Training workshop on “Methods in forest conservation genetics"

Background

Deforestation, recruitment failure and population decline are the most obvious threats to forest ecosystems posed by global change and human overexploitation. Demographic and habitat losses have immediate effects on the viability of tree species and populations, but they may also entail more subtle changes in species  genetic structure and dynamics. This has potential consequences on natural adaptive evolutionary processes and on the use and management of tree species genetic resources.

Forest conservation geneticists often need to assess genetic variation of adaptive significance within tree species, to identify populations especially exposed to climatic, demographic or introgression threats, and try to predict to what extent tree species will undergo shifts in their range or will have the capacity to respond to change though adaptive evolution and/or plasticity.

Course objectives

The purpose of this training workshop is to provide conceptual background and hands-on experience in the analysis of molecular and quantitative genetic data, and of trait-based species distribution models (ΔTraitSDM), for conservation genetics-related problems. Emphasis will be on statistical and modelling tools, rather than on the data acquisition process.

Who is the training for?

Graduate students, postdocs and early-career biologists with some background in population genetic data analysis and special interest in forest conservation genetics. Participation will be limited to 20 people; priority will be given to students from GenTree partners institutions, but 5 seats will be reserved to students from institutions not involved in the project.

Topics

• Theoretical summary of relevant parameters in conservation genetics. Molecular diversity, effective population size, inbreeding, genetic variance, evolvability.
• Estimation of effective population size and inbreeding.
• Estimation of genetic connectivity and introgression.
• Surveying genome-wide molecular diversity in natural populations. Inferences of selection (selective sweeps, outlier detection, genotype-environment association) and historical demography (maximum-likelihood methods, ABC).
• Design and analysis of common garden experiments to assess adaptive quantitative genetic variation and phenotypic plasticity. Estimation of additive genetic variance, heritability and evolvability.
• Trait-based Species distribution models (ΔTraitSDM) as forecast tools for genetic conservation. ΔTraitSDM quantify local adaptation, phenotypic plasticity and their interaction across species ranges to make predictions about the persistence of populations and species under new climates. They are based on reaction norms of different provenances planted together in series of common gardens across a species range.

Workshop format and schedule:

The course includes theoretical and practical sessions on each topic, including the analysis of real and/or dummy data sets (using the students own laptops and free software) illustrating the main analytical and practical challenges.

Day 1
9:00 registration
9:30 – 17h classroom session (coffee and lunch provided)

Day 2
9:00 – 17h classroom session (coffee and lunch provided)

Day 3
9:00 – 17h classroom session (coffee and lunch provided)

Day 4
9:00 – 16h classroom session (coffee and lunch provided)
16:00 – 17:00 wrap-up

Location:

INIA, Madrid
How to get there

To apply

Applications are now CLOSED

Deadline for application:

25 July 2019

Confirmation of successful application by organizers:

5 Sep 2019

Funding:

Registration is free. The organization will cover accommodation expenses, breakfast and lunches for all participants.

Instructors:

Marta Benito-Garzón (INRA-Bordeaux)
François Lefevre (INRA-Avignon)
Santiago C. González-Martínez (INRA-Bordeaux)
Leopoldo Sánchez (INRA-Orléans)
Juan José Robledo-Arnuncio (INIA)
Delphine Grivet (INIA)
José A. Ramírez-Valiente (INIA)
Miguel Navascués (INRA-Montpellier)

Contacts:

For more information : Juan José Robledo-Arnuncio (INIA, jjrobledo @ gmail.com)