【摘要】：華北落葉松(Larixprincipis-rupprechtii)是我國華北地區(qū)山地的主要造林樹種。其優(yōu)點(diǎn)眾多,生長速度快、木材材質(zhì)好、用途廣、腐朽耐力強(qiáng),是營造經(jīng)濟(jì)生態(tài)林的良好樹種,同時(shí)也是杰出的防護(hù)林樹種。樹冠是樹木進(jìn)行光合作用和積累能量的重要場所,它反映了樹木的生長活力和競爭力,是樹木一個(gè)重要的健康指標(biāo)。冠幅是描述樹冠生長的重要指標(biāo)也是森林生長收獲預(yù)估模型的重要預(yù)測變量。因此準(zhǔn)確預(yù)估冠幅對森林可持續(xù)經(jīng)營和森林生態(tài)研究極其重要。本文以多種樹木林分因子為協(xié)變量構(gòu)建了一般冠幅-胸徑預(yù)測模型,并且分析了地域效應(yīng)和區(qū)組效應(yīng)以及嵌套在區(qū)組里的樣地效應(yīng)對華北落葉松冠幅影響,以此為基礎(chǔ)使用了非線性混合效應(yīng)模型構(gòu)建了相應(yīng)的冠幅模型,最后還考慮了冠幅與東西南北四個(gè)方向的冠徑的相關(guān)性,并使用了四種可加性模型方法構(gòu)建了相應(yīng)的模型系統(tǒng),四種模型系統(tǒng)都解決了冠幅與東西南北四個(gè)方向的冠徑的相容性;最后通過綜合比較確定了最優(yōu)的可加性冠幅模型系統(tǒng)。主要研究結(jié)果如下:(1)三參數(shù)的邏輯斯蒂模型:CW=a/1+exp[b+cln(D+1)]能較好反映華北落葉松天然次生林冠幅和直徑之間的非線性關(guān)系,與其它候選模型相比,該模型有較高的擬合精度,并且模型各參數(shù)都具有一定的生物學(xué)意義;對象木冠長(CL)、對象木樹高(H)和每公頃株數(shù)(M)對冠幅影響較大,當(dāng)這些因子作為預(yù)測變量時(shí)能明顯改進(jìn)模型的預(yù)測精度;得到的改進(jìn)后的冠幅模型表達(dá)式為:CW = 1.4875-0.031 1H+exp[(-3.6416-0.0002M)+(2.4346+ 0.0045CL)ln(D+1)]通過大量實(shí)驗(yàn)數(shù)據(jù)驗(yàn)證,該模型具有較高的預(yù)測精度。(2)研究發(fā)現(xiàn)區(qū)組效應(yīng)和嵌套在區(qū)組里面的樣地效應(yīng)對華北落葉松的隨機(jī)影響較大,當(dāng)模型考慮這些隨機(jī)影響時(shí)模型預(yù)測精度能進(jìn)一步顯著提高;,指數(shù)方差函數(shù)且預(yù)測變量為胸高直徑能有效剔除模型的異方差,表達(dá)式為:var(εijk= σ2exp(2γxijk);利用所構(gòu)建的嵌套兩水平非線性混合效應(yīng)模型預(yù)測冠幅時(shí),利用隨機(jī)抽取的4株樣地計(jì)算隨機(jī)效應(yīng)參數(shù)效果較好。當(dāng)?shù)赜蛐?yīng)作用在固定效應(yīng)參數(shù)β1和β5上時(shí),模型對應(yīng)的AIC(5425)最小而LogLik(-2697)最大最終構(gòu)建了華北落葉天然林非線性回歸效應(yīng)單木冠幅模型。(3)以模型(4-3)為基礎(chǔ)模型,使用非線性聯(lián)立方程組(NSE)、非線性似然不相關(guān)回歸(NSUR)、比例平差法(AP)和最小二乘法獨(dú)立回歸(OLSSR)方法構(gòu)建冠幅可加性模型系統(tǒng),這幾種方法都能有效的考慮總冠幅和各樹冠半徑之間的相關(guān)性。通過綜合對比這幾種可加性模型系統(tǒng),對于總冠幅,分級聯(lián)合控制平差法構(gòu)建的冠幅模型系統(tǒng)對應(yīng)的指標(biāo)δ,RMSE和TRE均要低于NSUR、AP和OLSSR模型系統(tǒng);所以在可加性模型構(gòu)建冠幅模型方法中,分級聯(lián)合控制平差法構(gòu)建的冠幅可加性模型系統(tǒng)擬合效果最好。
[Abstract]:Larch of North China (Larixprincipis-rupprechtii) is the main afforestation tree species in the mountainous area of North China. It has many advantages, such as fast growth rate, good wood material, wide use and strong decadent endurance. It is a good tree species for economic and ecological forest, and is also an outstanding shelterbelt tree species. Tree crown is an important place for photosynthesis and energy accumulation of trees. It reflects the growth vitality and competitiveness of trees and is an important health index of trees. Canopy width is an important index to describe tree crown growth and an important predictor of forest growth and harvest prediction model. Therefore, it is very important for forest sustainable management and forest ecology to estimate the crown accurately. In this paper, a general prediction model of crown width and DBH was constructed using a variety of tree stand factors as covariables, and the effects of region effect, block effect and sample plot effect nested in block on crown width of Larix gmelini were analyzed. On this basis, the corresponding crown size model is constructed by using the nonlinear mixed effect model. Finally, the correlation between the crown width and the crown diameter