InVEST
A Tool for Mapping and Valuing Ecosystem Services
Emily McKenzie
Driss Ennaanay
Stacie Wolny
Gregg Verutes
– Evidence: Test tools, improve decisions, write stories
– Tools: Make it easy to quantify ecosystem services
– Influence: Achieve broader policy change
Outline
• What questions is InVEST designed to answer?
• What are InVEST’s key characteristics?
• What are common challenges using InVEST?
Filling the Gap
GLOBAL, SYNTHETIC
60% of global ES in decline (Millennium Assessment)
$33 Trillion/y
(Costanza et al. 1997 Nature)
Policy decisions:
Region/landscape scale
Short timeline
Forward looking, comparative
LOCAL, SPECIFIC
2 forest patches: $60K/year (Ricketts et al. 2004. PNAS)
22 others (just for pollination!)
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Challenge: Integrated decision-making
“You can only manage what you can measure”
– Ecosystem services ‘invisible’ in decisions
– Need to evaluate choices, quantify tradeoffs
Decision-maker questions
– How would a proposed dam or logging project affect
ecosystem services and biodiversity?
– What would be the best land use plan for balancing
different stakeholders’ visions for the future?
– How would upstream deforestation affect the quality &
quantity of water downstream?
– Where might REDD and payments for watershed
services projects be feasible?
ANSWERS:
Accounting tools for quantifying ES
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How might shoreline armoring affect
Erosion/flooding from storm events?
Coastal and marine recreation?
Nursery habitat for key species?
Fisheries?
How would a new cattle management approach affect
agricultural revenues?
How would a new cattle management approach affect
agricultural revenues
drinking water quality
erosion control
carbon sequestration
and biodiversity?
InVEST
Quantify, map & value ecosystem service
impacts of alternative resource decisions
InVEST within decision making
Policy input
Now
Mapping tool
2050
Now
Stakeholders
Scenarios
C (tons)
Results
Policy implementation
2050
“Top Ten” InVEST attributes
1. Applicable anywhere 7. Flexible data
2. Multiple services
requirements
3. Spatially explicit
8. Free and open source
4. Scenario based
9. Scientific foundation
5. Production functions 10.Accompanying policy
6. Biophysical & socioeconomic outputs
tools
1. Applicable anywhere - Terrestrial
California
Upper
Yangtze
Virungas
Hawai’i
Amazon
Colombia
Tanzania
Sumatra
Applicable anywhere – Marine
Vancouver Island
Puget
Sound
Monterey
Bay
Chesapeake Bay
Galveston Bay
Belize
Applicable anywhere Many kinds of decision context
Decision Context
Geography
Spatial Planning
Tanzania, Indonesia, British
Columbia, Hawai’i, China, Belize
Ecosystem-based management
(terrestrial-marine links)
USA (Puget Sound, Galveston &
Chesapeake Bays)
Climate adaptation
USA - Galveston & Monterey Bays
Payments for ecosystem services
Colombia (water funds), Indonesia
(REDD), Borneo, Tanzania
Impact assessment, permitting,
licensing
Colombia (mining)
Multilateral development bank
investments
World Bank in Malawi
Corporate strategy
Lafarge in Michigan, USA
2. Multiple Ecosystem Services
Recreation (0)
Aquaculture: finfish (1)
Fisheries (0)
Sediment retention (1)
Water purification (1)
Crop pollination (1)
Coastal Vulnerability (0)
Hydropower (1)
Wave Energy (1)
Biodiversity (1)
Carbon sequ’n (1)
Commercial timber (1)
Agricultural prod’n (1)
Flood control (1)
Irrigation water (1)
Aesthetic Quality (1)
Water Quality (1)
Habitat Risk Asst (1)
Carbon Sequestration (1)
Coastal Protection (1)
Aquaculture: shellfish (1)
NTFPs (1)
3. Spatially explicit
Python scripts packaged into an ArcGIS toolbox
4. Scenario-based
How might ecosystem services change with different:
•
•
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•
•
Interventions
Possible futures
Visions of the future
Future baselines
Quantitative modeled scenarios
Complementary scenario tools
•
Scenario primer for InVEST users
•
Scenario generator linked to InVEST
•
Linking to IDRISI Land Change Modeler
5. Production function
• Carbon storage
~ f(veg, storage/ha, harvest, decay)
• Inputs: land use/cover, C densities, harvest rates, decay rates of
harvested wood.
