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    Luo Hengchun, Zhang Chao, Wei Anchao, Lu Shuangfei. Stand average height growth model and environmental interpretation in model parameter of Pinus yunnanensis[J]. Journal of Beijing Forestry University, 2018, 40(4): 67-75. DOI: 10.13332/j.1000-1522.20170347
    Citation: Luo Hengchun, Zhang Chao, Wei Anchao, Lu Shuangfei. Stand average height growth model and environmental interpretation in model parameter of Pinus yunnanensis[J]. Journal of Beijing Forestry University, 2018, 40(4): 67-75. DOI: 10.13332/j.1000-1522.20170347

    Stand average height growth model and environmental interpretation in model parameter of Pinus yunnanensis

    • ObjectivePinus yunnanensis is the dominant species and plays an important role in southwestern China. The empirical model for growth dynamics of Pinus yunnanensis under global climate warming conditions may be provided via investigating the stand growth model and analyzing the relationship between optimal model parameters and environment impacting factors.
      MethodEvaluating the growth model of stand average height by nonlinear regression model and analyzing the relationship between the optimal model parameters and the environment impacting factors, the continuous forest inventories (CFI) data of Yunnan Province and meteorological data, as well as seven kinds of fundamental theory equations were used.
      ResultIdentifying the average stand height optimal growth model based on the adjustment R2 by fitting seven basic theoretical equations and the root mean square error (RMSE), the standardized environmental impacting factors were introduced into the parameters of the optimal growth model to explain the influence of environmental factors on the average stand height growth model. The variance analysis showed that there was a significant difference between the basic model and the modified model with introduced environmental impacting factors. The results of the study have good applicability and effects.
      Conclusion(1) Logistic model was selected from the optimal model by adjusting R2 and the minimum root means square error. The adjusted R2 was 0.616 and the minimum root mean square error was 2.328 m. (2) The best model was the one with introduced environmental factors as the different parameters, and the modified model was efficient to explain the influence of environmental factors on the average stand height growth model. The most significant increase of the model fitting precision adjustment R2 was obtained with humid index combined into the model parameters a, b, c and the increase rate was 5.375%. The lowest increase was the model when the soil thickness factor was introduced into the parameters a, b, c combination and the value was 1.938%. (3) The influence of environmental impacting factors on the height growth model was HI>MAP>ALT>ET0>MAT > WI > BT > SLO > ST. (4) The topographic/climatic factors and stand average height growth was positively or negatively correlated. The altitude in topographic factors has no significant effects on stand height growth. The effect of temperature on the stand height growth was achieved by the control of precipitation.
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