Latvian Institute of Aquatic Ecology, Voleru street 4, Riga, LV-1007, Latvia.
Environ Monit Assess. 2020 Apr 11;192(5):279. doi: 10.1007/s10661-020-08261-x.
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.
当比较不同地点或不同时期的鱼类组织中金属浓度时,由于鱼类样本池的年龄组成不同,会降低统计检验的性能,从而导致金属浓度与鱼类体型之间存在一定的相关性。为了克服这一问题,将 5 种鱼类组织中的 Hg、Cu 和 Zn 浓度归一化为选定的年龄组。基于经验获得的指数关系计算出的物种特异性方程,在金属和鱼类年龄存在大量协变的情况下,提供了归一化浓度的准确估计。然后,通过常用的方差分析(ANOVA)结合 Tukey 的 HSD 检验,将获得的归一化和实测浓度在采样站之间进行比较,在 18 个考虑的案例中,有 11 个显示出观察到的差异有明显的平滑化。该方法在局部分布的沿海物种种群中效果良好,因为转换后的数据可以更清晰地分离出污染水平不同的空间区域。然而,由于标本的高流动性以及不同区域的不同污染水平对种群的混合影响,该方法在洄游鱼类物种上的应用效果较差;因此,将样本池归因于特定的集水区可能会导致评估结果出现偏差。