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Linking thoughts to flows Integrated modeling of Social Ecological Systems

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Presentation about my PhD projects.

Presentation about my PhD projects.

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  • , i.e. tourism, regional co-operations etc.
  • The region of Eisenwurzen is a prime example of European cultural landscapes looking back on intensive land use over hundreds of years! The distinct temporal and spatial land use gradients – embedded in global trends – make this post-mining region an interesting study area within the European context. It is characterised by a more than 800-year-old land use history . Iron ore mining started in the 12th century , reached its peak in the 16th century with a proportion of 15 % of the European iron production. The whole region was characterised by a complex interaction of mining and transport as well as agriculture and forestry . This was possible thanks to a dense system of well organised services . The landscape had open character due to extensive deforestation . Population density was high . It is characterised by a more than 800-year-old land use history . Iron ore mining started in the 12th century , reached its peak in the 16th century with a proportion of 15 % of the European iron production. The whole region was characterised by a complex interaction of mining and transport as well as agriculture and forestry . This was possible thanks to a dense system of well organised services . The landscape had open character due to extensive deforestation . Population density was high .
  • Phänomene auf Landschaftsebene damit nicht erfassbar. Lokale Phänomene nicht mit Landschaftsebene in Verbindung gesetzt Wechselwirkungen zwischen wirtschaftlichen und gesellschaftlichen Trends verändern die Landschaft und alle ihre Elemente DAHER: ganzheitlichere Ansätze erforderlich, die diese Wechselwirkungen berücksichtigen
  • We used SERD as a tool to simulate future scenarios depending on changes in (1) external framework conditions, (2) local and regional policies and (3) preferences of individual agents with respect to income and leisure time expectations,willingness to co-operate, etc. Inspired bywell-known international or even global scenarios (Millenium Ecosystem Assessment 2005; Nakicenovic and Swart 2000; UNEP 2002), we developed assumptions for future developments of external framework conditions in three scenarios which we contrasted with a reference (REF) scenario that carries forward the initial values as inputs. Assumptions on local and regional policies as well as on the preferences of local agents were developed in the participatory process described above.
  • The Nicobars are a group of twenty-four islands belonging to India with a total area of 1841 km2. Twelve of the islands are inhabited. The population consists of mainland Indians how are either working for the administration or military or how are legal respectively illegal settlers and of two distinct ideginous groups: the Nicobarese and the . The latter living as hunter-gatheres only on great nicobar the southern most island. The nicobarese are of mongoloid origin and belong to the sout-east asian cultural complex. They are the only indigenous group of the andaman-nicobar archipelago with growing population numbers. Today about …. Live on the islands. The Islands are protected by the ANPTR which strictly regulates the access to the islands. Not only to shield the indigenous population from outside exploitation (which is the official reason) but also due to strategic and military interests of India. This makes it virtually impossible for non-Indians to visit the islands for what reason ever.
  • hallo
  • Model Structure II The model as a whole consists of four interlinked modules: (a) socioeconomic, (b) agent-based (c) ecosystem, and (d) output (see figure 1). The socio-economic module interacts with the ecosystem module via the agent that simulates human decisions. The combined effect of these decisions are then exhibited or displayed over the output module in terms of social and environmental indicators. The model has a user-friendly interface that allows the stakeholders to engage in an interactive process and play around with their decisions and test their assumptions on system behaviour. Let us know look into a bit more detail into the four modules.
  • The Output Module The Output Module displays the combined effects of human decisions and changes in framework conditions on the various socio-economic and ecosystem variables, thereby providing information on the system performance. The results calculated by this module are automatically fed back to the computer agent that influences its decision and actions according to a set of pre-defined rules derived from assumptions from the field. However, since the model also provides a user interface to make it possible for real agents (stakeholders) to interact with the model, they may directly intervene into the model by playing around with a set of sliders representing various system parameters and human preferences. Presently, we have introduced a set of five (land-use preference) sliders and check-boxes for the users to influence agent behaviour during run-time of the model. The model surface displays a map of Kamorta Island showing land-use and landcover Additionally, the surface also displays outputs of some relevant variables such as income and yield per unit of land or hour, loss of forest to agriculture, and required working time for meeting the needs of a given mix of lifestyles. This allows the agent or the user to react to benchmarks like maximum available time or comparing activities like gardening with fishing in terms of money or yield per hour of work invested.
