How to evaluate vulnerability in changing environmental conditions

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490 CHAPTER E.2 .Predictability and Uncertainty tions are assessed in an impacts model to estimate the theory: individualistic, egalitarian and hierarchical. sensitivity of water resources in this region to this as- Different parameterisations of the model may then pect of climate variability and change. be determined. There is also a strong water compo- In recent years there has been a growing number of nent within this modelling framework from which studies and modelling attempts on global environmen- to compute the basic supply and demand issues of tal change which take uncertainty into account. Within water resources (Hoekstra 1996). these studies one might want to distinguish between 3. There is a recent attempt to apply qualitative model- (1) classical probabilistic approaches, (2) new, quantitative ling techniques to the analysis of environmental approaches based on theoretical frameworks such as change. Originally :,uggested by the German Advisory cultural theory and u) qualitative, yet formal approaches. Council on Global Change (WBGU 1994) and in cooperation with the Council, and further developed by 1. More traditional approaches within integrated assess- Schellnhuber et al. (1997) and Petschel-Held et al. ments of climate change are taken, for example, in the (1999b), the syndrome approach tries to identify ma- PAGE 95 model (Plambeck and Hope 1996) or in the jor patterns of civilisation-nature interactions, which ICAM 2.0 and 2.5 models (Dowlatabadi and Morgan govern the dynamics of environmental change. Most 1995) which use probability distribution functions to interesting in the present context is the 1997 Annual represent uncertainties in parameters and functional Report of the Council (WBGU 1999) which focuses relationships. The implication of learning as the major process in reducing uncertainties is central to the on the sustainable use of freshwater resources. studies by Kolstad and Kelly (1999).A recent overview As discussed here, a vulnerability assessment provides on the issue of uncertainty in climate change assess- a comprehensive framework within which to estimate ments is given in Schellnhuber and Yohe (1998) or environmental risk. This is in contrast to starting with a Dowlatabadi (1999). scenario approach which limits the spectrum of estimates 2. An innovative approach is taken within the TARGETS to what can actually occur in the future. With the sce- modelling framework (Rotmans and de Vries 1997; nario approach, for example, environmental "surprises" Hilderink et al.1999) where uncertainties are related (Canadell 2000) will b,e missed. These two divergent ap- to three different world views, based on cultural proaches are discussed further in the next chapter.
Contrast between Predictive and Vulnerability Approaches Roger A. Pielke, Jr. Thomas J. Stohlgren While efforts to predict natural phenomena have be- These considerations suggest that the usefulness of come an important aspect of the Earth sciences, the value scientific prediction for policy making and the reso- of such efforts, as judged especially by their capacity to lution of societal problems dept~nds on relationships improve decision making and achieve policy goals, has among several variables, such as the timescales under been questioned by a number of constructive critics. The consideration, the scientific complexity of the phenom- relationship between prediction and policy making is ena being predicted, the political and economic context not straightforward for many reasons. In practice, con- of the problem, and the availability of alternative sciensolidative and exploratory models are often confused tific and political approaches to the problem. by both scientists and policy-makers alike, thus a cen- In light of the likelihood of complex interplay among tral challenge facing the community is the appropriate these variables, decision makers and scientists would use of such models and resulting predictions (Sarewitz benefit from criteria that would allow them to judge the and Pielke 1999). potential value of scientific prediction and predictive Among the reasons for this criticism is that accurate modelling for different types of political and social prob- prediction of phenomena may not be necessary to relems related to Earth processes arid the environment. spond effectively to political or socio-economic problems Pielkeet al.(1999) provide the fcMowing six guidelines created by such phenomena (for example, see Pielke et al. 1999). Indeed, phenomena or process~s of direct concern for the effective use of prediction :in decision making. to policy-makers may not be easily predictable or useful. 1. Predictions must be generated primarily with the Likewise, predictive research may reflect discipllne-spe"",- needs of the user in mind. For stakeholders to parcific scientific perspectives that do not provide "answers" ticipate usefully in this process, they must work closely to policy problems since these may be complex mixtures and persistently with the scientists to communicate of facts and values, and which are perceived differently their needs and problems. by different policy-makers (for example, see Jamieson 2. Uncertainties must be clearly articulated (and under- and Herrick 1995). In addition, necessary political action may be deferred stood) by the scientists, so that users understand their implications. Failure to understand uncertainties has in anticipation of predictive information that is not forth- contributed to poor decisions that then undermine coming in a time frame compatible with such action. relations among scientists and decision makers. But Similarly, policy action may be delayed when scientific merely understanding the uncertainties does not uncertainties associated with predictions become politi- mean that the predictions will be useful. If policycally charged as in the issue of global climate change, for makers truly understood the uncertainties associated example (Rayner and Malone 1997>. with predictions of, for example, global climate Predictive information may also be subject to manip- change, they might decide that strategies for action ulation and misuse, either because the limitations and should not depend on predictions (Rayner and Ma- uncertainties associated with predictive models are not lone 1997>. readily apparent or because the models are applied in a 3. Experience is an important fa(:tor in how decision climate of political controversy and high economic makers understand and use prt~dictions. stakes. In addition, emphasis on predictive sciences 4. Although experience is important and cannot be re- moves both financial and intellectual resources away placed, the prediction process can be facilitated in from other types of research that might better help to other ways, for example by fully considering alterna- guide decision making as, for example, incremental or tive approaches to prediction, such as "no-regrets" adaptive approaches to environmental management that require monitoring and assessment instead of predic- public policies, adaptation, and better planning and engineering. Indeed, alternatives to prediction must tion (see Lee and Black 1993). be evaluated as a part of the prE~diction process.
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Page 19 and 20: 500 CHAPTER E.5 .The Vulnerability
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Page 33: Case Studies Roger A. Pielke, Sr. I
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Page 57 and 58: References Part E Adams RM, Crocker
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Schellnhuber H-J, Yohe G (1998) Com
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