Valuing User Preferences for Geospatial Fire Monitoring in Guatemala

Like many landscapes across Central America, forests in Guatemala’s Maya Biosphere Reserve (MBR) are increasingly susceptible to forest fire, with most forest fires resulting from untended agricultural fires. Fire damage poses significant risk to the MBR’s natural resources and cultural heritage, bu...

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Autores principales: Jared Berenter, Isaac Morrison, Julie M. Mueller
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/cd0c9f313ec7448e9f26160c9049ea96
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Sumario:Like many landscapes across Central America, forests in Guatemala’s Maya Biosphere Reserve (MBR) are increasingly susceptible to forest fire, with most forest fires resulting from untended agricultural fires. Fire damage poses significant risk to the MBR’s natural resources and cultural heritage, but budget challenges limit the capacity of national, regional, and local institutions to effectively detect, monitor, and control forest fires. The Geospatial Information System for Fire Management (SIGMA-I) is a United States government-subsidized suite of geospatial fire management tools that are widely disseminated, free of charge, to land managers and other users in Guatemala for on-the-ground fire prevention and response. Provision of SIGMA-I geospatial data and tools such as daily thermal “hotspot” maps provide positive benefits for sustainable fire management. However, little research exists supporting the nonmarket monetary value of geospatial fire monitoring tools and their component features. We used a choice experiment to estimate land managers’ willingness to pay for individual attributes of SIGMA-I hotspot mapping in Guatemala. We found quantitative evidence of positive willingness to pay for geospatial data, demonstrating positive nonmarket value of geospatial data for sustainable fire management in developing countries and regions where agricultural fires are common. Our results indicate strong preferences from Guatemala’s forest fire management community for improving the frequency of hotspot reporting and reducing detection of erroneous hotspots. As the availability of geospatial data increases, use of tools like SIGMA-I has the potential to significantly improve fire management, especially in regions where funding and resources for fire management are scarce. Our results support continued multinational funding for tools like SIGMA-I for forest fire management in Guatemala and other developing countries.