Co-learning our way to sustainability: An integrated and community-based research approach to support natural resource management decision-making
Sustainability is an elusive goal. The notorious vagueness of the term, and its scope for varied and seemingly legitimate interpretation by different parties, appear to make it all but useless as an operational guide (O'Riordan, 1988). One has only to consider simple questions - sustain what? how? for whom? over what time period? measured by what criteria? - to appreciate that sustainability can never be precisely defined. Regardless of the ambiguity of the term, however, there appears to be a general consensus that achieving sustainability will place new demands on individuals, society and science.
Getting serious about sustainability means acknowledging the intricate interdependency of environmental, economic and social issues on a finite planet. Within this broader context, science and technology are seen as providing means to achieve ends that are continually redefined by major social concerns. The challenge facing science is how best to structure and undertake research to meet the diverse - and often apparently conflicting - needs of society, local communities and individual natural resource users. In an uncertain and constantly changing environment, science must strive to develop the understanding, knowledge, forums and learning environments to better inform and support more sustainable decision-making.
From this perspective, successful research and development (R&D) efforts will be participatory in nature, and be based on a process of active adaptive management. In turn, finding out about complex and dynamic situations, then taking action to improve them, forms the basis for developing the necessary learning environment.
The theoretical foundations on which natural resource R&D policies and practices are based are undergoing a paradigm shift. Conceptually, traditional approaches are generally based on reductionist scientific methodologies and often on the expertise within single disciplines (Dahlberg, 1991). Despite a growing recognition of the increasing complexity and social construction of resource management issues, there have been few recent innovations in research methodology other than the development of quantitative modelling and an increased focus on the development of expert systems (Ison and Ampt, 1992). In addition, the research systems in which these DSS have been developed have been, and still are, largely characterised by the linear transfer of technology (TOT) model of research and development (Russell et al, 1989). The dominant metaphors are those of "information transfer", "channels of communication" and "teaching", most of which arise from mistakenly seeing human communication in the same way as data transferred between computers. (Ison, 1991).
Despite the vast amounts of time and money that have been and are being spent on natural resource management R&D, the results as Hadley (1993) points out, are often illusory or counterproductive. For example, in African countries conservation attempts have largely been ineffective (Bosch, 1989), and few range management projects have had a discernible, positive and permanent impact on the way communal rangeland is used (Behnke and Scoones, 1991). In New Zealand, the slowness with which land use and land administration have responded to changes in ecological conditions has been noted by O'Connor (1986). Perhaps most telling, the majority of these development initiatives have failed to enlist the active cooperation of the communities they were supposed to serve.
Recognition of such failures has triggered attempts to rethink approaches for linking research with management and policy. Increasingly, alternative approaches are based on concepts of open and evolving systems. They are participatory in nature. There is a growing acceptance of the need to build on principles of experiential learning and systems thinking (Bawden et al, 1985). Research, technology (extension), education and users are therefore recognised as forming elements of one agricultural information system (Roling, 1988). Such a system must be seen as going beyond the TOT paradigm. An information system, in this sense, cannot be usefully regarded only in terms of its transfer. Rather, it is a "social system", within which people interact to create new knowledge, and broaden their perspective of the world (Land and Hirschheim, 1983; Ison, 1991). Given the diverse set of decision environments inherent in the resource management arena, such a system will, to an increasing extent, rely on information technology for its function.
Because there can never be perfect knowledge of ecological processes within non-equilibrium systems, the ideas underpinning our perceptions of sustainable resource management will change as knowledge expands (Burnside and Chamala, 1994). As evolving economic, technical and social systems impact on management they also contribute to changing definitions of sustainability. Accordingly, successful resource management must be based on a process of active adaptive management, or "learning by doing" (Walters and Hilborn, 1978; Westoby et al., 1989).
INTEGRATED SYSTEMS FOR KNOWLEDGE MANAGEMENT
The Integrated Systems for Knowledge Management (ISKM) approach is designed to support such an ongoing process of constructive community dialogue and to provide practical resource management decision support for land managers and policy makers. This framework has been developed in the South Island high country of New Zealand to help communities (policy makers, land managers and other interest groups) share their experiences and observations to develop the knowledge needed to support sound resource management decision-making.
The focus of the ISKM framework (Figure 1) is to provide an organised set of principles and methodologies which will guide our actions as we go about "managing" real-world problem situations. It builds on principles of experiential learning and systems thinking, and is applicable to developing the knowledge and action needed to change real situations constructively. In practice, the process is cyclical and highly iterative with many steps likely to be carried out simultaneously. There are also numerous entry points. The process comprises two phases, which together serve to create an effective learning environment for those involved. The ISKM framework can, however, be usefully viewed as having four main steps as illustrated in Figure 1.
