Abstract
A prototype multi-purpose index is proposed for use in the evaluation of practices for adaptation to climate variability and change. The Index of Usefulness of Practices for Adaptation (IUPA) allows the user to assign weights and scores to a set of user-defined evaluation criteria. Individual criterion scores are aggregated into a final index value. Both the final value and the individual parameter scores provide useful information for improved decision making in the context of climate change. An innovative aspect of IUPA is that guidance is given to the user through the inclusion of recommendations on evaluation criteria and criterion-specific weight factors. These have been defined by a panel of experts from the Latin-American and Caribbean Region (LAC). Application of the index is demonstrated for an existing adaptation practice from the Coquimbo Region, Chile. The IUPA tool is recommended for use in the evaluation of adaptation practices in their design, implementation and post-implementation phase. It is practical for a quick first assessment or when limited financial resources are available, making the tool especially useful for practitioners in the developing world. The index is flexible both from the perspective of its construction and use. Additional expert opinions can easily be included in the future versions of the tool.
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Acknowledgements
The authors would like to specially thank the Inter American Institute for Global Change Research IAI for the financial support provided through Grant [TISG-P-1] which is supported by the US National Science Foundation (Grant GEO-0436199). The authors further wish to thank their respective home institutions for all received support. Activities at EULA-CHILE and CIEMA-Nicaragua were developed in the context of the TWINLATIN Project (EC 6FP, Contract No 018436).
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Appendix
Appendix
1.1 User manual (description of the matrix structure)
The proposed matrix has been incorporated in an excel workbook called ‘checklist IUPA.xls’. Interested readers can obtain a copy of the workbook by sending an electronic message to paldunce@uchile.cl.
1.2 Structure of the matrix
The matrix used for calculating the IUPA value consists of 14 columns grouped according to three major topics: (I) ‘variables’; (II) ‘suggestions of the panel’: relative importance of each variable, as perceived by the group of experts; and (III) ‘evaluation by the user’: user assigned variable weights and scores.
Group I lists and describes the different variables (criteria) that can be evaluated in the evaluation of the usefulness of an adaptation practice. Column A organizes the variables according to three different types: (i) Class A or core variables whose inclusion in the evaluation process is considered ‘obligatory’; (ii) Class B or complementary variables that are suggested by the panel of experts; and (iii) Class C or additional user-defined variables that have been identified by the user himself as being important for the specific case under study, and whose inclusion in the matrix was originally not suggested by the panel of experts.
The numerical value given in Column B corresponds to a unique identifier (ID) and does not reflect any kind of ranking or evaluation of importance of a variable by the group of experts. Column C contains the name of the evaluation criteria for the adaptation practices. A short description of the meaning of each variable is contained in Table 1 of the article.
The second group of columns contains suggestions from the expert team with respect to the relative importance of the different evaluation criteria. Column D contains the suggested weight that each variable should have in the calculation of the final index value. The suggested weight for a given variable was obtained by taking the mean of the weights assigned by each member of the IUPA expert panel (n = 8). A value close to 0 means a low relevance to the variable under consideration in the evaluation of the global usefulness of an adaptation practice and a weight of 10 indicates highest relevance. Zero indicates that the variable is not being considered in the calculation of the index value. The values suggested in Column D, if considered adequate, can be adapted by the user or modified accordingly; it is the user-defined weight factors (to be entered in Column I of Group III) that will finally be used in the index calculation.
Column E is a qualitative interpretation of the value that has been assigned by the experts to the variable ‘suggested relevance’. It is not used in the calculation; its content is automatically generated by the spreadsheet based on ‘relevancy’ intervals which have been defined by the group of experts (see Table 4 of the article for the used classification criteria). When assigning the final value for the weight factor in Column J, the user is free to follow or not the suggestion to place the user-defined weight value within the corresponding relevancy intervals (Table 4).
The next three columns give additional information on the expert panel opinions with respect to the variable weight. Column F indicates the number of experts (‘n’) that have emitted an opinion with respect to the variable weight. Column G contains the standard deviation (‘σ’) of the assigned weights, and gives a quantitative indication of the homogeneity/heterogeneity of expert opinions. Column H, finally, allows a quick interpretation of the degree of homogeneity in the answers from the experts, helping the user to evaluate how recommended it is to follow the suggestions given in Column F (homogeneity classification criteria are given in Table 5).
The third group of columns corresponds to the interactive part of the matrix. The user can assign ‘weights’ and ‘scores’ to each one of the selected variables, and by doing so evaluate the usefulness of a given practice, based both on individual variable scores, as well as by interpreting the calculated integrated IUPA index value.
User-assigned weights for each variable and variable score (between 0 and 10) for the adaptation practice under consideration are entered through Column I and Column K, respectively. User-defined weight factors for the different variables can be developed and assigned in a similar way as was done by the expert panel: the user can consult one or a group of local experts and then determine a mean value (ideally experts would have a good knowledge of the specific context of the case area and/or adaptation practice or need); or alternatively, the user can opt to determine and assign the weight factors himself; in this last case, he can base his decision on the expert-panel suggested weight factors, but introduce modifications to these values based on his own knowledge of the specific characteristics and needs for the case study under consideration.
The intermediate Column J corresponds once more to a spreadsheet-generated automatic interpretation of the weight value, this time the weight value that has been assigned by the user. It can be used to quickly evaluate how far the user opinion with respect to parameter relevance differs from the opinion of the expert panel. Column L contains the net contribution of each variable to the final index score, which is obtained by multiplying the weight by score (Columns I and K). Finally, the weighted sum of individual parameter scores leads to the IUPA index value, which is contained in the lowermost cell of Column L.
Columns M and N have a similar functionality as Columns K and L, but are used for evaluating practices in the post-implementation phase. Columns K and L versus M and N facilitate comparison of scores, obtained, for example, for a given practice in its pre- and post-implementation phase. Alternatively, these additional columns can also be used to evaluate the effect of incorporating modifications to a proposed adaptation strategy, or for comparing alternative strategies for dealing with a given adaptation need.
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Debels, P., Szlafsztein, C., Aldunce, P. et al. IUPA: a tool for the evaluation of the general usefulness of practices for adaptation to climate change and variability. Nat Hazards 50, 211–233 (2009). https://doi.org/10.1007/s11069-008-9333-4
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DOI: https://doi.org/10.1007/s11069-008-9333-4