• Outputs: C stored/ha
• Valuation: damage costs avoided
Sediment retention
~ f(soil, slope length, veg, rain, neighbors)
• Inputs: land use/cover, topography, soils, precip, basins
• Outputs: tons sediment retained/ha
• Valuation: replacement costs avoided (dredging)
6. Biophysical & socio-economic
outputs
Water for Irrigation
Total surface runoff
from each land
parcel on landscape
(vol. ha-1)
Crop Pollination
Insect abundance
(# insects ha-1)
Use
Intermediate service
Amount of water
used for crop
irrigation (vol. ha-1)
Insect abundance
contributing to crop (# of
insects ha-1)
Use
Final service
Additional crop yield
given additional
water available for
irrigation (kg ha-1)
Crop yield due to insects
(kg crop ha-1)
Value
NPV of additional
crop yield($ ha-1)
NPV of additional crop
yield ($ ha-1)
Supply
Maximum potential
services
Marine
Input Data
reflect scenarios
Models
Production functions
Wave energy
Coastal Protection
Fisheries
Aquaculture
Socioeconomic
Recreation
Model
Model Output
ecosystem services & values
Captured
wave energy
Valuation
Value of
captured
wave
Avoided area
Eroded/flooded energy
Landed
biomass
Harvested
biomass
Avoided
damages
NPV of
fish &
shellfish
Values of
recreation
activities
I am out of the office until 15 June, with little email access. I will get back to you on my return.
Thanks,
Emily
7. Flexible data requirements
Models
Simple
Complex
Data
Tier 0
Tier 1
InVEST
Tier 2
Tier 3
8. Strong Scientific Foundation
100 +
authors
Oxford
University
Press
Published
April 2011
Many disciplines
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•
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•
•
Hydrology
Economics
Policy
GIS analysis
Software
engineering
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•
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•
•
•
Ecology
Marine biology
Coastal engineering
Fisheries
Programming
Oceanography
9. Free and open source
Ready to use, but customizable
http://invest.ecoinformatics.org
10. Accompanying policy tools
Meet the SPIes
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•
•
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InVEST in Practice e.g. SEA
InVEST Tip Sheets e.g. REDD
Scenario Primer & Generator
Screening Criteria
TEEB (& other) Case Studies
….
Challenges
– Data – even for Tier 1 models
– Capacity to interpret and apply
– Water-related services
– Governmental silos
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Data preparation
• Expertise needed
– GIS expertise for gathering and formatting data
– Subject matter experts e.g. hydrology, economics, carbon
– Both applying InVEST and subsequent analysis
• Time estimate vary depending on
– location
– scale of work
– expertise of working team
• Full run of model, from data gathering to results
– As little as 1 to 3 months
– But often much longer!! (18-24 months and counting)
Data collection
• In some countries
– Good resolution data often freely available online
– From government sources and research institutions.
• For other regions
– Free global data online (Global landcover, Tier 1
carbon, HydroSHEDS etc)
– But often coarse scale
– Finer scale data may be available
– Partnerships with regional organizations very helpful
More information
http://invest.ecoinformatics.org
www.naturalcapitalproject.org
People
Andrew Balmford
Taylor Ricketts
Neil Burgess
Gretchen Daily
Brendan Fisher
Peter Kareiva
Eric Lonsdorf
Guillermo Mendoza
Robin Naidoo
Erik Nelson
Nasser Olwero
Steve Polasky
Jim Regetz
Amy Rosenthal
Mathieu Rouget
Mary Ruckelshaus
Heather Tallis
Buzz Thompson
Kerry Turner
…
People
Anne Guerry
Jodie Toft
Katie Arkema
Rich Sharp
Jon Foley
CK Kim
Gregg Verutes
Driss Ennaanay
Stacie Wolny
Amy Rosenthal
Nirmal Bhagabati
Jim Salzman
Chris Colvin
Mike Papenfus
Greg Guannel
Joey Bernhardt
Spencer Wood
Pam Matson
…
Thanks…
Support
NSF
NSF-NCEAS
NASA
Leverhulme Trust
Google
Packard Foundation
MacArthur Foundatio
Moore Foundation
Summit Foundation
Roger and Vicki San
Peter and Helen Bin
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…
Any questions?
InVEST testing and validation
• Currently being tested against SWAT and
FIESTA (peer-reviewed water yield models)
• Comparison with ARIES in progress
•Arizona (DOI) and Oregon (EPA)
•Ground-truthing in multiple sites
• In Baoxing, China, modeled water yield is >
90% of observed
•Applied water pollution model in Minnesota –
InVEST only 9% off actual observed loading
into basin
Testing/Verification of Water Yield
Comparison of Annual water yield
between SWAT and InVEST in
Texas Gulf Basin
600
R² = 0.8242
500
400
SWAT
InVEST
300
200
100
SWAT
0
0
200
400
InVEST
600