Estimating gametic introgression rates in a risk assessment context A case study with Scots pine relicts

The estimation of recent gene immigration is fundamental to a wide range of evolutionary and conservation studies. In a risk assessment context, gene flow estimation procedures are needed that are both accurate and readily amenable to formal evaluation of statistical uncertainty. However, genetic methods for estimating recent migration rates that are specific and have been thoroughly evaluated are scarce. Here we use an original and straightforward maximum-likelihood method to estimate recent uniparental gametic immigration from non-local plantations into an endangered population of the Iberian relict pine variety Pinus sylvestris var. nevadensis D. H. Christ. Our approach is not intended to ascertain population membership of individuals, but rather to obtain accurate immigration rate estimates with reliable confidence limits. We found very high (40%) pollen introgression at the seed-crop level into the Scots pine relict, and substantial (10-15%) male gametic introgression among naturally regenerated recruits. Using numerical simulation, we show that our method yields uniparental gametic immigration estimates that are expected to be virtually unbiased and usually accurate under our sampling conditions. Among four tested methods to estimate the confidence intervals for immigration estimates, the profile-likelihood method was the best, as it outperformed bootstrapping procedures and yielded coverage close to nominal limits under different sample sizes and migration rates. This study presents a method by which researchers can facilitate decision making within a gene flow risk assessment context. © 2009 Macmillan Publishers Limited All rights reserved.

Bibliographic Details

Main Authors:	Robledo Arnuncio, Juan José, Navascués, M., González-Martínez, S. C., Gil, L.
Format:	journal article biblioteca
Language:	English
Published:	Springer Nature 2009
Subjects:	Gene flow, Recent migration, Long distance pollen and seed dispersal, Maximum likelihood, Genetic introgression,
Online Access:	http://hdl.handle.net/20.500.12792/3748 http://hdl.handle.net/10261/293330
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