Jim Champion and Willip Von Ree), who in no way endorse this work or its contents.
COUNTRY REPORT
FIELD WORK MISSION TO UNITED KINGDOM
MARCH 2014
This specific contract No 9, SI2.656808 “Field work specific contract for Lithuania, Romania,
Spain and the United Kingdom”, has been implemented within the framework contract,
MARE/2009/08 “Assistance for the monitoring of the implementation of national
programmes for the collection, management and use of data in the fisheries sector”,
funded by the DG Mare.
1
TABLE OF CONTENTS EXECUTIVE SUMMARY 3 1. INTRODUCTION 7 2. GENERAL OVERVIEW 9 3.3.1. Organisation and management 9 3.2. Inter-Institutional Coordination 14 3.3. IT Infrastructure and flow of information 15 3.4. Users request management 17
BIOLOGICAL DATA – MÉTIER RELATED VARIABLES 19 4.4.1. Programme monitoring 19 4.2 Data upload, storage, processing and access 24 4.3. Statistical quality 27 4.4. Conclusions 27
BIOLOGICAL STOCK DATA 28 5.5.1. Programme monitoring 28 5.2. Data upload, storage, processing and access 29 5.3. Statistical quality 29 5.4. Conclusions and recommendations 30
RECREATIONAL FISHERIES 31 6.6.1. Programme monitoring 31 6.2. Data upload, storage, processing and access 31 6.3. Statistical quality 31 6.4. Conclusions and recommendations 32
TRANSVERSAL DATA 33 7.7.1. Programme monitoring 33 7.2. Data upload storage, processing and access 34 7.4. Conclusions and recommendations 36
RESEARCH SURVEYS AT SEA 37 8.8.1. Programme monitoring 37 8.2. Data upload, storage, processing and access 37 8.3. Statistical quality 38 8.5. Conclusions and recommendations 38
ECONOMIC DATA – CATCHING SECTOR 39 9.9.1. Programme monitoring 39 9.2. Data upload, storage, processing and access 40 9.3. Statistical quality 43 9.4. Conclusions and recommendations 44 ECONOMIC DATA – AQUACULTURE 45 10.10.1. Programme monitoring 45 10.2. Data upload, storage, processing and access 45 10.3. Statistical quality 46 10.4. Conclusions and recommendations 48 ECONOMIC DATA – PROCESSING SECTOR 49 11.11.1. Programme monitoring 49 11.2. Data upload, storage, processing and access 49 11.3. Statistical quality 50 11.4. Conclusions and recommendations 51 VARIABLES ON THE EFFECTS OF FISHERIES ON MARINE ECOSYSTEM 53 12. CONCLUSIONS BY CHAPTER 54 13.13.1. General IT 54 13.2. Transversal data 54 13.3. Biological data 55 13.4. Economic data 55 13.5. Ecosystem indicators 56 RECOMMENDATIONS BY CHAPTER 57 14.14.1. General IT 57 14.2. Transversal data 57 14.3. Biological data 57 14.4. Economic data 58
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ACRONYMS
ABI Annual Business Inquiry
AFBI Agri-Food and Biosciences Institute, Northern Ireland
AR Annual Report
ARINI Agricultural Research Institute of Northern Ireland
BSS Biological Sample System
CEFAS Centre for Environment, Fisheries and Aquaculture Sciences
CPUE Catch Per Unit Effort
DARD Department of Agriculture and Rural Development
DCF / DCR Data Collection Framework / Regulation
DEFRA Department for Environment, Fisheries and Aquaculture Sciences
DG MARE Directorate General for Maritime Affaires and Fisheries
EC European Commission
EFF European Fisheries Fund
FAD Fishing Activity Database
FAO Food and Agriculture Organisation
FHI Fish Health Inspectorate
FIFG Financial Instrument for Fisheries Guidance
FMD Fishery Management Database
FTE Full-time equivalent
FSS Fishing Survey System
FWC Framework Contract
GARI Gathering and Reporting Information system
ICES International Council of the Exploitation of the Sea
JNCC Joint Nature Conservation Committee
JRC Joint Research Centre
MCSS Monitoring Control Surveillance System
MMO Marine Management Organisation
MSFD Marine Strategy Framework Directive
MSS Marine Scotland Sciences
NDPB Non-Departmental Public Body
NC National Correspondent
ONS Office for National Statistics
PO Producer Organisation
RCM Regional Coordination Meeting
RFMOs Regional Fisheries Management Organisations
RSS Registry of Seamen and Shipping
RV Research Vessel
SAT Statistics and Analysis Team
SBS Structural Business Survey
SEAFISH Sea Fish Industry Authority
SFM Sea Fish Management
STECF Scientific, Technical and Economic Committee for Fisheries
ToR Terms of Reference
TR Technical Report
UKSA UK Statistics Authority
VCU Vessel Capacity Unit(s)
VMS Vessel Monitoring System
WG(s) Working Group(s)
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EXECUTIVE SUMMARY 1.
This report presents the result of the third field work mission within the Third Horizontal Contract for
2013-2014 of the Framework contract (FWC) “Assistance for the monitoring of the implementation of
national programmes for the collection, management and use of data in the fisheries sector”, which
took place in United Kingdom (UK).
This third field work mission took place in the United Kingdom from 24th to 27th March 2014 and it
was coordinated together with the UK National Correspondent (NC) Mr. Matthew Elliott.
Organisation
The main organizations intervening in the DCF in UK are the Marine Management Organisation
(MMO); the Sea Fish Industry Authority (SEAFISH) and the following coordinators: Centre for
Environment, Fisheries and Aquaculture Science (CEFAS) and the Environment Agency for England
and Wales; Agri-Food and Biosciences Institute (AFBI) for Northern Ireland; and Marine Scotland
Sciences (MMS) for Scotland.
Guidelines for data collection / division of work
The responsibility for the collection of the DCF data is distributed as follows:
MMO is responsible for the management of information on transversal data (logbooks,
sales notes…). The MMO system is hosted and maintained at CEFAS and covers England,
Wales and Northern Ireland. Marine Scotland transmits transversal data on a daily basis to
CEFAS to build the full set of transversal data for UK.
Biological data are managed at CEFAS for England and Wales, at Marine Scotland for
Scotland and at AFBI for Northern Ireland.
Aquaculture data is compiled by CEFAS for all UK from aquaculture production data coming
from UK Fish Health Inspectorates for England and Wales, Marine Scotland Sciences (MSS)
and DARD for Northern Ireland. This input is supplemented with economic information
extracted from the Annual Business Inquiry (ABI) results provided by the Office for National
statistics (ONS).
Economics fleet, fish processing DCF data is collected and compiled by SEAFISH for all UK.
IT systems
The IT systems were set up a long time before the DCF started, some of the biological database
systems in place are now under revision/reconstruction to better answer the today requirements like
for example the system used for processing the biological sampling at CEFAS.
An attempt was made of using common tool was experienced: Marine Scotland bought the FSS
survey database to CEFAS but the experience was not judged as very satisfactory from financial and
technical perspectives.
The compilation of UK data is a bit complex as it requires combining the results from different
independent country system. To achieve this, UK has implemented solutions allowing the different
4
countries within UK to work together (SharePoint web site) and umbrella system to compile
transversal data from different systems when primary data are needed at UK level (IFISH).
The UK benefit from a huge in house experience in fisheries statistics, internal experienced IT
development team and is always thinking of continuously improving the process in place. This is
particularly true at CEFAS while Marine Scotland loses most of the IT staff due to retirements
recently.
Nevertheless it is to be noted that UK developed a well performing system for the transversal data,
is redeveloping a system for biological sample while the aquaculture database is not yet available.
Regarding the fleet and fish processing data, the system in place at SEAFISH is based on the use of
Access/Excel and STATA tools. Most of the experience in the domain relies on the head of
department due to internal restructuring.
Biological variables
The collection of biological variables is geographically subdivided and is performed in practice by
CEFAS for England and Wales, AFBI for Northern Ireland and Marine Scotland Science for Scotland.
The MS has adopted an interesting probability sampling strategy that has potential to avoid the
statistically biased samples of quota sampling (métiers). The sampling scheme is based on own
experience as well as the recommendations issued by the various ICES expert workshops and
planning groups, constrained, however, by the limited number of person-days available for sampling
purposes (sampling effort).
Métier related variables
The UK does not target the métiers identified by the 90% ranking system in the first place, but
constructs its sampling strategy along a random selection of trips in more aggregated gear groups
and areas. This is mainly due to the polyvalent nature of some fleet segments and the high variability
of effort within métiers from one year to the other as well as the constraints related to the available
sampling days. In any case there is an attempt to cover all fleet segments and gear groups, allocating
the sampling effort according to their relative importance (with regard to number of trips, landings,
discards and number of vessels). Moreover, a randomisation of the list of vessels to be sampled (on-
board sampling) and a randomisation of the order of ports and trips to be to be sampled (on-shore
sampling) is done.
In some cases discrepancies between the number of trips expected and sampled in relation to the
number of fishing trips recorded in the reference year and in the actual year have been observed.
These deviations were explained by constraints related to seasonality and limited sampling
resources; however, they may be also an indication for problems in the randomisation of the
samples.
5
Stock related variables
Data for stock-related biological variables derives from concurrent market sampling of commercial
fisheries (complemented with stock specific sampling) and research surveys, the latter being the
most important source for maturity and sex ratio data. While for some species the determination of
certain biological variables (sex ratio, maturity) can be done at the market, others rely completely on
data provided by surveys. Besides research surveys, otoliths are also collected from commercial
fisheries where possible, both from on-board (discards) and market sampling.
Apart from some exceptions, the UK achieves the planned minimum number of individuals/species
to be sampled and, in many cases, exceeds the target to a large extent. For those species where
under sampling was recorded, problems with reduced catches during surveys or logistical
constraints while sampling a large number of species were reported.
Also for the collection and determination of stock-related data, the UK follows international
standards and methodologies and is very active within working groups, e.g. in the international
coordination and exchange of otoliths for the improvement of age reading expertise.
Surveys at sea
The UK has conducted all expected research surveys according to internationally agreed
methodologies and standards. Some minor deviations of the achieved number of samples with
respect to the planned numbers have been recorded due to technical issues or problems of the
weather conditions in the field.
Recreational fishery
CEFAS has conducted an extensive survey on the sea angling activity in England. Sea angling effort
and catch per unit effort (CPUE) have been estimated based on data provided through the
nationwide ONS household survey, on-site surveys of shore and private boat anglers and on data
obtained from angling charter boats. Total annual catch estimates for seabass and cod were
produced for England, while for Scotland, Northern Ireland and Wales this data is incomplete. It is
being considered at present whether to apply a similar approach in the various countries or to
directly include them into the survey carried out by CEFAS. For stock assessment purposes, data on
eel and salmon (commercial and recreational fisheries) is collected from different sources (number
of fishing licences for inland waters, angling reports, electrofishing, fish counters, etc.) and is well
covered. Legislation with regard to angling on eel varies from one country to the other.
Transversal variables
UK managed to build an efficient integrated IFISH system for the management of transversal data
combining the data provided by the existing systems. The UK transversal data are accessible to the
partners feeding the common database. UK focuses a lot on the automated checks allowing
verifying the quality of the data at the data entry stage and has consequently reduced the time
devoted to post validation checks.
6
Economic data on catching sector
Economic data on the catching sector is traditionally (since 1980s) collected by Seafish Industry
Authority, which covers the whole UK.
The survey is based on a panel of about 450 vessels, about 10% of the active fleet in number of
vessels, but about 40% in terms of production value. The survey achieves significant level of
coverage, in particular for the fleet above 10m. Seafish has developed a model in STATA to estimate
the costs of each individual vessel, using the revenues from logbooks and sale notes and costs from
the survey. Having estimates at this level of detail allows making different types of aggregations,
incl. regional analysis.
The procedures of estimation are described in various documents.
Aquaculture sector
Collection of data on production of aquaculture is coordinated with UK administrations by the Fish
Health Inspectorate, which resorts within CEFAS. This data is used to meet the requirements of
Eurostat.
UK has not collected any costs data directly from aquaculture firms. Instead it relied on the Annual
Business Inquiry (ABI) by the ONS. However, the data coming from ABI is not only related to
aquaculture, but to a broad spectrum of economic activities. The aquaculture content is small and
unclear. A new data collection system, directed at aquaculture only was piloted in 2013 is being put in
place and should produce first results in 2014. It could not be evaluated as it is not yet operational.
Fish processing
Data on fish processing is also collected by Seafish, which carries out an in-depth census every four
years and a lighter survey bi-annually. Also in this case, Seafish relies on long experience, prior to the
establishment of DCF. The survey covers about one third of the firms, which represent about half of
the total production. In addition to its own survey, Seafish acquires financial data from the Company
Registry at Companies House.
