Freezer Trawler as scientific platforms by sustainovate

Improved knowledge of pelagic fish stocks by using commercial data - A practical approach to explore and test the potentials of the Pelagic Freezer Trawler Association in providing valuable information to science and fisheries policy makers in an efficient way. Project report

Collaboration between:

Publication Date: Location:

Pelagic Freezer Trawler Association

Sustainovate

Institute for Marine Research

Centre for Marine Policy

- THE NETHERLANDS

- NORWAY

- THE NETHERLANDS

Monday, 2 January 12 Oslo

This project has been selected for the Dutch Operational Programme “Perspectives for a sustainable fishery industry” and co-‐financed by the European Fisheries Fund.

The European Fisheries Fund Investing in Sustainable Fisheries

“The best management regimes are those based on robust knowledge. A way to maximize the knowledge is to engage the fishing fleet together with the management authorities and research institutions.”,Øystein Lie, Executive manager of MareLife, Biomarine innovation network.

Preface Intention of this study This report describes a practical approach to explore and test the potentials of the Pelagic Freezer Trawler Association in providing valuable information to science and fisheries policy makers in an efficient way. We demonstrate the mutual benefit for fishermen and scientist in exchanging and utilizing data and information on a daily basis. The topic turns out to relate to a mind-‐set in full development, at the time of writing probably more in Norway than in The Netherlands. Nevertheless, what has been achieved in Norway by now is very relevant for the Netherlands fisheries industry. Currently success stories are still limited, but it is clear that fishermen are definitely capable in filling gaps in common fish stock knowledge. Both in Norway and the Netherlands there is an increasing interest in opportunities for fishing vessels to science-‐related activities that serve the common interest. In Norway, several scientific technologies are already in use onboard commercial vessels and its data is being used for improved stock assessment or dedicated projects. The project team This project is fronted by Sustainovate Inc., a solution provider in the marine business environment, and supported by the European Pelagic Freezer Trawler Association (PFA) of Dutch Pelagic Ship-‐owners Association (RVZ), the Centre for Marine Policy (CMP) and the Institute of Marine Research (Norway) and. This cross-‐fertilization between Norwegian and Dutch expertise on fishing industry involvement in stock management is funded by the Dutch Fisheries Innovation Platform and the European Fisheries Fund. Pelagic Freezer Trawler Association -‐ Gerard van Balsfoort Sustainovate -‐ Sytse Ybema, Sven Gastauer Centre for Marine Policy -‐ Martin Pastoors Institute for Marine Research Bergen, Norway -‐ Olav Rune Godø The cooperation between partners is based on recently established relationships: the Observation technology Department within the IMR has provided input on the acoustic chapter and the assessment/management utilization of survey results; CMP, part of Wageningen University & Research Centre, has provided input on describing how to embed business related information in policy processes. The PFA has provided valuable information on onboard data collection opportunities and ideas on improved fisheries management and research approaches. Document structure The document has been structured in such a way that it follows each of these objectives in a logical way. Chapter 1 is an introduction setting the boundaries of this study and justifying why this study has been executed in the first place. Chapter 2can be seen as a chapter exemplifying success stories of fleet involvement in the past. Chapter 3 explains why the PFA was chosen as a case Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

example for potential improved collaboration between science, the industry and authorities. Chapter 4 is a more technical chapter about how why and which data could or should potentially be collected in the future, what are the main benefits and where are drawbacks that need to be considered. Chapter 5 describes the decision making process, how it is at the moment and where the previously described data could fit in. In other words how the collected data could influence the final decision, and hence work towards an improved mutual understanding of the different players involved. Furthermore this chapter points out how long term continuation of the project could be assured.

Figure 1 Structure of the document; From why and how to involve the fleet over to the data collection process up to how to contribute to the decision making process and how to ensure a continuation of fleet involvement

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Chapter 1. Study objective and boundaries ................................................................................... 14 Motivation .............................................................................................................................................. 14 Main goal & objectives ........................................................................................................................... 14 Most relevant questions for industry involvement ............................................................................ 15 Project boundaries ................................................................................................................................. 16 European waters ................................................................................................................................ 16 Target species: Mackerel, horse mackerel, blue whiting and mesopelagics ...................................... 16 Dutch pelagic fleet: Pelagic Freezer Trawler Association ................................................................... 17

Chapter 2. Examples of international success models of fleet involvement ................................... 18 1) Utilizing fish-‐processing time to carry out acoustic surveys .......................................................... 18 2) Sharing standardized commercial catch data with the scientific community ................................ 19 3) Charter vessels for standardized surveys ....................................................................................... 20 5) Fishing company investment in krill survey ................................................................................... 22 6) Continuous electronic monitoring of the catch .............................................................................. 23

Chapter 3. Justification for Dutch fleet involvement ..................................................................... 25 General lack of common knowledge on pelagic fish .............................................................................. 25 Stock specific potentials for fleet involvement ...................................................................................... 25 Blue Whiting (Micromesistius poutassou) ......................................................................................... 26 Atlantic mackerel (Scomber scombrus) .............................................................................................. 29 Horse Mackerel (Trachurus trachurus) .............................................................................................. 31 Mesopelagic fish ................................................................................................................................ 33 Need for fishermen’s technical and maritime competence ................................................................... 34

Chapter 4. Feasibility of the data collection process ...................................................................... 36 Using echosounder data ........................................................................................................................ 39 Basic advantages & recent developments ......................................................................................... 39 Hardware compatibility (sounders and sensors) ................................................................................ 40 Data quality assurance ...................................................................................................................... 47 Analysing opportunistic acoustic data ............................................................................................... 52 Joined forces on acoustic species identification ................................................................................. 53 Optimize the value of commercial catch and environmental data ........................................................ 57 Catch data .......................................................................................................................................... 57 Environmental data ........................................................................................................................... 60

Chapter 5. Feasibility of using commercial data in decision making process .................................. 63 Current knowledge and advisory process .............................................................................................. 65 Who is informing the European Commission on pelagic fisheries? ....................................................... 65 Who takes the final decision? ................................................................................................................ 66 Key uncertainties in the scientific advice and decision making ............................................................. 67 Reasons for closer fishermen’s involvement in the new CFP ................................................................. 67 Key requirements for data and information when applied in scientific advice ..................................... 68 Potential route for involving “new” fisheries data in scientific advice and decision making ................. 68 Route 1: Contributing to ICES ............................................................................................................. 68 Route2: Provide independent second opinions for decision-‐making .................................................. 70 Specific suggested strategies: ................................................................................................................ 71 Ensuring continuation of fleet involvement ........................................................................................... 73

Appendix I .................................................................................................................................... 74 Appendix II ................................................................................................................................... 77 Appendix III .................................................................................................................................. 78 Appendix IV .................................................................................................................................. 79 References .................................................................................................................................... 79 Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Table of tables Table 1: Acoustic equipment, catch sensors, and other hardware components needed (N), desirable (D) or optional (O) to answer the questions formulated within this document and their availability on PFA vessels (light orange = available on all vessels, to dark orange up to now not available on any PFA vessel), in addition the second table indicates which frequencies are needed to allow an acoustic detection of the selected species .................................. 39 Table 2 Instrumentation onboard ICES research vessels (details as specified by ICES in 2009) ........... 42 Table 3 Instrumentation onboard PFA fishing vessels (details provided by the PFA) ........................... 43 Table 4: Comparison between scientifically used EK60, commercially used ES60/70 and the brand new ME70 Simrad echosounders ............................................................................................... 46 Table 5: potentials and benefits of calibrated or uncalibrated (stable or unstable) acoustic system ................................................................................................................................................... 48 Table 6: Benefits of using the calibration module within Myriax Echoview software .......................... 49 Table 7 Technical information about different Simrad Split-‐beam transducers ranging from 18 -‐ 200 kHz, including transmission power and range ........................................................................ 55 Table 8 Catch information directly available online by HERMES .......................................................... 59 Table 9 Comparison of the three main environmental data providers ................................................. 61 Table 10: Comparison of the different temperature data sources ....................................................... 61 Table 11 Comparison of the different current information data sources ............................................. 62 Table 12 Comparison of the different plankton information data sources .......................................... 62 Table of Figures Figure 1 Structure of the document; From why and how to involve the fleet over to the data collection process up to how to contribute to the decision making process and how to ensure a continuation of fleet involvement ............................................................................................ 3 Figure 2 Annual Dutch catches for blue whiting (red), mackerel (blue) and horse mackerel (green) according to ICES from 1950 to 2009 in tons ........................................................................... 25 Figure 3Total (Red surface) and Dutch (blue surface) blue whiting catches from 1950 to 2009 according to ICES in tons ....................................................................................................................... 26 Figure 4 Annual Dutch blue whiting catches from 1950 to 2009 according to ICES in tons ................. 26 Figure 5Total (Red surface) and Dutch (blue surface) Atlantic mackerel catches from 1950 to 2009 according to ICES in tons .............................................................................................................. 29 Figure 6 Annual Dutch Atlantic mackerel catches from 1950 to 2009 according to ICES in tons ......... 29 Figure 7Total (Red surface) and Dutch (blue surface) Horse mackerel catches from 1950 to 2009 according to ICES in tons .............................................................................................................. 32 Figure 8 Annual Dutch Horse mackerel catches from 1950 to 2009 according to ICES in tons ............ 32 Figure 9 Distribution of Horse Mackerel in the Northeast-‐Atlantic: Stock definitions as used by the 2004 WG MHSA. Note that the “Juvenile Area” is currently only defined for the Western Stock distribution area – juveniles do also occur in other areas (like in Di ............................ 32 Figure 10: Illustration of ME70 data; a) data collection or what is seen, b) snapshots of recorded data in time, c) real 3-‐D view of the bottom structure and schools after the data has been processed wit post-‐processing software ............................................................................... 47 Figure 11 Illustration of remotely operated EK60 echosounders via satellite link ................................ 50 Figure 12: Illustration of Marec LSSS, acoustic post-‐processing software; a) Typical workflow within LSSS, c) typical view of LSSS during normal operational phase, including details about Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

a selection, an overview map, information from auxiliary data sources and the echogram, c) detailed view of an echogram and a selected school within LSSS ........................................................ 52 Figure 13: Overview of MyriaxEchoview, acoustic post-‐processing software; a) typical echogram view in MyriaxEchoview software, b) typical Echoview flow chart showing the mind map for separating fish species. The software processes data according to this mind map ....................................................................................................................................................... 53 Figure 14 Visualisation of 2 fish schools at 38 kHz and 200 kHz as seen in MyriaxEchoview] .............. 54 Figure 15 Multiple frequency operation: Mackerel. These five screens captures show how the same school of mackerel is detected and displayed using a Simrad EK60 scientific echo sounder with five operational frequencies in use simultaneously ....................................................... 55 Figure 16 Indication of common PFA fishing grounds and the area where scientific multi-‐ frequency analysis on mackerel or other species where high frequency transducers of 200 kHz are needed would work up to the bottom (green areas). .............................................................. 56 Figure 17 SILLQUID microwave tool to predict fat content .................................................................. 58 Figure 18 Workflow onboard of the Hermes vessel .............................................................................. 59 Figure 19 Current decision-‐making process .......................................................................................... 63

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Executive summary This report describes a practical approach to explore and test the potentials of the Pelagic Freezer Trawler Association in providing valuable information to science and fisheries policy makers in an efficient way. We demonstrate the mutual benefit for fishermen and scientist in exchanging and utilizing data and information on a daily basis. This project is fronted by Sustainovate Inc., a solution provider in the marine business environment, and supported by the Dutch Freezer Trawler Association (PFA), the Centre for Marine Policy (CMP) and the Institute of Marine Research (Norway) and. This cross-‐fertilization between Norwegian and Dutch expertise on fishing industry involvement in stock management is funded by the Dutch Fisheries Innovation Platform and the European Fisheries Fund. The topic turns out to relate to a mind-‐set in full development, at the time of writing probably more in Norway than in The Netherlands. Nevertheless, what has been achieved in Norway by now is very relevant for the Netherlands fisheries industry. Currently success stories are still limited, but it is clear that fishermen are definitely capable in filling gaps in common fish stock knowledge. Both in Norway and the Netherlands there is an increasing interest in opportunities for fishing vessels to science-‐related activities that serve the common interest. In Norway, several scientific technologies are already in use onboard commercial vessels and its data is being used for improved stock assessment or dedicated projects. Unforeseen changes in blue whiting, mackerel stock dynamics and the lack of information on Atlantic horse mackerel is the direct motivation of this study. These circumstances have lead to international disagreements on quota allocation and unnecessary by-‐catches in commercial fisheries. The project limitations form 3 important pelagic fish species in European waters that are essential to the Dutch pelagic industry: blue whiting, Atlantic mackerel and horse mackerel. In addition we touch upon mesopelagic fish that is often found in the same ecosystem. This report describes challenges for these stocks and in an attempt to address the issues and suggest practical solutions. The project team has zoomed in on the following questions of industry involvement in fisheries management: 1. Could we use relative abundance estimates when absolute scientific measurements prove difficult? 2. Can we use commercial data and local knowledge from the fleet to better design and execute scientific surveys and thus to improve scientific stock assessment? How do seasonal distribution patterns change and how does this relate to the snapshot taken during scientific surveys? What does this mean for the value of information from outside the survey season? 3. Can data from core fish aggregations tell us more on fish behaviour and wellbeing in an effort to understand fluctuations in stock size, fish species interactions, the health of the stock or stock differentiation? 4. Can high spatial and temporal resolution data from the fleet in combination with remote sensing data and/or onboard water samplers inform us about fish interactions with the environment and plankton? 5. Could scientists and fishermen co-‐develop acoustic characterisation algorithms that can lead to improved size and species selectivity and thus reduce discarding (e.g. on mackerel and horse mackerel mixed fisheries)? Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Could we use commercial data to improve insight in stock distribution and migration patterns? (e.g. help us understand sudden changes in stock distribution of Atlantic mackerel)? 7. Could monitoring of mesopelagic fish (e.g. absence/presence) be used for pre-‐assessment of the potentials of unexploited stocks? 8. Can sharing of data contribute to corporate sustainability and improved co-‐management? Different models of fleet involvement that are found around the globe illustrate how fishing companies and their vessels can provide valuable data and competence that is needed for improved stock management. Examples range from industry initiated sampling in New Zealand to a more monitoring activity with no direct impact on stock evaluation and management in Europe where all fisheries data is kept for further analysis. Efforts of the commercial fleet to collect and contribute with fisheries data can be justified because each company fully supports the idea of science based fisheries. Secondly, both fishermen and scientists see great benefit in having skippers’ ideas on changing stock dynamics and catch selectivity scientifically tested. Third, PFA skipper’s competencies potentially directly relevant to fisheries research, for example their efficiency in detecting and catching fish and their efficient logistics and operating capabilities in heavy weather. Last, we believe that fisheries data could contribute to improved efficiency in utilization of available scientific surveys effort, in particular surveys that are carried out under the supervision of ICES (International Council for the Exploration of the Seas). As far as the research challenges (see above) are concerned we see a clear added value for the catch-‐, acoustic-‐ and simple environmental data collected by commercial vessels. Acoustic data collected by echosounders and sonars is believed to have the highest potential for revealing behaviour and abundance of migratory, pelagic fish. Utilizing acoustic data In the past, it was argued that data from undirected commercial surveys could not be used for biomass estimates due to high uncertainty. Nowadays, most information provided by fisheries vessels is used for qualitative studies and high uncertainty ranges are taken as given when running any quantitative studies. Although opportunistic acoustic data from fishing vessels proves less suitable for direct quantified fish stock assessments due to the nature of the vessel tracks, some efforts are being made to have fishing vessels run (mini)-‐surveys or to utilize only certain segments of their vessel tracks that resemble scientific surveys the most. Many of today’s echosounders onboard commercial vessels are of scientific quality and support the function of data storage and export, allowing an in-‐depth analysis of the data. However, most data is not stored and is only used for real-‐time fishermen’s observations. All of the PFA vessels are equipped with at least one split beam sounder and transducer (Simrad ES60 available on every vessel) allowing the usage of multiple frequency analysis when more frequencies are made available. These vessels have in addition at least one sonar installed. The South Pacific Regional Fisheries Management Organisation (SPRFMO) standards split vessels into different categories or ‘levels’, according to their acoustic equipment onboard. Based on this classification we can conclude that all vessels can be classified as LEVEL1 research platforms. The acoustic equipment of a typical PFA vessel can be used for tasks such as advanced multi-‐frequency fish species identification, plankton mapping and long term fish mapping. The main efforts for fishing companies to assure high quality acoustic data from fishing vessels are • Minimize water disturbance close to the acoustic transducer, • Minimize acoustic noise that is picked up by the transducer, • Using a well calibrated acoustic system • Assuring continuous data storage and processing Improved knowledge of pelagic fish stocks by using commercial data 8 2 jan 2012

Data processing technology developments have rapidly evolved, especially over the past 3 decades. Fishermen have only been able to profit from these developments to a very limited extend. Joined forces on acoustic species identification If skippers and marine scientists would join forces in the acoustic species identification process, unexpected by-‐catch could be avoided, trawling can be executed more efficiently and species abundance estimates could be more accurate.

