# River-Wide Habitat Availability for Fish Habitat Guilds: Implications for In-Stream Flow Protection
## 3 Results
The habitat generalist and run guilds were the only two guilds that exhibited a continuous increase in CA available as discharges increased in segment 3. The slackwater guild had the least amount of available habitat of all the guilds in segment 3 with 13% CA at 0.16 cfsm. Increases in habitat availability leveled off with increasing discharge at approximately 0.15 cfsm, 0.13 cfsm, and 0.07 cfsm for segments 1, 2, and 3, respectively. The relationship between the relative proportions of fish habitat guilds in the existing fish community and the modeled habitat availability suggests habitat and guild composition were generally in similar proportion with a few exceptions (Table 3). For instance, habitat for the lobate margin guild appeared underrepresented in segment 1 (Table 3). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Guild** & **Presence Model** & **Estimate** & **Abundance Model** & **ESTIMATE** \\ \hline \multirow{8}{*}{Lobate Margin} & Area under ROC & 77\% & Area under ROC & 54\% \\  & Vegetation (overhanging) & \(-\)0.85 (0.32) & Velocity 75–90 cm s\({}^{-1}\) & 0.51 (1.13) \\  & Woody Debris & 0.82 (0.43) & Velocity 90–105 cm s\({}^{-1}\) & \(-\)0.96 (1.44) \\  & Shallow Margin & 0.79 (0.25) & & \\  & Eroded & \(-\)0.56 (0.28) & & \\  & Fast Run & 2.68 (1.51) & & \\  & Run & 1.45 (0.46) & & \\  & Depth \(>\)125 cm & 5.79 (5.10) & & \\  & Velocity 15–30 cm s\({}^{-1}\) & 4.35 (1.36) & & \\  & Microlithal & \(-\)5.2 (2.21) & & \\  & Area under ROC & 68\% & Area under ROC & 66\% \\  & Woody Debris & 0.88 (0.42) & Velocity 75–90 cm s\({}^{-1}\) & 3.33 (1.78) \\  & Eroded & 0.52 (0.25) & Velocity 90–105 cm s\({}^{-1}\) & \(-\)6.01 (2.68) \\ Run & Depth 75–100 cm & \(-\)2.9 (2.2) & Gigalithal & 6.01 (4.11) \\  & Depth \(>\)125 cm & \(-\)23.2 (13.10) & & \\  & Velocity 15–30 cm s\({}^{-1}\) & \(-\)1.77 (1.10) & & \\  & Microlithal & \(-\)5.18 (1.90) & & \\  & Area under ROC & 81\% & Area under ROC & 86\% \\  & Eroded & \(-\)0.63 (0.34) & Vegetation (submerged) & 4.72 (3.09) \\  & Stable & \(-\)0.43 (0.25) & Shading & \(-\)0.76 (0.85) \\ Riffle & Main Lobe & \(-\)1.21 (0.52) & Woody Debris & 2.74 (1.47) \\  & Depth 50–75 cm & 3.22 (1.05) & Stable & 1.03 (0.66) \\  & Velocity 90–105 cm s\({}^{-1}\) & \(-\)4.22 (2.13) & Secondary Lobe & \(-\)4.21 (1.54) \\  & Akal & 6.91 (2.09) & Sidearm & \(-\)8.6 (2.89)) \\  & Mesolithal & 4.37 (1.46) & Velocity 30–45 cm s\({}^{-1}\) & 15.03 (4.66) \\  & Area under ROC & 79\% & Area under ROC & 74\% \\  & Depth 25–50 cm & 3.57 (1.32) & Shallow Margin & 1.64 (0.95) \\  & Depth 50–75 cm & 3.81 (1.18) & Run & \(-\)1.88 (1.11) \\  & Velocity 60–75 cm s\({}^{-1}\) & \(-\)6.4 (1.90) & & \\  & Akal & 2.27 (1.93) & & \\  & Microlithal & \(-\)8.4 (3.37) & & \\  & Area under ROC & 78\% & Area under ROC & 74\% \\  & Vegetation (submerged) & 1.68 (0.52) & Shallow Margin & \(-\)0.89 (0.38) \\  & Woody Debris & 0.74 (0.47) & Depth 50–75 cm s\({}^{-1}\) & 2.69 (1.28) \\  & Eroded & 0.64 (0.28) & Velocity 60–75 cm s\({}^{-1}\) & \(-\)2.42 (1.49) \\  & Stable & \(-\)0.55 (0.23) & Gigalithal & \(-\)6.08 (4.49) \\ Habitat Generalist & Glide & 2.24 (0.78) & & \\  & Depth 50–75 cm & 2.97 (1.07) & & \\  & Depth \(>\) 125 cm & \(-\)22.38 (13.51) & & \\  & Velocity 15–30 cm s\({}^{-1}\) & 3.46 (1.38) & & \\  & Velocity 45–60 cm s\({}^{-1}\) & \(-\)2.37 (1.10) & & \\  & Macrolithal & 6.73 (3.36) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Multiple logistic regression model results for each habitat guild including area under receiver operator curves (ROC) and beta values of habitat characteristics associated with presence and abundance models to determine suitability and optimal habitat conditions in the Niobrara River. Values in parentheses indicate standard error. Figure 2: The percentage of hydromorphologic units (HMUs) estimated at non-suitable, optimal, or suitable for each fish guild across river segments of the Niobrara River using predictions from multiple logistic regression models.