optimization and evolution of traits in models of fish

Optimization and evolution of traits in models of fish

Christian Jørgensen Uni Research, Bergen, Norway

Micro-organisms Large organisms

Local populations

Slow

Focus on species to predict trait composition

Trade-offs

Ubiquitous seed-bank

Fast

Focus on traits to predict species

composition

Competition

Recruitment

Trait shifts

Perspective

Strength

Adaptation

Immigration

Trait Trait

Community dynamics

Feeding area

Spawning area

Life for a cod larva…

Drifting particles, but at which depth?

30 m 1 m

Vikebø F, Sundby S, Ådlandsvik B, and Fiksen Ø. 2005. ICES J Mar Sci 62: 1375-1386.

Fiksen Ø, Jørgensen C, Kristiansen T, Vikebø F, Huse G. 2007. Mar. Ecol. Progr. Ser., 347: 195-205.

A highway intersection in the deep

Life for a cod larva…

Vikebø F, Sundby S, Ådlandsvik B, and Fiksen Ø. 2005. ICES J Mar Sci 62: 1375-1386.

Dept

h

Light, vision, encounters, and predation

Fiksen, Ø., Aksnes, D.L., Flyum, M.H., and Giske, J. 2002. Hydrobiologia, 484: 49-59.

Optimal daily vertical migrations

0 6 12 18 24 Time of day

Fiksen Ø, Jørgensen C (2011) MEPS 432:207-219

Swimming

Behavior in ROMS Vestfjorden Moskenesgrunnen • Growth model g

-Size, temperature -Light-dependent encounters with prey

• Survival model m -Light-dependent encounters with visual predators -Tactile predators

• Fearfulness π -High π – risk averse -Low π – seeking risk

Vikebø F, Jørgensen C, Kristiansen T, Fiksen Ø (2007) MEPS 347:207-219

8

7

6

5

4

Tem

pera

ture

exp

osur

e

Opdal AF, Vikebø FB, Fiksen Ø. 2011. MEPS 439:255-262.

Feeding area

Spawning area

Spawning distribution 1910 and 1948

Jørgensen C, Dunlop ES, Opdal AF & Fiksen Ø (2008) Ecology 89:3436-3448

Food intake

Stored energy

Offspring

Growth

External factors Mortality Food intake Migration costs

States

Age Body length Stored energy

Mechanism: Energy allocation

Jørgensen C, Fiksen Ø. 2006. Can J Fish Aquat Sci. 63:186-199

′′′+⋅′+= ∑′F

FELAVFFPSEBFELAV ),,,1()|()(max),,,(α

Migration costs versus body size

50 cm 110 cm

Migration S

Migration N

Fecundity

Jørgensen C, Dunlop ES, Opdal AF, Fiksen Ø. 2008. Ecology 89:3436-3448.

Fitness per offspring

3

2

1

Migration distance

Lofoten Møre

Egg spawned

Small fish

Large fish

Evolution driven by mortality

Pict

ure

cour

tesy

of D

avid

Con

over

Removal of the 90% smallest fish

Removal of the 90% largest fish

Conover DO, Munch SB. 2002. Science 297: 94-96.

Heritable changes after 4 generations of harvesting

Spawning distribution 1910 and 1948

Jørgensen C, Dunlop ES, Opdal AF and Fiksen Ø. 2008. Ecology 89:3436-3448

Historic stock Adapted to fishing

Migration distance (km) 750 1500 0

Jørgensen C, Dunlop ES, Opdal AF & Fiksen Ø (2008) Ecology 89:3436-3448

0

2

4

6

8

10

12

14

16

0

50

100

150

Body

leng

th (c

m)

Age

(yea

rs)

Mat

urat

ion

age

(yea

rs)

Which fish migrate longest?

Long-term consequences

Less ice

What about sensitivity to

environmental fluctuations?

Climate warming

A potential problem for thermal conformers

Routine metabolism

Reproduction

Cognition Behaviour

Digestion

Habitat

Mating

Gonads

Parental care

Territoriality

Migration Signalling

Cognition

Immune defence

Behaviour Digestion

Maintenance

Ingestion

Sensing

Acquisition Allocation

Growth

Morphology

Resources Resources Structural growth Stores

Enberg K, Jørgensen C, Dunlop ES, Varpe Ø, Boukal DS, Baulier L, Eliassen S, Heino M. 2012. Fishing-induced evolution of growth: concepts, mechanisms and the empirical evidence. Marine Ecology 33:1-25.

