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data-dom-id="ProfileCheckPaperUpdate-react-component-276483ae-9047-4f5d-93e4-dc3412924b51"></div> <div id="ProfileCheckPaperUpdate-react-component-276483ae-9047-4f5d-93e4-dc3412924b51"></div> <div class="DesignSystem"><div class="onsite-ping" id="onsite-ping"></div></div><div class="profile-user-info DesignSystem"><div class="social-profile-container"><div class="left-panel-container"><div class="user-info-component-wrapper"><div class="user-summary-cta-container"><div class="user-summary-container"><div class="social-profile-avatar-container"><img class="profile-avatar u-positionAbsolute" border="0" alt="" src="//a.academia-assets.com/images/s200_no_pic.png" /></div><div class="title-container"><h1 class="ds2-5-heading-sans-serif-sm">Dean Urban</h1><div class="affiliations-container fake-truncate js-profile-affiliations"><div><a class="u-tcGrayDarker" href="https://duke.academia.edu/">Duke University</a>, <a class="u-tcGrayDarker" 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class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Dean Urban</h3></div><div class="js-work-strip profile--work_container" data-work-id="14011594"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011594/Focused_Assessment_of_Scale_Dependent_Vegetation_Pattern"><img alt="Research paper thumbnail of Focused Assessment of Scale-Dependent Vegetation Pattern" class="work-thumbnail" src="https://attachments.academia-assets.com/44707826/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011594/Focused_Assessment_of_Scale_Dependent_Vegetation_Pattern">Focused Assessment of Scale-Dependent Vegetation Pattern</a></div><div class="wp-workCard_item"><span>Predictive Species and Habitat Modeling in Landscape Ecology</span><span>, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="983a27eda966ec9afebd34999851ffa9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707826,"asset_id":14011594,"asset_type":"Work","button_location":"profile"}" 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Diversity","url":"https://www.academia.edu/Documents/in/Species_Diversity"},{"id":171338,"name":"Spatial Scale","url":"https://www.academia.edu/Documents/in/Spatial_Scale"},{"id":235745,"name":"Environmental Heterogeneity","url":"https://www.academia.edu/Documents/in/Environmental_Heterogeneity"},{"id":530920,"name":"Scale dependence","url":"https://www.academia.edu/Documents/in/Scale_dependence"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011593"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011593/Reconciling_Oil_Palm_Expansion_and_Climate_Change_Mitigation_in_Kalimantan_Indonesia"><img alt="Research paper thumbnail of Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011593/Reconciling_Oil_Palm_Expansion_and_Climate_Change_Mitigation_in_Kalimantan_Indonesia">Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia</a></div><div class="wp-workCard_item"><span>PLOS ONE</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Our society faces the pressing challenge of increasing agricultural production while minimizing n...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s national emissions mitigation goal, while allowing oil palm area to double.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011593"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011593"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011593; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011593]").text(description); $(".js-view-count[data-work-id=14011593]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011593; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011593']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011593, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011593]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011593,"title":"Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia","translated_title":"","metadata":{"abstract":"Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s national emissions mitigation goal, while allowing oil palm area to double.","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"PLOS ONE"},"translated_abstract":"Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s national emissions mitigation goal, while allowing oil palm area to double.","internal_url":"https://www.academia.edu/14011593/Reconciling_Oil_Palm_Expansion_and_Climate_Change_Mitigation_in_Kalimantan_Indonesia","translated_internal_url":"","created_at":"2015-07-13T17:55:13.409-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075158,"work_id":14011593,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":780009,"email":"j***t@duke.edu","display_order":0,"name":"Jeffrey Vincent","title":"Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia"},{"id":3075192,"work_id":14011593,"tagging_user_id":33044090,"tagged_user_id":32982424,"co_author_invite_id":null,"email":"p***9@duke.edu","display_order":4194304,"name":"P. 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Halpin</a></span></div><div class="wp-workCard_item"><span>Proceedings of the ninth ACM international symposium on Advances in geographic information systems - GIS '01</span><span>, 2001</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7aff9ff172842f7eef6632bc6021192e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707775,"asset_id":14011592,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707775/download_file?st=MTczMjc1MTc5Miw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011592"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011592"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011592; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011592]").text(description); $(".js-view-count[data-work-id=14011592]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011592; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011592']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011592, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7aff9ff172842f7eef6632bc6021192e" } } $('.js-work-strip[data-work-id=14011592]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011592,"title":"Flow computation on massive grids","translated_title":"","metadata":{"grobid_abstract":"As detailed terrain data becomes available, GIS applications target larger geographic areas at finer resolutions. 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Halpin</a></span></div><div class="wp-workCard_item"><span>Geoinformatica</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">As detailed terrain data becomes available, GIS terrain applications target larger geographic are...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. Processing the massive data involved in such applications presents signicant challenges to GIS systems and demands algorithms that are optimized for both data movement and computation. 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Halpin</a></span></div><div class="wp-workCard_item"><span>Geoinformatica</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">As detailed terrain data becomes available, GIS terrain applications target larger geographic are...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. Processing the massive datasets involved in such applications presents signicant challenges to GIS systems and demands algorithms that are optimized for both data movement and computation. In this paper we present ecient algorithms for flow routing on massive grid terrain datasets, extending our previous</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5323332ec21058e73528998d114469b0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":38180219,"asset_id":14011588,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/38180219/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011588"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011588"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011588; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011588]").text(description); $(".js-view-count[data-work-id=14011588]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011588; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011588']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011588, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "5323332ec21058e73528998d114469b0" } } $('.js-work-strip[data-work-id=14011588]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011588,"title":"Efficient Flow Computation on Massive Grid Terrain Datasets","translated_title":"","metadata":{"abstract":"As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. 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SCALE-SPECIFIC INFERENCE USING WAVELETS" class="work-thumbnail" src="https://attachments.academia-assets.com/44707846/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011587/SCALE_SPECIFIC_INFERENCE_USING_WAVELETS">SCALE-SPECIFIC INFERENCE USING WAVELETS</a></div><div class="wp-workCard_item"><span>Ecology</span><span>, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet eco...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. We introduce wavelet-coefficient regression, in which the dependent and independent variables are wavelet transformed prior to analysis, as a means to formalize scale-specific relationships in ecological data. We apply this</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ee1e7f84db43bf41dc0b0723d190da17" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707846,"asset_id":14011587,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707846/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011587"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011587"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011587; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011587]").text(description); $(".js-view-count[data-work-id=14011587]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011587; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011587']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011587, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ee1e7f84db43bf41dc0b0723d190da17" } } $('.js-work-strip[data-work-id=14011587]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011587,"title":"SCALE-SPECIFIC INFERENCE USING WAVELETS","translated_title":"","metadata":{"abstract":"Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011586"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011586/Potential_response_of_pacific_northwestern_forests_to_climatic_change_effects_of_stand_age_and_initial_composition"><img alt="Research paper thumbnail of Potential response of pacific northwestern forests to climatic change, effects of stand age and initial composition" class="work-thumbnail" src="https://attachments.academia-assets.com/44707813/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011586/Potential_response_of_pacific_northwestern_forests_to_climatic_change_effects_of_stand_age_and_initial_composition">Potential response of pacific northwestern forests to climatic change, effects of stand age and initial composition</a></div><div class="wp-workCard_item"><span>Climatic Change</span><span>, 1993</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We used an individual-based forest simulator (a gap model) to assess the potential effects of ant...