The Contribution of the Barcode of Life Initiative to the Discovery and Monitoring of Biodiversity

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Abstract

Biodiversity has been fundamental to sustain the human population, which is currently estimated at nearly 7 billion people. However, less than one fifth of the extant species are known to science, and among those only a minuscule proportion was described in any biological detail. This huge gap in our knowledge of biodiversity is in deep contrast with the extraordinary level of scientific and technological development that modern society has reached. How can we take advantage of the technology currently available to detect the putative high rates of biodiversity loss? How can we efficiently manage our ecosystems and biological communities if we do not even have a comprehensive inventory of biodiversity to start with?

The Barcode of Life Initiative (BOLI) aims to contribute to resolve these questions by building a new system for species identification using DNA sequences from standardized regions of the genome—DNA barcodes. Once fully implemented, this novel system will greatly facilitate the access to taxonomic knowledge globally and revolutionize our ability to rapidly and rigorously identify life forms in a multitude of scenarios.

We anticipate major contributions of DNA barcodes for biodiversity research when integrated with other ongoing technological, organizational and conceptual developments. This can be illustrated by the growing capacity to monitor biodiversity, which has lead to the recognition of cryptic species, their prevalence and distribution patterns. The coupling of DNA barcoding with next generation sequencing will enable to capture the structure and dynamics of complex communities with unprecedented degree of detail. This can catalyze the rate of species discovery globally and contribute to improve the way in which we conserve biodiversity.

Keywords

Internal Transcribe Spacer Arbuscular Mycorrhizal Fungus Invasive Species Cryptic Species Global Biodiversity Information Facility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

This is a contribution from F.O. Costa in the scope of grants PTDC/MAR/69892/2006 from “Fundação para a Ciência e a Tecnologia”, and a European Commission’s Reintegration Grant (ERG-224890). P.M. Antunes thanks the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ontario Ministry of Natural Resources (OMNR) for financial support. We thank the Consortium for the Barcode of Life for permission to reproduce Fig. 4.1, and John Wiley and Sons publishers for granting permission to reproduce Fig. 4.2. Special thanks to Luisa Borges and Ana Cunha for comments on an early draft of the manuscript.

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© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Departamento de BiologiaUniversidade do Minho, CBMA – Centro de Biologia Molecular e AmbientalBragaPortugal
  2. 2.Department of BiologyAlgoma UniversitySault Ste. MarieCanada

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