Social vulnerability

1. Social vulnerability Anand Patwardhan IIT-Bombay

2. Outline • Concepts • Indicators and measures • Drawing inferences from empirical analysis • Understanding response • Research needs

3. Frameworks

4. Operationalizing vulnerability assessment • A composite measure of the sensitivity of the system and its adaptive (coping) capacity • Combine hazard, exposure and response layers • The layers (and their interactions) evolve dynamically (future vulnerability) • Need indicators to represent the layers • How do we represent the interactions? • For example, to link hazard and impacts we may use (empirical) damage functions, or complex, process-based models (ex: crop models) • What are the implications of dynamic evolution? • Model parameters and structure may change • Can some changes be parameterized (for example technological change?)

5. Social vulnerability • What is it? • How do we measure? • Distinct from economic vulnerability? • Often, the emphasis tends to be on the first two layers, with insufficient thought given to response • Who responds, why & how? • Why is it important? • Critical for understanding response • Ultimately, response in local, and the scale of response can vary significantly

6. Indicators • We are awash in a sea of indicators • Comparison, prioritization • Self-assessment and continuous improvement • Constructing scenarios / futures • Why should we look beyond indicators? • Abstraction and reduction • Process complexity • May help for policy evaluation, but do they help for policy formulation & design? • Indicators for all components of vulnerability (hazard, exposure, impacts and response)

7. Hazard – representing climate risk • Climate change or climate variability? • To which variable(s) is the system most sensitive? • May be a primary (temperature, precipitation), compound (degree days, heat index, AISMR) or derived (proxy) quantity (storm surge) • May be expressed as a statistic – flood return period • Spatial and temporal resolution: capture the actual processes leading to adverse consequences • Examples of resolution

8. Characteristics of cyclone hazard Spatial Distribution of Cyclonic Events during the period 1877 to 1990 by state

9. There is quite a bit of heterogeneity at the district level

10. State Trend (cyclone/100yr) Depression Storm Severe Storm WB 0.884* -0.229 0.313* Orissa -0.979* -0.925* -0.011 AP 0.187 -0.345 0.54* TN 0.0044 -0.154 0.116 Gujarat 0.532* -0.074 -0.067 State wise trend in Cyclone incidences Trends are not significant at the aggregate level

11. Exposure: what is at risk? • Things we value • Market & non-market • Stocks • Population • Capital stock – public and private • Land (more correctly, properties of land – fertility) • Flows • Services • Environmental amenities • Matters in terms of the impacts being considered • Example: housing stock at risk from cyclones

12. Housing • Construction material of the houses important for determining exposure • Census of India gives the distribution of houses at the district and the sub district level by 10 predominant materials of wall in the, 8 predominant materials of roof and 7 predominant materials of flooring. The data is for both urban and rural categories

13. Grouping housing stock based on types of wall materials – creating a smaller set of categories Category Wall Material X Grass leaves, reeds, thatch and bamboo, GI and other metal sheets and other materials. A Mud, unburnt brick, stone, wood and Ekra. B Burnt brick C Concrete Aggregation is a common procedure – need to think carefully about how and why it is being done!

14. Hazard Districts %X %A %B %C Exposure High cyclone Incidence Districts Baleshwar 10.3 80.4 7.8 1.6 High Exposure High cyclone Incidence Districts Nellore 8.8 49.1 38.5 3.6 Relatively Low Exposure Low Cyclone Incidence Districts Sindhudurg 7.9 88.1 2 2.1 High Exposure Low Cyclone Incidence Districts Alaphuza 22.7 13.3 55.5 8.4 Relatively Low Exposure How is the housing stock exposed?

15. Another example Though the damage to total no. of houses is more in case of Tanjavur, South Arcot has a considerably higher number of houses completely damaged. This is expected as the exposure of South Arcot in terms of houses (X&A) more prone to cyclone damage is higher

16. Interactions between the layers • Interactions are dynamic, evolutionary • Path dependency • Specification of scenarios • Linked and dynamic vs. static • Modeling issues • An adjustable parameter in an impacts model? (for example, think of AEEI in energy-economic models) • Endogenous dynamics, capture the essential elements of the adaptation process

17. Interaction of hazard and exposure: state level trends in mortality due to heat waves

18. Indicators for capacity and response • What are we trying to measure? • Inputs, process, outcomes • Number of beds / 1000 people • Process: state of the public health system? • Life expectancy • System dynamics vs. system state. Adaptive capacity (perhaps like sustainability) is more directly related to dynamical and response properties than end-points – for example, resilience or flexibility • Measuring attributes such as salience, perception, institutional and policy preparedness • Most existing indicators in the latter category. For example: • Education – Adult literacy (state of the system), or relative growth rates of male vs. female literacy (dynamics of the process)? • Example “standard” indicators – HDI, Poverty, Competitiveness, Technology achievement

