Improved management of small pelagic fisheries through seasonal climate prediction

Tommasi, Désirée; Stock, Charles A.; Pegion, Kathleen; Vecchi, Gabriel A.; Methot, Richard D.; Alexander, Michael A.; Checkley, David M.

doi:10.1002/eap.1458

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

Improved management of small pelagic fisheries through seasonal climate prediction

2017
By Tommasi, Désirée ; Stock, Charles A. ; Pegion, Kathleen ; ...
Source: Ecological Applications 27(2): 378-388, 2017

Public Access Version Available on: January 01, 2030, 12:00 AM

Please check back on the date listed above.

Details You May Also Like

Details:

Journal Title:

Ecological Applications
Personal Author:

Tommasi, Désirée ; Stock, Charles A. ; Pegion, Kathleen ; Vecchi, Gabriel A. ; Methot, Richard D. ; ... More +

Tommasi, Désirée ; Stock, Charles A. ; Pegion, Kathleen ; Vecchi, Gabriel A. ; Methot, Richard D. ; Alexander, Michael A. ; Checkley, David M. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; PSL (Physical Sciences Laboratory) ; GFDL (Geophysical Fluid Dynamics Laboratory) ; NMFS (National Marine Fisheries Service) ; ... More +

OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; PSL (Physical Sciences Laboratory) ; GFDL (Geophysical Fluid Dynamics Laboratory) ; NMFS (National Marine Fisheries Service) ; NWFSC (Northwest Fisheries Science Center) ; OST (Office of Science and Technology) Less -
Description:

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.
Keywords:

[+]

Climatology Fishery Management Numerical Weather Prediction
Source:

Ecological Applications 27(2): 378-388, 2017
DOI:

https://doi.org/10.1002/eap.1458
Document Type:

Journal Article
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:c309f1015fb9aa869131ce06bc5c24bef0824536b5cc402fc4fc31325e265593
File Type:

Supporting Files:

No Additional Files

More +