Designing Sustainable Ecological Economic Systems

Robert Costanza

Defining Sustainability

There is a huge amount of discussion in the literature these days about how one "defines" sustainability, sustainable development, and related concepts (see Costanza, 1991; Pezzey, 1989; World Commission on Environment and Development, 1987). Many argue that the concept is useless because it cannot be "adequately defined." Most of this discussion is misdirected because it (1) attempts to cast the problem as definitional, when in fact it is a problem of prediction, and (2) fails to take into account the many time and space scales over which the concept must apply.

Defining sustainability is actually quite easy: a sustainable system is one that survives for some specified (non-infinite) time. The problem is that one knows one has a sustainable system only after the fact. Thus, what usually pass for definitions of sustainability are actually predictions of what set of conditions will actually lead to a sustainable system. For example, keeping harvest rates below rates of natural renewal should, one could argue, lead to a sustainable system for extracting natural resources—but that is a prediction, not a definition. We know if the system actually is sustainable only after we have had the time to observe whether the prediction holds. Usually there is so much uncertainty in our ability to estimate natural rates of renewal and our ability to observe and regulate harvest rates that a simple prediction such as this is, as Ludwig et al. (1993) correctly observe, always highly suspect.

Likewise, sustainable economic development can only be observed after the fact. Most "definitions" of sustainable development, encompassing elements of (1) a sustainable scale of the economy relative to its ecological life-support



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--> Designing Sustainable Ecological Economic Systems Robert Costanza Defining Sustainability There is a huge amount of discussion in the literature these days about how one "defines" sustainability, sustainable development, and related concepts (see Costanza, 1991; Pezzey, 1989; World Commission on Environment and Development, 1987). Many argue that the concept is useless because it cannot be "adequately defined." Most of this discussion is misdirected because it (1) attempts to cast the problem as definitional, when in fact it is a problem of prediction, and (2) fails to take into account the many time and space scales over which the concept must apply. Defining sustainability is actually quite easy: a sustainable system is one that survives for some specified (non-infinite) time. The problem is that one knows one has a sustainable system only after the fact. Thus, what usually pass for definitions of sustainability are actually predictions of what set of conditions will actually lead to a sustainable system. For example, keeping harvest rates below rates of natural renewal should, one could argue, lead to a sustainable system for extracting natural resources—but that is a prediction, not a definition. We know if the system actually is sustainable only after we have had the time to observe whether the prediction holds. Usually there is so much uncertainty in our ability to estimate natural rates of renewal and our ability to observe and regulate harvest rates that a simple prediction such as this is, as Ludwig et al. (1993) correctly observe, always highly suspect. Likewise, sustainable economic development can only be observed after the fact. Most "definitions" of sustainable development, encompassing elements of (1) a sustainable scale of the economy relative to its ecological life-support

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--> system, (2) a fair distribution of resources and opportunities between present and future generations, as well as between agents in the current generation, and (3) an efficient allocation of resources that adequately accounts for natural capital, are thus really predictors of sustainability and not really elements of a definition. Like all predictions, they are uncertain and are subject to much discussion and disagreement. The second problem is that when one says a system has achieved sustain-ability, one does not mean an infinite life span, but rather a life span consistent with its time and space scale. Figure 1 indicates this relationship by plotting a hypothetical curve of system life expectancy on the y axis as a function of time and space on the x axis. We expect a cell in an organism to have a relatively short life span, the organism to have a longer life span, the species to have an even longer life span, and the planet to have a longer life span. But no system (even the universe itself in the extreme case) is expected to have an infinite life span. A sustainable system in this context is thus one that attains its full expected life span. Individual humans are sustainable by this definition if they achieve their normal life span. At the population level, average life expectancy is often used as an indicator of health and well-being of the population, but the population itself is expected to have a much longer life span than any individual and would not be FIGURE 1 Sustainability as scale (time and space) dependent concepts.

