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Special Feature Ihpeiin H Oe Aaeesadtesaeof State the and Know, Parameters Nature Ecology, 84(6), 2003, pp. 1403±1411 q 2003 by the Ecological Society of America UNCERTAINTY AND THE MANAGEMENT OF MULTISTATE ECOSYSTEMS: AN APPARENTLY RATIONAL ROUTE TO COLLAPSE G. D. PETERSON,1 S. R. CARPENTER,1 AND W. A. B ROCK2 1Center for Limnology, 680 N. Park St, University of Wisconsin, Madison, Wisconsin 53706 USA 2Department of Economics, University of Wisconsin, Madison, Wisconsin 53706 USA Abstract. We use a simple model of ecosystem management to demonstrate that ap- parently rational management approaches can lead to ecological collapse. Our model of the ecosystem management of lake eutrophication integrates lake dynamics, management decision-making, and learning in a framework that is deliberately simpli®ed to highlight the role of model uncertainty. The simulated lake can switch between alternate eutrophic and oligotrophic states. Managers consider two management models of the lake, one for an oligotrophic lake and the other for a eutrophic lake. As managers observe the lake varying from year to year, they estimate how well each of the two management models is supported by the observed data. Management policies maximize the expected net present value of the lake. Even under optimistic assumptions about environmental variation, learning ability, and management control, conventional decision theory and optimal control ap- proaches fail to stabilize ecological dynamics. Rather, these methods drive ecosystems into cycles of collapse and recovery. We suggest how scientists could help prevent ecosystem management from driving ecosystems toward collapse. Key words: collapse; ecological economics; ecosystem management; eutrophication; model un- certainty; optimal control; resilience. Special Feature INTRODUCTION the management of salmon in the Columbia River for example, ecological management has focused on ex- Ecosystem management has a long and diverse his- pensive and sophisticated attempts to assess the cred- tory. It has sometimes been successful (Berkes and ibility of a wide variety of alternate models of eco- Folke 1998), and sometimes not. For example, histor- system functioning (Marmorek and Peters 2001). The ical societies, such as the Maya (Hodell et al. 2001), aim is to discover which model or set of models appears and modern scienti®cally managed resource extraction to best forecast the future behavior of the ecosystem. systems, such as that for the Northern cod (Walters and Although such efforts are certainly worthwhile, there Maguire 1996), have appeared to succeed at ecosystem may be pressure for science to act as a dispassionate management until an abrupt and surprising collapse. tool to assess the relative validity of a selected set of Researchers have tried to explain these collapses. Some alternative models. Too often, the consideration of un- researchers attribute ecological collapse to ignorance certainty focuses only upon the prediction errors of a of gradual ecological change (Martin 1973, Alroy single model while the credibility of the model itself 2001), rational overexploitation (Clark 1973), or the is not assessed (Clark et al. 2001). The credibility of dif®culties of creating effective institutions to manage a given model depends on the other models with which common pool resources (Hardin 1968). Others focus it is compared and on the data available for comparing on the role of social inequality and greed (Blaikie and models. If the data represent only a subset of the po- Brook®eld 1987). Although few people would argue tential behavior of the ecosystem, then the model com- that resource collapses derive from single causes, we believe that downplaying the uncertainty of manage- parison may be biased, or the appropriate model may ment models may be a neglected cause of ecological not even be discovered, because the behaviors of the collapse. ecosystem relevant to the appropriate model have not A large portion of ecological management involves been observed. If an important model is omitted from decision-making under conditions of uncertainty. Cur- the set of models under consideration, substantial errors rent approaches to ecosystem management often cope can occur in assessing the credibility of models, making with uncertainty by ®tting models to data, or using data predictions, and choosing management actions. Thus, to compare competing models (Hilborn and Mangel model uncertainty has critical implications for ecosys- 1997, Clark et al. 2001). In some ecological con¯icts, tem management, but the assessment of model uncer- tainty is limited by the range of ecosystem behaviors observed in the data, and by the diversity of models Manuscript received 3 December 2001; revised 3 June 2002; accepted 21 June 2002; ®nal version received 3 July 2002. Cor- created by the analyst. responding Editor: J. S. Clark. For reprints of this Special Fea- In this paper, we show that when the family of mod- ture, see footnote 1, p. 1349. els being considered does not adequately capture key 1403 1404 G. D. PETERSON ET AL. Ecology, Vol. 84, No. 6 dynamics, even sophisticated management approaches