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■ Abstract Species extinctions and the deterioration of other biodiversity features worldwide have led to the adoption of systematic conservation planning in many regions of the world. As a consequence, various software tools for conservation planning have been developed over the past twenty years. These tools implement algorithms designed to identify conservation area networks for the representation and persistence of biodiversity features. Budgetary, ethical, and other sociopolitical constraints dictate that the prioritized sites represent biodiversity with minimum impact on human interests. Planning tools are typically also used to satisfy these criteria. This chapter reviews both the concepts and technical choices that underlie the development of these tools. Conservation planning problems can be formulated as optimization problems, and we evaluate the suitability of different algorithms for their solution. Finally, we also review some key issues associated with the use of these tools, such as computational efficiency, the effectiveness of taxa and abiotic parameters at choosing surrogates for biodiversity, the process of setting explicit targets of representation for biodiversity surrogates, and

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Most models that examine the effects of habitat conversion on species extinctions assume that habitat conversion occurs at random. This assumption allows predictions about extinction rates based on the species-area relationship. We show that the spatially aggregated nature of habitat conversion introduces a significant bias that may lead species-loss rates to exceed those predicted by species-area curves. Correlations between human activity and major compositional gradients, or species richness, also alter predicted species extinction rates. We illustrate the consequences of nonrandom patterns of habitat conversion by using a data set that combines the distribution of native vascular plants with human activity patterns in California.habitat-conversion ͉ California ͉ species-area ͉ conservation ͉ biodiversity H umans have caused numerous species extinctions (1-9) primarily through the conversion of natural habitat into land dominated by agriculture and other anthropogenic activities (3,(10)(11)(12)(13)(14). Despite attempts to conserve global biological diversity, habitat conversion rates are accelerating, particularly in tropical countries (14). Policies for the preservation of global biodiversity rely on accurate predictions of the effects of habitat conversion on species distributions (15-17).Attempts to estimate the relationship between habitat loss and extinction rates have focused on species-area relationships (6,(18)(19)(20)(21)(22) and metapopulation models (23)(24)(25)(26)(27)(28). Although these methods differ in their predictions about the types of species that are most at risk and the delay between conversion of habitat and extinction (i.e., the ''extinction debt'') (29), both approaches assume random habitat loss (26,29). This assumption ignores two related biases. First, the distribution of species is influenced by underlying habitat characteristics such as rainfall, soil quality, and elevation. Secondly, these characteristics influence the rate at which areas are converted to human-dominated land uses. Specifically, humans have clear habitat preferences for coastal or other low-lying lands with adequate supplies of water (30, 31). The rate of habitat conversion is significantly faster in these areas than in areas less suitable for agriculture (26). Consequently, habitat-loss rates may be correlated with gradients of species composition and diversity (Fig. 1).Furthermore, extinction rates will be sensitive to the specific distribution of species across the landscape as well as the spatial configuration of habitat conversion (32-34). A correlation between habitat-loss rate and species richness may cause extinction rates to deviate from the predictions of the species-area relationship. If species-rich areas are lost first, we would expect that initial species extinction rates to exceed those predicted under the assumption of random habitat loss.The systematic nature of anthropogenic habitat conversion also changes the relationship between species extinctions and habitat loss, because species turnover ...

Invasive species are one of the fastest growing conservation problems. These species homogenize the world's flora and fauna, threaten rare and endemic species, and impose large economic costs. Here, we examine the distribution of 834 of the more than 1000 exotic plant taxa that have become established in California, USA. Total species richness increases with net primary productivity; however, the exotic flora is richest in low-lying coastal sites that harbor large numbers of imperiled species, while native diversity is highest in areas with high mean elevation. Weedy and invasive exotics are more tightly linked to the distribution of imperiled species than the overall pool of exotic species. Structural equation modeling suggests that while human activities, such as urbanization and agriculture, facilitate the initial invasion by exotic plants, exotics spread ahead of the front of human development into areas with high numbers of threatened native plants. The range sizes of exotic taxa are an order of magnitude smaller than for comparable native taxa. The current small range size of exotic species implies that California has a significant "invasion debt" that will be paid as exotic plants expand their range and spread throughout the state.

Ecosystem-based management is logistically and politically challenging because ecosystems are inherently complex and management decisions affect a multitude of groups. Coastal ecosystems, which lie at the interface between marine and terrestrial ecosystems and provide an array of ecosystem services to different groups, aptly illustrate these challenges. Successful ecosystem-based management of coastal ecosystems requires incorporating scientific information and the knowledge and views of interested parties into the decision-making process. Estimating the provision of ecosystem services under alternative management schemes offers a systematic way to incorporate biogeophysical and socioeconomic information and the views of individuals and groups in the policy and management process. Employing ecosystem services as a common language to improve the process of ecosystem-based management presents both benefits and difficulties. Benefits include a transparent method for assessing trade-offs associated with management alternatives, a common set of facts and common currency on which to base negotiations, and improved communication among groups with competing interests or differing worldviews. Yet challenges to this approach remain, including predicting how human interventions will affect ecosystems, how such changes will affect the provision of ecosystem services, and how changes in service provision will affect the welfare of different groups in society. In a case study from Puget Sound, Washington, we illustrate the potential of applying ecosystem services as a common language for ecosystem-based management.

Purpose Geospatial details about land use are necessary to assess its potential impacts on biodiversity. Geographic information systems (GIS) are adept at modeling land use in a spatially explicit manner, while life cycle assessment (LCA) does not conventionally utilize geospatial information. This study presents a proof-of-concept approach for coupling GIS and LCA for biodiversity assessments of land use and applies it to a case study of ethanol production from agricultural crops in California. Materials and methods GIS modeling was used to generate crop production scenarios for corn and sugar beets that met a range of ethanol production targets. The selected study area was a four-county region in the southern San Joaquin Valley of California, USA. The resulting land use maps were translated into maps of habitat types. From these maps, vectors were created that contained the total areas for each habitat type in the study region. These habitat compositions are treated as elementary input flows and used to calculate different biodiversity impact indicators in a second paper (Geyer et al., submitted). Results and discussion Ten ethanol production scenarios were developed with GIS modeling. Current land use is added as baseline scenario. The parcels selected for corn and sugar beet production were generally in different locations. Moreover, corn and sugar beets are classified as different habitat types. Consequently, the scenarios differed in both the habitat types converted and in the habitat types expanded. Importantly, land use increased nonlinearly with increasing ethanol production targets. The GIS modeling for this study used spatial data that are commonly available in most developed countries and only required functions that are provided in virtually any commercial or opensource GIS software package. Conclusions This study has demonstrated that GIS-based inventory modeling of land use allows important refinements in LCA theory and practice. Using GIS, land use can be modeled as a geospatial and nonlinear function of output. For each spatially explicit process, land use can be expressed within the conventional structure of LCA methodology as a set of elementary input flows of habitat types.

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