Also, all the regression lines passed very nearly through the origin. For example, 

 treating all debris of age 2 years and less as one set and all debris older than 2 years 

 as another set gave the following relationships: 



AGE <2: y = -0.0245 + 0.661X (r 2 = 0.78) 



AGE >2: y = 0.303 + 0.602X (r 2 = 0.74) 



where 



y = bulk depth (inches) 



x = high intercept depth (inches). 



Variation among regression coefficients was restricted as shown by the histogram 

 of ratios of bulk depth-to-high intercept depth computed for 118 transects (fig. 5) . 

 Sixty percent of the ratios were between 0.55 and 0.75. Regression coefficients 

 pertaining to the major skidding, species, and age groups are shown in table 4. Vari- 

 ability of coefficients within slash groups is comparable to variability among slash 

 groups. Thus, the narrow range of variability and probable difficulty in establishing 

 significant differences among slash groups seems to warrant application of one rela- 

 tionship between bulk depth and high intercept depth to all slash. Combining all 

 measurements produced the regression: 



y = 0.638X 

 (s = 0.76) 



which simply states that bulk depth is 64 percent of high intercept depth. This com- 

 pares with 52 percent observed by Bevins (1976) in studying Douglas-fir and hemlock 

 slash in Washington. 



Interestingly, the finding of 64 percent is consistent with fire spread verifica- 

 tion studies (Brown 1972; Bevins 1976; Hough and Albini 1978) in which fuel bed depths 

 that were reduced by factors in the range of 0.6 to 0.7 improved fire spread predictions 

 by the Rothermel model. 



25 r 



20 



MEAN = 0. 633 

 I 



Fx 



10 



H 



0.3 



Figure 5. — Histogram of 

 regression coefficients 

 for the constrained 

 relationship between 

 bulk depth versus high 

 intercept depth deter- 

 mined for individual 

 transects. 



0.4 0.5 0.6 0.7 



BULK DEPTH / HIGH INTERCEPT DEPTH 



12 



