|Title||Defining a marginal value function for setting conservation priorities in NatureServe Vista|
|Year of Publication||2005|
|Authors||Stoms, DM, Davis, FW|
|Keywords||marginal conservation value VISTA decision support system conservation planning cost-effectiveness utility|
This function measures cost-effectiveness for conservation planning as a way to prioritize of planning units. How it is calculated in Vista depends on the user's concepts of "cost" and "effectiveness." Depending on the user's choices about several factors, this function can create a useful array of conservation measures. Planners generally consider four different types of cost values. The simplest is to ignore costs (essentially assume that costs are equal) or to only consider costs at a later step in the planning/implementation process. In this case, the measure focuses strictly on the biological values of a site. Slightly more sophisticated is to adjust the biological benefits by the size of the site as a proxy for actual costs (assume equal cost per unit area). Some planners further refine this measure with factors that affect the management suitability of the site, such as how disturbed the site is or whether it is publicly or privately owned. In other words, an index that relates management costs to suitability. And last, planners may need to consider the actual (or estimated) costs to conserve a site in order to set priorities for the most cost-effective sites. How Vista measures effectiveness is actually based on three factors, each with several options to meet the user's needs. The first factor answers the question: effective for what? There are many different strategies or objectives that may be important for planning. Vista currently supports three of these: fine-filter hotspots, coarse-filter representation, and making small reserves large enough to be viable. Users can select which of these are important by choosing a set of weights. The second factor looks at the gain or benefit of conservation. The simplest option merely sums the biodiversity that is present in a site. This "richness" value may be modified by the viability/integrity for each element and/or the weight assigned to the elements so that sites receive highest scores if the contain high quality occurrences of many highly imperiled species and ecological systems. The second option only counts the element values for a site if the site's management is compatible with that element's persistence. That is, if current management is incompatible, the element cannot effectively be conserved at that site. Both these options can also be weighted by protection status, so that only unprotected sites receive conservation value. The third option considers the net gain that conservation would provide (either in loss prevented in the case of protection or of improvement of viability in the case of restoration practices). For this, the user needs a scenario of what would happen to the site without conservation. The final factor calculates the social value or utility of adding more conservation as a function of how rare an element is and how well it is already protected. The simplest option is to assume that the utility is based solely on the presence of an element and does not change in relation to management decisions. The second option is similar, except that it assumes there would be no utility once the conservation goal for the element was reached. The final option uses an economics perspective of diminishing returns, so that more emphasis is given to elements that are rare with the least compatible management in setting priorities. The best choices for these options will depend on what task you want to perform. Here we describe three common tasks and the options that would be chosen to perform them. Suppose you want to identify biologically important sites for the set of elements you have identified. This would be a map of element richness, perhaps weighted by elements and by their viability in each site. Vista calls this a Conservation Value Summary. Therefore, you would choose the simplest options for costs (equal or none), for biological objectives (but not expansion of reserves), for presence or amount of each element (without consideration of protection or compatible management), and for constant utility (independent of goals). Another common task is to select sites to achieve conservation goals efficiently, based on the complementarity of the site to the biodiversity already protected. In this case, you might pick whichever measure of cost you want to minimize. You would want to choose either the amount of each element present unless the site is already protected. In that case, the site could not contribute further to the reserve system. You would also choose the goal-limited utility option because you don't want to credit a site for elements that have already met their goals. A map produced with these options would show which sites would contribute most effectively towards the conservation goals. Another important task you may want to perform is the prioritize sites for conservation by their cost-effectiveness in order to maximize the biodiversity that remains in the future under a land use scenario. Here, estimated costs of conservation are critical. You would also want to consider the loss of biodiversity that conservation would achieve by considering the change in compatibility between a conservation practice and the expected practices in a land use scenario. That is, a site would get no credit if the future use would be compatible anyway or if the conservation practice would not be compatible. Finally, you might want to select the diminishing returns form of utility so that the most imperiled elements get protected first. Of course, these three tasks represent some benchmarks along a continuum. One can select different combinations of options to achieve intermediate products that suit your task and database more effectively.