Preliminary Understanding of Complexities in Swimming Performance of Common Minnow (Cyprinidae) Taxa
DOI:
https://doi.org/10.18061/ojs.v118i2.6117Keywords:
Swimming performance, flow regime alterations, swimming performance chamber, Cyprinidae ecologyAbstract
Understanding swimming performance of native freshwater fishes has implications for ecology, conservation, and management. In particular, this type of information has practical importance for improving the understanding of fish dispersal, occurrence, migration, and invasive potential. The objective of this study was to characterize swimming performance of 2 taxa from the comparatively understudied minnow family (Cyprinidae) and test for potential drivers as a function of total length, sex, habitat, morphology, or some combination. The study assessed Spotfin Shiner (Cyprinella spiloptera; n = 66) and Bluntnose Minnow (Pimephales notatus; n = 24) populations from an ontogenic range of male and female individuals from lentic and lotic habitats in Indiana and Ohio. Akaike information criterion (AIC) model selection identified the most parsimonious linear regression model to predict swimming performance of Spotfin Shiner and Bluntnose Minnow independently. Overall, larger Spotfin Shiners were superior swimmers compared with smaller individuals. In both species, individuals having more streamlined heads and elongated caudal regions were better swimmers. Additionally, Spotfin Shiners that were collected from lotic environments were generally better swimmers than individuals from lentic environments. Models did not recover sex-specific effects in either species—or meaningful total length, or habitat effects, in Bluntnose Minnows. Overall, this study provides evidence of a complex series of swimming performance covariates when assessing or understanding performance. This has implications for aquatic population, assemblage, and community ecology as well as management and conservation efforts.
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Copyright (c) 2018 Crystal Nichols, Austin Smith, Stephen Huelsman, Cara Schemmel, Jason C. Doll, Stephen J. Jacquemin
This work is licensed under a Creative Commons Attribution 4.0 International License.