Mandy Haggith

Participatory modelling to enhance social learning, collective action and mobilization among users of the Mafungautsi forest, Zimbabwe

Participatory modelling can be a useful process to encourage critical examination of livelihood options and foster sustainable natural resource use through enhanced social learning, collective action and mobilization. The broom-grass group in the Mafungautsi Forest Reserve serves as a case study of the process and outcomes of such participatory modelling. Innovative group facilitation methods enhanced participation in the modelling process. The modelling process complements broader efforts to achieve higher levels of adaptive collaborative management.

ZimFlores: A Model to Advise Co-management of the Mafungautsi Forest in Zimbabwe

ZimFlores (version 4) is the outcome of a participatory modelling process and seeks to provide a shared factual basis for exploring land-use options for the communal lands surrounding the Mafungautsi forest. The ZimFlores experience underscores the importance of a sharing a common problem and a common location in which all participants have an interest. Participatory modelling has proved an effective way to consolidate a diverse body of knowledge and make it accessible. Results demonstrate the importance of model outputs that are diagnostic, and which offer insights into the issues under consideration.

Modelling decision-making in rural communities at the forest margin

The FLORES simulation model aims to capture the interactions between rural communities living at the forest margin and the resources that they depend upon, in order to provide decision-makers with a tool that they can use to explore the consequences of alternative policy options. A key component of the model is simulating how decision-making agents within the system (individuals, households and the whole village) go about making their decisions. The model presented here is based on an anthropological description of the rules and relationships that people use, rather than on the assumption that people behave in an economically optimal fashion. The approach addresses both short-term decision-making (primarily the allocation of labour to various activities on a weekly basis), and long-term strategic land-use planning, taking into account the variety of tenure and inheritance patterns that operate in real communities. The decision-making sub-model has been implemented in the Rantau Pandan (Sumatra) version of FLORES, using the Simile modelling environment.

Unlocking Complexity: The Importance of Idealisation in Simulation Modelling

Idealisation is the process of finding simple representations of the real-world whilst conceptualising a model. There are three ways to limit complication in a model of a complex real-world: byfocussing the scope of the modelling process onto a clearly defined issue; byidealising elements of the real-world during model conceptualisation; and bysimplifying the implemented simulation program. Careful idealisation has the greatest potential for increasing model tractability whilst generating insights during the model design process. The Forest Land Oriented Resource Envisioning System (FLORES) project deals with social forest landscapes which are highly complex. Benefits of idealisation are demonstrated using six examples from this modelling work. These examples encompass issues dealing with land tenure, forest management, economic values, social diversity, communication and collaboration. Each example illustrates a different method to achieve an idealisation which yields insights relevant for policy players. A number of lessons about idealisation are also identified: (1) sometimes it is only possible to recognise what is key by omitting it; (2) an effective idealisation is not just achieved by leaving things out, or adding them back in; it can also be achieved by restructuring the representation; (3) it is important challenge the use of different units where consistency is possible; (4) it is easier to keep a simple model simple, than to make simple modifications to a large model. Similarly, it is easier to generate insights with a simple concept for a sub-model than with a simple modification to an existing model; and (5) even the most useful idealisations may have a limited shelf-life.

Infectious Ideas: Modelling the Diffusion of Ideas across Social Networks

Will the practice of collecting wild honey wearing no clothes become a widespread practice in Zimbabwe? Or will beekeeping take over as the main way that people acquire honey? Both practices impact on forest resources; how can the foresters influence the uptake of these ideas? This paper describes an exploratory modelling study investigating how social network patterns affect the way ideas spread around communities. It concludes that increasing the density of social networks increases the spread of successful ideas whilst speeding the loss of ideas with no competitive advantage. Some different kinds of competitive advantage are explored in the context of forest management and rural extension.

Participation and Model-building: Lessons Learned from the Bukittinggi Workshop

FLORES (the Forest Land Oriented Resource Envisioning System) was initially constructed by 50 people during a multidisciplinary workshop in Bukittinggi, Sumatra, in 1999. It proved that a model of a complex system could be constructed in a participatory way by a diverse team; that it could be done with a graphically-based package such as Simile; and that the resulting model could remain reasonably accessible to all participants, and could run on an ordinary notebook computer. Many useful insights can be gained through building such a model, and subsequent experience has demonstrated that modelling in this way can foster continuing interdisciplinary collaboration. Participants founded the FLORES Society, a loose collective open to all researchers interested in pursuing the development and use of such models. The Society conducts an e-mail discussion group on FLORES@cgnet.com (subscription requests to JV anclay@scu.edu.au).

The challenges of effective model scoping: A FLORES case study from the mafungautsi forest margins, Zimbabwe

This paper explores the challenge of defining the scope of a systems model, emphasising three aspects: boundary, granularity and conceptual scope. The significance of these is illustrated by reference to a model of land-use decisions made in villages bordering on the Mafungautsi forest in Zimbabwe. The purpose of this model was to help policy players (Forestry Commission staff, non-governmental organisations, researchers and local people) to understand the impact of policy interventions on local people’s livelihoods. Scoping decisions that were made in building the Mafungautsi model were deliberately liberal, to encompass the interests of all participants in the modelling process. These decisions now present a range of serious challenges: the difficulty of model calibration, the computational expense of running simulations, and the difficulty for new users to understand the model. Facilitators of modelling teams need to consider the serious implications of giving everyone what they want and including all participants’ ideas in a model. In the long run, it may be better to be tough and reject many suggestions at the outset. The former approach is unlikely to lead to a tractable model, while the latter may ultimately offer greater satisfaction for all.

BIRDZ: Making Ecological Data Digestible

Increasingly ecologists are asked to contribute to decision-making processes in resource management and development by giving their assessment of the impact of natural and artificial environmental changes. In many cases time or resource constraints make detailed ecological studies impossible and so ecologists must make educated guesses based on available data. The accuracy of these assessments can be improved by making data more accessible to ecologists, and increasing their ability to analyse data rapidly and efficiently. User-friendly database systems are hence a vital ecological tool.