LOG-VEROSSIMILHANÇA COMBINADA PARA COMPARAÇÃO DE ESTRUTURAS DE CONTINUIDADE ESPACIAL EM FLORESTA ESTACIONAL DECIDUAL

J. Wojciechowski, Julio Eduardo Arce, Saulo Henrique Weber, P. Junior, Carlos Pires
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Abstract

The present study aimed to examine spatial dependence and distribution of volume in three fragments of Subtropical forest, geographically separated and the different post-intervention ages, using a single geostatistical model or combined model. Data were collected from 56 sampling units of 250 m 2 systematically distributed in a grid of 40 x 40 m. Trees with DBH ≥ 10 cm were measured according to Prodan’s methodology. Two types of analysis were applied to the data. The first one was an individual adjustment for comparison between their models and the second one consisted in the proposed combined approach adjustment. Both analysis used geostatistical models with adjustment function maximizing log-likelihood. Models were compared using Akaike criterion (AIC) and relational range parameter as an indication of spatial dependence degree. Results show that combined models had lower AIC values as well as greater spatial dependence degree on adjustments of individual areas models. This research indicates the use of combined log-likelihood geostatistical models to study fragmented forests for analysis and detection of spatial volume correlation structure.
落叶林空间连续性结构比较的对数似然组合
采用单一地质统计模型和组合模型,研究了不同地理位置和不同干预后年龄的亚热带森林3个片段的体积空间依赖性和分布特征。数据从56个250平方米的采样单位收集,系统地分布在40 x 40米的网格中。根据Prodan的方法测量胸径≥10 cm的树木。对数据进行了两种类型的分析。第一个是对模型进行比较的个别调整,第二个是提出的组合方法调整。两种分析都使用了具有最大对数似然调整函数的地质统计模型。以赤池准则(Akaike criterion, AIC)和相关极差参数作为空间依赖程度指标,对模型进行了比较。结果表明,组合模型的AIC值较低,对单个区域模型调整的空间依赖性较大。本研究提出利用对数似然组合地统计模型对破碎林进行空间体积相关结构分析和检测。
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