understanding, modeling and valuing ecosystem services · alabama power’s motto: ... robert...

Understanding, Modeling and Valuing Ecosystem Services

Robert CostanzaGordon and Lulie Gund Professor of Ecological Economics and Director, Gund Institute of Ecological EconomicsRubenstein School of Environment and Natural ResourcesThe University of VermontBurlington, VT 05405 www.uvm.edu/giee

Full World Full World AnthroposphereAnthroposphere

Marc ImhoffBiosphericSciences Branch

NASA

QuickTime™ and aCinepak decompressor

are needed to see this picture.

Source: Stern review on the economics of climate change, 2006

QuickTime™ and a decompressor


Potential policy-relevant tipping elements in the climate system. (from Lenton et al. 2008)

In a full world context, what is “the economy” and what is it for?

”Empty World" Model of the Economy

Labor

Land

EconomicProcess

GoodsandServices

CulturalNorms andPolicy

IndividualUtility/welfare

Consumption(based on fixedpreferences)

Improvement

Education, Training,Research

Building

Investment(decisions about, taxesgovernment spending,education,science andtechnologypolicy, etc., basedon existing propertyrights regimes)

Property rights

Private Public

GNP

Manufacturedcapital

Per

fec t

Sub

stitu

tabi

li ty

Bet

wee

n F a

ctor

s

Empty World Energy

Planning?

Alabama Power’s motto:“Always on”

“With Electricity prices at least 15% below the national average, why not?

Human Capital EconomicProductionProcess

GoodsandServices

EvolvingCulturalNorms andPolicy

Well Being(Individual andCommunity)

Consumption(based on changing,adaptingpreferences)

Education, training,research.

BuildingInvestment(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

S ubs

titut

abilit

yBe

twee

n C

apita

l For

ms

“Full World” Model of the Ecological Economic System

Institutionalrules, norms, etc.

Materially closed earth system

Waste heat

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.

The key is developing a

better understanding

of the opportunities

to create a sustainable

future with a high quality of

life

The Commons“ refers to all the gifts we inherit or create together. This notion of the commons designates a set of assets that have two characteristics:

they’re all gifts, andthey’re all shared.

A gift is something we receive, as opposed to something we earn. A shared gift is one we receive as members of a community, as opposed to individually. Examples of such gifts include air, water, ecosystems, languages, music, holidays, money, law, mathematics, parks, the Internet, and much more”.

Peter Barnes, Capitalism 3.0

QuickTime™ and aTIFF (Uncompressed) decompressor


TrumanEisenhower

Kennedy

Johnson

Reagan

G. H. W.Bush

NixonFord

Carter

ClintonG. W.Bush

Gross Production vs. Genuine Progress for the US, 1950 to 2002(source: Redefining Progress - http://www.rprogress.org)

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. 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.

From: Costanza, R. R. d'Arge, R. de Groot, S. Farber, M. Grasso, B. Hannon, S. Naeem, K. Limburg, J. Paruelo, R.V. O'Neill,R. Raskin, P. Sutton, and M. van den Belt. 1997. The value of the world's ecosystem services and natural capital. Nature387:253-260

