TY - JOUR T1 - Prioritizing farmland preservation cost-effectively for multiple objectives JF - Journal of Soil and Water Conservation Y1 - 2006 A1 - Machado, E. A. A1 - Stoms, D. M. A1 - Davis, F. W. A1 - Kreitler, J. KW - amenities KW - Bay Delta bioregion KW - California Legacy Project KW - conservation planning KW - cost-effectiveness KW - decision analysis KW - ecosystem services KW - farmland preservation KW - GIS KW - marginal value KW - public preferences KW - social welfare KW - urban growth boundary KW - urban growth management KW - utility AB - American society derives many benefits from farmland and is often willing to pay to preserve it from urbanization. We present an innovative framework to support farmland preservation programs in prioritizing conservation investments. The framework considers the full range of social benefits of farmland and improves the application of decision analysis methods to the process. Key factors for ranking farms are: 1) social objectives and priorities 2) how much farmland value is expected to be lost to development if not preserved, 3) how much farmland value is already secured in the agricultural region; and 4) how much it will cost to secure the farm's benefits. The framework can be applied strategically over an entire region or to rank a set of applications from landowners. We demonstrate our framework using three criteria in the Bay Area/Delta bioregion of California, USA. VL - 61 UR - ://000242001800007 ER - TY - RPRT T1 - Defining a marginal value function for setting conservation priorities in NatureServe Vista Y1 - 2005 A1 - Stoms, David M. A1 - Davis, Frank W. KW - conservation planning KW - cost-effectiveness KW - decision support system KW - marginal conservation value KW - utility KW - VISTA AB - 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. PB - University of California Santa Barbara ER - TY - RPRT T1 - A systematic framework for prioritizing farmland preservation Y1 - 2003 A1 - Machado, E. A. A1 - Stoms, D. M. A1 - Davis, F. W. KW - Bay Delta bioregion KW - California Legacy Project KW - conservation planning KW - cost-effectiveness KW - farmland preservation KW - GIS KW - marginal value AB - The California Legacy Project (CLP) mission is "to enable the state and its partners in conservation to develop and implement a strategic and inclusive approach to conserving and restoring California's lands and natural resources." In 2001 The Resources Agency of California contracted with the National Center for Ecological Analysis and Synthesis at UC Santa Barbara to convene a working group to help bring systematic conservation planning theory and methods to bear on the design and implementation of CLP. The conservation planning framework for farmland described in this report for is one of the products from that working group. The framework is intended to serve the dual purpose of helping decision makers to evaluate current opportunities (e.g., current proposal applications for State conservation funds) and to help planners develop longer term conservation strategies that highlight areas for more focused analysis and collaborative planning. We do not present a plan or "blueprint" for future conservation activities. Instead, we offer an analytical, data-driven planning process that could be applied to ongoing conservation assessments and evaluations by State conservation planning staff and collaborating organizations over the State or regions of the State. We organize the planning framework based on a hierarchy of conservation goals and objectives, each of which is further elaborated in terms of specific objectives, criteria, and sources of evidence. For farmland preservation, we summarize these goals as retaining farmlands: 1) with the greatest sustained production capacity, 2) that provide high amenity values (e.g., habitat, open space, floodplain management, and scenic values), and 3) whose location reduces the risk of urban sprawl. The framework applies GIS technology to map farmland conservation value and investment priorities based on available spatial data, derived indices and simple algebraic functions. A planning region is divided into sites, and each site is scored in terms of its marginal conservation value, that is, the incremental value added to the current system of conservation lands by making the next conservation investment in that site. Site prioritization depends on the farmland resources the site contains, the threat to those resources, and the conservation cost of mitigating that threat. The strategic objective is to allocate conservation funds among a set of candidate sites such that there is the greatest possible farmland value remaining at the end of the planning period. We demonstrate the framework for preservation of farmlands in the Bay Area/Delta Bioregion. Because the criteria for measuring objectives 2 and 3 require spatial and nonspatial data that are not readily available statewide or even for a bioregion, we only develop and demonstrate the framework for objective 1. Existing data are used to map resource values and threats to arrive at maps of marginal conservation value without consideration of site cost. We use a crude estimate of the cost of conservation easements to demonstrate how the framework could then be used to prioritize conservation investments subject to a fixed budget. PB - National Center for Ecological Analysis and Synthesis CY - Santa Barbara UR - http://www.nceas.ucsb.edu/nceas-web/projects/4040/Farmland_framework_report.pdf ER -