Straying and life history of adult steelhead in a small California coastal stream revealed by otolith natural tags and genetic stock identification

2021 ◽  
Author(s):  
Christopher J. Donohoe ◽  
David E. Rundio ◽  
Devon E. Pearse ◽  
Thomas H. Williams
Keyword(s):  
Life History ◽  
Stock Identification ◽  
Genetic Stock ◽  
Natural Tags ◽  
Genetic Stock Identification ◽  
History Of

Estimating Abundance and Life History Characteristics of Threatened Wild Snake River Steelhead Stocks by Using Genetic Stock Identification

2012 ◽  
Vol 141 (5) ◽  
pp. 1310-1327 ◽  
Author(s):  
Matthew R. Campbell ◽  
Christine C. Kozfkay ◽  
Timothy Copeland ◽  
William C. Schrader ◽  
Michael W. Ackerman ◽  
...  
Keyword(s):  
Life History ◽  
Snake River ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification ◽  
Life History Characteristics

Comprehensive microsatellite baseline for genetic stock identification of Atlantic salmon (Salmo salar L.) in northernmost Europe

2017 ◽  
Vol 74 (8) ◽  
pp. 2159-2169 ◽  
Author(s):  
Mikhail Ozerov ◽  
Juha-Pekka Vähä ◽  
Vidar Wennevik ◽  
Eero Niemelä ◽  
Martin-A. Svenning ◽  
...  
Keyword(s):  
Atlantic Salmon ◽  
Salmo Salar ◽  
Stock Identification ◽  
Genetic Stock ◽  
Atlantic Salmon Salmo Salar ◽  
Genetic Stock Identification

Genetic Stock Identification of Steelhead in the Columbia River Basin: An Evaluation of Different Molecular Markers

2004 ◽  
Vol 24 (2) ◽  
pp. 672-685 ◽  
Author(s):  
Gary A. Winans ◽  
Melanie M. Paquin ◽  
Donald M. Van Doornik ◽  
Bruce M. Baker ◽  
Perry Thornton ◽  
...  
Keyword(s):  
Molecular Markers ◽  
River Basin ◽  
Columbia River ◽  
Columbia River Basin ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification

Genetic Stock Identification Reveals That Angler Harvest Is Representative of Cryptic Stock Proportions in a High‐Profile Kokanee Fishery

2019 ◽  
Vol 39 (3) ◽  
pp. 415-425
Author(s):  
Hillary G. M. Ward ◽  
Paul J. Askey ◽  
Tyler Weir ◽  
Karen K. Frazer ◽  
Michael A. Russello
Keyword(s):  
Stock Identification ◽  
Genetic Stock ◽  
High Profile ◽  
Genetic Stock Identification

Genetic Stock Identification of Russian Honey Bees

2010 ◽  
Vol 103 (3) ◽  
pp. 917-924 ◽  
Author(s):  
Lelania Bourgeois ◽  
Walter S. Sheppard ◽  
H. Allen Sylvester ◽  
Thomas E. Rinderer
Keyword(s):  
Honey Bees ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification ◽  
Russian Honey Bees

scholarly journals Development of molecular markers for genetic stock identification of chum salmon

2002 ◽  
Vol 68 (sup1) ◽  
pp. 353-356 ◽  
Author(s):  
SYUITI ABE ◽  
SHUNPEI SATO ◽  
HIROYUKI KOJIMA ◽  
JUNKO ANDO ◽  
HIRONORI ANDO ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Chum Salmon ◽  
Stock Identification ◽  
Genetic Stock ◽  
Genetic Stock Identification

scholarly journals Genetic stock identification of Atlantic salmon and its evaluation in a large population complex

2017 ◽  
Vol 74 (3) ◽  
pp. 327-338 ◽  
Author(s):  
Juha-Pekka Vähä ◽  
Jaakko Erkinaro ◽  
Morten Falkegård ◽  
Panu Orell ◽  
Eero Niemelä
Keyword(s):  
Atlantic Salmon ◽  
Large Population ◽  
Identification Accuracy ◽  
Lower Sensitivity ◽  
Stock Identification ◽  
Genetic Structuring ◽  
Genetic Stock ◽  
Factors Affecting ◽  
Genetic Stock Identification ◽  
Genetic Structure And Diversity

Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate among distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon (Salmo salar) population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed-stock fisheries.

Sign in / Sign up

Export Citation Format

Share Document