Ralf Seppelt, GEO BON Working Group 6 Meeting, 19-21.3. Paris

1. Martin-Luther Universität Halle-Wittenberg Some thoughts on ecosystem service based environmental management: Models, Tools, Examples & Applications. Ralf Seppelt, GEO BON Working Group 6 Meeting, 19-21.3. Paris

2. Figures 15 National Centers 24,000 Total staff 8,500 Scientists & Engineers 3,250 Doctorial Students Helmholtz Association of German Research Centres List Helgoland Greifswald Bremerhaven Hamburg Geesthacht Berlin Braunschweig Potsdam Zeuthen Wolfenbüttel-Remlingen Teltow Magdeburg Niemegk Göttingen Halle Bad Lauchstädt Leipzig Jülich Energy Earth & Environment Human Health Key-Technologies Structure of Matter Infrastracture and Space Köln Bonn Darmstadt Figures • 900 total staff • 200 Doctorial Students www.ufz.de Heidelberg Lampoldshausen Karlsruhe Stuttgart Neuherberg Garching München Oberpfaffenhofen Headquarters of Helmholtz Centres Regional branch Helmholtz office

3. Computational Landscape Ecology Fields and Methods Catchment management Biotic Ecosystem Services Urban land use and Ecosystem services Scenario Develop-ment and Analysis Plant pheno-logy, stress Fields Optimization, High perfor-mance computing Methods Land use change modelling Agent based modlling Statistics Remote Sensing Model based quantification of robust, reliable relationships between land use, structure and the functions provided by the ecosystems www.ufz.der/cle

4. Todays menue • Challenges, methods and tools to analyseecosystemsservices on the regional scale • Modeling & Analysis • Global vs. Regional Scale • Project (GLUES) and research programme in Germany • Database • Synthesis • Model-based analysis

5. Global vs. regional assessments • Land management is a regional process • direct feedbacks between ecosystem services and human well being • Regional case studies are key • What are the feedbacks between regions? • How to synthesize regional results? Roudsepp-Haerne et al. (2010, BioScience) • Human well-being and ecosystem services show globally different trends. Why? • Reject Hypothesis • Lack of data? • Lack of undersrtanding • Wrong Scale?

6. Global pollination demand Lautenbach et al. (in prep)

7. Examplepollination • Lautenbach et al. (in prep)

8. Experimental results on pollination • Summer 2010 Experiment: • Distribution of bee netsts • Yield increase of 20% Apple yield [kg/tree] ** no yes beesreleased • Dorman et al. (subm.)

9. Analysis of feedbacks: artificial landscapes • Recreation = f(forestarea, shape) • Production = f(fielsize, pollination, soilfertity) • Pollination= f(forestedge) Generation 800 10 Generations Generation 1 ~lineare Trade-offs Non-linearTrade-offs

10. Spatialconfiguration Pollination

11. Parthe basin and biofuel production • study trade-offs between bioenergy production, food production, water quality and water quantity • Varyation of the crop rotation schemes • Objective function: • 5 percentile discharge • Average NO3- concentration • Yield food production • Yield bioenergy crops Modifications

12. Results scenario analysis • trade-offs regarding scenario assumptions • but: how good are the scenario assumptions? Strauch 2010, Strauch, Ullrich, Volk 2010

13. Generation 2, e.g. Monte Carlo Analysis • Use of genetic algorithms for variation of crop rotation, e.g. variation of land use intensity

14. Generation 2 -> 30

15. Generation 30 - 100

16. Generation 100 - 500 • Processes • Food yield ~ Bioenergy yield-1 • NO3 ~ Food yield-1 • NO3 ~ Bioenergy yield • Uncertainty • Hydrology: high (equifinality pattern) • Yield: low

17. Mariage of apple and oranges Leipzig, Germany Red-Backed Shrike Middle Spotted Woodpecker Wood Lark Holzkämper & Seppelt, 2007

18. 1.0 b) a) 0.8 0.6 HSIopt optimized mean habitat suiatbility 0.4 0.2 0.0 30000 0 15000 0 5000 10000 15000 P profit loss [€/ha] P profit loss [€/ha] Habitat improvement and its valuation Leipzig, Germany Task: optimise land use patterns for maximum habitat performance while minimizing costs for land use change Wood Lark Red-Backed shrike Middle Spotted Woodpecker Holzkämper & Seppelt, 2007

19. Habitat suitability & Economy Leipzig, Germany Task: optimise land use patterns for maximum habitat performance while minimizing costs for land use change Holzkämper & Seppelt, 2007