Ecosystem services are the benefits humans derive from ecosystem functioning

Ecosystem Services: the benefits humans derive from ecosystems

Example Valuation Techniques•Avoided Cost (AC): services allow society to avoid costs that would have been incurred in the absence of those services; flood control provided by barrier islands avoids property damages along the coast. •Replacement Cost (RC): services could be replaced with man-made systems; nutrient cycling waste treatment can be replaced with costly treatment systems. •Factor Income (FI): services provide for the enhancement of incomes; water quality improvements increase commercial fisheries catch and incomes of fishermen. •Travel Cost (TC): service demand may require travel, whose costs can reflect the implied value of the service; recreation areas attract distant visitors whose value placed on that area must be at least what they were willing to pay to travel to it. • Hedonic Pricing (HP): service demand may be reflected in the prices people will pay for associated goods: For example, housing prices along the coastline tend to exceed the prices of inland homes. •Marginal Product Estimation (MP): Service demand is generated in a dynamic modeling environment using production function (i.e., Cobb-Douglas) to estimate value of output in response to corresponding material input. •Contingent Valuation (CV): service demand may be elicited by posing hypothetical scenarios that involve some valuation of alternatives; people would be willing to pay for increased preservation of beaches and shoreline. •Group Valuation (GV): This approach is based on principles of deliberative democracy and the assumption that public decision making should result, not from the aggregation of separately measured individual preferences, but from open public debate.

Valuation of ecosystem services based on the three primary goalsof efficiency, fairness, and sustainability. ___________________________________________________________________________

Goal or Who Preference Level of Level of Specific Value Basis votes Basis Discussion Scientific Input Methods

Required Required ___________________________________________________________________________

Efficiency Homo Current low low willingness economius individual to pay

preferences

Fairness Homo Community high medium veil ofcommunicus preferences ignorance

Sustainability Homo Whole system medium high modeling naturalis preferences with

precaution ___________________________________________________________________________

from: Costanza, R. and C. Folke. 1997. Valuing ecosystem services with efficiency, fairness and sustainability as goals. pp: 49-70 in: G. Daily (ed.), Nature's Services: Societal Dependence on Natural Ecosystems. Island Press, Washington, DC, 392 pp.

EcoServices classified according to spatial characteristics

1. Global-Non Proximal (does not depend on proximity)1&2. Climate Regulation

Carbon sequestration (NEP)Carbon storage

17. Cultural/Existence value2. Local Proximal(depends on proximity)

3. Disturbance Regulation/ Storm protection9. Waste Treatment10. Pollination11. Biological Control12. Habitat/Refugia

3. Directional Flow-Related: flow from point of production to point of use4. Water regulation/flood protection5. Water supply6. Sediment regulation/Erosion control 8. Nutrient regulation

4. In situ (point of use)7. Soil formation13. Food production/Non-timber forest products14. Raw materials

5. User movement related: flow of people to unique natural features15. Genetic resources16. Recreation potential17. Cultural/Aesthetic

EcoServices Classified According toRivalness and Excludability

Excludable Non-Excludable

MarketGoods andServices(most provisioning services)

Open AccessResources(some provisioning services) Rival

Public Goods and Services(most regulatory and cultural services)

CongestableServices(some recreation services)

Non-rival

Picture taken by an automatic camera located at an electrical generating facility on the Gulf Intracoastal Waterway (GIWW) where the Route I-510 bridge crosses the GIWW. This is close to where the Mississippi River Gulf Outlet (MRGO) enters the GIWW. The shot clearly shows the storm surge, estimated to be 18-20 ft. in height..

1839187019932020

Past and Projected Wetland Loss in the Mississippi Delta (1839 to 2020)

NEW ORLEANS

Coastal Louisiana

History of coastal Louisiana wetland gain and loss over the last 6000 years, showing historical net rates of gain of approximately 3 km2/year over the period from 6000 years ago until about 100 years ago, followed by a net loss of approximately 65 km2/yr since then.

Global Storm Tracks 1980 - 2006

Figure 1. Typical hurricane swath showing GDP and wetland area used in the analysis.

The value of coastal wetlands for hurricane protectionln (TDi /GDP i)= α + β1 ln(gi) + β 2ln(wi) + ui (1)

Where:

TDi = total damages from storm i (in constant 2004 $U S);

GDPi = Gross Domestic Produc t in the swath of storm i (in constant 2004 $U S). The

swath was considered to be 100 k m wide by 100 km inland.

gi = maximum wind sp eed of storm i (in m/sec)

wi = area of herbaceou s wetlands in the storm swath (in ha).

ui = error

Predicted total damages from storm i

TDi = eα ∗ giβ 1 ∗ wi

β 2 ∗GDPi

∆TDi = eα ∗ giβ 1 ∗ (wi −1)β 2 − wi

β 2( )∗GDPi

Avoided cost from a change of 1 ha of coastal wetlands for storm i

Figure 2. Observed vs. predicted relative damages (TD/GDP) for each of the hurricanes used in the analysis.

