Section 3: WKCB2 Term of Reference (a)
Comparative Impact Analysis - Long-term Sustainability Assessment of Traditional vs. Collecting Bag Fisheries
ICES Expert Group
2025-11-06
This analysis addresses WKCB2 Term of Reference (a): Assess whether conservation, technical and management measures are compatible for the purpose of stock conservation and management of targeted fish stocks and bycatch fish stocks in their entirety.
An analytical approach is taken integrating data-rich (Category 1 stock assessments) and data-limited stocks (Category 4) with empirical observer programs for bycatch data (2018-2024) within a simulation framework (FLR tools).
The Barents Sea shrimp trawl fishery primarily targets Northern shrimp (Pandalus borealis) in NEAFC Regulatory Area 27.1.a. The fishery employs mandatory Nordmøre sorting grids (22mm bar spacing) to separate fish from shrimp. However, different gear configurations are in operation by NEAFC member states: S1 (Grid-only: Norway, Russia, Faroe Islands), S2 (Grid + 135mm collecting bag: EU, UK, Iceland south of 62°N), and S3 (Mixed fishery with both configurations).
This study quantifies the differential impacts on bycatch species, with particular focus on stocks subject to rebuilding plans. The major bycatch species are Atlantic cod (Gadus morhua), Greenland halibut (Reinhardtius hippoglossoides) and haddock (Melanogrammus aeglefinus). Secondary bycatch species include Beaked redfish (Sebastes mentella), Golden redfish (Sebastes norvegicus), American plaice (Hippoglossoides platessoides), wolffish (Anarhichas lupus), Capelin (Mallotus villosus), and snow crab (Chionoecetes opilio).
Table 1: Species included in the analysis with ICES stock codes (SID).
| Species | Stock ID | SID |
|---|---|---|
| Northern shrimp (Pandalus borealis) | 27.1.a Barents Sea (NEAFC Reg.) | pra.27.1-2 |
| Cod (Gadus morhua) | 27.1.a, 27.1.b Barents Sea | cod.27.1-2 |
| Haddock (Melanogrammus aeglefinus) | 27.1.a, 27.1.b Barents Sea | had.27.1-2 |
| Greenland halibut (Reinhardtius hippoglossoides) | 27.1.a, 27.1.b Barents Sea | ghl.27.1-2 |
| Beaked redfish (Sebastes mentella) | 27.2.a Norwegian Sea | reb.27.1-2 |
| Golden redfish (Sebastes norvegicus) | 27.2.a Norwegian Sea | reg.27.1-2 |
| American plaice (Hippoglossoides platessoides) | 27.1.a, 27.2.a | ple.27.1-2 |
| Capelin (Mallotus villosus) | 27.1.a, 27.1.b Barents Sea | cap.27.1-2 |
| Wolffish (Anarhichas lupus) | 27.1.a, 27.1.b Barents Sea | |
| Snow crab (Chionoecetes opilio) | 27.1.a, 27.1.b Barents Sea |
The analysis is organised under six main sections:
- 3.1 Stock Assessments - Stock assessment estimates of stock status and biological reference points, and associated data sources.
- 3.2 Life History and Biological Parameters - Growth models, maturity ogives, MCRS, and life history predictions for data-limited stocks.
- 3.3 Gear Selectivity and Bycatch Impact - Selectivity parameters, fate probabilities, and modeled bycatch impacts.
- 3.4 Empirical Bycatch Analysis - Observed catch distributions, age-length keys, and empirical bycatch quantification.
- 3.5 Management Scenario Evaluation - Stock projections, \(F_{MSY}\) reference cases, and multi-fleet dynamics.
- 3.6 Compatibility Assessment and Conclusions - Overall assessment, recommendations, and final conclusions.
3.1 Stock Assessments
Since March 2022, Russian participation in ICES has been suspended. Consequently, Barents Sea stocks (cod, haddock, capelin, beaked redfish, Greenland halibut) are no longer assessed by ICES working groups. Instead, assessments are conducted by the Joint Russian-Norwegian Arctic Fisheries Working Group (JRN-AFWG), using the data, models, and analytical methods as previously employed under ICES. This ensures continuity and comparability of stock advice.
ICES classifies stock assessments based on data availability and availability of analytical methods.
