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Scientia Silvae Sinicae ›› 2022, Vol. 58 ›› Issue (10): 89-100.doi: 10.11707/j.1001-7488.20221009

• Special Issue: Forest Fire Prevention Relevant Resource Monitoring, Analysis and Management Techniques in Zhangjiakou Competition Area of the Beijing Olympic Winter Games • Previous Articles     Next Articles

Comparison of Single Tree Crown Prediction Models of Larix principis-rupprechtii and Betula platyphylla in the Core Area of the Winter Olympics in China

Xiaofang Zhang1,2,Xuzhan Guo1,2,3,Liang Hong1,2,4,Tao Chen6,Liyong Fu1,2,Huiru Zhang1,2,5,*   

  1. 1. Research Institule of Forest Resource Information Techniques, CAF Beijing 100091
    2. Key Laboratory of Forest Management and Growth Modeling, National Forestry and Grassland Administration Beijing 100091
    3. College of Computer and Information Technology, Xinyang Normal University Xinyang 464000
    4. College of Mathematics and Statistics, Xinyang Normal University Xinyang 464000
    5. Experimental Center of Forestry in North China, CAF Beijing 102300
    6. Forestry and Grassland Bureau of Chongli District, Zhangjiakou City, Hebei Province Zhangjiakou 075000
  • Received:2021-11-23 Online:2022-10-25 Published:2023-04-23
  • Contact: Huiru Zhang

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Abstract:

Objective: This study was implemented to construct a high-accuracy model of single-wood crowns of Larix principis-rupprechtii and Betula platyphylla in the core area of the Winter Olympics, and to compare the advantages and disadvantages of different models to provide theoretical supports for scientific management decisions. Method: We took 4 537 L. principis-rupprechtii trees and 2 603 B. platyphylla trees in the core area of the Winter Olympics as the research objects. Firstly, we fitted our data with 10 commonly used crown diameter models, and then selected the best performance model as the basic model for L. principis-rupprechtii and B. platyphylla, respectively. Secondly, other variables were further added as covariates to construct an improved model based on the basic model. Finally, on the basis of the improved model, the nonlinear least squares model, single-level mixed effects model, generalized additive model and group-level Bayesian model of L. principis-rupprechtii and B. platyphylla were constructed, respectively. Result: Among the 4 L. principis-rupprechtii crown models, the additive model had the highest prediction accuracy(R2_mean=0.704 3, RMSE_mean=0.512 7), and the mixed effect model among the 4 B. platyphylla crown models had the highest prediction accuracy(R2_mean =0.664 3, RMSE_mean =0.794 4). In terms of variables, the crown width of L. principis-rupprechtii and B. platyphylla both increased with the growth of the diameter at breast height. However, the crown width of L. principis-rupprechtii slowly increased with the height of the tree, and decreased with the height to crown base. The B. platyphylla crown width first decreased and then increased with the crown length ratio increasing, on the other hand, the B. platyphylla crown width fluctuated greatly under the change of stand density. When the stand density ranged from 600 to 800 hm-2, the B. platyphylla crown width decreased with larger stand density, and appropriate replanting should be carried out at this time. When the stand density was in the range of 800 to 1 000 hm-2, the B. platyphylla crown width increased with larger stand density, and an inflection point of stand density to crown curve appeared at 1 000 hm-2. Therefore, if the management purpose was to protect the environment, the stand density could be controlled at 1 000 hm-2. When the stand density was in the range of 1 000 to 1 200 hm-2, the B. platyphylla crown width decreased with larger stand density. At this time, the forest should be tended and thinned to adjust its stand density. Conclusion: The crown width of L. principis-rupprechtii in the core area of the Winter Olympics was greatly affected by the diameter at breast height, tree height and height to crown base, while the crown width of B. platyphylla was greatly affected by the diameter at breast height, crown length ratio and stand density. All in all, the performances of the group-level Bayesian model, additive model, and nonlinear mixed-effect model were better than those of the nonlinear least squares model, regardless of whether it was used to predict the crown width of L. principis-rupprechtii or B. platyphylla. When only the random effect of sample plot was added, generalized additive model and the nonlinear mixed effects model should be used first, followed by group-level Bayesian models. However, because of group-level Bayesian model's lengthy training period and sensitivity to expressions, it was recommended that it should not be developed when another model could be used instead.

Key words: crown prediction models of Larix principis-rupprechtii, crown prediction models of Betula platyphylla, nonlinear mixed effect model, group-level Bayesian model, generalized additive model, core area of the Winter Olympics

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