Modelling the role of neighbourhood support in regional climate change adaptation Friedrich Krebs, Sascha Holzhauer, Andre...
Climate is changing – globally and in Germany © Trampert/Pixelio IPCC 2001
Heat wave in summer 2003 Image by Reto Stöckli, Robert Simmon and David Herring, NASA Earth Observatory, based on data fro...
Climate is changing – globally and in Germany
Purpose of KUBUS <ul><li>Investigate </li></ul><ul><ul><li>Individual adaptation to the consequences of climate change </l...
Project setup Multi-Agent- Model Cooperating Research Projects (Health, Traffic, Legal and Informational Instruments) Disc...
10 SINUS ®  Milieus ® Sinus Sociovision 2006 3 2 1 Consumption Materialists 11% Establisheds 10% Ground Breakers 8% Post M...
10 SINUS ®  Milieus – 4 Lifestyles ® Sinus Sociovision 2006 3 2 1 Consumption Materialists 11% Establisheds 10% Ground Bre...
Household Data <ul><li>Microm® Market Cells </li></ul><ul><ul><li>1133 cells in Northern Hesse  </li></ul></ul><ul><li>Sin...
Composition of local subpopulations in 2007
http://www.sinus-sociovision.de From lifestyles to agent profiles 3 2 1 Consumption Materialists 11% Establisheds 10% Grou...
Analysis of Household Data
<ul><li>IPCC scenario A1B </li></ul><ul><li>coarse spatial resolution: 14 x 22 km </li></ul>Climate Data
Health care during heat waves <ul><li>22 000 to 45 000 excess deaths during 2003 heat wave in Europe </li></ul><ul><li>Fra...
Abstraction and theoretical context <ul><li>Provision: A support network has to be provided by a group of potential helper...
Model setup – Neighbourhood support as a public good <ul><li>Individual group members contribute a fraction x of a given t...
Model setup – Individual obtained benefits <ul><li>Benefit of neighbourhood support is shared among group members. </li></...
Subjective utility (Charness & Rabin, 2002) <ul><li>Reflect “distributional preferences” as subjective utility function </...
Decision-making (Janssen & Rollins) <ul><li>The final decision-making of the agents is utility-based </li></ul><ul><li>Age...
Imitation and group selection (Boyd et al 2003) <ul><li>Compare pairs of agents with respect to their obtained benefit (no...
Effects <ul><li>Imitation </li></ul><ul><ul><li>selection that causes higher payoff behaviours to spread within groups </l...
Initial sensitivity analysis <ul><li>Generation cycle </li></ul><ul><ul><li>5 repetitions of individual decision-making ba...
Initial sensitivity analysis – capacity of support network
Initial sensitivity analysis – Gini index of contributions
Initial sensitivity analysis – Gini index of contributions  Need for neighbourhood support – maximum „value“ of public goo...
Literature <ul><li>Boyd, R., Gintis, H., Bowles, S., & Richerson, P. J. (2003). The evolution of altruistic punishment.  P...
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Modelling the role of neighbourhood support in regional climate change adaptation

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  • Located in the middle of Germany with its regional centre, the major city of Kassel, being an important node for both railway and car traffic Topology is characterized by low mountain ranges largely covered by woods, and the river Fulda One million people live on approx. 6,900 km² area apart from Kassel is rather sparsely populated and organised at a small scale Main future challenges for the region are the ageing and the decline of the population in rural areas, the expected increase in precipitation during autumn, winter and spring seasons, and extreme weather situations like heat waves, storms, and flooding. The visualization displays TERRA MODIS (MODerate resolution Imaging Spectroradiometer) derived land surface temperature data of 1km spatial resolution (Click on the image to get the high resolution TIFF file). The difference in land surface temperature is calculated by subtracting the average of all cloud free data during 2000, 2001, 2002 and 2004 from the ones in measured in 2003, covering the date range of July 20 - August 20. (Cite this image as: Image by Reto Stöckli, Robert Simmon and David Herring, NASA Earth Observatory, based on data from the MODIS land team. Correspondance: rstockli -at- climate.gsfc.nasa.gov).
  • Located in the middle of Germany with its regional centre, the major city of Kassel, being an important node for both railway and car traffic Topology is characterized by low mountain ranges largely covered by woods, and the river Fulda One million people live on approx. 6,900 km² area apart from Kassel is rather sparsely populated and organised at a small scale Main future challenges for the region are the ageing and the decline of the population in rural areas, the expected increase in precipitation during autumn, winter and spring seasons, and extreme weather situations like heat waves, storms, and flooding. The visualization displays TERRA MODIS (MODerate resolution Imaging Spectroradiometer) derived land surface temperature data of 1km spatial resolution (Click on the image to get the high resolution TIFF file). The difference in land surface temperature is calculated by subtracting the average of all cloud free data during 2000, 2001, 2002 and 2004 from the ones in measured in 2003, covering the date range of July 20 - August 20. (Cite this image as: Image by Reto Stöckli, Robert Simmon and David Herring, NASA Earth Observatory, based on data from the MODIS land team. Correspondance: rstockli -at- climate.gsfc.nasa.gov).
