Humans and fire in Amazonia: mapping fire to land user groups
Lead supervisors: Dr Matthew Jones
Location: School of Environmental Sciences, University of East Anglia
Duration: 8 weeks
Suitable undergraduate degrees: Geography, Environmental Science, Climate Science, Earth Science or similar
Amazonia is one of Earth’s critical biodiversity hotspots and the region stores vast quantities of carbon, however these vital environmental services are threatened by human expansionism and exploitation of natural resources. Fire is the key agent for forest clearing in Amazonia. While fire and deforestation rates have fallen significantly since the early 2000s, a worrying resurgence of deforestation fires has been seen since 2015 and is associated with development agendas of large landowners in response to international demand for commodity production. Meanwhile, fire also has a key and distinct role in traditional small-scale agriculture and has been used by indigenous and traditional communities to manage their land sustainably over generations. Nonetheless, there has been little attempt to explicitly quantify distinct fire types, for example through spatially mapping fire activity to regions with a high density of expansionist land users versus traditional small-scale agricultural communities. This quantitative work is critical to evaluating the long-term impacts of Amazonian fires on the carbon budget and biodiversity, and to tailoring policies to the capacities, resources and attitudes of different fire users. We are engaged in exploratory research that strives to characterise fire types associated with land user groups in Amazonia at the municipality level, and to map fire activity to those land user spaces. The project will make novel use of records of crop, livestock and forestry production data available via our partners in Brazil, as well census data indicative of land user groups and trade data representing the flow of agricultural produce and timber products within Brazil and across international borders. These socioeconomic data are vital and under-utilised proxies for the diverse uses of land in Amazonia. The student will drive the first exploratory use of the data and will be supported to develop novel methods for characterising Amazonian fire regimes using statistical classification techniques.
The student will provide key input to this project by (i) collaborating across the partnership to collate the diverse datasets, (ii) processing the data into a common municipality-level format, and (iii) designing a new methodology for characterising land user types in municipalities with regular support from the lead supervisor (see ‘Skills development’). The student will also have access to fire hotspot and footprint data from international collaborators, enabling them to explore trends in fire activity in ‘case study’ municipalities of their choosing in Amazonia, and to relate those trends to shifts in land user groups. The student will prepare a short report and will be encouraged to present their findings to our international partners (see ‘End users’).
Supervisors: Matthew Jones (lead, UEA ENV), Rachel Carmenta (UEA DEV), Rachel Warren (UEA ENV).
Partners: Luiz Aragão (National Institute for Space Research, Brazil); Liana Anderson (National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN, Brazil); Niels Andela (Cardiff University).
Three ARIES themes: Ecology and Biodiversity; Geosciences, Resources and Environmental Risk; Agri-environments and Water.
Beneficiaries/End users: Project partners INPE and CEMADEN jointly contribute to the monitoring and understanding of threats to biodiversity and carbon storage in Amazonia and hold capacity to influence national policy on protection of the region. Our partners are also involved in the REDD+ network (Reducing Emissions from Deforestation and forest degradation in Developing countries), an initiative of the United Nations Framework Convention on Climate Change. The results of this exploratory work will be presented to partners (the student will be encouraged to present).