Raising the sample data to the population is based on average costs per FTE (Full-time equivalent), as
employment figures are available for all firms.
Seafish does not cooperate with the ONS and does not use any of their Structural Business Survey
(SBS) result. The procedures are described in several documents.
Ecosystem indicators
Data for DCF requirements on the effects of fisheries on the marine ecosystem are collected and
allow end-users to calculate the ecosystem indicators. Data is available on national databases and,
within CEFAS and Marine Scotland, is accessible to the in-house staff responsible for the reporting
obligations related to the Marine Strategy Framework Directive (MSFD). Besides, data for Indicators
1-4 are also provided to ICES to be available on the online database of trawls surveys DATRAS.
7
INTRODUCTION 2.
This report is the result of the third field work visit planned for 2014 within the 9th Specific Contract
signed between DevStat and DG MARE (Directorate General for Maritime Affairs and Fisheries) on
12th July 2013 whose objective is the monitoring of the implementation of the data collection
framework in the UK.
The main objective of this field work contract is to verify whether and to which extent the
programme implementation is being followed up by the UK institutions and whether all the
biological, technical, environmental and socio-economic data specified in the programme are being
collected according to the specified methods, procedures and quality requirements.
For this specific field work mission, the team members were:
Mr Pavel Salz. Leading Technical Expert for the Horizontal Contract and fisheries socio-
economics expert;
Mrs Christine Alberti-Schmitt. Information Systems expert;
Ms Anna Madriles. Fisheries biology and environmental issues expert;
Mr Iosu Paradinas. Fisheries biology and environmental issues expert;
Mrs Ester Azorín. Project Assistant and socio-economic expert.
To achieve the mission objectives, the team of experts conducted a preparatory work for the field
work mission to UK, consisting mainly in the revision of the basic documentation and specific
technical documentation in order to obtain a first evaluation of the UK situation.
After this first revision and diagnosis, the team visited from 24th to 27th March 2014 the UK scientific
organisations and institutions dealing with the National Programme (NP), in Lowestoft, Edinburgh
and Aberdeen. The findings of the mission are detailed in this report.
Acknowledgements
The team wants to acknowledge the fruitful collaboration and openness of the Marine Management
Organisation (MMO) as well as of the other UK institutions involved in DCF and its staff for their
personal contribution to the success of the field work mission.
Implementation of the mission (counterparts, calendar)
The agenda of the mission, shared with Mr Matthew Elliott (NC for the DCF) prior to the mission, was
implemented as planned and all the topics were revised according to the agenda (see Annex 1).
The team worked in parallel during the first, second, third and fourth days of the mission, sharing
afterwards the findings of the different meetings.
8
Participants from the UK institutions involved in DCF were:
1. Marine Management Organisation. MMO
Mr Matthew ELLIOTT, NC for the DCF
2. Centre for Environment, Fisheries and Aquaculture Science. CEFAS
Mr Mike ARMSTRONG;
Mr David PETTENGELL;
Mr Wendy DAWSON;
Mr Richard GARDINER;
Mr Gareth NORMAN;
Mr Jon ELSON;
Ms Ana RIBEIRO SANTOS;
Mrs Lisa READDY;
Mr Andy GOULDBY
Mr Iain HOLMES.
3. Agri-Food and Biosciences Institute. AFBI
Mr Pieter-Jan SCHÖN
4. Sea Fish Industry Authority. SEAFISH
Mr John ANDERSON;
Mr Steve LAWRENCE;
Mrs Alison GRANT.
5. Marine Scotland
Mr Phil KUNZLIK;
Mrs Margaret BELL;
Mr Jens RASMUSSEN;
Mr Alastair POUT.
Structure of the report
The Country Report is organised according to the requirements of the Terms of Reference (ToR) and
includes the following sections:
Section 3: General Overview.
Section 4: Biological data – Métier-related variables.
Section 5: Biological data – Stock-related variables.
Section 6: Recreational Fisheries.
Section 7: Transversal data.
Section 8: Research Survey at Sea.
Section 9: Economic data – Catching sector.
Section 10: Economic data – Aquaculture.
Section 11: Economic data - Processing Industry.
Section 12: Ecosystem data.
Section 13: Conclusions.
Section 14: Recommendations.
The Report is accompanied by 8 Annexes.
9
GENERAL OVERVIEW 3.
This chapter contains a presentation of the main UK institutions involved in DCF as well as their
organisation, management, IT infrastructure and inter-institutional coordination established
between them, in what respects the implementation of DCF.
3.1. Organisation and management
The main Institutions involved in DCF in UK are described below:
a. MMO. Marine Management Organisation
The MMO is an executive non-departmental public body (NDPB) established and given powers under
the Marine and Coastal Access Act 2009. This brings together key marine decision-making powers
and delivery mechanisms.
MMO is in charge to:
Implementing a new marine planning system designed to integrate the social requirements,
economic potential and environmental imperatives of their seas.
Implementing a new marine licensing regime that is easier for everyone to use with clearer,
simpler and quicker licensing decisions.
Managing UK fishing fleet capacity and UK fisheries quotas.
Working with Natural England and the Joint Nature Conservation Committee (JNCC) to
manage a network of marine protected areas (marine conservation zones and European
marine sites) designed to preserve vulnerable habitats and species in UK marine waters.
Respond to marine emergencies alongside other agencies.
Developing an internationally recognised centre of excellence for marine information that
supports the MMO’s decision-making process.
MMO is responsible for the following main areas of the CFP:
1. Licensing of fishing vessels: by issuing licences for English vessels in the inshore and offshore
fleets.
2. Managing fleet capacity: by working with fisheries authorities in the devolved
administrations to monitor boats entering and leaving the fleet and also producing the AR
(Annual Report) for the EC. MMO also can issue entitlements to fish in restricted areas, and
will process transfers between vessels of entitlements to days at sea.
3. Managing fisheries quotas: by preparing and distributing quota management rules,
managing international quota swaps, issuing annual quota allocations to producer
organisations and other groups, monitoring quota uptake, managing quota allocations for
the non-sector and inshore fleets and set catch limits for those fleets where necessary.
4. Managing European funding schemes: by processing European Fisheries Fund (EFF) grant
applications and claims in England. MMO also reports on behalf of the UK to the EU on the
implementation of the EFF.
5. Collecting, co-ordinating and providing information: by preparing and coordinating financial
and technical reports on fishing activity to the EC, the International Council of the
Exploitation of the Sea (ICES), the United Nations Food and Agriculture Organisation (FAO)
10
and relevant Regional Fisheries Management Organisations (RFMOs), such as the North East
Atlantic Fisheries Commission. To collect this data, MMO monitors catches and fishing
activities from markets, merchants, logbooks, landing declarations and sales notes and
analyses the data to inform the development of fishing policy.
6. Enforcing fisheries rules: by ensuring compliance with the rules of the CFP and with quota
management rules. In particular MMO is required to implement the EU marketing regime by
inspecting and verifying withdrawal of fish from the market, and by ensuring compliance
with marketing standards through routine checks. Buyers and sellers of fish are monitored
at their initial point of sale as required by EU rules.
Human resources
The MMO has 321 members of staff1, with:
- 51 working within the marine licensing function;
- 16 working within the marine planning function;
- 159 working within operations, which includes fisheries vessel licensing, quota management,
marine conservation and enforcement, statistics and analysis, and staff based in their
coastal offices; and
- 76 working in support functions such as finance, IT, communications, human resources,
legal, health and safety and board and executive teams.
For the DCF purpose, MMO has no dedicated staff as the database are hosted and maintained by
CEFAS.
b. CEFAS. Centre for Environment, Fisheries and Aquaculture Science
CEFAS is an executive agency of the Department for Environment, Food and Rural Affairs (Defra) in
charge to provide evidence-based scientific advice, managing related data and information,
conducting scientific research, and facilitating collaborative action through wide-ranging
international relationships.
CEFAS is a key delivery partner for Defra and for the MMO. It also works for the Welsh government
in the area of DCF. In addition to partnerships with organisations across the Defra Network, and
numerous links at project level, CEFAS’ collaborative work across Government includes:
- Coordinating activities with comparable centres in Scotland and Northern Ireland (MSS and
AFBI);
- Linking with relevant science institutes and research councils to ensure best use made of
national assets, through the Marine Science Coordination Committee;
- Strategic alliances with selected universities such as the University of East Anglia
- Collaborating more broadly across Government scientific laboratories to promote
knowledge sharing.
CEFAS also work with the Welsh Government on DCF related activities.
1 At 31st of March 2013
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Main areas of expertise:
Conserve and enhance marine and wide aquatic environments and ecosystems;
Ensure sustainable use of natural resources, in particular fish stocks;
Collect, interpret and manage data to underpin decisions and to support long-term
monitoring;
Protect society and the economy from the effects of aquatic contaminants and fish
diseases;
Promote adaptation to the impacts of climate change on the aquatic contaminants and fish
diseases;
Enable government and other customers’ response to emergencies.
Human resources
The server used for DCF are hosted and managed in Lowestoft by an internal team and the
development and maintenance of the existing applications is ensured in house by a team of 20 IT
experts working on different projects. A team of 3 IT developers and a project manager is currently
developing the GARI system for the renewal of the biological sampling system.
c. AFBI. Agri-Food and Biosciences Institute
AFBI was created on April 2006 as an amalgamation of the Department of Agriculture and Rural
Development (DARD) Science Service and the Agricultural Research Institute of Northern Ireland
(ARINI). AFBI is a DARD Non-Departmental Public Body (NDPB).
AFBI is a multidisciplinary science institute engaged in cutting edge science in agriculture, food,
fisheries, horticulture and the environment. It carries out high technology research and
development, statutory, analytical, and diagnostic testing functions for DARD and other Government
departments, public bodies and commercial companies.
In the field of fisheries and aquatic ecosystem branch, the mission of the AFBI is to carry out research
and development, monitoring and technology transfer in support of the sustainable management of
fisheries and aquatic resources in Northern Ireland. The branch delivers evidence-based science in
marine and freshwater environments for a wide range of customers.
The sections primarily involved in DCF work is the Marine Fisheries and Freshwater Fisheries
Sections.
The Fisheries and Aquatic Ecosystems Branch conducts science programmes across several core
areas:
1. Marine fisheries stock assessment: combining outputs from both fishery-dependent and
fishery-independent programmes.
2. Coastal zone science: including marine resource assessment and modelling of carrying
capacity of Northern Ireland’s sea loughs.
3. Biological oceanography and marine ecosystem health, in support of the above.
4. Freshwater fisheries stock assessment and development of systems for the sustainable
management of the fishery resources.
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Human resources
AFBI has internal IT staff for the administration of the server and developers, with one dedicated
developer for DCF related work and one data manager. Support in application and database
development is also provided by other IT staff, if required.
d. SEAFISH. Sea Fish Industry Authority
SEAFISH is a Non-Departmental Public Body (NDPB) set up by the Fisheries Act 1981 to improve
efficiency and raise standards across the seafood industry. SEAFISH is funded by a levy on the first
sale of seafood products in the UK, including imported seafood.
Their purpose is to secure a sustainable and profitable future for the UK seafood industry helping to
improve marine and fisheries management and seafood supply chains to enhance sustainable
profitability of UK seafood business by providing economic evidence, analysis and advice-expert,
relevant, impartial and trusted.
Work streams:
Reputation and integrity: reinforce positive messages about the UK seafood industry;
Promoting consumption: encourage the consumption of seafood using clear and targeted
messages to educate the consumer.
Regulation: monitor planned EU and UK regulations, issue guidance and ensure timely
coordinated industry responses as required. Provide a forum to enable industry,
government and administrators to fully understand each party’s perspectives.
Fishing safety: improve safety, knowledge and skills amongst fishermen, through the
adoption of safer working practices and implementation of improved safety standards.
Responsible sourcing: provide and information source for the whole supply chain regarding
the responsible sourcing of seafood and the risks associated with this.
International trade: provide assistance in raising the profile of UK sourced seafood in export
markets and provide UK exporting companies with up-to-data market information.
Information: provide economic evidence, expertise and advice to UK government, the EC
(European Commission) and industry. Provide retail and foodservice market data to UK
industry and ensure the efficient dissemination of information from Seafish to industry.
Human Resources
The team is composed by five experts: 1 Chief Economist, 1 Senior Economist, 1 Project Manager and
2 Economic Researchers.
Number of IT and statistics staff
SEAFISH does not have any capacity for software development, only for the management of the IT
infrastructure. Development is usually sub-contracted to an external expert, with whom there is a
long term working relation.
