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

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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

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10

• Isolated for 1000s ofyrs

• High among-populationgenetic differentiation

• Extremely low within-population geneticvariability

• Genetic bottlenecks at neutral loci

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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