应用生态学报2024，Vol.35Issue(8)：2082-2090,9.DOI:10.13287/j.1001-9332.202408.006
辽东山区日本落叶松一级枝条数量及密度预估模型
Prediction model for the quantity and density of first-order branches of Larix kaempferi in eastern area of Liaoning Province,China
摘要
Abstract
As an important branch characteristic factor,the quantity of branches could influence crown structure,tree growth,and wood quality.Taking Larix kaempferi plantation in Dagujia Forest Farm,Qingyuan County,Liao-ning Province as the research object,we developed a mixed effect prediction model of the first-order branches quan-tity of L.kaempferi including sprouting branches based on the negative binomial distribution model,and a mixed effect prediction model of the first-order branches density of L.kaempferi including sprouting branches based on the negative exponential model.The results showed that the mixed effect model considering sample level as the random effect effectively decreased the heteroscedasticity and autocorrelation.The fitting goodness was better than the tradi-tional model.The quantity of the first-order branches increased with increasing crown ratio.The mixed effect model with the basic model intercept of the first-order branches quantity as the random effect parameter was determined as the optimal model,with Ra2=0.552 and the RMSE=7.242.As for the density of the first-order branches,the heteroscedasticity and autocorrelation were also reduced when the random effect was added.The density of the first-order increased with increasing crown ratio.The mixed effect model with the basic model intercept of the first-order branches density model and branch depth as random effects was determined as the optimal model,with Ra2=0.792 and the RMSE=4.447.The model for branch quantity and density of L.kaempferi constructed would lay an impor-tant foundation for making scientific forest management plans and improving wood quality.关键词
日本落叶松/枝条数量/枝条密度/混合效应Key words
Larix kaempferi/branch quantity/branch density/mixed effect引用本文复制引用
倪铭岐,高慧淋,刘家腾,佟艺玟,邱瑜,邢晖..辽东山区日本落叶松一级枝条数量及密度预估模型[J].应用生态学报,2024,35(8):2082-2090,9.基金项目
本文由"十四五"国家重点研发计划项目(2023YFD2200801)和林草科技创新发展研究项目(2023132015)资助. （2023YFD2200801）
