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Management Scenarios for Fished Resources of the New Caledonian Lagoon Using a Spatially-Explicit Model Bastien PREUSS Dominique Pelletier and Laurent.

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Presentation on theme: "Management Scenarios for Fished Resources of the New Caledonian Lagoon Using a Spatially-Explicit Model Bastien PREUSS Dominique Pelletier and Laurent."— Presentation transcript:

1 Management Scenarios for Fished Resources of the New Caledonian Lagoon Using a Spatially-Explicit Model Bastien PREUSS Dominique Pelletier and Laurent Wantiez UNC/LIVE – IFREMER/LEAD – IRD/CoRéUs2 – ZONECO Tuesday 23 th 2014, FFMB, Nouméa

2 Context  New-Caledonia: km² land km² lagoon inhabitants

3 Context MPA (no take) Legend UNESCO World Heritage Central area Buffer area  New-Caledonia: km² land km² lagoon inhabitants  Noumea and suburbs: inhabitants  Important fishing pressure  Management : MPA network (7 units)  Growing population: Request for additional management measures Decision support tool

4 ISIS-Fish model Existing knowledge Management scenarios assessment Sensitivity analysis Modeled system Calibration Field work Natural system Approach

5 Model Isis-Fish spatially explicit population and fisheries dynamic model. Population model Fisheries model Management model Simulation of the modeled system ISIS-Fish

6 Population model Population Age groups Z1Z1 Z1Z1 … … … … ZkZk ZkZk … … … … ZmZm ZmZm … … … … Study site

7 Population model Time Year 1 Year 0 Year 2 Change of age group Movement Reproduction Recruitment Natural mortality + Fishing mortality

8 Soutenance de thèse B. PREUSS - 8 octobre 2012 Biology and ecology : – Max length : 120 cm – Max age : 26 years – Piscivore – Territorial – Hermaphrodite protogynous – Low mobility Biology and ecology : – Max length : 62 cm – Max age : 27 years – Macrocarnivore – Non territorial – Hermaphrodite protogynous – High mobility

9 Spatial structure

10 North South Center South edge North – South gradient

11 Spatial structure Coast Intermediate Barrier Coast – Barrier reef gradient

12 Spatial structure

13 NorthSouthCenter Coast Intermediate Barrier South edge MPA Spatial structure

14 NorthSouthCenter Coast Intermediate Barrier South edge MPA Fish mobility Dispersal Reproduction

15 Fishing activities Professionallogbook data Recreationalfield work interviews Nb of fishing strategies Annual catch Professional23.5 t20.5 t Recreational t5.8 t Data analysis = MCA + HCA

16 Minimisation of an target fonction by multiple objective calibration : f = ( observed - modeled ) ² Natural system Modeled system Observations Model outputs = ? Parameters X Soutenance de thèse B. PREUSS - 8 octobre 2012 Fenicia et al., 2005, simulations is 34.5 days Calibration

17 Validation Recreational Annual cath (kg) Professional Simulated Observed estimated

18 Sensitivity Analysis Interest : highlighting main sources of uncertainty Method : fractional factorial simulation plan

19 Results Population biomassCatches Indice de sensibilité

20 Scenarios Scenario 1Reference (statu quo) Scenario 2Creation of 1 MPA Scenario 3Legal size (maturity) Scenario 410 more professional fishing licences

21 H1H2 Recruitment Management Other sources of uncertainty Scenario 1Scenario 2Scenario 3Scenario 4Scenario 1Scenario 2Scenario 3Scenario 4 Simulation plan Scenario 1Scenario 2Scenario 3Scenario 4 Recruitment uncertainty Other sources of uncertainty Management scenarios assessment under uncertainty reference optimistic

22 Population biomassCatches Management scenarios assessment Statu quo 10 pro Legal size MPA H1 H2 H1 H2

23 Management scenarios assessment

24 Focus on MPA Local effect – Biomass variation (%) between scenario statu quo and scenario MPA

25 Conclusion

26 Soutenance de thèse B. PREUSS - 8 octobre 2012 Fish populations Fisheries Lack of knowledge Uncertainty (Reproduction – recruitement ; stock assessment) Lack of knowledge Uncertainty (precision of data) Knowledges review and data analysis Research goal Field and data analysis Management goal Constraint = Data Scenarios assessment Constraint = Computer capability

27 Perspectives Assessing more hypothesis of recruitment. Assessing different types of mobility (density dependence). Assessing different hypotheses of larval dispersal. Assessing more management scenarios (MPA location, MPA network, large vs small).

28 Thank you Bon appétit !

29 Management scenarios assessment Biomass Catch H1 H2 H1 H2 Statu quo MPA Legal size 10 pro Statu quo 10 pro Legal size MPA Statu quo 10 pro Legal size MPA

30 Méthode d’Analyse de sensibilité i valeurs par paramètre Si i = 2 Plan d’expérience factoriel fractionnaire Modèle Sorties du modèle Paramètre x Soutenance de thèse B. PREUSS - 8 octobre 2012 Plan factoriel fractionnaire 2 k simulations Classement des paramètres Indice de sensibilité 137 simulations soit 6 jours 30

31 Recruitment (3 months/yr) Stock-recruitment: 1 simulation (red line) Random recruitment : 35 simulations (black lines) H1 H2

32 Recruitment (1 month/yr) Yr 1 Yr 2Yr 3Yr 4Yr 5Yr 6Yr 7 Yr 8 Yr 9Yr 10Yr 11Yr 12 Yr 13Yr 14 1 year of recruitment (1 cohort) support the population H2


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