genetic assignment
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2021 ◽  
Author(s):  
Dilan Saatoglu ◽  
Alina K. Niskanen ◽  
Markku Kuismin ◽  
Peter S. Ranke ◽  
Ingerid J. Hagen ◽  
...  

Diversity ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 245
Author(s):  
Francisco A. Rivera-Ortíz ◽  
Jessica Juan-Espinosa ◽  
Sofía Solórzano ◽  
Ana M. Contreras-González ◽  
María del C. Arizmendi

The Military Macaw (Ara militaris) faces a number of serious conservation threats. The use of genetic markers and assignment tests may help to identify the geographic origin of captive individuals and improve conservation and management programs. The purpose of this study was to identify the possible geographic origin of a captive individual using genetic markers. We used a reference database of genotypes of 86 individuals previously shown to belong to two different genetic groups to determine the genetic assignment of the captive individual of unknown origin (captive specimen) and five individuals of known geographic origin (as positive controls). We evaluated the accuracy of three assignment/exclusion criteria to determine the success of correct assignment of the individual of unknown origin and the five positive control individuals. WICHLOCI estimated that eight loci were required to achieve an assignment success of 83%. The correct geographic origin of positive controls was identified with 83% confidence. All of the analyses assigned the captive individual to the genetic group from the Sierra Madre Oriental. Bayesian assignment tests, tests for genetic distance and allele frequency tests assigned the unknown individual to the locations from the Sierra Madre Oriental with a probability of 71.2–82.4%. We show that the use of genetic markers provides a promising tool for determining the origin of pets and individuals seized from the illegal animal trade to better inform decisions on reintroduction and improve conservation programs.


Author(s):  
Romeo Di Pietro ◽  
Antonio Luca Conte ◽  
Piera Di Marzio ◽  
Paola Fortini ◽  
Emmanuele Farris ◽  
...  

AbstractMolecular diversity analysis of deciduous pubescent oaks was conducted for populations from Calabria, Sicily and Sardinia. The aims of this study were twofold. First, to provide data on the genetic diversity of pubescent oaks from an understudied area which currently exhibits one of the highest concentrations of pubescent oak species in Europe. Second, to verify if these groups of oaks are genetically distinct and if their identification is in accordance with the current taxonomic classification. Molecular analyses of leaf material of 480 trees from seventeen populations belonging to putatively different pubescent oak species (Quercus amplifolia, Q. congesta, Q. dalechampii, Q. ichnusae, Q. leptobalanos, Q. virgiliana) were performed. Twelve gene-based Expressed Sequence Tag-Simple Sequence Repeat markers were selected, and genetic diversity and differentiation were calculated. The results showed relatively high values of allelic richness, heterozygosity and number of private alleles for the populations investigated. A weak but positive correlation between geographical and genetic distance was detected. Genetic assignment (STRUCTURE) and principle coordinate analyses exhibited a weak separation into two genetic groups which, however, did not correspond to the taxonomic, chorological and ecological features of the populations investigated. Sardinian populations formed one group which was separated from the Calabrian and Sicilian populations. In light of the results obtained, the taxonomic classification for the pubescent white oaks currently reported in the major Italian floras and checklists for the study area was not confirmed by molecular analyses.


The Condor ◽  
2020 ◽  
Author(s):  
Benjamin J Lagassé ◽  
Richard B Lanctot ◽  
Mark Barter ◽  
Stephen Brown ◽  
Chung-Yu Chiang ◽  
...  

Abstract The degree to which individuals migrate among particular breeding, migration, and wintering sites can have important implications for prioritizing conservation efforts. Four subspecies of Dunlin (Calidris alpina) migrate along the East Asian−Australasian Flyway. Each subspecies has a distinct and well-defined breeding range, but their migration and winter ranges are poorly defined or unknown. We assessed the migratory connectivity of 3 of these subspecies by evaluating a dataset that encompasses 57 yr (1960–2017), and comprises more than 28,000 Dunlin banding records and 818 observations (71 recaptures and 747 band resightings). We present some of the first evidence that subspecific segregation likely occurs, with arcticola Dunlin wintering in areas of Japan, and other arcticola, actites, and sakhalina Dunlin wintering in areas of the Yellow and China seas. Observations indicate that whether an arcticola Dunlin winters in Japan or the Yellow and China seas is independent of their breeding location, sex, or age. Furthermore, observations indicate that ≥83% of arcticola Dunlin exhibit interannual site fidelity to specific wintering sites. This suggests that the degradation of specific wetland areas may negatively affect particular individuals of a particular subspecies (or combination of subspecies), and, if widespread, could result in population declines. Given the possible biases inherent in analyzing band recovery data, we recommend additional flyway-wide collaboration and the use of lightweight tracking devices and morphological and genetic assignment techniques to better quantify subspecies’ migratory movements and nonbreeding distributions. This information, when combined, will enable effective conservation efforts for this species across the East Asian−Australasian Flyway.


2020 ◽  
Vol 16 (4) ◽  
Author(s):  
M. A. Millar ◽  
K. Mezgebe ◽  
N. Hagazi ◽  
P. Cunningham ◽  
M. Byrne

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Charlie D. Ellis ◽  
Tom L. Jenkins ◽  
Linda Svanberg ◽  
Susanne P. Eriksson ◽  
Jamie R. Stevens
Keyword(s):  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Luciana Inés Oklander ◽  
Mariela Caputo ◽  
Agustín Solari ◽  
Daniel Corach

2019 ◽  
Vol 11 (2) ◽  
pp. 333-344
Author(s):  
Markku Kuismin ◽  
Dilan Saatoglu ◽  
Alina K. Niskanen ◽  
Henrik Jensen ◽  
Mikko J. Sillanpää

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