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We used an individual-based forest simulator (a gap model) to assess the potential effects of anthropogenic climatic change on conifer forests of the Pacific Northwestern United States. Steady-state simulations suggested that forest zones could be shifted on the order of 500–1000 m in elevation, which could lead to the local extirpation of some high-altitude species. For low-elevation sites, species which</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="05513c22150be124af2675df90f6a0c7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707813,"asset_id":14011586,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707813/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011586"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011586"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011586; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011586]").text(description); $(".js-view-count[data-work-id=14011586]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011586; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011586']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011586, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "05513c22150be124af2675df90f6a0c7" } } $('.js-work-strip[data-work-id=14011586]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011586,"title":"Potential response of pacific northwestern forests to climatic change, effects of stand age and initial composition","translated_title":"","metadata":{"abstract":"We used an individual-based forest simulator (a gap model) to assess the potential effects of anthropogenic climatic change on conifer forests of the Pacific Northwestern United States. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011585"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011585/Gradient_analysis_the_next_generation_towards_more_plant_relevant_explanatory_variables"><img alt="Research paper thumbnail of Gradient analysis, the next generation: towards more plant-relevant explanatory variables" class="work-thumbnail" src="https://attachments.academia-assets.com/44707785/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011585/Gradient_analysis_the_next_generation_towards_more_plant_relevant_explanatory_variables">Gradient analysis, the next generation: towards more plant-relevant explanatory variables</a></div><div class="wp-workCard_item"><span>Canadian Journal of Forest Research-revue Canadienne De Recherche Forestiere</span><span>, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The long history of gradient analysis is anchored in the observation that species turnover can be...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. This model is unsatisfying in that elevation is not directly relevant to plants and the ubiqui- tous &quot;elevation gradient&quot; is composed of multiple intertwined environmental factors. We offer an approach to landscape- scale vegetation analysis that disentangles the elevation gradient</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="23203035350015985f1405e7ee2fc11a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707785,"asset_id":14011585,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707785/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011585"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011585"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011585; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011585]").text(description); $(".js-view-count[data-work-id=14011585]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011585; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011585']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011585, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "23203035350015985f1405e7ee2fc11a" } } $('.js-work-strip[data-work-id=14011585]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011585,"title":"Gradient analysis, the next generation: towards more plant-relevant explanatory variables","translated_title":"","metadata":{"abstract":"The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. 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For example, if increasing numbers of migratory species is of primary concern, then conservation areas should be located outside of urban boundaries or in areas with low road density. 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Topographic orientation is often used as a proxy for relative radiation load due to its effects on evaporative demand and local temperature. Common methods for incorporating this information (i.e., site measures of slope and aspect) fail to include daily or annual changes in solar orientation and shading effects from local topography. As a result, these static measures do not incorporate the level of spatial and temporal heterogeneity required to examine vegetation patterns at the landscape level. We developed a widely applicable method for estimating potential relative radiation (PRR) using digital elevation data and a widely used geographic information system (Arc/Info). We found significant differences among four increasingly comprehensive radiation proxies. Our GIS-based proxy compared well with estimates from more data-intensive and computationally rigorous radiation models. We note that several recent studies have not found strong correlations between vegetation pattern and landscape-scale differences in radiation. We suggest that these findings may be due to the use of proxies that were not accurately capturing variability in radiation, and we recommend PRR or similar measures for use in future vegetation analyses.","publication_date":{"day":null,"month":null,"year":2005,"errors":{}},"publication_name":"Landscape Ecology","grobid_abstract_attachment_id":44707786},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011583/A_simple_method_for_estimating_potential_relative_radiation_PRR_for_landscape_scale_vegetation_analysis","translated_internal_url":"","created_at":"2015-07-13T17:55:12.546-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075149,"work_id":14011583,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":560433,"email":"t***l@al.umces.edu","display_order":0,"name":"Todd Lookingbill","title":"A simple method for estimating 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class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011582/Semivariograms_from_a_forest_transect_gap_model_compared_with_remotely_sensed_data">Semivariograms from a forest transect gap model compared with remotely sensed data</a></div><div class="wp-workCard_item"><span>Journal of Vegetation Science</span><span>, 1992</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Page 1. - Semivariograms from a gap model compared with remotely sensed data-521 Semivariograms f...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa 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Jr. 1 ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011582"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011582"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011582; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011582]").text(description); $(".js-view-count[data-work-id=14011582]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011582; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011582']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011582, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011582]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011582,"title":"Semivariograms from a forest transect gap model compared with remotely sensed data","translated_title":"","metadata":{"abstract":"Page 1. - Semivariograms from a gap model compared with remotely sensed data-521 Semivariograms from a forest transect gap model compared with remotely sensed data Weishampel, John F.1*, Urban, Dean L.1,2, Shugart, Herman H.1 \u0026amp; Smith, Jackson B. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011581"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011581/Tree_damage_risk_factors_associated_with_large_infrequent_wind_disturbances_of_Carolina_forests"><img alt="Research paper thumbnail of Tree damage risk factors associated with large, infrequent wind disturbances of Carolina forests" class="work-thumbnail" src="https://attachments.academia-assets.com/44707818/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011581/Tree_damage_risk_factors_associated_with_large_infrequent_wind_disturbances_of_Carolina_forests">Tree damage risk factors associated with large, infrequent wind disturbances of Carolina forests</a></div><div class="wp-workCard_item"><span>Forestry</span><span>, 2008</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8364e878bea48355e8f3c7a0a8b1f880" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707818,"asset_id":14011581,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707818/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011581"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011581"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011581; 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We present a multi-scale, comparative analysis to examine how risk factors change over spatial scales and to evaluate the consistency in risk factors associated with three major wind events: a North Carolina Piedmont tornado of 1988, Hurricane Hugo of 1989 and Hurricane Fran of 1996. Our results reveal that the risk factors that best explain variation in damage vary with scale of observation. Tree size and species explain damage variation at the stand scale; topographic, site and stand factors explain damage variation at the landscape scale and wind speed and precipitation explain damage variation at the regional scale. However, it is possible to integrate these factors by incorporating factors from the fi ner scales into coarser-scale studies. We also found distinct differences in the damage caused by the hurricanes relative to the tornado, and to some extent consistency between hurricanes.","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"Forestry","grobid_abstract_attachment_id":44707818},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011581/Tree_damage_risk_factors_associated_with_large_infrequent_wind_disturbances_of_Carolina_forests","translated_internal_url":"","created_at":"2015-07-13T17:55:12.379-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075160,"work_id":14011581,"tagging_user_id":33044090,"tagged_user_id":34111085,"co_author_invite_id":780011,"email":"w***i@tamuk.edu","display_order":0,"name":"Weimin Xi","title":"Tree damage risk factors associated with large, infrequent wind disturbances of Carolina forests"},{"id":3075162,"work_id":14011581,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":629793,"email":"j***e@ua.edu","display_order":4194304,"name":"Jamie Decoster","title":"Tree damage risk factors associated with large, infrequent wind disturbances of Carolina forests"}],"downloadable_attachments":[{"id":44707818,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/44707818/thumbnails/1.jpg","file_name":"Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l.pdf","download_url":"https://www.academia.edu/attachments/44707818/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Tree_damage_risk_factors_associated_with.