Category 1 Stocks (full quantitative assessments): Atlantic cod (cod.27.1-2), Haddock (had.27.1-2), Greenland halibut (ghl.27.1-2), Beaked redfish (reb.27.1-2), Golden redfish (reg.27.1-2) and Capelin (cap.27.1-2). These stocks benefit from comprehensive data including commercial landings by fleet, discard information, age-structured catch data from commercial and survey sources, and indice of abundance. Age-structured models (e.g. SAM - State-space Assessment Model) are used to estimate fishing mortality, recruitment, and stock numbers-at-age, and reference points.
Category 4 Stocks (data-limited): American plaice (ple.27.1-2), wolffish and snow crab. These stocks rely primarily on catch data of uncertain quality, with limited abundance indices, minimal or no age-structure information, and sparse length-frequency data.
Stock assessment data were extracted from
- ICES Standard Graphs (SID): Time series of catches, fishing mortality, spawning stock biomass, and recruitment with reference points
- SAM Assessment Outputs: Age-structured model results for cod.27.1-2 and had.27.1-2
- FLR stock Database: Age-structured model results for reb.27.1-2 and reg.27.1-2
In addition data on Collecting bag fishery characterization and bycatch composition were from the data calls.
Stock Status Overview
The ICES Standard Graphs database provides historical time series of stock metrics including catch, spawning stock biomass (SSB), fishing mortality (F), and recruitment, along with biological reference points for assessed stocks.
Northern Shrimp (pra.27.1-2) - Target Species
JRN-AFWG advises 2025 catches should not exceed 150,000 tonnes under the \(MSY\) approach. Biomass has remained above \(MSY_{Btrigger}\) and \(B_{lim}\) throughout the time series, with fishing pressure below \(F_{MSY}\) and \(F_{lim}\). The advice employs a fractile rule using 35th percentiles of fishing mortality and biomass distributions.
Figure 1: ICES Standard Graphs for Northern shrimp (pra.27.1-2). Panels show catch, spawning stock biomass (SSB), fishing mortality (F), and recruitment. Dashed reference lines: red=limit (\(B_{lim}\), \(F_{lim}\)), orange=precautionary (\(B_{pa}\), \(F_{pa}\)), green=MSY targets (\(MSY_{Btrigger}\), \(F_{MSY}\)).
For Northeast Arctic Cod (cod.27.1-2) JRN-AFWG advice in 2025 is 311,587 tonnes, a 31% reduction from 2024 and the lowest quota since 2003. SSB is projected to fall below \(B_{pa}\) (460,000 tonnes) in 2025, triggering a precautionary reduction. Fishing pressure is above \(F_{pa}\) but below \(F_{lim}\). Recent below-average recruitment (2019, 2020 year classes) is a cause for concern. The stock requires rebuilding, and so any additional juvenile mortality from collecting bags will conflict with recovery objectives.
In 2025 advice for Northeast Arctic Haddock (had.27.1-2) is 106,912 tonnes (16% reduction). SSB remains above \(B_{pa}\) and \(B_{lim}\), though fishing pressure exceeds \(F_{MSY}\) although below \(F_{pa}\). Stock decline is expected until the strong 2021 year-class fully recruits after age 5 (2026). With respect to bycatch there is only moderate conservation concern, although there is risk of growth overfishing if juveniles are retained.
Catch advice for beaked redfish (reb.27.1-2), based on status quo F (0.077), is for 67,191 tonnes (2025) and 69,177 tonnes (2026). F is currently below \(F_{MSY}\), and SSB above \(B_{pa}\) and \(B_{lim}\). Bycatch hould be minimised.
For golden redfish (reg.27.1-2) a zero catch is recommended for 2025-2026, since F exceeds \(F_{MSY}\), \(F_{pa}\), and \(F_{lim}\); SSB is below \(MSY_{Btrigger}\), \(B_{pa}\), and \(B_{lim}\), and so the stock requires rebuilding. Any retention in collecting bags directly conflicts with zero-catch advice.
Figure 2: ICES Standard Graphs for major bycatch groundfish species (cod.27.1-2, had.27.1-2, reb.27.1-2, reg.27.1-2). Panels show catch, spawning stock biomass (SSB), fishing mortality (F), and recruitment. Dashed reference lines: red=limit (\(B_{lim}\), \(F_{lim}\)), orange=precautionary (\(B_{pa}\), \(F_{pa}\)), green=MSY targets (\(MSY_{Btrigger}\), \(F_{MSY}\)).
For Greenland halibut (ghl.27.1-2) JRN-AFWG in 2024 advice was 15,560 tonnes (16% reduction from 2023). Female SSB slightly above \(B_{pa}\) but declining rapidly, and the harvestable biomass (≥45 cm) is in steep. The harvest rate now exceeds \(HR_{MSY}\), due to recent below-average recruitment coupled with high fishing pressure. 12.1% of collecting bag catches were below MCRS, directly undermining rebuilding efforts.
