Natural variability of enzymatic biomarkers in freshwater invertebrates
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- 作者：Alessio Ippolito ; Roberto Giacchini…
- 关键词：Biomarker ; Enzymes ; Natural variability ; Freshwater invertebrates ; Biomonitoring ; Ecological risk assessment
- 刊名：Environmental Science and Pollution Research
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：24
- 期：1
- 页码：732-742
- 全文大小：
- 刊物类别：Earth and Environmental Science
- 刊物主题：Environment, general; Environmental Chemistry; Ecotoxicology; Environmental Health; Atmospheric Protection/Air Quality Control/Air Pollution; Waste Water Technology / Water Pollution Control / Water M
- 出版者：Springer Berlin Heidelberg
- ISSN：1614-7499
- 卷排序：24
文摘
Biomarkers have been widely employed in ecotoxicology as early warning indicators of exposure to toxicants. Very often, they are used to compare reference and polluted sites, or to analyse time trends. However, very few studies focus on the natural variability range of biomarkers in the environment, which is pivotal to understand if the detected differences are actually determined by any adverse effects due to pollution. This work assesses the natural spatio-temporal variability of some enzymatic levels, frequently used as biomarkers, in freshwater benthic invertebrates. The influence of some environmental parameters on the enzymatic levels was also evaluated. Three families of insect larvae (Perlidae, Baetidae, and Heptageniidae) were sampled in three pristine streams and in eight different dates. Four enzymes (acetylcholinesterase, glutathione-S-transferase, alkaline phosphatase, and catalase) were measured. The natural variability of enzymatic levels was often significant in all considered species across both space and time. The observed pattern was poorly explained by the monitored environmental parameters. The results of this work show that great care should be paid when interpreting monitoring data in which biomarker levels are measured and compared among sites or dates. Presuming that measured differences are due to anthropogenic factors can be misleading, when other potentially influencing factors have not been accounted for.