R2 = 0.60

$100

$1,000

$10,000

$100,000

$1,000,000

1,000 10,000 100,000 1,000,000

Area of coastal wetlands in average swath (ha)

A B

Figure 3. Area of coastal wetlands (A) in the average hurricane swath vs. the estimated marginal value per ha (MVsw) and (B) in the entire state vs. the total value (TVs) of coastal wetlands for storm protection.

•A loss of 1 ha of wetland in the model corresponded to an average $33,000 (median = $5,000) increase in storm damage from specific storms.

•Taking into account the annual probability of hits by hurricanes of varying intensities, the annual value of coastal wetlands ranged from $250 to $51,000/ha/yr, with a mean of $8,240/ha/yr (median = $3,230/ha/yr)

• Coastal wetlands in the US were estimated to currently provide $23.2 Billion/yr in storm protection services.

From: Costanza, R., O. Pérez-Maqueo, M. L. Martinez, P. Sutton, S. J. Anderson, and K. Mulder. 2008. The value of coastal wetlands for hurricane protection. Ambio (in press)

NATURE |VOL 387 | 15 MAY 1997 253

article

The value of the world’s ecosystemservices and natural capitalRobert Costanza*†, Ralph d’Arge‡, Rudolf de Groot§, Stephen Farberk, Monica Grasso†, Bruce Hannon¶,Karin Limburg#I, Shahid Naeem**, Robert V. O’Neill††, Jose Paruelo‡‡, Robert G. Raskin§§, Paul Suttonkk& Marjan van den Belt¶¶* Center for Environmental and Estuarine Studies, Zoology Department, and † Insitute for Ecological Economics, University of Maryland, Box 38, Solomons,Maryland 20688, USA‡ Economics Department (emeritus), University of Wyoming, Laramie, Wyoming 82070, USA§ Center for Environment and Climate Studies, Wageningen Agricultural University, PO Box 9101, 6700 HB Wageninengen, The NetherlandskGraduate School of Public and International Affairs, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA¶ Geography Department and NCSA, University of Illinois, Urbana, Illinois 61801, USA# Institute of Ecosystem Studies, Millbrook, New York, USA** Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, Minnesota 55108, USA†† Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA‡‡ Department of Ecology, Faculty of Agronomy, University of Buenos Aires, Av. San Martin 4453, 1417 Buenos Aires, Argentina§§ Jet Propulsion Laboratory, Pasadena, California 91109, USAkkNational Center for Geographic Information and Analysis, Department of Geography, University of California at Santa Barbara, Santa Barbara, California 93106,USA¶¶ Ecological Economics Research and Applications Inc., PO Box 1589, Solomons, Maryland 20688, USA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The services of ecological systems and the natural capital stocksthat produce them are critical to the functioning of theEarth’s life-support system. They contribute to human welfare, both directly and indirectly, and therefore representpart of the total economic value of the planet.We have estimated the current economic value of 17 ecosystem servicesfor 16 biomes, based on published studies and a few original calculations. For the entire biosphere, the value (most ofwhich is outside the market) is estimated to be in the range of US$16–54 trillion (1012) per year, with an average ofUS$33trillion per year. Because of the nature of the uncertainties, thismust be considered a minimum estimate. Globalgross national product total is around US$18 trillion per year.

2nd most cited article in the last 10 years in the Ecology/Environment area according to the ISI Web of Science.

