A Closer Look at the 1918 Bluejay Fire: Searching for Cruiser Bias within Recorded Fire Damage in Oregon Dry Forest Monica Seeley and Keala Hagmann (advisor) and Jerry Franklin, School of Environmental and Forest Science , University of Washington Spring 2015 IntroducSon The dry pine forest landscape has historically been one of ponderosa pine dominance with a scaVering of mixed conifer. Large and old ponderosa pine grew in clumps interspersed with open areas of grasses, shrubs (antelope biVerbrush and big sagebrush), and small trees that were kept in check by frequent low severity fires. Leaving the large ponderosa pine with their thick and fire-­‐
resistant bark relaSvely unscathed, the fire paVern pruned the forest and maintained a low-­‐density and clumped tree distribuSon, low fuel beds, and a simple canopy structure. This landscape dramaScally changed when European immigrants began seVling the west. Livestock reduced grass fuel beds with their intense grazing, and later conversion of prairies to farmland reduced places for lighSng to start a wildfire. Logging removed the largest and most fire-­‐tolerant ponderosa pine and Douglas fir trees, and the less fire-­‐tolerant grand and white fir filled the newly opened areas. Roads and railways divided the landscape and acted as firebreaks for low-­‐severity fires. These changes along with the fire suppression that conSnued from the 19th to the 20st century turned the open and ponderosa-­‐dominate forest into dense forests with a complicated canopy structure. Today, these new forests have a much higher fuel load, and therefore experience fires of higher severity. The eliminaSon of regular low severity fires has allowed firs to grow next to ponderosa pine trees, and these firs act as a ladder for the fire to reach up and become a raging crown fire. With fire suppression against increasingly severe wildfires becoming more expensive, restoraSon of forests back to their historically fire tolerant condiSons has become necessary (Hessburg 2005). Two years a]er the Bluejay fire of 1918, a Smber cruise was conducted. Stored in the Sand Point NaSonal Archive, these surveys offer a look at what forest condiSons were like a]er a large, unrepressed fire in this area of southern Oregon. Unfortunately every set of data like this is biased in someway. To beVer realize this bias, three townships of the fire were analyzed for fire damage bias according to cruiser idenSty. References Hessburg, PF, Agee, JK, Franklin, JF. 2005. Dry forests and wildland fires of the inland Northwest USA: ContrasSng the landscape ecology of the pre-­‐seVlement and modern eras. Forest Ecology and Management. doi:10.1016/j.foreco.2005.02.016 Methods Results •  The Fire Damage data was linked to the transect layer. •  The Fire Damage data was divided where it it natural broke. •  The transect was color-­‐coded by severity, light yellow being 0% fire damage, red being 100% fire damage. In the same process as the Fire Damage layer, a transect layer was color coded by the ID of the cruiser that surveyed the transect. T-­‐test: FireDamage with and w/out Cruiser Influence w/out Cruiser with Cruiser Mean 22.349% 22.678% Variance 422.319% 635.117% ObservaSon 1239 386 t stat -­‐0.233 T CriScal 2 tail 1.964 F-­‐test: FireDamage with and w/out Cruiser Influence w/out Cruiser with Cruiser Variance 422.3196 635.1173 F 0.6649 P (F<=f) one tail 1.48E-­‐07 F CriScal one tail 0.8754 •  Using the Feature to Raster Conversion and the Raster to Polygon tool, the “FireDamage” and “CruiserID” layers were converted to polygons. •  Using the Intersect tool, places where the fire damage level changed were located. (Blue) •  Using the Intersect tool, places were the cruiser switched were located. (Pink) •  LocaSons where both the fire damage level and the cruiser changed were idenSfied using the Intersect tool on the two previously created intersects. (Yellow) Using the data generated by the Intersect tool, the difference between fire damage levels were separated into two bins: one where cruiser did not change, and one where cruiser did change. A t-­‐test, F-­‐test, and ANOVA test was conducted on the two groups. Cruiser AAS AG ASH BLL CRH ELF JHS RDW W-­‐Z-­‐ Average Weighted Average Average FireDamage 19.6739 0.5263 10.28 37.8571 25.1715 15.68 5.7209 9.8988 2.5030 13.4127 14.4618 # of Transects 207 23 299 16 427 208 64 401 194 Discussion The average fire damage level between the two groups are very similar. A t-­‐test confirms this similarity. Because the t stat (-­‐0.233) is between the T criScal 2 tail values (-­‐1.964 and 1.964), we cannot reject the null hypothesis. We can conclude that the difference in the two averages from the two groups is staSsScally insignificant. The variance between the two groups was pronounced. To study it further a F-­‐test was conducted. The F value (0.664) is smaller than the F CriScal value (0.875), and therefore the null hypothesis cannot be rejected. We cannot assume the two variances are staSsScally unequal. The ANOVA test further confirms the F-­‐test, showing that among the cruisers, the fire damage recorded did not staSsScally differ between them. The results of these tests lead to the conclusion that while the variaSon of changing fire damage increases greatly when the cruiser changes, cruiser bias is not a large enough factor to significantly affect the Bluejay fire data. However, future research should invesSgate the possibility of other factors being the major game changer of the fire damage data.