@booklet {396,
	title = {A framework for setting land conservation priorities using multi-criteria scoring and an optimal fund allocation strategy},
	year = {2003},
	publisher = {National Center for Ecological Analysis and Synthesis},
	type = {Report to the Resources Agency of California},
	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 Spring 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 framework described in this report 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 general areas, species and communities 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. At the highest level we distinguish three categories of conservation goals: Resource Production Capacity, Natural Capital, and Public Open Space. Under Natural Capital we distinguish terrestrial biodiversity from wetland and aquatic biodiversity. This report focuses on terrestrial biodiversity. The framework applies GIS technology to map 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 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 resource value remaining at the end of the planning period. We present a measure of ecological condition based on land use, land cover, roads, housing density and forest structure. The condition index is mapped for 2000 A.D. and 2040 A.D. (based on projected patterns of housing development) and the difference between the two is applied as a measure of threat to biodiversity. We then present formal measures for five different values that places can have for conserving terrestrial biodiversity: 1) hotspots of rare threatened and endangered species, 2) areas supporting vulnerable habitat types, 3) unique landscapes, 4) wildlands for area dependent species, and 5) areas to expand the size of existing reserves. We apply the framework to prioritize new conservation investments on private lands in the Sierra Bioregion. Our purpose is to demonstrate the end-to-end use of the framework and attention should be focused on the process, not the actual products. We first use existing, readily available data to map resource values and threats to produce maps of marginal conservation value without consideration of site cost. Spatial patterns in site value differ considerably among the five conservation criteria. We then use a crude estimate of land prices and allocate a hypothetical budget of $44 million to 50 sites scattered across the region. The framework can also be applied to other conservation concerns such as aquatic biodiversity, production lands, public open space, cultural resources and recreational opportunities. In a separate report we demonstrate its application for cropland conservation in the Bay Delta Bioregion. Our initial experiences in applying the framework to terrestrial biodiversity and cropland are very encouraging, but testing and refinement of the indices and value functions models are still needed and are currently underway.},
	keywords = {marginal value conservation planning cost-effectiveness GIS Sierra Nevada California Legacy Project},
	author = {Davis, F. W. and Stoms, D. M. and Costello, C. J. and Machado, E. A. and Metz, J. and Gerrard, R. and Andelman, S. and Regan, H. and Church, R.}
}
@article {347,
	title = {Understanding the tradeoffs between site quality and species presence in reserve site selection},
	journal = {Forest Science},
	volume = {46},
	number = {2},
	year = {2000},
	pages = {157-167},
	abstract = {A number of optimization models have been developed for natural reserve design and reserve site selection. The most common approach seeks to maximize the number of individual species that occur among chosen sites. A number of heuristics and mathematical programming algorithms have been applied to solve this problem. While attaining maximum overall species representation is important, the relative quality of representation (which could be affected by site attributes such as habitat value, adequate population size, presence of critical resources, existence (or lack thereof) of exotic competitors, etc.) has been absent from most representation models. Yet issues of site quality should be considered in order to have any assurance of long-term species persistence in a reserve system. Here we present a multiobjective optimization model that addresses the issue of balancing species presence with habitat quality. One type of interesting alternative yields more high quality representation at the price of some reduction in overall representation. We present an application using a large dataset from California Gap Analysis to demonstrate this and other tradeoffs. Optimal solutions are attained using commercial integer programming software with reasonable computational effort.},
	keywords = {weighted-benefits maximal covering location problem model},
	author = {Church, R. and Gerrard, R. and Hollander, A. and Stoms, D.}
}