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Scientific objectivity relies on methods and protocols Skippers expert judgment to identify fish species is that are truly science based. A scientist needs objective based on the morphology of fish schools or analysis of available information in situations where reflection on various echosounders: typically it the skipper is satisfied with his experience-‐based includes highly complex seasonal, regional and conclusion. Acoustically we can characterise the ecosystem characteristics that they have built up properties when more than one frequency is available. over many years being at sea. Based on this The more (calibrated) transducer frequencies are knowledge individual skippers can create a available the higher is the probability of correct competitive advantage, especially when fishing in identification. Identification is also dependent of specific areas. validation of the acoustic information through catches. Since PFA vessels are not using any acoustic data analysis software at the moment it makes sense to choose a software package that can be used by both scientists AND skippers. Skippers could greatly benefit from the features that are developed by the scientific community. Both the PFA fishing vessels and research vessels use similar echosounders equipped with multiple frequency transducers. However, up to now mainly scientists benefit from the species identification possibilities offered by advanced software. Norwegian scientists have developed a method utilizing the skipper’s experience and observations for training species identification software. Even without computer tools, skippers are masters in species identification. Draining on this competence might be a successful approach to enhance for scientific approach to mutual benefit. Parallel to this development, international scientists are making efforts to include additional information such as school characteristics, day/night characteristics and seasonal characteristics in their detection algorithms. This could add value to fisheries operations and improved selectivity. Getting the most out of the echosounder frequency range The transducers that are connected to the PFA SIMRAD echosounders have different frequencies and thus different detection ranges for fish. The pelagic fish we are focusing on in this study are usually caught shallower than 600m. Although all PFA vessels target mackerel, the 200 kHz acoustic frequency that is often essential to mackerel detection (especially when mixed with other species) is absent on all vessels. As a consequence, if the scientific approach to species identification for mackerel is to be applied onboard commercial vessels, a 200kHz transducer has to be installed, calibrated and working simultaneously with nearly identical and overlapping acoustic beams from lower frequency transducers such as the 38kHz. The physical limitation of this identification method is the constraint of the high frequency transducers (200 kHz) to penetrate the water depths below 200m. Optimize the value of commercial catch and environmental data Standardised catch information provided by the different type of electronic logbooks or fully documented fisheries allows a better integration of catch information into the dataflow of scientific procedures. This also increases the transparency of fisheries operations that satisfy the continuously increasing consumers’ demand for knowledge and the growing markets for eco-‐labelled products such as MSC. Standardised catch and effort data could easily be linked to environmental variables and acoustic data for example to study the importance of certain fishing grounds or to validate or discard typical skippers hypotheses. In many pelagic fisheries the skipper would be interested in more than just the ‘total weight by species’ in his catch. The quality of fish and perhaps even the origin can play an important role in getting the best available price for his catch. Since more seafood requires certification it makes sense to invest in improved catch sampling methods. These methods would reveal not only information about the catch itself but also about the stock when multiple data sources are combined. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Based on Norwegian experiences we have selected the following list of observations that could significantly add value to our common species knowledge: • Fish condition (length/weight relation) • Genetic stock component verification • Fish quality (fat content) Storing catch data in detailed digitized logbooks allows the application of scientific analysis on commercial data and creates a branding opportunity through higher transparency. Sampling can be low-‐budget and easy to perform by measuring length and weight for a few individual fish per species and size class in each catch and additional measurements can be performed when a contract requires this (otoliths, stomachs, genetics, fat content) as seen in recent contract research in Norway. As with acoustic and catch data, environment samples collected by fishing vessels will mainly be associated to the fishing grounds and thus directly related to the physical and biological forcing behind the distribution of the fish. This can be used to our benefit. In general, three important environmental properties behind fish migration can be collected by commercial vessels: water temperature can be collected through net sensors, water movements could be collected through acoustic Doppler measurements and plankton information, as an important indicator for prey availability, can be extracted from echosounder data. Value of plankton sampling Having more knowledge on plankton aggregations’ interaction with fish including impact of diel and seasonal behaviour variation is important for various purposes. It is needed for understanding and predicting of prey abundance and vertical migration behaviour of pelagic fish actively feeding on plankton. Further, satellite sensors’ registrations of plankton, density distributions might be important guiding of information to aggregations of fish during different seasons. Fishermen have acknowledged this link and have started to use satellite images to predict their catch success (for example through GeoEye services). However, a more scientific approach could help both fishermen and science to understand these links. Building up echogram reference databases, assuring an improved detection/discrimination of fish and plankton for fishermen and scientists, could support this avenue. Especially species as mackerel and blue whiting are sometimes mistaken for plankton or vice versa. Commercial data uptake in management process In 2012 the new CFP will be implemented, where a closer involvement of the industry into the decision making process should be granted. Before we look into potential future developments it is essential to understand present decision making process. Secondly, in order to judge where fisheries dependent data could contribute in the decision-‐making process it is important to understand how knowledge is currently treated. The institutions informing the European Commission on pelagic fisheries are ICES as provider of scientific advice, STECF as one of the main communicators and consultants. STECF secure communication between the EC and the other interest groups involved in the conservation and management of pelagic fish. The Pelagic RAC act as advisor on the management of pelagic fish stocks on behalf of the fisheries sector and other interest groups. The final management advice decision is taken by the North East Atlantic Fisheries Commission (NEAFC), that is responsible for recommending measures to promote a rational exploitation of fish stocks in the North East Atlantic, the Coastal states that share the responsibility for managing certain fish stocks and the European Union (EU) that is considered to be one coastal state in the sense of NEAFC. Key requirements for fisheries data and information when applied in scientific advice are: • Credibility: It’s important that the end-‐user knows where the information comes from, how it’s collected and if it has been treated according to agreed (scientific) quality standards. • Saliency: How will new commercial data be relevant for the policy issues that are to be resolved Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Legitimacy: How can we be sure that the new information is unbiased by interests of fishermen. There is a very strong suspicion from scientist that fisheries data could be biased. • Compatibility: How will it link to the current methodology? Does the new information “fit” within the current paradigm/model? What if we collect all kind of new information and it cannot be used because it does not fit into the current model or into the current advisory practice? What is the expected impact of the new information? Potential routes for involving commercial data in scientific advice and decision-‐making are defined as: • Contributing to ICES through improving scientific surveys. PFA roles could potentially be assessing current sampling strategies (e.g. review timing, spatial coverage en effort distribution), improving sampling strategies by providing signals from the fishing grounds prior and during surveys and improving acoustic detection of target species by joint efforts in developing species classification algorithms. • Contributing to ICES assessment groups and fleet sampling programmes. PFA roles could potentially be providing a second opinion on stock dynamics (qualitative or quantitative) or providing quantitative commercial data on real-‐time basis. Real-‐time sampling of the catch enables research institutes, e.g., to decide how to allocate commercial catch sampling resources in time and space. • Contributing to ICES study groups or other expert groups. PFA roles could potentially be creating support for combined scientific and commercial projects in the advisory process or cross-‐fertilisation of new methodologies on fish detection, identification and data use. • Provide second opinions through stakeholder groups such as the Pelagic RAC. The European Commission proposes an agenda for the Reform of the Common Fisheries Policy that is ambitious regarding regionalisation, which means that the role of the Pelagic RAC will only increase in the years to come. The EU and the industry typically fund ad-‐hoc robust projects on stock dynamics, -‐ differentiation and stock health. Studies where commercial-‐ scientific-‐ and auxiliary data are used for knowledge studies could more actively be organised as Public Private Partnerships (PPP) between PFA and scientific institutes or other private specialists. From the total list of potential applications (chapter 1) for industry involvement we believe the following are most relevant to our target species: Blue whiting • Improving existing surveys on the spawning grounds west or Ireland by providing real-‐time distribution maps, school morphology and fecundity information to scientists; • Contributing to model future spawning distribution by providing key ocean observations from the core aggregation areas; • Providing a relative abundance estimate now when the stock is in decline, using a analytical methodology that is currently being developed by Dutch scientists; • Contributing to stock health studies now when the general condition of blue whiting is inexplicable decreasing by providing length/weight measurements on commercial catches; • Contributing to study stock differentiation (north-‐ and south component) and to map year-‐round migration by providing genetic and acoustic data Mackerel Linkage of commercial acoustic and catch data with auxiliary environmental data could help verifying the above hypotheses or provide the directions in which science could focus. Temperature, salinity and currents, all available as live or near real-‐time data from various research institutes could be used to analyse migration patterns by looking at avoidance or preference characteristics of certain areas at different live stages. Acoustic surveys by commercial vessels can be used to estimate a new annual abundance index which performance can be evaluated by a triennial research vessel survey (egg survey). Annual acoustic data obtained from the commercial fishing vessels conducting this survey could provide an economic and timely way to augment the •

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

biennial fishery-‐independent data used to estimate the early life component of the North Atlantic mackerel stock. Other, less effort consuming activities can be: • Co-‐development of acoustic species detection algorithms that can lead to improved selectivity or reduced discarding on mackerel and horse mackerel mixed fisheries; • Contributing to study mackerel differentiation (north-‐ and west component) and to map year-‐round migration by providing genetic and acoustic data. Horse mackerel As we miss detailed knowledge about this species, data provided by fisheries vessel could substantially contribute to our understanding of the distribution and migration of horse mackerel. For example qualitative acoustic information could be used to analyse the occurrence or avoidance of certain areas with given environmental conditions. In combination with catch information, providing basic size class information and hence could be used as a proxy for age, could lead to a general overview of the migration patterns of the stock. Furthermore acoustic data from fisheries vessel could be used as added value to the triennial egg survey. Other, less effort consuming activities can be: • Co-‐development of acoustic species detection algorithms that can lead to improved selectivity or reduced discarding on mackerel and horse mackerel mixed fisheries; • Contributing to the effort of mapping year-‐round migration by providing genetic and acoustic data.

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Chapter 1. Study objective and boundaries Motivation Unforeseen changes in blue whiting, mackerel stock dynamics and the lack of information on Atlantic horse mackerel is the direct motivation of this study. These circumstances have lead to international disagreements on quota allocation for mackerel. With the revision of the Common Fisheries policy running in the background (due to be released in 2012), these developments have encouraged the discussion on industry involvement to increase our common knowledge on pelagic fish stocks. The topic turns out to relate to a mind-‐set in full development, at the time of writing probably more in Norway than in The Netherlands. Nevertheless, what has been achieved in Norway by now is very relevant for the Netherlands fisheries industry. Currently success stories are still limited, but it is clear that fishermen are definitely capable in filling gaps in common fish stock knowledge. Both in Norway and the Netherlands there is an increasing interest in opportunities for fishing vessels to science-‐related activities that serve the common interest. In Norway, several scientific technologies are already in use onboard commercial vessels and its data is being used for improved stock assessment or dedicated projects. A team of Dutch and Norwegian fisheries specialists, fronted by Sustainovate, an opportunistic developer of leads and solution provider in the marine business environment, formulated this feasibility study as starting point of true Dutch fishing industry involvement. Both the European Fisheries Fund as the Dutch Fisheries Innovation Platform, which provides encouragement and support to entrepreneurs throughout the fisheries supply chain, have financially supported this study.

Main goal & objectives This feasibility study aims at testing the potentials of the Pelagic Freezer Trawler Association in providing valuable information to science and fisheries policy makers. The project aims at maximum cross-‐fertilization between Norwegian and Dutch players active in fisheries management (Centre for Marine Policy), industry (Liegruppen AS and Pelagic Freezer Trawler Association), science (Institute for Marine Research and Norwegian veterinary high school) and instrumentation (Simrad and Metas AS). The project is fronted by Sustainovate, a fisheries business development company and solution provider that connects people. Concrete objectives of this study: Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

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Exemplify the benefits of using commercial data to enhanced knowledge in pelagic stocks (Chapter 2. Examples of international success models of fleet involvement) Advise on the usability of fisheries data and how to use this data for better understanding dynamics of the pelagic fish species (Chapter 3. Justification for Dutch fleet involvement). Listing potential sources of fisheries information that can be used for increasing the common knowledge on Atlantic mackerel, blue whiting, horse mackerel and mesopelagic species. In addition we will demonstrate how some of these sources become even more valuable when combined with auxiliary data sources (Chapter 4. Feasibility of the data collection process); Providing practical recommendations on how to start and improve information collection specifically onboard PFA fishing vessels (Chapter 4. Feasibility of the data collection process) Advise on standardization and uptake of fisheries dependent information in the fisheries management processes (Chapter 5)

Most relevant questions for industry involvement This report describes challenges for these stocks and in an attempt to address the issues and suggest practical solutions. The project team has zoomed in on the following questions of industry involvement in fisheries management that will work as a red line throughout this report: 1. Could we use relative abundance when absolute measurements prove difficult? 2. Can we use commercial data and local knowledge from the fleet to better design and execute scientific surveys and thus to improve scientific stock assessment? How do seasonal distribution patterns change and how does this relate to the snapshot taken during scientific surveys? What does this mean for the value of information from outside the survey season? 3. Can data from core fish aggregations tell us more on fish behaviour and fish (stock?) health to understand fluctuations in stock size, fish species interactions, the health of the stock or stock differentiation? 4. Can high spatial and temporal resolution data from the fleet in combination with remote sensing data or onboard water samplers tell us more on fish interactions with the environment and plankton? 5. Could scientists and fishermen co-‐develop acoustic characterisation algorithms that can lead to improved size and species selectivity and thus reduce discarding (e.g. on mackerel and horse mackerel mixed fisheries)? 6. Could we use commercial data to improve insight in stock distribution and migration patterns? (e.g. Help us understand sudden changes in stock distribution of Atlantic mackerel)? 7. Could monitoring of mesopelagic fish (e.g. absence/presence) be used for pre-‐assessment of the potentials of unexploited stocks? 8. Can sharing data contribute to corporate sustainability and improved co-‐management? Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Project boundaries With concrete follow-‐up activities in mind, the project team suggests to perform the first field activities close to home where the challenges are evident: in European waters. Well developed local fishermen’s and scientific knowledge, good remote sensing coverage, good logistics and collaborative fisheries management developments all make European waters the most favourable area for starting to use commercial data. Looking at current management issues, European pelagic fisheries that would benefit most from commercial knowledge are Atlantic mackerel and blue whiting but also management of horse mackerel, mesopelagic species, silversmelt, sprat and herring are based on very limited scientific knowledge Below an explanation of the project boundaries:

European waters The Dutch Ministry of Economic Affairs, Agriculture and Innovation is financially supporting cooperative actions in the fish value chain, partly funded by the European Fisheries Fund (EFF). It is therefore logic that fish stocks in European waters were chosen for this feasibility study. From a scientific point of view it makes sense to start the process of fishermen’s involvement close to the ‘playgrounds’ of the experts involved. Since Norwegian, Danish and Dutch scientists have been invited to take part in several commercial projects it makes sense to focus on the fishing grounds and stocks that they know best: a good knowledge of the local situation is of great importance for successful pilot studies. From a practical point of view, any pilot study or other non-‐conventional project would benefit from simple, local logistics involving crew, information transfer, equipment and time planning. Research in European waters allows relatively short trips and easy access to supplies and staff for Dutch vessels.

Target species: Mackerel, horse mackerel, blue whiting and mesopelagics The project limitations form 3 important pelagic fish species in Western waters and North Sea that are essential to the Dutch pelagic industry: blue whiting, Atlantic mackerel and horse mackerel. The recent mackerel war (see appendix IV) and fading-‐out of blue whiting fisheries have demonstrated the need for more knowledge on these stocks and better collaboration with scientists. However, over the past decade European fisheries scientists have gradually lost their interaction with the pelagic fleet and thus with their early warning system and sparring partner in the field. Only in recent years the pelagic RAC demonstrated good partnership again. In an attempt to develop science-‐based innovation together with the industry we believe that it is essential to target the most important bottlenecks in pelagic fisheries: improving data collection and information flows. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

For blue whiting it is still a mystery what is driving the extreme stock size dynamics that we have witnessed over the past decade. Fishermen state that predictions are very hard and each year it is unclear what to expect in terms of fishing success and fish migration. Only recently some studies are testing hypotheses that the behaviour of the blue whiting stock is largely related to deep ocean currents. Blue whiting remains a species relatively hard to study. It aggregates in large schools during the spawning season and its stock size can be best studied within a limited timeframe (March-‐April) only, in the rough waters west of Ireland. Apart from the relative remoteness of this area to foreign research vessels, this area is classified as one of the roughest seas in the world during spring season and many research days are therefore lost. Most potential for fleet involvement is therefore believed to relate to information about ocean currents at fishing grounds and improved scientific surveys at the spawning grounds (information about the timing and location of the bulk of the stock). Mackerel, despite being one of the commercially most important species, is currently only assessed during a 3-‐annual egg survey, which means that only limited information is available on stock distribution and actual stock size. A similar story counts for horse mackerel. The current expansion of the mackerel stock in Nordic waters doesn’t adhere to national or international boundaries, which has made international stock management a challenging job. Up to now among both scientists and fishermen many different ideas exist on the driving forces behind this migration and the interaction with other pelagic species abundance. Most potential for fleet involvement is therefore believed to relate to distribution mapping using a variety of available methods. Deep-‐sea pelagic fish or mesopelagics are of no commercial interest yet for the Dutch pelagic fleet, but several species are currently harvested by Iceland and Russia. This concerns mainly pearlsides (Maurolicus muelleri) during the saithe fishing season. It’s not very likely that large targeted fishing activities will take place on those species but in general, mesopelagic fish share the same ecosystem with blue whiting and hence could become a profitable auxiliary income. It may be that if we exploit these mesopelagics we will take out an important food source of blue whiting.

Dutch pelagic fleet: Pelagic Freezer Trawler Association The Pelagic Freezer Trawler Association (PFA) fleet counts as the largest pelagic fisheries association in Europe and is known to be trendsetting and active in the legislative decision making process in many ways. Its fleet consists of very advanced fishing vessels that are well equipped for fish tracking, effective capture and basic environmental sampling. This fact makes these vessels, to a certain extent, comparable to any currently available scientific vessel. The PFA fleet generally targets fish species based on released catch quota and among those are Atlantic mackerel, horse mackerel and blue whiting. The 30 vessels of the PFA are owned by few companies, which have shown strong collaboration drives. This makes these companies well suitable for testing ideas on sharing data among vessels and Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

processing fleet-‐based information. Furthermore, project-‐based collaboration with scientific institutes is getting more common for the Association. Recent discussions in relation to the Common Fisheries Policy touch upon a stronger involvement of the offshore fishing fleet in fisheries research in order to reduce research costs and to improve mutual understanding of different marine stakeholders. The principle of renting commercial vessels for scientific research has already been successfully executed in other countries, especially Norway. Consequently the PFA is expected to be an ideal partner when it comes to testing science-‐based innovation in fish stock research and -‐management.

Chapter 2. Examples of international success models of fleet involvement Different models of fleet involvement that are found around the globe illustrate how fishing companies and their vessels can provide valuable data and competence that is needed for improved stock management. Examples range from industry initiated sampling in New Zealand to a more monitoring activity with no direct impact on stock evaluation and management in Europe where all fisheries data is kept for further analysis. The cases that we have selected below are the most prominent models that are currently in use in Norway, completed with 2 cases that we believe are worth mentioning in relation to the pelagic fleet and EU developments.

