Forest Structure and Diversity

  • Klaus v. Gadow
  • Chun Yu Zhang
  • Christian Wehenkel
  • Arne Pommerening
  • Javier Corral-Rivas
  • Mykola Korol
  • Stepan Myklush
  • Gang Ying Hui
  • Andres Kiviste
  • Xiu Hai Zhao
Chapter
First Online:
Part of the Managing Forest Ecosystems book series (MAFE, volume 23)

Abstract

This contribution presents methods that can be used to describe and analyse forest structure and diversity with particular reference to CCF management. Despite advances in remote sensing, mapped tree data in large observation windows are very rarely available in CCF management situations. Thus, although we present methods of second order statistics (SOC), the emphasis is on nearest neighbor statistics (NNS). The first section gives a general introduction and lists the objectives of the chapter. Methods of analysing non-spatial structure and diversity are presented in the second section. The third section introduces procedures for analysing unmarked and marked patterns of forest structure and diversity. Relevant R codes are provided to facilitate application of the methods. Examples of measuring differences between patterns and of reconstructing forests from samples are also presented. Finally, in Sect. 4 we discuss some important issues and summarize the main findings of this chapter.

Keywords

Tree Species Tree Size Gini Coefficient Forest Structure Lorenz Curve 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Klaus v. Gadow
    • 1
  • Chun Yu Zhang
    • 2
  • Christian Wehenkel
    • 3
  • Arne Pommerening
    • 4
  • Javier Corral-Rivas
    • 3
  • Mykola Korol
    • 5
  • Stepan Myklush
    • 5
  • Gang Ying Hui
    • 6
  • Andres Kiviste
    • 7
  • Xiu Hai Zhao
    • 2
  1. 1.Burckhardt InstituteGeorg-August University GöttingenGöttingenGermany
  2. 2.Beijing Forestry UniversityBeijingChina
  3. 3.Universidad Juarez del Estado de DurangoDurangoMexico
  4. 4.Swiss College of Agriculture SHLBern University of Applied SciencesZollikofenSwitzerland
  5. 5.Ukrainian National Forestry UniversityLvivUkraine
  6. 6.Chinese Academy of ForestryBeijingChina
  7. 7.Estonian University of Life SciencesTartuEstonia

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