IAP-24-072

Bridging tradition and technology: advanced remote sensing and local knowledge for tropical forest biodiversity and biomass mapping in Amazonia.

This project is part of the UKRI-NERC funded project “Amazonian BioTechQuilombo – Amazonian Biodiversity, Technology Assessment and Knowledge Exchange with Quilombos”, within the Amazon+10 Initiative in Brazil (https://www.amazoniamaisdez.org.br/en/iniciativa). Your PhD project will focus on the use of advanced laser scanning and optical remote sensing methods to evaluate tropical forest diversity and carbon storage in remote areas of the Amazon rainforest. The main goal of this research is to assess the biodiversity, forest structure and forest biomass stocks at locations recognized as data gaps for Amazon rainforest ecosystems, and support understanding the role of habitat structure on faunal diversity. During your research, you will develop both a solid background in tropical forest ecology and strong field and analytical skills in forest inventory, terrestrial and aerial laser scanning, drone-based remote sensing and statistical modelling and AI/machine learning. You will also have the opportunity to participate on large multidisciplinary field expeditions to remote areas of the Amazon basin.

Our ideal candidate would have a background in both remote sensing and plant ecology biodiversity, but ample training opportunities will be offered in both aspects for the duration of the project. The candidate will be based mainly at University of Stirling, in Scotland, with frequent visits to University of Newcastle and University of Manchester, and will include up to 18 months of internship at Sylvera headquarters in London, UK. This project involves extended periods of remote field work in remote areas of the Amazon basin.

BioTech Quilombo is a large multidisciplinary project involving more than 40 scientists from Brazil, the UK and Switzerland, alongside 10 Quilombola leaders from Brazil, aimed at collaboratively diagnosing and filling biodiversity data gaps by combining the knowledge of traditional black peoples in the Amazon (Quilombolas) with state-of-the-art methods such as lidar and thermal remote sensing, e-DNA/DNA barcoding, bioacoustics and camera trapping to comprehensively record the biota and characterise the landscape. Drawing on the rich experiences of the Quilombola communities, we will identify animal and plant species that are critical to their livelihoods and evaluate how their way of life ensures the preservation of natural ecosystems. In addition, we will train traditional communities in biodiversity surveying, build a database documenting the biodiversity of the areas studied, and develop a technological framework that will facilitate future research and ongoing biodiversity assessments and monitoring efforts.

The first component of the research will be to integrate traditional knowledge with historical satellite imagery from both optical (Landsat/Sentinel-2/Planetscope), synthetic aperture radar (PALSAR / Sentinel-1) and digital terrain models (Copernicus DEM) to characterise forest disturbance and landscape variability and use this information to determine the optimal distribution of forest inventory plots that maximize environmental variability and potential biodiversity. You will then participate on field research expeditions to survey forest floristic composition and measure different metrics of forest structural diversity, as well as acquiring drone-based and terrestrial laser scanning (LIDAR) datasets that capture the 3D structure of the forest, together with very high spatial resolution (~3cm) drone optical imagery. You will then use this data to develop and deploy machine learning methods for identifying tree species and estimating biomass and carbon stocks. The biomass component of the research will be developed in collaboration with CASE partner Sylvera Ltd. (https://www.sylvera.com/), who are pioneers in developing multiscale, AI-enabled methods for biomass estimation using remote sensing. Within the project, you will also contribute to training Quilombola communities and Quilombola scientists in biodiversity monitoring.

Year 1

During year 1 you will perform an extensive literature review to familiarise yourself with theory and methods related to Amazon forest diversity and function and receive extensive training in the sampling methods. You will also participate in frequent research team meetings including recognized specialists in plant and animal ecology and remote sensing from multiple countries and contribute with the planning and experimental design of the expeditions. At the end of year 1 you will then draw from this knowledge to identify the research questions that will comprise the analysis chapters of your dissertation within the opportunities offered by the larger project scope. You will also be able to participate in IAPETUS training activities. Depending on your availability, you may participate on our first round of expeditions in July 2025 (before the official start of the PhD), and you will be expected to participate in the second round of expeditions in July 2026.

Year 2

During the first semester of year two, you will work on the organisation, processing and analysis of the data collected during the 2025 and 2026 expeditions, in relation to your research questions. You will also participate in the last round of scientific expeditions planned for January 2027. In the second semester of year two you will start working on a scientific manuscript reporting on the investigation of your first research question, as well as attend and present at a scientific conference. You may also use the data and results obtained to support your own independent applications for additional funding in support of further training and/or fieldwork, in addition to benefiting from training opportunities offered by IAPETUS and by the partner universities.

Year 3

During year three you will continue to work on answering your research questions and documenting the work as dissertation chapters/journal articles. You will also arrange your internship with CASE partner Sylvera, to focus on the biomass and carbon stock estimation of aspects of the project. You will ideally submit a second manuscript for publication during year 3 and present your work on at least one relevant international conference. You will also receive specific training and mentoring related to academic and career development, as offered by the supporting universities and IAPETUS, to prepare you for entering the job market.

Year 3.5

During year 3.5 you will finalise your thesis and ideally submit your third manuscript for publication. As you finalise your degree, you will be coached and supported in preparation for your next career stage.

You will receive training in the frontier of knowledge in tropical forest ecology. You will also be trained on advanced scientific programming and statistical methods, as well as LiDAR surveying, drone operation and remote sensing. There will also be opportunity to interact with collaborating researchers in the project working with camera trapping, bioacoustics, thermal remote sensing and environmental-DNA. Through IAPETUS and the supporting universities, you will have ample opportunity to engage with training on research practices, academic writing and speaking skills, career development and other specific technical training identified as require for your research.