in the four directions of the east, west, north and south is considered, and the corresponding model system is constructed by using four additive model methods. All the four model systems have solved the compatibility between the crown width and the crown diameter in the four directions from east to west, and the optimal additive crown model system has been determined by comprehensive comparison. The main results are as follows: (1) the three-parameter logical Stirt model: CWSA / 1 exp [b cln (D 1] can better reflect the nonlinear relationship between crown width and diameter of natural secondary forest of Larix gmelini. Compared with other candidate models, this model has higher fitting accuracy. All the parameters of the model have certain biological significance, the tree height (H) and the number of trees per hectare (M) have a great influence on the crown width, and the prediction accuracy of the model can be improved obviously when these factors are used as the prediction variables. The expression of the improved crown model is: CW = 1.4875-0.031 1H exp [(-3.6416-0.0002M) (2.4346 0.0045CL) ln (D 1)]. The model has a high prediction accuracy. (2) the block effect and the sample effect nested in the block have a great influence on the random effect of Larix gmelini. When these random effects are taken into account, the prediction accuracy of the model can be further improved significantly, and the exponential variance function and the prediction variable are sternum height diameter, which can effectively eliminate the heteroscedasticity of the model. The expression is: var (蔚 ijk= 蟽 2exp) (2 緯 xijk);). When the constructed nested two-level nonlinear mixed effect model is used to predict the crown amplitude, it is better to calculate the random effect parameters by using the random sampling plots. When the regional effect is on the fixed effect parameters 尾 _ 1 and 尾 _ 5, the corresponding AIC (5425) is the smallest and the LogLik (-2697) maximum is the largest. Finally, the model of the nonlinear regression effect of the North China deciduous natural forest is constructed. (3) the model (4-3) is taken as the basic model. Using (NSE), nonlinear likelihood uncorrelated regression (NSUR), proportional adjustment method (AP) and least square independent regression (OLSSR) method to construct the crown additive model system. These methods can effectively consider the correlation between total crown size and crown radius. Through the comprehensive comparison of these additive model systems, for the total crown amplitude, the corresponding indexes of the crown model system constructed by the hierarchical combined control adjustment method are lower than those of the NSUR,AP and OLSSR model systems. Therefore, in the method of building crown amplitude model with additive model, the fitting effect of the model system based on hierarchical combined control adjustment method is the best.
【學(xué)位授予單位】：中南林業(yè)科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S758
，

本文編號：2234436