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--> considered to be sustainable if it were to crash prematurely, even if all the individuals in the population were living out their full ''sustainable" life spans. Since ecosystems experience succession as a result of changing climatic conditions and internal developmental changes, they too have a limited (albeit fairly long) life span. The key is differentiating between changes due to normal life span limits and changes that cut short the life span of the system. Things that cut short the life span of humans are obviously contributors to poor health. Cancer, AIDS, and a host of other ailments do just this. Human-induced eutrophication in aquatic ecosystems causes a radical change in the nature of the system (ending the life span of the more oligotrophic system while beginning the life span of a more eutrophic system). We would have to call this process "unsustainable" using the above definitions since the life span of the first system was cut "unnaturally" short. It may have gone eutrophic eventually, but the anthropogenic stress caused this transition to occur "too soon.'' Sustainability is thus most accurately viewed as a long-term goal over which there is broad and growing consensus. Establishment of this goal is fundamentally a social decision about the desirability of a survivable ecological and economic system. Defining sustainability as a goal is relatively straightforward— we want the system to last as long as possible (remembering that it is necessary to specify the time and space scale for the system in order to interpret "as long as possible"). The real problems are not so much defining the goal as they are predicting what policies will lead to its achievement. Here there is ample room for, and need of, vigorous discussion, debate, analysis, and modeling to determine which policies have the best chance of achieving the goal. Ecosystems As Sustainable, Nonpolluting Producers Ecological systems play a fundamental role in supporting life on Earth at all hierarchical scales. They form the life-support system without which economic activity would not be possible. They are essential in global material cycles, such as the carbon and water cycles. They provide raw materials, food, water, recreation opportunities, and microclimate control for the entire human population. In the long run a healthy economy can exist in symbiosis only with a healthy ecology. The two are so interdependent that isolating them for academic purposes has led to distortions and poor management. Ecological systems are also our best current models of sustainable systems. Better understanding of ecological systems and how they function and maintain themselves can yield insights into designing and managing sustainable economic systems. For example, there is no "pollution" in mature ecosystems—all waste and by-products are either recycled and used somewhere in the system or they are fully dissipated. "Pollution" is defined as material or energy that is a by-product of the activity of one part of the system that has an unintentional disruptive effect on another part of the system. Some activities such as predation or the scent of a

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--> skunk intended to drive away predators are intentionally disruptive, so these are not pollution by the above definition. In general the lower the entropy of the pollution (the higher its organization), the more potentially disruptive it can be. On the other hand, some forms of pollution (i.e., anthropogenic CO2 emissions) are fairly high in entropy per unit emitted, but the sheer volume can be enough to cause major problems. The disruptive potential of a given pollutant can be thought of as the product of the quantity of production and its organization (negative entropy) per unit. This implies that a characteristic of sustainable economic systems should be a similar "closing the cycle" by finding productive uses and recycling currently discarded "pollution," rather than simply storing it, diluting it, or changing its state and allowing it to disrupt other existing ecosystems and economic systems that cannot effectively use it. Those things that have no possible productive uses should not be produced at all. Ecosystems have had countless eons of trial and error to evolve these closed, nonpolluting loops. Early in the earth's history there was certainly pollution in natural systems, and even today, early successional ecosystems have pollution under our definition. A general characteristic of closing the loops and building organized nonpolluting natural systems is that the process can take a significant amount of time. The connections in the system must evolve, and there are characteristics of systems that enhance and retard evolutionary change. Humans have the special ability to perceive this process and potentially to enhance and accelerate it. The first pollutant was probably oxygen, an unintentional by-product of photosynthesis that was very disruptive to anaerobic respiration. There was so much of this "pollution" that the earth's atmosphere eventually became saturated with it and new species evolved that could use this former pollution as a productive input in aerobic respiration. The current biosphere represents a balance between these processes—a balance that has evolved over millions of years to ensure that the formerly unintentional by-product is now an absolutely integral component of the system. Eutrophication and toxic stress are two current forms of pollution that can be seen as resulting from the inability of the affected systems to evolve fast enough to convert the "pollution" into useful products and processes. Eutrophication is the introduction of high levels of nutrients into formerly lower nutrient systems. The species of primary producers (and the assemblages of animals that depend on them) that were adapted to the lower nutrient conditions are outcompeted by faster-growing species adapted to the higher nutrient conditions. But the shift in nutrient regime is so sudden that only the primary producers are changed and the result is a disorganized collection of species with much internal disruption (i.e., plankton blooms, fish kills) that can rightly be called pollution. The introduction of high levels of nutrients into a system not adapted to them causes pollution (called eutrophication in this case), whereas the

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--> introduction of the same nutrients into a system that is adapted to them (i.e., marshes and swamps) would be a positive input. We can minimize pollution by finding the places in the system where it represents a positive input and placing it there. Toxic chemicals represent a form of pollution because there are no existing natural systems that have ever experienced them, so there are no existing systems to which they represent a positive input. The places where toxic chemicals can most readily find a productive use are probably in other industrial processes, not in natural ecosystems. The solution in this case is to encourage the evolution of industrial processes that can use toxic wastes as productive inputs, or, if these cannot be found, to eliminate their production and replace them with alternatives that do have positive uses. The Role of Diversity and Organization One strategy that natural systems have evolved to cope with pollution is diversity. The most disruptive pollutants are relatively low entropy. Low-entropy matter and energy also represent a potential resource. Given enough time, a species will evolve to take advantage of this potential. Thus, diversity may be linked to efficiency at the system level. A higher diversity system wastes fewer potentially productive resources by taking advantage of all the "pollution." Early successional systems with low diversity are wasteful of resources in the name of rapid growth and colonization. Later successional systems recycle more, close more of the loops, and require higher diversity to do this. A possible analogy in economic systems is competitive markets. To be "competitive" and efficient, markets must have a large and diverse set of participants. Monopolies can get the big jobs done,. but without diversity the system does not satisfy all the smaller product niches and is less efficient at producing what it does produce. But it is not simply the diversity of species that is important to minimizing pollution, it is how that diversity is organized into a coherent whole system. The degree of organization of a system is contained in the network of interactions between the component parts (Ulanowicz, 1980, 1986). This means that diversity is a necessary component for minimizing pollution, but it is not sufficient. The parts must also be organized so that the waste products from one process are productive inputs to other processes (Allenby and Richards, 1994). Energy, Entropy, Organization, and Embodied Energy Economists often think of energy as a commodity (i.e., oil, gas, coal) rather than as a property (the ability to do work), which is a characteristic of all commodities. Discussing the substitutability of energy for other factors of production makes sense if energy is a commodity, but not if it is a property of all commodities.

