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Emerging Issues and Internal Displacement in Africa: Interlinkages

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Emerging Issues in Internal Displacement in Africa

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Abstract

This chapter examines the nexus between the emerging issues and internal displacement, exploring the intersections and evidence that reflect interlinkages. The aim of this chapter is to respond to the knowledge gap required for the furtherance of discussion on these issues in the context of internal displacement.

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Notes

  1. 1.

    Paris Agreement (2015), art 2(1)(a).

  2. 2.

    United Nation Environment Programme (2019, 26).

  3. 3.

    United Nation Environment Programme (2019), Hausfather (2019).

  4. 4.

    World Bank (2018b).

  5. 5.

    See Kälin (2010, 84–91), McAdam (2012, 18–19).

  6. 6.

    Hugo (2011, 225, 261).

  7. 7.

    In the southern African region, the intensity of cyclones and torrential rainfall patterns have been linked to climate change. Yarnell and Cone observe that ‘scientists representing an overwhelming consensus in the scientific community have concluded that cyclone intensity and rainfall rates are expected to increase. Southern Africa must be prepared for more extreme and unusual weather.’ Evidently, the displacement situation brought about by Cyclone Idai in parts of Zimbabwe and Mozambique lends credence to the pertinence of underscoring this linkage. See Yarnell and Cone (2019).

  8. 8.

    See Casas et al. (2004, 139–150), Zahiri et al. (2016, 15, 23).

  9. 9.

    Sylla et al. (2016, 25–40), Zahiri et al. (2016, 16).

  10. 10.

    Zahiri et al. (2016, 15–16).

  11. 11.

    Bryne (2018, 765–766).

  12. 12.

    Jegede (2017, 172).

  13. 13.

    In a scientific research on 2011 East African drought and climate attribution, ‘evidence was found for an enhanced risk of failure of the long rains in 2011 due to human-induced climate change’. See Lott et al. (2013, 1177–1181), Straziuso (2013), Sengupta (2018).

  14. 14.

    Adaptive migration has become a co** mechanism among forest populations in parts of Central and East Africa where ‘lengthy dry season, are affecting the agricultural calendar and bringing about a scarcity of forest products, such as fruits and tubers of plants such as potatoes and yam’. See Jegede (2017, 172).

  15. 15.

    Reuveny (2007, 656–673), Freeman (2017, 351–374).

  16. 16.

    See International Crisis Group (2017, 3), International Crisis Group (2018).

  17. 17.

    Fasona and Omojola (2005); Amusan et al. (2017, 35).

  18. 18.

    Aluko (2018), Alindogan (2018), Amnesty International (2018b).

  19. 19.

    Cabot (2015, 159–160), Olaniyan et al. (2015, 53).

  20. 20.

    Gausset and Whyte (2012, 214), Mabikke (2014, 142).

  21. 21.

    World Bank Inspection Panel (2013, para 100).

  22. 22.

    World Bank (2007, 1).

  23. 23.

    Schmitd-Soltau (2006).

  24. 24.

    Langat (2014), Amnesty International (2018a, 7–8).

  25. 25.

    Grainger and Geary (2011).

  26. 26.

    World Bank (2009), Mushieta and Merrill (2010, 352).

  27. 27.

    Adrien (2007, 65).

  28. 28.

    Adrien (2007, 61).

  29. 29.

    With regards to REDD readiness project in the Rufiji Delta of Tanzania, Beymer-Ferris and Bassett observe that ‘the Warufiji [villagers] are resisting efforts to make the Rufiji Delta North “REDD ready” on the grounds that these efforts will increase their vulnerability and displacement.’ Beymer-Ferris and Bassett (2012, 339).

  30. 30.

    In a 2019 report, the United Nations Commission on Science and Technology for Development reinforced the pertinence of technology in driving the realization of the sustainable development goals. According to UNCTAD, ‘Frontier technologies, including big data and machine learning, can also be used to create, measure and develop and monitor more broadly the effectiveness of development programmes and progress towards the Sustainable Development Goals. Models based on both mobile telephone activity and airtime credit purchases have been shown to estimate multidimensional poverty indicators accurately, while recent studies have validated the potential of satellite imagery and machine learning in estimating household consumption and assets, using publicly available and non-proprietary data’. United Nations Commission on Science and Technology for Development (2019, para 7).

  31. 31.

    Sperber (2019).

  32. 32.

    Brookes (2019, 2), https://www.heritage.org/sites/default/files/2019-09/BG3437.pdf (accessed 28 March 2020).

  33. 33.

    While information on the impact of drone attacks in the African contexts, have been scarce, in part, due to the unavailability of accurate data and evidence, some of these impacts are well-documented in other regions. For instance, the UN Special Rapporteur on the Promotion and Protection of Human Rights and Fundamental Freedoms while Countering Terrorism has spotlighted the negative impact of these technologies on civilian populations in the Middle East region. With respect to Pakistan, for instance, the Special Rapporteur observed that ‘[o]n 30 October 2006, precision-guided munitions were reportedly fired at a religious seminary in Chenagai in the Bajaur tribal region. Remotely piloted aircraft under the control of the United States are alleged to have been involved in the operation. Up to 80 people were reportedly killed instantly during the attack; two more victims reportedly died in hospital shortly afterwards as the result of injuries sustained. It is alleged that as many as 69 of the dead were children under 18 years of age, and that 16 of those killed were under the age of 13. Eyewitnesses allege that the majority of those killed had been pupils at the seminary and were non-combatant civilians.’ See UN Human Rights Council (2014, para 47).

