• Used as a Consensus Building Tool in anOpen, Participatory Process

• Multi-scale, Landscape Scale and Larger

• Acknowledges Uncertainty and Limited Predictability

• Acknowledges Values of Stakeholders

• Simplifies by Maintaining Linkages and and Synthesizing

• Evolutionary Approach Acknowledges History, Limited Optimization, and the Co-Evolution of Humans and the Rest of Nature

Integrated Dynamic Ecological Economic Modeling

Gund Institute for Ecological Economics, University of Vermont

1. Scoping Models high generality, low resolution models produced with broad participation by all the stakeholder groups affected by the problem.

2. Research Models more detailed and realistic attempts to replicate the dynamics of the particular system of interest with the emphasis on calibration and testing.

3. Management Models medium to high resolution models based on the previous two stages with the emphasis on producing future management scenarios - can be simply exercising the scoping or research models or may require further elaboration to allow application to management questions

Three Step Modeling Process*

Increasing Complexity,

Cost, Realism,and Precision

*from: Costanza, R. and M. Ruth. 1998. Using dynamic modeling to scope environmental problems and build consensus. Environmental Management 22:183-195.

Modules

Site/PatchUnit Models

Small Watersheds

Large Watersheds

Global

Natural Capital Built Capital Human CapitalSocial Capital

hydrology,nutrients,plants

buildings,roads,power grid

population,education,employment,income

institutions,networks,well being

Biome BGC,UFORE

General Ecosystem Model (GEM)

Everglades Landscape Model (ELM)Patuxent Landscape Model (PLM)Gwyns Falls Landscape Model (GFLM)

General Unified Metamodel of the BiOsphere (GUMBO)

RHESSysHSPF

Spat

ial E

xten

t

Suite of interactive and intercalibrated models over a range of spatial, temporal and system scales (extents and resolutions)

Ln of Resolution

Higher(smaller grain)

Lower(larger grain)

Ln

of P

red i

c ta b

i lit y

Data Predictability

Model Predictability(different models have different slopes and points of intersection)

"Optimum" resolutions for particular models

from: Costanza, R. and T. Maxwell. 1994 . Resolution and predictability: an approach to the scaling problem. Landscape Ecology 9:47-57

GUMBO (Global Unified Metamodel of the BiOsphere)

Atmosphere

Anthropo-sphere

EcosystemServices

HumanImpacts

Natural Capital Human-madeCapital(includes Built CapitalHuman Capital,and Social Capital

SolarEnergy

Hydrosphere

Lithosphere

Biosphere

11 Biomes

From: Boumans, R., R. Costanza, J. Farley, M. A. Wilson, R. Portela, J. Rotmans, F. Villa, and M. Grasso. 2002. Modeling the Dynamics of the Integrated Earth System and the Value of Global Ecosystem Services Using the GUMBO Model. Ecological Economics 41: 529-560

AnthroposphereAnthroposphere

Marc ImhoffBiospheric Sciences BranchNASA

QuickTime™ and aCinepak decompressor

are needed to see this picture.

Gund Institute for Ecological Economics, University of VermontHuman impacts on global biology and material cycles

Atmosphere

QuickTime™ and aYUV420 codec decompressor

are needed to see this picture.

Weather-related economic damages have increased

Sea-viewing Wide Field-of-View Sensor (SeaWiFS) data on marine and terrestrial plant productivity

Biosphere

QuickTime™ and aYUV420 codec decompressor

are needed to see this picture.

Human Capital EconomicProductionProcess

GoodsandServices

EvolvingCulturalNorms andPolicy

Well Being(Individual andCommunity)

Consumption(based on changing,adaptingpreferences)

Education, training,research.

Building

Investment(decisions about, taxescommunity spending,education, science andtechnology policy, etc., basedon complex propertyrights regimes)

Individual Public

GNP

Wastes

Common

Ecologicalservices/amenities

having, being

- having,- being

negative impacts on all forms of capital

being, doing, relating

Restoration,Conservation

Natural Capital

ManufacturedCapital

having

positive impacts on human capital capacity

doing, relatingComplex propertyrights regimes

SolarEnergy

SocialCapital

Lim

ited

Sub

sti tu

tabi

li ty

Bet

wee

n C

api ta

l For

ms

“Full World” Model of the Ecological Economic System

Waste heat

Institutionalrules, norms, etc.

Materially closed earth system

From: Costanza, R., J. C. Cumberland, H. E. Daly, R. Goodland, and R. Norgaard. 1997. An Introduction to Ecological Economics. St. Lucie Press, Boca Raton, 275 pp.

