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Cited by 1,207

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Computational Improvements Reveal Great Bacterial Diversity and High Metal Toxicity in Soil

Gans, Jason, Wolinsky, Murray, Dunbar, John·2005·Science

Abstract

The complexity of soil bacterial communities has thus far confounded effective measurement. However, with improved analytical methods, we show that the abundance distribution and total diversity can be deciphered. Reanalysis of reassociation kinetics for bacterial community DNA from pristine and metal-polluted soils showed that a power law best described the abundance distributions. More than one million distinct genomes occurred in the pristine soil, exceeding previous estimates by two orders of magnitude. Metal pollution reduced diversity more than 99.9%, revealing the highly toxic effect of metal contamination, especially for rare taxa.

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Metadata

Authors
Gans, J., Wolinsky, M., & Dunbar, J.
Venue
Science
Published
2005-08-26
Volume
309
Issue
5739
Pages
1387-1390
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2140175819
Cited by
1,207
References
17
FWCI
60.62
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Computational Improvements Reveal Great Bacterial Diversity and High Metal Toxicity in Soil. https://app.cochat.ai/papers/10.1126/science.1112665
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Gans, J., Wolinsky, M., & Dunbar, J. (2005). Computational Improvements Reveal Great Bacterial Diversity and High Metal Toxicity in Soil. Science. https://doi.org/10.1126/science.1112665

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.