  • Participative Process social learning and understanding of the system between the participants is fostered. structures a process in which the perception of stakeholders on a certain system (or problem) is uncovered Mapping FCM can be used to depict complex systems as perceived by different stakeholders. various elements from the social & cultural sphere, as well as institutions, physical structures ecosystems or individual species can be included
  • Methodological procedure Screening phase adaptation of questionnaire Stakeholder Forum I Diskussion of hotspots and specifics of the region and the product Assessment Data collection Calculation of indicators Evaluation of benchmarks - if nessecary adaptation Stakeholder Forum II Diskussion of benchmarks Labelling
  • Share of responsibility
  • Transcript

    • 1. Linking thoughts to flows Integrated modeling of Social Ecological Systems Martin WildenbergWildenberg – Presentation at the SSI, University of Maine | 1
    • 2. Structure of this talk - Introduction: - Modeling social-ecological systems (SES) - Some examples of integrated SES models - Modeling in LTSER Platforms - Model of Kamorta Island, Nicobars - Fuzzy Cognitive Modeling - Sustainability Indicator: Integration of models - Integrated Modeling - Partizipation - Process oriented modeling… - OutlookWildenberg – Presentation at the SSI, University of Maine | 2
    • 3. Social Ecological Systems Complex AdaptiveWildenberg – Presentation at the SSI, University of Maine | 3
    • 4. We are part of them… and thats what makes them especially messyWildenberg – Presentation at the SSI, University of Maine | 4
    • 5. Let´s zoom in…Wildenberg – Presentation at the SSI, University of Maine | 5
    • 6. Wildenberg – Presentation at the SSI, University of Maine | 6
    • 7. Wildenberg – Presentation at the SSI, University of Maine | 7
    • 8. Wildenberg – Presentation at the SSI, University of Maine | 8
    • 9. Wildenberg – Presentation at the SSI, University of Maine | 9
    • 10. Wildenberg – Presentation at the SSI, University of Maine | 10
    • 11. •Human behavior •Communication •Learning •Local knowledge Important for formulation & application of SES - modelWildenberg – Presentation at the SSI, University of Maine | 11
    • 12. Modeling in LTSER platforms LTSER: Focus on coupled socio-ecological systems Link biophysical processes to governance and communicationWildenberg – Presentation at the SSI, University of Maine | 12
    • 13. SERD (Simulation of Ecological Compatibility of Regional Development) Veronika Gaube, Heidi Adensam, Julia Lutz, Tina Kaiser, Andreas Richter, Helmut Haberl • Analysis links between socio-economic dynamics and substance, material and energy flows • Understand reasons and impacts of long-term changes in economic and social dimension, land use and ecosystems. • Contribute to local sustainable development: Involvement and support of the local stakeholders.Wildenberg – Presentation at the SSI, University of Maine | 13
    • 14. The Casestudy Area LTSER Platform Eisenwurzen •99 Municipalities •5.740 km² •304.762 Inhabitants •Forest Cover = 64% Reichraming EisenwurzenWildenberg – Presentation at the SSI, University of Maine | 14
    • 15. Reichraming The municipality: • 103km² • 80% Forest • 356 m – 2000m • National-park Kalkalpen • 1880 people • Decreasing Population The farms: • Average size: 20ha • Family owned (extended families) • Greenland / milk cows • Highly dependent on subsidies • Decreasing number of FarmsWildenberg – Presentation at the SSI, University of Maine | 15
    • 16. Landscape I Extensive land-use leads to: • Small structured landscapes • Extensive species rich meadows • Hedgerows • Forest on steep slopesWildenberg – Presentation at the SSI, University of Maine | 16
    • 17. Landscape II Forest: • Long (historical) period of deforestation • After breakdown of industry reforestation • Continuing today • Mostly intensive forest: species poor spruce monocultureWildenberg – Presentation at the SSI, University of Maine | 17
    • 18. Land use 1900Wildenberg – Presentation at the SSI, University of Maine | 18
    • 19. Land use 2001Wildenberg – Presentation at the SSI, University of Maine | 19
    • 20. Model concept External conditions Socio-economic / political Environmental conditions framework e.g. climate Agent-based module farms Integrated stock-flow tourism module firms municipality Socio-economic stocks/flows (humans, livestock, artifacts) Land use Ecological stocks flows (forests, grasslands, cropland) Land cover Socio- Land-use Changes in material/ economic change energy flows change Model outputsWildenberg – Presentation at the SSI, University of Maine | 20