13
e. Marine Scotland Sciences
The Marine Scotland is responsible for marine and fisheries issues in Scotland and its main purpose is
to manage Scotland’s seas for prosperity and environmental sustainability.
Areas of expertise:
Aquaculture
Compliance: effective monitoring and enforcement of marine and fish laws in order to
protect Scotland’s valuable marine areas and fisheries. These are protected by detecting
breaches of fisheries regulations by monitoring and inspection at sea and in ports, report as
appropriate to the prosecuting authorities.
Grants: Marine Scotland will target the EFF (European Fisheries Fund) and the Financial
Instrument for Fisheries Guidance (FIFG) to assist with capital investment in the aquaculture,
fishing and fish processing industries.
Licensing: there are a number of different types of licensing requirements, but Marine
Scotland has made a number of changes to simplify the existing licensing process and more
streamlined licensing will be developed over the coming months.
Offshore renewable energy
Marine environment: Marine Scotland has the role to ensure that the natural environment,
and the diversity of industries which depend upon it, is safeguarded for the future by
working to assess the quality of the aquatic environment and leading research in improving
knowledge on the potential environmental impacts of marine renewables.
Marine planning: the introduction of the Marine (Scotland) Act means better management
of the competing demands on marine resources is key and Marine Scotland is involved at
various level: (i) at national level, by creating Scotland’s first National Marine Plan; (ii) at
regional level, by creating Scottish Marine Regions; and (iii) Sectorial Planning for offshore
renewable energy and (iv) More widely, by working with a range of others within UK and
Europe.
Salmon & recreational fisheries
Science & data: the Marine Scotland Science2 (MSS) undertakes research and provides
scientific and technical advice on a number of marine and fisheries issues including
aquaculture and fish health, freshwater fisheries, sea fisheries and the marine ecosystem.
The nature of the work includes boat and shore based monitoring, laboratory work, building
bespoke monitoring equipment and state of the art computer technology and GIS systems
to analyse, plot and present the information.
Sea fisheries: Marine Scotland manages quota for fish stocks and all inshore fisheries within
the 12 nautical mile territorial water limit. It is also responsible for controlling the activities of
fishing vessels and fishing effort in the North Sea, West of Scotland and Faroese waters.
Number of IT and statistics staff
The servers used by the Marine Scotland scientific division in Aberdeen are hosted in Edinburg:
therefore no dedicated IT staff are currently working as support for the DCF in Aberdeen. Some staff
with IT background was trained on the use of a business object interface allowing extracting
information from the biological database (FMD).
A new team of 2 IT developers and a project manager is currently working on the development of a
new semantic database since 2 years. This approach could be later extended to fishery.
3.2. Inter-Institutional Coordination
MMO has the responsibility for managing distribution of the EU co-funding from DCF. The National
Correspondent position also resides within the MMO. DEFRA leads the UK control policy with strong
involvement from other administrations, particularly Marine Scotland. Control and enforcement
responsibilities reside within the individual country administrations. MMO Stats Team is responsible
for supply of UK’s transversal data for DCF purposes.
Regularity of meetings
2 annual coordination meetings are held (annex to the technical report).
Marine Scotland is hosting a SharePoint web site where the UK country partner can access
information on the DCF and deposit their contributions to UK reports.
The preparation of responses to the DCF related data calls is considered a major job. The tools in
place do not allow an easy automatic compilation of the information from the four different
countries. In each institution, that task requires at least one man month human resources. At CEFAS,
the IBIS system (see chapter 4), when fully operational, will help achieving this task but the
compilation issue will not be improved in the coming years at Marine Scotland.
MMO, CEFAS and Marine Scotland suggest as a ‘rule of thumb’ that the time taken to respond each
call is at least one to two times the length of the actual meeting where the data are to be discussed.
For a new data call the time taken to adapt systems may be many times longer than that. For existing
calls, data processing times are extended where requirements change. It can be extremely
problematic if there is a little advance warning of changes and also if they are not highlighted within
the calls. Collation of data from UK administrations can be a complicating factor where transnational
datasets don’t already exist.
The columns required in the DCF data call templates (provided by JRC) are duplicated for each
country and the compilation of the information is made by the end at UK level.
Relation between DCF and Control data
MMO/CEFAS is compiling the transversal data which are accessible to the DCF partners through the
IFISH system.
International coordination (e.g. Regional Coordination Meetings – RCM)
UK institutions are involved in a number of ICES workshops and working groups and actively
collaborate in the elaboration of best practices and methodologies with regard to biological data
collection and stock assessment. Moreover, the UK participates in the international programme for
the improvement of age reading and exchange of otoliths coordinated by ICES. Besides, all surveys
conducted under DCF are subject to international coordination.
15
Cooperation with the Office National for Statistics (ONS)
The Statistics and Analysis Team of the MMO are part of the Government Statistical Service and
operate in compliance with the Code of Practice for Official Statistics. The SAT team provide the UK
lead for provision of fisheries statistics and responsibility for this is devolved to them. The SAT team
produces a number of outputs which are designated as ‘National Statistics’3 . The UK Statistics
Authority (UKSA) is empowered to determine and assess compliance with the Code of Practice. In
order to do this the UKSA carry out regular assessments of official statistics produced by
Government Departments. The most recent assessment for UK fisheries statistics was carried out in
20114. The next assessment is due in 2014.
It was noted that there is scope for constructive involvement of ONS in particular in relation to the
collection of economic data on fish processing and aquaculture.
3.3. IT Infrastructure and flow of information
The standard definition for IT infrastructure refers to the hardware, software, network and services
required for delivering IT solutions and services to its employees, partners and/or customers.
The main hardware in place in the institutions involved in DCF are:
CEFAS maintains servers hosting the transversal data for England, Wales and Northern
Ireland as well as a compilation of all UK transversal data. CEFAS also hosts and maintains
the biological databases as well as the aquaculture databases for England and Wales and the
compilation of aquaculture data for UK.
Marine Scotland servers used for DCF are located in a secured governmental computer
centre in Edinburgh.
AFBI: servers are in a local secured network.
SEAFISH in Edinburgh works mainly with Access, Excel and SPSS and use dedicated directory
on SEAFISH file server maintained internally.
The institutions use a common SharePoint site for exchanging information for preparing the
DCF reports and data calls for UK.
Backups: Regular backup of the servers are ensured by the internal IT teams at CEFAS and AFBI or by
the governmental computer centre in Edinburgh for Scotland. At SEAFISH, server backup are ran
every three hours and synchronised with another server in Grimsby.
Security: High level of security is ensured as governmental secured networks are used: SCOTS or OSE
(another governmental network a bit more permissive in terms of security requirements) to access
the server located in the governmental data centre in Edinburgh for Scotland. For the other
countries, the CEFAS server can be connected also through the government secured network (GSI)
or using secured CITRIX system and only authenticated users can connect.
AFBI main databases are only accessible from AFBI LAN. Data and some reports can be accessible
from outside using a secured 3G encrypted card.
3 http://www.statistics.gov.uk/hub/what-are-national-statistics 4Report No, 126 at http://www.statisticsauthority.gov.uk/assessment/assessment/assessment-reports/
16
At SEAFISH, all economics files are stored on a common drive whose access is controlled by the IS
department. The drive is divided into folders with different levels of permissions in terms of simple
access, access with reading only rights or access with read/write rights depending if the SEAFISH
staff belongs to the economics team or not and inside this economics team if he is an economic
manager or not. In all cases, confidential data access is limited to economics staff only. All laptops
hard disks are encrypted. Staff cannot use memory sticks that are not SEAFISH approved and
encrypted. Hard copies of survey forms and financial accounts are kept under lock and key, only
accessible by SEAFISH economics.
The flow of information between the involved institutions is summarised in the figure below.
Figure 1. Flow of Information
Source: own production
The responsibility for the compilation and storage of the DCF data is distributed as follows:
Transversal data: CEFAS hosts the transversal database managed by MMO for England,
Wales and Ireland in the Sea Fish Management (SFM) database covering different databases
among which the Fishing Activity Database (FAD) contains the logbooks and sales note
information. Marine Scotland has its own database called FIN from where data are
transmitted on a daily basis and made accessible at UK level in the IFISH system managed by
CEFAS.
Biological data: At marine Scotland, biological sampling and discards are managed in the
Fishery management database (FMD). There was no significant development of FMD since
three years and it was decided in the last review of the Marine Scotland fisheries database,
that FMD would not be included within the refresh of the corporate fisheries systems.
Nevertheless Marine Scotland Aberdeen is currently developing a semantic database
system. The first trial was made on zooplankton data, where there was a need but no
17
database. Depending on the results of the project, it could be possible to extend the
approach to the other themes including fisheries data.
CEFAS holds the biological data for England and Wales in different databases: the discard
data are in the OBSERVER database. The CEFAS is phasing out the current biological sample
system (BSS) in favour of the new Gathering and Reporting information system (GARI)
planned to be fully operational in 2015. A copy of the FAD database is made in the CEDER
database to increase the response time when transversal data are needed. All these
biological databases are planned to be connected and interoperable in an iBiS system
currently under tests. Possibly in the long terms, copies of the Scottish and Irish datasets
could also be connected to the iBis if required.
In AFBI, the biological sample for Northern Ireland are stored in a database with a similar
structure as BSS called Fishloggin and in a discard observer database and a discard self-
sampling database for Nephrops and small fish.
Research Survey: The same Fishing survey system (FSS) is used on board of research vessels
at Marine Scotland and at CEFAS while the AFBI stores acoustic and nephrops TV survey on a
secure server (post processing results are stored in Excel files). Trawl survey data are stored
in a Groundfish Database (current being migrated from Oracle to SQL Server), which also
stores a non DCF trawl survey data.
Recreational fisheries: no real database exists, but some Excel files or Access database are
available in the different countries.
Aquaculture: Aquaculture data is compiled by CEFAS for all UK from aquaculture production
data coming from UK Fish Health Inspectorates for England and Wales, MSS and DARDNI for
Northern Ireland completed with information extracted from Annual Business Inquiry (ABI)
results provided by the Office for National Statistics (ONS).
Economics fleet, fish processing DCF data is collected and compiled by SEAFISH for all UK.
3.4. Users request management
Dissemination: website
The UK DCF web site 5 describes the DCF and disseminates to the public all material related to the
national programs, annual reports, and financial reports.
Management of user requests
Data requested in official data call by ICES or DGMARE (JRC, STECF) is prepared by the individual
institutes and compiled and submitted by the NC. The centralised routing through the NC has been
introduced only in 20136. In addition, agencies like MMO, CEFAS or Marine Scotland can receive
general enquiries not mandatorily related to DCF data on a generic email address or directly to
specific staff email, which is forwarded to the most appropriate person able to answer. A log of the
answer is kept but there is no centralised user request management/follow up tool in place.
At AFBI, a system for following the data request using the “BugNet issue tracker” software was
recently implemented centralise the requests, correspondences and data provided. The BugNET is an
5 http://www.marinemanagement.org.uk/fisheries/statistics/dcf.htm 6 Similarly comprehensive overview does not exist for the preceding years.
open source issue tracking and project issue management solution built for use with SQL server 2008
and above.
Transmission of data
The transmission of the data is free of charge.
User satisfaction
No dedicated DCF user satisfaction is done. This is not considered necessary as STECF, JRC and ICES
carry out their own assessments and comments are fed back either directly or through the
Commission. Customer feedback is obtained on national statistics such as the UK Sea Fisheries
Statistics publication and most recently the user consultation on monthly statistics produced by the
MMO.
19
BIOLOGICAL DATA – MÉTIER RELATED VARIABLES 4.
4.1. Programme monitoring
Organisation for the production of métier-related data
In the UK, the responsibility of collecting biological data (métier related variables) is geographically
subdivided and lies with the administrations of the countries England, Wales, Northern Ireland and
Scotland. In practice, the three main scientific institutions to which the collection of biological data
has been delegated are:
CEFAS: responsible for the planning and data collection in England and currently working
with the Welsh Government to identify data collection needs in Wales and the split of
sampling activity between CEFAS and the Welsh Government;
AFBI: responsible for the planning and data collection in Northern Ireland;
Marine Scotland Science (MSS): responsible for the planning and for most of the data
collection in Scotland. Due to logistic reasons, besides, MSS has subcontracted NAFC Marine
Centre for data collection in the Shetland Islands.
In England and Wales, CEFAS has a network of 10-15 qualified observers/samplers responsible in the
various districts for both on-shore and off-shore sampling. The observers are able to enter the
sampling data directly themselves either into the observer database (for on-board, discard sampling)
or the GARI database (for on-shore sampling) and update the files on sampling achievements in the
shared drive.
