Testing fisheries data sets from port-intercept sampling and reference fleet for approximate representativeness using model validation tools. Presented at IFOMC 2018 in Vigo, panel 5: Assessing bias from monitoring programs.

1. Representativeness in
Norwegian ‘reference fleet’
and ‘intercept sampling’
Assessing representativeness and bias in vessel selection in
commercial catch sampling programs conducted in collaboration
with the industry
Edvin Fuglebakk, Gjert Dingsør, Tom Clegg, Håkon Otterå, Jon
Helge Vølstad

2. Key catch-sampling programs
Reference fleet (High-Seas) Intercept sampling
Sampling
frame
Catches, self-sampled
Vessel > 15m
Landings
Fresh fish
North of 64° N
Selection
14 vessels
Tender 4-6y contracts
Commercial fishing trips
Systematic day visits to landing sites
Intercepts vessels at port arrival
Gears
Trawl
Longline
Gillnet
D. seine
Longline
Gillnet
Jig
Strata Gear Gear - Season (High/Low)
Hierarchy
Area-Quarter
-
Vessel
-
Catch
Site-day
-
landing

3. Reference fleet – coverage (cod)
area / quarter w 2
vessels

4. Reference fleet – temporal and spatial
Clusters: area / quarter

5. Validation
• Model validation approach
• Generic estimators - parameter xp can be
exchanged.
• Estimate of parameters recorded in census:
• xp = catch weight
• xp = position
• xp = time
• Errors quantified in terms of estimated
precision (confidence intervals)

6. Reference fleet - validation

7. Reference fleet - validation

8. Intercept sampling - validation

9. Conclusions
• Classical model validation supports use of key sampling
programs.
• The reference fleet sample well important parameters: catch-
weight, position, time an depth (within clusters).
• Gear not adressed
• Clustering à trade-off with coverage. Total coverage 77% for
cod.

10. Acknowledgement
• Co-authors: Gjert Dingsør, Tom Clegg, Håkon
Otterå, Jon Helge Vølstad
Intercept sampling crew
Reference fleet