There is no formal assessment for American Plaice (ple.27.1-2) in the Barents Sea/Norwegian Sea, and it is not considered a primary commercial target occurring mainly as bycatch. Northwest Atlantic populations have experienced historical overfishing. Similarly there is no formal stock assessment for Atlantic wolffish (Anarhichas lupus) in the Barents Sea (ICES Subareas 1-2), which is classified as Category 4 (data-limited) with no specific management regime. ICES provides advice for Icelandic waters (Division 5.a): 9,378 tonnes for 2024/2025. There is low bycatch rates (15.3 kg/hour) and so only small population-level impact is expected from the collecting bag fishery.
JRN-AFWG 2024 advice for Capelin (cap.27.1-2) was 196,000 tonnes (a 216% increase from 2023). Management requires TAC setting ensures ≥200,000 tonnes SSB remains post-spawning with 95% probability. No fishing mortality reference points defined are defined and it’s pelagic nature limits trawl interactions, and so minimal collecting bag impact.
Figure 3: ICES Standard Graphs for secondary species (ghl.27.1-2, cap.27.1-2, ple.27.1-2). Note: shrimp figure repeated for layout consistency. Dashed reference lines: red=limit (\(B_{lim}\), \(F_{lim}\)), orange=precautionary (\(B_{pa}\), \(F_{pa}\)), green=MSY targets (\(MSY_{Btrigger}\), \(F_{MSY}\)).
For snow crab (Chionoecetes opilio) the Norwegian Ministry set a quota of 10,300 tonnes quota for 2024 (an increase of 2,510 tonnes from 2023) based on positive population trends from research surveys. Assessed through Norwegian national procedures, not ICES. Spatial analysis shows limited overlap between shrimp trawling areas and the main crab aggregations in the Loophole; northwestern and southwestern areas show very low crab densities.
3.2 Life History and Biological Parameters
This section establishes the biological foundation for evaluating fishery impacts. Growth patterns, maturity schedules, and minimum conservation reference sizes are compiled from stock assessments and life history databases. These parameters are essential for comparing selectivity patterns to biological reference points and identifying potential overfishing risks.
Growth and Maturity
To identify the potential for growth and recruitment overfishing, maturity ogives are compared across stocks. To ensure sustainability individuals should be allowed to spawn at least once before capture. Since catching fish before they have had a chance to reproduce reduces the spawning stock biomass and the potential number of recruits, increasing the risk of recruitment overfishing and eventual stock collapse Vasilakopoulos, O’Neill, and Marshall (2011). When immature fish are heavily exploited, stocks become dominated by younger, smaller fish. Targeting smaller fish before they mature leads to truncated age and size structures, making stocks more sensitive to environmental variability and reducing their capacity to recover and buffer recruitment fluctuations Brunel and Piet (2013). Persistent early capture can induce selection for earlier maturation at smaller sizes, or other undesirable life-history shifts that affect population resilience and productivity Uusi-Heikkilä et al. (2015). Such fisheries-induced evolution may be hard to reverse, even with management.
The spawn-at-least-once principle is therefore central to sustainability and is often implemented by setting minimum landing sizes or gear restrictions to ensure the majority of individuals have the opportunity to contribute to the next generation before being exposed to fishing mortality. Allowing gear selectivity to target fish before maturity undermines sustainability, productivity, and recovery potential of exploited stocks, and long-term management should strive for selectivity patterns that favour post-maturation exploitation. Therefore for the stocks of interest a Minimum Conservation Reference Size (MCRS) is set, which has been converted to age by applying von Bertalanffy growth equations.
Individual growth is described using the Von Bertalanffy growth model:
\[L(a)=L_{\infty}(1 - e^{-K(a-t_0)})\]
where \(L(a)\) is length at age \(a\), \(L_{\infty}\) is asymptotic length, \(K\) is the growth coefficient, and \(t_0\) is the theoretical age at zero length.
Table 2: Von Bertalanffy growth parameters
| Species | Linf | K | t0 |
|---|---|---|---|
| cod.27.1-2 | 132 | 0.10 | -1.0 |
| ghl.27.1-2 | 120 | 0.08 | -0.5 |
| had.27.1-2 | 112 | 0.15 | -0.8 |
| reb.27.1-2 | 55 | 0.09 | -0.7 |
| reg.27.1-2 | 55 | 0.09 | -0.7 |
Figure 4: Von Bertalanffy growth curves showing length-at-age relationships for key species. Dashed lines indicate MCRS in both length (horizontal) and age (vertical), demonstrating the conversion between length-based and age-based reference sizes.
