Evaluating wildland fire liability standards – does regulation incentivise good management?
Christopher J. Lauer A , Claire A. Montgomery B C and Thomas G. Dietterich B
+ Author Affiliations
- Author Affiliations
A National Oceanic and Atmospheric Administration, National Oceanic and Atmospheric Administration (NOAA), 1315 East-West Hwy, Silver Spring, MD 20910, USA.
B Oregon State University, Corvallis, OR 97331, USA.
C Corresponding author. Email: claire.montgomery@oregonstate.edu
International Journal of Wildland Fire 29(7) 572-580 https://doi.org/10.1071/WF19090
Submitted: 16 June 2019 Accepted: 27 February 2020 Published: 24 March 2020
Journal Compilation © IAWF 2020 Open Access CC BY-NC-ND
Abstract
Fire spread on forested landscapes depends on vegetation conditions across the landscape that affect the fire arrival probability and forest stand value. Landowners can control some forest characteristics that facilitate fire spread, and when a single landowner controls the entire landscape, a rational landowner accounts for spatial interactions when making management decisions. With multiple landowners, management activity by one may impact outcomes for the others. Various liability regulations have been proposed, and some enacted, to make landowners account for these impacts by changing the incentives they face. In this paper, the effects of two different types of liability regulations are examined – strict liability and negligence standards. We incorporate spatial information into a model of land manager decision-making about the timing and spatial location of timber harvest and fuel treatment. The problem is formulated as a dynamic game and solved via multi-agent approximate dynamic programming. We found that, in some cases, liability regulation can increase expected land values for individual land ownerships and for the landscape as a whole. But in other cases, it may create perverse incentives that reduce expected land value. We also showed that regulations may increase risk for individual landowners by increasing the variability of potential outcomes.
Additional keywords: approximate dynamic programming, ecological disturbance, fire policy, liability regulation, multi-agent reinforcement learning, risk, spatial, stochastic dynamic games.
References
Ager AA, Vaillant NM, Finney MA (2010) A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure. Forest Ecology and Management 259, 1556–1570.| A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure.Crossref | GoogleScholarGoogle Scholar |
Ager AA, Palaiologou P, Evers CR, Day MA, Barros AM (2018) Assessing transboundary wildfire exposure in the south-western United States. Risk analysis 38, 2105–2127.
| Assessing transboundary wildfire exposure in the south-western United States.Crossref | GoogleScholarGoogle Scholar | 29694686PubMed |
Amacher GS, Malik AS, Haight RG (2005) Not getting burned: the importance of fire prevention in forest management. Land Economics 81, 284–302.
| Not getting burned: the importance of fire prevention in forest management.Crossref | GoogleScholarGoogle Scholar |
Bellman RE (1957) ‘Dynamic programming.’ (Princeton University Press: Princeton, NJ, USA).
Bourrinet J (1992) ‘Wildland fire and the law: legal aspects of forest fires worldwide.’ (Martinus Nijhoff Publishers: Dordrecht, Netherlands).
Busby GM, Albers HJ, Montgomery CA (2012) Wildfire risk management in a landscape with fragmented ownership and spatial interactions. Land Economics 88, 496–517.
| Wildfire risk management in a landscape with fragmented ownership and spatial interactions.Crossref | GoogleScholarGoogle Scholar |
Chung W, Jones G, Krueger K, Bramel J, Contreras M (2013) Optimising fuel treatments over time and space. International Journal of Wildland Fire 22, 1118–1133.
| Optimising fuel treatments over time and space.Crossref | GoogleScholarGoogle Scholar |
Crowley CSL, Malik AS, Amacher GS, Haight RG (2009) Adjacency externalities and forest fire prevention. Land Economics 85, 162–185.
| Adjacency externalities and forest fire prevention.Crossref | GoogleScholarGoogle Scholar |
Daigneault A, Miranda M, Sohngen B (2010) Optimal forest management with carbon sequestration credits and endogenous fire risk. Land Economics 86, 155–172.
| Optimal forest management with carbon sequestration credits and endogenous fire risk.Crossref | GoogleScholarGoogle Scholar |
Donovan GH, Brown TC (2007) Be careful what you wish for: the legacy of Smokey Bear. Frontiers in Ecology and the Environment 5, 73–79.
