Interim report of the HELCOM CORESET project

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analyses ICES data from various sources and can, therefore, be considered as a step towards a more comprehensive
integrated assessment.
Quality assurance is in place for externally visible diseases, macroscopic liver neoplasms and liver histopathology
via the ongoing BEQUALM programme. Regular intercalibration and ring-test exercises are conducted.
The basis for QA procedures are provided in two key publications in the ICES TIMES series (Bucke
et al. 1996, Feist et al. 2004) and a BEQUALM CD ROM of protocols and diagnostic criteria and reporting
requirements for submission of data to ICES. Guidelines on fi sh disease monitoring in the Baltic Sea have
been prepared by ICES (2006a).
Assessment Criteria
The development of assessment tools for externally visible diseases, macroscopic neoplasms and liver histopathology
has been addressed by the ICES Working Group on Pathology and Diseases of Marine Organisms
(WGPDMO) (ICES 2006b, 2007, 2008, 2009a, 2011). Further additions were proposed at the 2009 ICES/
OSPAR Workshop on Assessment Criteria for Biological Effects Measurements (WKIMC) (ICES 2009b) (see
further below).
For the analysis and assessment of fi sh disease data, the ICES WGPDMO developed a Fish Disease Index
(FDI), using data on diseases of the common dab (Limanda limanda) as a model. The aim of this tool is to
summarise information on the disease status of individual fi sh into one robust and easy-to-understand and
easy-to-communicate numeric fi gure. By applying defi ned assessment criteria and appropriate statistics, the
FDI can be used to assess the level and temporal changes in the health status of fi sh populations and can,
thus, serve as a tool for the assessment of the ecosystem health of the marine environment, e.g. related to
the effects of anthropogenic and natural stressors. Its design principle allows the FDI to be applied to other
species with other sets of diseases. Therefore, the FDI approach is applicable for wider geographical areas,
e.g. as part of a convention-wide HELCOM monitoring and assessment programme.
For the calculation of the FDI, the following components are required:
– information on the presence or absence of a range of diseases monitored on a regular basis, categorised
as externally visible diseases, macroscopic liver neoplasms as well as non-specifi c and contaminant-specifi
c liver histopathology (see Table 3.11);
– for most diseases, data on three severity grades (refl ecting a light, medium or severe disease status) are
included;
–disease-specifi c weighting factors, refl ecting the impact of the diseases on the host (assigned based on
expert judgements);
– adjustment factors for effects of size and sex of the fi sh as well as for season effects.
The result of the calculation is a FDI value for individual fi sh which is scaled in a way that values can range
from 0 to 100, with low values representing healthy and high values representing diseased fi sh. The maximum
value of 100 can only be reached in the (purely theoretical and unrealistic) case that a fi sh is affected
by all diseases at their highest severity grades. From the individual FDIs, mean FDIs for a sample from a fi sh
population in a given sampling area can be calculated. Usually a sample in the present sense consists of the
data collected in an ICES statistical rectangle during one cruise. All assessment is based on mean FDI values
calculated from these samples. Depending on the data available, FDIs can be calculated either for single
disease categories or for combinations thereof.
The assessment of the mean FDI data considers (a) long-term FDI level changes, (b) FDI trends in the recent
fi ve years time window and (c) comparing each FDI to its Background Assessment Criterion (BAC) and Environmental
Assessment Criterion (EAC) where these are defi ned. While assessments (a) and (b) are done on
a region-wise basis, global BAC and EAC are used by assessment (c). The assessment approaches (a) and (b)
do not apply any global background or reference values or assessment criteria as is often done for chemical
contaminants or for biochemical biomarkers. Instead, these assessment approaches use the development
of the mean FDI within the geographical units (usually ICES rectangles) over a given period of time, based