<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author><author><style face="normal" font="default" size="100%">Jenner, Mark W.</style></author><author><style face="normal" font="default" size="100%">Nogeire, Theresa M.</style></author><author><style face="normal" font="default" size="100%">Kaffka, Stephen R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling wildlife and other trade-offs with biofuel crop production</style></title><secondary-title><style face="normal" font="default" size="100%">GCB Bioenergy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">agroecosystems</style></keyword><keyword><style  face="normal" font="default" size="100%">biofuels</style></keyword><keyword><style  face="normal" font="default" size="100%">biomass feedstock</style></keyword><keyword><style  face="normal" font="default" size="100%">California Wildlife Habitat Relationships system</style></keyword><keyword><style  face="normal" font="default" size="100%">geographic information systems</style></keyword><keyword><style  face="normal" font="default" size="100%">habitat suitability</style></keyword><keyword><style  face="normal" font="default" size="100%">Marxan</style></keyword><keyword><style  face="normal" font="default" size="100%">renewable energy</style></keyword><keyword><style  face="normal" font="default" size="100%">trade-offs</style></keyword><keyword><style  face="normal" font="default" size="100%">water demand</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1111/j.1757-1707.2011.01130.x</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">330-341</style></pages><isbn><style face="normal" font="default" size="100%">1757-1707</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Biofuels from agricultural sources are an important part of California&#039;s strategy to reduce greenhouse gas emissions and dependence on foreign oil. Land conversion for agricultural and urban uses has already imperiled many animal species in the state. This study investigated the potential impacts on wildlife of shifts in agricultural activity to increase biomass production for transportation fuels. We applied knowledge of the suitability of California&#039;s agricultural landscapes for wildlife species to evaluate wildlife effects associated with plausible scenarios of expanded production of three potential biofuel crops (sugar beets, bermudagrass, and canola). We also generated alternative, spatially explicit scenarios that minimized loss of habitat for the same level of biofuel production. We explored trade-offs to compare the marginal changes per unit of energy for transportation costs, wildlife, land and water-use, and total energy produced, and found that all five factors were influenced by crop choice. Sugar beet scenarios require the least land area: 3.5 times less land per liter of gasoline equivalent than bermudagrass and five times less than canola. Canola scenarios had the largest impacts on wildlife but the greatest reduction in water use. Bermudagrass scenarios resulted in a slight overall improvement for wildlife over the current situation. Relatively minor redistribution of lands converted to biofuel crops could produce the same energy yield with much less impact on wildlife and very small increases in transportation costs. This framework provides a means to systematically evaluate potential wildlife impacts of alternative production scenarios and could be a useful complement to other frameworks that assess impacts on ecosystem services and greenhouse gas emissions.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Nogeire, Theresa M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Biofuels and Biodiversity in California: A Framework for Conducting a Trade‐Off Analysis</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">biofuels</style></keyword><keyword><style  face="normal" font="default" size="100%">CWHR</style></keyword><keyword><style  face="normal" font="default" size="100%">energy</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.energy.ca.gov/2013publications/CEC-500-2013-032/CEC-500-2013-032.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">California Energy Commission</style></publisher><pub-location><style face="normal" font="default" size="100%">Sacramento, California</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Contract Report</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sarkar, Sahotra</style></author><author><style face="normal" font="default" size="100%">Pressey, Robert L.</style></author><author><style face="normal" font="default" size="100%">Faith, Daniel P.</style></author><author><style face="normal" font="default" size="100%">Margules, Christopher R.</style></author><author><style face="normal" font="default" size="100%">Fuller, Trevon</style></author><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Moffett, Alexander</style></author><author><style face="normal" font="default" size="100%">Wilson, Kerrie A.</style></author><author><style face="normal" font="default" size="100%">Williams, Kristen J.</style></author><author><style face="normal" font="default" size="100%">Williams, Paul H.</style></author><author><style face="normal" font="default" size="100%">Andelman, Sandy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Biodiversity conservation planning tools: Present status and challenges for the future</style></title><secondary-title><style face="normal" font="default" size="100%">Annual Review of Environment and Resources</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bidiversity surrogates</style></keyword><keyword><style  face="normal" font="default" size="100%">conservation area networks</style></keyword><keyword><style  face="normal" font="default" size="100%">conservation planning</style></keyword><keyword><style  face="normal" font="default" size="100%">MCDM</style></keyword><keyword><style  face="normal" font="default" size="100%">MCE</style></keyword><keyword><style  face="normal" font="default" size="100%">reserve selection</style></keyword><keyword><style  face="normal" font="default" size="100%">surrogates</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://arjournals.annualreviews.org/eprint/SEiSEyzQeURDDzshKdNj/full/10.1146/annurev.energy.31.042606.085844</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">123-159</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial Analysis for a Potential UCLA Tejon Reserve: Notes of the Tejon Reserve Working Group</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of California Santa Barbara</style></publisher><pages><style