| Be careful what you wish for: the legacy of Smokey Bear.Crossref | GoogleScholarGoogle Scholar |
Epstein RA (2012) Common law liability for fire. In ‘Wildfire policy: law and economics perspectives’. (Eds K Bradshaw and D Lueck) pp. 3–31. (Routledge RFF Press: New York, NY, USA)
Faustmann M (1849) On the determination of the value which forest land and immature stands pose for forestry. English translation in ‘Martin Faustmann and the evolution of discounted cash flow’. (Ed. M. Gane) Oxford Institute Paper 42, 1968. (University of Oxford Press: Oxford, UK).
Fischer AP, Charnley S (2012) Risk and cooperation: managing hazardous fuel in mixed ownership landscapes. Environmental Management 49, 1192–1207.
| Risk and cooperation: managing hazardous fuel in mixed ownership landscapes.Crossref | GoogleScholarGoogle Scholar | 22525987PubMed |
Garcia-Gonzalo J, Pukkala T, Borges JG (2014) Integrating fire risk in stand management scheduling: an application to maritime pine stands in Portugal. Annals of Operations Research 219, 379–395.
| Integrating fire risk in stand management scheduling: an application to maritime pine stands in Portugal.Crossref | GoogleScholarGoogle Scholar |
Konoshima M, Montgomery CA, Albers HJ, Arthur JL (2008) Spatial-endogenous fire risk and efficient fuel management and timber harvest. Land Economics 84, 449–468.
| Spatial-endogenous fire risk and efficient fuel management and timber harvest.Crossref | GoogleScholarGoogle Scholar |
Konoshima M, Albers HJ, Montgomery CA, Arthur JL (2010) Optimal spatial patterns of fuel management and timber harvest with fire risk. Canadian Journal of Forest Research 40, 95–108.
| Optimal spatial patterns of fuel management and timber harvest with fire risk.Crossref | GoogleScholarGoogle Scholar |
Lauer CJ, Montgomery CA, Dietterich TG (2017) Spatial interactions and optimal forest management on a fire-threatened landscape. Forest Policy and Economics 83, 107–120.
| Spatial interactions and optimal forest management on a fire-threatened landscape.Crossref | GoogleScholarGoogle Scholar |
Lauer CJ, Montgomery CA, Dietterich TG (2019) Managing fragmented fire-threatened landscapes with spatial externalities. Forest Science fxz012
| Managing fragmented fire-threatened landscapes with spatial externalities.Crossref | GoogleScholarGoogle Scholar |
National Interagency Fire Center (2016) Fire information – statistics. Available at https://www.nifc.gov/fireInfo/fireInfo_stats_totalFires.html [Verified November 2016]
Oregon State Legislature (2013) Relating to civil actions regarding forest fires; and declaring an emergency 77th Oregon Legislative Assembly. Senate OR SB 709. Available at https://olis.leg.state.or.us/liz/2013R1/Measures/ProposedAmendments/SB0709 [Verified March 2020]
Palaiologou P, Ager AA, Nielsen-Pincus M, Evers CR, Kalabokidis K (2018) Using transboundary wildfire exposure assessments to improve fire management programs: a case study in Greece. International Journal of Wildland Fire 27, 501–513.
| Using transboundary wildfire exposure assessments to improve fire management programs: a case study in Greece.Crossref | GoogleScholarGoogle Scholar |
PG&E Corporation (2019) PG&E Corporation and Pacific Gas & Electric Company, Debtor. No. 19–30088-DM and No. 19–30089-DM (US Bankruptcy Court, Northern District of CA. 31 January 2019). Available at http://www.canb.uscourts.gov/case-info/pge-corporation-and-pacific-gas-and-electric-company [Verified March 2020]
Powell WB (2007) ‘Approximate dynamic programming: solving the curses of dimensionality.’ (John Wiley & Sons: Hoboken, NJ, USA).
Powell WB (2009) What you should know about approximate dynamic programming. Naval Research Logistics 56, 239–249.
| What you should know about approximate dynamic programming.Crossref | GoogleScholarGoogle Scholar |
Puterman ML (1994) ‘Markov decision processes: discrete stochastic dynamic programming.’ (John Wiley & Sons: Hoboken, NJ, USA).