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/44707818/Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l-libre.pdf?1460582945=\u0026response-content-disposition=attachment%3B+filename%3DTree_damage_risk_factors_associated_with.pdf\u0026Expires=1732755393\u0026Signature=Ii7QqIx6R20BjJPu-OQpBQh5PjrBg0V3kTZqSdo255VWG27qhhvCDr8RRAVDplTNxtiVjRoQVFwr5W5LSXrkU3SNcRbTIQ7~OoyXLPcWLGrRA9CHXTPAT8LiWVcQwftUm90AERsymzxSvedqqxq7Vdm~WFjlc7iDzbN52RETpvcLOQFykLPEb-tWbxH7qKMeNCTZgSmRJ2D-F86rlVo63T7QVb0iBygHhBOiPl5YmO5i-tQ21hQh5E27aau7Y9KdFGU31jKGx4nPjPeJc1iRe7NNXlqP4c6EfY6GYpbMksKxa3XmO~3iJxDayd-VMH8Gc1lhBSCL4uYs2ffVzZu~jA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Tree_damage_risk_factors_associated_with_large_infrequent_wind_disturbances_of_Carolina_forests","translated_slug":"","page_count":18,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean Urban","url":"https://duke.academia.edu/DeanUrban"},"attachments":[{"id":44707818,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/44707818/thumbnails/1.jpg","file_name":"Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l.pdf","download_url":"https://www.academia.edu/attachments/44707818/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Tree_damage_risk_factors_associated_with.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/44707818/Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l-libre.pdf?1460582945=\u0026response-content-disposition=attachment%3B+filename%3DTree_damage_risk_factors_associated_with.pdf\u0026Expires=1732755393\u0026Signature=Ii7QqIx6R20BjJPu-OQpBQh5PjrBg0V3kTZqSdo255VWG27qhhvCDr8RRAVDplTNxtiVjRoQVFwr5W5LSXrkU3SNcRbTIQ7~OoyXLPcWLGrRA9CHXTPAT8LiWVcQwftUm90AERsymzxSvedqqxq7Vdm~WFjlc7iDzbN52RETpvcLOQFykLPEb-tWbxH7qKMeNCTZgSmRJ2D-F86rlVo63T7QVb0iBygHhBOiPl5YmO5i-tQ21hQh5E27aau7Y9KdFGU31jKGx4nPjPeJc1iRe7NNXlqP4c6EfY6GYpbMksKxa3XmO~3iJxDayd-VMH8Gc1lhBSCL4uYs2ffVzZu~jA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":1041,"name":"Forestry","url":"https://www.academia.edu/Documents/in/Forestry"},{"id":93353,"name":"North Carolina","url":"https://www.academia.edu/Documents/in/North_Carolina"},{"id":152553,"name":"Comparative Analysis","url":"https://www.academia.edu/Documents/in/Comparative_Analysis"},{"id":161954,"name":"Regional scale","url":"https://www.academia.edu/Documents/in/Regional_scale"},{"id":171338,"name":"Spatial Scale","url":"https://www.academia.edu/Documents/in/Spatial_Scale"},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors"},{"id":317638,"name":"Forestry Sciences","url":"https://www.academia.edu/Documents/in/Forestry_Sciences"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1"},{"id":755542,"name":"Wind Speed","url":"https://www.academia.edu/Documents/in/Wind_Speed"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011580"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011580/Graph_models_of_habitat_mosaics"><img alt="Research paper thumbnail of Graph models of habitat mosaics" class="work-thumbnail" src="https://attachments.academia-assets.com/44707824/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011580/Graph_models_of_habitat_mosaics">Graph models of habitat mosaics</a></div><div class="wp-workCard_item"><span>Ecology Letters</span><span>, 2009</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7b98da6f8343cc43d5e58da2903df1d4" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707824,"asset_id":14011580,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707824/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011580"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011580"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011580; 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Theory","url":"https://www.academia.edu/Documents/in/Network_Theory"},{"id":139358,"name":"Conceptual Model","url":"https://www.academia.edu/Documents/in/Conceptual_Model"},{"id":373754,"name":"Ecosystem","url":"https://www.academia.edu/Documents/in/Ecosystem"},{"id":719974,"name":"Conservation of Natural Resources","url":"https://www.academia.edu/Documents/in/Conservation_of_Natural_Resources"},{"id":843856,"name":"Ecological Applications","url":"https://www.academia.edu/Documents/in/Ecological_Applications"},{"id":1213131,"name":"Geographic Information Systems","url":"https://www.academia.edu/Documents/in/Geographic_Information_Systems"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011579"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011579/Forest_ecosystem_dynamics_linking_forest_succession_soil_process_and_radiation_models"><img alt="Research paper thumbnail of Forest ecosystem dynamics: linking forest succession, soil process and radiation models" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011579/Forest_ecosystem_dynamics_linking_forest_succession_soil_process_and_radiation_models">Forest ecosystem dynamics: linking forest succession, soil process and radiation models</a></div><div class="wp-workCard_item"><span>Ecological Modelling</span><span>, 1993</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011579"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011579"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011579; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011579]").text(description); $(".js-view-count[data-work-id=14011579]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011579; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011579']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011579, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011579]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011579,"title":"Forest ecosystem dynamics: linking forest succession, soil process and radiation models","translated_title":"","metadata":{"abstract":"ABSTRACT","publication_date":{"day":null,"month":null,"year":1993,"errors":{}},"publication_name":"Ecological Modelling"},"translated_abstract":"ABSTRACT","internal_url":"https://www.academia.edu/14011579/Forest_ecosystem_dynamics_linking_forest_succession_soil_process_and_radiation_models","translated_internal_url":"","created_at":"2015-07-13T17:55:12.223-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075198,"work_id":14011579,"tagging_user_id":33044090,"tagged_user_id":86986301,"co_author_invite_id":263997,"email":"l***e@virginia.edu","display_order":4194304,"name":"Deborah Lawrence","title":"Forest ecosystem dynamics: linking forest succession, soil process and radiation models"}],"downloadable_attachments":[],"slug":"Forest_ecosystem_dynamics_linking_forest_succession_soil_process_and_radiation_models","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean Urban","url":"https://duke.academia.edu/DeanUrban"},"attachments":[],"research_interests":[{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary"},{"id":28697,"name":"Ecological Modelling","url":"https://www.academia.edu/Documents/in/Ecological_Modelling"},{"id":173025,"name":"Forest succession","url":"https://www.academia.edu/Documents/in/Forest_succession"},{"id":359455,"name":"Forest ecosystem","url":"https://www.academia.edu/Documents/in/Forest_ecosystem"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011578"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011578/Modeling_vegetation_structure_ecosystem_process_interactions_across_sites_and_ecosystems"><img alt="Research paper thumbnail of Modeling vegetation structure-ecosystem process interactions across sites and ecosystems" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011578/Modeling_vegetation_structure_ecosystem_process_interactions_across_sites_and_ecosystems">Modeling vegetation structure-ecosystem process interactions across sites and ecosystems</a></div><div class="wp-workCard_item"><span>Ecological Modelling</span><span>, 1993</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT We describe an approach to investigating and understanding the interactions between vege...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT We describe an approach to investigating and understanding the interactions between vegetation structure and ecosystem processes that uses simulation models as a framework for comparison and synthesis across ecosystems arrayed along environmental gradients. The models are individual-based vegetation simulators and compartment models of nutrient cycling and soil water relations. Applications focus on interactions and feedbacks between vegetation structure (species composition, size structure) and ecosystem processes (water balance, nutrient cycling), and how these relationships vary across environmental gradients. Preliminary results indicate that life-history traits of plants have a profound influence on system-level behaviors, and that differences between grasslands and forests can be attributed largely to contrasting traits of grasses and trees. Experiments with linked vegetation-ecosystem process models diverge from simulations with either model run independently, suggesting the importance of feedbacks between details of vegetation pattern and ecosystem processes. The development of a fully coupled vegetation-ecosystem process model that is sufficiently general to simulate systems dominated by multiple lifeforms presents several conceptual, logistical, and scaling challenges, but also provides for new opportunities in ecosystem theory.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011578"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011578"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011578; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011578]").text(description); $(".js-view-count[data-work-id=14011578]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011578; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011578']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011578, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011578]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011578,"title":"Modeling vegetation structure-ecosystem process interactions across sites and ecosystems","translated_title":"","metadata":{"abstract":"ABSTRACT We describe an approach to investigating and understanding the interactions between vegetation structure and ecosystem processes that uses simulation models as a framework for comparison and synthesis across ecosystems arrayed along environmental gradients. The models are individual-based vegetation simulators and compartment models of nutrient cycling and soil water relations. Applications focus on interactions and feedbacks between vegetation structure (species composition, size structure) and ecosystem processes (water balance, nutrient cycling), and how these relationships vary across environmental gradients. Preliminary results indicate that life-history traits of plants have a profound influence on system-level behaviors, and that differences between grasslands and forests can be attributed largely to contrasting traits of grasses and trees. Experiments with linked vegetation-ecosystem process models diverge from simulations with either model run independently, suggesting the importance of feedbacks between details of vegetation pattern and ecosystem processes. The development of a fully coupled vegetation-ecosystem process model that is sufficiently general to simulate systems dominated by multiple lifeforms presents several conceptual, logistical, and scaling challenges, but also provides for new opportunities in ecosystem theory.","publication_date":{"day":null,"month":null,"year":1993,"errors":{}},"publication_name":"Ecological