About

Dr. Paul Rougieux

Paul Rougieux is a forest economist specializing in the interface between forest science, economics, and European policy. With a PhD in Economics (Université de Lorraine, 2017), a master in woods products engineering (Université de Lorraine, 2004), and experience at the Joint Research Centre of the European Commission (JRC), at the French National Institute of Agricultural and Environmental Research (INRAE) and at the European Forest Institute (EFI), he develops demand forecasting models for the bioeconomy.

His research bridges forest economics, international trade, forest dynamics modelling, carbon cycle modelling and climate policy, supporting decision-makers through quantitative analysis and reproducible methodologies.

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Research Expertise

🌳 Forest Economics & Policy Modelling

  • Simulation of market dynamics, policy impacts, and resource allocation in forest-based economies.
  • Developer of models linking harvest decisions with forest carbon accounting.
  • Integration of ecological and economic models in long-term projections up to

🌍 International Trade Analysis

  • Analysis of global trade flows in forest and agricultural products.
  • Studies on deforestation risks in EU imports and timber regulation enforcement.

🍃 Forest Dynamics & Climate Change

  • Quantitative modelling of forest growth, climate impacts, and sink trajectories.
  • Contributor to EU forest carbon sink projections and strategic foresight assessments.

⚙️ Open Science & Research Software

  • Developer and maintainer of open-source software for trade and forest modelling.
  • Strong track record in reproducible research practices and data workflow design.
  • Support for sustainable software development in research organizations.
  • Tools used in international projects and EU policy studies.

Selected Publications

  • Migliavacca, M., Grassi, G., Bastos, A., Ceccherini, G., Ciais, P., Janssens-Maenhout, G., … & Cescatti, A. (2025). Securing the forest carbon sink for the European Union’s climate ambition. Nature. https://doi.org/10.1038/s41586-025-08967-3

  • Rougieux, P., Patani, S., & Migliavacca, M. (2023). Biotrade: A Python package to access and analyse the international trade of bio-based products. Journal of Open Source Software. https://doi.org/10.21105/joss.05550

  • Rougieux, P., & Jonsson, R. (2021). Impacts of the FLEGT action plan and the EU timber regulation on EU trade in timber product. Sustainability https://doi.org/10.3390/su13116030

  • Rougieux, P., Pilli, R., Blujdea, V., Mansuy, N., & MUBAREKA, S. B. (2024). Simulating future wood consumption and the impacts on Europe’s forest sink to 2070. 10.2760/17191

Full Publication List on Google Scholar | ORCID

Research Software & Tools

Collaboration & Consulting

Research Partnerships

  • Experience with interdisciplinary research networks.
  • Collaboration on project conceptualization, data integration, and scientific publishing.

Policy Analysis & modelling

  • Contribution to EU regulatory impact assessments (timber regulation, FLEGT, climate targets).
  • Expertise in connecting quantitative modelling to EU Green Deal and SDG objectives.

Capacity Building

  • Training and mentoring in data workflows, modelling, and reproducibility for research teams.
  • Organization of workshops on modelling tools.

Contact

Inspirational quotes

We are standing on the shoulders of giants. The following quotes will give you a flavour of the philosophy underpinning our training, programming and consulting services.

John K. Thompson in his 2020 book “Building Analytics Teams”:

“I traveled to every continent and spent much of my times on the road and in discussions with executives, managers and people who should be involved. The primary objectives of those meetings were to: […] - Let them know that we were not there to judge their ideas and current state of operating, but to help them see how data and analytics will help them reach and exceed their operating goals. - Improve employee engagement and remove the tedious parts of staff members’ duties to enable those staff members to focus on the more creative aspects of their work that leverages their experience and expertise.

On the critique of no-code approches to creating data science software. Think about the analogy with a word processor. You don’t write an article or a report by choosing every word in a drop down menu.

Matt Turck in Conversation with Florian Douetteau, CEO, Dataiku:

“Data and AI in the enterprise is mostly not about a magical product, or a flying machine driven by AI. It’s mostly about the business processes, probably hundreds of them that you have inside the company. Most companies operate like a clockwork, meaning you’ve got many, many business processes that work together in order to create value. Possibly for any decent-sized company, 500-1000 of them. And data and AI is mostly about optimizing each of them step-by-step to make them more efficient, and more automated. And that’s why it’s so hard, it’s because data and AI in the enterprise is mostly about this very long transformation that most enterprises will have to go through. It’s probably a 20-25 year journey, and we are one third into it. And at the end of the journey, you have completely new way to work, with data and AI being very pervasive.”

  • https://mattturck.com/saas-dead/

“for the more specialized enterprise apps, customers feel like they can/should “build” internally rather than “buy” ”