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--> The first law of thermodynamics tells us that energy and matter are conserved. But this refers to heat energy and mechanical work (call it raw energy or the bomb calorimeter energy), not to the useful part of the energy. The ability to do work is in general related to the degree of organization or order of a thing, the amount of information stored in it, not its raw energy content. Heat must be organized as a temperature gradient between a high-temperature source and a low-temperature sink before useful work is possible. Likewise, complex organized structures like cars or books have an ability to do work that is not related to their raw energy content, but is related to their degree of organization. Pollution, too, has an ability to do work (albeit unwanted, destructive work) that is proportional to its degree of organization. The second law of thermodynamics tells us that useful energy (organization) always dissipates (entropy or disorder always increases) in an isolated system, and to maintain organized structures (like trees, cars, books, and, in general, natural and man-made capital), one must constantly add energy from outside the system. But how does one measure the degree of organization of complex structures? Information theory holds some promise in this regard, but it has yet to live up to its potential. One way to approximate the degree of organization of complex structures is to calculate the amount of raw energy it takes, directly and indirectly, to build and maintain them. To do this, one must look at the complex web of interconnected production processes that are ecological and economic systems. Ecology is often defined as the study of the relationships between organisms and their environment. The quantitative analysis of interconnections between species and their abiotic environment has therefore been a central issue. The mathematical analysis of interconnections is also important in several other fields. Practical quantitative analysis of interconnections in complex systems began with the economist Wassily Leontief (1941) using what has come to be called input-output (I-O) analysis. More recently, these concepts, sometimes called the materials balance approach, or flow analysis, have been applied to the study of interconnections in ecosystems (Costanza and Neill, 1984; Finn, 1976; Hannon, 1973, 1976, 1979; Harmon et al., 1991). Related ideas were developed from a different perspective in ecology, under the heading of compartmental analysis (Barber et al, 1979; Funderlic and Heath, 1971). Isard (1972) was the first to attempt combined ecological economic system analysis using input-output methods. We refer to the total of all variations of the analysis of ecological or economic networks as network analysis. Network analysis holds the promise of allowing an integrated quantitative treatment of combined ecological economic systems. One promising route is the use of "ascendancy" (Ulanowicz, 1980, 1986) and related indices (Wulff et al., 1989) to measure the degree of organization in ecological, economic, or any

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--> other networks. Measures like ascendancy go several steps beyond the traditional diversity indices used in ecology. They estimate not only how many different species there are in a system but, more important, how those species are organized. This kind of measure may provide the basis for a quantitative and general index of system organization applicable to both ecological and economic systems. Another promising avenue of research in network analysis has to do with its use for "pricing" commodities (both productive commodities and pollution) in ecological or economic systems. The "mixed units" problem arises in any field that tries to analyze interdependence in complex systems that have many different types and qualities of interacting commodities. Ecology and economics are two such fields. Network analysis in ecology has avoided this problem in the past by arbitrarily choosing one commodity flowing through the system as an index of interdependence (i.e., carbon, enthalpy, nitrogen, etc.). This ignores the inter-dependencies between commodities and assumes that the chosen commodity is a valid "tracer" for relative value or importance in the system. This assumption is unrealistic and severely limits the comprehensiveness of an analysis whose major objective is to deal comprehensively with whole systems. There are evolving methods for dealing with the mixed units problem based on analogies to the calculation of prices in economic input-output models. Starting with a more realistic commodity by process description of ecosystem networks, which allows for joint products, one can calculate ecological interdependence factors (EIFs) to convert the multiple commodity description ultimately into a pair of matrices that can serve as the input for standard (single-commodity) network analysis. The new single-commodity description incorporates commodity and process interdependencies in a manner analogous to the way economic value incorporates production interdependencies in economic systems (Costanza and Hannon, 1989). This analysis allows the degree of organization of commodities in the system to be approximated as their direct and indirect energy cost, or embodied energy. To the extent that "organization" so defined is correlated with economic value,1 this approach may allow valuation of components of combined ecological and economic systems without resorting to subjective evaluations, which are inherently limited when applied to ecological commodities. Ecological networks evolve to use the low-entropy, high-embodied-energy by-products of processes in positive, productive ways. Economic systems may also evolve in this general direction, but we may wish to accelerate the evolutionary process to minimize the costs and disruptions inherent in trial and error. In addition, some of the possible "trials" could lead to destruction of our species, and we would not want to risk that. There are several problems and constraints that limit this accelerated but informed economic evolution. To develop sustainable, nonpolluting ecological economic systems, we need to understand and remove these constraints.

