody but as they move around, they cross boundaries and provoke potential conflicts between neighbouring owners who have differing management goals.

Researchers have developed many models to predict wildlife use of habitats. These are often of little value for local management because their predictions do not match observations, largely because they do not take account of the local management actions. For models to be credible tools to develop collaborative solutions for wildlife management, they need to bring together scientific knowledge with the wealth of insights held by those who manage these resources.

ji1.gifThe challenge was to capture the knowledge of local managers and use this in a model of deer distribution to then create predictions that fitted the observed data. The credibility of the deer distribution predictions in the eyes of managers would be enhanced, making it a useful tool to explore potential conflicts between neighbours or between local practice and national policy objectives.

The team developed a participatory approach to integrate deer managers' local knowledge with scientific understandings and ecological spatial data in a simple Geographic Information System (GIS).

Managers' knowledge on deer habitat use in relation to shelter and forage, together with local information on paths, fences and habitat changes was used to change the way in which the GIS developed deer distribution predictions. The results fitted very well with observed data and were much better than predictions from a model based only on the existing scientific data. They clearly showed the value of using local knowledge.

ji2.gifThis approach allows knowledge from different sources and at different spatial scales to be combined to give realistic predictions of deer distribution. Such participatory interdisciplinary approaches to wildlife-habitat models can improve communication and consensus across ownership boundaries where different management objectives exist and can therefore remove key obstacles to collaborative natural resource management.

The team also explored the perspectives of researchers and stakeholders on the successes and challenges of this way of working. Perceived benefits of a participatory interdisciplinary approach included improved social networking, social and technical learning and academic achievements. Challenges included the time and cost of intensive engagement, the building of relationships within the constraints of the research project, meeting diverse expectations and the difficulties of integrating different forms of knowledge.

Collaborative deer management
Justin Irvine, Macaulay Institute



Participatory modelling to support catchment management

Reductions in water pollution have so far been achieved mainly through regulation and investment in waste water treatment, but the underlying water quality problem in much of the UK is diffuse pollution derived from current and past land use, plus atmospheric deposition.

The project focused on how to improve the ecological quality of rivers and lakes and worked in two case study catchments: Tamar and Thurne. A key proposition has been that stakeholders with differing understandings and values must weigh up catchment management options. This requires a shared knowledge base and common understanding of processes of water quality degradation.

The team developed a participatory modelling approach and built an Extended Export Coefficient Model in which they incorporated local knowledge. Stakeholders were involved in developing the model and in testing and applying it, through a series of workshops and evening meetings. Stakeholder analysis and 'circuit riding' through face-to-face meetings and telephone conversations by a social scientist, first built interest and trust in the process. Continuity of engagement of key representatives of varied stakeholder groups was achieved through the series of meetings. These followed an adaptive planning and management cycle of visioning, catchment and pollution characterisation, pollution source and pathway modelling, scenario development and implementation planning.

Graphical modelling of catchment processes was used to clarify expectations and create a shared understanding. In the words of a leading Thurne farmer: "After living and farming in the area for so many years this diagram has brought home to me for the first time the importance of the pumps in the Thurne catchment and that otherwise surface inflows are relatively insignificant. It does provide a good means to capture local understanding of the catchment."

Whilst the mathematics of the modelling depends on expert knowledge, key assumptions, sources of uncertainty and limitations were all scrutinised by stakeholders. The local knowledge of stakeholders, in particular farmers, was essential to ground truth data like agricultural census data. This knowledge also allowed the inclusion of the impact of farmer adoption of management practices, best suited to local conditions, into the model.

Using farmers' knowledge for otherwise unknown parameters, and ground truthing data and outputs with farmers - who had previously been disengaged - built trust and demonstrated social learning. This built ownership of the process and a commitment to collective action. Stakeholder testing also helped the design of user-friendly interfaces for running scenarios and showing outputs.

Expertise from the social sciences helped design and facilitate the processes of data collection and engagement. Advanced statistical methods were used to account for model uncertainties but the model's credibility and its probabilistic predictions were improved by the modeller explaining these in lay terms, and being open towards interpretation and suggestions by stakeholders. In the words of a Tamar farmer: "How on earth could you have come up with a single number as a result anyway?"

