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

2. Title Date2 WAVES © 2014 Modeling for ecosystem accounting

3. Title Date3 WAVES © 2014 Using modeling and valuation Biophysical modeling Monetary valuation Ecosystem condition X Ecosystem service capacity XX Ecosystem service flows XX

4. Title Date4 WAVES © 2014 The basics of modeling

5. Title Date5 WAVES © 2014 Biophysical modeling: why do it? Maps (spatial models) are appealing to people, but should be designed and evaluated critically (Hauck et al. 2013, Monmonier and de Blij 1996) Sumarga and Hein 2014

6. Title Date6 WAVES © 2014 Biophysical modeling: why do it? Show hotspots and coldspots for ecosystem service values Getis-Ord Gi* results (α = 0.10 significance level) for four overlaid ecosystem services, Shoshone National Forest, Wyoming, USA (Bagstad et al. in prep) HotWarmCold

7. Title Date7 WAVES © 2014 Biophysical modeling: why do it? Enable spatial scenario analysis Measure ecosystem service change under different scenarios Who wins or loses as a result of these changes? Nelson et al. 2009

8. Title Date8 WAVES © 2014 What is a model? A (usually) mathematical representation of reality A simplification of reality It’s always wrong, to some degree – some features of the real-world system get ignored or misrepresented A tool to explore relationships in a system, to predict and test cause and effect or how a system responds to change As simple as a spreadsheet model or as complex as a process model with hundreds of inputs Both an art and a science

9. Title Date9 WAVES © 2014 Examples of models 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.

10. Title Date10 WAVES © 2014 What do we need to model ecosystem services? Defined boundaries and goals, including a target spatiotemporal resolution Biophysical data: How do natural processes interact to generate ecosystem services (with ecological production functions)? Socioeconomic data: How do people demand and use ecosystem services? In order to map services, these data need to be geospatial

11. Title Date11 WAVES © 2014 Where do the data come from? International agencies and research consortia (U.N. agencies, space agencies, conservation organizations, academic & government researchers, etc.) National agencies – statistical agencies, national mapping agencies, ministries of natural resources, etc. Project-specific data (academics, national mapping agencies, development aid agencies, etc.) Data vary by accuracy, timeliness, resolution - there are almost always tradeoffs!

12. Title Date12 WAVES © 2014 How detailed should models be? Complex models take more time and resources to develop and run; high-resolution datasets need more storage space Processing data and running models at high spatial and temporal resolution takes longer Complex models do not always perform better than simple models (Fultona et al. 2004, Raicka et al. 2006), nor do they necessarily add value to decision making (Tallis & Polasky 2011)

13. Title Date13 WAVES © 2014 Should models be standardized? Within a country: To build a time series (the real value in national accounting), we need to use the same models with comparable data that change over time If better models become available, they must be re-run on old data to preserve the time series. This is another example of the tradeoff between “accuracy” and time and resources.

14. Title Date14 WAVES © 2014 Should models be standardized? Between countries: Using the same models allows for better international comparability But this may not be feasible because: Available time and resources to run models differ between countries The same model may not be as accurate in different countries (i.e., because of different ecological or socioeconomic conditions) Some models may have better or worse credibility and buy-in with decision makers in different countries

15. Title Date15 WAVES © 2014 Natural, human, & built capital combine to produce benefits to society Remme et al. 2014

16. Title Date16 WAVES © 2014 Measuring capacity and flow See Schröter et al. 2014; Bagstad et al. 2014 calls these theoretical & actual services Model an ecosystems’ capacity to provide each service Map the location of beneficiaries/ecosystem service demand Estimate the amount of a service that is accessible/used (some % of the capacity)

17. Title Date17 WAVES © 2014 Biophysical flows that extend beyond the system boundary Case 1: One country lies entirely upstream of another Easier case, one country exports, the other imports an ecosystem service India China Nepal Bhutan Bangladesh

18. Title Date18 WAVES © 2014 Biophysical flows that extend beyond the system boundary Case 2: A river is a shared boundary between two or more countries A somewhat harder case; each country imports and exports some of the ecosystem service Brazil Uruguay Argentina Paraguay

19. Title Date19 WAVES © 2014 Capacity and flow Ecosystem service capacity Ecosystem service flows Provisioning services Capacity to provide products (overharvesting may occur) Amount of products extracted/ harvested Regulating services Potential regulating capacity across an entire region Regulating impacts on actual people (beneficiaries) Cultural servicesDepends on service

20. Title Date20 WAVES © 2014 Schröter et al. 2014

21. Title Date21 WAVES © 2014 Spatiotemporal ES flows: Distinct from flows as year-to-year changes in ecosystem accounts Bagstad et al. 2013

