PARTICIPATORY MODELLING TO ENHANCE

UNDERSTANDING AND CONSENSUS WITHIN

FISHERIES MANAGEMENT: THE BALTIC HERRING

CASEPäivi Haapasaari

Samu Mäntyniemi

Sakari Kuikka

Fisheries and Environmental Management Group

(FEM)

University of Helsinki

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JAKFISH (EU 7TH PROGRAMME)

Aim: examine and develop institutions, practices and tools that allow complexity, uncertainty and ambiquity to be dealt with effectively within participatory decision making processes

Develop participatory facilitation tools, like participatory modeling

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CASE :PARTICIPATORY MODELLING OF BALTIC MAIN BASIN HERRING

Focus: Factors behind the negative biomass trend and poor growth rates of Baltic Main Basin herring stock

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PARTICIPATORY MODELLING OF BALTIC HERRING : TWOFOLD FOCUSES AND AIMS

Influencing factorsHypotheses →

modelsBuild a meta-

model?Embed parameters

provided by scientific research?

Examine, develop methodology

Validity and reliability of models?

Benefit knowledge base and management?

Understand herring fishery Participatory modelling

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TWO PARTS OF MODELLING

1. Five most important factors that influence

Survival of eggs Growth Mortality

2. + or - effect?3. Strengths of effects4. Uncertainty of

assessments?

1. Which variables?2. Objectives?3. Management

measures?

→ no quantitative information

Biological system model Boundaries for herring fishery management

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MODEL TYPE : BAYESIAN NETWORKS

Qualitative part (graphical model of variables and their relationships)

Model structure based on subjective conceptualisation of problem→ Structure complex systems in understandable

way→ Focus for discussion

Quantitative part: (probability distributions)→ Uncertainty explicit→ Knowledge from different sources and

accuracies6

PARTICIPATION MODE

6 selected stakeholders Researcher Manager Fisherman organisation Commercial fisherman Environmental NGO

Individual stakeholders separately → 6 different models

4-6 hours Stakeholder

(modeling decisions) Modeling expert

(facilitator) Social scientist

(observer) Documentation:

record modelling, discussions, enquiry

Stekeholders and models Modelling sessions

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STAKEHOLDER MODELS

Stakeholders had quite a similar understanding on factors influencing growth, recruitment and natural mortality (total sum of different factors not high) but more differences emerged in assessing strengths of the links → most difficult task!

Defining boundaries and components for herring fishery system easier, but different perspectives brought much variability

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Growth

NaturalMort.

Survival ofeggs

Size distribution

Biomass

Number of fish

Catch inweight

Catch innumbers

Size dist.In catch

Decision Uncertain UtilityBaltic Main Basin herring: framing the problem

Time frame: Annual dynamics

Average salary for fiehermen, stable over years. Nation specificForever, uncertain value

Fishing capacity

Number of fishermen

Price of fish

Fishing effort

Fishing cost

TAC

Dist. Of TAC

Feedback!

Marketsituation

State of economy

Type of processing

Price of fuel

Fishing taxPort costs

Gear cost

Gear regulationsClosed areas/seasons

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Baltic Main Basin herring: framing the problem

Time frame: Annual dynamics

Decision

Growth

NaturalMort.

Survival ofeggs

Size distribution

Biomass

Number of fish

Catch inweight

Catch innumbers

Size dist.In catch

Uncertain

Keep herring pop..on certain level

Fish.mort

SSB not affecting Recr. (H-stick)Seas.&spatial closure

on Sp. groundsTAC

ObserverScientific surv.

Stomach sampling

Cod

Manag. Measures for cod

Sprat

Manag. Measures for sprat

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STAKEHOLDER FEEDBACK

Complexity and high uncertainty of herring fishery Epistemic

uncertainty: general lack of knowledge

Variability uncertainty: system in constant change

Improve understandin Raise awareness Share questions Demonstrate views Combine viewpoints to

improve consensus Improve communi-

cation and cooperation Bring decision-making

closer to grass root level

Difficult Positive

Mee

t eac

h ot

her: G

o th

roug

h th

e st

eps to

gethe

r!

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RESEARCH CONTINUES… Analyse, compare individual models and

build meta-model with the BN tool Present the model to stakeholders, ask

Whether they can adopt the information? Problems?

Assess how well meta-model covers important variables?

Discuss major areas of uncertainty Analyse differences between views →update

model Consider management actions Analyse the process!

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SUMMARY: INCLUDING ECONOMIC AND SOCIAL INFORMATION TO FISHERIES ANALYSIS AND ADVICE: WHY, HOW AND BY WHOM?

Why? Improve understanding of a complex system and its uncertainties.

How? Through synthesising relevant knowledge from different stakeholders and sources through participatory modeling using BNs

By whom? Individuals from different stakeholder groups + scientific expertise of statisticians, fishery scientists, social scientists (etc.)

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Thank you!

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