Table 3: Minimum Conservation Reference Size (MCRS) in length (cm) and age (years)
| Species Code | Length (cm) | Age | |
|---|---|---|---|
| 1 | cod.27.1-2 | 44 | 3.05 |
| 2 | ghl.27.1-2 | 45 | 5.38 |
| 3 | had.27.1-2 | 40 | 2.15 |
| 4 | reb.27.1-2 | 32 | 8.99 |
| 5 | reg.27.1-2 | 32 | 8.99 |
| 7 | ple.27.1-2 | 27 | |
| 8 | wlf | 50 |
The MCRS (Table 3) is compared to the selectivity and maturity-at-age for the category 1 assessments (Table 4, Figure 5).
Table 4: Biological and regulatory reference points for Category 1 stocks showing MCRS, maturity (M50), and selectivity (L50) in both length (cm) and age (years)
| Stock | MCRS (cm) | M₅₀ (cm) | L₅₀ Sel. (cm) | MCRS (years) | A₅₀ Mat. (years) | A₅₀ Sel. (years) |
|---|---|---|---|---|---|---|
| cod.27.1-2 | 44 | 77.2 | 57.3 | 3.1 | 7.8 | 4.7 |
| ghl.27.1-2 | 45 | 5.4 | ||||
| had.27.1-2 | 40 | 70.1 | 51.1 | 2.1 | 5.8 | 3.3 |
| ple.27.1-2 | 27 | |||||
| reb.27.1-2 | 32 | 37.4 | 30.5 | 9.0 | 12.0 | 8.3 |
| reg.27.1-2 | 32 | 36.4 | 39.7 | 9.0 | 11.3 | 13.5 |
| wlf | 50 |
The MCRS is below the selectivity \(L_{50}\) at age, in all cases apart from reg.27.1-2 where it coincides. The \(L_{50}\) is below the age at which 50% of individuals are mature, other than for reg.27.1-2. Therefore, while the MCRS are consistent with the observed selectivities there is potentially a problem for reg.27.1-2.
Figure 5: Selectivity and maturity ogives by stock from ICES assessment data. Red solid line=maturity, blue dashed line=catch selectivity. Dotted vertical lines indicate A₅₀ (age at 50%) for each ogive and MCRS (black).
A summary table of key life-history and assessment parameters for Northeast Arctic Greenland halibut in the Barents Sea was compiled from the most recent ICES AFWG (ICES 2024, 2016), IMR-PINRO joint survey reports (IMR-PINRO 2024, 2025), and published literature. The table provides age-specific values for length (cm), weight (kg), maturity proportion, gear selectivity, and constant natural mortality (M=0.2). Maturity and selectivity ogives reflect typical assessment values for the population under current management (ICES 2022; Wieland, Storr-Paulsen, and Hovgård 1999). Length and weight-at-age are derived from averaged survey datasets (2023–2025), with values matching data used for stock assessment input. Natural mortality estimates follow ICES workshop recommendations (ICES 2022) and are consistent with published age validation studies (Albert, Harbitz, and Høines 2013).
Table 5: Life-history and assessment parameters for Greenland halibut in the Barents Sea
| Age (years) | Length (cm) | Weight (kg) | Maturity | Selectivity | Natural Mortality (M) |
|---|---|---|---|---|---|
| 3 | 32 | 0.20 | 0.00 | 0.10 | 0.2 |
| 4 | 37 | 0.29 | 0.00 | 0.30 | 0.2 |
| 5 | 41 | 0.42 | 0.00 | 0.55 | 0.2 |
| 6 | 45 | 0.54 | 0.00 | 0.75 | 0.2 |
| 7 | 50 | 0.65 | 0.15 | 0.90 | 0.2 |
| 8 | 54 | 0.80 | 0.50 | 1.00 | 0.2 |
| 9 | 58 | 0.96 | 0.85 | 1.00 | 0.2 |
| 10 | 61 | 1.15 | 1.00 | 1.00 | 0.2 |
| 11 | 64 | 1.38 | 1.00 | 1.00 | 0.2 |
| 12 | 66 | 1.44 | 1.00 | 1.00 | 0.2 |
Figure 6: Maturity and catch selectivity ogives for Greenland halibut in the Barents Sea. Red solid line=maturity, blue dashed line=catch selectivity. Dotted vertical lines indicate A₅₀ (age at 50%) for each ogive and MCRS (black, 45 cm ≈ 6 years).
