@article {908,
	title = {Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture},
	year = {2014},
	keywords = {conservation planning},
	doi = {10.7717/peerj.690/supp-1},
	url = {https://peerj.com/articles/690/$\#$additional-information},
	author = {Kreitler, J. and Stoms, D.M. and Davis, F.W.}
}
@article {742,
	title = {Comprehensive criteria for biodiversity evaluation in conservation planning},
	journal = {Biodiversity and Conservation},
	volume = {16},
	year = {2007},
	month = {2007},
	pages = {2715-2728},
	abstract = {In this paper we present the results of a multi-criteria decision analysis used to identify a comprehensive set of criteria for assigning biodiversity value to sites for conservation planning. For effective conservation management, biodiversity value needs to be a composite of biotic and abiotic factors. However, in the reserve design literature, conservation value is assigned with a limited set of metrics usually based on comprehensiveness, representativeness and persistence which may be insufficient at fully capturing biodiversity value. A group of conservation specialists in California, USA, used a multi-criteria decision making framework to elucidate and weight criteria for scoring biodiversity value at sites. A formal model for consensus and negotiation was applied to aggregate individuals{\textquoteright} criteria weights across all group members. The group identified ecological condition, followed by biotic composition as the most important contributors to site conservation value. Long- and short-term threats causing fragmentation and degradation are also important criteria to consider. Key criteria are identified for which further data collection would serve the greatest purpose in prioritizing sites and the role of prioritization criteria in the larger context of systematic conservation planning is discussed. With the recognition that biodiversity value plays an important role in conservation decisions, the criteria presented here represents a comprehensive suite of factors to consider when assigning biodiversity value to sites for conservation planning. These can serve as an encompassing list which other groups can customize for the purpose of biodiversity evaluation for alternative conservation planning contexts.},
	keywords = {AHP, Biodiversity value, conservation planning, Group decision making, MCDM, MCE, Multi-criteria decision making},
	url = {http://www.ingentaconnect.com/content/klu/bioc/2007/00000016/00000009/00009100DOI	10.1007/s10531-006-9100-3},
	author = {Regan, Helen M. and Davis, Frank W. and Andelman, Sandy J. and Widyanata, Astrid and Freese, Mariah}
}
@article {745,
	title = {Biodiversity conservation planning tools: Present status and challenges for the future},
	journal = {Annual Review of Environment and Resources},
	volume = {31},
	year = {2006},
	month = {2006},
	pages = {123-159},
	abstract = {Species extinctions and the deterioration of other biodiversity features worldwide have led to the advocacy of systematic conservation planning for many regions of the world. This process has encouraged the development of various software tools for conservation planning during the last twenty years. These tools implement algorithms designed to identify conservation area networks for the representation and persistence of biodiversity features. Budgetary, ethical, and socio-political constraints dictate that the prioritized sites represent biodiversity economically with minimum impact on human interests. Planning tools are typically used also to satisfy these criteria. This paper reviews both the concepts and technical choices that underlie the development of these tools. The former concepts include complementarity, persistence, irreplaceabilty, and various concepts of economy and efficiency. Planning problems can be formulated as mathematical programs and this paper also evaluates the suitability of different algorithms for their solution. Methods are assessed using the criteria of economy, efficiency, flexibility, transparency, genericity, and modularity. The paper also reviews some key research questions pertaining to the use of these software tools such as computational efficiency, the effectiveness of taxa and abiotic parameters as surrogates for biodiversity, and the problem of setting explicit targets of representation for biodiversity surrogates. Multiple-criteria decision analysis for conservation planning is also discussed. Finally, areas for future research are identified. These include the scheduling of conservation action over extended time periods and the incorporation of data about site vulnerability into place prioritization.},
	keywords = {bidiversity surrogates, conservation area networks, conservation planning, MCDM, MCE, reserve selection, surrogates},
	url = {http://arjournals.annualreviews.org/eprint/SEiSEyzQeURDDzshKdNj/full/10.1146/annurev.energy.31.042606.085844},
	author = {Sarkar, Sahotra and Pressey, Robert L. and Faith, Daniel P. and Margules, Christopher R. and Fuller, Trevon and Stoms, David M. and Moffett, Alexander and Wilson, Kerrie A. and Williams, Kristen J. and Williams, Paul H. and Andelman, Sandy}
}
@booklet {751,
	title = {The Endangered Species Act at Thirty: Conserving Biodiversity in Human-Dominated Landscapes},
	volume = {2},
	year = {2006},
	month = {2006},
	pages = {360},
	publisher = {Island Press},
	address = {Washington},
	keywords = {conservation planning, critical habitat, endangered species, habitat recovery plans, incentives, working landscapes},
	author = {Scott, J. Michael and Goble, Dale D. and Davis, Frank W.}
}
@booklet {684,
	title = {The Endangered Species Act at Thirty: Renewing the Conservation Promise},
	volume = {1},
	year = {2006},
	month = {2006},
	pages = {372},
	publisher = {Island Press},
	address = {Washington},
	keywords = {conservation planning, critical habitat, endangered species, habitat recovery plans, incentives, working landscapes},
	url = {http://www.bren.ucsb.edu/news/FirstVoumeofEndangeredSpeciesActatThirty.htm},
	author = {Goble, Dale D. and Scott, J. Michael and Davis, Frank W.}
}
@article {716,
	title = {Prioritizing farmland preservation cost-effectively for multiple objectives},
	journal = {Journal of Soil and Water Conservation},
	volume = {61},
	year = {2006},
	month = {2006},
	pages = {250-258},
	abstract = {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{\textquoteright}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.},
	keywords = {amenities, Bay Delta bioregion, California Legacy Project, conservation planning, cost-effectiveness, decision analysis, ecosystem services, farmland preservation, GIS, marginal value, public preferences, social welfare, urban growth boundary, urban growth management, utility},
