Taxonomic and numerical resolutions of nepomorpha (insecta: heteroptera) in cerrado streams.

Nubia França Da Silva Giehl,Helena Soares Ramos Cabette,Karina Dias-Silva,Leandro Juen,Joana Darc Batista,Fabio S Nascimento

doi:10.1371/journal.pone.0103623

Nubia França Da Silva Giehl, Helena Soares Ramos Cabette + Show 4 more

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https://doi.org/10.1371/journal.pone.0103623

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Abstract

Transformations of natural landscapes and their biodiversity have become increasingly dramatic and intense, creating a demand for rapid and inexpensive methods to assess and monitor ecosystems, especially the most vulnerable ones, such as aquatic systems. The speed with which surveys can collect, identify, and describe ecological patterns is much slower than that of the loss of biodiversity. Thus, there is a tendency for higher-level taxonomic identification to be used, a practice that is justified by factors such as the cost-benefit ratio, and the lack of taxonomists and reliable information on species distributions and diversity. However, most of these studies do not evaluate the degree of representativeness obtained by different taxonomic resolutions. Given this demand, the present study aims to investigate the congruence between species-level and genus-level data for the infraorder Nepomorpha, based on taxonomic and numerical resolutions. We collected specimens of aquatic Nepomorpha from five streams of first to fourth order of magnitude in the Pindaíba River Basin in the Cerrado of the state of Mato Grosso, Brazil, totaling 20 sites. A principal coordinates analysis (PCoA) applied to the data indicated that species-level and genus-level abundances were relatively similar (>80% similarity), although this similarity was reduced when compared with the presence/absence of genera (R = 0.77). The presence/absence ordinations of species and genera were similar to those recorded for their abundances (R = 0.95 and R = 0.74, respectively). The results indicate that analyses at the genus level may be used instead of species, given a loss of information of 11 to 19%, although congruence is higher when using abundance data instead of presence/absence. This analysis confirms that the use of the genus level data is a safe shortcut for environmental monitoring studies, although this approach must be treated with caution when the objectives include conservation actions, and faunal complementarity and/or inventories.

Highlights

Human activities generate serious impacts on natural aquatic environments, especially by replacing the vegetation with plantations and pastures [1], constructing dams and reservoirs, and diverting the natural course of waterways [2,3]
Higher taxonomic levels have been analyzed, and this has been justified based on arguments such as an effective cost-benefit ratio, the time needed for processing samples [8], limited resources [12], a lack of taxonomists and/or data on the ranges and ecological requirements of the species [11,13]
This study aims to investigate the level of congruence in the data matrices of Nepomorpha genera versus species, by applying taxonomic and numerical resolutions and analyzing whether congruence remains similar when analyzing altered and preserved sites separately, in order to answer to the following questions: a) how much information is lost when the analyses are conducted with a genus-level data matrix in comparison with a species-level one; and b) whether the ordinating patterns obtained from the incidence of genera and/or species are similar to those obtained from abundance data

Summary

Introduction

Human activities generate serious impacts on natural aquatic environments, especially by replacing the vegetation with plantations and pastures [1], constructing dams and reservoirs, and diverting the natural course of waterways [2,3]. These processes, either alone or in synergy, result in decreased habitat heterogeneity, increased input of sediments into the channel, and the loss of aquatic biodiversity [4,5]. Higher taxonomic levels have been analyzed, and this has been justified based on arguments such as an effective cost-benefit ratio, the time needed for processing samples [8], limited resources [12], a lack of taxonomists and/or data on the ranges and ecological requirements of the species [11,13]

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