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Pet Project or Best Project? Online Decision Support Tools for Prioritizing Barrier Removals in the Great Lakes and Beyond

Moody, A.T., Neeson, T.M., Milt, A., Wangen, S., Dischler, J., Diebel, M.W., Herbert, M., Khoury, M., Yacobson, E., Doran, P.J., and others. (2017) Pet Project or Best Project? Online Decision Support Tools for Prioritizing Barrier Removals in the Great Lakes and Beyond. Fisheries, 42 (1). pp. 57-65. ISSN 0363-2415. (doi:10.1080/03632415.2016.1263195) (KAR id:60623)

Abstract

Structures that block movement of fish through river networks are built to serve a variety of societal needs, including transportation, hydroelectric power, and exclusion of exotic species. Due to their abundance, road crossings and dams reduce the amount of habitat available to fish that migrate from the sea or lakes into rivers to breed. The benefits to fish of removing any particular barrier depends on its location within the river network, its passability to fish, and the relative position of other barriers within the network. Balancing the trade-offs between ecological and societal values makes choosing among potential removal projects difficult. To facilitate prioritization of barrier removals, we developed an online decision support tool (DST) with three functions: (1) view existing barriers at various spatial scales; (2) modify information about barriers, including removal costs; and (3) run optimization models to identify portfolios of removals that provide the greatest amount of habitat access for a given budget. A survey of available DSTs addressing barrier removal prioritization indicates that barrier visualization is becoming widespread but few tools allow dynamic calculation of connectivity metrics, scenario analysis, or optimization. Having these additional functions, our DST enables organizations to develop barrier removal priorities based on

cost-effectiveness in restoring aquatic connectivity.

Item Type: Article
DOI/Identification number: 10.1080/03632415.2016.1263195
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
H Social Sciences > HA Statistics > HA33 Management Science
Q Science > QH Natural history > QH75 Conservation (Biology)
S Agriculture > SH Aquaculture. Fisheries. Angling
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Jesse O'Hanley
Date Deposited: 01 Mar 2017 15:19 UTC
Last Modified: 19 Sep 2023 15:03 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/60623 (The current URI for this page, for reference purposes)

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