learningforsustainability.netParticipatory model building
Knowledge management (KM)and information technology (IT) both link, and enhance each other in learning-based intititives such as participatory or cooperative model-building. Often one of the best techniques for generating improved thinking at a social level is to use models as an aid to help stakeholders visualise the wider social and bio-physical processes that they cannot see unaided. Many forms of modelling can be used in this participatory manner. Conceptual modelling is often done as a starting process, providing a graphical representation or diagram that involves stakeholders in clarifying the initial framing. Papers that illustrate a participatory approach to modeling as a link between information and knowledge management include:
- Public Participation and Perceptions
of Watershed Modeling
This 2009 paper by Mark Johnson acknowledges that public participation in environmental management is increasingly common across many natural resource sectors. Environmental policies in the water resources sector, in particular, depend upon both computer-based watershed modeling activities and public participation in watershed management decisions, though the integration of participation in watershed modeling remains uncommon. Case studies of two watershed councils in Central New York offer differing perspectives on the effectiveness of public participation in modeling efforts as a mechanism for improving environmental conditions in watersheds. Although watershed modeling is improved from public input in the forms of local knowledge and data contributions, care must be
taken at the outset to ensure that public participants appreciate what modeling can and cannot provide so that modeling activities are best able to inform watershed management decisions. A critical assessment of three A’s of public participation in watershed modeling (e.g., model applicability, accessibility and accuracy) should be undertaken prior to model development. - Lessons for successful participatory watershed modeling: A perspective from modeling practitioners This 2008 paper by Alexey Voinov and Erica Gaddis reminds us that participatory modeling is the process of incorporating stakeholders, often including the public, and decision makers into an otherwise purely analytic modeling process to support decisions involving complex natural resources questions. They present a series of lessons based on experience working with stakeholder groups to develop watershed and water quality models. The lessons relate to stakeholder engagement, modeling tools, model development and calibration, scenario testing, and applying results to management decisions.
- Evaluating Participatory Modelling This CSIRO working paper paper introduces a framework for evaluating projects that have adopted a participatory modeling approach. The framework assesses the extent to which different participatory modeling practices reinforce or divert from the theoretical assumptions they are built upon. The paper discusses the application of the framework in three case-studies.
- If you have a hammer everything looks like
a nail: 'traditional' versus participatory model building In this paper Christina Prell and colleagues argue that the modelling of complex, dynamic and uncertain socioenvironmental systems requires close collaboration between research disciplines and stakeholders at all levels, for if such
models are representations of aspects of reality, how can it be possible to build them without inputs from people who interact with the systems in reality? This paper reflects on findings of case study research involving stakeholders in knowledge creation through
conceptual and formal model building to support upland water catchment management. This poses a number of interesting new challenges for the organisation of the research process, leading to higher levels of uncertainty for researchers and funding agencies. A considerable amount of trust is required from funding agencies to devote money to financing processes with vaguely defined and surprising outcomes, as well as the flexibility to allow for modifications of design and ultimately to rely on the composition of
the project team to provide the expertise the problem requires.
- Companion modeling, conflict resolution, and institution building: sharing irrigation water in the Lingmuteychu Watershed, Bhutan. Companion modeling is a methodology which makes use of multi-agent systems in a participatory way in fields such as sustainable resource management. The objective is to apply simulation tools when dealing with these complex systems in order to understand the institutions and norms that drive the interactions among actors, and consequently between actors and their environment. This Ecology & Society paper by Tayan Raj Gurung, Francois Bousquet and Guy Trebuil shows how this methodology helped resolve a conflict over the sharing of water resources by establishing a concrete agreement and creating an institution for collective watershed management.
- Mediated modeling: a system dynamics approach to environmental consensus building This book by Marjan van den Belt introduces mediated modeling as an approach that enhances the use of computer models as invaluable tools to guide policy and management decisions. Rather than having outside experts dispensing answers to local stakeholders, mediated modeling brings together diverse interests to raise the shared level of understanding and foster a broad and deep consensus. It provides a structured process based on system dynamics thinking in which community members, government officials, industry representatives, and other stakeholders can work together to produce a coherent, simple but elegant simulation model.
