King, Steven, O'Hanley, Jesse R., Fraser, Iain (2021) How to Choose? A Bioeconomic Model for Optimizing River Barrier Mitigation Actions. Ecological Economics, 181 . Article Number 106892. ISSN 0921-8009. (doi:10.1016/j.ecolecon.2020.106892) (KAR id:83466)
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Official URL: https://doi.org/10.1016/j.ecolecon.2020.106892 |
Abstract
River infrastructure can cause adverse impacts on fish populations, which, in turn, compromises the ability of river ecosystems to provide a range of ecosystem services. In this paper, we present a methodological approach to assess the potential economics costs and benefits of river connectivity enhancement achieved through removal and mitigation of fish dispersal barriers. Our approach combines the results of a stated preference study for nonuse values of rivers and statistical models of fish population responses to barrier mitigation actions within an integrated bioeconomic optimization framework. We demonstrate the utility of our methodology using a case study of the River Wey catchment in southeast England, which contains over 650 artificial barriers. Our results reveal the presence of benefit-cost trade-offs which can form the basis for river barrier mitigation policy development. In particular, we find that benefits exceed costs in the River Wey for all levels of investment in barrier mitigation considered (£2.5 to 53.4M). Furthermore, from an economic efficiency standpoint, a total budget of approximately £22.5M allocated to barrier mitigation would maximize net societal benefits derived from anticipated increases fish species richness and abundance.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.ecolecon.2020.106892 |
Uncontrolled keywords: | fish passage barriers, river connectivity, discrete choice experiments, bioeconomic modeling, optimization, cost benefit analysis |
Subjects: |
G Geography. Anthropology. Recreation > GE Environmental Sciences H Social Sciences |
Divisions: |
Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation Divisions > Division of Human and Social Sciences > School of Economics Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Jesse O'Hanley |
Date Deposited: | 15 Oct 2020 09:03 UTC |
Last Modified: | 05 Nov 2024 12:49 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/83466 (The current URI for this page, for reference purposes) |
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