Timothy Lynam

Mental models: an interdisciplinary synthesis of theory and methods

Mental models are personal, internal representations of external reality that people use to interact with the world around them. They are constructed by individuals based on their unique life experiences, perceptions, and understandings of the world. Mental models are used to reason and make decisions and can be the basis of individual behaviors. They provide the mechanism through which new information is filtered and stored. Recognizing and dealing with the plurality of stakeholders perceptions, values, and goals is currently considered a key aspect of effective natural resource management (NRM) practice. Therefore, gaining a better understanding of how mental models internally represent complex, dynamic systems and how these representations change over time will allow us to develop mechanisms to enhance effective management and use of natural resources. Realizing this potential, however, relies on developing and testing adequate tools and techniques to elicit these internal representations of the world effectively. This paper provides an interdisciplinary synthesis of the literature that has contributed to the theoretical development and practical application of the mental model construct. It explores the utility and applicability of the construct in the context of NRM and includes a review of elicitation techniques used within the field. The major theoretical and practical challenges that arise in drawing on the construct to provide a cognitive dimension to NRM are also addressed.

Using Consensus Analysis to Assess Mental Models about Water Use and Management in the Crocodile River Catchment, South Africa

The content, structure, and distribution of mental models can be elicited and measured using a variety of methods. In this article we explore a method for eliciting mental models within the context of water use and management in South Africa. This method is consensus analysis, a technique developed in cognitive anthropology. We used it to analyze qualitative data from semistructured interviews, pilesorts, and questionnaires to test quantitatively the degree of sharing and diversity of mental models within and across social groups. The consensus analysis method focused on comparing the mental models of two key stakeholder groups in the Crocodile River catchment in South Africa, i.e., conservationists and irrigators, to better understand the level of consensus between these groups. We specifically investigated the level of agreement regarding: (1) major water users of the Crocodile River, (2) causes of the current problems with flows in the river, (3) consequences of the river not flowing, and 4) priorities for future use. We discuss the results and examine the strengths and challenges of consensus analysis for eliciting and measuring mental models. We also evaluated the usefulness of this method in assisting natural resource managers to identify strategies for improving integrated management of water resources.

Waypoints on a Journey of Discovery: Mental Models in Human- Environment Interactions

Although the broad concept of mental models is gaining currency as a way to explore the link between how people think and interact with their world, this concept is limited by a theoretical and practical understanding of how it can be applied in the study of human-environment relationships. Tools and processes are needed to be able to elicit and analyze mental models. Because mental models are not directly observable, it is also important to understand how the application of any tools and processes affects what is measured. Equally important are the needs to be clear on the intent of the elicitation and to design the methods and choose the settings accordingly. Through this special edition, we explore how mental models are elicited using two approaches applied in two case-study regions. We analyze two approaches used in the Crocodile River catchment of South Africa: a graphically based approach, i.e., actors, resources, dynamics, and interactions (ARDI); and an interview- or text-based approach, i.e., consensus analysis (CA). A further experiment in the Rhone Delta (Camargue), France, enabled us to test a cross- over between these two methods using ARDI methodology to collect data and CA to analyse it. Here, we compare and explore the limitations and challenges in applying these two methods in context and conclude that they have much to offer when used singly or in combination. We first develop a conceptual framework as a synthesis of key social and cognitive psychology literature. We then use this framework to guide the enquiry into the key lessons emerging from the comparative application of these approaches to eliciting mental models in the two case regions. We identify key gaps in our knowledge and suggest important research questions that remain to be addressed.

Mental Models in Human-Environment Interactions: Theory, Policy Implications, and Methodological Explorations

with many different geographical settings and scales. The issues discussed and the interrogation of methods have much broader applicability. The methods themselves and the investigation of mental models can be applied to communities of place as well as communities of practice. In addition, some of the methods have been tested in other contexts and the reports of these applications greatly enrich the learning that is reflected in this special feature. In 2006 a mental models group was established within the Resilience Alliance to explore the contributions that different stakeholders and stakeholder groupings make to natural resources dynamics and the resilience of social-ecological systems. A study of water management practices associated with the National Water Act in South Africa provided an excellent opportunity to study mental models, and to assess the application of different methods for studying them, and the role that improved understanding of mental models could make in integrated water resource management at the catchment and other scales. It was felt in particular that the development of multistakeholder water management in the form of Catchment Management Agencies within the context of the National Water Act increased the potential relevance of understanding mental models and their consequences for water resource management. A central part of the collaborative research process that produced these papers was a 10-day long intensive workshop held in Mpumalanga Province of South Africa. The workshop was not only a data gathering and method testing exercise. Importantly it was an interdisciplinary learning experience with shared explorations of methods, theory, and ultimately the analysis of mental models of human-environment interactions. There were good reasons to choose the Inkomati Catchment as the site for the empirical research reported in these papers. Among these were the extent of existing research and good access to and knowledge of social and professional networks. However, even with the links to these established networks of knowledge and practice and with the direct involvement of individuals with long experience of the context, there was still not enough time to complete a full suite of techniques prescribed by the methods tested. This highlights one of the core lessons from this research exercise: that the process of

Eliciting Mental Models: a Comparison of Interview Procedures in the Context of Natural Resource Management

The sustainable management of natural resources largely depends on peoples conceptions of environmental systems and how they function. The mental model construct provides an appropriate means to explore the cognitive dimension of peoples interactions with such systems. Mental models are cognitive representations of external reality that people use as the basis for acting with and within the world around them. We aimed to improve the application of the mental model construct to the field of natural resource management, with an emphasis on creek, i.e., stream, systems, by exploring how certain elicitation procedures may affect the mental models expressed. One of the initial hurdles that must be overcome is to work out how to effectively elicit peoples mental models of complex, dynamic phenomena. By improving their understanding of mental model elicitation procedures, researchers can make better use of the mental model construct to further explore the cognitive and social dimensions of human-environment interactions. The procedures compared were oral interviews and a drawing task with oral commentary, conducted at either a creek location, where visual cues were available, or in the interviewees home. We found that the location of the interview had a greater effect on the expressed mental models than the interview task. The locations also evoked different emphases in the mental models: those elicited by a creek featured more concepts and were more specific, whereas those elicited at home were typically more generic and dense. The interview task was found to have minimal effect on the mental models expressed.

