Evaluation of the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) Within the Missouri Ozarks

Evaluation of the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) Within the Missouri Ozarks
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Total Pages : 98
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ISBN-10 : OCLC:986230086
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Book Synopsis Evaluation of the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) Within the Missouri Ozarks by : Casey Ghilardi

Download or read book Evaluation of the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) Within the Missouri Ozarks written by Casey Ghilardi and published by . This book was released on 2016 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Forest Vegetation Simulator (FVS) is a stand-based, individual tree growth and yield model designed and maintained by the USDA Forest Service. It is used by land managers on public and private ownerships to simulate and compare the effects of silvicultural treatments on forest stand dynamics including tree growth, mortality, and regeneration. The Fire and Fuels Extension (FFE) of FVS is designed to simulate changes in fuel loading through time and can incorporate user-specified fuel treatments into projections. We tested whether the default model fuel loading values from two FVS variants (Central States and Southern variants) were representative of field-based fuel loads using FIA data collected in the Ozark Highland region. We also compared fuel loads projected by FVS-FFE to empirical data collected from a 14-year study examining the impact of harvesting and burning on fuel loading in the Missouri Ozarks. Preliminary findings indicate that default values for both variants were not representative of light fuels (litter, 1, and 10 hour fuels), while larger fuel classes were represented better by the Central States variant than the Southern variant. Choice of variant did not significantly change projected fuel loading for all fuel classes at the end of the 14-year simulation. Results suggest that choice of variant has little impact on short-term projections and that using observed fuel values rather than defaults can improve projection accuracy in the short-term.


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