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Restoring stream habitat connectivity: A proposed method for prioritizing the removal of resident fish passage barriers

O'Hanley, J.R., Wright, J., Diebel, M., Fedora, M.A., Soucy, C.L. (2013) Restoring stream habitat connectivity: A proposed method for prioritizing the removal of resident fish passage barriers. Journal of Environmental Management, 125 . pp. 19-27. ISSN 0301-4797. (doi:10.1016/j.jenvman.2013.02.055) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:34016)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL
http://dx.doi.org/10.1016/j.jenvman.2013.02.055

Abstract

Systematic methods for prioritizing the repair and removal of fish passage barriers, while growing of late, have hitherto focused almost exclusively on meeting the needs of migratory fish species (e.g., anadromous salmonids). An important but as of yet unaddressed issue is the development of new modeling

approaches which are applicable to resident fish species habitat restoration programs. In this paper, we develop a budget constrained optimization model for deciding which barriers to repair or remove in order to maximize habitat availability for stream resident fish. Habitat availability at the local stream

reach is determined based on the recently proposed C metric, which accounts for the amount, quality, distance and level of connectivity to different stream habitat types. We assess the computational performance of our model using geospatial barrier and stream data collected from the Pine-Popple Watershed, located in northeast Wisconsin (USA). The optimization model is found to be an efficient and practical decision support tool. Optimal solutions, which are useful in informing basin-wide restoration planning efforts, can be generated on average in only a few minutes.

Item Type: Article
DOI/Identification number: 10.1016/j.jenvman.2013.02.055
Subjects: H Social Sciences
H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Jesse O'Hanley
Date Deposited: 30 May 2013 10:33 UTC
Last Modified: 16 Nov 2021 10:11 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/34016 (The current URI for this page, for reference purposes)
O'Hanley, J.R.: https://orcid.org/0000-0003-3522-8585
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