mse and coastal zone management bill de la mare cmar february, 2011
TRANSCRIPT
MSE and Coastal Zone Management
Bill de la Mare
CMAR
February, 2011
Adaptive management
WorldDecisionRules
OutcomesHumanactivity
Measurements
Objectives
Adaptive management simulator
Model worldManagementDecisions
Outcomes
Modelhumanactivity
Simulated measurements
Objectives
Performance criteria
ManagementObjectives
ManagementProcedure
Exploited Population CatchCatch
DataDataEstimation of
Status
DataData
Physical WorldManagement WorldInvestment
Benefits
Fisheries
Regulationsand Catch Limits
Constraints
Environment
Social
Economic
Natural Capital
Institutional
More Best possible
Aspirations
Environment
Social
Economic
Natural Capital
Institutional
More Best possible
Environment
Social
Economic
Natural Capital
Institutional
More Best possible
Environment
Social
Economic
Natural Capital
Institutional
More Best possible
Reachable
space
Dealing with structural uncertainty and scenarios
Model World 1Outcome
s
Modelhuman
activity 1
Simulated measurements
Performance criteria
Model World 2
Model World 3
Model World n
Objectives
......
Modelhuman
activity 2
Modelhuman
activity n
...
Decisions
Component models in C2C MSE
Management decision and action models
Rural land-usemodels
Urban land-usemodels
River and stream biophysical models
Receiving water quality biophysical models
Selected taxa models
EHMP model
Future weather and climate scenarios
Future development scenarios
Assessment against objectives: environmental, social, economic
Water treatmentmodels
The information you …
… have is not the information you want
… want is not the information you need
… need is not the information you can obtain
… can obtain costs more than you can afford
Sod’s Law of Information
Objectivesof client or organiser
Science / Expertfacts, relationships,
models, maps, scenarios
ParticipatoryIntegrated Assessment
procedures, group interaction, moderation, information presentation,
scenarios, surprises
Policyfacts, relationships,
models, maps, scenarios
Policy-oriented synthesisfacts, relationships,
models, maps, scenarios
Adaptive management “open loop” simulator
Model world
Outcomes
Modelhumanactivity
Simulated measurements
Objectives
Decision maker
Adaptive management “closed loop” simulator
Model world
Outcomes
Modelhumanactivity
Simulated measurements
Objectives
Simulated decision maker
ManagementObjectives
ManagementStrategy
Natural capital CatchEcosystemservices
DataData
DataData
Physical WorldManagement WorldInvestment
Benefits
Economicactivities
Managementactions
Constraints
Estimation of status
DataData
DataData
Science / Research
AssessmentPolicy development
Political decision
Information flow
Strong / normative
Weak / normative
Weak
Very weak / absent
Current paths to science impact
Influence of assessments
External Factors-Historical context-User characteristics
Design of assessment-Process-Product
RelevanceCredibilityLegitimacy
Influences on:-Understanding-Goals-Decisions-Behaviour
RelevanceCredibilityLegitimacy
Influence of assessments
External Factors-Historical context-User characteristics
Design of assessment-Process-Product
RelevanceCredibilityLegitimacy
Influences on:-Understanding-Goals-Decisions-Behaviour
RelevanceCredibilityLegitimacy
Science / Research
AssessmentPolicy development
Political decision
Information flow
Strong / normative
Normative
Useability
More effective paths to science impact
Proposed increment in human activities
Region highlyImpacted?
Plan with existing/qualitative
models
Sustainability Probable?
OK
Plan with highfidelity models
A
Yes
Yes
No
No
Precautionary approachhas been satisfied
Multiple-useIssues?
Single-use MSE
Sustainability Probable?
OK
Multiple-use MSE
A
Sustainability Probable?
Adjust proposeduse
Rebalancemultiple uses
Yes
YesYes
No
No NoPrecautionary approachhas been satisfied
Science Challenges
Frontier science (combining natural and social sciences)
Interaction between natural and socio-economic systems
Complexity
Irredeemable uncertainty
Institutions, governance and policy
Competing demands, values and interests
Diversity of stakeholders
Uncertain management goals
Scarce scientific resources