  • Individual adaptation in terms of change of habit or preventative measures
  • Social status: social class, income, education Basic values: orientations concerning work-leisure time balance, health/wellness also: scale along age
  • Social status: social class, income, education Basic values: orientations concerning work-leisure time balance, health/wellness also: scale along age
  • demographic change / rural exodus of the younger generation -&gt; (no working family networks) Potentially, active neighbourhood support networks already exist in the target region and they could be activated as a source for flexible assistance for the elderly during heat waves
  • In principle, the ρ and σ parameters could be set individually in an agent’s profile. We could also assume heterogeneity only between groups, i.e. agents of the same group have identical profiles. However, for the initial results that are reported here we assume identical profiles for all agents, i.e. fixed settings for the two parameters.
  • In principle, the ρ and σ parameters could be set individually in an agent’s profile. We could also assume heterogeneity only between groups, i.e. agents of the same group have identical profiles. However, for the initial results that are reported here we assume identical profiles for all agents, i.e. fixed settings for the two parameters.
  • Modelling the role of neighbourhood support in regional climate change adaptation

    1. 1. Modelling the role of neighbourhood support in regional climate change adaptation Friedrich Krebs, Sascha Holzhauer, Andreas Ernst
    2. 2. Climate is changing – globally and in Germany © Trampert/Pixelio IPCC 2001
    3. 3. Heat wave in summer 2003 Image by Reto Stöckli, Robert Simmon and David Herring, NASA Earth Observatory, based on data from the MODIS land team. Correspondance: rstockli@climate.gsfc.nasa.gov
    4. 4. Climate is changing – globally and in Germany
    5. 5. Purpose of KUBUS <ul><li>Investigate </li></ul><ul><ul><li>Individual adaptation to the consequences of climate change </li></ul></ul><ul><ul><li>Public reaction to policy-defined adaptation strategies </li></ul></ul><ul><li>Represent and model </li></ul><ul><ul><li>individual perceptions of regional impacts of climate change </li></ul></ul><ul><ul><li>individual attitudes and (limitations of) behavioural options </li></ul></ul><ul><li>Empirical grounding by </li></ul><ul><ul><li>surveys of psychological indicators and processes </li></ul></ul><ul><ul><li>geographically differentiated socio-demographic data </li></ul></ul><ul><ul><li>quantitative projections from regional climate models </li></ul></ul><ul><li>Provide decision support for policy makers </li></ul>
    6. 6. Project setup Multi-Agent- Model Cooperating Research Projects (Health, Traffic, Legal and Informational Instruments) Discussion,Evaluation Identifications of „Hot-Themes“ Survey of Psychological Indicators and Processes Scenarios & Simulation Providing Data Quantitative Climate Scenarios Geographically Differentiated, Socio-Demographic Data
    7. 7. 10 SINUS ® Milieus ® Sinus Sociovision 2006 3 2 1 Consumption Materialists 11% Establisheds 10% Ground Breakers 8% Post Materialists 10% Pleasure Seekers 11% Modern Mainstream 16% Modern Performers 9% Traditionals 14% 6% Conser- vatives 5% Higher Middle Lower Social Status Basic Values A Tradition Sense of Duty and Order C Re-orientation Multiple Options, Experimentation, Paradoxes GDR- Nostal- gia B Modernization Individualization, Selfactualization, Pleasure low social status, refuse to accept the expectations of a performance-oriented society self-confident, think in terms of success and feasibility young and unconventional elite liberal and postmaterial values, intellectual interests old German educated class, humanistic values and cultivated forms prefer security and orderliness socialist visions of solidarity and justice aiming at professional and social establishment, very status-oriented feel socially discriminated, aspire to the consumption patterns of the Mainstream very individualistic, see themselves as lifestyle avant-garde
    8. 8. 10 SINUS ® Milieus – 4 Lifestyles ® Sinus Sociovision 2006 3 2 1 Consumption Materialists 11% Establisheds 10% Ground Breakers 8% Post Materialists 10% Pleasure Seekers 11% Modern Mainstream 16% Modern Performers 9% Traditionals 14% 6% Conser- vatives 5% Higher Middle Lower Social Status Basic Values A Tradition Sense of Duty and Order C Re-orientation Multiple Options, Experimentation, Paradoxes GDR- Nostal- gia B Modernization Individualization, Selfactualization, Pleasure Traditional Lifestyles Leading Lifestyles Mainstream Lifestyles Hedonistic Lifestyles
