Evaluating fisheries management advice for some North Sea stocks: is bias inversely related to stock size

Abstract Biological scientific advice is often used as input into fisheries management of commercially exploited fish stocks. The quality of that advice is often debated in public discourses but is much less often formally evaluated. We looked at the scientific advice provided by the International Council on the Exploration of the Sea (ICES) for some North Sea stocks (cod, haddock, plaice and sole) over the period 1980-2002 in order to assess the quality of the scientific advice. We compared the predicted landings from the scientific advice with the realized landings in the fishery and also evaluated the estimates of fishing mortality and spawning stock biomass in predictions and in the most recent stock assessments. We found that for North Sea stocks considered, there have periods of overestimation and periods of underestimation of spawning stock size. As can be expected, bias in fishing mortality is generally opposite to the bias observed for SSB. Bias tends to be larger in the short term forecasts compared to the stock assessment results. For the two flatfish stocks, there appears to have been a negative relationship between the bias in SSB and the size of the stock, indicating that low stocks are overestimated and large stocks are underestimates. This relationship is less clear for the two roundfish stocks

Limiting inter-annual variation in total allowable catch strategies. An application to ICES roundfish stocks

This study evaluated through simulation management strategy that stabilise catch levels by setting bounds on the inter-annual variability in Total Allowable Catches (TACs). An integrated modelling approach was used, which modelled both the ‘real’ and observed systems and the interactions between all system components. The modelling framework therefore allowed evaluation of the robustness of candidate management strategies to both the intrinsic properties of the systems, and the ability to observe, monitor, assess and control them. Strategies were evaluated in terms of level of risk (measured as the probability of spawning stock biomass falling below the biomass limit reference level for the stock) and cumulative yield. The simulation approach used provides a powerful tool for the examination of the performance of candidate management strategies. It has shown that better management is not necessarily going to be achieved by improving the assessement, since even with a perfect assessment (where the simulated working group knew stock status perfectly) stocks may crash at fishing levels that standard stochastic projections would suggest were safe. Also explicitly modelling the assessment process can result in quite different outcomes than those predicted by the simple projection traditionally used by stock assessment working groups. This is because the simple projection assumes that the status of the stock in the current year is known without error and that the target fishing mortality can be achieved without error. However, in practice the assessment is based on last years data and the effect of any management measure on SSB is only manifest, following the implementation of the quota, at the end of the following year. The choice of target and fishing mortality levels and minimum stock levels results from ICES interpretation of the precautionary approach. This lead to the definition of fishing mortality and biomass reference points that are intended to prevent over-fishing and to trigger recovery plans when a stock is overfished respectively. Although, fishing mortality and biomass reference points were originally intended to be independent, a fishing mortality level implies a corresponding biomass level. In the case of saithe a fishing mortality of 0.40 (i.e. the FPA level) would drive the stock to Blim, suggesting that the choice of biomass and target reference points are not consistent for this stock

Limiting inter-annual variation in total allowable catch strategies. An application to ICES roundfish stocks

This study evaluated through simulation management strategy that stabilise catch levels by setting bounds on the inter-annual variability in Total Allowable Catches (TACs). An integrated modelling approach was used, which modelled both the ‘real’ and observed systems and the interactions between all system components. The modelling framework therefore allowed evaluation of the robustness of candidate management strategies to both the intrinsic properties of the systems, and the ability to observe, monitor, assess and control them. Strategies were evaluated in terms of level of risk (measured as the probability of spawning stock biomass falling below the biomass limit reference level for the stock) and cumulative yield. The simulation approach used provides a powerful tool for the examination of the performance of candidate management strategies. It has shown that better management is not necessarily going to be achieved by improving the assessement, since even with a perfect assessment (where the simulated working group knew stock status perfectly) stocks may crash at fishing levels that standard stochastic projections would suggest were safe. Also explicitly modelling the assessment process can result in quite different outcomes than those predicted by the simple projection traditionally used by stock assessment working groups. This is because the simple projection assumes that the status of the stock in the current year is known without error and that the target fishing mortality can be achieved without error. However, in practice the assessment is based on last years data and the effect of any management measure on SSB is only manifest, following the implementation of the quota, at the end of the following year. The choice of target and fishing mortality levels and minimum stock levels results from ICES interpretation of the precautionary approach. This lead to the definition of fishing mortality and biomass reference points that are intended to prevent over-fishing and to trigger recovery plans when a stock is overfished respectively. Although, fishing mortality and biomass reference points were originally intended to be independent, a fishing mortality level implies a corresponding biomass level. In the case of saithe a fishing mortality of 0.40 (i.e. the FPA level) would drive the stock to Blim, suggesting that the choice of biomass and target reference points are not consistent for this stock

Site formation and chronology of the new Paleolithic site Sima de Las Palomas de Teba, southern Spain

