Morgane Travers
Yunne Shin, John Field, Philippe Cury, Simon Jennings
Ecosystem effects of representing predation Ecosystem effects of representing predation feedback in a twofeedback in a two--way coupling between a plankton way coupling between a plankton
model (model (ROMSROMS--NN22PP22ZZ22DD22) and a fish model () and a fish model (OsmoseOsmose))
ECEM’07 Conference
Marine Marine FoodFood WebsWebs andand externalexternal factorsfactors
A strong primary productionwould favor a bottom-up control (Frank et al. 2006)
Top down
Top predators diversity would buffer top-down effects of fishing (Yodzis 2001, Frank et al. 2006)Bottom up
Top predators abundancewould dampen ecosystem variability (e.g. induced by climate variability) (Sala 2006)
Coexistence of two types of trophic controls, with predominance of one or the other,
variable in time and space. (Frank et al. 2006)
How marine food web would respond to top-down effects of fishing and bottom-up effects of environmental variability ?
Coupling of LTL and HTL models.
End-to-end model of marine food webs
Copepods
Flagellates
Nitrates
Large Detritus
Ciliates
Small Detritus
Ammonium
Diatoms
- Double compartments of plankton
Penven, 2000
Koné , 2006
Integrated annual primary production (gC m-2 j-1). Koné 2006
Biogeochemical model coupled with a hydrodynamic model of the southern Benguelaupwelling and a large part of Agulhas Bank
LOW TROPHIC LEVELS: LOW TROPHIC LEVELS: planktonplankton modelmodel ROMS ROMS –– NN22PP22ZZ22DD22
- Environmental effects on growth rates
Possible alternative pathways
SOUTH AFRICA- 76.2% of the total fish biomass- 93.8% of the catch of the fish community- trophically important species
Pelagic fish
Demersal fish
Euphausiids
Benthopelagic fish
HIGH TROPHIC LEVELS: HIGH TROPHIC LEVELS: sizesize--basedbased fishfish modelmodel OSMOSEOSMOSEShin, 2000
Multi-species model based on opportunistic predation:- Spatio-temporal co-occurrence - Size adequacy between prey and predator
Individual-based model (IBM) :- variability in size (according to the feeding past)- variability in geographical location
Shin and Cury, 2001, 2004
HIGH TROPHIC LEVELS: HIGH TROPHIC LEVELS: sizesize--basedbased fishfish modelmodel OSMOSEOSMOSE
OSMOSE
Naturalmortality
Forage andpredation
GrowthStarvationmortality
Fishingmortality
Reproduction
e.g., anchovy
ξ
J F M A M J J A S O N D
J F M A M J J A S O N Dspawning periods fishing closure
months
To specify a maximal and a minimal size ratio between a predator and its potential preys
Ratio max
Ratio min
ln abd
2 µm – 20 µm: Flagellates
20 µm – 200 µm: Diatoms and ciliates
200 µm – 2 mm: Copepods
1 µm 1 mm 1 m ln size
To determine a size range for plankton compartments
pred size
Prey size
COUPLING COUPLING ofof Osmose Osmose andand NN22PP22ZZ22DD22: PREDATION PROCESS: PREDATION PROCESS
Food availability
(x, y, t, size)
COUPLING COUPLING ofof Osmose Osmose andand NN22PP22ZZ22DD22: 2: 2--WAYS INTERACTIONSWAYS INTERACTIONS
OSMOSE ROMS-PLUME
Copepods
Flagellates
Nitrates
Large Detritus
Ciliates
Small Detritus
Ammonium
Diatoms
20 µm
200 µm20 µm20 µm2 µm
2 mm200 µm200 µmNaturalmortality
Forage andpredation
Growth
Reproduction
Fishingmortality Starvation
mortality
1
FEEDBACK : Resulting predation mortality applied on plankton
1
2
2
FORCING : Plankton as a prey field for fish
FEEDBACK FEEDBACK fromfrom OSMOSE to NPZD OSMOSE to NPZD modelmodel
Spatio-temporal variation of fish-induced mortality on plankton
Copepods
1
2
3
4
10-3
6
5
> Higher mortality on Agulhas bank vs upwelling
> High mortality coastal vs offshore
> Relatively high mortality on St Helena’s bayJ F M A M JJ A S O N D
2.6E-03
2.8E-03
3.0E-03
3.2E-03
3.4E-03Mortality rate
St Helena’s bay
FEEDBACK FEEDBACK fromfrom OSMOSE to NPZD OSMOSE to NPZD modelmodel
Contributors in copepods mortality:
lightfish lanternfish
redeye
Horse mackerel
sardine anchovyeuphausiids
J F M A M JJ A S O N D2.6E-03
2.8E-03
3.0E-03
3.2E-03
3.4E-03
Mortality rate
1.3E + 06
1.4E + 06
1.4E + 06
1.5E + 06
1.5E + 06
1.6E + 06
1.6E + 06
1.2E + 06
1.3E + 06
1.4E + 06
1.5E + 06
1.6E + 06
1.7E + 06
lightfis hlanternfish
lanternfish
lightfish
6.8E + 05
7.2E + 05
7.6E + 05
8.0E + 05
1.3E + 06
1.3E + 06
1.4E + 06
1.4E + 06
1.4E + 06
Horse mackerel
redeye
5.0E+06
9.0E+06
1.3E+07
1.7E+07
2.1E+07
2.5E+07
43 44 45 46 47
Bio
mas
s
Diatoms
Copepods
FEEDBACK FEEDBACK fromfrom OSMOSE to NPZD OSMOSE to NPZD modelmodel
Fish-induced mortality variable in space and time
Effects on simulated plankton dynamics ?
