Graduation Date

Spring 2017

Document Type



Master of Science degree with a major in Natural Resources, option Forestry, Watershed, & Wildland Sciences

Committee Chair Name

Dr. John-Pascal-Berrill

Committee Chair Affiliation

HSU Faculty or Staff

Second Committee Member Name

Dr. Abeer Hasan

Second Committee Member Affiliation

HSU Faculty or Staff

Third Committee Member Name

Dr. Lucy Kerhoulas

Third Committee Member Affiliation

HSU Faculty or Staff

Subject Categories





Walter A. Kast

There is a need for better understanding of how woody biomass is allocated above and belowground and how this allocation might differ among tree species. In this field of research, investigators face challenges such as the laborious task of removing trees from the soil with destructive sampling, and the cleaning, drying, and weighing of belowground biomass (BGB). Therefore, researchers and practitioners most often rely on existing models to predict BGB from easily-measurable aboveground variables such as stem diameter and height. Such models have been developed for many tree species, but commonly these models require inputs of diameter at breast height (dbh) and are not designed to make predictions for younger saplings (i.e., below 5 cm dbh). To fill knowledge gaps in young conifer BGB allocation, we studied three conifers native to the north coast of California: coast redwood (Sequoia sempervirens), coast Douglas-fir (Pseudotsuga menziesii var menziesii), and grand fir (Abies grandis). We sought to determine: (i) Does the root-to-shoot ratio differ between the three species Douglas-fir, grand fir, and coast redwood in afforestation plots? (ii) Does the root-to-shoot ratio of the three species differ according to age (i.e. sampling across a span of three years?) (iii) Does the competing flora alter the root-to-shoot ratio of any of the three species? (iv) What are the best “easily-measurable” aboveground variables to be included in prediction equations for BGB in the three tree species?

Experimental plots were planted in 2008/09, and another in 2009/10 at the L. W. Schatz Demonstration Tree Farm located in Humboldt County, CA. Five species were planted: coast redwood, coast Douglas-fir, grand fir, red alder (Alnus rubra), and black cottonwood (Populus balsamifera). Redwood, Douglas-fir, and grand fir were destructively sampled for BGB measurement. A random sample of these three species were excavated by hand, and separated into three sections: stems, roots and branches. Each species had 24 trees sampled across the 3 years of data collection for a total of 72 trees. The sapling biomass components were weighed, dried in an oven, and re-weighed to determine bone dry weight and root-to-shoot biomass ratios.

Before final root-to-shoot ratios and BGB models were created, auxiliary models were developed to predict the weight of any roots that were broken off during the excavation of the saplings. Models for severed root weight were tested against sapling height, average crown width, lower crown base height, and stem diameter. Results showed high correlation between root weight and stem diameter at ground line (caliper, mm). Exponential models made the best predictions of weight of individual pieces of broken root for all three species: Douglas-fir (R2= 0.86), grand fir (R2= 0.91), and redwood (R2= 0.79).

After missing root weights had been predicted for each broken root on the root system of each sample tree, summed, and added to the overall root mass, equations to predict BGB were developed and tested. Multivariable models were tested for all three species, but showed no statistical significance. Bivariate regressions of BGB as function of tree height (cm), average crown width (cm), lower crown base height (cm), stem diameter (mm), year, and percent cover of competing flora were tested. In species-specific bivariate regressions, tree height, average crown width, and stem diameter were all found to be statistically significant predictors of BGB for all three species. Douglas-fir BGB was best predicted with a linear model utilizing caliper as the explanatory variable (R2= 0.77). Grand fir BGB was also predicted well by a linear model with caliper as the explanatory variable (R2= 0.92). Redwood BGB exhibited an exponential relationship with caliper (R2= 0.91).

Root-to-shoot ratios for the three species averaged between 0.27 and 0.46. All variables tested for BGB were also tested as predictor of root-to-shoot ratios, however for Douglas-fir and grand fir, no significant relationships between root-to-shoot ratio and the candidate predictor variables were found. For redwood, stem diameter, average crown width, and sapling height all were significant predictors of root-to-shoot ratio. Redwood sapling height was the best predictor of root-to-shoot ratio (R2= 0.37). For all three species, ANOVA tested for differences in root-to-shoot ratios among sample ages. The youngest Douglas-fir saplings (three years old) had higher root-to-shoot ratio than the five and seven year old trees. Grand fir showed no differences in root-to-shoot ratios according to age. Redwood root-to-shoot ratios were significantly different between ages three and four, between ages four and five, and between ages four and six years old.

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