Degree Name

Master of Science (MS)

Semester of Degree Completion

1992

Thesis Director

Clay L. Pierce

Abstract

Growth is an important component in the ecology and management of stream fisheries. Growth of stream fish has received relatively little attention and relationships with habitat variables are largely unknown. We quantified growth of juvenile and adult size classes of bluegill (Lepomis macrochirus), common carp (Cyprinus carpio), channel catfish (Ictalurus punctatus), largemouth bass (Micropterus salmoides), rock bass (Ambloplites rupestris), and smallmouth bass (M. dolomieui) from Illinois streams. Growth rates for each species fell within ranges previously reported for lakes and rivers in the United States although they averaged slightly lower. Within each species except channel catfish, growth of juvenile and adult size classes were uncorrelated with one another. This suggests ontogenetic shifts occurred in diet or habitat use, similar to those reported for lentic populations of many of these species. The influence of habitat on abundance, biomass, and production is known for many species, yet relationships between habitat features and growth rates are largely unknown. We related 12 biological, 23 physical, and 10 chemical macrohabitat variables to growth of each species-size class. Five variables were most often correlated with growth: number of sunfish species, average depth, percent stream area shaded, percent sand substrate, and a water quality index. These empirical relationships with macrohabitat variables may enhance the efficiency of stream fisheries management by providing an inexpensive, a priori basis for directing management efforts. As an initial effort, we have developed multiple regression models of growth based on our 45 macrohabitat variables. These models were relatively precise, describing 20 to 100 percent of growth variation in nine species-size class combinations among several sites. Although these models require testing against independent data for general applicability, they demonstrate the potential for predicting growth of stream fish based on commonly collected, and often readily available habitat data.

Download

Share

COinS