Structural analysis and growth modeling of natural forests in Vietnam

by Cao Thi Thu Hien
Doctoral thesis
Date of Examination:2015-02-05
Date of issue:2015-02-11
Advisor:Prof. Dr. Joachim Saborowski
Referee:Prof. Dr. Joachim Saborowski
Referee:Prof. Dr. Ralph Mitlöhner
Referee:Prof. Dr. Jürgen Nagel
Persistent Address: http://dx.doi.org/10.53846/goediss-4915

 

 

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Abstract

English

Forest growth and yield models are the oldest and most expansive class; as such, they are the most widely used in forest management. The most significant benefits of those models are their ability to provide an efficient way to forecast resources and predict tree/stand characteristics in detail. This detail regarding stand structure, species composition, and silvicultural treatment response makes this kind of model well suited for examining alternative methods for compatible forest management. Growth and yield models describe forest dynamics, including regeneration, tree growth, recruitment, mortality, reproduction, and associated changes in the stand (Oliver and Larsen, 1996); Vanclay (1994) defined forest growth models as abstractions of the natural dynamics of a forest stand. Most forest dynamic models are split into three components: diameter increment, recruitment, and mortality. These days, modeling diameter increment, recruitment, and mortality in natural forests within the tropics is a subject that has been widely developed. Despite the significant progress made, there has been relatively little study illustrating the growth model of tree species in tropical forests, especially in the tropical forests of Southeast Asia. The purpose of this study is thus twofold: first, to provide a description of the changes in the forest structure and tree species diversity over time, and second, to provide the first analysis of stand dynamics, including diameter increment, recruitment, and mortality, in tropical rainforests of Vietnam.
Keywords: Forest growth and yield models; tropical rainforests; Vietnam; Recruitment and mortality models
 
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