David Makowski

Current position

Director of research (DR1)

Unit MIA-PS
University Paris-Saclay, campus AgroParisTech INRAE
Palaiseau 91120 France

Email : david.makowski@inrae.fr or david.makowski@universite-paris-saclay.fr 

https://github.com/davemakowski 

Recent publications in 2024

• Mitigating nitrogen losses with almost no crop yield penalty during extremely wet years. https://www.science.org/doi/epdf/10.1126/sciadv.adi9325
• Drivers of natural gas use in US residential buildings. https://www.science.org/doi/full/10.1126/sciadv.adh5543 
• Global spatially explicit yield gap time trends reveal regions at risk of future crop yield stagnation. https://doi.org/10.1038/s43016-023-00913-8 
• Efficacy of neonicotinoid and non-neonicotinoid treatments on virus yellows and sugar beet yields. https://doi.org/10.1016/j.cropro.2024.106658   
• Assimilating Sentinel-2 data in a modified vegetation photosynthesis and respiration model (VPRM) to improve the simulation of croplands CO2 fluxes in Europe. https://doi.org/10.1016/j.jag.2024.103666
• A hierarchical model to evaluate pest treatments from prevalence and intensity data. https://doi.org/10.57750/6cgk-g727
• High temperature sensitivity of monoterpene emissions from global vegetation. https://doi.org/10.1038/s43247-023-01175-9

Full list of publications accessible here:

• https://scholar.google.fr/citations?hl=en&user=vcnWi7IAAAAJ&view_op=list_works&sortby=pubdate 
• https://www.researchgate.net/profile/David-Makowski/publications

Students and junior researchers supervised in 2024

• Han Zhang (Post-doc): Effect of climate change on pests and diseases
• Claudia Mendes (Research Engineer): Estimation of the impact of extreme weather events on crop prodution
• Armand Favrot (PhD student): Prediction of ammonia emission using machine learning
• Oudya Tahiri (PhD student): Mappy agroforestry for estimating carbon stocks (in collab. with CIRED)
• Florian Teste (PhD student): Impact of production shocks on prices of agricultural commodities

Research

My main interests are in statistical/machine learning modelling applied to environmental risk management, agroecology, climate change, and food safety. I manage scientific projects and support research groups in analyzing complex datasets using statistical and machine learning methods.

Methods

• Meta-analysis
• Mixed-models
• Machine learning
• Forecasting
• Dynamic models
• Bayesian statistics

Fields of application

• Climate change impact and adaptation
• Greenhouse gas and pollutants
• Agroecology
• Food security and food safety
• Environmental risk assessment
• Decision support tools for crop management (crop protection, fertilization)

Teaching in graduate schools

• Generalized linear models and Mixed-models applied to agroecology
• Meta-analysis and analysis of networks of experiments
• Uncertainty and Sensitivity analysis with complex crop and environmental models
• Time series and Machine learning

Check my lectures on GitHub:

https://github.com/davemakowski?tab=repositories

Consultancy

I support research groups and public organisations in analyzing their datasets:

• Climate change and agroecology,
• Risk analysis (environmental risk, food safety),
• Development of modelling, classification and forecasting tools,
• Support in conducting meta-analysis.

Education

• HDR (equivalent to DSc) University Paris-Sud (University Paris-Saclay), France, 2007
• PhD INA PG (AgroParisTech-University Paris-Saclay), Paris, France, 2001
• MSc and Engineer INA PG (AgroParisTech-University Paris-Saclay), Paris, France, 1996

Books in english and special issues

• From Experimental Network to Meta-analysis. Methods and Applications with R for Agronomic and Environmental Sciences. Springer. https://www.springer.com/gp/book/9789402416954
• Working with Dynamic Crop Models (3rd edition). Methods, Tools and Examples for Agriculture and Environment. Elsevier. https://www.elsevier.com/books/working-with-dynamic-crop-models/wallach/978-0-12-811756-9
• Environmental Impact of Land Use Change in Agricultural Systems. Sustainable Agriculture Reviews 30. Springer. https://www.springer.com/gp/book/9783319962887
• Special issue in European journal of Agronomy: Evidence synthesis in agronomy. https://www.sciencedirect.com/journal/european-journal-of-agronomy/special-issue/10CLKSSZSF5
• Special issue in Journal of Environmental Management: Multifunctional agriculture - From farm diagnosis to farm design and institutional innovation. https://www.sciencedirect.com/journal/journal-of-environmental-management/vol/90/suppl/S2

Books in French

• Data science pour l’agriculture et l’environnement - Méthodes et applications avec R et Python. Editions Ellipses. https://www.editions-ellipses.fr/
• De l’analyse des réseaux expérimentaux à la méta-analyse. Quae. https://www.quae.com/produit/1514/9782759228164/de-l-analyse-des-reseaux-experimentaux-a-la-meta-analyse
• Initiation à la statistique bayésienne - Bases théoriques et applications en alimentation, environnement, épidémiologie et génétique. Editions Ellipses. https://www.editions-ellipses.fr/
• Analyse statistique des risques agro-environnementaux. Springer. https://link.springer.com/book/10.1007/978-2-8178-0251-0
• Analyse de sensibilité et exploration de modèles. Quae. https://www.quae.com/produit/1179/9782759219070/analyse-de-sensibilite-et-exploration-de-modeles