2014
DOI: 10.1038/hdy.2014.93
|View full text |Cite
|
Sign up to set email alerts
|

A parameter to quantify the degree of genetic mixing among individuals in hybrid populations

Abstract: Hybridization between genetically distinct taxa is a complex evolutionary process. One challenge to studying hybrid populations is quantifying the degree to which non-native genes have become evenly mixed among individuals in the population. In this paper, we present a variance-based parameter, m d , that measures the degree to which non-native genes are evenly distributed among individuals in a population. The parameter has a minimum value of 0 for populations in which individuals from multiple taxa are prese… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
9
0

Year Published

2016
2016
2017
2017

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 8 publications
(9 citation statements)
references
References 34 publications
0
9
0
Order By: Relevance
“…Yet we found, as have many others, that parental fish were common and allele distributions often nonrandom in hybrid zones, and consequently that hybrid swarms were rare. One could regard this as a semantic argument (e.g., Kalinowski and Powell 2015) that rests on the definition of a hybrid swarm, for example, the mere presence of hybridized individuals beyond the first generation (Rhymer and Simberloff 1996) or the more restrictive conditions that we and others (Allendorf et al. 2013) have adopted.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…Yet we found, as have many others, that parental fish were common and allele distributions often nonrandom in hybrid zones, and consequently that hybrid swarms were rare. One could regard this as a semantic argument (e.g., Kalinowski and Powell 2015) that rests on the definition of a hybrid swarm, for example, the mere presence of hybridized individuals beyond the first generation (Rhymer and Simberloff 1996) or the more restrictive conditions that we and others (Allendorf et al. 2013) have adopted.…”
Section: Resultsmentioning
confidence: 99%
“…Yet we found, as have many others, that parental fish were common and allele distributions often nonrandom in hybrid zones, and consequently that hybrid swarms were rare. One could regard this as a semantic argument (e.g., Kalinowski and Powell 2015) that rests on the definition of a hybrid swarm, for example, the mere presence of hybridized individuals beyond the first generation (Rhymer and Simberloff 1996) or the more restrictive conditions that we and others (Allendorf et al 2013) have adopted. Regardless, the presumption that hybrid swarms will inevitably form following nonnative species introductions continues to influence the conservation of cutthroat trout (Allendorf et al 2005;Campton and Kaeding 2005;Shepard et al 2005) and of many other species (Blum et al 2010;Bean et al 2013;Hasselman et al 2014).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Evidence for the persistence of Yellowstone Cutthroat Trout Gunnell et al 2008;Kovach et al 2011) and Cutthroat Trout (McKelvey et al, in press) in sites threatened by Rainbow Trout and hybrid invasion is growing. Kalinowski and Powell (2015) used computer simulations to show that the complete loss of native genotypes is expected after only five generations of random mating between taxa. Further, a recent rangewide examination of Westslope Cutthroat Trout presented empirical evidence showing that apparently nonadmixed Cutthroat Trout persist in many populations facing hybrid invasions.…”
Section: Discussionmentioning
confidence: 99%
“…In this context, STRUCTURE [52] is the most extensively used software to detect population genetic structure. STRUCTURE generates clusters based on both transient Hardy-Weinberg disequilibrium and LD caused by admixture between populations [53,54]. EIGENSOFT is another widely used statistical package for the detection and correction of population stratification in GWAS using principal component analysis [55].…”
Section: Gwasmentioning
confidence: 99%