共查询到18条相似文献，搜索用时 421 毫秒
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基于计数模型方法的林分枯损研究 总被引：4，自引：0，他引：4
利用吉林省汪清林业局金沟岭林场落叶松林分连续观测数据,分别利用Poisson回归模型、负二项模型、零膨胀模型和Hurdle模型拟合林木枯损株数,并通过AIC值以及Vuong检验对这些模型进行详细分析比较。结果表明:Poisson回归模型不适用于模拟林木枯损株数,负二项回归模型相对于Poisson回归模型比较适用;但是对于零枯损过多的数据,这2类模型拟合效果较差。零膨胀模型和Hurdle模型对这类数据有很好的解决办法,其中,零膨胀负二项模型和Hurdle-NB模型拟合效果优于其他几种模型,且Hurdle-NB模型略好于零膨胀负二项模型。 相似文献
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黔南地区气象因子与森林火灾发生次数之间的关系 总被引：2，自引：0，他引：2
对黔南区春季防火期森林火灾数据进行分析,分别引入Poisson回归模型、负二项模型、零膨胀负二项模型和Hurdle模型拟合该地区火险天气森林火灾发生数,并对这些模型进行逐步筛选。结果表明:Poisson回归模型不适用于处理过度离散的数据,负二项回归模型相对于Poisson回归模型,比较适用于过离散数据;但是对于零个数过多的数据,这2类模型拟合效果较差,零膨胀负二项模型和Hurdle模型对这类数据有很好的解决办法。零膨胀负二项模型和Hurdle模型拟合效果优于其他2种模型,而且Hurdle模型好于零膨胀负二项模型。 相似文献
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【目的】构建能够准确预测华北落叶松林分枯死木的计数模型,探究影响华北落叶松林中林木枯死数量的主要原因,为冬奥会核心区的华北落叶松人工林科学经营与管理提供决策依据。【方法】以张家口市崇礼冬奥核心区45块华北落叶松人工林样地为研究对象,构建华北落叶松林分枯死数量Poisson回归模型、负二项回归模型、零膨胀Poisson回归模型和零膨胀负二项回归模型、Hurdle-Poisson回归模型、Hurdle负二项回归模型,根据AIC值选出最优计数模型。基于最优计数模型,考虑不同随机效应水平和作用在截距和协变量上的随机参数,根据模型收敛情况和AIC值确定最优的随机效应水平和随机参数组合,构建最优林分枯死数量混合效应模型。【结果】林分平均直径、林分优势木平均高、林龄、林分断面积和林分胸径Gini系数为影响林分枯死的林分因子,立地因子对林分枯死的影响并不大。未考虑零膨胀现象时,负二项回归模型拟合效果优于Poisson回归模型;考虑零膨胀现象后,Hurdle-Poisson回归模型拟合效果优于零膨胀Poisson回归模型。最终几种考虑零值过多的计数模型的拟合精度表现为：Hurdle负二项回归模型(HNB... 相似文献
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《林业科学》2019,(11)
【目的】基于混合效应模型和零膨胀模型方法构建林分水平枯损模型,为选择科学的经营措施提供理论依据。【方法】以吉林省1994年设置的295块蒙古栎固定样地为数据源,236块样地作为模拟数据,59块样地作为验证数据。构建基于林分因子、立地因子和气象因子的蒙古栎林分水平枯损模型,其基本形式包括泊松分布和负二项分布。考虑样地中存在大量零值问题,在基础模型上加入零膨胀和零改变模型。为解决模型的嵌套和纵向数据问题,在构建模型时考虑样地的随机效应,选择验证数据进行精度验证。【结果】样地断面积、株数和最暖月平均气温是枯损概率和数量最重要的影响因子;考虑样地随机效应后,可明显提高模型模拟精度;负二项分布模型因考虑数据过度离散问题,模拟精度高于泊松分布。【结论】同时考虑随机效应和零膨胀的负二项分布模型,其模拟效果最好。 相似文献
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利用两水平非线性混合模型对杉木(Cunninghamia lanceolata)优势高进行分析。概述了两水平非线性混合模型并简单介绍了该模型的参数估计方法;选用了5种常见的Richards和Logistic 形式模型作为构建混合模型的基础模型,利用建模数据分别对这些基础模型各自衍生出的19种混合模型进行计算及比较,结果表明:这5种基础模型对应的最佳混合模型分别为模型(3-1) 模型(3-5);最后把这些最佳混合模型及传统的回归模型两两进行比较,结果表明:二水平非线性混合模型拟合效果比传统的回归模型拟合效果要好,并且基础模型4对应的二水平混合模型(式3-4)拟合效果最好。 相似文献
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广义线性模型在林火发生预报中的应用 总被引：2，自引：0，他引：2
《林业工程学报》2017,(1)
首先介绍了国内外广义线性模型在林火发生预报中的应用,其次分别阐述了常用于林火发生预测的正态分布、逻辑斯蒂分布、泊松分布、负二项分布、零膨胀、栅栏等6种广义线性回归模型的表达式、参数估计方法和几种相关的假设检验方法,其中,逻辑斯蒂广义线性模型主要用于预测林火发生的概率,其他5种模型主要用于预测林火发生的频次。根据林火发生频次的数据结构特点和前人的研究结果分析得出,与正态分布相比,泊松分布、负二项分布、零膨胀、栅栏4种广义线性回归模型更适于预测林火发生的次数。当林火发生频次的方差接近于期望,应采用泊松或零膨胀泊松广义线性模型;如林火发生频次的方差显著大于期望,则宜采用负二项或零膨胀负二项广义线性模型。最后,对广义线性模型在我国林火发生预测中的应用提出了三方面建议:第一,增加模型的自变量(如森林可燃物特征、地形、人类活动等因子);第二,增加模型在景观层次林火发生预报中的应用;第三,拓展模型的建模方法,如建立广义线性混合效应模型和广义相加模型。 相似文献
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间伐林分的断面积生长模型研究 总被引：3，自引：0，他引：3
利用Richards和Schumacher模型对人工落叶松和杉木林分进行断面积模型的拟合,结果表明:两种模型在同时选择单位面积株数或同时选择林分密度指数作为自变量时,Schumacher式都比Richards式拟合和预估效果好。Richards式用林分密度指数比用单位面积株数的拟合和预估效果明显要好,Schumacher式用林分密度指数比用单位面积株数拟合效果略好。在生产实践中,由于单位面积株数容易测定,而Schumacher形式比较简单,建议用来预估林分的断面积,并可作为间伐和未间伐林分的兼容模型。 相似文献
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The occurrence of lightning-induced forest fires during a time period is count data featuring over-dispersion (i.e., variance is larger than mean) and a high frequency of zero counts. In this study, we used six generalized linear models to examine the relationship between the occurrence of lightning-induced forest fires and meteorological factors in the Northern Daxing’an Mountains of China. The six models included Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), Poisson hurdle (PH), and negative binomial hurdle (NBH) models. Goodness-of-fit was compared and tested among the six models using Akaike information criterion (AIC), sum of squared errors, likelihood ratio test, and Vuong test. The predictive performance of the models was assessed and compared using independent validation data by the data-splitting method. Based on the model AIC, the ZINB model best fitted the fire occurrence data, followed by (in order of smaller AIC) NBH, ZIP, NB, PH, and Poisson models. The ZINB model was also best for predicting either zero counts or positive counts (≥1). The two Hurdle models (PH and NBH) were better than ZIP, Poisson, and NB models for predicting positive counts, but worse than these three models for predicting zero counts. Thus, the ZINB model was the first choice for modeling the occurrence of lightning-induced forest fires in this study, which implied that the excessive zero counts of lightning-induced fires came from both structure and sampling zeros. 相似文献
