Article: The use of coarser data is an effective strategy for biological assessments
Hydrobiologia. 2015 Mar., v. 747, no. 1
2015
Abstract: Ecological studies are usually based on species abundance data per sample. As a consequence, the research can be time-consuming and require a significant amount of financial resources to overcome uncertainties in taxonomic identifications and estimations ...
Abstract | Ecological studies are usually based on species abundance data per sample. As a consequence, the research can be time-consuming and require a significant amount of financial resources to overcome uncertainties in taxonomic identifications and estimations of relative abundances. We assessed the use of genus-level data as a surrogate for species-level data in studies attempting to describe the beta-diversity patterns of several aquatic communities. Furthermore, we investigated whether presence–absence data is sufficient to describe ecological patterns and whether the spatial variation of rare species can also be described by genus-level data. We used data from five biological aquatic groups sampled over periods of up to 2 years in different sites of the Upper Paraná River floodplain. We found strong evidence that beta-diversity patterns in species-level data can be successfully described using genus-level and presence–absence data in all biological groups, although efficacy of using genus-level data as a surrogate for species-level may depend on the species:genus ratio. Moreover, communities with both taxonomic resolutions had similar responses to environmental variation. Our results indicate ecological studies in floodplains with different biological groups can benefit from strategy based on genus-level or presence–absence data to reduce cost and time. |
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Keywords | aquatic communities ; floodplains ; rare species ; rivers ; species diversity |
Language | English |
Dates of publication | 2015-03 |
Size | p. 83-95. |
Publishing place | Springer-Verlag |
Document type | Article |
ZDB-ID | 214428-1 |
ISSN | 1573-5117 ; 0018-8158 |
ISSN (online) | 1573-5117 |
ISSN | 0018-8158 |
DOI | 10.1007/s10750-014-2128-6 |
Database | NAL-Catalogue (AGRICOLA) |
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