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Ecological Economics
Article . 2013 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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The evolution and empirical estimation of ecological-economic production possibilities frontiers

Authors: Bekele, Elias G.; Lant, Christopher L.; Soman, Sethuram; Misgna, Girmay;

The evolution and empirical estimation of ecological-economic production possibilities frontiers

Abstract

Abstract This paper presents a graphical model of an ecological-economic production possibilities frontier (EEPPF) that explicitly considers the roles of market failure and technological asymmetry in the provision of ecosystem goods and services. An empirical example of a 6-dimensional EEPPF is provided using a watershed in Illinois where three provisioning ecosystem services (corn, soybeans, hay) and three regulating services (flood control, water quality, and carbon retention) are the objectives. When aggregated, provisioning and regulatory services form a linear-to-convex EEPPF, but regulatory services can be increased from 10 to over 90% of optimal with a reduction in provisioning services (crops) from 100 to 78% of optimal. While corn and soybeans are shown to form a trade-off with all other ecosystem services, hay is complementary with flood control, water quality and carbon retention. These three regulating services are complementary with one another, with water quality and carbon correlated at 0.80. These results demonstrate the use of GIS, distributed watershed models such as SWAT, and genetic algorithms as a valuable method to estimate empirical EEPPFs.

Country
United States
Keywords

production possibilities frotntier, 381, Life Sciences, genetic algortithms, market failure, SWAT

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 10%
Green