towards end-to-end modeling of the marine food web
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Towards end-to-end modeling of the marine food web
Wolfgang FennelLeibniz Institute of Baltic Sea Research (IOW)
Warnemündee-mail: wolfgang.fennel@io-warnemuende.de
• Motivation,• construction of the model system, (WFM),• test experiments (incl. eutrophication),• comparison with independent data,
• skill assessment issue (truncated food webs).
The coupled system
N, P, Z, D, .......lower part of the food webTime scales-1…12 months
FishTime scales – 1….20 years
physics
loads fishery
food
mortality
For example, what are the reasons for the interannual variations?
1955 1960 1965 1970 1975 1980 1985 1990 1995 20000.0
0.2
0.4
0.6
0.8
1.0
1.2
( )Eastern Gotland BasinJan.-April
1960 1965 1970 1975 1980 1985 1990 1995 20000.0
2.0
4.0
6.0
8.0( )
Eastern Gotland BasinJan.-April
phosphate mmol/m³nitrate mmol/m³
Bottom up?
Nutrient loads
Normal fish community
The piscivorous fish removedCourtesy S.Hanson
S.CarpenterUW Madison
zooplanktivores
Sprat
eggslarvaeyear classes
Herring
eggslarvaeyear classes
Cod
eggs
larvae
year classes
piscivore
Fish modelBaltic case
copepods
copepods
Cod, herring and sprat -> 80% of fish biomass
Define size- (or mass-) classes to formulate predator-prey interaction
Use Bertalanffy Formula, with fitted parameters,
(H and k, carries a lot empirical information)to define consumption and growth rates
Map the Bertanlanffy dynamics onto piece-wise constant effective growth rates
HX1=5HX2=10
CX1=5CX2=30
SX1=5SX2=10SX3=15SX4=20
mass
CX6=1500
CX5=800
CX4=200
CX3=60
HX5=150
HX4=60
HX3=30
Interaction of Cod, Herring and Sprat, Feeding limited by an Ivlev function
Predator- prey interaction, example Cod-Herring the predators ‚sees‘ all smaller prey animals
Prey-predator interaction, example herring –cod, the prey ‚sees‘ all larger predator animals
Further dynamic ingredients:
Metabolism:respirations- and excretion rates transferring part of the ingested food(or bodymass) to nutrients and detritus
(rating: good, quantification of parameters can be improved)
Reproduction:off-spring approach (rating: reasonable, but needs refinement)
Mortality:natural deaths and starvation rates, fishing mortalities,
(rating: reasonable, but difficult, partly questionable, needs further consideration)
The result is:
Warnemuende Food web Model (WFM)
Predator (cod):Model-equations
for biomass
and
abundance
WMF (show just a few equations)
averaged individual mass m=B/N
Prey (herring):Model-equations
for biomass
and
abundance
Feeding on herring reduces prey biomass and numbers!!!
Exp=9.1
initial number / km 3Nc = 10 4 - codNH = 10 5 - herringNs = 10 6 - sprat----------------------------------
Initial vectors of Cod, Herring and Sprat
MC0 = [0,0, 0,0, 0,0, 0,0, 0,0,Nc*CX5,Nc, 0,0]; MH0 = [0,0, NH*HX1,NH, NH*HX2,NH, NH*HX3,NH, NH*HX4,NH, 0,0]; MS0 = [0,0, Ns*SX1,Ns, Ns*SX2,Ns,Ns*SX3,Ns,0,0]; Pair structure:[…, initial mass in gram / km 3 , initial number / km 3, ...]
----------------------------------------------------------------------------------------------------------
Fishing mortality applied to larger mass classesFC6 = 6.8/104/d; FC7 = 8/103/d; FH5= 1/103/d
runs over 20 years
General increase of ind.-number, (prey development not limited by food (Z) )
Interannual variations of Catches
General increase in fish biomass due to missing limitation of food for prey,(bottom up)
Fishing pressure affects reproduction, (no reprod. in years 12-16)
Link to lower food web
P
DN
Z
Light, Tfish
Truncated model
Truncated modellZD = 0.03 /d
adjusted zooplankton mortality,
Coupling the NPZD-model to fish - three channels
Respirationof fish
Feeding of fish on Z
Fish mortality feeds back into D
1mmolC => 12 mgC => 100 mg = 0.1 g wetmass conversion
Exp 30.15 mor_opt=1
initial distributionZ-mortality rates [1/day]lZD=0.02/d;
No fishing mortality
Total Balance
high fishing mortalityExp 30.15 mor_opt=1.1
Total balanceNo external loads
Mortality rates [1/day]lZD=0.02/d;Fishing mortalities [1/day]FmortC6 = 6.8 10-4; FmortC7 = 8 10-3; FmortH6 = 2.7 10-4; FmortS5 = 2.7 10-4;
High fishing mortality,No external loads
Exp=30.15;option_mort=1.1;import_N=0,
Indication of a trophic cascade, orjust a decline due to removal of mass?
W.Fennel, Jour. Mar. Syst. (2007) in press
Exp=30.15;option_mort=1.1;import_N=0
Exp=30.15;option_mort=1.1;import_N=0.0063g/m³/d(0.003 mmolC/m³/d),
Exp=30.15;option_mort=1.1;import_N=0.0063g/m³/d( 0.003 mmolC/m³/d),
Increase in nutrients correlateswith catches until the mid 1980ties
Note
(F. Thurow 1997)
_______________________________________________________________________NO3 ~ 2-2.5 mmol/m³ , modelled total catches: 37 tons/km³ amounts to 481 10³ tonsNitrate level was observed around 1965Catch data ~ 500 10³ tons, in the 1960ties, ---------------------------------------------------------------------------------------------------------------------NO3 ~ 3 mmol/m³ , modelled total catches: 60 tons/km³ amounts to 780 10³ tonsNitrate level was observed around 1970-75Catch data ~ 800-850 10³ tons, in the 1970ties,
Catches provide independent data – (Volume of the central Baltic ~ 13 10³km³)Use the three example runs:
---------------------------------------------------------------------------------------------------------------------NO3 ~ 5 mmol/m³ , modelled total catches: 100 tons/km³ amounts to 1300 10³ tonsNitrate level was observed around 1975-85Catch data ~ 950-1000 10³ tons, in the 1980ties,
in this simple model, catches are controlled by nutrientsOverall values of the catches are consistent!
HoweverThe nitrate level of ~ 5 mmol/m³, was also observed in1985-95(implying modelled total catches ~ 1300 10³ tons)
but
Catch data dropped to ~ 500 10³ tons, in 1985-95!
Clearly, the model is in the current stage too simple, to mimic recruitment failures through combined actions of fishing and oxygen depletion in the halocline, etc.
virtually identical results for:N-load: dN/dt ~ 3 10-3 mmolC/m³/d, lZ = 2 10-4/d, extra Z mortality, andD-loss - flux into sediments: dD/dt ~ - 1.25 10-3 mmolC/m³/dorextra Z-mortality, lZ = 4. 1 10-4/d, and no D-loss
Opportunity
Skill assessment of truncatedmodels
Exp=30.15;option_mort=1.1;import_N=0.0063g/m³/d(0.003 mmolC/m³/d),
Issues & challenges:consolidation of parameter choices,
step by step increase of complexity of the NPZD componentoxygen dynamicsphytoplankton successionstate resolved copepods
Higher resolution of reproduction processes (refine the off-spring approach)
Higher order interactionprey feed on predator eggscannibalism
spatial explicit model migration from spawning to nursery region etc.behavior (forage, environmental preferences, etc)
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