The newly identified Paleolithic site Sima de Las Palomas de Teba hosts an almost seven -m-thick sediment profile investigated here to elucidate the rock shelter's chronostratigraphy and formation processes. At its base, the sediment sequence contains rich archeological deposits recording intensive occupation by Neanderthals. Luminescence provides a terminus ante quem of 39.4 ± 2.6 ka or 44.9 ± 4.1 ka (OSL) and 51.4 ± 8.4 ka (TL). This occupation ended with a rockfall event followed by accumulation of archeologically sterile sediments. These were covered by sediments containing few Middle Paleolithic artifacts, which either indicate ephemeral occupation by Neanderthals or reworking as suggested by micromorphological features. Above this unit, scattered lithic artifacts of undiagnostic character may represent undefined Paleolithic occupations. Sediment burialagesbetweenabout23.0±1.5ka(OSL)and40.5±3.4ka(pIRIR)provideanUpperPaleolithicchronology for sediments deposited above the rockfall. Finally, a dung-bearing Holocene layer in the upper most part of the sequence contains a fragment of a human mandible dated to 4032 ± 39 14C yr BP. Overall, the sequence represents an important new site for studying the end of Neanderthal occupation in southern Spain

A baseline for the genetic stock identification of Atlantic herring, Clupea harengus, in ICES Divisions 6.a, 7.b-c

Atlantic herring in International Council for Exploration of the Sea (ICES) Divisions 6.a, 7.b-c comprises at least three populations, distinguished by temporal and spatial differences in spawning, which have until recently been managed as two stocks defined by geographical delineators. Outside of spawning the populations form mixed aggregations, which are the subject of acoustic surveys. The inability to distinguish the populations has prevented the development of separate survey indices and separate stock assessments. A panel of 45 single-nucleotide polymorphisms, derived from whole-genome sequencing, were used to genotype 3480 baseline spawning samples (2014-2021). A temporally stable baseline comprising 2316 herring from populations known to inhabit Division 6.a was used to develop a genetic assignment method, with a self-assignment accuracy greater than 90%. The long-term temporal stability of the assignment model was validated by assigning archive (2003-2004) baseline samples (270 individuals) with a high level of accuracy. Assignment of non-baseline samples (1514 individuals) from Divisions 6.a, 7.b-c indicated previously unrecognized levels of mixing of populations outside of the spawning season. The genetic markers and assignment models presented constitute a 'toolbox' that can be used for the assignment of herring caught in mixed survey and commercial catches in Division 6.a into their population of origin with a high level of accuracy

A baseline for the genetic stock identification of Atlantic herring, Clupea harengus, in ICES Divisions 6.a, 7.b-c

Atlantic herring in International Council for Exploration of the Sea (ICES) Divisions 6.a, 7.b-c comprises at least three populations, distinguished by temporal and spatial differences in spawning, which have until recently been managed as two stocks defined by geographical delineators. Outside of spawning the populations form mixed aggregations, which are the subject of acoustic surveys. The inability to distinguish the populations has prevented the development of separate survey indices and separate stock assessments. A panel of 45 single-nucleotide polymorphisms, derived from whole-genome sequencing, were used to genotype 3480 baseline spawning samples (2014-2021). A temporally stable baseline comprising 2316 herring from populations known to inhabit Division 6.a was used to develop a genetic assignment method, with a self-assignment accuracy greater than 90%. The long-term temporal stability of the assignment model was validated by assigning archive (2003-2004) baseline samples (270 individuals) with a high level of accuracy. Assignment of non-baseline samples (1514 individuals) from Divisions 6.a, 7.b-c indicated previously unrecognized levels of mixing of populations outside of the spawning season. The genetic markers and assignment models presented constitute a 'toolbox' that can be used for the assignment of herring caught in mixed survey and commercial catches in Division 6.a into their population of origin with a high level of accuracy

A new era for science-industry research collaboration – a view towards the future

Direct engagement of the fishing industry in the provision and co-creation of knowledge and data for research and management is increasingly prevalent. In both the North Atlantic and North Pacific, enhanced and targeted engagement is evident. More is needed. Science-Industry collaborative approaches to developing questions, collecting data, interpreting data, and sharing knowledge create opportunities for information transfer and improved understanding of ecosystem interactions, stock dynamics, economic incentives, and response to management. These collaborations require clear communication and awareness of objectives and outcomes. These initiatives also require careful attention to conditions and interactions that foster respect, trust, and communication. Respect is critical and entails acknowledging the respective skills and expertise of both scientists and fishers. Trust is needed to build confidence in the information developed and its use. Communication is essential to maintain relationships and leverage shared insights. To assess current trends and future opportunities related to this type of engagement, we convened a networking session of research scientists, industry scientists, industry leaders, and fishers at the Annual Science Meeting of the International Council for the Exploration of the Sea (ICES) to address the following questions: (1) What are scientific needs that could be addressed with industry-collected data or knowledge? And (2) How can science-industry collaboration be made sustainable? Here we identify opportunities and acknowledge challenges, outline necessary conditions for respectful and sustainable collaborative research, and highlight ways to promote stakeholder involvement in developing science. We address industry concerns and solicit industry advice. We also address challenges to scientists in ensuring standards for scientific data, conflict of interest, and applying information to advise management. The discussions in this session and subsequent correspondence have led to a set of guidelines and best practices that provide a framework to advance further collaboration between industry and research science. We identify opportunities for directed engagement. We also detail potential approaches to clarify expectations and develop avenues for iterative communication and engagement to sustain collaborative efforts over time. The intent is to improve and expand data streams and contextual understanding of ecosystem processes, stock assessment, and socio-economic dynamics to the benefits of science and industry alike