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--> Problems and Constraints of Economic Evolution Human beings, like all other animals, make decisions based on responses to local, immediate reinforcements. They follow their noses, with some mediation by genetic (and in the case of humans and some other species cultural) programming. To understand the human population problem, one needs to understand how this complex of local reinforcements and programmed responses interacts over several different time scales with the ecosystem within which humans are embedded. Biological evolution has a built-in bias toward the long run. Changing the genetic structure of a species requires that characteristics (phenotypes) be selected and accumulated by differential reproductive success. Characteristics learned or acquired during the lifetime of an individual cannot be passed on genetically. Biological evolution is therefore an inherently slow process requiring many generations to significantly alter a species' physical characteristics or behavior. Of course if the species goes through many generations rapidly (like bacteria or fruit flies), then the real time required for evolution can be much shorter than for slow-breeding species. Larger, slow-growing species inherently take more time to evolve genetically than small, fast-growing ones. Cultural evolution is much faster than genetic evolution for large, slow-growing species like humans, and in recent years it has accelerated to hyperspeed. Learned behaviors that are successful can be almost immediately spread to other members of the culture and passed on in the oral, written, or video record. The increased speed of adaptation that this process allows has been largely responsible for Homo sapiens' amazing success at controlling the resources of the planet. For example, Vitousek and coauthors (1986) estimate that humans now directly control 25 to 40 percent of the planer's primary production. But there is a significant downside. Like a car that has picked up speed, we are in much more danger of running off the road or over a cliff. Human activity is beginning to have an effect on global climate and the planet's protective ozone shield. We have lost the built-in, long-run bias of biological evolution and are susceptible to being led by our hyperefficient short-run adaptability over a cliff into the abyss. Social Traps This process of short-run incentives becoming out of sync with long-term goals has been well studied in the last decade under several rubrics (Axelrod, 1984; Hardin, 1968), but the one I like best is John Platt's notion of "social traps" (Brockner and Rubin, 1985; Costanza, 1987; Cross and Guyer, 1980; Platt, 1973; Teger, 1980). In all such cases the decision maker may be said to be trapped by the local conditions into making what turns out to be a bad decision viewed from a longer or wider perspective. We go through life making decisions about which path to take based largely on "road signs," the short-run, local reinforcements that

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--> we perceive most directly. These short-run reinforcements can include monetary incentives, social acceptance or admonishment, and physical pleasure or pain. In general, this strategy of following the road signs is effective, unless the road signs are inaccurate or misleading. In these cases we can be trapped into following a path that is ultimately detrimental because of our reliance on the road signs. For example, cigarette smoking has been a social trap because by following the short-run road signs of the pleasure and social status associated with smoking, we embark on the road to an increased risk of earlier death from smoking-induced cancer. This particular positive reinforcement has in the last few years begun to turn into a negative one. As smoking becomes less socially acceptable, we should expect the number of new smokers to fall and many old smokers to escape the trap. But the process of escape is much more difficult than the process of avoidance, Once this road has been taken, it is difficult to change to another (as most people who have tried to quit smoking can attest). Pollution is a social trap because the long-term and distributed costs of pollution (and benefits of not polluting) are not incumbent on the economic actors in the short run. The speed of cultural evolution has adversely affected our ability to adequately incorporate the long run. The Importance of Uncertainty and How to Deal with It One key element that has limited our perception of the long run and frustrated environmental policy is the enormous degree of uncertainty about long-run human impacts on the biosphere. Ignorance about the consequences is a particularly effective cause of social traps (Cross and Guyer, 1980). As regards resources, the environment, and technology, the argument can be summarized as differing opinions about the degree to which technological progress can eliminate resource constraints and solve pollution problems. Current economic world views (capitalist, socialist, and the various mixtures) are all based on the underlying assumption of continuing and unlimited economic growth. This assumption allows a whole host of very sticky problems, including population growth, equity, and sustainability to be ignored (or at least postponed), since they are seen to be most easily solved by additional economic growth. Indeed, most conventional economists define "health" in an economy as a constant and high rate of growth. Energy and resource limits to growth, according to these world views, will be eliminated as they arise by clever development and deployment of new technology. This line of thinking is often called technological optimism. An opposing line of thought (often called technological pessimism) assumes that technology will not be able to circumvent fundamental energy and resource constraints and that eventually economic growth will stop. It has usually been ecologists or other life scientists who take this point of view largely because they study natural systems that invariably do stop growing when they reach funda-