Reed WJ (1984) The effects of the risk of fire on the optimal rotation of a forest. Journal of Environmental Economics and Management 11, 180–190.
| The effects of the risk of fire on the optimal rotation of a forest.Crossref | GoogleScholarGoogle Scholar |
Reed WJ (1989) Optimal investment in the protection of a vulnerable biological resource. Natural Resource Modeling 3, 463–480.
| Optimal investment in the protection of a vulnerable biological resource.Crossref | GoogleScholarGoogle Scholar |
Reed WJ (1993) The decision to conserve or harvest old-growth forest. Ecological Economics 8, 45–69.
| The decision to conserve or harvest old-growth forest.Crossref | GoogleScholarGoogle Scholar |
Routledge RD (1980) The effect of potential catastrophic mortality and others unpredictable events on optimal forest rotation policy. Forest Science 26, 389–399.
| The effect of potential catastrophic mortality and others unpredictable events on optimal forest rotation policy.Crossref | GoogleScholarGoogle Scholar |
US Congress (2005) S.807 – Enhanced safety from wildfire act of 2005. 109th Congress (2005–2006) Available at https://www.congress.gov/bill/109th-congress/senate-bill/807/text [Verified June 2016]
Samuelson PA (1976) Economics of forestry in an evolving society. Economic Inquiry 14, 466–492.
| Economics of forestry in an evolving society.Crossref | GoogleScholarGoogle Scholar |
Schmidt KM, Menakis JP, Hardy CC, Hann WJ, Bunnell DL (2002) Development of coarse-scale spatial data for wildland fire and fuel management. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-87. (Fort Collins, CO, USA).
Spies TA, White EM, Kline JD, Fischer AP, Ager A, Bailey J, Bolte J, Koch J, Platt E, Olsen CS, Jacobs D, Shindler B, Steen-Adams MM, Hammer R (2014) Examining fire-prone forest landscapes as coupled human and natural systems. Ecology and Society 19, art9
| Examining fire-prone forest landscapes as coupled human and natural systems.Crossref | GoogleScholarGoogle Scholar |
Sutton RS, Barto AG (1998) ‘Introduction to reinforcement learning (1st edn).’ (MIT Press: Cambridge, MA, USA).
Washington State Legislature (2014) Specifying recovery for fire damages to public or private forested lands. 63rd Legislature, Senate WA SB 5972. Available at https://apps.leg.wa.gov/billsummary/?BillNumber=5972&Year=2013&Initiative=false [Verified March 2020].
Watkins C, Dayan P (1992) Q learning: technical note. Machine Learning 8, 279–292.
| Q learning: technical note.Crossref | GoogleScholarGoogle Scholar |
Wei Y, Rideout D, Kirsch A (2008) An optimization model for locating fuel treatments across a landscape to reduce expected fire losses. Canadian Journal of Forest Research 38, 868–877.
| An optimization model for locating fuel treatments across a landscape to reduce expected fire losses.Crossref | GoogleScholarGoogle Scholar |
Yoder J (2004) Playing with fire: endogenous risk in resource management. American Journal of Agricultural Economics 86, 933–948.
| Playing with fire: endogenous risk in resource management.Crossref | GoogleScholarGoogle Scholar |
Yoder J, Tilley M, Engle D, Fuhlendorf S (2003) Economics and prescribed fire law in the United States. Review of Agricultural Economics 25, 218–233.
| Economics and prescribed fire law in the United States.Crossref | GoogleScholarGoogle Scholar |
Zaimes GN, Tufekcioglu M, Tufekcioglu A, Zibtsev S, Corobov R, Emmanouloudis D, Uratu R, Ghulijanyan A, Borsuk A, Trombitsky I (2016) Transboundary collaborations to enhance wildfire suppression in protected areas of the Black Sea Region. Journal of Engineering Science and Technology Review 9, 108–114.
| Transboundary collaborations to enhance wildfire suppression in protected areas of the Black Sea Region.Crossref | GoogleScholarGoogle Scholar |
