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Fish assemblages as influenced by environmental factors in streams in protected areas of the Czech Republic
Author(s) -
Humpl M.,
Pivnička K.
Publication year - 2006
Publication title -
ecology of freshwater fish
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.667
H-Index - 55
eISSN - 1600-0633
pISSN - 0906-6691
DOI - 10.1111/j.1600-0633.2006.00126.x
Subject(s) - detrended correspondence analysis , canonical correspondence analysis , streams , relative species abundance , abundance (ecology) , ordination , ecology , habitat , gradient analysis , correspondence analysis , environmental change , environmental science , environmental gradient , canonical correlation , biology , climate change , statistics , computer network , mathematics , computer science
– Three streams of comparable size located in different landscape‐protected areas were selected for studying the effect of environmental factors on fish assemblages using indirect (detrended correspondence analysis, DCA) and direct (canonical correspondence analysis, CCA) gradient analysis. DCA of species showed well a gradient of assemblage changes in the longitudinal profile. DCA of sites stressed the variability between the fish assemblages of the three streams. This pattern was then confirmed by the highly significant between‐stream CCA. In the within‐site CCA, environmental factors explained 50.7% variability for presence–absence data and 58.3% for the relative abundance data. The analysis revealed that number of ponds and land use are the most influential factors of the strongest environmental gradient. However, in the partial CCAs, factor substratum type explained the largest proportion of the variability affecting fish in their habitat choice. Generally, presence–absence and relative abundance data of fish gave similar results in both DCA and CCA analyses; the same environmental factors proved to be important in both data type analyses. The environmental factors explain more variability than the regional (between‐stream) one. The total proportion of variability explained by the presence–absence data analysis was 71.9% and in the relative abundance analysis even 80.8%. The environmental factors measured during the field survey explain 2.1‐ and 3.4‐times more assemblages’ variability than factors measured from a hydrological map.