| Autor: |
Venla Niva, Marko Kallio, Raya Muttarak, Maija Taka, Olli Varis, Matti Kummu |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Environmental Research Letters, Vol 16, Iss 11, p 114019 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1748-9326 |
| DOI: |
10.1088/1748-9326/ac2e86 |
| Popis: |
Migration manifests an important response and adaptation measure to changes in the environment and socioeconomic conditions. In a time when environmental stressors and risks are unprecedentedly increasing, understanding the interplay between the underlying factors driving migration is of high importance. While the relationships between environmental and socioeconomic drivers have been identified conceptually, the comprehensive global-scale spatial quantification of their interactions is in its infancy. Here, we performed a geospatial analysis of gridded global net migration from 1990 to 2000 using a novel machine learning approach which analyses the interplay between a set of societal and environmental factors simultaneously at the place of origins (areas of net-negative migration) and destinations (areas of net-positive migration). We diagnosed the importance of eight environmental and societal factors in explaining migration for each country, globally. Nearly half of global in- and out-migration took place in the areas characterized by low adaptive capacity and high environmental stress. Regardless of the income level, income was the key factor in explaining net-migration in half of the countries. Slow-onset environmental factors, drought and water risk, were found to be the dominant environmental variables globally. Our study highlights that factors representing human capacity need to be incorporated into the quantitative diagnosis of environmental migration more rigorously. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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