invest a tool for mapping and valuing ecosystem services emily mckenzie driss ennaanay stacie wolny...
TRANSCRIPT
![Page 1: InVEST A Tool for Mapping and Valuing Ecosystem Services Emily McKenzie Driss Ennaanay Stacie Wolny Gregg Verutes](https://reader036.vdocuments.mx/reader036/viewer/2022062300/56649e685503460f94b63bec/html5/thumbnails/1.jpg)
InVEST A Tool for Mapping and Valuing Ecosystem Services
Emily McKenzieDriss EnnaanayStacie WolnyGregg Verutes
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– Evidence: Test tools, improve decisions, write stories
– Tools: Make it easy to quantify ecosystem services
– Influence: Achieve broader policy change
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Outline
• What questions is InVEST designed to answer?
• What are InVEST’s key characteristics?
• What are common challenges using InVEST?
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Filling the Gap
Policy decisions:Region/landscape scale
Short timelineForward looking, comparative
GLOBAL, SYNTHETIC
60% of global ES in decline (Millennium Assessment)
$33 Trillion/y (Costanza et al. 1997 Nature)
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
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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?
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How would a new cattle management approach affect agricultural revenues?
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How would a new cattle management approach affect agricultural revenuesdrinking water qualityerosion controlcarbon sequestrationand biodiversity?
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InVEST
Quantify, map & value ecosystem service impacts of alternative resource decisions
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InVEST within decision making
Stakeholders
ScenariosResults
Policy input
Mapping toolNow 2050
Now 2050
C (
tons
)Policy implementation
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7. Flexible data
requirements
8. Free and open source
9. Scientific foundation
10.Accompanying policy
tools
“Top Ten” InVEST attributes
1. Applicable anywhere
2. Multiple services
3. Spatially explicit
4. Scenario based
5. Production functions
6. Biophysical & socio-
economic outputs
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1. Applicable anywhere - Terrestrial
Upper Yangtze
Tanzania
California
Hawai’i
Colombia Sumatra
Virungas
Amazon
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Applicable anywhere – Marine
Vancouver Island
Belize
Chesapeake BayPuget Sound
Galveston BayMonterey Bay
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Applicable anywhere - Many kinds of decision context
Decision Context Geography
Spatial PlanningTanzania, 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 servicesColombia (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
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2. Multiple Ecosystem Services
Fisheries (0)
Aquaculture: finfish (1)
Coastal Vulnerability (0)
Recreation (0)
Wave Energy (1)
Carbon Sequestration (1)
Habitat Risk Asst (1)
Aesthetic Quality (1)
Water Quality (1)
Water purification (1)
Sediment retention (1)
Crop pollination (1)
Hydropower (1)
Irrigation water (1)
NTFPs (1)
Flood control (1)
Commercial timber (1)
Coastal Protection (1)Aquaculture: shellfish (1)
Biodiversity (1)Carbon sequ’n (1)
Agricultural prod’n (1)
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3. Spatially explicit
Python scripts packaged into an ArcGIS toolbox
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How might ecosystem services change with different:
4. Scenario-based
• Interventions• Possible futures• Visions of the future• Future baselines• Quantitative modeled scenarios
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Complementary scenario tools
• Scenario primer for InVEST users
• Scenario generator linked to InVEST
• Linking to IDRISI Land Change Modeler
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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)
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6. Biophysical & socio-economic outputs
Water for Irrigation Crop PollinationSupplyMaximum potential services
Total surface runoff from each land parcel on landscape (vol. ha-1)
Insect abundance (# insects ha-1)
UseIntermediate service
Amount of water used for crop irrigation (vol. ha-1)
Insect abundance contributing to crop (# of insects ha-1)
UseFinal 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)
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Valuation
Value of captured
wave energy
Avoided damages
NPV of fish &
shellfish
Values of recreation activities
Avoided areaEroded/flooded
Harvested biomass
Captured wave energy
Visitation
Landed biomass
Fisheries
Recreation Model
Aquaculture
Wave energy
Coastal Protection
Production functions
Socioeconomic
Oceanography
Habitat type
Species distribution
Bathymetry Topography
Model Outputecosystem services & values
ModelsInput Datareflect scenarios
Marine
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7. Flexible data requirements
Tier 1 Tier 2 Tier 3
Models
Data
Simple Complex
Tier 0
I am out of the office until 15 June, with little email access. I will get back to you on my return.Thanks,Emily
InVEST
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8. Strong Scientific Foundation
100 + authors
Oxford University
Press
Published April 2011
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Many disciplines
• Hydrology• Economics• Policy• GIS analysis• Software
engineering
• Ecology• Marine biology• Coastal engineering• Fisheries• Programming• Oceanography
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9. Free and open source
Ready to use, but customizable
http://invest.ecoinformatics.org
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10. Accompanying policy tools
• InVEST in Practice e.g. SEA• InVEST Tip Sheets e.g. REDD• Scenario Primer & Generator• Screening Criteria• TEEB (& other) Case Studies• ….
Meet the SPIes
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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)
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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
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More information
http://invest.ecoinformatics.org
www.naturalcapitalproject.org
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Thanks…People
Andrew BalmfordTaylor RickettsNeil Burgess
Gretchen DailyBrendan FisherPeter KareivaEric Lonsdorf
Guillermo MendozaRobin NaidooErik Nelson
Nasser OlweroSteve Polasky
Jim RegetzAmy RosenthalMathieu Rouget
Mary RuckelshausHeather Tallis
Buzz ThompsonKerry Turner
…
SupportNSF
NSF-NCEASNASA
Leverhulme TrustGoogle
Packard FoundationMacArthur Foundation
Moore FoundationSummit Foundation
Roger and Vicki SantPeter and Helen Bing
…
PeopleAnne Guerry
Jodie ToftKatie ArkemaRich SharpJon FoleyCK Kim
Gregg VerutesDriss Ennaanay
Stacie WolnyAmy Rosenthal
Nirmal BhagabatiJim SalzmanChris Colvin
Mike PapenfusGreg GuannelJoey BernhardtSpencer WoodPam Matson
…
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Any questions?
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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
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Testing/Verification of Water Yield
0 100 200 300 400 500 6000
100
200
300
400
500
600
R² = 0.824150696427196
Comparison of Annual water yield between SWAT and InVEST
in Texas Gulf Basin
InVEST
SW
AT
InVEST
SWAT