Skip to main content

Modelling stand development

  • Chapter
Modelling Forest Development

Part of the book series: Forestry Sciences ((FOSC,volume 57))

Abstract

Most managed forests are conveniently subdivided into a discrete number of geographical units known as stands. A stand may be even-aged or uneven-aged, depending on the type of management history. An even-aged stand is characterized by one age, which facilitates modelling its development. Even-aged stands are usually, though not always, more uniform with regard to the distribution of tree diameters and heights.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

  1. vide Schumacher (1939). In Eastern and Central Europe the Schumacher-function is known as the Michailoff function, according to Michailoff (1943).

    Google Scholar 

  2. The height range is subdivided into a number of equally wide sections; in Germany this technique is known as the Streifenverfahren (Baur, 1877; Sterba, 1991, p. 71).

    Google Scholar 

  3. with α0=(19.962), α1=(-0.02642) and α2=(l/0.46) for SI1∞=17 and α0=(31.83), α1=(-0.03431) and α2=(1/0.3536) for S1,∞=29.

    Google Scholar 

  4. Height curves are not always disjoint as will be shown in the next section.

    Google Scholar 

  5. The coefficient of determination is a ratio indicating how the model compares with a simple average (R2=0) and with the perfect fit (R2=l). It is given by R2=l-RSSn/RSSM where RSSm is the residual sum of squares of the model and RSSn is the residual sum of squares about the mean. A high R2 does not necessarily mean that the model is the best possible one, nor that it will provide good predictions.

    Google Scholar 

  6. Class 3: weakly co-dominant; class 4:suppressed; class 5: completely suppressed.

    Google Scholar 

  7. Class 1: dominant with exceptionally large crowns; class 2: co-dominant with well developed crowns.

    Google Scholar 

  8. The degree of stocking is the basal area per hectare expressed as a proportion of some normal basal area, defined by a yield table.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Von Gadow, K., Hui, G. (1999). Modelling stand development. In: Modelling Forest Development. Forestry Sciences, vol 57. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-4816-0_3

Download citation

  • DOI: https://doi.org/10.1007/978-94-011-4816-0_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-0276-2

  • Online ISBN: 978-94-011-4816-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics