Improving coastal resilience to climate change hazards requires understanding past shoreline changes. As the coastal population grows, evaluation and monitoring of shoreline changes are essential for planning and development. Population growth increases exposure to sea level rise and coastal hazards. Nigeria, where the study is situated, is among the top fifteen countries in the world for coastal population exposure to sea level rise. This study provided a novel lens in establishing a link between social factors and the intensifying coastal erosion along the Akwa Ibom State study coast. The mixed-method approach used in the study to assess the vulnerability of the Nigerian coast and communities to climate change-induced coastal erosion proved to be essential in gathering a wide range of data (physical, socio economic, participatory GIS maps and social learning) that contributed to a more robust and holistic assessment of coastal erosion, which is a complex issue due to the interplay between the human and natural environments. Remotely sensed data was used to examine the susceptibility and coastal evolution of Akwa Ibom State over 36 years (1984 -2020). Longer-term (1984- 2020) and short-term (2015-2020) shoreline change analyses were used to understand coastal erosion and accretion. From 1984-2020, the total average linear regression rate (LRR) was - 2.7+0.18m/yr and from 2015-2020, it was -3.94 +1.28m/yr, demonstrating an erosional trend along the study coast. Although the rate of erosion varies along the study coast, the linear regression rates (LRR) results show a predominant trend of erosion in both the short and longer term. According to the 2022 Intergovernmental Panel on Climate Change report, loss of land, loss of assets, community disruption and livelihood, loss of environmental resources, ecosystem, loss of life, or adverse health impact are all potential risks along the African coast due to climate change – this study shows that these risks are already occurring today. To quantify the anticipated future coastal erosion risk by 2040 along the study coast, the findings in this study show an overall average LRR of -2.73+ 0.99 m/yr which anticipates that coastal erosion will still be prevalent along the coast by 2040. And, given the current global climate change situation, should be expected to be much higher than the current forecasting.
This study re-conceptualised the European Environmental Agency Driver-Pressure StateImpact-Response (DPSIR) model to show Hazard-Driver-Pressure-State-Impact ResponseObservation causal linkages to coastal erosion hazards. The results showed how human activities and environmental interactions have evolved through time, causing coastal erosion. Removal of vegetation cover/backstop for residential and agricultural purposes, indicate that human activities significantly contribute to the study area's susceptibility, rapid shoreline changes, and vulnerability to coastal erosion, in addition to oceanic and climate change drivers such as sea level rise and storminess. Risk perception of coastal erosion in the study area was analysed using the rhizoanalytic method proposed by Deleueze. The method demonstrates how connections and movements can be related and how data can be used to show multiplicity, mark and unmark ideas, rupture pre-conceptions and make new connections.
This study shows that coastal erosion awareness is insufficient to build a long-term management plan and sustain coastal resilience. The Hino's conceptual model which provides in-depth understanding on planned retreat was used to illustrate migratory and planned retreat for the study coast where relocation has already occurred due to coastal erosion. The result fell within the Self-Reliance quadrant, indicating that people left the risk zone without government backing or retreat plans. Other coastal residents who have not relocated fell within the Hunkered Down quadrant, showing that they are willing to stay in the risk zone and cope with the threat unless the government/environmental agencies relocate them. This study shows that coastal resilience requires adaptive capacity and government support. However, multilevel governance has inhibited government-community dialogue and involvement, increasing coastal erosion vulnerability. The coastal vulnerability index to coastal erosion was calculated using the Analytical Hierarchy Process weightings. It revealed that 67.55% of the study coast falls within the high-very high vulnerability class while 32.45% is within the very low-low vulnerability class. This study developed and combined a risk perception index to coastal erosion (RPIerosion) and participatory GIS (PGIS) mapping into a novel coastal vulnerability index called the integrated coastal erosion vulnerability index (ICEVI). The case study evaluation in Akata, showed an improvement in the overall vulnerability assessment to reflect the real-world scenario, which was consistent with field data.
This study demonstrated not only the presence and challenges of coastal erosion in the research area but also the relevance of involvement between the local stakeholders, government and environmental agencies. Thus, showing the potential for the perspectives of the inhabitants of these regions to inform the understanding of the resilience capacity of the people impacted, and importantly to inform future co-design and/or selection of effective adaptation methods, to better support coastal climate change resilience in these communities. Overall, the study provides a useful contribution to coastal erosion vulnerability assessments in data-scarce regions more broadly, where the mixed-methods approach used here can be applied elsewhere