We use cookies on our website. Some are necessary for the operation of the website. You can also allow cookies for statistical purposes. You can adjust the data protection settings or agree to all cookies directly.
Data Protection Declaration
Imprint
The health status of marine fishes - tools for the analysis and assessement
Project
Project code: TI-FI-08-PID1562
Contract period: 01.01.2010
- 31.12.2015
Purpose of research: Inventory & Assessment
How can the health status of marine fishes be described? To answer this question, many data have to be collected. The health status of a fish is depending on the sum of its diseases, their effects on the fish and the risk to get sick. With the 'Fish Disease Index', we have developed a tool that takes into account these complex interactions and, thus, facilitates the analysis and assessment of regional patterns and trends in the framework of marine environmental monitoring. Since the 1980s, the Thünen Institute of Fisheries Ecology is studying (as part of its monitoring programme on the status of the marine environment) the prevalence and regional distribution of fish diseases in the North Sea and Baltic Sea. We apply internationally standardised ICES procedures that are also used by other countries with similar monitoring programmes. In past, only regional patterns and temporal trends of single diseases were addressed and related to environmental stressors, such as contaminants, temperature, oxygen concentrations and salinity. With this approach, various and partly contradictory relationships were identified, and, thus, a more holistic assessment of the status of the marine environment was difficult to achieve. Therefore, we are developing a 'Fish Disease Index (FDI)', which a) mathematically combines information on all diseases of an individual fish as well as impact factors and b) enables the analysis and assessment of regional and temporal patterns in the overall health status of fishes. The development of the FDI for dab (Limanda limanda) is almost finalised, for cod (Gadus morhua) and flounder (Platichthys flesus) it is underway. For the calculation of the 'Fish Disease Index (FDI)', the presence (yes/no), the severity (3 grades) and the effects of the diseases on the host (according to expert judgement) are taken into account. For dab, e.g., the FDI encompasses 9 regularly recorded externally visible diseases and parasites, and is presently expanded to also include data on liver tumours and liver histopathology. Since the risk of a fish to get sick is depending on its sex, age, length as well on the season, these variables derived from empirical data are mathematically incorporated in the FDI calculation as adjustment factors. For each fish, we calculate a FDI value. From this, mean values can be calculated for representative groups of fish, enabling conclusions on the health status of populations. For the assessment of the health status (good, medium, bad), the results are compared to longterm FDI data from the region under study. It is tested if the FDI exceeds threshold values which lead to proven negative impacts on the fitness of the fish (measured as condition factor). An assessment based on such criteria is a prerequisite for the use of the FDI as indicator meeting the requirements of the international marine protection conventions (OSPAR, HELCOM) and the EU Marine Strategy Framework Directive. Longterm data of the FI on diseases of marine fishes of the North Sea, Baltic Sea and adjacent areas are the basis for the calculation of the FDI. They have been obtained during reserach vessel cruises by applying internationally standardised procedures. We currently transfer the data to the newly established joint database of the Thünen fisheries research institutes.
Our FDI results indicate that there are regional differences in the health status of North Sea dab. In most areas, the mean FDI currently reflects a good or medium health status, but there are also areas where the health status of dab is bad and is apparently getting worse over time.
Section overview
Subjects
- Animal health
- Marine fisheries
- Computer science
