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    <titleInfo>
      <title>How climate, fire types and topography drive forest biomass vulnerability to fires assessed from high resolution space-for-time analysis</title>
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    <name type="personnal">
      <namePart type="family">Vallet</namePart>
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    <name type="personnal">
      <namePart type="family">Mouillot</namePart>
      <namePart type="given">Florent</namePart>
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    <abstract>Climate change is driving the expansion of fire-prone areas and the intensification of wildfire events, threatening European forests. Yet, how this shift in fire regime might be more impactful on ecosystems lacks data-driven assessments of forest ecosystem vulnerability to this disturbance. We propose a comprehensive framework for assessing forest biomass vulnerability to wildfires across France, leveraging high-resolution tree height data and Landsat-based fire history reconstruction. We developed a new mapping of forest aboveground biomass (AGB) at 10m resolution, providing detailed insights into biomass distribution across various forest types. Additionally, we compiled a new database of fire polygons in France since 1984, encompassing 1762 fires, which serves as a critical resource for time since last fire and fire characteristics. Utilizing a space-for-time approach, we characterized post-fire drivers of biomass recovery, integrating species-specific fire response traits, fire characteristics, climatic conditions, and topographic variables. Our findings reveal significant regional variations, with temperate forests exhibiting higher vulnerability due to greater biomass exposure, lower resistance, and recovery rates, with local effects of topo-climates and fire size. The high-resolution mapping of quantitative vulnerability offers a robust tool for fire risk management, emphasizing the importance of considering post-fire recovery in carbon stock assessments. This work aims to inform decision-makers and enhance fire prevention strategies, contributing to sustainable forest management under changing climate conditions.</abstract>
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    <subject>
      <topic>Vulnerability</topic>
      <topic>Aboveground biomass</topic>
      <topic>postfire dynamics</topic>
      <topic>Space-for-time</topic>
      <topic>remote sensing</topic>
      <topic>fire ecology</topic>
      <topic>GEDI</topic>
      <topic>landsat</topic>
      <topic>Forest</topic>
      <topic>Random Forest</topic>
      <topic>Driver</topic>
    </subject>
    <subject authority="local">
      <geographic>FRANCE</geographic>
    </subject>
    <classification authority="local">021</classification>
    <classification authority="local">082</classification>
    <classification authority="local">126</classification>
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      <titleInfo>
        <title>Ecological Indicators</title>
      </titleInfo>
      <part>
        <detail type="volume">
          <number>186</number>
        </detail>
        <extent unit="pages">
          <list> 114850 [22 p.]</list>
        </extent>
      </part>
      <originInfo>
        <dateIssued>2026</dateIssued>
      </originInfo>
      <identifier type="issn">1470-160X</identifier>
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    <identifier type="uri">https://www.documentation.ird.fr/hor/fdi:010097057</identifier>
    <identifier type="doi">10.1016/j.ecolind.2026.114850</identifier>
    <identifier type="issn">1470-160X</identifier>
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