Department of Management, University of Rome, Rome, Italy.
Ecotoxicology. 2012 May;21(4):1112-25. doi: 10.1007/s10646-012-0866-7. Epub 2012 Feb 18.
With the aim to evaluate the mollusk Nacella (P)magellanica as biomonitor of elemental pollution in seawater of the Beagle Channel, more than one hundred individuals of the gastropod were sampled, separated in viscera and muscle, and then examined with respect to the accumulation of Cd, Cr, Cu, Ni, Pb and Zn. Collection was performed in seven strategic locations along 170 km of the coastal area of the Beagle Channel (Tierra del Fuego, Argentina) in two campaigns during 2005 and 2007. Samples of surrounding seawater in the different sites were obtained and tested for the same metals as well. The accumulation capacity of Nacella (P)magellanica and thus its aptitude as biomonitor, was evaluated through the calculus of the preconcentration factors of the metals assayed. A discussion involving the comparison with other mollusks previously tested will be given. Several statistical approaches able to analyze data with environmental purposes were applied. Non parametric univariate tests such as Kruskal-Wallis and Mann-Whitney were carried out to assess the changes of the metal concentrations with time (2005 and 2007) in each location. Multivariate methods (linear discriminant analysis on PCA factors) were also applied to obtain a more reliable site classification. Johnson's probabilistic method was carried out for comparison between different geographical areas. The possibility of employing these results as heavy metals' background levels of seawater from the Beagle Channel will be debated.
为了评估腹足纲软体动物 Nacella (P)magellanica 作为贝格尔海峡海水元素污染的生物监测物，我们采集了一百多个该腹足类动物的样本，将其分为内脏和肌肉两部分，然后检测其对 Cd、Cr、Cu、Ni、Pb 和 Zn 的积累情况。这项研究在 2005 年和 2007 年的两次考察中，在贝格尔海峡（阿根廷火地岛）沿岸的 170 公里长的七个战略地点进行。在不同地点采集了周围海水中的样本，并对相同的金属进行了测试。通过计算所测金属的浓缩因子，评估了 Nacella (P)magellanica 的积累能力及其作为生物监测物的适宜性。将讨论涉及与以前测试过的其他软体动物的比较。应用了几种能够分析环境数据的统计方法。非参数单变量检验（Kruskal-Wallis 和 Mann-Whitney）用于评估每个地点金属浓度随时间（2005 年和 2007 年）的变化。还应用了多元方法（基于 PCA 因子的线性判别分析）来获得更可靠的地点分类。进行了 Johnson 的概率方法，用于比较不同地理区域。将讨论这些结果作为贝格尔海峡海水重金属背景水平的可能性。
