Estimation of Forest Diversity with Misclassification

  • George Gertner
  • Xiangchi Cao
  • Dieter Pelz
Chapter
Part of the Forestry Sciences book series (FOSC, volume 51)

Abstract

In this paper, the consequences are assessed of species identification errors when estimating species diversity with the Shannon-Weaver index. Species misclassification can be due to recording error, editing error, poor field crew training, etc. In certain situations, misclassification can lead to biased estimates of the biodiversity index as well as inflated variance estimates. Different approaches are presented for assessing the consequences of misclassification. The results of a control study are presented. The work presented is part of an ongoing study to develop error budgets for different types of comprehensive stochastic dynamic modelling systems for both plant and forest communities.

Keywords

Forest Community Beta Distribution Shannon Index Misclassification Error Error Budget 
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 Dordrecht 1998

Authors and Affiliations

  • George Gertner
    • 1
  • Xiangchi Cao
    • 2
  • Dieter Pelz
    • 3
  1. 1.Department of Natural Resources and Environmental SciencesUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.National Center for Super Computer Applications (NCSA)University of Illinois at Urbana-ChampaignUrbanaUSA
  3. 3.Abteilung für Forstliche BiometrieUniversität Freiburg i. Br.FreiburgGermany

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