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Title Date1 WAVES © 2014 Wealth Accounting and the Valuation of Ecosystem Services www.wavespartnership.org Biophysical modeling of ecosystem services:

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Presentation on theme: "Title Date1 WAVES © 2014 Wealth Accounting and the Valuation of Ecosystem Services www.wavespartnership.org Biophysical modeling of ecosystem services:"— Presentation transcript:

1 Title Date1 WAVES © 2014 Wealth Accounting and the Valuation of Ecosystem Services www.wavespartnership.org Biophysical modeling of ecosystem services: Module 2A: Introduction WAVES Training Module

2 Title Date2 WAVES © 2014 The modeling process

3 Title Date3 WAVES © 2014 Defining model boundaries What spatial extent do we want to analyze? Political boundaries (nations, subnational political units)? Biophysical boundaries (watersheds, biomes)? May often be determined by the ecosystem service and its spatial dynamics (Bagstad et al. 2013)

4 Title Date4 WAVES © 2014 Defining model boundaries Over what time period(s)? Annually is often good for statistical estimates Subannual time scales matter some resources Wet vs. dry-season water availability Some services have important temporal dynamics Flood regulation – flood event Crop pollination – timing where flowers are open for pollination Forestry/fisheries – annual population growth

5 Title Date5 WAVES © 2014 Defining model boundaries What kind of model structure do we want? How complex a model is desirable? Where are there gaps in our understanding of what we’re trying to model? At what spatial & temporal resolution? Tradeoffs in complexity and computing requirements

6 Title Date6 WAVES © 2014 Building a conceptual model Identify system boundaries: What gets included in the model? What gets left out? Which variables matter? How are they connected? Are there redundant variables? Adding model complexity may lead to diminishing returns. Risk of overfitting the model – having it perform well on an existing dataset, but with worse predictive power on new data.

7 Title Date7 WAVES © 2014 Formalizing the model Define mathematical relationships between variables Deterministic – simple mathematics to differential equations Probabilistic – including Bayesian approaches, also Monte Carlo simulation May include dynamic models that run across time steps (the output of one time step is the input to the next one), versus being calculated once.

8 Title Date8 WAVES © 2014 Fundamental rules of modeling 1. Keep it simple at first, add complexity as you go 2. Always keep your goals in mind (fit for purpose; don’t add complexity past the point of usefulness) 3. More complexity is not always a good thing (Ockham’s razor, principle of parsimony)

9 Title Date9 WAVES © 2014 Testing models Calibration: Test model’s inputs to see how well they describe outputs (data). Adjust the model if there’s strange or unexpected behavior (But, once the model’s working, predictions of unexpected behavior may be a useful finding) Sensitivity analysis: Vary the input parameters, see which ones most influence the results (good examples for ecosystem services in Kareiva et al. 2011) Validation: Withhold some data and develop the model using only part of your dataset. Then, test the model against the withheld data to understand its predictive power.

10 Title Date10 WAVES © 2014 Overview of modeling methods

11 Title Date11 WAVES © 2014 Methods for mapping ecosystem services 1.Binary lookup tables 2.Qualitative lookup tables 3.Aggregated statistics lookup tables 4.Multiple layer lookup tables 5.Causal relationships 6.Spatial interpolation 7.Environmental regression models Schröter, M., et al. In press. Lessons learned for spatial modeling of ecosystem services in support of ecosystem accounting. Forthcoming in: Ecosystem Services.

12 Title Date12 WAVES © 2014 Methods for mapping ecosystem services Schröter et al. in press

13 Title Date13 WAVES © 2014 Different modeling methods can be used for different services within the same study Schröter et al. in press

14 Title Date14 WAVES © 2014 Tools for mapping ecosystem services Traditional valuation methods Primary valuation Point transfer Function transfer (multiple regression) Function transfer (Bayesian) Function transfer (Wildlife Habitat Benefits Estimation Toolkit) Spatially explicit models, generalizable ARIES InVEST MIMES SolVES EcoServ LUCI Co$ting Nature Proprietary/consultant-driven EcoAIM EcoMetrix ESValue NAIS SERVES Spatially explicit models, place-specific Envision EPM InFOREST Qualitative tools ESR TESSA EVI Bagstad et al. 2013

