鲁中山区不同立地条件下侧柏、赤松、刺槐生长分析与模拟
发布时间:2019-03-19 08:50
【摘要】:森林生态系统在全球气候变化中占据主导地位,是地球生态平衡的重要保证。准确的监测与评价,对于掌握和管理森林生态系统有重要意义。人工林的生长分析与模拟,可以及时地掌握林分动态变化,为人工林的经营管理和生产实践提供科学合理的理论依据。本研究以山东省鲁中山区侧柏、赤松、刺槐三个树种为研究对象,分别对六种立地类型进行标准地和解析木调查,采用控制变量法,进行方差分析与多重比较,研究不同树种在不同立地条件下生长状况,结果表明:刺槐树高、胸径、材积平均生长量均高于赤松和侧柏,赤松高于侧柏;侧柏在阳坡厚土各项生长量最大,在阴坡薄土各项生长量最小;赤松在阳坡各项生长量大于阴坡各项生长量;刺槐在阳坡厚土生长最好;三个树种在鲁中山区生长状况良好,刺槐优于赤松,赤松优于侧柏。研究结果可为鲁中山区不同立地条件下营造林提供参考依据。同时,本文以鲁中山区侧柏、赤松、刺槐人工林作为研究对象,将不同立地条件下589块固定样地调查数据和142株解析木数据按比例分为建模数据和检验数据,通过对前人总结的经验方程筛选单木生长基础理论模型,采用多元逐步回归技术和非线性回归技术构建侧柏、赤松、刺槐人工林与距离无关的单木胸高断面积生长模型、树高曲线模型、材积生长模型和枯损率模型,结果表明:模型变量的系数全部通过t检验和F检验,P0.05,复相关系数R2均在0.7以上,且残差分布近似正态分布并通过模型检验,模型拟合效果比较理想。本研究克服以往研究数据量偏小、地域局限、缺乏代表性的问题,首次对鲁中山区不同立地类型下侧柏、赤松、刺槐人工林系统分析,成功构建鲁中山区侧柏、赤松、刺槐人工林单木生长模型,从数学和生物学上对鲁中山区人工林生长动态进行了客观地反映,四类生长模型对林木生长过程的模拟精度较高,为鲁中山区人工林今后的经营管理和生产实践提供了重要决策依据,具有较高推广价值。
[Abstract]:Forest ecosystem plays a dominant role in global climate change and is an important guarantee for the ecological balance of the earth. Accurate monitoring and evaluation is of great significance to grasp and manage forest ecosystem. The growth analysis and simulation of plantation can grasp the dynamic change of plantation in time, and provide scientific and reasonable theoretical basis for the management and production practice of plantation. In this study, three tree species, namely Platycladus orientalis, Pinus pseudoacacia, and Pinus pseudoacacia, were used to investigate the six site types in Shandong Province. The variance analysis and multiple comparisons were carried out with the method of controlled variables, and the results were compared with each other. The growth status of different tree species under different site conditions was studied. The results showed that the height, DBH and volume of Robinia pseudoacacia trees were higher than those of red pine and Platycladus orientalis, and that of red pine was higher than that of Platycladus orientalis. The growth of Platycladus orientalis was the largest in the thick soil on the sunny slope, and the smallest in the thin soil on the overcast slope, the growth of the red pine in the sunny slope was greater than that in the shady slope, the growth of Robinia pseudoacacia in the thick soil on the sunny slope was the best. The three tree species grew well in the middle mountain area of Shandong Province, the black locust was superior to the red pine, and the red pine was superior to the lateral cypress. The results can provide reference for afforestation under different site conditions in the mountainous area of central Shandong. At the same time, the data of 589 fixed sample plots and 142 analytical trees in different site conditions were divided into modeling data and testing data in proportion with the plantation of Platycladus cedar, Pinus pseudoacacia and Pinus pseudoacacia in the central mountain area of Shandong Province. By selecting the basic theory model of single tree growth based on the empirical equation summarized by predecessors, the growth model of high basal area of single tree chest independent of distance was constructed by using multiple stepwise regression technique and nonlinear regression technique, and the growth model of high basal area of single tree chest independent of distance was constructed by using the techniques of multiple stepwise regression and nonlinear regression. The results of tree height curve model, volume growth model and withering rate model show that the coefficients of model variables pass t-test and F-test, P0.05 and R ~ 2 are above 0.7, respectively. The residual distribution is similar to normal distribution and through model test, the fitting effect of the model is ideal. This study overcame the problems of small amount of data, regional limitation and lack of representativeness in the past. For the first time, the system analysis of different site types of Platycladus cedar, red pine and Robinia pseudoacacia plantation was carried out in the middle mountain area of Shandong Province, and the lateral cypress and red pine were successfully constructed. The single tree growth model of Robinia pseudoacacia plantation was used to objectively reflect the growth dynamics of plantation in Luzhong Mountain area from mathematical and biological aspects. The simulation accuracy of the four growth models for forest growth process was high. It provides important decision-making basis for future management and production practice of plantation in Luzhong mountain area, and has high popularization value.