Life History Parameters for Data-Limited Stocks
For species without full stock assessments (Category 4 stocks), life history traits are predicted using the FishLife database. The life history equilibrium approach uses life history invariants to estimate biological reference points when formal stock assessments are not available. This provides a consistent framework for evaluating bycatch impacts across all species, regardless of data availability. These predictions are integrated with ICES assessment data to provide comprehensive biological reference points throughout the analysis. (Note: Detailed FishLife parameter estimation and application are presented in Section 3.4 alongside empirical catch observations.)
3.3 Gear Selectivity and Bycatch Impact
This section analyzes gear selectivity patterns and their consequences for bycatch species. Selectivity parameters are used to model fate probabilities (retention, escape-and-survive, escape-and-die) for different gear configurations. These modeled impacts provide the theoretical foundation for evaluating management scenarios.
Selectivity Parameters
Analysis of selectivity patterns provides a basis for the evaluation of management scenarios to assess impacts. This section compares selectivity patterns across gear configurations, assesses maturity vs selectivity for key species, evaluates overfishing potential, and calculates optimal age.
Gear configurations evaluated:
- S1 (Traditional Trawl): Grid-only operations, where fish that pass through the sorting grid and escape with high survival
- S2 (Collecting Bag): Grid+collecting bag operations, fish diverted to the collecting bag experience additional selectivity with different retention and survival patterns
Table 6: Selectivity parameters for main species. L50=length at 50% retention; SR=selection range; C_contact=contact probability.
| Species | Contact L₅₀ (cm) | Contact SR (cm) | Contact Asym. | Grid Contact Prob. | Grid L₅₀ (cm) | Grid SR (cm) | To Bag Prob. | 35mm Bag L₅₀ (cm) | 35mm Bag SR (cm) | 130mm Bag L₅₀ (cm) | 130mm Bag SR (cm) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| cod.27.1-2 | 10 | 5 | 1 | 0.83 | 18.51 | 3.46 | 0.9 | 13.38 | 2.42 | 39.80 | 14.50 |
| ghl.27.1-2 | 12 | 6 | 1 | 1.00 | 20.22 | 5.46 | 0.9 | 10.74 | 2.20 | 40.10 | 7.71 |
| had.27.1-2 | 8 | 4 | 1 | 1.00 | 14.85 | 4.32 | 0.9 | 12.18 | 2.71 | 46.30 | 10.30 |
| reb.27.1-2 | 8 | 4 | 1 | 0.90 | 13.61 | 3.46 | 0.9 | 9.78 | 1.74 | 35.15 | 9.05 |
| reg.27.1-2 | 8 | 4 | 1 | 0.90 | 13.61 | 3.46 | 0.9 | 9.78 | 1.74 | 35.15 | 9.05 |
Length-Based Selectivity
Selectivity curves are described using a logistic function:
\[P(L)=\frac{C_{contact}}{1+e^{-(L-L_{50})/SR}}\]
where \(P(L)\) is the probability of retention at length \(L\), \(C_{contact}\) is the contact probability (probability that fish encounter the gear), \(L_{50}\) is the length at 50% retention probability, and \(SR\) is the selection range.
Figure 7: Length-based selectivity patterns for grid and mesh configurations. Black dotted vertical lines indicate Minimum Conservation Reference Size (MCRS) for each species.
Age-Based Selectivity
Age-based selectivity is derived by converting age to length using the Von Bertalanffy growth equation (presented above) and then applying the length-based selectivity function.
Figure 8: Age-based selectivity showing retention probability as a function of age for different gear configurations; \(P(a)=P(L(a))\) where \(P(a)\) is the selectivity at age \(a\) and \(L(a)\) is the length at age from the Von Bertalanffy growth model. Black dotted vertical lines indicate age corresponding to Minimum Conservation Reference Size (MCRS) for each species.
Scenario Comparison
This analysis compares final fates under S1 (Traditional Trawl) versus S2 (Collecting Bag). The fate probabilities are calculated as:
- Retained/Landed: Fish that are caught and retained for landing
- Escaped & survived: Fish that escape the gear and survive with probability \(s_{discard}\)
- Escaped & died: Fish that escape but do not survive with probability \((1 - s_{discard})\)
The survival probability for escaping fish differs between scenarios: \(s_{discard}=0.70\) for S2 (collecting bag) and \(s_{discard}=0.90\) for S1 (traditional trawl/grid-only).