In Northern Ireland only few métiers have to be sampled according to the 90% ranking system
(mainly OTB-CRU). The sampling design is similar to the one in England, having a close coordination
with CEFAS in this respect. Data collected by observers and samplers are entered into the respective
database (either FishLoggin or Discard databases, both observer and self-sampling) centrally at AFBI.
In Scotland, observers are divided in three teams (demersal, pelagic and shellfish) and have direct
communication with their team leader. For each trip that an observer has to sample, the observer is
given a randomised list of vessels. Paper sheets are different for on-board and market sampling but
in essence do the same, randomisation. Data (métier related) is entered into the respective database
(FMD) by dedicated staff at Marine Scotland.
The identification of métiers is based on log-book data, sales notes and vessel register data from the
reference years (2007-2008). The identification of métier is done through an algorithm developed by
Marine Scotland that identifies the targeted species in a fishing trip (required for métier level 6)
based on the landings in weight or value7. This identification is done to a finer scale than the level
required by DCF. Therefore, different groups of species are merged when reporting DCF related data
to the Commission.
7 In the cases where molluscs or crustaceans are the single most valuable part of the landing, the target assemblage is defined according to either one or the other group of species. Otherwise, the highest amount of landings (in weight) is considered.
20
For example, mid-water otter trawl for mackerel and for herring are identified as separate groups
while for DCF purposes they have to be merged into mid-water otter trawl for small pelagic fish:
OTM_MCK (UK) U OTM_HRR (UK) = OTM_SPF (DCF)
Once all métiers are identified, the 90% ranking system is performed at UK level according to the
2010/93/EC Regulation using an R script (developed in Marine Scotland) to report table III.C.1. Vertical
merging of métiers is performed in those cases where similar species and size compositions are
expected for different métiers, as explained in the National Programme; the final list of métiers to be
sampled are thus reported in Table III.C.2. However, the MS does not use this ranking to develop the
sampling scheme.
With regard to the sampling strategy, the main constraint the countries of the UK have to face is the
restricted sampling effort, i.e. the number of person-days available for sampling purposes. This is the
main limiting factor for the various institutions and, thus, the fixed variable when setting up the
sampling strategy. In this regard, it has to be highlighted that the UK bases its sampling scheme on
the recommendations elaborated through the various workshops and planning groups of ICES
The data collection scheme in the UK does not focus on métiers in the first place, but targets more
aggregated gear groups and areas in its sampling strategy. This is mainly due to the polyvalent
nature of some fleet segments, the high variability of métiers from one year to the other and the
difficulty to anticipate the relative importance of one métier ahead of a fishing season.
Each country in the UK has developed a different sampling method but along the same lines. All of
them try to overcome logistic problems derived from the extensive shoreline that the UK has.
On-board sampling: The primary sampling unit is the fishing vessel. The list of vessels in the sampling
frame is stratified by region and predominant fishing method/vessel category (see Figure 2). In
Figure 2 the number of trips to be sampled in each of these strata is calculated based on the volume
of discards, number of vessels, landings and effort (number of trips) of these strata.
England, for example, allocates its sampling effort to 6 broader vessel categories (which aggregate
various of the identified métiers): Under 10m: all gears; Any size: Beam CRU; Over 10m: Nets, Trawls,
Beam DEF and Scallop (see Figure 2). According to the nominal trips, the landings (tonnes), the
discards (tonnes) and the number of vessels (each criteria weighing 25%) per gear group and nominal
region, the number of sampling days is allocated (see also Annex 2). The respective sampling effort is
updated on an annual basis based on the data of the previous year.
8 WKPRECISE: Workshop on methods to evaluate and estimate the precision of fisheries data used for assessment 9 WKMERGE: Workshop on methods for merging métiers for fishery based sampling 10 WKPICS: Report of the Workshop on Practical Implementation of Statistical Sound Catch Sampling Programs 11 PGCCDBS: Planning Group on Commercial Catches, Discards and Biological Sampling
21
Figure 2. Off-shore sampling frame stratification in England
Source: CEFAS
For each of these strata there is an actual list of vessels12 that will be used to choose which vessel has
to be sampled. At the start of each quarter, the list for each regional stratum (vessels fishing in a
certain region) is randomised. Sampling staff operating in a region work down the randomised vessel
list and contact skippers in order to arrange a trip to go on-board. The selection of process,
successes and failures, are recorded in order to provide statistics on refusal rates. For instance, the
skipper might refuse to go due to safety concerns. All class of refusal is recorded and this can be
used to provide statistics on the potential for bias.
Also in Scotland, where on-board sampling is done either on boats targeting demersal fish or
crustaceans13, a randomised list of vessels to be sampled is produced.
On-shore sampling: In England the primary sampling unit is day at port. The sampling is divided into
different frames based on the target species and gear used (gear groups). Then each of these frames
is stratified by region and port importance for specific landings (see Figure 3).
12 Vessels with a LOA below 7 m are excluded due to health and safety reasons for observers. 13 The small pelagic fleet is excluded from on-board sampling in Scotland.
22
Figure 3. English regional stratification
Source: CEFAS
Port sampling trips are allocated systematically to ports bi-weekly. Due to logistical reasons and staff
constraints these are combined to form monthly targets in some cases.
In Wales, no port sampling programme has been taking place for some years. At present, a
memorandum of understanding (MoU) is being agreed between England and Wales so that CEFAS
also processes the Welsh data.
In Northern Ireland, only 2 to 3 ports are being sampled, applying the same sampling scheme as in
England.
In Scotland, the on-shore sampling programme contemplates 3 vessel categories targeting either
pelagic fish, demersal fish or crustaceans; the available sampling effort is thus divided between these
3 strata. A similar approach as in England is used in the Scottish sampling strategy, covering
systematically the selected (48) ports with random visits (Mondays and Thursdays) within each
quarter. However, in Scotland, the weighing of each port is done afterwards according to the
relative landings.
Achievement of objectives with respect to sampling plans
During the field mission, the team had the opportunity to check the databases in England (CEFAS)
and Scotland (MSS).
The team asked England and Scotland institutions to show or reproduce the number of off-shore
trips sampled for certain métiers as indicated in table III.C.3. In general terms, numbers did not
completely match with those reported in the xls-files but differences were rather slight in most of
the cases. Nevertheless, the reasons for diverging numbers could not be fully clarified in the course
23
of the field visit. In the case of Scotland, for example, some difficulties were encountered in tracing
back the data and running queries to reproduce the numbers reported within DCF. Discrepancies
between reported numbers and those produced ad-hoc were attributed to problems associated with
the allocation of a métier to a trip, which in the FMD database is recorded according to the
indications of the observer (based on own observations, indications of skippers or fishery officers,
etc.). Although these indications are cross-checked with the information provided through the FIN
database, the métier allocated manually might be different from the métier calculated through the
algorithm. As indicated, another possible reason for differing numbers could be related to
inconsistencies in the definition of one trip.
With regard to the measured fish per species, the team could not track back the exact numbers
reported in table III.C.5 due to the fact that the table contains the total number of fish measured at a
national level (aggregating the fish measured by the different countries). However, the team asked
for those stocks that, due to accessibility, should be fished mostly by only one country (such as
herring in areas I & II for Scotland); the numbers produced matched up quite well to those reported.
In general terms, the number of trips sampled in practice exceeds the expected number of trips to
be sampled. At the métier level, fluctuations between the expected and the achieved number of
trips (table III.C.3) were observed. To some extent, this can be a consequence of the fact that the UK
does not target métiers in the sampling scheme and is based on a stratified random selection of
samples.
The DCF Regulation foresees a sampling scheme where sample sizes should be proportional to the
relative effort (number of trips) of a métier for a reference period. However, as said before, the UK
takes into account also other factors in its sampling strategy; besides effort, the size of the fleet, the
discard rate and the landings influence where sampling effort is directed. Fluctuations in the number
of trips sampled are also explained by the seasonality of certain fisheries and best sampling practice
(number of samples per stratum).
Table 1 presents for several métiers a comparison between planned and achieved number of
sampled trips along with the expected (reference years) and the actual number of fishing trips. The
UK technical report 2012 (table C_III_4) shows that, overall, UK sampled 3,696 trips which is more
than the 3,182 which were planned for. Still sampling of two segments did not meet the objective,
although the number of trips of those segments has increased. It may be pointed out that random
selection of the sample based on the UK strata does not guarantee the representativeness of the
sample for the DCF métiers.
Recommendation: Post-enumeration studies of the representativeness of sample data for the
DCF métiers could be carried out by analysing the homogeneity of the distribution of
measures in the sampled trips within a métier: if the distribution of biological stock-related
variables is quite homogeneous in the different fishing trips, it can be assumed that the
sample may provide representative results; if they are significantly different, this means that
the sample was not large enough to ensure representativeness. Statistical tests for checking
the homogeneity of distributions include Chi-square and other non-parametric tests.
24
Table 1. Extract from table III.C.3
Fishing Ground
Sampling strategy
Métier LVL 6
Average total nº of
trips in the
reference years
Total nº of trips during
the sampling
year
Total nº of trips during
the sampling
year
Achieved nº of trips
UKS VI Concurrent at sea
OTB_CRU_70-99_0_0
21544 16346 21 47
UKS IV-VIId Market stock specific
OTB_DEF_>=120 2704 1621 209 317
UKE IV-VIId Concurrent at sea
GNS_DEF_0_0_0 13499 20247 27 23
UKE IV-VIId Concurrent at sea
OTB_DEF_100-119 1587 1754 24 15
UKE VIIe Concurrent at the market
OTB_DEF_70-99 9803 5252 24 98
UKN VIIa Concurrent at sea
OTB_CRU_70-99 8344 7313 72 167
Source: Extract from DCF table III.C.3
In view of these examples, it should be reconsidered if these fluctuations are only due to the above
mentioned factors and constraints, or may be an indication of other problems or bias in the selection
of vessels/trips/ports to be sampled.
4.2. Data upload, storage, processing and access
All countries have their own system to collect and compile the biological data.
England and Wales – OBSERVER, BSS and GARI at CEFAS
CEFAS holds the biological data in different SQL server databases:
OBSERVER database: it is used to store the discard data from on sea sampling. The database
architecture allows entering nested information like to define a project, enter trip details
against a project, enter the hauls details against a trip, then to enter catch components
information against a gear deployment in a haul, then to enter sample details against a gear
deployment per sex and species.
BSS and GARI: The full set of biological sampling is currently available in the Biologic Sample
System (BSS). Since 2012, the data are loaded in the new GAthering and Reporting
information (GARI) system which is expected to replace definitely the BSS by the end of
2014. The data entered in GARI are shadowed over onto the BSS. At the opposite data from
BSS were in the process of being imported into GARI but only until 1999 as the other data
are very incomplete and do not fit well with the GARI Database structure. When GARI will
replace the BSS, a copy of the old BSS datasets not uploaded will be saved in GARI to keep a
memory of the historical series.
25
The GARI database is connected to market electronic data capture (market EDC), a
technology tested to automatically measure the fish and to feed automatically the database
directly from the market site.
CEDER: A copy of the Fishing Activity database (FAD) is made in the CEDER database, in
order to increase the performance of the requests on this database and to save resources
for the users of the FAD database.
All these biological databases are planned to be connected and interoperable in an iBiS
system currently under tests. The system should use data warehouse technology and OLAP
cubes to perform data raising and integration. Possibly in the long terms, copies of the
Scottish and Irish datasets could also be connected to the iBis if required.
Figure 4. Overview of CEFAS databases related to biological data
Source: CEFAS
The access to the data is secured through a CITRIX connection allowing sharing the application
installed on the server through a light client, facilitating the deployment of the application and
increasing the security. The data are only accessible from authorised PC with ad hoc logging and
password.
The data are entered in the database when coming back from the field mission for the observer
database. For the biological sample, they can be entered manually or using the electronic data
capture system for the biological sampling at the market. This system is supposed in the long term to
save time and resources and to reduce the data entry error. In addition to that, CEFAS has elaborated
very detailed procedure and compilations checks manual to be applied by inspector when collecting
the data and many checks were also in place in the database to identify typing errors. Post validation
checks are implemented as described in chapter 4.3.
The reporting system: The users could retrieve information from the database content using SQL
server query interface or ad-hoc R program, meaning it is sometimes not so easy to extract relevant
26
information. In addition, the observer database uses different nomenclatures (ex: for gears) which
requires to run some mapping to convert the data in the required DCF format. In the new GARI
system, a powerful reporting interface was designed allowing running queries in a very user-friendly
and efficient manner.
The users have access to an online manual. For the observer database, there is a data entry user
guide as well as technical description of the database.
FMD is an SQL Server database. There was no significant development of FMD since three years.FMD
database contains discard information, onshore sample and biological information as well as
transversal data.