Many of these components and processes are in trade-offs with survival

is not size

Small fish more often encounter a mouth large enough to engulf them

Predation

Body length (cm)

Pred

atio

n

0.0

0.1

0.2

0 25 50 75 100 125

Typical trade-offs

Foraging is risky

Predation Growth

0

1

2

3

4

0 0.5 1 1.5 2

Growth-related risk Fo

od in

take

Body length (cm)

Pred

atio

n

0.0

0.1

0.2

0 25 50 75 100 125

Reproduction is risky Stout body shape impedes

swimming performance. Finding mates takes time

and involves exposure to predators.

Predation Growth Reproduction Mortality:

0.0

0.5

1.0

1.5

0 0.1 0.2 0.3

Gonad size (GSI)

Extr

a m

orta

lity

0

1

2

3

4

0 0.5 1 1.5 2


od in

take

Body length (cm)

Pred

atio

n

0.0

0.1

0.2

0 25 50 75 100 125

Predation Growth Reproduction Mortality:

0.0

0.5

1.0

1.5

0 0.1 0.2 0.3

Gonad size (GSI)

Extr

a m

orta

lity

0

1

2

3

4

0 0.5 1 1.5 2


od in

take

Body length (cm)

Pred

atio

n

0.0

0.1

0.2

0 25 50 75 100 125

0.0

0.5

1.0

0% 50% 100%

Used scope Ex

tra

mor

talit

y

Burs

t spe

ed

Fed Unfed

Pred

atio

n

Billerbeck JM, Lankford TE, Conover DO. 2001. Evolution of intrinsic growth and energy acquisition rates. I. Trade-offs with swimming performance in Menidia menidia. Evolution 55:1863-1872. Lankford TE, Billerbeck JM, Conover DO. 2001. Evolution of intrinsic growth and energy acquisition rates. II. Trade-offs with vulnerability to predation in Menidia menidia. Evolution 55:1873-1881.

Pörtner HO. 2010. Oxygen- and capacity-limitation of thermal tolerance: a matrix for integrating climate-related stressor effects in marine ecosystems. J Exp Biol 213: 881-893

Oxygen- and capacity-limited thermal tolerance

0

50

100

150

200

0 5 10 15 20

Met

abol

ic ra

te (m

gO2·k

g−1 ·h

−1)

Temperature (°C)

Bioenergetics budgets – with overhead costs

Max

imum

aer

obic

scop

e

SMR

AMR

SDA Activity

Free scope

Survival Growth Reproduction

Ocean temperature (°C)

0.0

0.2

0.4

0.6

0.8

1.0

0

2

4

6

8

10

12

0 5 10 15 20

0.0

0.2

0.4

0.6

0.8

1.0

0

20

40

60

80

100

120

0 5 10 15 20

Age

at m

atur

atio

n (y

ears

)

Gon

ado-

som

atic

inde

x Fo

ragi

ng b

ehav

iour

To

tal u

sed

scop

e

Leng

th a

t age

15

(cm

)


Nat

ural

mor

talit

y (y

ear−

1 )

What the model says

Constant temperature throughout life. No temperature effects on spawning or early life stages. Find optimal strategies and their consequences.

0

50

100

150

200

0 5 10 15 20



SMR

AMR

Met

abol

ic ra

te

(mg

O2·k

g−1 ·h

−1)

0 5 10 15 20

Max Aerobic Scope: Max AMR: 15 °C

14 °C Max Fitness: 9 °C

Adding behavioural and life history perspectives modifies predictions based on physiology alone.