19. More on process vs. end-point • How can one replicate system innovations? • Amul as an example • Perhaps need new intermediaries? Where / how will these come from? • Value judgments come to the fore, because we are making judgments about the extent to which system properties enhance adaptive capacity / sustainability

20. Issues in understanding and characterizing response • Role of the group • Mediating individual perception / response • There are groups at different scales (individual, household, community etc.) and for different roles (social, political, professional). What is the interplay across these scales and the different groups in which an individual may participate? • Role of the signal(s) • That is, does the individual feel that he has any control over the signal? To what extent will that affect the response? Will there be quicker hedonic adaptation for drivers over which the individual does not have control? What about action? In that respect, where do environmental / climate drivers figure? • Role of the context in which response happens • Marketplace behavior, voting behavior?

21. Relevance for global change • What will drive individuals to action? • What will lead to group response? Presumably, non-marginal response will happen only after aggregation of action • What kind of action is most likely – as consumers in the marketplace? As political agents for regulation? • Are there “markers” that will be perceived – for example, how will the climate change signal be perceived / interpreted?

22. Elements of the response process • Role of agency and institutions • Response at various scales: spatial (local, regional, national) and political / institutional (individual – household – community – province – country – international) • Perception of environmental change and vulnerability • Stakeholder communication and engagement • Identification of interventions • Evaluation of options • Evaluation frameworks (utilitarian, rights-based, multi-criteria decision-making) • Ancillary costs and benefits • Characteristics of the outcomes • Equity • Procedural and outcome equity • Efficiency • Effectiveness • Role of uncertainty, use of sensitivity analysis

23. From one-off responses to management systems • In practice, response to vulnerability due to environmental change is institutionalized in the form of a management system, since responding to hazards and change is a continuous process • Explore in the context of specific key sectors that are actively managed: • Water • Forests and ecosystems • Agriculture • Focus on the way in which environmental change (including climate change) is factored (or not factored) into the management systems and processes for these sectors • Role of uncertainty

24. What kinds of questions could we ask from a response standpoint? • Prioritizing regions and modes of intervention: • What are the vulnerability hot-spots? • How do different risk management elements map onto vulnerability components, and how do we evaluate across these elements? • Evaluating current / planned local coping strategies from the viewpoint of adaptation to climate change: • Are anticipated project benefits at risk? • How (and to what extent) will the project lead to enhanced adaptive capacity? • Understanding response is likely to tell us much about specific and generic adaptive capacity

25. Specific adaptive capacity • To what extent do responses (including management systems) help in reducing vulnerability? • Concepts such as thresholds and coping ranges • Barriers and constraints to adaptation • Ability of the individuals, systems and institutions to perceive changes and respond autonomously • Mal-adaptation

26. Generic adaptive capacity • Adaptation – development linkage • Integrating responses into planning • Measuring capacity • Indicators • Sector-specific approaches • Health • Water • Agriculture

27. How can the understanding and analysis of past and current local coping strategies help? • Developing and validating the underlying theories and conceptual frameworks for vulnerability & adaptation • This is an area where practice drives theory • We have made a start at creating an observational and empirical base, we now need to look at experiments • In practice this might mean pilot adaptation projects • Cross-sectional and temporal analysis of past impacts can help in ground-truthing indicators for specific and generic adaptive capacity by looking at actual, past outcomes • Important, but depends critically on the availability of data • Do we have mal-adaptation? • Hazard & exposure correlation

28. Research needs • What really is adaptive capacity? • Indicators • Scale, process relevance • Impacts – proximate, non-proximate; marginal, non-marginal • Interactions across scales (spatial, temporal, institutional) – aggregation issues • Extremes and variability

29. Policy issues • What are the limitations of local coping strategies? • Or, what is the coping range? • Limits of “autonomous” adaptation: adaptation may be neither automatic, nor successful • How do we replicate successful or viable coping strategies? • Diffusion of system innovations (Amul, Grameen Bank) • How do we create an environment in which local coping strategies will be identified, design and implemented more readily and effectively? • How do we ensure synergies and resolve conflicts between local and regional or national processes and objectives?

30. Adaptation to climate change needs to reach three communities of practice Resource management Adaptation Disaster management Development activities