1) Utilizing fish-‐processing time to carry out acoustic surveys Country: New-‐Zeeland Time period: 2002 -‐ 2003 Participating players: National Institute of Water and Atmospheric Research & fisheries vessels from Independent Fisheries Limited. In some fisheries large factory freezer trawlers have periods of down time as the catch is processed. By utilizing this time, scientific acoustic surveys can be carried out between commercial-‐fishing operations without compromising fishing success. A good example where this idea has successfully been implemented are three acoustic surveys for hoki (Macruronus novaezelandiae) in New Zealand waters during 2002 and 2003 conducted onboard a commercial vessel fitted with a scientifically calibrated SIMRAD ES-‐60 echosounder. These surveys confirmed the presence of a new spawning area for hoki and provided biomass estimates from known fishing grounds. The approach described for this study, works well for small-‐scale acoustic surveys, adjacent to areas of high catch rates and is cost-‐effective, as the vessel “pays for itself” through commercial fishing activities. The major limitation is that the boundaries of the survey area are determined by the time available during processing, which is related to the size of the catch and the time required searching for a suitable location for the next commercial trawl. In the New Zealand hoki surveys, respectively processing time, was typically 3–8 h, which Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

was sufficient to carry out about 10–70 km of acoustic transects. Furthermore, acoustic research was limited to periods of relatively good weather conditions as a hull-‐mounted transducer was used. For more information refer to: Richard L. O'Driscoll and Gavin J. Macaulay Using fish-‐processing time to carry out acoustic surveys from commercial vessels ICES J. Mar. Sci. 2005 62: 295-‐305. Full text available at: http://icesjms.oxfordjournals.org/content/62/2/295.full.pdf

2) Sharing standardized commercial catch data with the scientific community Country: Norway Time period: Since 2000 and ongoing Participating players: IMR (initiator), around 15 Norwegian fishing vessels (Reference Fleet) About: The REFERENCE FLEET is a group of fisheries vessel providing the Norwegian Institute of Marine Research (IMR) with catch and activity information of scientific quality, which is used for management purposes, including stock assessments. Catch and effort statistics are collected in accordance to instruction and under guidance from IMR and are directly used in stock assessment. More time consuming and advanced sampling, e.g. otolith and genetic, can be done onshore from samples collected on board by the fishermen. Starting in 2000 16 high seas and 18 coastal fishing vessels (the Reference Fleet) have been contracted by IMR. The fishing boats are equipped and crewmembers trained to conduct sampling. This trust-‐based cooperation between fishermen and scientists provides a framework for testing official catch statistics, data collecting systems and procedures (e.g. electronic logbooks). The collected information is send to IMR and stored in their scientific database in real-‐time via satellite connection. Additionally IMR has direct email contact with the vessels, access to satellite information and may ask the fleet to spontaneously execute small dedicated surveys or collect additional data according to their compensation plan. Need for industry involvement: To obtain better and continuous samples from the fishing fleet, as well as knowledge about fleet behaviour and technical developments to enhance legitimacy in fish resource management, international authorities advise involvement of all stakeholders in the process Success: The collaboration seems to reduce controversies and build a common understanding and ownership of data, fisheries regulations and management (International evaluation in autumn 2011). Challenges: • Up to now the coverage of all areas and species at the different seasons is not fully accomplished yet, as too few vessels are currently involved in the project • Vessel catch estimates are possibly partly biased when it comes to discards and non targeted species • Constant and consistent training and quality assurance processes are necessary Science benefits: • Improved time-‐space coverage in biological sampling of commercial catches • Possibility to continuously monitor species which are difficult to assess using the traditional survey methodology, e.g. near coastal species and deep sea species • Improved flexibility for testing new survey methodologies that satisfy scientific standards and equipment (e.g. electronic logbooks, discard sampling) • Insight view into the fisheries industry including improved documentation of the entire catch; • Higher flexibility for specific data collection at the right place and at the right moment Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Fisheries industry benefits: • Better stock assessment • Higher involvement in scientific projects, stock assessments and legislations • Quota based advantages • Alternative source of income • Trust based rather than a top down management Authorities benefits: • Very useful results for assessment purposes (improved stock assessment and management plan: “Being at the right place at the right time” • Improved information sources for legislative decision making and quota allocations • Direct insight on the practicability of new legislations More information: http://www.imr.no/filarkiv/2010/08/referanseflaaten.web.2010.pdf/en http://brage.bibsys.no/imr/bitstream/URN:NBN:no-‐bibsys_brage_3676/1/N0506.pdf

3) Charter vessels for standardized surveys Country: Norway Time period: Since 1980’s Participating players: Institute of Marine Research, Bergen and several Norwegian fishing companies (large sized pelagic trawlers) About: Commercial vessels have been used for trawl surveys and acoustic surveys since the beginning of the 1980s. Vessels are being compensated with catch quota. Need for industry involvement: Industry involvement improves the quality of surveys through their unique competence and experience in fishing technology and efficient marine operations. For example operation of fishing gears in relation to wind and current, as well as operation in relation to diel variability. This competence is in particular important to obtain representative samples for identification of acoustic recordings but is also helpful to produce instruction for systematic unbiased sampling. The opportunity to collect biological samples with gears that are not available onboard research vessels, e.g. purse seine is of particular importance. Success: This approach has enhanced survey vessel capacity and improved geographical coverage in limited time. The quality of assessment and management of the commercially most important fish stock have been and are dependent on the capacity and competence from the fleet. Science benefits: • There is an indication that commercial trawls are less selective on fast swimming pelagic species such as mackerel, compared to trawls used onboard scientific vessels (research trawl selects younger, smaller, and perhaps weaker fish). This finding has a significant influence on the acoustic abundance estimation of mackerel. • More flexible use of vessels • Relatively low operational costs compared to scientific vessels. Fisheries industry benefits: • Stable income; • Improved communication with scientists and understanding about their methodologies Improved knowledge of pelagic fish stocks by using commercial data 20 2 jan 2012

• Improved communication allows quicker teaming up for private research activities? • Improved knowledge on fish stocks and ecosystem Authorities benefits: • Different financial models lead to higher efficiency. More information: There are numerous studies that involve chartered commercial vessels the following are simply a few examples of recent studies or surveys involving fisheries vessel. • Joint investigations on mackerel and herring north of the Faroes (8 -‐ 23 July 2010) onboard M/V FinnurFríði XPXP: http://www.google.com/url?sa=t&source=web&cd=4&ved=0CCsQFjAD&url=http%3A%2F%2Fwww.fiskerid ir.no%2Fenglish%2Fcontent%2Fdownload%2F20522%2F188011%2Fversion%2F1%2Ffile%2F100708.pdf&rc t=j&q=acoustics%20brennholm&ei=U_USTtnCOsvAswbUs52HDw&usg=AFQjCNGtSMNYRaB054a-‐ 1Z616qt5neil6g&cad=rja • Using acoustic data from fishing vessels to estimate walleye pollock abundance in the eastern Bering Sea: ftp://ftp.afsc.noaa.gov/posters/pRessler01_acoustic-‐data-‐pollock.pdf • Cruise report from the coordinated ecosystem survey with M/V ”Libas” and M/V ”Brennholm”, M/V “FinnurFridi” and R/V “Arni Fridriksson” in the Norwegian Sea and surrounding waters, 9 July-‐ 20 August 2010: http://www.imr.no/filarkiv/2010/09/toktrapport_nr_7.pdf/en

4) Industry initiated project on mackerel stock identification

Country: Norway Time period: 2009 Participating players: Project partners included the Norwegian School of Veterinary Science, Oslo, Institute of Marine Research, Bergen, NIFES Bergen and fisheries operator Libas AS, the lead partner and the commercial party both being MareLife members. The project was supported by the Research Council of Norway. About: Liegruppen, a trendsetting Norwegian fishing company has taken the initiative to apply new DNA technologies to verify the existence of mackerel stock components. It launched a project, where innovative technologies, which were present within the bio-‐marine innovation network (MareLife), that they are member of, were implemented. The project revealed an extraordinary high level of genetic variation in the North Atlantic mackerel stock, but no evidence of stock segregation to support national stock exclusivities was found. Need for industry involvement: For years the EU have claimed the Biscaya mackerel stock” as an exclusive right. However, the so-‐called “Western stock” (West of Ireland) and the third “North Sea stock” have been co-‐ managed and shared quota wise. As a consequence of this regime, Norway claims it has been given a too small quota, with regards to its historical rights. Consequently, in autumn 2009, Norway and the Faroe Islands granted themselves an exclusive quota, equivalent to the exclusive EU quota in Biscay. This elicited the so-‐ called ”mackerel war”. At the time the mackerel crossed from the Norwegian to the EU zone, the Norwegians believed to be evicted from that zone when attempting to fish, even though they were entitled to do so, through the standing agreement. Against this background and during a critical phase of the negotiations between Norway and EU in January 2010, MareLife was able to step in as potential peacemakers by putting results from a unique genetic mackerel research project initiated by MareLife’s member ‘Liegruppen’ on the table. Success: On January 22 2010, having accepted the results of this project, the EU and Norway concluded a long term mackerel fishing framework agreement based on the principle of common management and exploitation of a common stock. The agreement will enhance stock management and ensure predictability for the fishery operators. According to Øystein Lie of MareLife Biomarine Innovation Network in Norway, the study is typical for how life science research can be used to provide a basis for sustainable management of fish stocks. • Challenges: Securing private funding. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

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More information: http://www.oslo.teknopol.no/English/MainMenu/news2/Newsletters/Oslo-‐Bio/Arkiv/Oslo-‐Bio-‐Update-‐ February-‐2010/Blue-‐and-‐Green/

5) Fishing company investment in krill survey Country: Norway Time period: Since2007 Participating players: Krill fisheries and biotechnology company Aker Biomarine, WWF-‐Norway, Institute of Marine Research, Bergen (IMR), and the Marine Research Assessment Group (MRAG) Ltd. About: Aker BioMarine is an integrated biotechnology company dedicated to harvesting krill and the development of krill-‐derived biotech products. WWF has had an open and direct dialogue with Aker resulting in areas of environmental labelling for fish caught in Norwegian waters and simultaneously combating illegal fishing activities in the Barents Sea. Need for industry involvement: Krill fisheries takes place in remote areas, difficult to survey by scientific vessels. Ongoing effort from WWF-‐Norway and Aker BioMarine to support sustainable fishing practices and to assist in the collection of scientific data to monitor the health and size of the krill biomass in Antarctica have resulted in the offer from the company to place their fishing trawler to the disposal of researchers for a period of 5 days each year. Success: The survey provides fresh data to the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) by which to monitor and set the annual krill fishing quotas. Furthermore it helps to ensure that the current krill fisheries in the Antarctic seas are harvesting on a sustainable level. Dedicating a week of their harvest season to scientific studies, is a substantial commitment and demonstrates Aker's understanding of their responsibility, as members of the world-‐wide community concerned with the health of the Antarctic and its living resources. Challenges • Little value in exchanging public and private research results because of different interests • Working with key scientists to get the method accepted as quickly as possible • Keep this commitment to policy makers and NGO’s since the company has invested one geographical area and one key species. Owning the value chain will make Aker Biomarine adhere more to their own sustainability policies • Making the economy of the vessel (profit) carry the expenses of additional scientific work Science benefits • Acquiring resource data in remote areas: krill, by-‐catch information, sea mammal observations, etc. • Collection of fisheries behaviour data (which goes directly to CCAMLR) Fisheries industry benefits: • The companies’ advantage is to set high standards so that competitors can only enter this market when complying with the rules. • Getting rid of negative sounds by getting MSC certified • Since more seafood is getting certified collaboration with NGO’s and scientists provides a premium in this market Authorities benefits: • Science based information on krill distribution and harvesting. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

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Development of sustainability standards with full transparency from the industry

More information: http://www.akerbiomarine.com/news.cfm?path=143,534&id=3-‐1168

6) Continuous electronic monitoring of the catch Country: Denmark Time period: September 2008 to July 2009 Participating players: The Danish Technical University (DTU) (initiator), several Danish fisheries companies (small to medium sized vessels) About: Full catch documentation by electronic observation through means of CCTV cameras, GPS, hydraulic pressure and rotation of the winch sensors. The approach requires that all catches, not only landings are monitored, reported and can be documented. Need for industry involvement: The present TAC and quota system has for different stocks and in particular demersal stocks not resulted in fishing mortality at desired levels consistent with maximum sustainable yields and for many stocks in Community waters there is a substantial gap between the reported total landings and the actual total outtake of the stock. This project would make the individual fisher responsible for the impact their fishing activities have on the stocks rather than just being accountable for the fish landed. Success: This project has demonstrated that the fishers become more aware of discard areas. In such instances, fishers respond by changing fishing grounds, or making changes to gear or mesh size. The idea of giving the fishers an incentive, by way of a quota increase, is seen as a way forward toward sustainable fishing. The experiences obtained during this pilot have shown that the (low cost) system can be applied on almost all types of pelagic vessels including vessels fishing for sandeel, sprat, blue whiting and Norway pout. Challenges • Preparation of vessels: not all vessels are directly suitable • Manual labour when up-‐scaling the program with semi-‐automated image analysis • Fully automated image processing when up scaling the program • Taking away negative responses from colleague fishermen and fisheries associations Science benefit: • Higher accuracy in biological data collection • Insight view into the fisheries industry, studying fishermen’s behaviour • Verification of VMS data assumptions (steaming, fishing, searching etc.) Fisheries industry benefit: • Closer involvement in stock assessments and legislations verified by their own systems • Improved awareness of own activities • Quota based advantages • In relation to market requirements, some fishermen have pointed to the systems strong advantages compared to the MSC certification scheme Authorities benefit: • Improved information sources for legislative decision making and quota allocations Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

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Improved insight into the fisheries industry Insight into the applicability of released legislations The costs for verifying a vessels fishery using EM is significantly less than obtaining the same information by using human observers onboard.

More information: http://www.aqua.dtu.dk/upload/dfu/pulikationer/forskningsrapporter/204-‐ 09_final_report_of_fully_documented_fishery.pdf

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Chapter 3. Justification for Dutch fleet involvement Efforts of the PFA commercial fleet to collect and contribute with fisheries data can be justified because each company fully supports the idea of science based fisheries. Secondly, both fishermen and scientists see great benefit in having skippers’ ideas on changing stock dynamics and catch selectivity scientifically tested. Third, PFA skipper’s competence is potentially directly relevant to fisheries research, for example their efficiency in detecting and catching fish and their efficient logistics and operating capabilities in heavy weather. Last, scientists, governmental representatives and fishing companies all believe that fisheries data could contribute to improved efficiency in utilization of available scientific surveys effort, in particular surveys that are carried out under the supervision of ICES (International Council for the Exploration of the Seas).

General lack of common knowledge on pelagic fish It has to be recognised that up to now relatively little is known about the reasons for fluctuations in stock abundance and migration patterns, even when it comes to the most commercially important species such as Atlantic mackerel or blue whiting. Although the importance of such knowledge, not only from a conservationist perspective but also for management purposes appears to be obvious when looking at the current status of fisheries facing events such as the recent mackerel war. Several attempts have been undertaken previously, some of which are laid out in more detail within this document, to further involve the fisheries industry as research platforms in order to cope with this lack of knowledge(Gastauer 2010). Main focus will be given to species with a high commercial interest. The following will outline the current commercial importance, the state of knowledge, known unknowns and in how far an involvement of fisheries vessel could increase our understanding of the respective topics.

Stock specific potentials for fleet involvement Three of the main commercially exploited pelagic species, blue whiting, mackerel and horse mackerel have been chosen to exemplify specific needs for fishermen’s input. The graph below illustrates the development of Dutch catches for blue Figure 2 Annual Dutch catches for blue whiting (red), mackerel (blue) whiting, mackerel and horse mackerel in tons and horse mackerel (green) according to ICES from 1950 to 2009 in tons from 1950 to 2009, according to ICES data (Figure 2). The graph clearly shows the famous peak in blue whiting catches of 2004, though declining strongly ever since. Similarly mackerel and horse mackerel catches where at long term high in the late 70s to the mid – 80s or the late 80s to the mid 90s respectively.

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

In the following, we will briefly describe the current state of knowledge (from a scientific and commercial point of view) and how commercial data could address current challenges. Additionally the situation will be described for mesopelagics, whom receive an increasing commercial interest but where most basic knowledge is lacking.

Blue Whiting (Micromesistius poutassou) Stock importance to the industry The graphs below clearly show the very low commercial importance of blue whiting prior to the early 70s. In the Netherlands commercial blue whiting fisheries really started off in the mid 80s. Blue whiting catches clearly peaked in 2004, but are drastically going down ever since.

