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Populations and sustainability :- Fisheries


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An hour long lecture on the role of Management and Operational Research in the governance of global fisheries. Global fisheries, like many open access natural resources, suffer for a tragedy of the commons effect. Population dynamic modelling can help provide the insights and understanding necessary to achieve sustainability.

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Populations and sustainability :- Fisheries

  1. 1. Populations and sustainability :- Fisheries Daniel Sandars (10-12-2014)
  2. 2. 2010=US$ 91.2 billion
  3. 3. EU Fishing Effort 1950
  4. 4. EU Fishing effort Now
  5. 5. Conflicts
  6. 6. Global fish stocks
  7. 7. The ‘tragedy of the commons’
  8. 8. Play the fisheries game
  9. 9. Fisheries Management Biological conservation Fish stocks & Natural habitats Fishing Employment, viable remote communities, foreign exchange, economic efficiency, & social equity
  10. 10. Sustainability's-commitment
  11. 11. Biological Conservation fish_survey2.html Population Dynamics Stock Assessment Environment Stock Interactions
  12. 12. Socio economics – markets, labour, & incomes Fishing – access, rights & enforcement Fishing - effort, technology, structure, & investment Exploitation management
  13. 13. Management system Management Economic Direct Days at sea, number of vessels, fishing times, holding capacity, engine size Indirect Taxes on fuel or sales of fish Fishing rights – licences, sole ownership, individual quota, community quota, territorial rights Monitoring Judicial system Biological Net sizes, quotas, area closures, nursery area protection Fisheries management
  14. 14. Scientific approach to fisheries management
  15. 15. Operational Research methods •Descriptive Mathematical Modelling •Qualitative information on complex variable systems •Anticipate stock behaviour in response to environment, fishing, regulation •Computer Simulation •What-if of management choices •Qualitative evaluation of management strategies •Information on the dynamic behaviour of complex systems •Mathematical Programming •The optimal solution/ management decisions •Most profitable fishing effort and investment •Least cost regulation and monitoring •Decision Theory •Evolving decisions given evolving information (catch data) availability •Fisheries management decisions •Fishing management decision •Statistical Estimation •The impact of uncertainty/ stochasticity •Statistical analysis of other modelling approaches •Design of exploitation and monitoring efforts
  16. 16. Operational Research methods Descriptive mathematical modelling Population dynamics Stock exploitation Stock interactions Stock allocation Socio-economic issues Computer simulation Population dynamics Stock assessment Stock exploitation Stock interactions Environmental dependencies Stock allocation Socio-economic issues Optimizing mathematical programming Population dynamics Stock assessment Stock exploitation Environmental dependencies Decision theory Population dynamics Stock exploitation Statistical estimation Stock assessment Stock exploitation
  17. 17. Fish Population Dynamics WelcometoSustainableDevelopmentatQueens/RelatedResearch/EcosystemApproachtoF isheriesManagement/
  18. 18. Population dynamics Learn about the behaviour and sensitivity of the fishery • Given key assumptions and parameter estimates • Do equilibrium conditions develop? • What are the nature of any dynamic fluctuations? • Is the population stable? • Does it exhibit statistical stationarity? • How robust and complete is the model? Are results repeatable?
  19. 19. Model typology Population dynamics Lumped parameters Discrete time Ricker 1975 Continuous time Schafer model (Schafer 1957) Dynamic pools (age cohorts) Beverton and Holt 1957 • Beverton RJH and Holt SJ 1957 On the dynamics of exploited fish populations. Fisheries Investigations Series II, vol. 19. Ministry of Agriculture, Fisheries and Food, Her Majesty's Stationary Office, London, UK, 533pp • Ricker WE 1975 Computation and interpretation of biological statistics of fish populations. Bulletin Fisheries Research Board Canada 191, 382pp • Schaefer MB (1957) "Some considerations of population dynamics and economics in relation to the management of marine fishes" Journal of the Fisheries Research Board of Canada, 14: 669–81.
  20. 20. BIDE Model • N1 = N0 + B − D + I − E • N=Number in population in time period 1 or 0 • B=Births • D=Deaths • I=Immigrants • E=Emmigrants Caswell, H. 2001. Matrix population models: Construction, analysis and interpretation, 2nd Edition. Sinauer Associates, Sunderland, Massachusetts. ISBN 0-87893-096-5.
  21. 21. Carrying capacity • Ricker model –density dependence • N= population size at time t • r0 = intrinsic growth rate (births and immigration)- (deaths + emigration) • K = carrying capacity
  22. 22. Harvest Control Rule
  23. 23. Population data –data poor environments • Birth rate or recruitment to catchable size • + Growth rate – size and length • - Death rate –harvested or natural (predation, age, disease) • Commercial catches give regular data on the catchable fraction – Survey ships give less data on all age groups • NB Over-simplistic modelling of fisheries has resulted in the collapse of key stocks
  24. 24. Concluding remarks • Wild fisheries suffer from the tragedy of the commons • Global competitive markets are emerging • Strong fishing drivers for increased productivity with lower investment and operating costs • Increasing awareness of complex environmental issues • Better sustainable fisheries management practice are needed • The significant role of OR models seems unquestionable
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  26. 26. References • Lane, D.E. Operational research and fisheries management (1989) European Journal of Operational Research, 42 (3), pp. 229-242. Cited 6 times. • Bjørndal, T., Lane, D.E., Weintraub, A. Operational research models and the management of fisheries and aquaculture: A review (2004) European Journal of Operational Research, 156 (3), pp. 533-540. Cited 26 times. • Arnason, R. Fisheries management and operations research (2009) European Journal of Operational Research, 193 (3), pp. 741-751. Cited 11 times.