Assessment of restocking as a strategy for rehabilitating a native population of brown trout Salmo trutta L. in a fast-flowing mountain stream in the northern French Alps

An attempt was made to extend the area of distribution of a native population of brown trout Salmo trutta belonging to a Mediterranean lineage (ML), which has maintained itself in the Dranse d’Abondance, a fast‐flowing alpine stream (Haute‐Savoie, France), despite several decades of intensive restoc...

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Published inJournal of fish biology Vol. 69; no. sa; pp. 127 - 139
Main Authors Caudron, A., Champigneulle, A., Guyomard, R.
Format Journal Article
LanguageEnglish
Published Oxford, UK Blackwell Publishing Ltd 01.09.2006
Blackwell
Wiley
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Summary:An attempt was made to extend the area of distribution of a native population of brown trout Salmo trutta belonging to a Mediterranean lineage (ML), which has maintained itself in the Dranse d’Abondance, a fast‐flowing alpine stream (Haute‐Savoie, France), despite several decades of intensive restocking with brown trout derived from the Atlantic lineage (AL). This was done by releasing an ML component into the predominantly AL population still present on the Ugine, the main tributary of the Dranse d’Abondance. This strategy of rehabilitation restocking was tested using fluoro‐marked juveniles produced from a captive breeding stock derived from the wild Dranse d’Abondance ML stock. Samples of 0+ year fish were collected over the period 1995–2003 in order to assess the impact of the restocking. Percentages of fluoro‐marked otoliths revealed significant contributions of ML restocking in the 0+ year autumnal standing population, with levels ranging from 34·3 to 61·4%. The change in the genetic characteristics of the 0+ year population produced by natural recruitment was monitored by analysing the unmarked subjects. Frequencies observed at two microsatellite loci revealed a considerable rise (from 0 to 60%) in the level of Mediterranean alleles in the natural 0+ year population since the introduction of restocking using ML individuals.
Bibliography:ark:/67375/WNG-PW4J2JD1-K
ArticleID:JFB1156
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ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0022-1112
1095-8649
DOI:10.1111/j.1095-8649.2006.01156.x