Figure 3Total (Red surface) and Dutch (blue surface) blue whiting catches from 1950 to 2009 according to ICES in tons

Figure 4 Annual Dutch blue whiting catches from 1950 to 2009 according to ICES in tons

Stock management Until a few years back there were no agreements or managements plan. The peak-‐catch was taken by a free fishery (but not for EU-‐fishermen who always have been restricted by catch limits). Also there have been problems with the management advice: some years ago ICES advised to close the fishery at the time of high abundance due to poor data. This was the reason for The Netherlands to start the blue whiting survey on the spawning grounds in 2004. The ICES recommendation for the Total Allowable Catch (TAC) for 2011 was: 40.100 tonnes (compared to 2.378.000 tons caught 2004, according to ICES, see graphs below). The graphs below illustrate the development of international (Figure 3: Red surface) and Dutch catches (Figure 3: blue surface and more in detail in Figure 4) of blue whiting, from 1950 to 2009, according to ICES. Current assessment is based on scientific survey data (2 acoustic surveys at the time of writing) and fisheries dependent catch data (including discard sampling). It is confirmed from several time series that the year classes 2005-‐2008 are in the very low end of the historical recruitments. The very low recruitment in the last 5-‐6 years means that there is no immediate recovery for the stock even without fishery. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Main biological questions and practical difficulties in studying blue whiting Unexplained stock decline The strong decline of recruitment to the stock in the past few years has lead to marginal fishery quota for blue whiting. The underlying reason for this decline is not fully been understood. Although some fishermen believe that mackerel and hake are competing for food items and might even be predating on blue whiting larvae (source: this project’s questionnaire), fishing pressure and changing ocean currents could all be reasons. After the strong year-‐classes in the early years of the 20th century we call all the other ones poor. This has set our mind and prevents to think more rational on this stock. We have no knowledge on long-‐term dynamics going back more than a few decades so all we have are hypotheses. Apart from a few year-‐classes, recruitment (at age 1) was stable until 1995 from when an increasing trend was observed, which peaked in 2001 at 62 billions (Figure 4). A steep annual decline followed, and since 2005 recruitment has been at 1980s levels. The low recruitment is confirmed by concurrence in survey and catch data (ICES, 2009a). A possible ecological interaction between mackerel and blue whiting has been suggested as one of the causes, as feeding mackerel overlap with blue whiting spawning grounds and predation on blue whiting eggs and larvae could be contributing to the recruitment collapse(ICES, 2009b). According to ICES (ICES, 2010) this should be investigated further. Unexplained decrease in fish condition (weight at age relation) The condition of Blue whiting stocks has been reported to be decreasing substantially over the past 15 years. There are several possible explanations for this overall negative trend: • Lower plankton concentrations in general • Lower plankton concentrations in particular areas and times occupied by blue whiting – an unfortunate match in time and space. • Intra-‐ or interspecific competition – too many fish competing for the same food resource. Survey uncertainties The scientific survey on the spawning grounds has proven difficult to perform due to the large distribution area and bad weather affecting the survey operations. Improving survey timing Survey timing is fixed annually to coincide with the peak of the spawning season. However, peak spawning is not determined solely by time. Other environmental factors including water temperature are believed to highly influence the timing of the spawning season, resulting in a geographical shift of the stock. In some years the bulk of the stock can be located further north than the central spawning area, indicating an earlier migration northwards. Trivially such an offset can lead to huge differences in the stock estimation value of a survey following a fixed annual route, depending on if the bulk of Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

the stock is contained within the survey area or not. This occasional mismatch between survey effort and spawning activity is confirmed by PFA fishermen (source: questionnaire). Apart from this potential mismatch in time it remains largely unknown to scientists and fishermen where blue whiting is to migrate during and outside the spawning season and how this affects the accuracy of the scientific survey. The precision of the blue whiting survey on the spawning grounds west of Ireland is in general believed to be high (PGNAPES, ICES CM 2009/RMC:06) but this does not mean that the result is true. The commercial fleet could substantially decrease the level of uncertainty in this case and better indicate the peak-‐spawning time and areas, if catch data and/or acoustic observations would be made available to scientists prior to a definite planning of the cruise track. Improving survey area coverage In order to use the ICES spawning stock surveys for estimating spawning-‐stock biomass, there has to be confidence that the entire spawning stock is contained within the survey area. Historical research has shown that the spawning area of blue whiting does change, and therefore that it is important that survey practice be reviewed in the light of the knowledge of such changes. With decreasing stock size, the level of detectability uncertainty can increases dramatically due to highly localized aggregations. ICES demonstrated this in 2007 when a large part of the stock was found in a single school. PFA fishermen are familiar with this phenomenon and criticize scientists for not taking appropriate actions to decrease uncertainty (source: questionnaire). The use of sonars or commercial information is mentioned as possible direction for solution. Unknown stock differentiation In the last decade large fluctuations were observed in blue whiting recruitment. The relative amount of eggs, and the proportion of larvae drifting to northern or southern nursery areas (the spawning area may seed northern areas one year and southern areas the other) was varying largely (Skogen et al., 1999). Hátún et al. (2005) has shown a relationship between these apparent changes and the strength of the Sub Polar Gyre. PFA skippers and scientists have mixed opinions on the existence of multiple stock components (source: project questionnaire). Multiple stock components or not, BW remains a widely distributed stock with extensive mixing. Probably the situation is the same as for many other stocks. North Sea herring, plaice and sole have many spawning components. Nevertheless these are not considered as separate stocks. And even when they were they cannot be exploited separately. WGWIDE recommends that the assessment of blue whiting continues to be carried out under the assumption that all blue whiting belongs to 1 stock. Where management and science could benefit from industry involvement From the total list of research questions (chapter 1) for industry involvement we can identify the following applications:

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

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Q1 -‐› Providing a relative abundance estimate now the stock is in decline, using a analytical methodology that is currently being developed by Wageningen IMARES; Q2 -‐› Improving existing surveys on the spawning grounds west or Ireland by providing real-‐time distribution maps, school morphology and fecundity information to scientists and advice on the timing and location of the surveys; Q3 -‐› Contributing to stock health studies now the general condition of blue whiting is inexplicable decreasing by providing length/weight measurements on commercial catches. This could include mackerel stomach samples to study predation on blue whiting larvae; Q4 -‐› Contributing to model future spawning distribution by providing key ocean parameters from the core aggregation areas; Q6 -‐› Contributing to study stock differentiation (north-‐ and south component) and to map year-‐round migration by providing genetic and acoustic data

Atlantic mackerel (Scomber scombrus) Stock importance to the industry Figure 6clearly illustrates the relatively high mackerel catches in the Netherlands during the late 70s to the mid 80s. Nowadays the catches seem rather comparable to the amount caught in the 50s and 60s. The graphs below illustrate the development of international (Figure 5: Red surface) and Dutch catches (Figure 5: blue surface and more in detail in Figure 6) of Atlantic mackerel, from 1950 to 2009, according to ICES.

Figure 5Total (Red surface) and Dutch (blue surface) Atlantic mackerel catches from 1950 to 2009 according to ICES in tons

Figure 6 Annual Dutch Atlantic mackerel catches from 1950 to 2009 according to ICES in tons

Stock managment The absence of agreed management plans and a failure to respect scientific advice have led to the current escalating ‘mackerel war’ pitting the EU and Norway against Iceland and the Faroe Islands. Warming seas, increasing abundance or a combination of both have probably caused the fish to move north. When they arrived in Icelandic and Faroese waters, those nations argued that their Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

mackerel fishing agreement with Norway and the EU should be changed to allow them to catch more. Norway and the EU refused since it was not clear whether this is a temporary migration, so Iceland and the Faeroes tore the agreement up and each awarded themselves a unilateral quota of 150,000 tonnes. As a result, the northeast Atlantic mackerel catch has risen almost 50%, and is now well beyond the replacement rate. Main biological questions and practical difficulties in fishing mackerel Problematic species identification in mixed fisheries Borges et al. (2008) showed that for the Dutch freezer trawler fleet between 2002 and 2005, mackerel was the most important discarded commercial species, accounting for 40% of total pelagic discards. Furthermore, in some of the horse mackerel directed fisheries, mackerel is regarded as by-‐ catch, where an acoustic distinction between both species remains difficult. As the level of discards is greatly influenced by quotas (in a mixed fisheries with horse mackerel), reports from these fisheries have suggested that the amount of mackerel discards could at least partly be explained by the relatively low mackerel quota compared to a relatively high horse mackerel quota and the large mackerel stock. This appears to be especially valid for fisheries carried out by freezer trawlers in the fourth quarter of the year. Slippage is estimated to partly contribute to unaccounted mortality for mackerel (Borges, van Keeken, van Helmond, Couperus, & Dickey-‐Collas, 2008) although there is insufficient information about the frequency of slipping for all fleets. Improved transparency on catch information could deal with this lack of knowledge. Suggested approach: Echosounder-‐ and sonar recordings from areas where the problem of mixed fisheries occurs, accompanied by catch composition information, could help developing improved species detection algorithms to avoid mislead catches. Such algorithms are a software approach of analysing echosounder or sonar data based on scientific knowledge and expert judgement. Fishermen could benefit from up to date scientific tools that increase the ability of distinguishing between mackerel and horse-‐mackerel on sonar and echosounder recordings. Such an increased precision in automated species detection on acoustic images could provide the scientific community with a more in depth knowledge on species co-‐existence and interactions. Unexplained changes in mackerel distribution in northern waters Catch and survey data from recent years indicate that the stock has expanded Northwest wards during spawning and summer feeding migrations. Such changes could be a consequence of observed warming, changes in food availability, other environmental factors (such as changes in currents direction/velocity) and/or increased stock size. At present scientists cannot verify any ongoing trends in migration due to a lack of data and suitable time series. Fishery-‐independent data for this stock is extremely limited, with only a single data point for egg production every three years. ICES WGWIDE encourages research in physical forcing of mackerel stock dynamics and resulting changes in trophic interactions and recruitment variability. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Possible scientific explanations that could be tested by using commercial and auxiliary data The increased temperature observed in the Nordic Seas during summer in recent years (WGNAPES 2010) might have increased the potential habitat for mackerel. The zooplankton biomass has been declining in the Nordic Seas since 2002 (WGNAPES 2010, WD Nøttestad et al. 2010). This could be forcing the pelagic species to expand their feeding areas. The seemingly larger degree of horizontal species segregation in 2010 compared to 2009 (WD Nøttestad et al. 2010), could be due to competition between mackerel and Atlanto Scandian herring during the feeding season and might have forced the herring to the cooler fringe areas. The herring in this area was observed to be in poorer condition than in previous years. Another explanation to the apparent expansion could also be, that due to the increased size of the mackerel stock with a greater number of large individuals, able to migrate long distances foraging for prey. Simultaneously, the timing of peak spawning in the main spawning areas was observed to set off earlier, compared to egg surveys executed in previous years (WGMEGS 2010). While the cause of this remains unknown, changes in the timing of the critical larval stages will most likely affect mortality due to changes in match/mismatch with larval food, as different plankton groups have been shown to react in a different way to temperature fluctuations (Beaugrand et al. 2003). Suggested approach: Linkage of commercial acoustic and catch data with auxiliary environmental data could help verifying the above hypotheses or provide the directions in which science could focus. Temperature, salinity and currents, all available as live or near real-‐time data from various research institutes could be used to analyse migration patterns by looking at avoidance or preference characteristics of certain areas at different live stages. Where management and science could benefit from industry involvement From the total list of potential applications (chapter 1) for industry involvement we believe the following are most relevant: • Q5 -‐› Could scientists and fishermen co-‐develop acoustic species detection algorithms that can lead to improved selectivity or reduced discarding on mackerel and horse mackerel mixed fisheries?; • Q6 -‐› Contributing to study stock differentiation (north-‐ and west component) and to map year-‐round migration by providing genetic and acoustic data.

Horse Mackerel (Trachurus trachurus) Stock importance to the industry It is apparent that there was virtually no commercial horse mackerel fishery in the Netherlands up to the mid 70’s. In the last 30 years, the Netherlands has a proportionally high share of the total catches compared to mackerel and blue whiting. The graphs below illustrate the development of international (Figure 7: Red surface) and Dutch catches (Figure 7: blue surface and more in detail in Figure 8) of horse mackerel, from 1950 to 2009, according to ICES. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

There has been a gradual shift from an industrial fishery for meal and oil towards a human consumption fishery, although the Dutch horse mackerel fishery was always destined for human consumption purposes.

Figure 7Total (Red surface) and Dutch (blue surface) Horse mackerel catches from 1950 to 2009 according to ICES in tons

Figure 8 Annual Dutch Horse mackerel catches from 1950 to 2009 according to ICES in tons

Stock management There are no horse mackerel management agreements between EU and non-‐EU countries. The TAC set by EU therefore only apply to EU waters and the EU fleet in inter-‐ national waters. The western stock (see image below) is considered a management unit and advised accordingly. At present there are no international agreed management and TAC of western horse mackerel. EU has set TACs for western horse mackerel in EU waters since 1987. However, these TACs cover a mixture of western, North Sea and southern horse mackerel areas (Figure 9).

Figure 9 Distribution of Horse Mackerel in the Northeast-‐Atlantic: Stock definitions as used by the 2004 WG MHSA. Note that the “Juvenile Area” is currently only defined for the Western Stock distribution area – juveniles do also occur in other areas (like in Di

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Uncertainties in the assessment Incomplete information on horse mackerel migration and abundance Fishery-‐independent data for this stock is extremely limited, with only a single data point for egg production every three years. In addition, the assessment contains a fecundity model which links the egg production to spawning stock biomass that could be improved if further evidence was obtained on the spawning biology of this stock which at present is considered an indeterminate spawner. That means that fecundity is not determined prior to spawning. Therefore it is not possible currently to provide a realistic estimate of the spawning biomass. The assessment could be improved by the inclusion of information such as survey tuning indices on the numbers at age in the stock. However, obtaining a reliable tuning series is likely to be hampered by the large geographic area in which the stock occurs and the strong variable migration patterns. It does not seem that changes to the modelling methodology alone will fundamentally solve this problem. Another problem is the dependency of fisheries on strong year-‐classes. Traditional assessment methods find it difficult handling this. Problem is that the trend in spawning stock biomass is consistent in the assessment, but the level varies annually. All horse mackerel assessments show problems and we have yet to find the causes. There are only opinions and prejudices. Suggested approach: As we miss detailed knowledge about this species, data provided by fisheries vessel could substantially contribute to our understanding of the distribution and migration of horse mackerel. For example qualitative acoustic information could be used to analyse the occurrence or avoidance of certain areas with given environmental conditions. In combination with catch information, providing basic size class information and hence could be used as a proxy for age, could lead to a general overview of the migration patterns of the stock. Furthermore acoustic data from fisheries vessel could be used as added value to the triennial egg survey. How management and science could benefit from industry involvement From the total list of potential applications (chapter 1) for industry involvement we believe the following are most relevant: • Q5 -‐› Co-‐development of acoustic species detection algorithms that can lead to improved selectivity or reduced discarding on mackerel and horse mackerel mixed fisheries; • Q6 -‐› Contributing to study to map year-‐round migration and contributing to study horse mackerel differentiation (North Sea, Western, Norwegian and Southern component) by providing genetic and acoustic data. Data provided by fisheries vessel could substantially contribute to our understanding of the distribution and migration of horse mackerel.

Mesopelagic fish Stock importance to the industry and current stock assessment ICES advice: No advice given by ICES. No species is currently important to the Dutch pelagic fleet, but several species could become of commercial interest. The following questions would then become relevant: Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

-‐

What is the distribution of selected mesopelagic species with a commercial potential (mainly of lanternfish (Mictophidae), pearlsides (Maurolicus muelleri) and white barracudina (Litlageirsili))? What is their position in the ecosystem, density of these species and what is their commercial potential?

Only very little mesopelagic fish species are exploited commercially. Currently the main species suspected to have potential for a further commercial exploitation are pearlsides. According to Súni et al (2008) none of the mesopelagic species surveyed showed a high potential for commercial exploitation. This is in line with previous Russian studies. Although most species were found all along the surveyed area none showed very high densities (mostly<1g/m3 seawater, min. for good commercial results: 25 g/m3 seawater). Main potential for commercial exploitation are estimated from the family members of lanternfish (Mictophidae), pearlsides (Maurolicus muelleri) and white barracudina (Litlageirsili). Quantitative values about the catches of these species are very sparse. There are no dedicated scientific stock assessments for any mesopelagic species executed on a regular base at the moment. Suggested approach: High spatial and temporal resolution of current by-‐catches and future commercial caches, leading towards an improved insight into the seasonal distribution, migration patterns, dynamics and stock composition of these species. Acoustic species separation and catch information could help developing improved species detection algorithms, define the density of the stocks in certain areas and estimate the commercial potential of these species and simultaneously define the need of a management plan. How management and science could benefit from industry involvement • Q7 -‐› Using acoustic observations and by-‐catches of mesopelagic fish for pre-‐assessment, estimations and potentials of unexploited stocks

Need for fishermen’s technical and maritime competence Detecting fish Fishing vessels are often well equipped with the latest echosounders and sonars to detect fish. Recently, even the latest scientific sounders have been added to their instrumentation, which gives the vessels a benefit in automated echo classification. When skippers add their expert judgement to science based species classification software, the acoustic system becomes even more powerful. Catching fish Several scientific studies have proven that fishing vessels are better in catching a representative sample of the school of fish that was seen on the echosounder (see also chapter 2, case 3). A Norwegian study even revealed that the research vessel was more selective for fish with a weaker condition (Slotte et al., 2007). This alarming signal has direct implications for stock assessment. Most European research vessels are using their echosounder to detect fish and no additional instruments to actually catch the school that was observed on the echosounder. Onboard some scientific vessels the sonar remains unused throughout the survey or cannot be setup for the target species. A substantial part of the detected schools are never caught (personal experience). Fishing vessels would typically use their sonars and net sondes to guide the targeted school into the net. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Planning and logistics Scientific surveys are typically planned by scientists who have, compared to skippers, limited sea going experience. Skippers are obviously dealing with weather, currents, vessel limitations, fuel price development and more on a daily basis, which makes them the most efficient planners at sea. Instead of ad hoc adjustments in survey plans in accordance with abrupt changes in environmental condition, more advanced survey strategies and procedures that enable adequate statistical treatment of skipper induced adjustments should be developed. Operation in heavy weather Most PFA vessels are experienced in fishing even in rough weather condition. Such conditions are more of a ‘routine’ work for fishing vessels rather than for research vessels. Norwegian vessels as developed by Liegruppen Fiskeri AS have even invested in improved stability to acquire offshore projects.

