Ecology and Development Series No. 10, 2003 - ZEF

Conservation of the wild Coffea arabica populations in situPCA axis. The second PCA axis represents the second gradient of environmental variables.The PCA axis scores can better explain the variations of environmental gradients, sincethey account for all possible combinations of variables that were not or could not bemeasured (Mora and Iverson 2002; Reyers et. al 2002). The distribution patterns of theabundances of coffee and diversity index predicted by these relationships (figure 6.3 a, b)are similar to the patterns observed in the forest vegetation (Chapter 4.3). Similarly, theareas at low altitudes had high diversity indices, and those at the mid and high altitudes ongentle slopes show high coffee abundance.Ideally, decision-making concerning biodiversity conservation should take intoaccount as many relevant criteria as possible (Kamppinen and Walls 1999). However, inmultiple criteria evaluation, increasing the number of input criteria may decrease the degreeof suitability and the areas that can be classified as highly suitable (Basnet 2001).6.4.2 Reserve zonesThe multi-criteria decision analysis carried out using the OWA model is found to besuitable for identifying potential reserve areas and, thus, supporting the relevant decisionmaking considerably. In the past, different techniques for designing reserves have beenused (e.g., Diamond 1967; MacArthur and Wilson 1967; Higgs and Usher 1980; Higgs1981; Margules et al. 1982; Buckley 1982; Blouin and Connor, 1985; Usher 1986; Li et al.1999; Clemens et al. 1999; Heijnis et al. 1999; Akcakaya 2000; Scot and Sullivan 2000).Most of the recent reserve design methods were based the heuristic method, which has rulesfor including mandatory polygons, forcing adjacency, including desirable and excludingundesirable features (Bedward et al. 1992; Williams and ReVelle 1996; Heijnis et al. 1999;Clemens et al. 1999). These approaches are similar to Boolean evaluation methods in thatthe input criteria are not continuous map layers, but polygons with values of either 1 or 0.The OWA model is more interesting and relevant since the resulting map has continuousindex values and varying degrees of suitability (Jiang and Eastman 2000; Eastman 2001).As opposed to a single solution obtained either using intersection or union in the Booleanoperations, OWA provides different sets of solutions, which fall anywhere in between theintersection (AND, or minimum suitability) and union (OR, or maximum suitability). It is122