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Armed conflicts in drylands: a statistical investigation of natural and socio-economic causes

This statistical investigation explores the distribution of armed conflict in global drylands through a socio-ecological vulnerability lens, providing valuable insights into the complex interplay between natural and social variables. The study compares linear and non-linear models of conflict explanation and highlights the importance of resource endowment and socio-economic factors in determining the likelihood of conflict occurrence. This empirical research contributes to the ongoing discourse on the "neo-Malthusian" versus "neo-Durkheimian" explanations of conflict.

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Armed conflicts in drylands: a statistical investigation of natural and socio-economic causes

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  1. Armed conflicts in drylands: a statistical investigation of natural and socio-economic causes Armed conflict distribution in global drylands through the lens of a typology of socio-ecological vulnerability Till Sterzel*, Matthias Lüdeke*, Marcel Kok+, Carsten Walther*, Diana Sietz**, Indra de Soysa++, Paul Lucas+, Peter Janssen+ + Netherlands Environmental Assessment Agency (PBL), 3720 AH Bilthoven, The Netherlands ++Norwegian University of Science and Technology, Dept. of Sociology and Political Science, N-7491 Trondheim, Norway **Wageningen University, Rural Development Sociology Group, Hollandseweg 1, 6706 KN Wageningen, The Netherlands Reg Environ Change (2014) 14:1419–1435 Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  2. Empirical, large N investigation contributing to the discourses: (1) “neo-Malthusian“ vs. “neo-Durkheimian“ explanation of conflict (2) linear vs. non-linear models of conflict explanation Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  3. Armed conflict data: • UCDP/PRIO ACD, version 4-2006 • Uppsala Conflict Data Program and International Peace Research Institute, Oslo • at least 25 battle-related deaths’ • 1990-2005 • geo-referenced Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  4. Colored & dark grey areas: global drylands (CBD, 2007): - 41% of global land surface - 36% of global population Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  5. Socio-economic & environmental data: For the choice of core areas see Reynolds et al (2007) and Safriel and Adeel (2008) Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  6. The linear approch: multivariate logistic regression AIC for different logit – models: (measure for goodness of fit, corrected by number of free parameters, the smaller the better) Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  7. The non-linear approch: clusters in the 7-dimensional indicator space are related to conflict incidence Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  8. The non-linear approach: the cluster profiles (=cluster centers which represent the resp. point clouds) Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  9. The non-linear approach: the cluster profiles and related conflict numbers Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  10. The non-linear approach : the cluster profiles, conflict numbers and resulting rules Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  11. Quantitative comparison: explanatory power of linear vs. nonlinear model AIC for different logit – models: ROC for the different models: ROC (receiver operating characteristic) Shifting threshold of independent variable, resulting false/true positive/negative predictions. AUC = 1: exact AUC = 0.5: no relation Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  12. Empirical, large N investigation contribution to the discourse: “neo-Malthusian“ vs. “neo-Durkheimian“ explanation of conflict: The dependence of conflict incidence on natural and social variables seems to be non-linear. Depending on the resource endowment different socio/economic variables determine the probability of conflict occurence. In this sense both, natural and social varibles play their role Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

  13. Matthias K. B. Lüdeke & Till Sterzel Climate Impacts and Vulnerabilities Lübeck, 23.9.2014

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