PhD position now closed for applications (SeNSS-ARIES DTP)

Following the light: using ‘brightspots’ to avoid future Amazonian fires

Interested in what drives variability in the relationship between humans and fire in Amazonia, and how lessons from success stories can be transferred into policies that prevent forest loss? This is the PhD for you!

For any enquiries related to the studentship topic, please contact Dr Rachel Carmenta (

The deadline for applying to University of East Anglia is 23:59 GMT on 23 February 2022. The deadline for submitting your application on HEIApply is 12:00 GMT on 28 February 2022


Responding to the reality of pervasive tropical forest fires is an urgent social and environmental challenge of our time. Tropical fires emit disproportionate quantities of carbon, harm public health and human well-being through smoke exposure, and damage the economy. Reducing their incidence, especially during droughts, has the potential to deliver benefits to people and nature, as well as contributing to climate commitments. Yet leading top-down approaches have failed, and underscore the need for integrated approaches that combine methods and scales of analysis across the natural and social science to inform management responses.

This project will adapt the notion of brightspots to the case of tropical fire for the first time. It will inform our understanding of how, despite high fire-risks, some endogenous local responses have been successful. Contrasting with brightspots are darkspots where fire outcomes are worse than expected, and a third instance are examples of success stories. These transformation sites are where darkspots have transformed to brightspots. Taking the concept of a brightspot typology to the tropical fire complex and observing (remotely) and learning from (locally) the existence of bright-, dark- and transformation sites creates an important and timely opportunity to inform adaptation and mitigation policies with locally grounded knowledge, experience and practice.

This project will make a critical new contribution to the design of future fire interventions by assessing the prevalence of the brightspot policy. It will identify the circumstances that differ between brightspots and darkspots and begin to disentangle the critical factors that underpin the success stories and shortfalls of past fire management. Locating sites in Amazonia across this brightspot typology will inform our understanding of how, despite high fire-risks, some endogenous local responses have been successful and provide evidence needed to contribute towards steering the Amazon away from a fire-prone future. This project offers an important and timely opportunity to inform adaptation and mitigation policies with locally grounded knowledge, experience and practice.

Guided by a set of research questions, the student will first use geospatial analysis and regression modelling to identify, locate and quantify the brightspot typology across Amazonia. This desk-based analysis will guide selection of fieldwork sites, that will be visited in a field season using social science and participatory methods to understand the processes that explain fire prevalence.

 The funded student will receive support from a team of leading interdisciplinary researchers and non-academic partners at the forefront of risk-reduction in the Amazon (CEMADEM). The studentship comes with an exceptional cross-disciplinary training programme and will benefit from the dynamic research centres at UEA, including the Environmental Justice group, the Critical Decade DTC, and the Tyndall Centre.

Study Region

The project focuses on the Brazilian Amazon, which has been a particular epicentre of extensive forest-fire events. Brazil has suffered greatly from rising frequencies of fires relative to background levels. However, coarse scale analyses at state level mask considerable variation that only becomes visible and explainable at smaller spatial scales. Even at the landscape level, where typical social and economic indicators and environmental factors are relatively consistent, variability in fire frequency can be observed. For instance, within the Tapajós-Arapíuns reserve in Pará, some regions have experienced repeated burning in recent decades whereas other areas have evaded fire. Our scoping research in two sustainable use reserves in Pará has indicated the role of social capital, community organization and place-based knowledge as contributing to fire protection, but an in-depth analysis across the brightspot typology remains lacking.

Multidisciplinary Research Ethos

This PhD will enable the design of equitable and integrated fire management interventions by combining methods and scales of analysis. Notably it will harness the temporal and geographic breadth of geospatial analysis of fire in combination with empirical social science fieldwork to understand the endogenous socio-cultural and economic factors have mitigated fire risk.

