Environmental Risk Assessment and Management from a Landscape Perspective (Kapustka/Environmental Risk) || Metrics and Indices for Sustainable Social-Ecological Landscapes
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18METRICS AND INDICES FOR
LANDSCAPESRonald J. McCormick
Most people think the future is the ends and the present is the means. In fact, thepresent is the ends and the future the means.
This discussion started (Chapter 16) by introducing a question from ecological eco-nomics, What is the scale of the economy that fits inside the ecology? We presenteda general deconstruction of neoclassical economics and explored how scale appearsmerely implicit in economic models, whereas explicit definition of scale is required inany model of a complex system. Providing explicit definitions of scale and ecologicaltype sets a clear level of analysis. In Chapter 16, we described how recent advances insystems theory (high-gain/low-gain analysis) allows for the blending of market ther-modynamics and social regulation via the field of economic ecology, which naturallyleads to issues of sustainability. As society moves to a low-gain perspective on man-aging for sustainable socialecological landscapes, the assumptions and limitationsinherent in available economic valuation techniques become quite apparent.
The primary limitation of most valuation techniques lies in how one sets theboundaries of a system of interest. Benefitcost analysis has limited temporal rele-vance due to the inherent uncertainty in any financial forecast data. The majority offinancial prognostications put forth in early 2008 proved to be completely and utterly
Environmental Risk and Management from a Landscape Perspective, edited by Kapustka and LandisCopyright 2010 John Wiley & Sons, Inc.
382 METRICS AND INDICES FOR SUSTAINABLE SOCIALECOLOGICAL LANDSCAPES
useless by the autumn of that year. At the root of the subprime mortgage meltdownwas the idea that one could take securities developed under one (local) level of anal-ysis and (presumed minimal) risk scenario and expand those same risks upscale to aglobal market. Moving upscale changed the initial level of analysis that the systemwas working within, but most analysts, placing total trust in mathematical models,missed that fact. Indeed, even Alan Greenspan, in his testimony to the U.S. Congresson October 23, 2008, said I found a flaw in the model that I perceived is the criticalfunctioning structure that defines how the world works. The flaw was that his modelassumed self-correction in the securities market would take place at an individualinstitution level, thus protecting local investors. Self-correction did occur, but notat the level in the system where it was needed, it occurred at a global, and nearlycatastrophic, level.
Though the subprime debacle is attributable to no single action, a key indicatorof lender risk, interest rate, was reduced in variance as part of the process of offeringmore loans (Rajan et al. 2008). A person with a poor credit rating received a loan atan interest rate very similar to what someone with a good credit rating was offered.The effect of this was that once a single degree of separation existed between theperson receiving the loan and the person or institution holding the note, there wasno way to compare relative risk between mortgage packages (interest rate providedinsufficient signal). Lack of transparency of actual risk at a low level in the processallowed unequally risky loans to appear as equally risky loans at a different level inthe system.
Human systems, especially socioeconomic systems with designed allowableinteractions, are fraught with these kinds of unrecognized risks. Landscapes supportingecosystem processes and intact communities are self-organizing (no set interactionrules) and open to the flow of energy, materials, and information (total transparency).If a plant or animal signals that I taste bad via bright red markings, then mostanimals will heed the warning and steer clear. However, as the communicationof information is open, some animal might see and accept the risk and have asnack. Whether accepting that risk was wise or unwise is answered very quicklyvia feedback from the consumers body, not years later via a party not involved inthe original snack decision. Timely and relevant feedback and open communicationmake ecosystems function effectively. Businesses that mimic these characteristicsusually prosper (sensu Pascale et al. 2001). Sustainable socialecological landscapesneed to adopt these strategies in order to manage risk and flourish in the face ofchange.
Aldo Leopold urged people to think like a mountain, a mantra often used bythe deep ecology movement. However, while environmentalists were thinking like amountain, the rest of society built roads, logged off the trees, extracted any valuableores, and harvested the edible wildlife, all while the mountains glaciers were meltingand relentlessly eroding it, becoming silt in some valley. Perhaps in this, the 21stcentury, we need to think like an ecosystem, to know where the matter and energywe use came from, where it is going, and how effectively we use it while we havecontrol. This is the heart of economic ecology and is the root of sustainability.