Modelling"},"translated_abstract":"ABSTRACT We describe an approach to investigating and understanding the interactions between vegetation structure and ecosystem processes that uses simulation models as a framework for comparison and synthesis across ecosystems arrayed along environmental gradients. The models are individual-based vegetation simulators and compartment models of nutrient cycling and soil water relations. Applications focus on interactions and feedbacks between vegetation structure (species composition, size structure) and ecosystem processes (water balance, nutrient cycling), and how these relationships vary across environmental gradients. Preliminary results indicate that life-history traits of plants have a profound influence on system-level behaviors, and that differences between grasslands and forests can be attributed largely to contrasting traits of grasses and trees. Experiments with linked vegetation-ecosystem process models diverge from simulations with either model run independently, suggesting the importance of feedbacks between details of vegetation pattern and ecosystem processes. The development of a fully coupled vegetation-ecosystem process model that is sufficiently general to simulate systems dominated by multiple lifeforms presents several conceptual, logistical, and scaling challenges, but also provides for new opportunities in ecosystem theory.","internal_url":"https://www.academia.edu/14011578/Modeling_vegetation_structure_ecosystem_process_interactions_across_sites_and_ecosystems","translated_internal_url":"","created_at":"2015-07-13T17:55:12.155-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Modeling_vegetation_structure_ecosystem_process_interactions_across_sites_and_ecosystems","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean Urban","url":"https://duke.academia.edu/DeanUrban"},"attachments":[],"research_interests":[{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary"},{"id":28697,"name":"Ecological Modelling","url":"https://www.academia.edu/Documents/in/Ecological_Modelling"},{"id":1640562,"name":"Vegetation Structure","url":"https://www.academia.edu/Documents/in/Vegetation_Structure"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011577"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011577/Models_of_forest_dynamics_based_on_roles_of_tree_species"><img alt="Research paper thumbnail of Models of forest dynamics based on roles of tree species" class="work-thumbnail" src="https://attachments.academia-assets.com/44707794/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011577/Models_of_forest_dynamics_based_on_roles_of_tree_species">Models of forest dynamics based on roles of tree species</a></div><div class="wp-workCard_item"><span>Ecological Modelling</span><span>, 1996</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="bb8a00ce1a5d62eb22c017d6124ebccd" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707794,"asset_id":14011577,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707794/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011577"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011577"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011577; 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This patch transition model utilizes functional roles instead of species. The roles or types are based on the regeneration and mortality characteristics of tree species; specifically, the requirements of canopy gaps for regeneration and the capacity to create canopy gaps upon death. A gap-size plot can be assigned to each of a set of states defined according to dominance of one of the roles. Transition probabilities among these states and mean holding times in each transition lead to semi-Markovian analytical calculations of the stationary state probabilities. Forest dynamics, as the proportions of total canopy space occupied by each role in a collection of gap-size plots, can be analyzed and simulated using a chain of first-order differential equations to emulate the distributed time-delays. Additional fixed time-delays in the transition of every pair of states is also included to account for long latencies. In addition to simplifying the simulations, the resulting model can also utilize available results of the theory of semi-Markov processes; and therefore, can provide analytical guidance to the simulations, the feasibility of direct exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can especially be useful in the simulation of landscape dynamics and species-rich tropical forests.","publication_date":{"day":null,"month":null,"year":1996,"errors":{}},"publication_name":"Ecological Modelling","grobid_abstract_attachment_id":44707794},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011577/Models_of_forest_dynamics_based_on_roles_of_tree_species","translated_internal_url":"","created_at":"2015-07-13T17:55:12.086-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075207,"work_id":14011577,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":780022,"email":"m***o@usdoj.gov","display_order":0,"name":"M. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011576"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011576/GRAPH_THEORY_AS_A_PROXY_FOR_SPATIALLY_EXPLICIT_POPULATION_MODELS_IN_CONSERVATION_PLANNING"><img alt="Research paper thumbnail of GRAPH THEORY AS A PROXY FOR SPATIALLY EXPLICIT POPULATION MODELS IN CONSERVATION PLANNING" class="work-thumbnail" src="https://attachments.academia-assets.com/44707776/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011576/GRAPH_THEORY_AS_A_PROXY_FOR_SPATIALLY_EXPLICIT_POPULATION_MODELS_IN_CONSERVATION_PLANNING">GRAPH THEORY AS A PROXY FOR SPATIALLY EXPLICIT POPULATION MODELS IN CONSERVATION PLANNING</a></div><div class="wp-workCard_item"><span>Ecological Applications</span><span>, 2007</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c501a20d52d115cd7b3b09610dfd5864" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707776,"asset_id":14011576,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707776/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011576"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011576"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011576; 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However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.","publication_date":{"day":null,"month":null,"year":2007,"errors":{}},"publication_name":"Ecological 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dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011575"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011575/A_Graph_Theory_Framework_for_Evaluating_Landscape_Connectivity_and_Conservation_Planning"><img alt="Research paper thumbnail of A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning" class="work-thumbnail" src="https://attachments.academia-assets.com/44707803/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011575/A_Graph_Theory_Framework_for_Evaluating_Landscape_Connectivity_and_Conservation_Planning">A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning</a></div><div class="wp-workCard_item"><span>Conservation Biology</span><span>, 2008</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="789f6170d30e87e4d520aa9082da9231" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707803,"asset_id":14011575,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707803/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span 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We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). . We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"Conservation Biology","grobid_abstract_attachment_id":44707803},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011575/A_Graph_Theory_Framework_for_Evaluating_Landscape_Connectivity_and_Conservation_Planning","translated_internal_url":"","created_at":"2015-07-13T17:55:11.908-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":44707803,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/44707803/thumbnails/1.jpg","file_name":"A_Graph-Theory_Framework_for_Evaluating_20160413-17563-mr23gj.pdf","download_url":"https://www.academia.edu/attachments/44707803/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"A_Graph_Theory_Framework_for_Evaluating.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/44707803/A_Graph-Theory_Framework_for_Evaluating_20160413-17563-mr23gj-libre.pdf?1460582947=\u0026response-content-disposition=attachment%3B+filename%3DA_Graph_Theory_Framework_for_Evaluating.pdf\u0026Expires=1732755393\u0026Signature=BLvzW30lNdOIaqLUZ4Hu40sjrm1gUfmyxS-G~xoBP9vp6g7nFEByC27-a5zcfKMlekQImIA3FLwLr~44cqRPtvFehrxkGsRhVdHSsew8EitMFRzZ9sbCbHt77YCZ0QGNiMdapJlhqUw527eDchSv0e2xUxMusGhtYf0zb8MbdsuIpY022HL-gR3GfHxVxN98nAX20YdXD6IFg1ccHljJh6YUDEghihsi8cHckd8I2aiQooOki2ZKOaSb26zU-piKP8vNz0KOlAWYj2ErZqkn2okoAAVhc3PERUrGA7wk3U3EDfwUe4z-qtEnJmI9TbhhecuTJr5I3GkUD8jfpW91og__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"A_Graph_Theory_Framework_for_Evaluating_Landscape_Connectivity_and_Conservation_Planning","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean 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Biology","url":"https://www.academia.edu/Documents/in/Conservation_Biology"},{"id":2616,"name":"Graph Theory","url":"https://www.academia.edu/Documents/in/Graph_Theory"},{"id":7466,"name":"Human Development","url":"https://www.academia.edu/Documents/in/Human_Development"},{"id":11417,"name":"Population Dynamics","url":"https://www.academia.edu/Documents/in/Population_Dynamics"},{"id":30491,"name":"Conservation planning","url":"https://www.academia.edu/Documents/in/Conservation_planning"},{"id":47884,"name":"Biological Sciences","url":"https://www.academia.edu/Documents/in/Biological_Sciences"},{"id":58054,"name":"Environmental Sciences","url":"https://www.academia.edu/Documents/in/Environmental_Sciences"},{"id":93353,"name":"North Carolina","url":"https://www.academia.edu/Documents/in/North_Carolina"},{"id":134820,"name":"Network Theory","url":"https://www.academia.edu/Documents/in/Network_Theory"},{"id":171338,"name":"Spatial 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href="https://www.academia.edu/14011574/Edge_Effects_on_Species_Composition_and_Exotic_Species_Abundance_in_the_North_Carolina_Piedmont"><img alt="Research paper thumbnail of Edge Effects on Species Composition and Exotic Species Abundance in the North Carolina Piedmont" class="work-thumbnail" src="https://attachments.academia-assets.com/44707802/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011574/Edge_Effects_on_Species_Composition_and_Exotic_Species_Abundance_in_the_North_Carolina_Piedmont">Edge Effects on Species Composition and Exotic Species Abundance in the North Carolina Piedmont</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://duke.academia.edu/DeanUrban">Dean Urban</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://tnc.academia.edu/RobertMcDonald">Robert McDonald</a></span></div><div class="wp-workCard_item"><span>Biological Invasions</span><span>, 2006</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="33c7c2b35bc2bcb8516bc3d2c47033d0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707802,"asset_id":14011574,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707802/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011574"><a 