Notes from two talks from the session on the role of expert knowledge. Details of the session in full are here.
The potential of citizen science to inform expert understanding: a case study of an urban river in London
Iain Cross (St Mary’s University, UK), Rob Gray (Friends of the River Crane Environment), Joe Pecorelli (Zoological Society of London, UK)
Richard Haine (Frog Environmental, UK)
Richard Haine (Frog Environmental, UK)
Abstract: “Increasingly, expert knowledge is becoming only one of many sources of understanding that influence environmental decision making and policy formulation. Traditional, top-down and technocratic modes of knowledge production are being challenged and, through what has been termed the ‘participatory turn’, knowledge is often co-produced among ‘experts’ and ‘non-experts’. A particularly widespread source of ‘non-expert’ knowledge is the citizen science (CS) community. CS projects can enable data to be collected over spatial or temporal scales that would be prohibitively expensive or logistically impossible for ‘expert’ data collection techniques. Whilst this data might be highly useful for policy and decision making, there can be a tension between the perceived reliability, accuracy or value of CS data compared to ‘scientifically collected’ data. This paper explores this tension in the context of an urban river CS project in London, through interviews with ‘experts’ and ‘non-experts’ from a variety of stakeholders. It highlights how significant events affecting the river environment mobilised public interest and the subsequent generation of ‘non-expert’ knowledge of the river. The paper provides an insight into how the perceived credibility and value of CS data by ‘experts’ can evolve over time, to become a significant driver of decision making. Key factors that have shaped this process include formal reporting mechanisms, partnerships with local authorities and statutory bodies, and corroboration of CS data with ‘expert’ data. The paper argues that CS blurs the traditional boundary between experts and non-experts and therefore challenges traditional definitions of ‘expert’ knowledge in environmental decision making.”
Iain Cross discussed citizen science as a source of expertise in an urban river. The situation is multiple stressors and degraded situation, ecosystems that deserve attention. They are subject to social/cultural interaction with the environment and nature. This makes it useful for citizen science – people volunteer to local groups, and also desire to do something – the intersection of volunteering and activism, there is a potential pool of local residents, and need for data. Look at the small catchment in west London ith multiple transport routes, lots of draining: urban run-off, sewage, domestic misconnections, surface water – and there are two major incidents in 2011 and 2013. The catchment partnership was created as a compensation for a major pollution incident. The £400K established a partnership that is working through the delivery of specific projects. Citizen science in three areas: water quality, riverfly monitoring, outfalls safari to identify where they are and their sources. The citizen science had a key role in the management decision. Try to identify differences between direct influence – data is used for regulation, and indirect. Examples for direct: reprioritisation of water company outfall projects (so where they dedicate resources to address them), and enforcement and additional investigations based on the data. Indirect – more reporting of water quality, empowering to understand the process a common language on what the regulator need, and exporting the model to neighbouring catchments. The research try to understand how did it became a credible source of knowledge, understand its influence and what happen in the future, through semi-structured interviews. So far there are 3 interlinked themes: early engagement with water company, a tight leadership of the project, and reliable data. Participants understand the regulatory environment , harmonisation of expert practices and reporting at conferences. In terms of project management 0 influence of certain people – and past contact and engagement with citizen science. The champions are very important – even within the regulators. The last thing is the production of good quality data – awareness of accreditation, QA process, spatial and temporal coverage attention and interpretation and reporting of data.
Expert and Experiential Knowledge in Pollinator Policy: The Perspectives of Beekeepers Siobhan Maderson (Aberystwyth University, UK)
Abstract: “Recent policy initiatives aim to counter the precipitous decline of pollinators and thus secure their role in food security and broader ecosystem services. The practical experiences and observations of beekeepers are recognised as having the potential to both monitor, and improve, the wellbeing of pollinators As part of wider trends towards participatory governance, many initiatives notably stress the importance of engaging with beekeepers, as well as scientists, and other stakeholders whose study or practice holds the potential to improve environmental conditions that impact pollinator wellbeing. However, such multi-stakeholder engagement still prioritises ‘experts’, and struggles to adequately incorporate knowledge which contradict wider policies. This paper will discuss the perceptions of beekeepers on the relative influence and use of ‘expert’ and ‘experiential’ knowledge in pollinator policy-making. Unlike the expert scientific knowledge relied upon by policy-makers as central to EBPM, beekeepers’ understanding of bee health engages with systemic factors that are often hard to quantify or prove according to conventional scientific criteria. Beekeepers’ views result from long-term observation and engagement with specific local environments. Beekeepers are also a disparate community, holding contrary views on land use, agriculture, and the best means of ensuring pollinator wellbeing. My current PhD research focuses on interviews with long-term beekeepers whose tacit expertise is widely recognised throughout diverse beekeeping communities. I address the knowledges appropriated, and sidelined, in current pollinator policy, and how experiential knowledge is utilised by experts. I also address the challenges resulting from beekeepers’ tacit knowledge contrasting with current agricultural, land use, and economic policies.”
The research is concerned with pollinator decline, the threat to food security and the beekeepers seen as key stakeholders – both as monitoring: grounded knowledge in wellbeing and have the practical knwoledge. They can provide direct knwoeldge. The beekeepers also have a history of collaboration with scientists – e.g. providing details on harmful material (spraying incidents). Research include 36 beekeepers, archive and ethnography – many have a long term experience in the field. The discourse is about enthusiasm, citizen science, lay knowledge and related areas. She understand about environmental knowledge and observations, understanding their position within the community of practice and association, and also understanding views of policy making process and on the scientific process. The interviewees have massive knowledge – playing roles of inspectors, farmers, teaching others, board members of association, some several generations of beekeeping families – detailed local knowledge. The interviewees have STEM background. The results are showing that beekeepers combine tacit and explicit knowledge, and have profound specific local knowledge – microclimate, forage. Also had experience of involvement in policy and scientific research – they engage with entomologists. They do have empathy with farmers, frustration with voluntary initiatives and the wider food systems are seen as responsible for the problems. They collect data on phenology in the area, weather etc. There was a question about the debate and someone sceptic to media and public response to pollinator. In terms of participation in research – they do read scientific papers, but they feel that it is one way system – they put input and don’t feel that scientists take their views seriously. They feel lack of addressing local needs and policy process. They are doing lots of scientific processes – microscopy, pollen analysis and all sort of other information.