JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2023, Vol. 47 ›› Issue (3): 129-136.doi: 10.12302/j.issn.1000-2006.202110024

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Construction of the stand-level biomass model of Larix olgensis plantations based on stand and topographic factors

SUN Yu(), LI Fengri, XIE Longfei, DONG Lihu()   

  1. College of Forestry, Northeast Forestry University, Harbin 150040, China
  • Received:2021-10-12 Accepted:2022-01-07 Online:2023-05-30 Published:2023-05-25
  • Contact: DONG Lihu E-mail:3057135814@qq.com;donglihu2006@163.com

Abstract:

【Objective】Larix olgensis is widely distributed in northeastern China and it is considered to be an important afforestation and timber species with advantages like the rapid growth and cold tolerance. To accurately estimate the biomass of larch plantations, an additive system of biomass equations for larch plantations was established. 【Method】This study investigated larch plantations using the forestry inventory data of 304 larch plantations in Heilongjiang Province. An additive system of biomass equations was established using the method of non-linear and seemingly uncorrelated regression and employed a leave-one-out cross method for the model validation. 【Result】The stand basal area and stand mean tree height had a significant effect on the stem, branch, foliage and root biomass, the stand age and elevation also significantly affect the stem, foliage and root biomass. The branch rate and aspect had a significant effect on branch biomass. Foliage biomass was negatively correlated with stand mean tree height, stand age and elevation, whereas stem and root biomasses were positively correlated with the explanatory variables, and branch biomass was positively correlated with stand mean tree height. In terms of the additive system of the biomass equation, the adjusted coefficients of determination ( R a d j 2) were greater than 0.94, and the root mean square error (RMSE) was small. The average bias (MPE) and average bias percentage (MPE%) were both close to 0, the fit indices were all greater than 0.93, the average absolute bias (MAE) was small, and the average absolute bias percentage (MAE%) was less than 11%. 【Conclusion】The additive biomass model of larch plantations established in this study is effective for fitting and prediction, and can be used to predict the stand-level biomass of larch plantations in Heilongjiang Province.

Key words: larch (Larix olgensis) plantation, stand-level biomass, topographic factor, seemingly uncorrelated regression, regression heteroscedasticity, additive equation

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