face="normal" font="default" size="100%">40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial Analysis for a Potential UCLA Tejon Reserve: Notes of the Tejon Reserve Working Group</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">April 2006</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of California Santa Barbara</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Final Report to the UCLA Tejon Reserve Working Group</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Defining a marginal value function for setting conservation priorities in NatureServe Vista</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">marginal conservation value VISTA decision support system conservation planning cost-effectiveness utility</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March 2005</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of California Santa Barbara</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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&#039;s concepts of &quot;cost&quot; and &quot;effectiveness.&quot; Depending on the user&#039;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&#039;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 &quot;richness&quot; 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&#039;s management is compatible with that element&#039;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&#039;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.</style></abstract><work-type><style face="normal" font="default" size="100%">Final Report to NatureServe</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Defining a marginal value function for setting conservation priorities in NatureServe Vista</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">conservation planning</style></keyword><keyword><style  face="normal" font="default" size="100%">cost-effectiveness</style></keyword><keyword><style  face="normal" font="default" size="100%">decision support system</style></keyword><keyword><style  face="normal" font="default" size="100%">marginal conservation value</style></keyword><keyword><style  face="normal" font="default" size="100%">utility</style></keyword><keyword><style  face="normal" font="default" size="100%">VISTA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">University of California Santa Barbara</style></publisher><pages><style face="normal" font="default" size="100%">29</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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&#039;s concepts of &quot;cost&quot; and &quot;effectiveness.&quot; Depending on the user&#039;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&#039;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 &quot;richness&quot; 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&#039;s management is compatible with that element&#039;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&#039;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.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author><author><style face="normal" font="default" size="100%">Andelman, Sandy J.</style></author><author><style face="normal" font="default" size="100%">Carr, Mark H.</style></author><author><style face="normal" font="default" size="100%">Gaines, Steven D.</style></author><author><style face="normal" font="default" size="100%">Halpern, Benjamin S.</style></author><author><style face="normal" font="default" size="100%">Hoenicke, Rainer</style></author><author><style face="normal" font="default" size="100%">Leibowitz, Scott G.</style></author><author><style face="normal" font="default" size="100%">Leydecker, Al</style></author><author><style face="normal" font="default" size="100%">Madin, Elizabeth M. P.</style></author><author><style face="normal" font="default" size="100%">Tallis, Heather</style></author><author><style face="normal" font="default" size="100%">Warner, Robert R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrated coastal reserve planning: making the land-sea connection</style></title><secondary-title><style face="normal" font="default" size="100%">Frontiers in Ecology and the Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">coastal ecosystems</style></keyword><keyword><style  face="normal" font="default" size="100%">integrated planning</style></keyword><keyword><style  face="normal" font="default" size="100%">open ecosystems</style></keyword><keyword><style  face="normal" font="default" size="100%">reserve selection</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial interactions</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.esajournals.org/esaonline/?request=get-abstract&amp;issn=1540-9295&amp;volume=003&amp;issue=08&amp;page=0429&lt;Go to ISI&gt;://000232295800016</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">429-436</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Land use, watershed processes, and coastal biodiversity can be strongly coupled. Land-sea interactions are ignored, however, when selecting terrestrial and marine reserves with existing models, with the risk that reserves will fail to achieve their conservation objectives. The conceptual model underlying existing reserve selection models presumes each site is a closed ecological system, unaffected by inputs from elsewhere. As a short-term objective, we recommend extending land conservation analyses to account for effects on marine biodiversity by consideration of linkages between them. This level of integration seems tractable and directly relevant to agencies and conservancies engaged in protecting coastal lands. We propose an approach that evaluates terrestrial sites based on whether they benefit or harm marine species or habitats. We then illustrate the approach with an example on the Central Coast of California, USA. Whether the effort will produce more effective terrestrial reserves needs to be proven.