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Research Design IdeasDouglas Wilson Institute for Fisheries Management BackgroundI approach ecological knowledge through an interest in participatory fisheries management regimes. The problem is how an adequate scientific basis for management decisions can be maintained while inviting broad participation in decision making: Is it possible to reconcile scientists' and local knowledge about the resource system in a way which is acceptable to all stake holders and elicits cooperation? This means that several sources of knowledge, including both "research-based" knowledge and the "ecological" knowledge found in fishing communities, need to play some role in the decision process. How can we define this "ecological knowledge" found in fishing communities, and how and should we differentiate it from "research-based" knowledge produced, in principle if not in practice, by pre-established, depersonalized and decontextualized methodologies? Community knowledge has been called many things in the literature. One term "indigenous ecological knowledge" emphasizes how this knowledge is situated in a culture. Another term " traditional ecological knowledge" emphasizes how it is rooted in a long community memory. A third term "local knowledge" emphasizes that this is place-based knowledge. And a fourth term "anecdotal data" emphasizes its non-systematic production and, whether intending to or not, implicitly delegitmates community knowledge in comparison with research-based knowledge. All of these terms, even the last, communicate an insight into the nature of ecological knowledge. My own preference is "indigenous ecological knowledge" because this term emphasizes the cultural while referring indirectly to both the traditional and place-based nature of the knowledge. In many contexts, however, including I would guess the present one, this term may have other implications beyond simply a description of knowledge. So I will use community ecological knowledge (CEK) here. CEK and research-based knowledge can complement one another. The question research-based knowledge is good at answering is "how do you know that?" The issue that interests me is how management institutions are able to use such multiple sources of information to develop resource management which is considered valid and legitimate by all stake holders. The knowledge that research based knowledge yields is, on smaller scales, more shallow than CEK, but on larger scales it becomes very important to be able to explain to other resource stakeholders as precisely as possible the basis of a claim one is making about the resource. A related challenge, then, is to understand as well as we can how people account for and explain their ecological knowledge. An important lesson from previous CEK research, following Felt (1994), is that this knowledge is so local that considerable knowledge about the locality itself is needed to read and evaluate it. The CEK literature suggests several other complications with the use of local knowledge in management. Users tend to see fisheries as systems in which small perturbations may have substantial future consequences (Smith 1990) and are likely to emphasize the importance of habitat over population dynamics (Berkes 1993, Pinkerton 1989). People in fishing communities also tend to view the resource in much smaller temporal and spatial scales than it is conceived of by managers (Smith 1995). This literature, therefore, illuminates several difficulties that fishery managers face from the perspective of the knowledge base. One is the appropriate scales at which management should be organized. User groups respond to management in terms of the scale of their own resource use, while managers are often responsible for much more. Managers need to simplify ecological complexity to a point where decisions can be identified and made. Yet, at the same time they must justify these decisions to people who see the problems in accuracy that these simplifications make unavoidable. Finally, and perhaps most important, for managers to be able to make use of CEK observations they must be able to evaluate them, and such evaluations are highly dependent on having enough background information about the fishing communities to understand where the messages are coming from. Nor is the use of information from research-based science in management unproblematic. Fisheries and aquatic science is a form of "mandated science," (Jasanoff 1990, Salter 1988), i.e., it is a science that is trying to respond to political and legal, as well as scientific questions. When government managers in any area draw on science to get their jobs done they are looking for clear distinctions about what is at issue, precise decision rules and efficiencies in presentation and procedure (Smith and Wynne 1989). Thus mandated science is an idealized science (Salter 1988) that must facilitate clear choices and be intelligible to non-scientific audiences. Real science is not, however, an ideal. Science applied to policy often produces conflicting results, makes moral dilemmas more explicit, and can even be seen as corrupt (Salter 1988). Competing user groups use both science and gaps in science to define the issues in terms of their own social objectives (Jasanoff 1990). Scientists often must respond to this policy environment and become an interest group of their own. This