【学位授予单位】:山东农业大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:S791.38;S791.245;S792.27
[Abstract]:Forest ecosystem plays a dominant role in global climate change and is an important guarantee for the ecological balance of the earth. Accurate monitoring and evaluation is of great significance to grasp and manage forest ecosystem. The growth analysis and simulation of plantation can grasp the dynamic change of plantation in time, and provide scientific and reasonable theoretical basis for the management and production practice of plantation. In this study, three tree species, namely Platycladus orientalis, Pinus pseudoacacia, and Pinus pseudoacacia, were used to investigate the six site types in Shandong Province. The variance analysis and multiple comparisons were carried out with the method of controlled variables, and the results were compared with each other. The growth status of different tree species under different site conditions was studied. The results showed that the height, DBH and volume of Robinia pseudoacacia trees were higher than those of red pine and Platycladus orientalis, and that of red pine was higher than that of Platycladus orientalis. The growth of Platycladus orientalis was the largest in the thick soil on the sunny slope, and the smallest in the thin soil on the overcast slope, the growth of the red pine in the sunny slope was greater than that in the shady slope, the growth of Robinia pseudoacacia in the thick soil on the sunny slope was the best. The three tree species grew well in the middle mountain area of Shandong Province, the black locust was superior to the red pine, and the red pine was superior to the lateral cypress. The results can provide reference for afforestation under different site conditions in the mountainous area of central Shandong. At the same time, the data of 589 fixed sample plots and 142 analytical trees in different site conditions were divided into modeling data and testing data in proportion with the plantation of Platycladus cedar, Pinus pseudoacacia and Pinus pseudoacacia in the central mountain area of Shandong Province. By selecting the basic theory model of single tree growth based on the empirical equation summarized by predecessors, the growth model of high basal area of single tree chest independent of distance was constructed by using multiple stepwise regression technique and nonlinear regression technique, and the growth model of high basal area of single tree chest independent of distance was constructed by using the techniques of multiple stepwise regression and nonlinear regression. The results of tree height curve model, volume growth model and withering rate model show that the coefficients of model variables pass t-test and F-test, P0.05 and R ~ 2 are above 0.7, respectively. The residual distribution is similar to normal distribution and through model test, the fitting effect of the model is ideal. This study overcame the problems of small amount of data, regional limitation and lack of representativeness in the past. For the first time, the system analysis of different site types of Platycladus cedar, red pine and Robinia pseudoacacia plantation was carried out in the middle mountain area of Shandong Province, and the lateral cypress and red pine were successfully constructed. The single tree growth model of Robinia pseudoacacia plantation was used to objectively reflect the growth dynamics of plantation in Luzhong Mountain area from mathematical and biological aspects. The simulation accuracy of the four growth models for forest growth process was high. It provides important decision-making basis for future management and production practice of plantation in Luzhong mountain area, and has high popularization value.
【学位授予单位】:山东农业大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:S791.38;S791.245;S792.27
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