    9. 9. Household Data <ul><li>Microm® Market Cells </li></ul><ul><ul><li>1133 cells in Northern Hesse </li></ul></ul><ul><li>Sinus® Milieus </li></ul><ul><ul><li>capture perceivable patterns of behaviour, symbolic integration and underlying orientations </li></ul></ul><ul><ul><li>commercial market research </li></ul></ul><ul><ul><li>milieus are expected to have different preferences, opinion and behaviour </li></ul></ul>TRA Traditionals KON Conservatives DDR GDR Nostalgia BMU Modern Mainstream MAT Consumption-Materialists ETA Establisheds PMA Post Materialists PER Modern Performers EXP Ground Breakers HED Pleasure Seekers 2015 2020 2007 2010           x 10 milieus 5 sizes of household     >
    10. 10. Composition of local subpopulations in 2007
    11. 11. http://www.sinus-sociovision.de From lifestyles to agent profiles 3 2 1 Consumption Materialists 11% Establisheds 10% Ground Breakers 8% Post Materialists 10% Pleasure Seekers 11% Modern Mainstream 16% Modern Performers 9% Traditionals 14% Conser- vatives 5% Higher Middle Lower Social Status Basic Values A Tradition Sense of Duty and Order C Re-orientation Multiple Options, Experiment., Paradoxes GDR- Nostal- gia 6% B Modernization Individualization, Selfactualization, Pleasure Demonstration: Two Milieus Spatially Explicit Data of Microm® 3 2 1 Consumption Materialists 11% Establisheds 10% Ground Breakers 8% Post Materialists 10% Pleasure Seekers 11% Modern Mainstream 16% Modern Performers 9% Traditionals 14% Conser- vatives 5% Higher Middle Lower Social Status Basic Values A Tradition Sense of Duty and Order C Re-orientation Multiple Options, Experimentation, Paradoxes GDR- Nostal- gia 6% B Modernization Individualization, Selfactualization, Pleasure
    12. 12. Analysis of Household Data
    13. 13. <ul><li>IPCC scenario A1B </li></ul><ul><li>coarse spatial resolution: 14 x 22 km </li></ul>Climate Data
    14. 14. Health care during heat waves <ul><li>22 000 to 45 000 excess deaths during 2003 heat wave in Europe </li></ul><ul><li>France alone recorded 14 800 deaths in 9 days, 7000 in Germany </li></ul><ul><li>Most victims found dead at home </li></ul><ul><ul><li>In France 8584 victims (58%) died without the benefit of hospital care </li></ul></ul><ul><li>Vulnerable population group </li></ul><ul><ul><li>older people, babies, and children </li></ul></ul><ul><li>Increased vulnerability of socially isolated individuals </li></ul><ul><li>Public health service will not be able to provide the required flexible and comprehensive home care. </li></ul><ul><li>Active neighbourhood support networks could fill the gap </li></ul><ul><ul><li>decrease the risk of heat-related health damages </li></ul></ul><ul><li>For effective health policy, knowledge of the potential of (potentially existing) support networks is crucial. </li></ul><ul><li>A dynamic ABM of the formation of neighbourhood support networks could help to investigate the effects of social mobilisation campaigns for neighbourhoods with low support potential. </li></ul>
    15. 15. Abstraction and theoretical context <ul><li>Provision: A support network has to be provided by a group of potential helpers from a local neighbourhood. </li></ul><ul><li>Potential: The potential (or capacity) of a support network depends on the sum of the “investments” (e.g. in terms of time devoted to the task) by the potential helpers. </li></ul><ul><li>Shared social benefit: We assume that the social benefit of a well established support network is visible and valuable to all potential helpers, i.e. the positive effect of the support network is “shared” among all potential helpers, not only between those actively contributing. </li></ul><ul><li>Timing: Up to a certain level of individual investments there will be no perceivable benefit from the support network (i.e. the provided support network will have a negligible potential). Above that level the potential of the support network rises more steeply with increasing individual investments up to a certain maximum. </li></ul><ul><li>Maximum condition: The provision of a support network with maximum potential does not require maximum investments by all potential helpers. </li></ul><ul><li>Variability: The beneficial effects of a working support network vary spatially depending on the local demographic structure as well as temporarily because they are most crucial under conditions of (unpredictable) heat waves. </li></ul>