Figure 9: Length-based fishery fate probabilities comparing S1 (Traditional Trawl) versus S2 (Collecting Bag) showing retention probability, escape-and-survive probability, and escape-and-die (discard mortality) probability by length class and species. Black dotted vertical lines indicate MCRS for each species.
Figure 10: Age-based fate probabilities comparing S1 versus S2 showing retention, survival, and mortality patterns across life stages. Black dotted vertical lines indicate age corresponding to MCRS for each species.
Fate Probabilities and Modeled Bycatch Impact
Using the selectivity parameters defined above, this subsection quantifies modeled bycatch impacts by estimating juvenile retention rates, calculating catches below MCRS, and assessing discard mortality. Fishery fate probabilities are overlaid with maturity curves to visualize growth overfishing patterns. For cod.27.1-2, had.27.1-2, reb.27.1-2 & reg.27.1-2, ICES assessment maturity ogives are used; for other stocks, FishLife predictions are used.
Age-Based Fate Probabilities
Figure 11: Age-based fishery fate probabilities overlaid with maturity ogives by scenario and stock. Green ribbon=escaped and survived, blue ribbon=retained/landed, red ribbon=escaped and died. Red solid line=maturity ogive, blue dashed line=catch selectivity from ICES assessments (cod.27.1-2, had.27.1-2, reb.27.1-2, reg.27.1-2).
Length-Based Fate Probabilities
Figure 12: Length-based fishery fate probabilities overlaid with maturity curves by scenario and stock. Green ribbon=escaped and survived, blue ribbon=retained/landed, red ribbon=escaped and died. Red solid line=maturity curve, blue dashed line=catch selectivity from ICES assessments (cod.27.1-2, had.27.1-2, reb.27.1-2, reg.27.1-2), both converted from age to length using von Bertalanffy growth parameters.
3.4 Empirical Bycatch Analysis
This section analyzes observed catch data from collecting bag operations to quantify actual bycatch composition and impacts. Unlike the modeled fate probabilities in Section 3.3, this analysis is based on empirical data from observer programs (2018-2024) covering Estonian, Lithuanian, and UK fleets. Age-length keys are developed to convert length-based observations to age-structured catches for comparison with stock assessment data.
Catch Length Distributions
Figure 13: Catch length distributions by codend type and species from collecting bag data. Densities are scaled to maximum=1 within each panel for comparability. Red solid vertical line=length at 50% maturity (L₅₀) derived from FishLife predictions, black dotted line=MCRS.
Life History Parameters
For species without full stock assessments, life history traits are predicted using the FishLife database. The life history equilibrium approach uses life history invariants to estimate biological reference points when formal stock assessments are not available. This is particularly relevant for Category 4 species where data-limited approaches are required.
Figure 14: Catch length distributions overlaid with optimal age and maturity curves by species. Shaded areas represent scaled catch densities by codend type (blue=CD, red=DM35, green=DM130). Purple line=optimal age curve, red solid line=maturity curve, red solid vertical line=L₅₀ maturity, black dotted vertical line=MCRS. All biological references converted to length using von Bertalanffy growth parameters.
Age-Length Keys and Age Distributions
Figure 15: Age-length key showing the probability distribution of age given length for each species. Derived from catch-at-age data. Warmer colors indicate higher probability. Red solid vertical line=age at 50% maturity, black dotted lines=MCRS in both age (vertical) and length (horizontal).
Figure 16: Age distributions by species and codend type. Top row (ICES) shows catch-at-age from stock assessments (cod.27.1-2 2024, had.27.1-2 2023). Lower rows show age distributions from collecting bag data derived using the age-length key. Red solid vertical line=A₅₀ maturity, blue dashed vertical line=A₅₀ selectivity, black dotted vertical line=MCRS age.
Equilibrium Life History Analysis
This subsection examines optimal age-at-capture and growth patterns using life history equilibrium models to evaluate growth overfishing potential.
Figure 17: Optimal age and maturity patterns by species. Purple line=normalized optimal age (age at maximum biomass per recruit), red line=maturity ogive. Red solid vertical line=age at 50% maturity, black dotted line=MCRS age. Shows comparison of when fish reach maximum biomass versus reproductive maturity.
Figure 18: Optimal age and maturity patterns by length. Purple line=normalized optimal age, red line=maturity ogive. Red solid vertical line=length at 50% maturity, black dotted line=MCRS length. Shows the relationship between growth, optimal age-at-capture, and reproductive maturity as a function of fish length.
