Venla Niva, Alexander Horton, Vili Virkki, Matias Heino, Maria Kosonen, Marko Kallio, Pekka Kinnunen, Guy J. Abel, Raya Muttarak, Maija Taka, Olli Varis, Matti Kummu
{"title":"高分辨率数据揭示了2000-2019年全球人类迁徙模式。","authors":"Venla Niva, Alexander Horton, Vili Virkki, Matias Heino, Maria Kosonen, Marko Kallio, Pekka Kinnunen, Guy J. Abel, Raya Muttarak, Maija Taka, Olli Varis, Matti Kummu","doi":"10.1038/s41562-023-01689-4","DOIUrl":null,"url":null,"abstract":"Despite being a topical issue in public debate and on the political agenda for many countries, a global-scale, high-resolution quantification of migration and its major drivers for the recent decades remained missing. We created a global dataset of annual net migration between 2000 and 2019 (~10 km grid, covering the areas of 216 countries or sovereign states), based on reported and downscaled subnational birth (2,555 administrative units) and death (2,067 administrative units) rates. We show that, globally, around 50% of the world’s urban population lived in areas where migration accelerated urban population growth, while a third of the global population lived in provinces where rural areas experienced positive net migration. Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration—a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration. Producing a high-resolution global net migration dataset for 2000–2019, Niva et al. analyse how migration affects urban and rural population growth and show that socioeconomic factors are more strongly associated with migration than climatic ones.","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"7 11","pages":"2023-2037"},"PeriodicalIF":21.4000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10663150/pdf/","citationCount":"0","resultStr":"{\"title\":\"World’s human migration patterns in 2000–2019 unveiled by high-resolution data\",\"authors\":\"Venla Niva, Alexander Horton, Vili Virkki, Matias Heino, Maria Kosonen, Marko Kallio, Pekka Kinnunen, Guy J. 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Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration—a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration. 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World’s human migration patterns in 2000–2019 unveiled by high-resolution data
Despite being a topical issue in public debate and on the political agenda for many countries, a global-scale, high-resolution quantification of migration and its major drivers for the recent decades remained missing. We created a global dataset of annual net migration between 2000 and 2019 (~10 km grid, covering the areas of 216 countries or sovereign states), based on reported and downscaled subnational birth (2,555 administrative units) and death (2,067 administrative units) rates. We show that, globally, around 50% of the world’s urban population lived in areas where migration accelerated urban population growth, while a third of the global population lived in provinces where rural areas experienced positive net migration. Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration—a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration. Producing a high-resolution global net migration dataset for 2000–2019, Niva et al. analyse how migration affects urban and rural population growth and show that socioeconomic factors are more strongly associated with migration than climatic ones.
期刊介绍:
Nature Human Behaviour is a journal that focuses on publishing research of outstanding significance into any aspect of human behavior.The research can cover various areas such as psychological, biological, and social bases of human behavior.It also includes the study of origins, development, and disorders related to human behavior.The primary aim of the journal is to increase the visibility of research in the field and enhance its societal reach and impact.