Using Bayesian belief networks to analyse social-ecological conditions for migration in the Sahel

Lukas Drees, Stefan Liehr ISOE – Institute for Social-Ecological Research, Frankfurt am Main/Germany

Climate change in Africa. Negotiations, translations, and socio-political implications. 10th – 12th September 2014, at ZEF in Bonn, Germany

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 2

Overview

1. Project micle

2. Bayesian Belief Networks

3. Modelling procedure

4. Modelling results

5. Conclusion

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 3

Project micle – migration, climate change & environment in the Sahel ■ Analysis of interactions between climate change, land

degradation and migration in Senegal and Mali

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 4

Project micle – Overall Objectives and Research Questions ■ Analysis of interactions between climate change, land

degradation and migration in Senegal and Mali ■ local population‘s perception and evaluation of climate and

environmental changes ■ Identification of the role of climate and environmental changes in

migration decisions and of characteristical migration patterns

■ What are the specific social-ecological conditions under which migration takes place and how are these conditions influenced by climate and environmental changes?

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 5

Motivation and Goals of Modelling

Thematic: Better understanding of relations between climate-induced environmental change, social-ecological conditions and migration

basic project question

Integrative: Knowledge integration regarding results and insights from social and natural science domains

integration of empirical, multi-disciplinary data and information

Methodological: Further development and adaptation of methods for integrated analysis of diverse empirical data and application for formulating action-related conclusions

transferable methods with applicable results

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 6

■ combines graph theory and probability theory ■ directed acyclic graphical model ■ represents conditional probabilities between a set of variables (Bayesian statistics)

Modelling Approach: Bayesian Belief Networks (BBN)

gender age

migration yes 75 % no 25 %

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 7

■ combines graph theory and probability theory ■ directed acyclic graphical model ■ represents conditional dependencies between a set of variables (Bayesian statistics)

■ uncertain knowledge can be explicitly addressed

■ combination of different types of variables ■ e.g. empirical data and expert knowledge ■ social and natural science data

Modelling Approach: Bayesian Belief Networks (BBN)

male age

migration yes 85 % no 15 %

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 8

Modelling: Methodological procedure 1. conceptualization of the main structure

motives for migration

influential factors: environmental (incl. climatic)

influential factors: socio-economic

character of migration

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 9

Modelling: Methodological procedure 1. conceptualization of the main structure

2. spatial and temporal integration of social and environmental data based on the survey

3. building submodels based on migration motives (sensitivity analysis, train-&test-method)

4. joining submodels in one model

5. identification of interrelations between influential factors

migration motives

migration patterns

social-ecological conditions

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 10

Modelling: Methodological procedure – data integration

■ data basis: ■ social-empirical

survey (n=900) ■ remote sensing

data on rainfall and land cover (NDVI/FAPAR)

mean value within 3 km radius

temporal allocation to year of migration

ID F01 F07 age_ kat3 F09

country gender age marital_ situation

1001 1 2 1 2

1002 1 2 3 3

1003 1 2 1 1

1004 1 1 2 2

locating place of origin

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 11

Modelling: Results – probability distribution (Linguère)

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 12

Modelling: Results - Analysis

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 13

Modelling: Main results of analyses ■ migration in the study area is a result of complex social-

ecological interdependencies

■ in case of deteriorating environmental conditions a change of migration intensity cannot be observed

■ migration patterns & motives change in dependence on the specific conditions ■ worsening environmental conditions + poor supply situation

+ motive sustenance/employment + non-permanent migration + distant destinations

■ favourable conditions + improved economic situation + motive education + permanent migration + migration within the region of origin

Lukas Drees, Stefan Liehr ● Climate change in Africa. ZEF Bonn, 10th Sep. 2014 ● 14

Conclusions

Thematic: The impact of economical and institutional performance on migration motives and patterns is bigger than that of climatic changes (scenario analysis)

Integrative: Integration has to be planned from the beginning and integrative interfaces (temporal & spatial) have to be identified constant exchange between social and natural scientists

Methodological: BBN are capable to portray the complexity of migration. The validity and reliability of the analytical results depends on the data situation.

Thank you for your attention!