Tracing the geographic origin of Atlantic cod products using stable
Rationale: Increasing demand for fish and seafood means that
traceability of marine products is becoming ever more important for
consumers, producers and regulators. Highly complex and globalised
supply networks create challenges for verifying the claimed catch
region. Atlantic cod is one of the most commercially important species
in the northeast Atlantic. Several regional fisheries supply cod into
the trade network, of which some are at more risk of overexploitation
than others. Tools allowing retrospective testing of spatial origin for
traded cod products would significantly assist sustainable harvesting of
wild fish, reducing incentives for illegal fishing and fraud.
Methods: Here we investigate whether stable isotope ratios of
carbon, nitrogen and sulfur in muscle tissue can be used to identify the
catch region of Atlantic cod ( Gadus morhua). We measured the
isotopic composition of muscle tissue from 377 cod from ten known catch
regions across the Northeast Atlantic and Northeast Arctic, and then
applied three different assignment methods to classify cod to their
region of most likely origin. The assignment method developed was
subsequently tested using independent known-origin samples.
Results: Individual cod could be traced back to their true
origin with an average assignment accuracy of 70-79% and over 90%
accuracy for certain regions. Assignment success rates comparable to
those using genetic techniques were achieved when the same origin
regions were selected. However, assignment accuracy estimated from
independent samples averaged c25% overall. Conclusion: Stable
isotope techniques can provide effective tools to test for origin in
Atlantic cod. However not all catch regions are isotopically distinct.
Stable isotopes could be used in conjunction with genetic techniques to
result in higher assignment accuracy than could be achieved using either
method independently. Assignment potential can be estimated from
reference datasets, but estimates of realistic assignment accuracy
require independently collected data.