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1.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

2.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

3.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

4.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

5.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

6.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

7.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

8.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

9.

Variable importance plots for random forest regressions predicting abundances of Cyrtonaias tampicoensis , Lampsilis bracteata , and Utterbackia imbecillis using modeled hydraulic...

1.

Additional methodology for field data collection and HEC-RAS model preparation.

2.

Additional methodology for field data collection and HEC-RAS model preparation.

3.

Additional methodology for field data collection and HEC-RAS model preparation.

4.

Additional methodology for field data collection and HEC-RAS model preparation.

5.

Additional methodology for field data collection and HEC-RAS model preparation.

6.

Additional methodology for field data collection and HEC-RAS model preparation.

7.

Additional methodology for field data collection and HEC-RAS model preparation.

8.

Additional methodology for field data collection and HEC-RAS model preparation.

9.

Additional methodology for field data collection and HEC-RAS model preparation.

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1.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

2.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

3.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

4.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

5.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

6.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

7.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

8.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

9.

Data flow diagram describing inputs and outputs of data analysis, including the data used to create a two-dimensional HEC-RAS model to simulate flow conditions in a segment of the...

1.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

2.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

3.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

4.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

5.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

6.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

7.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

8.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

9.

Habitat preferences of freshwater mussels [67], as shown by percent of available habitat sampled ( i . e ., pool, riffle, run) compared to percent of the total mussel abundance fou...

1.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

2.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

3.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

4.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

5.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

6.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

7.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

8.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

9.

Getis Ord Gi* hotspots of species richness, Shannon-Wiener diversity, and Simpson’s diversity within the study segment in the San Saba River, TX.

1.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

2.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

3.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

4.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

5.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

6.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

7.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

8.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

9.

Results of Wilcoxon tests comparing average hydraulic conditions during low (0.42 m 3 s -1 ), moderate (5.32 m 3 s -1 ), moderate-high, (32.28 m 3 s -1 ), and high (361.89 m 3 s -1...

1.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

2.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

3.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

4.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

5.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

6.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

7.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

8.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

9.

Variable importance plots for random forest classification examining the response of freshwater mussel presence to modeled hydraulic variables during a low (0.42 m3s-1), moderate (...

1.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

2.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

3.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

4.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

5.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

6.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

7.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

8.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.

9.

Studies examining the impacts of hydraulic conditions on freshwater mussels at different flows in variable environments at multiple spatial scales.