  34. 34.

    Burke (2019b).

  35. 35.

    Crush et al. (2017b, 21).

  36. 36.

    Crush et al. (2017a, 5).

  37. 37.

    Chaskalson (2017).

  38. 38.

    The News Humanitarian (2009), UNHCR (2009), South African History Online (2015).

  39. 39.

    Hans (2015).

  40. 40.

    Provincial Government of KwaZulu-Natal (2015, 119).

  41. 41.

    Crush et al. (2017b, 25).

  42. 42.

    UNHCR (2019).

  43. 43.

    Opiyo and Githinji (2011), Human Rights Watch (2012b); Abdi (2012), Wambua-Soi (2012), Nzwili (2012), BBC (2012), Odula (2012), Relocation of urban refugees to officially designated camps, Letter from E Mutea Iringo, Permanent Secretary, Provincial Administration and Internal Security (2013), Human Rights Watch (2013), Reini (2013), Human Rights First (2013), Rinelli and Opondo (2015, 138), Lind et al. (2017, 118), Human Rights Watch (2012a).

  44. 44.

    Department of Refugee Affairs (2012).

  45. 45.

    As above.

  46. 46.

    As above, 1.

  47. 47.

    As above, 2.

  48. 48.

    As above, 2.

  49. 49.

    Kenya Citizen TV (2012).

  50. 50.

    Yarnell 2014.

  51. 51.

    **nhua News Agency 2001.

  52. 52.

    As above.

  53. 53.

    As above.

  54. 54.

    The New Humanitarian (2001).

  55. 55.

    As above.

  56. 56.

    Bilyeu (1999, 457), Mistiaen (2013), Klein (2014, 370), Boaten (2001, 91), Akonor (2019).

  57. 57.

    Mistiaen (2013).

  58. 58.

    Farah (2001), Lorraine Fiadjoe v. Attorney General of the United States (2005), Kerry Kennedy Cuomo, Camera Works. https://www.washingtonpost.com/wp-srv/photo/onassignment/truth/st/09.htm.

  59. 59.

    Gillard (2010, 14).

  60. 60.

    Gillard (2010, 14).

  61. 61.

    Bradley (2019).

  62. 62.

    Pemunta (2016, 335).

  63. 63.

    Koigi (2017), Selby and Ngalle (2018), Obaji (2020).

  64. 64.

    Selby and Ngalle (2018).

  65. 65.

    Selby and Ngalle (2018).

  66. 66.

    Tetchiada (2006), Fem (2011).

  67. 67.

    Tetchiada (2006).

  68. 68.

    Equality Now (2019).

  69. 69.

    Sanghani (2015), BBC (2016), Kiptoo (2016), FIGO (2018), UN Women (2019), BBC (2019), Jidovanu and Otieno (2019).

  70. 70.

    Kyle Almond (2017); Okiror (2018).

  71. 71.

    Wodon et al. (2018), World Bank (2018a).

  72. 72.

    Ennaji (2019).

  73. 73.

    UNICEF (2018).

  74. 74.

    UN Human Rights Council (2017, para 52), Seepersaud (2017, 116).

  75. 75.

    Dixon (2017).

  76. 76.

    CNN (2009).

  77. 77.

    BBC (2017).

  78. 78.

    Morris (2019), Burke (2019a); Bax et al. (2019); de Greef (2019).

  79. 79.

    The Guardian (2018), Al Jazeera (2019).

  80. 80.

    Gettleman (2006).

  81. 81.

    Rice (2010), BBC (2010), Zounmenou and Lamin (2011, 6).

  82. 82.

    UN Office for the Coordination of Humanitarian Affairs (2011).

  83. 83.

    Human Rights Watch (2017), UN High Commissioner for Human Rights (2008, 12), Human Rights Watch (2008).

  84. 84.

    Gardner (2019b), Internal Displacement Monitoring Centre (2018).

  85. 85.

    Internal Displacement Monitoring Centre (2019, 14–15), Gardner (2019a).

  86. 86.

    Gardner (2019a), Obulutsa (2018).

  87. 87.

    Kleinfeld (2020).

  88. 88.

    UNHCR (n.d.).

  89. 89.

    Kleinfeld (2020).

  90. 90.

    Parts of this issue has been discussed in this chapter under the section on technology.

  91. 91.

    Adeola (2021), See also Cernea (1996, 13), Oliver-Smith (2005, 189), de Wet (2006, 180), Penz et al. (2011), Downing and Garcia-Downing (2009, 225).

  92. 92.

    Tamakloe (1994, 99), Fahim (1981, 59), Scudder (2005), DeGeorges and Reilly (2006, 633), Thamae (2006).

  93. 93.

    Madebwe et al. (2011, 292), Oluyemi (2014, 28), West African Democracy Radio (2017).

  94. 94.

    FIAN (2012); FIAN International (2012).

  95. 95.

    Kachika (2010, 20), Cotula (2013), Makochekanwa (2014, 58), Batterbury and Ndi (2018, 573).

  96. 96.

    Human Rights Watch (2005), Masava (2012), Obiadi et al. (2019, 50).

  97. 97.

    Parts of this issue has been discussed in this chapter under the section on climate change.

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  1. Centre for Human Rights, University of Pretoria, Pretoria, South Africa

    Romola Adeola

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Adeola, R. (2021). Emerging Issues and Internal Displacement in Africa: Interlinkages. In: Emerging Issues in Internal Displacement in Africa. SpringerBriefs in Law. Springer, Cham. https://doi.org/10.1007/978-3-030-64562-5_3

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