The access to the data is secured through a connection to the SCOTS network only accessible from
authorised PC with ad hoc logging and password. The data are entered in the database when coming
back from the field mission. As for CEFAS, inspectors have to follow guideline lines for the data
collections. Post validation checks are implemented as described in chapter 4.3.
The reporting system: In the past, the users could retrieve information from the database content
using SQL server query interface. The database querying is now performed through a business object
(BO) interface only. This facilitates the task of the users but at the same time gives them access only
to the object defined in BO. Any requests to access information from a new field not yet accessible
through the BO interface, requires the computer centre to update the BO interface and initialise the
related configuration allowing extracting the new information from the database. This of course
requires for Marine Scotland to know exactly what can be extracted from the FMD database. Also
only a limited number of licences of BO are installed, meaning not all staff can perform the
extractions.
The technical documentation is not up to date.
Note: Marine Scotland is developing a project of semantic database: the first trial was made on
zooplankton data and a second deployment is foreseen for summary of data from acoustic survey.
The current development consists in building the underlying database structure including all the
integration aspects and metadata linkages; the user interface coming on top is foreseen a bit later.
The team will start developing the first custom interface for some of the plankton functionality. So
for the moment, the upload of data is made via csv files. But at the end, it will be possible to
manually enter data directly into this system using web forms. Therefore in time, it is considered as
possible to replace FMD data entry system with this functionality.
Northern Ireland – FISHLOGGIN at AFBI
In AFBI, data are stored in a database with a similar structure as BSS (old CEFAS database) called
FISHLOGGIN. Discard observer database is also in place as well as a discard self-sampling database
primarily for nephrops and small fish where the samples is collected by voluntaries fisherman paid
for ensuring that data collection and processed centrally at AFBI.
During the mission, the database could not be seen as only accessible from the LAN.
27
4.3. Statistical quality
The same institutes that are implementing the data collection in the various countries are
responsible for assuring the statistical quality of the scheme. National meetings are held every year
to discuss any topic under the DCF.
Data quality is assured through established protocols that observers have to follow in order to try to
maximise the random selection of the trip to be sampled. These comprise the (quarterly) generation
of randomised vessel lists (on-board sampling) and the random selection of vessels according to
individual forms (on-shore sampling). As said before, random sampling of the UK strata, does not
guarantee randomness in relation to DCF métiers.
During the whole data collection process, the following quality checks are carried out:
Non-response rates of skippers are recorded
At CEFAS, once the data is entered, data integrity is checked by another observer;
Information on gear type and mesh-size is cross-checked with the “control” information
available on FAD (England) or FIN (Scotland): CEFAS does this once the data is introduced,
Marine Scotland does a visual check of the observers form before entering the data into the
database;
Sampling achievements are monitored on an ongoing basis through spreadsheets available
on a shared file;
Moreover, quarterly reports of the sampling activity against fishing activity will provide an
indication of how well the sampling design is working.
The achievement of precision levels varies a lot depending on the species. Cost tools are in use for
this purpose.
4.4. Conclusions
The UK has a different sampling strategy than the one proposed in Commission Decision 2010/93/EC.
This is explained by the stronger focus on a stock-based approach on one side and the limited
sampling effort available on the other. In essence, the sampling targets an aggregation of métiers by
area and gear (see Figure 2). This strategy has potential to overcome some problems observed in
other countries, such as the fact that the effort of métiers can vary between the reference years and
the actual year. Nevertheless, other possible sources of bias should be considered such as
preferential sampling of ports/vessels/trips as well as the homogeneity of the defined strata in terms
of métiers.
Recommendations:
It is recommended to test the present assumption that métiers are sampled and random and
with sufficient intensity. Considering homogeneity of the defined strata in terms of métiers
may be a relevant starting point.
28
BIOLOGICAL STOCK DATA 5.
5.1. Programme monitoring
Organisation for the production of stock-related data
As for the métier related data, CEFAS, AFBI and Marine Scotland are responsible for the sampling of
stock related biological variables in England (and Wales), Northern Ireland and Scotland respectively.
Depending on the species and the variables measured, data derives either from market sampling of
commercial fisheries or from research surveys, being the latter the most important and
representative source. Also stock specific sampling is performed at the market in order to meet the
targets inherent to one stock and its assessment. Commercial and survey data are combined for
reporting purposes14, but are otherwise treated separately.
While length is measured in any case (commercial fisheries or survey), the determination of sex ratio
and maturity is done on commercial fisheries (at the market) only for certain species sampled. In the
case of pelagic fish, maturity can be identified at the market since these species are typically landed
as a whole. On the contrary, demersal fish are landed already gutted, thus maturity data has to be
gathered mainly during research surveys. Also for flat fish (plaice, sole, megrim) maturity is
determined at the market. Other than for plaice, sex ratio is also defined for whole skates, rays and
all shellfish species during the sampling of commercial fisheries, thus lengths are recorded by sex.
The maturity stage of most stocks is usually recorded during the 1st quarter of the year (for approx.
80% of the stocks). One exception constitutes the Norway lobster (Nephrops norvegicus) which is
measured between September and October.
Where possible, otoliths15 are collected during on-board sampling (from discards), at the market16
and on surveys (always together with the length). While all three laboratories, CEFAS, AFBI and MMS
dispose of in-house expertise for age-reading of otoliths (at least for certain species), only CEFAS and
AFBI have a quality management accreditation in place. In the case of Marine Scotland age reading
of certain species is commissioned to different external (national and international) institutes. For
example, hake otoliths have usually been sent to CEFAS, otoliths of witch flounder are sent to
Sweden for reading and Blue ling otoliths were usually sent to Norway before, although this is not
done anymore. In any case, the UK participates in workshops (organised by ICES) on age reading and
is an active partner in the international coordination and exchange of otoliths for the improvement
of age reading expertise.
The target number of fish to be sampled and the variables to measure are defined in the sampling
protocols handed to the observers/samplers.
14 The coefficient of variation reported is the median between the CV for commercial fisheries and surveys. 15 Alternatively, also scales are collected when sampling discards (for age determination). 16 In the case of sea bass scales are collected when sampling on-shore.
29
Achievement of objectives with respect to sampling plans
Each country in the UK holds its own database for biological variables, so there is no central
database that integrates all data together (data are only combined at UK level for reporting
purposes with regard to DCF or other obligations). For this reason, it was not possible to verify the
aggregated numbers provided for stock-related variables (table III.E.3) during the visits at CEFAS and
Marine Scotland; however, the institutes were asked to produce single stock-related numbers for
records stored at country level.
According to table III.E.3, the achieved number of individuals/species measured at national level
reaches in general terms the planned minimum number. In fact, in many cases the measured fish
exceeds the target number to a high degree displaying oversampling. This is due to the fact that on
research surveys, when catches of one species are large, the sampling rate can be increased without
having additional personnel costs. In a series of cases also under sampling is recorded, which is
explained by reduced catches during surveys or logistical constraints while sampling a large number
of species.
5.2. Data upload, storage, processing and access
For CEFAS, the biological information are stored in the OBSERVER and GARI /BSS databases whereas
for Marine Scotland the FMD database contains the detailed biological information and for AFBI it
will be the FishLogging and discard databases as described in the chapter 4.
For the stock assessment, at CEFAS, a COST-like method is foreseen to be implemented in the IBIS
system making it possible to link transversal data and biological samples.
At Marine Scotland, the raising of the data is made using R script applying the COST methodology
combining information sourced from the FMD obtained using an extraction from the BO interface
and an extraction from the Oracle database FIN obtained using oracle discover tool.
5.3. Statistical quality
Observers and scientific staff on research surveys are responsible for collecting the data. Data quality
is assured through sampling protocols and manuals for stock related variables. The quality of each of
the variables collected is assured using guides and is based on expert meetings’ agreed
methodologies and recommendations:
Otoliths: there are international agreements on how to read some otoliths and regular
international meetings are held for some species. Besides, there is an otolith exchange
scheme for which otoliths are circulated (by correspondence or also through digitised
images) between cooperating institutes at international level.
Maturity: species-specific maturity keys are used.
Sex: fish anatomy guides are used.
Precision values are calculated. The achievement of precision levels depends very much on the
variable and the species. Also the high number of stocks and the limited time available on research
surveys constitutes a constraint for achieving a good precision level for certain species at national
level.
30
5.4. Conclusions and recommendations
For most species the targeted number of individuals to be sampled is achieved and often largely
exceeded. Under sampling, which is observed for certain species, is explained by low catches and
constraints related to the available sampling time and the problems related to the sampling of a high
number of species during research surveys. The collection of biological variables is done according to
international standards and following the recommendations of ICES experts working groups.
31
RECREATIONAL FISHERIES 6.
6.1. Programme monitoring
According to Commission Decision 2010/93/EC, all four countries in the UK have to collect data on
salmon, seabass, eel and sharks. England and Scotland also have to collect data for cod in the east
coast.
England: CEFAS is in charge of an extensive survey that targets recreational sea anglers. This study
covers seabass, sharks and cod (DCF requirements) among other species. Recreational fishery for
salmon is covered by the Environmental Agency, every fisherman needs a licence to fish in inland
waters and catches are estimated through individual reports. As for eel, the English legislation
requires all freshwater eels caught recreationally to be returned alive to the water.
Scotland: In 2012 MSS started a survey (pilot study) to estimate cod catches, but unfortunately the
results were not good due to a very low response rate. Data for the salmon fishery is collected by the
Scottish government and used for stock assessment. Fishing eels and sharks is illegal in Scotland.
Scotland has committed itself to set up a strategy for monitoring recreational fisheries until 2014. It is
being assessed if a similar approach as in England is going to be applied and even if Scotland will be
integrated in the same survey on recreational sea anglers as conducted in England.
Northern Ireland: An online survey targeting sea anglers was launched in 2012 but the response rate
so far has been poor. The Agri-Food and Bio-sciences Institute in Northern Ireland is responsible for
the salmon fishery data collection and stock assessment is done by AFBI. There is no significant
recreational fishing for eel in Northern Ireland, but there is a commercial fishery on Lough Neagh
that is being monitored and assessed (governed by an EU eel management plan).
Achievement of objectives
Salmon and eel are well covered both for recreational and commercial catches. Data for sea angling
(cod and seabass in DCF requirements) is yet incomplete, since Scotland, Northern Ireland and Wales
did not manage to collect data of good quality.
6.2. Data upload, storage, processing and access
Data available are stored in Excel files in Marine Scotland, AFBI and Excel and Access database at
CEFAS.
6.3. Statistical quality
The sea angling survey in England is based on the design of similar surveys in the USA and Australia.
Moreover, the population survey to estimate sea angling effort is carried out using the monthly
multi-purpose government social survey carried out by the ONS using a stratified random sampling
scheme.
As for salmon data, the effort is a census of all the issued licenses. Catch data derive from individual
reports of catch.
32
6.4. Conclusions and recommendations
Data on recreational fisheries is not fully covered by all the countries in the UK. Scotland, Northern
Ireland and Wales do not have a programme that assures data quality for sea angling (cod and
seabass). However, there are plans to extend the English survey to the whole UK in the following
years. Unfortunately, ensuring a good statistical quality of the sea angling survey can be expensive in
terms of cost-effectiveness.
33
TRANSVERSAL DATA 7.
7.1. Programme monitoring
MMO is responsible for the management of information and the attribution of fishing licences and
authorizations, the management of quotas and collection of transversal data (logbooks, sales
notes). Fishing fleet register is maintained by the Registry of Shipping and Seamen, which resorts
under the Ministry of Transport.
The MMO system is hosted and maintained at CEFAS and cover England, Wales and Northern Ireland.
AFBI has the possibility to dump the content of the FAD database. Marine Scotland transmits
transversal data on a daily basis to CEFAS to have a full set of transversal data for UK accessible to
the partners feeding the common database through the IFISH system.
The two systems manage the electronic logbooks and sales note as well as the paper documents.
The transversal data is provided to SEAFISH when needed.
As in all MS, the fleet capacity is monitored through the fleet register. The register contained on
1.1.2012 6,432 vessels, but only 4,652 were active.
Effort and catches are monitored through logbooks and sales notes. In the UK all vessels below 10m,
which are members of a Producer Organisation (PO), are also subject to the logbook obligation.
Activity of small vessels, which are not in a PO, is followed on the basis of the sales notes.
Paper logbooks and sales notes are entered in the system by the port officers. For small vessels,
without logbooks, the port officers make an estimation of the effort on the basis of their experience,
of if in doubt, they contact the vessel owner.
The system in England, Wales and N. Ireland cross checks automatically the consistency between
landings declared on the logbook and the sale according to the sales notes. Such an automatic check
is not practiced in Scotland, although the software would allow this there as well.