leads to efforts to protect or enhance their authority through "boundary work," i.e., defining what is and is not science. Jasanoff (1990) concludes that open negotiations among scientists about how the authority of science will be used is as important to effective science-based policy as open communications between scientists and the public. Another critical question, then, that emerges from both the CEK and sociology of science literatures is how the information flows remain open and this is particularly important in the present context as we seek to compare the ways that different cultural groups construct ecological knowledge. The communications required are complex. Considerable give and take is required if managers, scientists and communities, all of them with different questions in mind, are to be satisfied that the proposed measures are based on as accurate a picture of the resource as can be expected. One example of this question of information flow emerged in my recent research on scientific issues around the management of bluefish (Pomatomus salatrix). The fishing public had constructed a very coherent, shared picture of the stock condition that differed to a very large degree with that of the formal stock assessment models (Wilson 2000). The fishers, both recreational and commercial, almost all believed that the stock had moved off-shore and that the drop in stock size showed by the models was an illusion created by this movement. One thing that struck me was that the reasons people raised to support this belief consisted to a large degree of reports of what other fishers had told them, confirmed by their own observations. Furthermore, the observations that seemed to stick in their minds were ones made by non-bluefish fishers operating at some distance from where they usually fished. An interesting question, then, is how this common picture of the resource was build up through interactions over a larger than local scale and between fishers with different gear and target species. Part of this scale issue is clearly attributable to the large geographical area in which bluefish swim. The abstract question of how, and between whom, information flows to build up, if it does so, a common picture of a fish stock seems to me to be generally applicable. It is a salient question as we seek to compare the ways that three different groups develop their perspectives on the resources. Methodological SuggestionThese issues of how people explain how they know things, the importance of information flows in all kinds of scientific constructions suggests that it would be interesting to gather some network data about ecological knowledge from both fishers and scientists. This kind of network data can be generated by a random seed snowball survey where the initial respondent is selected at random from a population of interest and then two or three of the people he or she names in response to the name generator questions. Some initial ideas about the name generator questions might be: 1. In the past month, do you remember anyone telling you something they observed about the lobsters (eels) that surprised you? [similar questions could read informed you, changed your mind about...] Who........various questions about the characteristics of this person such as location, age, occupation, gears they use etc.. 2. Aside from people you work with every day, who is someone you talk to regularly about lobster that you think is very knowledgeable..... 3. In the past month, did anyone tell you something they observed about the lobsters that you though was nonsense? ... who... 4. Have you sought out someone in the past month to get some information about the lobster? ... 5. Which magazines [and other media] do you read that you feel have reliable information about lobster? Which ones don't? With such data we could explore questions such as: to what degree do shared fishing and communal interests increase the influence of messages; how important are "weak ties" between communities, ports and gear types in creating pictures of the resource; what are the characteristics of people (age, high liners, education?) who influence other people's picture of the resource; or what role do media outlets play in influencing how fishers see the resource. References Cited Berkes, F. 1993 "Traditional Ecological Knowledge in Perspective" Pp 1 - 9 in Inglis, J. T. (Ed) Traditional Ecological Knowledge: Concepts and Cases Ottawa: International Program on Traditional Ecological Knowledge, International Development Research Center Felt, Lawrence,1994 "Two Tales of a Fish" in Dyer C. L. and J. R. McGoodwin (Eds) Folk Management of the World's Fisheries Boulder: University of Colorado Press Grafton, R.Q. and J. Silva-Echenique 1997 "How to Manage Nature? Strategies, Predator-Prey Models and Chaos" Marine Resource Economics 12:127-143 Jasanoff, S. 1990 The Fifth Branch: Science Advisors as Policy Makers Cambridge: Harvard University Press Smith, M.E. 1990 "Chaos in Fisheries Management" Marine Anthropological Studies 3(2):1-13 Smith, M.E. 1995 "Chaos, Consensus and Common Sense" The Ecologist (25):80-85 Smith, R. and B. Wynne 1989 "Introduction" pp 1 - 22 in Smith, R. and B. Wynne (Eds) Expert Evidence: Interpreting Science in the Law London: Routledge. Wilson, D.C. 2000 Bluefish Science in the Northeast Region: A Case Study. Institute for Fisheries Management. Research Publication No. 48 |