Linear and nonlinear influences of climatic changes on migration flows: A case study for the 'Mediterranean bridge'

The influence of climatic changes on migrations around the world is a topic widely discussed in the scientific literature, but investigations are often limited to particular regions. The possible causes of migration flows from Africa to Europe due to landings in Italy, a peninsula which can be considered as a "bridge" between these two continents, have not been investigated in detail even if, at present, this problem is at the top of the political agenda in Europe. Here a simple linear model and a fully nonlinear one (neural networks - NNs) are applied to the study of possible climatic influences on migration flows from the Sahel to Italy during the period 1995-2009. The results show the ability of the NN model to explain the majority of the variance found in the data and permit the identification of the major climatic drivers affecting the amount of yields in Sahelian countries and the migrations flows from them to Italy. In particular, the use of a NN model fully identifies both linear and nonlinear influences. We can explain much of the variance in the migration data (R2 = 0.775). Agriculture (harvest yields) is shown to link climatic changes and migration, and poor yields can enhance this latter phenomenon. Heat waves (during the cereal growing season) have an important nonlinear role. The annual temperature, however, is most likely the dominant climatic factor influencing migrations in this region.