The effects of forest fuel reduction on fire severity and long-term carbon storage Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/0z709162d

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • Two forest management objectives being debated in the context of federally managed landscapes in the US Pacific Northwest involve a perceived trade-off between fire restoration and C sequestration. The former strategy would reduce fuel (and therefore C) that has accumulated through a century of fire suppression and exclusion that has led to extreme fire risk in some areas. The latter strategy would manage forests for enhanced C sequestration as a method of reducing atmospheric CO2 and associated threats from global climate change. We explored the tradeoff between these strategies by modeling their effects at both the stand and landscape-scale. We began with an assessment of the extent to which uncertainties in model parameter values, model structure, and field measurements can influence model performance. We adapted the generalized likelihood uncertainty estimation (GLUE) methodology for Biome-BGC, a widely used terrestrial ecosystem model. We found that the phenomenon of parameter equifinality exerted significant control on model performance, but that issues with model structure in the Biome-BGC model may present an even greater obstacle to model accuracy. We then examined the effects of fuel reduction on fire severity and the resulting long-term stand-level C storage by utilizing the STANDCARB model for three Pacific Northwest ecosystems: the east Cascades Ponderosa Pine forests, the west Cascades Western hemlock–Douglas fir forests, and the Coast Range Western hemlock– Sitka spruce forests. Finally, we then tested the extent to which various landscape-level fuel reduction treatments, when applied at various annual treatment areas, altered pyrogenic C emissions and long-term C storage in the east Cascades Ponderosa pine ecosystems. For this we employed the LANDCARB model, which models forests throughout a landscape on a stand-by-stand basis. Results from both the stand and landscape-level modeling indicate that, for fuel reduction treatments to be effective in reducing wildfire severity, they must be applied at higher frequencies and over larger areas than they are currently. Furthermore, fuel reduction treatments almost always reduce stand and landscape-level C storage, since reducing the fraction by which C is lost in a wildfire requires the removal of a much greater amount of C, since most of the C stored in forest biomass (stem wood, branches, coarse woody debris) remains unconsumed even by high-severity wildfires.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Keyword
Subject
Rights Statement
Language
Replaces
Additional Information
  • description.provenance : Submitted by Stephen Mitchell (mitchste@onid.orst.edu) on 2009-06-05T18:46:31Z No. of bitstreams: 1 Mitchell_Dissertation.pdf: 1921239 bytes, checksum: 905daca44d0ae1f724ffd8625f941ddb (MD5)
  • description.provenance : Rejected by Julie Kurtz(julie.kurtz@oregonstate.edu), reason: Rejecting because this needs to be one PDF instead of a Word document. Once revised, open the item that was rejected, replace the attached file with the revised file and resubmit. Thanks, Julie on 2009-06-05T17:31:27Z (GMT)
  • description.provenance : Submitted by Stephen Mitchell (mitchste@onid.orst.edu) on 2009-05-26T17:40:09Z No. of bitstreams: 1 Mitchell_Dissertation_FinalVersion_Edited.doc: 2743296 bytes, checksum: 600a8f806aff83c6768c872e142d71ef (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2009-06-05T19:00:39Z (GMT) No. of bitstreams: 1 Mitchell_Dissertation.pdf: 1921239 bytes, checksum: 905daca44d0ae1f724ffd8625f941ddb (MD5)
  • description.provenance : Made available in DSpace on 2009-06-08T21:59:08Z (GMT). No. of bitstreams: 1 Mitchell_Dissertation.pdf: 1921239 bytes, checksum: 905daca44d0ae1f724ffd8625f941ddb (MD5)
  • description.provenance : Approved for entry into archive by Linda Kathman(linda.kathman@oregonstate.edu) on 2009-06-08T21:59:08Z (GMT) No. of bitstreams: 1 Mitchell_Dissertation.pdf: 1921239 bytes, checksum: 905daca44d0ae1f724ffd8625f941ddb (MD5)

Relationships

In Administrative Set:
Last modified: 10/20/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items