High value of ecological information for river connectivity restoration
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Abstract
Context
Efficient restoration of longitudinal river connectivity relies on barrier mitigation prioritization tools that incorporate stream network spatial structure to maximize ecological benefits given limited resources. Typically, ecological benefits of barrier mitigation are measured using proxies such as the amount of accessible riverine habitat.
Objectives
We developed an optimization approach for barrier mitigation planning which directly incorporates the ecology of managed taxa, and applied it to an urbanizing salmon-bearing watershed in Alaska.
Methods
A novel river connectivity metric that exploits information on the distribution and movement of managed taxon was embedded into a barrier prioritization framework to identify optimal mitigation actions given limited restoration budgets. The value of ecological information on managed taxa was estimated by comparing costs to achieve restoration targets across alternative barrier prioritization approaches.
Results
Barrier mitigation solutions informed by life history information outperformed those using only river connectivity proxies, demonstrating high value of ecological information for watershed restoration. In our study area, information on salmon ecology was typically valued at 0.8–1.2 M USD in costs savings to achieve a given benefit level relative to solutions derived only from stream network information, equating to 16–28% of the restoration budget.
Conclusions
Investing in ecological studies may achieve win–win outcomes of improved understanding of aquatic ecology and greater watershed restoration efficiency.
Publication type | Article |
---|---|
Publication Subtype | Journal Article |
Title | High value of ecological information for river connectivity restoration |
Series title | Landscape Ecology |
DOI | 10.1007/s10980-017-0571-2 |
Volume | 32 |
Issue | 12 |
Year Published | 2017 |
Language | English |
Publisher | Springer |
Contributing office(s) | Coop Res Unit Leetown |
Description | 10 p. |
First page | 2327 |
Last page | 2336 |
Country | United States |
State | Alaska |
Other Geospatial | Big Lake watershed |
Google Analytic Metrics | Metrics page |