Alternative Ways to Understand and Assessthe Impacts of Atmospheric Pollutants

Jon D. EricksonRubenstein School of Environment & Natural Resources

Gund Institute for Ecological Economics • University of Vermont

Colin M. BeierAdirondack Ecological Center

SUNY College of Environmental Science & Forestry

Capturing the Value of Ecosystem Services

Capturing the Value of Ecosystem Services

• Evolution of “Ecosystem Services”

• Role of Modeling

• Cases

– Climate Change & Disturbance Regulation

– Human Impact & Recreation Amenities

• ES & NYSERDA

Evolution of Ecosystem Services

Stock-Flow Fund-Servicevs.

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

Source: Costanza et al., “The Value of the World’s Ecosystem Services and Natural Capital,”Nature 387: 253-260, 1997.

Millennium

Ecosystem

Assessment

5-10% of the area of five biomes was converted between 1950 and 1990

More than two thirds of the area of two biomes and more than half of the area of four others had been converted by 1990

Net

Pre

sen

t V

alu

e($

/hec

tare

)

Source: Millennium Ecosystem Assessment

Role of Modeling

Three Levels of Modeling1. Scoping Models

High generality, low resolution, broad participation

by all stakeholder groups.

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

3. Management ModelsMedium to high resolution. Emphasis on producing future management scenarios. Can be exercising #1 or #2, or require further elaboration to apply management questions.

IncreasingComplexity,

Cost, Realism,and Precision

Source: Costanza, R. and M. Ruth, “Using Dynamic Modeling to Scope EnvironmentalProblems and Build Consensus,” Environmental Management 22: 183-195, 1998.

A systems framework for ES assessment…

EcosystemProcesses Benefit

Flows

Direct feedbacksto society

ProvisioningRegulatingCultural

ExternalDrivers

ExternalDrivers

Beier et al. (2008) Ecosystems

Beier et al. (2008) Ecosystems

Cases

Climate Change & Disturbance Regulation

(Scoping Model)

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

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..

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.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

-7000 -6000 -5000 -4000 -3000 -2000 -1000 0 1000

Years Before Present

We

tla

nd

Are

a (

sq

km

) 3 sq km/yr

Net wetland gain

65 sq km/yr

Net wetland loss

Global Storm Tracks 1980 - 2006

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

TDi e gi

1 wi 2 GDPi

TDi e gi

1 (wi 1) 2 wi 2 GDPi

Predicted total damages from storm i

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

The value of coastal wetlands for hurricane protection

ln (TDi /GDP i)= + 1 ln(gi) + 2ln(wi) + ui (1)

Where:

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

GDPi = Gross Domestic Product in the swath of storm i (in constant 2004 $US). The

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

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

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

ui = error

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

0.0001

0.0010

0.0100

0.1000

1.0000

0.0001 0.0010 0.0100 0.1000 1.0000 10.0000

TD/GDP observed

TD

/GD

P p

red

icte

d

Opal 2005

Jeanne 2004 Andrew 1992

Fran 1996

Katrina 2005

Allen 1980

Hugo 1989

Isabel 2003

Elena 1985

Erin 1995

Bill 2003

Allison 1989

Charley 1998

Isidore2002

Dennis 1999

Alberto 1994

Bob 1991

Gloria 1985

Gaston 2004

Keith 1988

Jerry 1989

Irene 1999

Danny 1997

Chantal 1989

Allison 2001

Floyd 1999

Bret 1999

Emil ly 1993

Alicia 1983

Frances 2004

Lili 2002

Bonnie 1998

Charley 2004

Ivan 2004

R2 = 0.60

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

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

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

Costanza, R., O. Pérez-Maqueo, M. L. Martinez, P. Sutton, S. J. Anderson, and K. Mulder, “The value of coastal wetlands for hurricane protection,” Ambio 37:241-248, 2008.

Cases

Human Impact & Recreation Amenities

(Research/Management Model)

Adirondack Park

• 6-million acre state park, established in 1880s.

• No harvesting or timber management on public land.

• Public land managed almost exclusively for wilderness / recreation.

• Matrix of mountains/lakes.

• Interspersed with a population of 131,000 (14 people/sq. mi.)

• Public land managed by NY Department of Environmental Conservation (DEC).

• 53 management units.

• Wilderness, Wild Forest, Primitive, Canoe, Intensive Use Areas

Adirondack Forest Preserve

Beier et al. (2008) Ecosystems

Provision Model

Add rasters together, slice into 10 equal-area classes

+ + +

Slice each raster into 20 equal-area classes

Distance to exemplary aquatic

communities

Provision Index

Distance to Megawetlands

Ecosystem Rarity

Distance to State Threatened/Endangered

Animal Habitat

1-10 scale

Blue = High Provision

Red = Low Provision

Provision Index

Use Model

+ +

Use Index

Distance to Roads Distance to Trails Distance to Recreation Points(Lean-tos, Boat Launches, etc.)

Use Index

1-10 scale

Blue = High Use

Red = Low Use

Disturbance Model

+ +

Disturbance Index

+Acid DepositionDistance to

StructuresDistance to Aquatic

Invasives Index of Biotic

Integrity

Disturbance Index

1-10 scale

Blue = Low Disturbance

Red = High Disturbance

Islands

Core Areas

Combining rasters illuminates relationships between provision, use & disturbance

Provision minus Use

Green = High Provision,Low Use

Red = Low Provision,High Use

PCA1

PCA2

3210-1-2-3

2

1

0

-1

-2

-3

Wild Forest

Wilderness/Primitive

William_Whitney West_Canada_Lake

Use

Using index scores to classify management units

PCA1

PCA2

3210-1-2-3

2

1

0

-1

-2

-3

Wild Forest

Wilderness/Primitive

William_Whitney West_Canada_Lake

“Average”

Units

Use

Using index scores to classify management units

PCA1

PCA2

3210-1-2-3

2

1

0

-1

-2

-3

Wild Forest

Wilderness/Primitive

William_Whitney West_Canada_Lake

High Prov.

Low Use

Low Dist.

Use

Using index scores to classify management units

PCA1

PCA2

3210-1-2-3

2

1

0

-1

-2

-3

Wild Forest

Wilderness/Primitive

William_Whitney West_Canada_Lake

Silver_Lake

Siamese_Ponds

Sentinel_Range

Raquette_River

Pigeon_Lake

Pharoah_Lake

Pepperbox

McKenzie_MtJay_Mt

Hoffman_Notch

High_Peaks

Ha_De_Ron_Dah

Giant_Mt

Five_Ponds Dix

Blue_Ridge

Wilmington

Wilcox_Lake

Whitehill

Watson_East_Triangle

Vanderwhacker

Taylor_Pond

Split_RockShaker_Mt

Sargent_PondsSaranac_Lakes

Raquette_Jordan_Boreal

Moose_River_Plains

Lake_George

Jessup_River

Independence_River

Hammond_Pond_West

Hammond_Pond

Grasse_River

Fulton_Chain

Ferris_Lake

Debar_Mt

Cranberry_Lake

Chazy_Highlands

Blue_MtBlack_River

Aldrich_PondWest_Canada_Mt

Wakeley_Mt

Round_Lake

Lake_Champlain_Islands

Hurricane_Mt

Hudson_Gorge

Bog_River

Whiteface_MtSt_Regis

Low Prov.

High Use

High Dist.

Use

Using index scores to classify management units

ES & NYSERDA

Scoping Research Management