Fitness

Topt

Aero

bic

scop

e (m

g O

2·kg−

1 ·h−1

)

TP

TP Tcrit

Life

time

expe

cted

go

nad

prod

uctio

n

Total egg production (109)0 5 10 15 20 25

Rec

ruits

0

20000

40000

60000

C

Total recruitment

Maturation

Age (years)0 5 10 15 20 25

Leng

th (c

m)

30

60

90

120

A

Lp50

Lp75

Lp25 w

MF

Length

Mor

talit

y ra

te

Mortality

Population Individual

Updated population

Time (years)0 20 40 60 80 100

0

2

4

6

8

Rel

ativ

e bi

omas

s

0.0

0.3

0.6

0.9

1.2

F

Relative population biomass0.0 0.5 1.0 1.5

Rel

ativ

e gr

owth

0.8

1.0

1.2

1.4

B

Growth conditions

Cycle over all individuals

Cycle over years

Growth•Density dependence

•Environmental variability

•Individual stochasticity

•Individual foraging intensity

If mature:

•Mating•Inheritance

•Growth of gonads

12

3

4


Rec

ruits

0

20000

40000

60000

C

Total recruitment


Rec

ruits

0

20000

40000

60000

C

Total recruitment

Maturation

Age (years)0 5 10 15 20 25

Leng

th (c

m)

30

60

90

120

A

Lp50

Lp75

Lp25 w

Maturation

Age (years)0 5 10 15 20 25

Leng

th (c

m)

30

60

90

120

A

Lp50

Lp75

Lp25 w

Age (years)0 5 10 15 20 25

Leng

th (c

m)

30

60

90

120

A

Lp50

Lp75

Lp25 w

MF

Length

Mor

talit

y ra

te

Mortality

MF

Length

Mor

talit

y ra

te

Mortality

Population Individual

Updated population

Time (years)0 20 40 60 80 100

0

2

4

6

8

Rel

ativ

e bi

omas

s

0.0

0.3

0.6

0.9

1.2

F

Updated population

Time (years)0 20 40 60 80 100

0

2

4

6

8

Rel

ativ

e bi

omas

s

0.0

0.3

0.6

0.9

1.2

F

Time (years)0 20 40 60 80 100

0

2

4

6

8

Rel

ativ

e bi

omas

s

0.0

0.3

0.6

0.9

1.2

F


Rel

ativ

e gr

owth

0.8

1.0

1.2

1.4

B


Rel

ativ

e gr

owth

0.8

1.0

1.2

1.4

B

Growth conditions

Cycle over all individuals

Cycle over years









If mature:


•Growth of gonadsIf mature:


•Growth of gonads

12

3

4

Enberg et al. 2009 Evol. Appl.

The model as a virtual laboratory

0

3

6

9

12

-200 -100 0 100 200 300 400

Age

at m

atur

atio

n

Year relative to start of fishing

400

0

50

200

100 F = 0.3

Evolutionary snapshots

f = 0.5

0 100 200 300 400 500

Time (years)

Rela

tive

popu

latio

n bi

omas

s

100 years of harvesting

Manipulating and comparing

Non-evolving

Evolving

F = 0.7 y−1

F = 0.3 y−1

Recovery time (years)

Non-evolving

Evolving

200 000 years without fishing

Initialized population • Random traits • Random population structure

Adapted pristine population • Traits and population structure adapted to natural mortality

Adaptations of life history traits to harvesting

R0(S) R50(S) R100(S) R200(S) R400(S)

Year 0

Populations fished for increasing durations, leading to life-history evolution

Year 50 Year 100 Year 200 Year 400

-Populations’ life history traits stored. Population dynamics simulated with traits drawn from stored trait distribution. -Simulations repeated for fixed number of seeded recruits in increasing intervals. S and R recorded to construct emerging stock-recruitment curves. -20 replicates to average over environmental variability. Repeated with and without harvesting.

Evol

utio

nary

snap

shot

s Tr

aits

free

zed

to sa

mpl

e ec

olog

ical

dyn

amic

s

Data shown in figures

5000 years without fishing

20 replicates to average over evolutionary trajectories

Acknowledgements Cod life cycle models: Øyvind Fiksen Frode Vikebø Anders F. Opdal

Cod and climate: Rebecca E. Holt

Evolving IBMs: Katja Enberg

Funding from: - EU project Ethofish - COST action Conservation Physiology of Marine Fishes - Research Council of Norway - Nordic Council of Ministers

optimization and evolution of traits in models of fish

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