    16. 16. Model setup – Neighbourhood support as a public good <ul><li>Individual group members contribute a fraction x of a given time budget. </li></ul><ul><li>Sum of contributions determines the support capacity of the neighbourhood network (i.e. level of the public good). </li></ul><ul><li>Spatially varying need for support </li></ul>Janssen & Rollins
    17. 17. Model setup – Individual obtained benefits <ul><li>Benefit of neighbourhood support is shared among group members. </li></ul><ul><li>Individual balance between time devoted to neighbourhood help and achieved benefit: </li></ul><ul><li>w i =1 - x i + g / n </li></ul>
    18. 18. Subjective utility (Charness & Rabin, 2002) <ul><li>Reflect “distributional preferences” as subjective utility function </li></ul><ul><li>Agents evaluate their obtained benefit w i with respect to the average obtained benefits of the other n-1 members of their group. </li></ul><ul><li>Consider 3 cases : </li></ul><ul><li>ρ describes an individual’s aversion to exploiting other group members </li></ul><ul><li>σ can be regarded as an individual’s degree of altruistic tendency </li></ul><ul><li>Charness & Rabin (2002) describe distributional preference scenarios from “Competition” to “Social Welfare Consideration” </li></ul>
    19. 19. Decision-making (Janssen & Rollins) <ul><li>The final decision-making of the agents is utility-based </li></ul><ul><li>Agents choose between 11 investment levels {0.0, 0.1, …, 1.0} </li></ul><ul><li>Each agent </li></ul><ul><ul><li>knows the present level of the PG </li></ul></ul><ul><ul><li>assumes that the n-1 other agents in its group keep to their previous investment decisions in the next time step </li></ul></ul><ul><li>Hence: calculate an associated utility for each of the 11 investment options </li></ul><ul><li>By roulette wheel selection with probability proportional to the expected utility agents select their investment level for the next time step. </li></ul>
    20. 20. Imitation and group selection (Boyd et al 2003) <ul><li>Compare pairs of agents with respect to their obtained benefit (not subjective utility). </li></ul><ul><li>Select a dominant agent (winner) probabilistically </li></ul><ul><li>Investment decision x of the winner is imitated by the other agent </li></ul><ul><li>With a fixed low probability m the two agents are selected from different groups. Else from the same group </li></ul><ul><li>Compare randomly selected pairs of groups (intergroup conflict) </li></ul>
    21. 21. Effects <ul><li>Imitation </li></ul><ul><ul><li>selection that causes higher payoff behaviours to spread within groups </li></ul></ul><ul><ul><li>migration that causes behaviours to diffuse from one group to another at a rate proportional to m </li></ul></ul><ul><ul><li>Because cooperation has no individual level benefits, defectors spread between groups more rapidly. </li></ul></ul><ul><li>Group selection only targets at cooperation </li></ul>
    22. 22. Initial sensitivity analysis <ul><li>Generation cycle </li></ul><ul><ul><li>5 repetitions of individual decision-making based on subjective utility </li></ul></ul><ul><li>Imitation cycle </li></ul><ul><ul><li>Each agent “encounters” one other agent (with probability m from different group) </li></ul></ul><ul><li>Group competition cycle </li></ul><ul><ul><li>Each group “conflicts” a randomly chose other group with given low probability n. </li></ul></ul><ul><li>Simulation sequence: </li></ul><ul><ul><li>20 repetitions of (generation – imitation – generation - group competition) </li></ul></ul><ul><ul><li>10 random seeds </li></ul></ul><ul><li>20 groups of size 10 </li></ul><ul><li>σ and ρ from {0.0, 0.05,… 1.0} </li></ul><ul><li>σ and ρ parameters are set homogenously to the same values for all agents. </li></ul>
    23. 23. Initial sensitivity analysis – capacity of support network
    24. 24. Initial sensitivity analysis – Gini index of contributions
    25. 25. Initial sensitivity analysis – Gini index of contributions Need for neighbourhood support – maximum „value“ of public good low high medium
    26. 26. Literature <ul><li>Boyd, R., Gintis, H., Bowles, S., & Richerson, P. J. (2003). The evolution of altruistic punishment. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 100 (6), 3531–3535. </li></ul><ul><li>Charness, G., & Rabin, M. (2002). Understanding Social Preferences with Simple Tests*. Quarterly Journal of Economics, 117 (3), 817–869, from http://www.mitpressjournals.org/doi/abs/10.1162/003355302760193904. </li></ul><ul><li>Janssen, M. A., & Rollins, N. Evolution of Cooperation in Asymmetric Commons Dilemmas, from http://ssrn.com/paper=1368783. </li></ul>

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