Post on 30-Jun-2015
description
Assessing rapid evolutionary responses in natural populations to climate change and intensification of weather extremes:
Ministero dell’Istruzione, Università e Ricerca Rome 26/07/2011
F
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extremes:an integrated approach combining genetics and evolutionary modeling
Principal Investigator: Simone VincenziInstitution: Università di Parma
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My research interests
• Adaptive processes and traits increasing resilience of natural populations
• Climate change and evolution of life-histories
University of
NOOA Santa Cruz
life-histories
Murres Northern fur seals Salmon
University of California
Climate change
IPCC, 2007. Fourth Assessment Report: Climate Change.
Most likely
Climate change and extreme events
Catastrophes
Max F
low
Time (yrs)
100-yr flood
Climate change ����
increased intensity, altered frequency and seasonality of catastropic events
Natural populations and climate change
• (i) move (ii) adapt (iii) die
• Rapid responses and adaptations
• Adaptations to altered patterns of catastropicevents?
• Lack of methods and model systems
Kittiwake Coral fishArtic Fox
Novel approach
• Combining:
– molecular genetics (genes under selection and genetic variation)
– demography and life-histories
– climate predictions
– eco-evolutionary simulation framework
• Predicting:
– risk of extinction
– adaptations
– population dynamics (size, fluctuations, age and size structure)
Marble trout
Trebuscica Marble troutSalmo marmoratus
10 wild isolated populations in Slovenia
monitored since 1996
> 10,000 individuals sampled
fish farm experiments
Distribution of marble trout
Marking
Marble trout populations
• 3 basins
• 30-500 fish in eachpopulation
• Isolated for 1000s of
Baca Idrijca Soca
9
10
• Isolated for 1000s ofyrs
• High among-populationgenetic differentiation
• Extremely low within-population geneticvariability
• Genetic bottlenecks at neutral loci
1
1 Gatsnik
2 Zadlascica
3 Lipovscek
4 Huda Grapa
5 Svenica
6 Studenc
7 Trebuscica
8 Upper Idrica
9 Zakojska
10 Gorska
Marble trout and climate change
Major flood
Medium flood
SS���� Spring
AA���� Autumn
YEAR
STREAM BASIN 99 00 01 02 03 04 05 06 07 08 09 10
Huda AA AA AA SS
Zakojska AA AA SSBaca
Gorska AA AA
Lipovesck Soca AA AA AA AA AA SS AA
Zadlascica AA AA AA SS AA
Trebuscica AA AA AA AA SS SS
Studenc AA AA AA AA SS SSIdrijca
Idrijca AA AA SS SS
Gatsnick AA AA SS SS
Svenica AA AA AA SS SS
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Main Research Questions
i. Molecular genetics
– adaptive divergence (among populations)
– adaptive evolution through time (within populations)
ii. Demographic and statistical analysesii. Demographic and statistical analyses
– adaptive life-histories and plasticity
– present and future patterns of floods
iii. Eco-evolutionary modeling
– evolutionary history
– evolution of life-histories and genetic composition with climate change
Research Unit
Parma Research Unit
Modeling Genetics
Research Unit
Research groups
Institutions
Parma PadovaNOAA SC
All leading research groups in their fields
Statistics &Modeling
Salmonid genetics
Adaptive genetics
Work plan
Mol genetics Field data Fish farm
I year
Demographic model
Mol genetics
II year
Flood patterns
Eco-evolutionary model
Selective forces Predictions
Mol genetics
III year
Molecular genetics
SNP
• Adaptive geneticdifferentiation
- body growth
- time of spawning
- morphology
• SNPs as molecular markers• SNPs as molecular markers
• Discovery using NextGeneration Sequencing
• SNPs discovery will beoutsourced
• Genome regions under selection, candidate loci, QTLs
• Heritability
Eco-Evolutionary Model
• Complex quantitative genetic traits
• Different levels of biological organization
Past environments
Mean traits
Climate change Novelenvironment
Individual fitness
Population performance
• What happened? - Approximate Bayesian Computation
• What will happen? - Forward Stochastic Simulations
Evolutionary history
Plasticity
Genetic variation
fitness
Evolution
performance
Population size
Persistence
Specific aims and expected results
• Conservation of marble trout
• Conservation of fish population
• Disentangle contributions of ecology
Local
• Disentangle contributions of ecology and environmental factors on evolution
• Methodology for predicting consequences of intensification of weather extremes
Global
Why fund this project?
• Model system
• Research questions of exceptional relevance
• Novel integrated methodology
• Interdisciplinary, international and outstanding expertise
Novelenvironment
Individual fitness
Evolution
Population performance
Population size
Persistence
Assessing rapid evolutionary responses in natural populations to climate change and intensification of weather extremes:
Ministero dell’Istruzione, Università e Ricerca Rome 26/07/2011
F
I
R
B
extremes:an integrated approach combining genetics and evolutionary modeling
Principal Investigator: Simone VincenziInstitution: Università di Parma
2
0
1
0
FinancingCo-financing Hiring
General expenses
P.I. salaryChiara fama
Expenses
P.I. A.1.1 A.1.2 A.2 B C.1 C.2 D E F G Total
Simone Vincenzi
€181,458 €0 €120,000 €261,275 €134,000 €0 €5,000 €15,000 €0 €19,875 €736,608
• Modeling
- statistics
- eco-informatics
• Molecular genetics
- adaptive divergence
- parentage analysis
Financing
Body growth
Approximate Bayesian Computation
Population collapses
Eco-Evolutionary Model
• Complex quantitative traits
• Stochastic simulations
• Backward (ApproximateBayesian Computation)
What are the most likely– What are the most likelycombination ofparameters?
• Forward
– Persistence? Extinction?
– Demographic or evolutionary
– Management actions
Novelties in methods
• SNPs as molecular marker discovered with NGS
– genome regions under selection (body growth, time of spawning, morphology), candidate loci, QTLs
– Parentage analysis with extremely low – Parentage analysis with extremely low variability (heritability)
• Integration of genetics, field data, experiments
• Eco-evolutionarymodeling with individual-based models
Costs of SNPs discovery and genotyping
Costs of SNPs discovery and genotyping