Abstract. We study the complexity of combinatorial problems that consist of competing infeasibility and optimization components. In particular, we investigate the complexity of the connection subgraph problem, which occurs, e.g., in resource environment economics and social networks. We present results on its worst-case hardness and approximability. We then provide a typical-case analysis by means of a detailed computational study. First, we identify an easy-hard-easy pattern, coinciding with the feasibility phase transition of the problem. Second, our experimental results reveal an interesting interplay between feasibility and optimization. They surprisingly show that proving optimality of the solution of the feasible instances can be substantially easier than proving infeasibility of the infeasible instances in a computationally hard region of the problem space. We also observe an intriguing easy-hard-easy profile for the optimization component itself. 1

This paper describes the design and construction of a prototype spatial decision support system (SDSS) for an interactive evaluation of integrated landscape restoration planning using spatial information technology. Landscape planning involves spatially explicit decisions about the types of landuses allowable, and the extent and location of these landuses. This decision-making needs to be supported by accurate and detailed information about the spatial distribution of numerous parameters affecting the distribution of landuse. The SDSS that we present in this paper comprises a geographic information system (GIS) tightly coupled with an analytical optimisation module by means of an interactive interface. The GIS is used for storage, manipulation and visualisation of spatial data, and for assessing the results of the analytical module computing optimal spatial pattern. Several user-selectable parameters allow consideration of management objectives related to planning for landscape restoration.

sustainable development.

In California, hundreds of different public and private organizations are involved in prioritizing and acquiring new conservation lands (California Environmental Dialogue 1999, California Continuing Resources Investment Strategy Project 2001). Although the State of California owns less than 3 percent of the land (Davis and Stoms 1998), it plays a significant role in the conservation of biodiversity, public open space, and commodity production. State government funding for land acquisitions and conservation easements comes from a variety of sources, including special funds, park-related bonds, and water-related bonds. Although bonds provide considerable public funds for conservation, they fall short of what most agencies and conservation groups believe is required to meet even short-term demands for farmland, open space, and habitat conservation (California Environmental Dialogue 1999). Thus, competition for these public funds is intense, and State funding agencies must make decisions in what are often acrimonious public forums. In a 1996 analysis of State agency land conservation activities, the California Legislative Analyst’s Office found that the State was unable to set clear conservation priorities because it lacked a comprehensive and cohesive statewide land conservation plan, suffered from poor

dtork@berkeley.edu. This research was done while working at AT&T Labs−Research.

Biodiversity conservation “area-selection ” strategies include not only trade-offs among society’s needs in land-use allocation, but also allocation of economic instruments such as incentives, levies, and biodiversity credits. For these applications, the key property of an area is its “complementarity”—the context-dependent, marginal gain in biodiversity provided by the area. Given that there has been little implementation of whole-sets of areas generated by the popular computer-based selection methods, we suggest that analogous “policy-based algorithms ” would be a more effective real-world application of complementarity. Areas would be “selected ” for conservation over time as a consequence of policies in which dynamic complementarity values influence application of economic instruments. These integrated biodiversity/economic strategies can use an extended form of complementarity reflecting marginal changes in regional probability of persistence of biodiversity. While probabilistic measures of biodiversity viability have been explored in area-selection for some time, it remains difficult to make viability statements about “all of biodiversity. ” New approaches that use biodiversity surrogate information for “biodiversity viability analysis ” (BVA) can take advantage of a general quantitative biodiversity framework in which pattern-based relationships among areas allow predictions at the species level. A standard assumption of “unimodal ” species responses to environmental gradients yields an expected distribution of species in an ordination pattern, and allows sampling of inferred species. Based on environmental correlates, inferred species can be mapped in geographic space, forming distribution fragments. This information, when linked to species persistence models, may allow ongoing calculation of areas ’ complementarity values. An example illustrates application of these ordination

Perhans, K. 2008. Cost-efficient conservation strategies for boreal forest biodiversity.

Does conservation planning matter in a dynamic

Modeling the compatibility of biological and economic objectives on a forested landscape

This dissertation contributes to the growing literature on the allocation of land for conservation in three fronts. First, I create a dynamic reserve design framework that incorporates location based amenity price effects and uncertainty of development and I study the impact of amenity price effects on site selection decisions. I find that the dynamic model with price feedback effects selects sites at a lower per-site cost. The policy implication of this finding is that conservation programs should avoid purchasing land in the same neighborhood over multiple time periods. Second, I study the public’s willingness to pay (WTP) for restoring ecosystems using a choice experiment survey and I analyze the structure of preferences over ecosystem attributes. The results reveal several interesting patterns of consumer preferences and choice. First, I find that the presence of nearby existing grasslands actually increases a respondent’s WTP for restoring a new grassland; this result is counter to what would be expected from neoclassical economics and can possibly be explained by endogenous preferences. Second, I find that respondents treat the conservation success measures as substitutes for each other. This latter