Figure 1: ISKM - a participatory research framework to facilitate the identification and introduction of more sustainable resource management practices. The two phases interact to create an effective learning environment.
Step 1: Scoping goals and objectives
The first phase of the approach emphasises developing a common understanding of any perceived issue or problem. This entails an initial scoping process to help those involved to clearly define the nature of the system under consideration. This serves as a basis for determining the needs of the different interest groups involved, and the specific goals and outcomes they wish to achieve. Because this provides an opportunity to involve all interested parties in the research process from the outset, it is more likely to lead to the development of opportunities and outcomes relevant to community needs.
Step 2: Accessing relevant knowledge
This emphasis on problem formulation ensures a focus on the collation and development of "relevant" knowledge. This clarity also ensures the provision of relevant monitoring tools by which the success of measures to achieve the stated goals can be assessed.
Years of experience have provided land managers with a wealth of knowledge on their local systems. This information, unfortunately, is rarely documented and not readily available to land managers on a collective basis. Similarly, much of the valuable knowledge that scientists have accumulated is fragmented, held in different databases and not always readily available. Accordingly, the second step of the ISKM process focuses on bringing local and scientific knowledge systems together. In this regard, the initial scoping activities also provide a basis for the design of appropriate processes (interviews, focus groups, questionnaires, etc.) to unlock and access the relevant existing data and information from both local and research communities. In turn, the process supports the successful implementation of relevant monitoring programmes as land managers become involved in the interlinked processes of monitoring and adaptive management.
Step 3: Community dialogue
Given the complexity and different social perceptions of many agricultural and environmental situations, the process actively supports improved communication flows among all those involved to develop the "useful knowledge" needed to provide practical decision support.
Facilitated workshops provide a learning environment within which participants develop a shared understanding of how others see the world and how that shapes the way they act in it (e.g. manage their land, carry out their research, develop policy). Importantly, the process recognises the contextual nature of information. A strategy or goal suggested by a farmer, policy maker or environmental group will always have been derived from within a particular social, economic and ecological setting. Scientific results are similarly derived from a particular context, which will include factors such as scale, site and the researcher's personal worldview. Accordingly, the community dialogue process is designed to seek the active cooperation of participants in developing a common understanding of the context in which any individual piece of information becomes relevant.
Generating useful knowledge
The ongoing community dialogue is designed to produce useful knowledge to help all those involved in the process. It provides those land managers and policy makers who participated in the process with immediate access to new ideas and perspectives which may help them re-evaluate their current management or policy strategies. Because many sustainability issues need to be addressed simultaneously at a number of different levels of decision-making, the workshops emphasise the generation of appropriate strategies for different system hierarchies (from block/field goals through individual enterprise objectives to catchment community goals). At the same time, it helps the different interest groups involved to develop a shared understanding which can reduce the level of conflict that currently surrounds many resource management issues.
The process automatically aids the identification of new and relevant research initiatives as knowledge gaps are identified. Importantly, these forums also provide farmers, conservators, policy makers and others with the opportunity to provide researchers with a greater appreciation of their information and technical needs.
Capturing knowledge for decision support
As demonstrated above, this ongoing community dialogue provides all those directly involved with a learning environment in which "useful knowledge" is developed. There is a need to capture this knowledge to benefit all of those who have not had the opportunity to be directly involved. Where appropriate this can be done through a range of presentation techniques such as manuals, posters or decision trees on paper. However, in many cases computer-based decision support systems are not only appropriate, but essential, to help deal with the complexity inherent in environmental decision-making.
The prototyping approach that is inherent in the ISKM framework encourages an interactive process where DSS developers and users collaboratively discover new requirements and refinements, which are then incorporated in succeeding versions. This is especially useful when DSS development is seen as a process that can be enhanced by the use of iterative 'soft' systems methodologies involving processes of feedback and learning among all the different participants in the situation under inquiry (Miles, 1988). In this way, the development process allows the user to learn and experience the system at an early stage. This process is important because it encourages user confidence in subsequent working versions (Brittan, 1980).
In the long term such a computer-based DSS is designed to integrate a diverse array of information sources and provide users with a more holistic perspective of a complex situation. It is perhaps best viewed as a library incorporating a wide range of experiential knowledge in the form of expert systems, DSS modules, software packages and databases.
The design encourages the user to define and then select a management goal. By answering simple questions and being prompted to provide further information with the help of associated models and specialist packages, the user can create new information (allowing for ecological diversity, etc.) relevant to the issue under investigation. Prompts act to provide a pathway towards the provision of management advice. Through the use of hypertext the user can obtain further explanation and clarification of the assumptions behind selected answers, along with the ability to access associated subject areas. In some cases this will simply require access to another part of the system, but it is envisaged that in the future access will also be provided to external information sources through links such as Internet. These related abilities are important as they allow users to assess the reliability of the decision support on their own terms (Stafford Smith and Foran, 1990), and to create a personal learning environment (Jonassen, 1992).