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Chapter 4. Feasibility of the data collection process Before starting a data collection programme it is necessary to understand the added commercial and scientific value of the potential data source. In practice not all scientific sampling programmes provide skippers with knowledge that actually improves their fisheries success and vice versa: not all commercial data is useful to science. In Chapter 1 we have defined the scientific questions that are currently relevant to Atlantic mackerel, horse mackerel and blue whiting. The next step is to define which information or knowledge is needed to answer these questions. Consequently the logical next step is to validate which sensors or sampling techniques are most suitable to collect this information, how often to sample, what would be the costs etc. In order to be able to answer these questions, different kinds of information are needed. The following will summarise the needs: Q1 -‐ Could we use relative abundance when absolute measurements prove difficult? Although opportunistic acoustic data from fishing vessels proves less suitable for direct quantified fish stock assessments due to the nature of the vessel tracks, some efforts are being made to have fishing vessels run (mini)-‐surveys or to utilize only certain segments of their vessel tracks that resemble scientific surveys the most. Q2 -‐ Can we use commercial data and local knowledge from the fleet to better design and execute scientific surveys and thus to improve scientific stock assessment? Acoustic data – School density, Distribution pattern, Relative abundance Echosounder data can act as an exploratory survey and thus provide a crude picture of the stock distribution prior to the scientific survey. School densities, morphology and catchability information can help scientists to prepare their surveys, survey routes and algorithms for acoustic detection of blue whiting including enhanced compatibility over years of the time series. Catch information – electronic logbook, length/weight relationship, and fecundity A crucial contribution to science could be logbook information on standard biological properties such as fish condition, length/weight distributions and fat content. This information can be used to verify the samples that were taken by research vessels. Additionally, fecundity information is important to verify if the geographic distribution of the spawning area. Q3 -‐ Can data from core fish aggregations tell us more on fish behaviour and fish (stock?) health to understand fluctuations in stock size, fish species interactions, the health of the stock or stock differentiation? Acoustic data – School density, Distribution pattern, Relative abundance, plankton & krill (relative abundance)

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Echosounder data can reveal interaction among species at school level when acoustic species characterization techniques are applied. Such techniques can reveal predation behaviour on krill and plankton layers. Catch information – electronic logbook, length/weight relationship, genetic sampling An electronic logbook, collecting standardized catch information is essential to ground-‐truth acoustic observations as described above. Length weight measurements should be included within this logbook, giving a good indication about the condition of the stock that is found feeding on prey species. Genetic sampling can be used for revealing prey species in the stomach of the fish. Q4 -‐ Can high spatial and temporal resolution data from the fleet in combination with remote sensing data or onboard water samplers tell us more on fish interactions with the environment and plankton? Combined acoustic and environment observations from the fleet may supply a unique basis for studying interactions that never could be supplied by standards research surveys. Q5 -‐ Could scientists and fishermen co-‐develop acoustic characterisation algorithms that can lead to improved size and species selectivity and thus reduce discarding? Acoustic data – Distribution pattern Using technologies that have been developed by the scientific community, combined with skippers experience in interpretation and classification, scientists and fishermen could co-‐ develop classification algorithms to reduce discards and improve scientific surveys. Q6 -‐ Could commercial data be used to improve insight in stock distribution and migration patterns? Acoustic data – School density, Distribution pattern, Relative abundance, plankton & krill (relative abundance) Echosounder data from fishing vessels could provide continuous information of relative abundance of the core component of pelagic fish stocks. Such data also give basic information on school densities and other school morphology parameters that could be used for enhance planning and thus optimizing scientific surveys. In many cases, even prey (krill and plankton) detections could result in similar overviews that can then be linked to pelagic fish distributions. The accuracy of fish distribution maps assembled by fishing vessels is to a large extent determined by the coverage of the total distribution area. Echosounder data at different frequencies is needed to acoustically detect individual fish species with a certain level of certainty. Catch information – electronic logbook, length/weight relationship, genetic sampling An electronic logbook, collecting standardized catch information is essential to keep track of catches at different locations and to be able to ground-‐truth acoustic findings. Such data also provide an alternative distribution map of the assumed core of the stock. Length/weight measurements should be included within this logbook, giving a good indication about the condition of the stock. Onboard genetic sampling is a relative new development but its outcome could substantially contribute to our understanding of fish stock migrations and stock composition. An electronic logbook, collecting standardized catch information is Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

essential to keep track about the catches at different locations and to be able to ground-‐ truth acoustic findings. Environmental observations – Temperature, Currents Temperature and currents (speed and direction are considered key stimuli for fish stock migrations. Temperature information can be easily collected through commercial catch sensors such as provided by SIMRAD. Current information can, to a certain extent, be provided by scientific databases although direct measurements with acoustic Doppler current meters is preferable and support the most accurate results. Q7 -‐ Could monitoring of mesopelagic fish (e.g. absence/presence) be used for pre-‐assessment of the potentials of unexploited stocks? For some species with commercial potential, acoustic observations could be used to roughly map density distribution. Acoustic characterisation algorithms already exist for mesopelagics that could be used for species and/or group identification of schooling deep-‐sea species. Q8 -‐ Can sharing data contribute to corporate sustainability and improved co-‐management? Fishing companies gain significant efficiency and improve their environmental profile (by-‐ catch reduction and corporate social responsibility) when collaborating as a fleet. Catch statistics can be share with scientists and authorities but also acoustic data and detection algorithms can be share among skippers and with scientists. As far as the above research challenges are concerned we see a clear added value for the catch-‐, acoustic-‐ and simple environmental data collected by commercial vessels. Acoustic data collected by echosounders and sonars is believed to have the highest potential for revealing behaviour and abundance of migratory, pelagic fish.

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The following table (Table 1) is summarising the hardware components needed and describing its general availability onboard PFA vessels, to collect the needed information to answer the specific questions. A more detailed description about these different hardware components will be delivered throughout the document. Table 1: Acoustic equipment, catch sensors, and other hardware components needed (N), desirable (D) or optional (O) to answer the questions formulated within this document and their availability on PFA vessels (light orange = available on all vessels, to dark orange up to now not available on any PFA vessel), in addition the second table indicates which frequencies are needed to allow an acoustic detection of the selected species

Acoustics

Species Identification Plankton

Multi-‐frequency

Detect

1 Frequency

-‐

Identify

Multi-‐frequency

-‐

Temperature

-‐

Salinity

-‐

Currents

-‐

Electronic Log.

Length/Weight

Genetics

-‐

Catch sensors Doppler

Catch Analysis

Fat

Content

N = Needed; D = Desirable; O = Optional Current availability onboard: All vessels Some vessels No vessel

Frequencies needed to separate the different species using current multifrequency technologies:

Species Depth range 38 kHz 70 kHz 120 kHz 200 kHz

Mackerel 0-‐350 Needed Optional Desirable Needed

Horse mackerel 0-‐350 Needed Optional Desirable Needed

Blue whiting 200-‐500 Needed Optional At fishing depth At fishing depth

Mesopelagics 200-‐1000 Needed Optional At fishing depth At fishing depth

In the next paragraphs we will discuss the applicability and feasibility of collecting this information already or potentially available to PFA vessels. We made an effort to include the latest technology developments in acoustics and remote sensing that can be applied by the industrial fleet. Most of this information is shared by our associated Norwegian project partners.

Using echosounder data Basic advantages & recent developments In the past, it was argued that data from undirected commercial surveys could not be used for biomass estimates due to high uncertainty. Nowadays, most information provided by fisheries vessels is used for qualitative studies and high uncertainty ranges are taken as given when running any quantitative studies. Although opportunistic acoustic data from fishing vessels proves less suitable for direct quantified fish stock assessments due to the nature of the vessel tracks, some

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

efforts are being made to have fishing vessels run (mini)-‐surveys or to utilize only certain segments of their vessel tracks that resemble scientific surveys the most. Many of today’s echosounders onboard commercial vessels are of scientific quality and support the function of data storage and export, allowing an in-‐depth analysis of the data. However, most data is not stored in any way and is only used for real-‐time fishermen’s observations. Scientists, authorities and fishermen all agree that acoustic data from industrial vessels has high potential for studying fish stock dynamics, fish behaviour and could lead to improved stock assessment and management. In 2003 ICES founded a study group (Collection of Acoustic Data from Fishing Vessels (SGAFV)), with the goal of evaluating these potentials and to recommend future applications. Currently, the South Pacific Regional Fisheries Organisation (SPRFMO) is testing the use of commercial data as its main information source on jack mackerel in international waters off the coast of Chile. Several protocols and other documentation provided by this group have been used as input for this feasibility study. Although opportunistic acoustic data from fishing vessels proves less suitable for direct quantified fish stock assessments due to the nature of the vessel tracks, some efforts are being made to have fishing vessels run (mini)-‐surveys or to utilize only certain segments of their vessel tracks that resemble scientific surveys the most. For this purpose, the Dutch marine institute, Wageningen IMARES for example has developed a simulation model based on horse-‐mackerel fisheries in the South Pacific(Ybema 2007). This model is planned to be tested with PFA vessels in 2012 as part of a joined effort. On a more practical level, data processing technology developments have rapidly evolved, especially over the past 3 decades. Main advances have been achieved in the field of fish species identification, seabed classification, real-‐time analysis and integration and compatibility with third party analysis and mapping tools. Taking the above developments into account and judging from personal communication it seems just a matter of time before the PFA starts applying science based technologies to increase common knowledge on pelagic fish and improve fishing success at the same time. The chapters below describe the possibilities and feasibility for such implementation.

Hardware compatibility (sounders and sensors) Norwegian pelagic trawlers such as EROS, GARDAR, BRENNHOLM and LIBAS are frequently used by researchers and sometimes preferred over scientific vessels because of their advanced echosounders Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

and sonars combined with the superior capabilities of catching pelagic species. As such, these systems have already proven to meet scientific standards. The tables below (Table 2 Table 3) allow an easy comparison of the instrumentation onboard the PFA fleet (Table 3) with scientific vessels (Table 2) such as Tridens (NL), Dana (DK) and G.O. Sars (NO). We show that scientific vessels primary use SIMRAD EK60 echosounders with multiple frequencies. The PFA pelagic fleet uses a non-‐scientific version of the SIMRAD EK60 that can easily be ‘upgraded’ to meet scientific standards (Ryan & Kloser, 2009).

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Table 2 Instrumentation onboard ICES research vessels (details as specified by ICES in 2009)

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Table 3 Instrumentation onboard PFA fishing vessels (details provided by the PFA)

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

All of the PFA vessels are equipped with at least one split beam sounder and transducer (Simrad ES60 available on every vessel) allowing the usage of multiple frequency analysis when more frequencies are made available. These vessels have in addition at least one sonar installed. The South Pacific Regional Fisheries Management Organisation (SPRFMO) standards split vessels into different categories or ‘levels’, according to their acoustic equipment onboard. Based on this classification we can conclude that all vessels can be classified as LEVEL1 research platforms. The acoustic equipment of a typical PFA vessel can be used for tasks such as advanced multi-‐frequency fish species identification, plankton mapping and long term fish mapping. In the table below (Table 4) we take a closer look at the PFA used echosounders (ES60/ES70), the scientific equivalent (EK60) and optional ME70 that can add significant value to understanding pelagic fish. This reference table can be used to quickly estimate what budget and practical work would be needed to upgrade the PFA acoustic systems. Table 4: Comparison between scientifically used EK60, commercially used ES60/70 and the brand new ME70 Simrad echosounders

Beam width

SIMRAD ES60/ES70 7°

GPT 38 4kW costs (EUR) Transducer costs (EUR) (All frequencies need their dedicated GPT) Frequency coverage Transducer diameter ∅ Pro’s

Con’s

SIMRAD EK60 7° 28.000 37.000 18kHz: 24.800 120kHz: 8.300 38kHz: 13.000 70kHz: 12.000 200kHz: 7.350 18-‐38-‐70-‐120-‐200. All optional. Ranges from 18kHz: 62cm to 200kHz: 20cm Easy to use and difficult to interrupt Simrad EK60 echo sounders data collection onboard fishing vessels can be remotely operated via satellite ES70 is more flexible and easier to use link from the respective than the already popular ES60 research institutes, where the scientist can take full control Bottom hardness information also of all echo sounder functions. allows the study of bottom conditions where the ES70 measures reflectivity Can be used directly for and calculates hardness on a scale of biomass estimation 1 to 100. All of this information can then be exported to a navigation chart More options than on a plotter. ES60/ES70 Perfectly suitable for multi-‐ frequency work

SIMRAD ME70 45°

Can be used for biomass estimations Limited visualisation options only after digital correction of data for multi-‐frequency use Limited visualisation options for multi-‐ frequency use

Only covering 70-‐120kHz Expensive

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500.000

70 to 120 kHz frequency range 70cm 3D school images covering large water volumes (45° angle compared to 7° by the ES/EK systems) Accurate biomass estimation very close to the bottom. Perfect for studying fish close to ridges, slopes and bottom. Image can be combined with EK60 views

Potentials of the ME70 compared to the basic acoustic equipment The SIMRAD ME70 (Figure 10) multi-‐beam & multi-‐frequency echosounder adds3D information on fish school density and distribution and can detect fish near the bottom and shelf edges in higher resolution than the ES60/EK60.

(a)

(b)

(c)

Figure 10: Illustration of ME70 data; a) data collection or what is seen, b) snapshots of recorded data in time, c) real 3-‐D view of the bottom structure and schools after the data has been processed wit post-‐processing software

Simrad in collaboration with IFREMER developed a calibrated, multibeam, vertical echosounder (ME70) for fisheries research. This sophisticated Simrad ME70 multibeam echosounder was designed for quantitative fisheries research and is currently installed on a few scientific and commercial vessels. The ME70 transmits in the range 70–120 kHz range. The fact that the Norwegian fishing company Brennholm AS has installed the ME70 for their combined commercial and scientific activities is an attempt to test the potentials for the industry. The ME70 would be in particular suitable for North Sea herring and mackerel/horse mackerel fisheries in the English Channel and Bay of Biscay. Implementation of the ME70 on PFA vessels would require an investment of 0.5 million EURO and an additional transducer to be mounted in the hull of the vessel (Ø 70cm). Nevertheless, it has to be respected as stated by IFREMER that this new hardware still needs some time to mature. Up to now it is estimated that a deployment onboard a commercial vessel would not yet be rentable until appropriate presentation and analysis tools in accordance with fishermen’s needs have been developed. Nonetheless the potentials of this new technology are believed to be very high.

Data quality assurance The main efforts for fishing companies to assure high quality acoustic data from fishing vessels are • Minimize water disturbance close to the acoustic transducer, • Minimize acoustic noise that is picked up by the transducer, • Using a well calibrated acoustic system • Assuring continuous data storage and processing Hull mounted transducers preferred over bow mounted The positioning of the transducer can have effects on the quality of data: the more air bubbles reach the transducer; the more this will negatively affect the quality of the echogram. Generally there are two different sources for the bubbles: 1) Wind induced: bubbles transported up to several meters below the surface (Novarini and Bruno 1982); 2) Vessel induced: a layer of forced air beneath the hull caused by vessel movement. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Currently the only way to minimise these effects is through using transducers mounted below the bubble layer. Many advanced vessels use drop keels that can lower the transducer by several meters. Drop keel mounted echosounders have become standard onboard scientific vessels and there are also a few commercial fisheries vessel equipped with drop keels (Knudsen, 2009). The PFA vessels have their tranducers mounted in the hull and the bow of the vessel. In general, hull mounted transducers can provide good quality echograms but only at reduced vessel speed (around 10 knots) and in good to moderate weather conditions. Vessel specific level of acoustic and electric noise Commercial vessels might have acoustic instruments that can interfere with the acoustic data collection equipment such as Doppler current metres, sonars, echosounders, power supplies or even microwaves, unless the systems are synchronized or the interfering equipment is turned off. Synchronizing different types of equipment is often problematic owing to inconsistencies in trigger pulse specifications. Some acoustic equipment cannot be externally triggered and must be turned off if interference occurs. In general, one of the acoustic instruments provides the master trigger, with the other instruments configured in slave mode. If a trigger delay or specific trigger pulse characteristics are required, it may be necessary to build a customized electronic interface. Since all PFA vessels are differently built and contain custom made instruments, the SPRFMO recommends that each vessel should execute self-‐noise tests using the noise measurement facility built into the echosounder. A noise measurement can easily be performed during normal fishing operations. Calibrating the acoustic system adds significant value It’s commonly known that calibration of echosounders allows absolute fish abundance estimates (Simmonds 2005; ICES 2007; Korneliussen et al. 2008; Barbeaux et al. 2009). But a calibrated acoustic system is also needed for multifrequency species identification. All acoustic frequencies that will be used in the analysis should therefore be calibrated (see Table 5 extracted from Dorn 2009). Not every operation though needs a calibrated system. Table 5summarises the potentials and benefits of calibrated or uncalibrated acoustic system, illustrating the minimum requirements for selected scientific undertakings. Table 5: potentials and benefits of calibrated or uncalibrated (stable or unstable) acoustic system

Echosounder

Unstable

Stable,

uncalibrated

calibrated

Scouting / Migration signals

Distribution estimation

Distribution estimation with improved comparability over time

Absolute Abundance Estimation

Relative Abundance Indices

Detection of prey (plankton, zooplankton)

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Multifrequency species identification (at least 2 frequencies available)

Until recently, calibration of the acoustic system was believed to be time consuming and did therefore not fit in the tight time schedule during fishing operations. All echosounders of PFA freezer trawlers are assumed to be stable but uncalibrated (Table 5). Realizing the potentials of calibrated data it pays off to find practical solutions. Below are summarized the latest developments in calibration technology that could help reducing effort and time spent on calibrations onboard PFA vessels. 1. Improved calibration efficiency methodology by IMR and CMR At best it takes a few hours to calibrate the main acoustic frequencies, but based on experience there are always some problems that have not occurred previously. IMR usually sets a day to calibrate. Scientists are not needed for calibration: experienced technicians will do (ME70 and MS70 need a different approach: two spheres have to be used for each). Currently the only way to minimise these effects is through using transducers mounted below the bubble layer. Many advanced vessels use drop keels that can lower the transducer by several meters. Drop keel mounted echosounders have become standard onboard scientific vessels and there are also a few commercial fisheries vessel equipped with drop keels. 2. Using software to simplify calibration Using Echoview for calibration can reduce calibration time and costs: Table 6: Benefits of using the calibration module within Myriax Echoview software Benefit

Explanation

Reduced time and cost associated with calibration

You can collect calibration data in environmental conditions where it would not normally be possible, e.g. in rougher than optimal seas. The data you collect will contain both on-‐axis and off-‐ axis single target detections but you can filter out the off-‐axis targets and use only on-‐axis single targets for calibration.

If you use Echoview in conjunction with one of Myriax's Echolog live viewing applications, you can monitor the collection of data in real time and collect only as much data as necessary to ensure statistically valid calibration, i.e. when you have enough on-‐axis single targets you can stop collecting calibration data, complete the calibration process, and begin your survey.

Increased accuracy of calibration

You can filter out off axis single targets (these may be detected even in light seas) to ensure calibration is performed using only on-‐axis data.

Appropriateness of calibration algorithms

Echoview may use different algorithms to those used in your echosounder, e.g. for single target detection. You should calibrate using the same algorithms that you use to process your data.

Check calibration in Echoview

If you collect calibration data as part of your survey you can check the accuracy of user calibration settings during post processing and adjust them as required to more accurately calibrate your data. Different variables can then be calibrated based on the core calibration data set.

New automated calibrated technology developed by NOAA.

