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Home Practical Application of Biodiversity Surrogates and Percentage Targets for Conservation in Papua New GuineaThe new approach to targets We propose a tighter linkage between surrogates, targets, and costs in which the required degree of biodiversity representation (and persistence; see below) is not an a priori determination (such as 10%), but only emerges after an initial priority-areas analysis that serves a baseline for actual planning. Our approach assumes that biodiversity over a set of areas is described as a continuous pattern, such as a numerical hierarchical classification, or an ordination. It is this structure, inherent in numerical classifications and ordinations, that can be used to set targets. In the case of a hierarchical classification, the idea is to find the level in the hierarchy - the number of clusters - that can be protected in a total of, say, 10% of a region, country or biome, pretending there are no people, no opportunity costs and no land use history. Once this level is found in the baseline analysis, the target then becomes this same level of representation and protection in a new set of places that takes into account opportunity costs and land use history (Figure 1; see also Faith 1997a,b). For PNG, these constraints include existing protected areas (Figure 2). The resulting set of places that reaches the target form an initial set of biodiversity priority areas. They are the areas to which scarce conservation resources should be directed. Some may become formal protected areas, though others may simply be managed in an appropriate way. Two initial tasks for implementing this approach, described below for PNG, are to decide on the map units and the data layers that are to provide biodiversity surrogate information, summarized as a continuous pattern. Any pixel or grid cell within a larger map unit or polygon can then be identified with a cluster at any level of a hierarchy (or, for a pixel in ordination space, identified with sets of implied attributes; see Faith and Walker 1996a). In practice, we have used repeated analysis trials with finer scales of clustering to explore the hierarchical continuum. In each analysis, we used TARGET software (Walker and Faith 1998; see also Faith and Walker 1996e, 1997 and Faith et al. 2001a,b) to select areas (polygons) in order to represent all the clusters defined at a given level. The input consisted of a listing of all polygons and, for each polygon, a recording of all the clusters contained in it. Because the purpose of the baseline analysis is to determine how much biodiversity can be represented and protected in 10% of the country, attribute occurrences and /or areas that are inadequate (e.g., too small) according to persistence/viability models can be excluded. A variety of persistence/viability criteria might be used. The linking of targets to biodiversity persistence need not be based on species-area curves; representativeness can be linked to persistence models from a variety of sources, and incorporated in the usual calculus of complementarity using probability values (Faith and Walker 1996c, 1997; Faith et al. 2001b). TARGET can search for sets of areas that represent biodiversity while minimising cost (Faith et al. 1994). The cost file for TARGET contains, for purposes of the baseline analyses, the area of each polygon. The use of polygon area as a cost enables us to represent any nominated number of clusters in the minimum total area possible. To search for the minimum-area solution, any single run of TARGET then proceeds by nominating a weight for the costs. The software then iteratively adds and deletes areas from a "select list", ensuring along the way that the complementary value for a selected area exceeds its weighted cost. No further areas are selected when no further area has a high enough complementarity to exceed its weighted cost. If too high a weight is nominated, the analysis will stop without representing all clusters. Over successive runs, the weight can be reduced, optionally starting with the results of the previous run, to ensure all clusters are eventually represented and that costs are minimized. The baseline analyses used to determine how much biodiversity can be represented in 10% of the country may requires adjustment of the number of clusters derived from the hierarchy. For example, a new set of analyses is carried out with a larger number of clusters from the hierarchy if the initial analyses represented all clusters, but did not select enough areas to total approximately 10% of the country in total area. The final baseline analysis will be the one in which the choice of weighting and cluster-level is such that 10% of the country was selected. This indicates approximately the maximum amount of biodiversity represented in that total area (the hollow circle along the dashed line in Figure 1). We then record that list of clusters/attributes and this provides our biodiversity target for all later analyses. In the next section, the measures of biodiversity for carrying out this analysis in PNG are described.
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