Pre-spawning habitat selection of subarctic brown trout (Salmo trutta L.) in the river Vindelälven, Sweden
Habitat selection of migratory brown trout at the upper reaches of River Vindelälven, was studied in September during the pre-spawning period. The fish migrate from down- or upriver lakes for spawning in the river and data was collected by habitat mapping and radio-telemetry. Habitat selection of fi...
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| Formato: | Second cycle, A1E |
| Lenguaje: | sueco Inglés |
| Publicado: |
2011
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| Acceso en línea: | https://stud.epsilon.slu.se/2423/ |
| Sumario: | Habitat selection of migratory brown trout at the upper reaches of River Vindelälven, was
studied in September during the pre-spawning period. The fish migrate from down- or
upriver lakes for spawning in the river and data was collected by habitat mapping and
radio-telemetry. Habitat selection of fish was analysed with preference curves and
statistical modelling, using the physical variables; depth, stream velocity and streambed
substrate. Preference curves were derived by comparing fish habitat use with their nearby
available environment while the statistical modelling aimed to answer three main questions.
1) Do the trout have a specific preference of depth, water velocity and streambed substrate?
2) Is there any difference in habitat selection between sexes? 3) Is there a shift in habitat
selection over time? The preference curves indicated that trout favored water depths of 1-2
m, velocity compositions characterized as glides (c. 0.2-0.4 m s-1), both fine (0.02-2 mm)
and large (>200 mm) substrate compositions. The overall habitat selection of fish was
significantly influenced by all three investigated physical variables. Stream velocity was the
only factor statistically segregating females and males in habitat selection, where males
used higher velocity areas. No shifts in habitat selection over the one month study period
were found. The complexity of streams and correlations between variables often results in
difficulties to evaluate fish habitat preferences and consequently future challenges lies in
the development of models accounting for a wider range of abiotic and biotic factors.
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