10/14/ :15pmGeog Adjustment to Hazards Individual Choice (Kates, in Cutter, Ch 6) Adjustment to Hazards Individual Choice (Kates, in Cutter, Ch 6 ) categories of adjustment individual adjustment options cognitive and affective influences on choice theory of choice behavioural choice patterns Geography 106b Hazards

10/14/ :15pmGeog Exercise Individual Choice Scenario What will you do to reduce/prevent the impact of drought? How would your choices differ if you were an Australian wheat farmer? You are a maize farmer on a mountain slope in Tanzania known to be at risk of drought.

10/14/ :15pmGeog Individual Adjustment Categories cultural adaptation more rapid than biological adaptation but relatively slow compared to purposeful adjustment typically stable relations - people and environment e.g., Inuit Mackenzie River Delta discovery of oil forces adaptation as resource is developed e.g., work in waged labour to offset subsistence losses (e.g. fishing)

10/14/ :15pmGeog Individual Adjustment Categories purposeful adjustment relatively rapid and overlapping adjustments hazard related focus of most research e.g., Tanzanian farmer grows drought resistant crops incidental adjustment relatively rapid not hazard related e.g, improved building materials due to increased wealth e.g., improved communications networks Pineapples, drought-resistant

10/14/ :15pmGeog Individual Adjustment Categories absorptive capacity measure of the ability of individuals or groups to sustain impacts from hazard or disaster results from combinations of cultural adaptation, purposeful adjustment and incidental adjustment e.g., Kilungu of Kenya – plant maize, beans, millet, cow peas, sorghum, ground nuts etc all together – appears chaotic but drought resistant (e.g., encourages deep roots)! Moving to monoculture potentially devastating.

10/14/ :15pmGeog Individual Adjustment Options (see also previous lecture) change location change use prevent effects modify events share loss bear loss - adjustment varies greatly by culture and hazard

10/14/ :15pmGeog Individual Adjustment Options Examples Note: Sri Lanka respondents listed 264 separate adjustments to flood

10/14/ :15pmGeog General Choice Model

10/14/ :15pmGeog Ordered Choice (decisions are social)

10/14/ :15pmGeog Choice Tree some strategies for preventing losses need to happen several years in advance of an event to be effective others only happen long after event occurs Adaptations to drought in Kenya (YouTube)

10/14/ :15pmGeog Cognitive and Affective Influences on Choice T or F? Based on 100 years of data, the estimated probability of a “100 years” tornado touching down in Disastertown in 2005 was In 2005 a tornado touched down in Disastertown. The likelihood of a “100 years” tornado touching down in 2006 year is considerably less than 0.01 because one already struck in 2005.

10/14/ :15pmGeog Cognitive and Affective Influences on Risk Appraisal gambler’s fallacy occurrence of a chance event influences the probability of future occurrences BUT, see Monty Hall probability problemMonty Hall probability problem anchoring start with a initial rough estimate of likely occurrence, then adjust slightly as new information arrives depends too much on the initial rough estimate typically leads to underestimation of risk (Note: both of these assume knowledge of a “correct answer”, is this the case in the real world of hazards/disasters?)

10/14/ :15pmGeog Event Prediction by Hazard and Country

10/14/ :15pmGeog People are more likely to be better appraisers of hazard probability if they are: rural vs urban have more experience with the hazard urban owner vs urban renter middle aged vs young or old Cognitive and Affective Influences on Risk Appraisal

10/14/ :15pmGeog Theory of Choice Based on this information, which would you choose?

10/14/ :15pmGeog Theory of Choice Based on this information, which would you choose?

10/14/ :15pmGeog Theory of Choice expected utility optimize, choose maximizing outcome choosing on the basis of all expected outcomes probabilities are multiplied against normative assessments of value (utility) (e.g., equipment, evacuation costs) major hurdle: ascribing probabilities to events aka “uncertainty” perfect information rare for individual “choosers”

10/14/ :15pmGeog Theory of Choice Based on this information, which would you choose?

10/14/ :15pmGeog Theory of Choice subjective expected utility optimize, choose maximizing outcome probabilities and values (utilities) ascribed by “chooser” experts and individuals may arrive at very different “optimum” outcomes

10/14/ :15pmGeog Theory of Choice Based on this information, which would you choose?

10/14/ :15pmGeog Theory of Choice bounded rationality satisfice, choose personally, socially acceptable option probabilities and values (utilities) ascribed by “chooser” and/or experts thresholds may apply or non- maximizing priorities e.g. fisher wants to remain debt-free so will evacuate up to the point that it keeps her out of debt – otherwise remains regardless of “utility”

10/14/ :15pmGeog Theory of Choice Review Difficult to know which form of choice people will use

10/14/ :15pmGeog Four Behaviour (Choice) Patterns Absorb deny risk outright, or viewed as “unproblematic” typically probability dismissed as too low to worry about fate determined by capacity of individuals/group to absorb losses e.g., San Andreas fault, virgin islands coast cognitive dissonance –recognizes that choice is limited by social influences –acknowledging hazard risk involves “uncomfortable feelings” –two general choices – a) action: admit there is a risk and thus take action (because that is socially required) b) no action: change your perception of the potential risk

10/14/ :15pmGeog Four Behaviour (Choice) Patterns Accept aware of hazard (no denial) fatalistic – little can affect impacts acts of “God” passive – actions are useless e.g. Malawi floods, Nigerian drought, Hawaiian lava

10/14/ :15pmGeog Four Behaviour (Choice) Patterns Reduce aware of hazard (no denial) take action to reduce impacts typically emergency action and some preparation usually “stay put” e.g., Malawi floods, many drought areas, snow and wind hazard sites Change aware of hazard (no denial) take action to reduce impacts radical action: move away or change land use (e.g., subsistence to cash cropping; waged labour instead of farming) e.g., Brazilian and Australian droughts

10/14/ :15pmGeog Implications of Individual Choice Patterns influences on choice are many and varied thus, patterns are tough to predict being in MDC does not assure maximum loss reduction thus, vigilance required individuals are influenced by social values and norms as well as government intervention thus, considerable capacity for governments to influence loss reduction (e.g., education/awareness campaigns)