000094949 001__ 94949
000094949 005__ 20180122213842.0
000094949 0247_ $$2Other$$aISSN 1835-9728
000094949 037__ $$a448-2016-33932
000094949 041__ $$aen
000094949 245__ $$aAn Integrated Assessment approach to linking biophysical modelling and economic valuation tools
000094949 260__ $$c2010-03
000094949 269__ $$a2010-03
000094949 270__ $$mmarit.kragt@anu.edu.au$$pKragt,   Marit
000094949 270__ $$mjeff.bennett@anu.edu.au$$pBennett,   Jeff
000094949 270__ $$mtony.jakeman@anu.edu.au$$pJakeman,   Tony
000094949 300__ $$a27
000094949 336__ $$aReport
000094949 490__ $$aEnvironmental Economics Research Hub Research Report
000094949 490__ $$a53
000094949 520__ $$aNatural resource management (NRM) typically involves complex decisions that affect a variety of stakeholder values. Efficient NRM, which achieves the greatest net environmental, social and financial benefits, needs to integrate the assessment of environmental impacts with the costs and benefits of investment. Integrated assessment (IA) is one approach that incorporates the several dimensions of catchment NRM, by considering multiple issues and knowledge from various disciplines and stakeholders. Despite the need for IA, there are few studies that integrate biophysical modelling tools with economic valuation.

In this paper, we demonstrate how economic non-market valuation tools can be used to support an IA of catchment NRM changes. We develop a Bayesian Network model that integrates: a process-based water quality model; ecological assessments of native riparian vegetation; estimates of management costs; and non-market (intangible) values of changes in riparian vegetation. This modelling approach illustrates how information from different sources can be integrated in one framework to evaluate the environmental and economic impacts of NRM actions. It also shows the uncertainties associated with the estimated welfare effects. By estimating the marginal social costs and benefits, a cost-benefit analysis of alternative management intervention can be gained and provides more economic rationality to NRM decisions.
000094949 542__ $$fLicense granted by Meredith Bacon (meredith.bacon@anu.edu.au) on 2010-10-20T01:07:08Z (GMT):

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000094949 650__ $$aEnvironmental Economics and Policy
000094949 650__ $$aResearch Methods/ Statistical Methods
000094949 6531_ $$aBayesian networks
000094949 6531_ $$abio-economic modelling
000094949 6531_ $$acatchment management
000094949 6531_ $$acost-benefit analysis
000094949 6531_ $$aenvironmental values
000094949 6531_ $$aintegrated assessment and modelling
000094949 6531_ $$anon-market valuation
000094949 6531_ $$ariparian vegetation
000094949 700__ $$aKragt, Marit Ellen
000094949 700__ $$aBennett, Jeffrey W.
000094949 700__ $$aJakeman, Tony
000094949 8564_ $$s253498$$uhttp://ageconsearch.umn.edu/record/94949/files/EERH_RR53.pdf
000094949 887__ $$ahttp://purl.umn.edu/94949
000094949 909CO $$ooai:ageconsearch.umn.edu:94949$$pGLOBAL_SET
000094949 912__ $$nSubmitted by Meredith Bacon (meredith.bacon@anu.edu.au) on 2010-10-20T01:11:12Z
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  Previous issue date: 2010-03
000094949 982__ $$gAustralian National University>Environmental Economics Research Hub>Research Reports
000094949 980__ $$a448