1 Adaptive Management: participatory collaboration to integrate research, policy and practice Jan...

Adaptive Management: participatory collaboration to

integrate research, policy and practice

Jan Sendzimir, Ph.D.International Institute for Applied Systems Analysis

sendzim@iiasa.ac.at

Illustration courtesy of WWF Hungary

Hungarian Tisza River Floodplain Pre- and Post- Engineering under the original Vasarhelyi Plan (1870)

The Tisza’s length was lowered by more than 400 kilometers

by cutting meanders to straighten the river to aid transport.

Floodplain area was lowered by squeezing channel between dikes

from 38500 km2 to 1800 km2 (in whole basin)

Multiple Crises in the Tisza River

Valley Ecology– Loss of biodiversity, habitat, beauty– Rising intensity and frequency of floods

Economic– Farms and related businesses disappearing– Loss of fishery, fruit, nut and timber industry

Socio-political– Disappearance of schools, communities– Children uninterested in history and culture

“Wicked” Problems:can recognize but not define

them.Malevolent “Policy Resistance”

Mix of Economical, Ecological, Political, Social factors

Cannot focus only one goal–No single objective function to maximize

Many players, actors, stakeholders–work at different levels (scales)–Use different values that are not commensurate - You can’t add them up

Wicked Problems*: Complex all the way

down. Can’t decompose any one level

into units that can be added back up to the whole picture.– EU, National, Provincial, County

Things are entangled within levels and across levels (up and down).

*Rittel, H., Webber, M. (1973). "Dilemmas in a General Theory of Planning." Policy Sciences 4:pp. 155-159.

Policy Resistance

Policies often create initial success, but in the long term the system evolves, re-configures, and creates surprises that completely defeat the initial policy.

Example from the USA– Policy: more appliances to reduce work and

create more leisure time,– Surprise: people have less leisure time now

than 1970 when they had fewer appliances.

Outline

Sources of Uncertainty – Nature – non-linear dynamics, hierarchical

structure– Society - management

Adaptive Management (AM)– Framework to integrate research and policy– Example applied to river renaturalization

AM applied for sustainability of river basins– SD Indicators - Oder River basin AM – Renaturalizing the Tisza river basin

Sudden Collapse of the Oldest, Richest Fishery on

Northwest Atlantic Cod Harvest (1895 – 1993)

AnnualCatchOf Cod(1000 tons)

1900 tons

90 tons25 yearsMore than 400 years

2003 – after 10 years, no sign of recovery

Catastrophic Examples ofSudden Shifts and Flips

Coral Reefscoral vs. algae

Arid Landscapesshrubland vs. grassland

Shallow Lakeseutrophic vs. clear

North Florida Forest– longleaf pine savanna & fire vs.

hardwood forest without fire

Adaptive System Dynamics

(after Peterson 2001 Using ecological dynamics to move toward an adaptive architecture IN Kibert,C., Sendzimir, J., Guy, B. (2001) Eds. Construction Ecology: Nature as a Basis for Green Building. Spon, Ltd., London )

HierarchyAsymmetrical Interactions between

levels

Constraint

Macro-

Micro-

Example

Forest

Person

Village

County

Constraint – higher to lower level– Global CO2 Plant productivity

Reorganization – higher to lower level– Wind Tree fall Light Shade tolerant plants

Disturbance – lower to higher level– Cigarette grass fire Tree fire Forest fire

Reorganization – small scale and surrounding areas– Mangrove forest recovery after hurricanes

Hierarchy – 4 Kinds of Relations

Asymmetrical Interactions between levels

Vegetative & Atmospheric Scales

Atmospheric processes occur faster than vegetative processes occurring at the same spatial scale.

LOG SPACE- km

century

decade

420- 2- 4- 6

1 000 yrs

1000km

standpatch

needle

forest

region

El Niño

long waves

thunderstorms

climate change

LOG TIME - years

Vegetative Structures

Atmospheric Processes

10 000 yrs

What Processes Produce the Forest Mosaic of Bialowieza?

