Salmo trutta, (Avila et al., 2018) (Avila, 2018)
publication ID |
https://doi.org/ 10.1111/jfb.14918 |
DOI |
https://doi.org/10.5281/zenodo.10945232 |
persistent identifier |
https://treatment.plazi.org/id/992587DC-FF86-FFFB-2E76-0F9EE09F74D6 |
treatment provided by |
Felipe |
scientific name |
Salmo trutta |
status |
|
3.3 | S. trutta View in CoL fry habitat associations
A quadratic relationship for D 50 appeared in the top four models of the S. trutta single pass count analysis and had the highest cumulative weight of any variable in the model set (cumulative AIC c weight = 0.81). The number of S. trutta fry per site was maximized at a D 50 of 151 mm and was ≥ 10 per site (658 fry per km) between a D 50 of 96 and 206 mm ( Figure 2 View FIGURE 2 ). Temperature (cumulative AIC c weight = 0.35) appeared in the top model, but the next highest model in which it was included had a ΔAIC c of 4.85. Depth and velocity (cumulative AIC c weights of 0.11), linear relationships of which were included in models with ΔAIC c of 2.29 and 2.39, respectively, appeared to have lesser effects on S. trutta fry counts ( Figure 2 View FIGURE 2 ). Upon further examination of fry sites with a D 50 between 96 and 206 mm containing ≥ 10 S. trutta fry per site (n = 13), counts were highest when depth averaged 0.18 (±0.03) m and velocity averaged 0.20 (±0.09) m s 1. Sites meeting these average depth and velocity criteria contained 2.2 and 1.5 times more S. trutta fry than stocked O. mykiss fry, respectively.
S. trutta abundance was similarly predicted by a quadratic relationship for D 50, which appeared in all but the second model of the set, and had a cumulative AIC c weight of 0.90. Abundance was highest in the site with a D 50 of 120 mm, within the optimum range obtained from the S. trutta fry count data. Presence of wood (cumulative AIC c weight = 0.99) was the only other variable to have an effect, appearing in the first two models. S. trutta abundance was lowest in one of the four sites that contained wood ( Figure 3 View FIGURE 3 ).
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