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Chomitz, Kenneth M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">TAMARIN: A landscape framework for evaluating economic incentives for rainforest restoration</style></title><secondary-title><style face="normal" font="default" size="100%">Landscape and Urban Planning</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity conservation planning</style></keyword><keyword><style  face="normal" font="default" size="100%">Brazil</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">Mata Atlântica</style></keyword><keyword><style  face="normal" font="default" size="100%">Opportunity costs</style></keyword><keyword><style  face="normal" font="default" size="100%">Spatial decision support system</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2004</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">&lt;Go to ISI&gt;://000220414700006</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">68</style></volume><pages><style face="normal" font="default" size="100%">95-108</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The rapid disappearance of the remaining Atlantic rainforest in Brazil exemplifies the need for efficient conservation planning in fragmented habitats under intense human pressure. Such planning needs to address key conservation criteria: representation, redundancy, and resilience. It also needs to recognize the opportunity cost of devoting land to conservation. Yet most existing planning frameworks fail to incorporate all three conservation criteria, and few allow for spatially variable opportunity costs of land. This paper presents a GIS-based spatial decision support system––TAMARIN––that incorporates all these features. TAMARIN can be used to evaluate particular landscape configurations, such as proposed enhancements to a conservation reserve network. It also allows simulation and assessment of market-based economic policies to promote conservation, such as rental or purchase of conservation easements. These may be particularly important in minimizing costs and securing landholder compliance in populous areas with highly fragmented natural habitats. Although TAMARIN was tailored to the planning issues and data sources of the south Bahia portion of the Atlantic rainforest, the ecological and economic underpinnings make it adaptable to many other locations.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">McDonald, Jennifer M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fuzzy assessment of land suitability for scientific research reserves</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Management</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Ecosystem Management Decision Support software</style></keyword><keyword><style  face="normal" font="default" size="100%">EMDS</style></keyword><keyword><style  face="normal" font="default" size="100%">fuzzy logic</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge base</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge-base</style></keyword><keyword><style  face="normal" font="default" size="100%">land suitability</style></keyword><keyword><style  face="normal" font="default" size="100%">Merced</style></keyword><keyword><style  face="normal" font="default" size="100%">Netweaver</style></keyword><keyword><style  face="normal" font="default" size="100%">NRS</style></keyword><keyword><style  face="normal" font="default" size="100%">research reserves</style></keyword><keyword><style  face="normal" font="default" size="100%">University of California Natural Reserve System</style></keyword><keyword><style  face="normal" font="default" size="100%">vernal pools</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://link.springer.de/link/service/journals/00267/bibs/2029004/20290545.html&lt;Go to ISI&gt;://000174557600008</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">545-558</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Evaluating the characteristics of a set of sites as potential scientific research reserves is an example of land suitability assessment. Suitability in this case is based upon multiple criteria, many of which can be linguistically imprecise and often incompatible. Fuzzy logic is a useful method for characterizing imprecise suitability criteria and for combining criteria into an overall suitability rating. The Ecosystem Management Decision Support software combined a fuzzy logic knowledge base we developed to represent the assessment problem with a GIS database providing site-specific data for the assessment. Assessment of sites as a potential natural reserve for the new University of California campus at Merced demonstrates the benefits of fuzzy suitability assessment. The study was conducted in three stages of successively smaller assessment regions with increasingly fine spatial resolution and specificity of criteria. Several sites were identified that best satisfy the suitability criteria for a reserve to represent vernal pool habitat.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank</style></author><author><style face="normal" font="default" size="100%">Kendall, Bruce</style></author><author><style face="normal" font="default" size="100%">Church, Richard</style></author><author><style face="normal" font="default" size="100%">Clarke, Keith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrated Modeling for Regional Biodiversity Conservation and Land Use Change</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><publisher><style face="normal" font="default" size="100%">University of California</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">RAD final report</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">McDonald, Jennifer M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Knowledge-based site suitability assessment for new NRS reserves for the proposed UC Merced campus</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Merced EMDS Netweaver knowledge base fuzzy logic</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><publisher><style face="normal" font="default" size="100%">University of California</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stoms, David M.</style></author><author><style face="normal" font="default" size="100%">McDonald, Jennifer M.</style></author><author><style face="normal" font="default" size="100%">Davis, Frank W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Knowledge-based site suitability assessment for new NRS reserves for the proposed UC Merced campus</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">EMDS</style></keyword><keyword><style  face="normal" font="default" size="100%">fuzzy logic</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge base</style></keyword><keyword><style  face="normal" font="default" size="100%">Merced</style></keyword><keyword><style  face="normal" font="default" size="100%">Netweaver</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2000</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.biogeog.ucsb.edu/projects/snner/nrs_report.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">University of California</style></publisher><pub-location><style face="normal" font="default" size="100%">Santa Barbara</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>