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Exotic species are often increased in abundance near forest edges. This increase in abundance could be either because of the increase in resource availability near edges, or because of increased dispersal into forest edges. We measured species composition and a set of geospatial variables on transects at 66 edges in the North Carolina Piedmont in an attempt to distinguish between these two factors. Mantel tests show that species composition is significantly different in forest edges than in the forest interior, but that this effect only penetrates about 5 m into the forest. Indicator species analysis finds several species that are indicative of edge communities, including trumpet vine (Campsis radicans), two drought-tolerant oak species (Quercus stellata and Q. falcata), a serviceberry (Amelanchier arboreum), and a common exotic species, tree-ofheaven (Ailanthus altissima). Poisson regression techniques showed that in both the seedling and tree strata of the forest, exotic species increased in abundance on flat sites with a high potential seed source. Mapping predicted exotic species abundance onto the landscape. We find that large-scale variation in exotic species abundance is due mostly to variation in potential seed sources, while small-scale variation relates more to edaphic factors. Our results stress that both dispersal and environmental filters are important for determining exotic species abundance, but potentially the filters operate at different spatial scales.","publication_date":{"day":null,"month":null,"year":2006,"errors":{}},"publication_name":"Biological Invasions","grobid_abstract_attachment_id":44707802},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011574/Edge_Effects_on_Species_Composition_and_Exotic_Species_Abundance_in_the_North_Carolina_Piedmont","translated_internal_url":"","created_at":"2015-07-13T17:55:11.828-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075167,"work_id":14011574,"tagging_user_id":33044090,"tagged_user_id":158463337,"co_author_invite_id":237812,"email":"r***d@tnc.org","affiliation":"The Nature Conservancy","display_order":0,"name":"Robert McDonald","title":"Edge Effects on 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data-work-id="14011594"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011594/Focused_Assessment_of_Scale_Dependent_Vegetation_Pattern"><img alt="Research paper thumbnail of Focused Assessment of Scale-Dependent Vegetation Pattern" class="work-thumbnail" src="https://attachments.academia-assets.com/44707826/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011594/Focused_Assessment_of_Scale_Dependent_Vegetation_Pattern">Focused Assessment of Scale-Dependent Vegetation Pattern</a></div><div class="wp-workCard_item"><span>Predictive Species and Habitat Modeling in Landscape Ecology</span><span>, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span 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Mitigation in Kalimantan, Indonesia" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011593/Reconciling_Oil_Palm_Expansion_and_Climate_Change_Mitigation_in_Kalimantan_Indonesia">Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia</a></div><div class="wp-workCard_item"><span>PLOS ONE</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Our society faces the pressing challenge of increasing agricultural production while minimizing n...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s national emissions mitigation goal, while allowing oil palm area to double.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011593"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011593"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011593; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011593]").text(description); $(".js-view-count[data-work-id=14011593]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011593; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011593']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011593, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011593]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011593,"title":"Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia","translated_title":"","metadata":{"abstract":"Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s national emissions mitigation goal, while allowing oil palm area to double.","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"PLOS ONE"},"translated_abstract":"Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia\u0026amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s national emissions mitigation goal, while allowing oil palm area to double.","internal_url":"https://www.academia.edu/14011593/Reconciling_Oil_Palm_Expansion_and_Climate_Change_Mitigation_in_Kalimantan_Indonesia","translated_internal_url":"","created_at":"2015-07-13T17:55:13.409-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075158,"work_id":14011593,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":780009,"email":"j***t@duke.edu","display_order":0,"name":"Jeffrey Vincent","title":"Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan, Indonesia"},{"id":3075192,"work_id":14011593,"tagging_user_id":33044090,"tagged_user_id":32982424,"co_author_invite_id":null,"email":"p***9@duke.edu","display_order":4194304,"name":"P. 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Halpin</a></span></div><div class="wp-workCard_item"><span>Proceedings of the ninth ACM international symposium on Advances in geographic information systems - GIS '01</span><span>, 2001</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7aff9ff172842f7eef6632bc6021192e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707775,"asset_id":14011592,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707775/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Miw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011592"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011592"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011592; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011592]").text(description); $(".js-view-count[data-work-id=14011592]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011592; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011592']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011592, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7aff9ff172842f7eef6632bc6021192e" } } $('.js-work-strip[data-work-id=14011592]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011592,"title":"Flow computation on massive grids","translated_title":"","metadata":{"grobid_abstract":"As detailed terrain data becomes available, GIS applications target larger geographic areas at finer resolutions. 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Halpin</a></span></div><div class="wp-workCard_item"><span>Geoinformatica</span><span>, 2001</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">As detailed terrain data becomes available, GIS terrain applications target larger geographic are...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. Processing the massive data involved in such applications presents signicant challenges to GIS systems and demands algorithms that are optimized for both data movement and computation. 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Halpin</a></span></div><div class="wp-workCard_item"><span>Geoinformatica</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">As detailed terrain data becomes available, GIS terrain applications target larger geographic are...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. Processing the massive datasets involved in such applications presents signicant challenges to GIS systems and demands algorithms that are optimized for both data movement and computation. In this paper we present ecient algorithms for flow routing on massive grid terrain datasets, extending our previous</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5323332ec21058e73528998d114469b0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":38180219,"asset_id":14011588,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/38180219/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011588"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011588"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011588; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011588]").text(description); $(".js-view-count[data-work-id=14011588]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011588; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011588']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011588, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "5323332ec21058e73528998d114469b0" } } $('.js-work-strip[data-work-id=14011588]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011588,"title":"Efficient Flow Computation on Massive Grid Terrain Datasets","translated_title":"","metadata":{"abstract":"As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at ner resolutions. 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SCALE-SPECIFIC INFERENCE USING WAVELETS" class="work-thumbnail" src="https://attachments.academia-assets.com/44707846/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011587/SCALE_SPECIFIC_INFERENCE_USING_WAVELETS">SCALE-SPECIFIC INFERENCE USING WAVELETS</a></div><div class="wp-workCard_item"><span>Ecology</span><span>, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet eco...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. We introduce wavelet-coefficient regression, in which the dependent and independent variables are wavelet transformed prior to analysis, as a means to formalize scale-specific relationships in ecological data. We apply this</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ee1e7f84db43bf41dc0b0723d190da17" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707846,"asset_id":14011587,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707846/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011587"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011587"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011587; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011587]").text(description); $(".js-view-count[data-work-id=14011587]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011587; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011587']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011587, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ee1e7f84db43bf41dc0b0723d190da17" } } $('.js-work-strip[data-work-id=14011587]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011587,"title":"SCALE-SPECIFIC INFERENCE USING WAVELETS","translated_title":"","metadata":{"abstract":"Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011586"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011586/Potential_response_of_pacific_northwestern_forests_to_climatic_change_effects_of_stand_age_and_initial_composition"><img alt="Research paper thumbnail of Potential response of pacific northwestern forests to climatic change, effects of stand age and initial composition" class="work-thumbnail" src="https://attachments.academia-assets.com/44707813/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011586/Potential_response_of_pacific_northwestern_forests_to_climatic_change_effects_of_stand_age_and_initial_composition">Potential response of pacific northwestern forests to climatic change, effects of stand age and initial composition</a></div><div class="wp-workCard_item"><span>Climatic Change</span><span>, 1993</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We used an individual-based forest simulator (a gap model) to assess the potential effects of ant...