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Developing additive systems of biomass equations for nine hardwood species in Northeast China

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We developed two additive systems of biomass equations based on diameter and tree height for nine hardwood species by SUR, and used a likelihood analysis to evaluate the model error structures.

Abstract

In this study, a total of 472 trees were harvested and measured for stem, root, branch, and foliage biomass from nine hardwood species in Northeast China. Two additive systems of biomass equations were developed, one based on tree diameter (D) only and one based on both tree diameter (D) and height (H). For each system, three constraints were set up to account for the cross-equation error correlations between four tree component biomass, two sub-total biomass, and total biomass. The model coefficients were simultaneously estimated using seemly unrelated regression (SUR). Likelihood analysis was used to verify the error structures of power functions in order to determine if logarithmic transformation should be applied on both sides of biomass equations. Jackknifing model residuals were used to validate the prediction performance of biomass equations. The results indicated that (1) stem biomass accounted for the largest proportion (62 %) of the total tree biomass; (2) the two additive systems of biomass equations obtained good model fitting and prediction, of which the model R 2 a was >0.89, and the mean absolute percent bias (MAB %) was <35 %; (3) the system of biomass equations based on both D and H significantly improved model fitting and performance, especially for total, aboveground, and stem biomass; and (4) the anti-log correction was not necessary in this study. The established additive systems of biomass equations can provide reliable and accurate estimation for individual tree biomass of the nine hardwood species in Chinese National Forest Inventory.

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Author contribution statement

Experiment design and funding: Fengri Li. Experiment layout and measurement: Lihu Dong. Data analyses and modeling: Lihu Dong and Lianjun Zhang. Manuscript writing: Lihu Dong, Lianjun Zhang and Fengri Li.

Acknowledgment

This research was financially supported by the Ministry of Science and Technology of the People’s Republic of China, Project# 2012BAD22B02 and the Scientific Research Funds for Forestry Public Welfare of China, Project# 201004026. The authors would like to thank the teachers and students of the Department of Forest Management, Northeast Forestry University (NEFU), PR China, who provided and collected the data for this study. We would like to express our appreciation to three anonymous reviewers for their constructive comments on the manuscript.

Conflict of interest

The authors declare no conflict of interests.

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Authors and Affiliations

  1. Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin, Heilongjiang, 150040, People’s Republic of China

    Lihu Dong & Fengri Li

  2. Department of Forest and Natural Resources Management, College of Environmental Science and Forestry (SUNY-ESF), State University of New York, One Forestry Drive, Syracuse, NY, 13210, USA

    Lianjun Zhang

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  1. Lihu Dong
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Correspondence to Fengri Li.

Additional information

Communicated by E. Priesack.

Appendix

Appendix

See Table 5.

Table 5 Information statistics (ΔAICC = AICcnorm − AICclogn) of likelihood analysis for the additive and multiplicative error structures
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Dong, L., Zhang, L. & Li, F. Developing additive systems of biomass equations for nine hardwood species in Northeast China. Trees 29, 1149–1163 (2015). https://doi.org/10.1007/s00468-015-1196-1

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