Use of Simulated Annealing for Identifying Essential Fish Habitat in a Multispecies Context

Use of Simulated Annealing for Identifying Essential Fish Habitat in a Multispecies Context Abstract: Essential fish habitat (EFH) is defined under U.S. federal law, which mandates its protection. Current single‐species approaches to identifying EFH for suites of managed species have resulted in areas designated for protection that are so large that protecting fish habitat has been difficult in the context of fishery management. We evaluated the potential for simulated annealing, a type of mathematical optimization, as a tool for simultaneously identifying EFH for multiple species in four ecological regions of the eastern continental shelf of the United States. Data were obtained from a shelf‐wide trawl survey with site‐specific abundance information spanning 37 years. The data were averaged within units of a sampling grid with 10‐minute squares. We used computer software with an objective function that includes a term for weighting the boundary length of selected sampling units and thereby identifies solutions that meet specific targets for representation under varying degrees of spatial aggregation. We defined representation as a percentage of the cumulative sampled abundance of individual species and examined the effects of these target values and spatial constraints on total (sea‐surface) area and boundary length of solution sets. We also evaluated the algorithm for its ability to select areas where juveniles occurred at high densities as a proxy for habitat value. Annealing solutions covered less total area than would the combined habitats of individual species that capture the same proportion of population abundance. For most species in most solutions, high‐density areas were selected in higher proportions to their relative abundance in a region and solutions contained less total habitat area and smaller boundary lengths. Additionally, sampling units were distributed among two or more discrete localities versus a single location for the same target level of representation. We suggest that simulated annealing is a viable tool for EFH planning with the potential for identifying more spatially conservative habitat areas for protection than a single‐species approach. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Conservation Biology Wiley

Use of Simulated Annealing for Identifying Essential Fish Habitat in a Multispecies Context

Conservation Biology, Volume 19 (3) – Jun 1, 2005

Loading next page...
 
/lp/wiley/use-of-simulated-annealing-for-identifying-essential-fish-habitat-in-a-0AqzyHbWbg
Publisher
Wiley
Copyright
Copyright © 2005 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0888-8892
eISSN
1523-1739
DOI
10.1111/j.1523-1739.2005.00613.x
Publisher site
See Article on Publisher Site

Abstract

Abstract: Essential fish habitat (EFH) is defined under U.S. federal law, which mandates its protection. Current single‐species approaches to identifying EFH for suites of managed species have resulted in areas designated for protection that are so large that protecting fish habitat has been difficult in the context of fishery management. We evaluated the potential for simulated annealing, a type of mathematical optimization, as a tool for simultaneously identifying EFH for multiple species in four ecological regions of the eastern continental shelf of the United States. Data were obtained from a shelf‐wide trawl survey with site‐specific abundance information spanning 37 years. The data were averaged within units of a sampling grid with 10‐minute squares. We used computer software with an objective function that includes a term for weighting the boundary length of selected sampling units and thereby identifies solutions that meet specific targets for representation under varying degrees of spatial aggregation. We defined representation as a percentage of the cumulative sampled abundance of individual species and examined the effects of these target values and spatial constraints on total (sea‐surface) area and boundary length of solution sets. We also evaluated the algorithm for its ability to select areas where juveniles occurred at high densities as a proxy for habitat value. Annealing solutions covered less total area than would the combined habitats of individual species that capture the same proportion of population abundance. For most species in most solutions, high‐density areas were selected in higher proportions to their relative abundance in a region and solutions contained less total habitat area and smaller boundary lengths. Additionally, sampling units were distributed among two or more discrete localities versus a single location for the same target level of representation. We suggest that simulated annealing is a viable tool for EFH planning with the potential for identifying more spatially conservative habitat areas for protection than a single‐species approach.

Journal

Conservation BiologyWiley

Published: Jun 1, 2005

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off