Time and Space Scales of Processes Structuring the

Bialowieza ForestNo. Process Time

(Cycle Time)

Space(Window Edge)

1 Competition (Light) Seconds Centimeters

2 Senescence/Wind Throw

Days to Months Cm – 5 meters

3 Browsing by Megafauna

Months to Years Cm – 5 meters

4 Contagious Agents (Moths, Fire)

Year to 10 Years 50 m - kilometer

5 Agriculture, tree harvest

Year to 80 years 100 m - kilometers

6 Drought 10 to 100 years 100 kilometers

7 Geomorphology (Glaciers)

1000 to 10 000 yrs

1000 kilometers

Conceptual Basis for Engineering

Physical Systems1. Static, Stable2. Monotonous,

Homogenous3. Ahistoric4. Rules apply

over a range of scales

Ecological Systems1. Dynamic, Evolving2. Diverse,

heterogeneous3. Historic (memory)4. Different rules

apply at different scales

Engineering DangersPhysics-based Ecology-

based Rules, laws

– Apply over many scales because one set of physical processes works at more than one scale

– Cross-scale interactions are predictable

Negative externality– Failure=local, abrupt,

catastrophic– Large load bridge

collapse

Rules, laws– Apply at one scale because

one set of ecological processes works at only one scale

– Cross-scale interactions are hard to predict

Negative externality– Failure= Delayed, diffused,

spread over large area, – Irrigation canal blindness

Engineering DangersNatural Systems Human

Systems Backward looking

– Memory of landscape

• Storages of seeds, nutrients and water

• Genetic legacy• Landscape mosaic

– History of self-organization

• Patterns created by mutually reinforcing processes

Backward looking– Path dependency

• Built environment• Political & Cultural

history

Forward looking– Study, anticipate and

plan for the future– Gather information

and resources, organize and schedule work.

Outline

Conventional Response to Crisis: Reliving Mistakes

Policy asPolicy asSolutionSolution

CrisisCrisis

ManagementManagementAction as FixAction as Fix

AssessmentAssessment

Report StoredReport StoredIn LibraryIn Library

NextNextCrisisCrisis

Forgetting

A Failed Management Paradigm Reduce Nature’s Variability = An Economic

Engine Examples of Emergent Problems

following initial success at reducing variability Variability Reduction

Tool1. Nurseries, Larger Catch

capacity

2. Pesticides reduce crop yield variation due to pests

3. CFCs sustain cool temperatures

4. Dikes and channelization contain river level fluctuations

Emergent Problem1. Lost salmon wild

stocks

2. New species become pests, new capacities in old species

3. Ozone hole

4. Rising floodplain, lower capacity to absorb floods

New challenges for toxicologyFrom Endocrine Disruptor Chemicals

1. EDC’s have many counter-intuitive properties:• threshold assumption and non-monotonic effects

dosage

effect

Non-Toxic

ConventionalAssumption

ObservedDose-Effect Relations

• Synergy At a certain dosage, Chemical A is safe by itself but toxic in combination with Chemical B

Non-Toxic

Systems evolve – animals respond to global warmingby giving birth earlier (2 weeks earlier in Europe).

Actions may yield irreversible resultsEcosystems change “permanently”, afterthousands years they do not change back.

Oak Forests in Scotland 3000 B.C.

Pre-historicForestClearance

SoilChemistryChanges

Bogs in Scotland – Present Day

Blocked

Functioning of Dynamic ComplexityFunctioning of Dynamic Complexity

Because we cannot go back, it is dangerous to compare past with present.

DroughtDrought

Dynamics in SocietyWomen’s Rights in the 20th

Century 1920 – Vote 1940 – Cannot own business without

husband’s permission (Germany). 1970 – Cannot file tax return alone,

husband must co-sign (Austria). 1990 – Earn less money than men for

the same work. 2020 – Genetic engineering

– Design your children – what color eyes do you want?

Summary of ChallengesComplexity forbids us to rely

on: Standards

– Official levels for toxicity, biodiversity– Physical laws apply at all scales

Rules, Strategies, Legal Codes– Management actions often succeed

initially but fail when no learning or adapting occur

Understanding, Theory– System structure and functions change

Outline

Ways of explaining realityLife is a series of events

Management Pathology created by Events World

ViewHealth

Crisis

Chernobyl

Research Report

Myth: every event has one cause and one effect

Library

Policy

After 5Years thePublic Forgets

Eventual feedback loop – unplanned, unexpected, often wasted

Challenge: to improve learning and avoid crises

Ways of explaining reality

Events

Patterns, Trends

Systemic Structures

Mental Models

What just happened?

