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.
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. Scientific approach
to fisheries
management
http://www.theorsociety.com/Pages/Feature/Feature201309Johari.aspx
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. 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. Fish Population
Dynamics
http://www.qub.ac.uk/research-centres/
WelcometoSustainableDevelopmentatQueens/RelatedResearch/EcosystemApproachtoF
isheriesManagement/
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. 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. 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. Carrying capacity
• Ricker model –density dependence
• N= population size at time t
• r0 = intrinsic growth rate (births and immigration)-
(deaths + emigration)
• K = carrying capacity
http://sites.duke.edu/ecologytools/populationdynamics/scenario-1/
24. 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
25. 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
27. 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.