Using social representations theory to make sense of climate change: what scientists and nonscientists in Australia think

The mass media has ensured that the challenging and complex phenomenon of climate change now has the household familiarity of a brand name. But what is it that is understood by climate change, and by whom? What frame of reference is drawn upon to communicate meaningfully about climate change? Do particular subgroups within our society hold different understandings, or have the debate and the prolific dissemination of information about this issue coalesced around a core perception or image of what climate change is? To answer these questions, we conceptualized climate change within the theory of social representations as emergent socially constructed knowledge. We analyzed word association data collected in Australia from persons identifying as having a scientific, government, or general public background (N = 3300). All respondents were asked to write the first words that came to mind when they thought about climate change. Comparative analyses of the word associations reveal that respondents from different backgrounds define climate change in different ways. The results suggest that there is a common core set of concepts shared by the different groups, but there are also a great many differences in how climate change is framed and conceived by respondents. The results are discussed in relation to what they imply for responses to climate change by these social groups and in relation to interventions designed to encourage climate adaptation.

Assessing the Importance of Woodland Landscape Locations for Both Local Communities and Conservation in Gorongosa and Muanza Districts, Sofala Province, Mozambique

In collaboration with two communities living in, and on the edge of, Gorongosa National Park (GNP), Mozambique, we researched the importance of different landscape units to these communities and used the information to develop a management plan for GNP. We conceived the importance of a landscape to local people as a ratio of the benefits they derive from it and the costs of accessing or using those benefits. To test this expectation, we developed Bayesian belief models, for which the parameters were the relative preference weightings derived from community members (the relative preferences for benefits and relative expectations of costs). We then collected field data to confront the models for each of the two sites. In a parallel process, we conducted a vegetation survey to generate a map of the vegetation types, as well as an index of biodiversity importance for each vegetation type of the two 20-km 2 sites. For each site, we simplified and converted the benefit:cost model into a local community importance surface, or map, and then overlaid a conservation importance surface on it in order to identify locations that were of high importance to both conservation groups and the local community. Such areas would require careful management attention. This paper discusses the implications of the research for the planning of GNP, as well as the strengths and weaknesses of the approach.

Sensemaking: a complexity perspective

Our intent was to provide a methodological overview of the primary data collection process in support of the other articles in this special issue. We documented and illustrated the use of a data collection and analysis suite, SenseMaker, that was designed to collect and work with narrative fragments. The approach presented adds a new and inherently mixed tool to the mixed methods toolbox. Despite its novelty and potential utility, little has been written in the academic literature on the application of SenseMaker to complex problems. To the best of our knowledge, the approach has not been used in relation to climate change or climate change adaptation and has not been presented in the mixed methods literature. We sought to contribute to filling this gap through describing the approach used to generate the data that underpin the articles in this special feature. Our purpose was to illustrate some of the potential and most notable challenges of using the SenseMaker data collection and analysis process in a complex domain through examining adaptation to climate change. Our overview was not exhaustive but rather sought to highlight capabilities and challenges through examining experiences of adaptation from a stages of change perspective. SenseMaker provides a remarkably powerful tool for the capture of micronarratives of complex phenomena such as climate change. The capacity to have respondents interpret, i.e., make sense of, their own narratives is an important innovation that provides one plausible solution to the problem of analysts coding narratives. Analytically, however, SenseMaker is relatively weak for those seeking strong statistical support for analyses and provides no capability for analyzing the narratives themselves.

Exploring social representations of adapting to climate change using topic modeling and Bayesian networks

When something unfamiliar emerges or when something familiar does something unexpected people need to make sense of what is emerging or going on in order to act. Social representations theory suggests how individuals and society make sense of the unfamiliar and hence how the resultant social representations (SRs) cognitively, emotionally, and actively orient people and enable communication. SRs are social constructions that emerge through individual and collective engagement with media and with everyday conversations among people. Recent developments in text analysis techniques, and in particular topic modeling, provide a potentially powerful analytical method to examine the structure and content of SRs using large samples of narrative or text. In this paper I describe the methods and results of applying topic modeling to 660 micronarratives collected from Australian academics/researchers, government employees, and members of the public in 2010-2011. The narrative fragments focused on adaptation to climate change (CC) and hence provide an example of Australian society making sense of an emerging and conflict ridden phenomena. The results of the topic modeling reflect elements of SRs of adaptation to CC that are consistent with findings in the literature as well as being reasonably robust predictors of classes of action in response to CC. Bayesian Network (BN) modeling was used to identify relationships among the topics (SR elements) and in particular to identify relationships among topics, sentiment, and action. Finally the resulting model and topic modeling results are used to highlight differences in the salience of SR elements among social groups. The approach of linking topic modeling and BN modeling offers a new and encouraging approach to analysis for ongoing research on SRs.

Making sense of climate change: orientations to adaptation

[Extract] In our story of this special feature we describe how many of the possible accounts and papers fell by the way side for one reason or another. And of course we did not know at the beginning what we have learned along the way. Therefore, in the final section we highlight some of the things we have learned as well as some of the things we wish we now knew and hope they might intrigue others so more stories can be told of the many facets of how the social and individual processes of making sense of climate change orient people to adaptation!