What’s been happening?Have we been here or some place similar before?

What are the forces at play contributing to these patterns?

What about our thinking allows this situation to persist?

Learning That Persistently Adapts

Truth is not constant but evolutionarySocial and natural systems continue to change

Initial responses to crises were not as important as the sustained capability to learn and respond accordingly.

Research and Management Linked in a

Cycle of Integrated Learning

Research and Management Linked in a

Cycle of Integrated LearningPolicy asPolicy asHypothesisHypothesis

EvaluationEvaluation

ManagementManagementActions asActions asTestsTests

AssessmentAssessment

Outline

StraighteningThe RiverKissimmee

1950 - 70

DECLINE or LOSS1. 75% of Floodplain Area2. 90% of Number of Birds3. 50% of River Length4. Hydrological link

between floodplain and river

5. Massive algal blooms on Lake Okeechobee

Restoring theKissimmee River Basin 1975 - 90Results – Project

restored1. River curves 2. Floodplain Area (11000

ha)3. Biodiversity 4. Hydrological link

between floodplain and river

5. Lake Okeechobee clear of algal blooms

6. Ecological functions of river and floodplain

Kissimmee River Basin Restoration

Elements of Success

Focus on large, slow driving variables– Raise big questions that inspire learning

• Don’t become lost in putting out fires

– Evolution of goals over 100 years• Survival Conquest Water Quantity

Control (Flood) Water Quality Control Provide Recreational and Environmental Values Provide Ecological Services Build Ecological Integrity Build Resilience

Elements of Success

Plan to learn, to change goals, adapt– We learn how to get there along the way

• We never know how at the beginning

– Demonstration and Pilot Projects• Explore technical issues related to restoring

ecological resilience• Research into public values and opinions

– Program to Monitor and Re-Evaluate• Hyrological performance and uncertainties

The Uncertainty ofUn-straightening a

River Stability of Back-filled Soils– 5 year monitored demonstration project

Sediment and River Mechanics– 3 year physical and math modeling

project Pre-channelization hydrology?

– Small scale restoration experiments with weirs in the floodplain established which hydrological regime was needed

Elements of Success

Stay close – learn and do things together– Build trust slowly

• Scoping: broad, inclusive initial assessment• Re-evaluation: persistently revisit key

questions

– Negotiated dialogue unites coalition• Technical Experts never too far in front • Public values challenge technical progress

Adaptive Management (AM):

Policies as Hypotheses

Adaptive Management (AM):

Policies as Hypotheses Policies• The question set, based on experience, that sets the stage of further action.

• Not magic bullets that address the right mix of objectives to solve a problem, rather they are astute hypotheses about how the world works

Embrace uncertainty by testing the best questions,

Avoid the trap of assuming certainty by rallying around “solutions.”

Adaptive Grazing Experiments Minnesota

Dairy Farm

Art Thicke, La Crescent, Minnesota

Adaptive Science and Practice in Minnesota Prairie

Streams

Adaptive Science and Practice in Minnesota Prairie

Streams Effective Collaboration

– Scientists provide theory and supervise fieldwork– Farmers manage cattle according to experimental

design and help monitor results– Local citizens help monitor stream conditions

Mutual Benefit– Stream conditions improve

– Erosion reduced, water quality improved– Diversity of habitats and species increased

– Farmers increase income and keep their farm– Local citizens learn science, ecology and farming and

spread the knowledge informally– Advance ecological theory on disturbances

Cycles of Erosion and Grazing

Outline

Connecting our Understanding to the

FutureHot and Dry

Unchanged

Cool and WetHypotheses

Understanding

Alternative Futures

Oder River Oder River BasinBasin

in Central in Central EuropeEurope

Study Study AreaArea

Oder River

PPoolliiccyy aassHHyyppootthheessiiss

((44,,55,,66))

EEvvaalluuaattiioonn((88))

MMaannaaggeemmeennttAAccttiioonnss aass TTeessttss

((77))

AAsssseessssmmeenntt((11,,22,,33))