22. Title Date22 WAVES © 2014 Measuring ecosystem capacity Ecological production function – use a model to represent this, plus spatial data Ecosystem condition matters But different condition metrics may matter for different services, and consensus is lacking Condition and capacity may vary from year to year (wet/dry years, natural disasters, changes in management)

23. Title Date23 WAVES © 2014 Measuring spatiotemporal flows Distinct from flows (i.e., changes in ES over time) Location and demand of users relative to supply matters Bagstad et al. 2014

24. Title Date24 WAVES © 2014 Capacity vs. Flow Flows are less than capacity, since access and beneficiary locations matter Schröter et al. 2014

25. Title Date25 WAVES © 2014 Measuring trends over time Estimating changes in stocks over time (i.e., flows) a key piece of the accounting exercise Depletion of natural capital stocks indicates non-sustainable condition Requires spatial data from different time periods Show an image of a time trend – Michael, Lars, do you have good examples?

26. Title Date26 WAVES © 2014 Summarizing the data (Remme et al. 2014) Maps Summary tables – can do this at different aggregation levels Total ecosystem service capacity & flow (EAU) Summaries by land cover type (LCEU) Summaries by pixel (BSU)

27. Title Date27 WAVES © 2014 Sources of uncertainty There are different types of uncertainty in ecosystem services mapping and valuation: Uncertainty in how model structure and components should be represented (ecological production function relationships) Coarse-resolution, dated, or inaccurate data Data with different spatial or temporal resolution Missing or conflicting parameters used to populate models

28. Title Date28 WAVES © 2014 Assessing ecosystem condition Condition relative to what? Using which metrics? Uniformity of metrics? Aggregation of metrics? How to account for interannual variability (due to climate variability, natural disasters, changes in management)?

29. Title Date29 WAVES © 2014 Getting started with modeling

30. Title Date30 WAVES © 2014 Who should be involved? Modeling should almost never be a 1-person exercise Who to involve: People who know the data (national statistical agencies, national mapping agencies, ministries of natural resources, researchers, etc.) People who understand the system and how it works (academic and agency researchers) Participatory modeling with scientists & stakeholders can build trust in model results Economists & accountants who will use the results to build ecosystem accounts

31. Title Date31 WAVES © 2014 When to involve more stakeholders? Project kickoff Understand which ecosystem services to model, map and value Understand existing models, data sources, expertise Completion of first round of model results Are results trustworthy? Do they pass a basic reality check? Are there other datasets or model adjustments that would improve the results? Completion of final model results How can results most effectively be summarized and communicated to wider audiences (decision makers, media, the public)?

32. Title Date32 WAVES © 2014 The modeling process Define ecosystem services and study boundaries Identify available financial and human resources – assemble modeling team Identify data and model resources to map and measure ecosystem services Determine best methods to model ecosystem services that will meet scientific needs within resource constraints

33. Title Date33 WAVES © 2014 Define ecosystem services & boundaries of analysis The services chosen to some extent determine the boundaries (i.e., for watershed services, analysis should take place at the watershed) Ideally, analysis would take place at the national level Realistically, this is easiest for small, physically and socioeconomically homogeneous countries

34. Title Date34 WAVES © 2014 Define boundaries of analysis In large, heterogeneous countries it’s often easier to begin with a subnational analysis How broadly can we apply the same data and models? (see module on ecological production functions and ecoregions) Spatial scale of analysis matters Tradeoff between computer runtime vs. level of precision Needed level of precision may differ by service (i.e., pollination at the scale of a small farm field)

35. Title Date35 WAVES © 2014 The modeling process Assemble models and data Conduct initial model runs – including validation, calibration, sensitivity analysis Review preliminary results with stakeholders and external scientists Conduct “final” model runs based on feedback Communicate results to stakeholders Use results for valuation & ecosystem account construction

36. Title Date36 WAVES © 2014 The modeling process Scale up results to the national level Run annually to generate time series analysis (on past data, or as new annual data become available) When new (i.e., incomparable, but better) data/models become available: Decide whether time and resource needs justify use of the new data and models If so, re-run new models on old data to backcast results and maintain time series

37. Title Date37 WAVES © 2014 Exercise 1: Gap analysis of data for ecosystem service modeling 1.In small groups (3-4 participants), choose one ecosystem service of interest (each group should select a different service) 2.For that service, write down at least one (more if you can) biophysical/ecological, one socioeconomic, and one spatial dataset needed to map and quantify that service. 3.For each dataset, identify a data source (i.e., national mapping agency, ministry of natural resources), and answer the following: 1.Do you think these data are of better quality than corresponding global datasets? Are they substantially better, or only somewhat better? 2.Where/when are global data unlikely to be adequate? 3.What data are lacking for your country (i.e., need to rely on global data)? 4.What data are entirely lacking (i.e., don’t exist at the global or national level?) 4.Present your conclusions to the full group for discussion.