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Uso de Recocido Simulado para la Identificación de Hábitat Esencial para Peces en un Contexto Multiespecífico
Author(s) -
COOK ROSAMONDE R.,
AUSTER PETER J.
Publication year - 2005
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/j.1523-1739.2005.00613.x
Subject(s) - habitat , abundance (ecology) , relative species abundance , environmental science , weighting , sampling (signal processing) , fishery , marine protected area , population , geography , ecology , computer science , biology , sociology , computer vision , radiology , medicine , demography , filter (signal processing)
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.