In the iterative and participatory planning process the model was the essential tool that enabled participants to frame the scale and severity of selected water quality problems. Management scenarios were explored in real time, stimulating dynamic and engaged debate. Management options were then costed and a collective assessment made of governance and implementation arrangements.

The lessons from this experience were combined with wider interdisciplinary assessments of international examples of catchment management programmes that integrate the best science with effective communication tools and decentralised and collaborative modes of governance. This provides guidance for catchment management in the UK and other areas of intensive agriculture and dense rural settlement.

Catchment management for protection of water resources
Laurence Smith,



Competency groups - an experimental method for collaborative environmental research

This project sought to understand how and why flood risk management, and the forecasting technologies on which it relies, become matters of public controversy.

It combined the ethnographic techniques of science and technology studies with hydraulic modelling and experimented with a new method of bringing the knowledge of local people with experience of flooding to bear on the modelling of flood risk - competency groups. This method was trialled in two localities in which flood risk management was already in dispute - Ryedale in Yorkshire and the Uck catchment in Sussex.

The competency group approach is designed to 'slow down reasoning' in the event of a knowledge controversy, enabling those affected by flood to interrogate the expert knowledge claims and practices that inform existing flood management policies and to try out alternative ways of understanding and mitigating local flooding problems. It centred on bi-monthly meetings over a 12-month period in which hands-on computer modelling became the key practice, supplemented by field visits, the production and analysis of video and photographic materials and other collaborative research activities.

The groups combined the different experiences and skills of the natural and social scientists in the project team (university members) with those of volunteer residents affected by flooding (local members) by working closely with various materials and artefacts that embody expert knowledge claims - flood maps and computer models. This way of working also emphasises the importance of producing new materials and artefacts to help the group's own knowledge; and propositions 'travel' and therefore make a difference to public debate and policy-making.

The approach requires a sustained commitment from all to negotiate the different modes of reasoning of fellow participants and to appreciate the different kinds of expertise brought to the collaborative production of knowledge. The project produced a web-resource to help others in trying out competency groups.

Understanding environmental knowledge controversies: the case of flood risk management
Sarah Whatmore, University of Oxford



Modelling environmental factors for the community

Algal blooms are excellent indicators of declining water quality. Their presence indicates that there are excessive nutrients in the water body. In Loweswater, the occurrence of regular potentially toxic blooms of blue-green algae and their impact on visitors and locals, made it important for scientists and local people to try to understand more about the sources of those nutrients. Then locals could begin to address potential causes and take on the management of their catchment area.

The algal problem at Loweswater clearly required studying linkages between humans and the land and also between land and water. This meant scientists from different disciplines had to step outside of their disciplinary boundaries and focus on how the specific systems that they specialise in are connected to, and interact with, other systems.

Scientists, local residents and agencies worked together to form a new organisation, the Loweswater Care Project, through which scientists could draw on the benefits gained from being closely engaged with catchment stakeholders from institutions and the community. This maximised the use of information, expertise and data available to the modellers and drew on the knowledge and experience of stakeholders to identify the important factors which needed to be included in the modelling. Residents' memories of land use changes, changes in agricultural practice, environmental changes and the ways in which relations within the community and the composition of the community of Loweswater have changed in time contributed substantially to inform the research priorities.

The team developed a series of three simple linked models, with outputs from one model leading into the other. The models linked land management processes and land cover to catchment hydrology and nutrient flow and further to algal populations in the lake. Modellers felt an unusual responsibility to make the model relevant to Loweswater Care Project participants, because of the close connections forged, especially with those involved in farming the land.

Modelling incorporated information from farmers on farm management and soil data, septic tanks data collected by a local resident, rainfall data collected by residents in the catchment area, alongside information collected by scientists and the Environment Agency.

The modelling demonstrated to the Loweswater Care Project how land cover and land use in the catchment impact on algal populations and showed various scenarios of change of algal populations in response to changes in land cover and use.

Testing a community approach to catchment management
Claire Waterton, Lancaster University