Development of fish age normalization technique for pollution assessment of marine ecosystem, based on concentrations of mercury, copper, and zinc in dorsal muscles of fish
Suhareva, N.; Aigars, J.; Poikane, R.; Jansons, M. (2020). Development of fish age normalization technique for pollution assessment of marine ecosystem, based on concentrations of mercury, copper, and zinc in dorsal muscles of fish. Environ. Monit. Assess. 192(5): 279. https://dx.doi.org/10.1007/s10661-020-08261-x In: Environmental Monitoring and Assessment. Kluwer: Dordrecht. ISSN 0167-6369; e-ISSN 1573-2959, more |  |
| Keyword | | | Author keywords | Trace metals; Baltic Sea; Gulf of Riga; Fish age; Normalization of concentration; Pollution assessment |
| Authors | | Top | - Suhareva, N., more
- Aigars, J.
- Poikane, R.
- Jansons, M.
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| Abstract | Correlation between metal concentrations in fish tissues and fish body size poses certain challenge when comparing concentration levels encountered at different locations or time periods by degrading performance of statistical tests due to variable age composition of fish sample pool. In order to overcome this, the concentrations of Hg, Cu, and Zn, measured in tissues of five fish species, were normalized to selected age group. Computed species-specific equations, based on empirically obtained exponential relationship, provided accurate estimates of the normalized concentrations under the conditions of substantial metal and fish age covariation. Obtained normalized and measured concentrations were then compared among sampling stations by means of commonly used analysis of variance (ANOVA) in combination with Tuckey's HSD test, where 11 out of 18 considered cases showed significant smoothing of the observed differences. The applied method worked well in the case of locally distributed coastal species populations where transformed data allowed clearer separation of spatial areas exhibiting different levels of pollution. At the same time, application of the method on pelagic fish species was less successful due to high mobility of specimens and mixed impact on the population originating from variable pollution levels at different areas of the entire migration region; therefore, attribution of a sample pool to a specific catchment area can cause a bias in assessment results. |
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