Thanks so much, Nils!

That said, I am glad for the chance to remain involved with research at Columbia through a President's Global Innovation Fund (PGIF) for a project on displaced livelihood in India. I am also enthusiatic about a new project funded with the Lincoln Institute of Land Policy, with @he-yin.bsky.social.

It is of course bittersweet to be leaving Columbia at a time when scientific research in the US is facing unprecedented attacks.

I throughly enjoyed the past 6+ years at Columbia University, and in particular at CIESIN, the Lamont-Doherty Earth Observatory and the Saltzman Institute of War and Peace Studies. I will be missing my many colleagues at Columbia. I am especially thankful to Alex de Sherbinin and Richard Seager.

We are excited to hear from Sarah Rosengaertner, Natalia Banulescu-Bogdan, Miyuki Hino, Jeroen Aerts and Michael Oppenheimer about the opportunities and pitfalls of quantitative models, as well as the promises of model intercomparison and integration to generate nuanced evidence-based policies.

This work was made possible by the generous support of Africa Climate Mobility Initiative (ACMI) and the NASA Socioeconomic Data and Applications Center (SEDAC). [7/7]

I am deeply thankful to Alex de Sherbinin, Jacob Schewe, Kamal Amakrane, Bryan Jones, Hélène Benveniste, Samir K.C., Sarah Rosengaertner, Richard Seager, Nina von Uexkull, Greg Yetman, as well as Robert Beyer and Michal Burzynski for their insightful comments and/or data sharing. [6/n]

And yet, close inspection of the calibration model suggests that its predictive ability should not be overstated. Examining the predictive ability of the model within individual migration corridors indicate that the model still struggles to capture temporal dynamics. [5/n]

An out-of-sample assessment of the posterior predictive ability of the model using leave-one-out cross-validated expected log pointwise density indicates that hierarchical models out-perform simpler models in replicating observed migration flows on the continent over the period 1990-2010. [4/n]

To calibrate the projection model underlying these projections, I use Bayesian hierarchical models in a gravity framework. Drawing on SSP and RCP scenarios, I then project future migration under different combinations of climate change and socio-economic scenarios. [3/n]

The results indicate that over the period 2010–2050 up to 17 million people are projected to migrate internationally on the African continent (from one African country to another one), though only at best 5% of these as a result of climate change.