Simulating the gene flow pattern in Cabralea canjerana fragments in Atlantic Forest, for genetic conservation
Serrote, C., Reiniger, L. and Costa, L. (2018). Simulating the gene flow pattern in Cabralea canjerana fragments in Atlantic Forest, for genetic conservation. 5th European Congress of Conservation Biology. doi: 10.17011/conference/eccb2018/107056
Date
2018Copyright
© the Authors, 2018
Gene flow assumes special importance in the conservation of genetic resources by allowing the connectivity of geographically isolated populations and, thus, subject to the reduction of genetic variability. Its effectiveness is a function of the model and the rate, thus justifying studies for planning genetic conservation. Simulation programs allow us to infer past events from current data or predict future phenomena under real genetic scenarios. Adverse phenomena can be predicted and measures can be taken to bypass them. In the present work we used simulations with the EASYPOP program (Balloux, 2001), using data from microsatellite markers obtained from eight fragments of the forest tree species Cabralea canjerana, growing in the Atlantic Forest, in Brazil, aiming to study the model and the rate of gene flow that best explain its genetic structure. Five models and nine migration rates were tested, and the model that presented the closest values to those obtained with microsatellite markers by Melo (2012) was selected. The selection criteria was the observed heterozygosity, expected heterozygosity, and Wright statistics FST and FIT obtained in the simulations. The selected gene flow model was the isolation by distance, with a rate of 0.1. High levels of genetic differentiation were observed among the fragments due to their reproductive isolation, suggesting the need to build ecological corridors to connect distant fragments and, thereby, allow the homogenization of their allelic frequencies through gene flow. In this study we suggest the use of computer simulations based on molecular
markers data in the conservation context to predict future phenomena, thereby enabling identification of priority populations for conservation.
Key references: 1. Computer simulations; 2. Forest conservation; 3. Molecular markers.
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Publisher
Open Science Centre, University of JyväskyläConference
ECCB2018: 5th European Congress of Conservation Biology. 12th - 15th of June 2018, Jyväskylä, Finland
Original source
https://peerageofscience.org/conference/eccb2018/107056/Metadata
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