    • 21. Behavior of the Farm Agents Farms aim to • maintain the cultivation • achieve at least a minimum of income • achieve at least a minimum of leisure time Farms percept framework conditions like • spatial characteristics of their land • subsidies • product prices • production costsWildenberg – Presentation at the SSI, University of Maine | 21
    • 22. Behavior of the Farm Agents Possible reactions are • Ex- or intensification of production • organic production • increase/Decrease of farm size • change of type of production • increase/Decrease of non-agricultural labour time • increase/Decrease of external wage labour • abandonment of farm Interaction • via land marketWildenberg – Presentation at the SSI, University of Maine | 22
    • 23. Participatory process • Questionnaire for farmers • 6 in-depth interviews with farmers • 6 expert interviews • 3 stakeholder workshops • 2 focus groups with women of the municipality • 3 working groups with farmersWildenberg – Presentation at the SSI, University of Maine | 23
    • 24. User InterfaceWildenberg – Presentation at the SSI, University of Maine | 24
    • 25. Three Scenarios TREND GLOB LOC + Base RunWildenberg – Presentation at the SSI, University of Maine | 25
    • 26. Trend Scenario More farms Less forestation (-15%) Households increase: 10% Less commuters Highest GHG emissions & Nitrogen loss form farms Land-use todayWildenberg – Presentation at the SSI, University of Maine | 26
    • 27. GLOB Scenario Less farms – extensive, high workloads More forestation Households decrease More commuters +75% Lowest GHG & Nitrogen emissions form farms Land-use todayWildenberg – Presentation at the SSI, University of Maine | 27
    • 28. LOC Scenario Less farms – extensive, high workloads less forestation (-15%) Households increase Less commuters Medium GHG & Nitrogen emissions form farms Land-use todayWildenberg – Presentation at the SSI, University of Maine | 28
    • 29. Another region, another topic, similar challenges:Wildenberg – Presentation at the SSI, University of Maine | 29
    • 30. Waves of change Modelling the Nicobar Islands in the Aftermath of the 2004 Sumatra TsunamiWildenberg – Presentation at the SSI, University of Maine | 30
    • 31. RECOVER (research on coping with vulnerability to environmental risk) Simron J. Singh, Willi Haas, Marina Fischer - Kowalski Understand how natural, cultural and institutional features determine the resilience of local socio-ecological systems. Explore the potential linking between functional tools and tools dealing with meaning, human preferences and choice. Scientific support for the planning, implementation and evaluation of reconstruction and development options after the 2004 Tsunami that maintain the social and cultural integrity of the indigenous population and the balance of the natural environment.Wildenberg – Presentation at the SSI, University of Maine | 31
    • 32. Workpackages of Recover Modelling Intervention Theory DevelopmentWildenberg – Presentation at the SSI, University of Maine | 32
    • 33. 2004 Tsunami More then 4000 dead Almost all Houses destroyed & infrastructure damaged coconut plantations destroyed Reef & coast topology changedWildenberg – Presentation at the SSI, University of Maine | 33
    • 34. The Second WaveOver 60 NGOs (in Port Blair) desperately wanting to spend millions of US$. Unrepresented inflow of money & commodities. The Nicobars - A badly hit region or a promising “development market”?Some Side Effects of Aid:Change in Family structure, Social coherence, Conflicts over land, increasing social stratification, change in Consumption and Production patterns…Wildenberg – Presentation at the SSI, University of Maine | 34
    • 35. Integrating different levels in RECOVER Level Focus Target group Tools Island Ecological constraints Tribal Council Integrated Biophysical Administration Model constraints NGOs Market Village Cooperate societies SIF (NGO) Village Planning Production (best mix) council Tool Cooperate societies Household What do people Determines other Participative want? levels Data Cultural constraints Collection & Lifestyle changes Time use Participative observationWildenberg – Presentation at the SSI, University of Maine | 35
    • 36. Model ComponentsWildenberg – Presentation at the SSI, University of Maine | 36
    • 37. Screenshot of the ModelWildenberg – Presentation at the SSI, University of Maine | 37
    • 38. Results IWildenberg – Kamorta at the SSI, University of Maine | 38 Presentation land-cover and land-use – 2005, 2015, 2025 and 2035.