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The mortality of trees across diameter class model is a useful tool for predicting changes in stand structure.Mortality data commonly contain a large fraction of zeros and general discrete models thus show more errors.Based on the traditional Poisson model and the negative binomial model,different forms of zero-inflated and hurdle models were applied to spruce-fir mixed forests data to simulate the number of dead trees.By comparing the residuals and Vuong test statistics,the zero-inflated negative binomial model performed best.A random effect was added to improve the model accuracy;however,the mixed-effects zero-inflated model did not show increased advantages.According to the model principle,the zeroinflated negative binomial model was the most suitable,indicating that the"0"events in this study,mainly from the sample"0",i.e.,the zero mortality data,are largely due to the limitations of the experimental design and sample selection.These results also show that the number of dead trees in the diameter class is positively correlated with the number of trees in that class and the mean stand diameter,and inversely related to class size,and slope and aspect of the site. 相似文献
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A Poisson regression model and a negative binomial regression model(NB model) are often used in areas such as medicine and economy,but rarely in the domestic forestry sector,especially in the forest fire forecasting.Based on the data of forest fire occurrences in Daxing’anling region in 1980- 2005,this paper profoundly analyzes the application conditions and test methods of the two models.The AIC method was used to check the fitting level of the models and the capability of the models for forecasting forest fires was discussed.This study provided necessary theoretical basis and data support for the application of the two models in the field of forestry in China. 相似文献
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《Forest Ecology and Management》1999,123(1):41-53
Individual tree-height increment models were developed for white spruce (Picea glauca (Moench) Voss) and aspen (Populus tremuloides Michx.) growing in the boreal mixed-species in Alberta. The models were formulated based on a selected base function (the Box–Lucas function), and the method of parameter prediction. Height increment was modeled as a nonlinear function of tree height, tree diameter, diameter increment, stand density, relative competitiveness of the tree in the stand, site productivity, and species composition. Since the data from permanent sample plots used in this study were time-dependent and cross-sectional, diagnostic techniques were applied to identify the models' error structure. Appropriate fits based on the identified error structure were accomplished using the nonlinear least squares procedures with a first-order autoregressive process. The models were also validated on independent testing data sets representing the population on which the models are to be used. Results showed that the average prediction biases were not significantly different from zero at α = 0.05, suggesting that the fitted models appropriately described the data and performed well when predictions were made. Biological implications of the variables that affect height increment in mixed-species stands were discussed. 相似文献
