Title

Barcoding of mygalomorph spiders (Araneae:Mygalomorphae) in the Pilbara bioregion of Western Australia reveals a highly diverse biota

Document Type

Conference Proceeding

Publisher

CSIRO Publishing

Faculty

Faculty of Health, Engineering and Science

School

School of Natural Sciences

RAS ID

19234

Comments

This article was originally published as: Castalanelli M.A., Teale R., Rix M.G., Kennington W.J., Harvey M.S. (2014). Barcoding of mygalomorph spiders (Araneae:Mygalomorphae) in the Pilbara bioregion of Western Australia reveals a highly diverse biota. Invertebrate Systematics. (pp. 375-385). CSIRO. Original article available here

Abstract

The Pilbara bioregion of Western Australia is an area that contains vast mineral deposits and unique ecosystems. To ensure that mineral deposits are mined with minimal impact on the natural environment, impact assessment surveys are required to determine what fauna and flora species are located within proposed development areas, in particular, by determining the distributions of short-range endemic species (SREs). One infraorder of Arachnida, the Mygalomorphae (trapdoor spiders and their kin), are frequently identified as SREs. These identifications are traditionally performed using morphological techniques; however, only males can be reliably identified to species. Furthermore, the majority of species have not been formally described and males comprise only ∼5% of specimens collected. To assess mygalomorph diversity and the distribution of species in the Pilbara, we employed a molecular barcoding approach. Sequence data from the mitochondrial DNA cytochrome c oxidase subunit I (COI) gene were obtained from 1134 specimens, and analysed using Bayesian methods. Only a fraction of the total mygalomorph fauna of the Pilbara has been documented, and using a species boundary cut-off of 9.5% sequence divergence, we report an increase in species richness of 191%. Barcoding provides a rapid, objective method to help quantify mygalomorph species identifications and their distributions, and these data, in turn, provide crucial information that regulatory authorities can use to assess the environmental impacts of large-scale developments.

DOI

10.1071/IS13058

Access Rights

Not open access

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