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Forecasting Resilience of Social Ecological Landscapes

Forecasting Resilience of Social Ecological Landscapes. Some Tools to Help Us Understand This Thing Called “Sustainability”. Lilian Alessa, Andrew Kliskey, Mark Altaweel

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Forecasting Resilience of Social Ecological Landscapes

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  1. Forecasting Resilience of Social Ecological Landscapes Some Tools to Help Us Understand This Thing Called “Sustainability” Lilian Alessa, Andrew Kliskey, Mark Altaweel Resilience and Adaptive Management Group, Water and Environmental Research Center, University of Alaska; Center for Social Dynamics and Complexity, Arizona State University, University of Chicago, Argonne National Lab

  2. A Few Sustainability Myths • Sustainability is about the environment. • Consumer choices and grassroots activism works. • There is no single critical piece of the sustainability challenge. Lemonik, 2009. Princeton, New Jersey.

  3. Humour Me….. • Sustainability is possibly one of the most misunderstood words in common usage. • Social structure, particularly agent types, are powerful determinants of emergent SES patterns. • The environment has become synonymous with “green” but we are more of a STS than an SES (something I’d like you to jot down for your Immersion Experience tomorrow).

  4. Water is the Critical Piece • Entering the “Century of Water” • Most issues depend on water availability, distribution and/or quality. • Transitions from common pool resource to trade commodity. • Several “solutions” are not possible unless water is factored in.

  5. Trends in Water Resources • Not just availability but also quality, we can only “clean” so well. Also see White, Hinzman, Alessa, JGR Biogeosciences, 2007

  6. Dealing with Future Change Requires a Paradigm Shift in “Science” Growing evidence that technological interventions alone are not effective and may drive critical changes in water use patterns.--UN Commission on Sustainable Development (1995). 1. Our understanding of the social dynamics in social ecological systems is poor. 2. Our incorporation of scale is sloppy. 3. Our treatment of SES is oversimplified. These may represent some of our greatest vulnerabilities to effectively coping with change.

  7. Scale ArcticRIMS_UNH

  8. Alessa et al. 2009. In Press, Sustainability

  9. Screen shot of SES types paper

  10. How Could We Possibly Fail? • Scale • Messy Social Ecological Systems • Underestimation of Social Dynamics • Hubris: we will engineer a solution or ‘sustainability as a hobby’

  11. Resources Technology Networks Learning Exposure Policies Resilience & Adaptation Perceptions, Values Desire, Means Disasters/Conflicts Resilient Vulnerable

  12. Gaining an Edge:TheTools • Social Ecological Hotspots Mapping. • The Arctic Water Resources Vulnerability Index (AWRVI). • Forecasting Environmental Resilience of Arctic Landscapes (FERAL). MapAssessModel

  13. Social Ecological Systems Hotspot Mapping • Takes social and biophysical values and uses GIS to map the coupled social ecological landscape. • Gives us information about where specific dynamics exist. • Was highlighted as innovative science by NSF in Spring 2008.

  14. Screen shot of paper

  15. Screen shot of paper

  16. Adapting to Change: AWRVI • The Arctic Water Resources Vulnerability Index: AWRVI (“Ar-Vee”). • Tool to assess status of water resources at the watershed scale. • Unifies western and traditional knowledge systems. • Can be used to determine resilience and best strategies for development. First and only of its kind for high latitudes and local scales.

  17. Environmental Vulnerability Indices • EVI: United Nations Environment Programme (2001). • UN Commission on Sustainable Development (1995). • Global Commission on Fresh Water Resources (2004). • Water recognized as single-most important variable in rapid change.

  18. Emergent toolsagent-based models (ABM)

  19. Agent Based Models • Specify the rules of behavior of individuals (agents) as well as rules of interaction • Simulate many agents using a computer model • Explore the consequences of the agent-level rules on the population as a whole • “Simple” models to produce complex behaviors “How could drops of water know themselves to be a river? Yet the river flows on” --Antoine du Sainte-Exupery

  20. Agents and Systems • agents have connections to each other, and form a system and operate in an environment with feedbacks • agents behave autonomously thus they each have their own parameters (data) and behaviors • systems change once the agents affect the threshold in a significant way

  21. Agent Based Models Are not • An attempt to perfectly reproduce reality (usually) Are • Are a tool to gain intuition about the system of interest without needing to know all of the details • A tool to run “experiments” which cannot be performed in real life • A tool to generate and test hypotheses about what is occurring • A tool to refine data collection foci