Summary of global values of annualecosystem services (From: Costanza et al. 1997)

Value per ha

($/ha/yr)

Global Flow Value

(e12 $/yr) Biome Area

(e6 ha)

577 252

4052 22832 19004 6075 1610

804 969

2007 302 232

14785 9990

19580 8498

92

20.9 8.4

12.6 4.1 3.8 0.3 4.3

12.3 4.7 3.8 0.9 0.9 4.9 1.6 3.2 1.7

0.1

33.3

MarineOpen OceanCoastal

Estuaries Seagrass/Algae Beds Coral Reefs Shelf

TerrestrialForest

Tropical Temperate/Boreal

Grass/RangelandsWetlands

Tidal Marsh/Mangroves Swamps/Floodplains

Lakes/RiversDesertTundraIce/RockCroplandUrban

Total

36,302 33,200

3,102 180 200 62

2,660

15,323 4,855 1,900 2,955 3,898

330 165 165 200

1,925 743

1,640 1,400

332

51,625

http://www.nj.gov/dep/dsr/naturalcap/

Problems with the Nature paper (as listed in the paper itself)1. Incomplete (not all biomes studied well - some not at all)2. Distortions in current prices are carried through the analysis3. Most estimates based on current willingness-to-pay or proxies4. Probably underestimates changes in supply and demand curves

as ecoservices become more limiting5. Assumes smooth responses (no thresholds or discontinuties)6. Assumes spatial homogeneity of services within biomes7. Partial equilibrium framework8. Not necessarily based on sustainable use levels9. Does not fully include “infrastructure” value of ecosystems10. Difficulties and imprecision of making inter-country

comparisons11. Discounting (for the few cases where we needed to convert from

stock to flow values)12. Static snapshot; no dynamic interactions

Solving any of these problems (except perhaps 6 which could go either way) will lead to larger values

Integrated Modeling of Humans Embedded in Ecological Systems

• Can be used as a Consensus Building Tool in anOpen, Participatory Process

• Multi-scale in time and space

• Acknowledges Uncertainty and Limited Predictability

• Acknowledges Values of Stakeholders

• Multiple Modeling Approaches, Cross-Calibration, and Integration

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

The Patuxent and Gwynns Falls Watershed Model s(PLM and GFLM)

http://www.uvm.edu/giee/PLMThis project is aimed at developing integrated knowledge and newtools to enhance predictive understanding of watershed ecosystems(including processes and mechanisms that govern the interconnect -ed dynamics of water, nutrients, toxins, and biotic components) andtheir linkage to human factors affecting water and watersheds. Thegoal is effective management at the watershed scale.

Participants Include:Robert CostanzaRoelof BoumansWalter BoyntonThomas MaxwellSteve SeagleFerdinando VillaAlexey VoinovHelena VoinovLisa Wainger

GUMBO (Global Unified Model 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

