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      Genetic structure of introduced populations: 120-year-old DNA footprint of historic introduction in an insular small mammal population

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          Abstract

          Wildlife populations have been introduced to new areas by people for centuries, but this human-mediated movement can disrupt natural patterns of genetic structure by altering patterns of gene flow. Insular populations are particularly prone to these influences due to limited opportunities for natural dispersal onto islands. Consequently, understanding how genetic patterns develop in island populations is important, particularly given that islands are frequently havens for protected wildlife. We examined the evolutionary origins and extent of genetic structure within the introduced island population of red squirrels ( Sciurus vulgaris) on the Channel Island of Jersey using mitochondrial DNA (mtDNA) control region sequence and nuclear microsatellite genotypes. Our findings reveal two different genetic origins and a genetic architecture reflective of the introductions 120 years ago. Genetic structure is marked within the maternally inherited mtDNA, indicating slow dispersal of female squirrels. However, nuclear markers detected only weak genetic structure, indicating substantially greater male dispersal. Data from both mitochondrial and nuclear markers support historic records that squirrels from England were introduced to the west of the island and those from mainland Europe to the east. Although some level of dispersal and introgression across the island between the two introductions is evident, there has not yet been sufficient gene flow to erase this historic genetic “footprint.” We also investigated if inbreeding has contributed to high observed levels of disease, but found no association. Genetic footprints of introductions can persist for considerable periods of time and beyond traditional timeframes of wildlife management.

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          Statistical confidence for likelihood-based paternity inference in natural populations.

          Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for delta that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.
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            R: A language and environment for statistical computing

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              Precision Farming: Technologies and Information as Risk-Reduction Tools

               Franklin Hall (1999)
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                Author and article information

                Journal
                Ecol Evol
                Ecol Evol
                ece3
                Ecology and Evolution
                Blackwell Publishing Ltd
                2045-7758
                2045-7758
                March 2013
                04 February 2013
                : 3
                : 3
                : 614-628
                Affiliations
                [1 ]Durrell Institute of Conservation and Ecology, School of Anthropology and Conservation, University of Kent Canterbury, CT2 7NR, United Kingdom
                [2 ]JSPCA Animals' Shelter 89 St. Saviours Road, St. Helier, Jersey, JE2 4GJ, United Kingdom
                [3 ]Institute of Zoology, Zoological Society of London Regent's Park, London, NW1 4RY, United Kingdom
                [4 ]Muséum national d'Histoire naturelle, Département “Ecologie et Gestion de la Biodiversité”, UMR 7204 “Conservation des espèces, restauration et suivi des populations” Case postale 53, rue Buffon, 75005, Paris, France
                [5 ]The Department of Environment, States of Jersey Trinity, Jersey, JE3 5JP, United Kingdom
                Author notes
                Siobhan Simpson, Durrell Institute of Conservation and Ecology, School of Anthropology and Conservation, University of Kent, Canterbury, CT2 7NR, United Kingdom. Tel: + 01227824097; Fax: + 01227827289; E-mail: siobhan.simpson@ 123456googlemail.com

                Funding Information This study was jointly funded by the States of Jersey Department of the Environment, the Jersey Society for Prevention of Cruelty to Animals, and the Jersey Ecology Fund.

                Article
                10.1002/ece3.486
                3605850
                23532702
                © 2013 Published by Blackwell Publishing Ltd.

                Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

                Categories
                Original Research

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