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We used an individual-based forest simulator (a gap model) to assess the potential effects of anthropogenic climatic change on conifer forests of the Pacific Northwestern United States. Steady-state simulations suggested that forest zones could be shifted on the order of 500–1000 m in elevation, which could lead to the local extirpation of some high-altitude species. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011585"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011585/Gradient_analysis_the_next_generation_towards_more_plant_relevant_explanatory_variables"><img alt="Research paper thumbnail of Gradient analysis, the next generation: towards more plant-relevant explanatory variables" class="work-thumbnail" src="https://attachments.academia-assets.com/44707785/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011585/Gradient_analysis_the_next_generation_towards_more_plant_relevant_explanatory_variables">Gradient analysis, the next generation: towards more plant-relevant explanatory variables</a></div><div class="wp-workCard_item"><span>Canadian Journal of Forest Research-revue Canadienne De Recherche Forestiere</span><span>, 2005</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The long history of gradient analysis is anchored in the observation that species turnover can be...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. This model is unsatisfying in that elevation is not directly relevant to plants and the ubiqui- tous &quot;elevation gradient&quot; is composed of multiple intertwined environmental factors. We offer an approach to landscape- scale vegetation analysis that disentangles the elevation gradient</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="23203035350015985f1405e7ee2fc11a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707785,"asset_id":14011585,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707785/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011585"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011585"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011585; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011585]").text(description); $(".js-view-count[data-work-id=14011585]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011585; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011585']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011585, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "23203035350015985f1405e7ee2fc11a" } } $('.js-work-strip[data-work-id=14011585]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011585,"title":"Gradient analysis, the next generation: towards more plant-relevant explanatory variables","translated_title":"","metadata":{"abstract":"The long history of gradient analysis is anchored in the observation that species turnover can be described along elevation gradients. 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href="https://www.academia.edu/14011584/Forest_bird_communities_across_a_gradient_of_urban_development"><img alt="Research paper thumbnail of Forest bird communities across a gradient of urban development" class="work-thumbnail" src="https://attachments.academia-assets.com/44707788/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011584/Forest_bird_communities_across_a_gradient_of_urban_development">Forest bird communities across a gradient of urban development</a></div><div class="wp-workCard_item"><span>Urban Ecosystems</span><span>, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="66658a64740be24bb2b5223f1243af24" class="wp-workCard--action" rel="nofollow" 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We used field data and multivariate statistical techniques to examine the effects of landscape context, roads, traffic noise, and vegetation characteristics on bird community composition in the North Carolina Piedmont (U.S.A.). Landscape-level variables, particularly those related to urbanization, were most important in structuring forest bird communities. Specifically, we found that road density and amount of urban land cover were the best predictors of species composition. We found that urban and rural bird communities were quite distinct from each other. Rural communities had more longdistance migrants and forest interior species but species richness did not differ between the communities. Our results suggest some specific guidelines to target bird species of interest both inside and outside of urban areas. For example, if increasing numbers of migratory species is of primary concern, then conservation areas should be located outside of urban boundaries or in areas with low road density. However, if maximizing species richness is the focus, location of the conservation area may not be as important if the conservation area is surrounded by at least 50 m of forest habitat in all directions.","publication_date":{"day":null,"month":null,"year":2010,"errors":{}},"publication_name":"Urban 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Statistics","url":"https://www.academia.edu/Documents/in/Multivariate_Statistics"},{"id":9846,"name":"Ecology","url":"https://www.academia.edu/Documents/in/Ecology"},{"id":28849,"name":"Urban Development","url":"https://www.academia.edu/Documents/in/Urban_Development"},{"id":79495,"name":"Land Cover","url":"https://www.academia.edu/Documents/in/Land_Cover"},{"id":93353,"name":"North Carolina","url":"https://www.academia.edu/Documents/in/North_Carolina"},{"id":199046,"name":"Species Composition","url":"https://www.academia.edu/Documents/in/Species_Composition"},{"id":199056,"name":"Species Richness","url":"https://www.academia.edu/Documents/in/Species_Richness"},{"id":641190,"name":"Urban Ecosystems","url":"https://www.academia.edu/Documents/in/Urban_Ecosystems"},{"id":653722,"name":"Rural Community","url":"https://www.academia.edu/Documents/in/Rural_Community"},{"id":843856,"name":"Ecological 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class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011583/A_simple_method_for_estimating_potential_relative_radiation_PRR_for_landscape_scale_vegetation_analysis"><img alt="Research paper thumbnail of A simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/44707786/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011583/A_simple_method_for_estimating_potential_relative_radiation_PRR_for_landscape_scale_vegetation_analysis">A simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis</a></div><div class="wp-workCard_item"><span>Landscape Ecology</span><span>, 2005</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="72f39d6c9a9fa3a3d570f919234125b0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707786,"asset_id":14011583,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707786/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011583"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011583"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011583; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011583]").text(description); $(".js-view-count[data-work-id=14011583]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011583; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011583']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + 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WowProfile.WorkStripView({ el: this, workJSON: {"id":14011583,"title":"A simple method for estimating potential relative radiation (PRR) for landscape-scale vegetation analysis","translated_title":"","metadata":{"grobid_abstract":"Radiation is one of the primary influences on vegetation composition and spatial pattern. Topographic orientation is often used as a proxy for relative radiation load due to its effects on evaporative demand and local temperature. Common methods for incorporating this information (i.e., site measures of slope and aspect) fail to include daily or annual changes in solar orientation and shading effects from local topography. As a result, these static measures do not incorporate the level of spatial and temporal heterogeneity required to examine vegetation patterns at the landscape level. We developed a widely applicable method for estimating potential relative radiation (PRR) using digital elevation data and a widely used geographic information system (Arc/Info). We found significant differences among four increasingly comprehensive radiation proxies. Our GIS-based proxy compared well with estimates from more data-intensive and computationally rigorous radiation models. We note that several recent studies have not found strong correlations between vegetation pattern and landscape-scale differences in radiation. We suggest that these findings may be due to the use of proxies that were not accurately capturing variability in radiation, and we recommend PRR or similar measures for use in future vegetation analyses.","publication_date":{"day":null,"month":null,"year":2005,"errors":{}},"publication_name":"Landscape Ecology","grobid_abstract_attachment_id":44707786},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011583/A_simple_method_for_estimating_potential_relative_radiation_PRR_for_landscape_scale_vegetation_analysis","translated_internal_url":"","created_at":"2015-07-13T17:55:12.546-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075149,"work_id":14011583,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":560433,"email":"t***l@al.umces.edu","display_order":0,"name":"Todd Lookingbill","title":"A simple method for estimating 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class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011582/Semivariograms_from_a_forest_transect_gap_model_compared_with_remotely_sensed_data">Semivariograms from a forest transect gap model compared with remotely sensed data</a></div><div class="wp-workCard_item"><span>Journal of Vegetation Science</span><span>, 1992</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Page 1. - Semivariograms from a gap model compared with remotely sensed data-521 Semivariograms f...