Reliability of heavy metal pollution monitoring utilizing aquatic animals versus statistical evaluation methods

Abstract

E A m h i v e s o f n v i r o n m e n t a l c o n t a m i n a t i o n a n d | oxicology© 1992 Springer-Verlag New York Inc. Reliability of Heavy Metal Pollution Monitoring Utilizing Aquatic Animals Versus Statistical Evaluation MethodsZoltfin Mastala, Katalin V.-Balogh, and J~inos Sal4nkiBalaton Limnological Research Institute of the Hungarian Academy of Sciences, Tihany, P.O. B. 35, Hungary Abstract. Heavy metal concentrations in two snail and two fish species were used to compare the pollution of four sites on the River Zala and on the Kis-Balaton Reservoir (Hungary). The effectiveness of different statistical methods (t-and Bartlett's test, analysis of variance and analysis of covariance) were compared. The most reliable results were obtained by using analysis of covariance, with body weight as the covariate, taking the seasonality in metal concentrations into consideration. The different species showed the same relations among sampling stations if analysis of covariance was applied. It is essential to use statistical methods that account for the most important effects (c0variates); otherwise, the reliability of the information supported by biomonitors is compromised.Heavy metal contamination in the aquatic environment is usually monitored by measuring concentrations in the water, sediment and biota. Determination of metal concentrations in surface water samples is problematical because concentrations are low and display wide fluctuations. Metal concentrations in sediments are high and relatively invariant with time. However, they are influenced by the organic matter, Mn and Fe contents, pH and oxidation-reduction potential, grain size distribution, etc. (F6rstner and Wittmann 1983;F6rstner 1984), which make direct comparisons between locations difficult. The main problem of utilizing aquatic animals is that metal concentrations in organs or in tissues depend not only on concentrations in the environment, but on several factors, such as temperature (Pentreath 1976a), salinity (Unlu and Fowler 1979), pH (Campbell and Stokes 1985;Wiener 1987), organic ligands (Gjessing 1981), seasonal changes in metal accumulation (Pentreath 1976b) and organism size (Phillips 1980;Beumer and Bacher 1982).Among them, the body weight dependence was the most critical factor, and there is no simple answer for its elimination from monitoring surveys (Phillips 1980). Although, Boyden's power model (Boyden 1974(Boyden , 1977 is used primarily to describe the effect of body weight on metal concentrations, it is an empirical relationship without a clearly defined, underlying mechanism. Boyden hypothesized that the exponents of the power functions were generally constant for some speciesmetal combinations. If this were so, the effects of size on metal levels could be easily eliminated using an exponent with universal validity. This hypothesis was supported by Smock (1983), but was refuted by Cossa et al. (1980) as well as by Strong and Luoma (1981).Another alternative is the deliberate selection of a large range of sizes at all locat...

Brown Trout as Biomonitor of Heavy Metal Pollution: Effect of Age on the Reliability of the Assessment

“…The increase in copper content with the aging of trouts is likely to be due to the fact that this metal could be bioaccumulated by some fish species without any toxic effect (Sternlieb, 1980), a positive relationship having been demonstrated between copper concentration and body size (Mastala et al, 1992). Conversely, lead and cadmium decreased with aging.…”

“…Other biological features such as age and genetic composition of population have not been known to interfere with heavy metal biomonitoring until now. With body size being directly correlated with age of fish (Reyes-Gavilan et al, 1995), the relationship between body weight and metal concentrations repeatedly reported (Mastala et al, 1992) could be a simple indication of the exposure time, age being the real factor influencing fish metal content. The assessment of the effect of this factor on the fish metal concentration is the main objective of this work.…”

“…A problem to deal with when using aquatic animals as biomonitors of heavy metal pollution is the relationship existing between metal concentration and several intrinsic factors of the fish, such as seasonal changes in metal accumulation (Penthreat, 1976) and organism size (Phillips, 1980;Beumer and Bacher, 1982;Mastala et al, 1992). Other biological features such as age and genetic composition of population have not been known to interfere with heavy metal biomonitoring until now.…”

<b>Heavy metal bioaccumulation of the characiform <i>Brycon falcatus</i> Muller & Troschel, 1844 in the Teles Pires basin, Southern Amazon

“…In this study, a positive correlation was observed between Cu concentration in liver tissue to the weight and standard length of matrinxã specimens collected in rivers from the Teles Pires River basin. Several other studies have also shown a positive correlation between metal concentration and fish body size (Mastala, Balogh, & Salansk, 1992;Farkas et al, 2003;Kasimoglu, 2014). Agricultural activity is intense in the vicinity of the rivers (Verde, Celeste, Tapaiúna, and Teles Pires) sampled in this study.…”

Combining Environmental Information. Ii: Environmental Epidemiology and Toxicology

“…Basic statistical research into combined analyses over multiple studies has included rich applications in biological areas; selected examples include ecotoxicology (Mastala et al 1992), cancer epidemiology (Morris 1994), and other medical/clinical settings (Chalmers 199 1;Hasselblad et al 1992). A common rubric for combining the results of independent epidemiological and clinical studies is meta-analysis (Hedges and Olkin 1985).…”