Valuation of Biodiversity Benefits (OECD)

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Several problems however exist, rendering category assessment quite difficult to apply inpolicy making. While the classification of a species in a category relies on an objective evaluation, theactual definitions of these categories rely on a subjective view. In practice, the large number ofavailable criteria (e.g. α , β and γ criterion) used for evaluation in some way already reflect thedifficulties that exist in determining value. Furthermore, the information provided by the list of speciesunder the category labelled as “threat” is not necessarily sufficient to determine priorities forconservation action Indeed, if Red Data Books are elected as the ecological method to establishbiodiversity priorities, it is likely that choices would be made based on the likelihood of speciesextinction rather than on the (differences) level of among the gene flow between the survival speciesand the species with higher probability of extinction. Finally, given the scientific understanding ofpopulation and ecosystems, it is possible to develop alternative and more complete indicatorsinvolving the use of numerous other criteria concerning conservation action.An early example of a multi-criteria rating is the method proposed by Randwell (1969). Themethod was used to evaluate coastal habitats and combines the use of eight criteria into a single score,the Comparative Biological Value Index (CBVI). Each of these criteria are rated according to the scaleshown in Table 8.2 and the final score is obtained by summing up the scores for all the nine criteria:CBVI = Ph + O + D + G + S + P + E + CThe maximum potential value is 28 and the minimum value is 7. The higher the CBVI valuethe greater the requirement for site protection. Since Randwell, the use of indices constitutes a popularpractice in ecological valuation and management (see Spellerberg 1992 for an extensive review ofCBVI assessment of landscape and urban habitats). However, this valuation approach relies on inputcriteria that require some subjective valuation. As such they may not be helpful to the decision-makingprocess as originally intended.Recently, computer-based systems have been used to develop a general, integratedframework where one can simulate natural/management changes and assess the respectiveconservation evaluations. One specific application of this valuation approach is to study speciespopulation dynamics and estimate a minimum viable population, defined as the smallest populationwhich has an acceptable probability of persisting over a given time period (Soulé 1987). 52 This in turnallows for the calculation of the minimum dynamic area, i.e. the geographical area of suitable habitatrequired to support the minimum viable population. Recent published studies on the leadbeaster’spossum (Lindenmayer et al. 1993), the eastern barred bandicoot (Lacy and Clark 1990), the Scottishwild boar, and the giant panda (Zhou and Pan 1997) confirm the use of the population viabilityanalysis in policy decision circles and help conservation decisions. Another example of the applicationof a computer system to ecological evaluation is the System for Evaluating Rivers for Conservation(SERCON) recently undertaken by the Scottish Natural Heritage, the nature conservation agency inScotland (Boon et al. 1997). The overall objective was to predict the impact of different developmentscenarios on river ecological conservation value as well as to provide a simple way of communicatingsuch results to planners, developers and policy-makers.Ecological valuation based on computer modelling presents important advantages. First, itencourages greater rigour in data evaluation since it permits the introduction of elements ofsubjectivity within a transparent and consistent framework. Second, it allows for a direct comparisonof alternative conservation policies, independently of the number of criteria involved and respectiveattributes. For example, it permits the comparison of a conservation policy involving a criterion with52Several general models have been developed for this task, e.g. VORTEX (Lacy 1993) and METAPOP(Akcakaya 1994), and these can be used to consider the complex interactions between demographic,environmental and genetic influences on a population.159
ten attributes that could score a maximum of 50, with another strategy involving a criterion with twoattributes that could only score a maximum of 10. Finally, it permits an evaluation even when some ofthe attribute data are missing, which is common in practice.Table 8.2 Rating of the criteria used by Randwell for evaluating coastal habitatsCriteriaPhysicochemical features(Ph)Optimum populations(O)Diversity(D)Geographic units(G)Size(S)Purity(P)Education and research use(E)Combinations of localities(C)Source: Randwell (1969).TypeHigh specialitySome special featuresType exampleBest populations of one or more local speciesLarge populations of local speciesLarge populations of common species and small populations of local speciesRepresentative populationsOutstanding populationsHigh diversitySpecies ranges smallMany species at limitSome species at limitDew species or no species at limitMud-flats (ha)> 40001600 – 3999800 – 1599400 – 799< 400Little disturbanceModerate disturbanceMuch ground disturbed or pollutedMuch usedSome usePotential useCliffs (km)> 8040-7924-398-23
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«ENVIRONMENTValuation ofBiodiversi
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ORGANISATION FOR ECONOMIC CO-OPERAT
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TABLE OF CONTENTSPART 1 ...........