The Fishery Resources Analysis and Monitoring (FRAM) division of the Northwest Fisheries Science Centre (NOAA, USA) have developed the automated acoustic calibration system (AACS), to more Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

effectively conduct the acoustic system calibration at sea. Main improvements of this technology compared to the traditional sphere calibration are: o Improved efficiency of the calibration which can result in reduced calibration time; o Can be operated by inexperienced staff o More control over calibration quality by using computerized calibration hardware. More information: http://www.nwfsc.noaa.gov/publications/displayallinfo.cfm?docmetadataid=7319 4. Calibration during down-‐time or shelter Since North Atlantic mackerel, blue whiting and horse mackerel are fished in the same European waters a single, annual calibration for all these species should be sufficient for the PFA systems. With the new technologies it would be feasible to calibrate when sheltering from bad weather in any Scottish or Irish fjord nearby the fishing grounds as alternative to a planned calibration. The latest calibration techniques require a certain level of expertise that could be covered by the vessels own technicians after a short training. Ensuring continuous acoustic data storage and processing Prior to any data recording it should be clearly decided which data to record when and how. ICES generally recommends the recording of raw acoustic data files from the beginning until the end of an entire fishing trip, acknowledging that these will result in the biggest possible file sizes. Therefore it might be worth considering recording data only in areas of interest. The question when data should be recorded is apparently a trade-‐off between the risks of missing important data and storage capabilities. Where possible the vessels should be equipped with sufficient storage volumes assuring the possibility to record raw acoustic and metadata files of the entire trip if not decided otherwise previously. Furthermore it is suggested that in addition to raw data files processed files with a lower resolution could be recorded, allowing a quick scan of the data and work as redundant data. A recent trend among marine institutes is to establish a reference fleet of commercial fishing vessels to collect scientific data (currently restricted to catch data only). EK60 Figure 11 Illustration of remotely operated EK60 echosounders via satellite link echo sounders onboard fishing vessels are remotely operated via satellite link from the respective research institutes (Figure 11), where the scientist can take full control of all echo sounder functions. One of the major challenges in using commercial vessels as platforms for fisheries acoustics data collection is the effective analysis of the large amounts of acoustic data collected. Traditional processing techniques cannot always be applied, so new methods need to be explored. Unfortunately, developing these techniques and algorithms in commercial acoustics software packages can be difficult given the limited flexibility of these programs. General data analysis tools such as MATLAB programs provide immense flexibility but lack normally the basic functions and autonomy required for processing acoustics data from multiple fishing vessels. A major goal of researchers involved in the acoustics program at the Alaska Fisheries Science Centre (AFSC) is to Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

create a library of MATLAB functions that form a framework for scientific treatment of acoustic data from fishing vessels. These applications are now released to the scientific community via the Institute for Marine Research's EchoLab toolkit. Contact: Rick Towler, Midwater Assessment and Conservation Engineering Group, NOAA Alaska Fisheries Science Centre. Acoustic system stability Modern echosounders are robust and reliable technology. Literature revealed that during tests at IMR onboard G.O. Sars using the EK60 a variation of only 0.22 dB was detected over a period of 5 years and only variations of a couple of hundreds of a dB where measurable when comparing year by year, for 38 kHz (the most commonly used frequency) ((Knudsen, 2009). Since the PFA is using relatively new acoustic equipment (see

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Table 3), it is estimated that an annual calibration of the echosounders of the PFA vessels should be sufficient, to assure data collection at high standards.

Analysing opportunistic acoustic data Data processing technology developments have rapidly evolved, especially over the past 3 decades. Fishermen have only been able to profit from these developments to a very limited extend. Since PFA vessels are not using any acoustic data analysis software at the moment it makes sense to choose a software package that can be used by scientists AND skippers. Skippers could greatly benefit from the features that are developed by the scientific community. See Appendix I for a comparison of the presented acoustic post-‐processing software packages which are described below. Analysis software: Large Scale Survey System (LSSS)

MAREC is a project initiated by Institute of Marine Research (IMR) and Christian Michelsen Research (CMR), both located in Bergen, Norway. The objective of MAREC is to establish processing tools for acoustic data and make them commercially available. The development was initiated based on an evaluation of existing post-‐processing systems that could not meet future demands of IMR. Therefore IMR decided to develop a new post-‐processing system, the Large Scale Survey System (LSSS) (Figure 12).

(a)

(c)

(b)

Figure 12: Illustration of Marec LSSS, acoustic post-‐processing software; a) Typical workflow within LSSS, b) typical view of LSSS during normal operational phase, including details about a selection, an overview map, information from auxiliary data sources and the echogram, c) detailed view of an echogram and a selected school within LSSS

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It serves a growing number of ICES scientists in their fisheries surveys and has a strong focus on species classification and fast daily scrutiny of the data. Recently, a commercial or fishermen’s version (SEAT) has passed its first round of pilots and is now in need for investment to finalize the product. LSSS and SEAT are science based by design. LSSS has users worldwide and SEAT is still in development. The LSSS (Figure 12) application is intended for interpretation of data from multi-‐frequency echosounders. LSSS support online operation offshore, as well as efficient post-‐processing onshore. LSSS is regarded as ideal tool for stock assessment and ecosystems surveys. Fast automatic school detection and automatic school categorization make it possible to interpret data as they are collected, and thus optimize ongoing surveys in a dynamic manner. Raw data as well as interpreted data are stored in a flexible configurable database. In this way, large amounts of historic data can easily be made available for resource management and research purposes. Analysis software: Echoview While LSSS focuses on efficient processing of routine survey date, Echoview(Figure 13) is the industry-‐standard hydro acoustic data-‐processing application for scientific investigation and monitoring for better understanding of the aquatic environments. Echoview software has a great flexibility and could perfectly suit the more specific skipper’s needs. It can be set up in a way that it’s fully automated in data collection, data analysis and visualization. Its flexibility makes it the ideal tool for future applications and optional integrations with third party software. Myriax has passed several successful pilots in the Chilean pelagic fleet. Echoview has several hundreds of users world wide constantly developing new applications and software improvements.

(a)

(b)

Figure 13: Overview of Myriax Echoview, acoustic post-‐processing software; a) typical echogram view in Myriax Echoview software, b) typical Echoview flow chart showing the mind map for separating fish species. The software processes data according to this mind map

Joined forces on acoustic species identification If skippers and marine scientists would join forces in the acoustic species identification process, unexpected by-‐catch could be avoided, trawling can be executed more efficiently and species abundance estimates could be more accurate.

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Since PFA vessels are not using any acoustic data analysis software at the moment it makes sense to choose a software package that can be used by both scientists AND skippers. Skippers could greatly benefit from the features that are developed by the scientific community. Both the PFA fishing vessels and research vessels use similar echosounders equipped with multiple frequency transducers. However, up to now mainly scientists benefit from the species identification possibilities offered by advanced software. Norwegian scientists have developed a method utilizing the skipper’s experience and observations for training species identification software. Even without computer tools, skippers are masters in species identification. Draining on this competence might be a successful approach to enhance for scientific approach to mutual benefit. Parallel to this development, international scientists are making efforts to include additional information such as school characteristics, day/night characteristics and seasonal characteristics in their detection algorithms. This could add value to fisheries operations and improved selectivity. Let us demonstrate the difference between a skippers and the scientific approach: Skippers expert judgement to identify fish species is based on the morphology of fish schools or reflection on various echosounders: typically it includes highly complex seasonal, regional and ecosystem characteristics that they have built up over many years being at sea. Based on this knowledge individual skippers can create a competitive advantage, especially when fishing in specific areas Scientific objectivity. Scientific objectivity relies on methods and protocols that are truly science based. A scientist needs objective analysis of available information (Figure 14) in situations where the skipper is satisfied with Figure 14 Visualisation of 2 fish schools at 38 kHz and 200 kHz as seen in Myriax Echoview] his experience-‐based conclusion. Acoustically we can characterise the properties when more than one frequency is available. The more (calibrated) transducer frequencies are available the higher is the probability of correct identification. Identification is also dependent of validation of the acoustic information through catches.

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Getting the most out of the echosounder frequency range The transducers that are connected to the PFA Table 7 Technical information about different Simrad Split-‐ SIMRAD echosounders have different frequencies beam transducers ranging from 18 -‐ 200 kHz, including transmission power and range and thus different detection ranges for fish. The pelagic fish we are focusing on in this study are usually caught shallower than 600m. Although all PFA vessels target mackerel, the 200 kHz acoustic frequency that is often essential to mackerel detection (especially when mixed with other species) is absent on all vessels. As a consequence, if the scientific approach to species identification for mackerel is to be applied onboard commercial vessels, a 200kHz transducer has to be installed, calibrated and working simultaneously with nearly identical and overlapping acoustic beams from lower frequency transducers such as the 38kHz. The physical limitation of this identification method is the constraint of the high frequency transducers (200 kHz) to penetrate the water depths below 200m. For mackerel this can be demonstrated as follows: In most schools, mackerel has a frequency-‐ independent backscatter below 100 kHz, but significantly higher levels of backscattered energy at 200 kHz (see Figure 15). This response is unique for mackerel compared to fish species with a swimbladder such as horse mackerel and herring. 18 kHz 38 kHz 70 kHz

120 kHz

200 kHz

Figure 15 Multiple frequency operation: Mackerel. These five screens captures show how the same school of mackerel is detected and displayed using a Simrad EK60 scientific echo sounder with five operational frequencies in use simultaneously

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As a consequence, if the scientific approach to species identification for mackerel is to be applied onboard commercial vessels, a 200kHz transducer has to be installed, calibrated and working simultaneously with nearly identical and overlapping acoustic beams from lower frequency transducers such as the 38kHz (a spatial separation can to some extent be compensated for if the exact distance between transducers is known). The only drawback of this identification method is the limitation of the high frequency transducers (200 kHz) to penetrate the water column below 200m depths. Figure 16indicates the Figure 16 Indication of common PFA fishing grounds and the area where scientific multi-‐frequency analysis on mackerel or other species where high areas where we can MOST LIKELY(green frequency transducers of 200 kHz are needed would work up to the bottom areas) use this method up to the (green areas). bottom (200m boundary).

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Optimize the value of commercial catch and environmental data Catch data Standardised catch information provided by the different type of electronic logbooks or fully documented fisheries allows a better integration of catch information into the dataflow of scientific procedures. This also increases the transparency of fisheries operations that satisfy the continuously increasing consumers’ demand for knowledge and the growing markets for eco-‐labelled products such as MSC. Standardised catch and effort data could easily be linked to environmental variables and acoustic data for example to study the importance of certain fishing grounds or to validate or discard typical skippers hypotheses. Commercial data are expected to become important tools in order to 1. Collect information on by-‐catch and school composition 2. Catch a representative part of a school of fast swimming pelagic species such as mackerel than trawls used onboard scientific vessels. 3. Allow an improved predictability of the spawning season, which could help improve the design and timing of scientific surveys. Increased landings from certain areas may also help to understand changes in spawning areas with relation to water temperature or food availability (Jansen & Gislason, 2010)). 4. Provide continuous near real time overview of ongoing stock processes such as migration, condition as well as information on stock identity and separation. Fish quality and origin information for improved branding In many pelagic fisheries the skipper would be interested in more than just the ‘total weight by species’ in his catch. The quality of fish and perhaps even the origin can play an important role in getting the best available price for his catch. Since more seafood requires certification it makes sense to invest in improved catch sampling methods. These methods would reveal not only information about the catch itself but also about the stock when multiple data sources are combined. Storing catch data in detailed digitized logbooks allows the application of scientific analysis on commercial data and creates a branding opportunity through higher transparency. Sampling can be low-‐budget and easy to perform by measuring length and weight for a few individual fish per species and size class in each catch and additional measurements can be performed when a contract requires this (otoliths, stomachs, genetics, fat content) as seen in recent contract research in Norway. Based on Norwegian experiences we have selected the following list of parameters that could significantly add value to our common species knowledge: Fish condition. Length/Weight measurements of several individual fish in the catch. The participating vessels are all equipped with an electronic fish sampling board (Scantrol) that is used to measure and weigh individual fish. The crew is trained by IMR to directly process the samples onboard. A maximum of 60 individuals per species per day and up to 7 catches sampled per species per week is sufficient for length measurements.(Nedreaas, Borge, Godoy, & Aanes) Alternatively samples could be stored in the freezer to be measured and analysed ashore, if the previously described methodology would not be applicable for example due to time constraints or the lack of a compensation plan satisfying all involved parties. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Genetic stock component verification Genetic verification of mackerel stock structures enhancing quality of management and catch regimes and contributing at building brands and reputation of trust. This method has successfully been demonstrated in 2009. What can this technology potentially be used for: • To indicate the degree of genetic exchange between putative distinct populations (the mackerel case). Populations with no or little genetic exchange (genetically isolated populations) tend to have developed distinct marker profiles during evolution. If there is no distinct marker profile there is a lack of support for considering them “different populations” that should be managed individually. • Provided genetically distinct populations can be identified, genetic analysis of fish samples can be used to verify if a fish actually belongs or does not belong to a defined population. In other words it is a too with potential to verify that catches are from populations that can legally be harvested; or to check if catches are from “illegal” fisheries (protected populations or populations for which the vessel has no license). Year round fish samples taken from fleets that cover large areas can only be analysed in molecular genetic laboratories (just like in the forensic medicine we see on movies) but equipment is being developed for automated fish sampling. Fish quality / fat content Measuring the fat content to study the stock health or even the origin of the fish as demonstrated in SILLQUID project. These measurements have both scientific and commercial benefits. A Microwave Quick Tool to Predict quality and origin of herring. In SILLQUID, the fast and non-‐destructive method MW-‐ spectroscopy, developed in two recent EU-‐projects, was tested for prediction of origin, compositional and quality parameters of a unique herring material collected and analysed during NI-‐ project 02106. Through participation of three pelagic companies, the MW-‐tool was also tested during industrial production of herring and mackerel fillets. The most important result from this project has been the promising ability of the MW-‐tool to predict fat content of pelagic fish, at least up to fat levels of 18% (herring) or 25% (mackerel). Apart from these above parameters by-‐catch information of any species can be used for scouting trends and early migration signs of commercial species and absence/presence of deep-‐sea fish with commercial potentials. Figure 17 SILLQUID microwave tool to predict fat content

Product traceability through digitized logbooks There is a growing market for fish product traceability systems, now the fight against IUU (Illegal, Unreported and Unregistered fishing) becomes noticeable and consumers demand for eco-‐labelled products such as MSC is growing stronger. An example of such a commercial system (used by Hermes AS Norwegian freezing trawler company) is developed by TraceTracker (tracetracker.com). This system was described by the EU TRACE project Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

as the most successful pilot of the entire 5-‐year programme (TRACE 2009). Figure 18 illustrates the workflow onboard of the Hermes vessel. If such logbook system is installed along the whole food chain it could function as a sort of “food passport” (TRACE 2009). Thanks to this investment, HERMES has now established a strong relationship with a major importing company from Denmark who is translated the retailers’ demand. HERMES is now building up an internal database on all its catches; well documented and highly standardised. This database will be used for fish studies that could improve the vessels catch success. An example of what kind of information is directly available online for the case of TraceTracker is summarized in Table 8. Table 8 Catch information directly available online by HERMES Freezer ID Haul ID (submenu of Freezer ID) Species Description Unit ID and Unit Type Latin Name Product description Size Grade Temperature condition Weight

Haul ID, Person responsible for loading, Start time, end time Date and time, Gear, FAO map code, Country, ICE code, Location(GPS coordinates), Species(name and amount of individuals in the catch), Trawl starting and end time (with the location shown on a map) Species common name ID numbers and description contain information about the quality of the product, e.g. presence of parasites, presence of blood, weight without head and comments Latin species name Code for the final product Commercial size grade E.g. Frozen Weight of the frozen block in kg

Figure 18 Workflow onboard of the Hermes vessel

Positive selectivity aspects of commercial fishing gear Biological data originating from fishing vessels can be seen as complementary data to scientific surveys, targeting different parts of the stocks. While scientific surveys generally aim to sample a stock in its entity, fishermen are solely interested in the core part, the part of the stock with highest commercial value. This core part of the stock is often less intensively covered by research vessels. Scientific fishing gear is constructed to be non-‐selective and designed for catching only a small sample of the fish school (R/V Tridens may be an exception). This has proven to have implications for the assumption that fish samples taken by a scientific vessel are more representative for the fish that was seen on the sonar or echosounder than samples taken by commercial fishermen. There are Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

indications that commercial trawls are less selective on fast swimming pelagic species such as mackerel and blue whiting compared to catches from scientific vessels (research trawls select younger, smaller, and perhaps weaker fish). This finding might have a significant influence on acoustic estimation of abundance of these species, and raise the awareness of the samples used to estimate year-‐class abundance and biomass and to study variations in growth and condition of fast-‐ swimming species such as mackerel (Slotte, A., Skagen, D., and Iversen, S. A. 2007). This phenomenon is currently dealt with in assessments by applying different catchability estimates but procedures that enable adequate statistical treatment of skipper-‐induced adjustments should simultaneously be developed. Involving catch samples from the commercial fleet secures a proper statistical coverage for a defined number of species in time and area.

