@article{bd576fe2f4564a18a90753119584acc0,
title = "Adapting to frequent fires: optimal forest management revisited",
abstract = "As the frequency and severity of wildfires escalates in many regions, the study of fire-resilient forestry practices becomes crucial. While forest owners may employ several silvicultural practices to mitigate fire damage, the analytical study of optimal forest management has been reduced to the effects of fire on optimal rotation only. The fundamental result of this literature date back to the early 1980s and has remained virtually uncontested since then. This paper develops an infinite rotation cycle forest model in which landowners optimally choose rotation age, volume, and timing of partial harvesting in the presence of fire risk. We show that this setting fundamentally changes earlier results. In particular, more frequent fires imply beginning commercial thinning sooner but not necessarily shortening the rotation age. Two numerical applications highlight the empirical relevance of our findings.",
keywords = "Climate change, Faustmann model, Fire risk, Optimal rotation, Optimal thinning",
author = "Patto, {Jo{\~a}o V.} and Renato Rosa",
note = "Funding Information: The authors are grateful to two anonymous referees for helpful comments. This work was funded by Fundac?a?o para a Ci?ncia e a Tecnologia (UID/ECO/00124/2019, UIDB/00124/2020 and Social Sciences DataLab, PINFRA/22209/2016), POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016). Renato Rosa acknowledges funding from FCT under the Scientific Employment Stimulus (CEECIND/02230/2017). Authors also gratefully acknowledge financial support by FCT under the project PTDC/EGE-ECO/30523/2017. Funding Information: The authors are grateful to two anonymous referees for helpful comments. This work was funded by Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia ( UID/ECO/00124/2019 , UIDB/00124/2020 and Social Sciences DataLab , PINFRA/22209/2016 ), POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016 ). Renato Rosa acknowledges funding from FCT under the Scientific Employment Stimulus ( CEECIND/02230/2017 ). Authors also gratefully acknowledge financial support by FCT under the project PTDC/EGE-ECO/30523/2017 . Publisher Copyright: {\textcopyright} 2021",
year = "2022",
month = jan,
doi = "10.1016/j.jeem.2021.102570",
language = "English",
volume = "111",
journal = "Journal of Environmental Economics and Management",
issn = "0095-0696",
publisher = "Elsevier",
}