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The influence of stream invertebrate composition at neighbouring sites on local assemblage composition
Authors:R. A. SANDERSON  M. D. EYRE   S. P. RUSHTON
Affiliation:Institute for Research on Environment and Sustainability, University of Newcastle, Newcastle upon Tyne, U.K.
Abstract:1. The composition of freshwater invertebrate assemblages at a location is determined by a range of physico‐chemical and biotic factors in the local environment, as well as larger‐scale spatial factors such as sources of recruits. We assessed the relative importance of the species composition of local neighbourhoods and proximal environmental factors on the composition of invertebrate assemblages. 2. Macroinvertebrate assemblages were sampled at 188 running‐water sites in the catchment of the River Rede, north‐east England. A total of 176 species were recorded. 3. Environmental data, in the form of 13 biotic and abiotic measurements that described stream physical structure, aquatic vegetation and water characteristics, were recorded for each site. Detrended correspondence analysis was then used to simplify nine of these stream environmental variables to create an index of stream structure. 4. The species composition of the invertebrate assemblages was related to the environmental variables, using an information theoretic approach. The impact of the species composition of neighbouring sites on each site was determined using Moran's I and autoregressive modelling techniques. 5. Species composition was primarily associated with water pH and stream structure. The importance of the species composition of neighbouring sites in determining local species assemblages differed markedly between taxa. The autoregressive component was low for Coleoptera, intermediate for Trichoptera and Plecoptera, and high for Ephemeroptera. 6. We hypothesise that the observed differences in the autoregressive component amongst these orders reflects variation in their dispersal abilities from neighbouring sites.
Keywords:information theoretic    model averaging    nearest neighbours    spatial autoregression
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