20. Conclusions & Next Steps • Conclusion • Trade-offs: Separate (landscape) pattern and process! • Bundles of ecosystem functions/services are determined by patterns (landscape) and processes and are non-linear. • Next Steps • Regional focus demands synthesis of place-based studies • Blueprint or standardized prototokoll required • This is a prerequisite for standardized data-bases • Modelling, requires data based backgrounds

21. Review: Regional Ecosystem Services Studies • Considered uncertainty • Data source • Ecosystem services in isolation • Modelling approaches • Valuation • Number of ecosystem services • Scenario-Analysis • Specific recommendations • Stakeholder involvement Seppelt et al. (2011, JApplEcol)

22. Review: Regional Ecosystem Services Studies • Considered uncertainty • Data source • Ecosystem services in isolation • Modelling approaches • Valuation • Number of ecosystem services • Scenario-Analysis • Specific recommendations • Stakeholder involvement Seppelt et al. (2011, JApplEcol) Seite 22

23. Review: Regional Ecosystem Services Studies It is unclear to what degree biophysical realism is required in ecosystem service assessments Methods to analyze trade offs among ecosystem services and economic goals are not well developed Consideration of off-site effects is extremely rare Involvement of stakeholders rarely extends to the implementation phase (‚ownership‘) Seppelt et al. (2011, JApplEcol) Seite 23

24. Blueprint for Assessment Studies • Purpose & Design • Problemscape & Concept • Analysis, Assessment, Valuation & Test • Recommendation & Results • Monitoring Seppelt et al. (subm)

25. Systainable Landmanagement Programme • Objective of RFP • methods and tools for sustainable land management • different regional, hot spot regions • support these regional research project with consistent global land use and climate change data www.sustainable-landmanagement.net Seite 25

26. Place-based studies in the programme

27. GLUES Overarching Scientific Support and Synthesis GLUES: Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services Communication & Outreach Stakeholder & Products Szenario, Models & Synthesis Common Geodata Infrastructure

28. GLUES’ methodology • GLUES GDI (Geodata Infrastructure) – provides a common infrastructure to publish, share and maintain distributed global and regional data sets, scenario data and model results. • Mid-Term Projections (2030/50) – incorporate feedbacks of agricultural markets, land use and climate • Long-Term Scenarios (2100) delivers land use change scenarios based on global sustainability goals and climate change, to be used to project land management impacts on global climate. • Synthesis develops methods and tools for trade-off and off-site effect analysis, valuation of ecosystem services and support instruments development

29. GLUES GDI • Concept • Global distributed Geodata Infrastructure: Data ramains with the owner • INSPIRE Conform • Links up GLUES partners • Links up regional projects (in Version 1) • Open to the community (in Version 2) • Content & Function • Holds global data land use, ecosystem services, scenarios, climate change etc. • Harvests available databses • (FAO, IUCN based on standardized links) • Product • embeddeable in Google Earth, ArcGIS • Prototype for internal testing available • Version 1 available 1/2012

30. GLUES modelling concept • Concept: Global scale • Model based generation of Scenarios on land use, climate change pattern for short and long term scenarios • Concept: Regional Scale • Generec ESF/ESS Models of intermediate complexity relating land use (change/intensity) to ecosystem services • Using knowlege form well tested established system • Covering processes in hot spot regions • Partly meta-model to cover processes from regional projects • Analysis • Analysis of trade-offs via optimization and Monte-Carlo Simulation • Analysis on off-site effects

31. GLUES synthesis • Concept • Use of avaliable data on regional ecosystem service assessments (meta-analysis, accross projects: TEEB, Conservation Internation, etc.) • Use network and statistical analysis • Analysis • Relate Environmental and Economic Conditions and assessed Ecosystem Services • Identification of threasholds, nonlinearites

32. Someconcluding statements • Diversity of model developments is beneficial for scientific progress but might be contraproductive for ecosystem service assessments • Off-site effects and trade-off analysis are core challenges for regional studies • Biophysical realism of models supporting ecosystem service assesments is support by systematic analysis

33. Thank you for your un-prejudice attention! Questions welcome: ralf.seppelt@ufz.de (I forgot my cards)

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35. SomeConcluding Statements • Various models and tools are helpful for untangling relationships between land use (intensity) and ecosystem services. In which do we belief? • Modeling provides virtual experiments with landscapes. How not to loose realistic constraints? • Regional resources management is embedded in global processes. How to be quantify off-site effects? • Need for research in appropriate development of reliable instruments and tools for supporting the Ecosystem Service Concept