    • 39. Results II Available, required and desired working times per adult. Required workingWildenberg – Presentation at the SSI, time for subsistence and market oriented activities. time includes University of Maine | 39
    • 40. Lets get softer… a tool for integrated modelling of SESWildenberg – Presentation at the SSI, University of Maine | 40
    • 41. Fuzzy Cognitive Mapping How does it work?Wildenberg – Presentation at the SSI, University of Maine | 41
    • 42. Experience from FCM projects Six case studies accross LTSER Plattforms FCM as eductaional tool at the PIK Summerschool Vulnerability of Indian cities towards extreme weather events (ongoing) www.FCMappers.netWildenberg – Presentation at the SSI, University of Maine | 42
    • 43. Structured data collectionWildenberg – Presentation at the SSI, University of Maine | 43
    • 44. Visual comparison of mapsWildenberg – Presentation at the SSI, University of Maine | 44
    • 45. Social Learning & EducationWildenberg – Presentation at the SSI, University of Maine | 45
    • 46. Vulnerability to climate change Collective Fuzzy cognitive map of professionals interviewed in Delhi (Diana Reckien et al.)Wildenberg – Presentation at the SSI, University of Maine | 46
    • 47. Simulation of future scenarios for the EisenwurzenWildenberg – Presentation at the SSI, University of Maine | 47
    • 48. FCM Simulation in a nutshell = value of concept Ci at iteration step k+1 Ai( k +1) ( N = value of concept Ci at iteration step k Ai( k +1) = Ai( k ) + ∑ A(j k ) w ji ) (k ) A i (k ) = value of concept Cj at iteration step k j ≠i A j j =1 w ji = weight of the link between Ci and Cj First iteration Seconde iteration Interaction Activation Matrix Vector C1 Cn C1 C1 C1 Cn C1 C1 C1 X = = X CnVector contains values Cn Cn Cn Cn … Matrix contains weights of Vector contains valuesrepresenting the state of the relations between concepts representing the state of theconcept concept after one iteration
    • 49. Again the three scenarios TREND GLOB LOC + Base RunWildenberg – Presentation at the SSI, University of Maine | 49
    • 50. P ro te c te d N a tu ra l P ro p e rty N a tu ra l L a n d s c a p e F o re s t a t io n N o . o f F a rm s A g ric u lt u ra l In c o m e P o p u la t io n Q u a lity o f L iv e T o u ris m C o m p a n ie s Wildenberg – Presentation at the SSI, University of Maine | 50Base Run W o rk p la c e s In d u s t ry N e g a t iv e P o s itiv e
    • 51. P ro te c te d N a tu ra l P ro p e rty N a tu ra l L a n d s c a p e F o re s t a t io n N o . o f F a rm s A g ric u ltu ra l In c o m e Wildenberg – Presentation at the SSI, University of Maine | 51 P o p u la t io n Q u a lit y o f L iv e T o u ris m C o m p a n ie sTrend W o rk p la c e s In d u s t ry N e g a t iv e P o s itiv e
    • 52. P ro te c te d N a tu ra l P ro p e rty N a tu ra l L a n d s c a p e F o re s t a tio n N o . o f F a rm s A g ric u lt u ra l In c o m e P o p u la t io n Q u a lit y o f L iv e T o u ris m C o m p a n ie s W o rk p la c e s In d u s t ry Wildenberg – Presentation at the SSI, University of Maine | 52 N e g a tiv e P o s itiv eGlob
    • 53. P ro te c te d N a tu ra l P ro p e rty N a tu ra l L a n d s c a p e F o re s t a t io n N o . o f F a rm s A g ric u ltu ra l In c o m e P o p u la tio n Q u a lit y o f L iv e T o u ris m C o m p a n ie s W o rk p la c e s In d u s t ry Wildenberg – Presentation at the SSI, University of Maine | 53 N e g a tiv e P o s it iv eLoc
    • 54. Comparison of results with ABM High overlap in predicted trends for three scenarios Predicted trend in Farmers income is seen in 2008 Statistical DataWildenberg – Presentation at the SSI, University of Maine | 54
    • 55. What can Fuzzy Cognitive Mapping offer? • Structured participative process • Social learning • Communication between participants • Depict complex systems as perceived by different stakeholders • Mapping of complex systems • Analysis • Comparing qualitative data • Modeling & scenariosWildenberg – Presentation at the SSI, University of Maine | 55
    • 56. Pros - Cons • (- )No time, no quantitative results • (+) more process oriented • (+) participative • (+) fasterWildenberg – Presentation at the SSI, University of Maine | 56
    • 57. The Sustainability-Programm of GLOBAL 2000 Objectives: Labeling of (conventional) products which are produced more sustainable then comparable products Develop measurable indicators Information for costumers Information and recommendations for producer Initiate progress towards sustainability Less resource use Less emissions Less environmental impactWildenberg – Presentation at the SSI, University of Maine | 57
