Interim report of the HELCOM CORESET project

Fish diseases may act at the individual level by adversely affecting behaviour, growth, reproduction, and
survival of affected specimens. Individual effects may lead to ecologically relevant population effects (especially
in epidemic situations) and ultimately to biodiversity effects at the community level. Diseases in wild
fi sh may affect aquaculture due to transmission of pathogens. A high prevalence of a conspicuous fi sh
disease may affect fi shery profi t because fi sh with prominent disease signs cannot be marketed. Although
direct human health effects of diseases affecting wild fi sh are unlikely (except for a few cases), diseased
fi sh may act as carriers of pathogens that pose a risk to human consumers.
Quality Assurance
Since the early 1980s, ICES has played a leading role in the initiation and coordination of fi sh disease surveys
and has contributed considerably to the development of standardised methodologies. Through the
work of the ICES Working Group on Pathology and Diseases of Marine Organisms (WGPDMO), its offspring,
the Sub-Group/Study Group on Statistical Analysis of Fish Disease Data in Marine Stocks (SGFDDS)
(1992–1994) and the ICES Secretariat, quality assurance procedures have been implemented at all stages,
from sampling of fi sh to submission of data to the ICES Data Centre and to data assessment.
A number of practical ICES sea-going workshops on board research vessels were organised by WGPDMO in
1984 (southern North Sea), 1988 (Kattegat), 1994 (Baltic Sea, co-sponsored by the Baltic Marine Biologists,
BMB) and 2005 (Baltic Sea) in order to intercalibrate and standardise methodologies for fi sh disease surveys
(Dethlefsen et al. 1986; ICES 1989, 2006a; Lang & Mellergaard 1999) and to prepare guidelines. Whilst fi rst
guidelines were focused on externally visible diseases and parasites, WGPDMO developed guidelines for macroscopic
and microscopic inspection of fl atfi sh livers for the occurrence of neoplastic lesions at a later stage.
Further intercalibration and standardision of methodologies used for studies on liver pathology of fl atfi sh
were a major issue of the 1996 ICES Special Meeting on the Use of Liver Pathology of Flatfi sh for Monitoring
Biological Effects of Contaminants (ICES 1997). This formed the basis from which the quality assurance programme
Biological Effects Quality Assurance in Monitoring (BEQUALM) (www.bequalm.org) developed for
the application of liver pathology in biological effects monitoring (see below) (Feist et al. 2004).
A fi sh disease database has been established within the ICES Data Centre, consisting of disease prevalence
data of key fi sh species and accompanying information, submitted by ICES Member Countries. Submission
of fi sh disease data to the ICES Data Centre has been formalised by the introduction of the ICES Environmental
Reporting Format designed specifi cally for the purpose. This is used for fi sh disease, contaminant
and biological effects data. The programme includes internal screening procedures for the validation of the
data submitted providing further quality assurance.
The ICES fi sh disease database is extended on an annual basis to include data from other species and areas
within the OSPAR and HELCOM area as well as data on studies into other types of diseases, e.g. macroscopic
liver neoplasms and liver histopathology. To date, the data comprise mainly information from studies
on the occurrence of externally visible diseases and macroscopic liver lesions in the common dab (Limanda
limanda) and the European fl ounder (Platichthys fl esus) from the North Sea and adjacent areas, including
the Baltic Sea, Irish Sea, and the English Channel. In addition, reference data are available from pristine
areas, such as waters around Iceland. In total, data on length, sex, and health status of more than 700 000
individual specimens, some from as early as 1981, have been submitted to ICES, as well as information on
sampling characteristics (Wosniok et al. 1999, Lang and Wosniok 2008).
Current ICES WGPDMO activities have focussed on the development and application of statistical techniques
for an assessment of disease data with regard to the presence of spatial and temporal trends in
the North Sea and western Baltic Sea (Wosniok et al. 1999, Lang and Wosniok 2008). In a more holistic
approach, pilot analyses have been carried out combining the disease data with oceanographic, nutrient,
contaminant and fi shery data extracted from the ICES Data Centre in order to improve the knowledge
about the complex cause-effect relationships between environmental factors and fi sh diseases (Lang and
Wosniok 2000; Wosniok et al. 2000). These analyses constituted one of the fi rst attempts to combine and
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