The influence of seasonal and taxonomic factors on the ordination and classification of running-water sites in Great Britain and on the prediction of their macro-invertebrate communities

Authors

  • M. T. FURSE,

    Corresponding author
    1. Freshwater Biological Association. River Laboratory, East Stoke, Wareham, DorsetInstitute of Terrestrial Ecology, Bangor Research Station, Bangor, Gwynedd
      Mr M. T. Furse, Freshwater Biological Association, River Laboratory, East Stoke, Wareham, Dorset BH20 6BB.
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  • D. MOSS,

    1. Institute of Terrestrial Ecology, Bangor Research Station, Bangor, Gwynedd
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  • J. F. WRIGHT,

    1. Freshwater Biological Association. River Laboratory, East Stoke, Wareham, DorsetInstitute of Terrestrial Ecology, Bangor Research Station, Bangor, Gwynedd
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  • P. D. ARMITAGE

    1. Freshwater Biological Association. River Laboratory, East Stoke, Wareham, DorsetInstitute of Terrestrial Ecology, Bangor Research Station, Bangor, Gwynedd
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Mr M. T. Furse, Freshwater Biological Association, River Laboratory, East Stoke, Wareham, Dorset BH20 6BB.

Abstract

SUMMARY. 1. Macro-invertebrate samples were collected from 268 running-water sites in Great Britain in each of three seasons (spring, summer and autumn). A combined seasons’treatment was generated by amalgamating the individual seasons’data. These four seasonal options were each subjected to four distinct taxonomic analyses differing in level of identification and whether the data were quantitative or qualitative. Thus sixteen data-sets were available for analysis. Environmental data on physical and chemical variables, macrophyte cover and date of sampling were also recorded for each site.

2. All sixteen data-sets were ordinated by detrended correspondence analysis and classified by two-way indicator species analysis. There were strong correlations between the sixteen ordinations and significant concordance between classifications.

3. The relationships between ordination scores and single environmental variables were investigated. Muhiple discriminant analysis was used to fit environmental data to eight selected classifications covering the full range of seasonal and taxonomic treatments. The environmental variables most useful in distinguishing between rivers were substratum characteristics, alkalinity and total oxidized nitrogen. Within-river differences were often highly correlated with discharge, distance from source, width and depth. Slope and altitude contributed strongly to both between-river and within-river distinctions.

4. Between-site variation (beta diversity), eigenvalues of ordination, the reliability of classifications, the proportion of sites correctly assigned to their biological group using environmental data and the standardized similarity between observed and predicted fauna were all higher when identifications were taken to species level, rather than one of three family treatments. Qualitative data on a reduced list of families gave comparable or better results than more detailed family treatments.

5. Combined seasons’data enabled better categorization and prediction than single season's.

6. The values of the Czekanowski Index of Similarity between the observed and predicted fauna of test sites were close to realistic maximum values.

7. Recommendations are made concerning potential usages of the various classifications. The species level classification has uses in the field of conservation and in the prediction of biological response to environmental change. The family level classifications have value in developing local site inventories and in the interpretation of pollution surveillance programmes.

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