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Molecular genetic variation in the African wild rice Oryza longistaminata A. Chev. et Roehr. and its association with environmental variables
Abstract
Molecular markers, complemented by appropriate Geographical Information System (GIS) software packages are powerful tools in mapping the geographical distribution of genetic variation and
assessing its relationship with environmental variables. The objective of the study was therefore to investigate the relationship between genetic diversity and eco-geographic variables using Oryza
longistaminata as a case study. The methodology used was a novel technique that combined hierarchical cluster analysis of both molecular diversity generated using Amplified Fragment Length Polymorphism (AFLP) and climate data available in a GIS software. The study clearly established that there is a close relationship between genetic diversity and eco-geographic variables. The study also revealed that genetic diversity is a function of annual rainfall, and peak diversity occurs in intermediate rainfall areas reflecting the ‘curvilinear theory’ of clinal relationship between the level of genetic diversity and rainfall. The clear association of genetic diversity with rainfall allows the extrapolation of
the potential impacts of global warming on diversity when empirical data on predicted climate models, particularly rainfall, are available. This knowledge would therefore be useful in the development of
conservation measures to mitigate the effects of genetic erosion through climate change.
assessing its relationship with environmental variables. The objective of the study was therefore to investigate the relationship between genetic diversity and eco-geographic variables using Oryza
longistaminata as a case study. The methodology used was a novel technique that combined hierarchical cluster analysis of both molecular diversity generated using Amplified Fragment Length Polymorphism (AFLP) and climate data available in a GIS software. The study clearly established that there is a close relationship between genetic diversity and eco-geographic variables. The study also revealed that genetic diversity is a function of annual rainfall, and peak diversity occurs in intermediate rainfall areas reflecting the ‘curvilinear theory’ of clinal relationship between the level of genetic diversity and rainfall. The clear association of genetic diversity with rainfall allows the extrapolation of
the potential impacts of global warming on diversity when empirical data on predicted climate models, particularly rainfall, are available. This knowledge would therefore be useful in the development of
conservation measures to mitigate the effects of genetic erosion through climate change.