蒙古栎低质林改造后2010—2023年林地土壤质量的综合评价及未来6a土壤质量变化趋势预测——以2009年改造的蒙古栎低质林为例  

Comprehensive Evaluation of Soil Quality in Quercus mongolica Low-Quality Forests from 2010 to 2023 after Transformation and Prediction of Future 6-Year Variation Trends in Soil Quality:A Case of Quercus mongolica Low-Quality Forests Transformed in 2009

作　　者：刘慧[1] 董希斌[1] 张佳旺 郭奔 滕弛 宋梓恺 张雨晨 Liu Hui;Dong Xibin;Zhang Jiawang;Guo Ben;Teng Chi;Song Zikai;Zhang Yuchen(Forest Sustainable Management and Environmental Microbial Engineering of Key Laboratory of Heilongjiang Province(Northeast Forestry University),Harbin 150000,P.R.China)

机构地区：[1]森林持续经营与环境微生物工程黑龙江省重点实验室(东北林业大学),哈尔滨150000

出　　处：《东北林业大学学报》2024年第6期106-113,128,共9页Journal of Northeast Forestry University

基　　金：国家重点研发计划(2022YFD2201001)。

摘　　要：在黑龙江省大兴安岭林区的加格达奇林业局翠峰林场174林班,以蒙古栎(Quercus mongolica)低质林为例,2009年进行不同采伐带宽度的顺山皆伐,每条采伐带设置在近似相同海拔高度,皆伐带带长均为300 m,带宽分别为6、10、14、18 m,采伐后在每种采伐带分别补植了西伯利亚红松(Pinus sibirica)、兴安落叶松(Larix gmelinii)、樟子松(Pinus sylvestris),共设置12个不同改造样地;2010—2023年,测定12个不同改造样地的7个土壤养分指标(有机质质量分数、全氮质量分数、全磷质量分数、全钾质量分数、速效氮质量分数、速效磷质量分数、速效钾质量分数),应用模糊综合评价法、主成分分析法对土壤质量进行综合评价;结合2010—2023年对样地土壤养分质量评价结果,采用非线性自回归外部输入(NARX)神经网络模型预测2024—2029年各样地的土壤养分质量状况,分析未来6 a土壤养分质量变化趋势。结果表明:2023年测定的改造样地的土壤养分质量,91.67%的改造样地满足功能标准。补植樟子松样地中,只有采伐宽度为14 m的样地土壤养分质量相对稳定,其他采伐宽度的样地土壤养分质量状态不稳定。在2024—2029年,除了采伐宽度为10、18 m宽带中补植樟子松的样地以及采伐宽度为14 m宽带中补植西伯利亚红松的样地土壤养分不稳定外,其他样地未来6 a总体看土壤养分质量均较好,为Ⅰ级。构建的评价模型框架,可为低质林改造样地土壤养分质量综合评价及预测提供技术支持,弥补了土壤观测的数据盲区。In the 174 forest class of Cuifeng Forest Farm of the Jagdaqi Forestry Bureau in the Greater Khingan Mountains Forestry Area of Heilongjiang Province,taking the low-quality Quercus mongolica forests as an example,in 2009,clear-cutting along the mountain with different logging zone widths was carried out,each logging zone was set at approximately the similar altitude,the length of the clear-cutting zone was 300 m,and the width was 6,10,14 and 18 m respectively.Following logging,Pinus sibirica,Larix gmelinii,and Pinus sylvestris were replanted in each logging strip,creating a total of 12 different transformed sites.From 2010 to 2023,seven soil nutrient indicators(organic matter content,total nitrogen content,total phosphorus content,total potassium content,available nitrogen content,available phosphorus content,and available potassium content)of the 12 transformed sites were measured.A comprehensive evaluation of soil quality was conducted using the fuzzy comprehensive evaluation method and principal component analysis.By combining the assessment results of soil nutrient quality from 2010 to 2023,a Nonlinear Autoregressive with External Inputs(NARX)neural network model was utilized to predict the soil nutrient quality status of each site from 2024 to 2029 and analyze the future 6-year trends in soil nutrient quality.The results showed that 91.67%of the soil nutrient quality of the transformed sites measured in 2023 met the functional criteria.Among the replanted P.sylvestris sites,only the site with a logging width of 14 m demonstrated relatively stable soil nutrient quality,while the others showed unstable soil nutrient conditions.From 2024 to 2029,except for the sites with P.sylvestris replanted in the 10 m and 18 m wide logging strips,and P.sibirica replanted in the 14 m wide logging strip,which exhibited unstable soil nutrient status,overall soil nutrient quality of the sites in the forthcoming 6 years was relatively good,classified as Class I.The framework of the evaluation model provides technical support for

关 键 词：蒙古栎 低质林改造 土壤养分 

分 类 号：S714.2[农业科学—林学] S756.5