Northwest Fisheries Science Center

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Document Type: Journal Article
Center: NWFSC
Document ID: 7626
Title: Cloudy with a chance of sardines: forecasting sardine distributions using regional climate models
Author: I. C. Kaplan, G. D. Williams, N. A. Bond, A. J. Hermann, S. A. Siedlecki
Publication Year: 2016
Journal: Fisheries Oceanography
Volume: 25
Issue: 1
Pages: 15  27
Keywords: ecological forecasting,sardine,forecast,J-SCOPE,climate,ROMS
Abstract:

Despite the significant advances in making monthly or seasonal forecasts of weather, ocean hypoxia, harmful algal blooms, and marine pathogens, few such forecasting efforts have extended to the ecology of upper trophic level marine species. Here, we test our ability to use short-term (up to nine month) predictions of ocean conditions to create a novel forecast of the spatial distribution of Pacific sardine, Sardinops sagax. Predictions of ocean conditions are derived using output from the Climate Forecast System (CFS) model downscaled through the Regional Ocean Modeling System (ROMS). Using generalized additive models, we estimated significant relationships between sardine presence in a test year (2009) and salinity, temperature, chlorophyll concentration, and dissolved oxygen levels. The top five models had moderate skill (AUC >= 0.8) in predicting sardine distributions, five to eight months in advance. The approach could be used to provide fishery managers with an early warning of distributional shifts of this species, which migrates from the US-Mexico border to as far north as British Columbia, Canada, in summers with warm water and other favorable ocean conditions. We expect seasonal and monthly forecasts of ocean conditions to be broadly useful for predicting spatial distributions of other pelagic and midwater species.

Description:

Despite the significant advances in making monthly or seasonal forecasts of weather, ocean hypoxia, harmful algal blooms, and marine pathogens, few such forecasting efforts have extended to the ecology of upper trophic level marine species. Here, we test our ability to use short-term (up to nine month) predictions of ocean conditions to create a novel forecast of the spatial distribution of Pacific sardine, Sardinops sagax. Predictions of ocean conditions are derived using output from the Climate Forecast System (CFS) model downscaled through the Regional Ocean Modeling System (ROMS). Using generalized additive models, we estimated significant relationships between sardine presence in a test year (2009) and salinity, temperature, chlorophyll concentration, and dissolved oxygen levels. The top five models had moderate skill (AUC >= 0.8) in predicting sardine distributions, five to eight months in advance. The approach could be used to provide fishery managers with an early warning of distributional shifts of this species, which migrates from the US-Mexico border to as far north as British Columbia, Canada, in summers with warm water and other favorable ocean conditions. We expect seasonal and monthly forecasts of ocean conditions to be broadly useful for predicting spatial distributions of other pelagic and midwater species. 

Theme: Ecosystem approach to improve management of marine resources
Foci: Provide scientific support for the implementation of ecosystem-based management
Understand how climate influences ecosystem variability.