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Seasonal forecasting of mussel aquaculture meat yield in the Pelorus Sound

Authors :
Neelesh Rampal
Niall Broekhuizen
David Plew
John Zeldis
Ben Noll
Tristan Meyers
Amy L. Whitehead
Nicolas Fauchereau
Jeanie Stenton-Dozey
Source :
Frontiers in Marine Science, Vol 10 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

This study develops a novel approach to forecasting anomalies of meat yield from mussel aquaculture in Pelorus Sound, New Zealand, based on the relationships between non-local sea surface temperature (SST) and observations of mussel meat yield over 13 years. Overall, we found strong associations between lagged SSTs in the Tasman Sea region and mussel meat yield, with a noticeable seasonal cycle in these relationships. Results also showed that oceanic variables such as SST correlate more strongly with mussel meat yield than atmospheric variables, such as surface wind and other indices of atmospheric flow. The relationship between SST and mussel meat yield is linked to patterns of surface wind anomalies along the west coast of New Zealand. We identified regions where the SST was most correlated with mussel meat yield anomalies for each season and derived empirical relationships from linear regression. We then applied these empirical relationships to seasonal forecasts of SST from the European Centre for Medium-Range Weather Forecasts to generate seasonal forecasts of mussel meat yield. By validating our mussel meat yield forecasts from 13 years of retrospective forecasts, we find significant skill at lead times of up to 3 months in December–February and 5 months in September–November. During March-August forecasts are only skillful at a lead-time of 1 month. The results of this study have the potential to improve the accuracy and reliability of mussel meat yield forecasts and to provide valuable insights for the mussel industry.

Details

Language :
English
ISSN :
22967745
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Marine Science
Publication Type :
Academic Journal
Accession number :
edsdoj.209c209226524ca5be0bd3828698d55f
Document Type :
article
Full Text :
https://doi.org/10.3389/fmars.2023.1195921