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Page 1. - Semivariograms from a gap model compared with remotely sensed data-521 Semivariograms from a forest transect gap model compared with remotely sensed data Weishampel, John F.1*, Urban, Dean L.1,2, Shugart, Herman H.1 &amp; Smith, Jackson B. Jr. 1 ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011582"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011582"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011582; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011582]").text(description); $(".js-view-count[data-work-id=14011582]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011582; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011582']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011582, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011582]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011582,"title":"Semivariograms from a forest transect gap model compared with remotely sensed data","translated_title":"","metadata":{"abstract":"Page 1. - Semivariograms from a gap model compared with remotely sensed data-521 Semivariograms from a forest transect gap model compared with remotely sensed data Weishampel, John F.1*, Urban, Dean L.1,2, Shugart, Herman H.1 \u0026amp; Smith, Jackson B. Jr. 1 ...","publication_date":{"day":null,"month":null,"year":1992,"errors":{}},"publication_name":"Journal of Vegetation Science"},"translated_abstract":"Page 1. - Semivariograms from a gap model compared with remotely sensed data-521 Semivariograms from a forest transect gap model compared with remotely sensed data Weishampel, John F.1*, Urban, Dean L.1,2, Shugart, Herman H.1 \u0026amp; Smith, Jackson B. Jr. 1 ...","internal_url":"https://www.academia.edu/14011582/Semivariograms_from_a_forest_transect_gap_model_compared_with_remotely_sensed_data","translated_internal_url":"","created_at":"2015-07-13T17:55:12.470-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Semivariograms_from_a_forest_transect_gap_model_compared_with_remotely_sensed_data","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean Urban","url":"https://duke.academia.edu/DeanUrban"},"attachments":[],"research_interests":[{"id":5541,"name":"Plant Biology","url":"https://www.academia.edu/Documents/in/Plant_Biology"},{"id":9846,"name":"Ecology","url":"https://www.academia.edu/Documents/in/Ecology"},{"id":113117,"name":"Scale","url":"https://www.academia.edu/Documents/in/Scale"},{"id":118805,"name":"Succession","url":"https://www.academia.edu/Documents/in/Succession"},{"id":224636,"name":"Vegetation","url":"https://www.academia.edu/Documents/in/Vegetation"},{"id":253853,"name":"Vegetation Science","url":"https://www.academia.edu/Documents/in/Vegetation_Science"},{"id":317638,"name":"Forestry Sciences","url":"https://www.academia.edu/Documents/in/Forestry_Sciences"},{"id":574000,"name":"THERMAL INFRARED REMOTE SENSING DATA","url":"https://www.academia.edu/Documents/in/THERMAL_INFRARED_REMOTE_SENSING_DATA"}],"urls":[]}, dispatcherData: dispatcherData }); 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We present a multi-scale, comparative analysis to examine how risk factors change over spatial scales and to evaluate the consistency in risk factors associated with three major wind events: a North Carolina Piedmont tornado of 1988, Hurricane Hugo of 1989 and Hurricane Fran of 1996. Our results reveal that the risk factors that best explain variation in damage vary with scale of observation. Tree size and species explain damage variation at the stand scale; topographic, site and stand factors explain damage variation at the landscape scale and wind speed and precipitation explain damage variation at the regional scale. However, it is possible to integrate these factors by incorporating factors from the fi ner scales into coarser-scale studies. We also found distinct differences in the damage caused by the hurricanes relative to the tornado, and to some extent consistency between hurricanes.","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"Forestry","grobid_abstract_attachment_id":44707818},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011581/Tree_damage_risk_factors_associated_with_large_infrequent_wind_disturbances_of_Carolina_forests","translated_internal_url":"","created_at":"2015-07-13T17:55:12.379-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075160,"work_id":14011581,"tagging_user_id":33044090,"tagged_user_id":34111085,"co_author_invite_id":780011,"email":"w***i@tamuk.edu","display_order":0,"name":"Weimin Xi","title":"Tree damage risk factors associated with large, infrequent wind disturbances of Carolina forests"},{"id":3075162,"work_id":14011581,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":629793,"email":"j***e@ua.edu","display_order":4194304,"name":"Jamie Decoster","title":"Tree damage risk factors associated with large, infrequent wind disturbances of Carolina forests"}],"downloadable_attachments":[{"id":44707818,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/44707818/thumbnails/1.jpg","file_name":"Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l.pdf","download_url":"https://www.academia.edu/attachments/44707818/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Tree_damage_risk_factors_associated_with.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/44707818/Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l-libre.pdf?1460582945=\u0026response-content-disposition=attachment%3B+filename%3DTree_damage_risk_factors_associated_with.pdf\u0026Expires=1732755393\u0026Signature=Ii7QqIx6R20BjJPu-OQpBQh5PjrBg0V3kTZqSdo255VWG27qhhvCDr8RRAVDplTNxtiVjRoQVFwr5W5LSXrkU3SNcRbTIQ7~OoyXLPcWLGrRA9CHXTPAT8LiWVcQwftUm90AERsymzxSvedqqxq7Vdm~WFjlc7iDzbN52RETpvcLOQFykLPEb-tWbxH7qKMeNCTZgSmRJ2D-F86rlVo63T7QVb0iBygHhBOiPl5YmO5i-tQ21hQh5E27aau7Y9KdFGU31jKGx4nPjPeJc1iRe7NNXlqP4c6EfY6GYpbMksKxa3XmO~3iJxDayd-VMH8Gc1lhBSCL4uYs2ffVzZu~jA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Tree_damage_risk_factors_associated_with_large_infrequent_wind_disturbances_of_Carolina_forests","translated_slug":"","page_count":18,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean Urban","url":"https://duke.academia.edu/DeanUrban"},"attachments":[{"id":44707818,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/44707818/thumbnails/1.jpg","file_name":"Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l.pdf","download_url":"https://www.academia.edu/attachments/44707818/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Tree_damage_risk_factors_associated_with.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/44707818/Tree_damage_risk_factors_associated_with20160413-14738-ur5m2l-libre.pdf?1460582945=\u0026response-content-disposition=attachment%3B+filename%3DTree_damage_risk_factors_associated_with.pdf\u0026Expires=1732755393\u0026Signature=Ii7QqIx6R20BjJPu-OQpBQh5PjrBg0V3kTZqSdo255VWG27qhhvCDr8RRAVDplTNxtiVjRoQVFwr5W5LSXrkU3SNcRbTIQ7~OoyXLPcWLGrRA9CHXTPAT8LiWVcQwftUm90AERsymzxSvedqqxq7Vdm~WFjlc7iDzbN52RETpvcLOQFykLPEb-tWbxH7qKMeNCTZgSmRJ2D-F86rlVo63T7QVb0iBygHhBOiPl5YmO5i-tQ21hQh5E27aau7Y9KdFGU31jKGx4nPjPeJc1iRe7NNXlqP4c6EfY6GYpbMksKxa3XmO~3iJxDayd-VMH8Gc1lhBSCL4uYs2ffVzZu~jA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":1041,"name":"Forestry","url":"https://www.academia.edu/Documents/in/Forestry"},{"id":93353,"name":"North Carolina","url":"https://www.academia.edu/Documents/in/North_Carolina"},{"id":152553,"name":"Comparative Analysis","url":"https://www.academia.edu/Documents/in/Comparative_Analysis"},{"id":161954,"name":"Regional scale","url":"https://www.academia.edu/Documents/in/Regional_scale"},{"id":171338,"name":"Spatial Scale","url":"https://www.academia.edu/Documents/in/Spatial_Scale"},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors"},{"id":317638,"name":"Forestry Sciences","url":"https://www.academia.edu/Documents/in/Forestry_Sciences"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1"},{"id":755542,"name":"Wind Speed","url":"https://www.academia.edu/Documents/in/Wind_Speed"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="14011580"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011580/Graph_models_of_habitat_mosaics"><img alt="Research paper thumbnail of Graph models of habitat mosaics" class="work-thumbnail" src="https://attachments.academia-assets.com/44707824/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011580/Graph_models_of_habitat_mosaics">Graph models of habitat mosaics</a></div><div class="wp-workCard_item"><span>Ecology Letters</span><span>, 2009</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7b98da6f8343cc43d5e58da2903df1d4" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707824,"asset_id":14011580,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707824/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011580"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011580"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011580; 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Recently, network applications have erupted in many fields, and graph models are now being applied in landscape ecology and conservation biology, particularly for applications couched in metapopulation theory. In these applications, graph nodes represent habitat patches or local populations and links indicate functional connections among populations (i.e. via dispersal). Graphs are models of more complicated real systems, and so it is appropriate to review these applications from the perspective of modelling in general. Here we review recent applications of network theory to habitat patches in landscape mosaics. We consider (1) the conceptual model underlying these applications;","publication_date":{"day":null,"month":null,"year":2009,"errors":{}},"publication_name":"Ecology Letters","grobid_abstract_attachment_id":44707824},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011580/Graph_models_of_habitat_mosaics","translated_internal_url":"","created_at":"2015-07-13T17:55:12.297-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075172,"work_id":14011580,"tagging_user_id":33044090,"tagged_user_id":28511454,"co_author_invite_id":null,"email":"e***l@unimelb.edu.au","display_order":0,"name":"Eric Anton Treml","title":"Graph models of habitat mosaics"},{"id":3075203,"work_id":14011580,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":780019,"email":"r***0@duke.edu","display_order":6291456,"name":"Robert Schick","title":"Graph 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data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/14011579/Forest_ecosystem_dynamics_linking_forest_succession_soil_process_and_radiation_models"><img alt="Research paper thumbnail of Forest ecosystem dynamics: linking forest succession, soil process and radiation models" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011579/Forest_ecosystem_dynamics_linking_forest_succession_soil_process_and_radiation_models">Forest ecosystem dynamics: linking forest succession, soil process and radiation models</a></div><div class="wp-workCard_item"><span>Ecological Modelling</span><span>, 1993</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011579"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011579"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011579; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011579]").text(description); $(".js-view-count[data-work-id=14011579]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011579; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011579']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011579, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 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structure-ecosystem process interactions across sites and ecosystems</a></div><div class="wp-workCard_item"><span>Ecological Modelling</span><span>, 1993</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT We describe an approach to investigating and understanding the interactions between vege...