Date of Award

2009

Document Type

Thesis

Degree Name

Master of Environmental Studies (MES)

First Advisor

Paul Rothrock

Second Advisor

Robert Reber

Third Advisor

Mitchell Alix

Abstract

Lake macrophyte assemblages in northeast Indiana were examined to compare the ability of four aquatic macrophyte-based lake assessment techniques to detect lake quality using two independent measures of human disturbance and one measure of water quality. Study objectives were to test the relationship of the four lake assessment techniques to the three measures of human disturbance or water quality, test the relationship of the four lake assessment techniques to each other, and to determine which lake assessment technique was the most time and resource efficient. Lake vegetation was sampled using two techniques. The first was a rake-based, stratified, random sampling technique. The second was a modified relevé sampling approach with a modified Braun Blanquet Cover Abundance Scale Method. The four aquatic macrophyte-based lake assessment indices investigated were the Aquatic Macrophyte Community Index (AMCI), the Plant Index of Biotic Integrity (PIBI), the Index of Aquatic Macrophyte Community Quality (IAMCQ), and the Floristic Quality Assessment (FQA). The two measures of human disturbance compared were the Lake Qualitative Habitat Evaluation Index (L-QHEI) and the Landscape Development Intensity Index (LDI). The measure of water quality was the Indiana Trophic State Index (ITSI). Additional investigations were made comparing the difference between FQA scores that included or excluded non-native species. The use of FQA scores weighted by species frequency or relative cover also was addressed. The two FQA scores, the Floristic Quality Index (FQI) and the Mean Coefficient of Conservatism (MC), were found to have the highest correlation to all three measures of human disturbance or water quality and were deemed best at assessing lake quality. AMCI and IAMCQ scores significantly correlated to L-QHEI and ITSI scores and were able to assess lake quality in northeast Indiana lakes. PIBI scores significantly correlated to L-QHEI and LDI scores, but were low enough to suggest recalibration of this index for lakes in northeast Indiana is needed. The use of non-native species in FQA calculations did not show a clear advantage over the use of only 2 native species. Additionally, weighting MC and FQI scores by species frequency did not provide any advantages when using FQA scores based on AMCI sampling to assess lake quality. However, weighting MC and FQI scores by relative cover did improve correlations to the L-QHEI and ITSI when PIBI sampling was used. The PIBI sampling method was slightly faster than the AMCI method, but both were able to be done rapidly and resulted in similar assessments of lake quality.

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