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Eukaryotic community distribution and its relationship to water physicochemical parameters in an extreme acidic environment, Rio Tinto (southwestern Spain).

ABSTRACT: The correlation between water physicochemical parameters and eukaryotic benthic composition was examined in Río Tinto. Principal component analysis showed a high inverse relationship between pH and most of the heavy metals analyzed as well as Dunaliella sp., while Chlamydomonas sp. abundance was positively related. Zn, Cu, and Ni clustered together and showed a strong inverse correlation with the diversity coefficient and most of the species analyzed. These eukaryotic communities seem to be more influenced by the presence of heavy metals than by the pH.

SUBMITTER: Aguilera A

PROVIDER: S-EPMC1538731 | biostudies-literature | 2006 Aug

REPOSITORIES: biostudies-literature

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Eukaryotic community distribution and its relationship to water physicochemical parameters in an extreme acidic environment, Rio Tinto (southwestern Spain).

Aguilera Angeles A Manrubia Susanna C SC Gómez Felipe F Rodríguez Nuria N Amils Ricardo R

Applied and environmental microbiology 20060801 8

The correlation between water physicochemical parameters and eukaryotic benthic composition was examined in Río Tinto. Principal component analysis showed a high inverse relationship between pH and most of the heavy metals analyzed as well as Dunaliella sp., while Chlamydomonas sp. abundance was positively related. Zn, Cu, and Ni clustered together and showed a strong inverse correlation with the diversity coefficient and most of the species analyzed. These eukaryotic communities seem to be more ...[more]

PMID: 16885283

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Project description:The Iberian Pyrite Belt (IPB) hosts one of the world's largest accumulations of acidic mine wastes and pit lakes. The mineralogical and textural characteristics of the IPB ores have favored the oxidation and dissolution of metallic sulfides, mainly pyrite, and the subsequent formation of acidic mining drainages. This work reports the physical properties, hydrogeochemical characteristics, and microbial diversity of two pit lakes located in the IPB. Both pit lakes are acidic and showed high concentrations of sulfate and dissolved metals. Concentrations of sulfate and heavy metals were higher in the Nuestra Señora del Carmen lake (NSC) by one order of magnitude than in the Concepción (CN) lake. The hydrochemical characteristics of NSC were typical of acid mine waters and can be compared with other acidic environments. When compared to other IPB acidic pit lakes, the superficial water of CN is more diluted than that of any of the others due, probably, to the strong influence of runoff water. Both pit lakes showed chemical and thermal stratification with well defined chemoclines. One particular characteristic of NSC is that it has developed a chemocline very close to the surface (2 m depth). Microbial community composition of the water column was analyzed by 16S and 18S rRNA gene cloning and sequencing. The microorganisms detected in NSC were characteristic of acid mine drainage (AMD), including iron oxidizing bacteria (Leptospirillum, Acidithiobacillus ferrooxidans) and facultative iron reducing bacteria and archaea (Acidithiobacillus ferrooxidans, Acidiphilium, Actinobacteria, Acidimicrobiales, Ferroplasma) detected in the bottom layer. Diversity in CN was higher than in NSC. Microorganisms known from AMD systems (Acidiphilium, Acidobacteria and Ferrovum) and microorganisms never reported from AMD systems were identified. Taking into consideration the hydrochemical characteristics of these pit lakes and the spatial distribution of the identified microorganisms, a model explaining their geomicrobiology is advanced.

Dataset Information

Eukaryotic community distribution and its relationship to water physicochemical parameters in an extreme acidic environment, Rio Tinto (southwestern Spain).

Publications

Eukaryotic community distribution and its relationship to water physicochemical parameters in an extreme acidic environment, Rio Tinto (southwestern Spain).

Similar Datasets

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