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Study on increment model of individual-tree diameter of Cunninghamia lanceolata in consideration of climatic factors
GUO Changyou, GUO Hongxian, WANG Baohua
JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2023, Vol. 47 ›› Issue (1) : 47-56.
PDF(5651 KB)
PDF(5651 KB)
Study on increment model of individual-tree diameter of Cunninghamia lanceolata in consideration of climatic factors
【Objective】 To accurately predict growth and formulate forest management strategies for Cunninghamia lanceolata in Hunan Province, a mixed-effects individual tree diameter increment model for Cunninghamia lanceolata was developed considering climatic factors. 【Method】 Based on the data of 3 638 observations in 73 plots from the 7th and 8th Chinese National Forest Inventory in Hunan Province, this study used the multiple stepwise regression method to introduce tree size, competition, site conditions, other stand variables, and climate factors as independent variables, and developed and evaluated four different dependent variables: i.e. 5-year diameter increment (D2-D1), the natural logarithm of 5-year diameter increment [ln(D22-D21+1)], the natural logarithm of 5-year squared diameter increment [ln(D22-D21+1)], and 5-year squared diameter increment (D22-D21). An optimal basic model was selected. A linear mixed-effects model with sample plots as random effects was then fitted. In addition, three commonly used variance functions and correlation structures were introduced to remove the heteroscedasticity of the residuals and autocorrelation. Finally, the 10-fold cross-validation method was used to assess predictive ability. 【Result】 Compared with the other three dependent variables, the model performed best with ln(D22-D21+1) as the dependent variable. Therefore, the model in which the dependent variable was ln(D22-D21+1) was selected as the optimal basic model. According to the results of the optimal basic model, the initial diameter, the ratio of the sum of the basal area of trees with diameters larger than the subject tree’s diameter to the initial diameter, stand basal area per hectare, the product of the sine of the slope and the natural logarithm of the altitude, mean annual precipitation, and mean minimum temperature in January significantly affected the increase in the diamteter of Cunninghamia lanceolata. Compared with the optimal basic model, the mixed-effects model showed a significantly improved prediction accuracy. Additionally, the introduction of variance functions and correlation structures also significantly improved the model’s performance, of which the exponent function (exponent) and ARMA(1,1) performed the best. In the 10-fold cross-validation, the mixed-effects model also showed better performance. 【Conclusion】 Climatic factors have a significant effect on the increase of diameter in Cunninghamia lanceolata. Compared with the basic model, the linear mixed-effects model with sample plots as random effects could greatly improve the model’s performance, and we hope that the model could provide support for the scientific management of Cunninghamia lanceolata in Hunan Province.
Cunninghamia lanceolata / individual-tree diameter increment / climate factor / mixed-effects model / 10-fold cross-validation
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