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Effects of species and tree size diversity on recruitment in the Alaskan boreal forest: A geospatial approach 总被引：1，自引：0，他引：1
This study empirically evaluates and maps the relationships between recruitment and species and tree size diversity, as measured with the Shannon’s index, within mixed poplar/birch and mixed spruce stands across the boreal forest of Alaska. Data were collected from 438 permanent sample plots re-measured at a 5-year interval. Significant explanatory factors of recruitment, including species and tree size diversity were first identified using hierarchical partitioning. The effects of tree diversity on recruitment were then studied using generalized linear models and universal kriging to account for non-spatial factors and for spatial autocorrelation. We found a consistent positive relationship between recruitment and species diversity and a general negative relationship between recruitment and tree size diversity, indicating a tradeoff between species diversity and tree size diversity in affecting recruitment. These relationships however were not uniform across the landscape, presumably because they were subject to strong spatial autocorrelation attributable to natural disturbances and environmental stressors. In general, diversity had least effect on recruitment in stressful environments where stress, rather than competition, most likely governed recruitment. 相似文献
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《Scandinavian Journal of Forest Research》2012,27(1-4):348-356
The risk of damage on trees from snow and wind was modelled using tree, stand, and site characteristics from 286 permanent Scots pine (Pinus sylvestris L.) sample plots within the Swedish National Forest Inventory. Three logistic risk assessment models were developed for the county of Västerbotten in the boreal zone of Sweden. The best model, using tree, stand, and site variables, correctly classified 81.1% of the undamaged and 81.8% of the damaged plots. The model over‐predicted the proportion of damaged plots (21.3%), compared to the observed proportion of 3.8%. When evaluating the models using temporary plots from Västerbotten, the model using tree, stand, and site variables showed the best overall predictability. When applied in southern Sweden, the models developed for Västerbotten showed poor predictability. The study shows possibilities for correctly classifying the overall susceptibility to damage from snow and wind if the models are used within their limits. 相似文献
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Felipe Crecente-Campo Margarida Tomé Paula Soares Ulises Diéguez-Aranda 《Forest Ecology and Management》2010
A generalized height–diameter model was developed for Eucalyptus globulus Labill. stands in Galicia (northwestern Spain). The study involved a variety of pure stands ranging from even-aged to uneven-aged. Data were obtained from permanent circular sample plots in which trees were sampled within different radii according to their diameter at breast height. A combination of weighted regression, to take into account the unequal selection probabilities of such an inventory design, and mixed model techniques, to accommodate local random fluctuations in the height–diameter relationship, were applied to estimate fixed and random parameters for several models reported in the relevant literature. The models that provided the best results included dominant height and dominant diameter as fixed effects. These models explained more than 83% of the observed variability, with mean errors of less than 2.5 m. Random parameters for particular plots were estimated with different tree selection options. Height–diameter relationships tailored to individual plots can be obtained by calibration of the height measurements of the three smallest trees in a plot. An independent dataset was used to test the performance of the model with data not used in the fitting process, and to demonstrate the advantages of calibrating the mixed-effects model. 相似文献