ULTIMATE MEANS, ULTIMATE ENDS 383
Science & Technology
Theology & Ethics
HappinessHarmony, identityFulfillment, self-respectSelf-realization, communityTranscendence, enlightenment
Health, wealthLeisure, mobilityKnowledge, communicationConsumer goods
Labor, toolsFactoriesProcessed raw materials
Solar energyThe biosphereEarth materialsBiogeochemical cycles
Figure 18.1. Connections inherent in any socialecological landscape. [Modified from Mead-ows (1988).]
ULTIMATE MEANS, ULTIMATE ENDS
Referring to a socialecological landscape is a short-hand way of referring to a soci-etys ultimate ends, the goals and values of that society, and the constraints placedon those goals by the natural capital available on a landscape, the ultimate means ofecological goods and services. Herman Daly, in his 1973 book Toward a Steady-StateEconomy [as quoted in Meadows (1998)], outlined a hierarchy where the economyand daily human endeavors (intermediate means and ends) were placed in contextbetween natural capital and human well-being (Fig. 18.1). This framework remainshighly relevant today, some 35 years later.
Meadows (1998) used Dalys framework to guide the selection of indicators forsustainable development. Her explanation of what indicators are and why they are sodifficult to develop closes with the notion that (a) we need more than just indicators,(b) we need information systems that are organized and scaled along a hierarchy fromfine-grained to coarse-grained, and (c) information is open to and modifiable at alllevels. This echoes my call to think like an ecosystem and reflects a low-gain view ofhow a sustainable world might be organized. Meadows went on to show how systems
384 METRICS AND INDICES FOR SUSTAINABLE SOCIALECOLOGICAL LANDSCAPES
thinking is vital to indicator development, and how conceptual modeling and dynamicmodeling are necessary to fully develop and evaluate any multilevel indicator system.
Hierarchy theory (Ahl and Allen 1996) and systems analysis focuses on bound-aries, specifically the porosity and rate of exchange at boundaries. The question Whatis the scale of the economy? is a simple model that seeks to know how much theboundary of the economy can infringe on the whole of the ecology. Indicators thatonly track the central tendencies of a system will not provide timely data on a sys-tems variance, and a system can fail well before a signal is seen in those indicators.Indicators need to focus on the boundaries of the system, the place where information,matter, and energy are exchanged at a rate. Again, Meadows (1998) reflected thesenotions in her statement The three most basic aggregate measures of sustainabledevelopment are the sufficiency with which ultimate ends are realized for all people,the efficiency with which ultimate means are translated into ultimate ends, and thesustainability of use of ultimate means.
Obviously, a thorough reading of Meadows work is recommended, because Ihave only presented the key points and there is much more depth to be explored. It isto me one of the most useful and cogent presentations on indicators and informationsystems. My intent in presenting Meadows work is to offer not just another genericset of indicators that may not work for your landscape, but instead a conceptualmodel of how to select and structure your own unique and usable indicator set. Toeffectively develop a set of indicators, you will also need a conceptual model of yoursocialecological landscape, outlining the hierarchy of interacting elements.
Conceptual Modeling in Ecological Risk Management
Monetized valuation systems are not sufficiently scalable and flexible to help us trackwhat we extract, degrade, and return to a landscape. Indicators are needed at multiplelevels in the system in order to fully assess the rate we extract goods and servicesfrom a landscape, as well as the rate at which we expel waste back into that landscape.There are myriad indicators that could be developed to answer these questions. TheEcological Footprint (Wackernagel and Rees 1996) is one very good example of ascaleable, multilevel indicator. The issue then is to decide which indicators actuallytell us what we need to know when we need to know it. The field of risk assessmentand management offers a process by which key social issues and ecological stressorscan be brought to the surface and analyzed in context. The holistic risk frameworkis presented elsewhere in this book (Chapter 8). Her