Calculating the Change-Potential Index

The coastal change-potential index (CPI) presented here is similar to the CVI used in Thieler and Hammar-Klose (1999) and Gornitz and others (1994), as well as to the sensitivity index employed by Shaw and others (1998). The CPI allows six variables to be related in a quantifiable manner that expresses the relative change potential of the coast to physical changes due to future lake-level change. This method yields numerical data that cannot be equated directly with particular physical effects. It does, however, highlight areas where the various effects of lake-level change may be the greatest. Once each section of coastline is assigned a change-potential value for each specific data variable, the coastal change-potential index (CPI) is calculated as the square root of the product of the ranked variables divided by the total number of variables;

where, a = geomorphology, b = shoreline erosion/accretion rate, c = coastal slope, d = relative lake-level change rate, e = mean significant wave height, and f = mean annual ice cover. The calculated CPI value is then divided into quartile ranges to highlight different vulnerabilities within the park. The CPI ranges (low - very high) reported here apply specifically to Apostle Islands NL, Indiana Dunes NL, and Sleeping Bear Dunes NL, respectively, and are not comparable to CPI ranges in other parks where the CPI has been employed (i.e. very high change-potential means the same among parks; it's the numeric values that differ). For example, a numeric value that equals very high change potential in one park may equal moderate change potential in another. We believe the approach used in this study best describes and highlights the change-potential specific to individual park units.