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PART 4 ............................
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Why value biodiversity?There are th
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Figure 1.1 Total economic value: us
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from biodiversity at the local leve
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in the database and also for undert
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in the policy context. This is high
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Table 1.3 Policy Options for the Cl
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Box 1.2 Value of Turkey’s Forests
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of the most important implications
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Additionally, valuation does not ju
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value is the habitat, many differen
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are very modest. More recently, new
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Table 2.2 Estimates of the Medicina
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The importance of indirect use valu
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pharmaceutical use, although the li
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McAllister, D., (1991). Estimating
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Simpson, D and Craft, A.. (1996).
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practice, the overlap between these
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aimed at giving more precise quanti
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structural values. There are a numb
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Reid (forthcoming) discusses the po
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Ecotourism as a Way to Generate Loc
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endangered Indian rhino and other t
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ReferencesBann, C., and M. Clemens
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PART 261
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many European countries, CBA has a
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(1) Cost and time constraintsThe co
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activity day, there is greater vari
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added independent variable C s= cha
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error in valuing respiratory sympto
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ReferencesArrow, K.J., R. Solow, E.
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OECD (1995). The Economic Appraisal
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CHAPTER 5:by José Manuel LIMA E SA
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linkages usually lead to diverse co
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A discrete choice approach to quest
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Table 5.2 Model-based point estimat
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is potentially very large for multi
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P3 is already in the mix is 2.51, s
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PART 391
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measures of value. An appendix to t
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features (such as parks, beaches or
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included in cost-benefit analysis o
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A Discussion of Past Efforts to Dev
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Satellite AccountsIn addition to th
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which many people argue are associa
Page 99 and 100: approach to competing uses of water
Page 101 and 102: Figure 6.2 Trade-Off AnalysisEnviro
Page 103 and 104: However, the farmers need not bear
Page 105 and 106: Appendix 1: Theory and Application
Page 107 and 108: iwhere C is the income adjustment n
Page 109 and 110: complete. If there are more than on
Page 111 and 112: Horowitz, Joel. L. and Jordan. J. L
Page 113 and 114: CHAPTER 7:by Dennis M. KING and Lis
Page 115 and 116: Box 7.1 Definition of terms related
Page 117 and 118: Box 7.2 Categories of Ecosystem Ser
Page 119 and 120: Box 7.4 Dollar-based ecosystem valu
Page 121 and 122: Non-monetary indicators of ecosyste
Page 123 and 124: Figure 7.1 Effects of Wetland Locat
Page 125 and 126: description, and that the usefulnes
Page 127 and 128: 2) Service capacity sub-indexIndica
Page 129 and 130: wetlands, for example, results in F
Page 131 and 132: (1) Functional CapacityIndexFigure
Page 133 and 134: constituents of runoff can be predi
Page 135 and 136: Service(on or off site)Recreational
Page 137 and 138: Table 7.3 Service Risk Sub-index De
Page 139 and 140: Measuring Service Preference Weight
Page 141 and 142: Table 7.4 Illustration of Paired Co
Page 143 and 144: PART 4151
Page 145 and 146: Ecological foundations for biodiver
Page 147 and 148: Phenotic diversity is a measure bas
Page 149: Operationalisation of the biotic-ri
Page 153 and 154: The choice of the scale relates to
Page 155 and 156: Nature measurement methodIn 1995, t
Page 157 and 158: Table 8.4 Value orientations and en
Page 159 and 160: Table 8.5 Identification of monetar
Page 161 and 162: Table 8.6 Valuation studiesSingle s
Page 163 and 164: in waterway systems for nine impact
Page 165 and 166: to other contexts, conditions, loca
Page 167 and 168: ReferencesAkcakaya, H.R. (1994).
Page 169 and 170: de Groot, R.S. (1994). “Environme
Page 171 and 172: Mace, G. M. & S. N. Stuart. (1994).
Page 173 and 174: Turner, R.K., Perrings, C. and Folk
Page 175 and 176: John A. DixonJohn A. Dixon is Lead
Page 177 and 178: Robert O’NeillDr. O’Neill recei
Page 179 and 180: Steven StewartSteven Stewart is Ass
Page 181: OECD PUBLICATIONS, 2, rue André-Pa
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