The Drama of the Commons (2002) / Chapter Skim
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10 Scientific Uncertainty, Complex Systems, and the Design of Common-Pool Institutions
10 Scientific Uncertainty, Complex Systems, and the Design of Common-Pool Institutions
Pages 327-360
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From page 327... ...
It has created pervasive uncertainty that has been magnified by the strategic behavior of the various human interests who play in the game of fisheries management. This paper argues that scientific uncertainty in complex systems creates a more difficult conservation problem than necessary because (1)
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This chapter suggests we are more likely to find ways to align individual incentives with ecosystem sustainability if we begin to view these systems as complex adaptive systems. This perspective alters especially our sense of the extent and kind of control we might exercise in these systems and, as a result, has strong implications for the kinds of individual rights and collective governance structures that might work.
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From page 329... ...
But the theorized relationship between the spawning stock and recruitment is generally unknown and only claimed to exist for a few stocks, and then only at very low population sizes (Hall, 1988; Myers et al., 1995~.4 In spite of the absence of confirming evidence, fisheries scientists are firmly convinced that the sustainability of each population depends on the maintenance of an adequate spawning stock biomass. Consequently, in the day-to-day management of fisheries, there is no attempt to predict recruitment.
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Economic hardship arguments were simply interpreted as exaggerated claims that reflected the expected zero-profit state of the industry given open access. However, members of the management council,5 who were nearly all nonscientists, were influenced by both the biological and economic hardship arguments.
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From page 331... ...
However, given the inability to verify the core relationship in the theory, this kind of approach to the uncertainty problem carries unusual risks. Precautionary management steps taken on the assumption that the single-species "spawning stock/recruitment" line of causation is the operative long-term determinant of sustainability may turn out to be highly risky if other ecological factors (e.g., habitat, spatial distributions of local stocks, population behavior, trophic hierarchy, and so on, which tend to be ignored in the single-species scientific agenda)
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From page 332... ...
The appropriateness of one or the other approach would appear to depend on the state of our scientific knowledge or, alternatively, our ability to test and validate. The next sections of the chapter turn to a brief discussion of the view of uncertainty in a normal, reductionist scientific environment and how one's view of uncertainty changes in the context of a complex adaptive system.
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From page 333... ...
The instance of model uncertainty is also best addressed through a scientific process, but in this case one that consists of the discovery of causal relationships. Once that discovery occurs, the problem of uncertainty melds almost indistinguishably into the statistical process associated with parametric uncertainty.7 From the social point of view, uncertainty is not a desirable state of affairs but it is not especially problematic when science is in a position to learn rapidly.
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From page 334... ...
What is problematical about complex systems in this regard are their pervasive nonlinear, causal relationships (Holling, 1987~. At any time a large number of factors may influence the outcome of a particular event, each one to a greater or lesser extent; at another time, the strength of those same causative factors on the same event may be very different.
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From page 335... ...
LEARNING IN COMPLEX ADAPTIVE SYSTEMS In complex ocean systems, learning the appropriate kind and extent of restraint required for sustainability is definitely a more difficult problem than one might be led to believe from a single-species theoretical perspective. Conventional resource management theory and practice is founded on the presumption that it is possible to simplify and predict fisheries systems at the scale of individual stocks using the same methods that have been applied so successfully to physical systems.
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available to harvest"~. These contracts would tend to be enforceable because individual incentives would be aligned with social goals and, as a result, would tend to lead to sustainable resources (Scott, 1992~.
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He describes checkers as a very simple example of a complex adaptive system. Checkers has a limited number of pieces subject to a very few rules of movement, and its slow variables (the rules of the game, the size of the board, the kinds of pieces)
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. Checkers, unlike an ecosystem, does not contain variables of differing time steps, which means that even though the number of board configurations can be very large, that set does not change.
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Both depend on the structure of rights and the process of governance. A typical openaccess regime contains private rights that nearly always generate individual incentives for short-run, profit-maximizing objectives that have little to do with conservation.