1000

800

600

400

200

0

Wetland 3000

2500

2000

1500

1000

500

0

Ice and Rock

2000

1500

1000

500

0

Tundra6000

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

0

21002050200019501900

Croplands2000

1500

1000

500

0

21002050200019501900

Desert

Years

Landuse Changes

23

22

21

20

°C

Global Temp

1300

1200

1100

1000

900

800

700

Gig

a To

n 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

Gig

a To

n C

equ

ival

ents

Alternative Energy

12

10

8

6

4

2

0

Gig

a To

n C

Fossil Fuel extraction

1.0

0.8

0.6

0.4

0.2

0.0

uel_

Mar

ket_

Sha

re e

quiv

alen

ts (n

orm

aliz

ed fo

21002050200019501900Year

Fossil FuelMarket share

16

14

12

10

8

6

4

Gig

a To

n C

equ

ival

ents

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

CIA

L_N

ETW

OR

K e

quiv

alen

ts (n

orm

aliz

ed fo

r21002050200019501900

Year

The Social Network

2000

1500

1000

500

0

Pro

duct

ivity

Inve

sted

Knowledge

8000

6000

4000

2000

0

Pro

duct

ivity

Inve

sted

Built Capital

800

600

400

200

0

Pro

duct

ivity

Inve

sted

Built capital per capita

300

250

200

150

100

50

0

Pro

duct

ivity

Inve

sted

Knowledgeper capita

1.2

1.0

0.8

0.6

0.4

0.2

_NE

TWO

RK

_Per

Cap

equ

ival

ents

(nor

mal

ize

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 treatment

30

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

0

2050200019501900Year

Climate price100

80

60

40

20

0

21002050200019501900Year

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_regulation

2.76

2.72

2.68

2.64

Disturbance Regulation

10.90

10.85

10.80

10.75

10.70

10.65

21002050200019501900Year

Climate Regulation500

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

0.08

21002050200019501900Year

food_per_capita2.0

1.5

1.0

0.5

21002050200019501900Year

Energy_per_Capita

10-4

10-3

are

per c

apita

equ

ival

ents

(nor

mal

ized

for 1

9

Welfare_GNP_Index

Ecotopia Startrek MadMax Big GovermentBasecase Observations

500

400

300

200

100

trill.

US

Dol

lars

(199

8)

2050200019501900Year

Ecosystem Services Value

Multiscale Integrated Modeling of

Ecosystem Services

(MIMES)www.uvm.edu/giee/mimes 1

Project Goals

Outcome 1. A suite of dynamic ecological economic computer models specifically aimed at integrating our understanding of ecosystem functioning, ecosystem services, and human well-being across a range of spatial scales.

Outcome 2. Development and application of new valuation techniques adapted to the public goods nature of most ecosystem services and integrated with the modeling work

Outcome 3. Web-based delivery of the integrated models & results to a broad range of potential users.

Major Accomplishments:

•Global network of collaborators (> 100, 14 countries)•Collaborative development of models (MIMES) including biophysical dynamics and valuation•Initial results and ongoing applications at calibration sites (Global, Vermont, Amazon, PNW, Mexico, Marine)•Web sites for collaboration, education, and model delivery•Publication of results in multiple venues•Commitments for applications to multiple sites around the world

Collaborative Model DevelopmentMeetings:October 2006, Burlington, VTMarch, 2007, Costa RicaJune, 2007, SeattleJuly, 2007, Burlington, VTOctober 2007, New HampshireNovember 2007 Burlington, VTDecember 2007 Brazil

University of VermontAustin Troy FacultyRobert Costanza FacultyRoelof Boumans FacultySerguei Krivov FacultyAmos Baehr Graduate StudentEric Garza Graduate StudentGalen Wilkerson Graduate StudentGary Johnson Graduate StudentJuan Alvez Graduate StudentKarim Chichakly Graduate StudentKenneth Bagstad Graduate StudentMark Gately Graduate StudentRobin Kemkes-Wengell Graduate StudentShuang Liu Graduate StudentValerie EspositoGraduate StudentAzur Moulaert Project ManagerAnju Dahiya Modeling ExpertErnie Bufford Spatial Analysis LaboratoryJarlath O'Neil-Dunne Spatial Analysis LaboratorySean McFaden Spatial Analysis LaboratoryEneida Campos Gund Fellow, BrazilJoe Roman Gund FellowGuy Derry Web Developer