builds up in soil that erodes into water bodies and caus- will function poorly. We model a management process es eutrophication (Bennett et al. 2001). Agricultural that uses passive adaptive management to select poli- production depends upon the use of fertilizer. Because cies. Passive adaptive management is thought to be the fertilizer increases the value of agriculture while de- best management practice when active adaptive man- creasing the value of ecosystem services, there is a agement experiments are not possible (Walters 1986). trade-off between the bene®ts from polluting activities In this case, passive adaptive management chooses pol- and the costs these activities impose on ecosystem ser- icies based on the posterior probabilities of two com- vices. peting models given observed data. We focus on model Phosphorus recycling within a lake can maintain a misspeci®cation by allowing the managers to know, eutrophic state. Recycling exhibits threshold behavior with precision, the model parameters and the state of that is related to the accumulation of P in sediments, nature. wind mixing, and the oxygen content of deep water (Carpenter et al. 1998a). Experimental lake manipu- RATIONALE lations have shown that only a few years of high P Case studies and detailed simulation models provide levels can lead to the accumulation of enough P in the insight into the diversity of ecosystem management sediment to initiate P recycling (Schindler et al. 1987). approaches that have been applied in different situa- In eutrophic lakes, the amount of P recycled from lake tions. However, the complexity of the examples and sediments may exceed annual inputs (Soranno et al. the multiple interacting sources of variation in each 1997). The ease with which a eutrophic lake can return situation make it dif®cult to isolate the role of uncer- to an oligotrophic state following a reduction of nu- tainty in a clear way. Therefore, we have created an trient inputs depends upon properties of the lake such exceptionally simple socioecological model of ecosys- as area, depth, food web structure, submerged vege- tem management that isolates the role of model un- tation, and the concentration of P in lake sediments. certainty. Some eutrophic lakes quickly return to an oligotrophic Our model greatly simpli®es the dynamics of the state following the cessation of nutrient addition, while ecosystem, the information available to managers, and others do not (Scheffer et al. 1993, Carpenter et al. the impact of management interventions, in order to 1998a). focus attention on model uncertainty, its interaction with decision-making, and its implications for ecosys- AMINIMAL MODEL tem dynamics. We use linear equations to describe lake Our model of ecosystem management consists of a dynamics, providing access to useful analytical sim- model of lake dynamics, a learning process, and a man- pli®cations. Our model omits social complexities, such agement decision-making process (Fig. 1). Lake P dy- as institutional interactions, and ecological complexi- namics can produce eutrophic or oligotrophic states. Special Feature ties, such as the interaction of local feedbacks with Managers have two competing management models of external drivers. Rather, our model focuses on the role the lake. Their degree of belief in each of these models of model uncertainty in the dynamics of a managed determines their expectation of the lake's response to ecosystem. We will show that the dynamics of model management. Lake management is based upon maxi- choice from a limited set of alternatives lead to cycles mizing the expected value of a trade-off between lake of collapse and recovery. pollution and lake ecosystem services. Each year, sci- To investigate the dynamics of ecosystem manage- entists collect data and update their beliefs about their ment we use the problem of lake eutrophication. Lakes management models. The details of the lake, learning, can exist in either an oligotrophic or eutrophic state and management components of our ecosystem man- (Scheffer et al. 1993, Smith 1998). Oligotrophic lakes agement model are presented in the following sections. are characterized by low nutrient inputs, low to mod- erate levels of plant production, and relatively clear Lake dynamics water. Eutrophic lakes have high nutrient inputs, high We represent the state of a lake by the concentration plant production, and murky water. They can also be of P. We assume that the dynamics of P within a lake anoxic and produce blooms of toxic algae. People usu- depends upon the loading of P, P removal, and P re- ally ®nd that oligotrophic lakes produce ecosystem ser- cycling. The P dynamics in a lake are modeled by the vices, such as water for human consumption, irrigation, difference equation or industrial use, resources such as ®sh or waterfowl, or recreation, that are more valuable than those pro- BXtttt1 b 1 l 1 S if X , Xcrit Xt11 5 duced by eutrophic lakes (Wilson and Carpenter 1999). 5BXtttt1 r 1 b 1 l 1 S if X $ Xcrit Eutrophication is usually caused by the excessive S ; N (0, s 2) (1) input of nutrients, primarily phosphorus (P) to a lake t (Schindler 1977).
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