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Abstract

Magnolias are characteristic tree species of the Tropical Montane Cloud Forest (TMCF) in Mexico, an ecosystem that is highly threatened by habitat fragmentation and climate change. In this study, based on DNA sequences from five regions (chloroplast: trnT-trnL, trnK5-matK, trnS-trnG, rpl32-trnL, nuclear: ITS) and seven nuclear microsatellite markers, we aimed to delineate species boundaries between two-endemic species of the TMCF, Magnolia pedrazae and Magnolia schiedeana, and to estimate levels of genetic structure and diversity among populations. Phylogenetic and haplotype network analyses for the chloroplast and ITS regions did not support genetic differentiation as two distinctive species. Results from Bayesian and multivariate cluster analyses based on microsatellite loci showed high genetic differentiation across most populations, which was consistent with a strong and significant pattern of isolation by geographical distance. We found moderate to high levels of population genetic diversity, but it was lower in small populations relative to large populations. Our results suggest a contemporary decrease of genetic connectivity among populations, likely as a consequence of the current decline of suitable TMCF habitat. Managing landscape connectivity among remnant Magnolia populations within protected natural parks and surroundings, and with emphasis of small populations, would be key for the species conservation.

Details

Title
Species delimitation and genetic structure of two endemic Magnolia species (section Magnolia; Magnoliaceae) in Mexico
Author
Rico, Yessica 1   VIAFID ORCID Logo  ; Gutiérrez Becerril, Bruno Alejandro 2 

 CONACYT, Red de Diversidad Biológica del Occidente Mexicano, Instituto de Ecología, A.C., Pátzcuaro, Michoacán, Mexico 
 Independent Consultant, Pátzcuaro, Michoacán, Mexico 
Pages
57-68
Publication year
2019
Publication date
Feb 2019
Publisher
Springer Nature B.V.
ISSN
0016-6707
e-ISSN
1573-6857
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2169501912
Copyright
Genetica is a copyright of Springer, (2019). All Rights Reserved.