1
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2
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3
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4
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5
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6
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7
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- Plots in 2005
- Focus in steep canyons & ridges of TU 2
- 224 new plots
- Implemented hurricane antenna with GPS for higher precision
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8
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- High Variation:
- Topography
- Vegetation type & condition
- Potential fire behavior
- Owl habitat quality
- Owl population density
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9
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10
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- Inventory attributes of all trees, fuels, etc. in area equivalent to
25ha (62ac)
- 12,449 trees thicker than 10cm (4 inches)
- Stocking density: 585/ha (234/ac)
- Basal area: 48.0m2/ha (207 ft2/ac)
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11
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12
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13
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14
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15
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- Goal: constrain & systematize observations
- Take quantitative data
- Bridge to Lidar methods
- Western Journal of Applied Forestry (accepted)
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16
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17
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18
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- Image acquisition 2 years, overlap in TU3
- Orthorectification
- Create NDVI
- Filter to SpECDA & other interpreted layers
- Export
- Share with team
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19
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20
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21
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22
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23
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24
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25
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- Fuel models tied to Vestra vegetation polygons
- Ready for intial modeling
- Coordinating fire parameter
modeling discussion with local expertise (April 2006; Jason Moghaddas)
- Suppression levels
- Ignition coverage
- Response variables for behavior and effects
- Improvements: link fuel samples from our plots to Vestra polygons
- Create finer grain fuels and forest structure coverage (fuel models
& fuel loads) using IKONOS imagery interpretation
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26
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- Weather scenarios:
- 70th percentile (moderate)
- 97th percentile (extreme)
- Comparisons
- Pre- and post-treatment
- Different treatment options: DFPZs, Group Selections, conceptual SPLATs
- Comparison of DFPZ approach and SPLATs
- Equivalent management intensity (area)
- Iterations: Scaling up management intensity (extent treated) to find
thresholds for reducing size and severity of fire
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27
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28
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- Severity: Mortality of trees by size class and species—(e.g., how
do oaks fare?)
- Direct severity: ratio of the area of canopy fire to total fire
- Post-fire severity at landscape scale: % of forest with canopy kill
(reduction in canopy cover by size class)
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29
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30
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31
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- Tom Ford in Washington: coupling owls and fire
- Sessions integrated planning
- Wildlife habitat relationships
- Bahro’s Fireshed approach
- CWHR approach to assessing habitat
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32
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33
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34
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- Deliver SpECDA coverage to Keane’s Spotted Owl Team by May 20,
2006
- Deliver forest “landscape” (spatial description of forest
structure and composition by July 31
- Work on integrated analysis & paper in autumn
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35
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36
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37
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- Two field workers, including rehiring a former field tech as field crew
leader
- Focus on
- resampling subsets of ’03-05 data for consistency analysis
- Random sampling across TU 2-4
(background data separate from stratified random)
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38
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39
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40
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41
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42
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43
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44
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45
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46
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47
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48
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- Ladder fuel hazard is a function of…
- Clumping of low aerial fuels
- Vertical continuity of fuels
- Slope (non-linear effect)
- Vegetation type
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49
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50
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- Assess annual production of fine fuels
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51
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52
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53
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54
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- 2 field crew personnel with
a part-time supervisor
- 198 new plots inventoried (TUs 2 and 3)
- 266 plots cumulative in project (68 in 2003)
- Songbird module: rapid fuel assessments at 625 sites
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55
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- 240 field plots
- 510 songbird
observation sites
- 3000 total observations: 750 plots
- A: Highest ladder hazard: 17%
- B: 2nd: 22%
- C: 3rd: 25%
- D: Lowest (4th): 36%
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56
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- Imagery covering
TUs 2 & 3
- Imagery overlaps imagery collected in 2003
(TUs 3 & 4)
- LANDSAT imagery will be purchased in 2005 for these areas covering the
summer of 2004
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57
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- Transfer of data to databases
- Raw field data being processed and extrapolated across the landscape
- Base layers essential inputs to all modeling efforts
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58
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- 2 person field crew & part-time supervisor
- Sample plots in
TUs 2 through 4
- Target: Additional
200 forest plots
- Hundreds more
songbird observation
sites
- Visit & learn about Cone & Cottonwood Fires
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59
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- Remote sensing merged into operational GIS
- IKONOS imagery
acquisition
- LANDSAT imagery
acquired post-field
season.
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60
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- Finalize the base layers: fuels and vegetation
- Initial runs of FARSITE and FlamMap
- Initial integrated modeling runs with owl module
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61
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