ISSN:
1573-5133
Keywords:
Distribution
;
Multivariate analysis
;
Binary data
;
Principal components analysis
;
Cluster analysis
;
Canonical discriminant analysis
;
Discriminant function analysis
Source:
Springer Online Journal Archives 1860-2000
Topics:
Biology
Notes:
Synopsis Principal components analysis was performed on fish presence/absence data for 39 common fish species from 410 stream sites in Kansas. The analysis confirmed ten ecologically meaningful fish assemblages, based on species associations. Factor scores based on these assemblages were then clustered into six geographic areas or fish ecoregions. Canonical discriminant analysis identified environmental variables that distinguished the derived fish ecoregions. Mean annual runoff, mean annual growing season, and discharge appear most important. Mean width, mean depth, chloride concentration, water temperature, substrate type, gradient, and percent of pool habitat were less important. Correspondence exists between these fish ecoregions and the patterns of physiographic regions, river basins, geology, soil, and potential natural vegetation in Kansas. The multivariate statistical approach used to classify fish ecoregions should have considerable potential value for fish assessment and management purposes in areas other than the state of Kansas.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00001493
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