Theoretical perspective

Theoretical perspective on genetic differentiation across space in mammals: impacts of body size, trophic level and landscape [/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row custom_padding=”0|0px|0|0px|false|false” _builder_version=”3.12.2″ make_fullwidth=”on”][et_pb_column type=”2_3″ _builder_version=”3.12.2″ parallax=”off” parallax_method=”on”][et_pb_text _builder_version=”3.12.2″]

Presented by 
Prachi Thatte 
National Center For Biological Sciences
Prachi Thatte, Uma Ramakrishnan
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Habitat fragmentation, a prevalent feature of modern landscapes, leads to population subdivision. Distribution of genetic variation within and between these sub populations depends upon gene flow between them and can be species specific. In this study we build predictions about spatial distribution of genetic variation for different mammalian species in a landscape with basic knowledge on their dispersal ability and landscape connectivity.


Dispersal ability and population size, in mammals, scales with body size and trophic level and hence these variables along with landscape variables like land- use type, topography and climate will be used to generate predictions. Species specific habitat suitability maps will be generated using landscape and species presence data and these will be used to model individual based dispersal and spatial distribution of genetic variation in the landscape.


Preliminary simulation results, without including landscape data, reveal that omnivores of large body size and intermediate mobility show higher genetic differentiation in a subdivided population compared to herbivores and carnivores of the same body size. Including landscape variables and species presence data to build habitat suitability models will give us an idea of species specific physical connectivity and its effect on distribution of genetic variation.


This study will provide some insights towards understanding how different species are impacted by habitat loss and fragmentation depending on the patterns of spatial distribution of genetic variation they show. In future, genetic data will be collected and analysed to investigate whether empirical data match theoretical predictions

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