The time lag for entry of electronic data is minimal – e-logbooks appear in real time, e-sale notes with
a delay of 15 minutes and Vessels Monitoring System (VMS) data with 5 minutes delay. The average
delay for uploading paper logbooks is about 5 days.
Lack of sufficient detail and coherence with fishing practices in the EC XSD scheme for electronic
reporting presents considerable difficulties. For example this lacks identifiers to allow correct
linkage of sales notes to a trips where the vessel lands only part of its catch at a time. While each
message is linked to fishing area and species, it is not linked to a trip. Consequently, when a vessel
discharges only part of its catch from trip 1 in a certain port, starts trip 2 and discharges the rest of
the catch later, the sales notes cannot be linked well to a fishing trip. In such cases manual correction
has to be introduced.
34
7.2. Data upload storage, processing and access
Logbook, sales note and VMS data are collected by UK Fisheries Administrations and stored in an
Oracle server database called FIN in Marine Scotland and in an SQL server database called Sea Fish
management (SFM) for the other three countries. The SFM database is split into the Licence system,
the vessel file system, the Fishing Activity Database (FAD) which holds information on catch and
effort for all recorded commercial landings (logbooks, elogbooks, sales notes, esales notes) and the
Monitoring Control Surveillance System (MCSS) registering among other the VMS data.
The following diagram illustrates the Sea fish management system implemented at CEFAS.
Figure 5. Overview of the Sea Fish Management system (CEFAS)
Source: CEFAS
For electronic data, a set of checks is performed before the data are integrated in the FAD database.
For the paper declaration, the inspectors have access to the FAD/FIN database using a secured
connection. Many checks are applied at the data capture stage (see 7.3).
There is no reporting interface, but advanced users were trained on using SQL Server query interface
to be able to retrieve information from the database.
35
By the end, the primary data related to individual trips by UK registered vessels and foreign vessels
landing in the UK meaning the catches and vessel data (logbooks, landings declaration and sales
notes (paper and electronic versions) are extracted on a daily basis from the FIN and FAD databases
and stored in the IFISH integrated UK database.
Documentation: The FAD data entry interface integrates an online help available to users.
Some technical description and database diagrams are also available.
7.3. Statistical quality
UK puts lots of effort on the quality of the data entered into in the system by implementing directly
many validation rules in the system. A confidential list of more than 400 rules was shown during the
mission. Each rule was characterised by:
The severity level: failure, warning, none.
An “Element” it refers to: it can be generic or specific (discard declaration, e-logbook,
transhipment…).
The coverage of the rule: applicable on a specific field or on the element as a whole.
The scope: field level mainly, but can also be applicable to individual elements, e.g. a fishing
activity record and across documents.
The validation type: cross check, range, mandatory, non-mandatory, mapping, pattern,
string length…
The current system allows filtering poor quality of information sometimes provided by the
elogbooks and to put them in a waiting stage until it is revised by an inspector.
In the FIN and FAD databases, sales notes, landing declarations and logbooks information are linked
and relevant checks can be performed automatically.
According to the information obtained during the interviews at CEFAS, data quality reports are
issued for ERS and paper declarations with different level of errors identified (“must”, “should”,
“missing”…) and if inconsistencies are detected, the inspector has to correct or justify the reason of
the inconsistency if relevant.
Thus UK is confident about the quality of the transversal data due to the many automated checks
implemented.
36
Table 2. Quality checks of PRIMARY (detailed) transversal data
Catch / landings Capacity Effort
No Manual check
Software check
Manual check
Software check
No Software check
Availability
Accessibility
Missing values
Duplicated records
Timeliness
Coding
Other
Typing errors
Arithmetic checks
Logical checks
Range/ outliers
cross section
time series
Other sources
Other
Source: DC MAP survey
7.4. Conclusions and recommendations
UK managed to build an efficient system for the management of transversal data combining the
systems from the UK countries. UK focuses a lot on the automated checks allowing checking the
quality of the data at the data entry stage and has reduced the time devoted to post validation
checks.
37
RESEARCH SURVEYS AT SEA 8.
8.1. Programme monitoring
Under the DCF framework, the UK is involved in 8 research surveys; for some surveys each country in
the UK covers different areas and quarters. In table III.G.1 we can see an overview of those surveys.
All surveys have been covered and it is believed that they are carried out according to established
international protocols. The achievement rate of survey days and targeted sample sizes is high. Most
deviations between the planned and achieved are below 5%. The UK keeps track of the surveys that
provide suitable data for the calculation of the ecosystem indicators 1-4.17
8.2. Data upload, storage, processing and access
Fishing survey system (FSS): Marine Scotland bought the FSS system for the 2013 survey campaign to
CEFAS, so now the two institutions run the same software. CEFAS ensures a charged maintenance
and no change can be applied on the package by Marine Scotland to adapt the package to the
Scottish needs else the guaranty and maintenance is not covered anymore.
A server is on the vessel boat hosting directly the survey SQL database that holds all fisheries survey
data. A backup is run every day.
Each survey is co-ordinated by an ICES Expert Group and follows the agreed survey protocol defined
at the co-ordinating Expert Group and the survey manual.
Research vessels (RV) are equipped with the electronic data capture system (RV-EDC):
The measuring software collects length and biological information from the trawl catch.
The biological data can be collected on a stratified sampling basis; the software will manage
the targeting and prompt the operator for samples as required.
Weight data is loaded directly from the balance, reducing data input errors.
Once the data for a station has been input and complied, this is then uploaded into the FSS.
Further checks implemented on the data are described in the next chapter.
The FSS data are accessible by R and SAS via read-only access. All DCF funded survey data are also
uploaded to DATRAS and can be seen from the DATRAS products outputs.
At AFBI, acoustic and nephrops survey data are achieved on a secure network server. Post
processing files are also archived and the final survey indices calculations are stored in Excel files.
Trawl survey data are stored in a Groundfish database (current being migrated from Oracle to SQL
Server), which also stores non DCF trawl survey data.
17 It has also been reported that other variables on the ecosystem are collected during some of the cruises, e.g. in view of the reporting obligations related to the Marine Strategy Framework Directive (MSFD), in a multi-purpose use of research vessels.
38
8.3. Statistical quality
The methodologies of these research surveys have been developed by expert working groups that
assure the statistical quality of the samples and the suitability of the data for stock assessment
purposes.
8.5. Conclusions and recommendations
The UK has carried out all the expected research surveys according to their respective protocols.
There have been some minor deviations of the achieved number of samples with respect to the
planned numbers due to technical or weather condition problems in the field. The results of such
surveys are always incorporated into the respective databases.
39
ECONOMIC DATA – CATCHING SECTOR 9.
9.1. Programme monitoring
Organisation for the production
Economics unit of the Seafish Industry Authority is the core group in the UK dealing with economic
analysis of fishing and fish processing. Its activities are presented in figure 7. The unit has 5 staff
members if whom 2-3 are involved on part-time basis in DCF data collection on the catching sector.
Seafish has been collecting economic data on the catching sector since the 1980s and it was one of
the founding institutes of the present Annual Economic Report, when it was set up in the early
1990s.
The staff responsible for data collection receives a week training and detailed guidelines, incl. draft
letters to approach fishing firms and / or their accountants and the description how data should be
entered. The file contains links to protected Data Entry Sheets (Annex 3).
The data collection is based on a panel of some 450 vessels. The Seafish staff maintains contacts with
the vessel owners in order to obtain access to their accounting. The owners sign usually an
agreement for 3 years, although they can also opt for one year only. Seafish attempts to extend all
the contracts annually, so that the data collection for the following 2-3 years is assured. Evidently,
some owners drop out of the panel while others are added. Additional effort is undertaken when the
number of vessels in a specific segment decreases too much.
The contract between Seafish and the vessels owners allows access to the detailed accounting,
which is usually collected from the accountants, either on paper or electronically.
40
Figure 6. Activities of the Economic Unit of Seafish
Source: Seafish
The fleet is stratified according to DCF and Seafish segmentation (18 resp. 30 segments). Seafish
segmentation, which is more detailed in some respects, is used for the reporting in the UK. However,
the processing of the data, as described in section 9.2, is such that almost any segmentation can be
derived.
Achievement of objectives
The data is available as stated in the Technical report.
The method for estimation of segment totals is in practice significantly more detailed than described
in the NP and TR. It is recommended to align the text of these documents to the present reality.
9.2. Data upload, storage, processing and access
The questionnaires (Annex 4) are sent to the accountants of the participating fishing firms who fill
them in and send them back either by post mail or electronically by email (scanned). The data cannot
be filled-in online. Three types of data may be provided by the accountants:
Survey questionnaire
Balance sheet
Profit and loss statement
1. DATA COLLECTION
3. DELIVERING EXPERT ADVICE
Chief EconomistSenior EconomistData Collection ManagerEconomic Researchers x 2
SEAFISH ECONOMICS
2. ANALYSIS AND EVIDENCE BASES
Fleetfinancialsurvey
Processorsfinancialsurvey
Fuel pricetracking
ad-hoc and one off surveys
FisheriesManagement
Business Performance
Benchmarking
UKFENSTECF
Best practiceguidance
Fishing into thefuture
EAFEBusiness of fishing
Multiplerstudies
Landingsobligation EIA
Fleet ProfitForecasts
Deep Sea EIA
Fleet and processing economicperformance reports and datasets (Seafish
and DCF)
41
The companies having accounting year from July till June or later are counted and processed for the
year in which they report their results. Firms with accounting year ending in June are included in the
results of the year when their accounting period starts.
The received data is entered in Excel files. The survey data is entered directly in the Excel file (Figure
7), while Excel upload sheets are used for the financial data (balance sheet and profit/loss
statement).
Figure 7. Storage of data in Excel
In addition to the above data, Seafish receives annually transversal data (revenues and effort) for all
active fishing vessels. All data are stored on the Seafish server in dedicated directories.
The quality of the data is checked manually as well as with an automated STATA process. (See
section 9.3).
The aggregation to the segment totals is done as follows:
1. All vessels of the fleet are allocated to the 30 Seafish segments on the basis of the
transversal data, logbooks, on the basis of gear, length, area, engine power and earnings.
The segmentation is done by MMO, not by Seafish.
2. Seafish uses a self-selecting stratified sampling approach to obtain an adequate sample size
of vessel financial accounts for each fleet segment.
42
3. Each segment is subdivided into three size categories on the basis of vessel capacity units18
(VCUs).
4. Average annual costs are calculated for each sub-segment, on the basis of the collected
data.
5. Costs of each individual vessel in the fleet are estimated using the proportion of its total
revenue to the average revenue of the sub-segment to which it belongs. The revenues are
either based on logbooks or on sales notes, depending on size of the vessel. The sales notes
have to be used for vessels <10m, which are not member of the Producer Organisation. All
PO members have to use logbooks. For example:
Other variable costs (vessel X) = [Revenues (vessel X) / Average revenues (segment)] * OVC (segment)
6. Fuel costs and crew costs are calculated differently from the other costs:
a. For crew share, Seafish assumes a minimum £100 per day in instances where the
actual observed amount within the sample is lower.
b. For fuel costs, the capacity units (VCUs) and fishing effort (days at sea) of each
vessel are used to estimate fuel consumption in litres, which is then combined with
the average annual red diesel price (excluding duty) to calculate the fuel cost
estimates for each vessel.
7. The costs and revenues of the vessels belonging to a specific segment can be simply added
up to generate the segment total.
The calculation is done using STATA software. The procedure is described in a separate document.
The followed approach offers two major advantages:
1. The detailed calculation per vessel allows almost any type of segmentation.
2. Calculation per vessel allows aggregation by region (and segment).
On the other hand, it must be pointed out that the used method considers all costs as variable costs
(i.e. related to revenues) and consequently it disregards the definition of fixed costs. Fixed costs like
insurance and depreciation should be related to non-variable characteristics of the vessels, e.g. gross
tonnage or the VCUs. In 2011 sum of non-variable and depreciation costs represented 20% of the total
costs of UK fleet. The change in methodology of calculating fixed probably will not have significant
effects on the fleet performance. It is recommended to adapt the software so as to reflect correctly
the nature of the fixed costs.
Contrary to DCF, for the UK analysis Seafish distinguishes normal and low activity vessels. ‘Low
activity vessels’ have a turn-over below 10,000 GBP per year. In this way the figures reflect better the
economic performance of the fleet which operates regularly / full time.
The results of the survey are published in annual reports of Seafish and in a newsletter. Participating
fishing firms receive a benchmarking report (Annex 5), which compares their performance to the
average of their segment.
The main encountered problems are:
- The data is collected from firms which participate voluntarily in the survey. This may
introduce a certain bias.
