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Journal of Environmental Biology

pISSN: 0254-8704 ; eISSN: 2394-0379 ; CODEN: JEBIDP

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    Abstract - Issue Apr 2007, 28 (2)                                     Back


Modeling individual tree mortality for crimean pine plantations

Mehmet Misir*, Nuray Misir and Hakki Yavuz

Faculty of Forestry, Karadeniz Technical University, Trabzon-610 80, Turkey

(Received: November 23, 2005 ; Revised received: July 21, 2006; Accepted: August 11, 2006)

Abstract: Individual tree mortality model was developed for crimean pine (Pinus nigra subsp. pallasiana) plantations in Turkey. Data came from 5 year remeasurements of the permanent sample plots. The data comprises of 115 sample plots with 5029 individual trees. Parameters of the logistic equation were estimated using weighted nonlinear regression analysis. Approximately 80% of the observations were used for model development and 20% for validation. The explicatory variables in the model were ratio of diameter of the subject tree and basal area mean diameter of the sample plot as measure of competition index for individual trees, basal area and site index. All parameter estimates were found highly significant (p<0.001) in predicting mortality model. Chi-square statistics indicate that the most important variable is , the second most important is site index, and the third most important predictor is stand basal area. Examination of graphs of observed vs. predicted mortality rates reveals that the mortality model is well behaved and match the observed mortality rates quite well. Although the phenomenon of mortality is a stochastic, rare and irregular event, the model fit was fairly good. The logistic mortality model passed a validation test on independent data not used in parameter estimation. The key ingredient for obtaining a good mortality model is a data set that is both large and representative of the population under study and the data satisfy both requirements. The mortality model presented in this paper is considered to have an appropriate level of reliability.

Key words: Growth model, Individual trees, Mortality, Logistic function


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