When landscape planning becomes landscape governance, what happens to the science? Raoul Beunena and Paul Opdama. Wageningen University, PO Box ...
This is a revised personal version of the article published in Landscape and Urban Planning. Please cite as: Beunen, R, & Opdam, P. (2011) When landscape planning becomes landscape governance, what happens to the science?. Landscape and Urban Planning 100: 324–326. doi:10.1016/j.landurbplan.2011.01.018
When landscape planning becomes landscape governance, what happens to the science? a
Raoul Beunen and Paul Opdam
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Wageningen University, PO Box 8130, 6700 EW Wageningen , The Netherlands
ABSTRACT
A key issue of scientific research is the impact of science in landscape planning. Two trends in society demand this issue to be a research priority: the decentralization of government power to the local level and the growing distrust towards experts and scientific knowledge in policy and the public. We show how these trends challenge the role and position of science in landscape planning. We conclude that it is urgent to systematically extend our knowledge on the impact of science in decision-making networks. Keywords: science-practice nexus, social networks, credibility.
challenged by two currents: the change from government to governance in landscape adaptation and the growing criticism and distrust towards scientific knowledge (Schermer, 2010). Hence, we focus on the local level of landscape planning where the sceptical attitude towards scientific knowledge is fed by a growing dissatisfaction among both citizens and experts about the outcomes of decision-making.
INTRODUCTION
In this essay we address the role of scientific knowledge in planning and decision-making concerning adapting landscapes to future demands, and conclude that research on the impact of scientific knowledge in local landscape planning should be a research priority. Many scientists have dealt with the relation between science and society in a general or philosophical way (e.g. Nowotny et al. 2001; Fischer, 2009 Latour, 2004). The main message from these discussions is that useful scientific knowledge merges from a coproduction between scientists and practitioners. However, these general discussions do not provide insight into the role scientific knowledge plays in landscape planning processes, and how this impact can be optimized by adapting the structure of this knowledge and the way it is incorporated into decision making. We propose that these questions should be high on the landscape research agenda, because the role of landscape science in society is
LANDSCAPE GOVERNANCE AS AN ARENA FOR SCIENTISTS
The term landscape governance reflects two contemporary, interrelated changes in the scale and organisation of decision-making about the landscape (Van Assche et al., 2014). Firstly, government power is decentralized to the lower tiers of the government, and secondly a growing number of private parties and citizens actively participate in decision-making. As a consequence the role of government organisation is shifting towards coordination and fusion of public and
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private resources (Domingo and Beunen, 2012; Van Assche et al., 2013).
area much better than scientist do, but have difficulties interpreting facts in a generic evidencebased knowledge context. Actors within the process are not always convinced by fact and figures and may deny the scientific basis for defining problems or sustaining solutions. Such critics can for example be found in the debates surrounding climate change, natural resource governance or public health (Schermer, 2010). In the decision-making processes scientific knowledge is also selectively used to advocate or reject claims, which further draws science into the domain of political arguing. Governmental and non-governmental organizations for example utilize knowledge to reinforce their own position of power, while de-legitimizing the knowledge of competing organizations, practitioners and citizens. These issues should be taken into account in the assessment of the impact of science in decisionmaking networks.
These changes have important implications for the role and position of scientific knowledge within landscape planning and management practices. The traditional government model focussed on scientist informing policy-makers who needed knowledge or technical advice is changing. According to the governance model private parties, like NGOs and citizens, are active actors at the science-practice nexus. The governance model takes into account the complexity of today’s society, which is dependent on the relationships between many formal and informal institutions and actors. Politicians, interests groups and citizens bring in a variety of competing and evolving perspectives upon the issues at stake. There is a growing awareness of the consequences of this complexity, ambiguity and uncertainty for the position of science in these planning practices, both among researchers and professionals (Van Assche et al., 2013; Fischer, 2009).
A NEW CHALLENGE TO LANDSCAPE RESEARCH
Several authors have addressed the difficult relationship between scientific and local knowledge and the consequences for the planning processes and their outcomes (Ellis & Waterton, 2005; Escobar, 1998). While in most of these studies the focus was on the impact of knowledge in environmental policy and the use by professionals (e.g. Yli-Pelkonen and Niemelä 2006), the impact of scientific knowledge in local collaborative landscape adaptation processes has been rarely addressed in environmental science. This is a critical issue since the societal position of landscape science heavily depends on its ability to show added value. It is not self-evident that local planning actors, who consider themselves as local experts, ask for the support of scientists to improve the evidence base for their decision making. How can science demonstrate its added value in landscape governance? How can science improve the quality of the decision making process, as well as of its outcome? We propose that landscape scientists must develop much more insight in how their knowledge and knowledge tools affect societal processes. We
While science aims for generic and universal phenomena, rules and relationships, the validity of such generalities is limited at the local level, because here problem solving requires a reinterpretation of generic rules in the local context, which almost by definition deviates from the average. For the application of scientific knowledge this means that the more generic guidelines which had been readily applied at the national or regional level are now replaced by site-specific interpretations involving a level of detail that is not addressed by peer-reviewed publications. Azerrad and Nilon (2005) have found that while technical guidance for environmental planning was useful at the state level, it was much less useful at the local scale. This reinterpretation of generic knowledge is a source of uncertainty, and may undermine the credibility of science among local practitioners. Decentralization also means that professionals of central governments, as users of knowledge, are replaced by local stakeholders who may know their 2
should be able to understand why scientific information is sometimes successfully used while in other situations it is not, how it contributes to the quality of the future landscape, and how it changes the social network in the area.
