Pre Recorded
The term ‘landscape genetics’ has been applied 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.
This course is suitable for graduate students, postdoctoral researchers, and primary investigators interested in learning how to integrate landscape ecological and population genetic tools using the R software.
Last Up-Dated 07:04:2021
Availability – 24 places
Duration – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
There will be morning lectures based on the modules outlined in the course timetable. In the afternoon there will be practicals based on the topics covered that morning. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
A basic understanding of statistical concepts. Specifically, generalised linear regression models, statistical significance, hypothesis testing.
Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
Approx. 7 hours
Module 1: Spatial & Ecological Data.
Installation & configuring R & RStudio
Acquiring spatial data, projections, and visualization
Vector and raster data
Approx. 7 hours
Module 2: Genetic markers and basic analyses
Genetic markers and sampling
Genetic distance, diversity, and structure
Ordination techniques based upon genetic markers
Approx. 7 hours
Module 3: Integrating spatial and genetic data
Barrier detection & population division
Resistance Modeling
Mantel and distance regressions
Remote sensing – LiDAR and Hyperspectral data
Approx. 7 hours
Module 4: Integrating spatial and genetic data
Spatial autocorrelation
Network Approaches
PCMN & Redundancy
Approx. 7 hours
Module 5: Adaptive Genetic Variance
Outliers & gradients
Quantitative genetics, why we should care.
Chromosome walking