Adaptive Management

Environmentallyfriendly farms

Revenues fromagri-environmental

programs

Brandattractiveness

Other farmsConversion/Abandoning

to env. friendly farm

Profits of env.friendly farms

Profits from greenlocal products

Region image

EnvironmentalQuality

Turisticattractiveness

R4Revenues from local products

through green image

Environmentalstandards

Social support forenvironmental

standards

Profitsfrom turism +

Environmental standardsrise costs and lower crops

Nature attractsturists

Economic Livingstandard in region +

Environmentallyfriendly practices

Revenues throughagri-environmental

programs

Revenuesfrom crops

Revenues from localproducts sales to tourists

Env. friendlyfarms supportlocal products

Rescueenvironment

Turisticinfrastructure

Attractiveness ofgreen local products

Cost of livingin region

Localself-sufficiency

Knowledge andExperience in env.friendly farming

Institutional Supportfor env. friendly farms+

Support for greenlocal products

Regional foodprocessing capacity

Local culturalidentity

Farmer's willingnessto cooperate

Brand promotion

Economic Livingstandard in region

Revenues fromagri-environmental

programs

Social support forenvironmental

standards

Environmental standardsrise costs and lower crops

Economic Livingstandard in region

Revenues throughagri-environmental

programs

Revenuesfrom crops

Rescueenvironment

Step by step (3)

Key Variables RegionalEnvironmentalModel (v.20)

Rules for Choosing Indicators

Each variable has at least one indicator

Goal: 15 indicators or less– Transparency in all phases of AM

requires a simple, small set of indicators understandable to everyone.

– Business experience supports this.

Importance (working group's view)

Measurabilty Compelling (Stakeholder's view)

No. Variable Indicator Explanation 0 - 5 0 - 3 0 - 41 Environmental Quality Biodiversity - Species number 5 1 3 9

2 Water quality 5 2 4 11

3 Percentage of viable habitat (green area) 5 1 3 9

4 Environmentally friendly farms Ratio EFF/Total in terms of Number 4 3 3 10

5 Ratio EFF/Total in terms of Area 4 3 3 10

6 Conversion rate 4 3 3 10

7 Revenues from agri-env programs Percentage of maximum subsidy 4 2 3 9

8 Percentage of min yearly income 4 2 3 9

9 GLP Production Sales revenues as percent of total sales per firm 3 2 3 8

10 Number of people employed 4 3 3 10

11 Number of firms 4 3 3 10

12 Profits from GLP total zlotych in region 4 2 2 8

13 Average profitability from GLP per firm 5 2 4 11

14 Profits from env friendly crops total zlotych in region 4 2 2 8

15 Average profitability from env friendly crops per farm 5 2 4 11

16 Profits from green tourism total zlotych in region 4 2 2 8

17 Average profitability from green tourism per firm 5 2 4 11

18 Organizational support for env friendly farms Hours of work on projects Government, NGO3 1 1 5

19 Perceived support by farmers Opinion surveys 4 2 3 9

20 Brand attractiveness Number of people who are aware and/or like brand Opinion surveys 5 1 3 9

21 Support for green local products Hours of work on projects Government, NGO 3 1 1 5

22 Perceived support by green local producers Opinion surveys 5 2 3 10

23 Social support for env standards Percentage of population who support Opinion surveys 5 1 3 9

Voting Criteria

Sustainability Indicators

Fitting Indicators to Variables

Key Variables Potential Indicators1. Environmental Quality

Biodiversity - Species number

Water quality

Percentage of viable habitat (green area)

2. Environmentally friendly farms

Ratio EFF/Total (Number)

Ratio EFF/Total (Area)

Conversion rate

Fitting Indicators to Variables

Key Variables Potential Indicators

3. Revenues from agri-environmental programs

Percentage of maximum subsidy

Percentage of minimum yearly income

4. Green LocalProduct Production

Sales revenues as percent of total sales per firm

Number of people employed

Number of firms

Setting Priorities in Choosing Indicators

Importance (Work Group’s Perspective)– Use experience from all exercises in mapping

interactions, key variables, and feedback loops to estimate what is important to achieve our sustainability goals.

Compelling (Stakeholders’ Perspective)– What is simple, clear, understandable, convincing or

communicable?

Measurability– What is accessible (inexpensive) and quantifiable?