+ 11.3%
1.5E+07
3.5E+07
5.5E+07
7.5E+07
9.5E+07
1.2E+08
1.4E+08
43 44 45 46 47
- 8.6%Coupling
Forcing
Copepods
Diatoms
FEEDBACK FEEDBACK fromfrom OSMOSE to NPZD OSMOSE to NPZD modelmodel
Spatial variation of plankton biomass
Forcing Coupling
Less phytoplankton on Helena’s bay (nursery area)
More copepods, but not in the nursery area
FOOD WEB structureFOOD WEB structure
Diatoms
Copepods
Euphausiids
Lanternfish
Redeye
Deep w. HakeShallow w. Hake
Diatoms
Copepods
Euphausiids
Lanternfish
Redeye
Deep w. HakeShallow w. Hake
Forcing Coupling
ConclusionConclusion
OSM
OSE
NPZ
D
Variability spatio-temporal of fish-induced mortality
Influence on plankton biomass (spatio-temporal)
TOP-DOWN
End-to-end modelling by coupling NPZD and Osmose
Influence on food web structure at the fish level
BOTTOM-UP
Importance of representing the feedback when coupling trophic models
Potential changes in food web structure when affected by fishing and climate changes
THANKS FOR YOUR ATTENTIONTHANKS FOR YOUR ATTENTION
- aims to represent the entire food web and the associated abiotic environment, - requires the integration of physical and biological processes at different scales, - implements two-way interaction between ecosystem components- accounts for the dynamic forcing effect of climate and human impacts at multiple trophic levels.
ENDEND--TOTO--END MODELEND MODEL
Osmose used for representing the fish community
Coupling of LTL and HTL models.
LTL:LTL: Biogeochemical model used for representing the plankton part
HTL:HTL:
- Models an opportunistic predation suitable for investigating changes in structure and function of marine food weds- Easily applicable in different ecosystems because requires basic parameters for fish species. Shin, 2000
Shin and Cury, 2001, 2004
Travers et al. In press
CALIBRATION : CALIBRATION : geneticgeneticalgorithmsalgorithms
PARAMETERS : 12 Larval mortalities + 4 plankton accessibility coefficients
DATA used for fitting : 12 Biomass + intervals of the fish species
Fitness
Generations
Creation of a population
Evaluation Parents Selection
Crossover/Mutation
Offspring Evaluation
Replacement
Stopping criterion
IBM
IBM
0
0.2
0.4
0.6
0.8
1
1 51 101 151 201 251 301
osmose
osmose
B
F
0.E+00
1.E-02
2.E-02
3.E-02
4.E-02
5.E-02
6.E-02
1.6% 4.2%8.3%
15%
0 0.1 0. 2
Dinoflagellates Diatoms
0 0.1 0. 2
Ciliates
0.0316
Den
sity
0 0.1 0. 2
Copepods
0.00667
0 0.1 0. 2
Den
sity 0.0192
Den
sity
0.129
Den
sity
CALIBRATION : CALIBRATION : geneticgenetic algorithmsalgorithms
Accessibility coefficients
Represent maximum available plankton and thus maximum mortality rates on plankton
Mor
talit
y ra
tes
(d-1
)
Osmose 0.15° x 0.15°
COUPLING modelsCOUPLING models
- Spatial interpolation
- Time step issue : 2-weeks time step
- Units • From N concentration to biomass
• Different for the plankton groupsOsmose
Roms
Conversion factors
Roms: curvilinear grid9-16 km
FOOD WEB structureFOOD WEB structure
Euphausiids
Sardine
2.0 2.4 2.8 3.2 3.6 4.0
2.0 2.4 2.8 3.2 3.6 4.0
Diatoms
Ciliates
Copepods
Diatoms
Ciliates
Copepods
TL distribution
< 18 cm > 18 cm
