Influences of watershed urban development on habitat heterogeneity and native fish diversity in a ridge and valley stream in Southeastern Tennessee

The present study examined relationships of landscape features with instream environmental conditions and fish assemblage attributes in a third-order Ridge and Valley stream in the Chattanooga, Tennessee area. Stream water quality, habitat, and fish assemblages were sampled in May-June 2005 at seven sites (drainage areas <17 km2) in the Mountain Creek system (Tennessee River drainage). Watershed urban land use (predominantly residential) ranged from 1.62 % to 18.97 % and housing density from 49 housing units/km2 to 72 housing units/km2. Natural riparian land cover at the sites ranged from 26.9 % to 53.1 %. A total of22 species offish and 3,686 individuals was found at the seven sites. Native species richness per drainage area ranged from 0.12 species/km2 to 1.15 species/km2 at the individual sites. Species evenness ranged from 0.56 to 0.79. Index of biotic integrity ratings varied from poor to good. Watershed urban land use was negatively correlated with species richness, species evenness, variation in stream shape, and variation in current velocity. Housing density in the watershed was positively correlated with sediment depth and negatively correlated with species richness, substrate diversity, and variation in stream shape. Riparian natural cover was positively correlated with variation in current velocity. Results of this study emphasize the negative influence of watershed residential land use on stream habitat heterogeneity and native fish diversity.

Grantor dc:publisher

University of Tennessee at Chattanooga

Author dc:creator

• Cookson, Nicholas B.

Contributors dc:contributor

• Schorr, Mark
• College of Arts and Sciences

• Fish populations--Tennessee--Chattanooga
• Urban watersheds
• Fishes--Habitat

Licence

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English, eng

Identifier

LB2369.2 .C664 2006

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-2076