Insights from the geospatial analysis will identify brightspots and determine the location of field work, enabling the social science to be conducted in the optimal locations representing the success stories and failures of past interventions. Place-based work will offer learning about the social, economic and institutional contexts that have enabled brightspots, and areas that transitioned from darkspots to brightspots will receive added focus as such a shift is indicative of a fundamental shift in the effectiveness of fire policy. Through this combination of scales and methods, the student will identify lessons that could inform effective policy intervention targeted across the brightspot typology to contribute to safeguarding the Amazon where conventional top-down approaches have failed.

Research Questions

The student will address four research questions as follows:

  1. Where and when do wildfires begin across the Brazilian Amazon, and what is the association between fire escape and climatic and socioeconomic predictors (e.g. drought, demographics, environment) of wildfire risk?
  2. Where are the bright- and darkspots located in Amazonia and how do these areas map onto land user groups? In addition, where are there examples of ‘transformation sites’?
  3. What local institutions, social norms, and resource management practices have enabled the persistence or emergence of brightspots?
  4. What policy recommendations can be gained from brightspots (fire-free success strories) and darkspots (fire-prone sites) to inform targeted policy that will help mitigate future fires and contribute to the resilience and well-being of local communities?

Expected Outcomes and Impact

Academic Outputs

The PhD thesis will be composed of a sequence of 3-4 research articles to be submitted or in preparation to scientific journals. The student will be encouraged to present at an international interdisciplinary conference (e.g RGS and European Geoscience Union Meeting).

Building Engagement

A solution-orientated focus is at the heart of the project, and non-academic outputs will distil empirical work in a variety of formats intended for policy makers, practitioners and the public, supported by the Tyndall centre’s renowned communications team.  These will include a policybrief, podcast, infographic and a far-reaching blog (e.g. the Conversation; CIFOR Forest News).  Twitter threads will accompany publications. Outreach will be available in Portuguese and English.

The student will have the opportunity to join vibrant research groups and communities of practice including the Tyndall Centre, notably the Overcoming Poverty with Climate Action research theme (TYN); the environmental justice research group (DEV); the Sustainable Amazon Network (RAS) and the MAP-Fire monitoring Platform (CEMADEM). The student will offer a Guest Seminar in the Postgraduate programme on Sustainability Science (Federal University of Pará (UFPA)). These networks offer fantastic opportunity for the student to make connections, share progress, integrate feedback and mature research plans and will help to ground the student in a firm understanding of the crucial contemporary issues related to the tropical fire.

Achieving Policy Impact

The project has been co-developed with project partners and the research focus speaks directly to their practical needs and priorities. Liana Anderson represents CEMADEN and is heavily involved in fire risk reduction in the Amazon region and can support in reaching Amazonian governors with project findings. All supervisory panel members have extensive networks that will help to ensure that findings are delivered to relevant stakeholders involved in fire management and risk mitigation in the region.


Dr. Rachel Carmenta (School of International Development, University of East Anglia)

Dr Matthew Jones (School of Environmental Sciences, University of East Anglia)

Dr. Liana Anderson (National Center for Monitoring and Alerting of Natural Disasters, Brazil)

Prof. Iokine Rodriguez (School of International Development, University of East Anglia)

Prof. Jos Barlow (Lancaster Environment Centre, University of Lancaster)


A number of training opportunities will ensure the foundations for excellent interdisciplinary research capacity and support the student to develop the methods and theoretical approaches needed for this project. The student will have access to the training opportunities provided by the SENSS and ARIES DTPs and UEA. Depending on the background and specific needs of the student, the training programme will be adapted, but is likely to include courses on: data science methods and modelling including machine learning; geospatial analysis; research design principles (including mixed methods); philosophy of science; participatory methods; language training.

Person Specification

  • 2:1 in a Bachelor’s degree.
  • IELTS 7.0 with at least 6.5 in every component or equivalent
  • Highly-motivated individual, who was excited by the prospect of cutting-edge interdisciplinary research of policy relevance.
  • Enthusiasm for working collaboratively with social scientists and ecologists.
  • Interest in applying qualitative and quantitative methods.
  • Strong analytical skills and GIS expertise.