Macroinvertebrate abundance and proportion of trait categories in river biotopes across England and Wales
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| Natura: | Dataset Open Access |
| Lingua: | en |
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PANGAEA
2012
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| _version_ | 1867169505229144064 |
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| author | Demars, Benoit O L Kemp, Joanna L Friberg, Nikolai Usseglio-Polatera, Philippe Harper, David M |
| author_facet | Demars, Benoit O L Kemp, Joanna L Friberg, Nikolai Usseglio-Polatera, Philippe Harper, David M |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | There is a long tradition of river monitoring using macroinvertebrate communities to assess environmental quality in Europe. A promising alternative is the use of species life-history traits. Both methods, however, have relied on the time-consuming identification of taxa. River biotopes, 1-100 m**2 'habitats' with associated species assemblages, have long been seen as a useful and meaningful way of linking the ecology of macroinvertebrates and river hydro-morphology and can be used to assess hydro-morphological degradation in rivers. Taxonomic differences, however, between different rivers had prevented a general test of this concept until now. The species trait approach may overcome this obstacle across broad geographical areas, using biotopes as the hydro-morphological units which have characteristic species trait assemblages. We collected macroinvertebrate data from 512 discrete patches, comprising 13 river biotopes, from seven rivers in England and Wales. The aim was to test whether river biotopes were better predictors of macroinvertebrate trait profiles than taxonomic composition (genera, families, orders) in rivers, independently of the phylogenetic effects and catchment scale characteristics (i.e. hydrology, geography and land cover). We also tested whether species richness and diversity were better related to biotopes than to rivers. River biotopes explained 40% of the variance in macroinvertebrate trait profiles across the rivers, largely independently of catchment characteristics. There was a strong phylogenetic signature, however. River biotopes were about 50% better at predicting macroinvertebrate trait profiles than taxonomic composition across rivers, no matter which taxonomic resolution was used. River biotopes were better than river identity at explaining the variability in taxonomic richness and diversity (40% and <=10%, respectively). Detailed trait-biotope associations agreed with independent a priori predictions relating trait categories to near river bed flows. Hence, species traits provided a much needed mechanistic understanding and predictive ability across a broad geographical area. We show that integration of the multiple biological trait approach with river biotopes at the interface between ecology and hydro-morphology provides a wealth of new information and potential applications for river science and management. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_777728 |
| institution | PANGAEA |
| language | en |
| publishDate | 2012 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Macroinvertebrate abundance and proportion of trait categories in river biotopes across England and Wales Demars, Benoit O L Kemp, Joanna L Friberg, Nikolai Usseglio-Polatera, Philippe Harper, David M Avon_River; Dove_River; England; RIVER; Sampling river; Smite_River; Swale_River; Teifi_River; Wales; Welland_River; Wissey_River There is a long tradition of river monitoring using macroinvertebrate communities to assess environmental quality in Europe. A promising alternative is the use of species life-history traits. Both methods, however, have relied on the time-consuming identification of taxa. River biotopes, 1-100 m**2 'habitats' with associated species assemblages, have long been seen as a useful and meaningful way of linking the ecology of macroinvertebrates and river hydro-morphology and can be used to assess hydro-morphological degradation in rivers. Taxonomic differences, however, between different rivers had prevented a general test of this concept until now. The species trait approach may overcome this obstacle across broad geographical areas, using biotopes as the hydro-morphological units which have characteristic species trait assemblages. We collected macroinvertebrate data from 512 discrete patches, comprising 13 river biotopes, from seven rivers in England and Wales. The aim was to test whether river biotopes were better predictors of macroinvertebrate trait profiles than taxonomic composition (genera, families, orders) in rivers, independently of the phylogenetic effects and catchment scale characteristics (i.e. hydrology, geography and land cover). We also tested whether species richness and diversity were better related to biotopes than to rivers. River biotopes explained 40% of the variance in macroinvertebrate trait profiles across the rivers, largely independently of catchment characteristics. There was a strong phylogenetic signature, however. River biotopes were about 50% better at predicting macroinvertebrate trait profiles than taxonomic composition across rivers, no matter which taxonomic resolution was used. River biotopes were better than river identity at explaining the variability in taxonomic richness and diversity (40% and <=10%, respectively). Detailed trait-biotope associations agreed with independent a priori predictions relating trait categories to near river bed flows. Hence, species traits provided a much needed mechanistic understanding and predictive ability across a broad geographical area. We show that integration of the multiple biological trait approach with river biotopes at the interface between ecology and hydro-morphology provides a wealth of new information and potential applications for river science and management. |
| title | Macroinvertebrate abundance and proportion of trait categories in river biotopes across England and Wales |
| topic | Avon_River; Dove_River; England; RIVER; Sampling river; Smite_River; Swale_River; Teifi_River; Wales; Welland_River; Wissey_River |
| url | https://doi.org/10.1594/PANGAEA.777728 |