	url = {<Go to ISI>://000242001800007},
	author = {Machado, E. A. and Stoms, D. M. and Davis, F. W. and Kreitler, J.}
}
@article {775,
	title = {Choosing surrogates for biodiversity conservation in complex planning environments},
	journal = {Journal of Conservation Planning},
	volume = {1},
	year = {2005},
	month = {2005},
	pages = {44-63},
	abstract = {The coarse filter/fine filter hypothesis suggests that by conserving high-quality examples of all ecological systems along with imperiled species and communities, we could protect the majority of native biodiversity. Given the cost of data collection, conservation planners might wonder how large this set of elements must be. We conducted an analysis of the sensitivity of selecting a set of reserves to the choice of surrogates in Napa County, California, USA. The study evaluated the extent to which conservation goals for the coarse/fine-filter elements were met by surrogates and whether the same general locations were being selected. Napa County represents a data-rich setting, whereas the test surrogates portrayed a range of circumstances where less data are available. A worst (data-poor) case, based only on landscape condition with no biological data, was tested to identify the value of improved information. Our results suggest that in complex planning environments, there are no simple shortcuts in collecting data. None of the surrogate sets was particularly effective at meeting all the goals for the full set of baseline elements. There was also relatively low spatial congruence between the test solutions and the baseline. However, we did find that all combinations of surrogates provided some degree of protection in notional reserves, suggesting that in less complex planning problems, simpler surrogates can serve a useful function. Studies like this will help planners gauge how much effort it is prudent to spend in compiling spatial data relative to the risks and irreplaceability to native biodiversity.},
	keywords = {coarse-filter, conservation planning, fine-filter, Napa County, reserve selection, sensitivity analysis, Sites, surrogates},
	url = {http://www.journalconsplanning.org/2005/volume1/issue1/stoms/manuscript.pdf},
	author = {Stoms, D. M. and Comer, P. J. and Crist, P. J. and Grossman, D. H.}
}
@article {798,
	title = {Defining a marginal value function for setting conservation priorities in NatureServe Vista},
	year = {2005},
	month = {2005},
	pages = {29},
	institution = {University of California Santa Barbara},
	abstract = {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{\textquoteright}s concepts of "cost" and "effectiveness." Depending on the user{\textquoteright}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{\textquoteright}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{\textquoteright}s management is compatible with that element{\textquoteright}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{\textquoteright}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.},
	keywords = {conservation planning, cost-effectiveness, decision support system, marginal conservation value, utility, VISTA},
	author = {Stoms, David M. and Davis, Frank W.}
}
@inbook {633,
	title = {A framework for setting land conservation priorities in the Sierra Nevada},
	booktitle = {Proceedings of the Sierra Nevada Science Symposium},
	volume = {General Technical Report PSW-GTR-193},
	year = {2004},
	note = {presented at Sierra Nevada Science Symposium 2002 October 7-10; Kings Beach, CA.},
	month = {2004},
	pages = {195-206},
	publisher = {Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture},
	organization = {Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture},
	address = {Albany, CA},
	abstract = {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{\textquoteright}s lands and natural resources." Here we provide a brief overview of a framework that we developed 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 general areas, species and communities for more focused analysis and collaborative planning. Site prioritization depends on the resources the site contains, the threat to those resources, and the conservation cost of mitigating that threat. We illustrate our framework using relatively coarse, readily available data for the Sierra Nevada Bioregion. Preliminary results suggest that many of the private lands of the region contribute important conservation value for terrestrial biodiversity. However, inter-site disparities in degree of threat and in conservation costs make the conservation "bang for buck" especially high in a smaller number of sites.},
	keywords = {California Legacy Project, conservation planning, decision support system, GIS, marginal value, prioritization},
	url = {http://www.fs.fed.us/psw/publications/documents/psw_gtr193/psw_gtr193_5_4_Davis_and_others.pdf},
	author = {Davis, F. W. and Costello, C. J. and Stoms, D. M. and Machado, E. A. and Metz, J.},
	editor = {Murphy, Dennis D. and Stine, Peter A.}
}
@article {769,
	title = {Linking GIS and reserve selection algorithms: Towards a geospatial data model},
	year = {2003},
	month = {2003},
	pages = {37},
	institution = {Biogeography Lab, Bren School of Environmental Science and Management, University of California Santa Barbara},
	abstract = {Most reserve selection algorithms used in research or conservation practice are only loosely coupled with geographic information system technology. This paper argues that formalizing a core geospatial data model would benefit algorithm developers, researchers, and practitioners through standardized data management and ease of database development with any reserve selection algorithm.},
	keywords = {conservation planning, data model, object-oriented, reserve selection},
	url = {http://www.biogeog.ucsb.edu/pubs/Technical\%20Reports/Reserve_Selection_Data_Model.pdf},
	author = {Stoms, D. M.}
}
@article {715,
	title = {A systematic framework for prioritizing farmland preservation},
	year = {2003},
	month = {2003},
	pages = {52},
	institution = {National Center for Ecological Analysis and Synthesis},
	address = {Santa Barbara},
	abstract = {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{\textquoteright}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.},
	keywords = {Bay Delta bioregion, California Legacy Project, conservation planning, cost-effectiveness, farmland preservation, GIS, marginal value},
	url = {http://www.nceas.ucsb.edu/nceas-web/projects/4040/Farmland_framework_report.pdf},
	author = {Machado, E. A. and Stoms, D. M. and Davis, F. W.}
}
