Mitigation of anthropogenic climate change takes place against the backdrop of poor countries being most affected by climate change impacts; climate-induced migration is expected to increase in the future. However, the interaction between mitigation, climate migration and poverty has not been investigated explicitly. Here, we represent simultaneous poverty- and climate-induced migration in a laboratory setting, within the collective-risk social dilemma that arises from attempts to avert dangerous climate change. The relatively rich participants try to prevent migration by the relatively poor but in the long run these attempts are unsuccessful because of free-riding among the rich. The rich are willing to increase their effort at averting dangerous climate change when the poor are hit by a climate extreme event exacerbating their poverty. Conversely, the poor are willing to compensate some weaker effort by the rich, as long as the effort by the rich lies above a threshold emerging within the experiment.
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The data analysis code is available from the corresponding author on request.
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We thank the students from the universities of Hamburg and Kiel for their participation. We also thank H. Brendelberger and S. Dobler for logistic support. M.M. acknowledges discussion at the NIMBioS sustainability conference at Knoxville. This study was supported by the Max Planck Society for the Advancement of Science.
The authors declare no competing interests.
Peer review information Nature Climate Change thanks Reuben Kline, Mathew Hauer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
in the rich country and the poor country dependent on the number of inhabitants. (a) with low overall harvest in T0 and T1, (b) with high overall harvest in T2. Source data
Mean + s.e.m. per group in T0, T1 and T2. P after Mann–Whitney U-test, n1 = 14, n2 = 14, z = −2.955. Effective blockings (mean ± s.e.m.) per group: 2.5 ± 0.7 in T0, 1.8 ± 0.2 in T1, and 7.1 ± 1.7 in T2, respectively. Source data
Group size per group (mean ±s.e.m.) in the last 5 rounds per round in the poor country in T0, in T1 and T2 dependent on the risk of a climate event to occur of either 0%, n = 13, 10%, n = 7, or 20%, n = 7, per round. There are fewer inhabitants in the poor country during the last five rounds with increasing risk of climate events (n = 3 treatments, P = 0.005, h = 10.534, Kruskal–Wallis test). Source data
rho, mean + s.e.m., between contributions of one class of players to contributions of the other class of players in previous round over 19 rounds per group. Poor player reacts to rich player’s contribution in previous round, rich player reacts to poor player’s contribution in previous round; a. T0, n = 13 groups of 10 players each, b. T1, n = 14 groups of 10 players each, c. T2, n = 14 groups of 10 players each; d. T0, 7 groups of 10 players each, where rich players contributed at least €300 total per group, e. T1, 8 groups of 10 players each, where rich players contributed at least €300 total per group. P calculated from Fisher combination test41, a. combining P values from each of 13 (T0), b, c. of 14 (T1, T2), d. of 7 (T0), e. of 8 (T1) independent groups of 10 players each. For each group the Spearman correlation coefficient rho was calculated from 19 rounds, providing a single p-value. Source data
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Marotzke, J., Semmann, D. & Milinski, M. The economic interaction between climate change mitigation, climate migration and poverty. Nat. Clim. Chang. 10, 518–525 (2020). https://doi.org/10.1038/s41558-020-0783-3
Nature Climate Change (2020)