COOL POWERPOINT 1-from ESR

Comparison Between Quality of Life and Its Components BetweenBurlington VT, and a Selection of Intentional Communities

1.00

2.00

3.00

4.00

5.00

Total Q

uality

of Life

Built Cap

ital

Natural

Capita

l

Human

Capita

l

Social

Capita

l1 (Fr

iends

& Family)

Social

Capita

l2 (Neig

hbors

)

Aver

age

Scor

e (1

=no

t at

all

to 5

= v

ery

grea

tly)

BurlingtonIntentional Communities

Goal

Basic Framework

Non-environmentally adjusted measures

Environmentallyadjusted measures

AppropriateValuationMethods

___________

Marketed

value ofmarketed goods

and servicesproduced and

consumed in aneconomy

GNP(Gross National

Product)GDP

(Gross DomesticProduct) NNP

(Net National Product)

NNP’(Net National Product

including non-produced assetts)

Market values

EconomicIncome Weak

Sustainability

1 + non-marketed goods

and servicesconsumption

ENNP (Environmental NetNational Product)

SEEA (System of

EnvironmentalEconomic Accounts)

1 + Willingness to Pay Based Values (see

Table 2)

___________

StrongSustainability

2 + preserveessential natural

capital

SNI(Sustainable National

Income)

SEEA(System of

EnvironmentalEconomic Accounts)

2 + Replacement Costs,+

ProductionValues

Economic Welfare

value of the wefareeffects of income and

other factors(including

distribution,household work, loss

of natural capitaletc.)

MEW(Measure of Economic

Welfare)

ISEW(Index of SustainableEconomic Welfare)

3 +ConstructedPreferences

HumanWelfare

assessment ofthe degree towhich human

needs arefulfilled

HDI (Human

Development Index)

HNA(Human NeedsAssessment)

4 + ConsensusBuildingDialogue

A range of goals for national accounting and their corresponding frameworks,measures, and valuation methods

from: Costanza, R., S. Farber, B. Castaneda and M. Grasso. 2000. Green national accounting: goals and methods. Chapter in: Cleveland, C. J., D. I. Stern and R. Costanza (eds.) The nature of economics and the economics of nature. Edward Elgar Publishing, Cheltenham, England (in press)

Column A: Personal Consumption ExpendituresColumn B: Income DistributionColumn C: Personal Consumption Adjusted for Income InequalityColumn D: Va lue of Household LaborColumn E: Va lue of Volunteer WorkColumn F: Services of Household CapitalColumn G: Services Highways and StreetColumn H: Cost of CrimeColumn I: Cost of Family BreakdownColumn J: Loss of Leisure TimeColumn K: Cost of UnderemploymentColumn L: Cost of Consumer DurablesColumn M: Cost of CommutingColumn N: Cost of Household Pollution AbatementColumn O: Cost of Automobile AccidentsColumn P: Cost of Water PollutionColumn Q: Cost of Air PollutionColumn R: Cost of Noise PollutionColumn S: Loss of WetlandsColumn T: Loss of FarmlandColumn U: Depletion of Nonrenewable ResourcesColumn V: Long-Term Environmental DamageColumn W: Cost of Ozone DepletionColumn X: Loss of Forest CoverColumn Y: Net Capital InvestmentColumn Z: Net Foreign Lending and Borrowing

ISEW (or GPI) by Column

US

40

90

140

1940 1960 1980 2000

UK

40

90

140

1940 1960 1980 2000

Germany

40

90

140

1940 1960 1980 2000

Austria

40

90

140

1940 1960 1980 2000

Netherlands

40

90

140

1940 1960 1980 2000

Sweden

40

90

140

1940 1960 1980 2000

Chile

4090

140190240

1940 1960 1980 2000

Indices of ISEW (Index of SustainableEconomic Welfare) and GDP (1970 = 100)

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

1950 1960 1970 1980 1990 2000Year

$/ca

pita

BurlingtonChittendenVermontUS

Genuine Progress Indicator (GPI) per capita

ECOSYSTEM SERVICES

Gas regulation

Climate regulation

Disturbance regulation

Water regulation Water supply

Erosion control and sediment retention

Soil formation

Nutrient cycling

Waste treatment

Pollination

Biological control

Refugia

Food production

Raw materials

Genetic resources

Recreation

Cultural

ECOSYSTEM FUNCTIONS

Regulation of atmospheric chemical composition.

Regulation of global temperature, precipitation, and other biologically mediatedclimatic processes at global, regional, or local levels. Capacitance, damping and integrity of ecosystem response to environmental fluctuations such as sea level rise. Regulation of hydrological flows.

Storage and retention of water.

Retention of soil within an ecosystem.

Soil formation processes.

Storage, internal cycling, processing, and acquisition of nutrients.

Recovery of mobile nutrients and removal or breakdown of excess or xenic nutrients and compounds. Movement of floral gametes.

Trophic-dynamic regulations of populations.

Habitat for resident and transient populations.

That portion of gross primary production extractable as food.

That portion of gross primary production extractable as raw materials.

Sources of unique biological materials and products.