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT We describe an approach to investigating and understanding the interactions between vegetation structure and ecosystem processes that uses simulation models as a framework for comparison and synthesis across ecosystems arrayed along environmental gradients. The models are individual-based vegetation simulators and compartment models of nutrient cycling and soil water relations. Applications focus on interactions and feedbacks between vegetation structure (species composition, size structure) and ecosystem processes (water balance, nutrient cycling), and how these relationships vary across environmental gradients. Preliminary results indicate that life-history traits of plants have a profound influence on system-level behaviors, and that differences between grasslands and forests can be attributed largely to contrasting traits of grasses and trees. Experiments with linked vegetation-ecosystem process models diverge from simulations with either model run independently, suggesting the importance of feedbacks between details of vegetation pattern and ecosystem processes. The development of a fully coupled vegetation-ecosystem process model that is sufficiently general to simulate systems dominated by multiple lifeforms presents several conceptual, logistical, and scaling challenges, but also provides for new opportunities in ecosystem theory.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="14011578"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="14011578"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14011578; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14011578]").text(description); $(".js-view-count[data-work-id=14011578]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14011578; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='14011578']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 14011578, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=14011578]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":14011578,"title":"Modeling vegetation structure-ecosystem process interactions across sites and ecosystems","translated_title":"","metadata":{"abstract":"ABSTRACT We describe an approach to investigating and understanding the interactions between vegetation structure and ecosystem processes that uses simulation models as a framework for comparison and synthesis across ecosystems arrayed along environmental gradients. 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Applications focus on interactions and feedbacks between vegetation structure (species composition, size structure) and ecosystem processes (water balance, nutrient cycling), and how these relationships vary across environmental gradients. Preliminary results indicate that life-history traits of plants have a profound influence on system-level behaviors, and that differences between grasslands and forests can be attributed largely to contrasting traits of grasses and trees. Experiments with linked vegetation-ecosystem process models diverge from simulations with either model run independently, suggesting the importance of feedbacks between details of vegetation pattern and ecosystem processes. 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This patch transition model utilizes functional roles instead of species. The roles or types are based on the regeneration and mortality characteristics of tree species; specifically, the requirements of canopy gaps for regeneration and the capacity to create canopy gaps upon death. A gap-size plot can be assigned to each of a set of states defined according to dominance of one of the roles. Transition probabilities among these states and mean holding times in each transition lead to semi-Markovian analytical calculations of the stationary state probabilities. Forest dynamics, as the proportions of total canopy space occupied by each role in a collection of gap-size plots, can be analyzed and simulated using a chain of first-order differential equations to emulate the distributed time-delays. Additional fixed time-delays in the transition of every pair of states is also included to account for long latencies. In addition to simplifying the simulations, the resulting model can also utilize available results of the theory of semi-Markov processes; and therefore, can provide analytical guidance to the simulations, the feasibility of direct exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can especially be useful in the simulation of landscape dynamics and species-rich tropical forests.","publication_date":{"day":null,"month":null,"year":1996,"errors":{}},"publication_name":"Ecological Modelling","grobid_abstract_attachment_id":44707794},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011577/Models_of_forest_dynamics_based_on_roles_of_tree_species","translated_internal_url":"","created_at":"2015-07-13T17:55:12.086-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":3075207,"work_id":14011577,"tagging_user_id":33044090,"tagged_user_id":null,"co_author_invite_id":780022,"email":"m***o@usdoj.gov","display_order":0,"name":"M. 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However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.","publication_date":{"day":null,"month":null,"year":2007,"errors":{}},"publication_name":"Ecological Applications","grobid_abstract_attachment_id":44707776},"translated_abstract":null,"internal_url":"https://www.academia.edu/14011576/GRAPH_THEORY_AS_A_PROXY_FOR_SPATIALLY_EXPLICIT_POPULATION_MODELS_IN_CONSERVATION_PLANNING","translated_internal_url":"","created_at":"2015-07-13T17:55:12.005-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":33044090,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":44707776,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/44707776/thumbnails/1.jpg","file_name":"minor_urban_2007.pdf","download_url":"https://www.academia.edu/attachments/44707776/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"GRAPH_THEORY_AS_A_PROXY_FOR_SPATIALLY_EX.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/44707776/minor_urban_2007-libre.pdf?1460582945=\u0026response-content-disposition=attachment%3B+filename%3DGRAPH_THEORY_AS_A_PROXY_FOR_SPATIALLY_EX.pdf\u0026Expires=1732755393\u0026Signature=D1Kie8~RBvVCEXsTBmIHGfA7BQ~R6meaIsiX7EdnTimO9LVBtZwlj3rpSI2o~4bXp-5H3Wj4rLFLNt0vR0F-bBvxV~E7ppk~sLNsFSNvX1ZeL5B-gdhqTfUJYMITfbXr-WfRNFeLYmueYgWlj9lVAxrnpww~IsP3kNDY0XSukiMafHQKkpxJUCalqBZYRa6EgcisiJzeFnO0C2dT1yHCHiyMTxnmtfJYwWGuG7rrzmZC2e1~yAD5BvUmmovdGSP-GagYaOFP1~ns38B1KS28VvwRn6ahX2Dps2xYbO3LCfN-WAD3tdOApJzz6YRNvaHj~i~8WdIOD4x~7Xb4YsI4LA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"GRAPH_THEORY_AS_A_PROXY_FOR_SPATIALLY_EXPLICIT_POPULATION_MODELS_IN_CONSERVATION_PLANNING","translated_slug":"","page_count":12,"language":"en","content_type":"Work","owner":{"id":33044090,"first_name":"Dean","middle_initials":null,"last_name":"Urban","page_name":"DeanUrban","domain_name":"duke","created_at":"2015-07-13T17:54:01.185-07:00","display_name":"Dean 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Ecology","url":"https://www.academia.edu/Documents/in/Landscape_Ecology"},{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms"},{"id":2616,"name":"Graph Theory","url":"https://www.academia.edu/Documents/in/Graph_Theory"},{"id":11417,"name":"Population Dynamics","url":"https://www.academia.edu/Documents/in/Population_Dynamics"},{"id":30491,"name":"Conservation planning","url":"https://www.academia.edu/Documents/in/Conservation_planning"},{"id":47884,"name":"Biological Sciences","url":"https://www.academia.edu/Documents/in/Biological_Sciences"},{"id":58054,"name":"Environmental Sciences","url":"https://www.academia.edu/Documents/in/Environmental_Sciences"},{"id":78719,"name":"Spatial Heterogeneity","url":"https://www.academia.edu/Documents/in/Spatial_Heterogeneity"},{"id":149059,"name":"Efficient Algorithm for ECG Coding","url":"https://www.academia.edu/Documents/in/Efficient_Algorithm_for_ECG_Coding"},{"id":162645,"name":"Population 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href="https://www.academia.edu/14011575/A_Graph_Theory_Framework_for_Evaluating_Landscape_Connectivity_and_Conservation_Planning">A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning</a></div><div class="wp-workCard_item"><span>Conservation Biology</span><span>, 2008</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="789f6170d30e87e4d520aa9082da9231" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707803,"asset_id":14011575,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707803/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span 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We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). . We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"Conservation 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href="https://www.academia.edu/14011574/Edge_Effects_on_Species_Composition_and_Exotic_Species_Abundance_in_the_North_Carolina_Piedmont"><img alt="Research paper thumbnail of Edge Effects on Species Composition and Exotic Species Abundance in the North Carolina Piedmont" class="work-thumbnail" src="https://attachments.academia-assets.com/44707802/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/14011574/Edge_Effects_on_Species_Composition_and_Exotic_Species_Abundance_in_the_North_Carolina_Piedmont">Edge Effects on Species Composition and Exotic Species Abundance in the North Carolina Piedmont</a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://duke.academia.edu/DeanUrban">Dean Urban</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://tnc.academia.edu/RobertMcDonald">Robert McDonald</a></span></div><div class="wp-workCard_item"><span>Biological Invasions</span><span>, 2006</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="33c7c2b35bc2bcb8516bc3d2c47033d0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":44707802,"asset_id":14011574,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/44707802/download_file?st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&st=MTczMjc1MTc5Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" 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Exotic species are often increased in abundance near forest edges. This increase in abundance could be either because of the increase in resource availability near edges, or because of increased dispersal into forest edges. We measured species composition and a set of geospatial variables on transects at 66 edges in the North Carolina Piedmont in an attempt to distinguish between these two factors. Mantel tests show that species composition is significantly different in forest edges than in the forest interior, but that this effect only penetrates about 5 m into the forest. Indicator species analysis finds several species that are indicative of edge communities, including trumpet vine (Campsis radicans), two drought-tolerant oak species (Quercus stellata and Q. falcata), a serviceberry (Amelanchier arboreum), and a common exotic species, tree-ofheaven (Ailanthus altissima). Poisson regression techniques showed that in both the seedling and tree strata of the forest, exotic species increased in abundance on flat sites with a high potential seed source. Mapping predicted exotic species abundance onto the landscape. We find that large-scale variation in exotic species abundance is due mostly to variation in potential seed sources, while small-scale variation relates more to edaphic factors. 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