3.5 Management Scenario Evaluation
Understanding stock productivity is essential for evaluating sustainable harvest strategies and comparing impacts across management scenarios. This section projects stock trajectories under different fishing scenarios, assesses compatibility with rebuilding plans, evaluates risks, and identifies conflicts.
Stock-Recruitment Relationships and Production Functions
This establishes the biological foundation for evaluating: - S1 (Traditional Trawl): Grid-only operations - S2 (Collecting Bag): Grid+collecting bag operations - S3 (Mixed Fishery): Current reality with both configurations
Figure 19: Stock-recruitment relationships fitted with alternative models showing observed data points (gray) and model predictions. Beverton-Holt and Ricker models with two parameterization scenarios.
Figure 20: Production functions showing yield-SSB relationships under different stock-recruitment model assumptions. Gray points=observed data.
\(F_{MSY}\) Reference Case Projections
Figure 21: Cod \(F_{MSY}\) reference case projection showing stock trajectories, harvest rates, and reference points.
Figure 22: Haddock \(F_{MSY}\) reference case projection showing stock trajectories, harvest rates, and reference points.
Figure 23: Beaked Redfish \(F_{MSY}\) reference case projection showing stock trajectories, harvest rates, and reference points.
## [1] "maxfbar has been changed to accomodate new plusgroup"
Figure 24: Golden Redfish \(F_{MSY}\) reference case projection showing stock trajectories, harvest rates, and reference points.
Multi-Fleet Projections (S3: Mixed Fishery)
This section demonstrates S3 (Mixed Fishery) - the current reality in the Barents Sea, with both traditional (grid-only) and collecting bag fleets operating simultaneously.
The projection uses haddock as an example, with: - Target Fleet: Grid-only operations (90% of catch) - Collecting Bag Fleet: CB operations (10% of catch)
This represents the current reality where different flag states use different gear configurations.
Figure 25: Haddock stock overview showing historical trends and reference case projections.
Fleet Configuration:
Two fleet scenario:
- Target Fishery: Traditional shrimp trawl with grid only (90% of catch)
- Collecting Bag Fishery: Shrimp trawl with collecting bag (10% of catch)
Figure 26: Age-based selectivity pattern for haddock fishery.
Projection Setup:
## Solver flags (1=success):## NULLProjection Results:
Figure 27: Biological metrics from projection showing SSB, recruitment, and total biomass trends under two-fleet scenario.
Figure 28: Fleet-specific catch and effort trajectories for target (grid-only) and collecting bag fisheries.
Figure 29: Total stock biomass trajectory under two-fleet scenario with separate catch targets.
Fleet Comparison:
Figure 30: Comparison of catch trajectories between target fishery (grid-only) and collecting bag operations.
The two-fleet projection demonstrates:
- Fleet Dynamics: Independent catch targets maintained across fleets
- Stock Response: SSB and recruitment trends under combined fishing pressure
- Differential Selectivity: Impact of different fleet selectivity patterns
- Management Implications: Total catch allocation between fleet types
This framework enables evaluation of scenarios with varying fleet compositions and catch allocations to assess compatibility with stock conservation objectives.
3.6 Compatibility Assessment and Conclusions
This section provides the overall compatibility assessment, determining support/conflict with conservation objectives, assessing regulatory consistency, and providing stock-specific ratings.
Stock Status Summary
Stocks Under Concern: - Northeast Arctic Cod (cod.27.1-2): Critical - SSB projected below \(B_{pa}\) in 2025, lowest quota since 2003, S2 juvenile retention (1.1%) undermines rebuilding - Greenland Halibut (ghl.27.1-2): Declining - 12% of S2 catches below MCRS, selectivity at age 5 but maturity at age 8, harvest rate exceeds HRmsy - Golden Redfish (reg.27.1-2): Critical - Zero catch advice for 2025-2026, S2 operations conflict with rebuilding requirements
Healthy Stocks: - Northern Shrimp (pra.27.1-2): Target species well managed, compatible with all scenarios - Beaked Redfish (reb.27.1-2): Favorable status, F below \(F_{MSY}\), SSB above reference points
Selectivity and Maturity Analysis
Critical Conservation Issue: For most stocks, catch selectivity occurs before age at maturity, violating the “spawn-at-least-once” principle.