Providing opportunities for recreational activities.

Providing opportunities for non-commercial uses.

Ecosystem Services and FunctionsEcosystem Services and Functions

GUMBO (Global Unified Metamodel of the BiOsphere)

Atmosphere

Anthropo-sphere

EcosystemServices

HumanImpacts

Natural Capital Human-madeCapital(includes Built CapitalHuman Capital,and Social Capital

SolarEnergy

Hydrosphere

Lithosphere

Biosphere

11 Biomes

From: Boumans, R., R. Costanza, J. Farley, M. A. Wilson, R. Portela, J. Rotmans, F. Villa, and M. Grasso. 2002. Modeling the Dynamics of the Integrated Earth System and the Value of Global Ecosystem Services Using the GUMBO Model. Ecological Economics 41: 529-560

Global Unified Metamodel of the BiOsphere (GUMBO)• was developed to simulate the integrated earth system and assess the dynamics and

values of ecosystem services. • is a “metamodel” in that it represents a synthesis and a simplification of several

existing dynamic global models in both the natural and social sciences at an intermediate level of complexity.

• the current version of the model contains 234 state variables, 930 variables total, and 1715 parameters.

• is the first global model to include the dynamic feedbacks among human technology, economic production and welfare, and ecosystem goods and services within the dynamic earth system.

• includes modules to simulate carbon, water, and nutrient fluxes through the Atmosphere, Lithosphere, Hydrosphere, and Biosphere of the global system. Social and economic dynamics are simulated within the Anthroposphere.

• links these five spheres across eleven biomes, which together encompass the entire surface of the planet.

• simulates the dynamics of eleven major ecosystem goods and services for each of the biomes

Built Capital

Knowledge

GOODS &

SERVICES

Knowledge Formation

Built Capital Formation

Social Capital FormationSocial Capital

Labor Force

Ecosystem Goods Production

Fossil Fuel ExtractionOrganic Matter Harvested

Ecosystem Services Production

Ore Production

Economic Production

Natural Capital Formation

Water use

WASTE

Disturbance Regulation

Gas RegulationClimate RegulationSoil Formation

Recreation and Cultural Services

Plant Nutrient Uptake

Waste Assimilation Potential

Personal Consumption

Economic Production

-

Savings rates

Welfare

Welfare from human made capital

Knowledge

Social Capital

- Welfare from waste

Welfare from consumption

Welfare from Ecosystem Services

Built Capital

Welfare

1000

800

600

400

200

0

Wetland 3000

2500

2000

1500

1000

500

0

Ice and Rock

2000

1500

1000

500

0

Tundra 6000

5500

5000

4500

4000

3500

3000

Grasslands

6000

5500

5000

4500

4000

3500

3000

Forests1000

800

600

400

200

0

Urban

4000

3000

2000

1000

021002050200019501900

Croplands2000

1500

1000

500

021002050200019501900

Desert

Years

Landuse Changes

23

22

21

20°C

Global Temp1300120011001000

900800700

Giga

Ton

C Atmospheric Carbon

0.4

0.3

0.2

0.1

0.0

met

ers

Sealevel 2000

1500

1000

500

0

Was

te e

quiv

alen

ts (n

orm

aliz

ed fo

r 190

0)

Waste

4.0

3.5

3.0

Giga

Ton

C eq

uiva

lent

s

Alternative Energy

1210

86420

Giga

Ton

C Fossil Fuel extraction

1.0

0.8

0.6

0.4

0.2

0.0

Foss

il_Fu

el_M

arke

t_Sh

are

equi

vale

nts

(nor

mal

ized

for 1

900)

21002050200019501900Year

Fossil FuelMarket share

16141210

864

Giga

Ton

C eq

uiva

lent

s

2050200019501900Year

Total Energy

Startrek Big Goverment Ecoptopia Mad Max

Basecase Observations

Physics

20

15

10

5billi

ons

of in

divi

dual

s

Human Population

4.0

3.5

3.0

2.5

2.0

1.5

SOCI

AL_N

ETW

ORK

equi

vale

nts

(nor

mal

ized

for 1

900)

21002050200019501900Year

The Social Network

2000

1500

1000

500

0

Prod

uctiv

ity In

vest

ed

Knowledge

8000

6000

4000

2000

0

Prod

uctiv

ity In

vest

ed

Built Capital

800

600

400

200

0Pr

oduc

tivity

Inve

sted

Built capital per capita

300250200150100

500

Prod

uctiv

ity In

vest

ed

Knowledgeper capita

1.2

1.0

0.8

0.6

0.4

0.2

SOCI

AL_N

ETW

ORK_

PerC

ap e

quiv

alen

ts (n

orm

aliz

ed fo

r 190

0)