- Why involving people is important: the forgotten part of environmental information system management. This paper by Will Allen and Margaret Kilvington points out that developing information management systems to support decision making on-the-ground cannot take place in isolation of the broader social context within which people generate and utilise information and learn. The technology and hardware components, which are the most visible aspects of such systems, receive most attention from researchers and funders. However, if we want people to use information more effectively to help change the way they look at the world -- and how they go about managing its resources -- then we must pay equal attention to the social aspects of information systems, in particular to ensure that they support learning. This paper outlines the requirements for collaborative learning, by which the differing perspectives of multiple stakeholders are coordinated to manage complex environmental problems. A process for utilising the principles of collaborative learning for developing integrated information systems to support decision making is discussed. Particular attention is paid to the new skills of relationship building, facilitation, and conflict management required by multidisciplinary teams developing such systems. Examples to illustrate how these skills could be used in practice are drawn from case studies in resource management in New Zealand.
- Allen, W.; Bosch, O.; Kilvington, M.; Oliver, J.; Gilbert, M. 2001. Benefits of collaborative learning for environmental management: Applying the Integrated Systems for Knowledge Management approach to support animal pest control. Environmental Management 27(2): 215-223
In this paper the ISKM (Integrated Systems for Knowledge Management) approach is presented to illustrate how learning-based approaches can be used to help communities develop, apply, and refine technical information within a larger context of shared understanding. Particular attention is paid to the issues that emerge as a result of multiple stakeholder involvement within environmental problem situations. Finally, the potential role for the Internet in supporting and disseminating the experience gained through ongoing adaptive management processes is examined. - Participatory Avenues this site acts as a focal point for sharing lessons learned and innovation in practicing ethically-conscious community mapping and participatory GIS as means to add value and authority to people's spatial knowledge and improve bottom-up communication.More lessons on participatory GIS can be found from the iapd site from Giacomo Rambaldi and colleagues and Doug Aberley and Renee Sieber
- Cooperative modelling: building bridges between science and the public - Journal of the American Water Resources Association, Apr 2006. This paper by Kristan Cockerill documents results from post-project interviews designed to identify strengths and weaknesses of cooperative modeling; to determine if and how the model facilitated the planning process; and to solicit advice for others considering model aided planning. Modeling team members revealed that cooperative modeling did facilitate water planning. Interviewees suggested that other groups try to reach consensus on a guiding vision or philosophy for their project and recognize that cooperative modeling is time intensive. The authors also note that using cooperative modeling as a tool to build bridges between science and the public requires consistent communication about both the process and the product.
- Allen, W.J. (2001) Working together for environmental management: the role of information sharing and collaborative learning. PhD (Development Studies), Massey University.
This thesis represents an inquiry into how an adaptive management ethic and practice that supports the concept of sustainable development can be initiated and implemented in complex, regional or large-scale contexts. An action research inquiry process is used to find improved ways of managing collaborative or multi-stakeholder approaches to environmental management, and to develop an integrated information framework to underpin subsequent decision making. - Complex Science for a Complex World This book recognises the impotance of applying principles of sustainability, resilience and triple-bottom-line accounting to the problem of managing and regulating the interaction of humans and their environment. The science to underpin these efforts must understand and ultimately predict the dynamic behaviour of coupled systems embodying human behaviour and biophysical responses. Unlike the natural systems that environmental and earth sciences have traditionally addressed, these human dominated systems display learning, adaptation and complex non-linear feedbacks. They are ‘Complex Adaptive Systems’. Traditional approaches to modelling and understanding such systems have treated the natural and human parts quite differently. Natural biophysical processes have been approached with confidence by modellers who understood that, however complex a system like the earth’s climate might be, it could still be expected to obey physical laws and its behaviour was, at least in principle, predictable. The human component, in contrast, was generally treated as entirely contingent and not subject to regular laws (with the notable exception of economics, whose practitioners make draconian simplifying assumptions about human choices with limited predictive success). This situation has changed drastically in the last decade with the growth of complexity theory and its application to human behaviour and decision making. Many aspects of human behaviour at the levels of large groups or whole societies prove to be amenable to simulation with remarkable fidelity by these techniques.Still in its infancy, complexity theory tends to employ an eclectic collection of theories and methodologies designed to deepen our limited understanding of the properties of complex adaptive systems. Among such dynamic techniques, agent-based modelling (ABM) is being used increasingly to simulate human ecosystems. Its major advantage is an ability to generate system-wide dynamics from the interaction of a set of autonomous agents interacting in the silicon world of the computer. ABM is particularly well suited for representing social interactions and autonomous behaviours, and for studying their environmental impact at different scales. It also helps us to study the emergence of and interactions within hierarchical social groups, as well as the emergence of adaptive collective responses to changing environments and environmental management policies.