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--> mental resource constraints. A healthy ecosystem is one that maintains a stable condition. Unlimited growth is cancerous, not healthy, under this view. The technological optimists argue that human systems are fundamentally different from other natural systems because of human intelligence. History has shown that resource constraints can be circumvented by new ideas. Technological optimists claim that Malthus's dire predictions about population pressures have not come to pass and that the "energy crisis" of the late 1970s is behind us. The technological pessimists argue that many natural systems also have "intelligence" in that they can evolve new behaviors and organisms (including humans themselves). Humans are therefore a part of nature, not apart from it. Just because we have circumvented local and artificial resource constraints in the past does not mean we can circumvent the fundamental ones that we will eventually face. Malthus's predictions have not come to pass yet for the entire world, the pessimists would argue, but many parts of the world are in a Malthusian trap now, and other parts may well fall into it. This debate has gone on for several decades now. It began with Barnett and Morse's (1963) Scarcity and Growth and really went into high gear with the publication of The Limits to Growth by Meadows et al. (1972) and the Arab oil embargo in 1973. There have been thousands of studies over the last 15 years on various aspects of our energy and resource future and different points of view have waxed and waned. But the bottom line is that there is still an enormous amount of uncertainty about the impacts of energy and resource constraints, and I doubt that the argument will ever be decided on scientific grounds. In the next 20-30 years we may begin to hit real fossil fuel supply limits as well as constraints on production due to global warming. Will fusion energy or solar energy or conservation or some as yet unthought of energy source step in to save the day and keep economies growing? The technological optimists say yes and the technological pessimists say no. Ultimately, no one knows. Both sides argue as if they were certain, but the worst form of ignorance is misplaced certainty. The optimists argue that unless we believe that the optimistic future is possible and behave accordingly it will never come to pass. The pessimists argue that the optimists will bring on the inevitable leveling and decline sooner by consuming resources faster and that to sustain our system we should begin to conserve resources immediately. How do we proceed in the face of this overwhelming uncertainty? We can cast this optimist/pessimist choice in a classic (and admittedly oversimplified) game theoretic format using the payoff matrix shown in Figure 2. Here the alternative policies that we can pursue today (technologically optimistic or pessimistic) are listed on the left and the real states of the world are listed on the top. The intersections are labeled with the results of the combinations of policies and states of the world. For example, if we pursue the optimistic policy and the world really does turn out to conform to the optimistic assumptions, then

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-->   Real state of the world   Optimists right Pessimists right Current policy Technological optimist policy High Disaster   Technological pessimist policy Moderate Tolerable FIGURE 2 Payoff matrix for technological optimism vs. pessimism. the payoffs would be high. This high potential payoff is very tempting and this strategy has paid off in the past. It is not surprising that so many would like to believe that the world conforms to the optimists' assumptions. If, however, we pursue the optimistic policy and the world turns out to conform more closely to the pessimistic technological assumptions, then the result would be "Disaster." The disaster would come because irreversible damage to ecosystems would have occurred and technological fixes would no longer be possible. If we pursue the pessimistic policy and the optimists are right, then the results are only "Moderate." But if the pessimists are right and we have pursued the pessimistic policy, then the results are "Tolerable." Within the framework of game theory, this simplified game has a fairly simple "optimal" strategy. If we really do not know the state of the world and if the game is only played once (which is the case at the global level), then we should choose the policy that offers the maximum of the minimum outcomes (i.e., the MaxiMin strategy in game theory jargon). In other words, we analyze each policy in turn, look for the worst thing (minimum) that could happen if we pursue that policy, and pick the policy with the best worst case. In the case stated above, we should pursue the pessimist policy because the worst possible result under that policy ("Tolerable") is preferable to the worst outcome under the optimist policy ("Disaster"). Given this analysis, what can one recommend for pollution policy? Because of the large uncertainty about the long-term impacts on ecological sustainability, we should at least provisionally assume the worst. We must assume that the dire predictions are correct and plan accordingly. If they are right we will still survive. If they are wrong we will be pleasantly surprised. This is a much different scenario than the consequences of provisionally assuming the best about the impacts. If we assume the optimists are right and they are not, we will have irreversibly degraded the planet's capacity to support life. We cannot rationally take that risk.

