摘 要
本研究以杨树人工林为研究对象，旨在构建精准的生长模型并估算其碳储量，为森林碳汇功能评估提供科学依据。通过选取华北地区典型杨树人工林样地，采用固定样地连续观测法获取胸径、树高、生物量等生长数据，结合遥感影像和气象资料，运用混合效应模型和机器学习算法构建了基于环境因子的杨树生长预测模型。研究创新性地将随机森林算法与过程模型相结合，显著提高了模型的预测精度。结果表明：所构建的模型对胸径和树高的预测R²分别达到0.89和0.86，较传统方法提高15%以上；20年生杨树人工林平均碳储量为112.3 t·hm⁻²，其中地上部分占78.6%，地下部分占21.4%；林分密度和立地条件是影响碳储量的关键因素。研究首次建立了适用于区域尺度的杨树人工林碳储量估算体系，提出了基于生长阶段的碳汇管理策略。研究成果可为杨树人工林的可持续经营和碳汇功能提升提供理论支撑和技术指导，对实现碳中和目标具有重要实践意义。
关键词：杨树人工林；碳储量估算；生长预测模型
ABSTRACT
This study focuses on poplar plantations, aiming to construct precise growth models and estimate their carbon storage capacity, thereby providing a scientific basis for assessing forest carbon sequestration functions. By selecting typical poplar plantation plots in North China and employing continuous observation methods in fixed sample plots, growth data including diameter at breast height (DBH), tree height, and biomass were collected. Integrating remote sensing imagery and meteorological data, mixed-effects models and machine learning algorithms were utilized to develop growth prediction models for poplar trees based on environmental factors. The research innovatively combines the random forest algorithm with process-based models, significantly enhancing the predictive accuracy of the models. The results demonstrate that the constructed models achieve R² values of 0.89 and 0.86 for DBH and tree height predictions, respectively, representing an improvement of over 15% compared to traditional methods; the average carbon storage of 20-year-old poplar plantations is 112.3 t·hm⁻², with aboveground and belowground portions accounting for 78.6% and 21.4%, respectively; stand density and site conditions are identified as key factors influencing carbon storage. This study establishes, for the first time, a regional-scale carbon storage estimation system for poplar plantations and proposes carbon sequestration management strategies based on growth stages. The research outcomes provide theoretical support and technical guidance for the sustainable management of poplar plantations and the enhancement of their carbon sequestration functions, holding significant practical implications for achieving carbon neutrality goals.
KEY WORDS：Poplar Plantation; Carbon Stock Estimation; Growth Prediction Model
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 杨树人工林生长模型及碳储量估算研究背景 1
1.2 杨树人工林生长模型及碳储量估算研究现状 1
第2章 杨树人工林生长模型的构建与验证 3
2.1 杨树人工林生长数据采集与处理 3
2.2 杨树人工林生长模型的构建方法 3
2.3 杨树人工林生长模型的验证与分析 4
第3章 杨树人工林碳储量估算方法研究 5
3.1 杨树人工林生物量测定方法 5
3.2 杨树人工林碳储量估算模型构建 5
3.3 不同立地条件下碳储量差异分析 5
第4章 杨树人工林碳汇功能评估与应用 7
4.1 杨树人工林碳汇功能评估指标体系 7
4.2 区域尺度杨树人工林碳汇潜力分析 7
4.3 基于碳汇功能的杨树人工林经营策略 8
第5章 结论 9
参考文献 10
致 谢 11
本研究以杨树人工林为研究对象，旨在构建精准的生长模型并估算其碳储量，为森林碳汇功能评估提供科学依据。通过选取华北地区典型杨树人工林样地，采用固定样地连续观测法获取胸径、树高、生物量等生长数据，结合遥感影像和气象资料，运用混合效应模型和机器学习算法构建了基于环境因子的杨树生长预测模型。研究创新性地将随机森林算法与过程模型相结合，显著提高了模型的预测精度。结果表明：所构建的模型对胸径和树高的预测R²分别达到0.89和0.86，较传统方法提高15%以上；20年生杨树人工林平均碳储量为112.3 t·hm⁻²，其中地上部分占78.6%，地下部分占21.4%；林分密度和立地条件是影响碳储量的关键因素。研究首次建立了适用于区域尺度的杨树人工林碳储量估算体系，提出了基于生长阶段的碳汇管理策略。研究成果可为杨树人工林的可持续经营和碳汇功能提升提供理论支撑和技术指导，对实现碳中和目标具有重要实践意义。
关键词：杨树人工林；碳储量估算；生长预测模型
ABSTRACT
This study focuses on poplar plantations, aiming to construct precise growth models and estimate their carbon storage capacity, thereby providing a scientific basis for assessing forest carbon sequestration functions. By selecting typical poplar plantation plots in North China and employing continuous observation methods in fixed sample plots, growth data including diameter at breast height (DBH), tree height, and biomass were collected. Integrating remote sensing imagery and meteorological data, mixed-effects models and machine learning algorithms were utilized to develop growth prediction models for poplar trees based on environmental factors. The research innovatively combines the random forest algorithm with process-based models, significantly enhancing the predictive accuracy of the models. The results demonstrate that the constructed models achieve R² values of 0.89 and 0.86 for DBH and tree height predictions, respectively, representing an improvement of over 15% compared to traditional methods; the average carbon storage of 20-year-old poplar plantations is 112.3 t·hm⁻², with aboveground and belowground portions accounting for 78.6% and 21.4%, respectively; stand density and site conditions are identified as key factors influencing carbon storage. This study establishes, for the first time, a regional-scale carbon storage estimation system for poplar plantations and proposes carbon sequestration management strategies based on growth stages. The research outcomes provide theoretical support and technical guidance for the sustainable management of poplar plantations and the enhancement of their carbon sequestration functions, holding significant practical implications for achieving carbon neutrality goals.
KEY WORDS：Poplar Plantation; Carbon Stock Estimation; Growth Prediction Model
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 杨树人工林生长模型及碳储量估算研究背景 1
1.2 杨树人工林生长模型及碳储量估算研究现状 1
第2章 杨树人工林生长模型的构建与验证 3
2.1 杨树人工林生长数据采集与处理 3
2.2 杨树人工林生长模型的构建方法 3
2.3 杨树人工林生长模型的验证与分析 4
第3章 杨树人工林碳储量估算方法研究 5
3.1 杨树人工林生物量测定方法 5
3.2 杨树人工林碳储量估算模型构建 5
3.3 不同立地条件下碳储量差异分析 5
第4章 杨树人工林碳汇功能评估与应用 7
4.1 杨树人工林碳汇功能评估指标体系 7
4.2 区域尺度杨树人工林碳汇潜力分析 7
4.3 基于碳汇功能的杨树人工林经营策略 8
第5章 结论 9
参考文献 10
致 谢 11
