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Related Experiment Video

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Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

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The power to detect recent fragmentation events using genetic differentiation methods.

Michael W Lloyd¹, Lesley Campbell, Maile C Neel

¹Department Plant Science and Landscape Architecture and Department of Entomology, University of Maryland, College Park, Maryland, United States of America. mlloyd13@umd.edu

|May 25, 2013

Summary

Genetic divergence metrics like Wright

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

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Published on: February 3, 2023

Area of Science:

Conservation Biology
Population Genetics
Ecology

Background:

Habitat loss and fragmentation threaten global biodiversity.
Population isolation in fragmented landscapes can negatively impact species.
Genetic divergence measures are proposed for monitoring landscape connectivity.

Purpose of the Study:

To assess the sensitivity of genetic divergence metrics (Fst, G'st, MI, D) to recent habitat fragmentation.
To evaluate the influence of population size, overlapping generations, and sub-structuring on these metrics.

Main Methods:

An individual-based model was developed with a factorial design.
Simulations varied population size, generational overlap, and sub-structuring.
Sensitivity of Fst, G'st, MI, and D to fragmentation was analyzed.

Main Results:

Fragmentation signals were detected within two generations for all metrics.
Larger population sizes (>100 individuals) and overlapping generations reduced the fragmentation signal.
The magnitude of change in genetic divergence metrics was generally small.

Conclusions:

Detecting fragmentation impacts using Fst, G'st, MI, or D is challenging due to small signal magnitudes and short detection windows.
Multi-generational sampling and accurate population estimates are crucial.
Genetic monitoring should be combined with direct movement estimates for reliable connectivity change detection.