18 VCU is based on the size and engine power of the vessel and are specified in the license. The formula is: (Length over all X Breadth) + ( Engine Power X 0.45 )
43
- The timing of the DCF data calls assumes implicitly that the accounting and the calendar year
are identical. However, this is not always the case. Seafish allocates the accounting data to
the year in which the vessel has spent most time, e.g. if the accounting year runs from 1.5.X
till 30.4.X+1, than the accounting is allocated to the year X.
- The preceding point implies that vessel performance is allocated to year X, despite the fact
that the fishing opportunities (TACs) of the year X+1 may be significantly different.
9.3. Statistical quality
The quality of the data is controlled by the Seafish staff involved in the data collection. The type of
quality checks and the way how they are implemented is presented in table 3. The sample
represented in 2012 40% of the total revenues of the UK fleet.
Table 3. Quality checks on data on fishing fleet
Primary data Aggregated data
Not relevant
Manual check
Software check
Not relevant
Manual check
Availability X
X
Accessibility X
X
Missing values
X
X
Duplicated records
X X
Timeliness X
X
Coding
X X
Std. deviation
X X
Coefficient of variation
X X
Sample size X X X
Sampling rate
X
X
Response rate
X
X
Coverage rate
X
X
Other
Typing errors
X X
Arithmetic checks
X
X
Logical checks
X
X
Range/ outliers X X
o cross section
X
X
o time series
X
X
Other sources
X
X
Source: DC MAP survey
In the table III-B-3 of the TR, in addition to the CVs, Seafish also presents a column ‘Other variability
indicator’. This reflects the coverage rate of the sample in relation to the gross revenues. This value
should be presented for the revenues only, but not in relation to other variables, because census
data is not available for them.
44
9.4. Conclusions and recommendations
The method for estimation of segment totals is in practice significantly more detailed than described
in the NP and TR. It is recommended to align the text of these documents to the present reality.
It is also recommended to adapt the estimation software so as to reflect correctly the nature of the
fixed costs. Fixed (i.e. non-variable and depreciation) costs should be related to the size of the
vessel.
The calculation of the costs per vessel and subsequent aggregation can be recommended as good
practice, which can be applied also by other MS. Also the provision of the benchmarking report to
the participants of the panel is good practice.
Separation of ‘low activity’ vessels can be also considered as good practice, in particular in relation to
the information provided in the benchmarking reports.
The technical characteristics of the segment and the sample vessels (e.g. VCU, GT, kW, length or
fishing effort) are not compared. As an additional means to assess the representativeness of the
sample, it is recommended to make such comparison.
45
ECONOMIC DATA – AQUACULTURE 10.
10.1. Programme monitoring
Organisation for the production
Economic data on aquaculture (in England, Wales) is collected by the UK Fish Health Inspectorate
(FHI), which resides within CEFAS. FHI is responsible for licensing and hygiene controls of the fish
farms and as such FHI staff visits all farms at least once per year. FHI has been traditionally
responsible for collection of aquaculture production data for Eurostat. Therefore it was a logical step
to assign the DCF tasks also to FHI / CEFAS. Six FHI inspectors are involved in the collection of the
production data.
In Scotland, aquaculture activities are monitored by the MSS through a postal census (with almost
100% response). DARDNI is responsible in Northern Ireland. DARD staff collects the data while it visits
the farms, on average 2 times per year.
The data collection is theoretically based on census approach using questionnaires which are sent to
all registered and active aquaculture farms. However, this applies only to the production figures
(value and volume by species). CEFAS compiles the information from the four countries and
completes them with the other missing economic indicators requested by DCF using the data from
the Annual Business Inquiry (ABI) provided by the ONS.
In 2013, a consortium of Frontline Consultants and Poseidon19 carried out a pilot study on
aquaculture data collection. This study was launched because the present data collection falls
seriously short of the DCF requirements. The report makes a number of recommendations for the
future collection of the DCF aquaculture data.
Achievement of objectives
The extent to which the data collection objectives have been achieved could not be well evaluated. It
is recognized by the NC that the present status of the data collection is very unsatisfactory and steps
are being taken to improve this in 2014. The production estimates are probably reasonable. The costs
have been estimated on the basis of the ABI and reflect the cost composition of all business included
in ABI. Aquaculture represents only a very small part of the ABI. This applies also to the very low CVs
(0.05-0.11) stated on p. 93 of the 2013 Technical Report. UK Statistics could not provide any details
regarding the aquaculture content of the ABI to the NC.
10.2. Data upload, storage, processing and access
Fish Health database is an SQL server database hosted by CEFAS which contains the registration and
authorizations and the production data for aquaculture. It is more than 10 years old and is currently
being redeveloped. The current system allows secured remote access, different level of access to the
data depending on the logging. Specific users were trained to use the SQL server query interface to
perform ad-hoc queries.
19 EU Data Collection Framework – Pilot Study into Collection of Economic Data on the Marine Aquaculture Sector, Final Report for the Seafish Industry Authority, 2013
46
The database is updated with information gathered during visits of the farms by data operators in
Weymouth. This information is first written on the “7-10 form” by the FHI staff after each visit to a
farm.
Similar forms and a database are used in Scotland. There the forms are sent by mail to the farms.
From the perspective of DCF this form contains only information on production and employment
responding to the Eurostat needs, but nothing on production costs.
The farms are assigned to the various DCF segments either on the basis of the judgement of the
visiting FHI staff (England, Wales) or on the basis of the information provided in the form (Scotland,
N. Ireland).
The data used for the estimation of costs originate from the ABI, carried out by the ONS. This data
covers a broad range of economic activities, not only aquaculture. The NS could not provide any
details regarding the actual data on aquaculture. In principle the ABI source cannot be considered
relevant for the purpose of DCF.
The census data on production (volume and value) is aggregated to generate the national total. The
costs data is taken as received. However, the responsible statistician at CEFAS retired recently and
further details on any processing could not be obtained.
The UK NC recognized that the state of data collection on aquaculture has been poor. A new system
is being set-up on the basis of the pilot study. It is expected that an improvement will be achieved
with data collected in 2014. The main characteristics of the new arrangement are:
CEFAS will assume a leading role, with support from Frontline Consultants and Seafish.
Survey will be carried out using paper forms and Survey Monkey software, already used by
Frontline during the pilot.
The system should allow to register and check the full set of aquaculture data needed for
the DCF.
NS is not involved, but DEFRA statistics department is part of the UK statistical system.
CEFAS is an executive agency of DEFRA, and consequently DEFRA’s position within the UK
statistical system guarantees the required quality.
Raising methodology is still under development.
The new implies a UK-wide approach, which is relatively unusual, considering the role of the four
regions. It was noted that co-funding of such UK-wide survey was still under discussion among the
four regional governments.
10.3. Statistical quality
CEFAS compiles all the aquaculture data from the four UK regions. Consequently, it bears the final
responsibility for the data quality. The text above illustrates that overall the quality is questionable.
This can be illustrated even with the employment data (which is collected through the present
census) submitted under the 2013 data call from JRC (Joint Research Centre) and reflected in the
Scientific, Technical and Economic Committee for Fisheries (STECF) 13-03 report (see box 1).
It was noted that the production values in STECF 13-03 were reported in GBP and not in Euro.
47
CEFAS holds several quality certificates20. However, along with the entire data collection and
processing procedure, also all details of quality assurance in relation to aquaculture will have to be
developed.
It may be pointed out, that the organizations responsible for the collection of the data are also
responsible for licensing and monitoring of the aquaculture farms (fresh water and marine), so that
they hold up to date lists of the active farms. There were in 2013 295 fresh water and marine farms in
England and Wales. In Scotland21 there are 84 firms operating 178 sites, although not all sites are in
use.
NSI provided some details of survey and CVs but confirmed that the sample was too low for the data
to be representative. ABI data will not be used in any future data collection.
Reliance on this survey does not seem justified. In addition, the ABI survey is based on VAT registers,
containing only firms with an annual turnover of more than 79,000 GBP. The small firms are not
surveyed.
Box 1. Estimation of employment in UK aquaculture
20 http://www.cefas.defra.gov.uk/media/588140/qualityploicyv1.2may2013.pdf 21 Marine Scotland Science, Scottish fish farm production survey, 2012
The table below presents data on employment and labour costs from STECF report and their implications. P.2007 puts the total employment at 4,000 FTE. With 1,064 FTE in salmon (p.211) there would be about 3,000 FTE in trout and mussel farming.
According to Eurostat (earn_ses10-27 series), the average earning in the UK were 34,800 euro per year in 2010. This means that labour costs in salmon farming were about 20% higher than the national average (bearing in mind that the two values are differently defined).
However, the labour costs of the remaining 3,000 FTEs amount only to 11 min GBP, i.e. about 4,600 Euro per FTE, i.e. only 13% of the national average. This means that although there may be 3,000 part time employees in the trout and mussel sector, this is probably on 400-500 FTE.
Table A. Employment and labour costs in the STECF 13-03 report*
Labour costs as % of
turnover
(p.211)
Turnover (mln GBP)
(P.210)
Total labour costs (mln
GBP)
(calculated)
Employment
(FTE)
(p.207 and 211)
Labour cost/ employed (GBP)
Labour cost/ employed
(euro)
Salmon 8.10% 442 35.802 1,064 33,648 42,060
Trout 16.40% 35 5.740
Mussels 25.20% 21 5.292
Trout + mussels 56 11.032 3,000 3,677 4,597
*Numbers in bold are from the STECF 13-03 report. Numbers in red highlight the inconsistency of the present results.
48
10.4. Conclusions and recommendations
Apart from the production figures (value and volume), all other DCF data on aquaculture seems
questionable. A new system is being put in place, but its performance can be only evaluated mid-
2015, at the earliest, after collection and processing of the 2012 data, which will be done during 2014.
It is recommended to check the data on its internal consistency, to avoid problems illustrated above,
and compare them with internationally available data. A comprehensive set of quality checks needs
to be formulated.
49
ECONOMIC DATA – PROCESSING SECTOR 11.
11.1. Programme monitoring
Organisation for the production
Seafish Industry Authority (Seafish) is responsible for collection of DCF data on fish processing for
the entire UK. It may be noted that Seafish has been involved in surveys of and publication on the
economic performance of the fish processing sector for many years before the DCF came into
power.
Seafish carries out a detailed census every 4 years and a bi-annual census for DCF. The list of fish
processing is compiled on the basis of several sources:
Seafish levy register (Seafish charges a levy on all fish processors to finance its activities on
behalf of the UK fishing industry)
Food Standards Agency (issuing hygiene permits on the basis of the EU Regulations 852, 853
and 882/2004)
Companies House, which receives summary of annual accounts.
The companies are approached with a simple hard copy questionnaire (see Annex 6). The responses
are received either by mail or email and entered in an Excel database for further analysis. Seafish
contacts non-respondents by phone in order to achieve sufficient representativeness, not only in
relation to the four size classes but also in relation to eight geographic regions which are
distinguished in Seafish publications.
The methodology is described in detail in Annex 7.
One staff member involved in collection and processing of the data.
Achievement of objectives
Selected responses indicated in the Technical Report 2013 were checked against data in the files of
Seafish. It can be confirmed that the number of responses stated in table IV-B-1 is correct. However,
it was noted that not all respondents provided full set of data, i.e. Seafish faces the problem of item
non-response. E.g. in out of 59 respondents in the 11-49 FTE size group only 24 filled in their energy
costs.
11.2. Data upload, storage, processing and access
Data is obtained from two complementary sources: survey forms distributed by Seafish and
complementary balance sheet information acquired from the Companies House.
Data of the survey is collected on paper forms and uploaded manually in an Excel file. The Companies
House provides up to 260 indicators on employment, profits, assets and debts (balance sheet data).
The Companies House does not provide data on production costs (i.e. details of profit and loss
statement). The data is received digitally and entered in a second Excel file.
50
The data is checked manually. Outliers are either checked with the source or eliminated. Excel files
are imported in an Access database and processed with STATA software.
On the basis of the collected data, Seafish estimates for every size group of firms the average value
per FTE for each variable, e.g. average costs of energy / FTE for the size group 11-49 FTEs. These
average values are than extrapolated to segment totals using the total FTE employment in each
segment.
Results are published in own Seafish publications and summaries22 and in the STECF reports on fish
processing.
Confidential data on individual firms is used only by the designated staff of Seafish, files being
protected with passwords. Seafish staff has to pledge not to distribute any confidential information
to which they may have access.
Seafish does not cooperate with UK NSI in any way, although there have been some ad hoc contacts.
Consequently, Seafish could not provide any information regarding the Structural Business Survey
(called ABI in the UK). It seems very likely that some overlap exists between the surveys carried out
by Seafish and data received by the NSI. However, Annex 8 shows that the data available at Eurostat
dates back to 2007 while data on 2008 is very incomplete.
