Journal of Northwest Forestry University, Volume. 40, Issue 4, 147(2025)

Robinia pseudoacacia Biomass Model in the Coastal Area of Qinhuangdao City

WEN Jialu1, ZHANG Chunxue1, MU Liqiang1、*, ZHAO Zhongbao2,3, and MA Hedan4
Author Affiliations
  • 1College of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, China
  • 2Department of Ecology, Hebei University of Environmental Engineering, Qinhuangdao 066102, Hebei, China
  • 3Hebei Key Laboratory of Agroecological Safety, Hebei University of Environmental Engineering, Qinhuangdao 066102, Hebei, China
  • 4Qinhuangdao Beidaihe New District Tuanlin Forest Farm, Qinhuangdao 066607, Hebei, China
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    Based on the measured biomass data of 40 Robinia pseudoacacia in the coastal forest areas of Qinhuangdao City, a single-tree biomass model was established, and the nonlinear measurement error model was used to establish the univariate and bivariate compatible biomass model of Robinia pseudoacacia. To eliminate heteroscedasticity, logarithmic transformation and weighted regression methods were applied. The accuracy of the model was tested by the determination coefficient (R2), standard deviation of the estimated value (SEE), total relative error (TRE), mean systematic error (MSE), mean prediction error (MPE) and mean percentage standard error (MPSE). The results showed that the parameters of the univariate model and bivariate model independent biomass models were stable and had good applicability, the determination coefficient (R2) was above 0.8, the total relative error (TRE), mean systematic error (MSE) and MSE were stable in a certain range, and the average predicted accuracy of the model was above 90%. The accuracy of the two models was the highest in the overall part and the lowest in the crown part. The test results of the univariate and bivariate compatible models were similar to the test results of the independent model, and the fitting effect, predicted accuracy and accuracy of the model were improved compared with the independent model. After comparing the independent model and the compatible model, the bivariate compatible model was selected as the optimal model, and considering the difficulty of variable measurement in field survey, the univariate compatible biomass model should be established with DBH as the variable in the future research of Robinia pseudoacacia biomass data. The results can provide reference for the accounting of Robinia pseudoacacia biomass and carbon storage in the coastal area of Hebei Province.

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    WEN Jialu, ZHANG Chunxue, MU Liqiang, ZHAO Zhongbao, MA Hedan. Robinia pseudoacacia Biomass Model in the Coastal Area of Qinhuangdao City[J]. Journal of Northwest Forestry University, 2025, 40(4): 147

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    Paper Information

    Received: May. 25, 2024

    Accepted: Sep. 12, 2025

    Published Online: Sep. 12, 2025

    The Author Email: MU Liqiang (mlq0417@163.com)

    DOI:10.3969/j.issn.1001-7461.2025.04.16

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