Developing Biomass Equations for Western Hemlock and Red Alder Trees in Western Oregon Forests

Hailemariam Temesgen,Krishna Poudel

doi:10.3390/f7040088

Abstract

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameter- and height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg.) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass equations was fitted simultaneously with a constrained seemingly unrelated regression. Additionally, a linear model that predicts total aboveground biomass as a function of DBH and height was also fitted. The predicted total biomass was then apportioned to different components according to the predicted proportions from beta, Dirichlet, and multinomial log-linear regressions. Accuracy of these methods differed between species with higher root mean squared error (RMSE) being produced in red alder trees. Within species, the accuracy of the equation for bole biomass was better than the equations for other components. None of these methods stood out as a clear winner, but the multinomial log-linear regression produced marginally better results compared to other methods in terms of RMSE, except for Western hemlock bark biomass and red alder bole and branch biomass. The equations based on a seemingly unrelated regression provided lower RMSEs for those species-component combinations.

Highlights

The U.S forest carbon inventories until 2009 were based on tree biomass estimates obtained from Jenkins et al [1] biomass equations along with sample tree measurements and forest area estimates of the U.S Forest Service’s Forest Inventory and Analysis (FIA) [2]
Current U.S official carbon inventories are based on tree biomass estimates obtained from the component ratio method (CRM) described by [3] and understory vegetation biomass estimates obtained from the Jenkins equations [4]
Even though a method that is consistently better than others is desired, none of the methods we used was a clear winner when all methods (SUR, beta, Dirichlet, is desired, none of the methods we used was a clear winner when all methods (SUR, beta, Dirichlet, and multinomial log-linear (MLL)) were compared to one another

Summary

Introduction

The U.S forest carbon inventories until 2009 were based on tree biomass estimates obtained from Jenkins et al [1] biomass equations (the Jenkins equations, hereafter) along with sample tree measurements and forest area estimates of the U.S Forest Service’s Forest Inventory and Analysis (FIA) [2]. Current U.S official carbon inventories are based on tree biomass estimates obtained from the component ratio method (CRM) described by [3] and understory vegetation biomass estimates obtained from the Jenkins equations [4]. The Jenkins equations were developed using the modified meta-analysis of the compiled diameter-based equations for total aboveground biomass (AGB). The Jenkins equation for AGB is a single entry equation that uses DBH as the only predictor of AGB. With their equation form, biomass continues to increase as diameter increases [2], does not account for the variation in stem form [5], and produces the same AGB for trees with the same DBH but different tree height

Methods

Results

Conclusion