Environmental data As with acoustic and catch data, environment samples collected by fishing vessels will mainly be associated to the fishing grounds and thus directly related to the physical and biological forcing behind the distribution of the fish. This can be used to our benefit. In general, three important environmental properties behind fish migration can be collected by commercial vessels: water temperature can be collected through net sensors, water movements could be collected through acoustic Doppler measurements and plankton information, as an important indicator for prey availability, can be extracted from echosounder data. The following is a quick scan of potential environmental observations that could be collected onboard fishing vessels and that would significantly contribute to our common knowledge on stocks of Atlantic mackerel, horse mackerel, blue whiting and mesopelagics. When studying blue whiting migration, the influence of the Sub polar Atlantic Gyre is mentioned as driving force for blue whiting spawning success west of Ireland( Hátún, Payne, & Jakobsen, 2009). Models have been developed but it remains to be seen whether we can test if the model has good predictive value. Scientific surveys systematically collect temperature data at the depth of blue whiting occurrence but this can only be used as incomplete snapshot in the surveyed area during the spawning season. Temperature data directly linked to the catch would supply an ongoing measurement of blue whiting preferred environment. Mackerel and horse mackerel are known for their large temperature tolerance, while they can apparently only cope with a small range of temperatures during spawning season. Recent ocean warming observations have raised questions on the effect on the boundaries of mackerel habitat and migration routes. In order to verify mackerel temperature preferences during different seasons, temperature measurements that can be directly linked to the catch might prove valuable. Sharing the same habitat with blue whiting, it is suggested that the occurrence/avoidance of mesopelagic fishes in certain areas could be used as an indicator for oceanic changes, induced by climate change and changing currents. This would make them ideal species to test hypotheses on the Sub polar Atlantic Gyre and thus distribution changes in blue whiting. Apart from data directly collected onboard fishing vessels we typically define 2 types of data information sources in this project that show high potential to be linked with fisheries data, to assure Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

a maximised scientific value outcome, namely data originating from scientific surveys or remote sensing (Table 9). Table 9 Comparison of the three main environmental data sources

Data quality

Directly from vessel Average (1 -‐2 digits)

Online Average – High

Spatial coverage

High -‐ Vessel tracks

Resolution

High resolution in fishing grounds

Temporal coverage Time series

Fishing season

Very high coverage, from local to worldwide, good interpolation methods Low – High resolution, sufficient for tracking long term changes although some limitations where very precise information is needed based on interpolation algorithms All year round

Standardised data

Not available up to now, though potential for commonly visited fishing grounds Generally standard methods if data storage is available

Yes

Scientific fisheries surveys Very High (Standard 5 digits behind the comma) Low -‐ only available along transects High resolution from defined stations allowing a good interpolation for the surveyed area Surveys Generally time series are available from the different surveys, following the same track Standardised collection and storage of data

Only standardised datasets

Extracting temperature data from catch sensors Temperature sensors (Table 10) are a common optional feature in most trawl nets. Temperature profile measurements, during fishing operations, directly link the presence of targeted and by-‐catch species to specific temperature ranges. The value of this information is obvious since we consider temperature to be one of the key driving environmental parameters behind fish migrations. Linking catch and temperature relations to the relative abundance measured by the echosounder adds a quantitative component to this temperature preference. The accuracy of temperature measurements is generally high enough to perform such correlation studies. Such, relatively easy to perform studies can visualize seasonal and regional behaviour and form the bases of larger ecosystem studies, starting with the fishing grounds. These studies would typically use remote sensing and buoy data. This data is in many cases public available. This means that, although a main focus of buoy data is to document seasonal to decadal climate variability and to aid our understanding of its predictability, fishermen could use buoy and remote sensing data in combination with their trawl sensor data to predict where to expect thermoclines and thus where to expect fish. Current software systems such as Orbmap and Maxsea are starting to integrate such information into their packages. Table 10: Comparison of the different temperature data sources

Net sensors

Argo floats

Remote sensing

Scientific surveys (CTD)

Pro’s

Directly linkable to fish / catch

Profile data, time series, standardised data

Flexible accuracy

Cons

Only available in high fish density areas

Low spatial resolution

High time and spatial resolution, large area coverage Only surface

use,

high

Low spatial and temporal resolution

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ICES states that mostly the sensors attached to the fishing nets support rough conditions and provide lower quality data compared to scientific equipment. If needed scientific devices could be mounted in a protection case on the net. Extracting water current data from acoustic dopplers Doppler devices (Table 11) are a kind of sonar that measures the speed of particles in the water column. Acoustic dopplers are used to determine the water current velocity and direction. Acoustic Doppler current profilers (ADCPs; Doppler logs) are often available on board modern fishing vessels (ICES 2007) including the PFA vessels. Continuous measurements of current velocity and current direction can be valuable when it comes to explaining local and regional migration of schooling pelagic fish. Linking water currents measured by doppler to scientific or remote sensing current profiles and the relative abundance measured by the echosounder could help explaining observed local migration patterns. Satellite imagery provides current measurements at the surface and could be used as a proxy, when fish schools are using the upper most water layers during their migration. Table 11 Comparison of the different current information data sources Pro’s

Cons

Acoustic doppler Directly linkable to fish / catch, Profile measurements, fish school movement detection Only available in high fish density areas

Buoy data Prediction possible of deep water currents

Satellite data High time and spatial resolution, large area coverage

Low spatial resolution

Only surface currents measured

A combined, integrated visualisation of current information and fish abundance would allow skippers to improve their fishing strategies as well as provide scientists with an enhanced insight into fish behaviour and migration strategies. Extracting plankton detections from echosounders Having more knowledge on plankton aggregations’ (Table 12)interaction with fish including impact of diel and seasonal behaviour variation is important for various purposes: 1. It is needed for understanding and predicting of prey abundance and vertical migration behaviour of pelagic fish actively feeding on plankton. 2. Further, satellite sensors’ registrations of plankton, density distributions might be important guiding of information to aggregations of fish during different seasons. Fishermen have acknowledged this link and have started to use satellite images to predict their catch success (for example through GeoEye services). However, a more scientific approach could help both fishermen and science to understand these links. 3. This avenue could be supported by building up echogram reference databases, assuring an improved detection/discrimination of fish and plankton for fishermen and scientists. Especially species as mackerel and blue whiting are sometimes mistaken for plankton or vice versa.

Table 12 Comparison of the different plankton information data sources

Echosounder

Plankton nets

Pro’s

Directly linkable to fish / catch,

Species differentiation, flexible use

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Ocean colour remote sensing High temporal

cons

Profile measurements, linkage to diurnal vertical migration patterns

Time consuming, labour intensive, low spatial and temporal resolution, special expertise required

resolution and regional overview Only surface measurement of phytoplankton

All PFA vessels use SIMRAD ES60/ES70 echosounders and are in principle able to detect plankton aggregations besides fish schools. Both zooplankton and phytoplankton traces can be detected and separated from fish schools using acoustic data processing techniques. Both plankton types form a major feed input for pelagic fish during their different life cycles. Where phytoplankton (plants) is a main source during younger stages, zooplankton (animals) can be a main prey item for mature pelagic fish.

Chapter 5. Feasibility of using commercial data in decision making process In 2013the new Common Fisheries Policy will be implemented, where a closer involvement of the industry into the decision making process could be one of the elements. But before we look into potential future developments it is essential to understand present decision making process. Secondly, in order to judge where fisheries dependent data could contribute in the decision-‐making process it is important to understand how knowledge is currently treated.

Figure 19 Current decision-‐making process

Speaking in very general terms the decision making process can be split up in three parts: 1. The scientific data collection process, where up to now the main fisheries dependent data is the catch data (modified through scientific age-‐sampling). For pelagic stocks like mackerel Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

and herring, the main other data sources originate from scientific survey work. This results in the formulation of the ICES advice. In the European Context the ICES advice is further reviewed by the Scientific, Technical and Economic Committee on Fisheries (STECF) 2. In the second stage this advice is communicated to client commission, like the European Commission, NEAFC and the Norway-‐Russian bilateral commission, and to stakeholder organizations like the Regional Advisory Councils (RACs) and the Advisory Council on Fisheries and Aquaculture (ACFA). The scientific advice is then commented upon by different stakeholders organizations, EU member states and coastal states. 3. The third step is the real decision making procedure, where all the coastal states and NEAFC discuss their mutual interests in the stocks and split up the shares and quotas. These discussions will then lead to the final coastal states agreement attributing a defined quota to each member state for the stocks in discussion. A more detailed description is listed in

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Appendix II. In order to judge where fisheries dependent data could be taken up the decision-‐making process it is important to understand how knowledge is currently treated.

Current knowledge and advisory process Currently the knowledge base of the decision process is mainly based on advice provided by ICES (ICES advice). ICES can be seen as an institution with three relevant components, namely: ICES Data Centre: The ICES database encompassing a large variety of data from scientific surveys to commercial catch information over oceanographic and environmental information. ICES science (Working and study groups, Science Committee): The science department of ICES with the goal of promoting science in the Northeast Atlantic with a special relation to sustainable fisheries” and the integrated management of marine activities. The science program is devoted to enhancing our understanding of marine systems and marine use and developing new approaches, data and models to improve our understanding. ICES advice (Advisory groups): Carry out annual stock assessments (in assessment working groups) and use the outcomes of the stock assessment to draft and finalise the advice. The advisory committee (ACOM), formulating the final advice with regards to the study and working groups, oversees the advisory process. The ICES advice is build up on: • Data collection & processing: Mainly scientific stock assessment surveys, executed through the different institutes at the member states (e.g. IMARES in the Netherlands, IMR in Norway). In some stocks fisheries dependent data is the only source (e.g. deepwater fisheries). In others, fisheries dependent data only consists of catch data (mackerel, horse mackerel and blue whiting) • Assessment & interpretation: Prepared at the different research institutes and then discussed and combined at ICES working and study groups meetings, documented in the working group reports. • Advice: The final advice is formulated and distributed by the advisory committee.

Who is informing the European Commission on pelagic fisheries? The institutions informing the European Commission on pelagic fisheries are ICES as provider of scientific advice, STECF as one of the main communicators and consultants. STECF secure communication between the EC and the other interest groups involved in the conservation and management of pelagic fish. The Pelagic RAC acts as advisor on the management of pelagic fish stocks on behalf of the fisheries sector and other interest groups. ICES ICES is an important provider of scientific advice to the European Commission and to other client commissions (e.g. NEAFC). Unbiased scientific advice is provided to member nation governments and international regulatory commissions in support of the management and conservation of coastal and ocean resources and ecosystems. Advice on the management of most commercial pelagic finfish Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

stocks is provided to the North-‐East Atlantic Fisheries Commission (NEAFC), North Atlantic Salmon Conservation Organization (NASCO), and the European Commission (EC) (Source Wikipedia). Scientific, Technical and Economic Committee for Fisheries (STECF) The STECF can be seen as one of the main communicators and consultants between the EC and the other interest groups involved in the conservation and management of living aquatic resources. Consulting aspects should include biological, economic, social and technical considerations of the fleets and fisheries. The EC should take the advice given by STECF into consideration when presenting proposals on fisheries management. More information at: https://stecf.jrc.ec.europa.eu/

Pelagic Regional Advisory Council (PRAC) The PRAC is one of seven Regional advisory councils (Baltic Sea RAC; Long Distance RAC; Mediterranean RAC; North Sea RAC; North Western Waters RAC; South Western Waters RAC; Pelagic RAC). The PRAC prepares and communicates advice on the management of pelagic fish stocks on behalf of the fisheries sector and other interest groups. The PRAC consists of a General Assembly, an Executive Committee and two Working Groups. The RACs are at the moment an important real entry point for stakeholder organizations (including the fishing industry) into the decision making process. In general, the PRAC feels that the EU, in comparison with Australia and the USA is relatively ‘old-‐fashioned’ when it comes to the models that are used in many stock assessments. The PRAC urges the Commission to be more innovative in the tools used by scientists and development of participatory modelling should be given high priority on the research agenda (PRAC Dec 2009). The Pelagic RAC has demonstrated to play a mature role in the fisheries management process. For example, the management plan for horse mackerel proposed by the Pelagic RAC in 2007 was evaluated by ICES and considered to be precautionary in the short term. The European Commission then adopted a proposal for a long-‐term plan for the sustainable management of horse mackerel across the eastern Atlantic from the Iberian Peninsula to the northern North Sea in response to this initiative launched by the fishing sector. More information at: http://www.pelagic-‐rac.org

Who takes the final decision? The final management decision on widely distributed pelagic stocks is taken by the North East Atlantic Fisheries Commission (NEAFC), that is responsible for recommending measures to promote a rational exploitation of fish stocks in the North East Atlantic, the Coastal states that share the responsibility for managing certain fish stocks and the European Union (EU) that is considered to be one coastal state in the sense of NEAFC. North East Atlantic Fisheries Commission (NEAFC) NEAFC is the organisation responsible for recommending measures to promote a rational exploitation of fish stocks in the North East Atlantic. The Commission is made up of delegations from five Contracting Parties: Denmark (in respect of the Faroe Islands and Greenland), the European Union, Iceland, Norway, and the Russian Federation, as well as many observers, including NGOs. The final decision step in the decision making process is taken at the annual NEAFC conference in London, as an agreement between the coastal states. More information at: http://www.neafc.org

Coastal states The coastal states that share the responsibility for managing certain fish stocks, they have to represent the interest of their country at the annual NEAFC meeting. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Include a list of coastal states involved for different species European Union The EU is considered to be one coastal state in the sense of NEAFC. For pelagic stocks like North Sea herring, the European Union negotiates directly with the other coastal state (Norway) to come to agreement on fisheries management measures.

Key uncertainties in the scientific advice and decision making The information that could address the key uncertainties in pelagic stock management and to what extent it is scientific, political, or legal has been described in chapter 1 and 3.In chapter 1 we have described the main potentials for industry involvement to address the current lack of our knowledge on pelagic fish stocks that is described in chapter 3.

Reasons for closer fishermen’s involvement in the new CFP The EU’s fisheries and seafood markets are managed centrally through the Common Fisheries Policy (CFP). This overarching legislation is reviewed and revised once per decade, with the latest ongoing reform due for completion in early 2013. The outcome is expected to be a full new set of basic rules, timelines and objectives of fisheries management, applying both in and outside EU waters. In 2009, the EU Commission launched a wide-‐ranging public debate on the way EU fisheries are managed and is in the process of releasing a revised version of the Common Fisheries Policy (CFP) to assure a more sustainable future of the marine resources. Recognising the current status of the seas, the EU consequently set itself a deadline at the Johannesburg Conference of development 2002, to guarantee a sustainable management of all their stocks by 2015 (Froese et al. 2010). This will optimise the management regimes and potentially reduce the number of political conflicts. Therefore fisheries management organizations have the ambition to engage the fishing industry to play an active role in stock-‐assessment and in the decision-‐making on implementation of this new policy. Science-‐industry partnerships can improve the quality and availability of data and knowledge. They can also foster mutual, common understanding between operators and scientists, without compromising the independence of the latter. Such partnerships should therefore be encouraged (EU Commission document COM 2011 417) NGO’s as the Coastal and marine union EUCC (2009) and WWF (2009) support this close involvement of the fisheries industry in management, control and to a fair extent in rulemaking itself to assure the compliance of the rules. ““The fishing industry should participate in stock-‐assessment and in decisions on implementation of this new policy” according Msc. Šarūnas Zableckis, coordinator of EUCC’s fisheries team. “With responsibility comes accountability; if they fish sustainably they keep these rights, if not they should lose them.” The Pelagic Regional Advisory Council also supports increased data collection and sees it as crucial to the sustainable exploitation of pelagic fish in EU waters. The Pelagic RAC and scientists acknowledge that this industry involvement should facilitate advisory needs in the medium term such as seen with the development of the Western horse mackerel plan and the preparation for a proposed amendment to the mackerel plan. Such an approach, where scientists are asked to evaluate a set of different Harvest Control Rules, should be the standard approach. By their nature the seasonal pelagic fisheries are multispecies and multi-‐stock; the fleets are highly dynamic in that they respond to markets and fishing opportunities with adaptive strategies. Thus, data collection schemes must be able to respond and account for this dynamism. Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Another priority issue, in the view of the PRAC, is to make more effort to find ways of incorporating all available data in the assessments. With regard to data collected by Member States under the Data Collection Regulation, all data should be compatible by ensuring that the same methodologies are used across different Member States. In addition, data collected by fishermen should be used in the assessment process as well. Especially with smaller, data poor stocks (like North Sea horse mackerel and sprat), there is a great potential for improving the quality of assessments in that way. In order to incorporate such data, the development of more novel modelling tools are needed, because currently this is often inhibiting scientists from using that information.

Key requirements for data and information when applied in scientific advice • • • •

Credibility: It’s important that the end-‐user knows where the information comes from, how it’s collected and if it has been treated according to agreed (scientific) quality standards. Saliency: How will new commercial data be relevant for the policy issues that are to be resolved Legitimacy: How can we be sure that the new information is unbiased by interests of fishermen. There is a very strong suspicion from scientist that fisheries data could be biased. Compatibility: How will it link to the current methodology? Does the new information “fit” within the current paradigm/model? What if we collect all kind of new information and it cannot be used because it does not fit into the current model or into the current advisory practice? What is the expected impact of the new information?

Potential route for involving “new” fisheries data in scientific advice and decision making Route 1: Contributing to ICES General strategies for uptake of commercial data in ICES advisory process: ü Assessing sampling strategies, interpolation of raw data: survey working groups, assessment working groups ü Promoting the use of commercial data in scientific advice: ICES Annual Science Conference, ICES journal, assessment working groups ü Involving key players (assessment scientists, advisors) in the process of generating and interpreting data Implications of the ICES route: • Credibility: including new fisheries dependent data introduces the risk of a loss of credibility in the view of end customers of advice, if the data collection and data analysis process is not fully transparent. In the absence of full transparency the scientific results could be challenged if they include data that could be perceived as having been generated by experts that have an interest in the results. • Saliency: including fisheries dependent data could affect the saliency of scientific advice if the new information would make a difference in the overall quality of the advice (e.g. more reliable stock assessments) or if new types of information could be generated (e.g. better data on distribution of fish stocks and recruits, stock structure etc.) Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

•

Legitimacy: including fisheries dependent data is expected to increase legitimacy for fisheries stakeholders who know that their information has been used in the scientific process. This does not necessarily also work that way for NGO stakeholders if the data collection process is not fully transparent. Compatibility: does the new fisheries dependent data fit into the current assessment process? This is often a major stumbling block that prevents uptake of new sources of information. The paradigms (methods, models) of fisheries science are relatively fixed because of the high political importance that is attached to the outcomes of the scientific advice. Petter Holm and his co-‐ workers have termed the co-‐production of science and policy the “TAC machine” (Holm and Nielsen 2004). In order to circumvent this issue, already in the stage of sampling and data collection strategy, ideas should be developed if and how this new information would fit into the current methods or what alternative methods would need to be developed to incorporate this information (and how that new method would be tested and benchmarked).

