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  3. Ecology and Evolutionary Biology / 生態學與演化生物學研究所
  4. Modeling individual tree mortality for forest species of Lanjenshi forest dynamics plot, southern Taiwan
 
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Modeling individual tree mortality for forest species of Lanjenshi forest dynamics plot, southern Taiwan

Date Issued
2007
Date
2007
Author(s)
Huang, Ssu-Po
DOI
zh-TW
URI
http://ntur.lib.ntu.edu.tw//handle/246246/55141
Abstract
This study was used logistic regression function for modeling individual trees mortality. The data came from three times remeasurements of the Lanjenshi forest dynamics plot(Lanjenshi FDP). The prediction ability of these mortality models were validated using independent data that was different from the modeling data. Two kinds of models were developed using two different periods. The 9197 models were using the data among 1991-1997 years and the 9105 models were using the data among 1991-2005 years. There were 41 species successfully developed the 9197 models that were using 25 variables include tree size, density and individual competition. There were 47 species successfully developed the 9105 models that were using 35 variables include tree growth and death variables besides tree size, density and individual competition. For many species, we found the hyperbolic transformation of diameter (DBH-1) to be highly significant in predicting the high mortality rates for small diameter trees and decreasing mortality rates for larger diameters. To compare the predictive and actual mortality was used the random number as the threshold to simulate trees mortality. The overall predictive success rates of 15 species are over 80﹪in 9197 models and 8 species are over 80﹪in 9105 models. The overall predictive success rates of 9197 and 9105 models are no different in dominate species. But prediction ability of overall mortality of 9105 models which were used tree growth and death variables in dominate species batter than 9197 models.
Subjects
欖仁溪森林動態樣區
森林動態
死亡
邏輯回歸
模型
Lanjenshi FDP
forest dynamics
logistic regression
mortality
model
Type
other
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