- Greenland halibut: 3-year gap between 50% selectivity (age 5) and 50% maturity (age 8)
- Only Golden redfish allows individuals to mature before full selection
- Current patterns create both growth and recruitment overfishing concerns
Scenario Comparison
S1 (Grid-Only Operations) - [+] Juvenile retention <0.1% for cod and halibut - [+] Supports rebuilding trajectories for all stocks - [+] Compatible with precautionary approach - [+] Fully compatible with conservation objectives
S2 (Collecting Bag Operations)
- [-] Cod: 1.1% juvenile retention undermines rebuilding (delays 2-3
years) - [-] Greenland halibut: 12% juvenile retention - critical
concern - [!] Growth overfishing risk for haddock - [-]
Incompatible with cod and halibut rebuilding
objectives
S3 (Mixed Fishery - Current Reality) - [!] Intermediate outcomes, high variability - [!] Regulatory fragmentation complicates enforcement - [!] Technically feasible but regulatory inconsistency reduces effectiveness
Compatibility Assessment by Stock
| Stock | S1 Status | S2 Status | Overall |
|---|---|---|---|
| Northern Shrimp | [+] Compatible | [+] Compatible | Well managed |
| Cod | [+] Compatible | [-] Incompatible | Critical - rebuilding |
| Greenland Halibut | [+] Compatible | [-] Incompatible | Critical - declining |
| Haddock | [+] Compatible | [!] Moderate | Growth overfishing risk |
| Beaked Redfish | [+] Compatible | [!] Moderate | Data-limited |
| Golden Redfish | [+] Compatible | [-] Incompatible | Zero-catch conflict |
| Capelin | [+] Compatible | [+] Compatible | Minimal interaction |
Overall Compatibility Assessment
Question: Are current conservation, technical and management measures compatible for the purpose of stock conservation and management of targeted fish stocks and bycatch fish stocks in their entirety?
Answer: [+/-] Partially Compatible - with significant variation by scenario
Compatible Elements
- Nordmøre Grid System: Effective mandatory baseline, proven bycatch reduction across all NEAFC member states
- MSY-Based Reference Points: Established for Category 1 stocks, annual assessments provide quantitative basis
- Grid-Only Operations (S1): Fully aligned with conservation objectives, supports rebuilding, low juvenile retention
- Stock Assessment Framework: Robust analytical assessments with life history methods for data-limited stocks
Incompatible Elements
- Collecting Bag Juvenile Retention:
- Cod 1.1% and halibut 12% retention below MCRS undermines rebuilding
- Delays recovery timelines by 2-3 years
- Growth overfishing concerns across multiple species
- Regulatory Fragmentation (S3):
- Inconsistent rules across NEAFC member states
- Different outcomes in same fishing grounds
- Enforcement challenges and uneven playing field
- Incomplete Observer Coverage:
- Current coverage <50% for S2 operations
- Data gaps limit enforcement effectiveness
- Verification impossible without full coverage
Critical Issues Identified
Premature Capture: Selectivity occurs before maturity for most stocks, violating the spawn-at-least-once principle essential for sustainable fisheries
Rebuilding Plan Conflicts: S2 operations directly conflict with cod and halibut rebuilding objectives under current ICES advice
Regulatory Inconsistency: Mixed fishery (S3) creates conservation uncertainty due to different regulations by flag state in the same area
Recommendations
Priority 1 - Regulatory Harmonisation [High Priority] - Establish consistent collecting bag regulations across all NEAFC member states - Eliminate current fragmentation ensuring uniform conservation outcomes
Priority 2 - Enhanced Monitoring [High Priority] - Increase observer coverage to 100% for collecting bag operations - Implement mandatory electronic monitoring systems (EMS) - Real-time data transmission and independent verification
Priority 3 - Stock-Specific Bycatch Limits [Medium Priority] - Develop hard caps for cod and halibut juveniles in S2 operations - Align with rebuilding plans and biological reference points - Real-time monitoring with closure authority
Priority 4 - Research Programme [Lower Priority] - Quantify survival rates and sublethal effects (current assumptions: 90% S1, 70% S2) - Species-specific tagging studies 2026-2029 - Alternative grid design trials
Final Statement
Grid-only operations (S1) are fully compatible with all stock conservation objectives. Collecting bag operations (S2) require additional safeguards including enhanced monitoring, stock-specific bycatch limits, and regulatory harmonisation to protect stocks under rebuilding plans.
The analysis demonstrates that while technical measures are partially compatible, full compatibility requires regulatory harmonisation, enhanced monitoring, and stock-specific bycatch limits aligned with stock rebuilding objectives.