Step 4: Monitoring and adaptive management
Importantly, the ISKM framework allows the substance and context of the required information flows to be updated as more knowledge becomes available, and different goals are set.
An ongoing role for land managers
In normal practice, land managers manipulate ecosystems primarily to achieve a management objective, rather than to find out how the system works. However, as a number of researchers observe, a management action can also be regarded as an experiment (Walters and Hilborn, 1978; Dankwerts et al, 1992). As land managers measure the outcomes of their management actions they continually gain new "experimental results". These results provide new information whereby the community-derived knowledge base developed through the third step of the ISKM process is re-evaluated and expanded in collaboration with scientists and other stakeholders (Figure 1).
Involvement in the participatory processes of monitoring and adaptive management in this way, means that individual land managers acquire greater technical expertise - building on both collective local knowledge and an associated scientific awareness of their physical environment. At the same time, by achieving specific objectives for improving their resource position through a collective effort, land managers develop greater confidence, which, in turn ensures the uptake needed for the process to continue.
An ongoing role for science
At any given time the research process can play an important role in helping the community and scientists to determine new research priorities jointly. It helps identify knowledge gaps, and assists in prioritizing new research initiatives. This is a continual process as evolving knowledge, technologies and value systems inevitably change our perceptions and provide new areas and issues for research (Stuth et al, 1991). It also acts to provide automatic feedback of research results to end users.
The addition of new local knowledge through monitoring and adaptive management will add to the range of strategies to be evaluated, and strategies and options will continually change in response to social, economic and ecological pressures. This creates a role for ongoing research to determine the wider applicability and environmental implications of management options and strategies.
The process is thus iterative, with each repetition serving to maximise the knowledge available at any time to support decision-making by those in the community. As those involved cooperate to develop the necessary knowledge and knowledge-based tools, new issues will be raised and the process expanded. Ultimately this concept of "learning by doing" could also be broadened to include policy initiatives. As Rondinelli (1983) argues, all social development activities must be seen primarily as experiments and dealt with as complex and uncertain ventures in which the participation of those who are expected to benefit is essential.
In the South Island high country of New Zealand the ISKM framework was initially used to help the community find practical land management strategies to address the problem of an invasive weed, Hieracium spp.. But, using this approach to look at the problem from the point of view of management also highlights how ecological, social and economic issues are inexorably linked. No-one manages for Hieracium alone. For example, farmers are primarily concerned with managing for goals such as increased stock production or available forage supply, while conservators will place an emphasis on management to protect a particular species or threatened ecosystem. Both these groups will also be concerned with other issues such as watershed and landscape management. Accordingly, the ISKM process is now being used in the high country to address a number of related issues such as conservation, grazing management, burning and water quality.
As we bring different knowledge systems together through this process, it becomes clear that what you look for is what you get. As Chris Argyris (1985) and his colleagues point out, depending on the community in which they operate, each different interest group will look for different facts and solutions in accord with their own set of norms for inquiry. In the example above, we find scientists concentrating on determining the effects of grazing on Hieracium (describing and accounting for some phenomenon). In contrast, farmers ask more focused questions such as the effects of different grazing regimes (rotational grazing vs set stocking, different grazing intensities and frequencies, etc.), and are concerned with applying the answers to real-life contexts "amidst all the complexity and multiple dilemmas of values they pose" (Argyris et al. 1985).
Much of the apparent conflict surrounding many resource management issues relates to the fact that different interest groups fail to appreciate the perspectives and values inherent in the actions of others. If these groups can be encouraged to share their experiences and viewpoints there will be a greater understanding of why these differences exist. Equally important, the involvement of different groups may well provide useful ideas and strategies that lie outside the normal perspective of those with the primary responsibility for managing any particular resource.
Collaboratively developing new management options and strategies through the ISKM process provides all interested parties with the opportunity to learn from local experiences gained within enterprise and catchment-level systems. This provides all those involved with an appreciation of management concerns and issues, and allows groups such as scientists and policy makers a better feeling of how their contributions fit into the total system. The result of such cooperation automatically leads to the design of relevant research that will directly benefit both land managers and policy makers.
Although co-operative ventures such as those described here may not yet offer definitive solutions to such elusive issues as sustainability, they can begin to offer a variety of knowledge-based tools and possible courses of action to enable the community to make better informed decisions. In turn, as communication flows between different sectors of the community are expanded and improved, the level of needless conflict surrounding a number of land management issues should be minimised. Accordingly, this participatory approach represents a framework through which different segments of society can cooperate to develop and work towards a more coordinated set of environmental goals.
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