From descriptive to causal analysis

Steering land systems towards sustainable pathways requires an understanding of what type of intervention worked well in the past and which didn’t: did a protected area (PA) lead to a reduction in deforestation? Under which condition and in which environment did this work well? I use quasi-experimental methods to establish causality between interventions (e.g., a PA) and outcomes (e.g., reduction in deforestation). I apply these methods in different environments & contexts.

Selected publications under this research theme

(2023). Deforestation and agricultural fires in South-West Pará, Brazil, under political changes from 2014 to 2020.. Journal of Land Use Science 18(1), 176-195.


(2022). Toward Causal Inference for Spatio-Temporal Data. Conflict and Forest Loss in Colombia. Journal of the American Statistical Association 117(538), 591-601.

Cite DOI

(2017). Quasi-experimental methods enable stronger inferences from observational data in ecology. Basic and Applied Ecology 19, 1-10.

Cite DOI

(2015). Land-use change in the Caucasus during and after the Nagorno-Karabakh conflict. Regional Environmental Change 15(8), 1703-1716.