It was noted that the description of the procedure presented in the National Programme and the
Technical Report does not quite match the present practice, e.g.
- Regressions (mentioned on p.117 of the NP) have been replaced by STATA programme.
- Reference to PRODCOM on p. 125 and 128 of the NP is not relevant.
11.3. Statistical quality
As shown in table 4, statistical quality of the data is mainly checked manually. It must be noted that
the 2012 survey was carried out by staff members who are not in Seafish anymore, and consequently
details of the quality checks could not be obtained. Quality checks have not been well documented
until present.
22 Accessible at : http://www.seafish.org/research--economics/industry-economics
51
Table 4. Quality checks on data on fish processing
Primary data Aggregated data
Not relevant
Manual check
Software check
Not relevant
Manual check
Software check
Availability X
X
Accessibility X
X
Missing values
X
X
Duplicated records
X X
Timeliness X
X
Coding
X X
Std. deviation
X
X
Coefficient of variation
X
X
Sample size X X
Sampling rate
X
X
Response rate
X
X
Coverage rate
X
X
Other
Typing errors
X X
Arithmetic checks
X
X
Logical checks
X
X
Range/ outliers X X
o cross section
X
X
o time series
X
X
Other sources
X
X
Source: survey of national correspondents, carried out under the study: Scientific data storage and transmission
under the 2014-2020 Data Collection Multi-Annual Programme (DC-MAP) – Feasibility Study, MARE/2012/22
The main problem encountered by Seafish in ensuring quality of the fish processing data is the level
of non-response. The causes of non-response are: 1. Commercial sensitivity, 2. Lack of time to
compile relevant data, 3. Lack of available data and 4. Lack of value from participating in the
exercise.
11.4. Conclusions and recommendations
Seafish has a long standing experience with collecting, analysing and publishing data on fish
processing industry. It also has an equally long relation with the sector, which helps to obtain
reasonable response, although intensive “chasing up” of non-respondents is still required.
The data processing procedure are continuously developed, which is at least partly a consequence of
the limited transfer of knowledge and experience among Seafish staff.
52
Recommendations:
Description of the methodology in the NP and TR should follow more precisely the present
practice.
The procedures of quality checks should be documented and their results should be
recorded for later reference.
53
VARIABLES ON THE EFFECTS OF FISHERIES ON MARINE 12.
ECOSYSTEM
Organisation for the production of related data
The responsibility of collecting the indicators to measure the effects of fisheries on the marine
ecosystem lies with the different institutes in UK dealing with biological and economic data
collection, depending on the type of indicator, as follows:
Ecosystem indicators 1 – 4: The data for the calculation of these indicators derive from a series of
IBTS research surveys carried out by the UK in the North Sea and the North Atlantic. The data are
stored either at CEFAS or Marine Scotland databases (depending on who carries the responsibility
for the research survey) and are transmitted to ICES for being introduced into the DATRAS database.
Ecosystem indicators 5 – 7: CEFAS and MSS have each developed own algorithms for linking VMS
data to log-book records (control data) for vessels with a LOA > 15m in order to describe the spatial
distribution of fisheries. Further developments are going on for improving the filtering of vessel
position data where actual fishing activity takes places as well as for linking VMS data to fishing gears
and métier-related variables.
Ecosystem indicator 8: Estimates of discarding rates of commercially exploited species are calculated
based on on-board observer programmes of commercial fisheries implemented by AFBI (Northern
Ireland), CEFAS (England and Wales in future) and Marine Scotland (Scotland). Besides discarded
fish, also seabirds, reptiles and marine mammals by-catches are recorded.
Ecosystem indicator 9: Data for the calculation of the fuel efficiency of fish capture derive from the
economic survey, i.e. the fuel costs raised, and the subsequent estimation based on the actual fishing
activity of every vessel down to the gear type employed (Level 4, Appendix IV of Commission
Decision 2010/93/EC). Capture data are obtained from logbooks, landing declarations and sales
notes.
Achievement of objectives
As requested by Commission Decision 2010/93/EC, Chapter V, data for the evaluation of the fisheries
sector on the marine ecosystem are collected according to Appendix XIII in order to allow end-users
to calculate the ecosystem indicators. Data is available on national databases; besides, data for
Indicators 1-4 are also provided to ICES to be available on the online database of trawls surveys
DATRAS. National databases within CEFAS and Marine Scotland are accessible to the in-house staff
responsible for the reporting obligations related to the Marine Strategy Framework Directive
(MSFD).
Compliance with methods and procedures
The National Proposal and the Technical Report describe the type of data collected and, broadly, the
procedures followed for the estimation of some ecosystem indicators (e.g. Indicators 5-7 and 9).
With regard to ecosystem indicator 9, it is recommended to put more efforts in determining the
indicator down to métier level 6 as requested by the DCF Regulation.
54
CONCLUSIONS BY CHAPTER 13.
13.1. General IT
The IT systems were in place since a long time before the DCF started, some of the biological
database systems in place are now under revision/reconstruction to better answer present
requirements (e.g. the system used for processing the biological sampling data at CEFAS).
Tools developed by another country were tested: Marine Scotland bought the FSS survey database
from CEFAS but the experience was not considered very satisfactory. The application was not fully
compliant with the Scottish procedure in place for processing the survey data. It was nevertheless
not possible to adapt the tool to the Scottish needs as this would require specific programming
which would inactivate the maintenance guarantee provided by CEFAS.
Also the costs were higher than expected.
At Marine Scotland, the improvement of the FMD database was stopped but some budgets were
allocated to Aberdeen to develop a semantic database on zooplankton data which could be in the
future extended to fisheries statistics. Nevertheless, this could take time as the project is very
innovative. In the meanwhile Marine Scotland will continue working in a non-scalable environment
for the coming years.
The compilation of UK data is a bit complex as it requires combining the results from different
independent country systems. To achieve this, UK implemented tools like the SharePoint site
allowing the different countries within UK to work together. In addition, all transversal data from
Marine Scotland FIN and CEFAS FAD databases are compiled on a daily basis in the IFISH system to
provide information at UK level. The integrated IBIS system is under construction at CEFAS to
connect the information from the biological sampling (GARI), transversal data (FAD/CEDER), discard
(OBSERVER) and survey (FSS) databases. Possibly in the long terms this IBIS could also connect
copies of other countries datasets.
The UK institutions benefits from a huge in house experience in fisheries statistics and internal
experienced IT development team which is continuously improving the process in place. This is
particularly true at CEFAS while Marine Scotland loses most of the IT staff due to retirements
recently.
13.2. Transversal data
The transversal data are compiled for the all UK and accessible to the DCF partners. Landing
declarations and logbooks can be connected and significant checks are applied directly before the
data are entered into the database ensuring a good quality.
55
13.3. Biological data
Métier related variables
The sampling strategy in place does not target métiers as such but is built around more aggregated
gear groups and areas instead. The sampling effort (person-day) is allocated according to the fishing
effort (number of trips), landings, discard rates and fleet size. Very interestingly, a probability based
sampling is adopted in each of these wider strata in order to overcome the inherent statistical
problems of quota sampling. IT is expected that all important métiers will be covered in this way.
In 2012 the UK has sampled 3,696 trips which is more than the 3,182 which were planned for. At the
same time, it may be pointed out that random selection of the sample based on the UK strata does
not guarantee randomness of sampling of the DCF métiers.
Stock related variables
For most species the targeted number of individuals to be sampled is achieved and often exceeded.
Under sampling, which is observed for certain species, is explained by low catches, limited sampling
time and problems encountered when sampling of a high number of species during research surveys.
The collection of biological variables is done according to international standards and working
groups’ recommendations.
Surveys at sea
The UK has carried out all the expected research surveys. Some minor deviations of the achieved
number of samples with respect to the planned numbers have been recorded which are due to
technical issues or bad weather condition.
Recreational fishery
Data on recreational fisheries is not yet fully covered by all the countries in the UK. However, there
are plans to extend the sea angling survey conducted in England to the whole UK in the following
years.
13.4. Economic data
Catching sector
The method for estimation of segment totals is in practice significantly more detailed than described
in the NP and TR.
Aquaculture sector
Apart from the production figures (value and volume), all other DCF data on aquaculture seems
questionable. A new system is being put in place, but its performance can be only evaluated mid-
2015, at the earliest, after collection and processing of the 2013 data, which will be done during 2014.
56
Fish processing sector
Seafish has a long standing experience with collecting, analysing and publishing data on fish
processing industry. It also has an equally long relation with the sector, which helps to obtain
reasonable response, although intensive “chasing up” of non-respondents is still required.
The data processing procedures are continuously developed, which is at least partly a consequence
of the limited transfer of knowledge and experience among Seafish staff.
13.5. Ecosystem indicators
Data on the ecosystem is collected and made available on national databases; besides, data for
Indicators 1-4 are also provided to ICES to be available on the online database of trawls surveys
DATRAS. National databases within CEFAS and Marine Scotland are accessible to the in-house staff
responsible for the reporting obligations related to the Marine Strategy Framework Directive
(MSFD).
57
RECOMMENDATIONS BY CHAPTER 14.
14.1. General IT
It is recommended to maintain an internal team of experienced IT staff involved in the development,
upgrade and maintenance of the fisheries applications.
There is a continuous process of improvements of the existing system. The most recent
developments are:
The GARI shows clearly how the internal knowledge, weakness from the previous system
were taken into account during the building of the GARI.
The electronic data capture system saves time and resources and is less error-prone.
The multiple checks implemented at data capture stage should improve the quality of the
source data
It would be very useful if the above mentioned topics or at least knowledge collected when building
the tools could be shared more widely with other MS.
The result of the innovative project on the semantic database should also be followed and in due
time presented to other research institutes.
14.2. Transversal data
The system built is powerful. The development focused on the quality of the data and the automated
checks to be applied. No user interface was developed to retrieve the information as it was
considered more efficient that users receive a training in SQL given by CEFAS to interrogate the
systems.
This implies that user needs to acquire a very good understanding of the underlying structure and
SQL statement grammar to be used in order to retrieve only the appropriate information from the
database and consequently produce meaningful statistics. MMO made the choice of full flexibility to
the detriment of ease of use, may be an intermediate solution (e.g. business object interface or
similar) could be proposed if users encounter problems.
14.3. Biological data
Métier related variables
It is recommend to test the present assumption that métiers are sampled ad random and with
sufficient intensity. Considering homogeneity of the defined strata in terms of métiers may be a
relevant starting point.
58
Stock related variables
The UK institutions are encouraged to keep on collaborating in developing and applying best
practices and methodologies for the collection of biological variables (e.g. age reading) not only at
international level (ICES working groups) but also within the UK among the different laboratories.
Both for métier and stock related biological data, some problems have been observed within Marine
Scotland in tracing back and reproducing data flows, processes and responsibilities. It is
recommended that:
An integrated data and information management system within MSS would improve to
improve and streamline the processes of data collection and assessment also with regard to
the reporting obligations.
Collaboration between the three teams of observers (demersal, pelagic and shellfish) is
improved.
Recreational fishery
The sea angling survey carried out in England can be considered a starting point for monitoring
recreational fisheries throughout the UK in the short term. It is up to the countries to develop own
survey programmes or to take part in one common survey. The latter is likely to be more cost
efficient.
14.4. Economic data
Catching sector
Recommendations for the UK practice:
It is recommended to align the text of the NP and TR documents to the present reality.
It is recommended to adapt the estimation software so as to reflect correctly the nature of
the fixed costs. Fixed (i.e. non-variable and depreciation) costs should be related to the size
of the vessel.
The technical characteristics of the segment and the sample vessels (e.g. VCU, GT, kW,
length or fishing effort) are not compared. As an additional means to assess the
representativeness of the sample, it is recommended to make such comparison.
Recommendations for STECF / DG Mare:
Separation of ‘low activity’ vessels can be also considered as good practice, in particular in
relation to the information provided in the benchmarking reports.
The calculation of the costs for each individual vessel in the population and subsequent
aggregation can be recommended as good practice, which can be applied also by other MS.
The provision of the benchmarking report to the participants of the panel is good practice.
In order to communicate the economic data to the fishing industry, it should be considered
to design a benchmarking report along the lines of the UK (and other MS which produce it,
e.g. NL).
59
Aquaculture sector
The new system which is put in place in 2014 should be evaluated in the course of 2015. It is
recommended to check the data on its internal consistency and to compare them with
internationally available data. A comprehensive set of quality checks needs to be formulated.
Fish processing sector
Description of the methodology in the National Programme and Technical Reports should
follow more precisely the present practice.
The procedures of quality checks should be documented and their results should be
