1. Public Experience, Attitudes, & Knowledge Toward Forest Fire, Risk, & Recovery J.M. Bowker, H.K. Cordell, S. Rideout-Hanzak, C.Y. Johnson USDA Forest Service S-H. Lim, G.T. Green University of Georgia JFSP PI Workshop Phoenix, AZ 4/8/04

2. Objectives Explore Public’s - Experience with forest fire - Experience with forest fire - Knowledge of fire & fire ecology - Knowledge of fire & fire ecology - Attitudes -Fire Management - Attitudes -Fire Management - Attitudes - Fire risk - Attitudes - Fire risk - Fire prevention behavior - Fire prevention behavior

3. Objectives Assess Explanatory Factors - Gender, Race, Age - Gender, Race, Age - Income, Education, Employment - Income, Education, Employment - Region, Immigration - Region, Immigration - Where-raised, Where-living - Where-raised, Where-living

4. Methods Data - National telephone survey (NSRE) - National telephone survey (NSRE) - Approx 40 questions - Approx 40 questions - Two treatments @ 3000 - Two treatments @ 3000 Fall 2002 – Spring 2003 Fall 2003 – Spring 2004 www.srs.fs.usda.gov/trends/Nsre/ nsre2.html

5. Methods Analysis - Frequencies (post sample wts) - Frequencies (post sample wts) - Logistic regression - Logistic regression Binary, Multinomial, Ordered - Poisson knowledge score model - Poisson knowledge score model - Excel probability spreadsheets - Excel probability spreadsheets

6. Results (n=3000+) Experience Yes (%) - Seen, heard, read 3 mo86 - Seen, heard, read 3 mo86 - Diff wild vs prescribed83 - Diff wild vs prescribed83 - Ever witness forest fire 40 - Ever witness forest fire 40 - Seen forest post burn 67 - Seen forest post burn 67 - Smoke affected travel39 - Smoke affected travel39 - Fire altered rec plans19 - Fire altered rec plans19

7. Results Risk Very Likely (%) - Fire w/i 10 mi home26 Concerned (%) Concerned (%) - Home damaged fire10 - Smoke prescribed fire 34 - Wildlife prescribed fire48 - Scenery prescribed fire40

8. Results Risk AvoidanceYes(%) - Clear vegetation from35 buildings - Spray herbicide control 12 undergrowth - Extra property insurance 36 - Keep firefighting equip 30 - Routinely burn under- 7 growth around home

9. Results Knowledge True(%) - Most wildfires natural40 - Most wildfires natural40 - Wildfire destructive52 - Wildfire destructive52 long-term forest health - Wildfire a leading 47 - Wildfire a leading 47 environmental problem

10. Results Knowledge True (%) - Prescribed & wildfire43 - Prescribed & wildfire43 similar effects - Prescribed fire kills too26 - Prescribed fire kills too26 many large trees - Prescribed regularly21 - Prescribed regularly21 out of control - Prescribed fire reduces79 - Prescribed fire reduces79 wildfire risk wildfire risk

11. Results KnowledgeTrue (%) - Fire increases chances23 insect or disease o-b’s - Fire useful to control64 undesirable weeds - Many plants require57 fire in life cycle

12. Results Attitudes Agree (%) - Natural recovery56 - Natural recovery56 - Put out all wildfires51 - Put out all wildfires51 - Allow remote burns38 - Allow remote burns38 if humans unthreatened - Post fire timber salvage71 - Post fire timber salvage71 makes sense makes sense

13. Results Attitudes Agree (%) - People choosing to live 91 near forests accept risks - Homeowners should follow 80 gov’t guidelines to manage for wildfire risk

14. Results Attitudes Agree (%) - Public land managers … - Public land managers … - Trusted to select best 66 methods for wildfire - Use mechanical ground 58 veg removal - Use chemical treatments 26 - Use prescribed fire 74

15. Results AttitudesConcerned (%) - Public land managers’ ability to manage fire 36 in forests & rangeland - Gov’t not consider tax- 51 payer costs… - Gov’t not consider long- 66 term ecosystem health …

16. Results Factors Significant - RaceMost - Gender Most - Region Most - AgeOften - IncomeOften - EducationOften

17. Some Implications Experience 15% - Simply not tuned in Attitudes Attitudes Buyer beware Buyer beware Timber salvage Timber salvage Anti-chemical Anti-chemical Prescribed fire wins Prescribed fire wins Ecosystem health Ecosystem health Pro’s generally trusted … Pro’s generally trusted …