A Bayesian decision network approach for assessing the ecological impacts of salinity management

A. Sadoddin*, R. A. Letcher, A. J. Jakeman, L. T.H. Newham

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    47 Citations (Scopus)

    Abstract

    This paper outlines one component of a study being undertaken to provide a new tool for integrated management of dryland salinity, a major environmental problem in Australia. The Little River Catchment in the upper Macquarie River basin of New South Wales (NSW) is used as a case study. A Bayesian decision network (BDN) approach integrates the various system components - biophysical, social, ecological, and economic. The method of integration of the system components is demonstrated through an example application showing the impacts of various management scenarios on terrestrial and riparian ecology. The ecological impacts of management scenarios are assessed using a probabilistic approach to evaluate ecological criteria which are compared with those for the present situation. In considering different ecological indices, the direction and magnitude of change under different management scenarios varies because of the diverse influence of habitat fragmentation.

    Original languageEnglish
    Pages (from-to)162-176
    Number of pages15
    JournalMathematics and Computers in Simulation
    Volume69
    Issue number1-2 SPEC. ISS.
    DOIs
    Publication statusPublished - 20 Jun 2005

    Fingerprint

    Dive into the research topics of 'A Bayesian decision network approach for assessing the ecological impacts of salinity management'. Together they form a unique fingerprint.

    Cite this