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--> Toward A Sustainable, Nonpolluting Ecological Economic System How then do we communicate these conclusions to the people who make the decisions--the economic actors--and escape the pollution trap? The elimination of social traps requires intervention--the modification of the reinforcement system. Indeed, it can be argued that the proper role of a democratic government is to eliminate social traps (no more and no less) while maintaining as much individual freedom as possible (Costanza, 1987). Cross and Guyer (1980) list four broad methods by which traps can be avoided or escaped. These are education (about the long-term, distributed impacts); insurance; superordinate authority (i.e., legal systems, government, religion); and converting the trap to a trade-off by correcting the road signs. Education can be used to warn people of long-term impacts that cannot be seen from the road. Examples are the warning labels now required on cigarette packages and the warnings of environmentalists about future hazardous waste problems. People can ignore warnings, however, particularly if the path seems otherwise enticing. For example, warning labels on cigarette packages have had little effect on the number of smokers. The main problem with education as a general method of avoiding and escaping from traps is that it requires a significant time commitment on the part of individuals to learn the details of each situation. Our current society is so large and complex that we cannot expect even professionals, much less the general public, to know the details of all the extant traps. In addition, for education to be effective in avoiding traps involving many individuals, all the participants must be educated. Governments can, of course, forbid or regulate certain actions that have been deemed socially inappropriate. The problem with this approach is that it must be rigidly monitored and enforced, and the strong short-term incentive for individuals to try to ignore or avoid the regulations remains. A police force and legal system are very expensive to maintain, and increasing their chances of catching violators increases theft costs exponentially (both the costs of maintaining a larger, better-equipped force and the cost of the loss of individual privacy and freedom). Religion and social customs can be seen as much less expensive ways to avoid certain social traps. If a moral code of action and belief in an ultimate payment for transgressions can be deeply instilled in a person, the probability of that person's falling into the "sins" (traps) covered by the code will be greatly reduced, and with very little enforcement cost. On the other hand, the problems with religion and social customs as means to avoid social traps are that the moral code must be relatively static to allow beliefs learned early in life to remain in force later, and it requires a relatively homogeneous community of like-minded individuals to be truly effective. This system works well in culturally homoge-

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--> neous societies that are changing slowly. In modem, heterogeneous, rapidly changing societies, religion and social customs cannot handle all the newly evolving situations or the conflict between radically different cultures and belief systems. Many trap theorists believe that the most effective method for avoiding and escaping from social traps is to turn the trap into a trade-off. This method does not run counter to our normal tendency to follow the road signs; it merely corrects the signs' inaccuracies by adding compensatory positive or negative reinforcements. A simple example illustrates how effective this method can be. Playing slot machines is a social trap because the long-term costs and benefits to the player are inconsistent with the short-term costs and benefits to the player. People play the machines because they expect a large short-term jackpot, while the machines are in fact programmed to pay off, say, $0.80 on the dollar in the long-term.2 People may ''win'' hundreds of dollars playing the slots (in the short ran), but if they play long enough they will certainly lose $0.20 for every dollar played. To change this trap to a trade-off, one could simply reprogram the machines so that every time a dollar was put in $0.80 would come out. This way the short-term reinforcements ($0.80 on the dollar) are made consistent with the long-term reinforcements ($0.80 on the dollar), and only the dedicated aficionados of spinning wheels with fruit painted on them would continue to play. Innovative Instruments for Environmental Management Current command-and-control systems of environmental regulation are not very efficient at managing environmental resources for sustainability, particularly in the face of uncertainty about long-term values and impacts. They are inherently reactive rather than proactive. They induce legal confrontation, obfuscation, and government intrusion into business. Rather than encouraging long-range technical and social innovation, they tend to suppress it. They do not mesh well with the market signals that firms and individuals use to make decisions and do not effectively translate long-term global goals into short-term local incentives. They do not effectively turn environmental traps into trade-offs. We need to explore promising alternatives to our current command-and-control environmental management systems, and to modify existing government agencies and other institutions accordingly. The enormous uncertainty about local and transnational environmental impacts needs to be incorporated into decision making. We also need to understand better the sociological, cultural, and political criteria for acceptance or rejection of policy instruments. One example of an innovative policy instrument currently being studied is a flexible environmental assurance bonding system designed to incorporate environmental criteria and uncertainty into the market system and to induce positive environmental technological innovation (Costanza and Perrings, 1990; Perrings, 1989, 1991).

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--> In addition to direct charges for known environmental damages, a company would be required to post an assurance bond equal to the current best estimate of the largest potential future environmental damages due to its activities; the money would be kept in interest-bearing escrow accounts. The bond (plus a portion of the interest) would be returned if the firm could show that the suspected damages had not occurred or would not occur. If they did, the bond could be used to rehabilitate or repair the environment or to compensate injured parties. Thus, the burden of proof would be shifted from the public to the resource-user, and a strong economic incentive would be provided to research the true costs of environmentally damaging activities and to develop technologies that cause little pollution and provide innovative and cost-effective pollution control. This is an extension of the "polluter pays" principle to "the polluter pays for uncertainty as well." In addition, we need to develop innovative instruments to handle transnational pollution problems and the costs of natural resource depletion. Two suggestions for handling these problems are the system of ecological tariffs and the natural capital depletion tax mentioned briefly below. Conclusions Balancing the human species in the ecosystem and developing sustainable, nonpolluting ecological economic systems is, in principle, a simple problem. Simply make the long-run, distributed, whole-system costs and benefits of human activities, including uncertainty, incumbent on all individuals in the short run and locally, at least provisionally until the uncertainty can be lowered. This will greatly accelerate the natural evolutionary processes and force a "closing of the loops" to happen more quickly. If this whole-system cost accounting (including uncertainty) is in place, we can expect individual decisions about pollution control and resource consumption to help move the system toward a sustainable and nonpolluting condition. Of course, in principle is very far from in practice in this particular case. The problems of devising cultural mechanisms to effectively communicate ecological costs to individual actors are daunting. The next stage of our cultural evolution must be the development of just this capacity to put back in the long-run constraints that the initial phase of cultural evolution appeared to release us from. We need to develop and use cultural "road maps" and "scouts" to counter our dependence on "road signs'' in the tricky terrain where we now find ourselves. I offer the following summary suggestions toward the goal of developing sustainable, nonpolluting, ecological economic systems. Establish a hierarchy of goals for national and global ecological economic planning and management. Sustainability should be the primary long-term goal, replacing the current GNP growth mania. Issues of justice, equity, and population are ultimately tied in with sustainability as preconditions. Only sustainable levels of human activity are desirable. Economic growth in this hierar-

