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Predicting Change or Assessing Resilience of Social-Ecological Systems?

Predicting Change or Assessing Resilience of Social-Ecological Systems?. Challenges and Opportunities for Sustainability Impact Assessment Modeling. Marco Janssen Center for the study of Institutions, Population and Environmental Change Indiana University, USA.

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Predicting Change or Assessing Resilience of Social-Ecological Systems?

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  1. Predicting Change or Assessing Resilience of Social-Ecological Systems? Challenges and Opportunities for Sustainability Impact Assessment Modeling Marco Janssen Center for the study of Institutions, Population and Environmental Change Indiana University, USA

  2. Sustainability Impact Assessment • Identification of economic, social and environmental impacts of a policy plan or regulation. • Objective analysis of the potential benefits and costs.

  3. Queries on SIA • Current analysis focused on predicting impacts using economic models, but • Economic markets are one of various types of institutions. • Predicting or assessing potential consequences of specific policies is challenging.

  4. The Connecticut Crackdown on Speeding • To reduce the number of traffic deaths, the control of speed in Connecticut in 1956 was enhanced by more effectively enforcing the law. There was an immediate drop in 1956 in speeding violations and fatalities, and the policy was concluded to be successful. • Campbell, D.T. and H.L. Ross (1968) The Connecticut Crackdown on speeding: Time series data in Quasi-experimental analysis, Law & Society Review 3: 33-53.

  5. Success of policy?

  6. Time series

  7. Suggestions for Alternatives • Using a broader framework of institutions instead of markets only. • Assessing resilience of social-ecological systems instead of predicting consequences of specific policies. • Using complex adaptive system models instead of general equilibrium models.

  8. Institutions and Rules • Institutions are the formal and informal rules that govern the interactions between people. • Different types of rules: Boundary rules, Position rules, Authority rules, Scope rules, Aggregation rules, Information rules, Payoff rules (see Ostrom et al., 1994).

  9. Physical Conditions Action Arena Patterns of Interactions Action Situations CommunityAttributes Evaluative Criteria Actors Rules- in-Use Outcome Institutional Analysis and Development Framework

  10. Institutions—Rules—Exist at Least at Three Analytical Levels • Operational level: where users and officials make decisions about day-to-day activities – harvesting, monitoring, maintenance, etc. • Collective choice level: where policies are made for operational level • Constitutional choice level: establishes who will be involved and rules to be used at collective choice level

  11. Design Principles Illustrated by Long-Enduring Common Pool Resource Institutions 1. Clearly defined boundaries 2. Congruence between appropriation and provision rules and local conditions 3. Collective-choice arrangements 4. Monitoring 5. Graduated sanctions 6. Conflict-resolution mechanisms 7. Minimal recognition of rights to organize 8. Nested enterprises Source: Ostrom (1990: 90).

  12. Social-Ecological Systemsas Complex Adaptive Systems • Complex adaptive system: A heterogeneous collection of individual units that interact locally, and evolve based on the outcomes of the interactions. • Units in SESs are agents and rules.

  13. Complex Adaptive System

  14. What is Resilience? Resilience is the capacity of a system to absorb disturbance without flipping to another type of system. A resilient system can withstand shocks and rebuild itself when necessary.

  15. Suppression of forest fires will cause an accumulation of fuel. When a fire event finally occurs, it will be hot and intensive, affecting soil conditions and the capacity of the forest to recover from fire events. Forest management can reduce the risk of flipping into an undesirable stability domain by tolerating small disturbances in order to prevent a big one. Resilience and Forest Fires

  16. Methods for Resilience Analysis • Participatory approach (e.g. stakeholder workshops) • Analysis of long-lasting institutions (e.g. waterboards, irrigation systems) • Modeling (e.g. Agent-based modeling)

  17. Agent-based modeling is a way to study the interactions of large numbers of agents and the macro-level consequences of these interactions. If <cond> then <action1> else <action2> ….. ….. Inanimate agents …. Observer Animate agents Data Organizations of agents Artificial world

  18. Balinese Irrigation System • Balinese irrigation system exists for at least 1000 years. • How are the farmers able to coordinate water supply and control pests?

  19. Location of subaks and irrigation systems • Synchronization of cropping pattern lead to effective control of pests (same variety of rice at the same time. When harvest, field can be burned and flooded to remove pest habitat). • But when number of subaks is too large it leads to water demand problems.

  20. Green Revolution • During the “green revolution” farmers were forced to switch to the miracle rice varieties which led from two to three harvests a year. • Farmers were stimulated by governmental programs that subsidized the use of fertilizers and pesticides. • The farmers continued performing their rituals, but now they no longer coincided.

  21. Effects • Soon after the introduction of the miracle rice, a plague of plant-hoppers caused a huge damage of the rice production. • A new variety was introduced, but then a new pest plague hit the farmers. • Furthermore, there were problems of water shortage. • Balinese farmers wanted to go back to traditional system. • “they need engineers no priests”

  22. Model of Lansing and Kremer • Model of the ecosystem dynamics. • Simple behavioral rule for subaks: • As a new year begins, each of the 172 subaks in the model begins to plant rice or vegetables. At the end of the year, each subaks look at its closest neighbors to see whether they got higher yields. If so, the subak copies the cropping pattern of the best neighbor.

  23. Cropping patterns

  24. Consequences from Lansing model • Interventions can have perverse effects since they do not take into account the complexity of formal and informal rules. • Importance of local experimentation, social learning and multi-layer institutions.

  25. Resilience of Social-Ecological Systems • System characteristics of resilience: • Redundancy • Diversity • Modularity • Currently starting to systematic analyze social-ecological systems of successes and failures

  26. Implications for SIA • Social-Ecological Systems can be seen as complex adaptive systems consisting of rules. • Manipulation of rules can have unintended consequences that are hard to predict. • Panaceas and quick fixes • Insights from case studies and agent-based modeling can contribute to insight on design principles to enhance resilience of SESs.

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