title: Improved management of small pelagic fisheries through seasonal climate prediction.
abstract: Populations of small pelagic fish are strongly influenced by climate. The inability of managers to anticipate environment-driven fluctuations in stock productivity or distribution can lead to overfishing and stock collapses, inflexible management regulations inducing shifts in the functional response to human predators, lost opportunities to harvest populations, bankruptcies in the fishing industry, and loss of resilience in the human food supply. Recent advances in dynamical global climate prediction systems allow for sea surface temperature (SST) anomaly predictions at a seasonal scale over many shelf ecosystems. Here we assess the utility of SST predictions at this "fishery relevant" scale to inform management, using Pacific sardine as a case study. The value of SST anomaly predictions to management was quantified under four harvest guidelines (HGs) differing in their level of integration of SST data and predictions. The HG that incorporated stock biomass forecasts informed by skillful SST predictions led to increases in stock biomass and yield, and reductions in the probability of yield and biomass falling below socioeconomic or ecologically acceptable levels. However, to mitigate the risk of collapse in the event of an erroneous forecast, it was important to combine such forecast-informed harvest controls with additional harvest restrictions at low biomass.
authors.affiliation: Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, New Jersey, 08544, USA.|Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton, New Jersey, 08540, USA.
authors.forename: Désirée
authors.initials: D
authors.lastname: Tommasi
authors.affiliation: Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton, New Jersey, 08540, USA.
authors.forename: Charles A
authors.initials: CA
authors.lastname: Stock
authors.affiliation: Department of Atmospheric, Oceanic, and Earth Sciences, George Mason University, Fairfax, Virginia, 22030, USA.
authors.forename: Kathleen
authors.initials: K
authors.lastname: Pegion
authors.affiliation: Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton, New Jersey, 08540, USA.
authors.forename: Gabriel A
authors.initials: GA
authors.lastname: Vecchi
authors.affiliation: Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, Washington, 98112, USA.
authors.forename: Richard D
authors.initials: RD
authors.lastname: Methot
authors.affiliation: Earth System Research Laboratory, Boulder, Colorado, 80305, USA.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Alexander
authors.affiliation: Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, 92093, USA.
authors.forename: David M
authors.initials: DM
authors.lastname: Checkley
mesh_terms: D000818:Animals; D018533:Biomass; D002980:Climate; D003247:Conservation of Natural Resources / Q000379:methods*; D005398:Fisheries; D005399:Fishes; D010140:Pacific Ocean; D019601:Pacific States; D012621:Seasons; D013696:Temperature; D014887:Weather
keywords: Pacific sardine; climate prediction; ecosystem-based management; fisheries management; forage fish; harvest guideline; seasonal forecast