External Participants & Current PartnersCutler Cleveland Boston UniversityLes Kaufman Boston UniversityGiselle Samonte Tan Conservation International, DCKeith Alger Conservation International, DCMiroslav Honzak Conservation International, DCRodrigo Moura Conservation International, BrazilRosimeiry Portela Conservation International, DCBrett Bryan CSIRO, AustraliaSo-Min Cheong University of KansasDavid Batker Earth Economics, SeattleKen Lindeman Florida Institute of TechnologyKathy Hibbard National Center for Atmospheric ResearchRobert Muetzelfeldt SimulisticsJasper Taylor SimulisticsHal Mooney Stanford UniversityRalph Seppelt UFZ, GermanyPaul C. Sutton University of DenverSteve Farber University of PittsburghTrista Patterson USDA Forest Service, Juneau AKRudolf deGroot Wageningen UniversityAdemar Romeiro Unicamp, BrazilPaolo Sinisgalli Embrapa, BrazilLuis Steinle Camargo BrazilMaria Ramos Fasabien BrazilWilson Rotatori Correa BrazilDaniel Caixeta Andrade BrazilWilson Cabral Sousa BrazilColin Beer State University of New York ESFMarcos Amend Conservation Strategy Fund, BrazilDenis Ojima Colorado State UniversityFred Sklar South Florida Water Management DistrictDan Childers Florida International UniversityPaul West The Nature ConservancyBelinda Morris The Nature ConservancyRichard Howart Dartmouth CollegeBrett Bryan CSIROCharles Hopkinson Woods Hole Marine Biological LaboratoryKenneth Mulder Green Mountain CollegeRobin Naidoo World Wildlife Fund

MIMESAncestry

Figure 1. MIMES ancestry, showing some of the models that have been incorporated in the MIMES framework.

The modeling software: Simile http://www.simulistics.com/

Mimes Version Control

C:\Documents and Settings\Roel\My Documents\My Models\MIMES\trunk\models

MIMESMulti-scale Integrated Models of Ecosystem Services

LocationBiosphere

Earth Surfaces

NutrientCycling

Hydrosphere Lithosphere Atmosphere

Anthroposphere

Cultures

Biodiversity

EcosystemServices

Water by

Reservoir

Geological Carbon

Ores

Earth Energy

Gasses

ExchangesBetweenLocations

Social Capital

Human Capital

Economie

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



Biosphere

Three complementary and synergistic ways to include humans in models and modeling:

1. As “stakeholders” and active participants in the model conceptualization, development, construction, testing, scenario development, and implementation processes.

2. As “players” of the models where the model is used as both a decision aid and as a research tool to better understand human behavior in complex valuation and decision processes.

3. As “agents” programmed into the model based on better understanding of their goals and behavior gleaned through 1 and 2.

Ability to select specific areas to model at variable spatial and temporal resolution, in their global and regional context

A range of calibrationsites used by project partners to test model applicability and performance. These include in the first phase:Amazon, Pacific northwest, Winoskiwatershed, Vermont, and Global

Landuse

Soil drainage

type

Water regulation

Land Use

Soil Drainage type

Water Regulation

Ecosystems (% Area)

Croplands Wetlands

Urban

Forests

Tundra

Oceans43

1990 economic production in $ PPP by country

Research Households

AgricultureTransportation

Tourism Fisheries44

Ecosystem Services

Climate Regulation

Biological Regulation

Natural Hazard Mitigation

Cultural Heritage

Genetic Information

Inorganic Resources

45

Case studies under development

Tab to web



Atmosphere

Next Steps:1. Further development and testing of MIMES

2. Application to a large number of sites around the world in support of PES systems, carbon trading, national accounting, etc. in collaboration with local partners

3. make MIMES the most widely used and trusted system for ecosystem service modeling and evaluation in the world

A Few Conclusions:

•If the goal is sustainable human well-being, a good or services’ value is it’s relative contribution to achieving that goal, whether people perceive that contribution or not. Conventional, preference-based valuation techniques are therefore limited and not the only alternatives.

•Integrated modeling at multiple scales is an essential tool for understanding and quantifying the complex interdependencies and trade-offs in human systems embedded in ecological systems.••Ecosystem services are largely public goods (non-rival and non-excludable) which means that privatization and conventional markets will not work well (if at all). We need alternatives like PES systems, ecological tax reform, Full cost accounting, etc.



www.eoearth.org

Thank YouPapers mentioned in this talk available at:

www.uvm.edu/giee/publications:

MIMES website at:www.uvm.edu/giee/mimes