1. Assessment of the main drivers of the Black Sea ecosystem functioning Mnemiopsis leidyi and Beroe ovata impact on the Black Sea ecosystem. Modeling approach.
Tamara Shiganova
P.P.Shirshov Institute of oceanology RAS, Moscow, RUSSIIA
Paul Nival
Laboratoire d'Oceanographie de Villefranche Villefranche-sur-Mer, FRANCE
The classical scheme of the functioning of a problem-free balanced ecosystem in an inland basin is based on а “top-down control” from large pelagic fishes and mammals to small pelagic fishes and lower to zooplankton (when large trophic zooplankton dominates) and algae (when diatom algae dominate. . In addition, in a problem-free ecosystem, the Si : N and Si : P ratios are higher than unity; otherwise, an eutrophication may emerge as it has happened in the northwestern part of the Black Sea in the 1970s–1980s

2. Distribution of M. leidyi in the native and invaded areas
Native area
Invaded area
Costello J. H., J. E. Purcell, K. M. Bahya, H. W. Mianzan & T. A. Shiganova, 2011

3. In the Black Sea, native gelatinous species belong to moderately cold-water species: the ctenophore Pleurobrachia pileus, scyphomedusa Aurelia aurita, and the pyrophyte alga Noctiluca scintillans. Two warm water invasive ctenophores arrived and established in the heated upper layer
Warm water species
Cold water species
Subdivision of the gelatinous species in their relation to mean seasonal, annual and minimal winter SST: analyses of field data according to main component method )

4. Dispersal of Mnemiopsis leidyi in the Eurasian seas
2006
2007
2005
2006
2006
2007
2005
1988
2005
1982
1999
2009
2009
1990
1992
1993
2009
Population genetic analyses supported its invasion from the Gulf of Mexico (e.g., Tampa Bay) into the Black Sea, then secondary into the Azov, northern Aegean and into the Caspian Sea and the Mediterranean (Ghaboolia, Shiganova et al., 2010)

5. Dispersal of Beroe ovata in the Eurasian seas
2000
2005
1997
1997
2004
1999
2011

6. Environmental data and M.leidyi invasion in the seas of Eurasia
Black Sea
Sea of Azov
The dark area
Corresponds to the
period of Mnemiopsis leidyi occurance
(observations)
Aegean Sea
Caspian Sea
Baltic Sea
After Shiganova et al., in press

7. Interannual variation of M.leidyi and B.ovata in the Black Sea

8. Zooplankton are the main food of M
Zooplankton are the main food of M.leidyi Change of interannual variability of edible zooplankton after appearance of invasive ctenophores in the inshore and offshore waters in August in the northeastern Black Sea

9. Field data in the coastal area
Mnemiopsis leidyi seasonal cycle in cold (1993) and warm (1994) year before B.ovata arrival
Field data in the coastal area
Warm year
Cold year
Cold year
r=0,6-08, p<0,001
Before the arrival of B.ovata, M.leidyi abundance was controlled by temperature and zooplankton prey

10. Temperature
Zooplankton A A E J
M.leidyi L L J E A
B.ovata

11. Interannual variability of phenology of ctenophores
M. leidyi and B.ovata in the coastal area of the NE Black Sea
--- M.leidyi
--- B.ovata
Time of appearance of B.ovata
Time of beginning reproduction of B.ovata
Time of appearance of M.leidyi
Time of pick of reproduction of M.leidyi

12.   -mortality Life stages and forcing factors
for M.leidyi and B.ovata J L A E
Individual based modeling approach was used to take into account life cycle and physiological features 
E – eggs
L-larva
J-juvenale
A-adult
 -mortality
Temperature
food

13. Forcing functions
Zooplankton biomass
Temperature

14. Mortality rate
Mortality rate
Temperature
Food
Model

15. Prey – predator individual based model structure
M.leidyi
food
B.ovata
Temperature

16. Age classes  1 2 no L 1 2 nL J 1 2 nJ A 1 2 nA
process
ageing

17.  Age classes 0% 50% 100% 1 2 no L 1 2 nL J 1 2 nJ A 1 2 nA process
0% % %  1 2 no L 1 2 nL J 1 2 nJ A 1 2 nA
process
ageing

18. Change in stage duration depending on physiology (food, temperature)

19. Ontogenetic cycle of M.leidyi and B.ovata development
Number individuals per unit of volume
Time (days)
first adult
first juvenile
Model
first larva
first egg

20. Reproduction rate
Experiments
Model
M.leidyi
B.ovata

21. Ingestion rate experiment Model Ingestion rate coefficient (0 – 1)
minFood
Food
C2= (Food- minFood)/ (Kf+ (Food-minFood))
C2 = when Food < minFood

22. Stage duration optimum conditions age to 50% transfer
Stage duration (days
Ingestion
Temperature (°C)
optimum conditions

23. First stage: M.leidyi present
B.ovata absent L A J
Simulation of a population of Mnemiopsis without Beroe
20 adults at begining of the year
Spawning start near day generations with low numbers befor the blooming when temperature and food are favorable E

24. Model Second stage B.ovata appears in surface water at time 200th day
M.leidyi
Model L A E J
Simulation of input of B.ovata in surface water at time 200th day.
M.leidyi develops a bloom, which is grazed by B.ovata
Predation on larvae, juveniles and adult on M.leidyi makes them disappear
B.ovata L
Simulation of imput of Beroe in surface water at time 200.
Mnemiopsiq develop a bloom which is grazed by Beroe
Predation on larva and juvenile Mn makes minimum in the abundance curve J E A

25. Model Field observations M.leidyi M.leidyi A E J B.ovata B.ovata
Simulation of imput of Beroe in surface water at time 200.
Mnemiopsiq develop a bloom which is grazed by Beroe
Predation on larva and juvenile Mn makes minimum in the abundance curve J E A A

26. Conclusions
In present Black Sea ecosystem there is a bottom up control from zooplankton to its consumer Mnemiopsis leidyi and finally to its predator Beroe ovata.
Annual changes in temperature and food availability are considered as the main factors that control these predators’ dynamics and their impact on pelagic ecosystem of the Black Sea.
Both field data analyses and individual based modeling confirmed that, with appearance B. ovata that controlled M. leidyi population, a recovering shift of the ecosystem appeared but was controlled by climate forcing.
Now in any case it is another ecosystem with two ctenophores that affected ecosystem but the time of high effect of M.leidyi is much shorter.

27. Acknowledgement
The research was performed in framework of project GK-0422

28. Thank you for attention