Potamodromous brown trout movements in the North of the Iberian Peninsula: Modelling past, present and future based on continuous fishway monitoring
Brown trout uses river flow and thermal regimens as main stimuli for initiating and maintaining behavioral reactions such as migration and spawning. Therefore, anthropogenic alterations on these factors may have strong impacts on its populations. The aim of this work is to understand these consequen...
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Veröffentlicht in: | The Science of the total environment 2018-11, Vol.640-641, p.1521-1536 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Brown trout uses river flow and thermal regimens as main stimuli for initiating and maintaining behavioral reactions such as migration and spawning. Therefore, anthropogenic alterations on these factors may have strong impacts on its populations. The aim of this work is to understand these consequences by assessing potamodromous brown trout movements in the past and present, and to model future responses. For this, brown trout movements in a fishway in the Marin River (Bidasoa basin, Northern Iberian Peninsula) have been monitored from 2008 to 2017. Random forest regression has been used to assess the influence of environmental variables on brown trout movements and to model the response under hypothetical climatic and hydrological scenarios. Results show that brown trout uses the fishway during the whole year, with more upstream movements during the spawning season. The model is able to predict accurately the timing and number of migrants. Its use under hypothetical climate change and flow regulation scenarios shows a delay in the migration time. Therefore, modelling using large time series can be a powerful tool to define management and conservation strategies and prepare compensation measures for future scenarios.
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•Anthropogenic impacts on hydrology, climate and habitat threaten freshwater fish.•Long-term study of potamodromous brown trout in its southern distribution area•Continuous fishway monitoring showed captures throughout the year.•Random forest model predicted accurately timing and quantification of migration.•Climate change and flow regulation scenarios would delay spawning migration. |
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ISSN: | 0048-9697 1879-1026 |
DOI: | 10.1016/j.scitotenv.2018.05.339 |