  22. Big Questions • What drives the human hydrological system? • How do societies ‘overshoot’ their resources (both social and physical)? • How can we learn to avoid this fate? (Should we? If so, why?) • Move beyond rhetoric. Source: Alessa , Kliskey, and Altaweel. 2009, In Press, Sustainability

  23. Resources Technology Networks Learning Exposure Policies Resilience & Adaptation Perceptions, Values Desire, Means Disasters/Conflicts Resilient Vulnerable

  24. Forecasting Environmental Resilience of Arctic Landscapes (FERAL)

  25. Developing “Real” Rules • Too often, ABMs rely on ‘artificial’ rules (e.g., games). • Or ….”what ifs”. • It is critical that rules be derived from the messy, real world. • Humans are not logical but they are predictable. "Man is a complex being; he makes the deserts bloom and lakes die." — Gil Stern

  26. Developing Real Rules • There are three rules of thumb to successfully developing rule sets for ABM. • Observe your system to the point of intimacy. • Establish colleagues in it who will assist you with field work and data collection. • Include modelers at the outset, not once you think it would be “nice” to model.

  27. Screen shot of JASSS 2 paper

  28. Your Immersion Experience • Tomorrow you will go out into three “SES” (two being primarily “STS”). • As yourself “who/what are the objects in the landscape” (e.g., people, terrain, interventions, others?). • For each of these objects, what would you need to know about them to develop meaningful rule sets?

  29. Applying Agent-Based Modeling Source: Altaweel, Alessa, and Kliskey, JASSS, Forthcoming

  30. Values held toward water Source: Alessa , Kliskey, Williams. Society & Natural Resources. 2008.

  31. Current Social ABM in FERAL Step 1: Assess water source selection process with observed trends and determine consequences of water selection choices.

  32. Integrated Models: Example Runtime Output 2 Maximum River Discharge Mean Quantity change belief

  33. How People Make Choices: Why We Need to Know This Social influence and behavior affects water use The thought process Person’s decision A person’s ideas People make decisions according to their life experiences, social relationships, and perceptions of what is around them. Different people have different influence and goals that influences other people around them: three agent types, alpha, beta and gamma.

  34. Decision Making: Divisions in the Decision Process Plot points show agents. Red=Reject Blue=Accept 1 10 Results show cliques forming and social position of those rejecting an idea. Different agent types affect whether decisions made result In collective or individual benefits 25

  35. Decision Making: Representation in Social Space 10 25 1 Black=Reject Light Blue=Accept Over a few ticks, more people agree to accept the initial idea. However, this often occurs if leaders agree initially and coordinate their efforts. Social network representation of relationships. Negative Relationships 25

  36. Changing Viewpoints: Effect on Decision Making Group vs. Individual goals

  37. FERAL: White Mountain Scenario White Mountain Municipal Water source Fish River World Wind 3D visualization view agent

  38. 10-Year Scenario: Travel To River Fish River agents White Mountain Agents concentrate at river sources nearest to White Mountain.

  39. 10-Year Scenario: Tracking Total Movements Aggregate agent movements during each Time tick. Concentration of movements over entire simulation and time.

  40. Municipal and non-municipal sources fluctuate seasonally. agents accessing the municipal source house icon varies in size based on population levels Colors in water sources indicate relative levels, blue colors indicate high volume, while red is lower volume.

  41. 10-Year Scenario: Travel To River Fish River agents White Mountain

  42. Evolution of Water Use on the Seward Peninsula In: Alessa, Kliskey, Busey, Hinzman, White. Global Environmental Change, 2008.

  43. Take Home Messages • Many of the challenges in sustainability are not ‘fixable’ using technologies or good will. • Agents drive the system from the bottom up and some dynamics simply aren’t pretty. • A powerful approach to understanding consequences is to use agent based models. • ABMs allow the unpredictable outcomes of simple choices and changes in patterns of use to be visualized in virtual worlds.

  44. Acknowledgements • The RAM Group at UAA • My colleagues at the International Arctic Research Center, and the Institute for Northern Engineering, UAF • My colleagues at the Center for Social Dynamics and Complexity, Arizona State University • Fabrice Renaud, Head, Environmental Assessment and Resource Vulnerability Section, United Nations University • Volker Grimm, Director, Center for Environmental Research, Leipzig-Halle, Germany. • The National Science Foundation.

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