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--> chy is a valid goal only when it is consistent with sustainability. The goals can be put into operation by having them accepted as part of the political debate and implemented in the decision making structure of institutions that affect the global economy and ecology (for example, the World Bank). Develop better global ecological economic modeling capabilities to allow us to see the range of possible outcomes of our current activities, especially the interrelated impacts of population, pollution, per capita resource use, and wealth distribution. Adjust current incentives to reflect both short- and long-run, local and global ecological costs, including uncertainty. To paraphrase the popular slogan, we should model globally and adjust local incentives accordingly. Below I list three broad, mutually reinforcing policy instruments that have a high likelihood of ensuring that economic development (as distinct from economic growth) is ecologically sustainable (Costanza, 1994). They use market incentives to produce the desired results (sustainable scale, fair distribution, and efficient allocation). These incentives are as follows: a.   Ecological tax reform. A natural capital depletion tax aimed at reducing or eliminating the destruction of natural capital would assume more of the tax burden instead of taxes on labor and income. Use of nonrenewable natural capital would have to be balanced by investment in renewable natural capital to avoid the tax. The tax would be passed on to consumers in the price of products and would send the proper signals about the relative sustainability cost of each product, moving consumption toward a more sustainable product mix. This policy will encourage the technological innovation that optimists are counting on while conserving resources in case the optimists are wrong. b.   The precautionary polluter pays principle (4P) would be applied to potentially damaging products to incorporate the cost of the uncertainty about ecological damages as well as the costs of known damages (Costanza and Cornwell, 1992; Costanza and Perrings, 1990). This would give producers a strong and immediate incentive to improve their environmental performance to reduce the size of the environmental bond and tax they would have to pay. The 4P approach can allow long-term worst-case ecological costs to be made apparent to individual actors in an efficient and culturally acceptable way. c.   A system of ecological tariffs aimed at allowing individual countries or trading blocks to apply incentives a and b above without forcing producers to move overseas to remain competitive. Countervailing duties would be assessed to impose fairly the ecological costs associated with production on both internally produced and imported products. Revenues from the tariffs would be reinvested in the global environment, rather than added to general revenues of the host country. The ecological tariffs should be proportional to the environmental damages that occur any-

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--> where in the world as a by-product of the product's production. They can be unilaterally applied by any country without damaging that country's trade balance or economic performance. Countries that do not implement systems to ensure ecologically benign production would be at a competitive disadvantage since their products will be harder to sell abroad in countries that have ecological tariffs. In other words, the ecological tariff system would protect local producers of ecologically benign products as well as discouraging ecologically destructive production abroad. Once a few large countries implemented the system, the rest of the world would be forced to follow suit. The ecological tariffs, in conjunction with the 4P system and the natural capital depletion tax, would provide the appropriate incentives to turn many of our current ecological traps into trade-offs and provide the appropriate constraints to lead to a sustainable ecological economic system. Notes 1.   Recent studies (Cleveland et al., 1984; Costanza, 1980; Costanza and Herendeen, 1984; Gever et al., 1986; Hall et al., 1986) indicate that in fact this correlation is surprisingly strong. 2.   Slot machines are obviously not a trap for the owners of the machines. References Allenby, B. R., and D. J. Richards, eds. 1994. The Greening of Industrial Ecosystems. Washington, D.C.: National Academy Press. Axelrod, R. 1984. The Evolution of Cooperation. New York: Basic Books. Barber, M., B. Patten, and J. Finn. 1979. Review and evaluation of I-O flow analysis for ecological applications. In Compartmental Analysis of Ecosystem Models. Vol. 10 of Statistical Ecology, J. Matis, B. Patten, and G. White, eds. Burtonsville, Md.: International Cooperative Publishing House. Barnett, H. J., and C. Morse. 1963. Scarcity and Growth: The Economics of Natural Resource Availability. Baltimore, Md.: Johns Hopkins. Brockner, J., and J. Z. Rubin. 1985. Entrapment in Escalating Conflicts: A Social Psychological Analysis. New York: Springer-Verlag. Cleveland, C. J., R. Costanza, C. A. S. Hall, and R. Kaufmann. 1984. Energy and the United States economy: A biophysical perspective. Science 225:890-897. Costanza, R. 1980. Embodied energy and economic valuation. Science 210:1219-1224. Costanza, R. 1987. Social traps and environmental policy. BioScience 37:407-412. Costanza, R., ed. 1991. Ecological Economics: The Science and Management of Sustainability. New York: Columbia University Press. Costanza, R. 1994. Three general policies to achieve sustainability. Pp. 392-407 in Investing in Natural Capital: The Ecological Economics Approach to Sustainability, A. M. Jansson, M. Hammer, C. Folke, and R. Costanza, eds. Washington, D.C.: Island Press. Costanza, R., and L. Cornwell. 1992. The 4P approach to dealing with scientific uncertainty. Environment 34:12-20, 42. Costanza, R., and B. M. Hannon. 1989. Dealing with the "mixed units" problem in ecosystem network analysis. Pp. 90-115 in Network Analysis of Marine Ecosystems: Methods and Applications. Coastal and Estuarine Studies Series, F. Wulff, J. G. Field, and K. H. Mann, eds. Heidleberg: Springer-Verlag.