    • 58. Calculating indicators: Integrating MIPS with REPRO Bilances (N,P,H) Pest management intensity Repro-model Energy intensity Erosion from INL Soil compaction Farm Distributor Retailer Water, abiotic, biotic, CO2 footprint, area footprint / kg product Footprint calculation in DBWildenberg – Presentation at the SSI, University of Maine | 58
    • 59. Most important: Willing participants! So, it is not just about collecting data and analysing it… It is about a PROCESS…Wildenberg – Presentation at the SSI, University of Maine | 59
    • 60. Discussion and involvment of stakeholders: Learning from praxis – What are the day to day problems faced by farmers? – What do the stakeholders perceive as sustainability problems? – What are workable solutions? => Work out guidelines to progress towards sustainable production Ensure good data quality – Make data collection as easy as possible! This reduces workload and avoids misunderstandings! – Ask the stakeholders what data has to be estimated and what data they already have measure forWildenberg – Presentation at the SSI, University of Maine | 60
    • 61. First results for strawberries: Ressourcenverbrauch Erdbeeren 9000 100 8000 biotisch, g/ 1 kg 90 Produkt abiotisch, g/ 1 kg 80 7000 Produkt g/kg Produkt; cm²/kg Produkt Fläche, cm²/1 kg 70 6000 Produkt / / kg Product literL kg Produkt CO2e, g/ 1 kg 60 5000 Produkt Wasser, l/ 1 kg 50 4000 Produkt 40 3000 30 2000 20 1000 10 0 0 Freiland, At Folientunnel, Israel Folientunnel, Es Gewächshaus, AtWildenberg – Presentation at the SSI, University of Maine | 61
    • 62. Challenges: • Enable win-win situation • Programme must be applicable for the broad market • Transparent and scientific approach • Workload for producers – remuneration? • Setting of benchmarksWildenberg – Presentation at the SSI, University of Maine | 62
    • 63. Part III Integrated modelingWildenberg – Presentation at the SSI, University of Maine | 63
    • 64. So, what is an integrated model?Wildenberg – Presentation at the SSI, University of Maine | 64
    • 65. And how can integration be achievd?Wildenberg – Presentation at the SSI, University of Maine | 65
    • 66. A integrated model integrates… - two (or more) independent models - knowledge from different disciplines - people from different disciplines - scientists and “other” people - theory and praxis - different modelling methodes (ABM, SD, GIS) - Different types of data (qualitative & quantitative)Wildenberg – Presentation at the SSI, University of Maine | 66
    • 67. Models can integrate: • people • topics • knowledge • technologyWildenberg – Presentation at the SSI, University of Maine | 67
    • 68. Integrating people, topics and knowledge: constructing models in iterative loops Simulation System model (e.g. integrates agents with stocks and Modeling flows) Formalization Scenarios Results Heuristic model, visualization of results Interpretation Agents, activities of local Stocks-flows knowledge Landscape Etc. Conclusions acceptance Stakeholders involved in modeling processWildenberg – Presentation at the SSI, University of Maine | 68
    • 69. Lessons learned: • Important to involve actors in the modeling process right from the beginning • Acceptance of the model among the stakeholders very high • Models can structures the discussion process during the whole process • The model helps the stakeholders to understand “their” system better • The model development process is an important focus of the researchWildenberg – Presentation at the SSI, University of Maine | 69
    • 70. The modeling process Always iterative Integration: Develop methods that help structure this process. Use models as form of communicationWildenberg – Presentation at the SSI, University of Maine | 70
    • 71. Building blocks for Integration Build common understanding of usability Interface Similar functionalities & appearance Common way of describing models (e.g. ODD) Definition of interface to higher and lower scales Formal Model Modular design Keep other models in mind Evaluation of basic analytic tools Conceptual Model Typologies of SES Development of consistent SES theoryWildenberg – Presentation at the SSI, University of Maine | 71
    • 72. There are common challenges in the creation of useful SES models To handle most of them some form of integration is required. To integrate between models or modelers a common fundament is needed.Wildenberg – Presentation at the SSI, University of Maine | 72
    • 73. Thank you!Wildenberg – Presentation at the SSI, University of Maine | 73
    • 74. Decision finding process of each farm Ecological dimension Social Economic dimension dimensionWildenberg – Presentation at the SSI, University of Maine | 74
    • 75. ODDWildenberg – Presentation at the SSI, University of Maine | 75

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