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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:Kendra Fallon Defense
X-WR-TIMEZONE:Mountain Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260617T034903Z
UID:tag:localist.com\,2008:EventInstance_51187791951533
DTSTART:20251112T220000Z
DTEND:20251113T010000Z
DESCRIPTION:Title: LEVERAGING DISPARATE WILDLAND FIRE DATASETS TO ADDRESS L
 ONGSTANDING FIRE MANAGEMENT QUESTIONS\n\nAbstract: While wildfire season i
 s perceived as occurring in the warm months\, and expanding\, wildfire man
 agement is a year-long process. Juxtaposed to wildfire seasons are the rea
 ctive seasons of mitigating for post-fire effects\, namely first-order eff
 ects of potential hydrological impacts in burn footprints\, and the proact
 ive implementation of fuels treatments to modify fire behavior to lessen t
 he reactive workload. In this dissertation\, I focus on answering lingerin
 g questions that are critical to the management of the shoulder seasons of
  wildfire season. To assist in resource allocation and identification of p
 ost-hydrological risks\, I present a model identifying the major drivers o
 f soil burn severity\, which cannot be dependably parameterized for modeli
 ng efforts using remotely sensed vegetation severity. This model is couche
 d within a larger distillation of applied fire management concepts as they
  pertain to hydrologic modeling to assist land managers\, and serves as a 
 cautionary demonstration for academic application. This dissertation also 
 presents a novel classification schema to track the compounded contributio
 ns of multiple fuels treatments on effective fire behavior modification ac
 ross a large geography\, all National Forest System lands in California. T
 he retention of past treatment combinations afforded the granularity of fi
 re-specific studies while leveraging a large amount of monitored interacti
 ons\, allowing for a substantial interaction sample size to analyze for dr
 ivers of effective fire behavior modification within treated areas. This m
 ethodology was expanded upon with statistical modeling and machine learnin
 g to evaluate the strength and ranking of top-down (i.e.\, weather and cli
 mate) variables and bottom-up (e.g.\, topography\, vegetation\, treatment)
  in fire behavior modification. Given the projected increase in wildland f
 ire acres and severity predicted across a majority of the Western United S
 tates\, it is imperative that land managers have tools to move from a reac
 tive to a proactive management stance. This pivot will not happen fast\; h
 owever\, understanding how to effectively increase and maintain treated ac
 res will afford great dividends over time in reducing undesirable wildfire
  effects.\n\nCommittee: Megan Cattau\, Moji Sadegh\, Stephanie Lenhart\, a
 nd Jim McNamara
GEO:43.600767;-116.199525
LOCATION:Micron Center for Materials Research (MCMR)\, 106
SUMMARY:Kendra Fallon Defense
URL;VALUE=URI:https://events.boisestate.edu/event/kendra-fallon-defense
CATEGORIES:Lectures and Presentations
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