摘要
为解决给大面积林分生物量估算提供估算模型、减少外业工作量等问题,以黄山松为研究对象,构建了兼容性林分生物量模型及全林分收获模型,采用混合蛙跳算法结合交叉建模和检验技术求解林分生物量模型参数,并确定全林分收获模型参数。结果表明,建立的兼容性林分生物量模型的平均系统误差(2.381%)、平均相对误差绝对值(7.964%)均在在±10%内、拟合效果较好,基于立地质量等级为哑变量的地位指数曲线模型、断面积模型、林分蓄积量模型等拟合效果较好、适用。与常规全林分经验收获模型相比,研究先建立可变密度林分模型,再经相对密度模型确定林分平均收获量,并编制黄山松林分生物量经验收获表。研究内容在监测森林生物量和碳储量、制定节能减排和造林计划等方面具有重要的生态环境意义。
In order to solve the problems of estimating biomass of Pinus taiwanensis stand in large area and reducing field workload,taking Pinus taiwanensis as the research object, the compatible stand biomass model and the whole stand harvesting model were constructed. The parameters of the stand biomass models were solved by the hybrid frog leaping algorithm combined with cross modeling and testing technology, and the parameters of the whole stand harvesting model were determined.The results showed that the average systematic error(2.381%) and average relative error absolute value(7.964%) of the established compatible stand biomass models were within ±10%, and the fitting effect was better. The fitting effect of the site index curve model, the basal area model and the stand volume model based on the site quality grade as dummy variable was better and applicable.Compared with the conventional stand empirical harvesting model, the variable density stand model was established, and then the average stand harvesting was determined by the relative density model. The research contents have important ecological and environmental significance in monitoring forest biomass and carbon storage, formulating energy-saving emission reduction and afforestation plan.
引文
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