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In summary, this perspective from complex systems theory leaves us with a sense that we have a very modest, very short-term capability for prediction at the species level, and an even more modest ability to control outcomes at that level in complex systems. We clearly influence the system, but the specificity of outcomes (especially in terms of short time step variables such as recruitment changes in population size)
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Nearly always, the literature on common-pool institutions assumes relatively complete (if stochastic) biological knowledge operating in a Newtonian world.
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Simon proposed a compellingly simple generalization about the organization of complex systems one that makes few assumptions about causal relationships. Namely, Simon proposed that these systems are organized hierarchically and partitioned into nearly decomposable (or independent)
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From page 343... ...
But they also govern many other specialized units and agreements whose purpose is to address interactions whose patterns of occurrence do not conform to the "normal" nested hierarchy. For example, states are part of the federal union but also members of various associations or agreements among states organized for particular purposes, such as the Atlantic States Marine Fisheries Commission.
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In other words, an aggregation, or clustering, of subsystems defines a larger scale subsystem. Changes in the composition of the organisms and other biological activity in subsystems (or patches)
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Similarly, understanding of local phenomena is clearly enhanced by knowledge of larger scale events. Thus, changes in aggregate phenomenon are better understood when combined with knowledge of the smaller scale factors from which they emerge, and smaller scale events are better understood in the context of the larger scale factors that contain them (Berkes, this volume:Chapter 9; O'Neill et al., 1986; Rosa 1998b; Young, this volume:Chapter 8~.
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From page 346... ...
Cities and states and, for that matter, all kinds of similar governing units tend to maintain collective organizations for the purpose of articulating their collective experience and developing new ways to operate. This information is then disseminated among members of the organization through publications, model legislation, personal discussions, conferences, and a variety of other networking activities (Levitt and March, 1995~.
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Organization, Rights, and Incentives Individual incentives are generally the most important factor in the transformation of organizational structure into outcomes (Williamson, 1986; Pfeffer, 1995~. Incentives are important for rule compliance and stewardship, as is usually emphasized, but in the context of complex systems they have a particularly strong bearing on the collective learning problem and the feasibility of developing restraining rules.
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From the perspective of individual incentives, this impaired and modest control argues strongly against species-specific rights. Such rights would provide no incentive to protect common resources, such as habitat, necessary for the sustainability of more than one species.
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But this is the period that is relevant to sustainability. Broad rights that correspond with the dimension at which there is at least limited control all species at the (subsystem level, or perhaps, the functional group align individual incentives with the need to learn about and maintain ecosystem function.
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Patterns at all scales and the efficacy of rules also at all scales are of interest to the individual. In short, in a complex system, the creation of individual incentives that might lead to collective restraint involves the identification of system patterns, the formation of a broad, not narrowly specified, vision of the future, and the ability to adapt to that future.
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From page 351... ...
This increases the feasibility of conducting a constructive "analytical deliberation," arriving at a shared vision of the future and aligning individual incentives. This kind of institutional arrangement, which I believe is principally consistent with decentralized, democratic governance, does not resolve scientific uncertainty but it does create a constructive environment in which the collective pursuit of useful knowledge can take place.
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suggests that learning in this kind of environment is based on the identification of recurring system patterns. The checker board game that he uses as an example of pattern learning is a relatively simple example of a complex adaptive system.
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5 The Fisheries Conservation and Management Act of 1977 established eight regional fisheries management councils that act as advisory bodies to NMFS. NMFS is located within the National Oceanic and Atmospheric Administration (NOAA)
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15 They do not, however, conform to the aggregation from species to system implicit in speciescentered population approaches such as used conventionally in fisheries management. I believe it is generally recognized that aggregation to the system from a species base presents intractable measurement and modeling problems.
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Gunderson 1996 Chaos and paradigms for fisheries management. Marine Policy 20:87-89
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1996 Spatial and temporal variation in the density of northern cod and a review of hypotheses for the stock's collapse. Canadian Journal of Fishery and Aquatic Sciences 53:943-962.
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Committee on Ecosystem Management for Sustainable Marine Fisheries. Ocean Studies Board.
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Smith, M.E. 1990 Chaos in fisheries management.
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From page 359... ...
Wilson, [A., ~ ~ncb, P Quebec, S.R.
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