Comparison of shrub biomass with three variables indicated a significant linear relationship between crown canopy height and biomass. A weaker but significant linear relationship was also found between basal area and biomass. No linear relationship was found between measured biomass and estimated LAI. Significant differences were found between the two study areas in terms of basal area, height, and biomass, but the relationships between the dependent and independent variables were similar on both study areas.
Linear regression analysis between height and biomass
Linear regression analysis was performed between biomass and height. Several transformations of the biomass variable were tested including, square root, cubic root, and natural log. The residual fit was best with the untransformed variable, and the R2 changed very little between transformed models, so that none of the transformations were employed in the following analysis. A significant linear relationship was found between biomass (grams) and crown canopy height, (adjusted R2= 0.46, P< 0.01, figure 2). The linear regression equation, biomass (grams) = 238.48 + 3701.36 height (meters), describes a biomass averaging 238.48 grams (standard error = 43.28 grams) for plots with stakes measuring zero crown canopy height and increasing by 3701.36 grams (standard error = 43.28 grams) per meter increase in height, for each square meter plot.
Linear regression analyses were also performed for each study site individually. Significant relationships were found between biomass and height on both sites. The linear regression for Golden Gate National Recreation Area was biomass (grams) = 303.20 + 2339.01 height (meters), with an adjusted R2 = 0.33 and P< 0.01. The linear regression equation for Point Reyes National Seashore was biomass (grams) = 950.23 + 4542.73 height (meters) with an adjusted R2 = 0.48 and P< 0.01.
Linear regression analysis between basal area and biomass
A linear regression analysis was performed between biomass and basal area (centimeters2). A significant, but weak, linear relationship was found (adjusted R2 = 0.17, P< 0.01). Linear regression analyses were also performed for each study site individually. No significant linear relationship was found between biomass and basal area on Golden Gate National Recreation Area. A significant linear relationship was found between biomass and basal area for Point Reyes National Seashore. The regression equation for Point Reyes National Seashore was biomass (grams) = 51.68 + 0.02 basal area (centimeters2) with an adjusted R2 = 0.53 and P= 0.01.
Linear regression analysis between leaf area index (LAI) and biomass
A linear regression analysis was performed for biomass versus estimated LAI. No significant linear relationship was found between estimated LAI and biomass. Linear regression analyses were also performed for each study site individually. No significant linear relationship was found for either site.
Multiple regression analysis between biomass and two independent variables
A multiple regression analysis was conducted with biomass versus height and basal area. A significant relationship was found (adjusted R2 = 0.48, P< 0.01). Multiple regression analyses were also performed for each study site individually. Significant linear relationships were found between biomass versus height and basal area on both study sites. The regression for Golden Gate National Recreation Area resulted in an adjusted R2 = 0.32 and P< 0.01. The regression statistics for Point Reyes National Seashore were adjusted R2 = 0.57 and P< 0.01. A simple linear regression model with biomass (grams) versus a unified variable, height (meters) x basal area (centimeters2), was also tested. This model indicated a significant linear relationship, but was a relatively weak predictor (adjusted R2 = 0.27, P< 0.01).