Route 1A: Improving scientific surveys These groups have as main task the coordination, evaluation and data analysis of scientific surveys. PFA roles could potentially be: 1. Assessing current sampling strategies: review timing, spatial coverage en effort distribution; 2. Improving sampling strategies by providing signals from the fishing grounds prior and during surveys; 3. Improving acoustic detection of target species by joint efforts in developing species classification algorithms. Relevant ICES groups are: WGIPS (Working Group for International Pelagic Surveys) WGNAPES (Working Group on Northeast Atlantic Pelagic Ecosystem Surveys) WGMEGS (Working Group on Mackerel and Horse Mackerel Egg Surveys) IBTSWG (International Bottom Trawl Survey Working Group)

Herring and sprat in North Sea, Baltic Sea, Skagerrak, Kattegat Blue whiting, herring in Norwegian sea Mackerel, horse mackerel in European waters Juvenile herring, sprat and Norway pout in North Sea

Route 1B: Contributing to assessment groups and fleet sampling programmes These groups have as main task to process scientific and commercial information and provide advise on their findings based on advanced stock assessment models. PFA roles could potentially be: 1. Providing a second opinion on stock dynamics (qualitative or quantitative) 2. Providing quantitative commercial data on real-‐time basis. Real-‐time sampling of the catch enables research institutes, e.g., to decide how to allocate commercial catch sampling resources in time and space. 3. Participate in benchmark assessment working groups Relevant ICES groups are: HAWG

Herring and sprat in North Sea, Baltic Sea, Skagerrak,

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

(Herring Assessment Working Group for the Area South of 62° N) WGWIDE (Working Group on Widely Distributed Stocks)

Blue whiting, mackerel, horse-‐mackerel, herring in Norwegian sea

Route 1C: Contribute to study groups or other expert groups These groups study have as main task to address specific scientific challenges or address specific methodology developments. PFA roles could potentially be: 1. Creating support for combined scientific and commercial projects in the advisory process 2. Cross-‐fertilisation of new methodologies on fish detection, identification and data use. Relevant ICES groups are: WGFAST Working Group on Fisheries Acoustic Science & Technology FTFB ICES -‐ FAO Working Group on Fishing Technology & Fish Behaviour

Route 1D: Advisory groups: STECF Scientific, Technical and Economic Committee for Fisheries

Route2: Provide independent second opinions for decision-‐making General strategies for having independent advice or studies accepted: Implications of the potential route: 1. Credibility: by not going through the accepted scientific routes, developing and maintaining credibility will be a major challenge. Unless the new advice would clearly be a co-‐production of fisheries organizations and NGOs, there is a low likelihood that the second opinion will be treated with sufficient weight. Incorporating dedicated scientists with a high reputation could help in improving credibility. 2. Saliency: the object of advice is to facilitate decision-‐making on fisheries management. If the main focus of decision-‐making is on the allocation of TACs, the independent scientific advice should be able to address those issues in a time frame that is needed for the decision-‐making process. 3. Legitimacy: if the advice would already include a common understanding between different interest groups, this could enhance the legitimacy of the results. 4. Compatibility: there is no real issue with compatibility with current methods because second opinions are currently free format. In order to gain credibility it is still required to develop or apply methods that are generally considered valid for these types of analyses. And it could involve the development and testing of new methods. Route 2A: North East Atlantic Fisheries Commission (NEAFC) According to the 1995 United Nations Fish Stocks Agreement (UNFSA), straddling fish stocks and highly migratory fish stocks are to be managed by Regional Fisheries Management Organisations (RFMOs), consisting of coastal states and relevant Distant Water Fishing Nations (DWFNs). In the Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

North East Atlantic there are several straddling stocks, including herring, mackerel and blue whiting, that are exploited both within coastal states‘ 200-‐mile Exclusive Economic Zones and on the high seas. Management of such stocks poses special management problems. In this area, the North East Atlantic Fisheries Commission (NEAFC) represents the relevant RFMO. There are currently five contracting parties or Coastal States: The European Union (EU), Denmark (on behalf of the Faeroe Islands and Greenland), Iceland, Norway, and the Russian Federation. Coastal States differ per stock. There is no internal scientific body since scientific advice is provided and accepted solely by the ICES, on the basis of a Memorandum of Understanding (NEAFC 2004). Potential PFA input: According to the chair of NEAFC there will be no room for any other advise that coming from ICES. The argument is that NEAFC can impossibly judge the quality of additional advise whereas ICES advise has been internationally recognised. Route 2B: Pelagic Regional Advisory Council (‘Pelagic RAC’) The Pelagic RAC prepares and provides advice on the management of pelagic fish stocks on behalf of the fisheries sector and other stakeholders as NGO’s and scientists. It covers the pelagic stocks of all the areas. A centralised, top-‐down approach makes it difficult to adapt the CFP to the specificities of the different sea-‐basins in the EU. Member States and stakeholders will take more responsibility for resource management at fisheries level, as well as for the coherence of such management with other actions in each sea basin. The EU Commission proposes an agenda for the Reform of the Common Fisheries Policy that is ambitious regarding regionalisation, which means that the role of the Pelagic RAC will only increase in the years to come. Current and potential PFA roles: 1. Taking active part in working groups 2. Dedicated research projects. Ad-‐hoc study results or other robust findings on stock dynamics, -‐ differentiation and health. Studies where commercial-‐ scientific-‐ and auxiliary data are used for knowledge studies could be organised as Public Private Partnerships (PPP) between PFA and scientific institutes or other specialists. EU and the industry typically fund such projects.

Specific suggested strategies: From the total list of potential applications (chapter 1) for industry involvement we believe the following actions are most relevant to our target species: Blue whiting • Improving existing surveys on the spawning grounds west or Ireland by providing real-‐time distribution maps, school morphology and fecundity information to scientists and advice on the timing and location of the surveys. This can all be done by collaborating with the ICES survey planning group; • Contributing to model future spawning distribution by providing key ocean observations from the core aggregation areas to ongoing studies performed by national institutes; Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

•

• • •

Providing a relative abundance estimate to the ICES working group for Northern Pelagics now when the stock is in decline, using a analytical methodology that is currently being tested on the Dutch pelagic fleet; Contributing to stock health studies now when the general condition of blue whiting is inexplicable decreasing by providing length/weight measurements on commercial catches; Contributing to study stock differentiation (north-‐ and south component) and to map year-‐ round migration by providing genetic and acoustic data Explore the possibilities of providing mackerel stomach samples to study predation on blue whiting larvae. This requires a quickscan on feasibility and project proposal for a collaboration project that could be funded by national or EU fisheries funds.

Mackerel Linkage of commercial acoustic and catch data with auxiliary environmental data could help verifying the above hypotheses or provide the directions in which science could focus. Temperature, salinity and currents, all available as live or near real-‐time data from various research institutes could be used to analyse migration patterns by looking at avoidance or preference characteristics of certain areas at different live stages. Acoustic surveys by commercial vessels can be used to estimate a new annual abundance index which performance can be evaluated by a triennial research vessel survey (egg survey). Annual acoustic data obtained from the commercial fishing vessels conducting this survey could provide an economic and timely way to augment the biennial fishery-‐independent data used to estimate the early life component of the North Atlantic mackerel stock. Other, less effort consuming activities can be: • Co-‐development of acoustic species detection algorithms that can lead to improved selectivity or reduced discarding on mackerel and horse mackerel mixed fisheries; • Contributing to study mackerel differentiation (north-‐ and west component) and to map year-‐round migration by providing genetic and acoustic data. Horse mackerel As we miss detailed knowledge about this species (there is no knowledge on North Sea horse mackerel at all), data provided by fisheries vessel could substantially contribute to our understanding of the distribution and migration of horse mackerel. For example qualitative acoustic information could be used to analyse the occurrence or avoidance of certain areas with given environmental conditions. In combination with catch information, providing basic size class information and hence could be used as a proxy for age, could lead to a general overview of the migration patterns of the stock. Furthermore acoustic data from fisheries vessel could be used as added value to the triennial egg survey. Other, less effort consuming activities can be: • Co-‐development of acoustic species detection algorithms that can lead to improved selectivity or reduced discarding on mackerel and horse mackerel mixed fisheries; • Contributing to the effort of mapping year-‐round migration and contributing to study horse mackerel differentiation (North Sea, Western-‐ Norwegian-‐ and Southern component) by providing genetic and acoustic data.

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Ensuring continuation of fleet involvement Data collection based on mutual interest and trust Onboard data processing is the most preferable, delivering instant results available to scientists and fishermen. This method implements a direct collaboration between the fishermen and scientist creating a truly trust based cooperation: working on a better mutual understanding, building up a common understanding, a common data ownership of fisheries data, and improved information for stock assessments and consequently an improved stock management. The only prerequisite for the execution of this kind of sampling is the will of scientists and fishermen to proceed in this direction and the establishment of a robust compensation scheme for the fishermen dedicating their time. In order to assure that fishermen and scientists both benefit from their cooperation, there has to be a compensation plan for the involved fishermen. IMR Reference Fleet as model for data collection protocols? Norway has allocated a special catch quota, which is part of the national TAC for this purpose. The quota is mainly set for cod, herring, mackerel and Greenland halibut although the fishermen collect information of all caught species. The value of the quota is shared 60/40 vessel/IMR, where all the fish is sold by the fishermen and IMRs part of the quota is used to repay the fishermen according to decided deliveries and running costs. There will be no extra TAC or fishing days in this model. All compensation will be at the expense of others. So there is no general benefit. The main benefit is the believe of the sector in a fishing policy that is based on information which they have supplied. The IMR reference fleet can be used as an example for processing samples onboard. Biological samples (length, otoliths, stomachs, genetics etc.) and logbook data are delivered according to contract. There is no obvious reason why such an allocation could not be implemented for the Netherlands too. If though for any reasons this might prove difficult to be realised other premises might be created such as direct fiscal compensation or other privileges when it comes to quota allocations.

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Appendix I Comparison between Myriax Echoview, Marec SEAT, Marec LSSS and Simrad ES70 software packages Package Name Developper

Echoview Myriax

SEAT Marec

LSSS Marec

Main strength

Power & Flexibility

Skippers based

Full cruise overview & Extensibility

Fishermen

Scientific surveys

Easy to use, especially tailored to the needs of fishermen

Rigid & efficient framework to process complete surveys or large datasets at a time with a nice immediate overview

Easy to use

YES (Norwegian vessels)

Yes

Application it is designed for

User friendliness

Experience with commercial fleet

Supported Echosounders Loading & Viewing Data Supported File formats Load multiple data from different acoustic instruments Live viewing of echograms Live view Frequency response Load additional information from sensors Load catch data

Any acoustic application Powerful & comprehensive interface for viewing and implementing algorithms without the need of prgramming (stinging together operators) YES (Chilean vessels) BioSonics Model 102, DE4000, DE5000, DE6000, DT4000, DT5000, DT6000 and DTX series of echosounder Furuno FQ80 and ETR-‐ 30N echosounders HTI Models 241/243/244 split beam digital echosounder system Kaijo KFC-‐500, KFC-‐ 1000, KFC-‐2000, KFC-‐ 3000, and KFS Precision Acoustic Systems PAS-‐103 Single-‐beam and PAS-‐ 103 Split-‐beam echosounder Simrad EK60, EQ60, ES60, EY60, EK500, EA500, EY500, EA600, and EA400 echosounder SonarDataEchoListener SciFish 2100 combined single-‐beam broadband/split-‐beam narrowband sonar

ES70 SIMRAD Overview of installed Simrad equipment Visualise acoustic data

SIMRAD

SIMRAD EK60/BI500

Yes

Yes (Up to 6 windows)

Yes

Yes (under revision)

Yes

Partly (through notes), probable future

Yes, direct linkage with electronic logbook

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Yes -‐ Simrad sensors Yes -‐ SimradCatch monitoring

Package Name Customisable startup window

Calibration

Noise Removal Pre-‐Processing

Filtering Automatic school detection Editing of detected schools Manual school selection Automatic bottom detection Line creation (exclusion/inclusion) Automation of processing & data export Automatic school detection & Manual selection/modification

Classification

Explanation

Self-‐teaching system

Interpretation tools Charaterisation Live view automatic fish school identification Live view freqeuncy responses Live view school densities Live view map with classification information

Echoview development

SEAT

LSSS

ES70 system

Yes

Apply external Calibration file

Change gain

Yes

Yes Yes (very flexible drawing tool) ?

Yes

Automatic or manual

Yes (Templates & COM scripts)

Yes

Classification in regions or cells through dB differeneces

Classification of layers or regions based on frequency response differences

Yes

Echogram Map

Echogram Bottom hardness Fish size distribution Biomass distribution

-‐Autocalibration of Ex60, ME70, DT4 and SMP data formats -‐Centralised calibration files for applying overrides to logged parameters -‐One Click removal -‐Algorithms for advanced removal Yes (predefined flexible filters) Yes, additionally single target detection & fish tracking Yes Yes (multiple drawing tools) Yes

No (possible future development) Echogram 2D/3D projection graph

Yes

Angles graph

Frequency response

Beam graph

Threshold response

Frequency Distribution graph Frequency Response Graph Threshold Response graph Heading graph Line graph Oing graph Relative mean dB graph TS vs Depth graph TL vs depth graph

Echogram

Target Strength Window

Echo position

Echosounder configuration

Fish position

Trawl Window Plankton Window CTD Window

Supp ort

Yes

Yes Yes (cruise track with various inforation about the selected regions) Telephone or E-‐mail contact

Map with species information

Telephone or E-‐ mail, work-‐days,

Telephone or E-‐mail, work-‐days, 09:00-‐15:00

Worldwide support, E-‐mail,

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Package Name

Echoview

Consulting services

Number of users

SEAT 09:00-‐15:00 GMT+1 Special agreements

ES70 phone

Special agreements

Remote desktop support Forums

in use by more than 200 research institutes in over 30 countries around the world

Not available for production yet. Pilot phase has been completed.

LSSS has more than 100 users and is installed on 5 research vessels

Base 2,590 Bathymetric 2,590 Analysis 6,560 Pricing Scheme

LSSS GMT+1

Virtual echogram 11,790 Schools detection 3,320 Scripting 2,660 Live viewing 3,25 TOTAL: 32.760 Euro

Not available

One ever-‐lasting license of LSSS: 16 000 Euro One year of support services: 1 440 Euro One year of maintenance services: 1 440 Euro

Free

TOTAL: 18 880 Euro

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Appendix II Fisheries management process in the EU

Collection of data National fisheries institutes are collecting data on selected fish stocks all year round, during different surveys. In the Netherlands the surveys are generally executed by IMARES and data is to be collected in the North Sea or the Northeast Atlantic. The collected information is then transmitted to the international forum of fishery biologists at ICES. At ICES, ACOM (Advisory Committee) in cooperation with dozens of groups, study groups and advisory groups formulate a draft on the status of numerous fish stocks. ICES advice and management proposal (TAC’s) Next, ICES formulates, based on the information provided by the various institutes, its opinion on the Total Allowable Catch (TAC) as well as other matters that seem relevant to the management of the resources. This forms the principle ICES advice which is then communicated to the European Commission. STECF The Scientific Technical and Economic Committee on Fisheries (STECF) reviews, comments and adopts advice from all sources (ICES, GFCM, ICCAT) and advices the European Comission. Consultations and recommendations by different stakeholders Next, different advisory boards, from within the Common Fisheries Policy (CFP), where all stakeholders are represented, have the possibility to comment and give recommendations as a reaction to the advice formulated by ICES. These are to be directed towards the EC, the Council of Ministers and/or the European Parliament (EP). This includes for example the Advisory Committee on Fisheries Affairs (ACFA) constituted of different RAC’s (Regional Advisory Council) giving their advice to the EC, Member States and EP. It has to be noted though that everything communicated is not binding but really just recommendations. Negotiations with Coastal states Next, the EC discusses the advice given by ICES on behalf of the EU with non-‐EU countries that form the coastal states. During these discussions it is decided which parts of the total TAC will be allocated to the different countries. For example mackerel is discussed between EU, Norway and Faroe Islands, whereas blue whiting also includes Iceland. The final accord is given yearly in London at the NEAFC (Northeast Atlantic Fisheries Commission) meeting. Furthermore there are bilateral discussions between the different countries, where the meeting between the EU and Norway is generally of highest importance, sharing many stocks of high commercial interest. The results of these formal negotiations have then to be approved by the EC board. Commission Considerations Prior to the final decision making a formal proposal for the TAC and quota regulations are formulated. This should be delivered shortly before the Scientific Technical and Economic Committee on Fisheries (STECF) checks and gives its final advises. TAC and quota fixing Then TAC’s are finally set at the meeting of the Fisheries Council with all fisheries ministers of the EU participating. National quotas are set as a fixed percentage.

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Appendix III Scientific pelagic surveys executed by the Netherlands In the Netherlands all scientific surveys that are contributing data to the ICES working groups are executed by IMARES. This includes mainly 3 different surveys relevant to pelagic species:

Acoustic Blue Whiting Survey in the Northeast Atlantic, since mid 1990s: Executed annually, 3 weeks in March-‐April Area: Atlantic Ocean west of Ireland Method: Echo-‐Integration & Pelagic trawls (at 300 m) onboard RV Tridens Research areas: Pelagic fish & hydrography Countries participating: Netherlands, Ireland, Norway, Iceland, the Faroer Islands, Russia

Herring Larvae Surveys (IHLS), 5 weeks (2 weeks in Sept., 1 week in Dec., 1 week in Jan.) Area: Buchan (NW North Sea), Central North Sea, Southern North Sea / Eastern English Channel Method: Plankton net (till Jan.2004: Gulf III, since Sept.2004: Gulf VII) with 280 mm mesh size Research areas: Herring and other fish larvae; sometimes the Dec. and Jan. surveys also target plaice eggs; hydrography, used for plankton quantification calculations only Countries participating: Netherlands, Germany Acoustic Herring Survey, since mid 1990s: Executed annually, 4 weeks in June-‐July Area: northern and central North Sea Method: Echo-‐Integration & Pelagic trawls onboard RV Tridens Research areas: Pelagic fish & hydrography Countries participating: Scotland, Netherlands, Germany, Denmark, Norway A) Northeast Atlantic Mackerel / Horse Mackerel Egg Surveys, since 1977 (NL since 1983) Executed every 3 years, 6 weeks (3 weeks in May, 3 weeks in June) Area: Gulf of Biscay, Celtic Sea (variable survey track), ICES Sub-‐areas VI to IX, North Sea Method: Plankton net (Gulf VII plankton-‐torpedo; 500 mm mesh size); Pelagic trawl Research areas: Mackerel and horse mackerel eggs, Fecundity/ maturity/ atresia of mature mackerel/horse mackerel, hydrography Countries participating: England, Germany, Ireland, Netherlands, Norway, Portugal, Scotland, Spain B) Dutch Atlantic Mackerel / Horse Mackerel Egg Surveys, 1968 (triennial since 1996) Executed every 3 years, 5 weeks (June-‐July) Area: Northern and central North Sea (ICES Sub-‐area IV) Method: Plankton net (Gulf VII plankton-‐torpedo; 500 mm mesh size); Pelagic trawl (up to 5m from the bottom or 10 m below the thermocline) Research areas: Mackerel eggs, Fecundity/ maturity/ atresia of mature mackerel, hydrography Countries participating: Netherlands, Norway

Improved knowledge of pelagic fish stocks by using commercial data 2 jan 2012

Appendix IV Mackerel War For years the EU have claimed the ”Biscaya stock” as an exclusive right. However, the so-‐called ”Western stock” (West of Ireland) and the third ”North Sea stock” have been co-‐managed and shared quota wise. As a consequence of this regime, Norway claims it has been given too small a quota, compared to its historical traditions. Part of this long lasting tension is also based on the fact that Norway for much of the Seventies barred its own fleets from mackerel fishing to protect the stocks. However, during the same period the EU (ironically with the support of Norwegian banks) built up its fleet, continued fishing and landed lots of mackerel in Norway, with the Norwegian mackerel operators left tied up in port as angry spectators. In the autumn of 2009, in response to this, Norway and the Faroe Islands granted themselves an exclusive quota equivalent to the exclusive EU one in Biscaya. This elicited the ”war”. When the mackerel biomass crossed from the Norwegian to the EU zone, the Norwegians were evicted from that zone when attempting to fish, even though they were entitled to through the standing agreement.

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