Variation in Carbon Fraction, Density, and Carbon Density in Conifer Tree Tissues

Dryw Jones,Kevin O’Hara

doi:10.3390/f9070430

Abstract

We analyzed variations in three tree properties: tissue density, carbon fraction, and carbon density within bole tissues of nine Californian conifer species. Model performance for all three tree properties was significantly improved with the addition of covariates related to crown characteristics and position within the tree. This suggests that biomass and carbon mass estimates that rely on fixed wood density and carbon fraction may be inaccurate across tree sizes. We found a significant negative relationship between tissue density and carbon fraction within tree bole tissues, indicating that multiplying biomass by an average carbon fraction to obtain carbon mass is likely to lead to inaccurate estimates. Measured carbon fractions in tree tissues deviated from the widely used 0.5 value from a low of 1.4% to a high of 17.6%. Carbon fraction model parameters indicate the potential for an additional deviation from this 0.5 value of up to 2.7% due to the interaction between relative height and wood density. Applying measured carbon fractions to whole bole biomasses resulted in carbon mass estimates as much as 10.6% greater than estimates derived using the 0.5 value. We also found a significant, though modest, improvement in carbon fraction model estimates by assigning trees to groups based on tree bark characteristics.

Highlights

Understanding where carbon is stored in forest structures is essential for accurately estimated forest carbon stocks
Our study found significant differences in measured carbon fraction values from the widely used value of 0.5 for different tissue types and for whole trees using nine western North American conifer species
Applying measured carbon fractions to biomass data resulted in estimates of whole tree bole carbon masses up to 10.6% higher than estimates that used a 0.5 carbon fraction

Summary

Introduction

Understanding where carbon is stored in forest structures is essential for accurately estimated forest carbon stocks. Accurate estimates of carbon stocks can inform climate change mitigation efforts at global scales [1] and are critical to understanding nutrient cycling as plant tissues release carbon over different lengths of time [2,3]. Because silvicultural treatments target specific stand components (e.g., thinning from below removes small trees), understanding how carbon varies between stand components is necessary in order to accurately estimate stand-level carbon impacts from a given silvicultural treatment. A species average tissue density (D) is used to convert tree bole volume into bole biomass [4,5]. Tissue density is typically calculated by dividing a sample’s oven-dry wood mass by that sample’s green wood volume. Allometric biomass models may be created from relationships between whole tree biomass and diameter at breast height (DBH), or total tree height (HT)

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Discussion

Conclusion