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Incidence of deformities and variation in shape of mentum and wing of Chironomus columbiensis (Diptera, Chironomidae) as tools to assess aquatic contamination

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  • Milton Leoncio Montaño-Campaz
  • Lucimar Gomes-Dias
  • Beatriz Edilma Toro Restrepo
  • Víctor Hugo García-Merchán

Abstract

Constantly, aquatic ecosystems are under pressure by complex mixtures of contaminants whose effects are not always easy to evaluate. Due to this, organisms are sought in which early warning signs may be detected upon the presence of potentially toxic xenobiotic substances. Thereby, the study evaluated the incidence of deformities and other morphometric variations in the mentum and wing of Chironomus columbiensis exposed to water from some of the Colombian Andes affected by mining, agriculture, and cattle raising. Populations of C. columbiensis were subjected throughout their life cycle (24 days) for two generations (F1 and F2). Five treatments were carried out in controlled laboratory conditions (water from the site without impact, site of mining mercury, mining mercury + cyanide, cattle raising, and agriculture) and the respective control (reconstituted water). Thereafter, the percentage of deformities in the mentum was calculated, and for the morphometric analysis 29 landmarks were digitized for the mentum and 12 for the wing. As a result, four types of deformities were registered in the C. columbiensis mentum, like absence of teeth, increased number of teeth, fusion and space between teeth, none of them detected in the individuals from the control. Additionally, the highest incidence of deformity in F1 occurred in the treatment of mining mercury, while for F2 this took place in the treatments of mining mercury + cyanide, cattle raising and agriculture. Differences were also found with respect to the morphometric variations of the mentum and wing of C. columbiensis among the control and the treatments with water from the creeks intervened. The treatments of mining mercury + cyanide and agriculture had the highest morphological variation in the mentum and wing of C. columbiensis. The results suggest that the anthropogenic impacts evaluated generate alterations in the oral apparatus of the larval state of C. columbiensis and in the adult state provoke alterations in the wing shape (increased width and reduced basal area). These deformities may be related to multiple stress factors, among them the xenobiotics metabolized by the organisms under conditions of environmental contamination.

Suggested Citation

  • Milton Leoncio Montaño-Campaz & Lucimar Gomes-Dias & Beatriz Edilma Toro Restrepo & Víctor Hugo García-Merchán, 2019. "Incidence of deformities and variation in shape of mentum and wing of Chironomus columbiensis (Diptera, Chironomidae) as tools to assess aquatic contamination," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-20, January.
  • Handle: RePEc:plo:pone00:0210348
    DOI: 10.1371/journal.pone.0210348
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    References listed on IDEAS

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    1. J. Gower, 1975. "Generalized procrustes analysis," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 33-51, March.
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