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Ten years of landscape genetics
Stéphanie Manel1, Rolf Holderegger
1Laboratoire LPED "Population Environnement, Développement" - UMR151 - Aix Marseille University - IRD Marseille, France; UMR Botanique et BioinforMatique de l'Architecture des Plantes, CIRAD, TA A51/PS2 34398 Montpellier Cedex 5, France.
Trends in Ecology & Evolution
|June 18, 2013
Summary
Landscape genetics, a decade-old field, examines how landscapes influence evolution. Future research will focus on integrating genetic variation with environmental factors for global change and conservation efforts.
Area of Science:
- Ecology and Evolutionary Biology
- Conservation Genetics
- Spatial Genomics
Background:
- Landscape genetics has matured over the past decade, significantly advancing our understanding of ecological and evolutionary processes.
- The field investigates the influence of landscape features on genetic variation and population connectivity.
Purpose of the Study:
- To review key conceptual and methodological advancements in landscape genetics.
- To explore future research directions, focusing on global change, conservation, and the management of specific ecosystems (tropical, urban).
- To highlight the importance of integrating neutral and adaptive genetic variation with environmental data.
Main Methods:
- Review of conceptual and methodological developments in landscape genetics.
- Analysis of progress in spatial and temporal patterns of gene flow.
- Examination of seascape genetics and landscape genomics approaches.
Main Results:
- Significant progress has been made in understanding gene flow patterns influenced by landscape structure.
- Landscape genomics has emerged as a powerful tool for identifying genes under selection related to environmental gradients.
- Seascape genetics provides insights into marine population connectivity.
Conclusions:
- Landscape genetics is crucial for assessing global change impacts and informing conservation strategies.
- Future research must integrate neutral and adaptive genetic variation with species distribution and environmental data for robust predictions.
- The field holds particular promise for managing biodiversity in tropical and urban environments.
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