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Publication Information

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Title: Using Bayesian belief networks in adaptive management.

Author: Nyberg, J.B.; Marcot, B.G.; Sulyma, R.;

Date: 2006

Source: Canadian Journal of Forest Research. 36(12): 3104-3116

Publication Series: Scientific Journal (JRNL)

Description: Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to calculating joint probabilities of decision options and predicting outcomes of management policies. We describe the nature and capabilities of BBNs, discuss their applications to various steps in the adaptive-management process, and provide a case example of adaptive management of forests and terrestrial lichens in north-central British Columbia.

Keywords: Bayesian belief networks, monitoring, adaptive management, caribou modeling

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

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Nyberg, J.B.; Marcot, B.G.; Sulyma, R. 2006. Using Bayesian belief networks in adaptive management. Canadian Journal of Forest Research. 36(12): 3104-3116

 


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