The value of spatial information in MPA network design.
The science of spatial fisheries management, which combines ecology, oceanography, and economics, has matured significantly. As a result, there have been recent advances in exploiting spatially explicit data to develop spatially explicit management policies, such as networks of marine protected areas (MPAs). However, when data are sparse, spatially explicit policies become less viable, and we must instead rely on blunt policies such as total allowable catches or imprecisely configured networks of MPAs. Therefore, spatial information has the potential to change management approaches and thus has value. We develop a general framework within which to analyze the value of information for spatial fisheries management and apply that framework to several US Pacific coast fisheries. We find that improved spatial information can increase fishery value significantly (>10% in our simulations), and that it changes dramatically the efficient management approach-switching from diffuse effort everywhere to a strategy where fishing is spatially targeted, with some areas under intensive harvest and others closed to fishing. Using all available information, even when incomplete, is essential to management success and may as much as double fishery value relative to using (admittedly incorrect) assumptions commonly invoked.
Costello
Christopher
C
Bren School of Environmental Science and Management, University of California, Santa Barbara, CA 93106, USA. costello@bren.ucsb.edu
Rassweiler
Andrew
A
Siegel
David
D
De Leo
Giulio
G
Micheli
Fiorenza
F
Rosenberg
Andrew
A
D000818:Animals; D018533:Biomass; D002140:California; D003247:Conservation of Natural Resources / Q000191:economics / Q000706:statistics & numerical data; D017753:Ecosystem; D005398:Fisheries / Q000191:economics / Q000706:statistics & numerical data; D005399:Fishes / Q000254:growth & development; D007814:Larva / Q000254:growth & development; D008386:Marine Biology / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D010140:Pacific Ocean