The term ‘landscape genetics’ has been applied to studies that integrate ecological context and intervening landscape into population genetic analyses of contemporary processes such as gene flow and migration.
This course will cover the basics of both quantitative landscape ecology and population genetics, focusing on how we develop and evaluate spatial/genetic analyses using the R platform.
Course content is as follows:
Day 1
- Spatial & Ecological Data
- Installation & configuring R & RStudio
- Acquiring spatial data, projections, and visualization
- Vector and raster data
Day 2
- Genetic markers and basic analyses
- Genetic markers and sampling
- Genetic distance, diversity, and structure
- Ordination techniques based upon genetic markers
Day 3
- Integrating spatial and genetic data
- Barrier detection & population division
- Resistance Modeling
- Mantel and distance regressions
- Remote sensing – LiDAR and Hyperspectral data
Day 4
- Integrating spatial and genetic data
- Spatial autocorrelation
- Network Approaches
- PCMN & Redundancy
Day 5
- Adaptive Genetic Variance
- Outliers & gradients
- Quantitative genetics, why we should care.
- Chromosome walking
For more information and to book please visit the website