15 Title Date15 WAVES © 2014 Tools for mapping ecosystem services http://www.aboutvalues.net

16 Title Date16 WAVES © 2014 Biophysical modeling of ecosystem services GIS database Nelson et al. 2009 Ecological production function Maps quantify ecosystem service tradeoffs, hotspots, co- benefits E.g., Artificial Intelligence for Ecosystem Services (ARIES), Integrated Valuation of Ecosystem Service Tradeoffs (InVEST), others

17 Title Date17 WAVES © 2014 Modeling toolkits: InVEST Spatial modeling toolkit for terrestrial & marine ecosystem services Very well tested and documented Codes ecological production functions as quantitative lookup tables (Tier 1) or more complex models (Tier 2) Operates independently of a specific GIS platform http://www.naturalcapitalproject.org

18 Title Date18 WAVES © 2014 Current InVEST limitations Tier 1 lookup table approach may be both too simplistic and too data-intensive for many applications (But see http://naturalcapitalproject.org/database.html - sediment and nutrient model parameters) http://naturalcapitalproject.org/database.html More complex Tier 2 approaches are not specifically supported by a software tool, and are even more data intensive

19 Title Date19 WAVES © 2014 Modeling toolkits: ARIES Semantic meta-modeling framework for building ecosystem service models Automated data handling & “intelligent” contextual data & model selection ARIES modeling interface, http://www.ariesonline.org

20 Title Date20 WAVES © 2014 Current ARIES limitations Semantic meta-modeling framework offers substantial flexibility to advanced users but with a very steep learning curve Build-out of data and model libraries and decision rules for model selection will offer substantial power, but not yet complete Web tool planned for ES mapping by less technical users, but still some time in the future

21 Title Date21 WAVES © 2014 Modeling toolkits: Co$ting Nature Web-based tool using preexisting models and global datasets to model ecosystem services anywhere on earth (1 km to 1 ha resolution) Co$ting Nature interface, http://www.policysupport.org/costingnature

22 Title Date22 WAVES © 2014 Current Co$ting Nature limitations Models likely too simplistic and often at too coarse resolution to support detailed decision making, economic accounting, or sophisticated scenario analysis (though potentially very useful for scoping)

23 Title Date23 WAVES © 2014 Other approaches Other approaches exist (see Bagstad et al. 2013) GIS software can be used to map ecosystem services independently of a dedicated ecosystem services modeling toolkit

24 Title Date24 WAVES © 2014 Comparative analysis of multiple models Comparison of results from multiple models at common sites using common input data is needed Application of ARIES and InVEST in the southwestern U.S. showed good landscape-scale agreement but poor site-scale agreement (Bagstad et al. 2013) WISER project (funded by UK-ESPA) will compare multiple tools at multiple sites

25 Title Date25 WAVES © 2014 Comparison of approaches Mapping approachBasic characteristicsMapping techniques applied Dedicated ecosystem services mapping tools (e.g., InVEST) Predefined modules for mapping ecosystem services Mostly based on lookup tables, predefined techniques for specific services Modeling framework (e.g., ARIES) Enables design of specific algorithms for individual ecosystem services in a GIS environment, using predefined models and data where appropriate Flexible, different mapping techniques supported GIS mapping independent of a modeling toolkit All services need to be modeled individually Flexible, all mapping techniques can be used but without the guidance of a toolkit

26 Title Date26 WAVES © 2014 Exercise 2: Ecosystem service capacity and flow 1.In small groups, select one ecosystem service of interest (each group should select a different service). Identify as specific a benefit type as possible. 2.Spend 5-10 minutes discussing which ecosystems and ecosystem processes provide that service. That information is used with data and models to map ecosystem service capacity for that service. 3.Spend 5-10 minutes discussing who benefits from that service. How could you map the location of the beneficiaries and quantify their demand? What access issues allow or restrict access to that benefit? 4.Present an overview from your small group to the full group for discussion.


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