<?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, D. M.</style></author><author><style face="normal" font="default" size="100%">Dashiell, S. L.</style></author><author><style face="normal" font="default" size="100%">Davis, F. W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Siting solar energy development to minimize biological impacts</style></title><secondary-title><style face="normal" font="default" size="100%">Renewable Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ecological condition</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">mitigation hierarchy</style></keyword><keyword><style  face="normal" font="default" size="100%">multicriteria analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">siting criteria</style></keyword><keyword><style  face="normal" font="default" size="100%">utility-scale solar energy</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><volume><style face="normal" font="default" size="100%">57</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;After solar and other renewable energy developers select generally suitable sites for exploration, they frequently encounter conflict over biodiversity conservation values that were not factored into the initial suitability rating methods. This paper presents a spatial multicriteria analysis method for modeling risk of conflict with biological resources and applies the model in the California deserts where such conflicts are rapidly rising. The premise of the model is that the least conflict will occur on sites that are the most ecologically degraded with low conservation value and that would engender low offsite impacts when connecting to existing transmission infrastructure. Model results suggest sufficient compatible land exists in flat, non-urban areas to meet state solar energy targets of 18-26 GW of installed capacity in the California deserts for 2050. The model is a promising tool to fill the gap between site suitability analysis for renewable energy and regional biodiversity conservation planning to identify areas where rapid impact assessment and permitting will generate the least regrets.&lt;/p&gt;
</style></abstract><section><style face="normal" font="default" size="100%">289</style></section></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%">Machado, E. A.</style></author><author><style face="normal" font="default" size="100%">Stoms, D. M.</style></author><author><style face="normal" font="default" size="100%">Davis, F. W.</style></author><author><style face="normal" font="default" size="100%">Kreitler, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prioritizing farmland preservation cost-effectively for multiple objectives</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Soil and Water Conservation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">amenities</style></keyword><keyword><style  face="normal" font="default" size="100%">Bay Delta bioregion</style></keyword><keyword><style  face="normal" font="default" size="100%">California Legacy Project</style></keyword><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 analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">ecosystem services</style></keyword><keyword><style  face="normal" font="default" size="100%">farmland preservation</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">marginal value</style></keyword><keyword><style  face="normal" font="default" size="100%">public preferences</style></keyword><keyword><style  face="normal" font="default" size="100%">social welfare</style></keyword><keyword><style  face="normal" font="default" size="100%">urban growth boundary</style></keyword><keyword><style  face="normal" font="default" size="100%">urban growth management</style></keyword><keyword><style  face="normal" font="default" size="100%">utility</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%">&lt;Go to ISI&gt;://000242001800007</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">250-258</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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&#039;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.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Davis, F. W.</style></author><author><style face="normal" font="default" size="100%">Costello, C. J.</style></author><author><style face="normal" font="default" size="100%">Stoms, D. M.</style></author><author><style face="normal" font="default" size="100%">Machado, E. A.</style></author><author><style face="normal" font="default" size="100%">Metz, J.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Murphy, Dennis D.</style></author><author><style face="normal" font="default" size="100%">Stine, Peter A.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A framework for setting land conservation priorities in the Sierra Nevada</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Sierra Nevada Science Symposium</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">California Legacy Project</style></keyword><keyword><style  face="normal" font="default" size="100%">conservation planning</style></keyword><keyword><style  face="normal" font="default" size="100%">decision support system</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">marginal value</style></keyword><keyword><style  face="normal" font="default" size="100%">prioritization</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%">http://www.fs.fed.us/psw/publications/documents/psw_gtr193/psw_gtr193_5_4_Davis_and_others.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture</style></publisher><pub-location><style face="normal" font="default" size="100%">Albany, CA</style></pub-location><volume><style face="normal" font="default" size="100%">General Technical Report PSW-GTR-193</style></volume><pages><style face="normal" font="default" size="100%">195-206</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The California Legacy Project (CLP) mission is &quot;to enable the State and its partners in conservation to develop and implement a strategic and inclusive approach to conserving and restoring California&#039;s lands and natural resources.&quot; 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 &quot;bang for buck&quot; especially high in a smaller number of sites.</style></abstract><notes><style face="normal" font="default" size="100%">presented at Sierra Nevada Science Symposium 2002 October 7-10; Kings Beach, CA.</style></notes></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>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Machado, E. A.</style></author><author><style face="normal" font="default" size="100%">Stoms, D. M.</style></author><author><style face="normal" font="default" size="100%">Davis, F. W.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A systematic framework for prioritizing farmland preservation</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bay Delta bioregion</style></keyword><keyword><style  face="normal" font="default" size="100%">California Legacy Project</style></keyword><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%">farmland preservation</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">marginal value</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.nceas.ucsb.edu/nceas-web/projects/4040/Farmland_framework_report.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">National Center for Ecological Analysis and Synthesis</style></publisher><pub-location><style face="normal" font="default" size="100%">Santa Barbara</style></pub-location><pages><style face="normal" font="default" size="100%">52</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The California Legacy Project (CLP) mission is &quot;to enable the state and its partners in conservation to develop and implement a strategic and inclusive approach to conserving and restoring California&#039;s lands and natural resources.&quot; 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 &quot;blueprint&quot; 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.