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--> Costanza, R., and R. A. Herendeen. 1984. Embodied energy and economic value in the United States economy: 1963, 1967, and 1972. Resources and Energy 6:129-163. Costanza, R., and C. Neill. 1984. Energy intensities, interdependence, and value in ecological systems: A linear programming approach. Journal of Theoretical Biology 106:41-57. Costanza, R., and C. H. Perrings. 1990. A flexible assurance bonding system for improved environmental management. Ecological Economics 2:57-76. Cross, J. G., and M. J. Guyer. 1980. Social Traps. Ann Arbor: University of Michigan Press. Finn, J. 1976. The cycling index. Journal of Theoretical Biology 56:363-373. Funderlic, R., and M. Heath. 1971. Linear Compartmental Analysis of Ecosystems. ORNL-IBP-71-4. Oak Ridge, Tenn.: Oak Ridge National Laboratory. Gever, J., R. Kaufmann, D. Skole, and C. Vörösmarty. 1986. Beyond Oil: The Threat to Food and Fuel in the Coming Decades. Cambridge, Mass.: Ballinger. Hall, C. A. S., C. J. Cleveland, and R. Kaufmann. 1986. Energy and Resource Quality: The Ecology of the Economic Process. New York: Wiley. Harmon, B. 1973. The structure of ecosystems. Journal of Theoretical Biology 41:535-546. Hannon, B. 1976. Marginal product pricing in the ecosystem. Journal of Theoretical Biology 56:256-267. Harmon, B. 1979. Total energy costs in ecosystems. Journal of Theoretical Biology 80:271-293. Hannon, B., R. Costanza, and R. Ulanowicz. 1991. A general accounting framework for ecological systems: A functional taxonomy for connectivist ecology. Theoretical Population Biology 40:78-104. Hardin, G. 1968. The tragedy of the commons. Science 162:1243-1248. Isard, W. 1972. Ecologic-Economic Analysis for Regional Development. New York: The Free Press. Leontief, W. 1941. The Structure of American Economy, 1919-1939. New York: Oxford University Press. Ludwig, D., R. Hilborn, and C. Walters. 1993. Uncertainty, resource exploitation, and conservation: Lessons from history. Science 260:17, 36. Meadows, D. H., D. L. Meadows, J. Randers, and W. W. Behrens. 1972. The Limits to Growth. New York: Universe. Perrings, C. 1989. Environmental bonds and the incentive to research in activities involving uncertain future effects. Ecological Economics 1:95-110. Perrings, C. A. 1991. Reserved rationality and the precautionary principle: Technological change, time and uncertainty in environmental decision making. Pp. 153-167 in Ecological Economics: The Science and Management of Sustainability, R. Costanza, ed. New York: Columbia University Press. Pezzey, J. 1989. Economic Analysis of Sustainable Growth and Sustainable Development. Environment Department Working Paper No. 15. Washington, D.C.: The World Bank. Platt, J. 1973. Social traps. American Psychologist 28:642-651. Teger, A. I. 1980. Too Much Invested to Quit. New York: Pergamon. Ulanowicz, R. E. 1980. An hypothesis on the development of natural communities. Journal of Theoretical Biology 85:223-245. Ulanowicz, R. E. 1986. Growth and Development: Ecosystems Phenomenology. New York: Springer-Verlag. Vitousek, P., P. R. Ehrlich, A. H. Ehrlich, and P. A. Matson. 1986. Human appropriation of the products of photosynthesis. BioScience 36:368-373. World Commission on Environment and Development. 1987. Our Common Future. Oxford: Oxford University Press. Wulff, F., J. G. Field, and K. H. Mann. 1989. Network Analysis of Marine Ecosystems: Methods and Applications. Coastal and Estuarine Studies Series. Heidleberg: Springer-Verlag.

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