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
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
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
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
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
)
Ocean temperature (°C)
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
Ocean temperature (°C)
Ocean temperature (°C)
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
Total egg production (109)0 5 10 15 20 25
Rec
ruits
0
20000
40000
60000
C
Total recruitment
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
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
Relative population biomass0.0 0.5 1.0 1.5
Rel
ativ
e gr
owth
0.8
1.0
1.2
1.4
B
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
Growth•Density dependence
•Environmental variability
•Individual stochasticity
•Individual foraging intensity
If mature:
•Mating•Inheritance
•Growth of gonadsIf mature:
•Mating•Inheritance
•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