Semester

Fall

Date of Graduation

2006

Document Type

Thesis

Degree Type

MS

College

Davis College of Agriculture, Natural Resources and Design

Department

Wildlife and Fisheries Resources

Committee Chair

Stuart A. Welsh.

Abstract

Crystallaria asprella spp. (Elk River crystal darter) is documented only in Elk River, West Virginia. Little life history detail is known about this lotic, benthic-dependent species. Previous studies have led to a very basic understanding of the use of depth, flow and substrate of the crystal darter (Crystallaria asprella), and less is known about the Elk River crystal darter. Due to substrate-specificity in crystal darters (which reportedly bury in sand), a study concerning benthic stream habitat modeling was undertaken. Substrate and depth modeling using >5% of an area sampled at a resolution of 0.093 m2 square spatial data in a Geographic Information System (GIS) was theorized possible. Representation of actual substrate using 2268 0.093 m2 data cells with UTM coordinates was created in ESRI ArcMap version 9.1. Each cell signified the dominant substrate type found in that area. We selected points representing 5% and 2.5% percent of the site area for both depth and substrate and natural neighbor interpolations were run on these points. The actual values of depth and substrate were compared with predicted values to determine accuracy of interpolated data. The 5% interpolations were more accurate for both depth and substrate than 2.5% sampling results. The 2.5% interpolations achieved accuracy up to 92% of actual values and interpolations based on 5% within 5% of actual when comparing area of substrate predicted. Depth predictions based on 2.5% attained accuracy from 49% to 92% when applied to threshold values while 5% percent interpolations illustrated accuracy levels ranged from 57% to 95% for the same thresholds. Our findings demonstrate the use of minimal amounts of fine-scale data of substrate and depth for interpolation of habitat in large areas of a stream channel. This approach allows time and cost saving options for sufficiently accurate microhabitat scale habitat assessments of large sections of rivers, and provides functional maps to aid habitat-based fisheries management.

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