</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>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hollander, A. D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A GIS framework for modelling wildlife species distributions</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">evidence</style></keyword><keyword><style  face="normal" font="default" size="100%">expert system</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">inference</style></keyword><keyword><style  face="normal" font="default" size="100%">scale</style></keyword><keyword><style  face="normal" font="default" size="100%">wild pigs</style></keyword><keyword><style  face="normal" font="default" size="100%">wildlife modeling</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Maps of wildlife species distributions are a fundamental display of data in biogeography, and increasingly GIS methods are used to develop models of distributions. This dissertation examines some of the major issues in constructing predictive maps of species, focusing on the capability of GIS to relate environmental factors to distributions through logical or mathematical inference. The dissertation is structured in three parts. The first part considers how a variety of data sources may be aggregated to build up a picture of a distribution, using the example of the orange-throated whiptail, a lizard species living in southern California. It discusses how structuring these data on a hierarchy of spatial scales can lead to new inferences about distributions and habitat relationships. The second and third sections elaborate this theme of data availability and spatial scale in distribution modelling, using the example of the feral pig in central California. The second section presents a case study of developing an expert system to predict relative pig abundance at a regional scale. It illustrates how an expert system provides a formal treatment of aggregation of evidence, and how increasing the degree of interaction with a GIS can lead to elicitation of better models from domain experts. The third section presents a habitat model for the feral pig at a local scale. The grain size of this model is very finely resolved with respect to the home range of a pig, so this model integrates habitat elements over the home range size of the animal to create a spatially sensitive model of habitat quality. This model is tested against observation data at a number of different spatial scales, the results illustrating that it is important to recognize the spatial scale of a habitat model when it is applied.</style></abstract><work-type><style face="normal" font="default" size="100%">phdPh.D.</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Davis, F. W.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Chou, C. I. Peng</style></author><author><style face="normal" font="default" size="100%">C. H.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Mapping and monitoring terrestrial biodiversity using geographic information systems</style></title><secondary-title><style face="normal" font="default" size="100%">Biodiversity and Terrestrial Ecosystems</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">connectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">evidence</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">southern California</style></keyword><keyword><style  face="normal" font="default" size="100%">whiptail</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1994</style></year></dates><publisher><style face="normal" font="default" size="100%">Institute of Botany, Academia Sinica</style></publisher><pub-location><style face="normal" font="default" size="100%">Taipei</style></pub-location><volume><style face="normal" font="default" size="100%">Monograph Series No. 14</style></volume><pages><style face="normal" font="default" size="100%">461-471</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Location in space and time are attributes of nearly all biodiversity data. Obvious examples include species&#039; collection localities, range maps and habitat maps. Geographic Information Systems for managing and analyzing spatial data are rapidly becoming an integral tool for scientists, resource managers and policy makers concerned with biodiversity conservation and ecosystem management. Database capabilities of GIS have extended the traditional map to a much more flexible and powerful representation of spatial information by allowing potentially large amounts of non-graphical information to be attached to each map unit. Biologists have yet to fully exploit this aspect of GIS in classification and mapping of biodiversity patterns. Some advantages of the GIS model over traditional maps are illustrated with a vegetation mapping project in southern California. In recent years GIS has been applied to a wide range of biodiversity issues, for example, modeling species distributions, Gap Analysis, population viability analysis, modeling ecosystem disturbance processes, and projecting the ecological impacts of global climate change. Specimen data can be of much greater use in conservation planning when coupled to predictive habitat relationship models and accurate habitat maps. The use of GIS to assemble multiple lines of evidence in modeling species&#039; distribution is illustrated for Cnemidophorus hyperythrus, an endangered lizard of coastal southern California. Lastly, an example is provided of the application of GIS modeling of habitat suitability and connectivity to conservation planning in southern California.</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%">Davis, F. W.</style></author><author><style face="normal" font="default" size="100%">Dozier, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Information analysis of a spatial database for ecological land classification</style></title><secondary-title><style face="normal" font="default" size="100%">Photogrammetric Engineering &amp; Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Burton Mesa</style></keyword><keyword><style  face="normal" font="default" size="100%">California</style></keyword><keyword><style  face="normal" font="default" size="100%">DEM data</style></keyword><keyword><style  face="normal" font="default" size="100%">entropy</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">map errors</style></keyword><keyword><style  face="normal" font="default" size="100%">mutual information analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">TMS</style></keyword><keyword><style  face="normal" font="default" size="100%">vegetation pattern</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1990</style></year></dates><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">56</style></volume><pages><style face="normal" font="default" size="100%">605-613</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>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Davis, F. W.</style></author><author><style face="normal" font="default" size="100%">Goetz, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling vegetation pattern using digital terrain data</style></title><secondary-title><style face="normal" font="default" size="100%">Landscape Ecology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">California</style></keyword><keyword><style  face="normal" font="default" size="100%">coast live oak forest</style></keyword><keyword><style  face="normal" font="default" size="100%">DEM</style></keyword><keyword><style  face="normal" font="default" size="100%">geology</style></keyword><keyword><style  face="normal" font="default" size="100%">GIS</style></keyword><keyword><style  face="normal" font="default" size="100%">Lompoc</style></keyword><keyword><style  face="normal" font="default" size="100%">remote sensing</style></keyword><keyword><style  face="normal" font="default" size="100%">solar radiation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1990</style></year></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">69-80</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>