Sánchez López F J, Gil García M D, Martínez Vidal Jose L, Aguilera P A, Garrido Frenich A
Department of Hydrogeology and Analytical Chemistry, University of Almería, Almería, Spain.
Environ Monit Assess. 2004 Apr-May;93(1-3):17-29. doi: 10.1023/b:emas.0000016789.13603.e5.
Water quality assessment in the Aznalcollar area was attempted using multivariate methods based on heavy metal concentrations in red swamp crayfish (Procamburus clarkii). Trace levels of four heavy metals, copper (Cu), zinc (Zn), cadmium (Cd) and lead (Pb), were detected in crayfish from eleven different stations. Principal component analysis (PCA) highlighted a gradient of contamination between the sampling stations. Cluster analysis (CA) distinguished three groups of stations. Discriminant analysis also differentiated three groups. The group centroids of the first discriminant function were used to devise an index that varies according to the source of the crayfish. These standardized values are proposed for use as a water quality index. The ability of this index to successfully predict environmental quality was proved with random samples.
尝试采用基于红沼泽螯虾(克氏原螯虾)重金属浓度的多变量方法,对阿兹纳科莱尔地区的水质进行评估。在来自11个不同站点的螯虾中检测到了四种重金属(铜(Cu)、锌(Zn)、镉(Cd)和铅(Pb))的痕量水平。主成分分析(PCA)突出了采样站点之间的污染梯度。聚类分析(CA)区分出三组站点。判别分析也区分出三组。利用第一判别函数的组质心设计了一个根据螯虾来源而变化的指数。建议将这些标准化值用作水质指数。通过随机样本证明了该指数成功预测环境质量的能力。