21002050200019501900Year

Social network per capita

Ecotopia Startrek Mad Max Big Goverment Basecase Observations

0.030

0.025

0.020

0.015

0.010

0.005

0.000

Price on waste treatment30

25

20

15

10

5

0

Price on soil formation

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Price on Cultural and recreational service

20

15

10

5

0

Price on Nutrient cycling

10

8

6

4

2

0

Price on gas regulation

30

25

20

15

10

5

0

Price on Disturbance regulatiuon

10

8

6

4

2

02050200019501900

Year

Climate price100

80

60

40

20

021002050200019501900

Year

Energy price

7000

6000

5000

4000

3000

Waste_Treatment7.2

6.8

6.4

6.0

Soil Formation

24

20

16

12

Recreation and_Culture 0.9

0.8

0.7

0.6

Nutrient_Cycling

12

10

8

6

4

2

Gas_regulation2.76

2.72

2.68

2.64

Disturbance Regulation

10.90

10.85

10.80

10.75

10.70

10.65

21002050200019501900Year

Climate Regulation 500

400

300

200

100

21002050200019501900Year

Ecosystem services value

Ecotopia StartrekMad Max Big Goverment Basecase

1.0

0.8

0.6

0.4

0.2

Global_Welfare

80

60

40

20

GWP_per_Capita120

100

80

60

40

20

1989

dol

lars

GWP

0.16

0.12

0.08

0.04

Welfare_per_capita

0.20

0.16

0.12

0.0821002050200019501900

Year

food_per_capita2.0

1.5

1.0

0.5

21002050200019501900Year

Energy_per_Capita

10-4

10-3

welfa

re p

er c

apita

equ

ival

ents

(nor

mal

ized

for 1

900)

Welfare_GNP_Index

Ecotopia Startrek MadMax Big GovermentBasecase Observations

In Conclusion:The main objective in creating the GUMBO model was not to accurately predict the future, but to provide simulation

capabilities and a knowledge base to facilitate integrated participation in modeling.

It should be noted that this is “version 1.0” of the model. It will undergo substantial changes and improvements as we continue to develop it, and the conclusions offered here can only be thought of as “preliminary.” Nevertheless, we can reach some

important conclusions from the work so far, including:

To our knowledge, no other global models have yet achieved the level of dynamic integration between the biophysical earth system and the human socioeconomic system incorporated in GUMBO.

Preliminary calibration results across a broad range of variables show very good agreement with historical data. This builds confidence in the model and also constrains future scenarios.

• We produced a range of scenarios that represent what we thought were reasonable rates of change of key

parameters and investment policies, and these bracketed a range of future possibilities that can serve as a basis for further discussions, assessments, and improvements. Users are free to change these parameters further and observe the results.

Assessing global sustainability can only be done using a dynamic integrated model of the type we have created in GUMBO. But one is still left with decisions about what to sustain (i.e. GWP, welfare, welfare per capita, etc.) GUMBO allows these decisions to be made explicitly and in the context of the complex world system. It allows both desirable and sustainable

futures to be examined.

Ecosystem services are highly integrated into the model, both in terms of the biophysical functioning of the earth system and in the provision of human welfare. Both their physical and value dynamics are shown to be quite complex.

The overall value of ecosystem services, in terms of their relative contribution to both the production and welfare functions, is shown to be significantly higher than GWP (4.5 times in this preliminary version of the model).

“Skeptical” investment policies are shown to have the best chance (given uncertainty about key parameters) of achieving high and sustainable welfare per capita. This means increased relative rates of investment in knowledge, social capital, and

natural capital, and reduced investment in built capital and consumption.

• To our knowledge, no other global models have yet achieved the level of dynamic integration between the biophysical earth system and the human socioeconomic system incorporated in GUMBO. This is an important first step.

• Historical calibrations from 1900 to 2000 for 14 key variables for which quantitative time series data was available produced an average R2 of .922.

• A range of future scenarios representing different assumptions about future technological change, investment strategies and other factors have been simulated

• Assessing global sustainability can only be done using a dynamic integrated model of the type we have created in GUMBO. But one is still left with decisions about what to sustain (i.e. GWP, welfare, welfare per capita, etc.) GUMBO allows these decisions to be made explicitly and in the context of the complex world system. It allows both desirable and sustainable futures to be examined.

• Ecosystem services are highly integrated into the model, both in terms of the biophysical functioning of the earth system and in the provision of human welfare. Both their physical and value dynamics are shown to be quite complex.

• The overall value of ecosystem services, in terms of their relative contribution to both the production and welfare functions, is shown to be significantly higher than GWP (4.5 times in this preliminary version of the model).

• “Technologically skeptical” investment policies are shown to have the best chance (given uncertainty about key parameters) of achieving high and sustainable welfare per capita. This means increased relative rates of investment in knowledge, social capital, and natural capital, and reduced relative rates of consumption and investment in built capital.

GUMBO Conclusions