Abstract
Climate variability and climate change influence human migration both directly and indirectly through a variety of channels that are controlled by individual and household socioeconomic, cultural, and psychological processes as well as public policies and network effects. Characterizing and predicting migration flows are thus extremely complex and challenging. Among the quantitative methods available for predicting such flows is the widely used gravity model that ignores the network autocorrelation among flows and thus may lead to biased estimation of the climate effects of interest. In this study, we use a network model, the additive and multiplicative effects model for network (AMEN), to investigate the effects of climate variability, migrant networks, and their interactions on South African internal migration. Our results indicate that prior migrant networks have a significant influence on migration and can modify the association between climate variability and migration flows. We also reveal an otherwise obscure difference in responses to these effects between migrants moving to urban and non-urban destinations. With different metrics, we discover diverse drought effects on these migrants; for example, the negative standardized precipitation index (SPI) with a timescale of 12 months affects the non-urban-oriented migrants’ destination choices more than the rainy season rainfall deficit or soil moisture do. Moreover, we find that socioeconomic factors such as the unemployment rate are more significant to urban-oriented migrants, while some unobserved factors, possibly including the abolition of apartheid policies, appear to be more important to non-urban-oriented migrants.
Highlights
Studies using diverse methods have established that environmental factors, including climate variability and change, affect patterns of human migration both directly and indirectly (McLeman & Gemenne, 2018)
As previous studies found that the effects of climate variability on human migration are not generalized (Beine & Jeusette, 2018), even if only in sub-Saharan African countries (Gray & Wise, 2016; Mueller et al, 2020), in this study, we only focus on one country, South Africa, to investigate in detail the mechanisms through which the climate influence is exerted in a particular set of circumstances
To analyze mechanisms controlling inter-district migration flows in South Africa and predict migration flows with higher accuracy, our study introduces a Bayesian model for networks that resolves a major limitation of the widely used gravity models—the assumption that network flows are mutually independent (Tiefelsdorf, 2003)
Summary
Studies using diverse methods have established that environmental factors, including climate variability and change, affect patterns of human migration both directly and indirectly (McLeman & Gemenne, 2018). As previous studies found that the effects of climate variability on human migration are not generalized (Beine & Jeusette, 2018), even if only in sub-Saharan African countries (Gray & Wise, 2016; Mueller et al, 2020), in this study, we only focus on one country, South Africa, to investigate in detail the mechanisms through which the climate influence is exerted in a particular set of circumstances. The high migration rate and increasing inflow to urban areas greatly influence the population growth, resource distribution, and public health for individual districts and pose challenges for planning, especially under future climate change
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