Adaptive Assessment in Choosing Indicators

Questions or suspicions at any point can lead back to any other point in the process– Uncertainty about an indicator can

cause re-evaluation of:• Suspect indicator or associated indicators• Key Variable• Structure of mental map (loops,

interactions)

The modeling process is iterative.

Figure 3-1 Results of any step can yield insights that lead to revisions in any earlier step (indicated by the links in the center of the diagram).

1. Problem Articulation(Boundary Selection)

3. Formulation4. Testing

5. PolicyFormulation& Evaluation

2. DynamicHypothesis

Adaptive FrameworkIntegrating Research, Policy, Management & Local

Action

ProblemArticulation

MappingAssumptions

SettingObjectives

FindingIndicators

DesigningPolicies

Implementation

Monitoring,Evaluation

How to open the door tonovel visions and solutions?

Events

Patterns, Trends

Systemic Structures

Mental Models

What just happened?

What’s been happening?Have we been here or some place similar before?

What are the forces at play contributing to these patterns?

What about our thinking allows this situation to persist?

How to create real, decisive policy impacts?

Real World

Decisions(Experiments)

InformationFeedback

Strategy, Structure,Decision Rules

Mental Models ofthe World

Management

Single LoopLearning

Assessment

Real World

InformationFeedback

Management

Single LoopLearning

Assessment

Double-LoopLearning

Reflexive Appraisal

Real World

InformationFeedback

Management

Single LoopLearning

Assessment

Multi-LoopLearning

Reflexive Appraisal

L1,L2,L3,L4

Outline

64Illustration courtesy of WWF Hungary

Hungarian Tisza River Floodplain

The original is unattainable, to restore structure and function we must create and

learn as we manage.

Within an Adaptive Management framework use models of Ecological-economic interactions to explore management options, prioritize research, monitor and evaluate indicators, challenge and change people’s underlying world views.

NagykörüNagykörü

Tisza River Basin – Ukraine, Romania, Slovakia, Hungary

What ecological and economic functions work on an enlarged

floodplain?

Nagykörü

Restore Fish NurseriesReconnect abandoned clay-pits along the

RenewAncientOrchardsReintroduce Grazing

Function (small scale disturbance)

Revitalize backwaternurseries in ephemeral ponds

(1)(2)

Tisza riv

Monitoring Ecosystem Structure

– Geomorphology• Floodplain elevation, cross-sectional area,

– Patch structure • Distribution of Habitat sizes (area) and inter-patch

distances,

– Ecotones (pattern, packing) • Pattern – type, length, curvature, perimeter/area ratio• Packing - density of ecotones,

– Habitat connectivity • Degree to which size, proximity and pattern link

habitats,

– Community structure• Animals - Guilds • Plants and Animals - Species composition

Schiemer, F. and G. Janauer (1994). "Monitoring rivers and floodplains". Proc. Monitoring of ecological change in wetlands of middle Europe, Linz, Austria, Botanische Arbeitsgemeinschaft am Oberosterreichischen Landesmusium. Stapfia 31 pp.93-107

Monitoring Ecosystem Function

– Patch Dynamics • Distribution of Habitat sizes (area) and inter-patch

distances,

– Processes (P/R, nutrients, sediments), • Production/Respiration• Nutrient and Sediment cycling and movement

– Hydrological connectivity • Floodplain and channel(s)

– Community Dynamics• Animals - Guilds • Plants and Animals - Species composition

Schiemer, F. and G. Janauer (1994). "Monitoring rivers and floodplains". Proc. Monitoring of ecological change in wetlands of middle Europe, Linz, Austria, Botanische Arbeitsgemeinschaft am Oberosterreichischen Landesmusium. Stapfia 31 pp.93-107

Institutionscan neutralize the best science and

methods

Society’s institutions (anthropology)– Incentives

• Formal – constitution, law, rulings, ordinances, policies

• Informal – understandings, customs, habits

Institutional barriers in the Tisza basin– Centralization of political and taxing power– Policies to manage water or set markets

Institutional bridge– EU requirement to lower grain production

SummarySummary

Durable solutions to wicked problems– require that understanding, policy and innovative action can flex and adapt to changes in nature and society

– require integration of theory, research and practice across disciplines and sectors of society

–We must work simultaneously on the parameters, the feedback loops and the world views.

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