<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T18:50:09Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/72651" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/72651</identifier><datestamp>2026-06-06T01:06:05Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Richard de Neufville.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Collins, Ross D. (Ross Daniel)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Technology and Policy Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Technology and Policy Program</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="accessioned">2012-09-11T17:33:06Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2012</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2012</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/72651</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">808381900</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M. in Technology and Policy)-- Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2012.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 122-135).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Managing forest fires is a serious national problem in Portugal. Burned area has increased steadily over the past several decades, with particularly devastating years in 2003 and 2005. Ignitions also spike dramatically in summer, which greatly strains firefighting resources and leads to fires that are insufficiently extinguished and later may rekindle. The response of policymakers and fire managers to these problems has largely been to increase fire suppression capacity and technology deployment. This research asks, what are the side effects or unintended consequences of policies dedicated to large and aggressive suppression forces? Much of the previous work in forest fire management focuses on narrowly-defined, static problems solved using optimization analysis. This research uses dynamic analysis, specifically System Dynamics, to explore how self-regulating feedback loops affect the outcomes of forest fire management decisions over time. Two models are developed. The strategic model explores the dynamic between suppression and prevention expenditure and its effect on long-term burned area. The operational model explores the dynamics through which rekindled fires occur. The results from both models show that interactions between relevant social and physical systems, in the form of public or institutional pressure, can force aggressive suppression decisions into practice. Furthermore, strict adherence to these policies can trap each system in a state of long-run worse behavior due to the overwhelming effects of negative feedback loops. Policy recommendations based on the results, and informed by an in-depth analysis of relevant stakeholders and impediments to implementation, are also presented.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Ross D. Collins.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Technology and Policy</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">166 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
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copyright. They may be viewed from this source for any purpose, but &#xd;
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permission. See provided URL for inquiries about permission.</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Technology and Policy Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Forest fire management in Portugal : developing system insights through models of social and physical dynamics</dim:field>
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   	&lt;Title>Forest fire management in Portugal : developing system insights through models of social and physical dynamics&lt;/Title>
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   	&lt;PublicationDate>2012&lt;/PublicationDate>
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   	&lt;Abstract>Managing forest fires is a serious national problem in Portugal. Burned area has increased steadily over the past several decades, with particularly devastating years in 2003 and 2005. Ignitions also spike dramatically in summer, which greatly strains firefighting resources and leads to fires that are insufficiently extinguished and later may rekindle. The response of policymakers and fire managers to these problems has largely been to increase fire suppression capacity and technology deployment. This research asks, what are the side effects or unintended consequences of policies dedicated to large and aggressive suppression forces? Much of the previous work in forest fire management focuses on narrowly-defined, static problems solved using optimization analysis. This research uses dynamic analysis, specifically System Dynamics, to explore how self-regulating feedback loops affect the outcomes of forest fire management decisions over time. Two models are developed. The strategic model explores the dynamic between suppression and prevention expenditure and its effect on long-term burned area. The operational model explores the dynamics through which rekindled fires occur. The results from both models show that interactions between relevant social and physical systems, in the form of public or institutional pressure, can force aggressive suppression decisions into practice. Furthermore, strict adherence to these policies can trap each system in a state of long-run worse behavior due to the overwhelming effects of negative feedback loops. Policy recommendations based on the results, and informed by an in-depth analysis of relevant stakeholders and impediments to implementation, are also presented.&lt;/Abstract>
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