politicians, policy-makers, consultants, entrepreneurs and citizens. Whether knowledge that is proposed by somebody in the network can be accepted as contributing to the networks knowledge base depends on the actors involved in the network. All these networks have their own ways and criteria to assess the quality of knowledge production within the networks. It is therefore relevant to study how scientific knowledge is recognized by these different networks, and whether they distinguish knowledge based on scientifically rigorous methods from knowledge based on the experience of local actors. And if they do, which criteria they use?
To achieve this aim, two complementary approaches can be distinguished. One approach focuses on the knowledge itself, its characteristics, structure and form, for example whether it concerns a prescriptive guideline or a range of options. These characteristics should be considered in relation to the demands of the planning process. Cash et al. (2003) proposed three criteria to define the quality of knowledge in the context of the transfer of knowledge from science to practice: whether it is regarded as credible by its users, whether it is relevant to problem solving at the local level (for example, whether it allows trade-offs between land use values to be taken into consideration), and whether it is regarded as legitimate to local planning groups (for example: can local actors manipulate the knowledge to bring in their wishes and values?). There is little systematic research showing in which form scientific evidence best fits different phases of the planning processes or different planning cultures.
ADDING PRIORITIES TO THE RESEARCH AGENDA
Focussing on the valuation of scientific knowledge within different decision-making networks opens up new research opportunities in landscape science. This research would link with the growing attention paid to participatory planning process and the changing relationship between experts and citizens within these processes (e.g. Beunen et al., 2013; Fischer, 2009). Scientific knowledge can only impact decisionmaking if it is used by the people involved in the decision-making process. In the field of landscape governance the decision-making networks are very diverse and continuously changing. Due to ongoing decentralisation the position of citizens and experts within these networks has changed. The distrust that is often shown towards experts and their knowledge can be seen as a consequence of this new position and the uneasiness of experts in dealing with their new role. Scientists who want to contribute to societal issues should be aware that the shift towards governance implies that they have to participate in networks that use different criteria to assess the value of scientific knowledge (Latour, 2004). These differences make it difficult to predict the role of scientific knowledge within different networks. We propose a critical need for a more reflexive approach to researching the role of scientific knowledge in landscape governance. We agree with McNie (2007) that more research is needed to explore and
The second approach emphasizes the human factor instead of the knowledge itself. It assumes that knowledge is always produced in social practices, and focuses on knowledge construction within social networks. From such a perspective knowledge is not defined as the sum of all the knowledge held by scientist or published in books and journals, but as an attribution or expectation of a social network (Fuchs, 2001). Fuchs suggested that a better understanding of the relationship between knowledge and practice starts with understanding how social networks acquire new knowledge and integrate it into their competence. Following his ideas we can distinguish different types of social networks of which scientists working on the science-policy nexus are part (for example scientific networks and networks in planning practices). Within the decision-making networks scientists are among a wide range of other people, like 3
understand the dynamics of the demand side of scientific knowledge. This implies focussing on how social networks make decisions and how scientific knowledge affects the decision-making processes. Effective use of scientific knowledge depends on the characteristic of the knowledge that it provides as well as on the social and political factors that influence the decision-making processes. Research should therefore take into account that within decision-making practices scientific knowledge is not simply used, but strategically produced, contested and ignored (Fischer, 2009; McNie, 2007; Ellis & Waterton, 2005). We propose that the following three 3 research questions capture the essence of the knowledge gap that we have put forward:
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Which criteria do different (types of) decisionmaking networks use to assess scientific knowledge? What are key characteristics of scientific knowledge that influence its impact in landscape governance? How can the added value of scientific knowledge in landscape governance be identified?
Answering these questions helps in understanding the variety of criteria used by actors in the decisionmaking network to attribute credibility and trust to scientific knowledge and how these deviate from the criteria used within scientific networks. Furthermore it provides insight in the required forms that scientific knowledge should have in order to be effective, taking into account the demands of the different actors involved and the different phases and forms of decision-making. REFERENCES Azerrad, J.M., Nilon C.H., 2005. An evaluation of agency conservation guidelines to better address planning efforts by local government. LANDSCAPE URBAN PLAN 77, 255-262. Beunen, R., Van Assche, K., Duineveld, M. (2013) Performing failure in conservation policy: The implementation of European Union directives in the Netherlands. Land Use Policy 31 : 280 - 288. Cash, D.W., Clark, W.C., Alcock, F., Dickson, M.N., Eckly, N., Guston, D.H., Jäger, J., Mitchel, R.B., 2003. Knowledge systems for sustainable development. PNAS 100, 8086-8091.
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