Combining demography with quantitative genetics to infer the adaptive potential of

small populations

Simone VincenziEU Marie Curie FellowUniversity of California Santa Cruz, USPolytechnic of Milan, Italy

ASN meeting, Asilomar 2014

People

Giulio De Leo

Alain Crivelli

Marc Mangel

Dusan Jesensek

Slovenian field crew

Hans Skaug

Gianluigi Rossi

Time (yrs)

100-yr flood

Extreme events

Climate change

Small populations• Peculiarities– Bottleneck effect– Less evolutionary potential– Persistence dependent on year effects– High risker of extinction following extremes– Generalities are difficult

• Can the (potential) evolution of traits increase persistence of small populations in an increasing extreme world?

• Eco-evolutionary feedbacks?

Model systemMarble trout

100 km

Slovenia

Marble trout

Stream-living

Size is highly plastic

Max age ~ 10 yo ~ 3-4 yo

Longitudinal data

Marble trout populations3 basins

30-1000 fish in each population

Isolated for 1000s of yrs

High among-population genetic differentiation

Extremely low within-population genetic variability

Baca Idrijca Soca

10 km

Marble trout and floods

Major flood

Medium flood

SS Spring AA Autumn

YEARSTREAM 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

910

1

DD growth and resilience

L D

High density

Low density

Variability of growth

Role of growth variation• Evolution of growth rates may increase

persistence probability of marble trout1.Need to tease apart shared and individual

contribution to growth2.Life-history model• Growth• Other life-history traits• Occurrence of floods

3.Run simulations of scenarios with or without evolution of growth rates

Random-effect vB growth model

0( )( ) (1 )k t tL t L e ( , )

( , )

L f x u

k f x v

x = covariates or groupsu,v = individual random effects

L

k

0t

Relationship between REs

0( )( ) (1 )k t tL t L e

Differences between year classes

Zakojska Gacnik

Heritability

Carlson SM, Seamons TR (2008) A review of quantitative genetic components of fitness in salmonids: implications for adaptation to future change. Evol Appl 1:222–238

Growth-mortality trade-off

Growth Survival

Stream discharge

10 km

SimulationsEVO

FIX

Realized length

EVO FIX

10-y moving average

Proportion of juveniles

EVO FIX

10-y moving average

Population sizeEVO FIX 10-y moving average

Same risk of extinction

Why

• Faster life histories, less BOFF• Faster life histories mainly after collapses• Realized length is only slightly different • Variation in egg production due to variation in

intrinsic growth is not crucial (given density-dependent growth and early survival)

≈

Conclusions

Growth rates – may evolve– have effects on population traits

through eco-evolutionary feedbacks– without affecting persistence

• Further insights from parentage analysis

• Non-linearities of density-dependence